• Journal of Internet Computing and Services
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• v.6 no.4
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• pp.21-35
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• 2005

Software product-lines is the software development paradigm to attain the rapid development of quality applications by customizing the reconfigurable components and composing them based on predefined software architectures. Recently various methodologies for the component-based product lines are proposed, but these don't provide the specific implementation techniques of the components in terms of variability resolution mechanism. In other hand, the several approaches to implement the component supporting the variabilities resolution are developed, but these don't define the systematic analysis and design method considering the variabilities from the initial phase. This paper proposes the integration of PLUS, the one of product line methodologies extending UML modeling, and component code generation technique in order to increase the efficiency of producing the specific product in the software product lines. In this paper, the component has the hierarchical architecture consisting of the implementation elements, and each implementation elements are implemented as XSLT scripts. The codes of the components are generated from the feature selection. Using the microwave oven product lines as case study, the development process for the reconfigurable components supporting the automatic variability resolution is described.

• Journal of Distribution Science
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• v.14 no.10
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• pp.147-152
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• 2016

Purpose - High quality films are affected by both the production stage and various variables such as the size of the movie investment and marketing that changes consumers' perceptions. Consumer preferences should be recognized first to ensure that the movie is successful. If a film is produced without pre-investigation and analysis of consumer demand and taste, the probability of success will be low. This study investigates the balance of production costs, marketing costs, and profits using game theory, suggesting an optimization strategy using the simplex method of linear programming. Research design, data, and methodology - Before the release of the movie, initial demand is assumed to be driven largely by marketing costs. In the next phase, demand is assumed to be driven purely by a movie's production cost and quality, which might also further determine consumer demand. Thus, it is essential to determine how to distribute pure production costs and other costs (marketing) in a limited movie production budget. Moreover, it should be taken into account how to optimally distribute under the assumption that the audience and production company's input resources are limited. This research simplifies the assumptions for large-scale and relatively small-scale movie investments and examines how movie distribution participant profits differ when each cost is invested differently. Results - When first movers or market leaders have to choose both quality and marketing, it has been proven that pursuing a strategy choosing only one is more likely than choosing both. In this situation, market leaders should maximize marketing costs under the premise that market leaders will not lag their quality behind the quality of second movers. Additionally, focusing on movie marketing that produces a quick effect while ceding creative activity to increase movie quality is a natural outcome in the movie distribution environment since a cooperative strategy between market competitors is not feasible. Conclusions - Government film development policy should ignore quality competition between movie production companies and focus on preventing marketing competition. If movie production companies focus on movie production quality improvement then a creative competition would ensue.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.11
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• pp.763-770
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• 2022

In an environment where multiple drones are operated, collisions can occur when path points overlap, and collision avoidance in preparation for this is essential. When multiple drones perform multiple tasks, it is not appropriate to use a method to generate a collision-avoiding path in the path planning phase because the path of the drone is complex and there are too many collision prediction points. In this paper, we generate a path through a commonly used path generation algorithm and propose a collision avoidance method using speed profile optimization from that path segment. The safe distance between drones was considered at the expected point of collision between paths of drones, and it was designed to assign a speed profile to the path segment. The optimization problem was defined by setting the distance between drones as variables in the flight time equation. We constructed the constraints through linearize and convexification, and compared the computation time of SQP and convex optimization method in multiple drone operating environments. Finally, we confirmed whether the results of performing convex optimization in the 20 drone operating environments were suitable for the multiple drone operating system proposed in this study.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.141-146
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• 2008

As the interest about ubiquitous environment is increasing, there are many researches about the services in this environment. These services have important issues in interpreting the users' context, using many kinds of sensors, like PDA, GPS and accelerometers. Low level raw data, which sensors like accelerometers calibrates, are hard to use, and to provide real-time services preprocessing and interpreting the data into context, in real-time, is important. This paper describes a context integrate system which can integrate these sensors and also sensors which has raw data, like accelerometers and physiological sensors, and define the context interpret rule with XML. The proposing system reduces programming operations when adding a sensor to the sensor network or modifying the context interpreting rule by using XML. By using this system, we implemented a real-time data monitoring system which can describe the numeric data into graphs, and assist the user to validate the data and results of the preprocess phase, and also support the external services and applications to use the context of the user.

• The Journal of the Korea Contents Association
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• v.16 no.10
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• pp.608-616
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• 2016

The Smith-Watrman (SW) algorithm is a local alignment algorithm which is one of important operations in DNA sequence analysis. The SW algorithm finds the optimal local alignment with respect to the scoring system being used, but it has a problem to demand long execution time. To solve the problem of SW, some methods to perform SW in distributed and parallel manner have been proposed. The ADAM which is a distributed and parallel processing framework for DNA sequence has parallel SW. However, the parallel SW of the ADAM does not consider that the SW is a dynamic programming method, so the parallel SW of the ADAM has the limit of its performance. In this paper, we propose a method to enhance the parallel SW of ADAM. The proposed parallel SW (PSW) is performed in two phases. In the first phase, the PSW splits a DNA sequence into the number of partitions and assigns them to multiple nodes. Then, the original Smith-Waterman algorithm is performed in parallel at each node. In the second phase, the PSW estimates the portion of data sequence that should be recalculated, and the recalculation is performed on the portions in parallel at each node. In the experiment, we compare the proposed PSW to the parallel SW of the ADAM to show the superiority of the PSW.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.222-222
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• 2012

Metal oxide gas sensors based on semiconductor type have attracted a great deal of attention due to their low cost, flexible production and simple usability. However, most works have been focused on n-type oxides, while the characteristics of p-type oxide gas sensors have been barely studied. An investigation on p-type oxides is very important in that the use of them makes possible the novel sensors such as p-n diode and tandem devices. Monoclinic cupric oxide (CuO) is p-type semiconductor with narrow band gap (~1.2 eV). This is composed of abundant, nontoxic elements on earth, and thus low-cost, environment-friendly devices can be realized. However, gas sensing properties of neat CuO were rarely explored and the mechanism still remains unclear. In this work, the neat CuO layers with highly ordered mesoporous structures were prepared by a template-free, one-pot solution-based method using novel ink solutions, formulated with copper formate tetrahydrate, hexylamine and ethyl cellulose. The shear viscosity of the formulated solutions was 5.79 Pa s at a shear rate of 1 s-1. The solutions were coated on SiO2/Si substrates by spin-coating (ink) and calcined for 1 h at the temperature of $200{\sim}600^{\circ}C$ in air. The surface and cross-sectional morphologies of the formed CuO layers were observed by a focused ion beam scanning electron microscopy (FIB-SEM) and porosity was determined by image analysis using simple computer-programming. XRD analysis showed phase evolutions of the layers, depending on the calcination temperature, and thermal decompositions of the neat precursor and the formulated ink were investigated by TGA and DSC. As a result, the formation of the porous structures was attributed to the vaporization of ethyl cellulose contained in the solutions. Mesoporous CuO, formed with the ink solution, consisted of grains and pores with nano-meter size. All of them were strongly dependent on calcination temperature. Sensing properties toward H2 and C2H5OH gases were examined as a function of operating temperature. High and fast responses toward H2 and C2H5OH gases were discussed in terms of crystallinity, nonstoichiometry and morphological factors such as porosity, grain size and surface-to-volume ratio. To our knowledge, the responses toward H2 and C2H5OH gases of these CuO gas sensors are comparable to previously reported values.

• Journal of KIBIM
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• v.1 no.2
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• pp.19-23
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• 2011

The planning stage of an architectural project has much more significant effects on the cost or outcome of the project than other stages of the project. In addition, the importance of architectural planning has been further increasing according to the recent trend of construction projects becoming larger in scale and more complex. In spite of this, the current situation is that the planning stage work is not being systematically managed. Accordingly, the purpose of this study was to develop a BIM-based simulation system for providing support during architectural planning stage such as spatial planning & review, cost review, project owner requirements management, etc. It is easy to review various alternatives using this system that allows not only the modeling of space object modeling but also the instantaneous review of spatial area & layout, cost, etc. based on object information. In addition, it can be used as a communication tool with the project owner as it provides the visualized information and quantitative data of the building model, and the information created through this system can be delivered to the following stage for usage. It is thought that using this system, the entire project work including the architectural planning stage can be supported and even contributing to the advancement of architectural process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.346-353
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• 2016

In the design conditions of some research reactors, the siphon phenomenon can cause continuous efflux of water during pipe rupture. A siphon breaker is a safety device that can prevent water efflux effectively. However, the analysis of the siphon breaking is complicated because many variables must be included in the calculation process. For this reason, a simulation program was developed with a user-friendly GUI to analyze the siphon breaking easily. The program was developed by MFC programming using Visual Studio 2012 in Windows 8. After saving the input parameters from a user, the program proceeds with three steps of calculation using fluid mechanics formulas. Bernoulli's equation is used to calculate the velocity, quantity, water level, undershooting, pressure, loss coefficient, and factors related to the two-phase flow. The Chisholm model is used to predict the results from a real-scale experiment. The simulation results are shown in a graph, through which a user can examine the total breaking situation. It is also possible to save all of the resulting data. The program allows a user to easily confirm the status of the siphon breaking and would be helpful in the design of siphon breakers.

• The Journal of Korean Association of Computer Education
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• v.18 no.2
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• pp.1-9
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• 2015

Excessive cognitive burdens caused by learning grammar should be reduced to cultivate high-level thinking skills in students through programing education. To this end, various educational programing languages have been developed. In recent years, block-based App Inventor that can used in real life have been introduced. This study intends to suggest an educational environment in which programing can be utilized as a leading problem solving tool by designing and producing an app that can be easily used by students in their real life. In particular, given the developmental phase of elementary school students, specific operational activities are important. For this reason, an App Inventor that can be proposed to enable dynamic interactions with the real world based on various smartphone sensors during the process of programing has significance as an educational programing language for elementary school students. In this regard, this study designed App Inventor programing education for elementary school students, which can be used in their daily life. The results of applying the education in fifth graders showed its positive effects on learning programing. LT collaborative learning where the students cooperated with each other, the theme of learning, which enables the utilization of various smartphone sensors in real life, and the app inventor may have generated and sustained the students' interest and attention.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.