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Copyright of Jordanian Journal of Computers & Information Technology is the property of Jordanian Journal of Computers & Information 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.)

Aspect-based sentiment analysis is a fine-grained sentiment analysis task, which aims to align aspects with the corresponding emotion words for aspect specific emotion polarity reasoning. In recent years, the graph neural network sentiment classification method based on syntactic dependent information has become a research hotspot in this field. However, due to the flexibility of comment sentences in content expression and syntactic structure, the modeling method using only syntactic dependent information still has some shortcomings. In order to enhance the comment sentences by affective knowledge and structural semantic information, a convolutional network model(DualSyn-GCN) of two channel knowledge enhancement graph is proposed. On one hand, the syntactic dependency adjacency matrix is enhanced according to the implicit relationship between aspect and aspect as well as aspect and context. On the other hand, the emotional dependency of aspect is learned from external emotional knowledge, and then the two different enhanced representations are fused to realize the sharing and complementarity between different representations. The experimental results show that, compared with the classical aspect based graph convolutional network model (ASGCN), this model improves the accuracy and MF1 value on LAP14 data set by 2.34% and 3.26% respectively. [ABSTRACT FROM AUTHOR]

In order to improve the detection accuracy of event-related potential (ERP) in subject-independent scenarios, a convolutional recurrent neural network model based on graph embedding and dual attention mechanisms is proposed. The model uses a graph to represent the spatial information in electroencephalogram (EEG) signals, and uses the cascade framework of convolutional neural network (CNN) and long short-term memory network (LSTM) as the basic framework. By embedding dual attention mechanisms (i.e., selective kernel convolution and self-attention mechanism), it can fully extract the temporal and spatial features of EEG signals of different subjects, so as to improve the ERP detection accuracy in subject-independent scenarios. A large number of experiments carried out on the benchmark dataset based on rapid serial visual presentation paradigm demonstrate that the proposed method has significant superiority over 7 existing ERP detection methods in subject-independent scenarios. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Data Acquisition & Processing / Shu Ju Cai Ji Yu Chu Li is the property of Editorial Department of Journal of Nanjing University of Aeronautics & Astronautics 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 Guangxi Normal University - Natural Science Edition is the property of Gai Kan Bian Wei Hui 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 Henan University of Science & Technology, Natural Science is the property of Editorial Office of Journal of Henan 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.)

Ａｉｍｉｎｇ ａｔ ｔｈｅ ｐｒｏｂｌｅｍ ｏｆ ｐａｔｈ ｐｌａｎｎｉｎｇ ｉｎ ｒｏｌｌｅｒ ｃｏｎｖｅｙｉｎｇ ｌｉｎｅ ｓｙｓｔｅｍꎬ ｔｈｅ ｅｎｖｉｒｏｎｍｅｎｔ ｍｏｄｅｌ ｏｆ ｃｏｎｖｅｙｏｒ ｌｉｎｅꎬ ｐａｔｈ ｐｌａｎｎｉｎｇ ａｌ￣ ｇｏｒｉｔｈｍ ａｎｄ ｏｐｔｉｍｉｚａｔｉｏｎ ｗｅｒｅ ｒｅｓｅａｒｃｈｅｄ. Ｂｙ ｅｘｔｒａｃｔｉｎｇ ｔｈｅ ｅｎｔｒａｎｃｅꎬ ｅｘｉｔꎬ ａｎｄ ｔｒａｎｓｆｅｒ ｏｆ ｔｈｅ ｔｈｒｅｅ ｍｏｄｕｌｅｓ ａｓ ｔｈｅ ｎｏｄｅ ａｎｄ ｔａｋｉｎｇ ｔｈｅ ｄｅ￣ ｌｉｖｅｒｙ ｒｏｕｔｅｓ ｂｅｔｗｅｅｎ ｔｈｅ ｎｏｄｅｓ ａｓ ｔｈｅ ｗｅｉｇｈｔｅｄ ｒｏｕｔｅｓꎬ ａ ｍｅｔｈｏｄ ｏｆ ｃａｌｃｕｌａｔｉｎｇ ｔｈｅ ｌｅｎｇｔｈ ｏｆ ｔｈｅ ｌｉｎｋｓ ｂｅｔｗｅｅｎ ｔｈｅ ｎｏｄｅｓ ｂｙ ｔｈｅ ｃｏｎｖｅｙｏｒｓ ｅ￣ ｑｕｉｖａｌｅｎｔ ｗａｓ ｐｒｏｐｏｓｅｄꎬ ｔｈｅｎ ａ ｓｔｒｅａｍｌｉｎｅｄ ｇｒａｐｈ ｓｔｒｕｃｔｕｒｅ ｍｏｄｅｌ ｗａｓ ｂｕｉｌｔ. Ｂｙ ｕｓｉｎｇ Ｄｉｊｋｓｔｒａ ａｌｇｏｒｉｔｈｍ ａｎｄ ｉｍｐｒｏｖｅｄ ａｎｔ ｃｏｌｏｎｙ ａｌｇｏｒｉｔｈｍ ｔｏ ｓｏｌｖｅ ｔｈｅ ｓｍａｌｌ￣ｓｃａｌｅ ａｎｄ ｌａｒｇｅ￣ｓｃａｌｅ ｐａｔｈ ｐｌａｎｎｉｎｇ ｐｒｏｂｌｅｍｓ ｒｅｓｐｅｃｔｉｖｅｌｙꎬ ａｎｄ ａｃｃｏｒｄｉｎｇ ｔｏ ｔｈｅ ｔｗｏ ｃｏｎｓｔｒａｉｎｔ ｃａｓｅｓ ａｂｏｕｔ ｔｈｅ ｎｅｃｅｓｓａｒｙ ｐａｓｓ￣ ｉｎｇ ｎｏｄｅｓ ａｎｄ ｔｈｅ ｃｏｎｇｅｓｔｉｏｎ ｒｏａｄ ｓｅｃｔｉｏｎｓ ｉｎ ｔｈｅ ａｐｐｌｉｅｄ ｔｒａｎｓｍｉｓｓｉｏｎ ｌｉｎｅꎬ ｔｈｅ ｐａｔｈ ｐｌａｎｎｉｎｇ ａｌｇｏｒｉｔｈｍ ｏｆ ｔｒａｎｓｍｉｓｓｉｏｎ ｌｉｎｅ ｗｈｉｃｈ ｃｏｍｂｉｎｅｓ Ｄｉｊｋｓｔｒａ ａｌｇｏｒｉｔｈｍ ａｎｄ ｉｍｐｒｏｖｅｄ ａｎｔ ｃｏｌｏｎｙ ａｌｇｏｒｉｔｈｍ ｗａｓ ｐｒｏｐｏｓｅｄꎬ ｗｈｉｃｈ ｔｗｏ ｍｅｔｈｏｄｓ ｗｅｒｅ ｂｌｅｎｔ ｗｉｔｈ ｓｅｇｍｅｎｔｅｄ ｓｐｌｉｃｉｎｇ ａｎｄ ｐａｔｈ ｌｅｎｇｔｈ ｗｅｉｇｈｔｉｎｇ. Ｔｈｅ ｒｅｓｕｌｔｓ ｉｎｄｉｃａｔｅ ｔｈａｔ ｔｈｅ ｍｅｔｈｏｄ ｐｒｏｖｉｄｅｓ ａｎ ｅｆｆｅｃｔｉｖｅ ｓｏｌｕｔｉｏｎ ｔｏ ｔｈｅ ｐａｔｈ ｐｌａｎｎｉｎｇ ｏｆ ｒｏｌｌｅｒ ｃｏｎｖｅｙｉｎｇ ｌｉｎｅ ｗｉｔｈ ｄｉｆｆｅｒｅｎｔ ｓｃａｌｅｓ ｕｎｄｅｒ ｔｗｏ ｋｉｎｄｓ ｏｆ ｃｏｎｓｔｒａｉｎｔｓ. [ABSTRACT FROM AUTHOR]

The basic theory of producing cylindricity error graph was studied， and a mathematical model for visualization of cylindricity error was established. The theory of computer graphics and three-dimensional wireframe models were used to realize the display of extracted integral feature， associated integral feature and associated derived feature of the measured cylinders. Axonometric projection transformation was adopted to fulfill the realization of basic geometric shapes. The space hidden method was used to solve the problem of geometrical graph hidden. According to the standard definition of cylindricity error， the mathematical model for cylindricity error graphic display was established. On the basis of theoretical study， software was developed to realize visualization of cylindricity error on the platform of LabWindows/CVI. [ABSTRACT FROM AUTHOR]

An equitable edge coloring of graph G is that adjacent edges of a graph have different color and the sizes of its color classes differ by at most 1. The minimum number of colors is called the equitable edge chromatic number. This paper proposed a new heuristic intelligent algorithm with the study of minimum equitable edge chromatic number. According to the conditions of edge coloring, it created object function, exchanged the color complement matrix of coloring matrix iteratively to find the optimum solution. It gave detailed algorithm, with lots of testing and analysis cases.For a graph with fixed number of vertices, this algorithm can find the minimum equitable edge chromatic number efficiently, while the time complexity of this algorithm is less than O(n3). [ABSTRACT FROM AUTHOR]

Copyright of Transactions of Beijing Institute of Technology is the property of Beijing 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.)

Node pair sampling in social networks is useful for friend recommendation and interest targeting. While the topology of the whole network is incomplete, or the cost of random generation of a user is very large, the performances of traditional uniform vertex sampling methods decrease quickly. So, this paper proposed a random walk based node pair sampling algorithm in large graph. Firstly, it analyzed systematically the problem of node pair sampling in social networks, and gave definitions of node pair in different hops. Secondly, it transformed the social network into an equivalent graph, whose nodes were edges in original graph, and whose edges contained two node having the same vertex. Finally, it applied random walk on the new graph and proposed a neighbor random walk sampling algorithm. The experiments show that, the proposed algorithm has less error, better performance, and is obviously better than uniform vertex sampling related methods. [ABSTRACT FROM AUTHOR]

Hyperlink induced topic search (HITS) is one of the most authoritative and widely used personalized ranking algorithm on graphs. The HITS algorithm ranks nodes on graphs according to power iteration, and has high complexity of computation. In order to improve computation time, this paper analyzed and modeled the HITS algorithm with the random walls approach, and proposed Monte Carlo based approximation computation algorithms for the HITS ranking. Theoretical analysis and experiments show that the proposed random walk based approach of HITS ranking is not only efficient, but also has higher accuracy, and is significantly better than related works. [ABSTRACT FROM AUTHOR]

To solve the problem that the spectrum allocation algorithm based on graph theory coloring algorithm has not fully considered the actual bandwidth needs of users, this paper proposes a spectrum allocation based on user priority algorithm improved CSGC and the original algorithm. The algorithm introduces two time factors that are respectively called idle spectrum and user demand, by setting the user priority, the function can meet the needs of users during the second spectrum allocation. Simulation results show that the algorithm not only retains the performance of the original algorithm CSGC, but also greatly improves the spectrum utilization. [ABSTRACT FROM AUTHOR]

Superpixel can capture redundancy of the image and reduce the complexity of subsequent processing tasks. These advantages make it receive more and more attentions from researchers at home and abroad. This paper first analyzed the development of the superpixel segmentation, and summarized the state-of-the-art superpixel segmentation algorithms in the view of graph-based and gradient-ascent-based methods. Then, it compared several superpixel segmentation algorithms by experiments, and illustrated their strengths and weaknesses respectively. At last, it introduced the latest applications of superpixel segmentation techniques with prospects. [ABSTRACT FROM AUTHOR]

In order to improve the effectiveness and efficiency of near-duplicate video detection, this paper proposed the graph-based video subsequence matching algorithm. The algorithm constructed a matching results graph from the similarity search results based on the key frame features, and then converted the problem of near-duplicate video detection into the problem of finding the longest path in the matching results graph. The method has three main advantages: a) Graph-based method could find the best matching sequence in many messy match results, which effectively excluded false "high similarity" noise and compensated the limited description of image low level visual features. b)The graph-based method took fully into account the spatiotemporal characteristic of video sequence, and had high location accuracy. c)The graph-based sequence matching method could automatically detect the discrete paths in the matching result graph. Thus, it could detect more than one near-duplicate video. The proposed algorithm not only improves the detection accuracy, but improves the efficiency of detection, achieves good practical effect. [ABSTRACT FROM AUTHOR]

The Box dimension of a class of Weierstrass function ... is discussed. Under the help of the λ-ary expansions, the Box dimension of Γ(f) is 2 when the sequence satisfies ..., where 1<λ is an integer and {an} is a summable sequence with positive terms. [ABSTRACT FROM AUTHOR]

Garey and Johxon have proved that the problem to determine the crossing number of graphs is NP-complete. Because of its difficulty, we only know the crossing number of some classes of special graphs. The crossing number of Cartesian products of paths and cycles with 5-vertex graphs are mostly known, but only few cartesian products of 5-vertex graphs with star K1, n are known. In this paper, we extend these results, and determine the crossing numbers of Cartesian products of two 5-vertex graphs with star K1, n. [ABSTRACT FROM AUTHOR]