Pub Date : 2017-08-01DOI: 10.1109/ICCSE.2017.8085573
Xiaofang Zhang, Xiaotao Huang, Fen Wang
Data mining technology is the key technology and core content of big data age. The undergraduate data mining course introduces the basic concepts, basic principles and application techniques of data mining, as well as the characteristics and new technologies of data mining under the background of big data. According to the characteristics of undergraduate students, the curriculum should weaken the theory and algorithm as much as possible, and emphasizing the application. Through analysis and experiment on various examples, to enable students to face the specific application problems, can use the SPSS Modeler to designing a data processing, select the appropriate data mining method, and finally get the ideal results of data mining.
{"title":"The construction of undergraduate data mining course in the big data age","authors":"Xiaofang Zhang, Xiaotao Huang, Fen Wang","doi":"10.1109/ICCSE.2017.8085573","DOIUrl":"https://doi.org/10.1109/ICCSE.2017.8085573","url":null,"abstract":"Data mining technology is the key technology and core content of big data age. The undergraduate data mining course introduces the basic concepts, basic principles and application techniques of data mining, as well as the characteristics and new technologies of data mining under the background of big data. According to the characteristics of undergraduate students, the curriculum should weaken the theory and algorithm as much as possible, and emphasizing the application. Through analysis and experiment on various examples, to enable students to face the specific application problems, can use the SPSS Modeler to designing a data processing, select the appropriate data mining method, and finally get the ideal results of data mining.","PeriodicalId":256055,"journal":{"name":"2017 12th International Conference on Computer Science and Education (ICCSE)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134028588","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}
Pub Date : 2017-08-01DOI: 10.1109/ICCSE.2017.8085587
Yufeng Chen, Xuemin Liu, Panpan Huo, Fengxia Li Lin Li'
This paper designs and implements an automatic evaluation system for experimental reports in the field of university computer virtual experiment. The evaluation type is divided into three types: the only answer type, the rule-related type and the subjective short answer type. For the problems of the subjective short answer, a simple and effective method based on the participle of the standard answer and the multi-level semantic similarity is proposed in this system. The application of this system in the university computer virtual experiment platform shows that it not only facilitates the mastery of the experimental knowledge points, but also ensures the accuracy rate and greatly improves the efficiency of judging.
{"title":"The design and implementation for automatic evaluation system of virtual experiment report","authors":"Yufeng Chen, Xuemin Liu, Panpan Huo, Fengxia Li Lin Li'","doi":"10.1109/ICCSE.2017.8085587","DOIUrl":"https://doi.org/10.1109/ICCSE.2017.8085587","url":null,"abstract":"This paper designs and implements an automatic evaluation system for experimental reports in the field of university computer virtual experiment. The evaluation type is divided into three types: the only answer type, the rule-related type and the subjective short answer type. For the problems of the subjective short answer, a simple and effective method based on the participle of the standard answer and the multi-level semantic similarity is proposed in this system. The application of this system in the university computer virtual experiment platform shows that it not only facilitates the mastery of the experimental knowledge points, but also ensures the accuracy rate and greatly improves the efficiency of judging.","PeriodicalId":256055,"journal":{"name":"2017 12th International Conference on Computer Science and Education (ICCSE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129419965","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}
Pub Date : 2017-08-01DOI: 10.1109/ICCSE.2017.8085595
Junshan Si, Yi Cao, Xianjiang Shi
Planetary gearbox of wind turbine works under changed load and speed and the vibration signal is nonlinear, non-stationary, this make it difficult to extract the weak fault characteristic frequency. In this paper, a new method of fault feature extraction and separation based on empirical mode decomposition (EMD) and resonance demodulation is proposed. The method uses EMD to decompose the vibration signal and gets the intrinsic mode function (IMF) which can represent different frequencies. Then, the IMF component of the structure resonance frequency which is caused by the fault gear impact is selected to demodulate and analyze, and the weak fault information is extracted. In order to verify the effectiveness of the proposed method, a simulation platform of the wind turbine is built based on the analysis of the structure and typical vibration characteristics of the planetary gear, we analyze the vibration signal of the planetary gear in normal and fault state. The experimental results show that it is feasible to denoise the fault information and extract the fault characteristic frequency components by using EMD and structural resonance demodulation technique.
{"title":"Fault diagnosis of wind turbine planetary gear box based on EMD and resonance remodulation","authors":"Junshan Si, Yi Cao, Xianjiang Shi","doi":"10.1109/ICCSE.2017.8085595","DOIUrl":"https://doi.org/10.1109/ICCSE.2017.8085595","url":null,"abstract":"Planetary gearbox of wind turbine works under changed load and speed and the vibration signal is nonlinear, non-stationary, this make it difficult to extract the weak fault characteristic frequency. In this paper, a new method of fault feature extraction and separation based on empirical mode decomposition (EMD) and resonance demodulation is proposed. The method uses EMD to decompose the vibration signal and gets the intrinsic mode function (IMF) which can represent different frequencies. Then, the IMF component of the structure resonance frequency which is caused by the fault gear impact is selected to demodulate and analyze, and the weak fault information is extracted. In order to verify the effectiveness of the proposed method, a simulation platform of the wind turbine is built based on the analysis of the structure and typical vibration characteristics of the planetary gear, we analyze the vibration signal of the planetary gear in normal and fault state. The experimental results show that it is feasible to denoise the fault information and extract the fault characteristic frequency components by using EMD and structural resonance demodulation technique.","PeriodicalId":256055,"journal":{"name":"2017 12th International Conference on Computer Science and Education (ICCSE)","volume":"206 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132468323","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}
Pub Date : 2017-08-01DOI: 10.1109/ICCSE.2017.8085517
Zhang Lingfeng, F. Feng, Huang Heng
For the quality of the wine big data identification technology, the introduction of data mining classification algorithm, effectively according to the content of several impact compounds in wine level identification;Are introduced including the Logistic regression and BP neural network and SVM classification algorithm, in view of the three algorithms identify the modeling analysis of wine quality. Data mining is closely related to big data, applying data mining to the wine in the quality detection of big data, can quickly to the quality of the wine.
{"title":"Wine quality identification based on data mining research","authors":"Zhang Lingfeng, F. Feng, Huang Heng","doi":"10.1109/ICCSE.2017.8085517","DOIUrl":"https://doi.org/10.1109/ICCSE.2017.8085517","url":null,"abstract":"For the quality of the wine big data identification technology, the introduction of data mining classification algorithm, effectively according to the content of several impact compounds in wine level identification;Are introduced including the Logistic regression and BP neural network and SVM classification algorithm, in view of the three algorithms identify the modeling analysis of wine quality. Data mining is closely related to big data, applying data mining to the wine in the quality detection of big data, can quickly to the quality of the wine.","PeriodicalId":256055,"journal":{"name":"2017 12th International Conference on Computer Science and Education (ICCSE)","volume":"294 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113968974","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}
Pub Date : 2017-08-01DOI: 10.1109/ICCSE.2017.8085526
Cunling Bian, Shijun Dong, Chunrong Li, Zheng Shi, Weigang Lu
In recent years, the research of adaptive learning path has drawn a lot of attentions, which organizes the learning resources in accordance with the learner's attributes. As a result, it is quite necessary to find an efficient implementation approach for generating the adaptive learning path. In this paper, we first create a learner-centered concept map by graph theory. Then learning object (LO) is applied as an organization model for learning resource and we apply the immune algorithm (IA) into its selection to generate the optimal learning path. The simulation results show that the proposed approach is effective for adaptive learning path generation.
{"title":"Generation of adaptive learning path based on concept map and immune algorithm","authors":"Cunling Bian, Shijun Dong, Chunrong Li, Zheng Shi, Weigang Lu","doi":"10.1109/ICCSE.2017.8085526","DOIUrl":"https://doi.org/10.1109/ICCSE.2017.8085526","url":null,"abstract":"In recent years, the research of adaptive learning path has drawn a lot of attentions, which organizes the learning resources in accordance with the learner's attributes. As a result, it is quite necessary to find an efficient implementation approach for generating the adaptive learning path. In this paper, we first create a learner-centered concept map by graph theory. Then learning object (LO) is applied as an organization model for learning resource and we apply the immune algorithm (IA) into its selection to generate the optimal learning path. The simulation results show that the proposed approach is effective for adaptive learning path generation.","PeriodicalId":256055,"journal":{"name":"2017 12th International Conference on Computer Science and Education (ICCSE)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114553968","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}
Pub Date : 2017-08-01DOI: 10.1109/ICCSE.2017.8085594
Minghui Weng, Lianfeng Huang, Chao Feng, Fenglian Gao, Hezhi Lin
Electronic medical record can greatly improve work efficiency of the hospital and medical quality in the clinical application. Meanwhile with the rapid development of virtual reality (VR) and augmented reality (AR) technology, people's life will adopt a new way. In this paper, Electronic medical record system (EMRS) based on augmented reality is proposed. The system consists of server, Android device and data glove. User can not only check the relevant medical information on the Android device, but also operate the 3D organ model based on AR through gestures. In addition, users can also wear AR/VR glasses and data gloves to operate the 3D organ model in order to get a stronger sense of immersion. Through this system, we can show more pathological information, which can not only help the communication between doctors and patients, but also can be used in medical teaching.
{"title":"Electronic medical record system based on augmented reality","authors":"Minghui Weng, Lianfeng Huang, Chao Feng, Fenglian Gao, Hezhi Lin","doi":"10.1109/ICCSE.2017.8085594","DOIUrl":"https://doi.org/10.1109/ICCSE.2017.8085594","url":null,"abstract":"Electronic medical record can greatly improve work efficiency of the hospital and medical quality in the clinical application. Meanwhile with the rapid development of virtual reality (VR) and augmented reality (AR) technology, people's life will adopt a new way. In this paper, Electronic medical record system (EMRS) based on augmented reality is proposed. The system consists of server, Android device and data glove. User can not only check the relevant medical information on the Android device, but also operate the 3D organ model based on AR through gestures. In addition, users can also wear AR/VR glasses and data gloves to operate the 3D organ model in order to get a stronger sense of immersion. Through this system, we can show more pathological information, which can not only help the communication between doctors and patients, but also can be used in medical teaching.","PeriodicalId":256055,"journal":{"name":"2017 12th International Conference on Computer Science and Education (ICCSE)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116354384","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}
Link prediction has become an important research topic in the field of complex networks. The purpose of link prediction is to find the missing links or predict the emergence of new links that do not present currently in a complex networks. Considering that the local centrality of common neighbor nodes have an important effect on the similarity-based algorithm, but every centrality measure has its own advantage and limitation. We proposed a multi-attribute ranking method based on the Technique for Order Preference by Similarity to Ideal Object (TOPSIS) to evaluate the local centrality of common neighbor nodes comprehensively. In order to make the local centrality indicator based on TOPSIS achieve better results, we also proposed a new weight calculation method for the attributes normalization matrix. Experimental studies on 6 real world networks from disparate fields verified the superiority of the algorithm proposed in this paper.
链路预测已成为复杂网络领域的一个重要研究课题。链接预测的目的是发现当前复杂网络中不存在的缺失链接或预测新链接的出现。考虑到共同邻居节点的局部中心性对基于相似度的算法有重要影响，但每种中心性度量都有其自身的优点和局限性。提出了一种基于TOPSIS (Order Preference Technique by Similarity to Ideal Object)的多属性排序方法，以综合评价共同邻居节点的局部中心性。为了使基于TOPSIS的局部中心性指标取得更好的效果，我们还提出了一种新的属性归一化矩阵权值计算方法。在不同领域的6个真实网络上进行的实验研究验证了本文算法的优越性。
{"title":"Link prediction algorithm based on local centrality of common neighbor nodes using multi-attribute ranking","authors":"Mingqiang Zhou, Rongcheng Liu, Xin Zhao, Qingsheng Zhu","doi":"10.1109/ICCSE.2017.8085544","DOIUrl":"https://doi.org/10.1109/ICCSE.2017.8085544","url":null,"abstract":"Link prediction has become an important research topic in the field of complex networks. The purpose of link prediction is to find the missing links or predict the emergence of new links that do not present currently in a complex networks. Considering that the local centrality of common neighbor nodes have an important effect on the similarity-based algorithm, but every centrality measure has its own advantage and limitation. We proposed a multi-attribute ranking method based on the Technique for Order Preference by Similarity to Ideal Object (TOPSIS) to evaluate the local centrality of common neighbor nodes comprehensively. In order to make the local centrality indicator based on TOPSIS achieve better results, we also proposed a new weight calculation method for the attributes normalization matrix. Experimental studies on 6 real world networks from disparate fields verified the superiority of the algorithm proposed in this paper.","PeriodicalId":256055,"journal":{"name":"2017 12th International Conference on Computer Science and Education (ICCSE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114765786","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}
Pub Date : 2017-08-01DOI: 10.1109/ICCSE.2017.8085549
He Ren-ya, Tang Long-li, Wang Xiao-liang, Yu Zheng-wei, Wu Yu-mei
This paper presents a method to evaluate the reliability of software. First, failure mechanism and characteristics of failure propagation are analyzed, then the measurement method of the fault propagation characteristic attribute value is given. How to build the fault propagation graph, determine the fragile paths and the fragile modules are also studied.
{"title":"Software reliability evaluation method based on fault propagation testing","authors":"He Ren-ya, Tang Long-li, Wang Xiao-liang, Yu Zheng-wei, Wu Yu-mei","doi":"10.1109/ICCSE.2017.8085549","DOIUrl":"https://doi.org/10.1109/ICCSE.2017.8085549","url":null,"abstract":"This paper presents a method to evaluate the reliability of software. First, failure mechanism and characteristics of failure propagation are analyzed, then the measurement method of the fault propagation characteristic attribute value is given. How to build the fault propagation graph, determine the fragile paths and the fragile modules are also studied.","PeriodicalId":256055,"journal":{"name":"2017 12th International Conference on Computer Science and Education (ICCSE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114973737","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}
Pub Date : 2017-08-01DOI: 10.1109/ICCSE.2017.8085455
Jeong Yang, Young Lee, Deep Gandhi, Sruthi Ganesan Valli
We propose a novel approach for visualizing reverse-engineered Unified Modeling Language (UML) diagrams (class, object, and sequence) to improve Object-Oriented Program (OOP) comprehension on a web-based programming environment, JaguarCode. It aims to help students better understand static structure and dynamic behavior of Java programs and object-oriented programming concepts. This paper presents an evaluation of JaguarCode, supporting those UML diagrams to investigate its effectiveness and user satisfaction. The results of the experimental study revealed having synchronized UML diagrams positively impacted students' understanding of program execution. It was also observed that students were satisfied with the aspects of the synchronized visualizations of UML diagrams with source code.
{"title":"Synchronized UML diagrams for object-oriented program comprehension","authors":"Jeong Yang, Young Lee, Deep Gandhi, Sruthi Ganesan Valli","doi":"10.1109/ICCSE.2017.8085455","DOIUrl":"https://doi.org/10.1109/ICCSE.2017.8085455","url":null,"abstract":"We propose a novel approach for visualizing reverse-engineered Unified Modeling Language (UML) diagrams (class, object, and sequence) to improve Object-Oriented Program (OOP) comprehension on a web-based programming environment, JaguarCode. It aims to help students better understand static structure and dynamic behavior of Java programs and object-oriented programming concepts. This paper presents an evaluation of JaguarCode, supporting those UML diagrams to investigate its effectiveness and user satisfaction. The results of the experimental study revealed having synchronized UML diagrams positively impacted students' understanding of program execution. It was also observed that students were satisfied with the aspects of the synchronized visualizations of UML diagrams with source code.","PeriodicalId":256055,"journal":{"name":"2017 12th International Conference on Computer Science and Education (ICCSE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132143038","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}
Pub Date : 2017-08-01DOI: 10.1109/ICCSE.2017.8085486
Zhaohui Luo, Weisheng He, M. Liwang, Lianfeng Huang, Yifeng Zhao, Jun Geng
Recently, abnormal evens detection in crowds has received considerable attention in the field of public safety. Most existing studies do not account for the processing time and the continuity of abnormal behavior characteristics. In this paper, we present a new motion feature descriptor, called the sensitive movement point (SMP). Gaussian Mixture Model (GMM) is used for modeling the abnormal crowd behavior with full consideration of the characteristics of crowd abnormal behavior. First, we analyze the video with GMM, to extract sensitive movement point in certain speed by setting update threshold value of GMM. Then, analyze the sensitive movement point of video frame with temporal and spatial modeling. Identify abnormal behavior through the analysis of mutation duration occurs in temporal and spatial model, and the density, distribution and mutative acceleration of sensitive movement point in blocks. The algorithm can be implemented with automatic adapt to environmental change and online learning, without tracking individuals of crowd and large scale training in detection process. Experiments involving the UMN datasets and the videos taken by us show that the proposed algorithm can real-time effectively identify various types of anomalies and that the recognition results and processing time are better than existing algorithms.
{"title":"Real-time detection algorithm of abnormal behavior in crowds based on Gaussian mixture model","authors":"Zhaohui Luo, Weisheng He, M. Liwang, Lianfeng Huang, Yifeng Zhao, Jun Geng","doi":"10.1109/ICCSE.2017.8085486","DOIUrl":"https://doi.org/10.1109/ICCSE.2017.8085486","url":null,"abstract":"Recently, abnormal evens detection in crowds has received considerable attention in the field of public safety. Most existing studies do not account for the processing time and the continuity of abnormal behavior characteristics. In this paper, we present a new motion feature descriptor, called the sensitive movement point (SMP). Gaussian Mixture Model (GMM) is used for modeling the abnormal crowd behavior with full consideration of the characteristics of crowd abnormal behavior. First, we analyze the video with GMM, to extract sensitive movement point in certain speed by setting update threshold value of GMM. Then, analyze the sensitive movement point of video frame with temporal and spatial modeling. Identify abnormal behavior through the analysis of mutation duration occurs in temporal and spatial model, and the density, distribution and mutative acceleration of sensitive movement point in blocks. The algorithm can be implemented with automatic adapt to environmental change and online learning, without tracking individuals of crowd and large scale training in detection process. Experiments involving the UMN datasets and the videos taken by us show that the proposed algorithm can real-time effectively identify various types of anomalies and that the recognition results and processing time are better than existing algorithms.","PeriodicalId":256055,"journal":{"name":"2017 12th International Conference on Computer Science and Education (ICCSE)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134463506","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}
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