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检索条件"任意字段=23rd International Conference on Control Systems and Computer Science Technologies, CSCS 2021"

共 285 条记录，以下是81-90 订阅

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Big Data Mining on Health Informatics Data for Cities 23

Big Data Mining on Health Informatics Data for Cities

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23rd IEEE international conference on High Performance Computing and Communications, 7th IEEE international conference on Data science and systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Leung, Carson K. Wen, Qi Zhao, Chenru University of Manitoba Department of Computer Science WinnipegMB Canada

ISBN: (纸本)9781665494571

Advancements in modern technologies has generated and collected very large volumes of data at a rapid rate. Embedded in these big data is implicit, previously unknown and potentially useful information and knowledge. This explains why big data are often considered as a new oil. Discovered knowledge may help cities to enhance performance and well-being, to reduce costs and resource consumption, and to engage more effectively and actively with its citizens. To elaborate, discovered knowledge from digital technologies may support urban and transportation analytics for smart cities. Discovered knowledge from healthcare data and disease reports may support and enhance decision or policy making for the well-being of citizens within a city. For example, analyzing and mining health informatics data - such as COVID-19 epidemiological data - for cities help decision markers get a better understanding of the disease and come up with ways to detect, control and combat the disease. It also help them prepare for the needs of their citizens (e.g., needs for hospital beds in regular wards or ICU, needs of patients of different age groups). Hence, in this paper, we present a solution for big data mining on health informatics data for cities. Specifically, we mine COVID-19 epidemiological data with spatial and demographic hierarchies capturing characteristics of COVID-19 patients. Evaluation on real-life COVID-19 data demonstrates the practicality of our solution. © 2021 IEEE.

关键词： COVID-19 Smart cities Sociology Transportation Big Data Spatial databases Fuel processing industries

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A Dynamic Algorithm for Submodular Maximization with a Knapsack Constraint 23

A Dynamic Algorithm for Submodular Maximization with a Knaps...

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作者： Zhu, Tianshuai Han, Kai Zhang, Enpei Wu, Benwei School of Computer Science and Technology University of Science and Technology of China Hefei China

ISBN: (纸本)9781665494571

Submodular maximization is a fundamental problem in computer science theory, as well as occupies a significant place in machine learning and data mining applications, including influence maximization in social networks, recommendation systems, exemplar-based clustering, viral marketing, and data summarization. In this paper, we study this classic problem under a knapsack constraint in a fully dynamic setting. Given a stream of arbitrary interleaved element insertions and deletions, the dynamic setting requires a solution quickly after each update. By adopting repeated sampling, threshold greedy and filtering technique, our algorithm achieves an approximation ratio of 1/3 for monotone submodular objective function, with polylogarithmic amortized update time. We extensively evaluate the performance of our algorithm against the existing work in two applications including maximum coverage and movie recommendation. The experimental results demonstrate the superiority of our algorithm. © 2021 IEEE.

关键词： Machine learning algorithms Social networking (online) Smart cities Filtering Heuristic algorithms Machine learning Approximation algorithms

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Design of athermal SiON waveguide structure for telecom photonics integrated circuits 23

Design of athermal SiON waveguide structure for telecom phot...

引用

23rd Slovak-Czech-Polish Optical conference on Wave and Quantum Aspects of Contemporary Optics

作者： Chovan, J. Uherek, F. Seyringer, D. Dohnal, F. Seyringer, H. Latal, J. Siska, P. International Laser Centre Slovak Centre of Scientific and Technical Information Ilkovičova 3 Bratislava841 04 Slovakia OptoNet Slovakia s. r. o. Detvianska Huta 215 Hriňová962 05 Slovakia Institute of Electronics and Photonics Slovak University of Technology Ilkovičova 3 Bratislava812 19 Slovakia Hochschulstraße 1 Dornbirn6850 Austria V-Research GmbH Industrial Research & Development CAMPUS V Stadtstraße 33 Dornbirn6850 Austria Dept. of Telecommunications Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava 17. listopadu 2172/15 Ostrava-Poruba708 00 Czech Republic

ISBN: (数字)9781510688094

ISBN: (纸本)9781510688087

The rapid advancement of optical communication technologies has necessitated the development of highly efficient and stable photonic integrated circuits that enable coherent signal processing in the optical domain. Among them, Arrayed Waveguide Gratings (AWG) has emerged as a crucial component in Dense Wavelength Division Multiplexing (DWDM) systems. However, the performance of conventional AWGs is strongly affected by temperature fluctuations, resulting in central wavelength shifts and increased insertion losses. The aim of this study is to achieve a significant reduction of this dependency by using silicon oxynitride and polymethyl methacrylate on a silicon substrate with a thermal silicon dioxide buffer layer, thereby improving the overall performance and reliability of AWG-based DWDM systems. To achieve this, we have designed an athermal waveguide structure that can operate efficiently over a wide temperature range of -40°C to 80°C without the need for active temperature control mechanisms. Such a waveguide creates the basis for the AWGs in photonics integrated circuits. © 2025 SPIE.

关键词： Dense wavelength division multiplexing

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Human Action Recognition Methods Based on CNNs for RGB Video Input 23

Human Action Recognition Methods Based on CNNs for RGB Video...

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23rd international conference on control systems and computer science technologies, cscs 2021

作者： Radulescu, Bogdan Alexandru Florea, Adina Magda University Politehnica of Bucharest Faculty of Automatic Control and Computers Romania

ISBN: (纸本)9781665439398

Human Action recognition is a complex problem that attracts more and more researchers from the scientific community due to its applicability in domains such as security and behavior analysis. At its core, this problem entails classifying an action into a finite set of classes. Neural network based approaches, and especially convolutional neural networks, are a good starting point for solving the problem of human action recognition. Due to their nature, they can recognize spatio-temporal features very well, making them ideal for working with sequences of RGB images. In this paper are proposed three types of convolutional neural network architectures that contribute to solving the problem of Human Action Recognition. The first one is based on 2D kernels, the second one on 3D kernels, and the third one on TCN (Temporal Convolutional Network) units. Each one is presented with its structure, advantages and disadvantages, along with metrics that measure their performance. The one based on 2D convolutions is the fastest, but it also has the lowest performances. The second one is a good middle ground, useful in certain situations which require a fast classifier operating on different action classes. Finally, the one based on TCNs performs close to some of the best existent models. It represents a viable solution to the proposed problem. It can classify many actions, using only RGB images of fairly low resolution, in real time. The three models have been tested on the RGB part of the NTU RGB+D dataset. The 2D convolution-based model obtained an accuracy of 7.43% on the Cross-Subject split and 10.28% on the Cross-View split. The 3D convolution-based model obtained 58.77% on Cross Subject and 56.11% on Cross-View. Finally, the TCN-based model obtained an accuracy of 80.45% on Cross-Subject and an accuracy of 82.57% on Cross-View. © 2021 IEEE.

关键词： computer vision

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Efficient Hardware Redo Logging for Secure Persistent Memory 23

Efficient Hardware Redo Logging for Secure Persistent Memory

引用

作者： Zhang, Zhan Yue, Jianhui Liao, Xiaofei Jin, Hai School of Computer Science and Technology Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab Wuhan China Michigan Technological University Computer Science Department HoughtonMI United States

ISBN: (纸本)9781665494571

Write-ahead log and data encryption technologies are employed to ensure both crash consistency and data security for persistent memory (PM). The encryption/decryption of both data and log requests increase the memory request latency, degrading the system performance. To tackle this issue, this paper proposes a novel log-aware memory encryption scheme to reduce encryption/decryption operations, without compromising data security. Specifically, redo log blocks are stored as ciphertext for their corresponding data blocks to avoid encryption/decryption of log data blocks when in-place update operations are applied to them. We further design a compact log record layout with fewer encryption metadata in log records to reduce logging traffic. Our simulation results show that the transaction throughput of the proposed design outperforms the baseline design and the state-of-the-art design by 87.3% and 55.3% on average, respectively. © 2021 IEEE.

关键词： Smart cities System performance Simulation Memory management Layout Memory architecture Metadata

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Resource-Efficient DNN Training and Inference for Heterogeneous Edge Intelligence in 6G 23

Resource-Efficient DNN Training and Inference for Heterogene...

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作者： Cui, Enfang Zhang, Weiting Yang, Dong Wu, Wen Lyu, Feng School of Electronic and Information Engineering Beijing Jiaotong University Beijing China University of Waterloo Department of Electrical and Computer Engineering Waterloo Canada School of Computer Science and Engineering Central South University Changsha China

ISBN: (纸本)9781665494571

Edge intelligence is expected to be a key enabler of the future sixth generation (6G) mobile network. However, the heterogeneous characteristics of edge intelligence, such as heterogeneous edge data, resources, and service requirements, pose challenges to deep neural network (DNN) training and inference at the edge. To fully tap the potential of DNN for 6G heterogeneous edge intelligence, a variety of solutions have been proposed to tackle the above challenges, such as federated learning and transfer learning, for DNN training;and DNN partitioning and early exiting, for DNN inference. In this paper, we provide a comprehensive survey about resource-efficient DNN training and inference in heterogeneous edge intelligence. We first discuss the challenges of DNN training and inference in heterogeneous edge intelligence. Then, we give a detailed review of the recent advances of DNN training and inference technologies in heterogeneous edge intelligence, including the principles and state-of-the-art solutions of these technologies. We further conduct a taxonomy and summary of the reviewed solutions to clarify their applicable scenarios and the limitations. Finally, we point out some potential future research opportunities on heterogeneous edge intelligence. © 2021 IEEE.

关键词： Training 6G mobile communication Deep learning Smart cities Taxonomy Transfer learning Neural networks

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A Case-Based Reasoning Solution for Urban Drinking Water Quality control 23

A Case-Based Reasoning Solution for Urban Drinking Water Qua...

引用

作者： Wu, Di Seidu, Razak Wang, Hao Ban, Xiaojuan Norwegian University of Science and Technology Department of Ict and Natural Science Ålesund Norway Norwegian University of Science and Technology Department of Ocean Operations and Civil Engineering Ålesund Norway Norwegian University of Science and Technology Department of Computer Science Gjφvik Norway University of Science and Technology Beijing Department of Computer Science and Technology Beijing China

ISBN: (纸本)9781665494571

The Urban Drinking Water Supply (UDWS) systems play a vital role nowadays to support global city management, especially in the context of the fast growth of urbanization. In Europe, there is a natural conflict between urban population growth and the aging drinking water supply infrastructure. In particular, according to European standards, water should be drinkable from the taps. The requirements from these standards not only bring easement in our modern daily life but also are examining the robustness of the risk warning and control response in the UDWS system. Water quality as the key factor in the urban water supply is by default strictly regulated in the municipality management. Currently, the most common water quality control is relying on periodic tests for various quality indicators. In addition, further processing in the treatment plant, including measures and doses, is relatively fixed and weak to respond to the risk in UDWS. In order to address these problems, we propose a Case-Based Reasoning (CBR) approach for water quality risk control in UDWS systems. First, we build a case-based analysis computational scheme for the risk control in the UDWS system. Then we provide our methods in feature selection and similarity evaluation between different cases. Finally, the results of an industrial case study are presented. This case is based on our data collection from the UDWS system in Oslo city in Norway. The discussion and analysis show the feasibility of this approach and practically provide decision support for water treatment actions. © 2021 IEEE.

关键词： Smart cities Sociology Europe Water quality control systems Cognition Robustness

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A CAN Bus anomaly Detection Based on FLXGBoost Algorithm 23

A CAN Bus anomaly Detection Based on FLXGBoost Algorithm

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作者： Wang, Jie Mo, Xiuliang School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9781665494571

Along with the networking and automation of smart vehicles and the accelerated application of information and communication technologies, controller Area Network (CAN) has become the most commonly used protocol in automotive bus networks, but it cannot protect the in-vehicle network from attacks because it does not provide a security system against network and physical attacks, so it is necessary to develop anomaly detection countermeasures to secure the CAN bus. This article proposes a CAN bus anomaly detection model for masquerade attacks, mining the distribution characteristics of each byte of Data messages of all IDs without the bus message identification function, combining the information entropy of message IDs to compose a new data set;introducing a focal loss function to improve the XGBoost algorithm for the case of sample imbalance, and realizing the FLXGBoost-based algorithm. The experimental results show that the anomaly detection model has a high accuracy rate in resisting tampered data domain messages. © 2021 IEEE.

关键词： Protocols Smart cities Computational modeling Memory management Feature extraction Data models Information and communication technology

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Design and Implementation of a Distributed control Platform for a Smart Building Testbed 23

Design and Implementation of a Distributed Control Platform ...

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作者： Puryear, Nathan Zaman, Mostafa Eini, Roja Abdelwahed, Sherif Virginia Commonwealth University Department of Electrical and Computer Engineering RichmondVA United States

ISBN: (纸本)9781665494571

One of the leading frontiers of the Internet of Things (IoT) era, smart building systems have made modern homes more innovative, interconnected, and autonomous. The goal of a smart home system is to enhance users' comfort, safety, and efficiency. In this paper, a smart building testbed is designed and constructed as a cyber-physical system that allows testing and validating building control algorithms, communication networks, and user interfaces. The building control unit is responsible for optimizing the performance of testbed actuators (thermal, lighting, and access systems), whereby building parameters are aggregated via a set of distributed sensors and communicated to a management system. This data is observed and analyzed by the control system to produce optimal control commands. The building communication network is developed based on the Message Queuing Telemetry Transport (MQTT) protocol, in which subscribers receive the measurement data, format it, and send it to the user-interface unit. The user interface is implemented in a Node-RED platform, where the data is visualized in real-time, and users are capable of interacting with the automation system. Experimental results demonstrate the usefulness of such a prototype for smart building monitoring and control research. © 2021 IEEE.

关键词： Smart buildings Smart homes Thermal sensors Thermal management Sensor systems Safety Internet of Things

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Study on Active Defense of Honeypot-Based Industrial control Network 23

Study on Active Defense of Honeypot-Based Industrial Control...

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作者： Wei, Xunsi Yang, Dequan Beijing Institute of Technology School of Computer Beijing100081 China Network Information Technology Center Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781665494571

With the rapid development of information, network security and information have played an increasingly important role in national production. As a result, the environment and application of industrial control networks are under more and more network security threats. Furthermore, most applications of industrial control networks belong to critical infrastructure, so to guarantee the security of industrial control networks has become more significant, and the defense of it is one of the essential issues in need of being solved. This paper focuses on studying the active protection for the security of industrial control networks and discusses the role of honeypot in the network security for the defense strategy of the industrial control network. Firstly, this paper introduces the theoretical knowledge of honeypots. Secondly, it analyzes the existing problems and development prospects of the honeypot. And finally, under the background of the industrial control network, it designs the SSH honeypot based on Transmission control Protocol/Internet Protocol (TCP/TP), which is divided into two modules, including SSH information collection and alarm. This system can deploy based on the Docker of Linux. Through simulation practice, it proves that honeypot can effectively capture the attackers' attack and make an early warning to improve network security. © 2021 IEEE.

关键词： Industrial control Linux TCPIP Production Network security Critical infrastructure

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