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2024 International Conference on Culture-Oriented Science and Technology, CoST 2024

作者： Feng, Lianze Mu, Lin Yang, Yi Li, Caihong Lanzhou University School of Information Science and Engineering Lanzhou730000 China Ministry of Culture and Tourism Key Laboratory of Tourism Information Fusion Processing and Data Ownership Protection Lanzhou730000 China Tourism Quality Supervision and Management Institute of China Beijing100740 China

ISBN: (纸本)9798350380347

Tourist flow prediction faces challenges in achieving high accuracy due to the complex and dynamic nature of tourism data. This study addresses these challenges by proposing a multi-feature combined prediction model, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise-Incremental Entropy-K-means clustering-Time Convolutional Network-Coati Optimization Algorithm (CEEMDAN-IEK-TT-COA). The model integrates signal decomposition, clustering reconstruction, component prediction, and optimization algorithms. key features are selected through feature engineering, followed by data decomposition and reconstruction using CEEMDAN, Incremental Entropy, and K-means clustering. A model pool of Time Convolutional Network (TCN), Bidirectional Gated Recurrent Unit (Bi-GRU), Long Short-Term Memory network (LSTM), and Transformer filters optimal sub-models for combined prediction. The Coati Optimization Algorithm (COA) refines the final prediction. Experimental results on Jiuzhaigou and Siguniangshan datasets demonstrate significant RMSE improvements of 21.81 % and 17.84 %, validating the model's effectiveness. © 2024 IEEE.

关键词： Long short-term memory

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Categorizing npm Packages by Analyzing the Text Information in Software Repositories

Categorizing npm Packages by Analyzing the Text Information ...

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Asia-Pacific Conference on Software engineering

作者： Yu Wang Huaxiao Liu Shanquan Gao Shujia Li College of computer science and technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun China

ISBN: (纸本)9781665437851

To prevent JavaScript developers from reinventing wheels, npm ecosystem provides numerous third-party libraries for developers to realize relevant functionalities. Npm displays the tags provided by the creators for these packages to help developers find suitable ones. However, not all creators have the habit of tagging their packages, and thus npm cannot provide tag information of a lot of packages for developers to help them understand the package functionalities effectively. Considering that many tags are unrelated to the functionality of packages, we propose a method to find out the tags that are important to distinguish the functionality categories of packages and assign them to untagged packages for assisting developers in the process of retrieving the packages. Firstly, we analyze the attribute of existing tags in npm to establish category tags (functionality categories). Then, we further mine the readme of tagged packages to generate keywords for each category tag. Finally, our method identifies category tags for untagged packages by measuring the similarity between their readme and the keywords of category tags. The evaluation demonstrates that our approach has a good performance in assigning category tags to untagged packages.

关键词： Correlation Codes Ecosystems Wheels Tagging Software Libraries

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Building a Private Cloud Based on Microservices for Computer Science laboratory in Universities

Building a Private Cloud Based on Microservices for Computer...

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International Conference on Information Science and Control engineering (ICISCE)

作者： Hao Liu Zhe Wang Lan Huang Kangping Wang School of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University Changchun China

Computer science labs in universities have different demands in cloud computing compared with typical IT companies. They differ greatly in software requirements and resource utilization. As an instance, we propose building a private cloud based on microservices with Docker and Kubernetes in our laboratory to match our labs’ typical *** private cloud proposed in this paper is composed of multiple components such as authentication, service gateway, distributed storage, knowledge management, code management, etc. Furthermore, some typical research software systems are deployed as microservices in the private cloud. To satisfy complex software environment requirements, a multi version microservice is implemented. In our microservices platform, users can submit their own microservices and manage these microservices’ life cycle through a web interface. In addition, the platform will automatically start and stop low frequency services to improve resource utilization rate. We use laboratory resources to conduct experiments and build a platform. With deploying the platform in our laboratory, it shows that the platform meets most of typical demands in research work and improves research efficiency.

关键词： Computer science Cloud computing Information science Control engineering Buildings Companies Logic gates

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A Bi-objective Optimal Scheme for 5G Base Station Deployment Based on BPSO 12th

A Bi-objective Optimal Scheme for 5G Base Station Deployment...

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12th International Conference on Computer engineering and Networks, CENet 2022

作者： Zhu, Tao Xu, Yin-qing Guo, Hao-qi Wang, Yi-bo Department of Computer Information and Cyber Security Jiangsu Police Institute Nanjing China Engineering Research Center of Electronic Data Forensics Analysis Jiangsu Province Nanjing China Key Laboratory of Digital Forensics Department of Public Security of Jiangsu Province Nanjing210031 China

ISBN: (纸本)9789811969003

The 5G mobile network is a kind of critical information infrastructure for future Internet of Things. Due to its rapid development, the planning and deployment of 5G network base stations is a more urgent and meaningful problem than ever before from the aspect of optimization. Because the purpose of establishing a 5G base station is to make its wireless signal cover as many areas as possible, a 0–1 programming model with two optimal objectives is proposed for 5G base stations based on the cover set. Then after analyzing the difficulties in solving the problem expressed by above model, employing the idea of divide and conquer and the strategies of parallelization, a scheme based on Binary Particle Swarm Optimization (BPSO) algorithm is proposed to solve this problem. In the first step of the scheme, the partition processing based on coordinate position is considered by the way of dividing the target area into many smaller sub-areas with the algorithm of Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH). The next step is to use BPSO algorithm improved by sparse particles initialization and a suppressor factor to solve each small sub-area with the parallel computing and the memory mapping technology. The proposed approach has been tested in several experiments and the experimental results demonstrate its effectiveness. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Base stations

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The design and analysis of distributed authentication scheme in VANET

The design and analysis of distributed authentication scheme...

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IEEE Youth Conference on Information, Computing and Telecommunication, YC-ICT

作者： Jian Wang Yanheng Liu Yu Jiao Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun Jilin China Jilin University Changchun Jilin CN

Vehicular ad hoc networks (VANETs) have many new characteristics unlike traditional network, such as centriclessness, mobility and multi-hop transmission, which invalidate conventional key managements. The fast development and successful application of trusted computing technology provide a potential solution to achieve effective authentication and trust evaluation. According to the VANETs with hierarchy organization structure like tank group, a new authentication and trust evaluation framework is proposed based on trusted computing technology, the concepts of "trusted attribute" and "trusted grade" are introduced, and the key management architecture as well as authentication process of mobile node are explained in detail. Moreover, the real applications of the presented framework in tank fight are discussed, and the trust evaluation methods and its argumentations in the presented framework are given.

关键词： Authentication Frequency Wire Electronic packaging thermal management Circuit simulation Scattering parameters Bonding Integrated circuit packaging Chip scale packaging Equivalent circuits

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Study on IoT and Big data Analysis of Furnace Process Exhaust Gas Leakage 15th

Study on IoT and Big Data Analysis of Furnace Process Exhaus...

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15th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2019, held in conjunction with the 12th International Conference on Frontiers of Information Technology, Applications and Tools, FITAT 2019

作者： Zhou, Yu-Wen Chang, Kuo-Chi Pan, Jeng-Shyang Chu, Kai-Chun Horng, Der-Juinn Lin, Yuh-Chung Jing, Huang Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China Department of Business Administration Group of Strategic Management National Central University Taoyuan Taiwan College of Information Science and Engineering Fujian University of Technology Fuzhou China

ISBN: (纸本)9789811397134

Modern FABs use a large number of high-energy processes such as plasma, CVD, and ion implantation;the furnace is one of the important tools of semiconductor manufacturing. The FAB installed FTIR system due to the 12" furnace tools based on the aforementioned production management requirements. This study used open-type FTIR and integrated IoT mechanism to connect to the cloud, which is suitable for a variety of gaseous pollutants. This study set up two measuring points of furnace process tools in the 12" factory of Hsinchu Science Park in Taiwan. This study obtained FTIR measurements, and according to the OHSA regulations, this study is set in the cloud database for big data analysis and decision-making, when the upper limits of TEOS, C2H4, and CO are 0.6 ppm, 2.0 ppm, and 1.7 ppm and the lower limits of TEOS, C2H4, and CO are 0.4 ppm, 1.5 ppm, and 1 ppm. The application architecture of this study can be extended to other semiconductor processes, so that IoT integration and big data operations can be performed for all processes;this is an important step in promoting FAB intelligent production and an important contribution of this study. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Big data

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Accelerating Intelligent Microfluidic Image Processing with Transfer Deep Learning: A Microchannel Droplet/Bubble Breakup Case Study

SSRN

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SSRN 2023年

作者： Zhang, Shuyuan Li, Haoran Wang, Kai Qiu, Tong Department of Chemical Engineering Tsinghua University Beijing100084 China Beijing Key Laboratory of Industrial Big Data Systems and Applications Tsinghua University Beijing100084 China State Key Laboratory of Chemical Engineering Department of Chemical Engineering Tsinghua University Beijing100084 China

Deep learning has recently been leveraged in the microfluidic research for intelligent image processing. However, it usually requires massive human efforts to label sufficient images for obtaining a precise deep learning model. We herein propose a transfer deep learning method for the rapid deployment of Mask R-CNN, which is capable of reutilizing models trained in previous microfluidic domains to accelerate the analysis of droplets and bubbles in the images of the target microfluidic domain. The transfer deep learning is validated in the microfluidic research with a constrictive microchannel, which is commonly used to break large droplets or bubbles to enhance emulsification. With only 40 labeled images and about 10 min training, the transfer deep learning achieves precise recognition results for both droplets and bubbles in the microfluidic experiments. Applying the trained Mask R-CNN to unlabeled images, the breakup of droplets is found to be highly dependent on the low flow rate, but the bubble breakup is much easier to happen in the same microfluidic equipment. Critical conditions of droplet breakup and size laws of droplet and bubble are precisely determined based on the recognition results of the trained Mask R-CNN. © 2023, The Authors. All rights reserved.

关键词： Microfluidics

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CommonCube-based conceptual modeling of ETL processes

CommonCube-based conceptual modeling of ETL processes

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International Conference on Control and Automation (ICCA)

作者： Zehai Li Jigui Sun Haihong Yu Jian Zhang College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Changchun China

ETL tools are responsible for the extraction of data from sources, their cleansing and loading into a target data warehouse. However, nowadays, the design and development of ETL processes are performed in an in-house fashion, and need uniformed methodological foundations. In this paper, we propose a novel conceptual model for the modeling of ETL processes. We employ CommonCubes to represent the cubes in a target data warehouse. CommonCubes release the design of ETL processes from overdependence on the physical schema of the target data warehouse, and enable the designers to pay more efforts to data transforming than data loading when designing ETL processes. Based on the constraint functions on source attributes and the transforming operations on target attributes, we define ETL mappings 1:0 capture the semantics of various relationship cardinalities between source attributes and target attributes, which provide a good basis for the design of ETL processes.

关键词： data warehouses data mining Cleaning Computer science Process design Costs Educational technology Laboratories knowledge engineering Computer science education

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Learning Essential Graph with Immune Co-Evolutionary Algorithm

Learning Essential Graph with Immune Co-Evolutionary Algorit...

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2010 International Conference of Informationa Science and Management engineering(2010年信息科学与管理工程国际学术会议 ISME 2010)

作者： Haiyang Jia Juan Chen Dayou Liu College of Computer Science and Technology Key Laboratory for Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun Jilin China 130012

Essential graph is a graphical representation for Markov equivalence classes of Bayesian networks. Learning essential graph can avoid some problems in traditional Bayesian networks learning algorithms: (1) the number of illegal structures is exponential, which infect the efficiency of structure learning;(2) comparing the structures in same equivalent class slow down the speed of convergence;(3) if the prior distribution for each structure is equal, the more structures contain in the equivalent class the higher prior probability of the class has. This paper employs two competitive bio-inspired algorithms, immune algorithm and co-evolutionary algorithm, for learning Essential graph. The algorithm combines dependency analysis and search-scoring approach together. Experiments show that the searching space was decreased, compare with prior works, the convergence speed and the efficiency was improved.

关键词： Bayesian network structure learining co-evolutionary algorithm artificial immune system

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Fuzzy kernel clustering based on particle swarm optimization

Fuzzy kernel clustering based on particle swarm optimization

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IEEE International Conference on Granular Computing (GRC)

作者： Libiao Zhang Chunguang Zhou Ming Ma Xiaohua Liu Chunxia Li Caitang Sun Miao Liu College of Computer Science and Technology Key Laboratory for Symbol Computation and Knowledge Engineering of the National Education Ministry of China Jilin University Changchun China

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