{"title":"Task assignment modeling and simulation for cooperative driving of multiple vessels","authors":"Shanshan Xiang, Yaojie Chen","doi":"10.1109/PIC.2017.8359508","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359508","url":null,"abstract":"The task assignment problem for multiple vessels cooperative driving is the key problem of the multiple vessels cooperative control. Due to the system showing multi-objective, multi-tasking and multi-constrained features, a cooperative multi-task assignment model is proposed, which can transform multiple constraints task assignment problem into multiple constraints optimization problem based on the multiple vessels task assignment cost function. This method optimizes the results of task assignment by using genetic ant colony hybrid algorithm to search optimization solution globally. In the simulation experiment, it is compared with the genetic algorithm and the ant colony algorithm alone, and experimental results show that the method can optimize task assignment on the basis of satisfying these constraints.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124859411","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}
{"title":"A research on adaptive calibration algorithm for multi-geometric projection","authors":"Li-jia Chen, Jie Wang, Yaohui Chen","doi":"10.1109/PIC.2017.8359584","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359584","url":null,"abstract":"To realize the adaptive projection of the projector on a variety of common projection planes and improve the efficiency of geometric correction, a multi-geometric function for adaptive correction algorithm is proposed. It uses the feature points to automatically fit out the curvilinear function. By automatically filtering the function corresponding to the pixel mapping relationship and calculating the projection pixel offset, the projection screen is cut according to the degree of correction, and finally the coordinates of the vertex are corrected by cutting the texture relationship to achieve geometric correction. The experimental results show that the proposed algorithm can achieve the practical application value of geometric distortion correction, such as cylindrical surface, spherical surface, common surface and projector non — projection, simply and quickly.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121898766","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}
{"title":"A short-term marginal price forecasting model based on ensemble learning","authors":"Kejia Pan, Wenbin Shi, Xin Wang, Jiazhou Li","doi":"10.1109/PIC.2017.8359519","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359519","url":null,"abstract":"This The system marginal price reflects the short-term supply and demand of electricity goods in the electricity market, which is an important economic link to the participating members of the market. The traditional prediction model has a large error and low generalization ability to forecast the short-term marginal price. Therefore, this paper proposes an ensemble learning algorithm for short-term marginal price forecasting based on AdaBoost. In this paper, the main factors influencing the short-term marginal electricity price are analyzed. Based on the AdaBoost algorithm, the short-term marginal electricity price forecasting problem is modeled. Four prediction models (C4.5, CART, Linear neural network, BP) are compared, and a short — term marginal price forecasting algorithm is proposed. By comparing the actual values with the predicted values, our proposed algorithm is superior to SVM and BP algorithm, which has high application values in power plant engineering.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129653590","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}
Chanying Huang, Kedong Yan, Songjie Wei, Dong Hoon Lee
{"title":"A privacy-preserving data sharing solution for mobile healthcare","authors":"Chanying Huang, Kedong Yan, Songjie Wei, Dong Hoon Lee","doi":"10.1109/PIC.2017.8359554","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359554","url":null,"abstract":"Personal Health Records (PHR) is patient-centric healthcare system, which allows patients to control who can get access to their health records and which section of the record can be accessed. Hot issues such as access control, patients control degree, and privacy protection, etc. are still the challenging concerns while designing a secure PHR system. In this paper, we propose dsPPS, a secure integrated PHR framework(from health data collection to health data sharing) that meets patients' full control of their PHR and sufficient privacy preservation. Specifically, dsPPS provides two schemes: Biometric-Based secure health data Collection (BBC) scheme and Attribute-Based health record Accessing (ABA) scheme. While BBC scheme enables patients to collect their scattered health data from multiple typical health systems securely and efficiently, the ABA scheme allows users (health systems) access to the PHR server with their sensitive attributes being protected. Comprehensive analysis is conducted to show the security of dsPPS against typical attacks. In addition, experiments in both smart phone and PC (Intel) platforms demonstrate that dsPPS produces reasonable performance in terms of storage, communication and computational overheads.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129481691","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}
{"title":"Polarization and solar altitude correlation analysis and application in object detection","authors":"Jie Shen, Zhe Chen, Cen Xu, Huibin Wang","doi":"10.1109/PIC.2017.8359538","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359538","url":null,"abstract":"Complicated optical scenes generally exist on the water surface. The noise originated from the light reflection seriously blocks the performance of the object detection method. This paper analyzes the correlation between the incident light angle and the flare noise, the relation between the solar altitude and the polarization state of the reflected light. Further, the correlation between the various imaging factors, such as the imaging time, the imaging angle of view, the polarization direction and the polarization state, is adjusted and optimized by the polarization imaging experiment. According to the experimental results, our polarization imaging method has good capability to suppress the noises generated by the light reflection, improving the accuracy of the object detection results.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"577 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115849893","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}
{"title":"An english subordinate clause connective correction model based on genetic algorithm and k-nearest neighbor algorithm","authors":"Guimin Huang, Chuang Wu, Sirui Huang, Hongtao Zhu, Ruyu Mo, Ya Zhou","doi":"10.1109/PIC.2017.8359561","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359561","url":null,"abstract":"In English writing, English learners will inevitably make a variety of grammatical mistakes, especially in English subordinate clause connective. To alleviate high error rate of connective in subordinate clauses of Chinese students' English writing, an automatic error correction model for English subordinate clause connective is studied and implemented from the perspective of machine learning — genetic algorithm (GA) and k-nearest neighbor (KNN) algorithm combination model. Firstly, an automatic feature selection algorithm based on GA is adopted to reduce time consuming and space cost, and to improve the accuracy of connective error correction. Secondly, through comparing the Naive Bayes, decision tree, maximum entropy and KNN algorithm, KNN algorithm is found better while classifying the connectives. Finally, we compared the performance of several hybrid models, which combine different machine learning algorithms with GA. This proves that the combination of GA and KNN algorithm is optimal.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"288 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117289122","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}
{"title":"Metrics analysis based on call graph of class methods","authors":"Du Qingfeng, Shi Kun, Yin Kanglin, Q. Juan","doi":"10.1109/PIC.2017.8359507","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359507","url":null,"abstract":"Evaluating software quality is a significant step in the process of developing software. Object-oriented metrics is an important way for software quality assessment and defect prediction. However, the existing object-oriented metric methods are difficult to reflect the complexity of software and vulnerabilities from the level of classes' method call relationship. A method is proposed in this paper, firstly we construct a call graph according to different classes methods call relationship in the system, and then three new software metrics are defined and analyzed by the call graph. The results of experiment indict that the metrics can reflect the complexity of software systems. These metrics can provide recommendations for evaluating software quality from the call graph.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129058613","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}
{"title":"Hot topic detection based on combined content and time similarity","authors":"Yi Zhao, Kun Zhang, Hong Zhang, Xia Yan, Ying Cai","doi":"10.1109/PIC.2017.8359580","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359580","url":null,"abstract":"Hot topic detection has always been a hot research field, and there are a large number of the applications of this technology in real life. Most of the previous work, however, focused only on the textual information of the news itself, while ignoring the other attributes of the news, such as the time the news was published, which can also tell the topic described in its perspective. And others use only one certain method to calculate the text similarity, which all have their disadvantages. To solve these problems, we proposed our own topic detection algorithm, which takes into account the information difference between the title and the text, combines several methods to calculate text similarity, and combines text and time similarity together. We tested the combined similarity calculation methods, and tested the effect of several time similarity equations. Then we took three different models to calculate the combined similarity which are linear model, quadratic polynomial model and neural network model. Finally, we give out the results and analysis of our experiments.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"491 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127574152","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}
{"title":"Multiple objects tracking based on multiple information integration","authors":"Kejia Pu, Z. Lian, Zhongeng Liu","doi":"10.1109/PIC.2017.8359543","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359543","url":null,"abstract":"Multi-target tracking algorithm often fail when targets are covered, or move fast, and it cannot be recovered from the failure. To solve this problem, firstly we use multiple information which integrate the target motion information and shape information. Based on the Fisher Criteria, we make the distance between same targets as close as possible which the distance between different targets far away. Secondly, the single target tracker based on strong discriminative ability and the Kalman predictor can track accurately when the target is covered or moves fast. The experimental results show that our multi-target tracking algorithm can track target in occlusion or in fast moving accurately in real time.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"296 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126880105","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}
Xian-xian Ma, X. Zhang, Li-xin Guo, Zhen-wei Ding, Li-long Zhang, S. Wei, Rong Fan, Yuanze Ma
{"title":"An intelligent old-age home endowment monitoring system based on Internet of Things","authors":"Xian-xian Ma, X. Zhang, Li-xin Guo, Zhen-wei Ding, Li-long Zhang, S. Wei, Rong Fan, Yuanze Ma","doi":"10.1109/PIC.2017.8359568","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359568","url":null,"abstract":"The intelligent home old-age service was an important way to solve the problem of current worsening old-age care reality in China[1-2]. An intelligent old-age home endowment monitoring system based on internet of things was proposed in this paper. The system has higher practical value, old-age health condition could be real-time monitored, the alerts could be sent when the unforeseen situation happened to the old man.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131130560","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}