• 한국게임학회 논문지
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• 제2권2호
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• pp.37-45
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• 2002

컴퓨터 게임은 실세계에 대한 시뮬레이션으로 간주되어질 수 있다. 소프트웨어 에이젼트의 제어 문제는 인공지능 분야에서 오랫동안 연구되어져 왔으며, 이는 행동기반 접근법이라는 것을 내놓았다. 인공지능 분야에서는 지금까지 크게 세 가지의 접근법을 볼 수 있다. 인지주의는 기호의 형태로 지능이 표현되어질 수 있고 다루어질 수 있다는 것을 제안하였으며, 연결주의에서는 표현이 신체 구조에 내포되어있어서 신체로부터 분리되어질 수 없음이 강조되었다. 행동기반 접근법에서는 인공지능은 동적인 성질을 가져서 어디서든지 존재하지 않는 대신에 에이젼트가 환경에서 행동할 때 비로소 우러나오는 성질을 가진 것으로 제시된다. 본 논문에서는 이러한 세 가지의 접근법을 비교하고 행동기반 접근법의 타당성과 문제점 에 대하여 논한다. 본 논문은 또한 행동기반 접근법의 컴퓨터 게임의 에이젼트 제어에 대한 활용을 제안한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2024년도 춘계학술발표대회
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• pp.891-894
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• 2024

The quest for reliability in Artificial Intelligence (AI) is progressively urgent, especially in the field of next generation wireless networks. Future Beyond 5G (B5G)/6G networks will connect a huge number of devices and will offer innovative services invested with AI and Machine Learning tools. Wireless communications, in general, and medium access control (MAC) techniques were among the fields that were heavily affected by this improvement. This study presents the applications and services of future communication networks. This study details the Medium Access Control (MAC) scheduler of Beyond-5G/6G from 3^rd Generation Partnership (3GPP) and highlights the current open research issues which are yet to be optimized. This study provides an overview of how AI plays an important role in improving next generation communication by solving MAC-layer issues such as resource scheduling and queueing. We will select C-V2X as our use case to implement our proposed MAC scheduling model.

• 인포메이션 디스플레이
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• 제23권4호
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• pp.35-44
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• 2022

AI기술의 유용성과 발전 가능성은 다양한 분야에서 확인되어 왔고, 디스플레이 산업에도 AI 기술들이 적극 도입되고 있다. 디스플레이 산업에 도입된 기존의 AI 기술들은 주로 engineer나 불량 검사자의 업무를 자동화하는 목적이었으나, 최근에는 engineer의 업무를 대체하는 고도의 지능화된 AI 기술들이 도입되고 있다. 본 논문에서는 이러한 지능화된 AI 기술 중에서 강화 학습, 자연어 처리, Pattern Matching 기술의 원리와 적용 사례들을 다루어 보았다. 첫번째로 강화 학습의 기본 개념을 설명하고, 설비 control (scheduling), 재료 탐색, 그리고 회로 설계에서의 적용 사례를 살펴보았다. 두번째로는 자연어 처리에서는 기술의 기본 원리 및 다양한 적용 방법론들에 대하여 다루었고, 제조 검사 리포트 분석, 지식재산권 분석, 연구문헌 분석 등에서의 활용 사례를 살펴보았다. 마지막으로 Pattern Matching에서는 기술 개요와 최근의 기술 동향을 기술하였고, Object Detection과 Object Tracking 기술 비교와 함께 패널 설계 도면으로부터 engineer 가 관심을 가져야 할 pattern 탐색에 대한 적용 사례를 살펴보았다.

• Journal of Information Processing Systems
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• 제19권4호
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• pp.439-449
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• 2023

This paper deals with a resource efficient artificial intelligence (AI) service architecture for multi-channel video streams. As an AI service, we consider the object detection model, which is the most representative for video applications. Since most object detection models are basically designed for a single channel video stream, the utilization of the additional resource for multi-channel video stream processing is inevitable. Therefore, we propose a resource efficient AI service framework, which can be associated with various AI service models. Our framework is designed based on the modular architecture, which consists of adaptive frame control (AFC) Manager, multiplexer (MUX), adaptive channel selector (ACS), and YOLO interface units. In order to run only a single YOLO process without regard to the number of channels, we propose a novel approach efficiently dealing with multi-channel input streams. Through the experiment, it is shown that the framework is capable of performing object detection service with minimum resource utilization even in the circumstance of multi-channel streams. In addition, each service can be guaranteed within a deadline.

• Journal of Information Technology Applications and Management
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• 제30권4호
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• pp.11-28
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• 2023

This paper proposes a method of integrating ChatGPT with traditional chatbot systems to enhance conversational artificial intelligence(AI) and create more efficient conversational systems. Traditional chatbot systems are primarily based on classification models and are limited to intent classification and simple response generation. In contrast, ChatGPT is a state-of-the-art AI technology for natural language generation, which can generate more natural and fluent conversations. In this paper, we analyze the business service areas that can be integrated with ChatGPT and traditional chatbots, and present methods for conducting conversational scenarios through case studies of service types. Additionally, we suggest ways to integrate ChatGPT with traditional chatbot systems for intent recognition, conversation flow control, and response generation. We provide a practical implementation example of how to integrate ChatGPT with traditional chatbots, making it easier to understand and build integration methods and actively utilize ChatGPT with existing chatbots.

• 산경연구논집
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• 제11권10호
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• pp.7-16
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• 2020

Purpose: It suggests that making a policy and strategies in a way of AI and its impact of commercialization on economic efficiency, social custom ethics. Research design, data, and methodology: The paper has analyzed the data based on the proposed model when derived as AI vs. FI job, etc. It is very different for each professional evaluation, which is artificial intelligence or robot job. One concept case was selected as a substitute job, with a relatively low level of occupation ability, such as direct labors, easily replaced. By the induction data has resulted in modeling. Results: The paper suggests that AI at high level become something how to make real decisions on ethical value modeling. Through physical simulation with the deduction data, it can be tuned to design and control what has not been solved, from human senses to climate. Conclusion: For the exploiting of new AI decision-making jobs in markets, the deduction data is possible to prove to AI's Decision-making that the percentage who can easily have different leadership as is different for each person. what is generated by some information silos may be applied to occupation societies. The empirical results indicate the deduction data that if AI determines ethical decisions (VC) for that modifications, it may replace future jobs.

• 한국소음진동공학회논문집
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• 제12권5호
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• pp.365-373
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• 2002

This paper concerns the design and application of an electro-rheological (ER) fluid damper to semiactive vibration control of rotor systems. In particular, the system under present study is constructed structurally flexible in order to explore multiple critical speeds within operation range. To this end, the dynamic models of the proposed ER damper and its associated amplifier are derived in the first place. Subsequently entire rotor system model is assembled along with the dynamics of the end effector based on a finite element method enabling prediction as to its free and forced vibration characteristics. Next, an artificial intelligent (AI) feedback controller is synthesized taking into account the peculiarity of Coulomb damping effect in rotor applications. Finally, computational and experimental results are presented including model validation and control performances. In practice, such an AI control proved effective whether the spin speed was either before or after critical speeds.

• 한국잡초학회지
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• 제14권4호
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• pp.291-297
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• 1994

토마토 품종간의 제초제(除草劑) Quinclorac에 대한 생육(生育) 저해(沮害) 정도의 차이를 알아 보기 위하여 토마토 8개 품종에 Quinclorac 0, 1, 2, 3, 4, 5g ai/ha을 토마토 유묘의 본엽 2 엽기에 토양 표면에 산포(散布)하였다. 약제 처리후 일주일 간격으로 초장을 조사하였고 약제 처리 28일후에 식물체의 건물중을 측정하였다. 무처리(無處理)에 대한 초장(草長)의 비율은 약제 처리 7일후에 최고 약량 5g ai/ha 에서 69-81%였고 나머지 약량에서는 무처리와 차이가 없었다. 약제 처리후 시간 경과에 따라 초장의 무처리에 비한 단축율(短縮率)이 커져 갔으며 약제 처리 28 일후에는 5g ai/ha에서 (2-26)*836038과(TR*VC8-1)-1-2F4가 각각 무처리의 88%와 89%로 높았고 나머지 6개 품종은 무처리의 61-68%로 낮았다. 약제 처리 28일후의 무처리에 대한 줄기의 건물중(乾物重) 비율은 초장보다 더 커서 최고 약량인 4-5g ai/ha에서 (TR*VC8-1)-1-2F4가 59%와 51%, (2-26)*836038이 각각 43%와 45%로 초장에서와 같이 가장 감소율(減少率)이 적었다. 뿌리의 건물중은 무처리보다 높았다. 줄기와 뿌리를 합한 식물체 전체의 건물중도 줄기와 동일한 경향이었다.

• 산업경영시스템학회지
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• 제44권4호
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• pp.227-233
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• 2021

Predictive maintenance has been one of important applications of data science technology that creates a predictive model by collecting numerous data related to management targeted equipment. It does not predict equipment failure with just one or two signs, but quantifies and models numerous symptoms and historical data of actual failure. Statistical methods were used a lot in the past as this predictive maintenance method, but recently, many machine learning-based methods have been proposed. Such proposed machine learning-based methods are preferable in that they show more accurate prediction performance. However, with the exception of some learning models such as decision tree-based models, it is very difficult to explicitly know the structure of learning models (Black-Box Model) and to explain to what extent certain attributes (features or variables) of the learning model affected the prediction results. To overcome this problem, a recently proposed study is an explainable artificial intelligence (AI). It is a methodology that makes it easy for users to understand and trust the results of machine learning-based learning models. In this paper, we propose an explainable AI method to further enhance the explanatory power of the existing learning model by targeting the previously proposedpredictive model [5] that learned data from a core facility (Hyper Compressor) of a domestic chemical plant that produces polyethylene. The ensemble prediction model, which is a black box model, wasconverted to a white box model using the Explainable AI. The proposed methodology explains the direction of control for the major features in the failure prediction results through the Explainable AI. Through this methodology, it is possible to flexibly replace the timing of maintenance of the machine and supply and demand of parts, and to improve the efficiency of the facility operation through proper pre-control.

• Nutritional Sciences
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• 제7권4호
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• pp.241-246
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• 2004

This study investigated the influence of weight perception on weight management strategies including diet and exercise in Korean female adolescents. Junior (J) and senior (S) high school girls were divided in two groups; those who had $\leq$100% (BI) and > 100% (AI) of ideal weight (J-BI, n=376, 14.8 yr, 46.1 kg; J-AI, 11=128, 15.0 yr, 57.4 kg; S-BI, n=325, 17.4 yr, 50.1 kg; and S-AI, n=133, 17.5 yr, 58.2 kg, mean values). Questionnaires to assess weight perception, desire to lose weight, body image, eating behavior, weight control strategies and physical activity (PPA) were administered J-AI(9.4 kg) and S-AI(9.8 kg) desired to lose weight more than J-BI(2.5 kg) and S-BI(3.6 kg), respectively (p < 0.001). 85% of J-AI and 93% of S-AI perceived their weight being above average and 23% of J-BI and 34% of S-BI responded similarly (p < 0.001). Body dissatisfaction index (BDI) and eating attitude (EAT26) scores were lower in J-BI(9.7, 12.0) vs. J-AI(16.4, 14.7) and S-BI(12.4, 12.4) vs. S-AI(19.5, 15.4) (p < 0.001). However, PPA was not different for J-BI vs. J-AI, and S-BI vs. S-AL Only 17, 18, 9, and 15% of J.BI, J.AI, S-BI, and S-AI, respectively, exercised regularly. PPA and BDI were only slightly correlated in J-BI(r=0.194, p < 0.005) and S-BI(r=0.220, p < 0.005). Even that the majority of Korean female adolescents perceived they were heavy and desired to lose weight, appropriate exercise and physical activities were not practiced.