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2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)最新文献

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A Strategy of Reusing Mode Selection for Device to Device Communication 一种设备间通信复用模式选择策略
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8686885
Ping Zeng, Xiaobin Li
{"title":"A Strategy of Reusing Mode Selection for Device to Device Communication","authors":"Ping Zeng, Xiaobin Li","doi":"10.1109/FSKD.2018.8686885","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8686885","url":null,"abstract":"Interference coordination is the focus for Device-to-Device (D2D)communication. Due to the fact that many works adopt single reusing mode for coordinating interference in D2D communication systems and the efficiency of spectrum is low, a strategy of reusing mode selection is proposed. The aim is let D2D pairs can flexibly select the most suitable reusing mode between one-to-one and multiple-to-one reusing mode according to the signal to interference plus noise power ratio (SINR)performance of D2D pairs and that of the cellular system. The selecting rule of reusing mode is derived, and four radiuses are achieved to determine the reusing mode and select the cellular user to be reused. By using the rule to select a reusing mode, not only the communication quality of D2D communication and cellular communication can be improved, but also more D2D users can successfully establish communication even at the case of insufficient spectrum resources. Simulation results show that the D2D system with the proposed reusing strategy can significantly improve the overall system throughput.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117122218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
A Gamma-Poisson Block Model for Community Detection in Directed Network 有向网络社区检测的Gamma-Poisson块模型
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8687311
Siyuan Gao, Ruifang Liu, Hang Miao
{"title":"A Gamma-Poisson Block Model for Community Detection in Directed Network","authors":"Siyuan Gao, Ruifang Liu, Hang Miao","doi":"10.1109/FSKD.2018.8687311","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8687311","url":null,"abstract":"Detecting communities in networks is to find subgroups of nodes with similar characteristics, which is commonly defined as finding groups of nodes with dense connection in undirected networks. However, communities in directed networks can represent connectivity patterns because of asymmetric relations' which is difficult to capture using traditional algorithms. In this paper, a Gamma-Poisson block model is proposed for community detection in directed networks, which can model not only assortative communities but also communities with various connectivity patterns due to a block matrix. The model can also be extended to undirected networks if we set the block matrix symmetric, and for assortative community detection task if we set the block matrix diagonal. We develop an efficient Gibbs sampling algorithm for the inference work, which can scale to large sparse networks since links other than node pairs are considered during each iteration. We compare our model with several previous ones on a variety of real-world networks and the results demonstrate the advantages in our model.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124896260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Design and Implementation of Oceangoing Ship Scheduling Data Warehouse 远洋船舶调度数据仓库的设计与实现
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8687180
F. Zhu, Shaobo Wang
{"title":"Design and Implementation of Oceangoing Ship Scheduling Data Warehouse","authors":"F. Zhu, Shaobo Wang","doi":"10.1109/FSKD.2018.8687180","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8687180","url":null,"abstract":"Currently, the shipping company's statistical data on cargo is usually obtained through the complex operation of the business database. The statistical items are also very limited. To improve the competitiveness of shipping company and optimize its ship scheduling business, this paper mainly researches on technology and application of data warehouse in oceangoing ship scheduling business. According to the customer's actual and objective needs, the ship scheduling data warehouse is designed. Based on Microsoft SQL Server 2008 platform and ship scheduling data of a shipping company, the ship scheduling data warehouse for cargo loading/discharging analysis in global ports is established in this paper, which can offer data deeply analysis and multidimensional display.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125557413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Automated Assessment of Small Bowel Motility Function Based on Feature Points Tracking 基于特征点跟踪的小肠运动功能自动评估
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8687193
K. Otsuki, A. Furukawa, S. Kanasaki, Y. Iwamoto, T. Tateyama, Yenwei Chen
{"title":"Automated Assessment of Small Bowel Motility Function Based on Feature Points Tracking","authors":"K. Otsuki, A. Furukawa, S. Kanasaki, Y. Iwamoto, T. Tateyama, Yenwei Chen","doi":"10.1109/FSKD.2018.8687193","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8687193","url":null,"abstract":"In this paper, we propose an automated method for assessing small bowel contraction movement with Cine-MRI based on automatic feature points tracking. The proposed method comprises two steps. First, in the initial frame, the user selects two arbitrary points on the boundary of the small bowel. The distance between the two points represents the size of the small bowl. Second, each of the two points is automatically tracked by the use of Kanade-Lucas-Tomasi (KLT) tracker method in the temporal sequence images. The contraction movement of the small intestine can be automatically analyzed by tracking these two points. Compared with the conventional method based on small bowel segmentation, The KLT-tracker method allows us to analyze the small intestinal contraction movement faster and establish a more objective analysis method.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"256 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116059334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Accurate Measurement of Reactive Power Based on Fryze's Definition of Time Domain Reactive Power 基于Fryze时域无功定义的无功精确测量
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8686983
Xiaoke Chen, Jianhua Yin, Xiao-Jian Zhao, Xiaolei Yuan, Xuemin Wang, Jin-quan Zhao
{"title":"Accurate Measurement of Reactive Power Based on Fryze's Definition of Time Domain Reactive Power","authors":"Xiaoke Chen, Jianhua Yin, Xiao-Jian Zhao, Xiaolei Yuan, Xuemin Wang, Jin-quan Zhao","doi":"10.1109/FSKD.2018.8686983","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8686983","url":null,"abstract":"In view of the lack of accuracy of reactive power measurement in reactive power measurement under nonsinusoidal unbalanced conditions, this paper proposes a nonsinusoidal unbalanced three-phase method based on the definition of Fryze's time domain reactive power. Three-wire system reactive power measurement theory. According to the definition of Fryze time domain reactive power, three-phase instantaneous current is decomposed into active current component and reactive current component, and three-phase instantaneous voltage and reactive current component are subjected to fast Fourier transform to obtain various harmonic reactive power. Size and direction to achieve accurate metering of reactive energy for non-sinusoidal unbalanced three-phase three-wire systems. This method divides the reactive power into positive reactive power and reverse reactive power, avoiding the situation where the harmonic reactive power and capacitive reactive power generated by the same harmonic source cancel each other out. Finally, this conclusion is verified by Matlab simulation, which provides a theoretical basis for accurate measurement of system reactive power under nonsinusoidal unbalanced conditions.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116407933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
The Academic Warning Model Based on TLBO-BP Algorithm 基于TLBO-BP算法的学术预警模型
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8687305
Longlong Liu, Shengnan Yu
{"title":"The Academic Warning Model Based on TLBO-BP Algorithm","authors":"Longlong Liu, Shengnan Yu","doi":"10.1109/FSKD.2018.8687305","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8687305","url":null,"abstract":"Tracking students' learning situations, analyzing test scores and predicting possible states of learning in the future are helpful for students who need academic intervention. And it is an important task with practical meaning and research value for teachers to provide targeted guidance and a decision-making basis. In this paper, a group intelligent optimization algorithm and the neural network theory are applied to the students' academic intervention problem. The TLBO-BP algorithm is proposed to optimize the initial weights in the BP neural network. It can speed up the convergence of the algorithm and avoid the instability of the training result caused by the random initialization of the BP neural network. The model shows satisfactory results in two examples, which further supports its validity.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122303629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Human positioning based on probabilistic occupancy map 基于概率占用图的人类定位
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8686844
Jijun Tong, Lingyu Chen, Yicheng Cao
{"title":"Human positioning based on probabilistic occupancy map","authors":"Jijun Tong, Lingyu Chen, Yicheng Cao","doi":"10.1109/FSKD.2018.8686844","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8686844","url":null,"abstract":"With the development of video analytics technology, Video surveillance system can detect and report suspicious objects location information in time, which gradually changes from post-mortem forensics to the pre-prevention mode. By defining a discrete occupancy map to describe whether the object is in the certain space, the algorithm in this paper iteratively estimates the occupancy probability for each location so as to quickly determine the specific position of the moving objects in the video. Videos from Internet and taken in the lab are both tested in this paper. The result shows that this method can effectively solve the problem of occlusion and information fusion of multiple camera. When monitoring the scene of 3 × 3 (m), the positioning accuracy is over 96%.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122097564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Classification of Reservoir Fracture Development Level by Convolution Neural Network Algorithm 基于卷积神经网络的储层裂缝发育程度分类
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8687232
Zhengyang Wu, Xiuwen Mo, Hao Zhou, Lipan Liu, Jinfeng Li
{"title":"Classification of Reservoir Fracture Development Level by Convolution Neural Network Algorithm","authors":"Zhengyang Wu, Xiuwen Mo, Hao Zhou, Lipan Liu, Jinfeng Li","doi":"10.1109/FSKD.2018.8687232","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8687232","url":null,"abstract":"Identifying and classifying fractures is an important task in the study of fractured oil and gas reservoirs. The most common solution is to identify it by artificial interpretation or synthetically probability methods, and to classify them according to the degree of fracture development. In order to improve the accuracy and reduce the man-made or computational errors, this study introduces the convolutional neural network (CNN) algorithm, one of the deep learning algorithms, to distinguish the degree of fracture development while constructing a new model which can automatically identify cracks and determine the category of fractured reservoirs in the meantime. Firstly, the logging curves with strong sensitivity to fractures are selected as the input data of convolution neural network, and the crack category is quantified as the output label of the network. A CNN model which is suitable for the classification of cracks is designed, whose parameters is continuously optimized through a small batch gradient descent method in the training stage. Then the trained convolutional neural network is applied to process the logging data of an oil field. The comparison of the result of crack classification by convolutional neural network with that by the traditional BP neural network indicates that the unique convolutional weight sharing structure of convolutional neural networks can extract the most effective features and greatly improve the accuracy of the fracture classification in dealing with complex nonlinear problems such as the classification of fractured reservoirs.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117102025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Grade Prediction of Student Academic Performance with Multiple Classification Models 基于多分类模型的学生学习成绩预测
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8687286
Xu Zhang, Ruojuan Xue, Bin Liu, Wenpeng Lu, Yiqun Zhang
{"title":"Grade Prediction of Student Academic Performance with Multiple Classification Models","authors":"Xu Zhang, Ruojuan Xue, Bin Liu, Wenpeng Lu, Yiqun Zhang","doi":"10.1109/FSKD.2018.8687286","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8687286","url":null,"abstract":"The achievement evaluation and development prediction of college students are the core of student management in universities. The traditional student evaluation method only focuses on the evaluation of students' past achievements, but lacks the prediction of students' future development. The change of grade prediction of students' future academic performance has great values for schools to strengthen education management. In this paper, Naive Bayes, Decision Tree, Multilayer Perceptron and Support Vector are utilized as classification models to predict students' academic performance. And an exhaustive comparative study is carried on the datasets of students' information provided by university of electronic science and technology. Among the models, multi-layer perceptron model has demonstrated powerful effectiveness, which achieved 65.90% accuracy on the training set and 62.04% accuracy in the test set. If the data sample is large enough, the experimental results will be more accurate.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128464453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
Kernel Based Visual Tracking with Scale-Free Network Model 基于核的无标度网络模型视觉跟踪
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8686848
Risheng Han
{"title":"Kernel Based Visual Tracking with Scale-Free Network Model","authors":"Risheng Han","doi":"10.1109/FSKD.2018.8686848","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8686848","url":null,"abstract":"A novel tracking algorithm is proposed based on kernel based object tracking and scale-free network model. The proposed method regards target model as degree distribution of scale-free complex network model. By taking advantage of scale-free network's characteristic, target's special pixels which have much larger effects than other pixels can be used in tracking process. Based on these special points, target's network can be produced and target scale and target model can also be updated. Experiments show that the proposed algorithm can keep tracking target under conditions of clutter background, varying scales, and partial occlusion. This is the first research about how to use complex network model into the visual tracking algorithm.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129353353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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