2018 5th NAFOSTED Conference on Information and Computer Science (NICS)最新文献_第2页

Building a Spelling Checker for Documents in Khmer Language 建立高棉语文档的拼写检查器

2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606850

Tran Van Nam, Nguyễn Thị Huệ, P. Khanh

{"title":"Building a Spelling Checker for Documents in Khmer Language","authors":"Tran Van Nam, Nguyễn Thị Huệ, P. Khanh","doi":"10.1109/NICS.2018.8606850","DOIUrl":"https://doi.org/10.1109/NICS.2018.8606850","url":null,"abstract":"The practice of Khmer language teaching at Tra Vinh University shows that students often deal with many difficulties when making reports on subjects of Khmer language. The need to print, edit Khmer text with MS Word by using conventional typing on the ASCII keyboard and the Unicode fonts available made students have many spelling errors, ranging from syllable level to vocabulary level, the syntax of the sentence. Students have not correctly identified the various syllables in word structures, encountered errors in pronunciation and spellings in Khmer. In fact, Khmer-Vietnamese community in Vietnam has few people, scattered, culturally and economically limited. Moreover, Khmer writing system is complex, from the rich alphabet to the multi-syllable structure of the syllable, with no whitespace separated from the sentences. There are many borrowed words which have changed much from the spoken words in Cambodian origins, so the users face many difficulties. These reasons have been a major obstacle in the process of dealing with Khmer language in Vietnam. So far, there have been no solutions to meet the demand for spelling checking in the Khmer scripts. Based on the actual analysis of the students' common misspellings, it can be proposed a solution to the application of the syllable model, the syllabus processing algorithm using the Khmer vocabulary that has been authored by the authors. Previously built KSC (KhmerSpellChecker), an automatic spell checker, integrated into MS Word, helps learners to compose Khmer texts. The approach is feasible. KSC was installed and test results were tested by Khmer language experts at Tra Vinh University for high accuracy.","PeriodicalId":137666,"journal":{"name":"2018 5th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"35 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":"122162300","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 effective implementation of Gaussian of Gaussian descriptor for person re-identification 一种有效实现高斯描述符的人再识别方法

2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606858

Thuy-Binh Nguyen, Duc-Long Tran, Thi-Lan Le, Thi Thanh Thuy Pham, H. Doan

{"title":"An effective implementation of Gaussian of Gaussian descriptor for person re-identification","authors":"Thuy-Binh Nguyen, Duc-Long Tran, Thi-Lan Le, Thi Thanh Thuy Pham, H. Doan","doi":"10.1109/NICS.2018.8606858","DOIUrl":"https://doi.org/10.1109/NICS.2018.8606858","url":null,"abstract":"Person re-identification (ReID), a critical task in surveillance systems, has obtained impressive advances in recent years. However, most current works focus on improving the person re-identification accuracy. In practical terms, the direct use of these works seems difficult, even infeasible. Among the features proposed for person representation in person ReID, Gaussian of Gaussian (GOG) has been proved to be robust. Towards applying this feature for practical usage, in this work, we simultaneously propose two improvements. First, we re-implement and perform intensive experiments to select the optimal parameters of GOG during feature extraction. Second, we propose and apply preprocessing techniques on person images. The experimental results show that the proposed approach allows to extract GOG 2 times faster than the available source code and achieve remarkably high accuracy for person ReID. The obtained accuracies at rank-1 on VIPeR dataset are 51.74% (with background) and 57.25% (without background). The implementations and evaluation datasets used in this paper are made publicly available.","PeriodicalId":137666,"journal":{"name":"2018 5th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"70 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":"124614890","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

The Influence of Icon Background Colors and Icon Symbols on Menu Item Selection for Smartphone 智能手机图标背景颜色和图标符号对菜单项选择的影响

2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606854

L. Punchoojit, Nuttanont Hongwarittorrn

引用次数: 4

Keynote Abstracts Keynote Talk #1 Preparing the University for Rapid Digital Evolution 主题演讲摘要:为大学的快速数字化发展做好准备

2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606855

I. Puri

{"title":"Keynote Abstracts Keynote Talk #1 Preparing the University for Rapid Digital Evolution","authors":"I. Puri","doi":"10.1109/NICS.2018.8606855","DOIUrl":"https://doi.org/10.1109/NICS.2018.8606855","url":null,"abstract":"New disruptions – technological, business and social – are being facilitated by the evolution of digital technologies. There are, of course, many valuable pilot efforts across the world that integrate a deep understanding of new research on digital technologies with student learning. Yet the classical classroom that does not fully include digital learning dominates globally. There are many curricula that allow postsecondary students to learn about digital opportunities, but these are not ubiquitous and neither are they based on current advances. As educators, we want students to learn and become more self-aware about how their academic disciplines intersect with the enlarging digital world and new research. How do we do so? First, we must convey that digital transformation and innovation are not synonymous. While digital transformations are typically realized over longer periods, digital innovations on the other hand are generated by the more immediate ignition of creativity and relatively shorter term design thinking. Digital creativity is enabled both within the classroom and outside it, in the latter case sometimes even without a formal curriculum. It thus follows that, in addition to discipline-specific fundamentals, students and researchers should learn to embrace digital evolution regardless of their area of academic discipline to enable longer term digital transformation. In this presentation, we will discuss some examples of how the awareness and understanding of digital evolution has been integrated into student learning and research in various engineering disciplines. This includes, for instance, teaching and learning related to new research in autonomous systems, data analytics, IoT implementations, e.g., for advanced manufacturing, and the evolution of graphical user interfaces and apps. Finally, we present some strategies to encourage the more ubiquitous implementation of these integrations.","PeriodicalId":137666,"journal":{"name":"2018 5th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"56 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":"132485222","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 role-based statistical mechanism for DDoS attack detection in SDN 基于角色的SDN DDoS攻击检测统计机制

2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606851

Phan The Duy, Do Thi Thu Hien, V. Pham

{"title":"A role-based statistical mechanism for DDoS attack detection in SDN","authors":"Phan The Duy, Do Thi Thu Hien, V. Pham","doi":"10.1109/NICS.2018.8606851","DOIUrl":"https://doi.org/10.1109/NICS.2018.8606851","url":null,"abstract":"There is a transformation of the traditional network into Software Defined Networking (SDN) which is an outstanding developing area recently. Among the most exciting features of SDN are the remarkable control over network infrastructure and decoupling of control and data plane. Although it helps more flexible network management, SDN should be considered current and upcoming security threats associated with its deployment. One of them is the DDoS attack which is a malicious attempt to bring down networks, applications, or services by overwhelming these resources with too much data or impairing them in some other ways. In SDN, we can offer or change the network functions or behavior program by monitoring controller to realize DDoS attacks. This paper presents an approach of DDoS attack detection in SDN environment by utilizing the entropy metric with consideration of differences in host role profile to suspect under-attack state, we also deal with time factor in information collecting activities. Then, a statistical method is used for investigating flow information sent from OpenFlow switches to confirm the previous suspicion.","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":"131011603","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: 11

FVI: An End-to-end Vietnamese Identification Card Detection and Recognition in Images FVI:端到端的越南识别卡检测与图像识别

2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606831

H. D. Liem, N. D. Minh, Nguyen Bao Trung, Hoang Tien Duc, Phạm Hoàng Hiệp, Doan Viet Dung, Dang Hoang Vu

引用次数: 16

The Participant-Pronoun Restriction: English and Vietnamese 参与人称限制:英语和越南语

2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606905

Tue Trinh, H. Truckenbrodt

引用次数: 0

On Temporal Cluster Analysis for Early Identifying In-trouble Students in an Academic Credit System 基于时间聚类分析的学分制问题学生早期识别

2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606827

Lê Minh Châu, Vo Thi Ngoc Chau, N. H. Phung

{"title":"On Temporal Cluster Analysis for Early Identifying In-trouble Students in an Academic Credit System","authors":"Lê Minh Châu, Vo Thi Ngoc Chau, N. H. Phung","doi":"10.1109/NICS.2018.8606827","DOIUrl":"https://doi.org/10.1109/NICS.2018.8606827","url":null,"abstract":"Early in-trouble student identification in an academic credit system is a challenging popular task in the educational data mining field. Only the first few semesters of the students can be observed for the task so that the in-trouble students can be recognized soon and have enough time for improving their study performance. The task can be tackled with different machine learning approaches. In this paper, we use the unsupervised learning approach to determine those students with higher effectiveness and no preparation of other labeled data sets. In this approach, a temporal cluster analysis method is proposed in our work based on the temporal clusters returned by dynamic topic models. In addition, we consider temporal characteristics in the study performance of each student to form a pattern from the temporal clusters he/she belongs to over the time. Similar students share similar patterns and therefore, allowing us to determine the pattern types of in-trouble students and recognize them more accurately. In an evaluation study, experimental results show that our method outperforms the other unsupervised and supervised learning methods with higher Recall and F-measure values. It also obtains better temporal clusters with dynamic topic modeling. As a result, our method is suitable for the early in-trouble student identification task.","PeriodicalId":137666,"journal":{"name":"2018 5th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"21 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":"134529329","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

A Deep Learning Model for Extracting User Attributes from Conversational Texts 从会话文本中提取用户属性的深度学习模型

2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/NICS.2018.8606804

Pham Quang Nhat Minh, N. Anh, Nguyen Tuan Duc

引用次数: 0

NICS 2018 List Reviewer Page nic 2018列表审核页面

2018 5th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2018-11-01 DOI: 10.1109/nics.2018.8606894

引用次数: 0