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Efficient Routing Protection Algorithm Based on Optimized Network Topology

computers, Materials & Continua 2022年第9期72卷 4525-4540页

作者： Haijun Geng Zikun Jin Jiangyuan Yao Han Zhang Zhiguo Hu Bo Yang Yingije Guo Wei Wang Qidong Zhang Guoao Duan School of Computer and Information Technology Shanxi UniversityShanxi030006China School of Automation and Software Engineering Shanxi UniversityShanxi030006China School of Computer Science and Technology Hainan UniversityHaikou570228China Department of Computer Science&Technology Tsinghua UniversityBeijing100084China Department of Urban&Regional Planning San JoséState University San JoséCA95192USA Key Laboratory of Embedded System and Service Computing(Tongji University) Ministry of EducationShanghai201804China Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of ChinaChengdu610054China Beijinng University of Technology Beijing-Dublin International CollegeBeijing University of TechnologyBeijing100124China

Network failures are unavoidable and occur *** the network fails,intra-domain routing protocols deploying on the Internet need to undergo a long convergence *** this period,a large number of messages are discarded,which results in a decline in the user experience and severely affects the quality of service of Internet Service Providers(ISP).Therefore,improving the availability of intra-domain routing is a trending research question to be *** usually employs routing protection algorithms to improve intra-domain routing ***,existing routing protection schemes compute as many backup paths as possible to reduce message loss due to network failures,which increases the cost of the network and impedes the methods deployed in *** address the issues,this study proposes an efficient routing protection algorithm based on optimized network topology(ERPBONT).ERPBONT adopts the optimized network topology to calculate a backup path with the minimum path coincidence degree with the shortest path for all source ***,the backup path with the minimum path coincidence with the shortest path is described as an integer programming *** the simulated annealing algorithm ERPBONT is used to find the optimal ***,the algorithm is tested on the simulated topology and the real *** experimental results show that ERPBONT effectively reduces the path coincidence between the shortest path and the backup path,and significantly improves the routing availability.

关键词： Routing protection algorithm network availability network failure shortest path backup path

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Enhancing Dental Caries Identification with Deep Learning: A Study of Convolutional Neural Networks and Transfer Learning Approaches

SSRN

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SSRN 2024年

作者： Mannan, Fayqa Adeel, Muhammad Arif, Erssa Li, Jianqiang Ullah, Amin Nawazish, Samra Mahmood, Tariq Rehman, Amjad Shoukat, Ijaz Faculty of Information Technology Beijing University of Technology Beijing100124 China Department of Computer Science Government College University Faisalabad38000 Pakistan Department of Computer Science School of Science National Textile University Faisalabad37610 Pakistan Department of Computer Science Faculty of Computing Riphah International University Faisalabad38000 Pakistan Beijing Engineering Research Center for IoT Software and Systems 100124 China Department of Computer Science Faculty of IT and Computer Science University of Central Punjab Lahore Pakistan School of Computer Science and Engineering Southeast University Nanjing China Software Engineering Department University of Engineering and Technology Taxila Pakistan Artificial Intelligence & Data Analytics Lab CCIS Prince Sultan University Riyadh11586 Saudi Arabia Faculty of information Sciences University of Education Vehari Campus Vehari61100 Pakistan

Various deep learning techniques have been employed to diagnose dental caries using X-ray images. In this study, we utilized deep learning models, including Convolutional Neural Networks (CNNs) and transfer learning models such as Visual Geometry Group (VGG16), VGG19, ResNet50, and Inception V3, to identify dental caries in periapical radiographs. The traditional CNN model comprises three sets of 2D convolutional layers, followed by an activation layer, a max-pooling layer, a flatten layer, one dense layer, another activation layer, dropout, another dense layer, and a final activation layer. For the VGG models, ResNet50, and Inception V3, the top convolutional layers were frozen to prevent retraining of the model, with only the last layers trained to produce the required output. The accuracy achieved by CNN, VGG16, VGG19, ResNet50, and Inception V3 was 90%, 96%, 73%, 70%, and 73%, respectively. VGG16 exhibited the highest accuracy among the models. Hyperparameters were carefully selected using a grid search approach, and the results were validated using the Shuffle-Split-Cross (SSC) validation method. These findings underscore the effectiveness of transfer learning in analyzing medical images, particularly in the diagnosis of dental caries. © 2024, The Authors. All rights reserved.

关键词： Convolutional neural networks

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Genetic overlap between household income and psychiatric disorders

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Schizophrenia research 2025年 282卷 95-104页

作者： Jianfei Zhang Guangxing Zhang Qiyu Zhao Yanmin Peng College of Computer and Control Engineering Qiqihar University Qiqihar 161006 Heilongjiang China. Department of Radiology and Tianjin Key Laboratory of Functional Imaging Tianjin Medical University General Hospital Tianjin 300052 China. School of Medical Imaging and Tianjin Key Laboratory of Functional Imaging Tianjin Medical University Tianjin 300204 China. Electronic address: pymnn@***.

Household income (HI), a significant socioeconomic factor influencing mental health, has seen its association with various mental disorders garnering increasing attention. However, the common genetic basis between HI and psychiatric disorders remains poorly understood. Utilizing genome-wide association study (GWAS) pooled statistics for HI, schizophrenia (SCZ), attention deficit hyperactivity disorder (ADHD), bipolar disorder (BIP), and autism spectrum disorders (ASD), bivariate mixed models of causality (MiXeR) were employed to quantify the shared genetic architecture between HI and psychiatric disorders. The conjunctional false discovery rate (conjFDR) approach was utilized to identify specific shared loci, and the resulting shared genetic loci were analyzed for functional annotation and gene set enrichment. The MiXeR analysis revealed that among the 8.9 K variants affecting HI, 8.7 K were shared with SCZ, 7.8 K with ADHD, 6.2 K with BIP, and 8.7 K with ASD. A total of 344 shared genetic loci were identified between HI and psychiatric disorders using the conjFDR method, with 254 of them being novel. Additionally, the shared loci of HI with SCZ and ADHD mainly demonstrated opposite effect directions, while those with BIP and ASD mainly exhibited mixed effect directions. Functional annotation indicated that the shared genetic loci were predominantly located in intronic and intergenic regions, and enrichment analysis demonstrated that they were involved in nervous system development, multicellular organism development, and neuron differentiation. In conclusion, our study reveals a shared genetic architecture between HI and psychiatric disorders, highlighting common biological processes that may contribute to understanding their complex etiologies and overlapping genetic mechanisms.

关键词： Genetic overlap Genome-wide association studies (GWAS) Household income (HI) Psychiatric disorders

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Industrial Semantic Communications for Tool Wear Monitoring in Industrial IoT Networks

Industrial Semantic Communications for Tool Wear Monitoring ...

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IEEE International Conference on Communications in China Workshops (ICCC)

作者： Mingqiang Zhang Yajuan Yang Baokun Song Zexin Chen Xiaocong Ma Dongyang Li Na Li Feng Cao Yanping Zhang Haixia Zhang School of Cyber Science and Engineering Qufu Normal University Qufu China College of Oceanography and Space Informatics China University of Petroleum (East China) Huangdao China School of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Jinan China School of Computer and Information Engineering Qilu Institute of Technology Jinan China School of Control Science and Engineering Shandong University Jinan China Shandong Key Laboratory of Intelligent Communication and Sensing-Computing Integration Shandong University Jinan China

ISBN: (数字)9798350377675

ISBN: (纸本)9798350377682

In this paper, we propose an Industrial Semantic Communications (ISC) framework to ensure efficient and in-telligent communication in Industrial Internet-of-Things (IIoT) networks, and further apply the proposed framework to the task of tool wear monitoring. A semantic-aware tool wear monitoring network (TWM-Net) is designed to accurately identify the idling state from tool wear data, thus assisting the semantic data transmission process of the ISC framework. Then, a demo software system is implemented to verify the delay performance of the proposed ISC framework. Experimental results demonstrated that the proposed ISC framework can facilitate the semantic information exchange between edge industrial system and cloud platform together with the deep compressed sensing method, and significantly reduce the amount of data transmissions in IIoT networks. The source code and dataset is available through https://***/pnixsoft/TWM-Net.

关键词： Vibrations Source coding software systems Multitasking Delays Data communication Monitoring Information exchange Industrial Internet of Things Testing

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A Simple Dashboard for OpenStack Horizon 4

A Simple Dashboard for OpenStack Horizon

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4th International Conference on Computing and Big Data, ICCBD 2021

作者： Wang, Hongbin Li, Shaoxu Deng, Dan Li, Leixiao Gao, Jing Li, Jie College of Data Science and Application Inner Mongolia University of Technology Hohhot China Inner Mongolia Autonomous Reg. Software Serv. Eng. Technology Research Center Based on Big Data Hohhot China College of Computer and Information Engineering Inner Mongolia Agricultural University Hohhot China

ISBN: (纸本)9781450387194

OpenStack is an open source cloud computing management project, which allows flexible resources applying. The traditional OpenStack dashboard is inflexible, thus a simple dashboard is designed. The simple dashboard integrates keystone, horizon, grace, nova, neutron, swift and other components, communicates with the traditional OpenStack dashboard and runs in the form of docker container. We implemented simple dashboard on a small cloud platform. Compared with the traditional dashboard, the interface of simple dashboard is simpler, more flexible and easy to use. © 2021 ACM.

关键词： Platform as a Service (PaaS)

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Classification of Real and Deepfakes Visual Samples with Pre-trained Deep Learning Models 7th

Classification of Real and Deepfakes Visual Samples with Pre...

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Proceedings of the 7th International Conference on Advances in Computing and Data Sciences, ICACDS 2023

作者： Nawaz, Marriam Javed, Ali Nazir, Tahira Khan, Muhammad Attique Rajinikanth, Venkatesan Kadry, Seifedine Department of Software Engineering UET Taxila Taxila47050 Pakistan Department of Computing Riphah International University Islamabad Pakistan Department of Computer Science HITEC University Taxila Pakistan Department of Computer Science and Engineering Division of Research and Innovation Saveetha School of Engineering SIMATS Chennai602105 India Department of Applied Data Science Noroff University College Kristiansand4612 Norway Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon

ISBN: (纸本)9783031379390

Serious security and privacy problems have arisen as a result of significant advancements in the creation of deepfakes. Attackers can easily replace a person’s face with the target person’s face in an image using sophisticated Deep learning (DL) algorithms to spoof their identity. Deepfakes detection algorithms have been proposed in response to the growing concerns about the potential harm caused by deepfakes. However, a reliable deepfakes detector that can keep up with contemporary deepfakes creation techniques is required. In this work, we have proposed an end-to-end methodology for detecting manipulated visual content. We used multiple CNN models i.e., ResNet18, ResNet50, DenseNet65, DenseNet77, and DenseNet100 along with the SVM classifier to compute effective cues from the input facial faces to distinguish between actual and altered content. We have also applied the concept of transfer learning to solve the issue of model over-fitting and improve generalizability against different manipulation algorithms. A comparison study is carried out to evaluate the performance of several feature extractors. Through thorough experiments performed using the Deepfakes Detection Challenge dataset, our results demonstrated that DenseNet100 surpasses the other CNN models by better recognizing deepfakes. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Learning algorithms

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DVS-RG: Differential Variable Speed Limits control using Deep Reinforcement Learning with Graph State Representation

arXiv

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arXiv 2024年

作者： Yang, Jingwen Wang, Ping Golpayegani, Fatemeh Wang, Shen School of Electronic and Control Engineering Chang'an University Shaanxi Xi’an710054 China School of Intelligent Systems Engineering Sun Yat-sen University Guangdong Shenzhen510006 China School of Computer Science University College Dublin Dublin4 D04 V1W8 Ireland

Variable speed limit (VSL) control is an established yet challenging problem to improve freeway traffic mobility and alleviate bottlenecks by customizing speed limits at proper locations based on traffic conditions. Recent advances in deep reinforcement learning (DRL) have shown promising results in solving VSL control problems by interacting with sophisticated environments. However, the modeling of these methods ignores the inherent graph structure of the traffic state which can be a key factor for more efficient VSL control. Graph structure can not only capture the static spatial feature but also the dynamic temporal features of traffic. Therefore, we propose the DVS-RG: DRLbased differential variable speed limit controller with graph state representation. DVS-RG provides distinct speed limits per lane in different locations dynamically. The road network topology and traffic information(e.g., occupancy, speed) are integrated as the state space of DVS-RG so that the spatial features can be learned. The normalization reward which combines efficiency and safety is used to train the VSL controller to avoid excessive inefficiencies or low safety. The results obtained from the simulation study on SUMO show that DRL-RG achieves higher traffic efficiency (the average waiting time reduced to 68.44%) and improves the safety measures (the number of potential collision reduced by 15.93% ) compared to state-of-the-art DRL methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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Sensing metric-based hybrid underlay/overlay transmission framework for CR-IoT networks for smart city applications

Sensing metric-based hybrid underlay/overlay transmission fr...

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7th IET Smart Cities Symposium (SCS 2023)

作者： Indu Bala Maad M. Mijwil Mostafa Abotaleb El-Sayed M. El-kenawy Abdelhameed Ibrahim School of Electrical and Electronics Engineering Lovely Professional University Punjab India Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

With the increasing number of IoT devices, there is a growing need for bandwidth to support their communication. Unfortunately, there is a shortage of available bandwidth due to preallocated bands for various services. To address this issue, Cognitive Internet of Things (CR-IoT) enables devices to optimize their efficiency and enhance their communication capabilities by intelligently accessing available bandwidth. This is achieved through the use of soft sensing metrics, where devices continuously monitor the RF environment and transmit data opportunistically in overlay mode if a free channel is detected, or in underlay mode if not. In this paper, a soft sensing metric based hybrid transmission framework is proposed for CR-IoT devices to meet the data rate requirement for the smart city applications. The efficacy of this approach is demonstrated through simulation results.

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FCloudless: A Performance-Aware Collaborative Mechanism for JointCloud Serverless

FCloudless: A Performance-Aware Collaborative Mechanism for ...

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IEEE International Conference on Joint Cloud Computing (JCC)

作者： Jianfei Liu Huaimin Wang Peichang Shi Yaojie Li Penghui Ma Guodong Yi National Key Laboratory of Parallel and Distributed Computing College of Computer Science National University of Defense Technology Changsha 410073 China Key Laboratory of Software Engineering for Complex Systems College of Computer Science National University of Defense Technology Changsha 410073 China Xiangjiang Lab Changsha 410073 China School of Advanced Interdisciplinary Studies Hunan University Of Technology and Business Changsha 410073 China

As a new stage in the development of the cloud computing paradigm, serverless computing has the high-level abstraction characteristic of shielding underlying details. This makes it extremely challenging for users to choose a suitable serverless platform. To address this, targeting the jointcloud computing scenario of heterogeneous serverless platforms across multiple clouds, this paper presents a jointcloud collaborative mechanism called FCloudless with cross-cloud detection of the full lifecycle performance of serverless platforms. Based on the benchmark metrics set that probe performance critical stages of the full lifecycle, this paper proposes a performance optimization algorithm based on detected performance data that takes into account all key stages that affect the performance during the lifecycle of a function and predicts the overall performance by combining the scores of local stages and dynamic weights. We evaluate FCloudless on AWS, AliYun, and Azure. The experimental results show that FCloudless can detect the underlying performance of serverless platforms hidden in the black box and its optimization algorithm can select the optimal scheduling strategy for various applications in a jointcloud environment. FCloudless reduces the runtime by 23.3% and 24.7% for cold and warm invocations respectively under cost constraints.

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End-to-End Delay Performance for Mobile Cyber-Physical Systems with Edge Computing 11

End-to-End Delay Performance for Mobile Cyber-Physical Syste...

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11th International Conference on Networks, Communication and Computing, ICNCC 2022

作者： Wu, Yan Yang, Qinghai Qiao, Feiyu Kwak, K.S. Leung, C.M. Pan, Guangchuan State Key Laboratory of ISN School of Telecommunications Engineering Xidian University No.2 South Taibai Road Shaanxi Xi'an710071 China Communication Engineering Inha University #100 Inha-Ro Nam-gu Incheon22212 Korea Republic of College of Computer Science and Software Engineering Shenzhen University 518060 China The Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada Xidian University No.2 South Taibai Road Shaanxi Xi'an710071 China

ISBN: (纸本)9781450398039

In this letter, we investigate the end-to-end (E2E) delay performance for mobile cyber-physical systems (M-CPS) with edge computing. The traditional delay analysis is based on flow conservation law, whereas the flow is not conserved in the M-CPS with edge computing due to the existence of edge computing node and remote controller. To tackle this problem, we introduce two scaling factors to ensure the flow conservation, then the E2E delay bound of M-CPS with edge computing is derived via stochastic network calculus. In addition, to cater for the delay demand for M-CPS stability, the stable-aware delay bound is obtained. Numerical results show the gap between the analytic bound and simulation can be narrower as the average signal-to-noise (SNR) growing. © 2022 ACM.

关键词： Cyber Physical System

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