检索结果-内蒙古大学图书馆

7th International Conference on Information Science, Communication and Computing, ISCC 2023

作者： Hua, Shuai Cheng, Jieren Han, Wenbao Xu, Wenhang Sheng, Victor S. School of Cyberspace Security Hainan University Haikou570228 China Hainan Blockchain Technology Engineering Research Center Haikou570228 China School of Computer Science and Technology Hainan University Haikou570228 China Department of Computer Science Texas Tech University LubbockTX79409 United States

ISBN: (纸本)9789819971602

At present, many of the popular semantic segmentation networks focus on accuracy and require a lot of computational overhead, which results in a very slow inference speed and is difficult to deploy in practical application scenarios. On the other hand, many works sacrifice the performance of segmentation networks in pursuit of real-time inference speed. Therefore, in semantic segmentation, balancing accuracy and real-time performance becomes a formidable challenge. For this challenge, we propose a lightweight semantic segmentation network that takes into account both accuracy and real-time performance, named CCMFRNet. The core components of CCMFRNet are the Context Cascade Module (CCM) and the Multi-scale Feature Refinement Module (MFRM). CCM consists of three Dense Cascade Dilated Convolution Modules (DCDM), which are cascaded in a short-term dense cascade, aiming to obtain rich multi-scale context information to enhance information representation. MFRM adopts the attention mechanism to realize deep features to guide the captured shallow multi-scale spatial features. It aims to capture high-quality and multi-scale shallow features to enrich the feature space and more effectively refine the spatial details information. The proposed method achieves an accuracy of 72.6% MIoU at speed of 32 fps on Cityscapes test datasets. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

A Blockchain-Based Architecture for Securing Industrial IoTs Data in Electric Smart Grid

引用

computers, Materials & Continua 2023年第3期74卷 5389-5416页

作者： Samir M.Umran Songfeng Lu Zaid Ameen Abduljabbar Xueming Tang School of Cyber Science and Engineering Huazhong University of Science and TechnologyWuhan430074China Iraqi Ministry of Industrial and Minerals Iraqi Cement State CompanyBaghdad10011Iraq Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen 518057China Department of Computer Science College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq

There are numerous internet-connected devices attached to the industrial process through recent communication technologies,which enable machine-to-machine communication and the sharing of sensitive data through a new technology called the industrial internet of things(IIoTs).Most of the suggested security mechanisms are vulnerable to several cybersecurity threats due to their reliance on cloud-based services,external trusted authorities,and centralized architectures;they have high computation and communication costs,low performance,and are exposed to a single authority of failure and *** technology(BC)is widely adopted in the industrial sector for its valuable features in terms of decentralization,security,and *** our work,we propose a decentralized,scalable,lightweight,trusted and secure private network based on blockchain technology/smart contracts for the overhead circuit breaker of the electrical power grid of the Al-Kufa/Iraq power plant as an industrial *** proposed scheme offers a double layer of data encryption,device authentication,scalability,high performance,low power consumption,and improves the industry’s operations;provides efficient access control to the sensitive data generated by circuit breaker sensors and helps reduce power *** also address data aggregation operations,which are considered challenging in electric power smart *** utilize a multi-chain proof of rapid authentication(McPoRA)as a consensus mechanism,which helps to enhance the computational performance and effectively improve the *** advanced reduced instruction set computer(RISC)machinesARMCortex-M33 microcontroller adopted in our work,is characterized by ultra-low power consumption and high performance,as well as efficiency in terms of real-time cryptographic algorithms such as the elliptic curve digital signature algorithm(ECDSA).This improves the computational execution,increases the implementation speed of the asymmetric c

关键词： Smart grids industrial IoTs electric power system blockchain technology IoT applications industry 4.0 decentralization applications

来源：评论

学校读者我要写书评

暂无评论

Machine Learning for Real-Time Language Translation: A Server-Side Approach to Overcome Cross-Cultural Communication Challenges

Machine Learning for Real-Time Language Translation: A Serve...

引用

Soft Computing for security Applications (ICSCSA), International Conference on

作者： S. Elango Mohanaprakash T A D. Siva Gowtham A Sasikumar A N Sunitha T Department of Computer Science and Engineering SOET CMR University Bengaluru Department of Computer Science and Applications SRM Institute of Science and Technology Chennai Department of CSE (Cyber Security) Madanapalle Institute of Technology & Science AP India Department of Computer Science and Engineering Panimalar Engineering College Chennai India Department of Artificial Intelligence & Data Science Saveetha Engineering College Chennai India

ISBN: (数字)9798331515720

ISBN: (纸本)9798331515737

The evolution of human civilization has been intrinsically linked to advancements in technology, leading to the development of multiple languages as mediums of communication. However, this linguistic diversity poses significant challenges in cross-cultural communication. Despite numerous efforts and achieving near state-of-the-art results in language translation, a universal solution remains elusive. This research study proposes an advanced approach to machine translation by utilizing server-side machine learning to enable seamless communication across various languages. By sending GET or POST requests through JQuery, users can efficiently translate text. The process is structured into three key steps: speech recognition (conversion of spoken words to text), translation using machine learning algorithms, and speech synthesis (conversion of translated text to audio). This approach aims to enhance real-time translation capabilities, offering a more effective and user-friendly solution for overcoming language barriers.

关键词： Translation Machine learning algorithms Speech recognition Machine learning Speech enhancement Cross-cultural communication Real-time systems Speech synthesis Machine translation security

来源：评论

学校读者我要写书评

暂无评论

Anchor Learning with Potential Cluster Constraints for Multi-view Clustering 39

Anchor Learning with Potential Cluster Constraints for Multi...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Chen, Yawei Wang, Huibing Peng, Jinjia Wang, Yang School of Information Science and Technology Dalian Martime University Dalian China School of Cyber Security and Computer Hebei University Baoding China School of Computer Science and Information Engineering Hefei University of Technology Hefei China

ISBN: (纸本)157735897X

Anchor-based multi-view clustering has received extensive attention due to its efficient performance. Existing methods only focus on how to dynamically learn anchors from the original data and simultaneously construct anchor graphs describing the relationships between samples and perform clustering, while ignoring the reality of anchors, i.e., high-quality anchors should be generated uniformly from different clusters of data rather than scattered outside the clusters. To deal with this problem, we propose a noval method termed Anchor Learning with Potential Cluster Constraints for Multi-view Clustering (ALPC) method. Specifically, ALPC first establishes a shared latent semantic module to constrain anchors to be generated from specific clusters, and subsequently, ALPC improves the representativeness and discriminability of anchors by adapting the anchor graph to capture the common clustering center of mass from samples and anchors, respectively. Finally, ALPC combines anchor learning and graph construction into a unified framework for collaborative learning and mutual optimization to improve the clustering performance. Extensive experiments demonstrate the effectiveness of our proposed method compared to some state-of-the-art MVC methods. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Cluster analysis

来源：评论

学校读者我要写书评

暂无评论

Efficient Segmentation Approach for Different Medical Image Modalities

引用

computers, Materials & Continua 2022年第11期73卷 3119-3135页

作者： Walid El-Shafai Amira A.Mahmoud El-Sayed M.El-Rabaie Taha E.Taha Osama F.Zahran Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

This paper presents a study of the segmentation of medical *** paper provides a solid introduction to image enhancement along with image segmentation *** the first step,the morphological operations are employed to ensure image detail protection and *** objective of using morphological operations is to remove the defects in the texture of the ***,the Fuzzy C-Means(FCM)clustering algorithm is used to modify membership function based only on the spatial neighbors instead of the distance between pixels within local spatial neighbors and cluster *** proposed technique is very simple to implement and significantly fast since it is not necessary to compute the distance between the neighboring pixels and the cluster *** is also efficient when dealing with noisy images because of its ability to efficiently improve the membership partition *** results are performed on different medical image ***(Us),X-ray(Mammogram),Computed Tomography(CT),Positron Emission Tomography(PET),and Magnetic Resonance(MR)images are the main medical image modalities used in this *** obtained results illustrate that the proposed technique can achieve good results with a short time and efficient image *** results on different image modalities show that the proposed technique can achieve segmentation accuracies of 98.83%,99.71%,99.83%,99.85%,and 99.74%for Us,Mammogram,CT,PET,and MRI images,respectively.

关键词： Image segmentation ultrasonic mammogram CT PET MRI morphological operations FCM active contours

来源：评论

学校读者我要写书评

暂无评论

Genetic-based Framework for Joint Latency and Cost Reduction in Edge-Fog Environments

Genetic-based Framework for Joint Latency and Cost Reduction...

引用

CSI Symposium on Real-Time and Embedded Systems and Technologies (RTEST)

作者： Sadra Galavani Soheil Mahdizadeh Mohammad Pourashory Amir Mahdi Rasouli Mohsen Ansari Department of Computer Engineering Cyber-Physical Systems Laboratory (CPSLab) Sharif University of Technology Tehran Iran

ISBN: (数字)9798331529284

ISBN: (纸本)9798331529291

Reducing latency in the Internet of Things (IoT) remains a critical concern. While cloud computing facilitates communication, it falls short of meeting real-time requirements reliably. Edge and fog computing have emerged as viable solutions by positioning computing nodes closer to end users, offering lower latency and increased processing power. An edge-fog framework comprises various components, including edge and fog nodes, whose strategic placement is crucial as it directly impacts latency and system cost. This paper presents an effective and tunable node placement strategy based on a genetic algorithm to address the optimization problem of deploying edge and fog nodes. The task assignment for this algorithm involves two key components: first, it identifies the nearest node to a given user; second, it assesses the node’s capacity to ensure it has sufficient frequency resources to handle the assigned tasks. The ultimate objective is to minimize latency and cost through optimal node placement. Simulation results demonstrate the proposed framework achieves up to 8.4% latency and 65.2% cost reduction.

关键词： Costs Heuristic algorithms Simulation Refining Real-time systems Internet of Things Reliability Optimization Genetic algorithms Edge computing

来源：评论

学校读者我要写书评

暂无评论

Cryptocurrency-Enabled Energy Trading in Micro-Grid Using Blockchain technology

Cryptocurrency-Enabled Energy Trading in Micro-Grid Using Bl...

引用

cyber Resilience (ICCR), International Conference on

作者： Ahsan Waseem Mohd Bilal Abhishek Bhardwaj M Saad Bin Arif Taher M. Ghazal Department of Electrical Engineering Aligarh Muslim University Aligarh India Computer Science Department Faculty of Information Science and Technology Centre for Cyber Physical Systems Khalifa University Center for Cyber Security Universiti Kebangsaan Malaysia (UKM) Bangi Selangor Malaysia

ISBN: (数字)9798350394962

ISBN: (纸本)9798350394979

This article explores energy trading in grid-connected microgrids powered by renewable sources, utilizing cryptocurrency and blockchain technology. Through net metering, it emphasizes the proactive roles of prosumers and consumers in managing excess energy. The study investigates peer-to-peer energy transfers with blockchain-based cryptocurrencies, high-lighting their advantages in affordability, trade efficiency, and openness. Real-world case like LO3 Energy and Power Ledger are examined to address regulation, scalability, and cybersecurity concerns. The paper explores blockchain-enabled energy trade revolutionizing the industry, enhancing community resilience, accelerating renewable energy adoption, and reducing reliance on outdated technologies.

关键词： Renewable energy sources Shape Scalability Smart contracts Regulation Blockchains Cryptocurrency

来源：评论

学校读者我要写书评

暂无评论

Rapid Autonomy Transfer in Reinforcement Learning with a Single Pre- Trained Critic 36

Rapid Autonomy Transfer in Reinforcement Learning with a Sin...

引用

36th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2024

作者： Karim, Muhammad Faraz Deng, Yunjie Niu, Luyao Ramasubramanian, Bhaskar Alexiou, Michail Sahabandu, Dinuka Poovendran, Radha Mertoguno, Sukarno Georgia Institute of Technology AtlantaGA United States University of Washington Network Security Lab Department of Electrical and Computer Engineering SeattleWA United States Western Washington University Electrical and Computer Engineering BellinghamWA United States Kennesaw State University MariettaGA United States

ISBN: (纸本)9798331527235

Reinforcement learning (RL) is a well-studied framework to solve complex decision-making problems in unknown environments. The actor-critic model in RL facilitates autonomy transfer by allowing agents to iteratively update their policies using ongoing dynamic evaluations of value functions via a critic. In this paper, we examine the impact of using different pretrained critics on the performance of actor-critic algorithms. First, in any single given environment, we show that a pretrained critic can be effective in reducing the duration of an initial training phase, thereby accelerating convergence by a factor of up to 2×. In this setting, we identify the critical range of the number of episodes for which a critic will need to be trained in order for it to be an effective pretrained critic. Second, we show that a critic trained in one environment enables transfer of autonomy by aiding learning of behaviors in a different, yet related environment. We carry out extensive experiments on a bipedal locomotion task in the MuJoCo physics engine to verify our hypotheses. Our results in this paper mark the first step towards demonstrating the role and impact of pretrained critics to achieve rapid autonomy transfer for complex reinforcement learning tasks while minimizing costs associated with retraining in new environments. © 2024 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

An Improved Neural Classification Logic to Predict Kidney Disease Identification Using Medical Image Processing Principles

An Improved Neural Classification Logic to Predict Kidney Di...

引用

2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2024

作者： Balaji, C.G. Balachandran, G. Imran, Md. Ujwala, S.Vamsi Edlabadkar, Ajinkya P. Fawareh, Hamed Department of Digital and Telecom Management Lavale Maharashtra Pune412115 India Jeppiaar Engineering College Department of Ece Rajiv Gandhi salai Chennai119 India Qis College of Engineering and Technology Department of S&h Pondur Road Vengamukkapalem Ongole Prakasam AndhraPradesh PrakasamDistrict523272 India Qis College of Engineering and Technology Department of Mba Pondur Road Vengamukkapalem Ongole Prakasam Andhra Pradesh PrakasamDistrict523272 India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India College of Information Technology Zarqa University Department of Cyber Security zarqa Jordan University of Business and Technology Jeddah21448 Saudi Arabia

ISBN: (纸本)9798331543617

Kidney disease is a significant global health concern, requiring accurate and early diagnosis to prevent progression and ensure timely treatment. This study proposes an improved neural classification logic combining an AutoEncoder and an Artificial Neural Network (ANN) to predict kidney disease using medical image processing techniques. A dataset comprising kidney images from CT, MRI, and ultrasound was utilized to train and test the model. The AutoEncoder was employed for unsupervised feature extraction, reducing dimensionality while retaining key information related to kidney abnormalities. The ANN then classified these features into healthy or diseased categories. Image preprocessing techniques such as noise reduction, resizing, normalization, and contrast enhancement were applied to ensure data consistency. Additionally, advanced segmentation algorithms like U-Net were used to isolate the kidney regions from the background, focusing on the Regions of Interest (ROI). Data augmentation was applied to improve generalization. The proposed model achieved a classification accuracy of 94.8%, outperforming baseline models such as CNN (92.1 %) and SVM (88.7%). The AutoEncoder + ANN combination demonstrated superior precision, recall, and Fl-score, with an AUC-ROC of 97.4%. The results highlight the model's robustness and potential for practical applications in the early detection of kidney disease. © 2024 IEEE.

关键词： Noise abatement

来源：评论

学校读者我要写书评

暂无评论

Hybrid Segmentation Approach for Different Medical Image Modalities

引用

computers, Materials & Continua 2022年第11期73卷 3454-3471页

作者： Walid El-Shafai Amira A.Mahmoud El-Sayed M.El-Rabaie Taha E.Taha Osama F.Zahran Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

The segmentation process requires separating the image region into sub-regions of similar *** sub-region has a group of pixels having the same characteristics,such as texture or *** paper suggests an efficient hybrid segmentation approach for different medical image modalities based on particle swarm optimization(PSO)and improved fast fuzzy C-means clustering(IFFCM)*** extensive comparative study on different medical images is presented between the proposed approach and other different previous segmentation *** existing medical image segmentation techniques incorporate clustering,thresholding,graph-based,edge-based,active contour,region-based,and watershed *** paper extensively analyzes and summarizes the comparative investigation of these ***,a prediction of the improvement involves the combination of these techniques is *** obtained results demonstrate that the proposed hybrid medical image segmentation approach provides superior outcomes in terms of the examined evaluation metrics compared to the preceding segmentation techniques.

关键词： Image segmentation ultrasonic images X-ray images CT images PET images MR images fuzzy c-mean morphological operations active contour

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：