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检索条件"任意字段=Proceedings of the 5th International Conference on Algorithms, Computing and Systems"

共 7660 条记录，以下是751-760 订阅

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Design of a Dual band Star Shaped Electromagnetic Bandgap (EBG) for 5G Communication 6

Design of a Dual band Star Shaped Electromagnetic Bandgap (E...

引用

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

作者： Silva Deena, J. Mohan, C. Prasanna, R. Prasanth, M. St.Joseph’s Institute Of Technology Tamil Nadu Chennai600119 India

ISBN: (纸本)9798331522667

this research study proposes a unique star-shaped electromagnetic bandgap (EBG) configuration for 5G communication at frequencies lower than 6 GHz. the suggested structure comprises an adjusted star-shaped supporting on FR-4 substrate which is designed for 5.8 GHz (N46 band) applications. According to the simulated results, both bandgaps are produced by the distinct EBG structure close to the resonant frequencies (5.8 GHz). Considering its 8.2 mm x 8.2 mm overall area, the suggested EBG accomplishes an integrated design that combines miniaturization and dual-band technology. the new EBG structure is straightforward, works effectively with microwave electrical systems, and can be employed in wireless networks that require a compact size for multiband applications. © 2025 IEEE.

关键词： 5G mobile communication systems

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7th EAI international conference on Science and Technologies for Smart Cities, SmartCity360° 2021

7th EAI International Conference on Science and Technologies...

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7th EAI international conference on Science and Technologies for Smart Cities, SmartCity360° 2021

ISBN: (纸本)9783031063701

the proceedings contain 45 papers presendted at a virtual meeting. the special focus in this conference is on Science and Technologies for Smart Cities. the topics include: Edge AI System Using a thermal Camera for Industrial Anomaly Detection;power Consumption Analysis for the Development of Energy Efficient Bluetooth 5 Based Real-Time Industrial IoT systems;towards Orchestration of Cloud-Edge Architectures with Kubernetes;simulated LoRa Sensor Network as Support for Route Planning in Solid Waste Collection;exploring the Effects of Precision Livestock Farming Notification Mechanisms on Canadian Dairy Farmers;concept for Safe Interaction of Driverless Industrial Trucks and Humans in Shared Areas;feature Fusion in Deep-Learning Semantic Image Segmentation: A Survey;MR-Based UAV Route Planning for the Coverage Task;inter-satellite Optical Analog Network Coding Using Modulated Retro Reflectors;low-cost Real-time IoT-Based Air Quality Monitoring and Forecasting;Channel Allocation Mechanism in C-RAN for Smart Transportation;Low Cost ICS Network Scanning for Vulnerability Prevention;the Development of the Sati Interactive System: A Computer-Based Interactive System that Creates a Sense of Deep Engagement in the User;benefits and Obstacles of Smart Governance in Cities;new Environmental Indicators for Sustainable Cities of Varying Size Scale: the Use Case of France;scalable and Sustainable Community Networks for Inclusive Smart Cities;security in V2X Communications: A Comparative Analysis of Simulation/Emulation Tools;implementation and Comparison of Four algorithms on Transportation Problem;critical Review of Citizens’ Participation in Achieving Smart Sustainable Cities: the Case of Saudi Arabia;3-Dimensional Reconstruction of a Highly Specular or Transparent Cylinder from a Single Image;An Overview of the Status of DNS and HTTP Security Services in Higher Education Institutions in Portugal;Prevention of IoT-Enabled Crime Using Home Routers (PITCHR);preface.

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Benign and Malignant Detection and Classification for Small Size Image of Breast Tumor Recognition System using U-Net Model 5

Benign and Malignant Detection and Classification for Small ...

引用

5th international conference on Artificial Intelligence and Data Sciences, AiDAS 2024

作者： Awang, Suryanti Kumar, Saumya Nafis, Nur Syafiqah Mohd Haroon, Raihanah Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah Pekan Malaysia Kuliyyah of Medicine International Islamic Universitiy of Malaysia Kuantan Malaysia

ISBN: (纸本)9798331528553

Breast tumor recognition is a critical task in the field of medical imaging systems, aiming to differentiate between benign and malignant tumors. To differentiate the tumors, an efficient technique is crucial to detect and classify it to avoid misdetection and misclassification, at the same time can accelerate the process. thus, this paper proposed a deep learning technique which is a modified architecture of U-net model that based on Convolutional Neural Network (CNN) to detect and classify the tumors. the aim is to have a less complex U-Net model that is effective for a small size of images. During the technique deployment, data augmentation, transfer learning, and ensemble approach are employed. the proposed technique is tested using Breast Ultrasound Images dataset (BUSI) that is available in Kaggle. the results obtained are promising with accuracy of 0.8, precision of 0.88, recall of 0.7, and F1-score of 0.8. It indicates that this technique can contribute to the advancement of breast tumor detection and classification by providing valuable insights for clinicians in making accurate and timely diagnoses. thus, the proposed technique has the potential to improve the efficiency and effectiveness of breast tumor recognition, aiding in the early detection and treatment of breast cancer. © 2024 IEEE.

关键词： Convolutional neural networks

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2024 international conference on Emerging Smart computing and Informatics, ESCI 2024

2024 International Conference on Emerging Smart Computing an...

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6th IEEE international conference on Emerging Smart computing and Informatics, ESCI 2024

ISBN: (纸本)9798350306613

the proceedings contain 192 papers. the topics discussed include: reducing gender and ethnicity bias in personality trait prediction;MDLGO: integrated multimodal deep learning framework for enhanced precision in glaucoma diagnosis using OCT A-scans;advancing manufacturing energy efficiency: the role of AI and web-based tools;integrated healthcare system for saline monitoring, patient communication, and heart disease prediction using IoT and machine learning algorithms;IoT based real time drainage monitoring system;software defect prediction by logistic regression with gradient descent cost computation;ONU: A reinforcement load balancing approach for resource-aware task allocation in distributed systems;a novel approach using feature fusion for android malware detection and classification;and graph based analysis technique for identification of key functionalities in malicious IoT binaries.

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Optimizing Bayesian Belief Network Analysis for Autonomous Vehicles 5

Optimizing Bayesian Belief Network Analysis for Autonomous V...

引用

5th international conference on Electronics and Sustainable Communication systems, ICESC 2024

作者： Jin, Hulin Jin, Zhiran Kim, Yong-Guk International Institute of Engineering Psychology DenverCO80202 United States Foothill Preparatory School Temple CityCA91780 United States Sejong University Department of Computer Engineering Seoul05006 Korea Republic of

ISBN: (纸本)9798350379945

this study investigates the extension of Bayesian Belief Network (BBN) analysis tailored for autonomous vehicles (AVs), specifically targeting the optimization of lane change decision making in structured road environments. Structured roads, characterized by clear lane markings and predictable traffic patterns, provide a controlled environment for AV operations. However, efficient and safe lane changes remain critical to improving traffic flow and overall driving safety. To address this challenge, advanced BBN models are used that integrate real-time data and communication technologies to improve decision accuracy. the methodology involves constructing BBNs to model lane-changing behavior based on historical driving data, using rigorous statistical analysis to understand driver responses under different conditions. Results show significant improvements in lane change efficiency, highlighting implications for AV operations in complex urban environments. © 2024 IEEE.

关键词： Road and street markings

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5G Application for Methodologies for Big Data Application 5

5G Application for Methodologies for Big Data Application

引用

5th IEEE international conference on computing, Power, and Communication Technologies, IC2PCT 2024

作者： Singh, Amanveer Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350383522

the advantages and benefits of big data and cellular networks are discussed in this essay. First, a summary of their interactions, together with big data-driven and big data-assisted communication networks, is given. the erstwhile caters for big data characteristics like number, pace, and variation by utilizing diverse means such as transmission, storage, and processing in cellular networks in order to accommodate big data apps and services. In order to gather wireless big data and gain detailed information about the networks and users for better network management and scheduling, the latter makes use of big data methods. Two examples that focus on channel data collection and big data-aided peripheral information storage are offered that will further highlight the reciprocal advantages. the discussion concludes with a few intriguing open study questions. © 2024 IEEE.

关键词： 5G Convergence Big Data Cellular Networks Cloud computing Data Analytics Data Collection Data Processing Data Storage and Data Security Data Transmission Edge computing Network Infrastructure Network Management Resource Allocation Wireless Communications

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Analysis and Research on Generative Artificial Intelligence in the Field of international Library and Information Science 24

Analysis and Research on Generative Artificial Intelligence ...

引用

5th international conference on Computer Science and Management Technology, ICCSMT 2024

作者： Yan, Erkai Gao, Mengxiao Tang, Mei Library Northwestern Polytechnical University Shaanxi Xi'an China

ISBN: (纸本)9798400709999

Generative artificial intelligence is an artificial intelligence technology based on deep learning whose core lies in leveraging computer algorithms and training data to generate new, practically valuable content, encompassing text, images, audio, videos, etc. this technology is poised to exert profound impacts on the transformation and development of libraries. Drawing on generative artificial intelligence research publications in the field of international library and information science included in the Scopus database as the data source, this paper employs CiteSpace software and SciVal tools to conduct a visual analysis of literature outputs, core authors, journal sources, and keywords. the results show that generative artificial intelligence research in the international library and information science field is applied primarily in areas such as reference services, information literacy education, and smart libraries. Recommendations are made to promote the application and development of generative artificial intelligence technology in libraries by strengthening technological research and application, boosting data analysis and data sharing, emphasizing information security and privacy protection, promoting cross-boundary integration and ecological development, etc. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Generative adversarial networks

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A Framework for Evaluating Integration Testing Criteria in Serverless Applications 15

A Framework for Evaluating Integration Testing Criteria in S...

引用

15th international conference on Cloud computing and Services Science, CLOSER 2025

作者： Winzinger, Stefan Wirtz, Guido Distributed Systems Group University of Bamberg An der Weberei 5 Bamberg96047 Germany

ISBN: (纸本)9789897587474

Serverless applications are based on Function-as-a-Service (FaaS) platforms where serverless functions interact with other cloud-specific services. the integration of these components is crucial for the application’s functionality and must be adequately tested. Testing criteria can help here by supporting developers in evaluating test suites and identifying missing test cases. this paper presents a framework for evaluating integration testing criteria in serverless applications by showing the processes needed for evaluating the criteria. the process defined is shown for some control and data flow criteria and applied to some serverless applications showing the feasibility of the approach. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Coverage Criteria Data Flow FaaS Integration Testing Serverless computing

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5th international conference on computing in Engineering and Technology,ICCET 2020

5th International Conference on Computing in Engineering and...

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5th international conference on computing in Engineering and Technology,ICCET 2020

ISBN: (纸本)9789811540288

the proceedings contain 43 papers. the special focus in this conference is on computing in Engineering and Technology. the topics include: Machine learning techniques for homomorphically encrypted data;improving leaf disease detection and localization accuracy using bio-inspired machine learning;identification of medicinal plant using image processing and machine learning;Human gait analysis based on decision tree, random forest and KNN algorithms;adaptive mean filter technique for removal of high density salt and pepper (impulse) noise;a novel approach of image processing to identify type and name of snake;robust and secure lucas sequence-based video watermarking;creating video summary using speeded up robust features;fingerprint-based gender classification by using neural network model;segmentation of characters from degraded Brahmi script images;sentiment analysis of democratic presidential primaries debate tweets using machine learning models;a computational linguistics approach to preserving and promoting natural languages;Comparative analysis of geometric transformation effects for image annotation using various CNN models;prominent feature selection for sequential input by using high dimensional biomedical data set;an enhanced stochastic gradient descent variance reduced ascension optimization algorithm for deep neural networks;threat detection with facial expression and suspicious weapon;IMEXT text summarizer using deep learning;Integrated YOLO based object detection for semantic outdoor natural scene classification;customer feedback through facial expression recognition using deep neural network;implementation of e-health record with biometric authentication;modeling groundwater spring potential of selected geographical area using machine learning algorithms;lane detection and collision prevention system for automated vehicles;preface;singleton wavelet packet matrix.

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Efficient Quantum algorithms for Nonlinear Stochastic Dynamical systems 4

Efficient Quantum Algorithms for Nonlinear Stochastic Dynami...

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4th IEEE international conference on Quantum computing and Engineering, QCE 2023

作者： Gnanasekaran, Abeynaya Surana, Amit Sahai, Tuhin Raytheon Technologies Research Center BerkeleyCA United States Raytheon Technologies Research Center East HartfordCT United States Sri International Menlo ParkCA United States

ISBN: (纸本)9798350343236

In this paper, we propose efficient quantum algorithms for solving nonlinear stochastic differential equations (SDE) via the associated Fokker-Planck equation (FPE). We discretize the FPE in space and time using two well-known numerical schemes, namely Chang-Cooper and implicit finite difference. We then compute the solution of the resulting system of linear equations using the quantum linear systems algorithm. We present detailed error and complexity analyses for both these schemes and demonstrate that our proposed algorithms, under certain conditions, provably compute the solution to the FPE within prescribed ϵ error bounds with polynomial dependence on state dimension d. Classical numerical methods scale exponentially with dimension, thus, our approach, under the aforementioned conditions, provides an exponential speed-up over traditional approaches. © 2023 IEEE.

关键词： Linear systems

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