• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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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.

• International conference on construction engineering and project management
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• 2022.06a
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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.

• The Journal of Korea Robotics Society
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• v.7 no.4
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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.

• Journal of IKEEE
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• v.22 no.3
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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.

• Korean Management Science Review
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• v.23 no.2
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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.

• Journal of KIISE:Software and Applications
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• v.37 no.9
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• pp.694-705
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• 2010

The mutation operation is the main operation in the evolutionary programming which has been widely used for the optimization of real valued function. In general, the mutation operation utilizes both a probability distribution and its parameter to change values of variables, and the parameter itself is subject to its own mutation operation which requires other parameters. However, since the optimal values of the parameters entirely depend on a given problem, it is rather hard to find an optimal combination of values of parameters when there are many parameters in a problem. To solve this shortcoming at least partly, if not entirely, in this paper, we propose a new mutation operation in which the parameter for the variable mutation is theoretically estimated from the self-adaptive perspective. Since the proposed algorithm estimates the scale parameter of the Cauchy probability distribution for the mutation operation, it has an advantage in that it does not require another mutation operation for the scale parameter. The proposed algorithm was tested against the benchmarking problems. It turned out that, although the relative superiority of the proposed algorithm from the optimal value perspective depended on benchmarking problems, the proposed algorithm outperformed for all benchmarking problems from the perspective of the computational time.

• Journal of KIISE
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• v.44 no.2
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• pp.115-123
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• 2017

A message processor is server software that receives non-realtime messages as well as realtime messages from clients that need to be processed within a deadline. With the recent advances of micro-processor technologies and Linux, the message processor is often implemented in Linux-based multi-core servers and it is important to use cores efficiently to maximize the performance of system in multi-core environments. Numerous research efforts on a real-time scheduler for the efficient utilization of the multi-core environments have been conducted. Typically, though, they have been conducted theoretically or via simulation, making a subsequent real-system application difficult. Moreover, many Linux-based real-time schedulers can only be used in a specific Linux version, or the Linux source code needs to be modified. This paper presents the design of a Linux-based message processor for multi-core environments that maps the threads to the cores at user level. The message processor is implemented through a modification of the traditional RM algorithm that consolidates the real-time messages into certain cores using a first-fit-based bin-packing algorithm; this minimizes the response-time delay of the non-real-time messages, while guaranteeing the violation rate of the real-time messages. To compare the performances, the message processor was implemented using the two multi-core-scheduling algorithms GSN-EDF and P-FP, which are provided by the LITMUS framework. The benchmarking results show that the response-time delay of non-real-time messages in the proposed system was improved up to a maximum of 17% to 18%.

• Journal of the Korea Safety Management & Science
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• v.9 no.6
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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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• v.51 no.7
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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.

• Economic and Environmental Geology
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• v.52 no.6
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• pp.637-645
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• 2019

Due to the transformation to the intelligent information society, the rapid change of our life and environment is expected. The Ministry of Science and ICT (MSIT) and the National Research Council of Science and Technology (NST) introduced a five-year government supported research institution's planning and evaluation based on the mid-to long-term perspective. This study collects international benchmarking information including industry, academia, and research fields by collecting mid- and long-term strategy reports from public research institutes, surveys by experts from abroad universities and research institutes, and analyzing overseas market information reports. The British Geological Survey (BGS), the U.S. Geological Survey (USGS) and the japanese geological survey related institutes (AIST-GSJ) plans for three-dimensional national geological information, predictions of geological environmental disasters, and development of important metals and material in the low carbon economic transformation and in the era of the Fourth Industrial Revolution. The mid- and long-term program emphasizes basic and public research on geological information through abroad experts survey such as the IPGP-CNRS etc. The market analysis of the mining automation and digital map sectors has been able to derive the fields in which the role of public research institutes by the market is expected such as data collection on land and in the air, mobile or three-dimensional information production, smooth/fast/real-time maps, custom map design, mapping support to various platforms, geological environmental risk assessment and disaster management information and maps.