• Proceedings of the Korean Society of Computer Information Conference
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• 2016.01a
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• pp.267-269
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• 2016

본 논문에서는 언리얼 엔진4의 Behavior Tree(행동 트리)를 이용하여 NPC의 다양한 상태와 움직임을 가진 어드벤처 게임 AI를 설계 및 개발하였고, 그 효율성을 분석하였다. Behavior Tree는 상태와 행동을 계층적으로 나누어 AI의 행동을 결정하는 알고리즘으로 FSM(Finite State Machine, 유한상태기계)과 비교하여 유지보수와 행동 규칙 검증의 어려움을 해결하는 데 장점이 있음을 확인하였다.

• Journal of Digital Contents Society
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• v.8 no.4
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• pp.579-586
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• 2007

The process of developing a online 3D game engine involves designing details of the engine, alpha test, adjustment, supplementation, beta test and introduction, and an online 3D game engine is made of a server engine and client engine. The server engine, which is made of server construction part, distribution center and DB construction part for building asymmetric multiple servers, is developed by Linux, and the client engine, which is made of a graphic part, sound part, AI part and object management part, is developed by using DirectX in Windows, and it proposes an engine configuration and method based on 3D engine technology by analyzing the network technology, which is a common engine technology.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.286-292
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• 2023

This article is set against the backdrop of the rapid development of the metaverse and artificial intelligence technologies, and aims to explore the possibility and potential impact of integrating AI technology into the traditional 3D animation production process. Through an in-depth analysis of the differences when merging traditional production processes with AI technology, it aims to summarize a new innovative workflow for 3D animation production. This new process takes full advantage of the efficiency and intelligent features of AI technology, significantly improving the efficiency of animation production and enhancing the overall quality of the animations. Furthermore, the paper delves into the creative methods and developmental implications of artificial intelligence technology in real-time rendering engines for 3D animation. It highlights the importance of these technologies in driving innovation and optimizing workflows in the field of animation production, showcasing how they provide new perspectives and possibilities for the future development of the animation industry.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.16-21
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• 2008

Aero-engine, as one kind of rotating machinery with complex structure and high rotating speed, has complicated vibration faults. Therefore, condition monitoring and fault diagnosis system is very important for airplane security. In this paper, a vibration data acquisition and intelligent fault diagnosis system is introduced. First, the vibration data acquisition part is described in detail. This part consists of hardware acquisition modules and software analysis modules which can realize real-time data acquisition and analysis, off-line data analysis, trend analysis, fault simulation and graphical result display. The acquisition vibration data are prepared for the following intelligent fault diagnosis. Secondly, two advanced artificial intelligent(AI) methods, mapping-based and rule-based, are discussed. One is artificial neural network(ANN) which is an ideal tool for aero-engine fault diagnosis and has strong ability to learn complex nonlinear functions. The other is data mining, another AI method, has advantages of discovering knowledge from massive data and automatically extracting diagnostic rules. Thirdly, lots of historical data are used for training the ANN and extracting rules by data mining. Then, real-time data are input into the trained ANN for mapping-based fault diagnosis. At the same time, extracted rules are revised by expert experience and used for rule-based fault diagnosis. From the results of the experiments, the conclusion is obvious that both the two AI methods are effective on aero-engine vibration fault diagnosis, while each of them has its individual quality. The whole system can be developed in local vibration monitoring and real-time fault diagnosis for aero-engine.

• Journal of Internet Computing and Services
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• v.22 no.4
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• pp.99-110
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• 2021

Governments around the world are actively establishing strategies and initiatives to spread the use of artificial intelligence (AI), for AI is not a mere new technology, but is an innovative technology that brings about extensive changes in industrial and social structures and is a core engine that will lead the 4th Industrial Revolution. The South Korean government has also been paying attention to AI as a technology and tool for innovative growth, but its application to the industries is still rather sluggish. The government has prepared multifarious AI-related policies with the aim of constructing South Korea as an AI powerhouse, but there is no clear strategy on which detailed policies to implement first and which industries to apply AI preferentially. With these limitations of South Korea's AI policies in mind, this paper analyzed the priorities of industries in AI adoption and the priorities of AI-related national policies, using Delphi-AHP method for 30 top-level AI experts in South Korea. The results of analysis show that AI application is urgent and necessary in the fields of medical/healthcare, public and safety, and manufacturing, which seems to reflect the peak of the COVID-19 crisis in the second half of 2020 at the time of the investigation. And it turns out that policies related to AI talent cultivation, data, and R&D investment are important and urgent above all in order for organizations to apply AI. This suggests that strategies are required to focus limited national resources on these industries and policies first.

• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.21-40
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• 2019

This paper presents a comprehensive survey of various artificial intelligence (AI) techniques implemented in cognitive radio engine to improve cognition capability in cognitive radio networks (CRNs). AI enables systems to solve problems by emulating human biological processes such as learning, reasoning, decision making, self-adaptation, self-organization, and self-stability. The use of AI techniques is studied in applications related to the major tasks of cognitive radio including spectrum sensing, spectrum sharing, spectrum mobility, and decision making regarding dynamic spectrum access, resource allocation, parameter adaptation, and optimization problem. The aim is to provide a single source as a survey paper to help researchers better understand the various implementations of AI approaches to different cognitive radio designs, as well as to refer interested readers to the recent AI research works done in CRNs.

• Electronics and Telecommunications Trends
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• v.37 no.1
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• pp.53-62
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• 2022

With increasing size of transformer-based neural networks, a light-weight algorithm and efficient AI accelerator has been developed to train these huge networks in practical design time. In this article, we present a survey of state-of-the-art research on the low-precision computational algorithms especially for floating-point formats and their hardware accelerator. We describe the trends by focusing on the work of two leading research groups-IBM and Seoul National University-which have deep knowledge in both AI algorithm and hardware architecture. For the low-precision algorithm, we summarize two efficient floating-point formats (hybrid FP8 and radix-4 FP4) with accuracy-preserving algorithms for training on the main research stream. Moreover, we describe the AI processor architecture supporting the low-bit mixed precision computing unit including the integer engine.

• Journal of Digital Contents Society
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• v.14 no.2
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• pp.143-149
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• 2013

Many researchers and developers take a greater interest on the LOD AI techniques as users demand more elaborate and sophisticated game AI in recent years. However, contrary to the traditional geometry LOD, existing LOD AI techniques can be used only to a limited extent. Therefore, in this paper, I propose an LOD AI technique, which uses HSM(Hierarchical State Machine) and the Lua script language as the method to control game objects. Using the proposed approach, we can easily produce multilevel AI models for LOD and design various objects without hard-coding state machines. Moreover, in order to show the effectiveness of the presented technique, this paper exemplifies the results of the efficiency test through the prototype engine.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5083-5088
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• 2010

An implementation of NPC AI(artifical intelligence) is similar with real world's flocking can increase fun factor of game. To this end, we design fish flocking patten of analyzed real world, implement using Ogre engine in this paper. To determine the usefulness of implemented fish flocking, we compare fish flocking in real world with implemented fish flocking. Implemented behavioral patterns of fish flocking show similar behavioral patterns of fish flocking in real world.

• Information Systems Review
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• v.23 no.3
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• pp.77-96
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• 2021

This research investigates the pivotal role of AI-enabled technologies in vitalizing the local economy. Collaborating with a leading search engine company, we examine the direct and indirect of an AI-based location search service on the success of sampled 7,035 local restaurants in Gangnam area in Seoul. We find that increased use of AI-enabled search and recommendation services significantly improved the selections of previously less-discovered or less-popular restaurants by users, and it also enhanced the stores' overall conversion rates. The main research findings have contributions to extant literature in theorizing the value of AI applications in local economy and have managerial implications for search businesses and local stores by recommending strategic use of AI applications in their businesses that are effective in highly competitive markets.