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IEEE International Symposium on Smart Electronic Systems (iSES)

作者： Aniruddha Mallick Hriya Prasad Prasenjit Maji Sub.ab.ata b.nerjee Hemanta Kumar Mondal Electronics and Commu. Engg. Institute of Engineering & Management Kolkata India Electronics and Commu. Engg. National Institute of Technology Durgapur India Computer Science and Design ECE Dr. B. C. Roy Engineering College NIT Durgapur Durgapur India Electronics and Communication Engineering Institute of Engineering & Management University of Engineering and Management Kolkata India Electronics and Communication Engineering National Institute of Technology Durgapur India

ISBN: (数字)9798331533229

ISBN: (纸本)9798331533236

b.ain tumors, particularly gliomas, present significant challenges in medical science b.cause of their high incidence, recurrence, and mortality rates. Perfect diagnosis using Magnetic Resonance Imaging (MRI) is crucial. Recent developement in deep learning, particularly in Convolutional Neural Networks (CNNs) and transfer learning models, have significantly enhanced the automation and accuracy of medical image analysis. This work proposes a comprehensive framework for classification of b.ain tumor using MRI data, integrating CNN, VGG16, and EfficientNetb. models with a Field Programmab.e Gate Array (FPGA) implementation pathway. Our approach enhances the models' resilience and applicab.lity using rob.st data augmentation methods, including geometrical transformation. Experimental results demonstrate that b.th CNN and EfficientNetb. achieve classification accuracies exceeding 90%, showcasing their effectiveness in distinguishing b.tween gliomas, meningiomas, and pituitary tumors. The FPGA-b.sed accelerator significantly improves processing efficiency. This framework advances tumor classification and addresses computational challenges, paving the way for practical applications in medical diagnostics.

关键词： Deep learning Accuracy Magnetic resonance imaging b.ain tumors b.ain modeling Data models Convolutional neural networks Medical diagnosis Field programmab.e gate arrays Medical diagnostic imaging

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An ML-b.sed approach to transform stimuli into characteristic oscillatory activity of the b.ta b.nd

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AIP Conference Proceedings 2023年第1期2946卷

作者： Sunny b.att Aditi Jindal Department of Computer Engineering (B.E. Computer Engineering) Gujarat Technological University Ahmedabad-382424 Gujarat India Department of Computer Science and Engineering (B. Tech. Computer Science) Gurugram University Gurugram-122003 Haryana India

b.ain oscillations are essential to math and spatial skills. Cognition, attention, memory processing and language are influenced b. these oscillations. Neurological explanations proposed to account for the fluctuations in b.ain activity help us understand how important the relation of rhythmicity is within a neural network. Desynchronization refers to the sharp and irregular changes of the oscillations in b.ain waves called rapid-eye movement sleep spindle activity during sleep. It is the disruption of interactions b.tween resting oscillations of b.ain regions typically producing rhythmic neuronal firing that occur simultaneously in different frequency b.nds like alpha or b.ta. The b.ta b.nd is associated with attention and self-focused activities like perceiving, thinking, judging, and prob.em solving. In this paper, the authors develop a neural model of nonlinear oscillators that transforms stimuli into characteristic oscillatory activity of the b.ta b.nd.

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An Innovative Internet of Things (IoT) Computing-b.sed Health Monitoring System with the Aid of Machine Learning Approach 5

An Innovative Internet of Things (IoT) Computing-Based Healt...

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5th International Conference on Contemporary Computing and Informatics, IC3I 2022

作者： Dhinakaran, M. Priya, P. Krishna Alanya-b.ltran, Joel Gandhi, Vaib.av Jaiswal, Sushma Singh, Devesh Pratap Government College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Salem India KL Business School Koneru Lakshmaiah Education Foundation Andhra Pradesh Guntur India Universidad Tecnológica Del Perú Department of Electronic Peru Gujarat Technological University B. H. Gardi College of Engineering and Technology Rajkot Department of IT Engineering and MCA Gujarat Ahmedabad India C.G Bilaspur India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350398267

The community health area comprises an enormous measure of data, and specific methodologies are utilized to deal with that data. One of the most common approaches is handling as well as processing. This technique forecasts the likely consequences of cardiovascular disease. The result of this strategy is to foresee the former heart disease. The work controls IOT utilizing a sensor (a heartb.at sensor to screen b.ats) and Arduino, and the outcomes might b. seen on a successive screen. IFTTT is utilized to b.eak down sensor readings in Google Sheets, which are accordingly changed over into CSV go-like information. The datasets utilized are characterized b. treatment b.undaries, in addition to b.ing used for data preparation and testing. This technique assesses those b.undaries utilizing the data arrangement request strategy. With artificial intelligence calculations and order work. The dataset is first taken apart, analyzed, and screened, after which the accumulated information is handled in Python programming utilizing AI Calculations, specifically Choice Tree Calculation with Irregular Woodlands Arrangement Calculation. SVM (b.cking vector machine) creates the b.st outcomes concerning identifying coronary illness. Thus, the recommended worldview is demonstrated to b. a solid one for foreseeing past coronary illness. The recommended equipment and programming innovation help patients in anticipating heart illness in its underlying stages. © 2022 IEEE.

关键词： Internet of things

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Analysis of Diab.tes mellitus using Machine Learning techniques

Analysis of Diabetes mellitus using Machine Learning Techniq...

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International Conference on Multimedia, Signal Processing and Communication technologies, (IMPACT)

作者： Salliah Shafi b.at Venkatesan Selvam Gufran Ahmad Ansari Mohd Dilshad Ansari B. S. AbdurRahman Crescent Institute of Science and Technology Chennai India Faculty of Science MIT World Peace University (MITWPU) Pune India Dept. of Computer Science & Engineering Guru Nanak University Hyderabad India

ISBN: (纸本)9781665476485

Diab.tes Mellitus (DM) often known as hyperglycemia is caused b. high b.ood sugar levels. Although DM is a metab.lic chronic disease. Treatment and early detection are essential to reducing the risk of serious outcomes. The World Health Organization (WHO) reports that diab.tes has a significant mortality rate causing 1.5 million deaths worldwide. The disease can b. identified early b.cause to technology tremendous improvements. In order to b.ild a model with a few variab.es b.sed on the PIMA dataset this research focuses on evaluating diab.tes patients as well as diab.tes diagnosis using various Machine Learning techniques (MLT). Exploratory data analysis is the first step in our process after which the information is transferred for data pre-processing and feature selection. The relevant features are chosen and the data is then training and testing using three different MLT such as Support Vector Machine (SVC), Random Forest (RF) and K-Nearest Neighb.rs (KNN). Amongst all of the classifiers Random Forest has the highest accuracy of 97.75% followed b. Support Vector Machine (82.25%) and K-Nearest Neighb.rs (86.25%).

关键词： Training Radio frequency Support vector machine classification Static VAr compensators Organizations Signal processing Diab.tes

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Integration of A-I in implementation of Wire-less Web.ing: A detailed Review

Integration of A-I in implementation of Wire-less Webbing: A...

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Artificial Intelligence and Smart Communication (AISC), International Conference on

作者： Prab.akara Rao Kapula b.asker Pant b.desh Kanwer Dharam b.ddhi K.V. Daya Sagar S. Sinthu Department of ECE B. V. Raju Institute of Technology Narsapur Telangana Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Poornima Institute of Engineering and Technology Uttaranchal Institute of Technology Uttaranchal University Dehradun Uttarakhand Electronics and Computer Science Koneru LakshmA-Iah Education Foundation Vaddeswaram Guntur Andhrapradesh India English M. Kumarasamy College of Engineering (Autonomous) Karur Thalavapalayam

Mob.le computing and Internet of Things (IoT) web.ing s have b.en rapidly deployed in recent years, which is mostly due to the growing communication and sensing ab.lities of wire-less gadgets. The IoT is expected to b. used as the foundation for the deployment of b.g specifics analysis, ub.quitous computing, and ultimately artificial reconnaissance (A-I), which will usher in a new era of specifics-driven A-I. In this context, Wire-less A-I, a revolutionary paradigm for fusing A-I as well as wire-less communications, is widely recognised as a critical enab.er for future intelligent web.ing growth. Wireless A-I pushes A-I frontiers to the web.ing edge. In order to achieve this, we give a thorough analysis of the most recent wireless A-I projects from a specifics-driven approach. In particular, we initially suggest an unique Wire-less A-I architecture that addresses There are five mA-In specifics-driven A-I themes in wire-less web.ing s: sensing, access, user gadgets, and specifics provenance. Then, we give an overview of how A-I techniques are used to address new specifics-related prob.ems and demonstrate how A-I can enhance wire-less kind of sytem netwrk functionality for each specifics-driven A-I theme. We present an in-depth discussion on the Wire-less A-I applications in many specifics-driven sectors where A-I appears to b. incredib.y helpful for wire-less kind of sytem netwrk design and optimization, especially in comparison to the other related survey articles. To encourage more research in this promising field, prob.ems for future research and future perspectives are also explored.

关键词： Wireless communication Wireless sensor networks computer architecture Reconnaissance Ub.quitous computing Sensors Internet of Things

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Parking Prob.em b. Ob.ivious Mob.le Rob.ts in Infinite Grids

arXiv

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arXiv 2023年

作者： Chakrab.rty, Ab.inav Mukhopadhyaya, Krishnendu Department of Computer Science and Engineering Institute of Technical Education and Research Siksha O Anusandhan University Odisha Bhubaneswar India Advanced Computing and Microelectronics Unit Indian Statistical Institute 203 B. T. Road West Bengal Kolkata700108 India

In this paper, the parking prob.em of a swarm of mob.le rob.ts has b.en studied. The rob.ts are deployed at the nodes of an infinite grid, which has a sub.et of prefixed nodes marked as parking nodes. Each parking node pi has a capacity of ki which is given as input and equals the maximum numb.r of rob.ts a parking node can accommodate. As a solution to the parking prob.em, rob.ts need to partition themselves into groups so that each parking node contains a numb.r of rob.ts that are equal to the capacity of the node in the final configuration. It is assumed that the numb.r of rob.ts in the initial configuration represents the sum of the capacities of the parking nodes. The rob.ts are assumed to b. autonomous, anonymous, homogeneous, identical and ob.ivious. They operate under an asynchronous scheduler. They neither have any agreement on the coordinate axes nor do they agree on a common chirality. All the initial configurations for which the prob.em is unsolvab.e have b.en identified. A deterministic distrib.ted algorithm has b.en proposed for the remaining configurations, ensuring the solvab.lity of the prob.em. Copyright © 2023, The Authors. All rights reserved.

关键词： Mob.le rob.ts

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Cold Start Latency in Serverless Computing: A Systematic Review, Taxonomy, and Future Directions

arXiv

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arXiv 2023年

作者： Golec, Muhammed Walia, Guneet Kaur Kumar, Mohit Cuadrado, Felix Gill, Sukhpal Singh Uhlig, Steve School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom Abdullah Gul University Kayseri Turkey Department of Information Technology Dr. B. R. Ambedkar National Institute of Technology Punjab Jalandhar India Spain

Recently, academics and the corporate sector have paid attention to serverless computing, which enab.es dynamic scalab.lity and an economic model. In serverless computing, users only pay for the time they actually use resources, enab.ing zero scaling to optimise cost and resource utilisation. However, this approach also introduces the serverless cold start prob.em. Researchers have developed various solutions to address the cold start prob.em, yet it remains an unresolved research area. In this article, we propose a systematic literature review on clod start latency in serverless computing. Furthermore, we create a detailed taxonomy of approaches to cold start latency, which we use to investigate existing techniques for reducing the cold start time and frequency. We have classified the current studies on cold start latency into several categories such as caching and application-level optimisation-b.sed solutions, as well as Artificial Intelligence (AI)/Machine Learning (ML)-b.sed solutions. Moreover, we have analyzed the impact of cold start latency on quality of service, explored current cold start latency mitigation methods, datasets, and implementation platforms, and classified them into categories b.sed on their common characteristics and features. Finally, we outline the open challenges and highlight the possib.e future directions. Copyright © 2023, The Authors. All rights reserved.

关键词： Quality of service

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An Investigation and Development into the Use of AI-b.sed Analytical Methods for Forecasting the Stock Market

An Investigation and Development into the Use of AI-Based An...

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Smart Electronics and Communication (ICOSEC), International Conference on

作者： M. Sheeb. D. Ranjith Kumar S. Kirub.karan Ila Dixit D. Leela Rani Ajay Singh Yadav Department of B. Com Information System Management Guru Nanak College (Autonomous) Chennai Tamil Nadu India Department of B. Com Corporate Secretaryship Guru Nanak College (Autonomous) Chennai Tamil Nadu India Department of Computer Science and Engineering CMR College of Engineering and Technology Hyderabad Telangana India Department of Management Maharaja Agarsen International College Raipur Chhattisgarh India Department of Electronics and Communication Engineering School of Engineering Mohan Babu University Tirupati Andhra Pradesh India Department of Mathematics SRM Institute of Science and Technology Ghaziabad Utter Pradesh India

Forecasting the stock market is difficult due to the fact that a numb.r numerous factors, including the current situation of economy, current politics, and market sentiment. Traditional analytical methods have limitations in accurately predicting stock prices, leading to increased curiosity ab.ut using algorithms b.sed on artificial intelligence (AI) and machine learning (ML) stock market forecasting. This paper investigates the use of AI-b.sed analytical methods for forecasting the stock market and presents a detailed analysis of various algorithms used in AI-b.sed stock market forecasting. The use of AI-b.sed analytical methods for forecasting the stock market has several b.nefits. Firstly, AI-b.sed models can analyse vast amounts of financial data much faster than traditional methods, allowing for more accurate and timely predictions. Secondly, AI-b.sed models can handle complex relationships b.tween different factors affecting stock prices, such as market trends, news events, and economic indicators, which can b. challenging to capture using traditional methods. This study also discusses ab.ut the challenges and limitations of using AI-b.sed models for stock market forecasting research in the future research. Here, this study uses a novel theory of recurrent neural networks and a random forest model to enab.e prediction with more accuracy. One of the commonly used algorithms in AI-b.sed stock market forecasting is the recurrent neural network (RNN), which model that uses deep learning. RNNs are very helpful for modelling time-series information, like stock prices, just b.cause they may ensnare the temporal data dependencies. In addition, RNNs can b. used to generate forecasts b. predicting the next value in a set of timestamps b.sed on previous values. Another popular algorithm for stock market forecasting is the Random Forest (RF) ensemb.e model. RF models are a type of decision tree-b.sed algorithm that can generate accurate predictions b. comb.ning the output

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Temperature Variation Modelling in Mushroom Growing Hall with IAN-b.directional GRU Model

Temperature Variation Modelling in Mushroom Growing Hall wit...

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Sustainab.e Expert Systems (ICSES), International Conference on

作者： D. Kalpanadevi S. Nandhini Devi Silas Stephen D Sunita Jadhav P M D Ali Khan Muralidharan J Department of Computer Science School of Science Gitam University Karnataka India Department of CSE V. S. B. Engineering College Karudayanpalayam Karur Tamilnadu India Department of Electrical and Electronics Engineering Panimalar Engineering College Chennai Tamilnadu India Department of Botany Krishna Mahavidyalaya Rethare Bk Satara Maharashtra India School of Computing Mohan Babu University Tirupati Andhra Pradesh India Department of ECE KPR Institute of Engineering and Technology Coimbatore Tamilnadu India

ISBN: (数字)9798331540364

ISBN: (纸本)9798331540371

Modern developments in computing and electronics have made intelligent systems suitab.e for use in the mechanization of agricultural processes. This proposed used multilayered perceptron and radial b.sis function networks to forecast the temperature shifts in the mushroom cultivation chamb.r b.sed on independent variab.es including water temperature, amb.ent temperature, water tap, fresh air and circulation air dampers, and water tap. Preprocessing, feature extraction, and training the model are the three phases that comprise this proposed method. Reflectance calib.ation, normalization, and spectral smoothing are the steps involved in data preprocessing. Feature extraction made quick work of extracting information from mushroom photos b. employing the SIFT algorithm. The proposed model was trained using an IAN-b.directional GRU. When compared to more conventional approaches, the proposed methodology is superior. The method's application resulted in a 93.75% improvement in accuracy.

关键词： Training Reflectivity Smoothing methods Accuracy Data preprocessing Humidity Carb.n dioxide Feature extraction Shock ab.orb.rs Data mining

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Securing the Future of Communication with Quantum Cryptography

Securing the Future of Communication with Quantum Cryptograp...

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IEEE Electron Devices Kolkata Conference (EDKCON)

作者： Parna Kundu Sudipta b.nerjee Mousam Chatterjee Himadri Sekhar Das Aritra b.owmik Heranmoy Maity Electronics and Communication Engineering Maulana Abul Kalam Azad University of Technology Kolkata India Computer Science and Enginerring Symbiosis Institute of Technology Pune Symbiosis International (Deemed University) Pune India Electronics and Communication Engineering B. P. Poddar Institute of Management and Technology Kolkata India Electronics and Communication Engineering Haldia Institute of Technology-Haldia Haldia India Electronics and Communication Engineering Dr. B C Roy Engineering College Durgapur Durgapur India Electronics and Communication Engineering Pailan college of Management and Technology Kolkata India

ISBN: (数字)9798350374643

ISBN: (纸本)9798350374650

The study of quantum cryptography has b.come a ray of hope in the constantly changing field of cyb.rsecurity. Quantum cryptography uses the remarkab.e qualities of quantum mechanics to provide a level of security that classical cryptography finds difficult to achieve in light of the growing threats to digital information. This thorough analysis explores the many facets of quantum cryptography, including emerging quantum networks, practical applications, cryptographic protocols, and b.sic concepts. This review explains the intricacies of cost, infrastructure, and integration, and compares them with the continuous technological developments that indicate that it is ready for b.oad adoption. The impending threat of quantum computers, which calls for a switch to quantum-safe cryptography, looms large amid the promise of quantum security. Quantum-safe algorithms are important b.cause they provide strong security against quantum attacks.

关键词： Electric potential Reviews Government Finance Switches Medical services Encryption Quantum networks Quantum cryptography Faces

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