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3rd IEEE International Conference of Electron Devices Society Kolkata Chapter, EDKCON 2024

作者： Das, Indrajit Das, Debjit Bhattacharya, Abheepsa Debnath, Papiya Nath, Subhrapratim Chanda, Manash Meghnad Saha Institute of Technology Department of Information Technology Kolkata India Techno International New Town Department of Basic Science & Humanities Kolkata India Meghnad Saha Institute of Technology Department of Computer Science & Engineering Kolkata India Meghnad Saha Institute of Technology Department of Electronics & Communication Engineering Kolkata India

ISBN: (纸本)9798350374643

Physics-informed neural network integrates the physical properties of a structure through the border cost constraint within the loss property of the neural network. The methodology has demonstrated significant efficacy in estimating the relationship among the outcome of a PDE and its spatiotemporal variables. A unique PINN technique is presented by successively solving the PDE across multiple consecutive sections with only one neural network. The primary concept is to undergo rebuilding the identical neural network to address the PDE across consecutive duration intervals, during adhering to the previously acquired solutions across all prior time segment. The benefits of PINN are demonstrated by the resolution of the Allen-Cahn formulas. These formulas are extensively employed to characterise distinction of phases and reaction-diffusion processes. Novel approaches have been suggested to enhance the suggested PINN scheme. The strategy employs a transfer learning methodology that retains the characteristics acquired from prior training. This research demonstrates that this method considerably enhances the reliability and efficacy of the PINN scheme. © 2024 IEEE.

关键词： Reynolds equation

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Enhancing Healthcare Data Security in Cloud Computing Systems through Advanced Homomorphic Encryption Techniques Integrated with Cuckoo Search Optimization Algorithm

Enhancing Healthcare Data Security in Cloud Computing System...

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2024 IEEE International Conference on Recent Advances in Science and engineering technology, ICRASET 2024

作者： Sudha, I. Ramesh, P.S. Ponmalar, A. Jagannathan, J. Pandiarajan, Rajkumar Saveetha Institute of Medical and Technical Sciences Simats University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India R.M.K. Engineering College Tamilnadu Chennai India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Department of Software and Systems Engineering Katpadi Vellore India Kalasalingam Academy of Research and Education School of Computing Department of Information and Technology Krishnankoil Virudhunagar India

ISBN: (纸本)9798350388602

The studies in this research are focused on the mix of homomorphic encryption mechanisms and the Cuckoo Search Optimization Algorithm to promote the security of the healthcare data in the cloud computing system. I have observed that cloud solutions are now at the center of the contemporary health care systems, and security of patient's data remains a top priority. Earlier used encryption techniques, though secure if implemented, have problems in the way that data is to be processed first it has to be decrypted and then made ready for use - it is in this phase that data can be easily hacked into. Homomorphic encryption provides solution to this issue since it enables one to perform computations on encrypted data while maintaining its confidentiality. However, it takes a lot of computation which presents a lot of problems even in terms of simple performance. The Cuckoo Search Algorithm, a new nature-inspired metaheuristic, is incorporated into the encryption process to provide further optimization, whilst preserving the security benefits of the algorithm. The use of the proposed methodology takes place employing Python and its deployment at the cloud platform with elaborated dataset containing anonymized records extracted from electronic health records. The outcome proves that there are great enhancements in encryption and decryption time, computational complexity, and capacity, and thereby making the system appropriate for real-world healthcare solutions. This research offers a strong base for protection of healthcare data in cloud and is useful for the enhancement of adaptive, comprehensive and secure cloud computing systems. © 2024 IEEE.

关键词： Electronic health record

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A Systematic Review on Deepfake technology

A Systematic Review on Deepfake Technology

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International Conference on Data Analytics and Management, ICDAM 2022

作者： Khan, Ihtiram Raza Aisha, Saman Kumar, Deepak Mufti, Tabish Department of Computer Science and Engineering School of Engineering Sciences and Technology Jamia Hamdard New Delhi India Amity Institute of Information Technology Amity University Noida India

ISBN: (纸本)9789811976148

The twenty-first century has seen technology become an integral part of human survival. Living standards have been affected as the technology continues to advance. Deep fake is a deep learning-powered application that recently appeared on the market. It allows to make fake images and videos that people cannot discern from the real ones and is a recent technique that allows swapping two identities within a single video. A wide range of factors, including communities, organizations, security, religions, democratic processes as well as personal lives, are being impacted by deep fakes. In the case of images and videos being presented to an organization as evidence, if the images or videos are altered, the entire truth will be transformed into a lie. It is inevitable that with every new and beneficial technology, some of its adverse effects will follow, causing world problems. There have been several instances in which deep fakes have alarmed the entire network. During the last few years, the number of altered images and videos has grown exponentially, posing a threat to society. Additionally, this paper explores where deep fakes are used, the impacts made by them, as well as the challenges and difficulties associated with deep fakes in this rapidly developing society. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep learning

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Local-Global Temporal Difference Learning for Satellite Video Super-Resolution

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IEEE Transactions on Circuits and Systems for Video technology 2024年第4期34卷 2789-2802页

作者： Xiao, Yi Yuan, Qiangqiang Jiang, Kui Jin, Xianyu He, Jiang Zhang, Liangpei Lin, Chia-Wen The School of Geodesy and Geomatics Wuhan University Wuhan430000 China The School of Computer Science and Technology Harbin Institute of Technology Harbin150000 China The State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan430000 China The Department of Electrical Engineering the Institute of Communications Engineering National Tsing Hua University Hsinchu30013 Taiwan

Optical-flow-based and kernel-based approaches have been extensively explored for temporal compensation in satellite Video Super-Resolution (VSR). However, these techniques are less generalized in large-scale or complex scenarios, especially in satellite videos. In this paper, we propose to exploit the well-defined temporal difference for efficient and effective temporal compensation. To fully utilize the local and global temporal information within frames, we systematically modeled the short-term and long-term temporal discrepancies since we observe that these discrepancies offer distinct and mutually complementary properties. Specifically, we devise a Short-term Temporal Difference Module (S-TDM) to extract local motion representations from RGB difference maps between adjacent frames, which yields more clues for accurate texture representation. To explore the global dependency in the entire frame sequence, a Long-term Temporal Difference Module (L-TDM) is proposed, where the differences between forward and backward segments are incorporated and activated to guide the modulation of the temporal feature, leading to a holistic global compensation. Moreover, we further propose a Difference Compensation Unit (DCU) to enrich the interaction between the spatial distribution of the target frame and temporal compensated results, which helps maintain spatial consistency while refining the features to avoid misalignment. Rigorous objective and subjective evaluations conducted across five mainstream video satellites demonstrate that our method performs favorably against state-of-the-art approaches. Code will be available at https://***/ XY-boy/LGTD. © 2023 IEEE.

关键词： Three dimensional displays

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Grid Search Hyperparameters Tuning with Supervised Machine Learning for Awngi Language Named Entity Recognition 2

Grid Search Hyperparameters Tuning with Supervised Machine L...

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2nd International Conference Computational and Characterization Techniques in engineering and Sciences, IC3TES 2024

作者： Ayalew, Amogne Andualem Bitew, Gizachew Salau, Ayodeji Olalekan Tegegne, Melaku Lake Gupta, Shashi Kant Israr, Mohammad Tegegne, Tesfa Assegie, Tsehay Admassu Mizan-Tepi University School of Computing and Informatics Department of Information Technology Tepi Ethiopia Mizan Tepi University School of Computing Computer Science Department Mizan-Tepi Ethiopia Afe Babalola University Department of Electrical/Electronics and Computer Engineering Ado-Ekiti Nigeria Injibara University College of Engineering and Technology Department of Information Technology Injibara Ethiopia Eudoxia Research University Department of Computer Science and Engineering United States Maryam Abacha American University of Nigeria Hotoro Gra Kano State Nigeria Bahir Dar University Faculty of Computing Bahir Dar Institute of Technology Bahir Dara Ethiopia Injibara University College of Engineering and Technology Department of Computer Science Injibara Ethiopia

ISBN: (纸本)9798350364699

Named entity recognition has emerged as a critical step in recognizing, classifying, and extracting the most significant information from unstructured text without human intervention. It is used in information retrieval, conversation systems, machine translation, data mining, and information extraction. However, the Awngi language lacks a NER system due to inadequate datasets. This study combines feature extraction techniques with supervised machine learning algorithms, including support vector machines, Naïve Bayes, and conditional random fields with a grid search algorithm parameter optimization. These supervised machine-learning models often have various hyperparameters that must be tuned to optimize the model's performance by automatically selecting the parameter. Furthermore, the dataset used for training and testing consists of 20,193 annotated Awngi tokens, collected from Amhara Media Corporation, Awngi Telegram, and Facebook pages. The proposed SVM with grid search algorithm approach provided a promising result in ANER with an accuracy of 92% compared with Naïve Bayes, conditional random field, and decision-tree supervised machine learning models. Finally, the experiment results show that the proposed parameter tuning-based model can detect and categorize Awingi-named entities and outperforms the performance accuracy without parameter adjustment. © 2024 IEEE.

关键词： Support vector machines

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Building Highly Maintainable Software for Energy Automation Systems using Abstraction Layering 50

Building Highly Maintainable Software for Energy Automation ...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Liaqat, Arsalan Somerville, Max Kuo, Matthew M.Y. Spray, John Yang, Chen-Wei Sinha, Roopak Computer Science and Software Engineering Department Auckland University of Technology Auckland New Zealand Auckland New Zealand Lulea University of Technology Sweden School of Information Technology Deakin University Melbourne Australia

ISBN: (纸本)9781665464543

In smaller components of industrial or energy automation systems, such as device controllers of Protection and Control (PAC) systems in smart grids, controller functionality is tightly coupled with the physical device or sensor capabilities. At this level, software is small and therefore easy to maintain and test. However, when multiple controllers are interconnected and higher-level functionality is added, software applications grow exponentially, and ensuring maintainability becomes proportionally challenging. In this paper, we extend the IEC 61499 reference architecture used to develop industrial automation software with the principles of Abstraction Layered Architecture (ALA) that has shown up to 400% improvements in industrial software maintainability. We show that even a light application of abstraction layering on the top, application-level of IEC 61499 applications makes them significantly more readable and slightly more maintainable. More concrete gains in maintainability are expected when abstraction layering is integrated into lower layers. © 2024 IEEE.

关键词： Office automation

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Enhancing Blurred Image Processing with IoT Integration for Improved Clarity 2

Enhancing Blurred Image Processing with IoT Integration for ...

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2nd IEEE International Conference on Emerging Research in Computational Science, ICERCS 2024

作者： Tummalapalli, Geetamma Summia Parveen, H. Ramesh, S.M. Monica, P. Santhiya, B. Rajasekaran, Arun Sekar GMR Institute of Technology Department of Electronics and Communication Engineering Rajam India Sri Eshwar College of Engineering Department of Computer Science Engineering Coimbatore India KPR Institute of Engineering and Technology Department of Electronics and Communication Engineering Coimbatore India GITAM Deemed to be University Department of Electronics and Communication Engineering GST Visakhapatnam India Bannari Amman Institute of Technology Department of Information Technology Sathyamangalam India SR University Department of Electronics and Communication Engineering Warangal India

ISBN: (纸本)9798331534950

A blurred image is an image that has undergone a blurring or smoothing effect, resulting in a loss of sharpness and clarity. Blurring is a technique used in image processing to reduce noise, remove unwanted details, or create a visual effect. It involves averaging or blending neighboring pixels to create a smoother appearance. The specific processing techniques and algorithms used will depend on the nature and extent of the blur, the intended outcome, and the available software or programming tools. It's important to experiment with different methods and parameters to achieve the desired result. IoT (Internet of Things) can be used in image processing in several ways to enhance functionality, efficiency, and data processing capabilities enhances image processing by enabling real-time analysis, edge computing capabilities, integration with other IoT devices, and remote monitoring and control. These advancements facilitate applications such as object detection, image recognition, and real-time decision-making, contributing to more efficient and intelligent systems in various domains. Here is a proposed model for blurred image processing with IoT. This proposed model demonstrates the integration of IoT devices, image processing techniques, and cloud-based analytics to address the challenges of blurred image processing. It combines edge processing for real-time analysis and cloud-based processing for more complex algorithms, enabling efficient and intelligent image processing applications in various domains. © 2024 IEEE.

关键词： Edge computing

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Dynamic Insights: Well-being Activity Infused Fine-Tuning of Large Language Models

Dynamic Insights: Well-being Activity Infused Fine-Tuning of...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Mohammed, Hamza Haruna Kiss, Gabriel Serrano, J. Artur Lindseth, Frank Norwegian University of Science and Technology Faculty of Information Technology and Electrical Engineering Department of Computer Science Trondheim Norway Norwegian University of Science and Technology Faculty of Medicine and Health Sciences Department of Neuromedicine and Movement Science Trondheim Norway

ISBN: (纸本)9798350362480

The fast development of Large Language Models (LLMs) has made transformative applications in several fields attainable or possible. However, language models must often be more effective in specialized areas, especially health and prevention. This paper presents a novel method for fine-tuning LLMs using activity-related data to optimize them for the applicability of such models in health and wellbeing applications. We thus empirically evaluate this approach on the Cardiac Exercise Research corpus for fine-tuning the LLMs. The fine-tuning utilizes Quantized Low-Rank Adaptation (QLoRA) to ensure the models' size remains small while maintaining high performance and accuracy to keep the semantic understanding and relevance with health-related queries. Our results in answering domain-related prompts showed an improved user satisfaction and sentiment scores, providing strong confidence in the method's effectiveness. This study highlights the potential of domain-specific LLMs in advancing personalized healthcare. It instills a sense of optimism about the future of healthcare and the seamless integration of AI within health prevention and well-being domains. © 2024 IEEE.

关键词： Semantics

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Two-Mode Biomedical Sensor Build-up:Characterization of Optical Amplifier

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computers, Materials & Continua 2022年第3期70卷 5487-5501页

作者： Usman Masud Fathe Jeribi Mohammed Alhameed Faraz Akram Ali Tahir Mohammad Yousaf Naudhani Faculty of Electrical and Electronics Engineering University of Engineering and TechnologyTaxila47050Pakistan Department of Electrical Communication Engineering University of KasselKassel34127Germany College of Computer Science&Information Technology Jazan UniversityJazan45142Saudi Arabia Faculty of Engineering and Applied Sciences Riphah International UniversityIslamabad44000Pakistan Faculty of Information&Communication Technology Balochistan University of Information TechnologyEngineering and Management SciencesQuetta

Intracavity absorption spectroscopy is a strikingly sensitive technique that has been integrated with a two-wavelength setup to develop a sensor for human *** factors are considered in such a scenario,out of which Relative Intensity Noise(RIN)has been exploited as an important parameter to characterize and calibrate the said *** the performance of an electrical based assessment arrangement which has been developed in the laboratory as an alternative to the expensive Agilent setup,the optical amplifier plays a pivotal role in its development and operation,along with other components and their ***,the investigation and technical analysis of the amplifier in the system has been explored in *** algorithm developed for the automatic measurements of the system has been effectively deployed in terms of the laser’s *** this in perspective,a frequency dependent calibration has been pursued in depth with this scheme which enhances the sensor’s efficiency in terms of its *** this way,our investigation helps us in a better understanding and implementation perspective of the proposed system,as the outcomes of our analysis adds to the precision and accuracy of the entire system.

关键词： Biomedical sensor cavity optomechanics spectroscopy relative intensity noise semiconductor laser diode

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A Robust Web information Retrieval using PSO Approach Accelerated by Simulated Annealing 14

A Robust Web Information Retrieval using PSO Approach Accele...

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14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Ramya, C. Hamsha, K. Channagoudar, Savitha Department of Information Science and Engineering CMR Institute of Technology Karnataka Bengaluru India Department of Computer Science NMKRV College for Women Karnataka Bengaluru India Department of Information Science and Engineering Sri Taralabalu Jagadguru Institute of Technology Karnataka Ranebennur India

The process of information retrieval has evolved significantly with the usage of web. But unlike the traditional information retrieval set up, web information retrieval system succumbs to several problems. For resolving the issues and to provide an efficient and effective retrieval of web documents, a Modified Particle Swarm Optimization is proposed. This includes the Simulated Annealing technique which is the probabilistic approach that predicts the global optimization in the large search space along with the PSO. The documents similarity values are annealed and processed with the Simulated Annealing algorithm. The particles which are generated through this are then optimized with the PSO algorithm. The documents retrieved are measured for their correctness and accuracy based on several performance metrics that include precision and recall and response time as well. Experimental results clearly exhibit the superior performance of the proposed system over the existing system. © Grenze Scientific Society, 2023.

关键词： Simulated annealing

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