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MCWOA Scheduler:Modified Chimp-Whale Optimization Algorithm for Task Scheduling in Cloud Computing

computers, Materials & Continua 2024年第2期78卷 2593-2616页

作者： Chirag Chandrashekar Pradeep Krishnadoss Vijayakumar Kedalu Poornachary Balasundaram Ananthakrishnan School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India Center for Cyber Physical Systems School of Computer Science and EngineeringVellore Institute of TechnologyChennai600127India

Cloud computing provides a diverse and adaptable resource pool over the internet,allowing users to tap into various resources as *** has been seen as a robust solution to relevant challenges.A significant delay can hamper the performance of IoT-enabled cloud ***,efficient task scheduling can lower the cloud infrastructure’s energy consumption,thus maximizing the service provider’s revenue by decreasing user job processing *** proposed Modified Chimp-Whale Optimization Algorithm called Modified Chimp-Whale Optimization Algorithm(MCWOA),combines elements of the Chimp Optimization Algorithm(COA)and the Whale Optimization Algorithm(WOA).To enhance MCWOA’s identification precision,the Sobol sequence is used in the population initialization phase,ensuring an even distribution of the population across the solution ***,the traditional MCWOA’s local search capabilities are augmented by incorporating the whale optimization algorithm’s bubble-net hunting and random search mechanisms into MCWOA’s position-updating *** study demonstrates the effectiveness of the proposed approach using a two-story rigid frame and a simply supported beam *** outcomes reveal that the new method outperforms the original MCWOA,especially in multi-damage detection *** excels in avoiding false positives and enhancing computational speed,making it an optimal choice for structural damage *** efficiency of the proposed MCWOA is assessed against metrics such as energy usage,computational expense,task duration,and *** simulated data indicates that the new MCWOA outpaces other methods across all *** study also references the Whale Optimization Algorithm(WOA),Chimp Algorithm(CA),Ant Lion Optimizer(ALO),Genetic Algorithm(GA)and Grey Wolf Optimizer(GWO).

关键词： Cloud computing scheduling chimp optimization algorithm whale optimization algorithm

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Performance Investigation of HFR Full-bridge Inverter in Resonant Inductive Coupled Power Transfer System for an Electric Vehicle

EAI Endorsed Transactions on Energy Web

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EAI Endorsed Transactions on Energy Web 2024年 11卷 1-9页

作者： Geetha, P. Usha, S. Department of Electrical and Electronics Engineering SRM Institute of Science and Technology Kattankulathur Chennai603203 India

Inductive WPT of the resonant category is generally employed for medium and high-power transmission applications like electric vehicle charging due to it contributes excellent efficiency. The high-frequency resonant full-bridge inverter using series-series resonant topology is proposed. The design of the high-frequency resonant inverter is simulated and verified by MATLAB/SIMULINK software. The charging scheme which is available in the AC-DC as well as in the DC-DC converter should operate with the two steps to achieve a duty cycle-based voltage control and hysteresis current control. The resonant frequency of the proposed system has a frequency range of 65 kHz with a DC voltage of 12V. The simulation has been carried out successfully and transmitted a 5KW power load of constant current and voltage control. The Performance chart of with the existing method is carried out in terms of parameters and the efficiency can be achieved by 95%. © (2024), (European Alliance for Innovation). All Rights Reserved.

关键词： Electric vehicles

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Stability of a Jensen Type Cubic and Quartic Functional Equations over Non-Archimedean Normed Space

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IAENG International Journal of Applied Mathematics 2024年第2期54卷 149-154页

作者： Ramachandran, A. Sangeetha, S. Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur Chengalpattu603 203 India Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur Chengalpattu603 203 India

In this paper, we introduce the cubic and quartic Jensen type functional equations: (Formula presented) and discussed the Hyers-Ulam stability over non-Archimedean normed space. © 2024, International Association ... 详细信息

关键词： Functional analysis

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Apple Leaf Disease Detection Using Transfer Learning

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Annals of Data science 2025年第1期12卷 213-222页

作者： Wani, Ozair Ahmad Zahoor, Umer Shah, Syed Zubair Ahmad Khan, Rijwan Department of Computer Science & Engineering Islamic University of Science and Technology Jammu & Kashmir Awantipora India Department of Computer Science and Engineering ABES Institute of Technology Uttar Pradesh Ghaziabad India

Automated detection of plant diseases is crucial as it simplifies the task of monitoring large farms and identifies diseases at their early stages to mitigate further plant degradation. Besides the decline in plant health, reduced production severely impacts the country’s economy. Traditional disease identification methods, relying on human experts, are slow, time-consuming, and impractical for large farms. Our proposed model utilizes a combination of pre-trained Resnet18, Alexnet, GoogLeNet, and VGG16 networks to classify apple tree leaves into categories such as healthy, black rot, apple cedar rust, and apple scab based on images. Various image enhancement techniques were employed to enhance the model’s accuracy. Ultimately, our model achieved an accuracy of 97.25% on the validation dataset, demonstrating excellent performance across various metrics. This suggests its potential for efficient and accurate plant health monitoring in the agricultural sector. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Convolutional neural networks

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Smart Fish Farming Recommendation System using K-Means Algorithm 13

Smart Fish Farming Recommendation System using K-Means Algor...

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13th International Conference on Cloud Computing, Data science and engineering, Confluence 2023

作者： Praba, M.S. Bennet Roy, Sayanti Reddy, Mopuru Sahithi Yadav, Ishita Srm Institute of Science and Technology Computer Science and Engineering Chennai India

ISBN: (纸本)9781665462631

A pressing problem in fish farming is the shortage of high-quality stock. These fish now can be raised in ponds using hormonal stimulation as a treatment for this problem. The supply of pure fish stock in the required numbers has been guaranteed as a result. The purpose of our project is to help people predict the best type of fish to be cultivated in the habitat depending on the environmental variables and to help people do efficient fish farming or fish culture. Using Data Visualization and Data Processing, Unsupervised Algorithms and analyze the clustering of unlabeled datasets by K Means Clustering Algorithm and Hierarchical Algorithm. Finally, applying Logistic Regression to real-world problems to check the type of fish that will be suitable to cultivate in the habitat according to the input details about the cultivable area. The project aims to improve the ability of fish farmers to monitor, control, and document key factors affecting fish production. © 2023 IEEE.

关键词： Fish

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Fault classification and identification through machine learning approaches for a solar PV – battery based water pumping system

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Multimedia Tools and Applications 2025年第14期84卷 13843-13864页

作者： Sowmmiya, U. Abinaya, K. Jhunjhunwala, Rishik Satpathy, Prateek Arul, R. Department of Electrical and Electronics Engineering SRM Institute of Science and Technology Kattankulathur India Department of Electrical and Electronics Engineering Vellore Institute of Technology Chennai India

The world progresses towards enabling renewable sources into the mainstream supply of energy and it is imperative to develop systems that can handle new challenges and disturbances. This paper aims at machine learning model-based fault identification and classification of an islanded Solar PV – battery integrated system feeding a water pumping system. The system is powered through solar PV and battery (discharge mode) which are controlled through Semi Pilot Cell based Fractional Open Circuit Voltage (SFOCV) method and conventional voltage control method respectively. The water pumping system is simulated using MATLAB which is interfaced with RT-LAB software for extracting the real-time data from the OPAL – RT Controller (OP4510) through Software-in-Loop (SiL) approach. All possible faults associated with a stand-alone solar PV-battery system are aggregated to execute the machine learning model. This data is pre-processed and the distribution plots are observed to describe the statistical nature of the data. The processed data is then used to train a Logistic Regression (LR) Model and Artificial Neural Network (ANN) Model to identify whether there is a fault or non-fault condition (Binary Classification) and then classify which fault case has occurred (Multi-class Classification). The models are trained and validated in the controller. The resulting comparative parameters such as accuracy and kappa values indicate that ANN model proves to be a better solution for fault identification and classification. Also, the cost functions (error) seem to be less in ANN model and the comparative results are discussed in this work. The proposed intelligent, fault identification and classification model being implemented with real-time data ensures reliability and immediate indication to the stakeholders on the status of the fault in the system. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： MATLAB

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Analyzing Blockchain technology for Enhancing Security in Smart Home Systems: Current Developments and Future Directions 3

Analyzing Blockchain Technology for Enhancing Security in Sm...

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3rd International Conference on Disruptive Technologies, ICDT 2025

作者： Soni, Shiva Singh, Abhilasha Srm Institute of Science and Technology Department of Computer Science and Engineering Delhi-NCR Campus Modinagar Ghaziabad India

ISBN: (纸本)9798331519582

The Internet of Things (IoT) holds a great potential in revolutionizing the development of intelligent home environments. The Internet of Things is seamlessly integrated into our everyday routines, especially in modern smart homes, where it aids in streamlining resource management, enabling convenient remote control, and facilitating pervasive sensing. The use of smart home technology presents a significant challenge due to the range of issues it can cause, including concerns about transparency, security and privacy. The main reason for this is that devices are often used in open networks that may be susceptible to security breaches, due to inadequate device authentication methods, inefficient secure data storage and access procedures, and exposure to various threats. Blockchain shows great potential as a technology that can effectively tackle these challenges and fulfill the necessary criteria. This research study introduces a hybrid blockchain architecture, dynamic key management techniques, cross-domain authentication and lightweight cryptographic solutions to address critical IoT constraints, including security, scalability, latency, interoperability and energy efficiency, providing a unique contribution to advancing smart home security frameworks. In this paper, we studied and analyzed the various research works already done and provided a comprehensive review of current advancements, highlighted the major progress and discussed open challenges for future research directions. © 2025 IEEE.

关键词： Smart homes

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Driving Efficiency: A Literature Review of Energy-Efficient Data Collection Strategies for Mobile Sink-Based Wireless Sensor Network 1

Driving Efficiency: A Literature Review of Energy-Efficient ...

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1st International Conference on Computing, sciences and Communications, ICCSC 2024

作者： Upadhyay, Priyanka Meena, Uma Rana, Kamlesh SRM Institute of Science and Technology Department of Computer Science and Engineering Uttar Pradesh Modinagar India Bharat Institute of Technology and Science Department of Computer Science and Engineering Uttar Pradesh Meerut India

ISBN: (纸本)9798350353648

Portable sinks assume a vital part in information assortment within wireless sensor networks (WSNs), offering dynamic and flexible solutions to address the limitations of static sink-based architectures. Unlike their static counterparts, mobile sinks have the capability to traverse the network, adapt their trajectories, furthermore, gather information straightforwardly from sensor hubs. This versatility empowers a few critical benefits in information assortment proficiency, energy streamlining, and network execution upgrade. This survey paper presents an extensive outline of the writing on energy-effective information assortment plans for portable sink- based remote sensor organizations (WSNs). With the expansion of Web of Things (IoT) applications, WSNs have become integral for collecting data from the environment in various domains. However, traditional static sink-based approaches suffer from energy imbalances and limited network lifespans. The integration of mobile sinks offers a promising solution to these challenges by enabling dynamic data collection and energy-efficient routing. © 2024 IEEE.

关键词： Data collection

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Mobility Stick with Haptic Feedback for People with Vision Impairments

Mobility Stick with Haptic Feedback for People with Vision I...

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2024 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication, IConSCEPT 2024

作者： Raghul, J. Durga Devi, K. Sreya, M. Maithreye, S. SRM Institute of Science and Technology Department of Electronic and Computer Engineering Chennai Ramapuram India SRM Institute of Science and Technology Department of Electronics and Communication Engineering Chennai Ramapuram India

ISBN: (纸本)9798331540685

In this research, haptic motor, Node MCU, ultrasonic sensors are used to address the problem associated with the current walking stick for visually disabled people. These problems include disturbing their main sense of survival which is hearing. Hence, a system containing ultrasonic sensors, haptic motor and Internet of Things has been recommended in this study. This study illustrates that the implementation of haptic motors and ultrasonic sensors can successfully address the major issues that current alternatives face and it has a positive ad significant impact on visually disabled people. Using this method, one can monitor the person's movement and whether they fell down. This system makes use of IoT it integrate the data from sensors and update it onto the website for other person monitoring. © 2024 IEEE.

关键词： Ultrasonic sensors

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Milk Quality Prediction by Using a Supervised Machine Learning Algorithm and Arduino Uno 8th

Milk Quality Prediction by Using a Supervised Machine Learni...

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8th International Conference on Information System Design and Intelligent Applications, ISDIA 2024

作者： Priyadharshini, S. Sanjana, Neelapa Reddy Yoghasree, R.B. Ramkumar, K. Department of Computer Science SRM Institute of Science and Technology Chennai India

ISBN: (纸本)9789819765805

Adulteration of milk is common and observed recently with water and other substances like urea, whey, and some harmful substances in some cases. Existing instruments have some cons as they require procedures to be followed by skilled laborers and other related factors. Thus, the analysis of the quality of milk is performed to address this issue. In this study, the milk quality prediction is performed on applying Machine Learning algorithms. On comparing supervised machine learning algorithms like logistic regression, MP classifier, logistic regression, and random forest algorithm, it was concluded that XGBoost Classifier produced higher accuracy. Additionally, a connection is created between an arduino uno board that is given the instructions and connected with four sensors to measure the parameters and send them to the dataset through RS232 protocol. Then the values in the dataset are trained and tested using the machine learning algorithms resulting in a prediction thereby. This study overall helps with creating an effective and feasible outcome by reduction of manual processes. From milk factories to an ordinary milk consumer, this study provides an effective implication as it cuts down the complexity and requirement of skilled laborers by introducing instant prediction mechanisms in real time. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Logistic regression

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