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International Conference on Advanced Communication Technology (ICACT)

作者： Jun Guo Xiaoyu Zhang Zhiyuan Gao Ligeng Wang Wenyu Li Hangmin Chi Software College Northeastern University Shenyang Liaoning Province China School of Computer Science and Engineering Northeastern University Shenyang Liaoning Province China

ISBN: (数字)9791188428045

ISBN: (纸本)9781728149431

Expressway traffic flow is an important traffic information of expressway. At present, the main way to detect expressway traffic flow is through video image collection, which is easily affected by external light blocking and has high calculation cost of image analysis. In order to solve the problems of poor accuracy of image analysis and large amount of computation in dynamic image analysis, based on the study of audio signal of expressway traffic, this paper proposed a method of expressway traffic flow status identification based on depth neural network. The method proposed in this paper firstly classifies and defines the traffic flow status, denoises the audio signal and extracts the features, then uses Deep Neural Network (DNN) to build the model to get the DNN model to identify the traffic flow status of expressway, and then pretrains the DNN model. Then the parameters of the model are optimized, and the Hidden Markov Model (HMM) is used to decode the model. Finally, the DNN model is used to estimate the observation probability of audio signals of different expressway traffic flow status, and the result of expressway traffic flow status identification is given according to the calculated probability. The accuracy of the proposed method is compared with that of the existing methods. Experimental results show that the proposed method performs better in recognition accuracy.

关键词： Hidden Markov models Training Neural networks Mathematical model Data models Roads

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EDOA: an efficient delay optimization approach for mixed-polarity Reed-Muller logic circuits under the unit delay model

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Frontiers of computer science 2019年第5期13卷 1102-1115页

作者： Zhenxue HE Limin XIAO Fei GU Li RUAN Zhisheng HUO Mingzhe LI Mingfa ZHU Longbing ZHANG Rui LIU Xiang WANG College of Information Science and Technology Hebei Agricultural University Baoding 071001 China State Key Laboratory of Software Development Environment Beihang University Beijing 100083 China School of Computer Science and Engineering Beihang University Beijing 100083 China School of Electronic and Information Engineering Beihang University Beijing 100083 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China National Engineering Research Center for Science & Technology Resources Sharing Service Beijing 100083 China

Delay optimization has recently attracted signif-icant attention. However, few studies have focused on the delay optimization of mixed-polarity Reed-Muller (MPRM) logic circuits. In this paper, we propose an efficient delay op-timization approach (EDOA) for MPRM logic circuits under the unit delay model, which can derive an optimal MPRM logic circuit with minimum delay. First, the simplest MPRM expression with the fewest number of product terms is ob-tained using a novel Reed-Muller expression simplification approach (RMESA) considering don't-care terms. Second, a minimum delay decomposition approach based on a Huffman tree construction algorithm is utilized on the simplest MPRM expression. Experimental results on MCNC benchmark cir-cuits demonstrate that compared to the Berkeley SIS 1.2 and ABC, the EDOA can significantly reduce delay for most cir-cuits. Furthermore, for a few circuits, while reducing delay, the EDOA incurs an area penalty.

关键词： delay optimization mixed-polarity Reed-Muller logic circuits unit delay model don't-care terms,

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Locally Weighted DTW Method Based on Sparse Path Matrix

Locally Weighted DTW Method Based on Sparse Path Matrix

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International Conference on Information Systems and computer Aided Education (ICISCAE)

作者： Maobin Sun Lisheng Zhang College of Computer Science and Technology Chong Qing University of Post and Telecommunications Chongqing China College of Software Engineering Chong Qing University of Post and Telecommunications Chongqing China

ISBN: (数字)9781728183046

ISBN: (纸本)9781728194608

Dynamic time warping algorithm is one of the most effective time series similarity measures. The LDTW algorithm solves the problem that the dynamic time warping algorithm timing alignment method treats the instance features equally and ignores its local discriminative characteristics, but the time complexity of the LDTW generation of the weight matrix is too high. This paper proposes a LDTW algorithm based on sparse path matrices. In the process of iteratively generating a weight matrix from the training set, a sparse path matrix between homogeneous sequences and a sparse path matrix between different types of sequences are generated according to the type of sequence in the training set. Weight matrix over a sparse path matrix. The proposed algorithm is simulated and verified on the UCR dataset. The LDTW algorithm based on the sparse path matrix has the same classification error rate as LDTW, but the time cost of generating the weight matrix is significantly lower than the LDTW algorithm. It proves the effectiveness of path matrix LDTW in reducing time consumption.

关键词： Training Error analysis Heuristic algorithms Time series analysis Classification algorithms Sparse matrices Time complexity

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Fashion meets AI technology

Fashion meets AI technology

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Artificial Intelligence on Fashion and Textiles Conference, AIFT 2018

作者： Zou, Xingxing Wong, Wai Keung Mo, Dongmei Institute of Textiles and Clothing The Hong Kong Polytechnic University Hong Kong College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9783319996943

With the development of Artificial Intelligence (AI) technology, extensive research efforts have been devoted to the cross-disciplinary area of fashion and AI. This paper reviews previous research studies of AI on fashion aspect. Fundamental image processing technologies will be introduced first and followed by apparel recognition, and fashion aesthetic understanding. We finally propose a framework about the research direction of AI research on fashion as a reference for inspiring fashion and AI-related researchers. © Springer Nature Switzerland AG 2019.

关键词： Image processing

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Blockchain-based secure routing strategy for airborne mesh networks 2

Blockchain-based secure routing strategy for airborne mesh n...

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2nd IEEE International Conference on Industrial Internet Cloud, ICII 2019

作者： Liu, Yongxin Wang, Jian Song, Houbing Li, Jianqiang Yuan, Jiawei Embry-Riddle Aeronautical University Daytona BeachFL32114 United States College of Computer Science and Software Engineering Shenzhen University China

ISBN: (数字)9781728129778

ISBN: (纸本)9781728129778

Mesh networks are widely used to provide flexible communication support for spatially distributed devices in Cyber-Physical Systems (CPS), such as UAS (Unmanned Aerial Systems) swarms. In the mesh network for UAS, a critical factor causing security concern is its routing strategy, especially for enabling source routing without disclosing the mesh network's sensitive topology among participants. Besides, conventional UAS networks are vulnerable to malicious participants which broadcast erroneous routing information. In this paper, we propose a blockchain-based approach to enable UAS in mesh networks to collect, aggregate and redistribute routing information with a secure and trustworthy manner. Our method can avoid the disclosure of sensitive network topology in the presence of compromised peers. Evaluations show that our approach outperforms the conventional method in terms of information security. © 2019 IEEE.

关键词： Blockchain

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Synergy of edge intelligence and blockchain: a comprehensive survey

TechRxiv

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TechRxiv 2021年

作者： Wang, Xiaofei Ren, Xiaoxu Qiu, Chao Xiong, Zehui Yao, Haipeng Leung, Victor C.M. College of Intelligence and Computing Tianjin University Tianjin300350 China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore487372 Singapore Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100088 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518061 China Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada

Edge intelligence (EI), as an emerging technology, has been attracting significant attention. It pushes the frontier of artificial intelligence (AI) from the cloud to the network edge, aiming to embrace and support the next-generation communications while unleashing AI services. However, it faces challenges in its decentralized management and security, which limit its capabilities to support services with numerous requirements. On the other side, blockchain (BC), as a promising decentralized technology, is beneficial to tackle the above issues. However, there exist some technical challenges for BC, such as transaction capacity, scalability, and fault tolerance. Motivated by significant current interest around EI and BC, this survey examines whether the synergy of EI and BC can make a powerful network with combined functionalities of both cutting-edge technologies. Accordingly, we develop EI-chain and Chain-intelligence to realize reliable computing-power management, data administration, and model optimization at the edges, while improving the functions of BC by leveraging complementary characteristics of EI and BC, further making up for their own limitations. In this survey, a wide spectrum of literature is carefully reviewed to enable the EI-chain and Chain-intelligence. Moreover, we cover the technological aspects of EI-chain and Chain-intelligence: overview, motivations, and frameworks. Finally, some challenges and future directions are explored. We believe this survey will provide developers and researchers a comprehensive view on the synergy of EI and BC, while accelerating the design of a powerful integrated network. © 2021, CC BY-NC-SA.

关键词： Blockchain

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An Axiomatic Approach to BigrTiMo

An Axiomatic Approach to BigrTiMo

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Theoretical Aspects of software engineering (TASE)

作者： Wanling Xie Huibiao Zhu Shengchao Qin College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China College of Computer Science and Software Engineering Shenzhen University China

BigrTiMo [1], a process algebra that combines the rTiMo calculus [2] and the Bigraph model [3], is capable of specifying a rich variety of properties for structure-aware mobile systems. Compared with the rTiMo model, our BigrTiMo calculus can specify not only time, mobility and the local communication (the two communication components should be at the same location), but also the remote communication (the two communication components can be at the different locations). In this paper, we present an axiomatic approach to BigrTiMo program language verification based on Hoare-style [4] proof rules. In order to describe the timing of observable actions and the state of the bigraph, we extend the assertion language with primitives. Moreover, we prove the soundness of our proof rules and show the application of the proof rules via an example.

关键词： Algebra Semantics Calculus Cognition Timing software engineering

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Node MCU based DoS attack evaluation in IoT device

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AIP Conference Proceedings 2022年第1期2519卷

作者： G. Amudha P. Prem Priya V. Dinesh A. Akash 1Department of Computer Science and Engineering RMD Engineering College Kavaraipettai Tamil Nadu India 2Department of Computer Science and Engineering RMK College of Engineering and Technology Thiruvallur Tamil Nadu India 3Software Developer Virtusa Pvt. Ltd Chennai Tamil Nadu India

In the Internet of Things (IoT) projects Node MCU ESP12 controller chip is used. During the assault simulation, it is necessary to access the safety and capacity of such a simple device in developing a number of projects that address the Internet of Things to influence system security. This device can stop the various findings that indicate the sort of attacks that spread, the incapacity of withstanding these attacks, and the *** audit archive refines the appropriate threat model for the security of WSN and IoT-based correspondences. It analyses the security demands, numerous potential risks, and various scenarios in WSN-based and IoT-based communications. Different designs of correspondence conditions are viewed as development at that time, based on WSN and IoT; the present problems and advancements in WSN and IoT are analyzed. A logical structure of security and assurance may be observed in WSN and IoT to secure the show. For feasibility, a number of investigations should be followed in this post. To show the network security choices from the integrated IoT-WSN, it is tabulated from the performance data.

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Quality Assurance for Automated Commit Message Generation

Quality Assurance for Automated Commit Message Generation

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IEEE International Conference on software Analysis, Evolution and Reengineering (SANER)

作者： Bei Wang Meng Yan Zhongxin Liu Ling Xu Xin Xia Xiaohong Zhang Dan Yang Key Laboratory of Dependable Service Computing in Cyber Physical Society (Chongqing University) Ministry of Education China School of Big Data and Software Engineering Chongqing University Chongqing China College of Computer Science and Technology Zhejiang University Hangzhou China Monash University Australia

ISBN: (纸本)9781728196305;9781728196312

Many automated commit message generation (CMG) approaches have been proposed for facilitating the understanding of software changes. They are shown to be promising and can generate commit messages that are semantically relevant to the reference messages for a number of commits. However, a large proportion (over 50%) of semantically irrelevant commit messages are also generated simultaneously. Such messages may mislead developers, require additional efforts of developers to confirm and filter out, and hinder the application of existing CMG approaches in practice. For tackling this problem, prior work mainly focuses on proposing new methods to improve the generation accuracy. However, another promising way for bridging the gap between CMG approaches and the practice has not been well investigated, which is: can we automatically assure the semantic relevance of the generated messages?To that end, in this work, we propose an automated Quality A ssurance framework for commit message generation (QAcom). QAcom can assure the quality of generated commit messages by automatically filtering out the semantically-irrelevant generated messages and preserving the semantically-relevant ones as many as possible. In particular, QAcom consists of a Collaborative-Filtering-based (CF) component and a Retrieval-based (RE) component. Given a commit message generated by a CMG approach, QAcom estimates whether this generated message is semantically relevant to its ground truth, which is unknown when estimating, based on both the collaborative filtering algorithm and the similarity between this commit and historical commits. We evaluate the effectiveness of QAcom by "plugging" it in three state-of-the-art CMG approaches. Experimental results on three public datasets show that QAcom can effectively filter out semantically-irrelevant generated messages and preserve semantically-relevant ones.

关键词： Quality assurance Filtering Conferences Collaborative filtering Semantics Writing Filtering algorithms

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MERITS: Medication Recommendation for Chronic Disease with Irregular Time-Series

MERITS: Medication Recommendation for Chronic Disease with I...

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IEEE International Conference on Data Mining (ICDM)

作者： Shuai Zhang Jianxin Li Haoyi Zhou Qishan Zhu Shanghang Zhang Danding Wang Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University China School of Computer Science and Engineering Beihang University China Shenyuan Honors College Beihang University China School of Software Beihang University China National University of Singapore >Singapore

ISBN: (纸本)9781665423991

Medication recommendation for chronic diseases based on the complex historical electronic medical records (EMR) is an important and challenging research problem in medical informatics because the medical records are often irregularly sampled and contain many missing data. However, most existing approaches fail to explore the irregular time-series dependencies and ignore the consecutive correlation in dynamic prescription history. To fill this gap, we propose the MEdication Recommendation network on Irregular Time-Series (MERITS), which captures the irregular time-series dependencies with the neural ordinary differential equations (Neural ODE). Meanwhile, it leverages a drug-drug interaction knowledge graph and two learned medication relation graphs to explore the co-occurrence and sequential correlations of the medications. We further propose an attention-based encoder-decoder framework to combine the historical information of patients and medications from EMR. Besides, we collect and annotate a diabetes inpatient medication dataset and demonstrate the effectiveness of MERITS by comparing it with several state-of-the-art methods of medication recommendations.

关键词： Correlation Data visualization Ordinary differential equations Data models Diabetes History Electronic medical records

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