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Authors: Hou, Jingyu

Article Type: Research Article

Abstract: The rapid development of network technologies has made the web a huge information source with its own characteristics. In most cases, traditional database-based technologies are no longer suitable for web information processing and management. For effectively processing and managing web information, it is necessary to reveal intrinsic relationships/structures among concerned web information objects such as web pages. In this work, a set of web pages that have their intrinsic relationships is called a web page community. This paper proposes a matrix-based model to describe relationships among concerned web pages. Based on this model, intrinsic relationships among pages could be revealed, …and in turn a web page community could be constructed. The issues that are related to the application of the model are deeply investigated and studied. The concepts of community and intrinsic relationships, as well as the proposed matrix-based model, are then extended to other application areas such as biological data processing. Some application cases of the model in a broad range of areas are presented, demonstrating the potentials of this matrix-based model. Show more

Keywords: web page community, matrix model, hyperlink analysis, bioinformatics

Citation: Informatica, vol. 18, no. 2, pp. 217-238, 2007

Authors: Majbouri Yazdi, Kasra | Majbouri Yazdi, Adel | Khodayi, Saeid | Hou, Jingyu | Zhou, Wanlei | Saedy, Saeed | Rostami, Mehrdad

Article Type: Research Article

Abstract: One of the most important challenges of social networks is to predict information diffusion paths. Studying and modeling the propagation routes is important in optimizing social network-based platforms. In this paper, a new method is proposed to increase the prediction accuracy of diffusion paths using the integration of the ant colony and densest subgraph algorithms. The proposed method consists of 3 steps; clustering nodes, creating propagation paths based on ant colony algorithm and predicting information diffusion on the created paths. The densest subgraph algorithm creates a subset of maximum independent nodes as clusters from the input graph. It also determines …the centers of clusters. When clusters are identified, the final information diffusion paths are predicted using the ant colony algorithm in the network. After the implementation of the proposed method, 4 real social network datasets were used to evaluate the performance. The evaluation results of all methods showed a better outcome for our method. Show more

Keywords: Diffusion paths prediction, information diffusion patterns, densest subgraphs, ant colony algorithm, centrality

DOI: 10.3233/JHS-200635

Citation: Journal of High Speed Networks, vol. 26, no. 2, pp. 141-153, 2020

Authors: Sajjanhar, Atul | Lu, Guojun | Zhang, Dengsheng | Hou, Jingyu | Zhou, Wanlei | Chen, Yi-Ping Phoebe

Article Type: Research Article

Abstract: In this paper, we propose a spectral descriptor for shapes of objects. The method relies on transforming the 2D objects into 3D space; distance transform and scale space theory is used to transform objects into 3D space. Spherical harmonics of the voxel grid are used to obtain shape descriptors. The proposed methods are compared against two existing methods which use spherical harmonics for shape based retrieval of images. Comparison is done based on ranking of images which is articulated in recall-precision curves. MPEG-7 Still Images Content Set is used for performing experiments. Experimental results show that the performance of the …proposed descriptor is significantly better than other methods in the same category. Show more

Keywords: CBIR, feature extraction, shape representation

DOI: 10.3233/ICA-2010-0335

Citation: Integrated Computer-Aided Engineering, vol. 17, no. 2, pp. 167-173, 2010

Authors: Yao, Weitao | Hou, Jingyu | Liu, Guoqing | Wu, Fangxing | Yan, Qiang | Guo, Liangyu | Wang, Chuchu

Article Type: Research Article

Abstract: BACKGROUND: LncRNA STK4 antisense RNA 1 (STK4-AS1) has been identified as a potential biomarker associated with multiple cancers. We proposed that STK4-AS1 plays a role in the proliferation of osteosarcoma by regulating the cell cycle. METHODS: We compared the expression of STK4-AS1, p53, and p21 in osteosarcoma vs normal samples in clinical tissues and cell lines. We determined the effect of overexpression and knockdown of STK4-AS1 in p53 expressing osteosarcoma cells U2OS, p53 muted osteosarcoma cells MG63, and osteoblast cells hFOB on p53 and p21 expression and the cell viability. For U2OS and MG63, the cell cycle was analyzed and …the expression of cyclin proteins was determined. We overexpressed p53 or p21 in STK4-AS1 overexpressed cells to explore the association of STK4-AS1 and p53 in U2OS. RESULTS: The STK4-AS1 expression was higher and p53 and p21 expression were lower in osteosarcoma tissue and cells than in their non-cancer counterparts. The expression of STK4-AS1 was negatively correlated with the expression of p53 or p21. Knockdown of STK4-AS1 in U2OS decreased the cell viability, increased cells in the G0/G1 phase, decreased cells in the S and G2/M phase, decreased expression of cyclin A and B, increased p53 and p21, and had no effect on cyclin D and cyclin E, while overexpression of STK4-AS1 did the opposes. Overexpression of p53 or p21 recovered some changes caused by STK4-AS1 overexpression in U2OS. MG63 expressed no p53 and the expression of p21, cyclin A, and cyclin B, cell viability, and cell cycle were not affected by altered STK4-AS1 levels. In hFOB cells, the expression of p53 and p21 was decreased and the cell viability was increased when STK4-AS1 was overexpressed, but they were not affected when STK4-AS1 was knocked down. CONCLUSION: LncRNA STK4-AS1 promoted the cell cycle of osteosarcoma cells by inhibiting p53 expression. Show more

Keywords: STK4-AS1, osteosarcoma, cell cycle, p53 protein

DOI: 10.3233/CBM-210291

Citation: Cancer Biomarkers, vol. 36, no. 1, pp. 1-16, 2023

Authors: Majbouri Yazdi, Kasra | Hou, Jingyu | Khodayi, Saeid | Majbouri Yazdi, Adel | Saedi, Saeed | Zhou, Wanlei

Article Type: Research Article

Abstract: With the rapid development of social networks, studying and analyzing their structures and behaviors has become one of the most important requirements of businesses. Social network analysis can be used for many different purposes such as product ads, market orientation detection, influential members detection, predicting user behaviors, recommender systems improvements, etc. One of the newest research topics in social network analysis is the enhancement of the information propagation performance in different aspects based on application. In this paper, a new method is proposed to improve few metrics such as distribution time and precision on social networks. In this method, the …local attributes of nodes and also the structural information of the network is used to forward data across the network and reduce the propagation time. First of all, the centrality and Assortativity are calculated for all nodes separately to select two sets of nodes with the highest values for both criteria. Then, the initial active nodes of the network are selected by calculating the intersection of the two sets. Next, the distribution paths are detected based on the initial active nodes to calculate the propagation time. The performance analysis results show that the proposed method has better outcomes in comparison to other state-of-the-art methods in terms of distribution time, precision, recall, and AUPR criteria. Show more

Keywords: Information propagation time, node assortativity, VoteRank centrality, data forwarding, influential nodes detection

DOI: 10.3233/JHS-220695

Citation: Journal of High Speed Networks, vol. 28, no. 4, pp. 275-285, 2022