发布求助
文献互助 智能选刊 最新文献

2020 7th NAFOSTED Conference on Information and Computer Science (NICS)最新文献

筛选
英文 中文
Real-time Online Learning for Pattern Reconfigurable Antenna State Selection 模式可重构天线状态选择的实时在线学习
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335872
Xaime Rivas Rey, G. Mainland, K. Dandekar
{"title":"Real-time Online Learning for Pattern Reconfigurable Antenna State Selection","authors":"Xaime Rivas Rey, G. Mainland, K. Dandekar","doi":"10.1109/NICS51282.2020.9335872","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335872","url":null,"abstract":"Pattern reconfigurable antennas (PRAs) can dynamically change their radiation pattern and provide diversity and directional gain. These properties allow them to adapt to channel variations by steering directional beams toward desired transmissions and away from interference sources, thus enhancing the overall performance of a wireless communication system. To fully exploit the benefits of a PRA, the key challenge is being able to optimally select the antenna state in real time. Current literature on this topic, to the best of our knowledge, focuses on the design of algorithms to optimally select the best antenna mode with evaluation performed in simulation or postprocessing. In this study, we have not only designed a real-time online antenna state selection framework for SISO wireless links but we have also implemented it in an experimental software defined radio testbed. We benchmarked the multi-armed bandit algorithm against other antenna state selection algorithms and show how it can improve system performance by mitigating the effects of interference taking advantage of the directionality PRAs provide. We also show that when the optimal state changes over time the bandit approach does not work very well. For such a scenario, we show how the Adaptive Pursuit algorithm works well and can be a great solution. We also discuss what changes could be done to the bandit algorithm to work better in this case.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121795617","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
An Alternative Lightness Control with GAN for Augmenting Camera Data 一种用于增强相机数据的GAN亮度控制方法
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335862
Tan Phan, D. Nguyen
{"title":"An Alternative Lightness Control with GAN for Augmenting Camera Data","authors":"Tan Phan, D. Nguyen","doi":"10.1109/NICS51282.2020.9335862","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335862","url":null,"abstract":"To build an autonomous car, many technologies have to be taken into application. The most important component of a fully self-driving car is the object detection system. This system is responsible for detecting obstacles on the street. However, these detection models still face many difficulties such as unable to work on extreme conditions (storm, night, chaotic road,…). To tackle one aspect of this problem, in this paper we propose an augmentation method that creates more data by generating night images from day images and vice versa using LCcycleGAN, a Lightness conditional Unpaired Image-to-Image Translation approach, this framework is the fusion of CycleGAN [1] and conditional GAN [2]. To evaluate our method, we measure performance of YoloV3 [3] on our collected dataset (and augmented data) consists of day and night images of Vietnamese streets which are often highly chaotic and extreme. Our method increases AP of base vehicle detection model's performance from 0.5 to 0.56.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115379659","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
Sentiment Analysis Implementing BERT-based Pre-trained Language Model for Vietnamese 基于bert的越南语预训练语言模型的情感分析
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335912
Trong-Loc Truong, Hanh-Linh Le, Thien-Phuc Le-Dang
{"title":"Sentiment Analysis Implementing BERT-based Pre-trained Language Model for Vietnamese","authors":"Trong-Loc Truong, Hanh-Linh Le, Thien-Phuc Le-Dang","doi":"10.1109/NICS51282.2020.9335912","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335912","url":null,"abstract":"Continuous Improvement Process Model contributes effectively to the educational development of any school. Sentiment analysis of student feedback is a step in this model to find suitable solutions to enhance the performance of instructors and the quality of material facilities. However, most of the state-of-the-art sentiment classification models only focus on English, by which some disadvantages in Vietnamese researches are brought on. We study a sentiment analysis model using PhoBERT pre-trained model for Vietnamese, which is a robust optimization for Vietnamese of the prominent BERT model. We then employ alternative fine-tuning techniques to generalize the model for multi-class classification other than the binary task. Our method achieves state-of-the-art results on the UIT-VSFC dataset with an F1-score of 93.92% and an accuracy of 94.28%. This is expected to be helpful for the improvement of Vietnam's education and set the foundation for researching in Vietnamese which is the language that lacks resources.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129230801","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: 7
Jointly Optimized Cache Control and Energy Efficiency for Downlink Cellular Networks 下行蜂窝网络缓存控制与能量效率联合优化
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335908
Tat Dat Nguyen, Phuc Truong Quang, Tan Do-Duy, Hoc Phan
{"title":"Jointly Optimized Cache Control and Energy Efficiency for Downlink Cellular Networks","authors":"Tat Dat Nguyen, Phuc Truong Quang, Tan Do-Duy, Hoc Phan","doi":"10.1109/NICS51282.2020.9335908","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335908","url":null,"abstract":"In this paper, we propose an optimal scheme for solving the joint cache control and energy efficiency optimization problem for the downlink transmission in a backhaul cellular network. The first short-term subproblem is aimed at finding the optimal beamforming matrices at the hub and BSs to maximize the energy efficiency for the scenario where the network operates in the non-caching mode. The second short-term subproblem is aimed at solving the optimal beamforming matrices at the base stations (BSs) to maximize the energy efficiency for the scenario where the network operates in the caching mode. On the other hand, the goal of the long-term subproblem is to maximize the long-term energy efficiency of the examined network. Finally, numerical results show that the proposed cache control and energy efficiency optimization scheme provides significant performance improvement over the conventional non-caching schemes.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132181558","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 Web-based Tool for Semi-interactively Karyotyping the Chromosome Images for Analyzing Chromosome Abnormalities 基于web的染色体图像半交互核型分析工具，用于分析染色体异常
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335893
N. H. Thinh, Nguyen Huu Hoang Son, Pham Thi Viet Huong, Nguyen Thi Cuc Nhung, Do Thi Ram, Nguyen Thanh Binh Minh, Luu Manh Ha
{"title":"A Web-based Tool for Semi-interactively Karyotyping the Chromosome Images for Analyzing Chromosome Abnormalities","authors":"N. H. Thinh, Nguyen Huu Hoang Son, Pham Thi Viet Huong, Nguyen Thi Cuc Nhung, Do Thi Ram, Nguyen Thanh Binh Minh, Luu Manh Ha","doi":"10.1109/NICS51282.2020.9335893","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335893","url":null,"abstract":"Chromosome abnormalities relate to several genetic diseases. These abnormalities can be diagnosed based on the analysis of karyogram of the human chromosomes. However, the manual chromosome karyotyping process is often time consuming. This paper presents a novel web-based tool, Biochrom, to assist the cytogeneticist in producing the karyogram. Biochrom is a semi-automated tool, which provides both manual and automated functions in chromosomes segmentation and classification using image processing combined with machine learning techniques. The study is carried on 612 metaphase images with 48 of those containing abnormal chromosomes. We compare the proposed tool to a conventional public tool, Metasel, for karyotyping based on performance by two cytogeneticists using user experience metrics such as number of manual interactions and processing time. Moreover, we quantitatively evaluate the accuracy of the classification of two approaches: Support Vector Machine (SVM) and deep learning. The evaluation results show that the deep learning classification outperforms SVM classification, and our proposed tool requires fewer interactions and less time consuming to complete the karyotyping task on average.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130665587","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
On an improvement of Graph Convolutional Network in semi-supervised learning 图卷积网络在半监督学习中的改进
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335914
M. Ngo, An Mai, Thanh Bui
{"title":"On an improvement of Graph Convolutional Network in semi-supervised learning","authors":"M. Ngo, An Mai, Thanh Bui","doi":"10.1109/NICS51282.2020.9335914","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335914","url":null,"abstract":"Nowadays, we can easily face with many real-world datasets having the form of graphs, such as social networks, knowledge-based graphs, protein-interaction networks, the World Wide Web, etc., while there was still lack of in-depth research on the generalization of neural network models to such structured datasets. Hopefully, in the last few years, a plenty of encouraging results devoted to generate neural networks to work on arbitrarily structured graphs. Among them, it can be seen an important scalable approach of Kipf and Welling in 2016, which employs an efficient variant of convolutional neural networks for semi-supervised learning on graph-structured data. The experimental results applied for citation networks and on a knowledge graph dataset show that their proposed approach can outperform all related methods by a significant margin. In this paper, we present an adaptive approach for semi-supervised learning on graph-structured data that is also based on an efficient variant of convolutional neural networks which improves the pilot work of Kipf and Welling. In a number of separated experiments on citation networks datasets (Citeseer, Cora, Pubmed), we demonstrate that our approach is able to outperform the baseline graph convolutional network (GCN).","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116338256","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
Prediction of Forest Fire Risk to Trigger IoTs Reconfiguration Action 森林火灾风险预测触发物联网重构行动
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335854
Tuan Nguyen-Anh, Quan Le-Trung
{"title":"Prediction of Forest Fire Risk to Trigger IoTs Reconfiguration Action","authors":"Tuan Nguyen-Anh, Quan Le-Trung","doi":"10.1109/NICS51282.2020.9335854","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335854","url":null,"abstract":"Nowadays, the ever-increasing demand for IoT nodes for adapting to changing environment conditions and application requirements rapidly raising the need of reconfiguring already existing IoTs nodes. Forest fires is one of the main causes of environmental degradation and its detection and prediction is a challenge, a case study of predicting IoTs reconfiguration. Each prediction algorithm has its own advantages and disadvantages, which lead to different predictive results for each specific IoT application reconfiguration behavior. It is important to determine which set of metrics are effective for predicting. The objective of this work is to choose the most suitable prediction algorithms for detection of Forest Fire Risk for trigger IoTs reconfiguration actions. In this work, a comparative study between various prediction algorithms is carried out. The performance metric is based on the accuracy, precision, recall, and the training time. The experimental results show that Feedforward Neural Network is the most accurate that gives a good prediction accuracy.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"30 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123206196","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
Social constraints-based socially aware navigation framework for mobile service robots 基于社会约束的移动服务机器人社会感知导航框架
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335878
Van Bay Hoang, V. Nguyen, L. A. Nguyen, T. D. Quang, Xuan-Tung Truong
{"title":"Social constraints-based socially aware navigation framework for mobile service robots","authors":"Van Bay Hoang, V. Nguyen, L. A. Nguyen, T. D. Quang, Xuan-Tung Truong","doi":"10.1109/NICS51282.2020.9335878","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335878","url":null,"abstract":"In this paper, we propose a social timed elastic band (STEB)-based navigation framework which enables a mobile service robot to safely and socially avoid a human in dynamic social environments. The main idea of the proposed framework is to incorporate the socio-spatio-temporal characteristics of the humans including human position, motion related to the robot, and social rules into a conventional online trajectory planing algorithm. We evaluate the developed framework through a series of simulation experiments. The simulation results show that the proposed framework is fully capable of autonomously driving the mobile robot to avoid the individual humans in dynamic social environments, providing the safety and comfort for the humans and the socially acceptable behaviours for the mobile robot.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128881609","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
Uplink non-orthogonal multiple access protocol in two-way relaying networks: realistic operation and performance analysis 双向中继网络中的上行非正交多址协议:现实运行与性能分析
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335902
Thu-Thuy Thi Dao, Pham Ngoc Son
{"title":"Uplink non-orthogonal multiple access protocol in two-way relaying networks: realistic operation and performance analysis","authors":"Thu-Thuy Thi Dao, Pham Ngoc Son","doi":"10.1109/NICS51282.2020.9335902","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335902","url":null,"abstract":"In this paper, we study a two-way non-orthogonal multiple access cooperative schemes with two sources and the aid of a decode-and-forward relay under the overall effects of perfect/imperfect successive interference cancellation and perfect/imperfect channel state information. In this scheme, the digital network coding technique is used at the relay to decrypt sequentially the received data from sources, then encode these data by the XOR operation and transmit back to the sources. System performance in terms of outage probabilities and throughput is analyzed by exact and asymptotic closed-form expressions. Besides, the proposed protocol performance is compared to the performance of a conventional two-way scheme. The Monte Carlo simulation results evidence the validity of the analysis expressions.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129349304","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
Generating test data for energy property in mobile applications 在移动应用程序中生成能量属性的测试数据
2020 7th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2020-11-26 DOI: 10.1109/NICS51282.2020.9335868
A. Bui, Van-Viet Nguyen, Ninh-Thuan Truong
{"title":"Generating test data for energy property in mobile applications","authors":"A. Bui, Van-Viet Nguyen, Ninh-Thuan Truong","doi":"10.1109/NICS51282.2020.9335868","DOIUrl":"https://doi.org/10.1109/NICS51282.2020.9335868","url":null,"abstract":"In recent years, mobile software has been rapidly developing. The key requirement of mobile software is to ensure optimum power throughout its run. Unlike testing other software properties, energy testing is usually done on real devices to check actual energy consumption. As such, testers need to have optimal test data to save time and effort in testing. In this paper, we propose an approach to automatically generating test data in mobile software testing, concentrate on energy properties. The approach, firstly, builds CFGs (Control Flow Graph) from the source code of the application. We then propose algorithms to select testable paths from CFG such that the mobile applications consume more energy. Finally, test data are generated from the testable paths.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"21 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129753262","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
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