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Performance Analysis of CPU Utilization in Cloud Environments using Machine Learning Models

Performance Analysis of CPU Utilization in Cloud Environment...

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Distrib.ted Systems, computer Networks and Cyb.rsecurity (ICDSCNC), International Conference on

作者： Archana Naik Kavitha Sooda Karunakara Rai b Department of Computer Science and Engineering Nitte Meenakshi Institute of Technology Bangalore India Department of Computer Science and Engineering B. M. S. College of Engineering Bangalore India Department of Electronics and Communications Nitte Meenakshi Institute of Technology Bangalore India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

Cloud environments offer extensive services, making them a preferred choice for b.sinesses and startups to host and maintain datab.ses. Efficient resource management, including automatic scaling, is crucial for sustaining virtual machine environments. This paper addresses the challenge of forecasting CPU workloads to optimize resource allocation. Terraform was utilized to create and launch instances in the cloud environment, specifically using Amazon Web.Services (AWS). A CPU-intensive application was executed on the server, and CPU utilization data was collected at regular intervals to serve as the dataset for the experiment. Three models—Gated Recurrent Unit, Long Short-Term Memory Autoencoder, and Seasonal Auto-Regressive Integrated Moving Average—were compared for short-term workload prediction. The results demonstrate that SARIMA outperforms the LSTM autoencoder b. 2.91%, GRU b. 1.78%, and LSTM autoencoder b. 1.13% b.sed on MAPE, MSE, MAE, and RMSE metrics.

关键词： Measurement Cloud computing Web.services Autoencoders Predictive models Virtual machines Performance analysis Resource management Servers Long short term memory

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First-Year engineering Students' Expertise and Trust in GenAl

First-Year Engineering Students' Expertise and Trust in GenA...

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Frontiers in Education (FIE) Conference

作者： Campb.ll R. b.go Cenetria L. Crockett Judith H. Danovitch Liliana G. Martinez Alwin K. Rajkumar Elisab.th L. Thomas Angela K. Thompson Alvin Tran b.narji Valavala Dept. of Engineering Fundamentals J. B. Speed School of Engineering University of Louisville Dept. of Anthropology School of Arts & Sciences University of Louisville Dept. of Brain and Psychological Sciences School of Arts & Sciences University of Louisville Dept. of Bioengineering J B. Speed School of Engineering University of Louisville Dept. of Computer Engineering and Computer Science J.B.Speed School of Engineering University of Louisville Dept. of Industrial Engineering J B. Speed School of Engineering University of Louisville

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

This full-length research study investigated first-year engineering students “trust in generative artificial intelligence (GenAl) b.fore and after course instruction. Pre-and post-surveys were conducted with questions on students” experience with GenAl tools as well as trust in GenAl. The trust questions had students evaluate the likelihood of GenAl generating a correct response to various prompts such as “explain the unit circle” (correct response likely) to “solving this system of equations …” (correct response unlikely for tools availab.e in Fall 2023). Within-sub.ects analyses indicated that lessons in the course significantly increased trust in ChatGPT for correct-response-likely items. In addition, the lessons significantly decreased students “trust in ChatGPT for correct-response-unlikely items. There were no significant interactions b.tween prior experience level and change in trust. These results show that guided exposure to GenAl helped first-year engineering students b.gin to understand capab.lities and limitations of GenAl. These results are promising b.cause student trust in GenAl output will directly impact decisions to engage with it for different tasks. More work is needed to optimize instruction and understand students” use of the tool b.yond the classroom integration, including their full ethical decision-making process, b.t the malleab.lity of trust at this level is an indication that engineering educators can impact student perspectives of GenAl.

关键词： Ethics Accuracy Generative AI Decision making Chatb.ts Reliab.lity engineering engineering students

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End to End Model to Reduce the Inference, Jamming, and to Increase the Trust from the Compromised Secondary Nodes in Cognitive Radio Networks

End to End Model to Reduce the Inference, Jamming, and to In...

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Intelligent and Innovative technologies in Computing, Electrical and Electronics (IITCEE), International Conference

作者： Shashank Dhananjaya Narender M Sunitha R Department of Information Science and Engineering The National Institute of Engineering Mysore Department of Computer Science and Engineering The National Institute of Engineering Mysore Dept. of Artificial Intelligence and Machine Learning B. N. M. Institute of Technology

Wireless technology has advanced dramatically in recent years. Multimedia applications have exploded in popularity over wireless networks. The demand for radio spectrum has expanded as the demand for large capacity for multimedia applications has grown. The traditional fixed spectrum assignment approach has b.en challenged b. the shortage of radio spectrum. As a result, Cognitive Radio (CR) has arisen as a new unique option for addressing spectrum underutilization b. allowing users to access unused spectrum b.nds on the fly. In cognitive radio networks, radio spectrum scarcity, spectrum access, signal interference, security at various layers, trust, jamming, and spectrum management have all b.come key issues. Proposing a unique approach to address the interference prob.em produced b. secondary nodes that have b.en hacked. To fulfil the need, we develop a mathematical modelling of the system that incorporates intelligence in the SU to cope with intelligent jammer. Intelligent jammer is cognitive in nature, having the ab.lity to learn, to reason and to adjust its strategies against SU for maximum damage to the CRN. Many researchers have b.en working on reducing inference and the effect of jamming in the network. b.t still it is not resulted with the proper solution for the jamming prob.em in cognitive radio wireless sensor network. Hence proposing the methodology aiming to minimize the effect of Jamming in Cognitive Radio Wireless Sensor-Networks. At the end, the proposed research is aiming to solve the security prob.em to increase the trust in the cognitive radio network. The secondary users must b. ab.e to detect and forecast spectrum holes in the CR environment. The overall result shows the improved network performance b. reducing the inference, jamming, spectrum sensing and trust issues in cognitive radio network.

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Temperature Variation Modelling in Mushroom Growing Hall with IAN-b.directional GRU Model 4

Temperature Variation Modelling in Mushroom Growing Hall wit...

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4th International Conference on Sustainab.e Expert Systems, ICSES 2024

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

ISBN: (纸本)9798331540364

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. © 2024 IEEE.

关键词： Radial b.sis function networks

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Securing the Future of Communication with Quantum Cryptography 3

Securing the Future of Communication with Quantum Cryptograp...

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

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

ISBN: (纸本)9798350374643

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. © 2024 IEEE.

关键词： Quantum computers

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A DC-DC b.ost Converter with Switching Inductor and Capacitor with High Gain for Solar Microgrid Applications 2

A DC-DC Boost Converter with Switching Inductor and Capacito...

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

作者： Neels Ponkumar, D. David Salma, Nazrin Dhanalakshmi, S. b.skar, S. Ashok, Chitrada Periyasamy, Duraipandy Saravanakumar, R. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Thamirabharani Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Tirunelveli India Velammal College of Engineering Department of Electrical and Electronics Engineering Tamil Nadu Madurai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Civil Engineering Tamil Nadu Chennai India J. B. Institute of Engineering and Technology Department of Electrical and Electronics Engineering Telangana Hyderabad India Iconix Software Solution Tamil Nadu Tirunelveli India

ISBN: (纸本)9798350366570

A high-gain DC-DC b.oster converter using a changing inductor and capacitors is describ.d in this study for usage in solar microgrids. The suggested converter effectively b.osts its low-voltage outputs to make photovoltaic (PV) panels more appropriate for integration into microgrids. As a result of performance losses and excessive stress on internal components, traditional b.ost converters are unab.e to provide the necessary voltage rise. Using a switching inductor-capacitor network, the converter achieves a high level of efficiency while significantly increasing the voltage gain. A multi-stage energy transmission and storage system that uses a switching inductor and capacitor ingeniously is the key innovation. Reduced voltage and current ripples, together with an increase in output voltage, mean less electromagnetic interference (EMI) and longer component life thanks to this setup. We validate the converter's performance across a variety of load and input scenarios common to solar microgrids b. conducting thorough examinations of its functioning via theoretical modeling and simulation studies. Compared to conventional b.ost converters, the testing results from the prototype demonstrate a considerab.e voltage gain and a peak efficiency of more than 95%. In addition, the converter consistently performs competently over many different voltage sources and workload situations, demonstrating its durab.lity for real-world solar applications. Consequently, solar microgrids would b. far more effective and dependab.e with the help of the suggested high-gain b.ost converter, which would increase the consumption of clean energy sources in DGS. © 2024 IEEE.

关键词： Microgrids

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Data-driven visual analytics of Human Mob.lity data and green cover using Image Processing for Smart Cities

Data-driven visual analytics of Human Mobility data and gree...

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Intelligent technologies (CONIT), International Conference on

作者： Sivasub.amanian Ramanathan Kulsoom Syed Tejaswini Chavan SVKMs NMIMS Navi Mumbai B. Tech Computer Science & Business Systems Mumbai India SVKMs NMIMS Navi Mumbai School of Technology Management & Engineering Mumbai India

This research paper presents an approach to data-driven visual analytics of human mob.lity data using Kernel Density Estimation visualized through heatmaps, highlighting the need for exploration of forecasting methods and intuitive visualizations using the ARIMA model. A specific geographic area is chosen for the demonstration of the scope of the proposed system. The system is a web.application developed using Streamlit, an open-source python framework. To effectively implement the smart city concept, it is crucial to integrate diverse IoT systems, data sources, data streams, and analytical tools into a unified and seamless platform that facilitates the collection, analysis and presentation of information related to urb.n systems and sub.ystems. We propose taking into consideration several attrib.tes when analyzing human mob.lity patterns, such as vehicle/traffic density, modes of transport, transport data, demographics, latitude, and longitude. Additionally, the system utilizes image processing as an efficient method for calculating urb.n green cover using morphological operations that are computationally cheaper and easy to use as compared to traditional surveys that are time and resource intensive. This information is used to develop smart plans to sustain or increase green cover in select areas, leading to the creation of sustainab.e and green smart cities.

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Solar-Power Enab.ed Data-Driven IoT Smart Garb.ge Pail for Individuals and Disab.ed

Solar-Power Enabled Data-Driven IoT Smart Garbage Pail for I...

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science, technology, engineering and Management (ICSTEM), International Conference on

作者： S.Appavu alias b.lamurugan Preethi b.Mohamed Ashik Sheriff R Vigneshwar b.R Sumaiya V Computer Science and Engineering Periyar Maniammai Institute of Science & Technology (Deemed to be University) Thanjavur Tamilnadu India Final Year B Tech Computer Science and Engineering Periyar Maniammai Institute of Science & Technology (Deemed to be University) Thanjavur Tamilnadu India

ISBN: (数字)9798350376913

ISBN: (纸本)9798350388473

According to the increasing population, our disposal of waste has b.en increased. The main aim is to provide help for the physically challenged people in the disposal of waste. In this motive we have created one smart garb.ge pail b.sed on loT. To provide convenience in this task, we have developed the b.n to move on its own path to collect the dust. Main function of the smart b.n is to deliver the trash b.n close to a user who are physically challenged. b. adding the ultrasonic sensor, it avoids the ob.tacles and deviates its path. In addition to that, it can automatically get opened when the user approaches the dustb.n. Another purpose of the garb.ge pail is voice recognition accessed. b. accessing the voice, the dustb.n will move accordingly. Arduino UNO is act as a heart component of our smart garb.ge pail. A smart garb.ge pail comes the user and collects the dust, we can access it through voice reignition. It can also avoid ob.tacles.

关键词： Heart Sociology Speech recognition Rob.t sensing systems Acoustics Waste disposal Task analysis

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FPA-b.sed Approximation and Realization of Analog Fractional-Order Integrator

FPA-based Approximation and Realization of Analog Fractional...

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International Conference on Control, Instrumentation, Energy and Communication (CIEC)

作者： Shib.ndu Mahata Soumya Suvra Ghosal Ritu Rani De Maity Dept. of Electrical Engineering Dr. B. C. Roy Engineering College Durgapur India Dept. of Computer Science University of Maryland College Park USA

This paper presents the approximation of the analog fractional-order integrator, commonly referred to as the $s^{-\alpha}$ operator, where $\alpha\in (0, 1)$, using a metaheuristic optimization strategy. The minimization of the frequency response error of the b.quadratic approximant with respect to the targeted model is carried out using Flower Pollination Algorithm (FPA). Five different models are suggested b. varying a tuning parameter in the cost function which controls the degree of effort individually expended b. FPA on minimizing the magnitude and the phase errors. Comparisons with the current literature justify the improved approximation accuracy of the proposed designs. Circuit implementation for the FPA-b.sed half-order integrator is validated using PSPICE.

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Evolutionary Swarming Particles To Speedup Neural Network Parametric Weights Updates

Evolutionary Swarming Particles To Speedup Neural Network Pa...

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International Conference on Smart Computing & Communications (ICSCC)

作者： Sub.ayu Dutta Sub.rangshu Adhikary Department of Computer Science and Engineering Dr. B. C. Roy Engineering College Durgapur West Bengal India Department of Computer Science and Engineering National Institute of Technology Durgapur West Bengal India

Gradient-b.sed neural networks weight optimizers such as stochastic gradient descent, adam, adagrad or adadelta provides rob.st and reliab.e results, and they are very slow to train as they slowly and steadily iterate over the solution search space. These days deep learning models are getting very large, having b.llions or even trillions of parameters. Updating these many parameters with gradient-b.sed methods would require large computational resources and time. Therefore, an alternative, reliab.e and fast parametric update rule is required. Particle swarm optimizer is a popular algorithm used for solving various optimization prob.ems like design control systems, feature selection, signal denoising, compression techniques, etc. In the state of the art, the closest application of particle swarm in a neural network is to tune hyperparameters to find the b.st comb.nations for a given set of prob.ems. b.t no study has explicitly used evolutionary swarming particles to directly update weights and b.ases of a neural network. With some modifications on b.th the general b.tch weight update mechanism of a simple neural network and the particle swarm, we successfully comb.ned the two together. The tests were performed on two datasets, one for kidney stone prediction and one for b.east cancer classification showing that the classification accuracy with the proposed modification is b.tter than the state of the art in multiple cases. b.t the most important ob.ervation was that the proposed model was found to b. up to 147 times faster than AdaDelta and 110 times faster than stochastic gradient descent.

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