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International Conference on Computing and Networking technology (ICCNT)

作者： Aruna Sri Rongali Shweta Saxena Umi Salma Manal Alkhammash Isa Mishra Shibani C Aich Sr. Software Engineer Information Technology Emphasis/Information Technology Ph.D University of The Cumberlands US University amity business school amity university madhya pradesh gwalior madhya pradesh india Department of Computer Science Jazan University Jazan Saudi Arabia KIIT Deemed to be University School of Management College KIIT School of Management Bhubaneswar Department of English Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

This look investigates the utility of blockchain technology for reinforcing consideration in Wi-Fi networks. Networks are verbal exchange networks shaped on-the-fly, requiring no predefined infrastructure for dependable verbal exchange of facts. With the boom in IoT gadgets, wireless sensors, linked buses, and drones, the quantity of networks is anticipated to increase. The security and trustworthiness of networks rely on the trustworthiness of the nodes within the network, and this turns into a chief difficulty in ad-hoc networks. The proposed approach looks at the usage of the benefits of the blockchain era along with disbursed garages, clever contracts, and cryptography to enhance consideration in networks. The blockchain generation can validate the beginning and integrity of facts and assist an agreed/popular device, which would provide a straightforward manner for the nodes in an ad-hoc network to believe every difference. Wi-Fi ad-hoc networks are prone to malicious attacks because of the decentralized and allotted environment..

关键词： Wireless communication Wireless sensor networks Scalability Standardization Ad hoc networks Blockchains Sensors Communication system security Reliability Wireless fidelity

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A Heatmap Regression Approach for Right Ventricle Anatomical Landmarks Localization on Echocardiography

A Heatmap Regression Approach for Right Ventricle Anatomical...

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Image Processing and computer Applications (ICIPCA), IEEE International Conference on

作者： Hailiang Wan Jingjun Gu Zhi Yu Shuyi Song Polytechnic Institute Zhejiang University Hangzhou China Zhejiang Provincial Key Laboratory of Service Robot College of Computer Science Zhejiang University Hangzhou China Zhejiang Provincial Key Laboratory of Service Robot School of Software Technology Zhejiang University Ningbo China DBAPPSecurity Ltd. College of Computer Science Zhejiang University Hangzhou China

In the process of quantitative cardiac analysis based on echocardiography, the localization of right ventricle anatomical landmarks is a critical step. However, manual labeling of these landmarks by professional physicians is a costly, time-consuming, and labor-intensive process that is also prone to both inter-observer and intra-observer variations. Therefore, we propose n heatmap regression approach to automatically locate right ventricle anatomical landmarks on echocardiography. Firstly, we propose an improved U-Net model, which has a stronger ability to extract features and exploit relationships between the coordinates of landmarks. Secondly, we analyze the limitations of L2 loss in our task. Building on this analysis, we propose a new loss function, Weighted Smooth L1 loss, which not only balances foreground and background pixels but also makes the model more robust to noise. Experiments show that the proposed improved U-Net and Weighted Smooth L1 loss can effectively enhance the landmark localization effect of the model.

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Energy Data Center: Review and Vision

Energy Data Center: Review and Vision

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Sustainable Power and Energy Conference (iSPEC)

作者： Hankai Sun Chaoyue Wu Panhao Qin Yan Huang Jing Peng Yinbin Yang School of Computer Science & Technology China University of Mining and Technology Xuzhou China School of Software(Suzhou) Southeast University Suzhou China

ISBN: (纸本)9781665414401

With the development of the smart grid, energy Internet, and big data technology, value mining and collaborative analysis of various energy data have become a hot direction of current energy research. As a platform for the aggregate analysis of various energy data such as hydropower, oil, and gas, the energy data center can explore the value of data and derive various applications based on historical energy data, real-time data, and other information. Based on the introduction of the current research status and basic concepts of the energy data center, this paper introduces the overall architecture of the energy data center and demonstrates the critical technology research related to the energy data center. Finally, the application status of the energy data center is carried out from multiple perspectives Summary and outlook

关键词： Data centers Oils Conferences Hydroelectric power generation Collaboration Big Data applications Real-time systems

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Automatic Text Summarization Method Based on Improved Textrank Algorithm and K-Means Clustering

SSRN

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SSRN 2023年

作者： Liu, Wenjun Sun, Yuyan Yu, Bao Wang, Hailan Peng, Qingcheng Hou, Mengshu Guo, Huan Wang, Hai Liu, Cheng Chengdu611731 China School of Computer and Software Engineering XiHua University Chengdu610039 China School of Big Data and Artificial Intelligence Chengdu Technological University Chengdu611730 China Science and Technology on Communication Security Laboratory The 30th Research Institute of China Electronics Technology Group Corporation Chengdu610041 China

Automatic text summarization is to obtain a summary by compressing the text while retaining its important information, and then users can obtain the important content of the text by reading the summary. In the research literatures, the extraction method is widely used and is also one of the main research methods of most abstracts. However, this summary method still has some problems. The selection of the initial cluster center has not been carefully determined, and in articles with complex sentences, the sentence redundancy summarized is high. In order to solve the above problems, this paper proposes an automatic text summarization method based on improved TextRank algorithm and K-Means clustering. This method uses the improved BM25 model to calculate the BM25 similarity between sentences, and then uses the TextRank model to obtain the TR score of sentences. Then, the TR score is used to select the initial center of K-Means clustering. Finally, the summary is obtained through the class score and sentence score. The experimental results show that the proposed BM25Rank algorithm has a better effect on DUC2004 dataset. In conclusion, the improved TextRank and K-Means method proposed in this paper improve the accuracy of automatic text summarization and reduce the redundancy. © 2023, The Authors. All rights reserved.

关键词： K-means clustering

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software quality assessment model: a systematic mapping study

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science China(Information sciences) 2019年第9期62卷 5-22页

作者： Meng YAN Xin XIA Xiaohong ZHANG Ling XU Dan YANG Shanping LI College of Computer Science and Technology Zhejiang University Faculty of Information Technology Monash University School of Software Engineering Chongqing University

Quality model is regarded as a well-accepted approach for assessing, managing and improving software product quality. There are three categories of quality models for software products, i.e., definition model, assessment model, and prediction model. Quality assessment model(QAM) is a metric-based approach to assess the software quality. It is typically regarded as of high importance for its clear method on how to assess a system. However, the current state-of-the-art in QAM research is under limited *** address this gap, the paper provides an organized and synthesized summary of the current QAMs. In detail, we conduct a systematic mapping study(SMS) for structuring the relevant articles. We obtain a total of 716 papers from the five databases, and 31 papers are selected as relevant studies at last. In summary, our work focuses on QAMs from the following aspects: software metrics, quality factors, aggregation methods,evaluation methods and tool support. According to the analysis results, our work discovers five needs that researchers in this area should continue to address:(1) new method and criteria to tailor a quality framework(i.e., structure of software metrics and quality factors) according to different specifics,(2) systematic investigations on the effectiveness, strength and weakness of different aggregation methods to guide the method selection in different context,(3) more investigations on evaluating QAMs in the context of industrial cases,(4) further investigations or real-world case studies on the QAMs related tools, and(5) building a public and diverse software benchmark which can be adopted in different application context.

关键词： software quality systematic mapping study quality assessment model aggregation method

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A Novel Image Segmentation Algorithm Based on Hesitant Neutrosophic and Level Set

A Novel Image Segmentation Algorithm Based on Hesitant Neutr...

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Electronic Information technology and Smart Agriculture (ICEITSA), International Conference on

作者： Yiran Zheng Lan Zhang Anhui University of Technology School of Computer Science and Technology Anhui China Yunnan university Natioal Pilot School of software Yunnan China

ISBN: (纸本)9781665413015

The first step of dermoscopy image analysis technology is image segmentation, the segmentation result will directly affect the subsequent processing process, aiming at the background noise, blurred edge and gray uneven dermoscopy image, a new image segmentation method combining the hesitant neutrosophic set with level set is proposed. Firstly, the image is transformed into the hesitant neutrosophic image by using the hesitant neutrosophic set theory. The hesitant neutrosophic set image is composed of three subsets (T, I, F), and the hesitant neutrosophic image is used to highlight the target information and edge information of the image. Then, we improved the traditional DRLSE level set, constructed a new edge stop function, and added a gray energy term. Finally, we used the improved DRLSE level set to test the ISIC(2018) dermoscopy image. The Jaccard Index values of the experimental results are all greater than 95%, and the mean square error (MSE), peak signal-to-noise ratio (PNSR) and structural similarity Index (SSIM) all perform well, indicating that the proposed method can accurately and effectively segment the skin mirror images with fuzzy edges and uneven gray scales. It's a foundation for the processing and diagnosis of the subsequent dermoscopy image.

关键词： Image segmentation PSNR Level set Image edge detection Mean square error methods Set theory Skin

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SUBGRAPH-UNIVERSAL PLANAR GRAPHS FOR TREES

arXiv

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arXiv 2024年

作者： Bergold, Helena Iršič, Vesna Lauff, Robert Orthaber, Joachim Scheucher, Manfred Wesolek, Alexandra Technical University of Munich Germany TUM School of Computation Information and Technology Department of Computer Science Germany Freie Universität Berlin Germany Faculty of Mathematics and Physics University of Ljubljana Slovenia Institute of Mathematics Physics and Mechanics Ljubljana Slovenia Institut für Mathematik Technische Universität Berlin Germany Institute of Software Technology Graz University of Technology Austria

We show that there exists an outerplanar graph on O(nc) vertices for c = log2(3 + √10) ≈ 2.623 that contains every tree on n vertices as a subgraph. This extends a result of Chung and Graham from 1983 who showed that there exist (non-planar) n-vertex graphs with O(n log n) edges that contain all trees on n vertices as subgraphs and a result from Gol’dberg and Livshits from 1968 who showed that there exists a universal tree for n-vertex trees on nO(log(n)) vertices. Furthermore, we determine the number of vertices needed in the worst case for a planar graph to contain three given trees as subgraph to be on the order of 3/2n, even if the three trees are caterpillars. This answers a question recently posed by Alecu et al. in 2024. Lastly, we investigate (outer)planar graphs containing all (outer)planar graphs as subgraph, determining exponential lower bounds in both cases. We also construct a planar graph on nO(log(n)) vertices containing all n-vertex outerplanar graphs as *** Codes 05C05, 05C10, 05C78 © 2024, CC BY.

关键词： Graph theory

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BERT Multilingual and Capsule Network for Arabic Sentiment Analysis

BERT Multilingual and Capsule Network for Arabic Sentiment A...

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International Conference on computer, Control, Electrical, and Electronics Engineering (ICCCEEE)

作者： Zeinab Obied Aiman Solyman Atta Ullah Ahmed Fat’hAlalim Alhag Alsayed School of computer science and engineering Wuhan University of Technology Wuhan China School of Software South China University of Technology Guangzhou China

Sentiment Analysis (SA) is one of the fast-growing research tasks in Natural Language Processing (NLP), which aims to identify the attitude of online users or communities regarding to a specific topic, service, or product. It helps to evaluate the overall tonality of a document to make a good decision in the right direction. Arabic SA still growing slowly compared to English and Chinese languages because of some challenges including lack of corpora, Arabic language complexity, and the spread of many local Arabic dialects. The current study presents a work-in-progress for Arabic SA based on capsule network and Google BERT *** Google language model achieved state-of-the-art results for several NLP tasks, that aim to pre-train deep bidirectional (right and left) representations on the context in all layers. Recently, capsule networks become one of the most successful techniques in image processing and NLP, it is consists of a group of neurons that represents different features of the same entity. Each layer in a capsule network contains many capsules that encode spatial information and the likelihood of existing input data. Not like traditional neural techniques, capsule networks allow the model to capture the likeliness of each feature and its variants, which affects positively the quality of the final predicted features. The proposed model was trained based on a small dataset. Although, the results were encouraging and competitive compared to the state-of-the-art Arabic SA models.

关键词： Training Sentiment analysis Bit error rate Training data Process control Tools Predictive models

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SIBW: A Swarm Intelligence-Based Network Flow Watermarking Approach for Privacy Leakage Detection in Digital Healthcare Systems

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IEEE Journal of Biomedical and Health Informatics 2025年 PP卷 PP页

作者： Qiao, Sibo Guo, Qiang Shi, Fengdong Wang, Min Zhu, Haohao Khan, Fazlullah Rodrigues, Joel J.P.C. Lyu, Zhihan School of Software Tiangong University Tianjin300387 China School of Artificial Intelligence Tiangong University Tianjin300387 China National Demonstration Center for Experimental Engineering Training Education Tiangong University Tianjin300387 China School of Life Sciences Tiangong University Tianjin300387 China School of Control Sciences and Engineering Tiangong University Tianjin300387 China School of Computer Science Faculty of Science and Engineering University of Nottingham Ningbo China Zhejiang Ningbo315104 China Higher School of Technology Amazonas State University Amazonas Manaus69050-010 Brazil Department of Game Design Faculty of Arts Uppsala University Uppsala Sweden

The exponential growth of sensitive patient information and diagnostic records in digital healthcare systems has increased the complexity of data protection, while frequent medical data breaches severely compromise system security and reliability. Existing privacy protection techniques often lack robustness and real-time capabilities in high-noise, high-packet-loss, and dynamic network environments, limiting their effectiveness in detecting healthcare data leaks. To address these challenges, we propose a Swarm Intelligence-Based Network Watermarking (SIBW) method for real-time privacy data leakage detection in digital healthcare systems. SIBW integrates fountain codes with outer error correction codes and employs a Multi-Phase Synergistic Swarm Optimization Algorithm (MPSSOA) to dynamically optimize encoding parameters, significantly enhancing the robustness and interference resistance of watermark detection. Additionally, a reliable synchronization sequence and lightweight embedding mechanism are designed to ensure adaptability to complex, dynamic networks. Experimental results demonstrate that SIBW achieves over 90% detection accuracy under high latency jitter and packet loss conditions, surpassing existing methods in both robustness and efficiency. With a compact design of only 3.7 MB, SIBW is particularly suited for rapid deployment in resource-constrained digital healthcare systems. © 2013 IEEE All rights reserved.

关键词： Information leakage

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Age-Aware Query Evaluation for Big Data Analytics in Mobile Edge Clouds 22

Age-Aware Query Evaluation for Big Data Analytics in Mobile ...

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22nd IEEE International Conference on High Performance Computing and Communications, 18th IEEE International Conference on Smart City and 6th IEEE International Conference on Data science and Systems, HPCC-SmartCity-DSS 2020

作者： Xia, Qiufen Ren, Wenhao Li, Mingchu Ren, Jiankang Dalian University of Technology International School of Information Science and Engineering Dalian116621 China Dalian University of Technology School of Software Dalian116621 China Dalian University of Technology School of Computer Science and Technology Dalian116024 China

ISBN: (纸本)9781728176499

The advancement of 5G technology and extensive usage of smart devices have led to a deluge of data. It is invaluable to analyze such big data by issuing queries to derive real-Time business insights for better, smarter and fact-based decisions. Timely big data analytics are crucial in many service domains, thus the age of data (AoD) required by queries is emerging as a novel metric that measures the freshness of data and evaluates the quality of data analytics. Traditional big data analytics that are performed in remote clouds cannot satisfy the AoD requirements of queries, due to the congested core networks and long transmission latency between users and clouds. The technique of mobile edge computing (MEC) is expected to reduce the age and guarantee the timeliness of queries for big data analytics, by processing data at edge cloudlets close to users. In this paper, we investigate a problem of age-Aware query evaluation for big data analytics in a mobile edge cloud network. We first formulate the problem with certain data processing latency as an Integer Linear Program (ILP). We then develop an online learning algorithm for the problem with uncertain data processing latency. We finally evaluate the performance of proposed algorithms against existing studies by simulations and testbed implementations. Evaluation results show that the proposed algorithms outperform existing works by achieving 20% lower AoD. © 2020 IEEE.

关键词： Data Analytics

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