• Title/Summary/Keyword: 컴퓨터 자동화 시스템

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Development of a gridded crop growth simulation system for the DSSAT model using script languages (스크립트 언어를 사용한 DSSAT 모델 기반 격자형 작물 생육 모의 시스템 개발)

  • Yoo, Byoung Hyun;Kim, Kwang Soo;Ban, Ho-Young
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.20 no.3
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    • pp.243-251
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    • 2018
  • The gridded simulation of crop growth, which would be useful for shareholders and policy makers, often requires specialized computation tasks for preparation of weather input data and operation of a given crop model. Here we developed an automated system to allow for crop growth simulation over a region using the DSSAT (Decision Support System for Agrotechnology Transfer) model. The system consists of modules implemented using R and shell script languages. One of the modules has a functionality to create weather input files in a plain text format for each cell. Another module written in R script was developed for GIS data processing and parallel computing. The other module that launches the crop model automatically was implemented using the shell script language. As a case study, the automated system was used to determine the maximum soybean yield for a given set of management options in Illinois state in the US. The AgMERRA dataset, which is reanalysis data for agricultural models, was used to prepare weather input files during 1981 - 2005. It took 7.38 hours to create 1,859 weather input files for one year of soybean growth simulation in Illinois using a single CPU core. In contrast, the processing time decreased considerably, e.g., 35 minutes, when 16 CPU cores were used. The automated system created a map of the maturity group and the planting date that resulted in the maximum yield in a raster data format. Our results indicated that the automated system for the DSSAT model would help spatial assessments of crop yield at a regional scale.

Ontology Based Semantic Information System for Grid Computing (그리드 컴퓨팅을 위한 온톨로지 기반의 시맨틱 정보 시스템)

  • Han, Byong-John;Kim, Hyung-Lae;Jeong, Chang-Sung
    • Journal of Internet Computing and Services
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    • v.10 no.4
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    • pp.87-103
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    • 2009
  • Grid computing is an expanded technology of distributed computing technology to use low-cost and high-performance computing power in various fields. Although the purpose of Grid computing focuses on large-scale resource sharing, innovative applications, and in some case, high-performance orientation, it has been used as conventional distributed computing environment like clustered computer until now because Grid middleware does not have common sharable information system. In order to use Grid computing environment efficiently which consists of various Grid middlewares, it is necessary to have application-independent information system which can share information description and services, and expand them easily. Thus, in this paper, we propose a semantic information system framework based on web services and ontology for Grid computing environment, called WebSIS. It makes application and middleware developer easy to build sharable and extensible information system which is easy to share information description and can provide ontology based platform-independent information services. We present efficient ontology based information system architecture through WebSIS. Discovering appropriate resource for task execution on Grid needs more high-level information processing because Grid computing environment is more complex than other traditional distributed computing environments and has various considerations which are needed for Grid task execution. Thus, we design and implement resource information system and services by using WebSIS which enables high-level information processing by ontology reasoning and semantic-matching, for automation of task execution on Grid.

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Cooperative Multi-Agent Reinforcement Learning-Based Behavior Control of Grid Sortation Systems in Smart Factory (스마트 팩토리에서 그리드 분류 시스템의 협력적 다중 에이전트 강화 학습 기반 행동 제어)

  • Choi, HoBin;Kim, JuBong;Hwang, GyuYoung;Kim, KwiHoon;Hong, YongGeun;Han, YounHee
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.8
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    • pp.171-180
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    • 2020
  • Smart Factory consists of digital automation solutions throughout the production process, including design, development, manufacturing and distribution, and it is an intelligent factory that installs IoT in its internal facilities and machines to collect process data in real time and analyze them so that it can control itself. The smart factory's equipment works in a physical combination of numerous hardware, rather than a virtual character being driven by a single object, such as a game. In other words, for a specific common goal, multiple devices must perform individual actions simultaneously. By taking advantage of the smart factory, which can collect process data in real time, if reinforcement learning is used instead of general machine learning, behavior control can be performed without the required training data. However, in the real world, it is impossible to learn more than tens of millions of iterations due to physical wear and time. Thus, this paper uses simulators to develop grid sortation systems focusing on transport facilities, one of the complex environments in smart factory field, and design cooperative multi-agent-based reinforcement learning to demonstrate efficient behavior control.

Design and Implementation of Sequential Pattern Miner to Analyze Alert Data Pattern (경보데이터 패턴 분석을 위한 순차 패턴 마이너 설계 및 구현)

  • Shin, Moon-Sun;Paik, Woo-Jin
    • Journal of Internet Computing and Services
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    • v.10 no.2
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    • pp.1-13
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    • 2009
  • Intrusion detection is a process that identifies the attacks and responds to the malicious intrusion actions for the protection of the computer and the network resources. Due to the fast development of the Internet, the types of intrusions become more complex recently and need immediate and correct responses because the frequent occurrences of a new intrusion type rise rapidly. Therefore, to solve these problems of the intrusion detection systems, we propose a sequential pattern miner for analysis of the alert data in order to support intelligent and automatic detection of the intrusion. Sequential pattern mining is one of the methods to find the patterns among the extracted items that are frequent in the fixed sequences. We apply the prefixSpan algorithm to find out the alert sequences. This method can be used to predict the actions of the sequential patterns and to create the rules of the intrusions. In this paper, we propose an extended prefixSpan algorithm which is designed to consider the specific characteristics of the alert data. The extended sequential pattern miner will be used as a part of alert data analyzer of intrusion detection systems. By using the created rules from the sequential pattern miner, the HA(high-level alert analyzer) of PEP(policy enforcement point), usually called IDS, performs the prediction of the sequence behaviors and changing patterns that were not visibly checked.

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Analysis of the application of image quality assessment method for mobile tunnel scanning system (이동식 터널 스캐닝 시스템의 이미지 품질 평가 기법의 적용성 분석)

  • Chulhee Lee;Dongku Kim;Donggyou Kim
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.26 no.4
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    • pp.365-384
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    • 2024
  • The development of scanning technology is accelerating for safer and more efficient automated inspection than human-based inspection. Research on automatically detecting facility damage from images collected using computer vision technology is also increasing. The pixel size, quality, and quantity of an image can affect the performance of deep learning or image processing for automatic damage detection. This study is a basic to acquire high-quality raw image data and camera performance of a mobile tunnel scanning system for automatic detection of damage based on deep learning, and proposes a method to quantitatively evaluate image quality. A test chart was attached to a panel device capable of simulating a moving speed of 40 km/h, and an indoor test was performed using the international standard ISO 12233 method. Existing image quality evaluation methods were applied to evaluate the quality of images obtained in indoor experiments. It was determined that the shutter speed of the camera is closely related to the motion blur that occurs in the image. Modulation transfer function (MTF), one of the image quality evaluation method, can objectively evaluate image quality and was judged to be consistent with visual observation.

DOVE : A Distributed Object System for Virtual Computing Environment (DOVE : 가상 계산 환경을 위한 분산 객체 시스템)

  • Kim, Hyeong-Do;Woo, Young-Je;Ryu, So-Hyun;Jeong, Chang-Sung
    • Journal of KIISE:Computing Practices and Letters
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    • v.6 no.2
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    • pp.120-134
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    • 2000
  • In this paper we present a Distributed Object oriented Virtual computing Environment, called DOVE which consists of autonomous distributed objects interacting with one another via method invocations based on a distributed object model. DOVE appears to a user logically as a single virtual computer for a set of heterogeneous hosts connected by a network as if objects in remote site reside in one virtual computer. By supporting efficient parallelism, heterogeneity, group communication, single global name service and fault-tolerance, it provides a transparent and easy-to-use programming environment for parallel applications. Efficient parallelism is supported by diverse remote method invocation, multiple method invocation for object group, multi-threaded architecture and synchronization schemes. Heterogeneity is achieved by automatic data arshalling and unmarshalling, and an easy-to-use and transparent programming environment is provided by stub and skeleton objects generated by DOVE IDL compiler, object life control and naming service of object manager. Autonomy of distributed objects, multi-layered architecture and decentralized approaches in hierarchical naming service and object management make DOVE more extensible and scalable. Also,fault tolerance is provided by fault detection in object using a timeout mechanism, and fault notification using asynchronous exception handling methods

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A Study for Autonomous Intelligence of Computer-Generated Forces (가상군(Computer-Generated Forces)의 자율지능화 방안 연구)

  • Han, Chang-Hee;Cho, Jun-Ho;Lee, Sung-Ki
    • Journal of the Korea Society for Simulation
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    • v.20 no.1
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    • pp.69-77
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    • 2011
  • Modeling and Simulation(M&S) technology gets an attention from various parts such as industry and military. Especially, military uses the technology to cope with a different situation from the one in the Cold War and maximize the effect of training against the cost in the new environment. In order for the training based on M&S technology to be effective, the situations of a battlefield and a combat must be more realistically simulated. For this, a technique development on Computer-Generated Forces(CGF) which represents a unit's simulation logic and a human's simulated behaviors is focused. The CGF simulating a human's behaviors can be used in representing an enemy force, experimenting behaviors in a future war, and developing a new combat idea. This paper describes a methodology to accomplish Computer-Generated Forces' autonomous intelligence. It explains the process of applying a task behavior list based on the METT+T element onto CGFs. On the other hand, in the domain knowledge of military field manual, fuzzy facts such as "fast" and "sufficient" whose real values should be decided by domain experts can be easily found. In order to efficiently implement military simulation logics involved with such subjectivity, using a fuzzy inference methodology can be effective. In this study, a fuzzy inference methodology is also applied.

A Study on the Development Direction of Medical Image Information System Using Big Data and AI (빅데이터와 AI를 활용한 의료영상 정보 시스템 발전 방향에 대한 연구)

  • Yoo, Se Jong;Han, Seong Soo;Jeon, Mi-Hyang;Han, Man Seok
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.9
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    • pp.317-322
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    • 2022
  • The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.

Wet-end Monitoring Experience in Liner Paper Mill (라이너지 제지공장의 습부공정 모니터링 경험)

  • 신종호;류정용;김용환;송봉근
    • Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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    • 2001.11a
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    • pp.57-58
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    • 2001
  • 용수 다소비 산업으로 분류되는 제지공업의 특성 상, 용수사용의 억제 및 용수의 무방류화에 대한 압력이 증가되고 있는 반면, 초지환경은 날로 열악해지고 있는 실정이다. 한 예로써, 용지의 재활용율 및 재사용 비율이 증가함에 따라 원료의 저급화가 심 각한 수준에 이르고 있으며, 이러한 초지환경의 변화는 각질화되고 극도로 미세화된 다량의 미세섬유 발생 및 잡고지로부터 유입되는 점착성 이물질과 무기 충진제의 도입 등을 유발함으로서 제품의 물리적 성질 저하, 탈수부하 증가로 인한 생산성 저하, 약품사용량 증가 등을 초래하여, 결과적으로는 폐수처리장의 부하를 증대시킴과 동시에 청수사용량 및 폐수방류량을 증가시키는 악순환을 되풀이하게 된다. 국내 제지산업이 국제적 경쟁력을 갖추기 위해서는 제품의 증대가 필수적이나, 원료와 설비의존도를 감안할 때, 제품특성과 공정 분을 결정하는 습부공정을 정확히 파악하여 최적 운전조건을 확립하는 것이 가장 경제적이고 용이한 방법일 뿐만 아니라 전체 제지공정의 정정화에도 기여할 수 있을 것으로 판단된다. 일정규모이상의 종이를 생산하는 제지공장은 거의 대부분 컴퓨터로 처리되는 온라인 공정조절 시스템(On-line process control system)을 구비하고 료의 도입에서부터 설비운전 및 제품의 기본적인 품질관리까지 실시간의 자동화되고 안정적인 운전과 관리시스템을 유지하고 있다. 그러나 전체 제지공정 중, 제품 물성과 운전조건의 대부분을 결정하는 습부공정만큼은 아직도 주기적인 분석이 행해지고 있지 않을 뿐만 아니라, 슬러리의 농도나 보류도 정도를 제이하면 분석항목 조차도 변변히 확립되어 있지 않을 실정이다. 이는 다량의 물 속에 존재하게 되는 용전물질(Dissolved solids, DS), 부유물질(Suspended solids, SS), 섬 유(Fibers), 무기 미 세분(Inorganic f fines), 그리고 투입되는 약품간에 발생하는 계면동전현상 및 이러한 현상과 최종 지제 품의 물성간의 상관관계에 대한 이해 정도나 경험 부족에서 기인하는 것으로 생각된다. 1 1983년 미국제지기술연합회(T APpI)의 제지용 첨가제 분과위원회(Papermaking A Additive Committee)에서는 습부공정의 적절한 조절을 위해 어떤 항목들이 필요하며 그 중요도는 어떠한가를 조사하였으며, 그 결과로 전하밀도, 제타전위, 보류도 및 여수 도, 무기 미세분 함량 등이 중요하다고 보고하였다. 그러나 지료의 전기적 특성을 실시 간으로 측정하는 기자재류가 최근에 이르러서야 도입되고 있는 실정이기 때문에 충분 한 현장적용 사례가 보고되지 못하고 있으며, 결과적으로 얻어진 정보와 최종 지제품의 물성 및 초지기 운전조건과의 상관관계를 확립하는 작업결과는 더욱 찾아보기 어렵다. 따라서, 본 연구에서는, 라이너지 제조공장의 습부공정에 투입되는 약품이 지료 의 전기적 성질, 즉 전하밀도와 제타전위에 미치는 영향을 모니터링함으로서 지료의 전기적 성질들과 습부 공정상태와의 상관관계를 살펴보고자 하였다. 본 연구는 다음과 같은 순서로 진행하였다.

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Big Data based Tourist Attractions Recommendation - Focus on Korean Tourism Organization Linked Open Data - (빅데이터 기반 관광지 추천 시스템 구현 - 한국관광공사 LOD를 중심으로 -)

  • Ahn, Jinhyun;Kim, Eung-Hee;Kim, Hong-Gee
    • Management & Information Systems Review
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    • v.36 no.4
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    • pp.129-148
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    • 2017
  • Conventional exhibition management information systems recommend tourist attractions that are close to the place in which an exhibition is held. Some recommended attractions by the location-based recommendation could be meaningless when nothing is related to the exhibition's topic. Our goal is to recommend attractions that are related to the content presented in the exhibition, which can be coined as content-based recommendation. Even though human exhibition curators can do this, the quality is limited to their manual task and knowledge. We propose an automatic way of discovering attractions relevant to an exhibition of interests. Language resources are incorporated to discover attractions that are more meaningful. Because a typical single machine is unable to deal with such large-scale language resources efficiently, we implemented the algorithm on top of Apache Spark, which is a well-known distributed computing framework. As a user interface prototype, a web-based system is implemented that provides users with a list of relevant attractions when users are browsing exhibition information, available at http://bike.snu.ac.kr/WARP. We carried out a case study based on Korean Tourism Organization Linked Open Data with Korean Wikipedia as a language resource. Experimental results are demonstrated to show the efficiency and effectiveness of the proposed system. The effectiveness was evaluated against well-known exhibitions. It is expected that the proposed approach will contribute to the development of both exhibition and tourist industries by motivating exhibition visitors to become active tourists.

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