• Journal of Internet Computing and Services
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• v.8 no.6
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• pp.135-144
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• 2007

Feature models are widely used in domain engineering phase of software product lines development to model the common and variable concepts among products. From the feature model, the feature configurations are generated by selecting the features to be included in target product. The feature configuration represents the requirements for the specific product to be implemented. Although there are a lot of researches on how to build and use the feature models and feature configurations, the researches on the formal semantics and reasoning of them are rather inactive. This paper proposes the feature configuration verification approach based on JESS, java-based rule-base system. The Graph Product Line, a standard problem for evaluating the software product line technologies, is used throughout the paper to illustrate this approach. The approach in this paper has advantage of presenting the exact reason causing inconsistency in the feature configuration. In addition, this approach should be easily applied into other software product lines development environments because JESS system can be easily integrated with Java language.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.211-217
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the teaming control field was teaming in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Error wave propagation method will show up in the numerical simulation for five-bar linkage as a vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link at each time step in repetition domain. Those can be helped to apply to the vertical multiple dynamic systems for precision quality assurance in the industrial robots and medical equipments.

• Atmosphere
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• v.24 no.2
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• pp.245-251
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• 2014

Statistical trajectory analysis has been widely used to identify potential source regions for chemically and radiatively important chemical species in the atmosphere. The most widely used method is a statistical source-receptor model developed by Stohl (1996), of which the underlying principle is that elevated concentrations at an observation site are proportionally related to both the average concentrations on a specific grid cell where the observed air mass has been passing over and the residence time staying over that grid cell. Thus, the method can compute a residence-time-weighted mean concentration for each grid cell by superimposing the back trajectory domain on the grid matrix. The concentration on a grid cell could be used as a proxy for potential source strength of corresponding species. This technical note describes the statistical trajectory approach and introduces its application to estimate potential source regions of $CO_2$ enhancements observed at Korean Global Atmosphere Watch Observatory in Anmyeon-do. Back trajectories are calculated using HYSPLIT 4 model based on wind fields provided by NCEP GDAS. The identified $CO_2$ potential source regions responsible for the pollution events observed at Anmyeon-do in 2010 were mainly Beijing area and the Northern China where Haerbin, Shenyang and Changchun mega cities are located. This is consistent with bottom-up emission information. In spite of inherent uncertainties of this method in estimating sharp spatial gradients within the vicinity of the emission hot spots, this study suggests that the statistical trajectory analysis can be a useful tool for identifying anthropogenic potential source regions for major GHGs.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.135-140
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• 2015

The Cyber-Physical Systems (CPS) complexly perform modeling and simulation (M&S) for the various embedded systems. In this case, due to use diverse formatted models, we suggest to apply with the SEDRIS to systematically manage the different formatted data on M&S. The SEDRIS can reduce time and cost with reusing and interoperating environment data developed in the specific domain. To do this, we should input the data transformed the height map for terrain representation in a simulator into raster data of SEDRIS for which interoperate between the existed simulator and the SEDRIS. To solve the problem, we propose the transformation method to transfer the polygon data from RAW file used in terrain representation. With the proposed method, we can provide two advantages. First, it can possibly express the environment data into SEDRIS. Second, we can see the terrain like an image file through a viewer. Therefore, even non-expert easily constructs the terrain environment data.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.48-55
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• 2020

Recently, a study of prognosis and health management (PHM) was conducted to diagnose failure and predict the life of air craft engine parts using sensor data. PHM is a framework that provides individualized solutions for managing system health. This study predicted the remaining useful life (RUL) of aeroengine using degradation data collected by sensors provided by the IEEE 2008 PHM Conference Challenge. There are 218 engine sensor data that has initial wear and production deviations. It was difficult to determine the characteristics of the engine parts since the system and domain-specific information was not provided. Each engine has a different cycle, making it difficult to use time series models. Therefore, this analysis was performed using machine learning algorithms rather than statistical time series models. The machine learning algorithms used were a random forest, gradient boost tree analysis and XG boost. A sliding window was applied to develop RUL predictions. We compared model performance before and after applying the sliding window, and proposed a data preprocessing method to develop RUL predictions. The model was evaluated by R-square scores and root mean squares error (RMSE). It was shown that the XG boost model of the random split method using the sliding window preprocessing approach has the best predictive performance.

• Korean Journal of Microbiology
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• v.50 no.4
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• pp.275-280
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• 2014

Leucine-responsive Regulatory Protein (Lrp) from Escherichia coli is an 18.8 kDa protein composed of 164 amino acids. Wild type Lrp (Lrp Wt) does not possess any tryptophan amino acid which has strong intrinsic fluorescence, whereas the mutant Lrp R145W contains a single tryptophan at the position 145 in the leucine-responsive domain. To investigate the fluorescence character, the Lrp R145W and Lrp Wt proteins were purified. The fluorescence intensity of Lrp R145W is much higher than that of wild type protein, and the intensity of Lrp R145W was decreased by binding to its specific DNA designed from ilvIH operon and to L-leucine. In addition, the tryptophan fluorescence intensity of Lrp R145W was strongly quenched by addition of acrylamide even in the least amount of concentration as well as by urea. The data obtained from this study may give valuable information on the three dimensional structure of Lrp R145W.

• Korean Institute of Interior Design Journal
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• v.24 no.5
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• pp.117-127
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• 2015

This paper depicts a case study of the BIM (Building Information Modeling)-enabled evaluation of design alternatives for an actual remodeling project in Yeongwol, Korea. The increase of urban population and income followed by the growth of economy has derived massive supply of grand scale housing project in Korea since 1970s. Consequently, building remodeling became one of the feasible resolutions for renovating such old housings in these days. This paper aims to introduce a technical approach to such remodeling projects based on BIM-enabled applications focusing on quantitative analysis of design alternatives. Among the technical issues of such building remodeling projects, this paper focuses on the BIM-enabled area analysis and comparison between design alternatives to support decision-making even in early phase of remodeling design process. BIM and its variety of applications have broadly influenced the domain of AEC-FM (Architecture, Engineering, Construction, and Facility Management) within the lifecycle of buildings. As one of the applications facilitated by BIM, the automated area calculation and scenario-based comparison between alternatives can play an important role in the early phase of remodeling project. We modeled three design alternatives (buildings) and three housing modules (units) based on the actual case in Yeongwol city, Korea using a BIM design authoring tool. Nine combinatorial BIM models were demonstrated for the BIM-enabled review process described in this paper. To determine the most optimal design scenario among nine alternatives, this paper demonstrates a result of the conducted spatial program review. The main subject includes specific spatial program issues on; 1) the number of unit spaces; and 2) area of individual/grouped and private/shared spaces.

• Journal of KIISE:Software and Applications
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• v.29 no.9
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• pp.645-653
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• 2002

The unit commitment problem in a power system involves determining the start-up and shut-down schedules of many dynamos for a day or a week while satisfying the power demands and diverse constraints of the individual units in the system. It is very difficult to derive an economically optimal schedule due to its huge search space when the number of dynamos involved is large. Tabu search is a popular solution method used for various optimization problems because it is equipped with effective means of searching beyond local optima and also it can naturally incorporate and exploit domain knowledge specific to the target problem. When given a large-scaled problem with a number of complicated constraints, however, tabu search cannot easily find a good solution within a reasonable time. This paper shows that a large- scaled optimization problem such as the unit commitment problem can be solved efficiently by using a parallel tabu search. The parallel tabu search not only reduces the search time significantly but also finds a solution of better quality.

• The KIPS Transactions:PartD
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• v.9D no.4
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• pp.619-628
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• 2002

Reusable software component is an ultimate goal for the software development. Component based development is focused on advanced concepts rather than passive manipulation or class library with source codes. However, the primary component construction in component based development lead to an additional development cost and effort for reconstructing the new software component within a component model. Java application provides several features based on component model. But, we only have an opportunity to develop the smallest reuse units or the restricted set of GUI components. It cannot contributed as a component and only used in the specific domain component with high cost and efforts. In this paper, we apply java component model to the existing java application and extract javabeans through extending the component scalability. We also discuss the algorithm for transformation mechanism from legacy class to javabeans with a partial of business logic.

• Journal of KIISE:Software and Applications
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• v.33 no.6
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• pp.525-538
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• 2006

Component-Based Software Engineering (CBSE) is widely accepted as new paradigms for building applications with reusable assets. Mismatch problems occur while integrating the assets and make a burden in CBSE. Therefore, a larger-grained reuse unit than a component such as a framework is required, and it consists of relevant components, connectors and domain-specific architecture. The benefits of frameworks over components are commonly known, however, the key elements and internal structure of framework has not been clearly defined. We believe most of the framework models proposed in recent works remain at conceptual level. In this paper, we propose a practical-level framework reference model, and define key elements of frameworks. The research goal is to precisely identify concrete elements of a framework, inter-connection of components within a framework, extended notion of connectors, and tailored meaning of architecture In a framework. Hence, the proposed framework can be practically implemented in common object-oriented languages and with middleware such as lava, J2EE, CORBA Component Model (CCM) and NET.