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Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence最新文献

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Sentimental Analysis of Chinese New Social Media for stock market information 中国新社交媒体对股市信息的情感分析
Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence Pub Date : 2019-08-26 DOI: 10.1145/3357777.3357778
Guanhang Chen, Lilin He, Konstantinos Papangelis
{"title":"Sentimental Analysis of Chinese New Social Media for stock market information","authors":"Guanhang Chen, Lilin He, Konstantinos Papangelis","doi":"10.1145/3357777.3357778","DOIUrl":"https://doi.org/10.1145/3357777.3357778","url":null,"abstract":"The popularity of social media provides a new platform to collect big social data. With the development of social sentiment analysis, high business value extracted from social data are applied to various fields. Asset price prediction, as an emerging topic based on the behavioral economics, is closely linked to social data analysis. This research aims to explore the effort of sentiment analysis data in the prediction of China composite index. Data from Sina Weibo and financial community is processed to get the useful sentiment information. A linear regression model and a multilayer neural network algorithm are used to prove the relationship between social data and price market prediction. The experiments show a strong relationship between the numbers of negative sentiment and a multilayer perceptron model is effectively built to predict the composite index.","PeriodicalId":127005,"journal":{"name":"Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132312740","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
A Neural Network Model of the NBA Most Valued Player Selection Prediction NBA最有价值球员评选预测的神经网络模型
Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence Pub Date : 2019-08-26 DOI: 10.1145/3357777.3357786
Yuefei Chen, Junyan Dai, Changjiang Zhang
{"title":"A Neural Network Model of the NBA Most Valued Player Selection Prediction","authors":"Yuefei Chen, Junyan Dai, Changjiang Zhang","doi":"10.1145/3357777.3357786","DOIUrl":"https://doi.org/10.1145/3357777.3357786","url":null,"abstract":"This study analyzed all the performance of the players in the National Basketball Association (NBA) during a particular season and predicted the most valued players (MVP) of that season. The NBA game is the most popular basketball game all over the world. Every game attracted hundreds of and thousands of audiences and fans. Some fans supported the specific teams and many of fans supported some specific players in these teams. When they want to observe the performance of their preferred basketball stars and determine whether they can be awarded as the most valued player in the current season. Our study can help answer this question. We developed a novel NBA MVP prediction system with the neural network. We trained and tested this neural network using each season performances of NBA players from 1997 to 2019. These features of inputs are specific and optimized with training results. Based on our model, we randomly chose testing dataset from season 2009-2010 and season 2016-2017, and successfully predicted that the most valued players of the chosen seasons are LeBron James(season 2009-2010) and Russell Westbrook(season 2016-2017).","PeriodicalId":127005,"journal":{"name":"Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126239204","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: 5
Generating Artificial Images by Generative Adversary Network 生成对抗网络生成人工图像
Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence Pub Date : 2019-08-26 DOI: 10.1145/3357777.3357794
Yunhao Zhang, Yanxin Zhou, Ching-Yu Huang
{"title":"Generating Artificial Images by Generative Adversary Network","authors":"Yunhao Zhang, Yanxin Zhou, Ching-Yu Huang","doi":"10.1145/3357777.3357794","DOIUrl":"https://doi.org/10.1145/3357777.3357794","url":null,"abstract":"This paper presents a case study of the structure, generative adversary network (GAN). The primary goal of this project is to apply the concept of GAN (Generative Adversary Network) to generate a group of artificial images with same theme, which are expected to give a realistic view to human eyes in final stage. This independent research mainly focuses on basic structure of GAN and the improvement of its quality via implementing a variation, DCGAN. Thus, it can offer solid foundations and help to our team to focus on exploring a possibility of this fair new technology.","PeriodicalId":127005,"journal":{"name":"Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121247597","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
Modifying FCM with grids and density peaks 用网格和密度峰修改FCM
Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence Pub Date : 2019-08-26 DOI: 10.1145/3357777.3357783
Renxia Wan, Weiqi Wang
{"title":"Modifying FCM with grids and density peaks","authors":"Renxia Wan, Weiqi Wang","doi":"10.1145/3357777.3357783","DOIUrl":"https://doi.org/10.1145/3357777.3357783","url":null,"abstract":"In this paper, we modify the FCM algorithm with grids and density peaks. We apply the density peak clustering algorithm mixed with grid technology to determine the initial clustering positions of FCM. We also use cluster cores instead of cluster centroids, so that the modified algorithm can effectively discover arbitrary shape clusters. Experimental results show that the performance of the proposed algorithm is found to be superior to its ECTs.","PeriodicalId":127005,"journal":{"name":"Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115167566","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
Ghanaian Sign Language Recognition Using Deep Learning 使用深度学习的加纳手语识别
Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence Pub Date : 2019-08-26 DOI: 10.1145/3357777.3357784
L. K. Odartey, Yonfeng Huang, Effah E. Asantewaa, P. Agbedanu
{"title":"Ghanaian Sign Language Recognition Using Deep Learning","authors":"L. K. Odartey, Yonfeng Huang, Effah E. Asantewaa, P. Agbedanu","doi":"10.1145/3357777.3357784","DOIUrl":"https://doi.org/10.1145/3357777.3357784","url":null,"abstract":"Sign Languages, unlike natural languages, involve the use of continuous gestures, body languages, facial expressions and hand movements to convey meaning and most importantly express a signer's thoughts more effectively. Ghanaian Sign Language is the standard sign language used by the deaf in Ghana with a substantial difference to other sign languages as well as cultural conditions that led to its emergence. In this paper, we proposed and implemented a novel yet deep convolutional neural network to classify and recognize Ghanaian Sign Language and attained an accuracy of 96.0%. Further, we leveraged transfer learning techniques by fine-tuning state-of-the-art network architectures pre-trained on the ImageNet database and improved the accuracy with a reported increase of 3.1%. There was no large publicly Ghanaian Sign Language dataset available, so we created our own dataset for evaluation of the proposed convolutional neural network architecture. Conclusively, we plan of extending the dataset with a view of releasing it in the future, subsequently, allowing researches to apply changes to the dataset using image processing and computer vision tools and techniques they consider can be applicable for their task at hand.","PeriodicalId":127005,"journal":{"name":"Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence","volume":"197 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133201933","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: 5
An Intelligent LEGO Tutoring System for Children with Autism Spectrum Disorder 自闭症谱系障碍儿童智能乐高辅导系统
Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence Pub Date : 2019-08-26 DOI: 10.1145/3357777.3357795
Qiming Sun, Pinata Winoto1
{"title":"An Intelligent LEGO Tutoring System for Children with Autism Spectrum Disorder","authors":"Qiming Sun, Pinata Winoto1","doi":"10.1145/3357777.3357795","DOIUrl":"https://doi.org/10.1145/3357777.3357795","url":null,"abstract":"Prior studies have shown the effectiveness of LEGO-based activities to improve children's social skills, especially those with autism spectrum disorder (ASD). In such activities, teachers are expected to provide instructions/guidance and facilitate communication among children during their collaborative play. When the ratio of children to teacher increases, an intelligent monitoring system could be very helpful to prompt the teachers of any necessary intervention, or to provide children some trivial feedback so that their teachers could focus on other tasks. In this paper, we propose such a system to assist both teachers and children in playing with LEGO bricks. At first, teachers may use the system to create some models. The system will then generate step-by-step instructions in both visual and auditory forms. In addition, the system can track the children's brick-building process in real time and provide some feedback when any mistakes were made. Two cameras with a unique image recognition module are used to capture the 3D structure of LEGO bricks.","PeriodicalId":127005,"journal":{"name":"Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130314494","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
Power Load Forecasting Based on the Combined Model of LSTM and XGBoost 基于LSTM和XGBoost组合模型的电力负荷预测
Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence Pub Date : 2019-08-26 DOI: 10.1145/3357777.3357792
Chen Li, Zhenyu Chen, Jinbo Liu, Dapeng Li, Xingyu Gao, Fangchun Di, Lixin Li, Xiaohui Ji
{"title":"Power Load Forecasting Based on the Combined Model of LSTM and XGBoost","authors":"Chen Li, Zhenyu Chen, Jinbo Liu, Dapeng Li, Xingyu Gao, Fangchun Di, Lixin Li, Xiaohui Ji","doi":"10.1145/3357777.3357792","DOIUrl":"https://doi.org/10.1145/3357777.3357792","url":null,"abstract":"Accurate power load forecasting can provide effective and reliable guidance for power construction and grid operation, and plays a very important role in the power grid system. In order to improve the accuracy of power load forecasting, this paper proposes a combined forecast model based on LSTM and XGBoost. The LSTM forecast model and the XGBoost forecast model are firstly established and the power load is predicted by using the two models respectively. Then the combined model predicts the power load by using the error reciprocal method to combine the results from the two single models. Through the experimental verification of the power load data of The Electrician Mathematical Contest in Modeling, the forecast error of the combined model we got is 0.57%, which is significantly lower than the single forecast model.","PeriodicalId":127005,"journal":{"name":"Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115358705","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: 22
Virtual simulation of glue coating training for industrial robots 工业机器人涂胶训练的虚拟仿真
Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence Pub Date : 2019-08-26 DOI: 10.1145/3357777.3357785
Liang Zhang, Xinming Gu, Bin Shen
{"title":"Virtual simulation of glue coating training for industrial robots","authors":"Liang Zhang, Xinming Gu, Bin Shen","doi":"10.1145/3357777.3357785","DOIUrl":"https://doi.org/10.1145/3357777.3357785","url":null,"abstract":"Industrial robot glue coating training course is an intermediate operation course in industrial robot training course. Due to the limitation of training venues and operating equipment, the effect of using actual equipment for initial training is not ideal. With the rapid development of virtual reality technology, virtual simulation technology has been widely used in industrial production. Therefore, this paper studies the simulation technology of gluing training for industrial robots. This paper uses Unity3D as the system development platform, uses Solidworks software to complete three-dimensional modeling, 3DMAX software to complete model rendering and animation production. Based on virtual reality technology, this paper studies a simple virtual spraying system, which is very helpful to the preview work before the actual learning. In this paper, SolidWorks is used to build the machine arm model and various spraying scenes, and the established three-dimensional model is imported into the rendering process of 3D MAX to generate FBX files. Then, this paper imports the model into Unity3D to load. Finally, this paper chooses Unity3D as the development platform of the simulation system. Through the understanding of the virtual simulation situation at home and abroad and the user's demand for the simulation system of automatic virtual painting equipment, how to choose and develop the virtual painting simulation system is worked out.","PeriodicalId":127005,"journal":{"name":"Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114766766","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
CVAE-Attention: CVAE based Semi-Supervised Sentiment Classification using Attention CVAE-Attention:基于CVAE的使用注意力的半监督情感分类
Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence Pub Date : 2019-08-26 DOI: 10.1145/3357777.3357780
Jifang Yu, Jiangqin Wu, Baogang Wei, Yuanyuan Liu
{"title":"CVAE-Attention: CVAE based Semi-Supervised Sentiment Classification using Attention","authors":"Jifang Yu, Jiangqin Wu, Baogang Wei, Yuanyuan Liu","doi":"10.1145/3357777.3357780","DOIUrl":"https://doi.org/10.1145/3357777.3357780","url":null,"abstract":"Text sentiment classification is an important domain in NLP, and the related technical research has been mature. The sentiment classification of text with the \"but\" contrastive marker is a challenging problem. In this paper, a semi-supervised framework based on conditional variational autoencoder using attention, called CVAE-Attention, is proposed for sentiment classification. In the CVAE-Attention framework, the attention mechanism is introduced to cope with the contrastive structure. The latent semantic information of the clause after \"but\" (but-clause) is extracted through the attention model, and is incorporated into the generative model to enlarge the effect of the but-clause. Experiments show that the proposed method is effective compared with other state-of-the-art semi-supervised methods.","PeriodicalId":127005,"journal":{"name":"Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123231368","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
Safety monitoring of power industrial control terminals based on data cleaning 基于数据清洗的电力工业控制终端安全监测
Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence Pub Date : 2019-08-26 DOI: 10.1145/3357777.3357781
Zhining Lv, Ziheng Hu, Baifeng Ning, Wei Li, Gangfeng Yan, Lifu Ding, Xiasheng Shi, Ningxuan Guo
{"title":"Safety monitoring of power industrial control terminals based on data cleaning","authors":"Zhining Lv, Ziheng Hu, Baifeng Ning, Wei Li, Gangfeng Yan, Lifu Ding, Xiasheng Shi, Ningxuan Guo","doi":"10.1145/3357777.3357781","DOIUrl":"https://doi.org/10.1145/3357777.3357781","url":null,"abstract":"Stable and high-quality electric energy is the main driving force for the development of social science, technology, and the national economic leap. The assessment and monitoring of electrical safety rely on the generation, collection and statistics of large amounts of data by the power system. For the possible problems and impurities in these data, this paper uses the 'local Chebyshev theorem' and the 'near data averaging method' for the attribute values. The error is cleaned, and the 'sorting neighbor algorithm' is used to clean the duplicate data, thereby improving the data quality and realizing the accuracy of the safety monitoring of the power grid of the smart grid.","PeriodicalId":127005,"journal":{"name":"Proceedings of the 2019 the International Conference on Pattern Recognition and Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129432127","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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