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Fusing Heterogeneous Traffic Data by Kalman Filters and Gaussian Mixture Models

Fusing Heterogeneous Traffic Data by Kalman Filters and Gaus...

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17th international IEEE conference on intelligent Transportation Systems & the Asia-Pacific Council on Systems Engineering conference 2014

作者： Chunhui Wang Qianqian Zhu Zhenyu Shan Yingjie Xia Yuncai Liu Hangzhou Institute of Service Engineering Hangzhou Normal University

Heterogeneous traffic data collected from different types of sensors are fused for estimating traffic states more *** quality and fusion method are two key issues required to be solved in the traffic state *** this paper,we propose a fusion method of heterogeneous traffic data based on the Kalman filters(KF) and Gaussian mixture models(GMM).the noise in collected raw data is reduced by the KF in order to improve the quality of input data for *** vectors of historical data from global positioning system(GPS) and remote traffic microwave sensors(RTMS) in different traffic states are modeled with multiple multi-variate GMM ***,the estimated traffic state can be obtained by computing the posterior probabilities with the vector data and *** of our work is examined by series of experiments,and the results show that the proposed method is effective for improving the precision of traffic state estimation.

关键词： GMM Fusing Heterogeneous Traffic Data by Kalman Filters and Gaussian Mixture Models Kalman Gaussian

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An Improved FTRLS Filtering Algorithm and Its Simulation Analysis

An Improved FTRLS Filtering Algorithm and Its Simulation Ana...

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2017 17th IEEE international conference on Communication technology (ICCT 2017)

作者： Jun Zhu Jingjing Zhang Qiang Chen Key Lab of Intelligent Computing and Signal Processing Ministry of Education China School of Electronics and Information Engineering Anhui University

Due to the large error of LMS algorithm and the slow convergence rate, the recursive least squares(RLS) algorithm is proposed. Although the recursive estimation error is greatly reduced, the convergence rate is one order of magnitude higher than that of the general LMS filter. When the order N increases, the amount of calculation for a single iteration of the RLS algorithm is increased significantly. Aiming at these problems, this paper proposes an improved FTRLS filtering algorithm, which is to find out the amount of large error and accumulate the error, and then make the error feedback to make the algorithm more stable. the analysis of MATLAB simulation results show that the improved algorithm can improve the convergence speed and stability of the algorithm, and effectively reduce the convergence of the noise.

关键词： adaptive filtering Least Mean Squares(LMS) Recursive Least Squares(RLS) Fast Transverse Recursive Least Squares(FTRLS) improved FTRLS algorithm convergence rate

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Smart EV Charging to Mitigate Range Anxiety in VANET Backbone Guided by Named Data Networking and Block-Chain

Smart EV Charging to Mitigate Range Anxiety in VANET Backbon...

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distributed computing and Electrical Circuits and Electronics (ICDCECE), IEEE international conference on

作者： Vetri Vendan Anamika Chaudhary Department of Computer Science and Engineering Galgotias University Greater Noida India Department of Information Technology Noida Institute of Engineering and Technology Greater Noida India

A interesting area of research for future connected car application is the development of an effective charging management system for on-the-go EVs, which is especially important given the inherent unpredictability in EV mobility. the main technological hurdles here are the necessity for intelligent decision making when choosing a CS and the related communication infrastructure for exchanging data between the grid and mobile EVs. Switching to electric vehicles has the potential to reduce pollution, vehicle maintenance expenses, and increasing gas prices (EVs). the range anxiety issue is a significant impediment to the rapid adoption of EV. Range anxiety can be alleviated by guaranteeing that a charging point will be found within the vehicle’s driving range, subject to other constraints such as waiting time, reliability, cost, and so on. In this research, we suggest building a P2P infrastructure on top of a VANET so that users may trade power with one another in a secure and reliable manner. Although the labour itself is decentralised, secure, and reliable, the associated financial transactions are not. the proposed framework for exchanging electric charge is based on the intersection of three concepts from the realm of automotive social networks: data connectivity, the bitcoin, and the anxiety of having insufficient battery power. We address reliability using an established collaborative paradigm rooted in the field of automotive social networks. Organizational verification previous to trading and encrypted parameter exchange provide safety. With the help of named data networking, reliable charging points may be located using a set of criteria. the simulation results demonstrate that the proposed technique decreases the amount of time it takes to complete an energy transaction by 17%, boosts coverage for picking charging providers by 13%, and decreases the amount of erroneous provider filtering by 18%.

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Exploring Robust DDoS Detection: A Machine Learning Analysis with the CICDDoS2019 Dataset

Exploring Robust DDoS Detection: A Machine Learning Analysis...

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India Council international Subsections conference (INDISCON), IEEE

作者： Kamal Saluja Susama Bagchi Vikas Solanki Muhammad Numan Ali Khan Esha Dhamija Sanjoy Kumar Debnath Chitkara University Institite of Engineering and Technology Chitkara University Punjab India College of Computing and Information Sciences University of Technology and Applied sciences Shinas Sultanate of Oman

ISBN: (数字)9798350376753

ISBN: (纸本)9798350376760

the ever-present threat posed by distributed Denial of Service attack is highlighted. the significance of building robust cybersecurity measures that are not just inventive but also flexible. the purpose of this study paper is to investigate the effectiveness of an algorithm based on machine learning in detecting distributed denial of service assault to strengthen the resilience of Internet infrastructure. Random forest, decision tree, naïve bayes, and KNN are some of the machine learning techniques that are investigated in this study. the dataset used for this investigation is the CICDDoS 2019 data, Moreover, the research broadened its approach to identify the role of Artificial Intelligence in the Cybersecurity Framework. It does this by providing insight into the relative merits of various algorithms. the study, in its essence, highlights the critical role that adaptive and intelligent defense systems play in decreasing the impact of distributed denial of service assaults (DDoS). this provides a foundation for prepared strategies in the constantly shifting world of cybersecurity.

关键词： Measurement Machine learning algorithms Accuracy Machine learning Nearest neighbor methods Internet Computer crime Random forests Classification tree analysis Resilience

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A selective and biased choice of techniques for building a distributed data store 23

A selective and biased choice of techniques for building a d...

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Proceedings of the 17th ACM international conference on distributed and Event-based Systems

作者： Paweł Tomasz Wojciechowski Faculty of Computing and Telecommunications Institute of Computing Science Poznan University of Technology Poznań Poland

ISBN: (纸本)9798400701221

Single-machine data stores cannot support the scale and ubiquity of data today. the Internet applications and services must process a huge number of concurrent requests and events per second. So, they use distributed (or replicated) data stores which store and process data on multiple machines, offering key advantages in performance, scalability, and *** purpose of the talk is to present a selective and biased choice of techniques and results which can be used for building an efficient distributed data store. Biased, because I only present solutions and results developed within a research project that I did with my PhD students. Selective, because an exhaustive description would be too exhausting to fit into a single talk. therefore I will be discussing in detail just the design of our novel database index for key-value data store systems, and only skim our other contributions that are directly related to distributed *** index, called Jiffy, has been designed with performance and scalability in mind. therefore it has been designed as a lock-free concurrent data structure, which can dynamically adapt to the changing workload. It achieves superior performance despite built-in atomic operations (batch updates, snapshots, and range scans). During the talk I will be presenting Jiffy's architecture, the algorithms for inserting and looking up the key-value pairs, and the operations used for resizing the data structure *** other contributions of our project include: efficient support for replica state recovery after failures, either by extending the classic Paxos consensus algorithm, or through the use of persistent memory, and some surprising theoretical results which are applicable to distributed data store systems that compromise consistency in favour of high availability and speed, but also support operations ensuring strong consistency (which requires consensus among replicas).

关键词： mixed consistency paxos concurrent data structures lock-free skip list replica state recovery ordered index

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A new paradigm for the study of corruption in different cultures

A new paradigm for the study of corruption in different cult...

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7th international conference on Social computing, Behavioral-Cultural Modeling, and Prediction, SBP 2014

作者： Gal, Ya'Akov Rosenfeld, Avi Kraus, Sarit Gelfand, Michele An, Bo Lin, Jun Department of Information Systems Engineering Ben-Gurion University Israel Department of Industrial Engineering Jerusalem College of Technology Israel Department of Computer Science Bar-Ilan University Israel Institute for Advanced Computer Studies University of Maryland United States Department of Engineering Nanyang Technological University Singapore Department of Engineering and Management Beihang University China

ISBN: (纸本)9783319055787

Corruption frequently occurs in many aspects of multi-party interaction between private agencies and government employees. Past works studying corruption in a lab context have explicitly included covert or illegal activities in participants' strategy space or have relied on surveys like the Corruption Perception Index (CPI). this paper studies corruption in ecologically realistic settings in which corruption is not suggested to the players a priori but evolves during repeated interaction. We ran studies involving hundreds of subjects in three countries: China, Israel, and the United States. Subjects interacted using a four-player board game in which three bidders compete to win contracts by submitting bids in repeated auctions, and a single auctioneer determines the winner of each auction. the winning bid was paid to an external "government" entity, and was not distributed among the players. the game logs were analyzed posthoc for cases in which the auctioneer was bribed to choose a bidder who did not submit the highest bid. We found that although China exhibited the highest corruption level of the three countries, there were surprisingly more cases of corruption in the U.S. than in Israel, despite the higher PCI in Israel as compared to the U.S. We also found that bribes in the U.S. were at times excessively high, resulting in bribing players not being able to complete their winning contracts. We were able to predict the occurrence of corruption in the game using machine learning. the significance of this work is in providing a novel paradigm for investigating covert activities in the lab without priming subjects, and it represents a first step in the design of intelligent agents for detecting and reducing corruption activities in such settings. © 2014 Springer international Publishing Switzerland.

关键词： Surveys

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Performance Optimization Blockchain-Enabled Fog computing with Deep Reinforcement Learning 22

Performance Optimization Blockchain-Enabled Fog Computing wi...

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Proceedings of the 2022 12th international conference on Communication and Network Security

作者： Yihe Zhang Shanshan Tu Shengju Zhang Yongjie Yang Aiming Wu Xuetao Bai Engineering Research Center of Intelligent Perception and Autonomous Control faculty of Information Technology Beijing University of Technology China China Mobile (Suzhou) Software Technology Co. Ltd China Mobile (Suzhou) Software Technology Co. Ltd China

ISBN: (纸本)9781450397520

With the rapid development of Internet of things technology and cloud computing technology, Fog computing emerges with the demand of distributed and decentralized. Blockchain is considered to be an advanced technology, which enables Fog computing data to be stored and shared safely, greatly improving the security and privacy of Fog computing. However, the Blockchain technology currently applied in Fog computing still has some significant disadvantages, one of which is the low throughput performance. In order to meet the demand of improving throughput, this paper proposes a Blockchain-Enabled Fog computing performance optimization framework based on Deep Reinforcement Learning (DRL), which can dynamically adjust according to the system state to improve throughput. Dueling Deep Reinforcement Learning is adopted to obtain the optimal configuration, which can be dynamically adjusted according to Fog node status, network bandwidth and user's quality of service (QoS) requirements, including dynamic selection of block producers, block size and network bandwidth allocation. Simulation results show that the proposed scheme can effectively improve throughput performance.

关键词： Blockchain quality of service Deep Reinforcement Learning Fog computing

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Spectrum Sharing in CBRS Using Blockchain

Spectrum Sharing in CBRS Using Blockchain

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IEEE Internatonal conference on Mobile Adhoc and Sensor Systems (MASS)

作者： Pavithra Chidambaram Pappa Aarushi Sarbhai Aniqua Baset Sneha Kasera Milind Buddhikot School of Computing University of Utah Salt Lake City Utah Nokia Bell Labs Murray Hill New Jersey

ISBN: (数字)9781728198668

ISBN: (纸本)9781728198675

We make a case for using the emerging blockchain technology for spectrum sharing in Citizen's Broadband Radio Service (CBRS). We show that blockchain can dynamically allocate channels in a transparent and fair manner by achieving distributed channel de-confliction. Furthermore, blockchain helps automate communication between the Spectrum Access Systems (SASs) belonging to competing, non-trusting organizations by providing consensus, while at the same time preserving confidentiality of sensitive information. We implement our CBRS blockchain architecture using the Hyperledger Fabric platform. In order to support high channel request rates, we also develop a novel feature that adaptively pre-processes channel allocation requests at the SAS before sending those to the blockchain network. We evaluate our blockchain solution under different settings and show that it meets the FCC latency requirements. We also analyze the scalability of our system and show that the latency and throughput guarantees can be maintained in scenarios involving multiple organizations.

关键词： Scalability System performance Blockchain FCC Organizations Channel allocation throughput

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Research of Cloud-Native AS/RS Warehouse Management and Control Platform Architecture

Research of Cloud-Native AS/RS Warehouse Management and Cont...

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international conference on Computer Engineering and Applications (ICCEA)

作者： Chuanjun Chen Junjie Liu Beijing Research Institute of Automation for Machinery Industry RIAMB RIAMB (Beijing) Technology Development Co. Ltd. Beijing China Tsinghua University Beijing China

ISBN: (数字)9798350386776

ISBN: (纸本)9798350386783

Since the invention of cloud computing technologies, the term "cloud-native" has been used. In recent years, research into cloud-native technology has grown along with the development of cloud computing technology. One of the most popular software architectures of our time, cloud-native architecture integrates cloud-native technology to conventional distributed architectures and aligns with the characteristics of modern cloud usage. this article examines the history of cloudnative technologies, warehouse information systems, and pertinent literature. It suggests a three-tier design for a Cloud-Native Warehouse Management and Control Platform (CWMCP), combining the traits of automated storage and retrieval systems (AS/RS). the study examines the functioning of the data layer, service layer, and application layer as well as their logical relationships and discusses each layer's specific design, deployment, and features in detail. Based on operational requirements of AS/RS warehouses, we developed a business analysis framework integrating algorithms, and created a prototype cloud-native warehouse management system (CWMS). We then analyzed the platform's advanced architecture and verified its effectiveness. CWMCP is in high demand and a promising trend for enabling digital and intelligent transformation of AS/RS systems.

关键词： Computers Productivity Cloud computing Technological innovation Software architecture Standards organizations Prototypes

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Realizing Large-scale Street Games using Heterogeneous Future Internet Technologies

Realizing Large-scale Street Games using Heterogeneous Futur...

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international conference on intelligent Environments

作者： Orestis Akribopoulos Marios Logaras Georgios Mylonas Ioannis Chatzigiannakis Irene Mavrommati Research Unit 1 Computer Technology Institute and Press Hellenic Open University (HOU)

ISBN: (纸本)9781479907458

A collection of pervasive street games is presented in this paper, that constitute a new social form of play taking place in public spaces, such as city parks, public spaces and streets. the main characteristic of these games is the ability to scale to a large number of players (in some cases involving more than 40 players) and can engage players located simultaneously in dispersed areas. Players interact with each other using a wide range of hardware devices that are either generic (such as smart phones) or specific (such as wireless sensor devices). We discuss a set of fundamental issues related to game design emphasizing on the one hand the interaction of the players with the ubiquitous computing environment and on the other hand the embedding of the game rules within the environment. the games are developed using open source technologies and evaluated in a series of events such as the Athens Plaython 2012 festival. the feedback received from the players indicates that this new form of gaming is indeed very promising.

关键词： Pervasive multiplayer street games Interactive installations Public exhibition Evaluation Smartphones Wireless sensor devices

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