• Journal of the Korean Society of Radiology
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• v.16 no.1
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• pp.67-75
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• 2022

The aim of this study is to establish a new QC method that can simultaneously evaluate the resolution of the x/y plane and the z-axis by producing a phantom that can reflect exposure and reconstruction parameter of MDCT system. It was used with Aquilion ONE(Cannon Medical System, Otawara, Japan), and the examination was scanned using of 120 kV, 260 mA, and the D-FOV of 300 mm². It produced new SSP phantom modules in which two aluminum plates inclined at 45° to a vertical axis and a transverse axis to evaluate high contrast resolution of x/y plane and z axis. And it changed factors such as the algorithm, distance from gantry iso-center. All images were reconstructed in five steps from 0.6 mm to 10.0 mm slice thickness to measure resolution of x/y plane and z-axis. The image data measured FWHM and FWTM using Profile tool of Aquarius iNtusion Edition ver. 4.4.13 P6 software(Terarecon, California, USA), and analysed SPQI and signal intensity by ImageJ program(v1.53n, National Institutes of Health, USA). It decreased by 4.09~11.99%, 4.12~35.52%, and 4.70~37.64% in slice thickness of 2.5 mm, 5.0 mm, and 10.0 mm for evaluating the high contrast resolution of x/y plane according to distance from gantry iso-center. Therefore, the high contrast resolution of the x/y plane decreased when the distance from the iso-center increased or the slice thickness increased. Additionally, the slice thicknesses of 2.5 mm, 5.0 mm, and 10.0 mm with a high algorithm increased 74.83, 15.18 and 81.25%. The FWHM was almost constant on the measured SSP graph for evaluating the accuracy of slice thickness which represents the resolution of x/y plane and z-axis, but it was measured to be higher than the nominal slice thickness set by user. The FWHM and FWTM of z-axis with axial scan mode tended to increase significantly as the distance increased from gantry iso-center than the helical mode. Particularly, the thinner slice thickness that increased error range compare with the nominal slice thickness. The SPQI increased with thick slice thickness, and that was closer to 90% in the helical scan than the axial scan. In conclusion, by producing a phantom suitable for MDCT detectors and capable of quantitative resolution evaluation, it can be used as a specific method in the management of research quality and management of outdated equipment. Thus, it is expected to contribute greatly to the discrimination of lesions in the field of CT imaging.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.39-70
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• 2017

Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

• The KIPS Transactions:PartD
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• v.12D no.4 s.100
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• pp.589-600
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• 2005

Application developers need effective reuseable methodology to meet rapidly changes and variety of users requirements. Product Line and CBD(Component Based Development) offer the great benefits on quality and productivity for developing the software that is mainly associate with reusable architectures and components in a specific domain and rapidly changing environments. Product line can dynamically focus on the commonality and variety feature model among the products. The product line uses the feature modeling for discovering, analyzing, and mediating interactions between products. Reusable architectures include many variety plans and mechanisms. In case of those architecture are use in product version for a long time, It is very important in architecture product line context for product line design phase. Application developer need to identify the proper location of architecture changing for variety expression. It is lack of specific variety managements to design the product line architecture until nowdays. In this paper, we define various variety types to identify the proper location of architecture changing for variety expression and to design the reusable architecture. We also propose architecture variety on feature model and describe variety expression on component relations. We implemented the web learning system based on the methodology. We finally describe how these methodology may assist in increasing the efficiency, reusability, productivity and quality to develop an application. In the future, we are going to apply the methodology into various domain and suggest international and domestic's standardization.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.507-516
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• 2013

Mobile devices have limited computing power and resources. Since mobile devices are equipped with rich network connectivity, an approach to subscribe cloud services can effectively remedy the problem, which is called Mobile Cloud Computing (MCC). Most works on MCC depend on a method to offload functional components at runtime. However, these works only consider the limited verion of offloading to a pre-defined, designated node. Moveover, there is the limitation of managing services subscribed by applications. To provide a comprehensive and practical solution for MCC, in this paper, we propose a self-stabilizing process and its management-related methods. The proposed process is based on an autonomic computing paradigm and works with diverse quality remedy actions such as migration or replicating services. And, we devise a pratical offloading mechanism which is still in an initial stage of the study. The proposed offloading mechanism is based on our proposed MCC meta-model. By adopting the self-stabilization process for MCC, many of the technical issues are effectively resolved, and mobile cloud environments can maintain consistent levels of quality in autonomous manner.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.697-702
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• 2008

Mobile display panel is small so that users are often difficult to perceive images clearly. About image we perceive much through colors and therefore we propose color fitting approach for clear perception even on the small and low quality LCD panels. Various color modifications have been studied and used in commercial software packages. For mobile usage, our approach instantly enhances color images by modifying colors in a way to contrast differences of them. The method includes tone enhancements (which contrast dark and bright sides) and color enhancements (which reduce saturation for pure colorants). Based on color theory, our method also modifies color values towards specified complementary and preference colors. We term this color fitting. This approach enables displaying photos, multimedia messages, videos and digital media broadcasting (DMB) for better perception in real-time on mobile devices. Index Terms.) color fitting, visualization on small display, mobile graphics, visual perception.

• Journal of Internet Computing and Services
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• v.13 no.1
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• pp.57-63
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• 2012

Recently, Development of high-speed internet networks can be a real-time video conference system. SD-quality still images using the software codec system exists, and two-way system with mobile systems, but in most video only send and receive video system. In this study, HD web-cam using the two-way live broadcasts simultaneously in the education system and the mobile system has developed an audible system. In the study using the H.264 standard video compression techniques were applied to high-bandwidth compression technology, smart phones, to develop a streaming server for broadcasting were applied. Video sharing, document, web-sharing was made possible in real time. In addition, the private IP for WiFi zone, available anytime, anywhere that can be converted to a public IP technology, IP tunneling technology applied.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.2
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• pp.145-150
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• 2004

A protocol for the web-based GPS data processing system has been developed. The system is developed following the typical ASP system, in which the GPS data acquired by various users can be uploaded through the web and the data is processed with data processing components selected by the users. After the processing, the results are also transported to the users through the web. The developed system is designed for easy software upgrade and it is an synchronous process mode so that the multiple accesses can be handled with high user flexibility. The database components for the efficient GPS data maintenance are developed so that the data from CORS can be used for the data processing. Currently, the absolute and relative positioning algorithms using code measurements are integrated and much more algorithms such as the data quality control, absolute and relative positioning using phases will be integrated in near future.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.1-17
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• 2015

In domestic game market, the video game market is getting smaller and also decreasing funds and high level developers. So we need the software that can help us to make more realistic and high quality contents by non-expert developer in poor environments. In this paper, we selected global studio's animations which were scored good evaluation by public and critics as a well-made emotional expression that can convey the emotion properly. We selected movements that express emotions from the animation scripts by using Ekman's 6 basic emotions and Greimas' dynamic predicate, and then we had analyzed and categorized with the data. We also analyzed the movements for which data we needed to create specific movements to express emotions by using 'Animation Layer' that used in Unity's blending process. And suggest concept of the program that to create the emotional expression movements by using those analyzed data.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.369-374
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• 2014

Path generation methods are required for safe and efficient driving in unmanned autonomous vehicles. There are two kinds of paths: global and local. A global path consists of all the way points including the source and the destination. A local path is the trajectory that a vehicle needs to follow from a way point to the next in the global path. In this paper, we propose a novel method for local path generation through machine learning, with an effective curve function used for initializing the trajectory. First, reinforcement learning is applied to a set of candidate paths to produce the best trajectory with maximal reward. Then the optimal steering angle with respect to the trajectory is determined by training an artificial neural network. Our method outperformed existing approaches and successfully found quality paths in various experimental settings, including the cases with obstacles.

• Journal of KIISE:Software and Applications
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• v.30 no.12
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• pp.1220-1227
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• 2003

To perform rational decision-making, autonomous agents need considerable computational resources. When other agents are present in the environment, these demands are even more severe. In these settings, it may be difficult for the agent to decide what to do in an acceptable time in multiagent situations that involve many agents. These problems motivate us to investigate ways in which the agents can be equipped with flexible decision-making procedures that enable them to function in a variety of situations in which decision-making time is important. The flexible decision-making methods explicitly consider a tradeoff between decision quality and computation time. Our framework limits resources used for agent deliberation and produces results that are not necessarily optimal, but provide autonomous agents with the best decision under time pressure. We validate our framework with experiments in a simulated anti-air defense domain. The experiments show that compiled rules reduce computation time while offering good performance.