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检索条件"任意字段=Conference on Internet Quality and Performance and Control of Network Systems"

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8th International conference on Information System Design and Intelligent Applications, ISDIA 2024

8th International Conference on Information System Design an...

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8th International conference on Information System Design and Intelligent Applications, ISDIA 2024

ISBN: (纸本)9789819748914

The proceedings contain 45 papers. The special focus in this conference is on Information System Design and Intelligent Applications. The topics include: Denoising and quality Enhancement of CT Scan/X-Ray Images of Lung Disease for Enhanced Diagnosis;changing Paradigms in Dementia Care: Technology-Based Solutions;dead Drop Covert Channel Technique Using Windows Registry;A Comparison of LEACH-Like Protocols to Improve Power Consumption Efficiency in Wireless Sensor networks;The Efficacy of α-Channels in PNG Image File Format for Covert Communication;smartening Energy Consumption: A Comparative Study of Energy Optimization Strategies in IoT Environments;performance Evaluation of IoT-Fog-Cloud System for Data Storage, Analysis and Visualisations Using Retrial Queues Approach;investigation in Future Autonomous Transport;comparative Analysis of Simulation Tools and IoT Platforms for Middleware;dual Band Dual Polarized Coaxial Feed Microstrip Patch Antenna for Wireless Applications;enhancing E-Learning Interactivity with Haar Cascade User Detection;a Novel Method for Implementing the IoT-Based Hybrid Energy System with Pollution Monitoring and control in Coastal Roadways;A Novel Proportional Integral Derivative (PID) controller-Based control Strategy for a Formula Student Vehicle;a Bluetooth and Smartphone-Based Geofencing Solution For Monitoring Objects;performance Analysis of LoRa Communication in Suburban Environments;LPWAN Technologies in Smart Cities: A Comparative Analysis of LoRa, Sigfox, and LTE-M;forewarning Disaster Alert systems and Mitigation Response;optimizing Cloud Computing Resource Allocation Through Intelligent Strategies;ioT-Enabled Neural network Analysis for Early Detection and Prediction of Mental Depression;connecting IoT Sensors for Enhanced Dementia Disease Monitoring and Intervention;an Effective Exploration of Accessing 5G Mobile Communication That Affects E-Commerce Using IoT;smart Agriculture Farming Using Drone Automation Technology.

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network Autonomous Learning Monitoring System Based on SVM Algorithm 23

Network Autonomous Learning Monitoring System Based on SVM A...

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10th International conference on Wireless Communication and Sensor networks, icWCSN 2023

作者： Wang, Yujiao Lin, Haiyun Li, Chunyu She, Lina Sun, Li Wang, Junwei College of Information Engineering Kunming University Kunming China College of Physical Science and Technology Kunming University Kunming China Library Kunming University Kunming China Lianjia Primary School Kunming China Kunming Radio and Television Network Limited Liability Company Kunming China

ISBN: (纸本)9781450398466

The network autonomous learning monitoring system is a subsystem of the learning quality monitoring system in the network education platform. Based on the training objectives of network education and the course learning objectives of learners, and on the basis of educational evaluation theory, it makes value judgments on learners' attitudes, knowledge and ability development level in the whole learning process. Through the planning, inspection, evaluation, feedback, control and adjustment of learners' learning activities, timely guide learners to correct their learning attitude, adjust their learning strategies, and effectively use learning resources and modern information technology means to carry out autonomous learning, so as to achieve the expected learning goals. The network self-learning monitoring system is based on the database created by SQL Server platform, supports C/S structure, has good scalability and usability, and is used to extract and analyze data. SVM algorithm is used to extract system features, which has the advantages of low system load, low response delay and good performance. An accurate network autonomous learning monitoring system model is constructed. After system test, the network autonomous learning monitoring system based on SVM algorithm has high data analysis ability, easy to understand, easy to maintain, reasonable structure and easy to use, which meets the needs of learners. Using SVM algorithm for feature extraction, the evaluation performance of the algorithm is improved by more than 3.2%. When learners learn in the system, the system load is small, the response delay is low, and the performance is good. It is an accurate network autonomous learning monitoring system. © 2023 ACM.

关键词： Learning systems

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8th International conference on Information System Design and Intelligent Applications, ISDIA 2024

8th International Conference on Information System Design an...

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8th International conference on Information System Design and Intelligent Applications, ISDIA 2024

ISBN: (纸本)9789819765805

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Attention-Guided Oriented Bounding Box Real-Time Image Analytics Model for Dense Wheat Imperfect Grains and Impurities

Attention-Guided Oriented Bounding Box Real-Time Image Analy...

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2024 International conference on Interactive Intelligent systems and Techniques, IIST 2024

作者： Jiao, Wenhua Luo, Yuan Tian, Yuyu Yu, Bo Aslam, Muhammad Shamrooz China University of Mining and Technology Artificial Intelligence Research Institute XuZhou China China University of Mining and Technology College of Information and Control Engineering XuZhou China China University of Mining and Technology Jiangsu Huashenzhixing Intelligent Technology Artificial Intelligence Research Institute XuZhou China

ISBN: (纸本)9798350374421

Impurities and imperfect grains in dense wheat are critical factors affecting wheat quality and secondary production. Despite the significance, detecting dense wheat grains still faces challenges, mainly due to poor detection accuracy and severe leakage. These issues hinder the model from meeting the reliability and real-time detection requirements in practical scenarios. To address these challenges, we propose an attention-guided oriented bounding box network (AG-OBBNet) for real-time detection of dense wheat imperfect grains and impurities. Firstly, the oriented bounding box method(OBB) is integrated to introduce the orientation of wheat grains into the YOLOX framework, which dramatically improves the accuracy of image analysis and result information visualization. Next, we construct a novel strong feature extraction network that integrates low-dimensional localization features with semantic features enhanced by DS-CSP and a global attention mechanism before fusion. This network facilitates deep mining of semantic information, improving wheat grain classification, reducing computational overhead, and enhancing the utilization of low-dimensional localization features to improve the leakage detection problem in dense wheat grains. Finally, we introduce the Focal-EIOU loss function for faster convergence speed and better localization effects, replacing the original IOU loss function to further enhance model detection performance. To validate the effectiveness and generalization ability of the model, we construct a dense wheat grain dataset (DWGD) categorized into 12 different classes. Experimental results indicate an average accuracy (mAP) of 96.4% for detecting imperfections and impurities in wheat grains, with the Frame Per Second(FPS) of 148.6. Additionally, the model features fewer parameters and meets real-time images analytics and visualization requirements in practical scenarios. © 2024 IEEE.

关键词： Visual analytics

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PAINT: Path Aware Iterative network Tomography for Link Metric Inference 30

PAINT: Path Aware Iterative Network Tomography for Link Metr...

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30th IEEE International conference on network Protocols (ICNP)

作者： Xue, Leyang Marina, Mahesh K. Li, Geng Zheng, Kai Univ Edinburgh Edinburgh Midlothian Scotland Huawei Technol Labs 2012 Shenzhen Peoples R China

ISBN: (纸本)9781665482349

Understanding link-level performance is key to assuring the quality of cloud-based and OTT services, optimal path selection, robust network operations and beyond. However, direct measurement of each link not only incurs high overhead at the internet-scale but also is infeasible due to lack of access to network measurement information beyond AS boundaries and functional limitations at relay nodes. Although network tomography is well suited, existing approaches are insufficient due to their unrealistic assumptions with respect to stability, control-lability, and visibility. Motivated by this, we propose PAINT, an online iterative algorithm that estimates and refines linklevel performance metrics based on path-level measurement. In PAINT, the link metrics are iteratively estimated by minimizing their least square error (LSE) and calibrated based on the comparison of weight between the estimated shortest paths (SPs) and best-known paths from end-to-end path measurements. The key insight is that when there is inconsistency between these paths, then weights of links on the estimated SP are likely misestimated, triggering a further round of estimation to refine the estimated link metrics. Evaluation of PAINT, focusing on link delay estimation, using four different real network topologies and two real-world measurement datasets (including one we collected) shows that relative to existing approaches, it yields up to 3x gain in absolute link delay estimation accuracy and improves decisions dependent on link delay estimation by up to 5x in relative error.

关键词： Measurement network topology Measurement uncertainty Estimation Delay estimation Tomography controllability

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Comparative Study of RIP, OSPF, and EIGRP in VoIP networks Across Different Ethernet Topologies

Comparative Study of RIP, OSPF, and EIGRP in VoIP Networks A...

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Artificial Intelligence, Computational Electronics and Communication System (AICECS), International conference on

作者： Anwesh Rao B S Gurucharan Kiran V Dept. of ECE R. V. College of Engineering Bangalore India

ISBN: (数字)9798350391244

ISBN: (纸本)9798350391251

Voice over internet Protocol (VoIP) has revolutionized communication by offering a flexible and cost-effective alternative to traditional telephony using internet-based voice transmission. This paper investigates the performance of VoIP traffic on various network topologies (mesh, tree, and star) using OPNET Modular 14.5 for simulation. It analyzes the impact of different routing protocols and quality of Service (QoS) mechanisms on important performance metrics including jitter, packet delay, and throughput. Research underscores the benefits and constraints of each topology and routing protocol for maintaining high-quality voice communication. Despite their simplicity, star topologies are vulnerable to single points of failure. Tree topologies strike a compromise between possible network weaknesses and scalability. This paper presents a detailed comparison of various network topologies, demonstrating that the Enhanced Interior Gateway Routing Protocol (EIGRP) is the most suitable for achieving high scalability. Additionally, it analyzes the significance of QoS in improving VoIP performance, emphasizing its impact on call quality and network reliability, and concluding that for applications like video or voice conferencing, star topology is the best suited while for large scale applications like database systems and Wide Area network (WAN) tree topology is the best suited.

关键词： Wide area networks network topology Scalability Stars quality of service Jitter Throughput Routing protocols Topology Delays

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Measurement and Analysis: Does QUIC Outperform TCP? 18

Measurement and Analysis: Does QUIC Outperform TCP?

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18th IEEE International conference on Mobility, Sensing and networking (MSN)

作者： Qin, Xiang Chen, Xiaochou Huang, Wenju Xie, Yi Zhang, Yixi Xiamen Univ Sch Informat Xiamen Peoples R China Xiamen Univ Informat Network Serv Ctr Xiamen Peoples R China Xiamen Univ Shenzhen Res Inst Shenzhen Peoples R China

ISBN: (纸本)9781665464574

Many web applications adopt Transfer control Protocol (TCP) as the underlying protocol, where congestion control (CC) plays a vital role in reliable transmission. However, some TCP mechanisms cannot cope with the requirements of new applications and ever-increasing network traffic. Therefore, people have proposed Quick UDP internet Connection (QUIC), an excellent potential alternative based on UDP, which introduces new features to improve transmission performance and is compatible with existing CC algorithms. This paper has conducted many experiments in the testbed and actual environments to measure and compare QUIC and TCP regarding communication quality, compatibility fairness, and user experience, while considering the impacts of three typical CC algorithms: NewReno, Cubic, and BBR. QUIC outperforms TCP in most experiments for web browsing and online video, but its performance is susceptible to CC algorithms and network conditions. For example, with the Cubic algorithm, QUIC enabling the 0-RTT feature can decrease the webpages loading time by 37.11% compared with TCP. Using the BBR algorithm, both QUIC and TCP achieve high throughput, slight fluctuation, and few delayed events when playing online videos. TCP with BBR provides better fairness, while QUIC with BBR is more robust in a network with high latency or packet loss.

关键词： QUIC TCP Congestion control Algorithm network Measurement

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A Real-Time Active Noise control System for Low Frequency Substation Noise Suppression

A Real-Time Active Noise Control System for Low Frequency Su...

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UNIfied conference of International Workshop on Defence Applications of Multi-Agent systems, DAMAS 2023, International conference on Maintenance Engineering, IncoME-V 2023, International conference on the Efficiency and performance Engineering network, TEPEN 2023

作者： Wang, Haohui Li, Yamin Hao, Ying Gao, Jianzheng Liang, Xiaoxia Feng, Guojin Zhen, Dong School of Mechanical Engineering Hebei University of Technology Tianjin300401 China Tianjin Eco-Environmental Monitoring Center Tianjin300191 China Advanced Equipment Research Institute Co. Ltd. of HEBUT Tianjin300401 China

ISBN: (纸本)9783031494123

Substation noise has become an important factor that influences the life quality of residents, especially in densely populated residential areas. Despite the relatively modest noise levels produced by small and medium-sized transformer facilities, their proximity to residential zones leads to significant annoyance, making them a focus in environmental noise-related complaints. The primary noise generated by these facilities falls within the medium and low-frequency range, where traditional passive noise reduction methods show limited success. This research develops a real-time active noise control (ANC) system based on the TMS320F28335 digital signal processor. The ANC algorithms, including FxLMS and FxNLMS, are implemented for real-time noise suppression. In the experiment, a series of sinusoidal signals and substation noises are employed to assess the system's effectiveness in noise suppression. The results highlight the efficacy of the ANC system, with an average noise reduction of over 12 dB for noises under 600 Hz. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Digital signal processors

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performance of Slotted ALOHA for LoRa-ESL Based on Adaptive Backoff and Intra Slicing 6

Performance of Slotted ALOHA for LoRa-ESL Based on Adaptive ...

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6th International conference on Communication and Information systems, ICCIS 2022

作者： Abid Ali Khan, Malak Ma, Hongbin Muhammad Aamir, Syed Baris Cekderi, Anil Ahamed, Mustak Abdo Ali Alsumeri, Abdulraman Beijing Institute of Technology School of Automation Beijing China

ISBN: (数字)9781665463850

ISBN: (纸本)9781665463850

Slotted ALOHA implemented in the internet of things (IoT) uses the LoRaWAN media access control (MAC) protocol to improve its performance. Various backoff algorithms have been proposed in LoRaWAN to evaluate the delay, throughput, and packet loss rate (PLR). However, an adaptive backoff algorithm has been implemented in this paper to examine the performance metrics for electronic shelf labels (ESLs). The use of adaptive backoff optimizes the delay and the bandwidth (BW) for more efficient and meaningful communication with a certain degree of data loss. The results illustrate that the intra-slicing model and adaptive backoff estimate the optimal delay for each slice, starting with the best slicing priority for the end device (ED) which brings mobility into the network. © 2022 IEEE.

关键词： internet of things

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Research of Multipath Routing Processes in Software Defined networks Based on Ant Colony Optimization 11

Research of Multipath Routing Processes in Software Defined ...

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11th Mediterranean conference on Embedded Computing (MECO) / 3rd Summer School on Cyber-Physical + systems and internet of Things (CPS and IoT)

作者： Perepelkin, Dmitry Nguyen, Tin Ryazan State Radio Engn Univ Fac Comp Engn Ryazan Russia

ISBN: (纸本)9781665468282

Currently, the data in the network is increasing in both size and complexity, while network resources are limited, leading to network management becoming more difficult. Traditional network architectures are becoming increasingly unsuitable for the network requirements to respond to rapidly changing parameters of bandwidth, latency, security, etc. Software defined network (SDN) has become a new approach, changing the current network architecture to meet the needs of network resource management and traffic control. The purpose of the work is to study and analyze the multipath routing processes in the software defined network based on ant colony optimization. The simulation results show that the proposed algorithm is effectively used to find the shortest paths. The paths found can be used at the same time to transmit data, instead of just using a single path. From there, the performance of the network is improved, limiting congestion, reducing latency and packet loss.

关键词： software defined network multipath routing ant colony optimization

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