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arXiv 2022年

作者： Yu, Li Chang, Wenshuai Wu, Shiyu Gabbouj, Moncef School of Computer and Software Nanjing University of Information Science and Technology Nanjing China Engineering Research Center of Digital Forensics Ministry of Education Nanjing University of Information Science and Technology Nanjing China Department of Computing Sciences Tampere University Tampere Finland

Convolutional neural networks have achieved excellent results in compressed video quality enhancement task in recent years. State-of-the-art methods explore the spatiotemporal information of adjacent frames mainly by deformable convolution. However, offset fields in deformable convolution are difficult to train, and its instability in training often leads to offset overflow, which reduce the efficiency of correlation modeling. In this work, we propose a transformer-based compressed video quality enhancement (TVQE) method, consisting of Swin-AutoEncoder based Spatio-Temporal feature Fusion (SSTF) module and Channel-wise Attention based Quality Enhancement (CAQE) module. The proposed SSTF module learns both local and global features with the help of Swin-AutoEncoder, which improves the ability of correlation modeling. Meanwhile, the window mechanism-based Swin Transformer and the encoder-decoder structure greatly improve the execution efficiency. On the other hand, the proposed CAQE module calculates the channel attention, which aggregates the temporal information between channels in the feature map, and finally achieves the efficient fusion of inter-frame information. Extensive experimental results on the JCT-VT test sequences show that the proposed method achieves better performance in average for both subjective and objective quality. Meanwhile, our proposed method outperforms existing ones in terms of both inference speed and GPU consumption. Copyright © 2022, The Authors. All rights reserved.

关键词： Convolution

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Information Technology for Education, Science, and Technics 1

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丛书名： Lecture Notes on Data engineering and Communications Technologies

1000年

作者： Emil Faure Yurii Tryus Olena Danchenko Tero Vartiainen Maksym Bondarenko Constantine Bazilo Grygoriy Zaspa

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GNN-Geo: A Graph Neural Network-based Fine-grained IP geolocation Framework

arXiv

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arXiv 2021年

作者： Ding, Shichang Luo, Xiangyang Wang, Jinwei Fu, Xiaoming State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou276800 China School of Computer and Software Nanjing University of Information Science & Technology Nanjing210044 China Institute of Computer Science University of Göttingen Göttingen37077 Germany

Rule-based fine-grained IP geolocation methods are hard to generalize in computer networks which do not follow hypothetical rules. Recently, deep learning methods, like multi-layer perceptron (MLP), are tried to increase generalization capabilities. However, MLP is not so suitable for graph-structured data like networks. MLP treats IP addresses as isolated instances and ignores the connection information, which limits geolocation accuracy. In this work, we research how to increase the generalization capability with an emerging graph deep learning method - Graph Neural Network (GNN). First, IP geolocation is re-formulated as an attributed graph node regression problem. Then, we propose a GNN-based IP geolocation framework named GNN-Geo. GNN-Geo consists of a preprocessor, an encoder, messaging passing (MP) layers and a decoder. The preprocessor and encoder transform measurement data into the initial node embeddings. MP layers refine the initial node embeddings by modeling the connection information. The decoder maps the refined embeddings to nodes' locations and relieves the convergence problem by considering prior knowledge. The experiments in 8 real-world IPv4/IPv6 networks in North America, Europe and Asia show the proposed GNN-Geo clearly outperforms the state-of-art rule-based and learning-based baselines. This work verifies the great potential of GNN for fine-grained IP geolocation. Copyright © 2021, The Authors. All rights reserved.

关键词： Deep learning

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Streamlining software Release Process and Resource Management for Microservice-based Architecture on multi-cloud

Streamlining Software Release Process and Resource Managemen...

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IEEE International Conference on Multi Topic

作者： Isuru Pathum Herath Samuditha Jayawardena Ahamed Fadhil Nuwan Kodagoda Udara Srimath S.Samaratunge Arachchillage Department of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Sri Lanka Faculty of Computing Sri Lanka Institute of Information Technology Sri Lanka Department of Computer Science Sri Lanka Institute of Information Technology Sri Lanka

The software development process is more flexible with the concept of containerization in the microservice platform. This research is on three key components to resolve problems faced by the developers and DevOps teams in the IT industry. First, the development phase expects a fully automated software release process from to the deployment phase and then optimize processes tailored to Docker, and Kubernetes, in microservice-based applications. Then streamline the process and leverage the container orchestration technologies to monitor the main aspect of the development lifecycle through the multi-cloud deployment on demand of the growth of day-today releases on multi-regions. A centralized monitoring platform is developed to monitor the deployed applications and that provides comprehensive visibility regarding performance and health of microservices. At the stage of scalarization in microservices, Vertical Pod Autoscaling (VPA) and Horizontal Pod Autoscaling (HPA) are available approaches for resource allocation, and they require measuring the minimum and maximum resource limits. As a result, an intelligent resource allocation system is proposed using a combination of Convolutional Neural Networks (CNN) and Bidirectional Long Short-Term Memory (Bi-LSTM) algorithms to cater to dynamic resource allocation, optimizing scalability, and improving cost-efficiency. This research aims to achieve practical insights into the IT industry’s automated deployment, managing, scaling, and monitoring of microservice-based applications through the mentioned components.

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A Robust Anonymous Authentication Scheme for Securing IoT-Enabled Healthcare Services

A Robust Anonymous Authentication Scheme for Securing IoT-En...

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Cyber Security in Networking Conference (CSNet)

作者： Sana Ullah Shanshan Tu Akhtar Badshah Muhammad Waqas Department of Enterprise and Technology Atlantic Technological University Galway Ireland College of Computer Science Beijing University of Technology Beijing China Department of Software Engineering Faculty of Engineering University of Malakand Dir Lower Pakistan Faculty of Engineering and Science School of Computing and Mathematical Sciences University of Greenwich U.K. School of Engineering Edith Cowan University Perth WA Australia

ISBN: (数字)9798331534103

ISBN: (纸本)9798331534110

Smart wearables and body implanted IoT devices continuously track and transmit health metrics wirelessly to a central controller, such as a personal server, enabling real-time monitoring, proactive treatment and timely assistance. However, the security of IoT-enabled healthcare systems remains a concern, particularly regarding the protection of sensitive patient data. To address the aforementioned issue and enhance security in IoT-enabled healthcare services, we propose a robust anonymous authentication scheme in this work. By leveraging lightweight cryptographic primitives including hash functions and XOR operations coupled with physical unclonable functions (PUFs) and fuzzy extractors, the proposed scheme introduces a novel authentication and key agreement mechanism for secure communication in IoT-enabled healthcare systems. The integration of PUF technology ensure the physical security of resource constrained implantable medical devices (IMDs) against various attacks including device physical capture and impersonation attacks that compromise the IoT-enabled healthcare operations. A thorough security analysis demonstrated the robustness and resilience of the proposed scheme against various active and pas-sive security attacks, thus ensure the integrity and confidentiality of sensitive healthcare data. Finally, comparative analysis of the proposed scheme with other state-of-the-art highlighted that our scheme outperformed other approaches in terms of providing security and additional features, positioning it as a comprehensive solution for authentication in IoT-enabled healthcare services.

关键词： Hash functions Medical devices Authentication Medical services Physical unclonable function Security Internet of Things Servers Wearable devices Resilience

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Integrating approximation methods with the generalised proportional sampling strategy

Integrating approximation methods with the generalised propo...

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Asia-Pacific Conference on software engineering

作者： T.Y. Chen P.K. Wong Y.T. Yu Department of Computer Science and Software Engineering University of Melbourne Parkville Australia Department of Computing and Mathematics Hong Kong Institute of Vocational Education Chaiwan Hong Kong China Department of Computer Science City University of Hong Kong Hong Kong China

Previous studies have shown that partition testing strategies can be very effective in detecting faults, but they can also be less effective than random testing under unfavourable circumstances. When test cases are allocated in proportion to the size of subdomains, partition testing strategies are provably better than random testing, in the sense of having a higher or equal probability of detecting at least one failure (the P-measure). Recently, the Generalised Proportional Sampling (GPS) strategy, which is always satisfiable, was proposed to relax the proportionality condition. The paper studies the use of approximation methods to generate test distributions satisfying the GPS strategy, and evaluates this proposal empirically. Our results are very encouraging, showing that on average about 98.72% to almost 100% of the test distributions obtained in this way are better than random testing in terms of the P-measure.

关键词： Approximation methods Sampling methods Fault detection software testing Computer science Global Positioning System Performance evaluation Mathematics Computer science education software engineering

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MobiIO: Push the limit of indoor/outdoor detection through human's mobility traces

MobiIO: Push the limit of indoor/outdoor detection through h...

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International Conference on Indoor Positioning and Indoor Navigation (IPIN)

作者： Hongwei Jia Shuai Su Weihao Kong Haiyong Luo Guoqiang Shang Beijing University of Posts and Telecommunications Beijing Beijing CN School of Software Beijing University of Posts and Telecommunications Beijing China Chinese Academy of Sciences Institute of Computing Technology Beijing China School of Electronic and Information Engineering of Beihang University Beijing China

Presently existing lightweight indoor/outdoor detection schemes on phones acquire accuracy by sensing variations of ambient physical environmental properties with inherent sensors on mobile phones, with which, however, the detection scheme cannot work well in some ambient environments, where the variations are not very observable. This detection scheme is with very high dependency on light. The I/O detector does not work well in poor lighting or fast changing lighting settings, therefore the I/O detection is very much challenged at times like dawn, dusk, or night. The target of this paper is finding a pervasive detection scheme independent of physical environments. In this paper, we present MobiIO, an lightweight indoor and outdoor detection scheme based on analyses of human activities. By recording human indoor and outdoor motion activities with sensors, typical features of their activities are extracted. We compare assorted combinations or groupings of various properties with SVM classifier. We classify indoor/outdoor settings through classifiers like SVM, Bayes, decision trees, HMM and compare the effects of classification in between various classifying algorithms.

关键词： Hidden Markov models Feature extraction Accuracy Legged locomotion Sensor phenomena and characterization Support vector machines

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Design of a robot cloud center

Design of a robot cloud center

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International Workshop on Assurance in Distributed Systems and Networks

作者： Du, Zhihui Yang, Weiqiang Chen, Yinong Sun, Xin Wang, Xiaoying Xu, Chen Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology Tsinghua University 100084 Beijing China School of Software and Microelectronics Peking University 102600 Beijing China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ 85287 United States Department of Computer Technology and Application Qinghai University Xining Qinghai 810016 China International School Beijing University of Posts and Telecommunications 102209 Beijing China

ISBN: (纸本)9780769543499

Service-oriented architecture and cloud computing have become the prevalent computing paradigm. In this paradigm, computing resources can be accessed like other utility services available in today's society. In the meantime, robotics applications are joining the trend. More and more robot applications are shifting from manufacture to non-manufacture and service industries. However, for the on-demand supply of the large-scale heterogeneous robots, It is still a problem have not yet been studied, including the fundamental management and efficiency issues in using of these resources. In this paper, we design a framework of "Robot Cloud Center" (RCC) following the general cloud computing paradigm to address the current limitations in capacity and versatility of robotic applications. In this framework, a robot can be provided as a service just like a public utility service so that everyone can access the powerful robotic services easily, efficiently, and cheaply. Based on a given scenario, a robot scheduling algorithm in RCC is proposed to take advantage of the heterogeneous robot resources to meet the end user's requirement with the minimum cost.

关键词： Robot programming

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Smart Irrigation Management System

Smart Irrigation Management System

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International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Bassem Sellami Abdelaziz El Fazziki Mohamed Taha Bennani Sadok Ben Yahia Dept of Computer Sciences Faculty of Sciences University of Tunis El Manar Tunis Tunisia Dept of Computer Science Cadi Ayyad University Computing Systems Engineering Laboratory Marrakech Morocco Department of Software Science Tallinn University of Technology Tallinn Estonia

The significant problem in the area of sustainable development is the effective management of water resources. There are a number of approaches for resolving this issue in the literature, particularly in the agricultural sector, which serves as the primary consumer through irrigation. As a result, irrigation management is a crucial and cutting-edge discipline that has been the focus of several research and study projects to address the various activities, behaviors, and conflicts between the various users. This paper introduces an intelligent irrigation system based on smart sensors that can be used sparingly and affordably to monitor farms. By incorporating some connected electronic devices and other useful tools frequently used in the field of IoT, it calculates the water requirement of each farm based on the water loss caused by the process of evapotranspiration. Data gathered from a number of sensors placed across the plantation farm are used to determine the amount of water needed. It may be utilized by farmer organizations whose endowments and irrigation planning are determined according to the requirement and quantity of water available in the rural municipality. This project focuses on smart irrigation based on IoT. Each node in the system functions as an IoT device and incorporates a microprocessor with the integration of sensors, actuators, and valve modules. An irrigation management system simplifies the operation of each node and configuration settings for irrigation allow for the direct monitoring of environmental factors. The Penman model is used to get the daily evapotranspiration baseline and is used to calculate the quantity of water needed for irrigation. The suggested irrigation approach is anticipated to help reduce water usage and distribute it fairly without affecting crop productivity compared to the traditional irrigation system.

关键词： Irrigation Crops Organizations Valves Planning Internet of Things Intelligent sensors

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Performance and Accuracy Evaluation of Distribution System State Estimators

SSRN

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SSRN 2024年

作者： Hebling, Gustavo M. Massignan, Julio A.D. de Melo, Vitor H.P. London Junior, Joao B.A. Department of Electrical and Computing Engineering University of Sao Paulo USP Avenida Trabalhador sao-carlense 400 - Parque Arnold Schimidt Sao Carlos Sao Paulo13566-590 Brazil Siemens AG Smart Infrastructure - Grid Software Curitiba Brazil

Recent initiatives towards smart grids have contributed to a growing inter- est in improving the real-time monitoring capabilities of active distribution systems. In this context, the sate estimator is the prevailing application, as it can provide reliable information about the current operational state of electrical networks. However, this application must be redesigned to deal with the complexity and challenges of distribution circuits and still be able to provide accurate estimates with low execution time. Therefore, this pa- per compares five different three-phase distribution system state estimators, namely, the Weighted Least Squares with Normal Equation State Estimator, Hatchel Augmented Matrix State Estimator, Branch Current Based State Estimator, Admittance Matrix Based State Estimator and the more recent Orthogonal QR State Estimator. The computational aspects assessed are execution time and iteration count until convergence and a Monte Carlo sim- ulation is used to determine accuracy. Furthermore, reordering algorithms focused on maintaining sparsity during the iterative process are evaluated for each distribution system estimator in order to determine the impact on the computational time. Simulations are carried out on IEEE distribution test systems and a real Brazilian test feeder with different measurement sets to represent a wide range of operating conditions. © 2024, The Authors. All rights reserved.

关键词： Numerical methods

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