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检索条件"任意字段=IEEE International Conference on Progress in Informatics and Computing"

共 16086 条记录，以下是71-80 订阅

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Load Balancing and Task Scheduling Methods in Cloud computing - A Review 7

Load Balancing and Task Scheduling Methods in Cloud Computin...

引用

7th international conference on Contemporary computing and informatics, IC3I 2024

作者： Makkar, Rashmi Mangla, Neeraj Cse Department Mullana Haryana Ambala India Panipat Institute of Engineering & Technology Department of Information Technology Haryana Panipat India

ISBN: (纸本)9798350350067

Nowadays, Cloud computing is an evolutionary method which gives on-demand flexible and scalable properties by pay-per-utilize model. Several companies are constructing extra data centres and moving their operations to the cloud because of the cloud flexibility. To assure optimal resource usage and reduce resource waste, these businesses required appropriate load-balancing. Requirements for optimal resource allocation include effective load-balancing and task scheduling. Effective scheduling combined with load-balancing maximizes the Quality of Service (QoS) metrics and divides resources in a balanced manner. The most effective approach to load-balancing is task migration. The research work will introduce a hybrid optimization method to improve the existing challenges and problems. The proposed work will define remarkable enhancements in response time as well as resource utilization parameters, etc. © 2024 ieee.

关键词： Cloud platforms

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On the Combinatorial Property of One Class of Groups 27

On the Combinatorial Property of One Class of Groups

引用

27th international conference on Soft computing and Measurements, SCM 2024

作者： Dobrynina, Irina V. Moscow Technical University of Communications and Informatics Department of Mathematical Analysis Moscow Russia

We consider the finite generation of an isolator of a subgroup with a finite number of generators from an Artin group generated by two elements, and indicate an effective procedure for its construction. © 2024 ieee.

ISBN: (纸本)9798350363708

关键词： Artin group combinatorial properties isolator subgroup

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DNN-Based Speech Enhancement on Microcontrollers

DNN-Based Speech Enhancement on Microcontrollers

引用

2024 ieee international conference on Communications, computing, Cybersecurity and informatics, CCCI 2024

作者： Kokhazad, Zahra Bournas, Charalampos Gkountelos, Dimitrios Keramidas, Georgios School of Informatics Aristotle University of Thessaloniki Thessaloniki Greece An Applied Materials Company Think Silicon S.A. Patras Greece

ISBN: (纸本)9798350349832

Deep Neural Networks (DNNs) have made remarkable advances across various domains, capturing the interest of researchers, also in the fields of signal processing and speech enhancement (SE). This growing of attention has led to numerous studies focusing on developing and improving models for SE. One of the persistent challenges in the area is in designing a lightweight model (in terms of memory and computation requirements) that still delivers satisfactory results in terms of sound quality. In this paper, we present a lightweight, DNN-based SE model that offers significantly less computations than the current state-of-The-Art SE models. By following a step-by-step approach, we re-evaluate the impact of various parts of typical SE models revealing the trade-offs between speech quality and computational costs. Assuming a single-core, 200MHz microcontroller device, our SE model can achieve real-Time SE performance (less than 3M Multiply-Accumulate operations, MACs) with a small degradation in SE capabilities compared to state-of-The-Art SE models. © 2024 ieee.

关键词： Noise abatement

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Synergy of Value Engineering and Green Energy Systems in Innovating Building Construction 10

Synergy of Value Engineering and Green Energy Systems in Inn...

引用

10th international conference on Smart computing and Communication, ICSCC 2024

作者： Kumara, I Nyoman Indra Ariana, I Komang Agus Tapa, I Gede Fery Surya Cipta Indrashwara, Decky Putu Merta Karunia Putri, Luh Putra, I Ketut Anzas Dwi Anggara Universitas Pendidikan Nasional Faculty of Engineering and Informatics Denpasar Indonesia

ISBN: (纸本)9798350363104

This research explores the synergistic integration of value engineering methods and green energy systems in Denpasar Health Polytechnic building construction innovations. The application of value engineering methods using Dell'Isola Theory in material substitution methods functions as a structured framework to streamline project value by balancing quality, performance and cost, while green energy systems emphasize development sustainability and energy efficiency. Through careful analysis and strategic application, this research explains how the combination of these methodologies improves cost efficiency, sustainability, and performance in building construction projects. These findings underscore the potential for innovation and progress in creating built environments that are environmentally conscious and economically viable. In addition, the integration of green energy systems not only increases energy efficiency but also contributes to reducing environmental impacts and supports sustainable development goals. © 2024 ieee.

关键词： Green buildings

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Dynamic Load Balancing for Enhanced Resource Utilization in IaaS Cloud computing 7

Dynamic Load Balancing for Enhanced Resource Utilization in ...

引用

7th international conference on Contemporary computing and informatics, IC3I 2024

作者： Kumar, Anshul Mathur, Sandeep Malviya, Adarsh Noida International University Department of Computer Science in School of Science Uttar Pradesh Noida India Amity University Amity School of Engineering and Technology Uttar Pradesh Greater Noida India Dronacharya Group of Institutions Department of Computer Science Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350350067

Efficient load balancing is vital in cloud computing to optimize resource use, enhance performance, and maintain application availability. Traditional methods often underutilize the scalability of IaaS models. Hence, a dynamic load balancing system is crucial for real-time traffic distribution among IaaS servers based on demand and resource availability. High traffic challenges in web hosting can degrade load times. Dynamic server load balancing is pivotal here. Our approach integrates ASA genetic algorithms with process scheduling. It queues and assigns requests randomly to virtual servers, verifying connections. A genetic algorithm optimizes schedules via selection, crossover, and mutation, iterating for the best schedule. This strategy markedly reduces load times and maximizes system performance. © 2024 ieee.

关键词： Dynamic scaling IaaS Load Balancing Web Services Virtual server

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Fuzzy computing in Healthcare

Fuzzy Computing in Healthcare

引用

2024 international Visualization, informatics and Technology conference, IVIT 2024

作者： Khushal, Rabia Fatima, Ubaida Ned University of Engineering and Technology Department of Mathematics Karachi Pakistan

ISBN: (纸本)9798350354447

Fuzzy computing, a computational intelligence technique can be employed in the healthcare industry for numerous purposes. The dataset available consists of several features that are equivalently important for the prediction or diagnosis however inclusion of all important features takes a large computation time. Application of fuzzy computing compares the binary variable features thus providing a vast set of values for the prediction of output moreover since two features are transformed into one the number of features is reduced hence taking less computation time for the computation of output. A healthy lifestyle is crucial to live a longer life. In this research work, fuzzy computing is applied to the healthcare dataset which is the healthy lifestyle dataset. Machine learning techniques which are random forest, k-nearest neighbors, and adaptive boosting are applied to the normal dataset and then these techniques are applied to the fuzzy modified dataset thus a fuzzy computing model is proposed in which machine learning techniques are utilized for inference and generation of fuzzy output that is defuzzified subsequently and provides crisp output. Machine learning techniques without fuzzy computing take more computation time for computation of the output moreover it doesn't consider the uncertainty of the binary input variables. However, machine learning techniques with fuzzy computing lead to a reduction of computation time and consideration of more features which provide a vast set of values for diagnosis of whether the individual is living a healthy lifestyle or unhealthy lifestyle. © 2024 ieee.

关键词： Electronic health record

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Exploring the Frontier of Technological progress in Plant Biotechnology 6

Exploring the Frontier of Technological Progress in Plant Bi...

引用

6th international conference on Contemporary computing and informatics, IC3I 2023

作者： Aggarwal, Aarohi Mehta, Ankit Saraswat, Manish Shekhar Independent Researcher Haryana Panchkula India Lloyd Institute of Engineering & Technology Greater Department of Computer Science Uttar Pradesh Noida India

ISBN: (纸本)9798350304480

Innovative solutions to major issues in agriculture and sustainability are now available because of the fusion of bio-inspired computing and plant biotechnology. This study examines how genetic algorithms and neural networks, two bio-inspired technologies, can be used to improve crop qualities, forecast plant responses, and manage crops more effectively. We demonstrate their potential influence on developing plant biotechnology by discussing their benefits and applications to conventional approaches. We showcase effective implementations, ranging from better planting schedules to creating disease-resistant crops. Its capabilities are further enhanced by combining omics and phenotyping technologies with bio-inspired computing. We discuss issues including data integration difficulties and moral concerns with regard to genetically modified creatures. Computer scientists and biotechnologists will be able to work together thanks to this multidisciplinary approach. In summary, we can conclude that combining bio-inspired computing with plant biotechnology has the potential to advance sustainable agriculture. This combination offers a crucial step toward resilient food systems and environmental stewardship as we move toward precision farming. © 2023 ieee.

关键词： Bio-inspired computing Biofortification Bioinformatics and Analytics CRISPR-Cas Genome Editing Nanotechnology Plant-Machine Interfaces Synthetic Biology Techniques

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Multimodal Contrastive Learning for Protein-Protein Interaction Inhibitor Prediction

Multimodal Contrastive Learning for Protein-Protein Interact...

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2024 ieee international conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Zhang, Zitong Wang, Zhixian Zhao, Lingling Wang, Junjie Wang, Chunyu Harbin Institute of Technology Faculty of Computing Harbin China Nanjing Medical University School of Biomedical Engineering and Informatics Department of Medical Informatics Nanjing China

ISBN: (纸本)9798350386226

Protein-protein interactions (PPIs) are crucial for various cellular activities and disease development, and modulating PPIs using small molecule inhibitors (PPIIs) has gradually become a promising therapeutic strategy. Recently, researchers have proposed several machine learning methods to screen PPIIs, but most of the works focused on unimodal representations of molecules or combining multimodal features in a naive splicing manner. Meanwhile, current research progress is being slowed by the lack of large-scale PPII datasets. To address these issues, we propose MCLPPII, a unified multimodal contrastive learning framework for PPII prediction. MCLPPII extracts comprehensive molecular information from four modalities and effectively combines them through an adaptive feature fusion method. Furthermore, we propose a three-stage training strategy to enhance the PPII prediction capability of MCLPPII by leveraging self-supervised pre-training on a large unlabeled dataset. We evaluate MCLPPII on nine PPI targets and two downstream tasks, including the PPI inhibitor identification task and potency prediction task. Experimental results show that MCLPPII achieves competitive performance. The source code and datasets are freely available at https://***/1zzt/MCLPPII. © 2024 ieee.

关键词： Contrastive Learning

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MFC based Smart Irrigation System using IoT and Machine Learning 6

MFC based Smart Irrigation System using IoT and Machine Lear...

引用

6th international conference on Mobile computing and Sustainable informatics, ICMCSI 2025

作者： Chaitanya, Manne Sai Uday Kiran Reddy, B. Sreekumar, K. Amaran, Sibi Department of Computing Technologies Technologies SRM Institute of Science and Technology Kattankulathur Chennai603203 India Department of Computing SRM Institue of Science and Technology Kattankulathur Chennai603203 India

ISBN: (纸本)9798331522667

This research study proposes a novel Smart Irrigation System that integrates Microbial Fuel Cells (MFCs) with IoT and Machine Learning for sustainable agricultural practices. The system uses MFCs to generate electricity from soil microorganisms, providing a renewable energy source for irrigation. IoT sensors monitor real-time environmental parameters such as temperature, humidity, and soil moisture, and transmit data to cloud platforms for analysis. Machine learning algorithms are used to process the historical data, weather forecast, and sensor information in real-time to predict the irrigation requirement and optimize water usage. Renewable energy generation, IoT-based monitoring, and machine learning-driven decision support strategy are integrated in this system to improve water efficiency, reduce energy consumption, and support sustainable agricultural practice. © 2025 ieee.

关键词： Smart agriculture

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progress in nanofabrication of superconducting devices and diverse applications

Progress in nanofabrication of superconducting devices and d...

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ieee international Magnetics conference (INTERMAG)

作者： Rebello, A. Klein, N. Y. Ruela, L. M. Martins, E. Rouxinol, F. Oliveira, I. S. Sinnecker, J. P. Ctr Brasileiro Pesquisas Fis Dept Condensed Matter Rio De Janeiro RJ Brazil Univ Estadual Campinas Inst Phys Glebb Wattagin Lab Quantum Devices Phys Campinas Brazil CENPES Rio De Janeiro RJ Brazil

ISBN: (纸本)9798350362213;9798350362220

Superconducting circuits have emerged as a highly promising platform for quantum computing, among other divices based on Josephson junctions. The fabrication and testing of these devices requires especiallized nanofabrication facilities and milikelvin range testing equipment. In the search for the fabrication of these devices we have ran into limitations which forced us into creative solutions for the fabrications of these superconducting circuits and Josephson Junctions. Furthermore the development of these technologies allows for application in a wide range of research fields such as quantum computing, magnonics, micro-electromechanical systems and more.

关键词： Superconducting Qubit Josephson Junction Quantum computing

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