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

作者： Yadav, Surendra Kaur, Manpreet Vivekananda Global University Department of Computer Science Engineering Jaipur India Chandigarh School of Business Department of Master of Computer Application Jhanjeri India

ISBN: (纸本)9798350399264

The recent growth of Internet-of-Things (IoT) applications using cloud computing has been amazing. One of the advancements is heterogeneous cloud computing, which has made it possible to use the cloud for a range of infrastructure solutions, including multimedia big data. The optimizations of on-premise heterogeneous memory have been the subject of several past studies. However, the performance and financial limits brought on by hardware distributions and manipulative techniques are placing restrictions on the heterogeneous cloud memory. It is an NP-hard combinatorial issue to distribute data jobs across dispersed memory with different capacities. In order to provide high performance cloud-based heterogeneous memory service offerings, this study focuses on this problem and suggests a unique solution called Cost-Aware Heterogeneous Cloud Memory Model. It allocates data to the cloud-based memory via genetic programming. In our suggested method, we take into account a number of important elements that have a significant influence on how well Communication expenses, data transfer operating costs, energy performance, and time constraints all play a role in how cloud memories operate. Finally, we put our suggested paradigm to the test via experimental assessments. The trial findings have demonstrated the viability and scalability of our technique as a cost-conscious cloud-based solution. © 2023 IEEE.

关键词： Genetic algorithms

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Multi-agent QoS-aware autonomic resource provisioning framework for elastic BPM in containerized multi-cloud environment

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Journal of Ambient Intelligence and Humanized Computing 2023年第9期14卷 12895-12920页

作者： Saif, Mufeed Ahmed Naji Niranjan, S.K. Murshed, Belal Abdullah Hezam Al-ariki, Hasib Daowd Esmail Abdulwahab, Hudhaifa Mohammed Department of Computer Applications Sri Jayachamarajendra College of Engineering VTU Mysore India Department of Studies in Computer Science University of Mysore Karnataka Mysore India Department of Computer Science College of Eng. &IT University of Amran Amran Yemen Department of Information Technology Faculty of Engineering and Information Technology Al-ata’a University for Science and Technology Taiz Yemen Department of Computer Networks Engineering and Technologies Sana’a Community College Sana’a Yemen Department of Computer Application Ramaiah Institute of Technology VTU Bangalore India

Cloud computing enables businesses to improve their market competitiveness, enabling instant and easy access to a pool of virtualized and distributed resources such as virtual machines (VM) and containers for executing their business operations efficiently. Though the cloud enables the deployment and management of business processes (BPs), it is challenging to deal with the enormous fluctuating resource demands and ensure smooth execution of business operations in containerized multi-cloud. Therefore, there is a need to ensure elastic provisioning of resources to tackle the over and under-provisioning problems and satisfy the objectives of cloud providers and end-users considering the quality of service (QoS) and service level agreement (SLA) constraints. In this article, an efficient multi-agent autonomic resource provisioning framework is proposed to ensure the effective execution of BPs in a containerized multi-cloud environment with guaranteed QoS. To improve the performance and ensure elastic resource provisioning, autonomic computing is utilized to monitor the resource usage and predict the future resource demands, then resources are scaled based on demand. Initially, the required resources for executing the incoming workloads are identified by clustering the workloads into CPU and I/O intensive, and the local agent achieves this with the help of an initialization algorithm and K-means clustering. Then, the analysis phase predicts the workload demand using the proposed enhanced deep stacked auto-encoder (EDSAE), further, the containers are scaled based on the prediction outcomes, finally, the multi-objective termite colony optimization (MOTCO) algorithm is used by the global agent to find suitable containers for executing the clustered workloads. The proposed framework has been implemented in the Container Cloudsim platform and evaluated using the business workload traces. The overall simulation results proved the effectiveness of the proposed approach compare

关键词： Quality of service

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Intelligent Personality Assessment and Verification from Handwriting using Machine Learning

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International Journal of Information Technology (Singapore) 2024年第7期16卷 4541-4546页

作者： Mishra, Pradeep Kumar Mishra, Gouri Sankar Abidi, Ali Imam Kumar, Rajiv Sahoo, Ashok Kumar Maini, Tarun Department of Computer Science and Application SSET Sharda University Department of Computer Science and Engineering SSET Sharda University NVIDIA AI Learning & amp Research Center Department of Applied Computational Science and Engineering G L Bajaj Institute of Technology and Management Greater Noida Graphic Era Hill University School of Computer Science and Engineering Galgotias University

It is possible to tell a lot about a person just by looking at their handwriting. The way someone writes might tell you a lot about who, they are as a person. There has been a lot of study on the possibility of deducing aspects of a person’s character from their handwriting. In this piece, we’ll look at the different personality qualities and how they might be utilized to make an evaluation. The report includes a dataset showing a correlation between several traits of personality. The Big Five Personality Traits are mapped using handwritten personality data. It was suggested that a comparison table should be used to spot distinctive character quirks. The article includes a review of previous studies and an assessment of the current status of the topic. Handwriting embodies have both creativity and expressiveness. © Bharati Vidyapeeth's Institute of computer applications and Management 2024.

关键词： Agreeableness Conscientiousness Extraversion Neuroticism Openness

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A Multi-Objective Hyper-Heuristic Improved Configuration of Svm Based on Particle Swarm Optimization for Big Data Cyber Security 3

A Multi-Objective Hyper-Heuristic Improved Configuration of ...

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

作者： Shekhawat, Jyoti Tajpal Vivekananda Global University Department of Computer Science Engineering Jaipur India Chandigarh School of Business Department of Master of Computer Application Jhanjeri India

ISBN: (纸本)9798350399264

Big Data Cyber security analytics is a growingly significant field of study and application that uses big data techniques and technology to analyses security event data in order to safeguard networks, computers, and data from illegal access. There have been several reports on Big Data Cybersecurity Analytic Systems in the literature, but an exhaustive and systematic analysis of the research from an architectural viewpoint is lacking. When In this paper, the SVM design process is organized as a bi-objective optimization problem with accuracy and model complexity as two competing goals. The system presents a novel, problem-independent hyper-heuristic framework for bi-objective optimization. It is novel to create a hyper heuristic for this situation. The hyper-heuristic structure proposed comprises of low-level heuristics and a significant level system. In light of the pursuit execution, the significant level system figures out which low-level heuristic ought to be utilized to create another SVM arrangement. Every one of the low-level heuristics look through the SVM design search space really utilizing an alternate arrangement of rules. To estimate the Pareto set of SVM arrangements, the suggested design adaptively combines the benefits of degradation with Pareto-based strategies for dealing with bi-objective enhancement. Microsoft's anomalous intrusion detection and big data malware classification have been used to gauge the efficiency of the suggested methodology. © 2023 IEEE.

关键词： Cybersecurity

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Convolutional Neural Network-Based Anomaly Detection for Cyber Security: A Survey 3

Convolutional Neural Network-Based Anomaly Detection for Cyb...

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

作者： Agarwal, Neha Kaur, Amandeep Vivekananda Global University Department of Computer Science Engineering Jaipur India Chandigarh School of Business Department of Master of Computer Application Jhanjeri India

ISBN: (纸本)9798350399264

There are many security risks as computer and communication technologies continue to advance. To reduce these worries, several different kinds Numerous processes with cyber-security enabled have been developed. Anomaly detection is one of these methods. Finding anomalies involves employing a variety of approaches and procedures to identify various patterns that do not adhere to predetermined characteristics of the entire body of data. Deep learning techniques have recently been accepted as an adequate option due to their capacity to take data properties directly from the data. Convolution neural network (CNN) is employed primarily because it can handle input with many dimensions. This study offers a thorough analysis of the use of CNN as a primary tool for anomaly identification. The majority of the known remedies have been compiled and categorized in the literature. Additionally, this research provides a bound together cross framework that mimics complete anomaly detection methods that were previously offered examinations, as per the information source. In-depth assessment from a brought together cross system upgrades this paper's top to bottom conversation of how CNN is utilized in the writing's response to the irregularity identification issue. Finally, this article makes a number of recommendations for future study areas that the audience may find useful in their own further activities in this area. © 2023 IEEE.

关键词： Anomaly detection

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Groundwater Evaluation with Classification Techniques

Groundwater Evaluation with Classification Techniques

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2023 International Conference on Artificial Intelligence and Smart Communication, AISC 2023

作者： Dogra, Yakesh Khan, Mizan Ali Chandigarh School of Business Department of Master of Computer Application India Sanskriti University Department of Computer Science Engineering Uttar Pradesh Mathura India

ISBN: (纸本)9798350322309

We has researched that your earth area contains % comprised of water and the remaining 28 part also with soil. From the 28 per cent, % water is seawater namely it is excessively salted for consuming, for agricultural production and more critical items. That's because the freshwater which seems utilised is extremely small in bulk and its condition is every day growing worse. The condition of the water must be kept since it is a crucial life factor not just the individuals as well as other creatures and flora. Humans demand a suitable level sustained liquid to consume and employ in varied daily tasks Assessments of groundwater recharge and assessment are thus essential for the development of economy and society. Photogrammetry is now a crucial technique for ground component assessment as a result of advances. So to assure if the groundwater we get is excellent or wouldn't we have gathered a set and used multiple Ml techniques to assess the auc. So, the research intends to determine the prognosis of water whether it is of good standard or not by utilizing two algorithms, rbfnn and perceptron and to demonstrate which outperforms. © 2023 IEEE.

关键词： Support vector machines

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Next Generation Digital Health Monitoring System Using Artificial Neural Network 5

Next Generation Digital Health Monitoring System Using Artif...

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5th IEEE International Conference on Recent Trends in computer Science and Technology, ICRTCST 2024

作者： Kadayat, Yunika Sharma, Sachin Painuly, Sakshi Graphic Era Deemed to be University Department of Computer Science and Engineering Dehradun India Graphic Era Deemed to be University Graphic Era Hill University Department of Computer Science and Engineering Dehradun India Graphic Era Hill University Department of Computer Application Dehradun India

ISBN: (纸本)9798350351378

By empowering early identification and provoke reaction within the occasion of health irregularities, another era digital health monitoring systems are basic to guaranteeing people's prosperity. ANNs, or artificial neural networks, have become successful devices for making exact and successful health monitoring systems. This ponder offers a careful examination of how ANNs are utilized in health monitoring systems. It covers the standards of ANNs, considers how they fit into systems for health monitoring, gives case illustrations, and talks around the obstacles and up and coming advancements in this region. © 2024 IEEE.

关键词： Neural networks

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An Analysis of Edge Computing with Multi Access in 5-G Technology 3

An Analysis of Edge Computing with Multi Access in 5-G Techn...

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

作者： Gupta, Sitaram Sonia Vivekananda Global University Department of Computer Science Engineering Jaipur India Chandigarh School of Business Department of Master of Computer Application Jhanjeri India

ISBN: (纸本)9798350399264

The demands of the rapidly expanding internet. However, since most end users have confined storage space and limiting computing power, it lately evolved into a natural issue how to execute computationally complex apps on resource-bound consumers. The emerging fifth generation (5G) corporation can benefit from Mobile Edge Computing (MEC) innovation upgrade portable assets by facilitating figure concentrated applications, handling a lot of information prior to sending them to the cloud, finding distributed computing assets inside the radio access organization (RAN) close to versatile clients, and giving setting mindful administrations utilizing RAN information. In reality, the paradigm shift from 4G to 5G is accompanied by the introduction of new technical concepts. We first give a comprehensive introduction of MEC technology and some of its possible applications. The most recent research on MEC integration with upcoming technologies that will be employed in 5G and beyond is then is summarized. © 2023 IEEE.

关键词： Mobile edge computing

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Studying the Effect of an Online Realm Based on Wearable Technology on Learners' Understanding

Studying the Effect of an Online Realm Based on Wearable Tec...

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2023 International Conference on Artificial Intelligence and Smart Communication, AISC 2023

作者： Kirti Ali Khan, Mizan Chandigarh School of Business Department of Master of Computer Application India Sanskriti University Department of Computer Science Engineering Uttar Pradesh Mathura India

ISBN: (纸本)9798350322309

An interactive system called imperative (AR) creates a realistic and genuine educational and learning environment. The latest crop clearly prefers innovation training over conventional teaching methods. Studies on scientific test techniques are still lacking, despite the fact that earlier research on virtual reality has shown some information on how it might enhance learning results in several subjects. Students need experimental information to better understand the phenomenon. The page discusses the steps involved in constructing & implementing a mobile application for a lab experiment that makes use of augmented reality technology. An extra educational resource for high school seniors is this. The prime purpose of this mobile-based augmented reality program for a scientific experiment is to provide thorough information in addition to conventional processes and educational materials. The experiments that will be shown in ElectroAR include a number of them. An professional review is conducted to evaluate input. In the future, user testing of ElectroAR in actual classroom environments will be conducted. © 2023 IEEE.

关键词： Students

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A Bioinspired Method for Optimal Task Scheduling in Fog-Cloud Environment

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computer Modeling in engineering & Sciences 2025年第3期142卷 2691-2724页

作者： Ferzat Anka Ghanshyam G.Tejani Sunil Kumar Sharma Mohammed Baljon Data Science Application and Research Center(VEBIM) Fatih Sultan Mehmet Vakif UniversityIstanbul34445Turkiye Department of Industrial Engineering and Management Yuan Ze UniversityTaoyuan320315Taiwan Applied Science Research Center Applied Science Private UniversityAmman11937Jordan Department of Information System College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia

Due to the intense data flow in expanding Internet of Things(IoT)applications,a heavy processing cost and workload on the fog-cloud side become *** of the most critical challenges is optimal task *** this is an NP-hard problem type,a metaheuristic approach can be a good *** study introduces a novel enhancement to the Artificial Rabbits Optimization(ARO)algorithm by integrating Chaotic maps and Levy flight strategies(CLARO).This dual approach addresses the limitations of standard ARO in terms of population diversity and convergence *** is designed for task scheduling in fog-cloud environments,optimizing energy consumption,makespan,and execution time simultaneously three critical parameters often treated individually in prior *** conventional single-objective methods,the proposed approach incorporates a multi-objective fitness function that dynamically adjusts the weight of each parameter,resulting in better resource allocation and load *** analysis,a real-world dataset,the Open-source Google Cloud Jobs Dataset(GoCJ_Dataset),is used for performance measurement,and analyses are performed on three considered *** are applied with well-known algorithms:GWO,SCSO,PSO,WOA,and ARO to indicate the reliability of the proposed *** this regard,performance evaluation is performed by assigning these tasks to Virtual Machines(VMs)in the resource *** are performed on 90 base cases and 30 scenarios for each evaluation *** results indicated that the proposed algorithm achieved the best makespan performance in 80% of cases,ranked first in execution time in 61%of cases,and performed best in the final parameter in 69% of *** addition,according to the obtained results based on the defined fitness function,the proposed method(CLARO)is 2.52%better than ARO,3.95%better than SCSO,5.06%better than GWO,8.15%better than PSO,and 9.41%better than WOA.

关键词： Improved ARO fog computing task scheduling GoCJ_Dataset chaotic map levy flight

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