• Title/Summary/Keyword: 활용과 탐색

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기계공학 전문가시스템과 인지(Cognitive) 컴퓨팅

  • Park, Jong-Won;Choe, Byeong-O
    • Journal of the KSME
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    • v.57 no.3
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    • pp.46-51
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    • 2017
  • 이 글은 전문가시스템의 개요와 사례를 살펴보고, 인지컴퓨팅을 활용하여 다양한 분야에 인공지능을 적용하고 있는 Watson의 사례를 제시하여 향후 기계공학 전문가시스템의 개발방향을 탐색한다.

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인터넷 IS 이용자의 업무성과에 관한 연구

  • 이대용;정광진
    • Proceedings of the Korea Society for Industrial Systems Conference
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    • 1998.10a
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    • pp.283-299
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    • 1998
  • 본 연구는 인터넷 기반의 정보시스템의 활용에 대한 성과 측정의 어려움으로 인한 문제를 성과 측정을 위한 도구로 이용도(Usage), 사용자만족(User Satisfaction)과 그 외 정보시스템 성과측정과 관련된 이론 및 모델을 바탕으로 연구모델을 설정하여 , 이용자의 특성과 조직의 지원이 인터넷 기반의 정보시스템 이용도와 만족도에 어떠한 영향을 미치는지 그 요인을 실증적으로 탐색해보고자했다. 결과로서는 이용자특성과 조직의 지원이 인터넷 정보시스템의 이용도와 만족도에 유의한 영향을 주고, 이용도와 만족도는 업무성과에 유의한 영향을 주는 것으로 나타났다. 이러한 연구결과를 바탕으로 현재 인터넷 기반의 정보시스템을 활용하고 있거나, 향후 도입하려는 조직에게 효과적이고 적극적인 활용에 대한 방향을 제시한다.

Inventory Management Platform Using Al Drone (인공지능 드론을 활용한 재고관리 플랫폼)

  • Oh, Se-Jin;Hong, Sung-An;Min, Jae-Hong
    • Proceedings of the Korean Society of Disaster Information Conference
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    • 2022.10a
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    • pp.367-368
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    • 2022
  • 인공지능을 활용한 시장이 확대되고 있다. 그중 기업의 공장에서는 생산 물품 관리를 위한 효율적인 재고관리 시스템이 요구된다. 본 연구는 AI를 기반으로 RFID Reader와 고해상도 카메라 모듈을 탑재한 드론을 활용하여, 재고 탐색 및 인식 기능이 있는 재고관리 플랫폼에 대하여, 안정적인 드론 운용 기술 방안을 연구해 보고자 한다.

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Mobile Robot Exploration in Unknown Environment using Hybrid Map (미지의 환경에서 하이브리드 맵을 활용하는 모바일 로봇의 탐색)

  • Park, Jung Kyu;Jeon, Heung Seok;Noh, Sam H.
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.4
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    • pp.27-34
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    • 2013
  • Mobile robot has the exploration function in order to perform its own task. Robot exploration can be used in many applications such as surveillance, rescue and resource detection. The workspace that robots performed in was complicated or quite wide, the multi search using the several mobile robots was mainly used. In this paper, we proposed a scheme that all areas are searched for by using one robot. The method to be proposed extract a area that can be explored in the workspace then the robot investigates the area and updates the map at the same time. The explored area is saved as a hybrid map that combines the nice attributes of the grid and topological maps. The robot can produce the safe navigation route without the obstacles by using hybrid map. The proposed hybrid map uses less memory than a grid map, but it can be used for complete coverage with the same efficiency of a topological map. Experimental results show that the proposed scheme can generate a map of an environment with only 6% of the memory that a grid map requires.

Design and Implementation of Navigation-Aid for 3D Virtual Environment using Topic Map (토픽맵을 이용한 3차원 가상환경 탐색항해 도구의 설계 및 구현)

  • Kim Hak-Keun;Song Teuk-Seob;Lim Soon-Bum;Choy Yoon-Chul
    • The KIPS Transactions:PartB
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    • v.11B no.7 s.96
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    • pp.793-802
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    • 2004
  • Users in 3D virtual environment get limited information which contains mostly images. It is the main reason for users getting lost during their Navigation. Various studies of Navigation-Aid have been done in order to solve this problem. In this study, we applied Topic Maps, which is one of semantic Web techniques, to the navigation in a 3D virtual environment. Topic Maps construct semantic linking maps through defining the relations between topics. Experiments in which Topic Map based Navigation-Aid was applied have shown that the Navigation-Aid was effective when the subjects find a detailed target rather than a highly represented one. Also, offering information around the target helped the users to find the target when they navigated without having specific targets.

Monte-Carlo Tree Search Applied to the Game of Tic-Tac-Toe (삼목 게임에 적용된 몬테카를로 트리탐색)

  • Lee, Byung-Doo
    • Journal of Korea Game Society
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    • v.14 no.3
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    • pp.47-54
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    • 2014
  • The game of Go is one of the oldest games and originated at least more than 2,500 years ago. In game programming the most successful approach is to use game tree searches using evaluation functions. However it is really difficult to construct feasible evaluation function in computer Go. Monte-Carlo Tree Search(MCTS) has created strong computer Go programs such as MoGo and CrazyStone which defeated human Go professionals played on the $9{\times}9$ board. MCTS is based on the winning rate estimated by Monte-Carlo simulation. Prior to implementing MCTS into computer Go, we tried to measure each winning rate of three positions, center, corner and side, in Tic-Tac-Toe playing as the best first move. The experimental result revealed that the center is the best, a corner the next and a side the last as the best first move.

Implementation and Evaluation of Path-Finding Algorithm using Abstract Graphs (추상 그래프를 활용한 경로 탐색 알고리즘의 구현 및 성능 평가)

  • Kim, Ji-Soo;Lee, Ji-wan;Cho, Dae-Soo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.245-248
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    • 2009
  • Recently, Many studies have been progressing to path-finding with dynamic information on the Terminal Based Navigation System(TBNS). However, the most of existing algorithms are based on $A{\ast}$ algorithm. Path-finding algorithms which use heuristic function may occur a problem of the increase of exploring cost in case of that there is no way determined by heuristic function or there are 2 way more which have almost same cost. In this paper, two abstract graph(AG) that are different method of construction, Homogeneous Node merging($AG^H$) and Connected Node Merging($AG^C$), are implemented. The abstract graph is a simple graph of real road network. The method of using the abstract graph is proposed for reducing dependency of heuristic and exploring cost. In result of evaluation of performance, $AG^C$ has better performance than $AG^H$ at construction cost but $AG^C$ has worse performance than $AG^H$ exploring cost.

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Integer Programming-based Local Search Technique for Linear Constraint Satisfaction Optimization Problem (선형 제약 만족 최적화 문제를 위한 정수계획법 기반 지역 탐색 기법)

  • Hwang, Jun-Ha;Kim, Sung-Young
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.9
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    • pp.47-55
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    • 2010
  • Linear constraint satisfaction optimization problem is a kind of combinatorial optimization problem involving linearly expressed objective function and complex constraints. Integer programming is known as a very effective technique for such problem but require very much time and memory until finding a suboptimal solution. In this paper, we propose a method to improve the search performance by integrating local search and integer programming. Basically, simple hill-climbing search, which is the simplest form of local search, is used to solve the given problem and integer programming is applied to generate a neighbor solution. In addition, constraint programming is used to generate an initial solution. Through the experimental results using N-Queens maximization problems, we confirmed that the proposed method can produce far better solutions than any other search methods.