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arXiv 2023年

作者： Nandita Arora, Rajan Department of Applied Mathematics Scientific Computing Indian Institute of Technology Roorkee India

In this paper, the propagation of the blast (shock) waves in non-ideal gas atmosphere in rotational medium is studied using a power series method in cylindrical geometry. The flow variables are assumed to be varying according to the power law in the undisturbed medium with distance from the symmetry axis. To obtain the similarity solution, the initial density is considered as constant in the undisturbed medium. Approximate analytical solutions are obtained using Sakurai's method by extending the power series of the flow variables in power of (Equation presented). where U and a0 are the speeds of the shock and sound, respectively, in undisturbed fluid. The strong shock wave is considered for the ratio (Equation presented). which is considered to be a small quantity. With the aid of that method, the closed-form solutions for the zeroth-order approximation is given as well as first-order approximate solutions are discussed. Also, with the help of graphs behind the blast wave for the zeroth-order approximation, the distributions of variables such as density, radial velocity, pressure and azimuthal fluid velocity are analyzed. The results for the rotationally axisymmetric non-ideal gas environment are compared to those for the ideal gas atmosphere. © 2023, CC BY-NC-ND.

关键词： Gases

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Exact Instability Margin Analysis and Minimum-Norm Strong Stabilization - Phase Change Rate Maximization

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IEEE Transactions on Automatic Control 2024年第4期69卷 2084-2099页

作者： Hara, Shinji Kao, Chung-Yao Khong, Sei Zhen Iwasaki, Tetsuya Hori, Yutaka Tokyo Institute of Technology Global Scientific Information and Computing Center Tokyo152-8550 Japan National Sun Yat-Sen University Department of Electrical Engineering Kaohsiung80421 Taiwan University of California at Los Angeles Department of Mechanical and Aerospace Engineering Los AngelesCA90095 United States Keio University Applied Physics and Physico Informatics Yokohama223-8522 Japan Monaco

This article is concerned with a new optimization problem named 'phase change rate maximization' for single-input-single-output linear time-invariant systems. The problem relates to two control problems, namely robust instability analysis against stable perturbations and minimum-norm strong stabilization. We define an index of the instability margin called 'robust instability radius (RIR)' as the smallest H∞-norm of a stable perturbation that stabilizes a given unstable system. This article has two main contributions. It is first shown that the problem of finding the exact RIR via the small-gain condition can be transformed into the problem of maximizing the phase change rate at the peak frequency with a phase constraint. Then, we show that the maximum is attained by a constant or a first-order all-pass function and derive conditions, under which the RIR can be exactly characterized, in terms of the phase change rate. Two practical applications are provided to illustrate the utility of our results. © 1963-2012 IEEE.

关键词： Robust control

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On the adaptive delegation and sequencing of actions 18

On the adaptive delegation and sequencing of actions

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18th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2021

作者： Stolpe, Audun Hannay, Jo Erskine Norwegian Computing Center Department of Applied Research in Information Technology Norway

ISBN: (纸本)9781949373615

Information systems support to crisis response and management relies on presenting actionable information in a manner that supports cognitive processes. We outline how AI Planning can be used viably to support the delegation and sequencing of tasks, using standard operating procedures as initial specifications of plans. When expressed in the AI planning language Answer set Programming (ASP), machine reasoning can be used in a pre-incident review to display the cooperative structure inherent in a plan. The purpose of this is to uncover weaknesses and to optimize the plan. Further, adaptive planning can be supported in during-incident reviews by updating the current status and recomputing the consequences. At this point, initial goals may no longer be viable and the explicit suggestion of prior sub-optimal goals now worth pursuing can be a game-changer under stress. © 2021 Information Systems for Crisis Response and Management, ISCRAM. All rights reserved.

关键词： Information systems

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Automated Fire Hydrant Monitoring and Maintenance using IoT Data Analytics and Naive Bayes Classifier

Automated Fire Hydrant Monitoring and Maintenance using IoT ...

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2024 International Conference on Distributed Systems, Computer Networks and Cybersecurity, ICDSCNC 2024

作者： Sarasu, R. Nandagopal, V. Shibu, N.V. Lakshminarayanan, Suresh Raj, T Saju Rajmohan, M. Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Spatial Informatics Chennai India Mohan Babu University School of Engineering Department of Electrical and Electronics Engineering Tirupathi India Srm Institute of Science and Technology School of Computing Department of Computing Technologies Kattankulathur Chennai India University of Technology and Applied Sciences Department of Engineering & Electronics South Al Batina Oman Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India Hindustan Institute of Technology and Science Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350375442

This paper introduces a new method for managing fire hydrants that uses a monitoring system based on the Internet of Things (IoT) and a Naive Bayes Classifier (NBC) for predictive maintenance. Water pressure, flow rate, and the physical state of fire hydrants are among the essential factors for the proposed system continually collecting data using an IoT sensor network. The system analyzes real-time data using NBC. These predictive capabilities reduce the potential of hydrant breakdowns during emergencies through preventive maintenance potential. It introduces a reliable IoT infrastructure for fire hydrant monitoring, improving the acquired data's granularity and timeliness. NBC provides a powerful instrument for early problem detection, significantly improving maintenance effectiveness. Since the technology is compatible with existing fire department procedures, it can easily integrate into current operational processes. Better public safety, more efficient use of resources, and more dependable fire hydrants are potential outcomes of responsive and proactive data-driven maintenance techniques. The findings improve overall fire safety and operational efficiency, with a 25% decrease in maintenance expenditures and a 40% increase in issue detection accuracy. © 2024 IEEE.

关键词： Predictive maintenance

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A Robust Model for Translating Arabic Sign Language into Spoken Arabic Using Deep Learning

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Intelligent Automation & Soft computing 2023年第8期37卷 2037-2057页

作者： Khalid M.O.Nahar Ammar Almomani Nahlah Shatnawi Mohammad Alauthman Department of Computer Sciences Faculty of Information Technology and Computer SciencesYarmouk University-Irbid21163Jordan School of Computing Skyline University CollegeSharjahP.O.Box 1797United Arab Emirates IT-Department-Al-Huson University College Al-Balqa Applied UniversityP.O.Box 50IrbidJordan Department of Information Security Faculty of Information TechnologyUniversity of PetraAmmanJordan

This study presents a novel and innovative approach to auto-matically translating Arabic Sign Language(ATSL)into spoken *** proposed solution utilizes a deep learning-based classification approach and the transfer learning technique to retrain 12 image recognition *** image-based translation method maps sign language gestures to corre-sponding letters or words using distance measures and classification as a machine learning *** results show that the proposed model is more accurate and faster than traditional image-based models in classifying Arabic-language signs,with a translation accuracy of 93.7%.This research makes a significant contribution to the field of *** offers a practical solution for improving communication for individuals with special needs,such as the deaf and mute *** work demonstrates the potential of deep learning techniques in translating sign language into natural language and highlights the importance of ATSL in facilitating communication for individuals with disabilities.

关键词： Sign language deep learning transfer learning machine learning automatic translation of sign language natural language processing Arabic sign language

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Cyberbullying Detection Using Deep Learning: A Comparative Study 2

Cyberbullying Detection Using Deep Learning: A Comparative S...

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2nd International Conference on Cyber Resilience, ICCR 2024

作者： Alkasassbeh, Mouhammd Almomani, Ammar Aldweesh, Amjad Al-Qerem, Ahmad Alauthman, Mohammad Nahar, Khalid Mago, Beenu Princess Sumaya University For Technology Computer Science Department Amman Jordan School Of Computing Skyline University College Sharjah United Arab Emirates AlHuson University College AlBalqa Applied University I.T. Department Irbid Jordan College Of Computing And It Shaqra University Shaqra Saudi Arabia Zarqa University Faculty Of Information Technology Computer Science Department Zarqa13110 Jordan University Of Petra Faculty Of Information Technology Department Of Information Security Amman Jordan Yarmouk University Faculty Of I.T Computer Science Department Irbid Jordan School Of Computing Skyline University College University City Of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9798350394962

Cyberbullying has become a serious issue with the rise in social media usage, especially among adolescents. Victims of cyberbullying often suffer from psychological distress, anxiety, depression and even suicidal tendencies. With the rapid growth of user-generated content online, manual detection of cyberbullying is extremely difficult. Hence, automated cyber-bullying detection systems are needed. In recent years, deep learning models have emerged as a promising technique for cyberbullying detection. This paper provides a comprehensive review of the use of deep learning for cyberbullying detection. The key contributions are: (1) a taxonomy of cyberbullying detection techniques, (2) a review of datasets used for model training and evaluation, (3) a comparative analysis of various deep learning models including CNN, RNN, LSTM, GRU and Transformer- based models, (4) a discussion of key challenges and limitations, and (5) suggestions for future research directions. The paper provides a critical perspective on model performance across multiple datasets. Key findings indicate RNNs and specifically LSTM and GRU models demonstrate state-of-the-art performance for sequential cyberbullying detection. The study concludes that deep ensemble models combining LSTMs and pretrained contextual embeddings show significant promise to advance the field. © 2024 IEEE.

关键词： Social networking (online)

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A Novel Feature Extraction Technique for ECG Arrhythmia Classification Using ML

A Novel Feature Extraction Technique for ECG Arrhythmia Clas...

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2023 IEEE International Conference on Dependable, Autonomic and Secure computing, 2023 International Conference on Pervasive Intelligence and computing, 2023 International Conference on Cloud and Big Data computing, 2023 International Conference on Cyber Science and technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Rahman, Mohammad Mominur Islam, Ashhadul Charni, Skander Bensmail, Halima Hilbel, Thomas Belhaouari, Samir Brahim College of Science and Engineering Hamad Bin Khalifa University Division of Information and Computing Technology Doha Qatar College of Engineering Qatar University Doha Qatar Doha Qatar Westphalian University of Applied Sciences Department of Electrical Engineering and Applied Sciences Gelsenkirchen Germany

ISBN: (纸本)9798350304602

Feature extraction is the process of transforming raw data into features that are more relevant for machine learning algorithms. The goal of feature extraction is to find a set of features that can be used to accurately predict the target variable. The specific features that are extracted will depend on the specific application. For example, features that are extracted for the purpose of diagnosing arrhythmias will be different from the features that are extracted for the purpose of assessing myocardial infarction. A generalized new algorithm for feature extraction could be helpful for all complex feature extraction data sets. In this paper, we propose a random selection process to generate the required number of new features with the help of existing specific features of the electrocardiogram (ECG) signal. We have named this novel feature extraction method the Random Feature Explorer (RFE). The proposed method was tested and evaluated using Physio Net's MIT-BIH datasets. The results indicate that the suggested method achieved an accuracy of 99.79% in arrhythmia classification. We have made the source code for our proposed method available on GitHub for open access and reproducibility. The code can be accessed at https://***/3NnrH4A © 2023 IEEE.

关键词： Electrocardiograms

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Adaptive energy-preserving algorithms for guiding center system

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Plasma Science and technology 2023年第4期25卷 11-22页

作者：朱贝贝刘健张嘉炜祝爱卿唐贻发 Department of Applied Mathematics School of Mathematics and PhysicsUniversity of Science and Technology BeijingBeijing 100083Peopleʼs Republic of China School of Nuclear Science and Technology University of Science and Technology of ChinaHefei 230026Peopleʼs Republic of China Advanced algorithm Joint Lab Shandong Computer Science CenterQilu University of TechnologyJinan 250014Peopleʼs Republic of China The State Key Laboratory of Scientific and Engineering Computing The Institute of Computational Mathematics and Scientific/Engineering ComputingAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190Peopleʼs Republic of China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049Peopleʼs Republic of China

We develop two types of adaptive energy preserving algorithms based on the averaged vector field for the guiding center dynamics,which plays a key role in magnetized *** adaptive scheme is applied to the Gauss Legendre’s quadrature rules and time stepsize respectively to overcome the energy drift problem in traditional energy-preserving *** new adaptive algorithms are second order,and their algebraic order is carefully *** results show that the global energy errors are bounded to the machine precision over long time using these adaptive algorithms without massive extra computation cost.

关键词： guiding center system energy-preserving methods adaptive energy conservation

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Blockchain and IIoT Enabled Solution for Social Distancing and Isolation Management to Prevent Pandemics

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Computers, Materials & Continua 2023年第7期76卷 687-709页

作者： Muhammad Saad Maaz Bin Ahmad Muhammad Asif Muhammad Khalid Khan Toqeer Mahmood Elsayed Tag Eldin Hala Abdel Hameed College of Computing and Information Sciences Karachi Institute of Economics&TechnologyKarachiPakistan Department of Computer Science Lahore Garrison UniversityLahorePakistan Department of Computer Science National Textile UniversityFaisalabad37610Pakistan Faculty of Engineering and Technology Future University in Egypt New Cairo11835Egypt Faculty of Computer and Information Systems Fayoum UniversityFaiyumEgypt Khaybar Applied College Taibah UniversityMedinaSaudi Arabia

Pandemics have always been a nightmare for humanity,especially in developing *** lockdowns are considered one of the effective ways to deal with spreading such ***,developing countries cannot afford such solutions because these may severely damage the country’s ***,this study presents the proactive technological mechanisms for business organizations to run their standard business processes during pandemic-like situations *** novelty of this study is to provide a state-of-the-art solution to prevent pandemics using industrial internet of things(IIoT)and blockchain-enabled *** to existing studies,the immutable and tamper-proof contact tracing and quarantine management solution is *** use of advanced technologies and information security is a critical area for practitioners in the internet of things(IoT)and corresponding ***,this study also emphasizes information security,end-to-end solution,and experimental ***,a wearable wristband is proposed,incorporating 4G-enabled ultra-wideband(UWB)technology for smart contact tracing mechanisms in industries to comply with standard operating procedures outlined by the world health organization(WHO).Secondly,distributed ledger technology(DLT)omits the centralized dependency for transmitting contact tracing ***,a privacy-preserving tracing mechanism is discussed using a public/private key cryptography-based authentication ***,based on geofencing techniques,blockchain-enabled machine-to-machine(M2M)technology is proposed for quarantine *** step-by-step methodology and test results are proposed to ensure contact tracing and quarantine *** existing research studies,the security aspect is also considered in the realm of *** practical implementation of the proposed solution also obtains the *** results indicate the successful implementation of blockchain-enabled contac

关键词： Blockchain contact tracing distributed ledger technology geo-fencing internet of things industrial internet of things isolation management social distancing ultra-wideband

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Vulnerability Management Using Open-Source Tools

Vulnerability Management Using Open-Source Tools

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IS and T International Symposium on Electronic Imaging 2024: Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications 2024

作者： Shivananjappa, Navaneeth Creutzburg, Reiner SRH Berlin University of Applied Sciences Berlin School of Technology Ernst-Reuter-Platz 10 BerlinD-10587 Germany Technische Hochschule Brandenburg Department of Computing and Media Magdeburger Str. 50 BrandenburgD-14770 Germany

In today's cybersecurity landscape, protecting information systems is crucial due to the rising threat of cyber-attacks. This research focuses on vulnerability management using open-source tools for domain and subdomain enumeration, vulnerability scanning, and remediation. Open-source software offers cost-effective and collaborative security solutions. Domain and subdomain enumeration tools play a vital role in mapping an organization's attack surface, providing insight into security posture. The analysis of vulnerability scanning tools highlights their effectiveness in identifying critical flaws in web applications and databases. Vulnerability remediation through patching, hardening, and exposure management processes closes security gaps. The research provides an empirical insight into using open-source tools for vulnerability management, listing their benefits and limitations empowering organizations to enhance their security posture. Recommendations for integrating these tools into existing security frameworks help combat cyber threats and protect valuable assets. © 2024, Society for Imaging Science and technology.

关键词： Open source software

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