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2018 5th NAFOSTED Conference on Information and Computer Science (NICS)最新文献

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Performance Comparison of Indoor Positioning Schemes Exploiting Wi-Fi APs and BLE Beacons 利用Wi-Fi ap和BLE信标的室内定位方案性能比较
2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606852
Younguk Yun, Jeongpyo Lee, Deock-hyeon An, Sangsoo Kim, Youngok Kim
{"title":"Performance Comparison of Indoor Positioning Schemes Exploiting Wi-Fi APs and BLE Beacons","authors":"Younguk Yun, Jeongpyo Lee, Deock-hyeon An, Sangsoo Kim, Youngok Kim","doi":"10.1109/NICS.2018.8606852","DOIUrl":"https://doi.org/10.1109/NICS.2018.8606852","url":null,"abstract":"In this paper, we compare the performance of the positioning scheme exploiting between Wi-Fi and Bluetooth low-energy (BLE) beacons for indoor environments. We use the received signal strength (RSS) of the wireless device and analyze the accuracy of estimated position by using the weighted centroid localization technique. For a comparison trough experiments, we developed an Android-based smartphone application to collect both Wi-Fi and BLE RSS simultaneously at the same smart-phone. Experiments were conducted on the 6th floor of the general office building and both schemes were compared at 8 points in 16m × 7m space. According to the experimental results, it is shown that the performance between Wi-Fi and BLE can be different with respect to the density as well as the deployment of Wi-Fi APs and BLE beacons.","PeriodicalId":137666,"journal":{"name":"2018 5th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127646999","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
A Comparative Study of Neural Network Models for Sentence Classification 神经网络模型在句子分类中的比较研究
2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-10-03 DOI: 10.1109/NICS.2018.8606879
Hong Phuong Le, Anh-Cuong Le
{"title":"A Comparative Study of Neural Network Models for Sentence Classification","authors":"Hong Phuong Le, Anh-Cuong Le","doi":"10.1109/NICS.2018.8606879","DOIUrl":"https://doi.org/10.1109/NICS.2018.8606879","url":null,"abstract":"This paper presents an extensive comparative study of four neural network models, including feed-forward networks, convolutional networks, recurrent networks and long short-term memory networks, on two sentence classification datasets of English and Vietnamese text. We show that on the English dataset, the convolutional network models without any feature engineering outperform some competitive sentence classifiers with rich hand-crafted linguistic features. We demonstrate that the GloVe word embeddings are consistently better than both Skip-gram word embeddings and word count vectors. We also show the superiority of convolutional neural network models on a Vietnamese newspaper sentence dataset over strong baseline models. Our experimental results suggest some good practices for applying neural network models in sentence classification.","PeriodicalId":137666,"journal":{"name":"2018 5th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124512266","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: 13
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