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Non-polynomial Cubic Spline Method for Three-Dimensional Wave Equation

International Journal of Applied and Computational mathematics 2023年第6期9卷 1-20页

作者： Sattar, Rabia Ahmad, Muhammad Ozair Pervaiz, Anjum Ahmed, Nauman Akgül, Ali Department of Mathematics and Statistics University of Lahore Lahore 54590 Pakistan Department of Mathematics University of Engineering and Technology Lahore 54590 Pakistan Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon Department of Mathematics Art and Science Faculty Siirt University Siirt 56100 Turkey Department of Mathematics Mathematics Research Center Near East University Near East Boulevard Nicosia Mersin 10 99138 Turkey

The scientific community has always been showing deep concern towards partial differential equations (PDEs) and to approximate its numerical solution. This research proposes a non-polynomial cubic spline-based numerical technique for approximating the three-dimensional (3D) wave equation with Dirichlet boundary conditions. The proposed method develops an algebraic scheme for 3D wave equation which can be solved for different spatial and temporal levels. The suggested method provides a three-time level scheme with higher accuracy of order O(h⁸+ k⁸+ σ⁸+ τ²h²+ τ²k²+ τ²σ²) by electing appropriate parameter values involved in the spline function. The stability analysis of the suggested numerical technique has been examined and numerical solution of some selected problems are included to exhibit the validity of the proposed method. Numerical results of the test problems are prepared through tables and graphs to demonstrate the effectiveness of the presented work. © 2023, The Author(s), under exclusive licence to Springer Nature India Private Limited.

关键词： Non-polynomial cubic spline function Stability analysis Three-dimensional (3D) wave equations Truncation error

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Automatic Recognition of Construction Worker Activities Using Deep Learning Approaches and Wearable Inertial Sensors

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Intelligent Automation & Soft Computing 2023年第5期36卷 2111-2128页

作者： Sakorn Mekruksavanich Anuchit Jitpattanakul Department of Computer Engineering School of Information and Communication TechnologyUniversity of PhayaoPhayao56000Thailand Department of Mathematics Intelligent and Nonlinear Dynamic Innovations Research CenterFaculty of Applied ScienceKing Mongkut’s University of Technology North BangkokBangkok10800Thailand

The automated evaluation and analysis of employee behavior in an Industry 4.0-compliant manufacturingﬁrm are vital for the rapid and accurate diagnosis of work performance,particularly during the training of a new *** techniques for identifying and detecting worker performance in industrial applications are based on computer vision *** widespread com-puter vision-based approaches,it is challenging to develop technologies that assist the automated monitoring of worker actions at external working sites where cam-era deployment is *** the use of wearable inertial sensors,we propose a deep learning method for automatically recognizing the activities of construction *** suggested method incorporates a convolutional neural network,residual connection blocks,and multi-branch aggregate transformation modules for high-performance recognition of complicated activities such as con-struction worker *** proposed approach has been evaluated using standard performance measures,such as precision,F1-score,and AUC,using a publicly available benchmark dataset known as VTT-ConIoT,which contains genuine con-struction work *** addition,standard deep learning models(CNNs,RNNs,and hybrid models)were developed in different empirical circumstances to compare them to the proposed *** an average accuracy of 99.71%and an average F1-score of 99.71%,the experimentalﬁndings revealed that the suggested model could accurately recognize the actions of construction ***,we examined the impact of window size and sensor position on the identiﬁcation efﬁciency of the proposed method.

关键词： Complex human activity recognition wearable inertial sensors deep learning construction workers automatic recognition

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Nonlinear topology network routing shortest path based on improved particle swarm optimization algorithm 5

Nonlinear topology network routing shortest path based on im...

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5th IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2023

作者： Zheng, Hui Jin, Jin Jin, Dongshuai Wang, Yifan Zhang, Guoquan Zhang, Shenguo Northwest Minzu University Gansu Engineering Research Center for Eco-Environmental Intelligent Networking College of Electrical Engineering Lanzhou China Northwest Minzu University College of Mathematics and Computer Science Lanzhou China

ISBN: (纸本)9798350310603

In the nonlinear topology network routing, through the research on the routing algorithm that guarantees QoS in the network, the different performance characteristics of the network are fully considered, and the network bandwidth, network delay, packet loss rate, demonstration jitter and other indicators are comprehensively considered constraints, citing the respective advantages of particle swarm optimization and simulated annealing algorithms in modern meta-heuristic algorithms, an improved particle swarm optimization algorithm SAPSO is applied to a multi-constrained nonlinear topology network routing model. The algorithm can be successfully applied to this problem through simulation verification. The introduction of simulated annealing algorithm can well prevent falling into local optimal solution. Using the SAPSO algorithm can reduce the comprehensive cost of the network in a multi-constrained nonlinear topology network. © 2023 IEEE.

关键词： Topology

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Transformative effects of ChatGPT on modern education: Emerging Era of AI Chatbots

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Internet of Things and Cyber-Physical Systems 2024年第1期4卷 19-23页

作者： Gill, Sukhpal Singh Xu, Minxian Patros, Panos Wu, Huaming Kaur, Rupinder Kaur, Kamalpreet Fuller, Stephanie Singh, Manmeet Arora, Priyansh Parlikad, Ajith Kumar Stankovski, Vlado Abraham, Ajith Ghosh, Soumya K. Lutfiyya, Hanan Kanhere, Salil S. Bahsoon, Rami Rana, Omer Dustdar, Schahram Sakellariou, Rizos Uhlig, Steve Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Raygun Performance Monitoring Wellington New Zealand Center for Applied Mathematics Tianjin University Tianjin China Department of Science Kings Education London United Kingdom Cymax Group Technologies BC Canada QM Academy Queen Mary University of London London United Kingdom Jackson School of Geosciences University of Texas at Austin AustinTX United States Centre for Climate Change Research Indian Institute of Tropical Meteorology Pune India Microsoft Hyderabad India Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Machine Intelligence Research Labs AuburnWA United States Faculty of Computing and Data Science FLAME University Maharashtra Pune India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Department of Computer Science University of Western Ontario London Canada Sydney Australia School of Computer Science University of Birmingham United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Distributed Systems Group Vienna University of Technology Vienna Austria Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom Laboratory School of Computing and Information Systems The University of Melbourne Australia

ChatGPT, an AI-based chatbot, offers coherent and useful replies based on analysis of large volumes of data. In this article, leading academics, scientists, distinguish researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research discusses ChatGPT capabilities and its use in the education sector, identifies potential concerns and challenges. Our preliminary evaluation shows that ChatGPT perform differently in different subject areas including finance, coding, maths, and general public queries. While ChatGPT has the ability to help educators by creating instructional content, offering suggestions and acting as an online educator to learners by answering questions, transforming education through smartphones and IoT gadgets, and promoting group work, there are clear drawbacks in its use, such as the possibility of producing inaccurate or false data and circumventing duplicate content (plagiarism) detectors where originality is essential. The often reported "hallucinations" within GenerativeAI in general, and also relevant for ChatGPT, can render its use of limited benefit where accuracy is essential. What ChatGPT lacks is a stochastic measure to help provide sincere and sensitive communication with its users. Academic regulations and evaluation practices used in educational institutions need to be updated, should ChatGPT be used as a tool in education. To address the transformative effects of ChatGPT on the learning environment, educating teachers and students alike about its capabilities and limitations will be crucial. © 2023 The Authors

关键词： Machine learning

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A blockchain-oriented covert communication technology with controlled security level based on addressing confusion ciphertext

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Frontiers of computer science 2025年第2期19卷 133-135页

作者： Lejun ZHANG Bo ZHANG Ran GUO Zhujun WANG Guopeng WANG Jing QIU Shen SU Yuan LIU Guangxia XU Zhihong TIAN Sergey GATAULLIN Cyberspace Institute Advanced Technology Guangzhou UniversityGuangzhou 510006China Research and Development Center for E-Learning Ministry of EducationBeijing 100039China College of Information Engineering Yangzhou UniversityYangzhou 225009China School Math and Computer Science Quanzhou Normal UniversityQuanzhou 362000China Pazhou Lab Guangzhou 510330China School of Physics and Materials Science Guangzhou UniversityGuangzhou 510006China Central Economic and Mathematics Institute Russian Academy of SciencesMoscow 117418Russia Industrial Programming Department MIREA-Russian Technological UniversityMoscow 119454Russia

1 Introduction Traditional covert communication[1]usually relies on centralized channels,which are efficient in transmission but susceptible to eavesdropping and attacks,leading to information ***,distributed methods also exist,such as peer-to-peer networks and distributed hash *** technology,which is decentralized,anonymous,non-tamperable and anti-attack,can be applied to covert communication to solve the problems of traditional methods and improve the quality of communication.

关键词： communication tables networks

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A Survey of Low-Resource Named Entity Recognition 7th

A Survey of Low-Resource Named Entity Recognition

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7th International Conference on Information science, Communication and Computing, ISCC 2023

作者： Tang, Xiangyan Xia, Dongwan Li, Yajing Xu, Taixing Xiong, Neal N. School of Computer Science and Technology Hainan University Haikou570228 China College of Intelligence and Computing Tianjin University Tianjin300072 China Hainan Blockchain Technology Engineering Research Center Haikou570228 China Department of Computer Science and Mathematics Sul Ross State University AlpineTX79830 United States

ISBN: (纸本)9789819971602

Named Entity Recognition, as one of the typical tasks of information extraction, has a wide range of applications. However, the difficulty of data collection and the lack of data annotation are common problems in real scenarios. It is difficult for classical named entity recognition methods to fully obtain hidden information when the dataset and data labels are insufficient. In this case, the recognition accuracy will drop significantly. In resource-poor scenarios, the use of multi-task learning, data augmentation, and transfer learning methods can effectively utilize limited data resources or introduce data from other fields to optimize model performance. In this survey, firstly, we introduce the reader to the state of research on named entity recognition, and outline the reasons for the survey and the contribution of this paper. Then, we comprehensively describe the datasets and evaluation methods included in named entity recognition, and propose a Classification of named entity recognition in the case of lack of resources. Finally, we analyze the existing problems on the basis of the above, and further look forward to the future development direction. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Classification (of information)

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Block Chain Technology: Anomaly Detection in Bitcoin Using RFMLPAlgorithm 4

Block Chain Technology: Anomaly Detection in Bitcoin Using R...

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4th International Conference on Emerging Trends in Networks and computer Communications, ETNCC 2024

作者： Elangovan, V.R. Revathi, S. Nusrat Jabeen, T. Obaid, Ahmed J. Kumar, Rahul SRM Institute of Science and Technology Kattankulathur Faculty of Science and Humanities Department of Computer Applications Chennai India City University Faculty Cybersecurity Ajman United Arab Emirates University of Kufa College Al-Ayen University Computer Science and Mathematics Department of Computer Technical Engineering Technical Engineering Thi-Qar Iraq Lovely Professional University Division of Research and Development Phagwara144411 India KKR and KSR Institute of Technology and Sciences Andhra Pradesh Guntur India

ISBN: (纸本)9798350353266

Block chain technology has been used in many different fields, including banking, logistics, healthcare, and government. However, billions have been lost to cyber attacks on block chain apps in the last several years. An efficient approach for identifying malicious behavior in block chain networks is urgently required. Anomaly detection is a well-studied issue with a lengthy history of research. Anomalies are, in a nutshell, unusual or improbable occurrences. Theft and other illicit activity in financial networks are often outliers. Participants in the network want to spot anomalies as soon as possible to safeguard the overall safety and security of the system. However, fraud and anomaly detection techniques are constantly developing along with the financial industry. Furthermore, the most secure approach being brought into money is block chain technology. The number of scams, however, increases every year alongside these innovative technology. This is why we suggested a safe Anomaly detection technique that combines Machine Learning with Deep Learning. For the purpose of classifying Anomaly transactions, we used a unique hybrid RFMLP approach. For Bitcoin transaction anomaly detection, the RFMLP combines Random Forest (RF) with multilayer perceptron (MLP). We found that our RFMLP was more accurate than competing algorithms. © 2024 IEEE.

关键词： Bitcoin

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Modelling and control of a multi-product pipeline transportation process

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International Journal of Information Technology (Singapore) 2025年 1-11页

作者： Jiménez-Cabas, Javier Piñeres-Espitia, Gabriel Rodelo-Serrano, Esteban Pamucar, Dragan Ramirez-Leon, Hermes Butt, Shariq Aziz Naz, Sumera Simic, Vladimir Computer Science and Electronic Department Universidad de La Costa Barranquilla Colombia Departamento de Ingeniería Mecánica Universidad Simón Bolívar Barranquilla Venezuela Department of Operations Research and Statistics Faculty of Organizational Sciences University of Belgrade Belgrade Serbia Department of Industrial Engineering & Management Yuan Ze University Taoyuan Taiwan Department of Mechanics and Mathematics Western Caspian University Baku Azerbaijan Faculty of Transport and Traffic Engineering University of Belgrade Vojvode Stepe 305 Belgrade 11010 Serbia Department of Computer Science and Engineering College of Informatics Korea University Seoul 02841 South Korea School of Systems and Technology Department of Computer Science University of Management and Technology Lahore Pakistan Department of Mathematics Division of Science and Technology University of Education Lahore Pakistan

One of the most critical processes in the petroleum industry is transporting crude oil and its derivatives. Usually, it is done, due to easiness and economic aspects, through pipelines;several products, such as gasoline, kerosene, naphtha, and liquefied petroleum gas, among others, are moved in batch processes to both distribution and storage centers or transport ships. Since these transport systems transport different products, many works have focused on developing optimization strategies for scheduling these pipelines. That is, strategies that seek to optimize the use of the pipeline by establishing at what time points certain products must be transported. These strategies would be located at the planning level in the automation pyramid. In this work, on the other hand, different control strategies are proposed for a pipeline, but at the operation level. These strategies would be located at the control level, below the planning strategies in the automation pyramid. A pipeline of three pipe sections is modeled to develop the proposed control strategies, and the mathematical model is validated with actual data. The results show that, first, the proposed model approximates the actual behavior of the pipeline quite well and, second, that the combination of PID and feedforward control is an excellent alternative to implement control strategies for the operation of liquid transportation systems through pipelines. © Bharati Vidyapeeth's Institute of computer Applications and Management 2025.

关键词： control strategies liquid transportation modeling of system

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Understanding the battery safety improvement enabled by a quasi-solid-state battery design

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Chinese Physics B 2022年第11期31卷 36-41页

作者： Luyu Gan Rusong Chen Xiqian Yu Hong Li Beijing Advanced Innovation Center for Materials Genome Engineering Institute of PhysicsChinese Academy of SciencesBeijing 100190China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Beijing Frontier Research Center on Clean Energy Huairou DivisionInstitute of PhysicsChinese Academy of SciencesBeijing 101400China

The rapid development of lithium-ion batteries(LIBs)is faced with challenge of its safety bottleneck,calling for design and chemistry *** the proposed strategies,the development of solid-state batteries(SSBs)seems the most promising solution,but to date no practical SSB has been in large-scale *** safety performance of SSBs is also *** this article,a brief review on LIB safety issue is made and the safety short boards of LIBs are emphasized.A systematic safety design in quasi-SSB chemistry is proposed to conquer the intrinsic safety weak points of LIBs and the effects are accessed based on existing *** is believed that a systematic and targeted solution in SSB chemistry design can effectively improve the battery safety,promoting larger-scale application of LIBs.

关键词： battery safety thermodynamics kinetics solid-state batteries

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Self-Immolative Electrochemical Redox Substrates: Emerging Artificial Receptors in Sensing and Biosensing

ACS Measurement Science Au

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ACS Measurement science Au 2024年第2期4卷 163-183页

作者： Manibalan, Kesavan Arul, Ponnusamy Wu, Hsin-Jay Huang, Sheng-Tung Mani, Veerappan Department of Materials Science and Engineering National Yang Ming Chiao Tung University Hsinchu 30010 Taiwan Institute of Biochemical and Biomedical Engineering Department of Chemical Engineering and Biotechnology National Taipei University of Technology Taipei 10608 Taiwan Advanced Membranes and Porous Materials Center (AMPMC) Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia High-Value Biomaterials Research and Commercialization Center National Taipei University of Technology No. 1 Sec. 3 Zhongxiao E. Rd. Taipei 10608 Taiwan

The development of artificial receptors has great significance in measurement science and technology. The need for a robust version of natural receptors is getting increased attention because the cost of natural receptors is still high along with storage difficulties. Aptamers, imprinted polymers, and nanozymes are some of the matured artificial receptors in analytical chemistry. Recently, a new direction has been discovered by organic chemists, who can synthesize robust, activity-based, self-immolative organic molecules that have artificial receptor properties for the targeted analytes. Specifically designed trigger moieties implant selectivity and sensitivity. These latent electrochemical redox substrates are highly stable, mass-producible, inexpensive, and eco-friendly. Combining redox substrates with the merits of electrochemical techniques is a good opportunity to establish a new direction in artificial receptors. This Review provides an overview of electrochemical redox substrate design, anatomy, benefits, and biosensing potential. A proper understanding of molecular design can lead to the development of a library of novel self-immolative redox molecules that would have huge implications for measurement science and technology. © 2024 The Authors. Published by American Chemical Society.

关键词： alkaline phosphatase artificial receptors electrochemical mediators electrochemical sensors and biosensors galactosidase hydrogen peroxide neuraminidase organic electrochemistry ratiometric sensors self-immolative sensors

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