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the Simulation Algorithms Based on RL and SFM in Emergency Evacuation 6

The Simulation Algorithms Based on RL and SFM in Emergency E...

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6th ieee international conference on cloud computing and big data Analytics, ICCCBDA 2021

作者： An, Zhenpeng Xu, Fang Zhang, Di Xing, Ao Yang, Shufeng Wu, Xiaochuan ShenYang Fire Science and Technology Reaserch Institute of Mem Shenyang China

ISBN: (纸本)9780738105338

Based on the predominance of Multi-Agents Simulation in evacuation simulation, the simulation algorithms Based on RL and SFM (Social Force Model) is designed in this paper to accommodate emergency evacuations. the A*, A* with SFM are compared with algorithms we designed. the result presented analytically and graphically, results indicate A* algorithm has theoretically optimal paths, but algorithms Based on RL and SFM is closer to human behavior patterns. © 2021 ieee.

关键词： Reinforcement learning

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big data Analytics in cloud computing 6

Big Data Analytics in Cloud Computing

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6th international conference on Image Information Processing, ICIIP 2021

作者： Suhasini, Nittala Swapna Puli, Srilatha Sreyas Institute of Engineering and Technology Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9781665433617

In this paper we will study the two unlike but related technologies-big data and cloud computing-and also examines the benefits and outcomes of using cloud computing for big data analytics. As information is being produced at a phenomenal scale and it is originating from every direction, such a monstrous measure of information makes enormous or complex informational indexes. these informational collections are known as big data. the blend of cloud and big data can be attributed to fresh IT (Information Technology) wave that is causing remarkable progress across IT departments of various industries. In this new environment of big data and cloud there are challenges associated with data storage as data are accumulating *** rapidly expansion of big data requires government agencies to extract relevant data and make sense of it in order to make evidence-based policy decisions, with a focus on translating data into information and subsequently information into knowledge. the way to do this is to employ so-called big data analytics, which involves analyzing numerous data sets in order to reveal information such as specific patterns, correlations, and trends, among other *** data analytics places rigorous needs on networks, storage, and servers. this is why few businesses use the cloud for this. big data and cloud are combining to create new business prospects that support big data research while also overcoming numerous architectural *** these mutually exclusive principles to coexist a solution architecture is required to truly exploit. Future breakthroughs and research difficulties in cloud computing that support big data analytics are presented in this review. © 2021 ieee.

关键词： big data

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Certificateless Public Auditing Scheme with data Privacy Preserving for cloud Storage 6

Certificateless Public Auditing Scheme with Data Privacy Pre...

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6th ieee international conference on cloud computing and big data Analytics, ICCCBDA 2021

作者： Zhou, Rui He, Mingxing Chen, Zhimin School of Computer and Software Engineering Xihua University Cheng'du610039 China

ISBN: (纸本)9780738105338

Rapid development of cloud storage services, users are allowed to upload heavy storage and computational cost to cloud to reduce the local resource and energy consumption. While people enjoy the desirable benefits from the cloud storage service, critical security concerns in data outsourcing have been raised seriously. In the cloud storage service, data owner loses the physical control of the data and these data are fully controlled by the cloud server. As such, the integrity of outsourced data is being put at risk in reality. Remote data integrity checking (RDIC) is an effective solution to checking the integrity of uploaded data. However, most RDIC schemes are rely on traditional public key infrastructure (PKI), which leads communication and storage overhead due to the certificate management. Identity-based RDIC scheme is not need the storage management, but it has a drawback of key escrow. To solve these problems, we propose a practical certificateless RDIC scheme. Moreover, many public auditing schemes authorize the third party auditor (TPA) to check the integrity of remote data and the TPA is not fully trusted. thus, we take the data privacy into account. the proposed scheme not only can overcome the above deficiencies but also able to preserve the data privacy against the TPA. Our theoretical analyses prove that our mechanism is correct and secure, and our mechanism is able to audit the integrity of cloud data efficiently. © 2021 ieee.

关键词： cloud storage

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Research on Embedding Unsupervised Learning and Application on Tobacco Leaf data 6

Research on Embedding Unsupervised Learning and Application ...

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6th ieee international conference on cloud computing and big data Analytics, ICCCBDA 2021

作者： Zhai, Qingchen Meng, Zhen Zhou, Yuanchun Zhang, Yanling Ju, Lei Shu, Ruxin University of Chinese Academy of Science Beijing100049 China

ISBN: (纸本)9780738105338

data-driven is the core of distance measurement, which is used to measure and classify the similarity of tobacco leaf producing areas and improve the accuracy of clustering. the article proposes a spectral clustering algorithm based on auto encoding called AESC, which consists of two parts: auto encoder and spectral clustering layer. the auto encoder is used for feature learning to improve the accuracy of distance construction, and the spectral clustering layer makes the algorithm more adaptable to data distribution. After experiments, the autoencoding spectral clustering algorithm proposed in this paper is higher than the traditional Kmeans, DBscan and spectral clustering algorithms in the Silhouette Coefficient. And the similarity measurement results are mutually verified with research in the tobacco industry, which proves the reliability of the algorithm for the similarity measurement of tobacco leaf quality and is of great significance for improving the stability of cigarette quality. © 2021 ieee.

关键词： Unsupervised learning

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An Evaluation Set for Tibetan Sentences Similarity computing 6

An Evaluation Set for Tibetan Sentences Similarity Computing

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6th ieee international conference on cloud computing and big data Analytics, ICCCBDA 2021

作者： Chen, Xilin Cai, Zhijie Zhuoma, CaiRang College of Computer Science and Technology Qinghai Normal University Xining Qinghai China College of Computer Science and Technology Qinghai Normal University Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province Key Laboratory of Tibetan Information Processing in Education Ministry Southwest National University Sichuan Chengdu Qinghai Xining China Southwest National University Sichuan Chengdu China

ISBN: (纸本)9780738105338

Sentence is not only the basic unit of natural language, but also the research object of Nature Language Process. Sentence similarity computing is the basic of text similarity computing, so sentence similarity evaluation set is an essential data set for similarity technology research. Only by establishing an appropriate evaluation set can we objectively evaluate the advantages and disadvantages of similarity computing methods. In order to objectively evaluate the performance of Tibetan sentence similarity, this paper designs the construction scheme of Tibetan sentence similarity evaluation set, and builds the evaluation set TSS_320 for evaluating Tibetan sentence similarity, based on the analysis of the construction method of English and Chinese sentence similarity evaluation set, also combined with the characteristics of Tibetan sentences. the validity of the evaluation set is verified by statistical methods. © 2021 ieee.

关键词： Natural language processing systems

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Improvement of the DPoS Consensus Mechanism in Blockchain Based on PLTS 7

Improvement of the DPoS Consensus Mechanism in Blockchain Ba...

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7th ieee international conference on big data Security on cloud, 7th ieee international conference on High Performance and Smart computing, and 6th ieee international conference on Intelligent data and Security, bigdataSecurity/HPSC/IDS 2021

作者： Chen, Shuyu Xie, Mingyue Liu, Jun Zhang, Yunan School of Big Data and Software Engineering Chongqing University Chongqing China College of Software Engineering Chongqing University of Posts and Telecommunications Chongqing China Guangdong Provincial Key Laboratory of Power System Network Security Guangzhou China

ISBN: (纸本)9781665439275

Contemporarily, DPoS is the fastest, most effective, decentralized and flexible consensus mechanism among all consensus mechanisms. Similar to the vote of the board, the holders cast a certain number of delegates to perform verification and accounting on their behalf in DPoS. In order to select the most appropriate delegates to implement the operations in blockchain, the DPoS consensus mechanism needs to be improved. therefore, an improved DPoS consensus mechanism based on Probabilistic Linguistic Term Set (PLTS) is proposed in this paper. Just like human elections, this method allows each node to vote 'support' and 'oppose' for the delegate node. the efficient and flexible method reduces the probability of malicious nodes becoming delegates and guarantees the security of block generation in the blockchain. the effectiveness of the improved DPoS was verified by examples. © 2021 ieee.

关键词： Blockchain

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Unsupervised Perturbation based Self-Supervised Adversarial Training 7

Unsupervised Perturbation based Self-Supervised Adversarial ...

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作者： Wang, Zhuoyi Lin, Yu Li, YiFan Mi, Feng Tian, Zachary Khan, Latifur thuraisingham, Bhavani The University of Texas at Dallas Department of Computer Science RichardsonTX United States Texas Academy of Mathematics and Science DentonTX United States

ISBN: (纸本)9781665439275

Deep neural networks (DNNs) are vulnerable to adversarial attacks. Existing adversarial defense approaches mostly use a large number of labels during the training step to improve the model's robustness. However, the labeling typically requires a lot of resources and is time-consuming, especially when the annotation is hard to generate (e.g., an emergency scene in autopilot). In this paper, we propose an instance-level unsupervised perturbation to replace the supervised class-level adversarial sample in the robust training. the unsupervised perturbation is generated on various transformed views of single input, which aims to make the model confuse the instance-level discrimination of this specific input. We further introduce the contrastive learning based adversarial learning(UPAT), which maximizes the agreement between the transformed instance with its corresponding unsupervised perturbed output, and encourages the model to suppress the vulnerability in the embedding space. We conduct comprehensive experiments on three image benchmarks, and the quantitative results demonstrate that our defense approach consistently outperforms prior state-of-the-art techniques, by improving the defense ability efficiently on various white-box attacks. © 2021 ieee.

关键词： Deep neural networks

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Influence of Spraying Speed of Spraying Robot on Coating thickness 6

Influence of Spraying Speed of Spraying Robot on Coating Thi...

引用

6th ieee international conference on cloud computing and big data Analytics, ICCCBDA 2021

作者： Zhang, Lin Zhang, Guang-Ming College of Electrical Engineering and Control Science Nanjing Tech University Nanjing Jiangsu211816 China

ISBN: (纸本)9780738105338

In the process of robot spraying operation, the outer surface of horizontal rectangular steel pipe in steel structure frame needs to be sprayed with fire retardant coating. Because the outer surface is in different planes, when spraying the upper and lower surfaces or side surfaces, due to the existence of gravity or external environment, or when the distance from the spray gun to the spraying operation surface changes, the coating efficiency will change. therefore, the thickness of the coating on the outer surface of the workpiece is inconsistent, which affects the quality of the coating and leads to the decline of the fireproof performance. Aiming at the above problems, this paper finds out the proportional relationship between spraying speed and coating efficiency, and solves the problem of coating thickness uniformity caused by the change of coating efficiency by increasing or decreasing the moving speed of spray gun. through MATLAB simulation, this method can improve the uniformity of coating thickness. © 2021 ieee.

关键词： thickness measurement

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Service Placement Considering Robustness and Dynamic in Edge computing 6

Service Placement Considering Robustness and Dynamic in Edge...

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6th ieee international conference on cloud computing and big data Analytics, ICCCBDA 2021

作者： Liu, Yang Ma, Qianpiao School of Software Engineering University of Science and Technology of China Hefei China

ISBN: (纸本)9780738105338

With the increasing popularity of the Internet of things, a huge requirement for low-latency in service response has spurred. Many researches have been proposed on service placement in mobile edge computing (MEC) to address the low-latency requirement, which pushes more service functions from the remote cloud to the network edge. However, they do not consider the scenarios with uncontrolled factors, such as disaster relief and battlefield monitoring, the edge server is likely to go down and fail to respond to the service requests from users. In this paper, we defined the service placement problem in the unreliable and dynamic network and developed a novel distributed service placement decision-making solution called RTSO which based on the greedy algorithm. the edge server using the RTSO algorithm will take into account service popularity and resource constraints, and judiciously adjust service placement decisions. We also verify through experiments that our proposed algorithm can converge to the global optimum through iteration. A large number of simulation results show that our algorithm can provide near-optimal performance and effectively improve the robustness of services in the system. © 2021 ieee.

关键词： Mobile edge computing

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data Mining of Association between Hyperuricemia and Common Chronic Diseases Based on Evolutionary Apriori Algorithm (EAA) 6

Data Mining of Association between Hyperuricemia and Common ...

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6th ieee international conference on cloud computing and big data Analytics, ICCCBDA 2021

作者： Huang, Jingwen Tan, Junyan Hua, Di Hohai University Dept. Internet of Things Changzhou China Changzhou Institute of Technology Dept. Electrical and Information Engineering Changzhou China Changzhou College of Information Technology Dept. Electronic Engineering Changzhou China

ISBN: (纸本)9780738105338

With the rapid development of medical information, a large amount of medical data has been generated, which contains huge potential information. data mining is widely used to discover hidden information in these large amounts of data. this application can promote the transformation of diagnosis and treatment mode of chronic diseases from medical research, clinical decision-making, disease early warning. In this paper, we take the hyperuricemia as the research object. An optimized Apriori Algorithm has been proposed to mine the correlation model of chronic diseases related to hyperuricemia in order to provide a basis for the precise treatment of hyperuricemia. An associated relation is proposed according to the experiments, which could apply an auxiliary support to doctor's clinical diagnosis and disease research in the local. the evaluation experiments of performances demonstrate an efficient performance for the proposed algorithm compared with the original Apriori Algorithm. © 2021 ieee.

关键词： data mining

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