In recent years, the integration of computation, communication, and physical systems has led to the emergence of a new paradigm called Cyber-Physical Systems (CPSs). Examples of CPS are ubiquitous, including home auto...
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The general increase in data size and data sharing motivates the adoption of Big Data strategies in several scientific disciplines. However, while several options are available, no particular guidelines exist for sele...
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Air Quality Index (AQI) is an important indicator for determining good or bad air quality. The accurate and efficient prediction of AQI plays a positive role in promoting the management of air pollution. However, curr...
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In this paper, a method for bearing fault diagnosis based on an improved deep residual contraction network is proposed. The method utilizes the residual contraction module in the deep residual contraction network, whi...
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The growing global market of electric vehicles (EVs) increasingly needs fast charging stations to be installed at many facilities such as university campuses, shopping malls, hospitals, parking facilities etc. When co...
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Monitoring respiration is an important component of personal health *** recent developments in Wi-Fi sensing offer a potential tool to achieve contact-free respiration monitoring,existing proposals for Wi-Fi-based mul...
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Monitoring respiration is an important component of personal health *** recent developments in Wi-Fi sensing offer a potential tool to achieve contact-free respiration monitoring,existing proposals for Wi-Fi-based mul-ti-person respiration sensing mainly extract individual's respiration rate in the frequency domain using the fast Fourier transform(FFT)or multiple signal classification(MUSIC)method,leading to the following limitations:1)largely ineffec-tive in recovering breaths of multiple persons from received mixed signals and in differentiating individual breaths,2)un-able to acquire the time-varying respiration pattern when the subject has respiratory abnormity,such as apnea and chang-ing respiration rates,and 3)difficult to identify the real number of subjects when multiple subjects share the same or simi-lar respiration *** address these issues,we propose Wi-Fi-enabled MUlti-person SEnsing(WiMUSE)as a signal pro-cessing pipeline to perform respiration monitoring for multiple persons ***,as a pioneering time domain approach,WiMUSE models the mixed signals of multi-person respiration as a linear superposition of multiple waveforms,so as to form a blind source separation(BSS)*** effective separation of the signal sources(respira-tory waveforms)further enables us to quantify the differences in the respiratory waveform patterns of multiple subjects,and thus to identify the number of subjects along with their respective respiration *** implement WiMUSE on commodity Wi-Fi devices and conduct extensive experiments to demonstrate that,compared with the approaches based on the FFT or MUSIC method,90％error of respiration rate can be reduced by more than 60％.
In many IIoT architectures,various devices connect to the edge cloud via gateway *** data processing,numerous data are delivered to the edge *** data to an appropriate edge cloud is critical to improve IIoT service **...
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In many IIoT architectures,various devices connect to the edge cloud via gateway *** data processing,numerous data are delivered to the edge *** data to an appropriate edge cloud is critical to improve IIoT service *** are two types of costs for this kind of IoT network:a communication cost and a computing *** service efficiency,the communication cost of data transmission should be minimized,and the computing cost in the edge cloud should be also ***,in this paper,the communication cost for data transmission is defined as the delay factor,and the computing cost in the edge cloud is defined as the waiting time of the computing *** proposed method selects an edge cloud that minimizes the total cost of the communication and computing *** is,a device chooses a routing path to the selected edge cloud based on the *** proposed method controls the data flows in a mesh-structured network and appropriately distributes the data processing *** performance of the proposed method is validated through extensive computer *** the transition probability from good to bad is 0.3 and the transition probability from bad to good is 0.7 in wireless and edge cloud states,the proposed method reduced both the average delay and the service pause counts to about 25%of the existing method.
Regression testing of software systems is an important and critical activity yet expensive and resource-intensive. An approach to enhance its efficiency is Regression Test Selection (RTS), which selectively re-execute...
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Regression testing of software systems is an important and critical activity yet expensive and resource-intensive. An approach to enhance its efficiency is Regression Test Selection (RTS), which selectively re-executes a subset of relevant tests that are impacted by code modifications. Previous studies on static and dynamic RTS for Java software have shown that selecting tests at the class level is more effective than using finer granularities like methods or statements. Nevertheless, RTS at the package level, which is a coarser granularity than class level, has not been thoroughly investigated or evaluated for Java projects. To address this gap, we propose PKRTS, a static package-level RTS approach that utilizes the structural dependencies of the software system under test to construct a package-level dependency graph. PKRTS analyzes dependencies in the graph and identifies relevant tests that can reach modified packages, i.e., packages containing altered classes. In contrast to conventional static RTS techniques, PKRTS implicitly considers dynamic dependencies, such as Java reflection and virtual method calls, among classes belonging to the same package by treating all those classes as a single cohesive node in the dependency graph. We evaluated PKRTS on 885 revisions of 9 open-source Java projects, with its performance compared to Ekstazi, a state-of-the-art dynamic class-level approach, and STARTS, a state-of-the-art static class-level approach. We used Ekstazi as the baseline to measure the safety and precision violations of PKRTS and STARTS. The results indicated that PKRTS outperformed static class-level RTS in terms of safety violation, which measures the extent to which relevant test cases are missed. PKRTS showed an average safety violation of 2.29% compared to 5.94% safety violation of STARTS. Despite this, PKRTS demonstrated lower precision violation and lower reduction in test suite size than class-level RTS, as it selects higher number of irrelevant te
We study temporal analogues of the Unrestricted Vertex Separator problem from the static world. An (s, z)-temporal separator is a set of vertices whose removal disconnects vertex s from vertex z for every time step in...
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There are many privacy risks when location data is collected and aggregated. We introduce the notion of using confidential smart contracts for building location-based decentralized applications that are privacy preser...
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