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Copyright of Cotton Textile Technology is the property of Cotton Textile Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objectives: Satellite mission planning is an important way to rationally allocate satellite resources and obtain effective data. In order to solve the problem of resource waste in the absence of user demand for Qimingxing-1(QMX-1), we proposed a semantic description driven autonomous mission planning method for QMX-1. Methods: By analyzing the characteristics of earth observation targets and their requirements for remote sensing data, we have construct a semantic description model for global tasks and form a global earth observation target database. Based on the description model, we design a satellite autonomous mission planning method. By building a mission planning model, we can achieve autonomous planning for high-value targets and maximize the value of satellite in orbit applications. Results and Conclusions: We verifyed the proposed model based on the QMX-1 and proved the feasibility of the method in this paper. The model is applicable to different types of remote sensing satellites and can play a certain value in the future remote sensing constellation real-time intelligent service applications. [ABSTRACT FROM AUTHOR]

Copyright of Cotton Textile Technology is the property of Cotton Textile Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

【Objective】This study proposes a tea knowledge graph construction method based on BERT-WWM-BiLSTM-AttTea-CRF, which aims to solve the problems in the field of tea science, such as imperfect corpus database, poor aggregation ability of multi-source heterogeneous data and difficult knowledge sharing.【Method】This method replaced the random masking BERT layer in the pre training model with the BERT-WWM（Whole Word Masking） layer based on the whole word masking. According to the global text characteristics of the corpus data in the tea field, an attention mechanism layer that can realize the weight distribution of key tea entities was designed to improve the accuracy of text extraction. The whole process of tea Chinese entity recognition was completed by extracting and classifying each entity in the sequence through conditional random field.【Result】The model can effectively identify the entities in the tea knowledge text data, and the entity extraction effect of unstructured tea data was better than RoBERTA＿BiLSTM＿CRF,ALBERT＿BiLSTM＿CRF. The recognition precision, recall and F1 value were 92.03%, 90.36% and 91.19%. The improved model has significantly improved the recognition rate of tea variety data and tea disease data, with F1 values reaching 94.32% and 94.05%.【Conclusion】The tea knowledge graph constructed by this research method has the advantages of wide data coverage, strong aggregation ability, and complete system, which is of great significance to the construction of knowledge graph in specific agricultural fields and the extraction of agricultural Chinese named entities. [ABSTRACT FROM AUTHOR]

Copyright of Railway Investigation & Surveying is the property of Railway Investigation & Surveying Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

It presents an improved FP-Growth frequent itemset mining algorithm for big data based on Hadoop framework and MapReduce programming model.Firstly, the transaction database is extracted according to each frequent 1-items to generate corresponding projection databases which are distributed to several node machines.Then each node machine divides the projection database into several smaller sub-databases, and uses the improved algorithm to mine partial frequent itemsets in parallel.Finally, all the frequent itemsets are obtained by merging all the partial frequent itemsets.This algorithm does not need to generate a huge FP tree for transaction database as the traditional FP-Growth algorithm and some other improved algorithm, so effectively solves the problem of FP-Growth algorithm and other improved algorithm failure because of insufficient memory for storage of huge FP tree in a single machine.At the same time, because the size of these sub-databases are close to each other, the load distributed to each node is more balanced, which makes the algorithm more efficient. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Road network selection is an important part of cartographic generalization and the existing selection methods only consider the static characteristics of road network. A hybrid multi-feature selection method based on trajectory data is proposed to solve these problems. Methods: The proposed method takes stroke as the basic selection unit. Firstly, a dual graph is constructed to describe the structural relationship of the road network. The static characteristics of the road network are evaluated using such indicators as length, degree, betweenness and closeness. Secondly, based on the characteristics of the trajectory data, the dynamic characteristics of the road network are evaluated using such indicators as vehicle flow, vehicle speed and vehicle density near the road intersection. Finally, the weight of each indicator and the comprehensive importance value of each road are calculated by the method of criteria importance through intercriteria correlation. At the same time, the Voronoi diagram is introduced to divide the road network, and the density characteristics are obtained, which are taken as the constraint indicator of road network selection. Results: The experimental results show that this method can maintain the overall structure, taking into account the connectivity and density distribution, and can combine the traffic characteristics of the trajectory data. Conclusions: The selection results are in accordance with the actual situation and have certain practicability. [ABSTRACT FROM AUTHOR]

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Liquid Crystal & Displays is the property of Chinese Journal of Liquid Crystal & Displays and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A spatial prevalent co-location pattern (SPCP) is a subset of spatial features whose instances frequently appear together in geographic space. Memory-based neighbor relationship materialization method to search for pattern's instances is efficient, but instance information is stored repeatedly. Graph database technology can efficiently model data with complex associations. Thus, it is possible to consider using the graph database technology to materialize neighbor relationships (i.e., to construct neighborhood graph), but directly transplanting existing mining methods cannot exert the advantages of graph traversal. To solve the above problem, this paper explores the graph databasebased approach to mine spatial prevalent co-location patterns. Firstly, the graph database is utilized to model the spatial instances and their neighbor relations, i.e., the instances and relations are stored in the graph database to construct the neighborhood graph. Then, a basic algorithm called subgraph (or clique) search is designed based on the graph database, using the way of clique search strategy to generate a pattern's table instance to obtain the participating instances, and avoid the inefficient combination or join operations in the traditional method. Considering the low efficiency of collecting participating instances by generating table instances, a participating instance verification algorithm is designed, including the filtering and verification phases. The filtering phase determines whether the features involved in the center instance's neighborhoods fully contain the features in the pattern, and the verification phase determines whether there is pattern instance containing the central instance. The participating instance verification algorithm determines as many participating instances as possible each time, thereby effectively reducing the search space and the number of clique searches. In addition, the correctness and completeness of the proposed algorithms are proven. Finally, extensive experiments are conducted on real and synthetic datasets to verify the efficiency and effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Objectives: Vector tile technology is considered as a new generation of Web map solution. Compared with raster tile, vector tile is more flexible. It renders the map based on vector data and preset styles on the client. Therefore, users can easily change map styles without reproducing tile data. However, in vector tile maps, the features that cross the grid are divided into multiple parts, which often cause non-uniform symbol discontinuities of point, line, and area features. It not only affects visualization effect, but also leads to spatial cognitive errors. Methods: On the premise of independence coordinate data and symbol style of vector tile, a schema combining preprocessing and real-time rendering is proposed to solve these problems. By analyzing the types and causes of discontinuity of different feature is symbols at the grid boundary, drawing auxiliary information for different types of symbols is extracted, which is used to adjust initial position of symbol unit in the tile and to realize the continuous representation of symbols. Results: A prototype system based on this scheme was developed and a large scale map mapping experiment was performed. Experimental results show that the proposed method can solve the problem of symbol discontinuity at the grid boundary. Conclusions: The proposed method can meet the needs of vector tile production and drawing in terms of reusability and efficiency. [ABSTRACT FROM AUTHOR]

When calculating similarity, the existing differential privacy recommendation algorithms directly calculate based on user-scheme data, but ignore the influence of scheme attributes on user preferences, fail to reflect the real preferences of users, and cannot make accurate recommendations. To solve this problem, this paper proposed differential privacy recommendation method considering user interest analysis. In this method, it collected firstly users' interest ratings for scheme attributes, and secondly clustered the user-scheme attributes rating data by K-means + +. Then, it used the differential privacy algorithm to select the nearest users, and recommended suitable schemes for the target user. Finally, taking the recommendation of nursing home schemes as an example, the experimental results show that compared with KDPC, DPCF and PNCF, the proposed algorithm can reduce the mean absolute error by about 19. 0%, 34. 0% and 37. 7% under the same privacy budget. The mean absolute error decreases by 10. 4%, 20. 3 % and 21. 4 % for the same size of the nearest neighbor set. Therefore, based on protecting the privacy of users, the algorithm further improves the recommendation accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Natural Gas Geoscience is the property of Natural Gas Geoscience and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Dynamic configuration technology provides users a non-stop, flexible and convenient way of service configuration, while it can bring a potential of misconfigurations and lead to system crashes and decline of service quality. To solve the problem, a dynamic configuration verification method of distributed framework was proposed based on finite state machine. The data type validation was achieved by data type conversion, which took advantage of the logic of finite state automation (FSA). The distributed framework configuration validation was implemented based on the dynamic configuration of Spring Cloud. To avoid unnecessary file reading and writing, Java compiler was improved to load the dynamically compiled bytecode in memory. The proposed configuration verification method was tested with the cases of misconfigurations of primitive and wrapped data types based on Spring Cloud config framework. The results show that the method can detect and process errors of data overflow, container unclosed, container nested error and mismatch of data type of primitive types and containers decoupling code by FSA, and it provides clear logic to the properties of configuration verification and reference for the configuration management of cloud framework. [ABSTRACT FROM AUTHOR]

Copyright of Natural Gas Geoscience is the property of Natural Gas Geoscience and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Wool Textile Journal is the property of National Wool Textile Science & Technology Information Center and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Harbin University of Science & Technology is the property of Journal of Harbin University of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

When there exist mixed contaminations in face images, traditional low-rank recovery algorithms usually imposes only one constraint on the corresponding contaminations, it cannot recover clean samples very well. In order to solve this problem, this paper proposed a structured robust low-rank recovery algorithm ( SRLRR) . The SRLRR algorithm imposed low-rank constraint on the 2D error image to remove the continuous contamination, and introduced sparse constraint to separate the noise that obeyed the Laplacian distribution in samples. Moreover, the proposed algorithm imposed a block-diagonal structured constraint on the representation coefficient to learn the more discriminative low-rank representation. The experimental results on three commonly and using standard databases verify the effectiveness and robustness of the proposed SRLRR algorithm. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Jilin University (Science Edition) / Jilin Daxue Xuebao (Lixue Ban) is the property of Zhongguo Xue shu qi Kan (Guang Pan Ban) Dian zi Za zhi She and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper proposed an improved residual network (ResNet) expression recognition algorithm. The algorithm used small convolution kernels and a deep network structure to solve the problem of accuracy reduction with the increase of depth by the residual module. The experiment overcame the shortcoming of insufficient data through transfer learning, which could effectively prevent overfitting. The network architecture used a linear SVM for classification. The experiment used the ImageNet database to pre-train network parameters to have an excellent ability to extract feature. According to transfer learning, the algorithm used the FER-2013 database and the expanded CK + database to fine-tune and train network parameters, and overcame the problem that shallow networks rely on manual features and deep networks were difficult to train. The results show the recognition rates is 91.333% and 95.775% on the CK + database and the GENKI-4K database,respectively. The classification accuracy of SVM in CK + database is about 1% higher than that of softmax. [ABSTRACT FROM AUTHOR]

In order to ensure the load balance of network storage and to avoid unrecoverable loss in case of node or disk failures, this paper proposed a distributed storage and coding scheme based on balanced data placement strategy, which gave different solutions for large caches and small caches . Firstly, it extended the Maddah scheme to multi-server system, and stored each file as a unit in the data server by combining balanced data placement strategy to solve the large-scale cache problem. Then, it extended the interference cancellation scheme to the multi-server system. It used the interference cancellation scheme to reduce the peak rate of the cache, and proposed the linear combination of cache segments by combining balanced data placement strategy so as to solving the problem of small caching . Finally,it carried out simulation experiments in one and two parity check server systems respectively through Linux-based NS2 simulation software. The simulation results show that the proposed scheme can effectively reduce the peak transmission rate. It achieves better performance comparing with the other two new caching schemes . In addition, although distributed storage limits the ability to combine content from different servers into a single message, resulting in performance loss of coding and caching schemes, it can make full use of the inherent redundancy in distributed storage systems, thereby improving the performance of storage systems. [ABSTRACT FROM AUTHOR]

Aiming at solving the problem of big data's large scale and complex computation, this paper adopted the idea of two-stage progressive clustering, and proposed a parallel computation algorithm for big data clustering based on MapReduce. In the first stage, this method acquired the initialized clustering center through Canopy algorithm, in order to find relatively accurate cluster center points quickly. In the second stage, it presented a novel scheme of parallel computation based on Map Reduce framework, which maked each data node cluster or merge around its adjacent Canopy center node. In this way, the algorithm could make the procedure of data clustering fast and accurately. The results of the experiments deployed on MapReduce show that this algorithm can effectively improve the efficiency of parallel computing, reduce computing time, and improve big data's clustering accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Liquid Crystal & Displays is the property of Chinese Journal of Liquid Crystal & Displays and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Basic Sciences Journal of Textile Universities / Fangzhi Gaoxiao Jichu Kexue Xuebao is the property of Basic Sciences Journal of Textile Universities and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)