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Correlating the Effect of Covid-19 Lockdown with Mobility Impacts: A Time Series Study Using Noise Sensors Data

Transportation Research Procedia 2022年 62卷 115-122页

作者： Antonio Pascale Simona Mancini Pedro M. d’Orey Claudio Guarnaccia Margarida C. Coelho Centre for Mechanical Technology and Automation Dept. of Mechanical Engineering University of Aveiro Campus Universitário de Santiago 3801-193 Aveiro Portugal Department of Information and Electric Engineering and Applied Mathematics University of Salerno Via Giovanni Paolo II 132 I-84084 Fisciano Italy Real-Time and Embedded Computing Systems Research Centre (CISTER) ISEP IPP Rua Dr. António Bernardino de Almeida 431 4200-072 Porto Portugal Dept. of Civil Engineering University of Salerno Via Giovanni Paolo II 132 I-84084 Fisciano Italy

The Covid-19 crisis forced governments around the world to rapidly enact several restrictions to face the associated health emergency. The Portuguese government was no exception and, following the example of other countries, established various limitations to flat the contagions curve. This led to inevitable repercussions on mobility and environmental indicators including noise. This research aims to assess the impact of the lockdown due to Covid-19 disease on the noise levels recorded in the city of Porto, Portugal. Data from four noise sensors located in strategic spots of the city were used to calibrate and validate Time Series Models, allowing to impute the missing values in the datasets and rebuild them. The trend and the cyclic information were extracted from the reconstructed datasets using decomposition techniques. Finally, a Spearman correlation analysis between noise levels values and traffic volumes (extracted from five inductive loop detectors, located nearby the noise sensors) was performed. Results show that the noise levels series present a daily seasonal pattern and the trends values decreased from 6.7 to 7.5 dBA during the first lockdown period (March-May 2020). Moreover, the noise levels tend to gradually rise after the removal of restrictions. Finally, there is a monotonic relationship between noise levels and traffic volumes values, as confirmed by the positive moderate-to-high correlation coefficients found, and the sharp drop of the former during March-May 2020 can be attributed to the strong reduction of road traffic flows in the city.

关键词： Traffic Noise Time Series Models Covid-19 Inductive Loops

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A configurable BNN ASIC using a network of programmable threshold logic standard cells

arXiv

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arXiv 2021年

作者： Wagle, Ankit Khatri, Sunil Vrudhula, Sarma School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ United States Dept. of Electrical and Computer Engineering Texas A&M University College StationTX United States

This paper presents TULIP, a new architecture for a binary neural network (BNN) that uses an optimal schedule for executing the operations of an arbitrary BNN. It was constructed with the goal of maximizing energy efficiency per classification. At the top-level, TULIP consists of a collection of unique processing elements (TULIP-PEs) that are organized in a SIMD fashion. Each TULIP-PE consists of a small network of binary neurons, and a small amount of local memory per neuron. The unique aspect of the binary neuron is that it is implemented as a mixed-signal circuit that natively performs the inner-product and thresholding operation of an artificial binary neuron. Moreover, the binary neuron, which is implemented as a single CMOS standard cell, is reconfigurable, and with a change in a single parameter, can implement all standard operations involved in a BNN. We present novel algorithms for mapping arbitrary nodes of a BNN onto the TULIP-PEs. TULIP was implemented as an ASIC in TSMC 40nm-LP technology. To provide a fair comparison, a recently reported BNN that employs a conventional MAC-based arithmetic processor was also implemented in the same technology. The results show that TULIP is consistently 3X more energy-efficient than the conventional design, without any penalty in performance, area, or accuracy. © 2021, CC BY.

关键词： Energy efficiency

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Zero Trust Management Over Consumer Technology Based IoT Edge Node for SDN Communication and Control of Cyber-Physical systems

引用

IEEE Transactions on Consumer Electronics 2025年

作者： Byeon, Haewon Alsaadi, Mahmood Gupta, Sachin Patni, Jagdish Chandra Ahanger, Tariq Ahamed Singh, Brajesh Kumar Srivastava, Ajeet Kumar Abdinabievna, Pardaeva Shakhnoza Boddupalli, Santhosh Korea University of Technology and Education Convergence Department Cheonan Korea Republic of University of Al Maarif College of Sciences Department of Computer Sciences Al Anbar31001 Iraq Maharaja Agrasen Institute of Technology Department of CSE Delhi India Alliance University Bengaluru Dept. of CSE Alliance School of Advance Computing Karnataka India CoBA Prince Sattam Bin Abdulaziz University Department of Management Information Systems Saudi Arabia Galgotia College of Engineering and Technology Department of Electronics and Communication Engineering Greater Noida India Chhatrapati Shahu Ji Maharaj University Department of ECE school of engineering and technology Kanpur India Tashkent State University of Economics The department of Bank Accounting and Audit Tashkent Uzbekistan Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Telangana Hyderabad500075 India

In response to the lack of effective means for detecting and locating malicious exchange nodes in data flow transmission links within the Internet of Things (IoT), this paper proposes a zero-trust management method for data flow between edge nodes based on software defined networking (SDN) communication and control of cyber-physical systems (CPS). To detect and prevent anomalous behaviors like data tampering, forwarding path anomalies, and malicious packet drops through forwarding verification by exchange nodes, SDN-ZTM applies SDN to the data transmission process between IoT edge nodes. This approach applies the SDN architecture to the transmission process of data flows between edge nodes, utilizing a fixed-length header overhead for zero-trust management of data flows, nodes, and paths, thereby enabling lightweight packet forwarding verification and malicious exchange node localization. Simulation studies and theoretical research show that SDN-ZTM offers more extensive security features than similar methods. Additionally, SDN-ZTM is a lightweight, useful solution appropriate for IoT application scenarios since it introduces a fixed-length header and has a smaller performance overhead. Experimental results show that the method introduces less than 10% forwarding delay and less than 8% throughput loss. © 1975-2011 IEEE.

关键词： Cybersecurity

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Proceedings Introduction

2021 IEEE Conference on Norbert Wiener in the 21st Century: ...

引用

2021 IEEE Conference on Norbert Wiener in the 21st Century: Being Human in a Global Village, 21CW 2021 2021年

作者： Love, Heather Adamson, Greg Gopal, T.V. Department of English Language and Literature University of Waterloo Canada Computing and Information Systems University of Melbourne MelbourneVIC Australia Dept. of Computer Science Engineering CEG Campus Anna University Chennai India

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TDSR: Transparent Distributed Segment-Based Routing

arXiv

引用

arXiv 2020年

作者： Crespo, Juan-Jose Maglione-Mathey, German Sánchez, José L. Alfaro-Cortés, Francisco J. Flich, Jose Dept. of Computing Systems University of Castilla-La Mancha Albacete Spain Dept. of Computer Engineering Technical University of Valencia Valencia Spain

Component reliability and performance pose a great challenge for interconnection networks. Future technology scaling such as transistor integration capacity in VLSI design will result in higher device degradation and manufacture variability. As a consequence, changes in the network arise, often rendering irregular topologies. This paper proposes a topology-agnostic distributed segment-based algorithm able to handle switch discovery in any topology while guaranteeing connectivity among switches. The proposal, known as Transparent Distributed Segment-Based Routing (TDSR), has been applied to meshes with defective link configurations. Copyright © 2020, The Authors. All rights reserved.

关键词： Topology

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A Survey on Explainable Artificial Intelligence for Cybersecurity

arXiv

引用

arXiv 2023年

作者： Rjoub, Gaith Bentahar, Jamal Wahab, Omar Abdel Mizouni, Rabeb Song, Alyssa Cohen, Robin Otrok, Hadi Mourad, Azzam King Hussein School of Computing Sciences Princess Sumaya University for Technology Jordan Concordia Institute for Information Systems Engineering Concordia University Montreal Canada Department of Computer and Software Engineering Polytechnique Montréal Montréal Canada Electrical Engineering and Computer Science Department Khalifa University Abu Dhabi United Arab Emirates Department of EECS Khalifa University Abu Dhabi United Arab Emirates David R. Cheriton School of Computer Science University of Waterloo Canada Cyber Security Systems and Applied AI Research Center Dept. of CSM Lebanese American University Lebanon Division of Science New York University Abu Dhabi United Arab Emirates

The "black-box" nature of artificial intelligence (AI) models has been the source of many concerns in their use for critical applications. Explainable Artificial Intelligence (XAI) is a rapidly growing research field that aims to create machine learning models that can provide clear and interpretable explanations for their decisions and actions. In the field of cybersecurity, XAI has the potential to revolutionize the way we approach network and system security by enabling us to better understand the behavior of cyber threats and to design more effective defenses. In this survey, we review the state of the art in XAI for cybersecurity and explore the various approaches that have been proposed to address this important problem. The review follows a systematic classification of cybersecurity threats and issues in networks and digital systems. We discuss the challenges and limitations of current XAI methods in the context of cybersecurity and outline promising directions for future research. © 2023, CC BY.

关键词： Cybersecurity

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Spider Monkey Optimization to Solve Traveling Salesman Problem 2

Spider Monkey Optimization to Solve Traveling Salesman Probl...

引用

2nd International Conference on Electrical, Computer and Communication engineering, ECCE 2019

作者： Ayon, Safial Islam Akhand, M.A.H. Shahriyar, S.A. Siddique, N. Dept. of CSE Khulna University of Engineering Technology Khulna Bangladesh School of Computing Engineering and Intelligent Systems Ulster University United Kingdom

ISBN: (纸本)9781538691113

Traveling Salesman Problem (TSP) is the most well-known combinatorial optimization real-world problem. TSP is also very popular to check proficiency in any newly developed optimization method. In addition, the optimization methods, which are developed for other tasks (e. g., numerical optimization), also test their proficiency in TSP. This study investigates a new technique to solve TSP based on a recently developed optimization technique stimulated through the foraging conduct of spider monkeys. Standard Spider Monkey Optimization (SMO) is established for numerical optimization which has six phases and each one has a different purpose. In this study, SMO is modified and updated to solve TSP;and Swap Operators (SOs), and Swap Sequence (SS) are considered to adapt SMO for TSP. In the proposed method, each spider monkey is considered as a TSP solution and SS is considered to update the solution. SS is an arrangement of several SOs in which each one holds two particular positions of a solution that might be swapped to make a new solution. All SOs of a SS is applied on a specific tour maintaining order and thus ramifications of the SS change the TSP tour into another one. The SOs are generated using the experience of a specific spider monkey as well as the experience of other members (local leader, global leader, or randomly selected spider monkey) of the group. The proposed strategy has been examined on a huge number of benchmark TSPs and final consequences are compared to other prominent methods. SMO shows 11 best result out of 15 benchmark TSP problem compare to Ant Colony Optimization (ACO) and Velocity Tentative PSO (VTPSO). Experimental consequences show that the proposed strategy is a decent technique to solve TSP. © 2019 IEEE.

关键词： Traveling salesman problem

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A Generic Deep Learning-Based computing Algorithm in Support of the Development of Instrumented Bikes

ASCE Open: Multidisciplinary Journal of Civil Engineering

引用

ASCE Open: Multidisciplinary Journal of Civil engineering 2024年第1期2卷

作者： Ho, Chun-Hsing Qiu, Peijie Zhang, Yifei Ren, Kewei Durham School of Architectural Engineering and Construction Univ. of Nebraska Ͽ Lincoln 113 Nebraska Hall P.O. Box 880500 900 N. 16th St. LincolnNE68588-0500 United States Dept. of Computer Science and Engineering Washington Univ. at St. Louis One Brookings Dive St. LouisMO63130 United States School of Informatics Computing and Cyber Systems Northern Arizona Univ. 1295 S. Knoles Dr. P.O. Box 5693 FlagstaffAZ8601 United States

The paper introduces a generic deep learning-based method using a sliding window computing algorithm based on long short-term memory (LSTM) networks for the classification of potential anomalies (e.g., cracks, potholes, bumps, and uneven surfaces) in support of the development of an instrumented bike. The instrumented bike provides a real-time platform to sense, store, transmit, and analyze cycling information through a sensor logger, smartphone, and the proposed LSTM-based sliding window computing algorithm. The paper is to address concerns with respect to existing factors such as weight of cyclists, speeds, types of bikes, and threshold setting that have an impact on the accuracy of identification of potential anomalies during instrumented cycling activities. The LSTM-based sliding window computing algorithm is designed in a way that it analyzes and localizes anomalies without any human-controlled supervision (threshold setting) while achieving human-level perception. Two bike routes were selected to validate the effectiveness of the sliding window computing algorithm in the identification of anomalies involving four cyclists. Based on the computing results from the two field tests, the numbers of distressed pavement areas from the four cyclists were 53, 51, 46, and 48, respectively. The follow-up p-value of ANOVA test result is 0.98, indicating the difference in detected anomalies among the four cyclists is not significant. Therefore, the paper concludes that the LSTM-based sliding window computing algorithm has the ability to effectively detect anomalies of cycling trails and it also provides an effective and efficient technique to replace the human-made threshold setting in support of the development of instrumented bikes and promote cycling as a daily mode of transportation. © 2024 This work is made available under the terms of the Creative Commons Attribution 4.0 International license,.

关键词： Long short-term memory

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Synthesis of Facial Image using Conditional Generative Adversarial Network 5

Synthesis of Facial Image using Conditional Generative Adver...

引用

5th International Conference on Computer, Communication, Chemical, Materials and Electronic engineering, IC4ME2 2019

作者： Roy, Shuvendu Akhand, M.A.H. Siddique, N. Khulna University of Engineering Technology Dept. of Computer Science and Engineering Khulna Bangladesh Ulster University School of Computing Engineering and Intelligent Systems United Kingdom

ISBN: (纸本)9781728130606

Face sketch is done by sketch artist for a suspected or missing person from the description of an eyewitness. These methods have been widely used by forensic investigators. It is difficult for the sketch artist to draw perfectly from such verbal descriptions given by eyewitness of scenes and hard for the informer to confirm whether the sketch looks like the real person. In this work, we proposed a conditional generative adversarial network (cGAN) for synthesizing real human face taking a sketch as an input image. The focus of our model is to generate realistic images that preserve the identity the target person verified by face recognition algorithms. The proposed cGAN has been verified on a variety of facial sketches, which confirms the effectiveness and improved facial recognition score. © 2019 IEEE.

关键词： Generative adversarial networks

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Sentiment analysis of users’ reviews on COVID-19 contact tracing apps with a benchmark dataset

arXiv

引用

arXiv 2021年

作者： Ahmad, Kashif Alam, Firoj Qadir, Junaid Qolomany, Basheer Khan, Imran Khan, Talhat Suleman, Muhammad Said, Naina Hassan, Syed Zohaib Gul, Asma Al-Fuqaha, Ala College of Science and Engineering HBKU Doha Qatar Qatar Computing Research Institute HBKU Qatar Dept.of EE Information Technology University Lahore Pakistan Dept. of Cyber Systems University of Nebraska Kearney United States DCSE University of Engineering and Technology Peshawar Pakistan University of Trento Italy Dept. of Stat. Shaheed Benazir Bhutto Women University Peshawar Pakistan

Contact tracing has been globally adopted in the fight to control the infection rate of COVID-19. Thanks to digital technologies, such as smartphones and wearable devices, contacts of COVID-19 patients can be easily traced and informed about their potential exposure to the virus. To this aim, several interesting mobile applications have been developed. However, there are ever-growing concerns over the working mechanism and performance of these applications. The literature already provides some interesting exploratory studies on the community’s response to the applications by analyzing information from different sources, such as news and users’ reviews of the applications. However, to the best of our knowledge, there is no existing solution that automatically analyzes users’ reviews and extracts the evoked sentiments. In this work, we propose a pipeline starting from manual annotation via a crowd-sourcing study and concluding on the development and training of AI models for automatic sentiment analysis of users’ reviews. In total, we employ eight different methods achieving up to an average F1-Scores 94.8% indicating the feasibility of automatic sentiment analysis of users’ reviews on the COVID-19 contact tracing applications. We also highlight the key advantages, drawbacks, and users’ concerns over the applications. Moreover, we also collect and annotate a large-scale dataset composed of 34,534 reviews manually annotated from the contract tracing applications of 46 distinct countries. The presented analysis and the dataset are expected to provide a baseline/benchmark for future research in the domain. © 2021, CC BY.

关键词： Viruses

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