• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.4
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• pp.22-31
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• 2002

A high-speed rail system represents a typical example of large-scale multi-disciplinary systems, consisting of subsystems such as train, electrical hardware, electronics, control, information, communication, civil technology etc. The system design and acquisition data of the large-scale system must be the subject under strict configuration control and management. Not only the requirements of the large-scale system dictate the contracts with the suppliers but also become the basis for the development process, project execution, system integration, and testing. The requirements database provide the system design specification of all development activities. Using the RDD-100, a systems engineering tool, the Korea next-generation high-speed rail program can establish requirements traceability and development process management in performing the enabling train technology development projects. This paper presents the results from a computer-aided systems engineering application to the Korea next-generation high-speed railway project. Especially, the focus of the study was on requirement management and PBS(Product Breakdown Structure) management.

• Korean Institute of Interior Design Journal
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• v.19 no.3
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• pp.260-268
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• 2010

At a passenger terminal which is a core facility of a large-scale airport, users are not easy to recognize its space and to approach each facility by composition of large-scale space not recognized at a glance and arrangement of complicated functional space. Such a passenger terminal should be designed by putting a focus on functionality, safety and convenience since diverse passengers use it. At a passenger terminal, a lot of passengers' circulation followed by diverse purpose appear. Therefore, it needs a lot of functional space and space to satisfy passengers' demands. When circulation is planed, it should be designed by a systematic standard. The study was carried out on the basis of international airports, considering features and functions of airport circulation system. In kind of circulation in passenger terminal of an airport, there are user's circulation (passenger's circulation, employee's circulation and service circulation) and baggage circulation. The study examined passenger's circulation which was a major circulation of passenger terminal out of user's circulation. The study examined elements which had an effect on circulation system at a large-scale airport passenger terminal and basic data for an efficient circulation system standard of passenger terminal through case analysis of passenger terminal circulation systems at international airports.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.13 no.1
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• pp.41-47
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• 1995

In this study, we try to develope the radio control photographing system with 35 mm camera to obtain 3-dimension large scale geographic information more effectively, to automatize and computerize the basic design and practical design of road. By applying this system on getting data which is needed to design road, this study has an object to promote efficiency in possesion and management of geographic information. As result of this study, this system could obtain geographic information effectively on the object region, could get large scale geographic information which was suitable for expected accuracy by photographing in 400 m height and could ac-quire profile, crossection and earth-work volume quickly and exactly.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1041-1045
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• 2010

Clusters can provide scalable and flexible architectures for parallel computing servers and data centers. Their performance prediction has been a very challenging issue. Existing performance measurement methodologies are able to measure the performance of servers already constructed. Thus they cannot provide a way to predict the overall system performance in advance when designing the system at the initial phase or adding more nodes for more capacity. Therefore, the performance modeling and prediction methodology for large-scale clusters is highly required. In this paper, we suggest a methodology to predict the performance of large-scale clusters, which consists of measurement, modeling and prediction steps. We apply the methodology to a real cluster server and show its usefulness.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.373-380
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• 2022

The field of land surveying is changing dramatically due to the way data is processed, analyzed and presented. Also, there is a growing demand for digital spatial information, coming primarily from the GIS (Geographical Information System) user community. Such a demand has created a strong development potential for a new land surveying software. An overview of the development and capabilities of a land surveying software platform based on the Windows system, SurveyingMap, is presented. Among its many features, SurveyingMap provides a lot of adaptability for networks adjustment, geodetic and plane coordinates transformation, contouring, sectioning, DTM (Digital Terrain Model) generation, and large scale mapping applications. The system output is compatible with well known computer aided drafting (CAD) /GIS packages to expand its scope of applications. SurveyingMap is also suitable for non-technical users due to the user-friendly graphic user interface. The system could be used in engineering, architecture, GIS, and academic teaching and research, among other fields. Two applications of SurveyingMap, extension of field control and large scale mapping, for the case study area are established. The results demonstrate that the system is adaptable and reasonably priced for use by college and university students.

• Phonetics and Speech Sciences
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• v.15 no.3
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• pp.83-88
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• 2023

This study investigates the fine-tuning of large-scale Automatic Speech Recognition (ASR) models, specifically OpenAI's Whisper model, for domain-specific applications using the KsponSpeech dataset. The primary research questions address the effectiveness of targeted lexical item emphasis during fine-tuning, its impact on domain-specific performance, and whether the fine-tuned model can maintain generalization capabilities across different languages and environments. Experiments were conducted using two fine-tuning datasets: Set A, a small subset emphasizing specific lexical items, and Set B, consisting of the entire KsponSpeech dataset. Results showed that fine-tuning with targeted lexical items increased recognition accuracy and improved domain-specific performance, with generalization capabilities maintained when fine-tuned with a smaller dataset. For noisier environments, a trade-off between specificity and generalization capabilities was observed. This study highlights the potential of fine-tuning using minimal domain-specific data to achieve satisfactory results, emphasizing the importance of balancing specialization and generalization for ASR models. Future research could explore different fine-tuning strategies and novel technologies such as prompting to further enhance large-scale ASR models' domain-specific performance.

• Journal of Korea Multimedia Society
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• v.16 no.5
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• pp.657-666
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• 2013

Today, many aspects of our lives are characterized by the rapid influx of large amounts of data from various application domains. The applications that produce this massive of data span a large spectrum, from social media to business intelligence or biology. This massive influx of data necessitates large scale parallelism for efficiently supporting a large class of analysis tasks. Recently, there have been extensive studies in using MapReduce framework to support large parallelism. While this technique has produced impressive results in diverse applications, the same can not be said for multimedia applications where most of users are interested in a small number of results having high or low score. Thus, in this paper, we develop the data partitioning algorithm which is able to efficiently process large data set having different data utility. The experiment results show that the proposed technique provides significant execution time gains over the existing solution.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.20 no.1
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• pp.37-50
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• 2016

A large eddy simulation (LES) of a turbulent channel flow is performed by using the third order low-storage Runge-Kutta method in time and second order finite difference formulation in space with staggered grid at a Reynolds number, $Re_{\tau}=590$ based on the channel half width, ${\delta}$ and wall shear velocity, $u_{\tau}$. To reduce the calculation cost of LES, algebraic wall model (AWM) is applied to approximate the near-wall region. The computation is performed in a domain of $2{\pi}{\delta}{\times}2{\delta}{\times}{\pi}{\delta}$ with $32{\times}20{\times}32$ grid points. Standard Smagorinsky model is used for subgrid-scale (SGS) modeling. Essential turbulence statistics of the flow field are computed and compared with Direct Numerical Simulation (DNS) data and LES data using no wall model. Agreements as well as discrepancies are discussed. The flow structures in the computed flow field have also been discussed and compared with LES data using no wall model.

• Journal of applied mathematics & informatics
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• v.28 no.1_2
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• pp.351-361
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• 2010

The solution of large sparse linear systems is one of the most important problems in large scale scientific computing. Among the many methods developed, the preconditioned Krylov subspace methods are considered the preferred methods. Selecting a suitable preconditioner with appropriate parameters for a specific sparse linear system presents a challenging task for many application scientists and engineers who have little knowledge of preconditioned iterative methods. The prediction of ILU type preconditioners was considered in [27] where support vector machine(SVM), as a data mining technique, is used to classify large sparse linear systems and predict best preconditioners. In this paper, we apply the data mining approach to the sparse approximate inverse(SAI) type preconditioners to find some parameters with which the preconditioned Krylov subspace method on the linear systems shows best performance.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.235-235
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• 2012

The "Widefield ASKAP L-band Legacy All-sky Blind surveY" (WALLABY) is an extragalactic HI survey which aims to examine HI properties and large-scale distribution of ~500,000 galaxies out to z ~ 0.27, covering a wide range of science goals associated with galaxy formation and evolution (P.I.: B. Koribalski & L. Staveley-Smith). The combination of ASKAP's exquisite column density sensitivity and a large primary beam will make it possible to systematically investigate the rarely explored low column-density HI in the universe. Ultimately, the largest and most homogeneous data set from WALLABY will drastically improve and broaden our knowledge on galaxy formation and evolution. ASKAP will be on-line in 2013, so to ensure timely and efficient reduction and analysis of the large WALLABY data set, we have been developing and testing reliable source finding tools and data analysis pipelines. In this talk I present recent progress of WALLABY, especially on the kinematic parameterisation pipeline for the spatially resolved galaxies detected by WALLABY.