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8th International Conference on Intelligent Computing and Signal Processing, ICSP 2023

作者： Yang, Chuxiong Chen, Zhuang Chongqing University of Posts and Telecommunications School of Software Engineering Chongqing China Chongqing University of Technology College of Computer Science and Engineering Chongqing China

ISBN: (纸本)9798350302455

The algorithm proposed in this paper aims to address the issue of structural content distortions in images that occur after applying image style transfer. It introduces a structural consistency-based approach called the PoolNet algorithm. This algorithm incorporates saliency regions to perform style transfer at the block level. By employing a saliency detection network, a saliency map is generated for both the synthetic and content images. During the training process, two losses are computed to ensure that the salient regions in the synthetic image remain consistent with those in the content image. Additionally, local affine constraints in the color space are employed to enhance the stylized images by constraining the image transformation. Experimental results demonstrate that the stylized images produced by this style transfer model exhibit improved visual effects and preserve the semantic information of the content images. This improvement is particularly noticeable when dealing with distorted migration images. © 2023 IEEE.

关键词： Convolutional neural networks

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Design of a Smart and Green Industry 4.0 Architecture 24

Design of a Smart and Green Industry 4.0 Architecture

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24th International Arab Conference on Information Technology, ACIT 2023

作者： Hamdan, Khaled Kazar, Okba College of It Uaeu Dept. of Computer Science and Software Engineering United Arab Emirates College of It Uaeu Dept. of Information Systems & Security United Arab Emirates

ISBN: (纸本)9798350384307

The industrial sector has entered a phase of profound change which sees digital technologies being integrated into the heart of industrial processes. This fourth industrial era gives birth to a new generation of factory called 'Digital Factory', 'Industry 4.0'. This industrial change is the result of the integration of new digital technologies into manufacturing processes and the optimization of energy consumption. The commitment to the environment is also a key and success factor of Industry 4.0 and green in particular the reduction of carbon emissions and pollution. This is how smart green industry try to take in charge the problem of energy consumption and to reduce the Co2 pollution. The goal of this paper is to present the new model of smart green industry using distributed artificial intelligence based on multi-agent system (MAS). The motivation to use the intelligent approach based on MAS is based on the similarity between the fundamental concepts of the cyber-physical system and those contained in the architecture and operation of MAS such as communication, coordination, decision and cooperation. © 2023 IEEE.

关键词： environmental impact Industry 4.0 smart and green Industry 4.0

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Kubernetes Cluster Disaster Recovery Using AWS 7

Kubernetes Cluster Disaster Recovery Using AWS

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2023 7th International Conference On Computing, Communication, control And Automation, ICCUBEA 2023

作者： Bhavsar, Simran Agrawal, Apoorva Ropalkar, Tanvi Kamdi, Pranjali Hajare, Aparna Deshpande, Shilpa Rathi, Rahul Garg, Devendra Cummins College of Engineering for Women Dept. of Computer Engineering Pune India Veritas Software Technologies India Private Limited Pune India

ISBN: (纸本)9798350304268

As applications in IT have been spanning multiple containers across servers, kubernetes is being used extensively for automating software deployment, scaling and management. Kubernetes eases the container tasks and also other activities like horizontal scaling and canary development. To run cloud-native applications, kubernetes has become the de facto standard for container orchestration, regardless of the underlying platform. This makes it very crucial to have a disaster recovery plan for kubernetes environments. This paper proposes a system for backup and restore of a kubernetes cluster using the snapshot method along with the Public Key Infrastructure (PKI) certificates of a cluster. It also focuses on automating the backup and restore operations using microservices. Furthermore, it makes use of Amazon Web Services (AWS) tools for the reliability, scalability and the automation of backup and restore operations. The user can run the proposed microservices to backup and restore the cluster from any specific timestamp before the disaster. The experimental results demonstrate the effective performance of the proposed method in terms of efficiently restoring the kubernetes cluster in optimal time. © 2023 IEEE.

关键词： Cluster backup Cluster initialization Cluster setup Disaster recovery Kubernetes Master node Restore Worker node

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Exploration of Logistic Transportation Problems Based on CNN BILSTM RF Prediction Model

Exploration of Logistic Transportation Problems Based on CNN...

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2023 International Conference on Data Science and Network Security, ICDSNS 2023

作者： Zhang, Xiwen Cheng, Wenlin Lan, Yiheng Chen, Li Xia, Wenjie School of Computer and Software Chengdu Jincheng College Chengdu China School of Architecture Chengdu Jincheng College Chengdu China School of Mining Engineering and Geology Xinjiang Institute of Engineering Urumqi China

ISBN: (纸本)9798350301595

This paper focuses on the impact of promotional activities on the order volume of e-commerce users and the influence of unexpected events such as the COVID-19 pandemic on logistics transportation volume. The VMD algorithm is utilized to preprocess the data, and a CNN_BILSTM_RF prediction model and simulated annealing optimization model are constructed. Various software tools such as Matlab and SPSS are comprehensively employed to address the issue of freight allocation for different routes in logistics transportation. Firstly, the VMD algorithm is used to denoise the grouped data, and the CNN_BILSTcM_RF prediction model is constructed using Matlab to forecast the freight volume between DC25 and DC62, yielding conclusions such as 1774.2, 2041.5, 2718.6, 2160.9, 2251.3, and so on. Secondly, the maximum freight volume and load factor for the remaining routes after shutting down the DC5 and DC9 routes are predicted and calculated. A simulated annealing model is then applied to optimize the solution, resulting in conclusions such as 11.7288, 11.332, and so on for the overall network load. Lastly, the routes are evaluated, and the optimal transportation routes are identified as DC14-DC8, DC14-DC9, and DC36-DC4, with the addition of a new route between stations 8 and 10 to alleviate their burden, among other conclusions. © 2023 IEEE.

关键词： Transportation routes

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Confidence-based Class Relation Embedding for Few-shot Domain Adaptation

Confidence-based Class Relation Embedding for Few-shot Domai...

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Internet of Things and Smart Cities (ISITSC), International Symposium on

作者： Baoxi Jia Junyang Chen Yirui Wu College of Computer Science and Software Engineering Hohai University Nanjing China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (数字)9798331505516

ISBN: (纸本)9798331505523

In visual tasks such as image classification, the presence of domain shift often renders deep neural network models trained solely on specific datasets unable to generalize to new domains. In practical applications, due to the high cost of annotating rare data, it is extremely challenging to label all source domain samples comprehensively. Moreover, existing unsupervised domain adaptation methods often lack modeling of class relationships. Therefore, we propose a few-shot unsupervised domain adaptation method based on confidence-guided class relationship embedding. This approach aims to identify high-confidence target samples corresponding to sparsely labeled source samples, forming an inter-domain cross-mixed dataset. By constructing inter-domain contrastive learning, we explicitly guide the transfer of knowledge from the source domain to the target domain, leveraging the domain invariance of class relationships. Additionally, considering the varying learning difficulties of different target samples, we have devised an intra-domain class relationship contrastive loss, which leverages easy samples to facilitate the learning of difficult-to-classify samples. Experiments demonstrate that this model contributes to enhancing the performance of domain adaptation tasks.

关键词： Training Adaptation models Visualization Costs Smart cities Contrastive learning Artificial neural networks Internet of Things Image classification

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Tensor Canonical Correlation Analysis Networks for Multi-view Remote Sensing Scene Recognition (Extended Abstract) 39

Tensor Canonical Correlation Analysis Networks for Multi-vie...

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39th IEEE International Conference on Data engineering, ICDE 2023

作者： Yang, Xinghao Liu, Weifeng Liu, Wei College of Control Science and Engineering Qingdao China University of Technology Sydney School of Computer Science Sydney Australia

ISBN: (纸本)9798350322279

Remote sensing (RS) images are frequently observed from multiviews. In this paper, we propose the tensor canonical correlation analysis network (TCCANet) to tackle the multiview RS recognition problem. Particularly, TCCANet learns filter banks by simultaneously maximizing arbitrary number of views with high-order-correlation and solves the optimization problem by decomposing a covariance tensor. After the convolutional stage, we utilize binarization and block-wise histogram strategies to generate the final feature. Furthermore, we also develop a Multiple Scale version of TCCANet, i.e., MS-TCCANet, to extract enriched representation of the RS data by incorporating all previous convolutional layers. Numerical experiment results on RSSCN7 and SAT-6 datasets demonstrate the advantages of TCCANet and MS-TCCANet for RS scene recognition. © 2023 IEEE.

关键词： Convolution

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Vaccine Prediction and Distribution Model under the New Situation in China Based on Informer 6

Vaccine Prediction and Distribution Model under the New Situ...

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6th IEEE International Conference on Universal Village, UV 2022

作者： Niu, Yupeng Xu, Jiaqi Tan, Jingxuan Sichuan Agricultural University College of Information Engineering Yaan China College of Computer and Software Chengdu Jincheng College Chengdu China

ISBN: (纸本)9781665474771

In this paper, a comprehensive prediction model of daily vaccination in China was established by using Informer long sequence prediction model. For the first time, we established a comprehensive prediction model considering the number of nearby residents, transportation convenience, number of medical personnel, vaccine storage and transportation costs. © 2022 IEEE.

关键词： Vaccines

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Evaluating Logical Expressions by Membrane Systems

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Chinese Journal of Electronics 2025年第2期23卷 278-283页

作者： Ping Guo Jinfang Ji Haizhu Chen Ran Liu College of Computer Science Chongqing University Chongqing China Chongging Key Laboratory of Software Theory and Technology Chongqing China Department of Software Engineering Chongqing College of Electronic Engineering Chongqing China

Boolean and relational operations, which are defined for solving mathematically logical problems, are always required in computing models. Membrane computing is a kind of distributed parallel computing model. In this paper, we design different membranes for implementing primary Boolean and relational operations respectively. And based on these membranes, a membrane system can be constructed by a present algorithm for evaluating a logical expression. Some examples are given to illustrate how to perform the Boolean, relational operations and evaluate the logical expression correctly in these membrane systems.

关键词： Computational modeling Parallel processing Mathematical models

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GrasOpen: Biometric Authentication via Reach-and-Grasp for Smart Door Access Using Smartwatch

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IEEE Internet of Things Journal 2025年第13期12卷 25240-25253页

作者： Ding, Lei Shi, Jiale Wu, Yuan Hu, Xinrong Bi, Hongliang Chen, Yanjiao Wuhan Textile University School of Computer Science and Artificial Intelligence Engineering Research Center of Hubei Province for Clothing Information 430200 China China University of Mining and Technology School of Information and Control Engineering Jiangsu Xuzhou221116 China Zhejiang University College of Electrical Engineering Hangzhou310027 China

In the domain of smart devices, biometric identity authentication has become a leading and crucial technology, mainly because of its improved security and user convenience. Traditional methods frequently depend on complex activities, facial recognition, or passwords, which can be cumbersome and error-prone. This paper presents GrasOpen, an innovative biometric authentication system tailored for door-opening scenarios, utilizing the natural reach-and-grasp motion linked to door handles. The system employs smartwatches with accelerometers and gyroscopes to track and analyze arm movements, ensuring a seamless and intuitive user experience. GrasOpen tackles key challenges by leveraging the unique characteristics of the reach-and-grasp motion, eliminating the necessity for users to remember complex motions, and avoiding redundant actions like waiting for facial recognition. Specifically, GrasOpen initially proposes a lightweight model to discern door-opening actions from daily activities. Then, to realize the robust authentication system, GrasOpen integrates a complementary filter (CF) method to capture diversity-dependent features in door-opening actions. These features are subsequently processed through a modified ConvBoost model for precise user authentication. Experimental results reveal an impressive accuracy of 98.78% for activity recognition and 98.65% for identity authentication, highlighting GrasOpen’s excellence in function and performance. The system’s security and robustness are validated across diverse authentication environments. © 2014 IEEE.

关键词： Biometrics

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Minimizing the cost of periodically replicated systems via model and quantitative analysis

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Frontiers of computer Science 2024年第5期18卷 11-24页

作者： Chenhao ZHANG Liang WANG Limin XIAO Shixuan JIANG Meng HAN Jinquan WANG Bing WEI Guangjun QIN State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China School of Cyberspace Security Hainan UniversityHaikou 570228China Smart City College Beijing Union UniversityBeijing 100101China

Geographically replicating objects across multiple data centers improves the performance and reliability of cloud storage *** consistent replicas comes with high synchronization costs,as it faces more expensive WAN transport prices and increased *** replication is the widely used technique to reduce the synchronization *** replication strategies in existing cloud storage systems are too static to handle traffic changes,which indicates that they are inflexible in the face of unforeseen loads,resulting in additional synchronization *** propose quantitative analysis models to quantify consistency and synchronization cost for periodically replicated systems,and derive the optimal synchronization period to achieve the best tradeoff between consistency and synchronization *** on this,we propose a dynamic periodic synchronization method,Sync-Opt,which allows systems to set the optimal synchronization period according to the variable load in clouds to minimize the synchronization *** results demonstrate the effectiveness of our *** with the policies widely used in modern cloud storage systems,the Sync-Opt strategy significantly reduces the synchronization cost.

关键词： periodic replication consistency maintenance synchronization cost synchronization strategy

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