• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2005년도 한국컴퓨터종합학술대회 논문집 Vol.32 No.1 (A)
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• pp.820-822
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• 2005

The current paper is on a study of the performance estimation fer data processing time and CPU utilization to efficiently develop the real-time system. The analytical modeling and OPNET modeling and benchmarking tests are applied to perform the estimation for data processing time and CPU utilization in real-time system. We demonstrate that the estimation results can be predicted fairly and accurately through the benchmarking test results although there is a small variance between the estimation results and the benchmarking test results.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.831-838
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• 2022

Machine Learning is a process of using computer algorithms to extract information from raw data to solve complex problems in a data-rich environment. It has been used in the construction industry by both academics and practitioners for multiple applications to improve the construction process. The Construction Industry Institute, a leading construction research organization has twenty-five years of experience in benchmarking capital projects in the industry. The organization is at an advantage to develop useful machine learning applications because it possesses enormous real construction data. Its benchmarking programs have been actively used by owner and contractor companies today to assess their capital projects' performance. A credible benchmarking program requires statistically valid data without subjective interference in the program administration. In developing the next-generation benchmarking program, the Data Warehouse, the organization aims to use machine learning algorithms to minimize human effort and to enable rapid data ingestion from diverse sources with data validity and reliability. This research effort uses a focus group comprised of practitioners from the construction industry and data scientists from a variety of disciplines. The group collaborated to identify the machine learning requirements and potential applications in the program. Technical and domain experts worked to select appropriate algorithms to support the business objectives. This paper presents initial steps in a chain of what is expected to be numerous learning algorithms to support high-performance computing, a fully automated performance benchmarking system.

• 로봇학회논문지
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• 제7권4호
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• pp.292-298
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• 2012

It is a real-time system that the system correctness depends not only on the correctness of the logical result of the computation but also on the result delivery time. Real-time Operating System (RTOS) is a software that manages the time of a microprocessor to ensure that the most important code runs first so that it is a good building block to design the real-time system. The real-time performance is achieved by using real-time mechanisms through data communication and synchronization of inter-task communication (ITC) between tasks. Therefore, test on the response time of real-time mechanisms is a good measure to predict the performance of real-time systems. This paper aims to analysis the response characteristics of real-time mechanisms in kernel space for real-time embedded Linux: RTAI and Xenomai. The performance evaluations of real-time mechanism depending on the changes of task periods are conducted. Test metrics are jitter of periodic tasks and response time of real-time mechanisms including semaphore, real-time FIFO, Mailbox and Message queue. The periodicity of tasks is relatively consistent for Xenomai but RTAI reveals smaller jitter as an average result. As for real-time mechanisms, semaphore and message transfer mechanism of Xenomai has a superior response to estimate deterministic real-time task execution. But real-time FIFO in RTAI shows faster response. The results are promising to estimate deterministic real-time task execution in implementing real-time systems using real-time embedded Linux.

• 전기전자학회논문지
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• 제22권3호
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• pp.585-589
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• 2018

Consumer demand for high quality image/video services led to growing trend in image quality enhancement study. Therefore, recent years was a period of substantial progress in this research field. Through careful observation of the image quality after processing by image enhancement algorithms, we perceived that the dark region in the image usually suffered loss of contrast to a certain extent. In this paper, the low-light stretch preprocessing algorithm is, hence, proposed to resolve the aforementioned issue. The proposed approach is evaluated qualitatively and quantitatively against the well-known histogram equalization and Photoshop curve adjustment. The evaluation results validate the efficiency and superiority of the low-light stretch over the benchmarking methods. In addition, we also propose the 255MHz-capable hardware implementation to ease the process of incorporating low-light stretch into real-time imaging systems, such as aerial surveillance and monitoring with drones and driving aiding systems.

• 경영과학
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• 제23권2호
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• pp.175-185
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• 2006

How to efficiently manage assembly blocks at shipyard has been a hot management issue in the shipbuilding Industry, because it has significantly influenced on the productivity of shipbuilding process. This paper introduces the real practice of assembly block operations management in Hyundai Heavy Industries (HHI) and the Ship Assembly Block Operations Optimization (SABOO) project that h3s been launched in HHI as an academy-and-industry collaborative project, aimed to diagnose problems, propose possible solutions, and develop a prototype system in order to search ways of improving the assembly block operations management. Through the field interviews, observations, and benchmarking studies, the SABOO project diagnosed the most rudimental and urgent problem and proposed possible solutions. In addition, the SABOO project developed the prototype system that embodied the visual function of monitoring the shipyard on a real-time and the Interactive block assignment function that utilized the assembly block assignment algorithm developed by the project. As a whole, the SABOO project tested the possibility and gained an insight in extending the functions of block transportation/stockyard management system.

• 한국정보과학회논문지:소프트웨어및응용
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• 제37권9호
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• pp.694-705
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• 2010

진화 프로그래밍은 실수형 최적화 문제에 널리 사용되는 알고리즘으로 돌연변이 연산이 중요한 연산이다. 일반적으로 돌연변이 연산은 확률 분포와 이에 따른 매개변수를 사용하여 변수값을 변화시키는데, 이 때 매개변수 역시 돌연변이 연산의 대상이 됨으로 이를 위한 또 다른 매개변수가 필요하다. 그러나 최적의 매개변수 값은 주어진 문제에 전적으로 의존하기 때문에 매개변수 개수가 많은 경우 매개변수값들에 대한 최적 조합을 찾기 어렵다. 이러한 문제를 부분적으로나마 해결하기 위하여 본 논문에서는 변수의 돌연변이 연산을 위한 매개변수를 자기 적응적 관점에서 이론적으로 추정한 돌연변이 연산을 제안하였다. 제안한 알고리즘에서는 코시 확률 분포의 축척 매개변수를 추정하여 돌연변이 연산에 적용함으로 축척 매개변수에 대한 돌연변이 연산이 필요하지 않다는 장점이 있다. 제안한 알고리즘을 벤치마킹 문제에 적용한 실험 결과를 통해 볼 때, 최적값 측면에서는 제안한 알고리즘의 상대적 우수성은 벤치마킹 문제에 의존하였으나 계산 시간 측면에서는 모든 벤치마킹 문제에 대하여 제안한 알고리즘이 우수하였다.

• 정보과학회 논문지
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• 제44권2호
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• pp.115-123
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• 2017

메시지 처리기란 다양한 클라이언트로부터 오는 메시지를 받아 처리하는 서버 소프트웨어이며, 메시지의 종류에 따라 마감기한 이내에 처리해야 하는 실시간 메시지와 비실시간 메시지를 처리한다. 최근 마이크로프로세서 기술의 발전과 리눅스의 빠른 보급에 따라 메시지 처리기는 멀티코어 기반의 리눅스 서버에서 구현되고 있으며, 멀티코어 환경에서는 코어를 효율적으로 사용해야 시스템의 성능을 극대화 시킬 수 있다. 멀티코어를 효율적으로 사용하기 위한 다양한 실시간 스케줄러가 제안되어 있지만, 많은 연구들이 이론적 분석이나 시뮬레이션에 국한되어 있고, 리눅스를 위해 제안된 일부 알고리즘들도 커널을 수정하거나 특정 커널 버전에서만 동작된다는 단점이 있다. 본 논문에서는 멀티코어 환경에서 쓰레드를 사용자 수준에서 코어에 직접 매핑하는 리눅스 기반 메시지 처리기의 구조를 제안한다. 구현된 메시지 처리기에서는 기존의 RM(Rate Monotonic) 알고리즘을 수정하여 사용하였고, 특정 코어에 최대한 실시간 메시지를 몰아서 처리하도록 First fit 기반의 빈패킹(Bin-Packing) 알고리즘을 사용하여, 실시간 메시지의 위배율을 보장하면서 비실시간 메시지의 응답시간의 지연을 최소화하였다. 성능평가를 위하여 LITMUS 프레임 워크에서 제공하는 2가지 멀티코어 스케줄링 알고리즘(GSN-EDF, P-FP)을 이용하여 메시지 처리기를 구현한 후 제안된 시스템과 비교한 결과, 비실시간 메시지의 응답시간이 2가지 알고리즘 대비 최대 17~18%까지 향상되는 것을 확인하였다.

• 대한안전경영과학회지
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• 제9권6호
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• pp.123-135
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• 2007

In the recent years, the companies have manually recorded a production status in a work diary or have mainly used a bar code in order to collect each process's progress status, production performance and quality information in the production and logistics process in real time. But, it requires an additional work because the worker's record must be daily checked or the worker must read it with the bar code scanner. At this time, data's accuracy is decreased owing to the worker's intention or mistake, and it causes the problem of the system's reliability. Accordingly, in order to solve such problem, the companies have introduced RFID which comes into the spotlight in the latest automatic identification field. In order to introduce the RFID technology, the process flow must be analyzed, but the ASME sign used by most manufacturing companies has the difficult problem when the aggregation event occurs. Hence, in this study, the RFID logistic flow analysis Modeling Notation was proposed as the signature which can analyze the manufacturing logistic flow amicably, and the manufacturing logistic flow by industry type was analyzed by using the proposed RFID logistic flow analysis signature. Also, to monitor real-time information through EPCglobal network, EPCISEvent template by industry was proposed, and it was utilized as the benchmarking case of companies for RFID introduction. This study suggested to ensure the decision-making on real-time information through EPCglobal network. This study is intended to suggest the Modeling Notation suitable for RFID characteristics, and the study is intended to establish the business step and to present the vocabulary.

• Nuclear Engineering and Technology
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• 제51권7호
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• pp.1715-1720
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• 2019

Jozef Stefan Institute (JSI), TRIGA Mark II reactor employs the homogeneous mixture of uranium and zirconium hydride fuel type. Since its upgrade, a series of fresh fuel steady state experimental benchmarks have been conducted. The benchmark results have provided data for testing computational neutronics codes which are important for reactor design and safety analysis. In this work, we investigated the JSI TRIGA Mark II reactor neutronics characteristics: the effective multiplication factor and two safety parameters, namely the control rod worth and the fuel temperature reactivity coefficient using SuperMC. The modeling and real-time cross section generation methods of SuperMC were evaluated in the investigation. The calculation analysis indicated the following: the effective multiplication factor was influenced by the different cross section data libraries; the control rod worth evaluation was better with Monte Carlo codes; the experimental fuel temperature reactivity coefficient was smaller than calculated results due to change in water temperature. All the results were in good agreement with the experimental values. Hence, SuperMC could be used for the designing and benchmarking of other TRIGA Mark II reactors.

• 자원환경지질
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• 제52권6호
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• pp.637-645
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• 2019

지능정보사회 전환에 따라 급격한 삶의 모습과 환경 변화가 예상되고 있으며, 과학기술부와 국가과학기술연구회는 기존의 3년 단위의 과학기술계 출연연구원의 기관평가를 중장기 관점으로 5년 단위의 기관 사업계획과 평가를 도입하였다. 따라서 지질자원 분야에 대해서도 공공적 관점으로 중장기 연구개발 주제 도출이 시급하다. 본 연구는 국외 지질자원 관련 공공 연구기관의 중장기 전략 수집, 국외 대학 및 연구기관의 전문가 서면 조사, 국외 시장정보 보고서 분석을 통해 산·학·연 분야를 두루 포함한 국외 벤치마킹 정보를 수집한다. 영국지질조사소, 일본산업기술종합연구소, 미국지질조사소는 중장기 계획에서 3차원 국가 지질정보, 화산/지진/토양 침식/산사태 등 지질환경재해 예측, 저탄소 경제 전환 및 4차 산업혁명 시대에 중요한 금속/소재 광물자원 개발 등을 제시했다. 프랑스 IPGP-CNRS와 핀란드 지질조사소 등의 국외 연구소 및 대학의 전문가 조사를 통해서 중장기계획으로 지질정보에 대한 기초·기반연구를 강조하고 있으며, 세부 연구 주제로 지구 핵에서부터 표면에까지 지구/지진의 변형 과정 연구, 최신 지질 정보 생산을 살펴볼 수 있었다. 광업자동화 및 디지털 지도 분야 시장 분석으로 시장에서 요구하는 공공연구기관의 역할이 기대되는 분야를 도출할 수 있었다. 육상·공중에서 데이터 수집 및 모바일/3차원 정보 제작, 자연스럽고 빠르며 실시간의 지도 제공, 주문제작 지도 설계, 여러 플랫폼에 적용가능한 지도 제작 지원, 지질환경재해 위험평가/재난관리 정보 및 지도 제공에 대한 지질자원 분야의 중장기적인 연구개발이 요구된다.