• Journal of Information Science Theory and Practice
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• v.1 no.1
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• pp.83-91
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• 2013

• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.235-236
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• 2014

• Proceedings of the Botanical Society of Korea Conference
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• 1999.07a
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• pp.95-95
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• 1999

• Journal of Korean Library and Information Science Society
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• v.33 no.1
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• pp.99-120
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• 2002

This study is to firstly investigate information infrastructure in North Korea such as communication network, hardware, software and etc, and then, based on it, to grasp the present condition of information technology in libraries there. Also, it is to analyze the information system of science technology in order to research the circulation system of science information with focusing on the Central Science Technology Intelligence (CSTI), a representative intelligence agency for science technology in North Korea, and on the retrieval program of “KWANGMYOUNG System”developed by CSTI and used broadly.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05c
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• pp.1611-1614
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• 2003

본 논문에서는 트랜잭션 기반의 데이터 관리 및 검색 기능을 갖춘 정보 관리 시스템인 KRISTAL-2000을 간략하게 소개하고, JAVA를 구현언어로 하는 사용자가 해당 시스템의 기능을 원활하게 사용할 수 있도록 하기 위한 JAVA 기반의 KRISTAL-2000 사용자 API 선계를 목표로 한다. 이때 사용자와 시스템간의 연결은 텍스트 기반의 소켓 통신을 전제로 한다.

• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.269-270
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• 2014

• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.247-248
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• 2014

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.1-11
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• 2022

As data-based research activities and outcomes increase and ontact or non-face-to-face activities become common, the demand for easy utilization of resources, tools, functions, and easily accessible information required for research in the R&D sector has increased accordingly. With the rapid increase in the demand for collaborative research based on online platforms, research support institutions strive to provide venues for research activities that merge various information and functions. ScienceON, an integrated science & technology (S&T) knowledge infrastructure service developed and operated by the Korea Institute of S&T Information (KISTI), supports open collaboration by connecting and merging all the information, functions, and infrastructure required for research activities. This paper describes the online research activity support tool provided by ScienceON and the remarkable results achieved through this activity. Specifically, the excellent creation of the following flow of meta-material research activities in the ontact space is elucidated. First, the papers required for a meta-material analysis are retrieved, virtual simulation is conducted with the experimental data extracted from the papers, and research data are accumulated. ScienceON's tools for supporting ontact research activity will play a role as an important service in the era of digital transformation and open science.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2011.06a
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• pp.161-173
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• 2011

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.225-234
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• 2023

In this era of information and communication technology (ICT), tremendous improvements have been witnessed in our daily lives. The impact of these technologies is subjective and negative or positive. For instance, ICT has brought a lot of ease and versatility in our lifestyles, on the other hand, its excessive use brings around issues related to physical and mental health etc. In this study, we are bridging these both aspects by proposing the idea of AI based mental healthcare (AIMS). In this regard, we aim to provide a platform where the patient can register to the system and take consultancy by providing their assessment by means of a chatbot. The chatbot will send the gathered information to the machine learning block. The machine learning model is already trained and predicts whether the patient needs a treatment by classifying him/her based on the assessment. This information is provided to the mental health practitioner (doctor, psychologist, psychiatrist, or therapist) as clinical decision support. Eventually, the practitioner will provide his/her suggestions to the patient via the proposed system. Additionally, the proposed system prioritizes care, support, privacy, and patient autonomy, all while using a friendly chatbot interface. By using technology like natural language processing and machine learning, the system can predict a patient's condition and recommend the right professional for further help, including in-person appointments if necessary. This not only raises awareness about mental health but also makes it easier for patients to start therapy.