scholarly journals Enabling Noninvasive Physical Assault Monitoring in Smart School with Commercial Wi-Fi Devices

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Qizhen Zhou ◽  
Chenshu Wu ◽  
Jianchun Xing ◽  
Shuo Zhao ◽  
Qiliang Yang
Keyword(s):  
School Violence ◽  
Domain Knowledge ◽  
Global Perspective ◽  
Detection Methods ◽  
Physical Assault ◽  
Indoor Environments ◽  
Time Frequency ◽  
True Detection ◽  
Body Sensors ◽  
Signal Processing Methods

Monitoring physical assault is critical for the prevention of juvenile delinquency and promotion of school harmony. A large portion of assault events, particularly school violence among teenagers, usually happen at indoor secluded places. Pioneering approaches employ always-on-body sensors or cameras in the limited surveillance area, which are privacy-invasive and cannot provide ubiquitous assault monitoring. In this paper, we present Wi-Dog, a noninvasive physical assault monitoring scheme that enables privacy-preserving monitoring in ubiquitous circumstances. Wi-Dog is based on widely deployed commodity Wi-Fi infrastructures. The key intuition is that Wi-Fi signals are easily distorted by human motions, and motion-induced signals could convey informative characteristics, such as intensity, regularity, and continuity. Specifically, to explicitly reveal the substantive properties of physical assault, we innovatively propose a set of signal processing methods for informative components extraction by selecting sensitive antenna pairs and subcarriers. Then a novel signal-complexity-based segmentation method is developed as a location-independent indicator to monitor targeted movement transitions. Finally, holistic analysis is employed based on domain knowledge, and we distinguish the violence process from both local and global perspective using time-frequency features. We implement Wi-Dog on commercial Wi-Fi devices and evaluate it in real indoor environments. Experimental results demonstrate the effectiveness of Wi-Dog which consistently outperforms the advanced abnormal detection methods with a higher true detection rate of 94% and a lower false alarm rate of 8%.

scholarly journals Towards Fingerprint Spoofing Detection in the Terahertz Range

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3379
Author(s):  
Norbert Pałka ◽  
Marcin Kowalski
Keyword(s):  
Theoretical Calculations ◽  
Complex Refractive Index ◽  
Detection Methods ◽  
Terahertz Time Domain Spectroscopy ◽  
Detection Rates ◽  
Time Frequency ◽  
Spoofing Detection ◽  
True Detection ◽  
Reflection Configuration ◽  
Frequency Features

Spoofing attacks using imitations of fingerprints of legal users constitute a serious threat. In this study, a terahertz time domain spectroscopy (TDS) setup in a reflection configuration was used for the non-intrusive detection of fingerprint spoofing. Herein, the skin structure of the finger pad is described with a focus on the outermost stratum corneum. We identified and characterized five representative spoofing materials and prepared thin and thick finger imitations. The complex refractive index of the materials was determined in TDS in the transmission configuration. For dataset collection, we selected a group of 16 adults of various ages and genders. The reflection results were analyzed both in the time (reflected signal) and frequency (reflectivity) domains. The measured signals were positively verified with the theoretical calculations. The signals corresponding to samples differ from the finger-related signals, which facilitates spoofing detection. Thanks to deconvolution, we provide a basic explanation of the observed phenomena. We propose two spoofing detection methods, predefined time–frequency features and deep learning based. The methods achieved high true detection rates of 87.9% and 98.8%. Our results show that the terahertz technology can be successfully applied for spoofing detection with high detection probability.

State of Research on Negative Pressure Techniques Applied to Leak Detection in Liquid Pipelines

2004 ◽  
Author(s):  
Wei Liang ◽  
Lai-bin Zhang ◽  
Zhao-hui Wang
Keyword(s):  
Pressure Wave ◽  
Analytical Techniques ◽  
Leak Detection ◽  
Point Of View ◽  
Detection Methods ◽  
Propagation Mechanism ◽  
Detection Techniques ◽  
Wave Detection ◽  
State Of Research ◽  
Signal Processing Methods

In China, the rarefaction-pressure wave techniques are widely used to diagnose the leakage fault for liquid pipelines. Many leaking propagating assumptions, such as stable single-phased flow hypothesis and none rarefaction wave front hypothesis, are often uncertain in the process of leak detection, which can easily result in some errors. Thus the rarefaction-pressure wave techniques should be integrated with other analytical techniques to compute a more accurate leak location. Additionally, the development trends of rarefaction-pressure wave techniques lie in three aspects. First, rarefaction-pressure wave detection techniques will be integrated with other compatible detection techniques and modern signal processing methods to solve the complex problems encountered in leak detection. Second, studies of rarefaction-pressure wave techniques have advanced to a new stage. The deductions on propagation mechanism of rarefaction-pressure wave have been successfully applied to determine leaks qualitatively. Third, analysis on rarefaction-pressure wave detection techniques will be made from a quantitative point of view. The quantitative data have been used to deduce leak amounts and location. The purpose of this paper is to present the recent achievements in the study of improved rarefaction-pressure wave detection techniques. The rarefaction-pressure wave detection methods, effects of incomplete information conditions, the improvements of rarefaction-pressure wave detection techniques with modified factors and propagation mechanisms are comprehensively investigated. The disfigurements of rarefaction-pressure wave are analyzed. The corresponding methods for resolving such problems as ill diagnostic information and weak amplitude values are put forward. Several methods for stronger small leakage detection ability, higher leakage positioning precision, lower false alarm rates are proposed. The application of rarefaction-pressure wave detection techniques to safety protection of liquid pipelines is also introduced. Finally, the prospect of rarefaction-pressure wave detection techniques is predicted.

scholarly journals Diagnosis of the Induction Machine Using Advanced Signal Processing Methods

2018 ◽  
Vol 3 (3) ◽  
pp. 143-150
Author(s):  
Abdelghani CHAHMI
Keyword(s):  
Induction Machine ◽  
Detection Methods ◽  
Diagnostic Tools ◽  
Simulation Tools ◽  
Electric Drives ◽  
Efficient Simulation ◽  
Squirrel Cage ◽  
Rotor Resistance ◽  
Three Phase ◽  
Signal Processing Methods

This work is a part of the thematic of monitoring and fault diagnosis of the squirrel cage three-phase induction machine. The choice of this type of machine is justified by the growing success it has exhibited, mainly, in the electric drives with variable speed. Signal based detection methods are presented is validated in simulation. The proposed diagnosis approach requires only little experimental data, and more importantly it provides efficient simulation tools that allow characterizing faulty behavior.In this study, the proposed approach considers the value of rotor resistance as fixed for condition monitoring. This value in the diagnostic tools which one uses is not fixed contrary to the classical approaches of control of machine.

scholarly journals Humans-as-a-Sensor for Buildings—Intensive Longitudinal Indoor Comfort Models

Buildings ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 174 ◽  
Author(s):  
Prageeth Jayathissa ◽  
Matias Quintana ◽  
Mahmoud Abdelrahman ◽  
Clayton Miller
Keyword(s):  
Human Perception ◽  
Indoor Environments ◽  
Physiological Variables ◽  
Occupant Comfort ◽  
Body Sensors ◽  
Thermal Light ◽  
Multi Class Classification ◽  
The Individual ◽  
Ecological Momentary ◽  
Indoor Comfort

Evaluating and optimising human comfort within the built environment is challenging due to the large number of physiological, psychological and environmental variables that affect occupant comfort preference. Human perception could be helpful to capture these disparate phenomena and interpreting their impact; the challenge is collecting spatially and temporally diverse subjective feedback in a scalable way. This paper presents a methodology to collect intensive longitudinal subjective feedback of comfort-based preference using micro ecological momentary assessments on a smartwatch platform. An experiment with 30 occupants over two weeks produced 4378 field-based surveys for thermal, noise, and acoustic preference. The occupants and the spaces in which they left feedback were then clustered according to these preference tendencies. These groups were used to create different feature sets with combinations of environmental and physiological variables, for use in a multi-class classification task. These classification models were trained on a feature set that was developed from time-series attributes, environmental and near-body sensors, heart rate, and the historical preferences of both the individual and the comfort group assigned. The most accurate model had multi-class classification F1 micro scores of 64%, 80% and 86% for thermal, light, and noise preference, respectively. The discussion outlines how these models can enhance comfort preference prediction when supplementing data from installed sensors. The approach presented prompts reflection on how the building analysis community evaluates, controls, and designs indoor environments through balancing the measurement of variables with occupant preferences in an intensive longitudinal way.

scholarly journals Indirect Immunodetection of Fungal Fragments by Field Emission Scanning Electron Microscopy

2015 ◽  
Vol 81 (17) ◽  
pp. 5794-5803 ◽  
Author(s):  
Komlavi Anani Afanou ◽  
Anne Straumfors ◽  
Asbjørn Skogstad ◽  
Ajay P. Nayak ◽  
Ida Skaar ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Field Emission ◽  
Polyclonal Antibodies ◽  
Detection Methods ◽  
Indoor Environments ◽  
Content Type ◽  
Freeze Dried ◽  
Scanning Electron

ABSTRACTSubmicronic fungal fragments have been observed inin vitroaerosolization experiments. The occurrence of these particles has therefore been suggested to contribute to respiratory health problems observed in mold-contaminated indoor environments. However, the role of submicronic fragments in exacerbating adverse health effects has remained unclear due to limitations associated with detection methods. In the present study, we report the development of an indirect immunodetection assay that utilizes chicken polyclonal antibodies developed against spores fromAspergillus versicolorand high-resolution field emission scanning electron microscopy (FESEM). Immunolabeling was performed withA. versicolorfragments immobilized and fixed onto poly-l-lysine-coated polycarbonate filters. Ninety percent of submicronic fragments and 1- to 2-μm fragments, compared to 100% of >2-μm fragments generated from pure freeze-dried mycelial fragments ofA. versicolor, were positively labeled. In proof-of-concept experiments, air samples collected from moldy indoor environments were evaluated using the immunolabeling technique. Our results indicated that 13% of the total collected particles were derived from fungi. This fraction comprises 79% of the fragments that were detected by immunolabeling and 21% of the spore particles that were morphologically identified. The methods reported in this study enable the enumeration of fungal particles, including submicronic fragments, in a complex heterogeneous environmental sample.

Method of Harmonic Detection Based on the Wavelet Transform

2013 ◽  
Vol 748 ◽  
pp. 646-650
Author(s):  
Qing Yang Liang ◽  
Zhe Sun ◽  
Chen Fei Zhang
Keyword(s):  
Wavelet Transform ◽  
Active Power Filter ◽  
Active Power ◽  
Detection Methods ◽  
Harmonic Detection ◽  
Harmonic Current ◽  
Time Frequency ◽  
Power Filter ◽  
Detection Technology ◽  
Current Detection

The harmonic current detection technology is one of the key technologies of active power filter technologies. The development of the harmonic current detection technology directly determines the development of the active power filter technologies. Based on this, this paper introduces some basis concepts of wavelet transform and analyzes its time-frequency localization properties, then, describes the harmonic detection methods based on wavelet transform in terms of program building, algorithm selection and wavelet function selection. The results show that the harmonic current detection methods based on wavelet transform are able to compensate the inadequacy of Fourier transforms and can achieve the functions of detecting the steady-state and time-varying harmonic current of the grid in harmonic detection of active power filter.

scholarly journals Design and implementation of the subsystem subject to emission of multicomponent high-frequency signals to ensure its reliability

2019 ◽  
Vol 9 (5) ◽  
pp. 4204
Author(s):  
Milad Daneshvar ◽  
Naser Parhizgar ◽  
Homayoon Oraizi
Keyword(s):  
High Frequency ◽  
Detection Methods ◽  
System Behavior ◽  
Time Frequency ◽  
Telecommunication Systems ◽  
Multicomponent Signals ◽  
Extensive Range ◽  
Interference Signals ◽  
Analytic Signals ◽  
Phase Differences

Telecommunication systems, especially digital ones, are mostly known to be immune to noise given their extensive range of applications. This study aimed to investigate the methods and tools used for the analysis of multicomponent signals input to high-frequency digital subsystems, including the analysis of changes in its electrical behavior. This research mainly focuses on analyzing a high-frequency telecommunication subsystem, recording the results, investigating the system behavior against signals with different amplitudes and phases, detecting the received signals, and measuring the phase differences. The study extended the mono-component signals to multi-component signals and accurately extracted the statistical signal specifications using analytic signals in the time-frequency domain. To this end, a method was proposed based on the switch matrix to relate the different components and parameters, and also a mathematical model based on the state-space equations was employed to evaluate the nonlinear system modes. Given that the decoupling of measurement parameters is a problem to be tackled from multiple aspects, the costs and test durations were also taken into calculations in addition to considering all the detection methods for interference signals, reliability and time under test.

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