As a result of the development of various digital technologies, relief generation tends to be digitization. At the same time, the copyright protection is becoming more prominent. Currently research on digital watermarking for bas-relief has not been found in the literature libraries. The relief is considered to be a medium between 2D images and 3D models, we think relief watermarking can provide great help for the study of 3D watermarking in the future. In this paper, we propose a new reference indicator—edge block ratio. Under this index, we combine the two-dimensional cepstrum image watermarking algorithm and edge detection technology to achieve bas-relief watermarking. Through a lot of experiments, the method can better meet the invisibility of the relief watermark, as well as the robustness to common relief editors. It points out a new direction for bas-relief watermarking.
{"title":"Watermarking Algorithm for Bas-Relief Based on Depth Grayscale Image","authors":"Shiru Zhang, Ye Wu, Yuhua Bao, Jun Bai","doi":"10.1109/CIIS.2017.49","DOIUrl":"https://doi.org/10.1109/CIIS.2017.49","url":null,"abstract":"As a result of the development of various digital technologies, relief generation tends to be digitization. At the same time, the copyright protection is becoming more prominent. Currently research on digital watermarking for bas-relief has not been found in the literature libraries. The relief is considered to be a medium between 2D images and 3D models, we think relief watermarking can provide great help for the study of 3D watermarking in the future. In this paper, we propose a new reference indicator—edge block ratio. Under this index, we combine the two-dimensional cepstrum image watermarking algorithm and edge detection technology to achieve bas-relief watermarking. Through a lot of experiments, the method can better meet the invisibility of the relief watermark, as well as the robustness to common relief editors. It points out a new direction for bas-relief watermarking.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115494784","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}
Recently the customer order scheduling models has continued growing attention in research community. However, customer order scheduling problem with the ready time is only relatively few. In light of this limitation, we then address a multi-facility order scheduling with ready times to find a sequence to minimize the total weighted completion time. Because the complexity of this problem is very difficult, we use five existing heuristics and two-type iterative greedy algorithms to find near-optimal solutions. All of the proposed heuristics are also improved by pairwise improvement. Finally, we conduct a one-way analysis of variance and Fisher's least significant difference tests to assess the performances of all the proposed algorithms.
{"title":"An Novel Metaheuristic for the Order Scheduling with Ready Times","authors":"Win-Chin Lin, Tzu-Hsuan Yang, Chin-Chia Wu","doi":"10.1109/CIIS.2017.11","DOIUrl":"https://doi.org/10.1109/CIIS.2017.11","url":null,"abstract":"Recently the customer order scheduling models has continued growing attention in research community. However, customer order scheduling problem with the ready time is only relatively few. In light of this limitation, we then address a multi-facility order scheduling with ready times to find a sequence to minimize the total weighted completion time. Because the complexity of this problem is very difficult, we use five existing heuristics and two-type iterative greedy algorithms to find near-optimal solutions. All of the proposed heuristics are also improved by pairwise improvement. Finally, we conduct a one-way analysis of variance and Fisher's least significant difference tests to assess the performances of all the proposed algorithms.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116133245","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}
In order to solve the problem that the similarity of asynchronous multi-source multi-track cannot be measured effectively, a new trajectory similarity model for asynchronous multi-source multi-track is proposed in this paper. Based on the idea of searching the potential matched data points under the spatial and temporal constraints, the optimal matched point is determined from the sets of nearly matched points by setting a certain spatial threshold and temporal threshold, and the similarity measure between multi-source trajectories is obtained. The spatial and temporal relation between potential matched points from multi-source trajectories has been totally considered. The temporal slots between potential mapped points are allowed, reducing the complexity sharply and ensuring the trajectory mapping accuracy. The application to a real data set shows that the model can evaluate the similarity of multi-source trajectory effectively, and its time cost is lower than traditional methods.
{"title":"A Real-Time Similarity Measure Model for Multi-source Trajectories","authors":"Lu Sun, W. Zhou, Baichen Jiang, J. Guan","doi":"10.1109/CIIS.2017.60","DOIUrl":"https://doi.org/10.1109/CIIS.2017.60","url":null,"abstract":"In order to solve the problem that the similarity of asynchronous multi-source multi-track cannot be measured effectively, a new trajectory similarity model for asynchronous multi-source multi-track is proposed in this paper. Based on the idea of searching the potential matched data points under the spatial and temporal constraints, the optimal matched point is determined from the sets of nearly matched points by setting a certain spatial threshold and temporal threshold, and the similarity measure between multi-source trajectories is obtained. The spatial and temporal relation between potential matched points from multi-source trajectories has been totally considered. The temporal slots between potential mapped points are allowed, reducing the complexity sharply and ensuring the trajectory mapping accuracy. The application to a real data set shows that the model can evaluate the similarity of multi-source trajectory effectively, and its time cost is lower than traditional methods.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123832880","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}
The course of tourism electronic commerce should follow the idea of higher vocational education, give prominence to cultivating occupation ability. Through the teaching experience of "Travel E-commerce" curriculum and the analysis of the demand ability of information technology talents of tourism enterprises, this thesis explored and studied the curriculum system, experimental teaching, teaching methods etc.
{"title":"Research on the Course of Tourism Electronic Commerce Based on the Perspective of Enterprise Demand in Higher Vocational Institutes","authors":"Hui Wang, Jie Kong","doi":"10.1109/CIIS.2017.68","DOIUrl":"https://doi.org/10.1109/CIIS.2017.68","url":null,"abstract":"The course of tourism electronic commerce should follow the idea of higher vocational education, give prominence to cultivating occupation ability. Through the teaching experience of \"Travel E-commerce\" curriculum and the analysis of the demand ability of information technology talents of tourism enterprises, this thesis explored and studied the curriculum system, experimental teaching, teaching methods etc.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129481170","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}
In this paper, the constrained group-wise k-means algorithm is proposed to select groups of features during clustering. The idea of the algorithm is it not only constrains the weight of individual features via the lasso penalty, but also restrains group-wise weight of features by the group lasso penalty. Under the effect of these two penalties, this algorithm not only performs better in clustering, but is also comparable to other approaches in its ability to obtain the correct features with costing less computational time than the sparse k-means algorithm.
{"title":"Studies on the Constrained Group-Wise K-Means Algorithm","authors":"Hu Yang, Xianhou Chang","doi":"10.1109/CIIS.2017.73","DOIUrl":"https://doi.org/10.1109/CIIS.2017.73","url":null,"abstract":"In this paper, the constrained group-wise k-means algorithm is proposed to select groups of features during clustering. The idea of the algorithm is it not only constrains the weight of individual features via the lasso penalty, but also restrains group-wise weight of features by the group lasso penalty. Under the effect of these two penalties, this algorithm not only performs better in clustering, but is also comparable to other approaches in its ability to obtain the correct features with costing less computational time than the sparse k-means algorithm.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134562720","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}
The software reliability of digital reactor protection system (RPS) plays an important role in the reliability of RPS. By analyzing the fault data set collected during the software development process of HTR-PM RPS, this paper proposes software reliability models considering fault severity and correction time. The proposed models assume that there are two types of faults with different severity, the ratio of non-critical faults within total faults decays exponentially with time, there is delay between the detection and correction of a fault, and the correction time for faults of the same type is independent and identically distributed. Parameter estimation is carried out by least-square estimation, the mean square error and the coefficients of determination are adopted to evaluate the models. Compared to the models without considering fault severity, the proposed models can reflect the software reliability in more aspects for engineering application.
{"title":"Software Reliability Model Considering Fault Severity and Correction Time for HTR-PM Reactor Protection System","authors":"Chao Gao, Duo Li, Chao Guo","doi":"10.1109/CIIS.2017.40","DOIUrl":"https://doi.org/10.1109/CIIS.2017.40","url":null,"abstract":"The software reliability of digital reactor protection system (RPS) plays an important role in the reliability of RPS. By analyzing the fault data set collected during the software development process of HTR-PM RPS, this paper proposes software reliability models considering fault severity and correction time. The proposed models assume that there are two types of faults with different severity, the ratio of non-critical faults within total faults decays exponentially with time, there is delay between the detection and correction of a fault, and the correction time for faults of the same type is independent and identically distributed. Parameter estimation is carried out by least-square estimation, the mean square error and the coefficients of determination are adopted to evaluate the models. Compared to the models without considering fault severity, the proposed models can reflect the software reliability in more aspects for engineering application.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133279622","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}
Change detection is one of the most exciting application of remote sensing image interpretation and processing. In this paper, we propose a novel approach for unsupervised change detection by integrating Speeded Up Robust Features (SURF) key points and Supporting Vector Machine (SVM) classifier. The approach starts by extracting SURF key points from both images and matches them using RANdom SAmple Consensus (RANSAC) algorithm. The matched key points are then viewed as training samples for unchanged class; on the other hand, those for changed class are selected from the remaining SURF key points based on Gaussian mixture model (GMM). Subsequently, training samples are utilized for training an SVM classifier. Finally, the classifier is used to segment the difference image into changed and unchanged classes. To demonstrate the effect of our approach, we compare it with the other four state-of-the-art change detection methods over two datasets, meanwhile extensive quantitative and qualitative analysis of the change detection results confirms the effectiveness of the proposed approach, showing its capability to consistently produce promising results on all the datasets without any priori assumptions.
{"title":"Unsupervised Change Detection of Remote Sensing Images Based on SURF and SVM","authors":"Lin Wu, Bowen Liu, B. Zhao","doi":"10.1109/CIIS.2017.39","DOIUrl":"https://doi.org/10.1109/CIIS.2017.39","url":null,"abstract":"Change detection is one of the most exciting application of remote sensing image interpretation and processing. In this paper, we propose a novel approach for unsupervised change detection by integrating Speeded Up Robust Features (SURF) key points and Supporting Vector Machine (SVM) classifier. The approach starts by extracting SURF key points from both images and matches them using RANdom SAmple Consensus (RANSAC) algorithm. The matched key points are then viewed as training samples for unchanged class; on the other hand, those for changed class are selected from the remaining SURF key points based on Gaussian mixture model (GMM). Subsequently, training samples are utilized for training an SVM classifier. Finally, the classifier is used to segment the difference image into changed and unchanged classes. To demonstrate the effect of our approach, we compare it with the other four state-of-the-art change detection methods over two datasets, meanwhile extensive quantitative and qualitative analysis of the change detection results confirms the effectiveness of the proposed approach, showing its capability to consistently produce promising results on all the datasets without any priori assumptions.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115715180","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}
Di Huang, Min Li, Rui-rui Zheng, Shuang Xu, Jiajing Bi
There are a few studies on Manchu recognition, and the existing methods are mainly based on segmentation on characters or strokes. Thus, their performances are strongly dependent on segmentation accuracy. In this paper, a whole word recognition method for segmentation-free Manchu word is proposed to avoid the mis-segmentation of Manchu word. Firstly, we build an initial Manchu word image dataset, and then augment it with synthetic data, which are harvested via structural distortions on Manchu word image. Secondly, the support vector machine classifier with polynomial kernel function combined with directed acyclic graph is used for classification of Manchu words from 2 to 100 classes. The experiment results show that the precise is 78% for the 100-way classification problem, even above 90% for classes less than 40. The synthetic data method proposed in this paper is an effective way to augment the training and test dataset for Manchu word recognition.
{"title":"Synthetic Data and DAG-SVM Classifier for Segmentation-Free Manchu Word Recognition","authors":"Di Huang, Min Li, Rui-rui Zheng, Shuang Xu, Jiajing Bi","doi":"10.1109/CIIS.2017.15","DOIUrl":"https://doi.org/10.1109/CIIS.2017.15","url":null,"abstract":"There are a few studies on Manchu recognition, and the existing methods are mainly based on segmentation on characters or strokes. Thus, their performances are strongly dependent on segmentation accuracy. In this paper, a whole word recognition method for segmentation-free Manchu word is proposed to avoid the mis-segmentation of Manchu word. Firstly, we build an initial Manchu word image dataset, and then augment it with synthetic data, which are harvested via structural distortions on Manchu word image. Secondly, the support vector machine classifier with polynomial kernel function combined with directed acyclic graph is used for classification of Manchu words from 2 to 100 classes. The experiment results show that the precise is 78% for the 100-way classification problem, even above 90% for classes less than 40. The synthetic data method proposed in this paper is an effective way to augment the training and test dataset for Manchu word recognition.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122528961","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}
The well performing functionalities of a system mainly relies on the reliability of the software, which is enrolled at all stages of the software design. Reliability allocation optimization under budget constraints offers effective way for enhancing the reliability of the software. In this paper, we focus on the software reliability allocation optimization for an Automatic Train Operating (ATO) system. The software reliability allocation model for the studied case based on the Analytic Hierarchy Process (AHP) was constructed in view of the software structures of the system. The reliability optimization based on Budget Constrained Utility Maximization (BCUM) is then executed for the system. The reliability allocation model transforms the allocation to a nonlinear problem that takes the importance, the calling frequency and the cost of the modules of the system into account. Genetic Algorithm (GA) is employed to solve the allocation optimization problem of the system.
{"title":"Software Reliability Optimization for Automatic Train Operating System","authors":"Zengkun Li, Xibin Zhao","doi":"10.1109/CIIS.2017.52","DOIUrl":"https://doi.org/10.1109/CIIS.2017.52","url":null,"abstract":"The well performing functionalities of a system mainly relies on the reliability of the software, which is enrolled at all stages of the software design. Reliability allocation optimization under budget constraints offers effective way for enhancing the reliability of the software. In this paper, we focus on the software reliability allocation optimization for an Automatic Train Operating (ATO) system. The software reliability allocation model for the studied case based on the Analytic Hierarchy Process (AHP) was constructed in view of the software structures of the system. The reliability optimization based on Budget Constrained Utility Maximization (BCUM) is then executed for the system. The reliability allocation model transforms the allocation to a nonlinear problem that takes the importance, the calling frequency and the cost of the modules of the system into account. Genetic Algorithm (GA) is employed to solve the allocation optimization problem of the system.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117307848","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}
The prediction of human mobility is based on the law of population development and is the description of the future population image. For it as a research method of economic and social, it has been paid more and more attention and got more and more applications. The communication network of mobile phone users reflects different aspects of human's societal structure and the records of calls of mobile phone users enable us to construct a communication network. With the availability of human digital footprints, investigation of massive human mobility of urban areas becomes possible. In this paper, we perform an analysis of the statistical properties of the communication network, and proposed a human mobility prediction model in urban area that based on the social network of mobile phone users. We test the transfer similarity of our model on a series of real communication data, experimental results show that our proposed model has good robust and accurate performance.
{"title":"Multi-scale Politics Analysis on Urban Function Area Human Mobility","authors":"Yiding Feng, Pengfei Jiao, Wenjun Wang, S. Shi","doi":"10.1109/CIIS.2017.70","DOIUrl":"https://doi.org/10.1109/CIIS.2017.70","url":null,"abstract":"The prediction of human mobility is based on the law of population development and is the description of the future population image. For it as a research method of economic and social, it has been paid more and more attention and got more and more applications. The communication network of mobile phone users reflects different aspects of human's societal structure and the records of calls of mobile phone users enable us to construct a communication network. With the availability of human digital footprints, investigation of massive human mobility of urban areas becomes possible. In this paper, we perform an analysis of the statistical properties of the communication network, and proposed a human mobility prediction model in urban area that based on the social network of mobile phone users. We test the transfer similarity of our model on a series of real communication data, experimental results show that our proposed model has good robust and accurate performance.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116338603","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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