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	1. Research on Video Distribution Strategy and Path Optimization for QoE Perception
	RONG Hui-Gui,ZHANG Na
	Computer Science and Technology 26 March 2019
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	Abstract:With the rapid development of the Internet, the continuous upgrading of the network infrastructure, a large amount of online video, making the Internet bear more and more pressure. Compared with the traditional network architecture, the Content Delivery Network (CDN) can improve the utilization of network bandwidth resources, especially the network bandwidth resources of the Backbone Network, improve the quality of network transmission, and can effectively reduce the load of the source server and improve the user\'s Quality of Experience (QoE). In this paper, we make QoE model improvements based on videos of interest to users, and propose a video distribution strategy for improved QoE model. Finally, the path of the distribution strategy is further optimized. We used the CDNsim simulation system to perform simulation experiments and verify the performance of the distribution strategy. The experimental results show that the video distribution strategy proposed in this paper has low response time and high hit rate, which makes QoE higher.
	TO cite this article:RONG Hui-Gui,ZHANG Na. Research on Video Distribution Strategy and Path Optimization for QoE Perception[OL].[26 March 2019] http://en.paper.edu.cn/en_releasepaper/content/4747933


	2. Research on Cache Strategy of Edge Image Based on Popularity Prediction
	ZOU Sheng,LIU Liang
	Computer Science and Technology 25 March 2019
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	Abstract:With the advent of the era of Internet of Everything, the edge computing used to make up for the lack of cloud computing comes into being. However, due to the light-weighting of edge clouds in edge computing, the problem of limited resources is caused, especially in terms of storage resources. At the same time, considering the problem that there are a lot of redundant images in the virtual machine or the container, this paper solves the problem of insufficient storage resources from the perspective of optimizing the edge image cache. To this end, this paper chooses Kubernetes as the edge platform, and uses the value of Baidu index as the popularity value, and proposes an edge image cache algorithm based on popularity prediction, namely b-GRU. Firstly, based on the feature analysis of the acquired data, the prediction of the image popularity based on GRU is performed. Then, the image cache replacement based on the popularity prediction is performed. Finally, the comparison experiment of b-GRU shows that the storage space of b-GRU is only 41% of LRU and LFU storage space under the condition of guaranteeing a certain cache hit ratio, which proves the effectiveness of this strategy.
	TO cite this article:ZOU Sheng,LIU Liang. Research on Cache Strategy of Edge Image Based on Popularity Prediction[OL].[25 March 2019] http://en.paper.edu.cn/en_releasepaper/content/4748074

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	3. InFun: A method to detect overlapping gene communities by integrating gene expression and protein-protein interaction data
	MIAO Qiumai,LU Xinguo
	Computer Science and Technology 14 March 2019
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	Abstract:The analysis of the gene expression data has great significance for clinical treatment, cancer diagnosis and other fields. Module network inference is an effective and established method to analyze the gene expression data. We hypothesized that exploring and analyzing the interaction between modules or no relationship modules will further improve our understanding of cancer mechanism. To this end, we proposed a novel method, InFun, for reconstruction different module networks. Our method applies two-ways clustering which contains Bayesian approach and overlapping community method to detect gene communities by integrating gene expression data and protein-protein interaction data. On the basis of The Cancer Genome Atlas (TCGA) breast cancer data, we observe that the InFun can recognize module networks which are significantly more enriched in the known pathways than another method like Lemon-Tree. These gene communities can serve as bio-markers to estimate the survival time of patients which is critical for cancer therapy. Discovery single function communities can predict breast cancer subtype by using different feature sets, and multiple function communities can communicate with other community which can be used to explain cancer processes. InFun brings new sight for understanding cancer machanism and novel technique for clustering gene expression data.
	TO cite this article:MIAO Qiumai,LU Xinguo. InFun: A method to detect overlapping gene communities by integrating gene expression and protein-protein interaction data[OL].[14 March 2019] http://en.paper.edu.cn/en_releasepaper/content/4747845


	4. A GDSF-M Cache Replacement Algorithm Based on Enterprise Reporting System
	LIANG Yuwei,XU Tong,ZHANG Lei,ZHANG Lejian
	Computer Science and Technology 14 December 2018
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	Abstract:Enterprise-level reporting systems play a key role in the operation of E-business platforms.The enterprise business reporting system is characterized by large amount of data and regular operation. The core of the cache replacement strategy of the Web proxy server is the cache replacement algorithm, which can effectively improve the performance of the proxy server. In this paper we implement a business reporting system and study the traditional web cache replacement algorithm. Based on the GDSF algorithm, an improved GDSF-M algorithm is proposed, which considers the cache size. Factor, a report type weight function is added to the target value function to apply to the current application scenario. Finally, the performance of GDSF-M algorithm is verified by Squid proxy server. Compared with LRU, LFU and GDSF algorithm, it is proved that the improved GDSF-M algorithm has better improvement in hit rate and byte hit ratio. At the same time, the hit rate in the current scene has better stability than other algorithms.
	TO cite this article:LIANG Yuwei,XU Tong,ZHANG Lei, et al. A GDSF-M Cache Replacement Algorithm Based on Enterprise Reporting System[OL].[14 December 2018] http://en.paper.edu.cn/en_releasepaper/content/4746709


	5. Integrating Ecological Effects Assessment and Scenario-Based Simulation to Optimize Spatial Management Decisions: a Case Study of Three Gorges Reservoir Area
	LIU Minghao,FENG Yuan,YUAN Min,LI Yuting
	Computer Science and Technology 14 May 2018
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	Abstract:It is of great significance to promote the sustainable development of land by revealing the spatial temporal evolution law of land use and land cover change (LUCC), and identifying the ecological security. Three different development scenarios (low speed development, inertia development, rapid development) of the Three Gorges Reservoir Area（TGR）are designed based on the dynamic change model of urban and rural land use by using DYNA-CLUE software to simulate the spatial distribution pattern of land use in TGR, along with the human affect index (HAI), ecological risk index (ERI) and ecosystem service value (ESV) are used to assess the ecological effects of the different development scenarios. Results shows that, (1) the ROC test values of the logistic regression model between driving factors and grassland, cultivated land, shrub land, forest land, wetland, water body and artificial surface respectively were 0.61, 0.647, 0.819, 0.987, 0.777, 0.935, 0.927; (2) the land use distribution was simulated from 2000 to 2010, and the model validation shows that the total kappa reaches 79%, comparing the simulation results with the land use status in 2010;（3）From the ecological effect evaluation, the scenarioⅠis the best, the scenarioⅡ is the worst, and the scenario III is between the scenarioⅠand the scenarioⅡ;（4）from the perspective of time , ecological risk presents a gradual shift trend of from low to medium and high risk with the passage of time; from the perspective of space, relatively strong ecological risk areas are mainly concentrated in the riparian zone along the Yangtze River west of Wanzhou, while the extremely strong ecological risk area are mainly concentrated in the urbanized area of Chongqing metropolitan area.
	TO cite this article:LIU Minghao,FENG Yuan,YUAN Min, et al. Integrating Ecological Effects Assessment and Scenario-Based Simulation to Optimize Spatial Management Decisions: a Case Study of Three Gorges Reservoir Area[OL].[14 May 2018] http://en.paper.edu.cn/en_releasepaper/content/4744748


	6. The registration algorithm of nonlinear scale and improved ORB
	Dong Hao,Lv Dongyue
	Computer Science and Technology 04 January 2018
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	Abstract:ORB algorithm doesn`t perform well in scale invariance and SIFT algorithm with high time complexity does not respect the natural boundaries of images. Aiming at the issue, we put forward an image registration algorithm based on the nonlinear scale space and improved the ORB. Firstly, the nonlinear scale space is used to smooth noise and retain object boundaries, to set scale parameters based on image entropy and to set proper distance between feature points, so that the ORB detectors are stable. Then, maxima is searched for in scale and spatial location and descriptors are computed. At last, we match features with RANSAC algorithm and hamming distance. We testify our improved algorithm through experiments and demonstrate that it can shorten time of registration, improve greatly robustness and perform well.
	TO cite this article:Dong Hao,Lv Dongyue. The registration algorithm of nonlinear scale and improved ORB[OL].[ 4 January 2018] http://en.paper.edu.cn/en_releasepaper/content/4743035


	7. Edge-preserving Smoothing based on Guided Image Filter of Video Streams
	Zhou Zhi,Qi Qi
	Computer Science and Technology 17 December 2017
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	Abstract:In this paper, a real-time edge preserving smoothing algorithm based on video stream-oriented image filtering is proposed, which can reduce the inconsistent results caused by frame-by-frame processing. The algorithm uses the characteristics of the video stream to introduce the time component to obtain more consistent and smooth results. Compared with the method of using image filter frame by frame, this method considers the inter-frame relationship, which can bring the advantage of time coherency. Compared with the omniscient method, this method does not need to use the future Data, it can be used for video streaming, reducing the occupation of computing resources to ensure the real-time processing.
	TO cite this article:Zhou Zhi,Qi Qi. Edge-preserving Smoothing based on Guided Image Filter of Video Streams[OL].[17 December 2017] http://en.paper.edu.cn/en_releasepaper/content/4742755


	8. A Novel q-Weighted Hybrid Machine Learning Technique in Chinese P2P Lending Sector
	SONG Mei-Na,JIA Mi-Mi,LIU Shao-Jie,E Hai-Hong, OU Zhong-Hong
	Computer Science and Technology 08 December 2017
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	Abstract:We often encounter imbalanced data in credit risk when there is an unequal representation in the classification categories.In order to provide loan company with a simple and novel approach to get the customer's credit prediction result. An analytic model for machine to learn from data ,then it can be able to do predictive analysis. Here, a machine learning model is needed to build to help the P2P lending sector which sometimes faced with risk challenge when advancing loans to customers. Obviously, the accuracy of the model plays a very important role when the loan companies make decision. The accuracy can be improved by many factors, some of these the use of better machine learning model and balanced data. In this work, we formulate a novel q-weighted hybrid model to gain performance improvement and to solve the problem of imbalanced data and missing value. The machine learning and statistical techniques can be combined in various ways for creating the effective hybrid models. Many Support Vector Machine(SVM) mod- els are combined by a q-weighted hybrid method, and the training sets used to construct the SVM model contained only selected attributes and were composed only of the complete examples. The final classification is made by the test statistic which is sequentially obtained from models. The test statistic are compared with two thresholds to get decision in the majority voting process. The results of the single and hybrid models shows that the proposed hybrid method had the best result.
	TO cite this article:SONG Mei-Na,JIA Mi-Mi,LIU Shao-Jie, et al. A Novel q-Weighted Hybrid Machine Learning Technique in Chinese P2P Lending Sector[OL].[ 8 December 2017] http://en.paper.edu.cn/en_releasepaper/content/4742659


	9. Application of density-based sine cosine algorithm in soil moisture interpolation model
	Li Gang,Li Ning,Chen Yuanzhi
	Computer Science and Technology 05 December 2017
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	Abstract:Focused on the issue that sine cosine algorithm is easy to fall into local optimum in complex optimization problems, a density-based sine cosine algorithm was proposed. The algorithm combines the density information around the individual. In iterative process, individuals with higher density are far away from the center of density, making the algorithm not overcrowded during the exploration period, which enhances the local optimal avoidance ability of the algorithm. The standard function was used to test the performance of the algorithm, and the algorithm was applied to optimize the ordinary kriging interpolation model. The experimental data was from Changge, Henan Province. The results showed that the proposed algorithm had good convergence speed, better local optimal avoidance ability and better performance in optimizing soil moisture interpolation model .
	TO cite this article:Li Gang,Li Ning,Chen Yuanzhi. Application of density-based sine cosine algorithm in soil moisture interpolation model[OL].[ 5 December 2017] http://en.paper.edu.cn/en_releasepaper/content/4742360


	10. Optimizing Sliding Performance in iOS
	Zhao Qin,Wang Jing,Shen Qi Wei,Wang Jing Yu,Qi Qi
	Computer Science and Technology 23 November 2017
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	Abstract:How to improve iOS sliding performance has always been the focus of iOS application optimization. This paper analyzes the principle of AutoLayout and Frame view layout, the opportunity of network loading, CPU and GPU performance consumption during sliding process. First, we provide the appropriate solution to avoid using AutoLayout, and adjust the time of network loading by preloading to reduce the waiting time dynamically. Pre-cache and asynchronous rendering to reduce the main thread CPU consumption is implemented to reduce the main thread CPU consumption, and at the same time, GPU consumption is reduced by asynchronous rendering. Finally, verify the feasibility and effectiveness of the optimization scheme by experiments. It is verified that the percentage of the main thread CPU consumption decreases by 17.2% and FPS increases from 37Hz to 60Hz.
	TO cite this article:Zhao Qin,Wang Jing,Shen Qi Wei, et al. Optimizing Sliding Performance in iOS[OL].[23 November 2017] http://en.paper.edu.cn/en_releasepaper/content/4742034

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