• Journal of the Korea Institute of Military Science and Technology
• /
• v.25 no.5
• /
• pp.513-521
• /
• 2022

This study deals with an AI architecture model for collecting battlefield data using the tactical C4I system. Based on this model, the artificial staff can be utilized in tactical echelon. In the current structure of the Army's tactical C4I system, Servers are operated by brigade level and above and divided into an active and a standby server. In this C4I system structure, the AI server must also be installed in each unit and must be switched when the C4I server is switched. The tactical C4I system operates a server(DB) for each unit, so data matching is partially delayed or some data is not matched in the inter-working process between servers. To solve these issues, this study presents an operation concept so that all of alternate server can be integrated based on virtualization technology, which is used as an source data for AI Meta DB. In doing so, this study can provide criteria for the AI architectural model of the ground tactical echelon.

• Journal of The Korean Association of Information Education
• /
• v.26 no.6
• /
• pp.553-566
• /
• 2022

This study collects social data and academic research data from portal sites and RISS, and analyzes TF-IDF, N-Gram, semantic network analysis, and CONCOR analysis to analyze the social awareness and current aspects of 'AI Literacy' and 'AI Convergence Education'. Through this, we tried to understand the social awareness aspect and the current situation, and to suggest implications and directions. In the social data, the collection of 'AI Convergence Education' was more than twice that of 'AI Literacy', indicating that awareness of 'AI Literacy' was relatively low. In 'AI Literacy', the keyword 'human' in social data showed no cluster to which it belonged, indicating a lack of philosophical interest in and awareness of humanities and AI. In addition, the keyword 'Ministry of Education' showed high frequency, importance, and centrality of connection only in the social data of 'AI convergence education', confirming that 'AI convergence education' is closely related to government policy.

• Journal of Korean Neurosurgical Society
• /
• v.66 no.2
• /
• pp.113-120
• /
• 2023

Artificial intelligence (AI) is a field of computer science that equips machines with human-like intelligence and enables them to learn, reason, and solve problems when presented with data in various formats. Neurosurgery is often at the forefront of innovative and disruptive technologies, which have similarly altered the course of acute and chronic diseases. In diagnostic imaging, such as X-rays, computed tomography, and magnetic resonance imaging, AI is used to analyze images. The use of robots in the field of neurosurgery is also increasing. In neurointensive care units, AI is used to analyze data and provide care to critically ill patients. Moreover, AI can be used to predict a patient's prognosis. Several AI applications have already been introduced in the field of neurosurgery, and many more are expected in the near future. Ultimately, it is our responsibility to keep pace with this evolution to provide meaningful outcomes and personalize each patient's care. Rather than blindly relying on AI in the future, neurosurgeons should gain a thorough understanding of it and use it to enhance their patient care.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.2
• /
• pp.439-449
• /
• 2019

The development of information technology represented by ICBMA (IoT, Cloud, Big Data, Mobile, AI), is leading to a surge in data and a numerical and quantitative increase in data centers to accommodate it. As the data center is recognized as a social infrastructure, It is very important to identify physical security threats in advance in order to secure safety, such as responding to a terrorist attack. In this paper, we develop physical security threat breakdown structure (PS-TBS) for easy identification and classification of threats, and verify the feasibility and effectiveness of the PS-TBS through expert questionnaires. In addition, we intend to contribute to the improvement of physical security level by practical use in detailed definition on items of PS-TBS.

• Journal of Information Technology Services
• /
• v.18 no.2
• /
• pp.123-141
• /
• 2019

The goal of this study is to review the major research trend on the convergence studies of AI and healthcare technologies. For the study, 15,260 English articles on AI and healthcare related topics were collected from Scopus for 55 years from 1963, and text mining techniques were conducted. As a result, seven key research topics were defined : "AI for Clinical Decision Support System (CDSS)", "AI for Medical Image", "Internet of Healthcare Things (IoHT)", "Big Data Analytics in Healthcare", "Medical Robotics", "Blockchain in Healthcare", and "Evidence Based Medicine (EBM)". The result of this study can be utilized to set up and develop the appropriate healthcare R&D strategies for the researchers and government. In this study, text mining techniques such as Text Analysis, Frequency Analysis, Topic Modeling on LDA (Latent Dirichlet Allocation), Word Cloud, and Ego Network Analysis were conducted.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2021.11a
• /
• pp.545-547
• /
• 2021

발전시설 장비는 이상이 생기면 큰 경제적 피해를 발생시키기 때문에, 장비의 계통마다 수십만 개의 센서들이 부착되어 장비의 정상 작동 여부를 모니터링 한다. 장비의 이상 감지를 위해서, 최근 활발히 연구되고 있는 딥러닝 등의 기술을 활용한 AI 모델을 생성하여 장비의 고장을 예측한다. AI 모델을 학습하고 추론하기 위해서는 수많은 센서 중에서 AI 모델을 생성할 센서들을 선택하고, 지속적으로 모니터링 되는 값들을 비교하여 이상 감지 여부를 스트리밍 환경에서 추론할 수 있는 센서 빅데이터 질의 처리 및 스트리밍 추론 시스템이 필요하다. 본 논문에서는 AI 모델을 학습하고 스트리밍 추론할 수 있는 빅데이터 질의 처리 시스템을 설계 및 구현한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2024.05a
• /
• pp.151-153
• /
• 2024

Edge AI 기술은 자동차, 가전, 스마트폰 등 우리 주변의 다양한 기기에 탑재되어 있다. Edge AI 를 구동하는 프로세서는 여러 종류로 나뉘는데, 대표적으로 저성능의 Microprocessor와 고성능 Microcomputer로 분류할 수 있다. 그중에서도 Microprocessor는 메모리와 저장 용량이 작아 Edge AI 를 구동하기 위한 빅 데이터를 메모리와 저장공간에 저장할 수 없기 때문에 통신을 사용하여 다른 기기로부터 데이터를 받아 연산을 수행해야 한다. 하지만 Microprocessor에서 통신은 빅 데이터와 같은 숫자로 이루어진 값을 전송하는 데에만 사용되는 것이 아니다. 디버깅이나 Processor의 정보 표시 등 문자열을 함께 사용하는 경우가 많은데, 문자열과 숫자 데이터를 함께 주고받으면 빅데이터와 같은 많은 데이터를 전송할때 시간이 오래 걸린다는 문제가 있다. 본 논문에서는 Edge AI에서의 빅데이터를 빠르게 전송할 수 있는 방법을 제안한다.

• Journal of Digital Convergence
• /
• v.17 no.9
• /
• pp.147-152
• /
• 2019

Infrastructure is rapidly growing as Internet business grows with the latest IT technologies such as IoT, BigData, and AI. However, in most companies, a limited number of people need to manage a lot of hardware and software. Therefore, Polestar Enterprise Management System(PEMS) is applied to monitor the system operation status, IT service and key KPI monitoring. Real-time monitor screening prevents system malfunctions and quick response. With PEMS, you can see configuration information related to IT hardware and software at a glance, and monitor performance throughout the entire end-to-end period to see when problems occur in real time.

• Electronics and Telecommunications Trends
• /
• v.36 no.3
• /
• pp.133-144
• /
• 2021

High-performance computing (HPC) is the underpinning for many of today's most exciting new research areas, to name a few, from big science to new ways of fighting the disease, to artificial intelligence (AI), to big data analytics, to quantum computing. This report captures the summary of a 9-day program of presentations, keynotes, and workshops at the SC20 conference, one of the most prominent events on sharing ideas and results in HPC technology R&D. Because of the exceptional situation caused by COVID-19, the conference was held entirely online from 11/9 to 11/19 2020, and interestingly caught more attention on using HPC to make a breakthrough in the area of vaccine and cure for COVID-19. The program brought together 103 papers from 21 countries, along with 163 presentations in 24 workshop sessions. The event has covered several key areas in HPC technology, including new memory hierarchy and interconnects for different accelerators, evaluation of parallel programming models, as well as simulation and modeling in traditional science applications. Notably, there was increasing interest in AI and Big Data analytics as well. With this summary of the recent HPC trend readers may find useful information to guide the R&D directions for challenging new technologies and applications in the area of HPC.

• Smart Media Journal
• /
• v.7 no.4
• /
• pp.30-36
• /
• 2018

Single domain model like DataLake framework is in spotlight because it can improve data efficiency and process data smarter in big data environment, where large scaled business system generates huge amount of data. In particular, efficient operation of network, storage, and computing resources in logical single domain model is very important for physically partitioned multi-site data process. Based on the advantages of Data Lake framework, we define and extend the concept of Connected Data Architecture and functions of DataLake framework for integrating multiple sites in various domains and managing the lifecycle of data. Also, we propose the design of CDA-based AI service and utilization scenarios in various application domain.