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检索条件"任意字段=Proceedings of the 6th International Conference on Algorithms, Computing and Systems"

共 6569 条记录，以下是621-630 订阅

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proceedings of CONECCT 2020 - 6th IEEE international conference on Electronics, computing and Communication Technologies

Proceedings of CONECCT 2020 - 6th IEEE International Confere...

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6th IEEE international conference on Electronics, computing and Communication Technologies, CONECCT 2020

ISBN: (纸本)9781728168289

the proceedings contain 255 papers. the topics discussed include: intelligent DDoS detection system in software-defined networking (SDN);enhancing QoS in a university network by using containerized generic cache;integrated Li-ion battery and super capacitor based hybrid energy storage system for electric vehicles;high-Q embedded LTCC inductors for high performance RF MCMs;deep learning-based LAP deployment and aerial infrastructure sharing in 6g;effect of temperature on the electrical characteristics of all silicon p-n-i-n TFET device;reconfigurable circuits based on single gate reconfigurable field-effect transistors;restoration of digital design using row and column major parsing a technique;novel high gain common grounded Z-source DC-DC converter;deep learning-based architecture for social anxiety diagnosis;and robotic vehicle for automated detection of leaf diseases.

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2023 international conference on Cloud computing and Artificial Intelligence: Technologies and Applications, CloudTech 2023

2023 International Conference on Cloud Computing and Artific...

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6th IEEE international conference on Cloud computing and Artificial Intelligence: Technologies and Applications, CloudTech 2023

ISBN: (纸本)9798350303063

the proceedings contain 36 papers. the topics discussed include: towards an IoT architecture based on machine learning for missing data prediction on the edge;a survey on recent intrusion detection systems in cloud environment;advancing breast cancer diagnosis with machine learning: exploring data balancing, feature selection, and Bayesian optimization;using serverless FaaS for invoking long-running jobs;security governance in IOT environment: a state of art;data-driven approach for residential occupancy modeling using PIR sensors: a Moroccan case study;attempts in worst-case optimal joins on relational data systems: a literature survey;assessing digital government maturity model for developed countries. application to Singapore;evaluation and analysis of network safety mechanisms in SDN infrastructure;comparison of a FaaS- and SaaS-based ETL process in a cloud environment;and sentiment analysis applied to Arabic tweets using machine learning and deep learning.

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Developing a Smart Drip Infusion System to Elevate Precision in Healthcare 4

Developing a Smart Drip Infusion System to Elevate Precision...

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4th international conference on Ubiquitous computing and Intelligent Information systems, ICUIS 2024

作者： Molefinyane, Sefemo Yahya, Abid Hamsadhwani, V. Rohini, R. Samikannu, Ravi Begam, K.Maruliya Botswana International University of Science and Technology Department of Electrical and Communications Systems Engineering Palapye Botswana Periyar Maniammai Institute of Science and Technology Department of Electrical and Electronics Engineering Thanjavur India Vivekanandha College of Engineering for Women Department of Computer Science and Engineering Tiruchengode India Saveetha School of Engineering Saveetha Institute of Medical and Technology Science Department of Computer Science and Communications Engineering Tiruchengode India

ISBN: (纸本)9798331529635

Intravenous (IV) therapy is a critical component of modern healthcare, yet traditional IV systems are prone to human errors, manual adjustments, and limited monitoring capabilities, which can jeopardize patient safety and hinder healthcare efficiency. this paper presents the development of the Smartdrip IV Infusion System, a sophisticated and automated solution that integrates advanced sensors, control algorithms, and intuitive user interfaces to address these limitations. the Smartdrip system minimizes human intervention, provides real-time monitoring, and automates fluid administration with enhanced precision and safety features. the system demonstrates high reliability through simulation and prototype testing in detecting anomalies, issuing alerts, and ensuring accurate infusion rates, thereby improving patient outcomes and reducing healthcare provider workload. the results validate the Smartdrip system as a transformative approach to optimizing IV therapy in diverse clinical settings. © 2024 IEEE.

关键词： Automated Infusion System Drip Rate Monitoring Healthcare Automation Intravenous therapy Patient

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Noma Based Full Duplex 6G Communication systems 6

Noma Based Full Duplex 6G Communication Systems

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

作者： Sohal, Asha Sharma, Sandeep Agarwal, Sweta Balaji, N.V. Bhanu, D. Mokashi, Mandar Krishnarao School of Engineering & Technology Department of Computer Science & Engineering K. R. Mangalam University Gurugram India School of Electronic and Electrical Engineering Dev Bhoomi Uttarakhand University Uttarakhand India Invertis University Department of Electronics Bareilly India Karpagam Academy of Higher Education Department of Computer Science Coimbatore India Karpagam Institute of Technology Department of Information Technology Coimbatore India Vishwakarma Institute of Information Technology Pune India

ISBN: (纸本)9798350304480

Current wireless communications use the microwave band as its medium. Present-day wireless network makes use of the majority of the available spectrum. the word innovative Full-Duplex (FD) as well as the use Getting NOMA sharing scheme called Reflecting In-Band Full-Duplex (R-IBFD) is suggested in which piece in order to advance technology and meet the requirements of better utilizing these natural assets. In order to meet the needs of smart cities for 6th Generations (6thG or 6G), the suggested R-IBFD offers efsfective use of airwaves with superior system characteristics, including Concealment Outage Potential (SOP), efficiency, communication percentage, and secrets capacity. the suggested method aims to address the need for innovative algorithms which foster better transformation and usher with a digital shift in business specifications for 6G. Addressing suggested R-IBFD within this research primarily responds to the phenomenon of interference between channels related security issues. Most interference from co-channels experienced by In-Band Full-Duplex type devices experience among their individual communicating and reception antennas is greater. the use of R-IBFD lessens the impact of this disturbance and helps to secure a necessary transmission infrastructure. Using the aid of SOP creation, formulas, and modeling outcome, simulation, the rise of concealment capability and interaction using R-IBFD are explored for an improved comprehension of its contributions. Among of the many evaluation technologies being utilized to increase the concealing capabilities is an artificial algorithm based on genes. © 2023 IEEE.

关键词： 5G in-band full-duplex 6G machine learning genetic algorithm non-orthogonal multiple access reflective-in-band full-duplex secrecy capacity

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4th international conference of Artificial Intelligence, Medical Engineering, Education, AIMEE 2020 held at the Mechanical Engineering Institute of the Russian Academy of Sciences, 2020

4th International Conference of Artificial Intelligence, Med...

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4th international conference of Artificial Intelligence, Medical Engineering, Education, AIMEE 2020 held at the Mechanical Engineering Institute of the Russian Academy of Sciences, 2020

ISBN: (纸本)9783030671327

the proceedings contain 37 papers. the special focus in this conference is on Artificial Intelligence, Medical Engineering, Education. the topics include: A Neural Network Featured System for Learning Performance of Students;method of Fuzzy Agreed Alternative Selection in Multi-agent systems;Evaluation of the Effect of Preprocessing Data on Network Traffic Classifier Based on ML Methods for Qos Predication in Real-Time;the Task of Improving the University Ranking Based on the Statistical Analysis Methods;deep-Learned Artificial Intelligence for Consciousness – thinking Objectization to Rationalize a Person;algorithmization of Computational Experiment Planning Based on Sobol Sequences in the Tasks of Dynamic systems Research;Modification of the Hausdorff Metric in Combination with the Nearest Point Algorithm ICP in Point Cloud Construction Problems;functional systems Integrated with a Universal Agent of Artificial Intelligence and Higher Neurocategories;calculation of the Current Distribution Function Over a Radiating Structure with a Chiral Substrate Using Hypersingular Integral Equations;influence of Image Pre-processing algorithms on Segmentation Results by Method of Persistence Homology;influence of Delays on Self-oscillations in System with Limited Power-Supply;cognitive Prediction Model of University Activity;temperature Reaction of a Person with a Contact Method of Exposure to a thermal Signal;study of the Force-Moment Sensing System of a Manipulative Robot in Contact Situations with Tenzoalgometry of Soft Biological Tissues;the Influence of Hydroplasma on the Proliferative and Secretory Activity of Human Mesenchymal Stromal Cells;the Biotechnological Method for Constructing Acoustic and Vibration Sequences Based on Genetic DNA Sequences;telemedicine Monitoring with Artificial Intelligence Elements.

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Modified DMGC Algorithm using ReLU-6 with Improved Learning Rate for Complex Cluster Associations 6

Modified DMGC Algorithm using ReLU-6 with Improved Learning ...

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6th international conference on Intelligent computing and Control systems, ICICCS 2022

作者： Mansuri, Sohaib Gupta, Sumit Kumar Singh, Dhirendra Pratap Choudhary, Jaytrilok Dept. Computer Science Engineering M.P. Bhopal India

ISBN: (纸本)9781665410359

this research work has presented a modified deep multi-graph clustering (MDMGC) for the enhancement of clustering accuracy. Multi-graph clustering is an important method for shallow models. Shallow models are known to have highly complex data. the proposed MDMGC is based on a graph auto encoder with a deep neural network. ReLU-6 is used as an activation function in the proposed method with a learning rate of 0.0002. A loss function is used for performance improvement. In this proposed MDMGC. T-distributed stochastic neighbor embedding (TSNE) uses data set visualization as well as embedding. Use Google Co-Lab for the implementation of the proposed method. the proposed modified clustering method shows better results as compared to other methods in terms of different parameters, normalized mutual information (NMI), and loss function. there are different data sets available to perform the proposed work;they are 20 news and DBLP. the proposed method also shows better clustering visual outcomes when it is calculated with the help of TSNE. © 2022 IEEE.

关键词： Deep neural networks

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proceedings of international conference on High Performance computing in Asia-Pacific Region, HPC Asia 2023

Proceedings of International Conference on High Performance ...

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6th international conference on High Performance computing in Asia-Pacific Region, HPC Asia 2023

ISBN: (纸本)9781450398060

the proceedings contain 15 papers. the topics discussed include: reducing shared memory footprint to leverage high throughput on tensor cores and its flexible API extension library;efficient large integer multiplication with arm SVE instructions;effectiveness of the oversubscribing scheduling on supercomputer systems;a new data conversion method for mixed precision Krylov solvers with FP16/BF16 Jacobi preconditioners;fault tolerance for ensemble-based molecular-continuum flow simulations;comparison of reproducible parallel preconditioned BiCGSTAB algorithm based on ExBLAS and ReproBLAS;a case study on DaCe portability & performance for batched discrete Fourier transforms;memory usage prediction of HPC workloads using feature engineering and machine learning;and associative operator precedence parsing: a method to increase data parsing parallelism.

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A Comprehensive Review on Object Detection in the Context of Autonomous Driving 4

A Comprehensive Review on Object Detection in the Context of...

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4th international conference on Ubiquitous computing and Intelligent Information systems, ICUIS 2024

作者： Islam, Md Moynul Chowdhury, Ismatul Jannat Mahboob, Tanvir Zobair Mazumder, Md Shah Jalal Hossain, Mohammad Jakaria Biswas, Md Siam Rone, Poncanon Datta Maharishi International University Department of Computer Science IA United States University of North Carolina Department of Electrical Engineering CharlotteNC United States Chittagong University of Engineering and Technology Department of Computer Science and Engineering Chittagong Bangladesh

ISBN: (纸本)9798331529635

In autonomous driving, safety assessment is becoming an essential component, particularly in the perception and analysis of the environment around them. To make safe driving judgments, autonomous cars mostly rely on their capacity to observe and comprehend their environment. Detecting objects is a frequent and challenging problem in autonomous driving. Over the course of the last ten years, as deep learning has rapidly advanced, researchers have conducted numerous experiments and made significant contributions to the performance improvement of object recognition and related tasks including object categorization, localization, and segmentation. In this paper, an overview of state-of-the-art object detection algorithms is presented with in depth analysis. Region proposal-based approaches and single-shot approaches are two main frameworks of object detection which are discussed here. R-CNN, SPP-net, Fast R-CNN, and Faster R-CNN refer to region proposal-based methods while single-shot methods consist of YOLOv2, YOLOv3, YOLOv4 and SSD. the authors truly believe that this study would have a meaningful impact on the current advances in object detection algorithms. © 2024 IEEE.

关键词： Zero-shot learning

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Towards exploiting custom equipped drones for enhanced slice service delivery in 6G 6

Towards exploiting custom equipped drones for enhanced slice...

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6th international conference on Pattern Analysis and Intelligent systems, PAIS 2024

作者： Bouzid, Tarek Chaib, Noureddine Bensaad, Mohamed Lahcen Université Amar Telidji De Laghouat Laboratoire d'Informatique Et De Mathématiques Laghouat Algeria

ISBN: (纸本)9798350350265

Novel cellular networks aim to connect different device types such as vehicles, drones, Internet of things (IoT), and more. Network slicing emerged as a key enabler to support diverse scenarios and users with varying requirements. However, limited dynamic coverage and adaptability hinder efficient support for diverse user demands in network slicing. As a result, this paper proposes a novel hybrid drone-based network slicing architecture for future 6G networks. We introduce specialized drones tailored for massive Machine-Type Communications (mMTC), enhanced Mobile Broadband (eMBB), and Ultra-Reliable Low-Latency Communications (URLLC) slices. Each drone type boasts distinctive capabilities optimized for its respective slice requirements. Our framework paves the way for significantly improved coverage, throughput, response times, and overall user satisfaction compared to traditional all-purpose drone deployments. While this work lays the foundation for future integration with AI-powered optimization, it showcases the significant potential of drone specialization to unlock efficient and adaptable network slicing for future-generation networks. © 2024 IEEE.

关键词： Drones

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Dynamic Service Level Agreements and Particle Swarm Optimization Methods for an Efficient Resource Management in 6G Mobile Networks 15th

Dynamic Service Level Agreements and Particle Swarm Optimiza...

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15th international conference on Ubiquitous computing and Ambient Intelligence

作者： Bordel, Borja Alcarria, Ramon Robles, Tomas Hermoso, Miguel Univ Politecn Madrid Madrid Spain

ISBN: (纸本)9783031485893;9783031485909

Future 6G networks are envisioned to provide ultra-massive machinetype communications. But such a huge number of devices implies an extraordinary resource consumption, which surely will exceed the network resources. To mitigate this problem, static optimization algorithms are used to efficiently distribute existing resources. However, this approach presents three basic problems. First, every 6G device must fulfill a different business case. So, some Service Level Agreements may be breached more easily than others. Second, in 6G mobile networks, base stations can increase their resources dynamically, although their operation cost would increase. However, some devices could accept this additional charge. And third, 6G mobile devices should know the actual Service Level Agreement offered by each base station before stablishing the final connection. therefore, in this paper, we propose a new resource management solution for 6G networks, based on the union of static optimization algorithms and Blockchain-enabled Service Level Agreements, which can be renegotiated dynamically. A transparent Blockchain network allows 6G devices to negotiate their Service Level Agreement with different base stations, before stablishing any connection. the guaranteed Quality-of-Service, the maximum Quality-of-Service, and the tariffication are included in Smart Contracts. Particle swarm optimization algorithms are employed to allocate resources and study the future potential resource distribution. A multilevel optimization scheme is proposed, so we ensure that devices receive resources according to their Service Level Agreement category. Also, an experimental validation based on simulation tools is provided. Results show that the Service Level Agreement fulfillment rate increases by up to 31% compared to equivalent static optimization mechanisms.

关键词： 6G networks particle swarm optimization Blockchain Service Level Agreement resource management Quality of Service

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