• Journal of the Korea Safety Management & Science
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• v.14 no.4
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• pp.229-238
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• 2012

Within last 10 years, internet has become a daily activity, and humankind had to face the Data Deluge, a dramatic increase of digital data (Economist 2012). Due to exponential increase in amount of digital data, large scale data has become a big issue and hence the term 'big data' appeared. There is no official agreement in quantitative and detailed definition of the 'big data', but the meaning is expanding to its value and efficacy. Big data not only has the standardized personal information (internal) like customer information, but also has complex data of external, atypical, social, and real time data. Big data's technology has the concept that covers wide range technology, including 'data achievement, save/manage, analysis, and application'. To define the connected technology of 'big data', there are Big Table, Cassandra, Hadoop, MapReduce, Hbase, and NoSQL, and for the sub-techniques, Text Mining, Opinion Mining, Social Network Analysis, Cluster Analysis are gaining attention. The three features that 'bid data' needs to have is about creating large amounts of individual elements (high-resolution) to variety of high-frequency data. Big data has three defining features of volume, variety, and velocity, which is called the '3V'. There is increase in complexity as the 4th feature, and as all 4features are satisfied, it becomes more suitable to a 'big data'. In this study, we have looked at various reasons why companies need to impose 'big data', ways of application, and advanced cases of domestic and foreign applications. To correspond effectively to 'big data' revolution, paradigm shift in areas of data production, distribution, and consumption is needed, and insight of unfolding and preparing future business by considering the unpredictable market of technology, industry environment, and flow of social demand is desperately needed.

• Proceedings of the KSR Conference
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• 1999.11a
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• pp.46-53
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• 1999

As of July 1999, i,185 lomocotives(excluding metropolitan area electric locomotives) are in Korean National Railroad(KNR). With this limited number of resources assigning locomotives to each trains of timetable is very important in the entire railway management point of view because schedule can be regarded as goods in transportation industry. On a simple rail network, it is rather easier to assign proper locomotives to trains with the experience of operating experts and get optimal assignment solution. However, as the network is getting bigger and complicated, the number of trains and corresponding locomotives will be dramatically increased to rover all the demands required to service all of the trains in timetable. There will be also numerous operational constraints to be considered. Assigning proper locomotives to trains and building optimal cyclic rotations of locomotive routings will result in increasing efficiency of schedule and giving a guarantee of more profit. The purpose of this study is two fold: (1) we consider a planning-level locomotive scheduling problem with the objective of minimizing the wasting cost under various practical constraints and (2) development of implementation prototype program of its assigning result. Not like other countries, i.e. Canada, Sweden, Korean railroad operates on n daily schedule basis. The objective is to find optimal assignment of locomotives of different types to each trains, which minimize the wasting cost. This problem is defined on a planning stage and therefore, does not consider operational constraints such as maintenance and emergency cases. Due to the large scale of the problem size and complexity, we approach with heuristic methods and column generation to find optimal solution. The locomotive scheduling prototype consists of several modules including database, optimization engine and diagram generator. The optimization engine solves MIP model and provides an optimal locomotive schedule using specified optimization algorithms. A cyclic locomotive route diagram can be generated using this optimal schedule through the diagram generator.

• Journal of the Korea Society of Computer and Information
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• v.18 no.12
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• pp.75-82
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• 2013

This paper proposes a $O(n^2)$ polynomial time algorithm to obtain optimal solution for Traveling Salesman problem that is a NP-complete because polynomial time algorithm has been not known yet. The biggest problem in a large-scale Traveling Salesman problem is the fact that the amount of data to be processed is $n{\times}n$, and thus as n increases, the data increases by multifold. Therefore, this paper proposes a methodology by which the data amount is first reduced to approximately n/2. Then, it seeks a bi-directional route at a random point. The proposed algorithm has proved to be successful in obtaining the optimal solutions with $O(n^2)$ time complexity when applied to TSP-1 with 26 European cities and TSP-2 with 46 cities of the USA. It could therefore be applied as a generalized algorithm for TSP.

• Journal of Software Engineering Society
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• v.26 no.4
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• pp.93-103
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• 2013

Complexity and maintenance cost of software increase as much as software has been evolved, therefore importance of software maintenance recently arise. There are many signs that are difficulties to maintain software, called bad smell, in a large-scale software. The bad smell should be removed to improve maintainability. Recently, many software refactoring methods have researched to terminate the bad smell. In this paper, we propose how to identify long parameter list, which causes bad smell, and how to solve the problem for increasing software maintainability. In our approach, we classify the parameters for creating new objects by measuring semantic similarity among them. This is evaluated by experienced software developers, and the result is statistically verified.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.181-186
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• 2018

With progress in industrialization, facilities for generating, delivering, and receiving high levels of electric power are in great demand. The scale of electric power equipment is increasing in both size and complexity. This has contributed to the development of our modern, high-tech and information-based society. However, if the generation of electric power is suspended due to unexpected accidents at power facilities or power stations, a range of equipment the operations of which are dependent on electric power can be damaged, causing substantial socioeconomic losses in an industrial society. A great deal of time and money would be expended to repair damaged facilities at a power station, causing enormous economic loss. In order to detect the deterioration processes of power cables, and to prevent the destruction of power cables, the operation status of power cables should be monitored on a regular basis. We studied the method in order to improve accuracy and reliability for diagnosising the junction where accident occurs frequently. We present the method of data acquisition and statistical processing.

• The Journal of the Acoustical Society of Korea
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• v.38 no.2
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• pp.145-153
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• 2019

Adaptive beamforming methods are known to suppress sidelobes and improve detection performance of weak signal by constructing weight vectors depending on the received signal itself. A standard adaptive beamforming like the MVDR (Minimum Variance Distortionless Response) is very sensitive to mismatches between weight vectors and actual signal steering vectors. Also, a large computational complexity for estimating a stable covariance matrix is required when wideband beamforming for a large-scale array is used. In this paper, we exploit the WBRCB (Wideband Robust Capon Beamforming) method for stable and robust wideband adaptive beamforming of a passive large uniform line array sonar. To improve robustness of adaptive beamforming performance in the presence of mismatches, we extract a optimum mismatch parameter. WBRCB with extracted mismatch parameter shows performance improvement in beamforming using synthetic and experimental passive sonar signals.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.63-68
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• 2019

Emerging applications such as Smart factory, in-car network, wide area power network require strict bounds on the end-to-end network delays. Flow-based scheduler in traditional Integrated Services (IntServ) architecture could be possible solution, yet its complexity prohibits practical implementation. Sub-optimal class-based scheduler cannot provide guaranteed delay since the burst increases rapidly as nodes are passed by. Therefore a leaky-bucket type regulator placed next to the scheduler is being considered widely. This paper proposes a simple server that achieves both fair scheduling and traffic regulation at the same time. The performance of the proposed server is investigated, and it is shown that a few msec delay bound can be achieved even in large scale networks.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.12
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• pp.145-156
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• 2018

This study explores changes of industrial scales and building activities in the semi-industrial area of Seoul's Seong-su, responding to the shifts of industrial structures and policies in the Korean society. The purpose of this study is to investigate patterns of construction activities of factory buildings in the Seong-su semi-industrial area by analyzing changes in industrial facilities. As a result of the analysis, the change of the factory building area come out from the recent survey implies the possibility of entrepreneurial inflow as much and the new constructions and some remodeling cases which are characterized by complexity seem to correspond to the industrial structure. However, it is unreasonable to believe that this phenomenon is a mainstream movement involving small-scale factory buildings and companies. This is because there are aspects that are not included in this movement, such as changing the use of buildings without accompanying physical changes. On the other hand, compared to various movements of individual companies in response to the industrial structure, the physical plan suggests a limited alternative centering on the floor area ratio and the building area ratio. This means that the efforts to attract and grow the power of knowledge based-industry through the designation of the Industrial Development Promotion District in part of the case sites, overlook the natural change through remodeling and reuse of existing buildings. In addition, considering the fact that the production space of industrial use can be greatly influenced by the behavior of users compared to general buildings such as residential and commercial, it is necessary to pay attention to various phenomena occurring in the area more locally than the uniform supply policy. Based on these findings, this study contributes to illuminate the legal system related to building act in the Seong-su semi-industrial area and the potential direction of architectural suggestions in related policies and researches.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.161-168
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• 2021

The corporate environment is undergoing many changes as the transition to a knowledge-based economy accelerates. Many changes are taking place in China, including the strategy of Chinese manufacturer 2025. It has no role in the manufacturing plant and is striving to lead the industry based on advanced technology. Therefore, the purpose of this research is to understand one's own mechanism as a result of technological innovation of Chinese companies. Therefore, in this study, based on the previous study, in the Delphi survey, eight factors were finally derived, and the eight factors were surveyed by practitioners of Chinese companies about their own mechanism. As a result of analysis, the importance of one's mechanism based on the industry as a whole is patent, design registration, lead time, confidentiality, complementary manufacturing, complementary sales and services, design complexity, learning curve effect / economies of scale. In turn, its importance appeared. The results of this study may help corporate practitioners develop their intellectual property strategic plans through their own mechanisms that are tailored to their company.

• The Journal of Korean Institute of Information Technology
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• v.17 no.9
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• pp.99-112
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• 2019

Cracks on pavement surfaces are critical signs and symptoms of the degradation of pavement structures. Image-based pavement crack detection is a challenging problem due to the intensity inhomogeneity, topology complexity, low contrast, and noisy texture background. In this paper, we address the problem of pavement crack detection and segmentation at pixel-level based on a Deep Neural Network (DNN) using gray-scale images. We propose a novel DNN architecture which contains a modified U-net network and a high-level features network. An important contribution of this work is the combination of these networks afforded through the fusion layer. To the best of our knowledge, this is the first paper introducing this combination for pavement crack segmentation and detection problem. The system performance of crack detection and segmentation is enhanced dramatically by using our novel architecture. We thoroughly implement and evaluate our proposed system on two open data sets: the Crack Forest Dataset (CFD) and the AigleRN dataset. Experimental results demonstrate that our system outperforms eight state-of-the-art methods on the same data sets.