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IoT, Communication and Automation Technology (ICICAT), International Conference on

作者： Rohit Agarwal T. Saravanan Hassan Mohamed Ali B. Premalatha Samyuktha P P. S. Ramesh Department of Computer Engineering & Applications GLA University Mathura Department of ECE New Prince Shri Bhavani College of Engineering and Technology Chennai Tamil Nadu India Department Of Computers Techniques Engineering College Of Technical Engineering The Islamic University Najaf Iraq Department of ECE CMR College of Engineering & Technology Department of AIML GRIET India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai

ISBN: (数字)9798350368109

ISBN: (纸本)9798350368116

This paper proposes a new SA-SCA based routing protocol for UWSNs with the objective of costing the better routing paths. The presented protocol has been designed to consider the nature of UWSNs which include energy limitation, dynamic network structure and high end to end delay. Simulation outcomes revealed that the proposed SA-SCA protocol saves energy consumption up to 13% and extend the network lifetime up to 9% as well as the delivery ratio is up to 5% more than the conventional SA based protocols. The outcomes established show the ability of the protocol in improving the throughput and dependability of UWSNs.

关键词： Energy consumption Wireless sensor networks Underwater communication Network topology Heuristic algorithms Simulated annealing Throughput Routing protocols Topology Delays

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Per-RMAP: Feasibility-Seeking and Superiorization Methods for Floorplanning with I/O Assignment

Per-RMAP: Feasibility-Seeking and Superiorization Methods fo...

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Electronics Design Automation (ISEDA), International Symposium of

作者： Shan Yu Yair Censor Ming Jiang Guojie Luo Department of Information and Computational Sciences School of Mathematical Sciences Peking University Beijing China Department of Mathematics University of Haifa Haifa Israel National Key Laboratory for Multimedia Information Processing School of Computer Science Peking University Beijing China Center for Energy-efficient Computing and Applications Peking University Beijing China

The feasibility-seeking approach provides a systematic scheme to manage and solve complex constraints for continuous problems, and we explore it for the floorplanning problems with increasingly heterogeneous constraints. The classic legality constraints can be formulated as the union of convex sets. However, the convergence of conventional projection-based algorithms is not guaranteed when the constraints sets are non-convex, which is the case with unions of convex sets. In this work, we propose a resetting strategy to greatly eliminate the divergence issue of the projection-based algorithm for the feasibility-seeking formulation. Furthermore, the superiorization methodology (SM), which lies between feasibility-seeking and constrained optimization, is firstly applied to floorplanning. The SM uses perturbations to steer the iterates of a feasibility-seeking algorithm to a feasible solution with shorter total wirelength. The proposed algorithmic flow is extendable to tackle various constraints and variants of floorplanning problems, e.g., floorplanning with I/O assignment problems. We have evaluated the proposed algorithm on the MCNC benchmarks. We can obtain legal floorplans only two times slower than the branch-and-bound method in its current prototype using MATLAB, with only 3 % wirelength inferior to the optimal results. We evaluate the effectiveness of the algorithmic flow by considering the constraints of I/O assignment, and our algorithm achieves 8 % improvement on wirelength.

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Explainable AI and Machine Learning for Robust Cybersecurity in Smart Cities

Cyber Security and Applications

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Cyber Security and applications 2025年

作者： Shruti Gupta Jyotsna Singh Rashmi Agrawal Usha Batra School of Computer Applications Manav Rachna International Institute of Research and Studies Sector 43 Faridabad Haryana 121004 Department of Computer Science and Engineering Narsee Monjee Institute of Management Studies Sarangpur Chandigarh Department of Computer Science and Engineering Shri Vishwakarma Skill University Palwal Haryana 121102

An emerging application of such new technologies is in urban development, with cities increasingly utilizing them to address social, environmental, and urban issues. IoT has paved the way for Smart Cities, while AI-fueled big data has revolutionized progressive urbanization. However, initiatives to promote technology must be balanced by principles of sustainability and livability. As deep learning has advanced rapidly, creating increasingly sophisticated technologies has led to highly complex — and often opaque — models that can be difficult to interpret. It becomes increasingly difficult to establish trust and maintain transparency when decision-making systems are based on such opaque and complex structures. This article explores the urban promise of AI and presents a new framework infusion of AI into cityscapes. The new direction is socially oriented through the inclusion of elements such as values, urban metabolism, and governance. A systematic review of machine-learning applications in cybersecurity also discusses the importance of explainability for overcoming the challenges it entails. The importance of assuring the explainability, interpretability, and intelligibility of autonomous systems will also be part of this discussion, especially in the context of developing smart cities using AI-based technologies.

关键词： Smart cities big data Internet of things Explainable AI Machine learning IoT Internet of Things AI Artificial Intelligence IDC International Data Corporation XAI You are an Explainable Artificial Intelligence ML Machine Learning LRP Long Range Planning DTD Document Type Definition PDA Personal Digital Assistant TCAV Time Controlled Adaptive Ventilation XGNN Graph Neural Networks DNN Deep Neural Network SHAP Shapley Additive exPlanations ASV Approved Scanning Vendor IoB Internet of Behaviours SVN Support Vector Machine CNN Convolutional Neural Network DL Deep Learning DBN Deep Belief Network SMS Short Message Service NB Naïve Bayes MLP Multi-Layer Perceptron HTTP Hypertext Transfer Protocol HTTPs Hypertext Transfer Protocol Secure

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Exploring the Intersection of Technology and Education: Artificial Intelligence in Language Learning and Communication

Exploring the Intersection of Technology and Education: Arti...

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Intelligent Systems and Advanced applications (ICISAA), International Conference on

作者： Rahul Pradhan Shamim Ahmad Khan Anslin Jegu P. Kavitha Revati Ramrao Rautrao M Ponni Valavan Department of Computer Engineering and Applications GLA University Mathura India Glocal School of Science & Technology Glocal University U.P India Department of English Panimalar Engineering College Chennai India Department of English Nandha Engineering College(Autonomous) Erode India Sinhgad Institute of Business Administration and Research Pune India Department of AI & DS K. Ramakrishnan College of Engineering Trichy Tamil Nadu India

ISBN: (数字)9798331539948

ISBN: (纸本)9798331539955

The exploration delves into the intersection of technology and education, specifically focusing on the integration of BERT (Bidirectional Encoder Representations from Transformers) in language learning and communication. BERT, an advanced natural language processing model developed by Google, has emerged as a transformative tool in the field of education, promising to revolutionize traditional approaches and open new horizons for learners worldwide. By leveraging BERT’s sophisticated language understanding capabilities, language learning applications can provide personalized, efficient, and immersive learning experiences across various domains, including vocabulary acquisition, grammar correction, reading comprehension, and writing assistance. This abstract examines the potential impact of BERT-based tools on language learning outcomes, exploring their effectiveness in enhancing language proficiency and communication skills. Through a mixed-methods approach encompassing both quantitative and qualitative analyses, this study investigates the efficacy of BERT in improving language learning experiences and gathers feedback from learners and educators on its usability and effectiveness. By understanding the implications of integrating BERT into language learning and communication, this exploration aims to shed light on the transformative potential of artificial intelligence in shaping the future of education.

关键词： Vocabulary Education Bidirectional control Learning (artificial intelligence) Transformers Encoding Natural language processing Internet Usability Intelligent systems

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Developing Robust Cybersecurity Policies and Governance Frameworks in Response to Evolving Legal and Regulatory Landscapes

Developing Robust Cybersecurity Policies and Governance Fram...

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Emerging Trends in Industry 4.0 (ETI 4.0)

作者： Radhika Pandey Shaik Anjimoon V Asha Atul Singla Irfan Khan Zain Alabdeen Hasan Abed DoCSE GyanGanga Institute of Technology and Science Jabalpur M.P India Institute of Aeronautical Engineering Dundigal Hyderabad Department of Computer Applications New Horizon College of Engineering Bangalore Lovely Professional University Phagwara Knowledge Park II Lloyd Institute of Engineering & Technology Greater Noida Uttar Pradesh College of Health and Medical Technology National University of Science and Technology Dhi Qar Iraq

ISBN: (数字)9798350373783

ISBN: (纸本)9798350373790

This research introduces a comprehensive cybersecurity framework consisting of five interlinked algorithms: Threat Intelligence Integration, Risk Assessment and Management, Compliance Mapping, Incident Response Planning, and Employee Training and Awareness. Through comparative performance evaluation and ablation study, the framework demonstrates consistent superiority across key parameters. Visual representations, including bar charts, line charts, and pie charts, provide intuitive insights into effectiveness, adaptability, compliance, and overall performance. The ablation study underscores the synergistic importance of each algorithm, emphasizing the framework’s holistic nature. This research contributes to advancing cybersecurity methodologies, offering a dynamic and adaptive approach to safeguarding against evolving cyber threats.

关键词： Training Performance evaluation Visualization Technological innovation Law Heuristic algorithms Planning

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AI-Based Virtual Screening for Identifying Novel Drug Candidates

AI-Based Virtual Screening for Identifying Novel Drug Candid...

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Recent Trends in computer science and Technology (ICRTCST), International Conference on

作者： S. RadhaMahendran Sheetal Vishal Deshmukh T. Thiyagasundaram K. Sivakumar S. B G Tilak Babu Surya Pratap Singh Department of Bioinformatics School of Life Sciences Vels Institute of Science Technology and Advanced Studies Pallavaram Chennai India Department of Computer Applications Bharati Vidyapeeth Yashwantrao Mohite Institute of Management Karad Maharashtra Department of NoiNaadal Sri Sairam Siddha Medical College Chennai Department of Mathematics Simats School of Engineering Saveetha University Thandalam Chennai Tamilnadu Department of ECE Aditya Engineering College Surampalem Department of Multi-Disciplinary Research Unit UPUMS Etawah UP

ISBN: (数字)9798350351378

ISBN: (纸本)9798350351385

VR screening uses computers to find large databases of chemical compounds and predict their potential as medications based on factors such as binding affinity, pharmacokinetics, and toxicity. This accelerates the process of discovering novel medications by concentrating on compounds with a higher likelihood of efficacy. This results in decreased expenses and increased effectiveness over an extended period. The study demonstrates the utilization of many artificial intelligence techniques in virtual screening, including deep learning networks, machine learning models, and other sophisticated computer technologies. The analysis examines the training of AI models on diverse datasets, incorporating data from existing databases, research publications, and experimental studies. This demonstrates the potential of AI in discovering novel chemicals for the treatment of cancer, infectious diseases, neurological disorders, and uncommon ailments. There are limitations associated with utilizing Molecular structure-based CADD methods. This research reviews current tools, applications, and methods for medication production speed and cost reduction. Structure-Based Virtual Screening (SBVS) is essential to medication development, according to research.

关键词： computers Training Neurological diseases Toxicology Databases Reviews Computational modeling

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Hydroponics Cultivation Using Real Time Iot Measurement System

Hydroponics Cultivation Using Real Time Iot Measurement Syst...

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2020 International Conference On Computational Physics in Emerging Technologies, ICCPET 2020

作者： Mishra, Piyush Jimmy, Laishram Ogunmola, Gabriel A. Phu, Tran Vang Jayanthiladevi, A. Latchoumi, T.P. Department of Computer Engineering and Applications Gla University Uttar Pradesh Mathura India Department of Computer Science and Engineering Manipur Technical University Govt. Polytechnic Campus Imphal Manipur India Faculty of Business Sharda University Uzbekistan School of Law Can Tho University Viet Nam Computer Science and Information Science Srinivas University Karnataka India Department of Computer Science and Engineering Vignan's University Vadlamudi Andhra Pradesh Guntur India

The concept hydroponic cultivation is performed in greenhouses or in various plat factories. This sort of cultivation is generally evaluated with pH and electrical conductivity. It may not provide complete information regarding any imbalance that is encountered in cultivation process. This causes poor yield or wastage of resources Thus, to overcome these limitation IoT measurement system has to be implanted in this cultivation process, where sensors and actuators may measure the corresponding reading when need and given to man power. Therefore, imbalance in attaining nutrients is eliminated by constant monitoring of resources towards plant cultivation. This facilitates farmers to handle the nutrients issues that are encountered in cultivation. The performance measurement of the system developed was computed with feasibility of IoT system for automatic measurements. The outcomes of the systems are computed and validated for further processing. Some specific measures are considered where there is no specific relationship among standardized analysis. The sensitive responses have to be examined and analyzed. © Published under licence by IOP Publishing Ltd.

关键词： Nutrients

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Hausa Visual Genome: A Dataset for Multi-Modal English to Hausa Machine Translation

arXiv

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arXiv 2022年

作者： Abdulmumin, Idris Dash, Satya Ranjan Dawud, Musa Abdullahi Parida, Shantipriya Muhammad, Shamsuddeen Hassan Ahmad, Ibrahim Said Panda, Subhadarshi Bojar, Ondřej Galadanci, Bashir Shehu Bello, Bello Shehu Department of Computer Science Ahmadu Bello University Zaria Nigeria School of Computer Applications KIIT University Bhubaneswar India Silo AI Helsinki Finland LIAAD - INESC TEC Faculty of Sciences University of Porto Portugal Faculty of Computer Science and Information Technology Bayero University Kano Nigeria Graduate Center City University of New York United States Charles University Faculty of Mathematics and Physics ÚFAL Prague Czech Republic

Multi-modal Machine Translation (MMT) enables the use of visual information to enhance the quality of translations. The visual information can serve as a valuable piece of context information to decrease the ambiguity of input sentences. Despite the increasing popularity of such a technique, good and sizeable datasets are scarce, limiting the full extent of their potential. Hausa, a Chadic language, is a member of the Afro-Asiatic language family. It is estimated that about 100 to 150 million people speak the language, with more than 80 million indigenous speakers. This is more than any of the other Chadic languages. Despite a large number of speakers, the Hausa language is considered low-resource in natural language processing (NLP). This is due to the absence of sufficient resources to implement most NLP tasks. While some datasets exist, they are either scarce, machine-generated, or in the religious domain. Therefore, there is a need to create training and evaluation data for implementing machine learning tasks and bridging the research gap in the language. This work presents the Hausa Visual Genome (HaVG), a dataset that contains the description of an image or a section within the image in Hausa and its equivalent in English. To prepare the dataset, we started by translating the English description of the images in the Hindi Visual Genome (HVG) into Hausa automatically. Afterward, the synthetic Hausa data was carefully post-edited considering the respective images. The dataset comprises 32,923 images and their descriptions that are divided into training, development, test, and challenge test set. The Hausa Visual Genome is the first dataset of its kind and can be used for Hausa-English machine translation, multi-modal research, and image description, among various other natural language processing and generation tasks. © 2022, CC BY.

关键词： Genes

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AVTENet: A Human-Cognition-Inspired Audio-Visual Transformer-Based Ensemble Network for Video Deepfake Detection

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IEEE Transactions on Cognitive and Developmental Systems 2025年

作者： Hashmi, Ammarah Shahzad, Sahibzada Adil Lin, Chia-Wen Tsao, Yu Wang, Hsin-Min Taiwan International Graduate Program Academia Sinica Social Networks and Human-Centered Computing Program Taipei11529 Taiwan National Tsing Hua University Institute of Information Systems and Applications Hsinchu30013 Taiwan National Chengchi University Department of Computer Science Taipei11605 Taiwan National Tsing Hua University Department of Electrical Engineering Institute of Communications Engineering Hsinchu300044 Taiwan Academia Sinica Research Center for Information Technology Innovation Taipei11529 Taiwan

The recent proliferation of hyper-realistic deepfake videos has drawn attention to the threat of audio and visual forgeries. Most previous studies on detecting artificial intelligence-generated fake videos only utilize visual modality or audio modality. While some methods exploit audio and visual modalities to detect forged videos, they have not been comprehensively evaluated on multimodal datasets of deepfake videos involving acoustic and visual manipulations, and are mostly based on convolutional neural networks with low detection accuracy. Considering that human cognition instinctively integrates multisensory information including audio and visual cues to perceive and interpret content and the success of transformer in various fields, this study introduces the audio-visual transformer-based ensemble network (AVTENet). This innovative framework tackles the complexities of deepfake technology by integrating both acoustic and visual manipulations to enhance the accuracy of video forgery detection. Specifically, the proposed model integrates several purely transformer-based variants that capture video, audio, and audio-visual salient cues to reach a consensus in prediction. For evaluation, we use the recently released benchmark multimodal audio-video FakeAVCeleb dataset. For a detailed analysis, we evaluate AVTENet, its variants, and several existing methods on multiple test sets of the FakeAVCeleb dataset. Experimental results show that the proposed model outperforms all existing methods and achieves state-of-the-art performance on Testset-I and Testset-II of the FakeAVCeleb dataset. We also compare AVTENet against humans in detecting video forgery. The results show that AVTENet significantly outperforms humans. © 2016 IEEE.

关键词： audio-visual AVTENet Deepfake detection

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Augmented Reality Shopping and IoT-Enabled Virtual Try-On with Cloud Services for Interactive Product Displays

Augmented Reality Shopping and IoT-Enabled Virtual Try-On wi...

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International Conference on Communications and Signal Processing

作者： V. Sridevi H. Azath R. Vijayakumar N. Anbuselvan V. Amirthalingam S Arunkumar Electrical and Electronics Engineering Academy of Maritime Education and Training Deemed to be University Chennai Tamil Nadu India School of Computing Science and Engineering VIT Bhopal University Bhopal India Department of Electronics and Communication Engineering Mahendra Engineering College (Autonomous) Namakkal Tamil Nadu India Department of Electrical and Electronics Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamil Nadu India Department of Computer Science and Engineering Vinayaka Missions Kirupananda Variyar Engineering College Vinayaka Missions Research Foundation (Deemed to be University) Salem Tamil Nadu India Department of Computer Applications Adhiparasakthi Engineering College Melmaruvathur Tamil Nadu India

ISBN: (数字)9798350353068

ISBN: (纸本)9798350353075

The research focuses on how augmented reality (AR) and the Internet of Things (IoT) might work together to create a novel retail environment. This integrated system revolutionizes how customers engage with products by fusing the digital and real worlds. Smartphones and other devices with AR capabilities allow customers to virtually try on products before purchasing. Smart mirrors and sensor-enabled shelving are just two examples of the IoT-powered interactive displays available today. These fusions of AR and the IoT improve the retail experience and facilitate choice. Capturing data from the physical environment, sensors allow for customized experiences. The extensive product data stored by cloud services paves the way for rapid data processing. However, there are obstacles, such as ensuring data privacy and security and coordinating AR-IoT smoothly. Finding a happy medium between technological complexity and ease of use is essential for a satisfying buying experience. The combination of AR and the IoT broadens the retail experience and has the potential to revolutionize the way people purchase.

关键词： Cloud computing Technological innovation Wireless networks Signal processing User experience Complexity theory Internet of Things

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