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  • 1
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    Sensors, Vol. 19, Pages 3662: Can We Use Satellite-Based FAPAR to Detect Drought? (2019)
    MDPI
    In: Sensors
    Details
    Publication Date: 2019
    Description: Drought in Australia has widespread impacts on agriculture and ecosystems. Satellite-based Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) has great potential to monitor and assess drought impacts on vegetation greenness and health. Various FAPAR products based on satellite observations have been generated and made available to the public. However, differences remain among these datasets due to different retrieval methodologies and assumptions. The Quality Assurance for Essential Climate Variables (QA4ECV) project recently developed a quality assurance framework to provide understandable and traceable quality information for Essential Climate Variables (ECVs). The QA4ECV FAPAR is one of these ECVs. The aim of this study is to investigate the capability of QA4ECV FAPAR for drought monitoring in Australia. Through spatial and temporal comparison and correlation analysis with widely used Moderate Resolution Imaging Spectroradiometer (MODIS), Satellite Pour l’Observation de la Terre (SPOT)/PROBA-V FAPAR generated by Copernicus Global Land Service (CGLS), and the Standardized Precipitation Evapotranspiration Index (SPEI) drought index, as well as the European Space Agency’s Climate Change Initiative (ESA CCI) soil moisture, the study shows that the QA4ECV FAPAR can support agricultural drought monitoring and assessment in Australia. The traceable and reliable uncertainties associated with the QA4ECV FAPAR provide valuable information for applications that use the QA4ECV FAPAR dataset in the future.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
    Published by MDPI
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  • 2
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    Sensors, Vol. 18, Pages 3743: Characterizing Focused Attention and Working Memory Using EEG (2018)
    MDPI
    In: Sensors
    Details
    Publication Date: 2018
    Description: Detecting the cognitive profiles of learners is an important step towards personalized and adaptive learning. Electroencephalograms (EEG) have been used to detect the subject’s emotional and cognitive states. In this paper, an approach for detecting two cognitive skills, focused attention and working memory, using EEG signals is proposed. The proposed approach consists of the following main steps: first, subjects undergo a scientifically-validated cognitive assessment test that stimulates and measures their full cognitive profile while putting on a 14-channel wearable EEG headset. Second, the scores of focused attention and working memory are extracted and encoded for a classification problem. Third, the collected EEG data are analyzed and a total of 280 time- and frequency-domain features are extracted. Fourth, several classifiers were trained to correctly classify and predict three levels (low, average, and high) of the two cognitive skills. The classification accuracies that were obtained on 86 subjects were 84% and 81% for the focused attention and working memory, respectively. In comparison with similar approaches, the obtained results indicate the generalizability and suitability of the proposed approach for the detection of these two skills. Thus, the presented approach can be used as a step towards adaptive learning where real-time adaptation is to be done according to the predicted levels of the measured cognitive skills.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
    Published by MDPI
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  • 3
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    Quantum speed limit and optimal control of many-boson dynamics (2015)
    American Physical Society (APS)
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    Publication Date: 2015-12-08
    Description: Author(s): Ioannis Brouzos, Alexej I. Streltsov, Antonio Negretti, Ressa S. Said, Tommaso Caneva, Simone Montangero, and Tommaso Calarco We apply the concept of quantum speed limit (QSL)—the minimal time needed to perform a driven evolution—to complex interacting many-body systems where the effects of interactions have to be taken into account. We introduce a general strategy to eliminate the detrimental effects of the interparticle … [Phys. Rev. A 92, 062110] Published Mon Dec 07, 2015
    Keywords: Fundamental concepts
    Print ISSN: 1050-2947
    Electronic ISSN: 1094-1622
    Topics: Physics
    Published by American Physical Society (APS)
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  • 4
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    Sensors, Vol. 19, Pages 1849: Continuous Stress Detection Using Wearable Sensors in Real Life: Algorithmic Programming Contest Case Study (2019)
    MDPI
    In: Sensors
    Details
    Publication Date: 2019
    Description: The negative effects of mental stress on human health has been known for decades. High-level stress must be detected at early stages to prevent these negative effects. After the emergence of wearable devices that could be part of our lives, researchers have started detecting extreme stress of individuals with them during daily routines. Initial experiments were performed in laboratory environments and recently a number of works took a step outside the laboratory environment to the real-life. We developed an automatic stress detection system using physiological signals obtained from unobtrusive smart wearable devices which can be carried during the daily life routines of individuals. This system has modality-specific artifact removal and feature extraction methods for real-life conditions. We further tested our system in a real-life setting with collected physiological data from 21 participants of an algorithmic programming contest for nine days. This event had lectures, contests as well as free time. By using heart activity, skin conductance and accelerometer signals, we successfully discriminated contest stress, relatively higher cognitive load (lecture) and relaxed time activities by using different machine learning methods.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
    Published by MDPI
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  • 5
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    Sensors, Vol. 19, Pages 927: Automated Modal Analysis for Tracking Structural Change during Construction and Operation Phases (2019)
    MDPI
    In: Sensors
    Details
    Publication Date: 2019
    Description: The automated modal analysis (AMA) technique has attracted significant interest over the last few years, because it can track variations in modal parameters and has the potential to detect structural changes. In this paper, an improved density-based spatial clustering of applications with noise (DBSCAN) is introduced to clean the abnormal poles in a stabilization diagram. Moreover, the optimal system model order is also discussed to obtain more stable poles. A numerical simulation and a full-scale experiment of an arch bridge are carried out to validate the effectiveness of the proposed algorithm. Subsequently, the continuous dynamic monitoring system of the bridge and the proposed algorithm are implemented to track the structural changes during the construction phase. Finally, the artificial neural network (ANN) is used to remove the temperature effect on modal frequencies so that a health index can be constructed under operational conditions.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
    Published by MDPI
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  • 6
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    Sensors, Vol. 18, Pages 4117: Structural Health Monitoring of a Prestressed Concrete Bridge Based on Statistical Pattern Recognition of Continuous Dynamic Measurements over 14 years (2018)
    MDPI
    In: Sensors
    Details
    Publication Date: 2018
    Description: This work describes a vibration-based structural health monitoring of a prestressed-concrete box girder bridge on the A100 Highway in Berlin by applying statistical pattern recognition technique to a huge amount of data continuously collected by an integrated monitoring system during the period from 2000 to 2013. Firstly, the general condition and potential damage of the bridge is described. Then, the dynamic properties are extracted from 20 velocity sensors. Environmental variability captured by five thermal transducers and traffic intensity approximately estimated by strain measurements are also reported. Nonlinear influences of temperature on natural frequencies are observed. Subsequently, the measurements during the first year are used to build a baseline health index. The multiple linear regression (MLR) method is used to characterize the nonlinear relationship between natural frequencies and temperatures. The Euclidean distance of the residual errors is calculated to build a statistical health index. Finally, the indices extracted from the following years gradually deviate; which may indicate structural deterioration due to loss of prestress in the prestressed tendons.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
    Published by MDPI
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  • 7
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    Waveguide coupling in the few-cycle regime (2016)
    American Physical Society (APS)
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    Publication Date: 2016-04-23
    Description: Author(s): Hervé Leblond and Said Terniche We consider the coupling of two optical waveguides in the few-cycle regime. The analysis is performed in the frame of a generalized Kadomtsev-Petviashvili model. A set of two coupled modified Korteweg–de Vries equations is derived, and it is shown that three types of coupling can occur, involving th… [Phys. Rev. A 93, 043839] Published Fri Apr 22, 2016
    Keywords: Quantum optics, physics of lasers, nonlinear optics, classical optics
    Print ISSN: 1050-2947
    Electronic ISSN: 1094-1622
    Topics: Physics
    Published by American Physical Society (APS)
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  • 8
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    Sensors, Vol. 18, Pages 3037: Fecal Volatile Organic Compounds in Preterm Infants Are Influenced by Enteral Feeding Composition (2018)
    MDPI Publishing
    In: Sensors
    Details
    Publication Date: 2018-09-12
    Description: Sensors, Vol. 18, Pages 3037: Fecal Volatile Organic Compounds in Preterm Infants Are Influenced by Enteral Feeding Composition Sensors doi: 10.3390/s18093037 Authors: Sofia el Manouni el Hassani Hendrik J. Niemarkt Hager Said Daniel J. C. Berkhout Anton H. van Kaam Richard A. van Lingen Marc A. Benninga Nanne K. H. de Boer Tim G. J. de Meij Fecal volatile organic compound (VOC) analysis has shown great potential as a noninvasive diagnostic biomarker for a variety of diseases. Before clinical implementation, the factors influencing the outcome of VOC analysis need to be assessed. Recent studies found that the sampling conditions can influence the outcome of VOC analysis. However, the dietary influences remains unknown, especially in (preterm) infants. Therefore, we assessed the effects of feeding composition on fecal VOC patterns of preterm infants (born at <30 weeks gestation). Two subgroups were defined: (1) daily intake >75% breastmilk (BM) feeding and (2) daily intake >75% formula milk (FM) feeding. Fecal samples, which were collected at 7, 14 and 21 days postnatally, were analyzed by an electronic nose device (Cyranose 320®). In total, 30 preterm infants were included (15 FM, 15 BM). No differences in the fecal VOC patterns were observed at the three predefined time-points. Combining the fecal VOC profiles of these time-points resulted in a statistically significant difference between the two subgroups although this discriminative accuracy was only modest (AUC [95% CI]; p-value; sensitivity; and specificity of 0.64 [0.51–0.77]; 0.04; 68%; and 51%, respectively). Our results suggest that the influence of enteral feeding on the outcome of fecal VOC analysis cannot be ignored in this population. Furthermore, in both subgroups, the fecal VOC patterns showed a stable longitudinal course within the first month of life.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
    Published by MDPI Publishing
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  • 9
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    Sensors, Vol. 18, Pages 2332: Fault Detection and Isolation via the Interacting Multiple Model Approach Applied to Drive-By-Wire Vehicles (2018)
    MDPI Publishing
    In: Sensors
    Details
    Publication Date: 2018-07-19
    Description: Sensors, Vol. 18, Pages 2332: Fault Detection and Isolation via the Interacting Multiple Model Approach Applied to Drive-By-Wire Vehicles Sensors doi: 10.3390/s18072332 Authors: Vincent Judalet Sébastien Glaser Dominique Gruyer Saïd Mammar The place of driving assistance systems is currently increasing drastically for road vehicles. Paving the road to the fully autonomous vehicle, the drive-by-wire technology could improve the potential of the vehicle control. The implementation of these new embedded systems is still limited, mainly for reliability reasons, thus requiring the development of diagnostic mechanisms. In this paper, we investigate the detection and the identification of sensor and actuator faults for a drive-by-wire road vehicle. An Interacting Multiple Model approach is proposed, based on a non-linear vehicle dynamics observer. The adequacy of different probabilistic observers is discussed. The results, based on experimental vehicle signals, show a fast and robust identification of sensor faults while the actuator faults are more challenging.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
    Published by MDPI Publishing
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  • 10
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    Sensors, Vol. 17, Pages 2771: Silver Nanoparticle Modified Electrode Covered by Graphene Oxide for the Enhanced Electrochemical Detection of Dopamine (2017)
    MDPI Publishing
    In: Sensors
    Details
    Publication Date: 2017-11-30
    Description: Sensors, Vol. 17, Pages 2771: Silver Nanoparticle Modified Electrode Covered by Graphene Oxide for the Enhanced Electrochemical Detection of Dopamine Sensors doi: 10.3390/s17122771 Authors: Jae-Wook Shin Kyeong-Jun Kim Jinho Yoon Jinhee Jo Waleed Ahmed El-Said Jeong-Woo Choi Several neurological disorders such as Alzheimer’s disease and Parkinson’s disease have become a serious impediment to aging people nowadays. One of the efficient methods used to monitor these neurological disorders is the detection of neurotransmitters such as dopamine. Metal materials, such as gold and platinum, are widely used in this electrochemical detection method; however, low sensitivity and linearity at low dopamine concentrations limit the use of these materials. To overcome these limitations, a silver nanoparticle (SNP) modified electrode covered by graphene oxide for the detection of dopamine was newly developed in this study. For the first time, the surface of an indium tin oxide (ITO) electrode was modified using SNPs and graphene oxide sequentially through the electrochemical deposition method. The developed biosensor provided electrochemical signal enhancement at low dopamine concentrations in comparison with previous biosensors. Therefore, our newly developed SNP modified electrode covered by graphene oxide can be used to monitor neurological diseases through electrochemical signal enhancement at low dopamine concentrations.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
    Published by MDPI Publishing
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