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2024 International Conference on Advances in Modern Age Technologies for Health and engineering science, AMATHE 2024

作者： Handa, Devansh Nikhil, Kindi Krishna Duvarakanath, S. Murali, K. Amrita School Of Computing Amrita Vishwa Vidyapeetham Department Of Computer Science And Engineering Bengaluru India Amrita School Of Engineering Amrita Vishwa Vidyapeetham Department Of Mathematics Bengaluru India

ISBN: (纸本)9798350371567

The proposed study realizes a novel quantum machine learning (QML) architecture that allows heuristic function evaluation and can actually perform quantum circuits during massive data processing. The Quantum-Circuit fusion or the Quantum-Data fusion approach to information technology is the latest strategy revolutionizing the major applications with vast computing needs in present time. Our method, which is task - agnostic, is aimed to increase the machine operations speed and scale as the concepts of quantum computing are applied. In this research article, the theoretical background and perspectives are described, so generally, the idea of the combination of quantum circuits is clarified. The research delivery shows as well of this combination as its importance and possibilities, offering a new and cool method in the competitive era of data-driven computational sciences, especially in the field of quantum machine learning. Within classical machine quantum-circuit fusion the potential capability to handle a large data set and obtain the new viewpoints consequently quantum machine learning progress represents a promising route. © 2024 IEEE.

关键词： Timing circuits

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MeshWGAN: Mesh-to-Mesh Wasserstein GAN with Multi-Task Gradient Penalty for 3D Facial Geometric Age Transformation

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IEEE Transactions on Visualization and computer Graphics 2024年第8期30卷 4927-4940页

作者： Zhang, Jie Zhou, Kangneng Luximon, Yan Lee, Tong-Yee Li, Ping The Hong Kong Polytechnic University Department of Computing The School of Design Hong Kong University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China The Hong Kong Polytechnic University School of Design Hong Kong Laboratory for Artificial Intelligence in Design Hong Kong National Cheng-Kung University Department of Computer Science and Information Engineering Tainan70101 Taiwan

As the metaverse develops rapidly, 3D facial age transformation is attracting increasing attention, which may bring many potential benefits to a wide variety of users, e.g., 3D aging figures creation, 3D facial data augmentation and editing. Compared with 2D methods, 3D face aging is an underexplored problem. To fill this gap, we propose a new mesh-to-mesh Wasserstein generative adversarial network (MeshWGAN) with a multi-task gradient penalty to model a continuous bi-directional 3D facial geometric aging process. To the best of our knowledge, this is the first architecture to achieve 3D facial geometric age transformation via real 3D scans. As previous image-to-image translation methods cannot be directly applied to the 3D facial mesh, which is totally different from 2D images, we built a mesh encoder, decoder, and multi-task discriminator to facilitate mesh-to-mesh transformations. To mitigate the lack of 3D datasets containing children's faces, we collected scans from 765 subjects aged 5-17 in combination with existing 3D face databases, which provided a large training dataset. Experiments have shown that our architecture can predict 3D facial aging geometries with better identity preservation and age closeness compared to 3D trivial baselines. We also demonstrated the advantages of our approach via various 3D face-related graphics applications. © 1995-2012 IEEE.

关键词： Face recognition

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Improved Dynamic Johnson Sequencing Algorithm(DJS)in Cloud computing Environment for Efficient Resource Scheduling for Distributed Overloading

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Journal of Systems science and Systems engineering 2024年第4期33卷 391-424页

作者： Anurag Sinha Pallab Banerjee Sharmistha Roy Nitasha Rathore Narendra Pratap Singh Mueen Uddin Maha Abdelhaq Raed Alsaqour Department of Computer Science Engineering ICFAI Tech SchoolICFAI UniversityJharkhandRanchi834004India Department of Computer Science Engineering Amity UniversityJharkhandRanchi835303India Department of Computing and Information Technology Usha Martin UniversityRanchi835103India Department of Information Technology Bharti Vidyapeeth’s College of EngineeringPaschim ViharNew DelhiIndia Department of CSE Delhi UniversityNew DelhiIndia College of Computing and Information Technology University of Doha for Science and TechnologyDoha24449Qatar Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdurrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Technology College of Computing and InformaticsSaudi Electronic University93499RiyadhSaudi Arabia

This study introduces an innovative approach to optimize cloud computing job distribution using the Improved Dynamic Johnson Sequencing Algorithm(DJS).Emphasizing on-demand resource sharing,typical to Cloud Service Providers(CSPs),the research focuses on minimizing job completion delays through efficient task *** Johnson’s rule from operations research,the study addresses the challenge of resource availability post-task *** advocates for queuing models with multiple servers and finite capacity to improve job scheduling models,subsequently reducing wait times and queue *** Dynamic Johnson Sequencing Algorithm and the M/M/c/K queuing model are applied to optimize task sequences,showcasing their efficacy through comparative *** research evaluates the impact of makespan calculation on data file transfer times and assesses vital performance indicators,ultimately positioning the proposed technique as superior to existing approaches,offering a robust framework for enhanced task scheduling and resource allocation in cloud computing.

关键词： First come first served(FCFS)scheduling round robin task scheduling queuing model Johnson scheduling algorithm

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Precaution Chatbot for Epilepsy Patients using Natural Language Processing and Deep Learning Sequential Model 5

Precaution Chatbot for Epilepsy Patients using Natural Langu...

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5th International Conference on Innovative Data Communication Technologies and Application, ICIDCA 2024

作者： Kasthuri, E. Subbulakshmi, S. Sreedharan, Rajasree Department of Computer Science and Engineering Amrita School of Computing Amritapuri India Department of Computer Science and Applications Amrita School of Computing Amritapuri India Division of Nephrology Department of Pediatrics Medical College of Wisconsin MilwaukeeWI United States

Epilepsy is a brain disorder that can affect people of all ages which is one of the most common neurological disorders affecting around 50 million individuals. Healthcare Chatbots schedule appointments, respond to patient inquiries, and offer relevant information, freeing medical staff to handle life crises. This paper implements a chatbot for epilepsy patients to increase awareness about epilepsy. Patients may easily access this AI-based healthcare chatbot whenever they have queries regarding precautions to be taken by epilepsy patients. Chatbot uses a rich set of epilepsy-related datasets collected from trusted websites which are preprocessed with NLP techniques to prepare the data for model ***, LSTM, and RNN models are created and evaluated to produce answers to user queries related to possible precautions to avoid seizures, safety measures to be taken by patients with seizure history, etc. Evaluation of models shows that the RNN model generates more accurate answers with 94% accuracy. Finally, the epilepsy question answering Chatbot for precaution is concluded with the RNN model. © 2024 The Authors. Published by Elsevier B.V.

关键词： Deep neural networks

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Recent Advances in In-Memory computing:Exploring Memristor and Memtransistor Arrays with 2D Materials

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Nano-Micro Letters 2024年第7期16卷 1-30页

作者： Hangbo Zhou Sifan Li Kah-Wee Ang Yong-Wei Zhang Institute of High Performance Computing(IHPC) Agency for ScienceTechnology and Research(A*STAR)1 Fusionopolis Way#16-16 ConnexisSingapore 138632Republic of Singapore Department of Electrical and Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117583Republic of Singapore Institute of Materials Research and Engineering Agency for ScienceTechnology and Research(A*STAR)2 Fusionopolis WaySingapore 138634Republic of Singapore

The conventional computing architecture faces substantial chal-lenges,including high latency and energy consumption between memory and processing *** response,in-memory computing has emerged as a promising alternative architecture,enabling computing operations within memory arrays to overcome these *** devices have gained significant attention as key components for in-memory computing due to their high-density arrays,rapid response times,and ability to emulate biological *** these devices,two-dimensional(2D)material-based memristor and memtransistor arrays have emerged as particularly promising candidates for next-generation in-memory computing,thanks to their exceptional performance driven by the unique properties of 2D materials,such as layered structures,mechanical flexibility,and the capability to form *** review delves into the state-of-the-art research on 2D material-based memristive arrays,encompassing critical aspects such as material selection,device perfor-mance metrics,array structures,and potential ***,it provides a comprehensive overview of the current challenges and limitations associated with these arrays,along with potential *** primary objective of this review is to serve as a significant milestone in realizing next-generation in-memory computing utilizing 2D materials and bridge the gap from single-device characterization to array-level and system-level implementations of neuromorphic computing,leveraging the potential of 2D material-based memristive devices.

关键词： 2D materials Memristors Memtransistors Crossbar array In-memory computing

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Machine Learning Technique to Detect Radiations in the Brain

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computer Systems science & engineering 2022年第7期42卷 149-163页

作者： E.Gothai A.Baseera P.Prabu K.Venkatachalam K.Saravanan S.SathishKumar Department of Computer Science and Engineering Kongu Engineering CollegeErode638060India School of Computing Science and Engineering VIT Bhopal UniversityBhopal466114India Department of Computer Science CHRIST(Deemed to be University)Bangalore560029India Department of Computer Science and Engineering CHRIST(Deemed to be University)BangaloreIndia Department of Computer Science and Engineering Erode Sengunthar Engineering CollegeThudupathi638057 Department of EEE M.Kumarasamy College of EngineeringKarur639113TamilnaduIndia

The brain of humans and other organisms is affected in various ways through the electromagneticﬁeld(EMF)radiations generated by mobile phones and cell phone *** variations in the brain are caused by the neurological changes due to the revelation of *** level analysis is used to measure and detect the effect of mobile radiations,but its utilization seems very expensive,and it is a tedious process,where its analysis requires the preparation of cell *** this regard,this research article proposes optimal broadcast-ing learning to detect changes in brain morphology due to the revelation of ***,Drosophila melanogaster acts as a specimen under the revelation of *** segmentation is performed for the brain to attain the microscopic images from the prejudicial geometrical characteristics that are removed to detect the effect of revelation of *** geometrical characteristics of the brain image of that is microscopic segmented are *** results reveal the occur-rence of several prejudicial characteristics that can be processed by machine learn-ing *** important prejudicial characteristics are given to four varieties of classiﬁers such as naïve Bayes,artiﬁcial neural network,support vector machine,and unsystematic forest for the classiﬁcation of open or nonopen micro-scopic image of *** *** results are attained through various experimental evaluations,and the said classiﬁers perform well by achieving 96.44%using the prejudicial characteristics chosen by the feature selection *** proposed system is an optimal approach that automatically identiﬁes the effect of revelation of EMF with minimal time complexity,where the machine learning techniques produce an effective framework for image processing.

关键词： Electromagneticﬁeld radiations brain morphology segmentation machine learning image processing

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Enhancing Medical Imaging: Denoising with Discrete Fourier Transform, Clustering, and Statistical Analysis 5

Enhancing Medical Imaging: Denoising with Discrete Fourier T...

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5th International Conference on Circuits, Control, Communication and computing, I4C 2024

作者： Nandini, Bandaru Jaya Sahithi, Mamidi Leha Harshika, Siddareddy Gari Jayan, Sarada Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Bengaluru India Amrita School of Engineering Department of Mathematics Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331528539

In the complex realm of medical imaging, noise poses a significant challenge as every pixel can convey crucial information that might save lives. Various factors, including environmental noise, sensor noise, and the intrinsic constraints of imaging equipment, can cause denoising in images. This study introduces a novel image denoising approach specifically applied to the Alzheimer's dataset, which is crucial for understanding and diagnosing Alzheimer's disease. The dataset comprises five distinct classes, each representing different stages or types of the disease, making it particularly significant in the medical field. Theproposed method leverages a combination of Discrete Fourier Transform (DFT), Inverse Discrete Fourier Transform (IDFT), Butterworth low-pass filtering, and Non-local Means denoising to enhance image quality. By employing Fourier Transform, the study performs frequency domain analysis on the image data, enabling the extraction of vital information while reducing noise. Furthermore, K-means clustering is used to categorize noisy and denoised images based on visual similarities. To validate the effectiveness of the denoising technique, statistical evaluations are conducted through hypothesis testing, comparing noise levelsand quality metrics between noisy and denoised images. Thisstudy not only offers a comprehensive approach to addressing the challenges of image denoising in medical imaging but alsohas significant societal benefits. By improving the clarity of images used in Alzheimer's research, the study contributes to more accurate diagnoses and better understanding of the disease, potentially leading to improved patient outcomes and advancing public health efforts in combating Alzheimer's disease. © 2024 IEEE.

关键词： Butterworth filters

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Advanced transformer model with fine-grained correlation fusion for Multimodal Emotion analysis 2

Advanced transformer model with fine-grained correlation fus...

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

作者： Krishnan, Sundara Rajulu Navaneetha Sangeetha, M. Srinivasulu, Senduru Surendran, R. Dhanalakshmi Srinivasan University Trichy Department of Computer Science and Engineering Samayapuram Campus Tiruchirappalli India Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College Department of Computer Science and Engineering Avadi Chennai India Sathyabama Institute of Science and Technology School of Computing Department of Computer Science and Engineering Chennai India Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Saveetha School of Engineering Chennai India

ISBN: (纸本)9798331534950

In recent days, Emotion recognition has garnered a lot of attention because of its important applications in human-computer interaction. Human emotion is expressed through a variety of verbal and nonverbal languages, including text, audio, and visual. Current multimodal emotion analysis techniques typically perform poorly because they don't fully utilize the link between various modalities. An advanced transformer model with fine-grained correlation fusion (AT-FGCF) is presented in this research to identify emotion in text, audio, and visual modalities. To enhance the representation of the input audio and video, dense hierarchical feature maps are captured using the Dense Swin Transformer (DSwinT) model. Also, an Emotion- Aware Cognitive BERT (EAC-BERT) is introduced to enhance text representation. Lastly, a fine-grained correlation fusion is carried out to take advantage of correlations between fine-grained features from multimodal data. Our experimental findings show that the suggested method is successful in reaching radical outcomes across two benchmark datasets. That is the datasets IEMOCAP, and MELD all have average accuracy improvements of about 88.35%, and 84.80% respectively. © 2024 IEEE.

关键词： Emotion Recognition

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Chatease: A Blockchain based Chat Application 2

Chatease: A Blockchain based Chat Application

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2nd International Conference on Applied Artificial Intelligence and computing, ICAAIC 2023

作者： Kuchimanchi, Akhil Vagdevi, Maddineni Reddy, Meghana Avugaddi, Ganesh Kumar, Sanjay S Amrita School of Engineering Department of Electronics and Communication Engineering Kerala India Amrita School of Computing Department of Computer Science Kerala India

ISBN: (纸本)9781665456302

Security problems have traditionally arisen when messages are exchanged through unsecured channels. Despite the fact that there are various strategies for encrypting messages, attempts on gathering Information continues to be sent. Furthermore, the fact that the vast majority of applications store their data in centralized databases is grounds for worry. Blockchain technology offers new ways to ensure data privacy, censorship resistance, immutability, and decentralization. Each node in the network receives a copy of the data sent directly into the Blockchain by users. Using their private key, only approved persons may access the data on the blockchain. It eliminates the need for trustworthy intermediates. Because the system is totally decentralized, users may send messages with confidence. This software shows how to hash messages and mine them in the blockchain. To provide decentralized storage and quick lookup, we'll use a distributed hash table (DHT) and blockchain. This paper describes how to build a decentralized chat program. © 2023 IEEE.

关键词： Blockchain

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Comparative Analysis of DFT, DCT, and DWT Transformations with ADMM and l1-Optimization for Compressed Sensing in Meningioma Tumor MRI Image Reconstruction 1

Comparative Analysis of DFT, DCT, and DWT Transformations wi...

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1st International Conference on Innovations in Communications, electrical and computer engineering, ICICEC 2024

作者： Narendran, Advik Hothri, Anantha Saga, Hemanth Jayan, Sarada Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Bangalore India Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Mathematics Bangalore India

ISBN: (纸本)9798350376517

In the context of modern medical imaging in MRI, it is becoming increasingly challenging to minimize the amount of time taken for scanning and data burden that is expected to be processed while still ensuring that high quality images are obtained. This study sought to compare the performances of different transforms in compressed sensing including DFT, DCT, and DWT based on conjugate ADMM and l1-optimization for reconstruction of meningioma tumor MRI images. The objective of this initiative is to entail the determination of the optimal transform and optimization methodologies whose outcomes will provide the best image reconstruction quality with the lowest computational complexities. Through the use of compressed sensing, the number of measurements used was much lower than normally expected, lowering the amount of data used. It was found DWT may be preferred for non-time-sensitive applications that demand the highest quality images, DCT's balanced attributes render it generally the best choice for the broadest range of medical imaging applications, expected to lead to a significant enhancement in the MRI diagnosis, patient comfort and the overall healthcare delivery system costs. The report outlines the method utilized for this study and the results observed using these techniques in real-world medical environments. © 2024 IEEE.

关键词： Magnetic resonance imaging

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