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2nd International Conference on Multidisciplinary engineering and Applied science, ICMEAS 2023

作者： Ifijeh, Ayodele H. Adetiba, Emmanuel Adewale, Adeyinka Thakur, Surrendra Moyo, Sibusiso Emmanuel, Dare O. Ukpong, Udeme C. Dept. of Electrical and Information Engineering Nigeria HRA Institute for Systems Science Durban University of Technology Durban South Africa Covenant University Dept. of Electrical and Information Engineering Ota Canaanland Nigeria Durban University of Technology KZN E-skills CoLab Durban4001 South Africa School for Data Science and Computational Thinking Stellenbosch University Department of Mathematical Sciences Stellenbosch7602 South Africa

ISBN: (纸本)9798350358834

Advancement in wireless transmission has enabled the communication among multiple devices all over the world, as well as expanding the frontiers of wireless Internet access. As a result of these advancement, numerous devices are questing for wireless connectivity thereby congesting the existing spectrum. If new measures are not taken to reduce depletion of the reserved radio resource, new allocations of wireless Internet access will be impossible, thereby risking the development of the entire wireless ecosystem. The demands for resourceful spectrum consumption have continually driven researchers and stakeholders in the wireless industry to search for spare radio spectrum to offer affordable and reliable wireless connectivity. The TV broadcasting is not fully utilizing the spectrum in some geographical zone. These TV unused spaces called TV White Spaces (TVWS), are well-thought-out to be the probable future resolutions for unavailability of spectrum. The low frequency band (470 to 694 MHz) of the unutilized TV channel has exceptional broadcast features over extensive distances and enables transmissions through high-rise buildings, trees, and mountains. These features allow the applications of TVWS in Internet of Things (IoT), wireless sensor network, wireless connectivity, wireless switching, smart grid and cities, automated transportation, and logistics as well as connectivity in cloud infrastructure. This paper presents a study on the advantages and benefits of television white space as an alternative to wireless broadband connectivity. © 2023 IEEE.

关键词： Tall buildings

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Retraction Note: Exploring subcellular location anomalies: a novel quantum bioimaging paradigm

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Optical and Quantum Electronics 2024年第11期56卷 1-2页

作者： Kumar, Kailash Abbas, Syed Hauider Gupta, Manish Waris, Saiyed Faiayaz Bordoloi, Dibyahash Kirubakaran, M. K. College of Computing and Informatics Saudi Electronic University Riyadh Kingdom of Saudi Arabia Department of Computer Science and Engineering Integral University Lucknow India Department of Electronics and Communication Engineering GLA University Mathura India Department of Computer Science and Engineering Vignan’s Foundation for Science Technology and Research Vadlamudi Guntur India Department of Computer Science and Engineering Graphic Era Hill University Dehradun India Department of Artificial Intelligence and Data Science St. Joseph’s Institute of Technology Chennai India

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The Nah Bandit: Modeling User Non-compliance in Recommendation systems

arXiv

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arXiv 2024年

作者： Zhou, Tianyue Cho, Jung-Hoon Wu, Cathy The School of Information Science and Technology ShanghaiTech University Shanghai China The Department of Civil and Environmental Engineering The Laboratory for Information & Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States The Laboratory for Information & Decision Systems The Institute for Data Systems and Society The Department of Civil and Environmental Engineering Massachusetts Institute of Technology CambridgeMA02139 United States

Recommendation systems now pervade the digital world, ranging from advertising to entertainment. However, it remains challenging to implement effective recommendation systems in the physical world, such as in mobility or health. This work focuses on a key challenge: in the physical world, it is often easy for the user to opt out of taking any recommendation if they are not to her liking, and to fall back to her baseline behavior. It is thus crucial in cyber-physical recommendation systems to operate with an interaction model that is aware of such user behavior, lest the user abandon the recommendations altogether. This paper thus introduces the Nah Bandit, a tongue-in-cheek reference to describe a Bandit problem where users can say ‘nah’ to the recommendation and opt for their preferred option instead. As such, this problem lies in between a typical bandit setup and supervised learning. We model the user non-compliance by parameterizing an anchoring effect of recommendations on users. We then propose the Expert with Clustering (EWC) algorithm, a hierarchical approach that incorporates feedback from both recommended and non-recommended options to accelerate user preference learning. In a recommendation scenario with N users, T rounds per user, and K clusters, EWC achieves a regret bound of O(N √T log K + NT), achieving superior theoretical performance in the short term compared to LinUCB algorithm. Experimental results also highlight that EWC outperforms both supervised learning and traditional contextual bandit approaches. This advancement reveals that effective use of non-compliance feedback can accelerate preference learning and improve recommendation accuracy. This work lays the foundation for future research in Nah Bandit, providing a robust framework for more effective recommendation systems. Copyright © 2024, The Authors. All rights reserved.

关键词： Supervised learning

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Execution of Convolution Coding Method for FPGA in Industrial Automation using VERILOG HDL

Execution of Convolution Coding Method for FPGA in Industria...

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International Conference on Computing Methodologies and Communication (ICCMC)

作者： Kanagaraj Venusamy S. Kannadhasan A. Vimalesh P Chandramohan M. Shanmugam K. Priyadarsini Department of Mechatronics Engineering Rajalakshmi Engineering College Chennai India Department of Electronics and Communication Engineering Study World College of Engineering Coimbatore Chennai India Department of Data Science and Business Systems School of Computing SRM Institute of Science & Technology Chennai India

In this paper, the performance study of the FPGA-based encoder is delivered and received with little errors given the large number of applications that employ digital communication to store and retrieve data recently. Forward Error Correction units a wireless communication system region that is essential. Several types of encryption methods have been measured, and the error is completely different Convolution code writing approach, an honest technique used to rectify mistakes during the data transfer. Convolutional encoder area unit compelled to provide the output in the kind of register style with specified positions in the register. The areas in which the region is entirely arranged are likewise shown as arrows. The position of the registers provides probable state transitions wherein example, L is the register's length. Using these facts, the best way to execute of data transmission in digital communication channels is to correct errors in codes. FPGA device utilized in convolutional encoder's hardware implementation. Vivado and XILINX ISE are used for performance analysis.

关键词： Convolutional codes Convolution Forward error correction Writing Digital communication Encoding Registers

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A Survey on Usage of Multimedia databases for Emotion Elicitation: A Quantitative Report on How Content Diversity Can Improve Performance

A Survey on Usage of Multimedia Databases for Emotion Elicit...

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Proceedings of the International Convention MIPRO

作者： M. Horvat P. Jerčić Department of Applied Computing Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia Graz University of Technology Institute of Interactive Systems and Data Science Graz Austria

Affective picture databases provide a standardized set of images to elicit controlled and consistent emotional responses in research participants. They are a valuable tool for studying various emotion-related phenomena across several research domains. These domains include emotion perception, emotion regulation, and the neural basis of emotion. However, affective picture databases have diverse schemas, structures, and content, making them difficult to use. Searching and retrieving optimal pictures relevant to affective stimulation may be challenging and time-consuming. In this context, we surveyed domain experts about their practices and experiences working with affective multimedia databases such as IAPS, NAPS, OASIS, GAPED, and others. The survey identified a need for novel data observatory software. This finding motivates the authors’ intention to develop and validate such software platform that relies on AI. Such a platform would describe better, retrieve, and integrate various semi-structured affective multimedia datasets. The results prominently indicate the overwhelming dissatisfaction regarding stimuli content diversity and cultural bias, specifically regarding emotional and semantic context. The main driver of satisfaction from users of existing automated retrieval software is the quality of semantic descriptors available. This points to the direction AI should take in novel data observatory software. This survey follows up on a similar survey conducted ten years ago and explores the differences in researchers’ opinions and experiences during that time. The complete aggregated results are publicly available at https://***/mhorvat/stimdbsurvey.

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Reduced clinical severity during 2022 Shanghai Spring epidemic of SARS-CoV-2 omicron BA.2 variant infection——an integrated account of virus pathogenicity and vaccination effectiveness

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National science Review 2024年第4期11卷 24-27页

作者： Xingyue Wu Yao Chen Kangli Cao Yao Shen Xueling Wu Yilin Yang Zhongshu Kuang Qingrun Li Zhenzhen Lu Yichen Jia Mian Shao Guorong Gu Xiangwei Wang Ye Yao Ying Wang Shaodie Chen Zhigao Yu Wei Wei Longfei Ding Lulu Lan Tianwen Gu Xiangyu Long Jian Sun Lingyu Xing Jiayuan Shen Yi Han Yue Luo Sucheng Mu Mengna Lin Xiaoyan Zhang Rong Zeng Jianqing Xu Guoping Zhao Lihong Huang Zhenju Song Department of Emergency Medicine Clinical Center for Bio-Therapy Department of Biostatistics and Department of UrologyShanghai Key Laboratory of Lung Inflammation and Injury Zhongshan Hospital Fudan University Department of Respiratory and Critical Care Medicine Shanghai Pudong Hospital Fudan University Department of Pulmonology Renji Hospital Shanghai Jiao Tong University School of Medicine Key Laboratory of Systems Biology Center for Excellence in Molecular Cell Science Shanghai Institute of Biochemistry and Cell Biology Chinese Academy of Sciences Shanghai Public Health Clinical Center Fudan University Department of Biostatistics School of Public Health Key Laboratory of Public Health Safety of Ministry of Education and Shanghai Institute of Infectious Disease and Biosecurity School of Public Health Fudan University Shanghai Institute of Immunology Department of Immunology and Microbiology Shanghai Institute of Virology Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of EducationSchool of Medicine Shanghai Jiao Tong University State Key Laboratory of Genetic Engineering Fudan Microbiome CenterSchool of Life Sciences Fudan University Bio-Med Big Data Center Shanghai Institute of Nutrition and Health Chinese Academy of Sciences

The emergence of SARS-Co V-2 variant of concern omicron BA.2 led to high infection incidence rates as well as reduced severity of COVID-19 during the Shanghai Spring epidemic of 2022 [1]. We assessed the role of viral pathogenicity and the effectiveness of inactivated vaccines in a retrospective observational study including 10 258 confirmed COVID-19cases identified between April and June of 2022, from four COVID-19 designated hospitals located in two areas of Shanghai, namely the West Bund and the East Bund, where the populations’ demographic characteristics varied significantly (Table S1, Fig. S1).

关键词： sars-cov-2 effectiveness epidemic shanghai integrated spring clinical variant virus account

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An Advanced Intrusion Detection Solution for Networks based on Honeypot Servers

An Advanced Intrusion Detection Solution for Networks based ...

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International Conference on Inventive Computation Technologies (ICICT)

作者： K. Veena K. Meena Mercy Theresa M Hemalatha C D. Rajalakshmi Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India Department of Computer Science and Engineering GITAM School of Technology GITAM- Bangalore India Department of Data Science and Business Systems School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai India Computer Science and Engineering Sri Sairam Institute of Technology Chennai

Network security is a critical issue in modern technology. Honey pot-based intrusion detection methods provide an additional layer of security and enhance network performance by analyzing hacker behaviour and detecting unauthorized clients. IP validation and vulnerability detection are used to ensure authorized customer access and prevent illegal client activity. A voice recognition system detects malicious attacks in stage two. If authorized, packets are passed to the server, otherwise, they are delivered to honeypot servers. Using Naive Bayes algorithm, the detection rate is 85.06% with an accuracy of 98.18% and a false alarm rate of 0.15 seconds.

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Oil Spill Detection Using 2D Convolution Neural Network and Generative Adversarial Network

Oil Spill Detection Using 2D Convolution Neural Network and ...

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Expert Clouds and Applications (ICOECA), International Conference on

作者： R. Madhura S. Nikkath Bushra A. Syed Ismail Haleema PK Department of Computing Technologies SRM Institute of Science and Technology Kattankulathur Chennai Tamil Nadu India Department of Data Science and Business Systems SRM Institute of Science and Technology Kattankulathur Chennai Tamil Nadu India School of Computing and Engineering University of West London RAK Branch Campus UAE

ISBN: (数字)9798350385793

ISBN: (纸本)9798350385809

Finding oil spills in the ocean is one of the most crucial tasks in preserving our ecosystem. Using satellite or aerial photographs as input to a deep learning model that makes use of 2D CNN (Convolution Neural Network) and GAN (Generative Adversarial Network). Deep learning assists in automatically detecting oil spills in the ocean. A strong model that may be applied to volumetric data is 2D CNN. To protect the environment and its biodiversity, it is critical to identify and minimize oil spills in delicate maritime environments. Conventional techniques for tracking oil spills in satellite imagery sometimes depend on labor-intensive, human error-prone manual inspection. When deep learning models are taught with a lot of data, they perform well. The Gathering of datasets, however the situation proved to be challenging. As a result, employing Generative Adversarial Networks (GAN) to produce new photos by utilizing preexisting ones. As a result, by giving the model a suitable number of photos to use for training and testing, it improves accuracy.

关键词： Deep learning Training Convolution Oils Biological system modeling Oceans Neural networks

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An overview of ML-based applications for next generation optical networks

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science China(Information sciences) 2020年第6期63卷 31-46页

作者： Ruoxuan GAO Lei LIU Xiaomin LIU Huazhi LUN Lilin YI Weisheng HU Qunbi ZHUGE Shanghai Institute for Advanced Communication and Data Science State Key Laboratory of Advanced Optical Communication Systems and NetworksDepartment of Electronic Engineering Shanghai Jiao Tong University

Over the past few decades, the demand for the capacity and reliability of optical networks has continued to grow. In the meantime, optical networks with larger knowledge scales have become sources of numerous heterogeneous data. In order to handle these new challenges, many issues need to be resolved,among which the low-margin optical networks design, power optimization, routing and wavelength assignment(RWA), failure management are quite important. However, the use of traditional algorithms in the above four applications shows some shortcomings. Fortunately, artificial intelligence(AI), especially machine learning(ML), is regarded as one of the most promising methods to overcome these shortcomings. In this study, we review the applications of ML methods in solving these four issues. Although many ML-based researches have emerged, the applications of ML techniques in optical networks still face challenges. Therefore, we also discuss some possible future directions of investigating ML-based approaches in optical networks.

关键词： optical networks artificial intelligence machine learning system margin power optimization routing and wavelength assignment failure management

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Shielding NLP systems: An In-depth Survey on Advanced AI Techniques for Adversarial Attack Detection in Cyber Security

Shielding NLP Systems: An In-depth Survey on Advanced AI Tec...

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Automation, Computing and Renewable systems (ICACRS), International Conference on

作者： T. Sai Lalith Prasad K. B. Manikandan J. Vinoj Research Scholar Department of Computer Science and Engineering Vignan's Foundation for Science and Technology & Research (Deemed to be University) Guntur Andhra Pradesh India Assistant Professor Department of Artificial Intelligence and Data Science Vignan Institute of Technology and Science Telangana India Assistant Professor Department of CSE Vignan's Foundation for Science Technology and Research (Deemed to be University) Guntur Andhra Pradesh India

ISBN: (数字)9798331532420

ISBN: (纸本)9798331532437

This research investigates the challenges posed by adversarial perturbations to the robustness and reliability of Natural Language Processing (NLP) models. The study focuses on three key paradigms for enhancing the resilience of NLP systems: meta-learning, reinforcement learning, and self-supervised learning. A comprehensive evaluation of these strategies is conducted, analyzing their strengths and weaknesses in mitigating adversarial attacks. The study provides insights into the most promising approaches for enhancing the robustness of NLP models and offers directions for future research in this critical area. By advancing the resilience of NLP systems, this research contributes to the development of more robust and trustworthy AI applications across various domains, including healthcare, finance, and security.

关键词： Training Surveys Renewable energy sources Scalability Self-supervised learning Natural language processing Robustness Security Artificial intelligence Resilience

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