2017 International Conference on Progress in Informatics and Computing (PIC)最新文献_第5页

Gravitational search algorithm combined with modified differential evolution learning for planarization in graph drawing 结合改进差分进化学习的引力搜索算法用于图形绘制中的平面化

2017 International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2017-12-01 DOI: 10.1109/PIC.2017.8359504

Hang Yu, Huisheng Zhu, Huiqin Chen, Dongbao Jia, Yang Yu, Shangce Gao

引用次数: 2

English mispronunciation detection based on improved GOP methods for Chinese students 基于改进GOP方法的中国学生英语发音错误检测

2017 International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2017-12-01 DOI: 10.1109/PIC.2017.8359585

Guimin Huang, Jing Ye, Zhenglin Sun, Ya Zhou, Yan Shen, Ruyu Mo

{"title":"English mispronunciation detection based on improved GOP methods for Chinese students","authors":"Guimin Huang, Jing Ye, Zhenglin Sun, Ya Zhou, Yan Shen, Ruyu Mo","doi":"10.1109/PIC.2017.8359585","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359585","url":null,"abstract":"In this paper, we proposed two approaches to detect mispronunciation in spoken English for Chinese Students which is based on improved Goodness Of Pronunciation (GOP) algorithm. We adopted a modified Maximum Likelihood Linear Regression (MLLR) to adjust the acoustic model which can reduce the mismatch between native original model and adaptive data from non-native speakers. Then we could calculate the ameliorated GOP value to improve the performance of phone-level pronunciation error detection. Besides, as Chinese students are likely to be influenced by their mother tongue in their oral English training, we collected the common pronunciation error patterns of Chinese students by introducing priori linguistic knowledge and established a phonemes set that are easy to confuse for optimizing the GOP probability space. The mispronunciation detection system with the above ways could review input speech and detect the flawed phone to allow the non-native learners to correct the mispronunciation duly. The experimental results suggested that the modified GOP method reached good effect of English pronunciation error detection for Chinese students.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"104 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":"124062688","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

3D model reconstruction based on plantar image's feature segmentation 基于足底图像特征分割的三维模型重建

2017 International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2017-12-01 DOI: 10.1109/PIC.2017.8359535

M. Zhang, Zhenning Zhang, Weiqing Li

引用次数: 1

Maximizing bichromatic reverse k nearest neighbor with multi-level tags queries in spatial-textual databases 利用空间文本数据库中的多层次标签查询最大化双色逆k近邻

2017 International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2017-12-01 DOI: 10.1109/PIC.2017.8359553

Chengyuan Zhao, Yongli Wang, Xiaohui Jiang, Chi Yuan, Yanchao Li, Isma Masood

{"title":"Maximizing bichromatic reverse k nearest neighbor with multi-level tags queries in spatial-textual databases","authors":"Chengyuan Zhao, Yongli Wang, Xiaohui Jiang, Chi Yuan, Yanchao Li, Isma Masood","doi":"10.1109/PIC.2017.8359553","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359553","url":null,"abstract":"With the popularity of mobile smart devices, location-based services have been more widely used. Bichromatic Reverse k Nearest Neighbor (BRkNN) queries have become a hotspot in spatial-textual databases domain. In this paper, we extend the concept of traditional BRkNN method to process the object with multi-level tags in some specific scenes, and we propose a new type of query, called Maximized Bichromatic Reverse k Nearest Neighbor with Multi-Level Tags queries (MaxBRkNN-MLT), to find the optimal position of object with multi-level tags in the spatial-textual database. Unlike traditional methods, the number of the results of the MaxBRkNN-MLT query is maximized, which can cross the great divide between space and text. The query method proposed in this paper has a wide range of application scenes. For example, in the advertising industry, advertisers expect to find an optimal position, so that the ads with a given tag can attract the most users. Finally, experiments show that the MLT method has better query precision and execution efficiency than the baseline approach.","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":"129146542","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

A random chemical reaction algorithm based on double containers for robot path planning 基于双容器的机器人路径规划随机化学反应算法

2017 International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2017-12-01 DOI: 10.1109/PIC.2017.8359581

Qing Yang, Zhong Yang, Guoxiong Hu, Wei Du

引用次数: 0

Underfloor heating users prediction based on SVDD 基于SVDD的地暖用户预测

2017 International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2017-12-01 DOI: 10.1109/PIC.2017.8359587

Xingguang Yang, Huiqun Yu, Jianmei Guo, Guisheng Fan, Kai Shi

引用次数: 0

Kernelized convex hull for visual tracking 用于视觉跟踪的核化凸包

2017 International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2017-12-01 DOI: 10.1109/PIC.2017.8359534

Jun Wang, Yuanyun Wang, Chengzhi Deng, Shengqian Wang

引用次数: 0

Scalable stream Bayes classification based on Dirichlet prior 基于Dirichlet先验的可扩展流贝叶斯分类

2017 International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2017-12-01 DOI: 10.1109/PIC.2017.8359593

O. Bina, Yuan Yanhua

引用次数: 0

A comparison study of outpatient visits forecasting effect between ARIMA with seasonal index and SARIMA 带季节指数的ARIMA与SARIMA预测门诊就诊效果的比较研究

2017 International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2017-12-01 DOI: 10.1109/PIC.2017.8359573

Zhang Xinxiang, Zhou Bo, Fu Huijuan

{"title":"A comparison study of outpatient visits forecasting effect between ARIMA with seasonal index and SARIMA","authors":"Zhang Xinxiang, Zhou Bo, Fu Huijuan","doi":"10.1109/PIC.2017.8359573","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359573","url":null,"abstract":"This paper delineates a case study analyzing and forecasting of the outpatient visits frequency of a hospital in Zhengzhou, China. By evaluating the annual out-patient data throughout the year of 2015, this paper applies the “Day” as timescale and carries out the experiment so as to forecast the number of visiting patients with the impact of the “Week” taken into consideration. Two models are used separately: the Autoregressive Integrated Moving Average (ARIMA) with seasonal index and the Seasonal Autoregressive Integrated Moving Average (SARIMA). Based on the empirical findings from the comparison of the fitting effect and forecasting effect of the above two models, it is clear that SARIMA reaches a satisfactory outcome: it displays optimum indexes. Therefore it is preferable to deploy the SARIMA model to proceed a forecasting of outpatient visits for medical institutions. Meanwhile the paper also aims to provide management of medical institution with theory grounds of working and personnel arrangement and insight so as to make a prompt and reasonable contingency plan when it comes to sudden disease.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"23 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":"121957656","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: 9

Pseudo-inverse locality preserving iterative hashing 伪逆保局域迭代哈希

2017 International Conference on Progress in Informatics and Computing (PIC) Pub Date : 2017-12-01 DOI: 10.1109/PIC.2017.8359569

Zhong-Hua Du, Yongli Wang, H. Sun

{"title":"Pseudo-inverse locality preserving iterative hashing","authors":"Zhong-Hua Du, Yongli Wang, H. Sun","doi":"10.1109/PIC.2017.8359569","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359569","url":null,"abstract":"Hashing learning has attracted increasing attention these years with the rapid increase of data. Some high-dimensional data have caused the ‘dimension disaster’ which make traditional methods ineffective. In this paper, we propose a method to find the nearest neighbor quickly from the high-dimensional data, named pseudo-inverse locality preserving iterative hashing(PLIH). We use pseudo-inverse to replace the inverse matrix in order to solve the problem of matrix singularity. We construct adjacency graphs and minimize the distance of the neighbors in the subspace to make the projected matrix maintain the neighborhood relations of high dimension, which solves the problem that the locality sensitive hashing cannot preserve the high-dimensional neighborhood relations effectively. Because different bit with different weight has more discriminating power than the same weight, Loss of the projection matrix in the quantization process is minimized by weighted iterative quantization. Experiments on public datasets Cnn_4096d_Caltech and Gist_512d_Caltech demonstrated that accuracy and recall of the PLIPH are both better than the traditional hashing algorithms.","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":"126633480","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