• Journal of Life Science
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• v.18 no.4
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• pp.565-571
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• 2008

Due to rapid development of bioinformatics technologies, various biological data have been produced in silico. So now days complicated and large scale biodata are used to accomplish requirement of researcher. Developing visualization and annotation tool using them is still hot issues although those have been studied for a decade. However, diversity and various requirements of users make us hard to develop general purpose tool. In this paper, I propose a novel system, Genome Viewer and Annotation tool (GenoVA), to annotate and visualize among genomes using known information and multiple relation graph. There are several multiple alignment tools but they lose conserved area for complexity of its constrains. The GenoVA extracts all associated information between all pair genomes by extending pairwise alignment. High frequency conserved area and high BLAST score make a block node of relation graph. To represent multiple relation graph, the system connects among associated block nodes. Also the system shows the known information, COG, gene and hierarchical path of block node. In this case, the system can annotates missed area and unknown gene by navigating the special block node's clustering. I experimented ten bacteria genomes for extracting the feature to visualize and annotate among them. GenoVA also supports simple and rough computational annotation of new genome.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.4
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• pp.305-312
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• 2007

Among many types of light rail transits (LRT), the rubber-tired automated guide-way transit (AGT) is prevalent in many countries due to its advantages such as good acceleration/deceleration performance, high climb capacity, and reduction of noise and vibration. However, AGT is generally powered by high-voltage electric power feeding system and it may cause electromagnetic interference (EMI) to measurement sensors. The fiber optic sensor system is free from EMI and has been successfully applied in many applications of civil engineering. Especially, fiber Bragg grating (FBG) sensors are the most widely used because of their excellent multiplexing capabilities. This paper investigates a prestressed concrete girder bridge in the Korean AGT test track using FBG based sensors to monitor the dynamic response at various vehicle speeds. The serviceability requirements provided in the specification are also compared against the measured results. The results show that the measured data from FBG based sensors are free from EMI though electric sensors are not, especially in the case of electric strain gauge. It is expected that the FBG sensing system can be effectively applied to the LRT railway bridges that suffered from EMI.

• Economic and Environmental Geology
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• v.38 no.1
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• pp.1-22
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• 2005

Carbon dioxide ($CO_2$) is the greatest contributor among the major greenhouse gases covered by the Kyoto Protocol. Therefore, substantial efforts for the control and reduction of $CO_2$ emissions, including increased efficiency of fossil fuel energy usage, development of energy sources with lower carbon content, and increased reliability on alternative energy sources, are being performed worldwide. However, development and industrial application of $CO_2$ sequestration techniques are needed to meet the requirements of the Kyoto Protocol. Among the $CO_2$ sequestration methods developed, geological sequestration methods such as the storage in deep aquifers, deep coal seams and oil and gas reservoirs and the mineral carbonation is considered most favorable because of its stability and environmental effectiveness. In this review, geochemical concepts and technologic development of geologic sequestration technology, especially the storage in deep aquifers and the mineral carbonation, are discussed. The weakness and strengths for each of geologic sequestration methods, are also reviewed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.709-717
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• 2016

In this study, the convenience and efficiency of vision-based displacement measurement (VBDM) to estimate the cable tension of cable-stayed bridges and the requirements for its effective application were examined. To demonstrate its convenience and efficiency, it was confirmed that VBDM can be accomplished with a minimum amount of equipment using a commercial camcorder. In this case, it was found that the accuracy of estimation of the natural frequencies is sufficient, even though magnitude errors can occur when conducting high-speed recording at the low resolution afforded by the minimal equipment employed. It was also confirmed that the most important factor in detecting the precise natural frequencies is the use of the appropriate frequency range in the tension estimation using vibration. Based on these results, a study was carried out on the accuracy variation of the estimated tension according to the frame rate of a commercial camcorder. For this purpose, an experiment was performed to estimate the cable tension in a cable-stayed bridge model. Through this experiment, the detectable tensions of cables with various natural frequencies as a function of the frame rate were summarized. As a result, it was shown that the frame rate should be determined based on the natural frequency which is estimated to be located within the appropriate frequency range (approximately 10~75% of theoretical range) considering the aliasing and low-frequency distortion due to excitations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.300-309
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• 2016

Curved beams are increasingly used in buildings, vehicles, ships, and aircraft, which has resulted in considerable effort towards developing an accurate method for analyzing the dynamic behavior of such structures. The stability behavior of elastic curved beams has been the subject of many investigations. Solutions to the relevant differential equations have traditionally been obtained by the standard finite difference or finite element methods. However, these techniques require a great deal of computer time for a large number of discrete nodes with conditions of complex geometry and loading. One efficient procedure for the solution of partial differential equations is the differential quadrature method (DQM). This method has been applied to many cases to overcome the difficulties of complex algorithms and high storage requirements for complex geometry and loading conditions. Out-of-plane buckling of curved beams with rotatory inertia were analyzed using DQM under uniformly distributed radial loads. Critical loads were calculated for the member with various parameter ratios, boundary conditions, and opening angles. The results were compared with exact results from other methods for available cases. The DQM used only a limited number of grid points and shows very good agreement with the exact results (less than 0.3% error). New results according to diverse variation are also suggested, which show important roles in the buckling behavior of curved beams and can be used for comparisons with other numerical solutions or experimental test data.

• Journal of KIISE:Software and Applications
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• v.29 no.7
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• pp.476-486
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• 2002

CBD(Component Based Development) has become the best strategical method for the business application. Because CBD is a new development paradigm which makes it possible to assemble the software components for application, it copes with the rapid challenge of business process and meets the increasing requirements for productivity. Since the business process is rapidly changing, CBD technology is the promising way to solve the productivity. Especially, the repository is the most important part for the development, distribution and reuse of components. In component repository, we can store and manage the related work-products produced at each step of component development as well as component itself. In this paper, we suggested a practical approach for repository construction to support and realize the CBD process and developed the CRMS(Component Repository Management System) as implementation product of the proposed techniques. CRMS can manage a variety of component products based on component architecture, and help software developers to search a candidate component for their project and to understand a variety of information for the component. In the paper, a practical approach for component repository was suggested, and a supporting environment was constructed to make CBD to be working efficiently. We expect this work wall be valuable research for component repository and the entire supporting Component Based Development Process.

• Journal of KIISE:Software and Applications
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• v.33 no.6
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• pp.550-563
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• 2006

Software product line engineering is a method that prepares for the future reuse and supports to seamless reuse in application development process. Commonality and variability play central roles in all product line development processes. Reusable assets will become core assets by explicitly representing C&V. Indeed, the variabilities that art identified at each phase of core assets development have different levels of abstraction. In the past, these variabilities have been handled in an implicit manner and without distinguishing the characteristics of each core assets. In addition, previous approaches have depended on the experience and intuition of a domain expert to recognize commonality and variability. In this paper, we suggest a 2-dimensional analyzing method that analyzes the variabilities of core assets in software product line. In horizontal analysis process, the variation types are analyzed in requirements, architecture, and component that are produced at each phase of development process. In vertical analysis process, variations are analyzed in different abstract levels, in which the region of commonality is identified and the variation points are refined. By this method, the traceability of variations between core assets will be possible and core assets can be reused seamlessly.

• Journal of The Korean Association For Science Education
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• v.39 no.4
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• pp.525-534
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• 2019

The purpose of this study is to investigate the influences of Science Core schools on students' positive experiences about science (PES) through in-depth interviews with teachers in charge of science core schools. In-depth interviews with teachers were conducted to explore the factors that led to the effectiveness of science core schools in improving the student's PES in light of operational characteristics of science core schools as leading schools, characteristic factors of science core schools on students PES, and improvement plans and requirements of science core schools as leading schools, as well as implications for general high schools. In the case of science core schools, the teacher's enthusiasm for science teaching encouraged students' participation in science classes, promoted students' interest in science other than science-core classes, improved students' inquiry and research skills, increased students' competencies such as communications and collaboration by improving science instructions, and affected career search and exploration based on interests in science experiences. Based on the results, ways to spread the characteristics of science core schools to general schools' curriculum implementation are suggested including providing opportunities to experience the value of science study, to experience science and engineering careers through senior students, to participate in team projects and self-regulated science inquires, and so on.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.11-19
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• 2021

A software system is required to change during its life cycle due to various requirements such as adding functionalities, fixing bugs, and adjusting to new computing environments. Such program code modification should be considered as carefully as a new system development becase unexpected software errors could be introduced. In addition, when reusing open source programs, we can expect higher quality software if code changes of the open source program are predicted in advance. This paper proposes a Convolutional Neural Network (CNN)-based deep learning model to predict source code changes. In this paper, the prediction of code changes is considered as a kind of a binary classification problem in deep learning and labeled datasets are used for supervised learning. Java projects and code change logs are collected from GitHub for training and testing datasets. Software metrics are computed from the collected Java source code and they are used as input data for the proposed model to detect code changes. The performance of the proposed model has been measured by using evaluation metrics such as precision, recall, F1-score, and accuracy. The experimental results show the proposed CNN model has achieved 95% in terms of F1-Score and outperformed the multilayer percept-based DNN model whose F1-Score is 92%.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.10
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• pp.391-398
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• 2021

Since the leased line is a structure that exclusively uses two connected areas for data transmission, a stable quality level and security are ensured, and despite the rapid increase in the number of switched lines, it is a line method that is continuously used a lot in companies. However, because the cost is relatively high, one of the important roles of the network operator in the enterprise is to maintain the optimal state by properly arranging and utilizing the resources of the network leased line. In other words, in order to properly support business service requirements, it is essential to properly manage bandwidth resources of leased lines from the viewpoint of data transmission, and properly predicting and managing leased line usage becomes a key factor. Therefore, in this study, various prediction models were applied and performance was evaluated based on the actual usage rate data of leased lines used in corporate networks. In general, the performance of each prediction was measured and compared by applying the smoothing model and ARIMA model, which are widely used as statistical methods, and the representative models of deep learning based on artificial neural networks, which are being studied a lot these days. In addition, based on the experimental results, we proposed the items to be considered in order for each model to achieve good performance for prediction from the viewpoint of effective operation of leased line resources.