发布求助
文献互助 智能选刊 最新文献

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

筛选
英文 中文
Closed-form Analysis of a Decode-and-Forward Scheme under Physical Layer Security over General Fading Channels 一般衰落信道下物理层安全下的译码转发方案的封闭分析
2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606897
Pham Ngoc Son, Van Phu Tuan, Sol Park, H. Kong
{"title":"Closed-form Analysis of a Decode-and-Forward Scheme under Physical Layer Security over General Fading Channels","authors":"Pham Ngoc Son, Van Phu Tuan, Sol Park, H. Kong","doi":"10.1109/NICS.2018.8606897","DOIUrl":"https://doi.org/10.1109/NICS.2018.8606897","url":null,"abstract":"In this paper, the performance analysis of the decode-and-forward scheme under physical layer security is investigated in the cooperation model where the maximum end-to-end achievable secrecy rate (ASR) is used for selecting the best relay. The system performance is then evaluated by the outage probability of ASR over the general fading channels such as Nakagami-m, Rician and Rayleigh. The cumulative distribution function (CDF) of ASR is obtained in closed-form, and hence, the outage probability is expressed exactly. The Monte-Carlo results are presented to verify the theoretical analysis.","PeriodicalId":137666,"journal":{"name":"2018 5th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"136 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":"127356143","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 review of feature indexing methods for fast approximate nearest neighbor search 快速近似最近邻搜索的特征索引方法综述
2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606853
T. Pham, Van-Hao Le, Dinh-Nghiep Le
{"title":"A review of feature indexing methods for fast approximate nearest neighbor search","authors":"T. Pham, Van-Hao Le, Dinh-Nghiep Le","doi":"10.1109/NICS.2018.8606853","DOIUrl":"https://doi.org/10.1109/NICS.2018.8606853","url":null,"abstract":"Fast feature matching is of crucial importance for time-critical applications in computer vision. The main goal of this work is to provide a comprehensive review of the state-of-the-art approaches dealing with the problem of feature indexing. Crucially, indexing methods can be grouped into four classes, including space partitioning, clustering, hashing, and product quantization. The methods are deeply presented, discussed, and linked to each other. An empirical report of performance analysis is also provided to characterize the studied methods. Lastly, we give comments on possible room of improvements for some indexing schemes.","PeriodicalId":137666,"journal":{"name":"2018 5th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"1 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":"129212267","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
Two new concepts "Picture Fuzzy Rough Soft Sets"and "Picture Fuzzy Dynamic Systems" in Picture Fuzzy Systems 图像模糊系统中的两个新概念“图像模糊粗糙软集”和“图像模糊动态系统”
2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606888
B. Cuong, Pham Huy Thong
{"title":"Two new concepts \"Picture Fuzzy Rough Soft Sets\"and \"Picture Fuzzy Dynamic Systems\" in Picture Fuzzy Systems","authors":"B. Cuong, Pham Huy Thong","doi":"10.1109/NICS.2018.8606888","DOIUrl":"https://doi.org/10.1109/NICS.2018.8606888","url":null,"abstract":"In 2013, B.C. Cuong and V. Kreinovich introduced the concept of picture fuzzy set [1], which is a directly generalization concept of the Zadeh’s fuzzy sets and Atanassov’s intuitionistic fuzzy sets. Picture Fuzzy Sets Theory and Picture Fuzzy Logic [5] was received many developments with applications in computational intelligent problems (see [5] and [9–19]). A combination of picture fuzzy sets with Molodsov’s soft sets [26] are Picture Fuzzy Soft Sets was given in section 5 of [1]. Rough set was introduced by Z. Pawlak in 1982 [4], which becomes a usefully mathematical tool for data mining, especially for redundant and uncertain data. The combination of fuzzy set and rough set theories lead to various models and receive many interesting results. Recently in the NICS 2017 [9] we defined the picture fuzzy rough sets for the soft computing problems. This paper is devoted to the new sets – Picture Fuzzy Rough Soft Sets and the a concept ”Picture Fuzzy Dynamic Systems”, which could be important branches of picture fuzzy systems and applications.","PeriodicalId":137666,"journal":{"name":"2018 5th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"40 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":"123855481","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
Fully Digital Background Calibration Technique for Channel Mismatches in TIADCs tiadc中信道失配的全数字背景校正技术
2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606871
Van-Thanh Ta, Yen Hoang Thi, Han Le Duc, Van‐Phuc Hoang
{"title":"Fully Digital Background Calibration Technique for Channel Mismatches in TIADCs","authors":"Van-Thanh Ta, Yen Hoang Thi, Han Le Duc, Van‐Phuc Hoang","doi":"10.1109/NICS.2018.8606871","DOIUrl":"https://doi.org/10.1109/NICS.2018.8606871","url":null,"abstract":"Time-interleaved analog-to-digital converter (TIADC) is a promising approach to meet the requirement of very high speed wireless communication systems. However, mismatches between the channels in a TIADC cause the spurious images in the output spectrum, thus decreasing its performance. Therefore, efficient correction techniques for these mismatches are highly required. In this paper, we present a fully digital background calibration technique for channel mismatches including offset, gain and timing mismatches in TIADCs using Hadamard transform and average offset mismatch errors. The proposed technique results in the removal of spurious images from the TIADC output spectrum, thus increases the signal-to-noise-and-distortion ratio (SNDR) and spurious-free dynamic range (SFDR). The performance improvement of TIADCs employing this technique is demonstrated through numerical simulations.","PeriodicalId":137666,"journal":{"name":"2018 5th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"40 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":"130012703","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
Invited Talk #2 Vietnamese Neural Language Model for NLP Tasks With Limited Resources 邀请演讲#2越南语神经语言模型在有限资源下的NLP任务
2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606865
Q. T. Tho
{"title":"Invited Talk #2 Vietnamese Neural Language Model for NLP Tasks With Limited Resources","authors":"Q. T. Tho","doi":"10.1109/NICS.2018.8606865","DOIUrl":"https://doi.org/10.1109/NICS.2018.8606865","url":null,"abstract":"A statistical language model is a probability distribution over sequences of words. Language modeling is used in various computing tasks such as speech recognition, machine translation, optical character and handwriting recognition and information retrieval and other applications. Whereas n-gram is considered as a traditional language model, neural language model has been emerging recently as a means to approximate the probability of a sentence using neural networks and word embeddings. An advantage of a neural language model is that it can be further applied to other NLP tasks where the training datasets may be limited. In this talk, we realize this idea by introducing the usage of a Vietnamese neural model language trained from a large corpus of social media data. When further applying this neural model language with other NLP tasks including entity recognition, spam detection and topic modeling with relatively small training datasets; we witness improved performance achieved, as compared to other existing approaches using deep learning with typical word embedding techniques.","PeriodicalId":137666,"journal":{"name":"2018 5th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"31 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":"134267730","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
Occluded Image Recognition with Extended Nonnegative Matrix Factorization 基于扩展非负矩阵分解的遮挡图像识别
2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606869
Viet-Hang Duong, Manh-Quan Bui, Jia-Ching Wang
{"title":"Occluded Image Recognition with Extended Nonnegative Matrix Factorization","authors":"Viet-Hang Duong, Manh-Quan Bui, Jia-Ching Wang","doi":"10.1109/NICS.2018.8606869","DOIUrl":"https://doi.org/10.1109/NICS.2018.8606869","url":null,"abstract":"This paper addresses the challenge of recognizing face and facial expression under occlusion situations. We have introduced an extension of nonnegative matrix factorization called angle and graph constrained nonnegative matrix factorization (AGNRIF). The proposed model is developed in term of minimizing angle of basic cone and preserving the geometrical structure of the projective data. The experimental results in the context of occluded images demonstrate that the technique of enforcing constraints on both basic and encoding matrices works well and the AGNMF method shows superior performance to other conventional NRIF approaches.","PeriodicalId":137666,"journal":{"name":"2018 5th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"43 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":"133916409","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
Deep Learning versus Traditional Classifiers on Vietnamese Students’ Feedback Corpus 越南学生反馈语料库上的深度学习与传统分类器之比较
2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606837
Phu X. V. Nguyen, T. T. T. Hong, Kiet Van Nguyen, N. Nguyen
{"title":"Deep Learning versus Traditional Classifiers on Vietnamese Students’ Feedback Corpus","authors":"Phu X. V. Nguyen, T. T. T. Hong, Kiet Van Nguyen, N. Nguyen","doi":"10.1109/NICS.2018.8606837","DOIUrl":"https://doi.org/10.1109/NICS.2018.8606837","url":null,"abstract":"Student’s feedback is an important source of collecting students’ opinions to improve quality of training activities. Implementing sentiment analysis into student feedback data, we can determine sentiments polarities which express all problems in the institution since changes necessary will be applied to improve the quality of teaching and learning. This study focused on the machine learning and natural language processing techniques (Naive Bayes, Maximum Entropy, Long Short-Term Memory, Bi-Directional Long Short-Term Memory) on the Vietnamese Students’ Feedback Corpus collected from a university. The final results were compared and evaluated to find the most effective model based on different evaluation criteria. The experimental results show that Bi-Directional Long Short-Term Memory algorithm outperformed than three other algorithms in term of the F1-score measurement with 92.0% on the sentiment classification task and 89.6% on the topic classification task. In addition, we developed a sentiment analysis application analyzing student feedback. The application will help the institution to recognize students’ opinions about a problem and identify shortcomings that still exist. With the use of this application, the institution can propose an appropriate method to improve the quality of training activities in the future.","PeriodicalId":137666,"journal":{"name":"2018 5th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"1 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":"131378004","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: 30
Improving the 3D model classification based on selecting proper features 在选择合适特征的基础上改进三维模型分类
2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606830
Nong Thi Hoa, Nguyen Van Tao, Dinh Thi Thanh Uyen
{"title":"Improving the 3D model classification based on selecting proper features","authors":"Nong Thi Hoa, Nguyen Van Tao, Dinh Thi Thanh Uyen","doi":"10.1109/NICS.2018.8606830","DOIUrl":"https://doi.org/10.1109/NICS.2018.8606830","url":null,"abstract":"Classifying 3D models helps to organise databases according to categories. As a result, models are quickly search to recommend models when designing virtual scenes in movies and games. Today, number of 3D models increases sharply and entertainment needs develop quickly. Therefore, classifying 3D models is essential task. Previous studies used many features to improve the accuracy of classifying. It takes a long time for both extracting features and classifying models. In this paper, we select three features and find a suitable classifier to drop the time for computing in classifying 3D models. Proposed features are eigenvalues associated with the principal axes of 3D models. We compare available classifiers to select the best one, Support Vector Machine, to classify models. Experiments are conducted on two benchmark databases including travel means in Princeton Shape Benchmark and animals in Shape Retrieval Contest 2010. Experiment results show our approach is useful for recommendation applications and roughly classifying 3D models.","PeriodicalId":137666,"journal":{"name":"2018 5th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"23 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":"114874086","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
Linguistic barriers to syllogistic reasoning 三段论推理的语言障碍
2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606892
A. Haida, Luka Crnič, Y. Grodzinsky
{"title":"Linguistic barriers to syllogistic reasoning","authors":"A. Haida, Luka Crnič, Y. Grodzinsky","doi":"10.1109/NICS.2018.8606892","DOIUrl":"https://doi.org/10.1109/NICS.2018.8606892","url":null,"abstract":"Experimental studies investigating logical reasoning performance show very high error rates of up to 80% and more. Previous research identified scalar inferences of the sentences of logical arguments as a major error source. We present new analytical tools to quantify the impact of scalar inferences on syllogistic reasoning. Our proposal builds on a new classification of Aristotelian syllogisms and a closely linked classification of reasoning behaviors/strategies. We argue that the variation in error rates across syllogistic reasoning tasks is in part due to individual variation: reasoners follow different reasoning strategies and these strategies play out differently for syllogisms of different classes.","PeriodicalId":137666,"journal":{"name":"2018 5th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"18 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":"122365655","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
Some observations on Vietnamese demonstratives 对越南指示语的几点观察
2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606856
T. Phan, Wei-tien Dylan Tsai
{"title":"Some observations on Vietnamese demonstratives","authors":"T. Phan, Wei-tien Dylan Tsai","doi":"10.1109/NICS.2018.8606856","DOIUrl":"https://doi.org/10.1109/NICS.2018.8606856","url":null,"abstract":"Here we outline some observations concerning the classification and distribution of demonstratives in Vietnamese. We challenge the traditional assumptions in which demonstratives are claimed to be DP-final and demonstratives are all the same. In addition, we propose a way to account for several minimal contrasts displayed by Vietnamese demonstratives and then conclude the paper by discussing some shortcomings of such account.","PeriodicalId":137666,"journal":{"name":"2018 5th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"2 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":"124600166","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
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信