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Topic 1: Real Time, Embedded systems and parallel Computing

Topic 1: Real Time, Embedded Systems and Parallel Computing

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international conference on Embedded & distributed systems (EDiS)

Presents the front cover, title page, cover page, or splash screen of the proceedings record.

ISBN: (数字)9798350397543

ISBN: (纸本)9798350397550

Presents the front cover, title page, cover page, or splash screen of the proceedings record.

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Optimizing Large Scale Ontology Alignment to Establish Interoperability for Efficient Retrieval

Optimizing Large Scale Ontology Alignment to Establish Inter...

引用

Disruptive Technologies (ICDT), international conference on

作者： Usha Yadav Gyanendra Kumar National Institute of Fashion Technology Bengaluru Karnataka Manipal University Jaipur Jaipur Rajasthan

ISBN: (数字)9798331519582

ISBN: (纸本)9798331519599

The Semantic Web is aiming to add meaning and structure to the vast amount of data available online. It aims to make information machine-readable and interpret, unlike traditional web pages that are designed for human consumption. The increase in adoption of semantic web technologies resulted in the generation of vast number of ontologies with varying size and heterogeneity. The efficient ontology matching system to align the large number of ontologies is extremely required to allow interoperability in cross domain. Although there are various ontology matching systems available which could handle matching small ontologies but when it comes to matching large scale ontologies, high computational and space requirements is always a challenge. In this paper, an ontologies matching system is proposed which partition the large-scale healthcare ontologies in parallel using base level ontology partitioning method and the similarity between the entities are computed using Adjustment similarity computation method. However, the alignment discovery process demands high computational requirement, therefore in this proposed system, the distributed and parallel approach of Map Reduce technique is used to make system more scalable and efficient.

关键词： Semantic Web Accuracy Scalability Memory management Web pages Medical services Ontologies distributed computing Disruptive technologies Interoperability

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Design and Implementation of a Big Data Platform for Production and Business Management: A Case Study from Vietnam National Coal and Mineral Industries Group 3rd

Design and Implementation of a Big Data Platform for Product...

引用

3rd international conference on Advances in information and Communication Technology, ICTA 2024

作者： Do, Thi-Thu-Trang Tran, Van-Dung Ngo, Manh-Hung Dang, Dinh-Dao Dam, Quang-Thinh Mai-Hoang, Thai-Bao Nguyen, Van-Quyet Huynh, Quyet-Thang Faculty of Information Technology Hung Yen University of Technology and Education Hungyen160000 Viet Nam Vinacomin-Mining Chemical Industry Holding Corporation Limited Hanoi100000 Viet Nam AI Academy Viet Nam Hanoi100000 Viet Nam School of Information and Communication Technology Hanoi University of Science and Technology Hanoi100000 Viet Nam

ISBN: (纸本)9783031809422

This paper introduces a modern Big Data platform for production and business management, utilizing a hybrid architecture that integrates distributed and cloud-based technologies to enhance processing efficiency. The system employs advanced big data processing technologies, including Hadoop, Spark, Kafka, and AI techniques such as YOLO and CNN, to effectively manage unstructured data. This platform improves system performance, facilitates detailed business queries, and enhances storage and query capabilities. We apply this system to the Vietnam National Coal and Mineral Industry Group (VINACOMIN), resolving inefficiencies in their existing software and achieving a tenfold improvement in speed and report generation efficiency. Experiments show that the system can analyze video data under various conditions using advanced AI techniques, particularly the DeepSearch algorithm. The results demonstrate that the platform optimizes report generation and provides a scalable framework for future Big Data applications in similar industrial settings. This research underscores the transformative potential of innovative Big Data solutions in improving data processing, enabling timely decision-making, and maintaining a competitive advantage in the current business environment. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Competition

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PA-Net: a parallel network for carotid vulnerable plaque segmentation in ultrasound images 3

PA-Net: a parallel network for carotid vulnerable plaque seg...

引用

3rd international conference on Computer Vision and Data Mining, ICCVDM 2022

作者： Yuan, Yanchao Li, Cancheng Hua, Yang Zhang, Jicong School of Biological Science and Medical Engineering Beihang University Beijing China Department of Vascular Ultrasonography XuanWu Hospital Capital Medical University Beijing China

ISBN: (纸本)9781510661363

Carotid arteries vulnerable plaques are a crucial factor in the screening of atherosclerosis by ultrasound technique. However, manual plaque segmentation may be time-consuming and variable, moreover, the unstable plaques are contaminated by various noises such as artifacts and speckle noise. This paper proposes an automatic convolutional neural network (CNN) method for plaque segmentation in carotid ultrasound images using a small dataset. Firstly, a parallel network with three independent scale decoders is utilized as our base segmentation network, and pyramid dilated convolutions are used to enlarge receptive fields in three decoder sub-networks. Subsequently, the merged feature maps from the three decoders are rectified by the SENet. Thirdly, in the testing, the initial segmented plaque is refined by the maximal contour postprocessing method to obtain the final segmentation result. The dataset consists of 30 carotid ultrasound images with severe stenosis plaques from 30 patients. Test results show that the proposed method yields a Dice value of 0.820, IoU of 0.701, Accuracy of 0.969, and modified Hausdorff distance (MHD) of 1.43 by 10-fold cross-validation, it outperforms some CNN-based methods on these metrics. Additionally, we apply an ablation experiment to show the validity of each proposed module. Our method may be useful in actual applications for carotid unstable (easily ruptured or severe stenosis) plaques segmentation from ultrasound images. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Convolution

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Research on the Development and Application of parallel Programming Technology in Heterogeneous systems 3

Research on the Development and Application of Parallel Prog...

引用

3rd international conference on Modeling, Simulation, Optimization and Algorithm, ICMSOA 2021

作者： Wu, Linghong School of Computer and Information Engineering Nanchang Institute of Technology JIANGXI Nanchang330044 China

In recent years, with the continuous improvement of high performance computing hardware platform,the application of high performance for a wide range of high-performance, traditional parallel programming environment tools cannot meet the growing demand for high-performance applications and the face of parallel software development environment in a relatively backward state. The heterogeneous system of the new coprocessor with a high performance and power ratio can have high performance computing needs to provide the task to accelerate. As a result, heterogeneous systems are becoming a new trend in high performance computing. However, with the introduction of the new coprocessor and the expansion of the system scale, heterogeneous systems are difficult to program the problem is also increasingly prominent. In view of this problem, this paper adopts the abstract technology to enhance the granularity of parallel programming, and designs a structured parallel programming prototype system which can achieve different levels of implicit parallelism © Published under licence by IOP Publishing Ltd.

关键词： parallel programming

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Research on Network Security Protection Techniques for the Central Station Side of distributed Power Dispatch and Control systems

Research on Network Security Protection Techniques for the C...

引用

Data Science and Computer Application (ICDSCA), IEEE international conference on

作者： Xiao Zhang Youhuai Wang Wenlu Zhang State Grid Hubei Electric Power Co. Ltd. Wuhan China

This research focuses on the study of network security protection techniques for the central station side of distributed power dispatch and control systems. It covers various aspects such as vulnerability discovery, information interaction security, device management, and threat tracing. The aim is to propose an integrated, multi-dimensional, and multi-level security protection system that combines active and passive data security measures and security analysis methods to ensure the safety and reliability of the distributed power dispatch and control systems.

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Research on distributed Sensor Network Faulty Recovery Method based on Attention Mechanism 3

Research on Distributed Sensor Network Faulty Recovery Metho...

引用

3rd international conference on Artificial Intelligence and Computer Engineering, ICAICE 2022

作者： Xing, Zheng Liu, Boya Guan, Haochen Zhang, Yiran Zhang, Ying Chengdu University of Technology The College of Nuclear Technology and Automation Engineering Sichuan Chengdu China Chengdu University of Technology College of Environment and Civil Engineering Sichuan Chengdu China Zhengzhou University of Light Industry International Education College Henan Zhengzhou China Hebei University School of Cyber Security and Computer Hebei Baoding China Northeast Petroleum University School of Electrical & Information Engineering Heilongjiang Daqing China

ISBN: (纸本)9781510663473

Faulty recognition and recovery is extremely essential component for existing sensor networks. However, current investigations concentrates on the recognition process and develop abundant advanced identification methods and existing recovery method is almost based on the multiple layers of neural network to achieve the recovery of sensor network, which would result in vast computation costs. Attention mechanism is proposed for neural network to focus some important neural nodes and perform high accuracy for training process with insignificant computation cost. In this article, we propose a novel neural network to recover the fault sensor network with attention mechanism. Thus, the developed mechanism can achieve rapid recovery of fault sensors network with reasonable computation costs and acceptable performance. From extensive experimental result, we can conclude that our proposed method can strictly process the fault sensor network and compared with existing fault sensor network recovery methods to illustrate the effective performance on recovery accuracy with reasonable costs of our proposed method. © 2023 SPIE.

关键词： Sensor networks

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3D Electrical Impedance Tomography System for Real-Time Annular Multiphase Flow Metering 3

3D Electrical Impedance Tomography System for Real-Time Annu...

引用

3rd international conference on distributed Sensing and Intelligent systems, ICDSIS 2022

作者： Tarek, Mohamed Meribout, Mahmoud Tiwari, Varun Kumar Department of Electrical and Computer Engineering Khalifa University Abu Dhabi United Arab Emirates

ISBN: (纸本)9781839538186

With the rapid progress of tomography systems, a need has emerged for innovation that can provide high accuracy measurements, fast acquisition rate, and low-cost robust systems for multi-phase flow and medical instruments. The main objective of this work is to design and implement a 3D Electrical Impedance Tomography (EIT) system to effectively monitor a multi-phase flow which consists of an annular flow comprising of an air-core of unknown diameter, surrounded by a liquid phase, such as oil and water mixture of high water-cut value. The system consists of an array of electrode sensors evenly distributed around the pipe confining the three-phase flow. Subsequently, a dedicated hardware module (GPU) is used to reconstruct these signals, captured from the sensors, into a 3D image of the flow by solving the forward-inverse problem. The annular flow is generated using a flow conditioner consisting of a swirl cage followed by a bluff body that generates vortices that push the high dense liquid phase to the outer side of the pipeline. The 3D EIT system is designed to accurately measure the gas liquid fraction and the liquid-liquid fraction and provide the 3D volume image of the flow. Hence, it can be utilized for pipeline and reservoirs characterization to achieve high efficiency, cost reduction, and safer production. The approach is to design a dedicated, highly parallel hardware architecture that can sustain the high computation complexity of the 3D EIT algorithm. Coincidentally, advanced software development tools are available to help effectively develop these parallel hardware algorithms. The main novelty is utilizing GPUs to outperform the existing real-time tomography hardware platforms, mainly based on Field Programmable Gate Array (FPGAs), which have the disadvantage of being less dense and feature lower precise arithmetic operations. Matrix multiplication and matrix inversion are considered the most intensive computation in Electric Impedance Tomography (EIT). T

关键词： Graphics processing unit

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A DNN-Based GLMB Algorithm for Multi-sensor Multi-target Tracking with Dense Group Clutter 1

引用

3rd international conference on Autonomous Unmanned systems, ICAUS 2023

作者： Zhang, Yongquan Shang, Aomen Li, Siwei Su, Zhenzhen Ji, Hongbing School of Electronic Engineering Xidian University Xi’an710071 China Science and Technology on Electronic Information Control Laboratory Chengdu610036 China

ISBN: (数字)9789819710911

ISBN: (纸本)9789819710904

Multi-sensor multi-target tracking (MTT) with dense group clutter is facing great challenges in data fusion. One is the high computational complexity caused by the dense group clutter;another is that existing fusion algorithms do not have uniform fusion guidelines. To handle these problems, we present a novel multi-sensor MTT algorithm in this paper, which is based on the generalized labeled multi-Bernoulli (GLMB) filter and distributed deep neural networks (DNN) track fusion under the multi-sensor (MS) system, named the MS-GLMB-DNN algorithm. Firstly, a clutter pre-processing is elaborated, it is based on a CFDP (cluster by finding density peaks) algorithm to reduce the effect of the dense group clutter. Then, the GLMB filter is applied to the DNN track fusion framework for effectively fusing various local tracks. Experimental results indicate that, compared with the commonly used covariance intersection (CI) fusion algorithm, the proposed algorithm can effectively eliminate the effect of clutter on target tracking results, reduce computational complexity, and improve tracking accuracy. © Beijing HIWING Scientific and Technological information Institute 2024.

关键词： Deep neural networks

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distributed Drive Electric Bus Torque Allocation Control Strategy Analysis with MOEA/D 3

Distributed Drive Electric Bus Torque Allocation Control Str...

引用

3rd international conference on Artificial Intelligence and Electromechanical Automation, AIEA 2022

作者： Su, Liang Jiang, Jin Chen, Chao Beijing Institute of Technology Beijing100081 China Xiamen King Long United Automotive Industry Co. Ltd. Xiamen361023 China

ISBN: (纸本)9781510657281

In this paper, the power performance, economical performance, handling stability and driving safety are regarded as major control targets of distributed Drive Electric Bus (DDEB). According to vehicle driving information, the weight coefficients of multiple control targets are calculated by neural network. Furthermore, multi-objective optimization algorithm is carried out to determine the driving torque of each wheel with Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D). The slalom test results demonstrate that the torque allocation control strategy can satisfy the demand of longitudinal driving force and direct yaw moment as far as possible, and improve the handling stability of test bus effectively. © 2022 SPIE.

关键词： Torque

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