• Proceedings of the Korea Contents Association Conference
• /
• 2014.06a
• /
• pp.179-180
• /
• 2014

• Proceedings of the Korea Contents Association Conference
• /
• 2014.06a
• /
• pp.319-320
• /
• 2014

• KNOM Review
• /
• v.22 no.2
• /
• pp.12-21
• /
• 2019

There is a rapid development of experimental equipment and ICT technology in data-intensive scientific areas, thus, big data of more than exabyte size is being generated. However, the big data transmission technology does not satisfy the needs of the application researchers who utilize it. Various high-performance transmission technologies have been developed based on QoS(Quality of Service), but they also require changes in the clean slate method. On the other hand, ScienceDMZ technologies improve the performance of scientific big data transmission by bypassing the firewall that causes a big problem in transmission performance. In addition, it is possible to implement without changing the existing network. In this paper, we built ScienceDMZ in an international long-distance environment based on KREONET(Korea Research Environment Open NETwork), and we verified the performance. We also introduced how GPU platform could be linked in a distributed ScienceDMZ environment.

• Proceedings of the Korean Information Science Society Conference
• /
• 2010.11a
• /
• pp.52-53
• /
• 2010

• Journal of Scientific & Technological Knowledge Infrastructure
• /
• s.16
• /
• pp.6-11
• /
• 2004

• Journal of Information Science Theory and Practice
• /
• v.10 no.spc
• /
• pp.154-163
• /
• 2022

The purpose of this paper is to illuminate the role and importance of National Research & Education Network (NREN) in the national research and education field and to establish the future strategy of KREONET in Korea. To this end, we first carefully analyze the footsteps of NREN in major overseas countries, KREONET achievements, and future demand for KREONET. The history of NREN's development is divided into the 2000s, 2010s, and present by era, and classified into network infrastructure, network service, and next-generation network technology by subject. KREONET achievements are divided into advanced research support, network backbone and operation, and network service. Future demand analysis of users who use KREONET was conducted through Korea Research International Incorporation, a survey company. This paper presents the future development strategy of KREONET by analyzing KREONET achievements and future demand.

• Journal of Information Management
• /
• v.38 no.2
• /
• pp.1-23
• /
• 2007

Korea, China and Japan are in great demand for each other’s science and technology information since they geographically lie adjacent and have common interest in a variety of science and technology fields. Yet, they have difficulties in obtaining the other two countries’ information due to the lack of an appropriate system to access the information and also to restrictions such as a language barrier. The purpose of this study is to suggest the ways of sharing science and technology information among Korea, Japan and China. It surveys the national science and technology information systems and policies of each country and proposes four stages of resource sharing.

• Proceedings of the Korean Information Science Society Conference
• /
• 2012.06b
• /
• pp.279-281
• /
• 2012

본 논문은 과학 기술 분야 학술 정보에 내재된 기술 지식을 효과적으로 추출하기 위한 시스템인 SINDI-WALKS를 소개한다. 이 시스템은 학술 정보에 자주 등장하며 내용 전개에 핵심적인 역할을 수행하는 PLOT, 즉 인명, 지명, 기관명, 그리고 기술용어를 자동으로 인식하고 이들 간의 의미적 연관 관계를 추출할 수 있는 통합 지원 도구이다. 논문에서 소개하는 다양한 지원 도구들을 바탕으로 기술 지식추출의 성능을 특정 분야 혹은 자원에 최적화할 수 있는 기반을 마련할 수 있다.

• Journal of Information Science Theory and Practice
• /
• v.10 no.spc
• /
• pp.86-95
• /
• 2022

Online recruitment websites discuss job demands in various fields, and job postings contain detailed job specifications. Analyzing this text can elucidate the features that determine job salaries. Text embedding models can learn the contextual information in a text, and explainable artificial intelligence frameworks can be used to examine in detail how text features contribute to the models' outputs. We collected 733,625 job postings using the WORKNET API and classified them into low, mid, and high-range salary groups. A text embedding model that predicts job salaries based on the text in job postings was trained with the collected data. Then, we applied the SHapley Additive exPlanations (SHAP) framework to the trained model and discovered the significant words that determine each salary class. Several limitations and remaining words are also discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.10
• /
• pp.4126-4142
• /
• 2015

Finger vein recognition is a biometric technology using finger veins to authenticate a person, and due to its high degree of uniqueness, liveness, and safety, it is widely used. The traditional Symmetric Local Graph Structure (SLGS) method only considers the relationship between the image pixels as a dominating set, and uses the relevant theories to tap image features. In order to better extract finger vein features, taking into account location information and direction information between the pixels of the image, this paper presents a novel finger vein feature extraction method, Multi-Orientation Weighted Symmetric Local Graph Structure (MOW-SLGS), which assigns weight to each edge according to the positional relationship between the edge and the target pixel. In addition, we use the Extreme Learning Machine (ELM) classifier to train and classify the vein feature extracted by the MOW-SLGS method. Experiments show that the proposed method has better performance than traditional methods.