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2023 IEEE International Conference on research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering, rMKMATE 2023

作者： Poongavanam, Elumalaivasan Munirathinam, T. Murugesan, Sankar Kayalvizhi, V. Department of Data Science and Business System SRM Institute of Science and Technology Tamil Nadu Chennai India Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai India

ISBN: (纸本)9798350305708

Cloud computing is extremely popular model among enterprises. It provides more availability of cloud resources when needed with high scalability and extremely cost-effective model. Security is one of the least understood concepts to provide and access for OWASP applications in cloud computing. Many enterprises especially banking clients are risk-averse and have less cloud adoption rate. In this study, security research in the area of cloud security is reviewed and AWS (Amazon Web Service) is the top provider of cloud computing. Since, we have also demonstrated how it works in the security exploration. This paper's major goal is to make cloud computing security is a key activity and prevent unauthorized access to the apps used in the real world. © 2023 IEEE.

关键词： cloud computing AWS On demand services security

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Alzheimer disease detection System using AlexNet a novel Eight Layered Convolutional Neural Network

Alzheimer Disease Detection System using AlexNet a novel Eig...

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2023 IEEE Global Conference on Information Technologies and Communications, GCITC 2023

作者： Jenifel, M. Geetha Shyamala devi, M. Umanandhini, d. Srm Institute of Science and Technology Data Science and Business Systems School of Computing Tamil Nadu Chengalpattu603203 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Computer Science & Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350308167

Alzheimer's disease (Ad), an incurable brain ailment that is irreversible, affects thinking and memory while also shrinking the size of the mind as a whole. Alzheimer's is a neurological illness that causes severe memory loss and makes it difficult to carry out regular chores. The development of more effective treatments for Ad depends on an early diagnosis of the condition. Finding Alzheimer's disease is a difficult and time-consuming task that requires a brain imaging report and competent people. This time-consuming and frequently inaccurate method of diagnosing Alzheimer's is traditional. There has been discussion of a different strategy that is quick, inexpensive, and more dependable. Better medical care and solutions can be provided with the use of artificial intelligence technologies. due to distractions, technological flaws, cognitive biases, and weariness, human diagnosis performance suffers. However, AI-based diagnosis tools support physicians' safe detection and decision-making and are less prone to error. This study offers a clever and trustworthy method for identifying Alzheimer's disease and its potential early stage, moderate mental impairment. The given system accurately diagnoses Alzheimer's disease and its early stages from structural MrI images and is based on deep learning. The ability to predict whether patients with moderate cognitive impairment (MCI) may develop Alzheimer's disease is essential in clinical practice and has the potential to significantly improve clinical studies. To classify Alzheimer's disease and its prodromal stages, this initiative suggests combining MrI data with the Mini-Mental State Examination (MMSE), a neuropsychological test. © 2023 IEEE.

关键词： AlexNet Alzheimer disease Convolutional Neural Network Mild Cognitive Impairment Mini-Mental State Examination

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Total losses and dispersion effects management and upgrading fiber reach in ultra-high optical transmission system based on hybrid amplification system

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Journal of Optical Communications 2025年第2期46卷 289-298页

作者： ramkumar, Govindaraj Shahila, Ferlin deva Lingaraj, Vanitha Chandran, Prabhu Chidambaram, Vivek Arumugam, Parimala ramadan, Hegazy Mahmoud Saveetha University Tamil Nadu Chennai India Department of ECE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamilnadu Chennai India Department of ECE S.A. Engineering College Tamilnadu Chennai India Department of ECE Prathyusha Engineering College Tamilnadu Chennai India Department of Artificial Intelligence and Data Science Panimalar Engineering College Tamilnadu Chennai India Department of ECE Sree Sastha Institute of Engineering and Technology Tamilnadu Chennai India Sina Institute of Technology Sina Egypt

This work demonstrated the total losses and dispersion effects management and upgrading the fiber reach in ultra-high optical transmission system based on hybrid amplification system. Based on the requirements of the system, a number of trade-offs must be made between the numerous interconnected performance characteristics of each component in the design of a high quality transmission link. The transmission distance is the greatest distance that an optical signal has to travel. It affects the choice of optical component, fiber type, and signal amplification techniques. Fiber amplifiers or signal regeneration may be required to compensate for signal loss over greater distances. reviewing these crucial aspects helps when selecting the best optical components and system layout. This ensures the optical link performs as expected. Hybrid amplification system unit (EdFA/raman/EdFA), (EdFA/raman), (BFA/PdFA) and (raman/EdFA) is employed in the transmission system to strength the signal and upgrade the system performance operation efficiency. Space division multiplexing scheme is also employed with the propagation scheme in order to upgrade and control of the total losses and dispersion effects. The optimum total losses/dispersion/repeater spacing are studied with the variations of the total number of links per fiber core channel. © 2024 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Amplification

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G-Bot: revealing Government Programs with Smarted Assistance 2

G-Bot: Revealing Government Programs with Smarted Assistance

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2nd International Conference on recent Trends in Microelectronics, Automation, Computing, and Communications Systems, ICMACC 2024

作者： ramathilagam, A. Gunasekaran, Kavitha Pandian, Elamparithi Kumar, M. Satheesh Ponkumar, d. david Neels Saravanakumar, r. P.S.R. Engineering College Department of Computer Science and Engineering Tamil Nadu Sivakasi India Ramco Institute of Technology Department of Artificial Intelligence and Data Science Tamil Nadu Rajapalayam India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Iconix Software Solution Tamil Nadu Tirunelveli India

ISBN: (纸本)9798350366570

residents have had trouble getting accurate state program information for years. G-bot's innovative technology employs NLP to link customers to state-level policies and activities to bridge this knowledge gap. G-bot's core NLP module is taught to deliver reliable and trustworthy information to help people make healthy and progressing decisions. G-bot provides real-time, reliable data to promote public awareness, transparency, and involvement in government processes. Users may explore the enormous state program and regulatory information using G-bot's simple interface. G-bot's Flask integration helps users locate vital information. G-bot enhances user-centric apps beyond information retrieval. AI-powered language processing ushers in a new era, letting individuals shape their communities. G-bot uses NEr to identify government entities. This tool simplifies identifying organizations, programs, laws, agencies, and people, improving search results and customizing insights for better decision-making. © 2024 IEEE.

关键词： Bot (Internet)

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3d E-commerce Using AI depth Algorithm Augmented reality 8th

3D E-commerce Using AI Depth Algorithm Augmented Reality

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8th International Conference on Microelectronics Electromagnetics and Telecommunications, ICMEET 2023

作者： Silviya, S. H. Annie devi, S. renuka Sriman, B. Aswinrani, M. raja, S. Sunitha, T. Rajalakshmi Institute of Technology Tamil Nadu Chennai India Department of Artificial Intelligence and Data Science Rajalakshmi Engineering College Chennai India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of Computer Science and Engineering Panimalar Engineering College Chennai India Department of Artificial Intelligence and Data Science Saveetha Engineering College Chennai India

ISBN: (纸本)9789819784219

In today's dynamic world of online shopping, augmented reality (Ar) integration has emerged as a game-changing innovation. It transcends the limitations of traditional online shopping by harnessing Ar technologies, such as Google's ArCore, to create immersive 3d product models. These models empower customers to virtually interact with and visualize products in their own environment, effectively bridging the experiential gap with in-store shopping. Employing Ar software development kits and game engines, these 3d models seamlessly come to life on customers’ devices, offering a more engaging and informative shopping experience. This not only bolsters customer satisfaction but also helps online retailers manage operational costs more efficiently. With Ar’s ability to let customers virtually try on clothes, visualize furniture placements, and inspect products from the comfort of their homes, it's poised to reshape the e-commerce landscape. The ongoing technological revolution is characterized by increasingly immersive, personalized online shopping, setting new benchmarks for customer expectations and retail success. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Sales

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Annotation Guided Generative Adversarial Networks for Image Augmentation of Age-related Macular degeneration 50

Annotation Guided Generative Adversarial Networks for Image ...

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

作者： Chandrasekaran, raja Balpunuri, Saketh reddy Senadheera, Isuru Nallagatla, Vishnu Sai Akula, Lokesh Praveen VelTech Rangarajan Dr Sagunthala R&D Institute of Science & Technology Avadi Chennai India Centre for Data Analytics and Cognition La Trobe Business School La Trobe University Melbourne Australia Department of Ophthalmology ACSR Government Medical College Andhra Pradesh Nellore India

ISBN: (纸本)9781665464543

Age-related macular degeneration (AMd) is a common eye disease that affects millions of people worldwide, leading to central vision loss. It mostly occurs in people over 50 years old. As per the literature, AMd diagnosis requires high-quality and diverse fundus images, which are often scarce and expensive to obtain. We propose a novel generative adversarial network (GAN) to address this challenge. It can synthesize realistic and clinically relevant images with AMd anomalies (drusen and Abnormalities of Choroidal Neovascular Membrane(CNVM)), enhancing dataset diversity and aiding automated diagnosis. Our GAN architecture is supplemented with (manual annotation guided) spatial attention maps to emphasize on anomalies guided through manually generated label maps. Further we propose 2 Siamese like discriminators, for individual anomalies which emphasize the Generator module to generate AMd anomaly (drusen and abnormalities of CNVM) specific images. The proposed GAN leverages various loss functions, including contrastive loss and anomaly loss in the Siamese like discriminator, and the adversarial loss in the combined model. The anomaly loss inspired by (retinal detail Loss) measures the prominence of AMd signatures in the generated images. Our approach successfully generates synthetic images with specific AMd anomalies, aiding early diagnosis. The proposed GAN extended excellent dataset augmentation capabilities with 3% and 4% increase in diagnostic accuracy of drusen and abnormalities of CNVM, respectively. © 2024 IEEE.

关键词： Generative adversarial networks

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A Method of Abnormal detection for Power Grid Control System Metrics Based on AI Platform

A Method of Abnormal Detection for Power Grid Control System...

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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Shen Jialing Ji Xuechun Gao Shang Kong Yanru Li Hao Lao Yingying Big Data Technology R&D Department NARI Group Corporation (State Grid Electric Power Research Institute) Nanjing China

ISBN: (数字)9798331523527

ISBN: (纸本)9798331523534

In the intelligent maintenance of power grid control system, a real-time anomaly detection algorithm for metrics based on sliding windows is proposed. Then, short-term prediction and dynamic threshold are distributed constructed based on AI platform. Finally, multi-dimensional correlation analysis are achieved. Based on the metric of a system, a case study was conducted to verify that the method proposed in this paper is significantly superior of timeliness, accuracy and efficient.

关键词： Measurement Accuracy System integration Control systems Power grids real-time systems Maintenance Artificial intelligence System analysis and design Anomaly detection

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Multi Party Secure Android Cash register

Multi Party Secure Android Cash Register

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Artificial Intelligence, Computer, data Sciences and Applications (ACdSA), International Conference on

作者： Keziban Çimen Mehmet Göktürk R&D Center E DATA Elektronik A.Ş İstanbul Türkiye GTU Institute of Information Technology Gebze Türkiye

As businesses prioritize integration with applications like ErP and inventory tracking, the Android Cash register POS device emerges as a transformative solution, aligning with modern POS trends. developed with a focus on usercentered design principles, the Android Cash register stands out as the first of its kind in the market. It ensures a decade-long usability, encompassing both hardware and software aspects. This study focuses on multipary software enabled Cash register POS device’s compatibility with digital transformations its collaborative development, and its potential for increased market share internationally. Key features of such a POS device include remote control capabilities, compliance with high-level financial regulations, and the unique combination of being a Payment recording device (ECr) with EFTPOS capabilities. The study introduces a Multi-Stakeholder Android Cash register connected to a Secure remote Software distribution Network, offering a distinctive product globally. The hardware design incorporates security measures like MESH and Electronic Seal to safeguard against physical impact and tampering. Security factors, including signing mechanisms like Sign2, are discussed, highlighting the enhanced protection against tampering attacks and the utilization of robust hash algorithms. The study also focuses on Android’s role in the payment sector, addressing security vulnerabilities related to internet access and NFC. In short, importance of a multi-party store model is emphasized, allowing only approved applications to run on the secure Android POS device. The proposed Android Cash register represents a significant leap, offering a secure, integrated, and technologically advanced solution to meet evolving business needs in the digital era, all within a concise framework.

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Negative data in data Sets for Machine Learning Training

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OrGANIC LETTErS 2023年第17期25卷 2945-2947页

作者： Maloney, Michael P. Coley, Connor W. Genheden, Samuel Carson, Nessa Helquist, Paul Norrby, Per-Ola Wiest, Olaf Department of Chemistry and Biochemistry University of Notre Dame Notre Dame Indiana 46556 United States Department of Chemical Engineering and Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 United States Molecular AI Discovery Sciences R&D AstraZeneca Gothenburg Pepparedsleden 1 SE-431 83 Mölndal Sweden Early Chemical Development Pharmaceutical Sciences R&D AstraZeneca Macclesfield SK10 2NA U.K. Data Science and Modelling Pharmaceutical Sciences R&D AstraZeneca Gothenburg Pepparedsleden 1 SE-431 83 Mölndal Sweden

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Hybrid Visual Verification 14

Hybrid Visual Verification

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14th International Conference on Cloud Computing, data Science and Engineering, Confluence 2024

作者： Bushra, S.Nikkath Syed Ismail, A. Sasigresa, P. Edwin Singh, C. Srm Institute of Scienece and Technology Department of Computing Technologies Chengalpattu Kattankulathur India Srm Institute of Scienece and Technology Department of Data Science and Business Systems Chengalpattu Kattankulathur India Veltech University Department: Computer Science and Engineering India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department: Computer Science and Engineering India

ISBN: (纸本)9798350344837

data security is becoming increasingly important as cloud computing advances. data security is the fundamental problem of all distributed computing systems. Cloud computing enables access to distributed applications and services belonging to various organizations spread across different locations. Cloud computing raises security concerns, because it shares data with distributed users via network in an open terrain. In this system, some of the most important security services like image-based security are handled by the cloud computing system. The proposed scheme takes care of several attacks like botnets, malware and guessing attacks. This scheme is contrasted withseveral established schemesand a new form of authentication is used for the purpose of storing files in a secure manner. © 2024 IEEE.

关键词： Authentication

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