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  • 1
    Publication Date: 2018-02-02
    Description: Sensors, Vol. 18, Pages 416: Facial Emotion Recognition: A Survey and Real-World User Experiences in Mixed Reality Sensors doi: 10.3390/s18020416 Authors: Dhwani Mehta Mohammad Siddiqui Ahmad Javaid Extensive possibilities of applications have made emotion recognition ineluctable and challenging in the field of computer science. The use of non-verbal cues such as gestures, body movement, and facial expressions convey the feeling and the feedback to the user. This discipline of Human–Computer Interaction places reliance on the algorithmic robustness and the sensitivity of the sensor to ameliorate the recognition. Sensors play a significant role in accurate detection by providing a very high-quality input, hence increasing the efficiency and the reliability of the system. Automatic recognition of human emotions would help in teaching social intelligence in the machines. This paper presents a brief study of the various approaches and the techniques of emotion recognition. The survey covers a succinct review of the databases that are considered as data sets for algorithms detecting the emotions by facial expressions. Later, mixed reality device Microsoft HoloLens (MHL) is introduced for observing emotion recognition in Augmented Reality (AR). A brief introduction of its sensors, their application in emotion recognition and some preliminary results of emotion recognition using MHL are presented. The paper then concludes by comparing results of emotion recognition by the MHL and a regular webcam.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 2
    Publication Date: 2018-02-02
    Description: Sensors, Vol. 18, Pages 419: Stress Prediction for Distributed Structural Health Monitoring Using Existing Measurements and Pattern Recognition Sensors doi: 10.3390/s18020419 Authors: Wei Lu Jun Teng Qiushi Zhou Qiexin Peng The stress in structural steel members is the most useful and directly measurable physical quantity to evaluate the structural safety in structural health monitoring, which is also an important index to evaluate the stress distribution and force condition of structures during structural construction and service phases. Thus, it is common to set stress as a measure in steel structural monitoring. Considering the economy and the importance of the structural members, there are only a limited number of sensors that can be placed, which means that it is impossible to obtain the stresses of all members directly using sensors. This study aims to develop a stress response prediction method for locations where there are insufficent sensors, using measurements from a limited number of sensors and pattern recognition. The detailed improved aspects are: (1) a distributed computing process is proposed, where the same pattern is recognized by several subsets of measurements; and (2) the pattern recognition using the subset of measurements is carried out by considering the optimal number of sensors and number of fusion patterns. The validity and feasibility of the proposed method are verified using two examples: the finite-element simulation of a single-layer shell-like steel structure, and the structural health monitoring of the space steel roof of Shenzhen Bay Stadium; for the latter, the anti-noise performance of this method is verified by the stress measurements from a real-world project.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 3
    Publication Date: 2018-02-02
    Description: Sensors, Vol. 18, Pages 431: A Review of Depth and Normal Fusion Algorithms Sensors doi: 10.3390/s18020431 Authors: Doris Antensteiner Svorad Štolc Thomas Pock Geometric surface information such as depth maps and surface normals can be acquired by various methods such as stereo light fields, shape from shading and photometric stereo techniques. We compare several algorithms which deal with the combination of depth with surface normal information in order to reconstruct a refined depth map. The reasons for performance differences are examined from the perspective of alternative formulations of surface normals for depth reconstruction. We review and analyze methods in a systematic way. Based on our findings, we introduce a new generalized fusion method, which is formulated as a least squares problem and outperforms previous methods in the depth error domain by introducing a novel normal weighting that performs closer to the geodesic distance measure. Furthermore, a novel method is introduced based on Total Generalized Variation (TGV) which further outperforms previous approaches in terms of the geodesic normal distance error and maintains comparable quality in the depth error domain.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 4
    Publication Date: 2018-02-02
    Description: Sensors, Vol. 18, Pages 432: Random Access for Underwater Acoustic Cellular Systems Sensors doi: 10.3390/s18020432 Authors: Rothna Pec Mohammed Khan Muhammad Asim Yong Cho In this paper, a random access preamble (RAP) design technique for underwater acoustic cellular systems is proposed. After showing that the conventional RAP used in long term evolution (LTE) systems is not appropriate for underwater acoustic cellular systems, two different types of RAPs (RAP 1 and RAP 2) are proposed to detect the identity of underwater equipment/nodes (UEs) and estimate the time delay between a UE and an underwater base station (UBS) at the physical layer. RAP 1 is generated using a Zadoff-Chu (ZC) sequence where the identity of the UE is mapped to its root index, whereas RAP 2 is generated using a linear frequency modulation (LFM) waveform where the identity of the UE is mapped to its frequency sweeping parameter and frequency shifting parameter. Ambiguity functions (AFs) and cross-ambiguity functions (CAFs) of RAP 1 and RAP 2 are derived to investigate their correlation properties under the effect of time delay and Doppler shift. The performance of RAP detection is investigated by analyzing the detection probabilities and false alarm probabilities of RAP 1 and RAP 2 in a Doppler environment. By evaluating the performances of RAP 1 and RAP 2 in various situations, it is concluded that RAP 2 is more suitable for underwater acoustic cellular systems. The AF and CAF analytically obtained in this paper are shown to be similar to those obtained using experimental data.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 5
    Publication Date: 2018-02-02
    Description: Sensors, Vol. 18, Pages 430: An Intraoperative Visualization System Using Hyperspectral Imaging to Aid in Brain Tumor Delineation Sensors doi: 10.3390/s18020430 Authors: Himar Fabelo Samuel Ortega Raquel Lazcano Daniel Madroñal Gustavo M. Callicó Eduardo Juárez Rubén Salvador Diederik Bulters Harry Bulstrode Adam Szolna Juan Piñeiro Coralia Sosa Aruma J. O’Shanahan Sara Bisshopp María Hernández Jesús Morera Daniele Ravi B. Kiran Aurelio Vega Abelardo Báez-Quevedo Guang-Zhong Yang Bogdan Stanciulescu Roberto Sarmiento Hyperspectral imaging (HSI) allows for the acquisition of large numbers of spectral bands throughout the electromagnetic spectrum (within and beyond the visual range) with respect to the surface of scenes captured by sensors. Using this information and a set of complex classification algorithms, it is possible to determine which material or substance is located in each pixel. The work presented in this paper aims to exploit the characteristics of HSI to develop a demonstrator capable of delineating tumor tissue from brain tissue during neurosurgical operations. Improved delineation of tumor boundaries is expected to improve the results of surgery. The developed demonstrator is composed of two hyperspectral cameras covering a spectral range of 400–1700 nm. Furthermore, a hardware accelerator connected to a control unit is used to speed up the hyperspectral brain cancer detection algorithm to achieve processing during the time of surgery. A labeled dataset comprised of more than 300,000 spectral signatures is used as the training dataset for the supervised stage of the classification algorithm. In this preliminary study, thematic maps obtained from a validation database of seven hyperspectral images of in vivo brain tissue captured and processed during neurosurgical operations demonstrate that the system is able to discriminate between normal and tumor tissue in the brain. The results can be provided during the surgical procedure (~1 min), making it a practical system for neurosurgeons to use in the near future to improve excision and potentially improve patient outcomes.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 6
    Publication Date: 2018-02-02
    Description: Sensors, Vol. 18, Pages 429: The Impact of Curviness on Four Different Image Sensor Forms and Structures Sensors doi: 10.3390/s18020429 Authors: Wei Wen Siamak Khatibi The arrangement and form of the image sensor have a fundamental effect on any further image processing operation and image visualization. In this paper, we present a software-based method to change the arrangement and form of pixel sensors that generate hexagonal pixel forms on a hexagonal grid. We evaluate four different image sensor forms and structures, including the proposed method. A set of 23 pairs of images; randomly chosen, from a database of 280 pairs of images are used in the evaluation. Each pair of images have the same semantic meaning and general appearance, the major difference between them being the sharp transitions in their contours. The curviness variation is estimated by effect of the first and second order gradient operations, Hessian matrix and critical points detection on the generated images; having different grid structures, different pixel forms and virtual increased of fill factor as three major properties of sensor characteristics. The results show that the grid structure and pixel form are the first and second most important properties. Several dissimilarity parameters are presented for curviness quantification in which using extremum point showed to achieve distinctive results. The results also show that the hexagonal image is the best image type for distinguishing the contours in the images.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 7
    Publication Date: 2018-02-02
    Description: Sensors, Vol. 18, Pages 428: Experimental Study of Multispectral Characteristics of an Unmanned Aerial Vehicle at Different Observation Angles Sensors doi: 10.3390/s18020428 Authors: Haijing Zheng Tingzhu Bai Quanxi Wang Fengmei Cao Long Shao Zhaotian Sun This study investigates multispectral characteristics of an unmanned aerial vehicle (UAV) at different observation angles by experiment. The UAV and its engine are tested on the ground in the cruise state. Spectral radiation intensities at different observation angles are obtained in the infrared band of 0.9–15 μm by a spectral radiometer. Meanwhile, infrared images are captured separately by long-wavelength infrared (LWIR), mid-wavelength infrared (MWIR), and short-wavelength infrared (SWIR) cameras. Additionally, orientation maps of the radiation area and radiance are obtained. The results suggest that the spectral radiation intensity of the UAV is determined by its exhaust plume and that the main infrared emission bands occur at 2.7 μm and 4.3 μm. At observation angles in the range of 0°–90°, the radiation area of the UAV in MWIR band is greatest; however, at angles greater than 90°, the radiation area in the SWIR band is greatest. In addition, the radiance of the UAV at an angle of 0° is strongest. These conclusions can guide IR stealth technique development for UAVs.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 8
    Publication Date: 2018-02-02
    Description: Sensors, Vol. 18, Pages 426: Amyloid Beta Detection by Faradaic Electrochemical Impedance Spectroscopy Using Interdigitated Microelectrodes Sensors doi: 10.3390/s18020426 Authors: Jin Park Hye Kim Ji-Hoon Lee Jung Park Jinsik Kim Kyo Hwang Byung Lee Faradaic electrochemical impedance spectroscopy (f-EIS) in the presence of redox reagent, e.g., [Fe(CN)6]3−/4−, is widely used in biosensors owing to its high sensitivity. However, in sensors detecting amyloid beta (Aβ), the redox reagent can cause the aggregation of Aβ, which is a disturbance factor in accurate detection. Here, we propose an interdigitated microelectrode (IME) based f-EIS technique that can alleviate the aggregation of Aβ and achieve high sensitivity by buffer control. The proposed method was verified by analyzing three different EIS-based sensors: non-faradaic EIS (nf-EIS), f-EIS, and the proposed f-EIS with buffer control. We analyzed the equivalent circuits of nf-EIS and f-EIS sensors. The dominant factors of sensitivity were analyzed, and the impedance change rates via Aβ reaction was compared. We measured the sensitivity of the IME sensors based on nf-EIS, f-EIS, and the proposed f-EIS. The results demonstrate that the proposed EIS-based IME sensor can detect Aβ with a sensitivity of 7.40-fold and 10.93-fold higher than the nf-EIS and the f-EIS sensors, respectively.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 9
    Publication Date: 2018-02-02
    Description: Sensors, Vol. 18, Pages 425: Game Theory-Based Cooperation for Underwater Acoustic Sensor Networks: Taxonomy, Review, Research Challenges and Directions Sensors doi: 10.3390/s18020425 Authors: Dalhatu Muhammed Mohammad Anisi Mahdi Zareei Cesar Vargas-Rosales Anwar Khan Exploring and monitoring the underwater world using underwater sensors is drawing a lot of attention these days. In this field cooperation between acoustic sensor nodes has been a critical problem due to the challenging features such as acoustic channel failure (sound signal), long propagation delay of acoustic signal, limited bandwidth and loss of connectivity. There are several proposed methods to improve cooperation between the nodes by incorporating information/game theory in the node’s cooperation. However, there is a need to classify the existing works and demonstrate their performance in addressing the cooperation issue. In this paper, we have conducted a review to investigate various factors affecting cooperation in underwater acoustic sensor networks. We study various cooperation techniques used for underwater acoustic sensor networks from different perspectives, with a concentration on communication reliability, energy consumption, and security and present a taxonomy for underwater cooperation. Moreover, we further review how the game theory can be applied to make the nodes cooperate with each other. We further analyze different cooperative game methods, where their performance on different metrics is compared. Finally, open issues and future research direction in underwater acoustic sensor networks are highlighted.
    Electronic ISSN: 1424-8220
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  • 10
    Publication Date: 2018-02-02
    Description: Sensors, Vol. 18, Pages 427: A New Real-Time Cycle Slip Detection and Repair Method under High Ionospheric Activity for a Triple-Frequency GPS/BDS Receiver Sensors doi: 10.3390/s18020427 Authors: Wanke Liu Xueyuan Jin Mingkui Wu Jie Hu Yun Wu Cycle slip detection and repair is a prerequisite for high-precision global navigation satellite system (GNSS)-based positioning. With the modernization and development of GNSS systems, more satellites are available to transmit triple-frequency signals, which allows the introduction of additional linear combinations and provides new opportunities for cycle slip detection and repair. In this paper, we present a new real-time cycle slip detection and repair method under high ionospheric activity for undifferenced Global Positioning System (GPS)/BeiDou Navigation Satellite System (BDS) triple-frequency observations collected with a single receiver. First, three optimal linearly independent geometry-free pseudorange minus phase combinations are selected to correctly and uniquely determine the cycle slips on the original triple-frequency carrier phase observations. Then, a second-order time-difference algorithm is employed for the pseudorange minus phase combinations to mitigate the impact of between-epoch ionospheric residuals on cycle slip detection, which is especially beneficial under high ionospheric activity. The performance of the approach is verified with static GPS/BDS triple-frequency observations that are collected with a 30 s sampling interval under active ionospheric conditions, and observations are manually inserted with simulated cycle slips. The results show that the method can correctly detect and repair cycle slips at a resolution as small as 1 cycle. Moreover, kinematic data collected from car-driven and airborne experiments are also processed to verify the performance of the method. The experimental results also demonstrate that the method is effective in processing kinematic data.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 11
    Publication Date: 2018-02-02
    Description: Sensors, Vol. 18, Pages 422: The Effects of Graphene Stacking on the Performance of Methane Sensor: A First-Principles Study on the Adsorption, Band Gap and Doping of Graphene Sensors doi: 10.3390/s18020422 Authors: Ning Yang Daoguo Yang Guoqi Zhang Liangbiao Chen Dongjing Liu Miao Cai Xuejun Fan The effects of graphene stacking are investigated by comparing the results of methane adsorption energy, electronic performance, and the doping feasibility of five dopants (i.e., B, N, Al, Si, and P) via first-principles theory. Both zigzag and armchair graphenes are considered. It is found that the zigzag graphene with Bernal stacking has the largest adsorption energy on methane, while the armchair graphene with Order stacking is opposite. In addition, both the Order and Bernal stacked graphenes possess a positive linear relationship between adsorption energy and layer number. Furthermore, they always have larger adsorption energy in zigzag graphene. For electronic properties, the results show that the stacking effects on band gap are significant, but it does not cause big changes to band structure and density of states. In the comparison of distance, the average interlamellar spacing of the Order stacked graphene is the largest. Moreover, the adsorption effect is the result of the interactions between graphene and methane combined with the change of graphene’s structure. Lastly, the armchair graphene with Order stacking possesses the lowest formation energy in these five dopants. It could be the best choice for doping to improve the methane adsorption.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 12
    Publication Date: 2018-02-02
    Description: Sensors, Vol. 18, Pages 424: A Simple Surface-Enhanced Raman Spectroscopic Method for on-Site Screening of Tetracycline Residue in Whole Milk Sensors doi: 10.3390/s18020424 Authors: Sagar Dhakal Kuanglin Chao Qing Huang Moon Kim Walter Schmidt Jianwei Qin C. Broadhurst Therapeutic and subtherapeutic use of veterinary drugs has increased the risk of residue contamination in animal food products. Antibiotics such as tetracycline are used for mastitis treatment of lactating cows. Milk expressed from treated cows before the withdrawal period has elapsed may contain tetracycline residue. This study developed a simple surface-enhanced Raman spectroscopic (SERS) method for on-site screening of tetracycline residue in milk and water. Six batches of silver colloid nanoparticles were prepared for surface enhancement measurement. Milk-tetracycline and water-tetracycline solutions were prepared at seven concentration levels (1000, 500, 100, 10, 1, 0.1, and 0.01 ppm) and spiked with silver colloid nanoparticles. A 785 nm Raman spectroscopic system was used for spectral measurement. Tetracycline vibrational modes were observed at 1285, 1317 and 1632 cm−1 in water-tetracycline solutions and 1322 and 1621 cm−1 (shifted from 1317 and 1632 cm−1, respectively) in milk-tetracycline solutions. Tetracycline residue concentration as low as 0.01 ppm was detected in both the solutions. The peak intensities at 1285 and 1322 cm−1 were used to estimate the tetracycline concentrations in water and milk with correlation coefficients of 0.92 for water and 0.88 for milk. Results indicate that this SERS method is a potential tool that can be used on-site at field production for qualitative and quantitative detection of tetracycline residues.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 13
    Publication Date: 2018-02-02
    Description: Sensors, Vol. 18, Pages 423: Energy Level-Based Abnormal Crowd Behavior Detection Sensors doi: 10.3390/s18020423 Authors: Xuguang Zhang Qian Zhang Shuo Hu Chunsheng Guo Hui Yu The change of crowd energy is a fundamental measurement for describing a crowd behavior. In this paper, we present a crowd abnormal detection method based on the change of energy-level distribution. The method can not only reduce the camera perspective effect, but also detect crowd abnormal behavior in time. Pixels in the image are treated as particles, and the optical flow method is adopted to extract the velocities of particles. The qualities of different particles are distributed as different value according to the distance between the particle and the camera to reduce the camera perspective effect. Then a crowd motion segmentation method based on flow field texture representation is utilized to extract the motion foreground, and a linear interpolation calculation is applied to pedestrian’s foreground area to determine their distance to the camera. This contributes to the calculation of the particle qualities in different locations. Finally, the crowd behavior is analyzed according to the change of the consistency, entropy and contrast of the three descriptors for co-occurrence matrix. By calculating a threshold, the timestamp when the crowd abnormal happens is determined. In this paper, multiple sets of videos from three different scenes in UMN dataset are employed in the experiment. The results show that the proposed method is effective in characterizing anomalies in videos.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 14
    Publication Date: 2018-02-03
    Description: IJERPH, Vol. 15, Pages 252: Residents’ Self-Reported Health Effects and Annoyance in Relation to Air Pollution Exposure in an Industrial Area in Eastern-Estonia International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020252 Authors: Hans Orru Jane Idavain Mihkel Pindus Kati Orru Kaisa Kesanurm Aavo Lang Jelena Tomasova Eastern Estonia has large oil shale mines and industrial facilities mainly focused on electricity generation from oil shale and shale oil extraction, which produce high air pollution emissions. The “Study of the health impact of the oil shale sector—SOHOS” was aimed at identifying the impacts on residents’ health and annoyance due to the industrial processing. First, a population-wide survey about health effects and annoyance was carried out. Second, the total and oil shale sectors’ emitted concentrations of benzene, phenol, and PM2.5 were modelled. Third, the differences between groups were tested and relationships between health effects and environmental pollution studied using multiple regression analysis. Compared to the control groups from non-industrial areas in Tartu or Lääne-Viru, residents of Ida-Viru more frequently (p < 0.05) reported wheezing, chest tightness, shortness of breath, asthma attacks, a long-term cough, hypertension, heart diseases, myocardial infarction, stroke, and diabetes. All health effects except asthma were reported more frequently among non-Estonians. People living in regions with higher levels of PM2.5, had significantly higher odds (p < 0.05) of experiencing chest tightness (OR = 1.13, 95% CI 1.02–1.26), shortness of breath (1.16, 1.03–1.31) or an asthma attack (1.22, 1.04–1.42) during the previous year. People living in regions with higher levels of benzene had higher odds of experiencing myocardial infarction (1.98, 1.11–3.53) and with higher levels of phenol chest tightness (1.44, 1.03–2.00), long-term cough (1.48, 1.06–2.07) and myocardial infarction (2.17, 1.23–3.83). The prevalence of adverse health effects was also higher among those who had been working in the oil shale sector. Next to direct health effects, up to a quarter of the residents of Ida-Viru County were highly annoyed about air pollution. Perceived health risk from air pollution increased the odds of being annoyed. Annoyed people in Ida-Viru had significantly higher odds of experiencing respiratory symptoms during the last 12 months, e.g., wheezing (2.30, 1.31–4.04), chest tightness (2.88, 1.91–4.33 or attack of coughing (1.99, 1.34–2.95).
    Print ISSN: 1661-7827
    Electronic ISSN: 1660-4601
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Medicine
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  • 15
    Publication Date: 2018-02-04
    Description: IJERPH, Vol. 15, Pages 258: Predicting Effects of the Self and Contextual Factors on Violence: A Comparison between School Students and Youth Offenders in Macau International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020258 Authors: T. Lo Christopher Cheng This study was designed to explore the self and contextual factors for violence in two samples of school students and youth offenders in Macau. There were 3085 participants who were between 12 and 20 years old; 48.3% of them were male and 51.7% female. Findings revealed that youth offenders exhibited more violence than school students. For the self factors, while lower self-esteem and higher self-efficacy of school students were associated with more violent behavior, these two variables had no significant effects for youth offenders. For the contextual factors, family conflict was the strongest predictor of violence, and school commitment/attachment was the weakest predictor for both samples. For youth offenders, family conflict had the largest direct effect, followed by susceptibility to negative peer influence and influence of the Triad gangs, while school commitment/attachment had a significant though mild direct effect. For school students, family conflict mediated the effect of self-esteem and self-efficacy on violence. While Triad gangs’ influence was the second strongest predictor of violence, being exposed to Triad gangs’ influence also mediated the effect of self-esteem and self-efficacy on violence. It is recommended that youth outreach services with a focus on family support and gang detachment for at-risk youth be strengthened.
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    Topics: Energy, Environment Protection, Nuclear Power Engineering , Medicine
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  • 16
    Publication Date: 2018-02-04
    Description: IJERPH, Vol. 15, Pages 253: Review of Non-Respiratory, Non-Cancer Physical Health Conditions from Exposure to the World Trade Center Disaster International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020253 Authors: Lisa Gargano Kimberly Mantilla Monique Fairclough Shengchao Yu Robert Brackbill After the World Trade Center attacks on 11 September 2001 (9/11), multiple cohorts were developed to monitor the health outcomes of exposure. Respiratory and cancer effects have been covered at length. This current study sought to review the literature on other physical conditions associated with 9/11-exposure. Researchers searched seven databases for literature published in English from 2002 to October 2017, coded, and included articles for health condition outcome, population, 9/11-exposures, and comorbidity. Of the 322 titles and abstracts screened, 30 studies met inclusion criteria, and of these, 28 were from three cohorts: the World Trade Center Health Registry, Fire Department of New York, and World Trade Center Health Consortium. Most studies focused on rescue and recovery workers. While many of the findings were consistent across different populations and supported by objective measures, some of the less studied conditions need additional research to substantiate current findings. In the 16 years after 9/11, longitudinal cohorts have been essential in investigating the health consequences of 9/11-exposure. Longitudinal studies will be vital in furthering our understanding of these emerging conditions, as well as treatment effectiveness.
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  • 17
    Publication Date: 2018-02-04
    Description: IJERPH, Vol. 15, Pages 259: Converging Human and Malaria Vector Diagnostics with Data Management towards an Integrated Holistic One Health Approach International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020259 Authors: Konstantinos Mitsakakis Sebastian Hin Pie Müller Nadja Wipf Edward Thomsen Michael Coleman Roland Zengerle John Vontas Konstantinos Mavridis Monitoring malaria prevalence in humans, as well as vector populations, for the presence of Plasmodium, is an integral component of effective malaria control, and eventually, elimination. In the field of human diagnostics, a major challenge is the ability to define, precisely, the causative agent of fever, thereby differentiating among several candidate (also non-malaria) febrile diseases. This requires genetic-based pathogen identification and multiplexed analysis, which, in combination, are hardly provided by the current gold standard diagnostic tools. In the field of vectors, an essential component of control programs is the detection of Plasmodium species within its mosquito vectors, particularly in the salivary glands, where the infective sporozoites reside. In addition, the identification of species composition and insecticide resistance alleles within vector populations is a primary task in routine monitoring activities, aiming to support control efforts. In this context, the use of converging diagnostics is highly desirable for providing comprehensive information, including differential fever diagnosis in humans, and mosquito species composition, infection status, and resistance to insecticides of vectors. Nevertheless, the two fields of human diagnostics and vector control are rarely combined, both at the diagnostic and at the data management end, resulting in fragmented data and mis- or non-communication between various stakeholders. To this direction, molecular technologies, their integration in automated platforms, and the co-assessment of data from multiple diagnostic sources through information and communication technologies are possible pathways towards a unified human vector approach.
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  • 18
    Publication Date: 2018-02-04
    Description: IJERPH, Vol. 15, Pages 255: Long-Term Effectiveness of Stress Management at Work: Effects of the Changes in Perceived Stress Reactivity on Mental Health and Sleep Problems Seven Years Later International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020255 Authors: Raphael Herr Amira Barrech Natalie Riedel Harald Gündel Peter Angerer Jian Li The reduction of stress reactivity resulting from stress management interventions prevents disorders and improves mental health, however, its long-term sustainability has been little examined. The objective of this study was, therefore, to determine the effectiveness of a stress management intervention, designed to improve stress reactivity, for mental health and sleep problems seven years later, using longitudinal data from 101 male industrial workers. Linear regressions estimated the adjusted effects of the changes in stress reactivity in general as well as in its six subdimensions (work overload, social conflict, social stress, failure at work, and anticipatory and prolonged reactivity) on depression, anxiety, and sleep problems seven years later. The improvement of the prolonged reactivity had positive effects on depression, anxiety, and sleep problems (unstandardized regression coefficients [Bs] ≥ 0.35, all p-values ≤ 0.01). Depression and sleep problems were further improved by a reduction of the reactivity to social conflicts (Bs ≥ 0.29, p-values < 0.05), and an improvement in the overall reactivity score positively influenced sleep problems (B = 0.07, p = 0.017). In conclusion, the improvement of stress reactivity resulting from a work stress intervention was effective and generally long-lasting in preventing mental health and sleep problems. The reduction of the prolonged reactivity seems of particular importance and efficient in inhibiting negative stress manifestations.
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  • 19
    Publication Date: 2018-02-04
    Description: IJERPH, Vol. 15, Pages 261: Adverse Pregnancy Outcomes among Adolescents in Northwest Russia: A Population Registry-Based Study International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020261 Authors: Anna Usynina Vitaly Postoev Jon Odland Andrej Grjibovski This study aimed to assess whether adolescents have an increased risk of adverse pregnancy outcomes (APO) compared to adult women. We used data on 43,327 births from the population-based Arkhangelsk County Birth Registry, Northwest Russia, for 2012–2014. The perinatal outcomes included stillbirth, preterm birth (<37 and <32 weeks), low and very low birthweight, 5 min Apgar score <7 and <4, perinatal infections, and the need for neonatal transfer to a higher-level hospital. Multivariable logistic regression was applied to assess the associations between age and APO. Altogether, 4.7% of deliveries occurred in adolescents. Both folic acid intake and multivitamin intake during pregnancy were more prevalent in adults. Adolescents were more likely to be underweight, to smoke, and to have infections of the kidney and the genital tract compared to adult women. Compared to adults, adolescents were at lower risk of low birthweight, a 5 min Apgar score <7, and need for neonatal transfer. Adolescents had no increased risk of other APO studied in the adjusted analysis, suggesting that a constellation of other factors, but not young age per se, is associated with APO in the study setting.
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    Topics: Energy, Environment Protection, Nuclear Power Engineering , Medicine
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  • 20
    Publication Date: 2018-02-04
    Description: IJERPH, Vol. 15, Pages 257: Air Pollution and Otitis Media in Children: A Systematic Review of Literature International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020257 Authors: Gayan Bowatte Rachel Tham Jennifer Perret Michael Bloom Guanghui Dong Nilakshi Waidyatillake Dinh Bui Geoffrey Morgan Bin Jalaludin Caroline Lodge Shyamali Dharmage Young children are particularly vulnerable to otitis media (OM) which globally affects over 80% of children below the age of 3 years. Although there is convincing evidence for an association between environmental tobacco smoke exposure and OM in children, the relationship with ambient air pollution is not clear. We aimed to systematically review the literature on the relationship between ambient air pollution exposure and OM in children. A systematic search was performed in PubMed and EMBASE databases. Of 934 references identified, 24 articles were included. There is an increasing body of evidence supporting an association between higher ambient air pollution exposure and a higher risk of OM in children. While NO2 showed the most consistent association with OM, other specific pollutants showed inconsistent associations. Studies were mainly conducted in high/middle income countries with limited evidence from low-income countries. Although there was a general consensus that higher air pollution exposure is associated with a greater prevalence of OM, the evidence for associations with specific pollutants is inconsistent. More well-designed studies on associations between specific air pollutants as risk factors for OM are warranted, especially in low income countries with high air pollution levels.
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  • 21
    Publication Date: 2018-02-04
    Description: IJERPH, Vol. 15, Pages 262: Stepping It Up: Walking Behaviors in Children Transitioning from 5th to 7th Grade International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020262 Authors: Sharon Ross Morgan Clennin Marsha Dowda Natalie Colabianchi Russell Pate The purpose of this study was to (1) describe children’s walking behaviors in 5th to 7th grade and change over time and (2) examine associations between walking behaviors and Walk Score®. Participants consisted of n = 586 students from the Transitions and Activity Changes in Kids (TRACK) Study. Children reported any walking behavior (e.g., exercise and transportation) over the past five days. Walk Score was calculated based on children’s home address. Descriptive statistics summarized walking behaviors by gender and time, and repeated measure mixed models examined the relationship between walking behaviors and Walk Score. Approximately 46.8% and 19.2% of 5th grade children reported walking for exercise and transportation, respectively, and these percentages declined through 7th grade. Girls reported higher levels of total walking behavior and walking for exercise than boys (p < 0.001). Girls with a higher Walk Score had 63% higher odds of reporting walking for transportation than girls with a lower Walk Score (OR = 1.63, 95% CI = 1.02, 2.62). Walking behaviors among children were infrequent with significant declines over time, and of the nine associations examined with Walk Score, only one was significant. Efforts should prioritize frequent walking behavior and community design to increase children’s physical activity.
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  • 22
    Publication Date: 2018-02-04
    Description: IJERPH, Vol. 15, Pages 256: Relative Contributions of Different Lifestyle Factors to Health-Related Quality of Life in the Elderly International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020256 Authors: Xiaona Zhang Ruyi Xia Shu Wang Wei Xue Jian Yang Shuliu Sun Guihua Zhuang Much of the previous literature has studied the relationship between individual lifestyle factors and the health-related quality of life (HRQOL). However, only a few studies combined them to explore their relative importance to the HRQOL in the elderly. This study assesses the HRQOL of the urban, rural, and institutionalized Chinese elderly and explores the relative contributions of different lifestyle factors to their HRQOL. The SF-36v2 Health Survey, the WHOQOL-OLD module, and the socio-demographic and lifestyle questionnaire were utilized in this study. Hierarchical regression was performed in order to analyze the results. The physical and mental component scores of the SF-36v2 survey were 47.05 ± 9.95 and 54.92 ± 9.92, respectively. The total score for the WHOQOL-OLD module was 73.01 ± 11.99, with institutionalized persons reporting lower scores. For the physical component of the elderly participants’ HRQOL, the R2 value changed the most (0.116) when exercise-and-labor-related factors were added in. For the mental component, sleep-related (0.054), and leisure-time-activity-related factors (0.053) caused the largest change of the R2 value. For the elderly-specific HRQOL, measured by the WHOQOL-OLD module, the leisure-time-activity-related factors caused the largest change in the R2 value (0.119), followed by exercise-and-labor-related factors (0.078). Heterogeneity was present among the three subgroups. In sum, compared with their community-dwelling counterparts, the HRQOL of institutionalized older people was relatively poor and different lifestyle factors contributed to the HRQOL differently.
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  • 23
    Publication Date: 2018-02-04
    Description: IJERPH, Vol. 15, Pages 254: Adapting, Pilot Testing and Evaluating the Kick.it App to Support Smoking Cessation for Smokers with Severe Mental Illness: A Study Protocol International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020254 Authors: Sharon Lawn Joseph van Agteren Sara Zabeen Sue Bertossa Christopher Barton James Stewart (1) Background: While the prevalence of tobacco smoking in the general population has declined, it remains exceptionally high for smokers with severe mental illness (SMI), despite significant public health measures. This project aims to adapt, pilot test and evaluate a novel e-health smoking cessation intervention to assist relapse prevention and encourage sustained smoking cessation for young adults (aged 18–29 years) with SMI. (2) Methods: Using co-design principles, the researchers will adapt the Kick.it smartphone App in collaboration with a small sample of current and ex-smokers with SMI. In-depth interviews with smokers with SMI who have attempted to quit in the past 12 months and ex-smokers (i.e., those having not smoked in the past seven days) will explore their perceptions of smoking cessation support options that have been of value to them. Focus group participants will then give their feedback on the existing Kick.it App and any adaptations needed. The adapted App will then be pilot-tested with a small sample of young adult smokers with SMI interested in attempting to cut down or quit smoking, measuring utility, feasibility, acceptability, and preliminary outcomes in supporting their quit efforts. (3) Conclusions: This pilot work will inform a larger definitive trial. Dependent on recruitment success, the project may extend to also include smokers with SMI who are aged 30 years or more.
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  • 24
    Publication Date: 2018-02-06
    Description: Future Internet, Vol. 10, Pages 17: Increasing Trustworthiness of Face Authentication in Mobile Devices by Modeling Gesture Behavior and Location Using Neural Networks Future Internet doi: 10.3390/fi10020017 Authors: Blerim Rexha Gresa Shala Valon Xhafa Personal mobile devices currently have access to a significant portion of their user’s private sensitive data and are increasingly used for processing mobile payments. Consequently, securing access to these mobile devices is a requirement for securing access to the sensitive data and potentially costly services. Face authentication is one of the promising biometrics-based user authentication mechanisms that has been widely available in this era of mobile computing. With a built-in camera capability on smartphones, tablets, and laptops, face authentication provides an attractive alternative of legacy passwords for its memory-less authentication process, which is so sophisticated that it can unlock the device faster than a fingerprint. Nevertheless, face authentication in the context of smartphones has proven to be vulnerable to attacks. In most current implementations, a sufficiently high-resolution face image displayed on another mobile device will be enough to circumvent security measures and bypass the authentication process. In order to prevent such bypass attacks, gesture recognition together with location is proposed to be additionally modeled. Gestures provide a faster and more convenient method of authentication compared to a complex password. The focus of this paper is to build a secure authentication system with face, location and gesture recognition as components. User gestures and location data are a sequence of time series; therefore, in this paper we propose to use unsupervised learning in the long short-term memory recurrent neural network to actively learn to recognize, group and discriminate user gestures and location. Moreover, a clustering-based technique is also implemented for recognizing gestures and location.
    Electronic ISSN: 1999-5903
    Topics: Computer Science
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  • 25
    Publication Date: 2018-02-06
    Description: IJERPH, Vol. 15, Pages 271: Empirical Study on the Sustainability of China’s Grain Quality Improvement: The Role of Transportation, Labor, and Agricultural Machinery International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020271 Authors: Ming Zhang Fang Duan Zisen Mao As a major part of farming sustainability, the issues of grain production and its quality improvement have been important in many countries. This paper aims to address these issues in China. Based on the data from the main production provinces and by applying the stochastic frontier analysis methodology, we find that the improvement of transportation and the use of agricultural machinery have become the main driving forces for grain quality improvement in China. After further studying different provinces’ potentials of grain quality improvement, we show that grain quality has increased steadily. Therefore, we can conclude China’s grain quality improvement is indeed sustainable. Furthermore, different grains like rice, wheat, and corn share similar characteristics in terms of quality improvement, but the improvement rate for rice is relatively low, while those of corn and wheat are relatively high. Moreover, the overall change of efficiency gain of grain quality improvement is not significant for different provinces. The efficiency gains of the quality improvements for rice and wheat even decrease slightly. In addition, we find that only expanding grain quality improvement potential can simultaneously achieve the dual objectives of improving grain quality and increasing yield.
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  • 26
    Publication Date: 2018-02-06
    Description: Sensors, Vol. 18, Pages 469: Secure Indoor Localization Based on Extracting Trusted Fingerprint Sensors doi: 10.3390/s18020469 Authors: Juan Luo Xixi Yin Yanliu Zheng Chun Wang [-5]Indoor localization based on WiFi has attracted a lot of research effort because of the widespread application of WiFi. Fingerprinting techniques have received much attention due to their simplicity and compatibility with existing hardware. However, existing fingerprinting localization algorithms may not resist abnormal received signal strength indication (RSSI), such as unexpected environmental changes, impaired access points (APs) or the introduction of new APs. Traditional fingerprinting algorithms do not consider the problem of new APs and impaired APs in the environment when using RSSI. In this paper, we propose a secure fingerprinting localization (SFL) method that is robust to variable environments, impaired APs and the introduction of new APs. In the offline phase, a voting mechanism and a fingerprint database update method are proposed. We use the mutual cooperation between reference anchor nodes to update the fingerprint database, which can reduce the interference caused by the user measurement data. We analyze the standard deviation of RSSI, mobilize the reference points in the database to vote on APs and then calculate the trust factors of APs based on the voting results. In the online phase, we first make a judgment about the new APs and the broken APs, then extract the secure fingerprints according to the trusted factors of APs and obtain the localization results by using the trusted fingerprints. In the experiment section, we demonstrate the proposed method and find that the proposed strategy can resist abnormal RSSI and can improve the localization accuracy effectively compared with the existing fingerprinting localization algorithms.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 27
    Publication Date: 2018-02-06
    Description: Sensors, Vol. 18, Pages 464: Foil Strain Gauges Using Piezoresistive Carbon Nanotube Yarn: Fabrication and Calibration Sensors doi: 10.3390/s18020464 Authors: Jandro Abot Mário Góngora-Rubio Jude Anike César Kiyono Luis A. Mello Valtemar Cardoso Reinaldo L. Rosa Derek Kuebler Grace Brodeur Amani Alotaibi Marisa Coene Lauren Coene Elizabeth Jean Rafael Santiago Francisco H. Oliveira Ricardo Rangel Gilles Thomas Kalayu Belay Luciana da Silva Rafael Moura Antonio Seabra Emílio C. Silva Carbon nanotube yarns are micron-scale fibers comprised by tens of thousands of carbon nanotubes in their cross section and exhibiting piezoresistive characteristics that can be tapped to sense strain. This paper presents the details of novel foil strain gauge sensor configurations comprising carbon nanotube yarn as the piezoresistive sensing element. The foil strain gauge sensors are designed using the results of parametric studies that maximize the sensitivity of the sensors to mechanical loading. The fabrication details of the strain gauge sensors that exhibit the highest sensitivity, based on the modeling results, are described including the materials and procedures used in the first prototypes. Details of the calibration of the foil strain gauge sensors are also provided and discussed in the context of their electromechanical characterization when bonded to metallic specimens. This characterization included studying their response under monotonic and cyclic mechanical loading. It was shown that these foil strain gauge sensors comprising carbon nanotube yarn are sensitive enough to capture strain and can replicate the loading and unloading cycles. It was also observed that the loading rate affects their piezoresistive response and that the gauge factors were all above one order of magnitude higher than those of typical metallic foil strain gauges. Based on these calibration results on the initial sensor configurations, new foil strain gauge configurations will be designed and fabricated, to increase the strain gauge factors even more.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 28
    Publication Date: 2018-02-07
    Description: Algorithms, Vol. 11, Pages 17: An Improved Bacterial-Foraging, Optimization-Based Machine Learning Framework for Predicting the Severity of Somatization Disorder Algorithms doi: 10.3390/a11020017 Authors: Xinen Lv Huiling Chen Qian Zhang Xujie Li Hui Huang Gang Wang It is of great clinical significance to establish an accurate intelligent model to diagnose the somatization disorder of community correctional personnel. In this study, a novel machine learning framework is proposed to predict the severity of somatization disorder in community correction personnel. The core of this framework is to adopt the improved bacterial foraging optimization (IBFO) to optimize two key parameters (penalty coefficient and the kernel width) of a kernel extreme learning machine (KELM) and build an IBFO-based KELM (IBFO-KELM) for the diagnosis of somatization disorder patients. The main innovation point of the IBFO-KELM model is the introduction of opposition-based learning strategies in traditional bacteria foraging optimization, which increases the diversity of bacterial species, keeps a uniform distribution of individuals of initial population, and improves the convergence rate of the BFO optimization process as well as the probability of escaping from the local optimal solution. In order to verify the effectiveness of the method proposed in this study, a 10-fold cross-validation method based on data from a symptom self-assessment scale (SCL-90) is used to make comparison among IBFO-KELM, BFO-KELM (model based on the original bacterial foraging optimization model), GA-KELM (model based on genetic algorithm), PSO-KELM (model based on particle swarm optimization algorithm) and Grid-KELM (model based on grid search method). The experimental results show that the proposed IBFO-KELM prediction model has better performance than other methods in terms of classification accuracy, Matthews correlation coefficient (MCC), sensitivity and specificity. It can distinguish very well between severe somatization disorder and mild somatization and assist the psychological doctor with clinical diagnosis.
    Electronic ISSN: 1999-4893
    Topics: Computer Science
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  • 29
    Publication Date: 2018-02-06
    Description: Sensors, Vol. 18, Pages 467: Implementation of a Surface Electromyography-Based Upper Extremity Exoskeleton Controller Using Learning from Demonstration Sensors doi: 10.3390/s18020467 Authors: Ho Chit Siu Ana M. Arenas Tingxiao Sun Leia A. Stirling Upper-extremity exoskeletons have demonstrated potential as augmentative, assistive, and rehabilitative devices. Typical control of upper-extremity exoskeletons have relied on switches, force/torque sensors, and surface electromyography (sEMG), but these systems are usually reactionary, and/or rely on entirely hand-tuned parameters. sEMG-based systems may be able to provide anticipatory control, since they interface directly with muscle signals, but typically require expert placement of sensors on muscle bodies. We present an implementation of an adaptive sEMG-based exoskeleton controller that learns a mapping between muscle activation and the desired system state during interaction with a user, generating a personalized sEMG feature classifier to allow for anticipatory control. This system is robust to novice placement of sEMG sensors, as well as subdermal muscle shifts. We validate this method with 18 subjects using a thumb exoskeleton to complete a book-placement task. This learning-from-demonstration system for exoskeleton control allows for very short training times, as well as the potential for improvement in intent recognition over time, and adaptation to physiological changes in the user, such as those due to fatigue.
    Electronic ISSN: 1424-8220
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  • 30
    Publication Date: 2018-02-06
    Description: Sensors, Vol. 18, Pages 468: Flexible Piezoelectric Sensor-Based Gait Recognition Sensors doi: 10.3390/s18020468 Authors: Youngsu Cha Hojoon Kim Doik Kim Most motion recognition research has required tight-fitting suits for precise sensing. However, tight-suit systems have difficulty adapting to real applications, because people normally wear loose clothes. In this paper, we propose a gait recognition system with flexible piezoelectric sensors in loose clothing. The gait recognition system does not directly sense lower-body angles. It does, however, detect the transition between standing and walking. Specifically, we use the signals from the flexible sensors attached to the knee and hip parts on loose pants. We detect the periodic motion component using the discrete time Fourier series from the signal during walking. We adapt the gait detection method to a real-time patient motion and posture monitoring system. In the monitoring system, the gait recognition operates well. Finally, we test the gait recognition system with 10 subjects, for which the proposed system successfully detects walking with a success rate over 93 %.
    Electronic ISSN: 1424-8220
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  • 31
    Publication Date: 2018-02-06
    Description: Sensors, Vol. 18, Pages 463: Naive Bayes Bearing Fault Diagnosis Based on Enhanced Independence of Data Sensors doi: 10.3390/s18020463 Authors: Nannan Zhang Lifeng Wu Jing Yang Yong Guan The bearing is the key component of rotating machinery, and its performance directly determines the reliability and safety of the system. Data-based bearing fault diagnosis has become a research hotspot. Naive Bayes (NB), which is based on independent presumption, is widely used in fault diagnosis. However, the bearing data are not completely independent, which reduces the performance of NB algorithms. In order to solve this problem, we propose a NB bearing fault diagnosis method based on enhanced independence of data. The method deals with data vector from two aspects: the attribute feature and the sample dimension. After processing, the classification limitation of NB is reduced by the independence hypothesis. First, we extract the statistical characteristics of the original signal of the bearings effectively. Then, the Decision Tree algorithm is used to select the important features of the time domain signal, and the low correlation features is selected. Next, the Selective Support Vector Machine (SSVM) is used to prune the dimension data and remove redundant vectors. Finally, we use NB to diagnose the fault with the low correlation data. The experimental results show that the independent enhancement of data is effective for bearing fault diagnosis.
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  • 32
    Publication Date: 2018-02-07
    Description: Entropy, Vol. 20, Pages 107: Detection of Parameter Change in Random Coefficient Integer-Valued Autoregressive Models Entropy doi: 10.3390/e20020107 Authors: Jiwon Kang This paper considers the problem of testing for parameter change in random coefficient integer-valued autoregressive models. To overcome some size distortions of the existing estimate-based cumulative sum (CUSUM) test, we suggest estimating function-based test and residual-based CUSUM test. More specifically, we employ the estimating function of the conditional least squares estimator. Under the regularity conditions and the null hypothesis, we derive their limiting distributions, respectively. Simulation results demonstrate the validity of the proposed tests. A real data analysis is performed on the polio incidence data.
    Electronic ISSN: 1099-4300
    Topics: Chemistry and Pharmacology , Physics
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  • 33
    Publication Date: 2018-02-07
    Description: IJERPH, Vol. 15, Pages 281: Stakeholders Opinions on Multi-Use Deep Water Offshore Platform in Hsiao-Liu-Chiu, Taiwan International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020281 Authors: Ya-Tsune Sie Pierre-Alexandre Château Yang-Chi Chang Shiau-Yun Lu This paper describes a group model building activity designed to elicit the potential effects a projected multi-use deep water offshore platform may have on its local environment, including ecological and socio-economic issues. As such a platform is proposed for construction around the island of Hsiao-Liu-Chiu, Taiwan, we organized several meetings with the local stakeholders and structured the debates using group modeling methods to promote consensus. During the process, the participants iteratively built and revised a causal-loop diagram that summarizes their opinions. Overall, local stakeholders concluded that a multi-use deep water offshore marine platform might have beneficial effects for Hsiao-Liu-Chiu because more tourists and fish could be attracted by the structure, but they also raised some potential problems regarding the law in Taiwan and the design of the offshore platform, especially its resistance to extreme weather. We report the method used and the main results and insights gained during the process.
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  • 34
    Publication Date: 2018-02-07
    Description: IJERPH, Vol. 15, Pages 275: Does Walkability Contribute to Geographic Variation in Psychosocial Distress? A Spatial Analysis of 91,142 Members of the 45 and Up Study in Sydney, Australia International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020275 Authors: Darren Mayne Geoffrey Morgan Bin Jalaludin Adrian Bauman Walkability describes the capacity of the built environment to promote walking, and has been proposed as a potential focus for community-level mental health planning. We evaluated this possibility by examining the contribution of area-level walkability to variation in psychosocial distress in a population cohort at spatial scales comparable to those used for regional planning in Sydney, Australia. Data on psychosocial distress were analysed for 91,142 respondents to the 45 and Up Study baseline survey between January 2006 and April 2009. We fit conditional auto regression models at the postal area level to obtain smoothed “disease maps” for psychosocial distress, and assess its association with area-level walkability after adjusting for individual- and area-level factors. Prevalence of psychosocial distress was 7.8%; similar for low (7.9%), low-medium (7.9%), medium-high (8.0%), and high (7.4%) walkability areas; and decreased with reducing postal area socioeconomic disadvantage: 12.2% (most), 9.3%, 7.5%, 5.9%, and 4.7% (least). Unadjusted disease maps indicated strong geographic clustering of psychosocial distress with 99.0% of excess prevalence due to unobserved and spatially structured factors, which was reduced to 55.3% in fully adjusted maps. Spatial and unstructured variance decreased by 97.3% and 39.8% after adjusting for individual-level factors, and another 2.3% and 4.2% with the inclusions of area-level factors. Excess prevalence of psychosocial distress in postal areas was attenuated in adjusted models but remained spatially structured. Postal area prevalence of high psychosocial distress is geographically clustered in Sydney, but is unrelated to postal area walkability. Area-level socioeconomic disadvantage makes a small contribution to this spatial structure; however, community-level mental health planning will likely deliver greatest benefits by focusing on individual-level contributors to disease burden and inequality associated with psychosocial distress.
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  • 35
    Publication Date: 2018-02-07
    Description: IJERPH, Vol. 15, Pages 279: Seasonal and Spatial Variability of Anthropogenic and Natural Factors Influencing Groundwater Quality Based on Source Apportionment International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020279 Authors: Xueru Guo Rui Zuo Li Meng Jinsheng Wang Yanguo Teng Xin Liu Minhua Chen Globally, groundwater resources are being deteriorated by rapid social development. Thus, there is an urgent need to assess the combined impacts of natural and enhanced anthropogenic sources on groundwater chemistry. The aim of this study was to identify seasonal characteristics and spatial variations in anthropogenic and natural effects, to improve the understanding of major hydrogeochemical processes based on source apportionment. 34 groundwater points located in a riverside groundwater resource area in northeast China were sampled during the wet and dry seasons in 2015. Using principal component analysis and factor analysis, 4 principal components (PCs) were extracted from 16 groundwater parameters. Three of the PCs were water-rock interaction (PC1), geogenic Fe and Mn (PC2), and agricultural pollution (PC3). A remarkable difference (PC4) was organic pollution originating from negative anthropogenic effects during the wet season, and geogenic F enrichment during the dry season. Groundwater exploitation resulted in dramatic depression cone with higher hydraulic gradient around the water source area. It not only intensified dissolution of calcite, dolomite, gypsum, Fe, Mn and fluorine minerals, but also induced more surface water recharge for the water source area. The spatial distribution of the PCs also suggested the center of the study area was extremely vulnerable to contamination by Fe, Mn, COD, and F−.
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  • 36
    Publication Date: 2018-02-07
    Description: Sensors, Vol. 18, Pages 486: VEHIOT: Design and Evaluation of an IoT Architecture Based on Low-Cost Devices to Be Embedded in Production Vehicles Sensors doi: 10.3390/s18020486 Authors: Jonatan Redondo Lisardo González Javier Guzman Beatriz Boada Vicente Díaz Nowadays, the current vehicles are incorporating control systems in order to improve their stability and handling. These control systems need to know the vehicle dynamics through the variables (lateral acceleration, roll rate, roll angle, sideslip angle, etc.) that are obtained or estimated from sensors. For this goal, it is necessary to mount on vehicles not only low-cost sensors, but also low-cost embedded systems, which allow acquiring data from sensors and executing the developed algorithms to estimate and to control with novel higher speed computing. All these devices have to be integrated in an adequate architecture with enough performance in terms of accuracy, reliability and processing time. In this article, an architecture to carry out the estimation and control of vehicle dynamics has been developed. This architecture was designed considering the basic principles of IoT and integrates low-cost sensors and embedded hardware for orchestrating the experiments. A comparison of two different low-cost systems in terms of accuracy, acquisition time and reliability has been done. Both devices have been compared with the VBOX device from Racelogic, which has been used as the ground truth. The comparison has been made from tests carried out in a real vehicle. The lateral acceleration and roll rate have been analyzed in order to quantify the error of these devices.
    Electronic ISSN: 1424-8220
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  • 37
    Publication Date: 2018-02-07
    Description: Sensors, Vol. 18, Pages 488: Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter Sensors doi: 10.3390/s18020488 Authors: Bingbing Gao Gaoge Hu Shesheng Gao Yongmin Zhong Chengfan Gu This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.
    Electronic ISSN: 1424-8220
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  • 38
    Publication Date: 2018-02-07
    Description: Sensors, Vol. 18, Pages 487: Off-Line Evaluation of Mobile-Centric Indoor Positioning Systems: The Experiences from the 2017 IPIN Competition Sensors doi: 10.3390/s18020487 Authors: Joaquín Torres-Sospedra Antonio Jiménez Adriano Moreira Tomás Lungenstrass Wei-Chung Lu Stefan Knauth Germán Mendoza-Silva Fernando Seco Antoni Pérez-Navarro Maria Nicolau António Costa Filipe Meneses Joaquín Farina Juan Morales Wen-Chen Lu Ho-Ti Cheng Shi-Shen Yang Shih-Hau Fang Ying-Ren Chien Yu Tsao The development of indoor positioning solutions using smartphones is a growing activity with an enormous potential for everyday life and professional applications. The research activities on this topic concentrate on the development of new positioning solutions that are tested in specific environments under their own evaluation metrics. To explore the real positioning quality of smartphone-based solutions and their capabilities for seamlessly adapting to different scenarios, it is needed to find fair evaluation frameworks. The design of competitions using extensive pre-recorded datasets is a valid way to generate open data for comparing the different solutions created by research teams. In this paper, we discuss the details of the 2017 IPIN indoor localization competition, the different datasets created, the teams participating in the event, and the results they obtained. We compare these results with other competition-based approaches (Microsoft and Perf-loc) and on-line evaluation web sites. The lessons learned by organising these competitions and the benefits for the community are addressed along the paper. Our analysis paves the way for future developments on the standardization of evaluations and for creating a widely-adopted benchmark strategy for researchers and companies in the field.
    Electronic ISSN: 1424-8220
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  • 39
    Publication Date: 2018-02-07
    Description: Sensors, Vol. 18, Pages 478: UV Absorption Spectroscopy in Water-Filled Antiresonant Hollow Core Fibers for Pharmaceutical Detection Sensors doi: 10.3390/s18020478 Authors: Mona Nissen Brenda Doherty Jonas Hamperl Jens Kobelke Karina Weber Thomas Henkel Markus Schmidt Due to a worldwide increased use of pharmaceuticals and, in particular, antibiotics, a growing number of these substance residues now contaminate natural water resources and drinking supplies. This triggers a considerable demand for low-cost, high-sensitivity methods for monitoring water quality. Since many biological substances exhibit strong and characteristic absorption features at wavelengths shorter than 300 nm, UV spectroscopy presents a suitable approach for the quantitative identification of such water-contaminating species. However, current UV spectroscopic devices often show limited light-matter interaction lengths, demand sophisticated and bulky experimental infrastructure which is not compatible with microfluidics, and leave large fractions of the sample analyte unused. Here, we introduce the concept of UV spectroscopy in liquid-filled anti-resonant hollow core fibers, with large core diameters and lengths of approximately 1 m, as a means to overcome such limitations. This extended light-matter interaction length principally improves the concentration detection limit by two orders of magnitude while using almost the entire sample volume—that is three orders of magnitude smaller compared to cuvette based approaches. By integrating the fibers into an optofluidic chip environment and operating within the lowest experimentally feasible transmission band, concentrations of the application-relevant pharmaceutical substances, sulfamethoxazole (SMX) and sodium salicylate (SS), were detectable down to 0.1 µM (26 ppb) and 0.4 µM (64 ppb), respectively, with the potential to reach significantly lower detection limits for further device integration.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 40
    Publication Date: 2018-02-07
    Description: Sensors, Vol. 18, Pages 473: A Quantization-Based Multibit Data Fusion Scheme for Cooperative Spectrum Sensing in Cognitive Radio Networks Sensors doi: 10.3390/s18020473 Authors: Yuanhua Fu Fan Yang Zhiming He Spectrum sensing remains a challenge in the context of cognitive radio networks (CRNs). Compared with traditional single-user sensing, cooperative spectrum sensing (CSS) exploits multiuser diversity to overcome channel fading, shadowing, and hidden terminal problems, which can effectively enhance the sensing performance and protect licensed users from harmful interference. However, for a large number of sensing nodes that need high bandwidth of the control channel for data transmitting, CSS increases cooperative overhead. To address this problem, we investigated the soft decision fusion strategy under a limited bandwidth of the control channel and proposed a simple quantization-based multibit data soft fusion rule for CSS for its simple structure and easily implementation. Under the quantization-based sensing strategy, each cooperative secondary user (SU) adopts an energy detector for local spectrum sensing. Each SU transmits quantized multibit data that sends local sensing information, instead of forwarding local one-bit hard decision results or original observation statistics, to the fusion center (FC). Furthermore, the closed-form expressions of the quantization levels and the quantization thresholds are analytically derived. Simulation results indicate that the detection performance of the proposed method approaches that of the conventional soft fusion rule with less cooperative overhead and outperforms the hard decision rules. Extensive simulations also show that multibit quantization fusion achieves a desirable tradeoff between the sensing performance and the control channel overhead for CSS.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 41
    Publication Date: 2018-02-07
    Description: Sensors, Vol. 18, Pages 474: Design and Implementation of Cloud-Centric Configuration Repository for DIY IoT Applications Sensors doi: 10.3390/s18020474 Authors: Shabir Ahmad Lei Hang Do Kim The Do-It-Yourself (DIY) vision for the design of a smart and customizable IoT application demands the involvement of the general public in its development process. The general public lacks the technical knowledge for programming state-of-the-art prototyping and development kits. The latest IoT kits, for example, Raspberry Pi, are revolutionizing the DIY paradigm for IoT, and more than ever, a DIY intuitive programming interface is required to enable the masses to interact with and customize the behavior of remote IoT devices on the Internet. However, in most cases, these DIY toolkits store the resultant configuration data in local storage and, thus, cannot be accessed remotely. This paper presents the novel implementation of such a system, which not only enables the general public to customize the behavior of remote IoT devices through a visual interface, but also makes the configuration available everywhere and anytime by leveraging the power of cloud-based platforms. The interface enables the visualization of the resources exposed by remote embedded resources in the form of graphical virtual objects (VOs). These VOs are used to create the service design through simple operations like drag-and-drop and the setting of properties. The configuration created as a result is maintained as an XML document, which is ingested by the cloud platform, thus making it available to be used anywhere. We use the HTTP approach for the communication between the cloud and IoT toolbox and the cloud and real devices, but for communication between the toolbox and actual resources, CoAP is used. Finally, a smart home case study has been implemented and presented in order to assess the effectiveness of the proposed work.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 42
    Publication Date: 2018-02-07
    Description: Sensors, Vol. 18, Pages 471: Knowledge Reasoning with Semantic Data for Real-Time Data Processing in Smart Factory Sensors doi: 10.3390/s18020471 Authors: Shiyong Wang Jiafu Wan Di Li Chengliang Liu The application of high-bandwidth networks and cloud computing in manufacturing systems will be followed by mass data. Industrial data analysis plays important roles in condition monitoring, performance optimization, flexibility, and transparency of the manufacturing system. However, the currently existing architectures are mainly for offline data analysis, not suitable for real-time data processing. In this paper, we first define the smart factory as a cloud-assisted and self-organized manufacturing system in which physical entities such as machines, conveyors, and products organize production through intelligent negotiation and the cloud supervises this self-organized process for fault detection and troubleshooting based on data analysis. Then, we propose a scheme to integrate knowledge reasoning and semantic data where the reasoning engine processes the ontology model with real time semantic data coming from the production process. Based on these ideas, we build a benchmarking system for smart candy packing application that supports direct consumer customization and flexible hybrid production, and the data are collected and processed in real time for fault diagnosis and statistical analysis.
    Electronic ISSN: 1424-8220
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  • 43
    Publication Date: 2018-02-08
    Description: Entropy, Vol. 20, Pages 110: An Auxiliary Variable Method for Markov Chain Monte Carlo Algorithms in High Dimension Entropy doi: 10.3390/e20020110 Authors: Yosra Marnissi Emilie Chouzenoux Amel Benazza-Benyahia Jean-Christophe  Pesquet In this paper, we are interested in Bayesian inverse problems where either the data fidelity term or the prior distribution is Gaussian or driven from a hierarchical Gaussian model. Generally, Markov chain Monte Carlo (MCMC) algorithms allow us to generate sets of samples that are employed to infer some relevant parameters of the underlying distributions. However, when the parameter space is high-dimensional, the performance of stochastic sampling algorithms is very sensitive to existing dependencies between parameters. In particular, this problem arises when one aims to sample from a high-dimensional Gaussian distribution whose covariance matrix does not present a simple structure. Another challenge is the design of Metropolis–Hastings proposals that make use of information about the local geometry of the target density in order to speed up the convergence and improve mixing properties in the parameter space, while not being too computationally expensive. These two contexts are mainly related to the presence of two heterogeneous sources of dependencies stemming either from the prior or the likelihood in the sense that the related covariance matrices cannot be diagonalized in the same basis. In this work, we address these two issues. Our contribution consists of adding auxiliary variables to the model in order to dissociate the two sources of dependencies. In the new augmented space, only one source of correlation remains directly related to the target parameters, the other sources of correlations being captured by the auxiliary variables. Experiments are conducted on two practical image restoration problems—namely the recovery of multichannel blurred images embedded in Gaussian noise and the recovery of signal corrupted by a mixed Gaussian noise. Experimental results indicate that adding the proposed auxiliary variables makes the sampling problem simpler since the new conditional distribution no longer contains highly heterogeneous correlations. Thus, the computational cost of each iteration of the Gibbs sampler is significantly reduced while ensuring good mixing properties.
    Electronic ISSN: 1099-4300
    Topics: Chemistry and Pharmacology , Physics
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  • 44
    Publication Date: 2018-02-08
    Description: IJERPH, Vol. 15, Pages 286: Clinical Aspects of Foot Health in Individuals with Alzheimer’s Disease International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020286 Authors: Daniel López-López Marta Grela-Fariña Marta Losa-Iglesias César Calvo-Lobo David Rodríguez-Sanz Patricia Palomo-López Ricardo Becerro-de-Bengoa-Vallejo Alzheimer’s disease (AD) shows a marked presence of physiologic changes and the start or aggravation of underlying diseases such as physical frailty in diverse anatomical regions. It is believed to have a particularly harmful effect on the health of the foot. We examined the foot health status in older persons with AD, with a specific focus on the extent to which people with AD may be using inadequate footwear in old age. Seventy-three community-dwelling people with probable, mild to moderate AD aged 65–95 years were recruited from a center of excellence for AD. A single trained physician evaluated health status and foot conditions. Current shoe and foot length and width measurements were taken using a calibrated Brannock device. The results indicate that sixty-five participants (89.04%) suffered from feet problems. Also, only twenty-two subjects (30.14%) used the correct shoes in width and size related with the morphology of their feet. Fifty-one participants (69.86%) were using incorrect shoes in length or width. The present study revealed that peoples with AD had a high presence of foot health problems. Also, the use of inappropriate shoes revealed measurable differences of association between shoe size and the morphology of the foot.
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  • 45
    Publication Date: 2018-02-08
    Description: IJERPH, Vol. 15, Pages 283: Depressive Symptoms of Chinese Children: Prevalence and Correlated Factors among Subgroups International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020283 Authors: Mi Zhou Guangsheng Zhang Scott Rozelle Kaleigh Kenny Hao Xue Economic growth and socioeconomic changes have transformed nearly every aspect of childhood in China, and many are worried by the increasing prevalence of mental health issues among children, particularly depression. To provide insight into the distribution of depressive symptoms among children in China and identify vulnerable groups, we use data from the 2012 China Family Panel Survey (CFPS), a survey that collected data from a large, nationally representative sample of the Chinese population. Using the CFPS data, we construct a sample of 2679 children aged 10–15 years old from 25 provinces in China. According to our results, the incidence of depression varies by geographic area. Specifically, we find that rates of depressive symptoms are significantly lower in urban areas (14% of sample children) than in rural areas (23% of sample children). Our results also show that children from ethnic minorities, from poorer families, and whose parents are depressed are more likely to be depressed than other children. In contrast, we find that depressive symptoms do not vary by gender.
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    Topics: Energy, Environment Protection, Nuclear Power Engineering , Medicine
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  • 46
    Publication Date: 2018-02-08
    Description: Sensors, Vol. 18, Pages 499: Acoustic Sensors for Air and Surface Navigation Applications Sensors doi: 10.3390/s18020499 Authors: Rohan Kapoor Subramanian Ramasamy Alessandro Gardi Ron Schyndel Roberto Sabatini This paper presents the state-of-the-art and reviews the state-of-research of acoustic sensors used for a variety of navigation and guidance applications on air and surface vehicles. In particular, this paper focuses on echolocation, which is widely utilized in nature by certain mammals (e.g., cetaceans and bats). Although acoustic sensors have been extensively adopted in various engineering applications, their use in navigation and guidance systems is yet to be fully exploited. This technology has clear potential for applications in air and surface navigation/guidance for Intelligent Transport Systems (ITS), especially considering air and surface operations indoors and in other environments where satellite positioning is not available. Propagation of sound in the atmosphere is discussed in detail, with all potential attenuation sources taken into account. The errors introduced in echolocation measurements due to Doppler, multipath and atmospheric effects are discussed, and an uncertainty analysis method is presented for ranging error budget prediction in acoustic navigation applications. Considering the design challenges associated with monostatic and multi-static sensor implementations and looking at the performance predictions for different possible configurations, acoustic sensors show clear promises in navigation, proximity sensing, as well as obstacle detection and tracking. The integration of acoustic sensors in multi-sensor navigation systems is also considered towards the end of the paper and a low Size, Weight and Power, and Cost (SWaP-C) sensor integration architecture is presented for possible introduction in air and surface navigation systems.
    Electronic ISSN: 1424-8220
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  • 47
    Publication Date: 2018-02-08
    Description: Sensors, Vol. 18, Pages 500: Real-Time and Meter-Scale Absolute Distance Measurement by Frequency-Comb-Referenced Multi-Wavelength Interferometry Sensors doi: 10.3390/s18020500 Authors: Guochao Wang Lilong Tan Shuhua Yan We report on a frequency-comb-referenced absolute interferometer which instantly measures long distance by integrating multi-wavelength interferometry with direct synthetic wavelength interferometry. The reported interferometer utilizes four different wavelengths, simultaneously calibrated to the frequency comb of a femtosecond laser, to implement subwavelength distance measurement, while direct synthetic wavelength interferometry is elaborately introduced by launching a fifth wavelength to extend a non-ambiguous range for meter-scale measurement. A linearity test performed comparatively with a He–Ne laser interferometer shows a residual error of less than 70.8 nm in peak-to-valley over a 3 m distance, and a 10 h distance comparison is demonstrated to gain fractional deviations of ~3 × 10−8 versus 3 m distance. Test results reveal that the presented absolute interferometer enables precise, stable, and long-term distance measurements and facilitates absolute positioning applications such as large-scale manufacturing and space missions.
    Electronic ISSN: 1424-8220
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  • 48
    Publication Date: 2018-02-08
    Description: Sensors, Vol. 18, Pages 498: Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement Sensors doi: 10.3390/s18020498 Authors: Hong Zhu Xinming Tang Junfeng Xie Weidong Song Fan Mo Xiaoming Gao There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L0 gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 49
    Publication Date: 2018-02-08
    Description: Sensors, Vol. 18, Pages 495: Measurement of Axial Rigidity and Postural Instability Using Wearable Sensors Sensors doi: 10.3390/s18020495 Authors: Dung Phan Malcolm Horne Pubudu Pathirana Parisa Farzanehfar Axial Bradykinesia is an important feature of advanced Parkinson’s disease (PD). The purpose of this study is to quantify axial bradykinesia using wearable sensors with the long-term aim of quantifying these movements, while the subject performs routine domestic activities. We measured back movements during common daily activities such as pouring, pointing, walking straight and walking around a chair with a test system engaging a minimal number of Inertial Measurement (IM) based wearable sensors. Participants included controls and PD patients whose rotation and flexion of the back was captured by the time delay between motion signals from sensors attached to the upper and lower back. PD subjects could be distinguished from controls using only two sensors. These findings suggest that a small number of sensors and similar analyses could distinguish between variations in bradykinesia in subjects with measurements performed outside of the laboratory. The subjects could engage in routine activities leading to progressive assessments of therapeutic outcomes.
    Electronic ISSN: 1424-8220
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  • 50
    Publication Date: 2018-02-08
    Description: Sensors, Vol. 18, Pages 497: An Improved Calibration Method for a Rotating 2D LIDAR System Sensors doi: 10.3390/s18020497 Authors: Yadan Zeng Heng Yu Houde Dai Shuang Song Mingqiang Lin Bo Sun Wei Jiang Max Meng This paper presents an improved calibration method of a rotating two-dimensional light detection and ranging (R2D-LIDAR) system, which can obtain the 3D scanning map of the surroundings. The proposed R2D-LIDAR system, composed of a 2D LIDAR and a rotating unit, is pervasively used in the field of robotics owing to its low cost and dense scanning data. Nevertheless, the R2D-LIDAR system must be calibrated before building the geometric model because there are assembled deviation and abrasion between the 2D LIDAR and the rotating unit. Hence, the calibration procedures should contain both the adjustment between the two devices and the bias of 2D LIDAR itself. The main purpose of this work is to resolve the 2D LIDAR bias issue with a flat plane based on the Levenberg–Marquardt (LM) algorithm. Experimental results for the calibration of the R2D-LIDAR system prove the reliability of this strategy to accurately estimate sensor offsets with the error range from −15 mm to 15 mm for the performance of capturing scans.
    Electronic ISSN: 1424-8220
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  • 51
    Publication Date: 2018-02-08
    Description: Sensors, Vol. 18, Pages 496: Determining Biogenic Content of Biogas by Measuring Stable Isotopologues 12CH4, 13CH4, and CH3D with a Mid-Infrared Direct Absorption Laser Spectrometer Sensors doi: 10.3390/s18020496 Authors: Teemu Kääriäinen Craig Richmond Albert Manninen A tunable laser absorption spectrometer (TLAS) was developed for the simultaneous measurement of δ13C and δD values of methane (CH4). A mid-infrared interband cascade laser (ICL) emitting around 3.27 µm was used to measure the absorption of the three most abundant isotopologues in CH4 with a single, mode-hop free current sweep. The instrument was validated against methane samples of fossil and biogenic origin with known isotopic composition. Three blended mixtures with varied biogenic content were prepared volumetrically, and their δ13C and δD values were determined. Analysis demonstrated that, provided the isotopic composition of the source materials was known, the δ13C and δD values alone were sufficient to determine the biogenic content of the blended samples to within 1.5%.
    Electronic ISSN: 1424-8220
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  • 52
    Publication Date: 2018-02-08
    Description: Sensors, Vol. 18, Pages 492: IoT-Forensics Meets Privacy: Towards Cooperative Digital Investigations Sensors doi: 10.3390/s18020492 Authors: Ana Nieto Ruben Rios Javier Lopez IoT-Forensics is a novel paradigm for the acquisition of electronic evidence whose operation is conditioned by the peculiarities of the Internet of Things (IoT) context. As a branch of computer forensics, this discipline respects the most basic forensic principles of preservation, traceability, documentation, and authorization. The digital witness approach also promotes such principles in the context of the IoT while allowing personal devices to cooperate in digital investigations by voluntarily providing electronic evidence to the authorities. However, this solution is highly dependent on the willingness of citizens to collaborate and they may be reluctant to do so if the sensitive information within their personal devices is not sufficiently protected when shared with the investigators. In this paper, we provide the digital witness approach with a methodology that enables citizens to share their data with some privacy guarantees. We apply the PRoFIT methodology, originally defined for IoT-Forensics environments, to the digital witness approach in order to unleash its full potential. Finally, we show the feasibility of a PRoFIT-compliant digital witness with two use cases.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 53
    Publication Date: 2018-02-08
    Description: Sensors, Vol. 18, Pages 491: Statistical Analysis of Stress Signals from Bridge Monitoring by FBG System Sensors doi: 10.3390/s18020491 Authors: Xiao-Wei Ye You-Hua Su Pei-Sen Xi In this paper, a fiber Bragg grating (FBG)-based stress monitoring system instrumented on an orthotropic steel deck arch bridge is demonstrated. The FBG sensors are installed at two types of critical fatigue-prone welded joints to measure the strain and temperature signals. A total of 64 FBG sensors are deployed around the rib-to-deck and rib-to-diagram areas at the mid-span and quarter-span of the investigated orthotropic steel bridge. The local stress behaviors caused by the highway loading and temperature effect during the construction and operation periods are presented with the aid of a wavelet multi-resolution analysis approach. In addition, the multi-modal characteristic of the rainflow counted stress spectrum is modeled by the method of finite mixture distribution together with a genetic algorithm (GA)-based parameter estimation approach. The optimal probability distribution of the stress spectrum is determined by use of Bayesian information criterion (BIC). Furthermore, the hot spot stress of the welded joint is calculated by an extrapolation method recommended in the specification of International Institute of Welding (IIW). The stochastic characteristic of stress concentration factor (SCF) of the concerned welded joint is addressed. The proposed FBG-based stress monitoring system and probabilistic stress evaluation methods can provide an effective tool for structural monitoring and condition assessment of orthotropic steel bridges.
    Electronic ISSN: 1424-8220
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  • 54
    Publication Date: 2018-02-09
    Description: Entropy, Vol. 20, Pages 111: A Coding Theorem for f-Separable Distortion Measures Entropy doi: 10.3390/e20020111 Authors: Yanina Shkel Sergio Verdú In this work we relax the usual separability assumption made in rate-distortion literature and propose f -separable distortion measures, which are well suited to model non-linear penalties. The main insight behind f -separable distortion measures is to define an n-letter distortion measure to be an f -mean of single-letter distortions. We prove a rate-distortion coding theorem for stationary ergodic sources with f -separable distortion measures, and provide some illustrative examples of the resulting rate-distortion functions. Finally, we discuss connections between f -separable distortion measures, and the subadditive distortion measure previously proposed in literature.
    Electronic ISSN: 1099-4300
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  • 55
    Publication Date: 2018-02-09
    Description: IJERPH, Vol. 15, Pages 295: The Impact of Sustainable Development Technology on a Small Economy—The Case of Energy-Saving Technology International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020295 Authors: Xiding Chen Qinghua Huang Weilun Huang Xue Li We investigated the impact of a sustainable development technology on the macroeconomic variables in a small economy utilizing a case study with a stochastically improving energy saving technology and a stochastically increasing energy price. The results show the technological displacement effects of energy saving technology are stronger, but there are more ambiguous instantaneous returns to physical capital. However, the energy saving technology’s displacement effects might not affect the conditions under which the Harberger-Laursen-Metzler (HLM) effect holds. The effects of rising energy prices on bonds are stronger, and there are more ambiguous instantaneous returns, but the conditions under which the HLM effect holds are different.
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  • 56
    Publication Date: 2018-02-09
    Description: Sensors, Vol. 18, Pages 519: Determination of Odour Interactions in Gaseous Mixtures Using Electronic Nose Methods with Artificial Neural Networks Sensors doi: 10.3390/s18020519 Authors: Bartosz Szulczyński Krzysztof Armiński Jacek Namieśnik Jacek Gębicki This paper presents application of an electronic nose prototype comprised of eight sensors, five TGS-type sensors, two electrochemical sensors and one PID-type sensor, to identify odour interaction phenomenon in two-, three-, four- and five-component odorous mixtures. Typical chemical compounds, such as toluene, acetone, triethylamine, α-pinene and n-butanol, present near municipal landfills and sewage treatment plants were subjected to investigation. Evaluation of predicted odour intensity and hedonic tone was performed with selected artificial neural network structures with the activation functions tanh and Leaky rectified linear units (Leaky ReLUs) with the parameter a = 0.03 . Correctness of identification of odour interactions in the odorous mixtures was determined based on the results obtained with the electronic nose instrument and non-linear data analysis. This value (average) was at the level of 88% in the case of odour intensity, whereas the average was at the level of 74% in the case of hedonic tone. In both cases, correctness of identification depended on the number of components present in the odorous mixture.
    Electronic ISSN: 1424-8220
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  • 57
    Publication Date: 2018-02-09
    Description: Sensors, Vol. 18, Pages 516: Non-Orthogonal Multiple Access for Ubiquitous Wireless Sensor Networks Sensors doi: 10.3390/s18020516 Authors: Asim Anwar Boon-Chong Seet Zhiguo Ding Ubiquitous wireless sensor networks (UWSNs) have become a critical technology for enabling smart cities and other ubiquitous monitoring applications. Their deployment, however, can be seriously hampered by the spectrum available to the sheer number of sensors for communication. To support the communication needs of UWSNs without requiring more spectrum resources, the power-domain non-orthogonal multiple access (NOMA) technique originally proposed for 5th Generation (5G) cellular networks is investigated for UWSNs for the first time in this paper. However, unlike 5G networks that operate in the licensed spectrum, UWSNs mostly operate in unlicensed spectrum where sensors also experience cross-technology interferences from other devices sharing the same spectrum. In this paper, we model the interferences from various sources at the sensors using stochastic geometry framework. To evaluate the performance, we derive a theorem and present new closed form expression for the outage probability of the sensors in a downlink scenario under interference limited environment. In addition, diversity analysis for the ordered NOMA users is performed. Based on the derived outage probability, we evaluate the average link throughput and energy consumption efficiency of NOMA against conventional orthogonal multiple access (OMA) technique in UWSNs. Further, the required computational complexity for the NOMA users is presented.
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  • 58
    Publication Date: 2018-02-09
    Description: Sensors, Vol. 18, Pages 515: Mutual-Information-Based Incremental Relaying Communications for Wireless Biomedical Implant Systems Sensors doi: 10.3390/s18020515 Authors: Yangzhe Liao Mark Leeson Qing Cai Qingsong Ai Quan Liu Network lifetime maximization of wireless biomedical implant systems is one of the major research challenges of wireless body area networks (WBANs). In this paper, a mutual information (MI)-based incremental relaying communication protocol is presented where several on-body relay nodes and one coordinator are attached to the clothes of a patient. Firstly, a comprehensive analysis of a system model is investigated in terms of channel path loss, energy consumption, and the outage probability from the network perspective. Secondly, only when the MI value becomes smaller than the predetermined threshold is data transmission allowed. The communication path selection can be either from the implanted sensor to the on-body relay then forwards to the coordinator or from the implanted sensor to the coordinator directly, depending on the communication distance. Moreover, mathematical models of quality of service (QoS) metrics are derived along with the related subjective functions. The results show that the MI-based incremental relaying technique achieves better performance in comparison to our previous proposed protocol techniques regarding several selected performance metrics. The outcome of this paper can be applied to intra-body continuous physiological signal monitoring, artificial biofeedback-oriented WBANs, and telemedicine system design.
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  • 59
    Publication Date: 2018-02-09
    Description: Sensors, Vol. 18, Pages 508: H∞ Robust Control of a Large-Piston MEMS Micromirror for Compact Fourier Transform Spectrometer Systems Sensors doi: 10.3390/s18020508 Authors: Huipeng Chen Mengyuan Li Yi Zhang Huikai Xie Chang Chen Zhangming Peng Shaohui Su Incorporating linear-scanning micro-electro-mechanical systems (MEMS) micromirrors into Fourier transform spectral acquisition systems can greatly reduce the size of the spectrometer equipment, making portable Fourier transform spectrometers (FTS) possible. How to minimize the tilting of the MEMS mirror plate during its large linear scan is a major problem in this application. In this work, an FTS system has been constructed based on a biaxial MEMS micromirror with a large-piston displacement of 180 μm, and a biaxial H∞ robust controller is designed. Compared with open-loop control and proportional-integral-derivative (PID) closed-loop control, H∞ robust control has good stability and robustness. The experimental results show that the stable scanning displacement reaches 110.9 μm under the H∞ robust control, and the tilting angle of the MEMS mirror plate in that full scanning range falls within ±0.0014°. Without control, the FTS system cannot generate meaningful spectra. In contrast, the FTS yields a clean spectrum with a full width at half maximum (FWHM) spectral linewidth of 96 cm−1 under the H∞ robust control. Moreover, the FTS system can maintain good stability and robustness under various driving conditions.
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  • 60
    Publication Date: 2018-02-09
    Description: Sensors, Vol. 18, Pages 509: Enrichment of OpenStreetMap Data Completeness with Sidewalk Geometries Using Data Mining Techniques Sensors doi: 10.3390/s18020509 Authors: Amin Mobasheri Haosheng Huang Lívia Degrossi Alexander Zipf Tailored routing and navigation services utilized by wheelchair users require certain information about sidewalk geometries and their attributes to execute efficiently. Except some minor regions/cities, such detailed information is not present in current versions of crowdsourced mapping databases including OpenStreetMap. CAP4Access European project aimed to use (and enrich) OpenStreetMap for making it fit to the purpose of wheelchair routing. In this respect, this study presents a modified methodology based on data mining techniques for constructing sidewalk geometries using multiple GPS traces collected by wheelchair users during an urban travel experiment. The derived sidewalk geometries can be used to enrich OpenStreetMap to support wheelchair routing. The proposed method was applied to a case study in Heidelberg, Germany. The constructed sidewalk geometries were compared to an official reference dataset (“ground truth dataset”). The case study shows that the constructed sidewalk network overlays with 96% of the official reference dataset. Furthermore, in terms of positional accuracy, a low Root Mean Square Error (RMSE) value (0.93 m) is achieved. The article presents our discussion on the results as well as the conclusion and future research directions.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 61
    Publication Date: 2018-02-09
    Description: Sensors, Vol. 18, Pages 506: Accurate Initial State Estimation in a Monocular Visual–Inertial SLAM System Sensors doi: 10.3390/s18020506 Authors: Xufu Mu Jing Chen Zixiang Zhou Zhen Leng Lei Fan The fusion of monocular visual and inertial cues has become popular in robotics, unmanned vehicles and augmented reality fields. Recent results have shown that optimization-based fusion strategies outperform filtering strategies. Robust state estimation is the core capability for optimization-based visual–inertial Simultaneous Localization and Mapping (SLAM) systems. As a result of the nonlinearity of visual–inertial systems, the performance heavily relies on the accuracy of initial values (visual scale, gravity, velocity and Inertial Measurement Unit (IMU) biases). Therefore, this paper aims to propose a more accurate initial state estimation method. On the basis of the known gravity magnitude, we propose an approach to refine the estimated gravity vector by optimizing the two-dimensional (2D) error state on its tangent space, then estimate the accelerometer bias separately, which is difficult to be distinguished under small rotation. Additionally, we propose an automatic termination criterion to determine when the initialization is successful. Once the initial state estimation converges, the initial estimated values are used to launch the nonlinear tightly coupled visual–inertial SLAM system. We have tested our approaches with the public EuRoC dataset. Experimental results show that the proposed methods can achieve good initial state estimation, the gravity refinement approach is able to efficiently speed up the convergence process of the estimated gravity vector, and the termination criterion performs well.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 62
    Publication Date: 2018-02-09
    Description: Sensors, Vol. 18, Pages 514: Nuclear Radiation Degradation Study on HD Camera Based on CMOS Image Sensor at Different Dose Rates Sensors doi: 10.3390/s18020514 Authors: Congzheng Wang Song Hu Chunming Gao Chang Feng In this work, we irradiated a high-definition (HD) industrial camera based on a commercial-off-the-shelf (COTS) CMOS image sensor (CIS) with Cobalt-60 gamma-rays. All components of the camera under test were fabricated without radiation hardening, except for the lens. The irradiation experiments of the HD camera under biased conditions were carried out at 1.0, 10.0, 20.0, 50.0 and 100.0 Gy/h. During the experiment, we found that the tested camera showed a remarkable degradation after irradiation and differed in the dose rates. With the increase of dose rate, the same target images become brighter. Under the same dose rate, the radiation effect in bright area is lower than that in dark area. Under different dose rates, the higher the dose rate is, the worse the radiation effect will be in both bright and dark areas. And the standard deviations of bright and dark areas become greater. Furthermore, through the progressive degradation analysis of the captured image, experimental results demonstrate that the attenuation of signal to noise ratio (SNR) versus radiation time is not obvious at the same dose rate, and the degradation is more and more serious with increasing dose rate. Additionally, the decrease rate of SNR at 20.0, 50.0 and 100.0 Gy/h is far greater than that at 1.0 and 10.0 Gy/h. Even so, we confirm that the HD industrial camera is still working at 10.0 Gy/h during the 8 h of measurements, with a moderate decrease of the SNR (5 dB). The work is valuable and can provide suggestion for camera users in the radiation field.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 63
    Publication Date: 2018-02-09
    Description: Sensors, Vol. 18, Pages 513: Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology Sensors doi: 10.3390/s18020513 Authors: Andrea Loddo Cecilia Di Ruberto Michel Kocher Malaria is an epidemic health disease and a rapid, accurate diagnosis is necessary for proper intervention. Generally, pathologists visually examine blood stained slides for malaria diagnosis. Nevertheless, this kind of visual inspection is subjective, error-prone and time-consuming. In order to overcome the issues, numerous methods of automatic malaria diagnosis have been proposed so far. In particular, many researchers have used mathematical morphology as a powerful tool for computer aided malaria detection and classification. Mathematical morphology is not only a theory for the analysis of spatial structures, but also a very powerful technique widely used for image processing purposes and employed successfully in biomedical image analysis, especially in preprocessing and segmentation tasks. Microscopic image analysis and particularly malaria detection and classification can greatly benefit from the use of morphological operators. The aim of this paper is to present a review of recent mathematical morphology based methods for malaria parasite detection and identification in stained blood smears images.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 64
    Publication Date: 2018-02-09
    Description: Sensors, Vol. 18, Pages 511: Energy Efficient Data Transmission for Sensors with Wireless Charging Sensors doi: 10.3390/s18020511 Authors: Xiaolin Fang Junzhou Luo Weiwei Wu Hong Gao This paper studies the problem of maximizing the energy utilization for data transmission in sensors with periodical wireless charging process while taking into account the thermal effect. Two classes of problems are analyzed: one is the case that wireless charging can process for only a limited period of time, and the other is the case that wireless charging can process for a long enough time. Algorithms are proposed to solve the problems and analysis of these algorithms are also provided. For the first problem, three subproblems are studied, and, for the general problem, we give an algorithm that can derive a performance bound of ( 1 − 1 2 m ) ( O P T − E ) compared to an optimal solution. In addition, for the second problem, we provide an algorithm with 2 m 2 m − 1 O P T + 1 performance bound for the general problem. Simulations confirm the analysis of the algorithms.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 65
    Publication Date: 2018-02-09
    Description: Sensors, Vol. 18, Pages 507: A Novel Method for Remote Depth Estimation of Buried Radioactive Contamination Sensors doi: 10.3390/s18020507 Authors: Ikechukwu Ukaegbu Kelum Gamage Existing remote radioactive contamination depth estimation methods for buried radioactive wastes are either limited to less than 2 cm or are based on empirical models that require foreknowledge of the maximum penetrable depth of the contamination. These severely limits their usefulness in some real life subsurface contamination scenarios. Therefore, this work presents a novel remote depth estimation method that is based on an approximate three-dimensional linear attenuation model that exploits the benefits of using multiple measurements obtained from the surface of the material in which the contamination is buried using a radiation detector. Simulation results showed that the proposed method is able to detect the depth of caesium-137 and cobalt-60 contamination buried up to 40 cm in both sand and concrete. Furthermore, results from experiments show that the method is able to detect the depth of caesium-137 contamination buried up to 12 cm in sand. The lower maximum depth recorded in the experiment is due to limitations in the detector and the low activity of the caesium-137 source used. Nevertheless, both results demonstrate the superior capability of the proposed method compared to existing methods.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 66
    Publication Date: 2018-02-10
    Description: Algorithms, Vol. 11, Pages 19: Common Nearest Neighbor Clustering—A Benchmark Algorithms doi: 10.3390/a11020019 Authors: Oliver Lemke Bettina Keller Cluster analyses are often conducted with the goal to characterize an underlying probability density, for which the data-point density serves as an estimate for this probability density. We here test and benchmark the common nearest neighbor (CNN) cluster algorithm. This algorithm assigns a spherical neighborhood R to each data point and estimates the data-point density between two data points as the number of data points N in the overlapping region of their neighborhoods (step 1). The main principle in the CNN cluster algorithm is cluster growing. This grows the clusters by sequentially adding data points and thereby effectively positions the border of the clusters along an iso-surface of the underlying probability density. This yields a strict partitioning with outliers, for which the cluster represents peaks in the underlying probability density—termed core sets (step 2). The removal of the outliers on the basis of a threshold criterion is optional (step 3). The benchmark datasets address a series of typical challenges, including datasets with a very high dimensional state space and datasets in which the cluster centroids are aligned along an underlying structure (Birch sets). The performance of the CNN algorithm is evaluated with respect to these challenges. The results indicate that the CNN cluster algorithm can be useful in a wide range of settings. Cluster algorithms are particularly important for the analysis of molecular dynamics (MD) simulations. We demonstrate how the CNN cluster results can be used as a discretization of the molecular state space for the construction of a core-set model of the MD improving the accuracy compared to conventional full-partitioning models. The software for the CNN clustering is available on GitHub.
    Electronic ISSN: 1999-4893
    Topics: Computer Science
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  • 67
    Publication Date: 2018-02-10
    Description: IJERPH, Vol. 15, Pages 307: Acute Effects of Ambient PM2.5 on All-Cause and Cause-Specific Emergency Ambulance Dispatches in Japan International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020307 Authors: Vera Phung Kayo Ueda Shunji Kasaoka Xerxes Seposo Saira Tasmin Shinichi Yonemochi Arthit Phosri Akiko Honda Hirohisa Takano Takehiro Michikawa Hiroshi Nitta Short-term health effects of ambient PM2.5 have been established with numerous studies, but evidence in Asian countries is limited. This study aimed to investigate the short-term effects of PM2.5 on acute health outcomes, particularly all-cause, cardiovascular, respiratory, cerebrovascular and neuropsychological outcomes. We utilized daily emergency ambulance dispatches (EAD) data from eight Japanese cities (2007–2011). Statistical analyses included two stages: (1) City-level generalized linear model with Poisson distribution; (2) Random-effects meta-analysis in pooling city-specific effect estimates. Lag patterns were explored using (1) unconstrained-distributed lags (lag 0 to lag 7) and (2) average lags (lag: 0–1, 0–3, 0–5, 0–7). In all-cause EAD, significant increases were observed in both shorter lag (lag 0: 1.24% (95% CI: 0.92, 1.56)) and average lag 0–1 (0.64% (95% CI: 0.23, 1.06)). Increases of 1.88% and 1.48% in respiratory and neuropsychological EAD outcomes, respectively, were observed at lag 0 per 10 µg/m3 increase in PM2.5. While respiratory outcomes demonstrated significant average effects, no significant effect was observed for cardiovascular outcomes. Meanwhile, an inverse association was observed in cerebrovascular outcomes. In this study, we observed that effects of PM2.5 on all-cause, respiratory and neuropsychological EAD were acute, with average effects not exceeding 3 days prior to EAD onset.
    Print ISSN: 1661-7827
    Electronic ISSN: 1660-4601
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Medicine
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  • 68
    Publication Date: 2018-02-10
    Description: IJERPH, Vol. 15, Pages 302: “I Was Relieved to Know That My Baby Was Safe”: Women’s Attitudes and Perceptions on Using a New Electronic Fetal Heart Rate Monitor during Labor in Tanzania International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15020302 Authors: Sara Rivenes Lafontan Johanne Sundby Hege Ersdal Muzdalifat Abeid Hussein Kidanto Columba Mbekenga To increase labor monitoring and prevent neonatal morbidity and mortality, a new wireless, strap-on electronic fetal heart rate monitor called Moyo was introduced in Tanzania in 2016. As part of the ongoing evaluation of the introduction of the monitor, the aim of this study was to explore the attitudes and perceptions of women who had worn the monitor continuously during their most recent delivery and perceptions about how it affected care. This knowledge is important to identify barriers towards adaptation in order to introduce new technology more effectively. We carried out 20 semi-structured individual interviews post-labor at two hospitals in Tanzania. A thematic content analysis was used to analyze the data. Our results indicated that the use of the monitor positively affected the women’s birth experience. It provided much-needed reassurance about the wellbeing of the child. The women considered that wearing Moyo improved care due to an increase in communication and attention from birth attendants. However, the women did not fully understand the purpose and function of the device and overestimated its capabilities. This highlights the need to improve how and when information is conveyed to women in labor.
    Print ISSN: 1661-7827
    Electronic ISSN: 1660-4601
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Medicine
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  • 69
    Publication Date: 2018-02-10
    Description: Sensors, Vol. 18, Pages 521: Silver Eco-Solvent Ink for Reactive Printing of Polychromatic SERS and SPR Substrates Sensors doi: 10.3390/s18020521 Authors: Mavlavi Dustov Diana Golovina Alexander Polyakov Anastasia Goldt Andrei Eliseev Efim Kolesnikov Irina Sukhorukova Dmitry Shtansky Wolfgang Grünert Anastasia Grigorieva A new reactive ink based on a silver citrate complex is proposed for a photochemical route to surface-enhanced Raman spectroscopy active substrates with controllable extinction spectra. The drop-cast test of the ink reveals homogeneous nucleation of silver and colloid particle growth originating directly from photochemical in situ reduction in droplets, while the following evaporation of the deposited ink produces small nano- and micron-size particles. The prepared nanostructures and substrates were accurately characterized by electron microscopy methods and optical extinction spectroscopy. Varying the duration of UV irradiation allows tuning the morphology of individual silver nanoparticles forming hierarchical ring structures with numerous “hot spots” for most efficient Raman enhancement. Raman measurements of probe molecules of rhodamine 6G and methylene blue reached the largest signal enhancement of 106 by the resonance effects.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 70
    Publication Date: 2018-02-10
    Description: Sensors, Vol. 18, Pages 522: OSCANN: Technical Characterization of a Novel Gaze Tracking Analyzer Sensors doi: 10.3390/s18020522 Authors: Erik Hernández Santiago Hernández David Molina Rafael Acebrón Cecilia García Cena Eye-movement analysis has grown exponentially in recent decades. The reason is that abnormalities in oculomotor movements are usually symptoms of injuries in the nervous system. This paper presents a novel regulated solution named OSCANN. OSCANN aims at providing an innovative tool for the control, management and visualization of oculomotor neurological examinations. This solution utilizes an eye-tracker sensor based on video electro-oculography (VOG) technology to capture eye movements and store them in video files. Such a sensor can store images at a rate of 100 frames per second. A characterization study was performed using twenty-two volunteers (13 male, 9 female, ages 22–45 years, mean 29.3 years, SD = 6.7) to assess the accuracy and precision specifications of OSCANN during oculomotor movement analysis. The accuracy was evaluated based on the offset, whereas precision was estimated with Root Means Square (RMS). Such a study reported values lower than 0.4 ∘ and 0.03 ∘ of accuracy and precision, respectively. These results suggest that OSCANN can be considered as a powerful tool to measure oculomotor movement alterations involved in some neurological disease progression.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 71
    Publication Date: 2018-02-10
    Description: Sensors, Vol. 18, Pages 530: Cave Pearl Data Logger: A Flexible Arduino-Based Logging Platform for Long-Term Monitoring in Harsh Environments Sensors doi: 10.3390/s18020530 Authors: Patricia A. Beddows Edward K. Mallon A low-cost data logging platform is presented that provides long-term operation in remote or submerged environments. Three premade “breakout boards” from the open-source Arduino ecosystem are assembled into the core of the data logger. Power optimization techniques are presented which extend the operational life of this module-based design to >1 year on three alkaline AA batteries. Robust underwater housings are constructed for these loggers using PVC fittings. Both the logging platform and the enclosures, are easy to build and modify without specialized tools or a significant background in electronics. This combination turns the Cave Pearl data logger into a generalized prototyping system and this design flexibility is demonstrated with two field studies recording drip rates in a cave and water flow in a flooded cave system. This paper describes a complete DIY solution, suitable for a wide range of challenging deployment conditions.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 72
    Publication Date: 2018-02-10
    Description: Sensors, Vol. 18, Pages 528: Hybrid Beamforming for Reduction of Inter-Beam Interference in Millimeter-Wave Cellular Systems Sensors doi: 10.3390/s18020528 Authors: Sung Maeng Su Park Yong Cho In millimeter-wave (mm-wave) cellular systems, beamforming antennas are necessary at both the base station (BS) and mobile station (MS) to compensate for high attenuation in mm-wave frequency bands and to extend the transmission range. The beamforming antennas also allow each BS to serve a number of MSs simultaneously, providing a substantial gain in system capacity. In space-division multiple access (SDMA) systems, the challenge is the inter-beam interference (IBI) caused by adjacent beams that are formed by the BS in the same cell and BSs in neighboring cells. The beams that are formed toward MSs in each cell may generate significant interference to MSs in neighboring cells, especially for MSs at the cell boundary. In this paper, we propose four different digital precoding techniques (Type-1, Type-2, Type-3, and Type-4) to reduce IBI in mm-wave cellular systems with a hybrid beamformer. Simulation results show that the proposed techniques can reduce the IBI in mm-wave cellular systems effectively, compared with a single-cell multiuser case.
    Electronic ISSN: 1424-8220
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  • 73
    Publication Date: 2018-02-10
    Description: Sensors, Vol. 18, Pages 529: Laser-Based Monitoring of CH4, CO2, NH3, and H2S in Animal Farming—System Characterization and Initial Demonstration Sensors doi: 10.3390/s18020529 Authors: Dorota Stachowiak Piotr Jaworski Paweł Krzaczek Grzegorz Maj Michał Nikodem In this paper, we present a system for sequential detection of multiple gases using laser-based wavelength modulation spectroscopy (WMS) method combined with a Herriot-type multi-pass cell. Concentration of hydrogen sulfide (H2S), methane (CH4), carbon dioxide (CO2), and ammonia (NH3) are retrieved using three distributed feedback laser diodes operating at 1574.5 nm (H2S and CO2), 1651 nm (CH4), and 1531 nm (NH3). Careful adjustment of system parameters allows for H2S sensing at single parts-per-million by volume (ppmv) level with strongly reduced interference from adjacent CO2 transitions even at atmospheric pressure. System characterization in laboratory conditions is presented and the results from initial tests in real-world application are demonstrated.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 74
    Publication Date: 2018-02-10
    Description: Sensors, Vol. 18, Pages 524: Fast Focal Point Correction in Prism-Coupled Total Internal Reflection Scanning Imager Using an Electronically Tunable Lens Sensors doi: 10.3390/s18020524 Authors: Chenggang Zhu Bilin Ge Ru Chen Xiangdong Zhu Lan Mi Jiong Ma Xu Wang Fengyun Zheng Yiyan Fei Total internal reflection (TIR) is useful for interrogating physical and chemical processes that occur at the interface between two transparent media. Yet prism-coupled TIR imaging microscopes suffer from limited sensing areas due to the fact that the interface (the object plane) is not perpendicular to the optical axis of the microscope. In this paper, we show that an electrically tunable lens can be used to rapidly and reproducibly correct the focal length of an oblique-incidence scanning microscope (OI-RD) in a prism-coupled TIR geometry. We demonstrate the performance of such a correction by acquiring an image of a protein microarray over a scan area of 4 cm2 with an effective resolution of less than 20 microns. The electronic focal length tuning eliminates the mechanical movement of the illumination lens in the scanning microscope and in turn the noise and background drift associated with the motion.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 75
    Publication Date: 2018-02-10
    Description: Sensors, Vol. 18, Pages 526: Monitoring of Soft Deposition Layers in Liquid-Filled Tubes with Guided Acoustic Waves Excited by Clamp-on Transducers Sensors doi: 10.3390/s18020526 Authors: Sabrina Tietze Ferdinand Singer Sandra Lasota Sandra Ebert Johannes Landskron Katrin Schwuchow Klaus Stefan Drese Gerhard Lindner The monitoring of liquid-filled tubes with respect to the formation of soft deposition layers such as biofilms on the inner walls calls for non-invasive and long-term stable sensors, which can be attached to existing pipe structures. For this task a method is developed, which uses an ultrasonic clamp-on device. This method is based on the impact of such deposition layers on the propagation of circumferential guided waves on the pipe wall. Such waves are partly converted into longitudinal compressional waves in the liquid, which are back-converted to guided waves in a circular cross section of the pipe. Validating this approach, laboratory experiments with gelatin deposition layers on steel tubes exhibited a distinguishable sensitivity of both wave branches with respect to the thickness of such layers. This allows the monitoring of the layer growth.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
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  • 76