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A task clustering based QoS aware scheduling algorithm for task execution in cloud-Iot model for education services

Multimedia Tools and Applications 2023年第29期82卷 44783-44800页

作者： Chowdhary, Sunil Kumar Rao, A.L.N. Faculty of Computer Science and Engineering Dr. A P J Abdul Kalam Technical University Uttar Pradesh Lucknow India Department of Computer Science and Engineering G.L. Bajaj Institute of Technology and Management Noida India

Some of the conventional approaches to task scheduling are discussed in this section. The scheduling of tasks in the Internet of Things (IoT) application is a complex job in cloud computing due to the heterogeneity characteristics of the IoT. Therefore, an efficient scheduling approach is vital in improving the performance of the Cloud-IoT applications. The improvement in QoS mainly depends on efficient task scheduling and allocating the task to the appropriate Virtual Machine (VM). This paper uses a clustering-based approach to design an optimal solution for task scheduling and VM allocation for IoT applications in education services. The workflow is simplified with horizontal and vertical clustering, and VM is allocated. The task is classified into coarse and fine-grained, based on the average execution time of the total number of tasks. The average execution time is calculated based on the best and worst performance of VM. The vertical clustering approach clusters the tasks into sequential and parallel, thereby turning the huge volume of tasks into simple ones. The horizontal clustering approach selects the VM with the help of a bipartite matching graph which enhances the Quality of Service (QoS). The proposed task clustering has been evaluated in metrics like makespan, response time, throughput, total execution time, task completion time, and VM utilization. The proposed approach achieved a makespan of 2500 ms and throughput of 83 Mbps for 100 tasks, a response time of 0.12 ms, a total execution time of 640 ms, and a total task completion time of 340,000 ms for a 2 arrival rate based on performance evaluation results. © 2023, The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature.

关键词： Quality of service

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Implementation of Secure and Verifiable Access Control Procedures using the NTRU Cryptosystem to Store Big Data in the Cloud Environment

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Recent Patents on engineering 2025年第2期19卷 57-70页

作者： Babu B, Ravindra Saxena, Swati Widjaja, Gunawan Vinodha D, Vedha Omarov, Batyrkhan Ramaiah, Gurumurthy B. Vats, Prashant Adama Ethiopia Department of Computer Science KCG College of Technology Chennai India Universitas Krisnadwipayana Jawa Barat 13077 Indonesia Department of Electronics and Communication Engineering JCT College Of Engineering and Technology Pichanur Coimbatore India International University of Tourism and Hospitality Turkistan Kazakhstan Technical and Vocational Training Institute Addis Ababa Ethiopia Department of Computer Science and Engineering Faculty of Engineering and Technology SGT University Haryana Gurugram India

Background: Due to their complexity and size, deploying ciphertexts for clouds is considered the most useful approach to accessing large data stores. Methods: However, access to a user's access legitimacy and improving a decrypted text on the cloud depending on an improved access policy (AP) specified by the data owner are the key challenges for making large data storage realistic and effective in clouds. The traditional ways either totally remove the problem of AP development or offer renewal to arbiter power, but in real-time, enhancing the AP is essential to maximising security and handling agility. Results: In this patent paper, a safe and verifiable access control program characterised by the NTRU cryptographic system for large storage of data in the clouds is proposed. Primarily, an improved NTRU decryption protocol to deal with the decryption failures of the prime NTRU is established, and in addition, the program is analysed for its security strength and computational performance. When a new AP is specified by the data owner, the cloud server allows the program to improve ciphertext and allows the owner to verify the upgrade to oppose the cloud's fraudulent behaviour. Conclusion: It enables (i) checking the user's legitimacy to access the data owner and qualified users, and (ii) allowing the user to verify the data provided by other users for the recovery of the right user. Strong analysis can prevent and block delinquency from various attacks, namely the collusion attack that could potentially target fraud users. © 2025 Bentham science Publishers.

关键词： Cloud security

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A Review of Blockchain-Based E-Voting Systems: Comparative Analysis and Findings

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2023年第23期17卷 49-67页

作者： Fatih, Rabia Arezki, Sara Gadi, Taoufiq Faculty of Sciences and Techniques Mathematics Computer Science and Engineering Sciences Laboratory Hassan first University of Settat Settat Morocco

The emergence of blockchain has ushered in a significant transformation in information systems research. Blockchain’s key pillars such as decentralization, immutability, and transparency have paved the path for extensive exploration in various research domains. This particular study is focused on electronic voting, aiming to improve voting procedures by making better use of the benefits offered by blockchain technology. Through a comprehensive review of existing literature, we highlight the potential benefits of blockchain-based electronic voting systems such as transparency, security, and efficiency. However, several challenges, such as scalability, personal data confidentiality, and ensuring robust identity verification, persist. Addressing these issues is necessary to unlock the full potential of blockchain-based electronic voting systems, thereby fostering the development of trustworthy election systems in the future. © 2023 by the authors of this article. Published under CC-BY. All Rights Reserved.

关键词： Blockchain

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A Deep Analysis of Medical Monitoring System Based on ESP32 IoT System 3

A Deep Analysis of Medical Monitoring System Based on ESP32 ...

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Kumar Sharma, Govind Tr, Mahesh Dev Bhoomi Uttarakhand University Dept of Computer Science and Engineering Uttarakhand Dehradun India Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350399264

However, to be intact is to emerge, and that is what we tried unsuccessfully to achieve here with in out Iot-enabled patient monitoring built on esp32 task. Efforts to oversee health with relevant Features and sensors, example MAX30102 which it emits light to perceive the concentration of person's blood and also in turn illustrate air pressure, are not new in this era. It assesses the vitals of the patient and sends the information through the internet to the parties involved. Its small size makes it portable and therefore also used everywhere. It is based on IoT principles and helps with illness prevention and accurate general health monitoring. Comparatively speaking to other projects that do comparable services as esp32, it is rather affordable and small. For the Esp8266 we would have had we do not need to utilise Shields. Since Uno is less expensive and has comparable characteristics to the Raspberry Pi series, we chose to utilise it. The effectiveness of the suggested approach depends on variables like minimum errors in Ejection fraction and heart readings. © 2023 IEEE.

关键词： Patient monitoring

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Quantifying Heterogeneity of Complex Networks based on Gintropy and Gini Indices 29

Quantifying Heterogeneity of Complex Networks based on Gintr...

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29th International computer Conference, computer Society of Iran, CSICC 2025

作者： Kouchak, Mohammad Mahdi Emadi Khazaei, Mahsa Safaei, Farshad Department of Computer Engineering Science and Research Branch Islamic Azad University Tehran Iran Faculty of Computer Science and Engineering Shahid Beheshti University Tehran Iran

ISBN: (纸本)9798331523114

Characterizing the heterogeneity of complex networks is a fundamental challenge in studying complex networks. Most of the proposed measures are vertex-degree based, falling short of capturing essential characteristic features of heterogeneous networks. The Gini index is an inequality measure extensively used in economics and the social sciences and Gintropy is a newly proposed inequality measure based on the Gini index. In this paper, we use Gintropy to characterize the heterogeneity of complex networks. Our experimental results show that Gintropy can be effectively used as a heterogeneity index. The benefit of adopting Gintropy as a heterogeneity index is that it accurately quantifies the rich club graph as the most heterogeneous graph. © 2025 IEEE.

关键词： Economic and social effects

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Enhancing Stock Price Prediction: A Hybrid Approach Leveraging Large Language Models and Deep Learning

Enhancing Stock Price Prediction: A Hybrid Approach Leveragi...

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2024 International Conference on computer and Applications, ICCA 2024

作者： Ahmed, Mohamed Erfan Ebrahim, Gamal A. Abdelaal, Marwa A. Ain Shams University Faculty of Engineering Computer and Systems Engineering Department Cairo Egypt Sadat Academy for Management Sciences Faculty of Computers and Information Computer Science Department Cairo Egypt

ISBN: (纸本)9798350367560

Accurate stock price prediction is a challenging yet crucial goal in finance, with significant implications for investment decisions and risk management. This paper presents a comprehensive review of machine learning techniques for stock price prediction, examining traditional methods such as regression and ensemble models, as well as advanced approaches that integrate sentiment analysis and textual data sources. With the emergence of powerful Large Language Models (LLMs) such as ChatGPT, Llama and Gemini, we explore their potential for enhancing predictive accuracy using historical stock data. Key challenges are discussed, including data quality, model interpretability, and adapting to dynamic market conditions. Additionally, this paper proposes a trustworthy stock price prediction model based on LLMs enabling informed investment decision-making. Experimental results demonstrate that ChatGPT-4o model achieved a prediction accuracy of approximately 97%, which can be improved by tuning model parameters. Consequently, the paper highlights the potential of LLMs in improving stock price forecasting. © 2024 IEEE.

关键词： Prediction models

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Research on Citrus Leaf Disease Recognition Using Class-Agnostic Contrastive Learning and Supervised Organizational Mapping

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IEEE Access 2025年 13卷 101592-101608页

作者： Xiao, Wen Shang, Jinxia Li, Fan Ao, Ou Wang, Xin Tian, Shiyi Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650500 China Kunming University of Science and Technology Yunnan Key Lab of Computer Technology Applications Kunming650500 China

Early detection of plant diseases is crucial for enhancing agricultural productivity and ensuring crop protection. While computer vision offers scalable alternatives to manual inspection, existing methods face two understudied challenges: (1) performance degradation in cluttered real-world conditions, and (2) ineffective feature separation for randomly distributed lesions with diverse symptoms. Notably, current research predominantly relies on controlled-environment datasets, lacking publicly accessible benchmarks with authentic field complexities. To address these, we present the first large-scale citrus leaf disease dataset (5,763 images, 6 categories) capturing complex field conditions including varying illumination, occlusion, multi-scale lesions, and deceptive backgrounds. Our key methodological innovations include a three-stage weakly supervised framework that systematically resolves background interference and feature redundancy: (i) Class-agnostic contrastive localization enabling precise lesion mapping without region annotations, (ii) Stable feature initialization through region-guided classification training, (iii) Sparse orthogonal mapping with experimentally-determined nodes introducing orthogonality constraints to enhance feature separation. Through feature alignment and feature fusion, an accuracy of 97.1% is achieved (+2.4% vs ResNet-18). Evaluations on citrus leaf and public datasets demonstrate superior accuracy and interpretable lesion localization, advancing plant disease diagnosis. © 2013 IEEE.

关键词： Citrus fruits

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Optihybrid: a modified firebug swarm optimization algorithm for optimal sizing of hybrid renewable power system

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Neural Computing and Applications 2024年第34期36卷 21517-21543页

作者： Abd El-Sattar, Hoda Kamel, Salah Hashim, Fatma A. Sabbeh, Sahar F. Luxor Higher Institute of Engineering and Technology Luxor85834 Egypt Department of Electrical Engineering Faculty of Engineering Aswan University Aswan81542 Egypt Faculty of Engineering Helwan University Cairo Egypt MEU Research Unit Middle East University Amman1183 Jordan College of Computer Science and Engineering University of Jeddah Jeddah21493 Saudi Arabia Faculty of Computers and Artificial Intelligence Benha University Benha13518 Egypt

In areas where conventional energy sources are unavailable, alternative energy technologies play a crucial role in generating electricity. These technologies offer various benefits, such as reliable energy supply, environmental sustainability, and employment opportunities in rural regions. This study focuses on the development of a novel optimization algorithm called the modified firebug swarm algorithm (mFSO). Its objective is to determine the optimal size of an integrated renewable power system for supplying electricity to a specific remote site in Dehiba town, located in the eastern province of Tataouine, Tunisia. The proposed configuration for the standalone hybrid system involves PV/biomass/battery, and three objective functions are considered: minimizing the total energy cost (COE), reducing the loss of power supply probability (LPSP), and managing excess energy (EXC). The effectiveness of the modified algorithm is evaluated using various tests, including the Wilcoxon test, boxplot analysis, and the ten benchmark functions of the CEC2020 benchmark. Comparative analysis between the mFSO and widely used algorithms like the original Firebug Swarm Optimization (FSO), Slime Mold Algorithm (SMA), and Seagull Optimization Algorithm (SOA) demonstrates that the proposed mFSO technique is efficient and effective in solving the design problem, surpassing other optimization algorithms. © The Author(s) 2024.

关键词： Hybrid power

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Exposing a False Source of News on Social Media by using Machine Learning 14

Exposing a False Source of News on Social Media by using Mac...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Deshmukh, Vaishnavi J. Ambhaikar, Asha Kalinga University Department of Computer Science & Engineering Chattisgarh Raipur India Kalinga University Faculty of Engineering Department of Computer Science and Engineering Chattisgarh Raipur India

ISBN: (纸本)9798350335095

Fake news, or information that seemed false with the intention of misleading the public, has been all too common in recent years. By fostering political polarization and scepticism towards the government, the dissemination of this kind of information harms societal cohesion. Human validation has become impossible due to the massive amount of news being shared on social media, leading to the development and organization of automated methods for spotting false information. To increase the appeal of their publications, fake news publishers employ a number of stylistic strategies, one of which is stirring up reader's emotions. Our proposed methodology for exposing false news by performing feature selection method of Ensemble Bagging Classifier (EBAC), and Ensemble Boosting Classifier (EBOC), Multi-Kernel SVM(MKSVM), to experiment and choose the best fit features to obtain the sensitivity, specificity, Kappa Score, and Matthews Correlation Coefficient (MCC). © 2023 IEEE.

关键词： Fake detection

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Research on IoT-Based Solutions 3

Research on IoT-Based Solutions

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Upadhyay, Ekta Shashikala, H.K. Dev Bhoomi Uttarakhand University Dept of Computer Science and Engineering Uttarakhand Dehradun India Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350399264

IOT is a network of numerous devices, sometimes referred to as "Stuff"online. Prior until recently, the internet is just accessible via basic gadgets like smartphones, and pcs. Now, however, everything is linked to the internet and can speak with one another. The cloud's Iot connects various things. It's a networked system or gadget composed of intelligent devices that connect and interact with others, as well as with roofs and sensors networking protocols. Our lives are made much more clear and secure as a consequence of the massive amount of data that is generated, stored, and utilised for the reasons why it was originally *** organisation needs sophisticated analytics or public knowledge. In such situation, letters and webpages were often utilised. And individuals use the internet to disseminate some many forms of knowledge. © 2023 IEEE.

关键词： Wireless local area networks (WLAN)

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