• Progress in Medical Physics
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• v.9 no.3
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• pp.127-136
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• 1998

On-line geometrical quality assurance system has been developed using electronic portal imaging system(OQuE). EPID system is networked into Pentium PC in order to transmit the acquisited images to analysis PC. Geometrical QA parameters, including light-radiation field congruence, collimator rotation axis, and gantry rotation axis can be easily analyzed with the help of graphic user interface(GUI) software. Equipped with the EPID (Portal Vision, Varian, USA), geometrical quality assurance of a linear accelerator (CL/2100/CD, Varian, USA), which is networked into OQuE, was performed to evaluate this system. Light-radiation field congruence tests by center of gravity analysis shows 0.2～0.3mm differences for various field sizes. Collimator (or Gantry) rotation axis for various angles could be obtained by superposing 4 shots of angles. The radius of collimator rotation axis is measured to 0.2mm for upper jaw collimator, and 0.1mm for lower jaw. Acquisited images for various gantry angles were rotated according to the gantry angle and actual center of image point obtained from collimator axis test. The rotated images are superpositioned and analyzed as the same method as collimator rotation axis. The radius of gantry rotation axis is calculated 0.3mm for anterior/posterior direction (gantry 0$^{\circ}$ and 170$^{\circ}$) and 0.7mm for right/left direction(gantry 90$^{\circ}$ and 260$^{\circ}$). Image acquisition for data analysis is faster than conventional method and the results turn out to be excellent for the development goal and accurate within a milimeter range. The OQuE system is proven to be a good tool for the geometrical quality assurance of linear accelerator using EPID.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.4
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• pp.335-340
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• 2010

The paper describes the objectives of Yellow Sea Large Marine Ecosystem (YSLME) project, focusing on procedural and practical aspects. YSLME is a highly productive sea yet possibly one of the most impacted large marine ecosystems, in terms of anthropogenic stressors, due the enormous coastal population. The aim of the YSLME project is the reduction of ecosystem stress through identification of the environmental problems in the Transboundary Diagnostic Analysis (TDA) that are then addressed in the Strategic Action Programme (SAP). One of the major problems found to be affecting biological diversity is habitat modification through wetland reclamation, conversion and degradation. Since the early 1900's more than 40% of intertidal wetlands have been reclaimed in Korea, and 60% of Chinese coastal wetlands have been converted or reclaimed. Damaging fishing practices, pollution and coastal eutrophication have further degraded the coastal environment reducing the biological diversity. To combat this loss, the YSLME project has mounted a public awareness campaign to raise environmental consciousness targeted at all different levels of society, from politicians at parliamentary workshops, local government officer training events, scientific conferences and involvement of scientists in the project research and reporting, to university and high school students in our visiting internship programmes and environmental camps. We have also built networks through the Yellow Sea Partnership and by liaising and working with other environmental organizations and NGOs. NGO's are recognised as important partners in the environmental conservation as they already have extensive local networks that can be lacking in international organisations. Effective links have been built with many of these NGOs through the small grants programme. Working with WWF's YSESP project and other academic and research institutions we have conducted our own biodiversity assessments that have contributed to the science-based development of the SAP for the YSLME. Our regional targets for biodiversity outlined in the SAP include: Improvements in the densities, distributions and genetic diversity of current populations of all living organisms including endangered and endemic species; Maintenance of habitats according to standards and regulations of 2007; and a reduction in the risk of introduced species. Endorsement of the SAP and its successful implementation, during the proposed second phase of the YSLEM project, will ensure that biological diversity is here to benefit future generations.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.3
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• pp.322-331
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• 2003

As the complexity of a 3D game is increased by various factors of the game scenario, it has a problem for controlling the interrelation of the game objects. Therefore, a game system has a necessity of the coordination of the responses of the game objects. Also, it is necessary to control the behaviors of animations of the game objects in terms of the game scenario. To produce realistic game simulations, a system has to include a structure for designing the interactions among the game objects. This paper presents a method that designs the dynamic control mechanism for the interaction of the game objects in the game scenario. For the method, we suggest a game agent system as a framework that is based on intelligent agents who can make decisions using specific rules. Game agent systems are used in order to manage environment data, to simulate the game objects, to control interactions among game objects, and to support visual authoring interface that ran define a various interrelations of the game objects. These techniques can process the autonomy level of the game objects and the associated collision avoidance method, etc. Also, it is possible to make the coherent decision-making ability of the game objects about a change of the scene. In this paper, the rule-based behavior control was designed to guide the simulation of the game objects. The rules are pre-defined by the user using visual interface for designing their interaction. The Agent State Decision Network, which is composed of the visual elements, is able to pass the information and infers the current state of the game objects. All of such methods can monitor and check a variation of motion state between game objects in real time. Finally, we present a validation of the control method together with a simple case-study example. In this paper, we design and implement the supervised classification systems for high resolution satellite images. The systems support various interfaces and statistical data of training samples so that we can select the most effective training data. In addition, the efficient extension of new classification algorithms and satellite image formats are applied easily through the modularized systems. The classifiers are considered the characteristics of spectral bands from the selected training data. They provide various supervised classification algorithms which include Parallelepiped, Minimum distance, Mahalanobis distance, Maximum likelihood and Fuzzy theory. We used IKONOS images for the input and verified the systems for the classification of high resolution satellite images.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.157-173
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• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.305-316
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• 2011

Recommender system is the system which, by using automated information filtering technology, recommends products or services to the customers who are likely to be interested in. Those systems are widely used in many different Web retailers such as Amazon.com, Netfix.com, and CDNow.com. Various recommender systems have been developed. Among them, Collaborative Filtering (CF) has been known as the most successful and commonly used approach. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. However, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting in advance whether the performance of CF recommender system is acceptable or not is practically important and needed. In this study, we propose a decision making guideline which helps decide whether CF is adoptable for a given application with certain transaction data characteristics. Several previous studies reported that sparsity, gray sheep, cold-start, coverage, and serendipity could affect the performance of CF, but the theoretical and empirical justification of such factors is lacking. Recently there are many studies paying attention to Social Network Analysis (SNA) as a method to analyze social relationships among people. SNA is a method to measure and visualize the linkage structure and status focusing on interaction among objects within communication group. CF analyzes the similarity among previous ratings or purchases of each customer, finds the relationships among the customers who have similarities, and then uses the relationships for recommendations. Thus CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. Under the assumption that SNA could facilitate an exploration of the topological properties of the network structure that are implicit in transaction data for CF recommendations, we focus on density, clustering coefficient, and centralization which are ones of the most commonly used measures to capture topological properties of the social network structure. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. We explore how these SNA measures affect the performance of CF performance and how they interact to each other. Our experiments used sales transaction data from H department store, one of the well?known department stores in Korea. Total 396 data set were sampled to construct various types of social networks. The dependant variable measuring process consists of three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used UCINET 6.0 for SNA. The experiments conducted the 3-way ANOVA which employs three SNA measures as dependant variables, and the recommendation accuracy measured by F1-measure as an independent variable. The experiments report that 1) each of three SNA measures affects the recommendation accuracy, 2) the density's effect to the performance overrides those of clustering coefficient and centralization (i.e., CF adoption is not a good decision if the density is low), and 3) however though the density is low, the performance of CF is comparatively good when the clustering coefficient is low. We expect that these experiment results help firms decide whether CF recommender system is adoptable for their business domain with certain transaction data characteristics.

• Journal of Intelligence and Information Systems
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• v.15 no.4
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• pp.1-22
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• 2009

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component based software development to promote application interaction and integration both within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web service repositories not only be well-structured but also provide efficient tools for developers to find reusable Web service components that meet their needs. As the potential of Web services for service-oriented computing is being widely recognized, the demand for effective Web service discovery mechanisms is concomitantly growing. A number of techniques for Web service discovery have been proposed, but the discovery challenge has not been satisfactorily addressed. Unfortunately, most existing solutions are either too rudimentary to be useful or too domain dependent to be generalizable. In this paper, we propose a Web service organizing framework that combines clustering techniques with string matching and leverages the semantics of the XML-based service specification in WSDL documents. We believe that this is one of the first attempts at applying data mining techniques in the Web service discovery domain. Our proposed approach has several appealing features : (1) It minimizes the requirement of prior knowledge from both service consumers and publishers; (2) It avoids exploiting domain dependent ontologies; and (3) It is able to visualize the semantic relationships among Web services. We have developed a prototype system based on the proposed framework using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web service registries. We report on some preliminary results demonstrating the efficacy of the proposed approach.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.5
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• pp.19-27
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• 2013

This paper claims that the One Million-peyong Park(hereafter abbreviated as OMP) project is different from a typical citizen participatory park project by recognizing the exceptional leadership of the Civic Committee for the One Million-pyeong Park Construction(CCOMPC) in promoting and developing the OMP project. Since 2001 the CCOMPC has published a variety of written promotional materials to inform and educate the public about the project. In terms of approaching the promotional materials, this research focuses on the use of language on how the CCOMPC justifies the OMP project, namely the OMP justification discourse, and considers the discourse as a unique form of social document that represents the perspective of the CCOMPC in explaining the local environmental issues and values of urban parks to the public. Using a discourse analysis method, this research analyzes the justification discourses and investigates how they changed over the three main development phases of the OMP: the initiation and preliminary development phase(1999-2001.2), the development phase (2001.2-2008), and the time period after the greenbelt policy release on Dunchi Island(2008-present). In each discourse, the OMP project is rationalized as a citizen participation park project that (1) aims to enhance the quality of public green space in Busan, (2) is accompanied by various community engagement programs that emphasize the value of urban nature and environmental education to expand citizen participation, and (3) has contributed to the National Urban Park Bill. This research emphasizes the role of the discourses in helping the public gain a critical understanding about the local environment and values of urban parks. By analyzing the contents of the discourses, it explains the social learning values of the OMP expressed in the discourses.

• Journal of the Korean Society for Marine Environment & Energy
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• v.9 no.2
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• pp.109-119
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• 2006

This study investigated the effect of artificially enhanced mesozooplankton on the phytoplankton dynamics during fall blooming period using a mesocosm in Jangmok bay located in the Southern Sea of Korea in 2001. The four bags with 2,500 liter seawater containment were directly filled with the ambient water. And then, abundances of mesozooplankton in two experimental bags were treated 6 times higher than those in control bags by towing with net($300{\mu}m$) through the ambient water. Phytoplankton community between control and experimental bags were not significantly different in terms of chlorophyll-a(chl-a) concentration and standing crop (one-way ANOVA, p>0.05) during the study period. Initial high standing crop and chl-a concentration of phytoplankton drastically decreased and remained low until the end of the experiment in all bags. Diatoms, accounting for most of the phytoplankton community, consisted of Skeletonema costatum, Pseudo-nitzschia seriata, Chaetoceros curvisetus, Ch. debilis, Cerataulina pelagica, Thalassiosira pacifica, Cylindrotheca closterium, and Leptocylindrus danicus. Noctiluca scintillans dominated the temporal variation of mesozooplankton abundances, which peaked on Day 10 in the control and experimental bags, while the next dominant copepods showed their peak on Day 7. Shortly after mesozooplankton addition, copepod abundance in the experimental bags was obviously higher than that in the control bags on Day 1, however, it became similar to that in the control bags during the remnant period. It was supported by the higher abundance and length of both ctenophores and hydromedusae in experimental bags relative to the control bags. However, the cascading trophic effect, commonly leading to re-increase of phytoplankton abundance, was not found in the experimental bags, indicating that copepods were not able to control the phytoplankton in the bags based on the low grazing rate of Acartia erythraea. Besides that, rapidly sunken diatoms in the absence of natural turbulence as well as N-limited condition likely contributed the no occurrence of re-increased phytoplankton in the experimental bags.

• Journal of Korean Society of Transportation
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• v.18 no.4
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• pp.51-62
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• 2000

The objective of this study was to reevaluate current Korean design values for lane width widenings on horizontal currie sections and to develop a new method for derivation of design values based on low-speed offtracking. For this purpose, earlier research were reviewed and necessary equations were derived. Also, the method for derivation of widening values of Korea was compared with that for other countries. The result showed that present Korean method could not consider the variation of lane widths and design speeds of roads. In this Paper, to solve such problems, the new concept of widening was developed. That is the current concept of widening which concerns only the dimension of vehicles and radius of curves was replaced by a new concept that lane width widenings on horizontal curve sections is the difference between the width required on curries and tangents. The width required on a curve consists of the swept Path of a vehicle, lateral clearance, and additional allowance. The width of a tangent is calculated by multiplying lane width by the number of lanes The result of applying new concept shows that the values derived from new concept are higher than current design values for curries have same radius. This study was based only on low-speed offtracking. Therefor, it is recommended that further studies which consider the superelevation and high-speed effect on offtracking be made to derive more accurate widening values .

• Journal of Technology Innovation
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• v.24 no.1
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• pp.113-142
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• 2016

T-50 exportation to Indonesia embodied an objective of governmental policy and became a catalyst accelerating the exportation of domestic defense industries. Defense industry exportation is recognized as a new growth engine creating economic interests and it became an important policy of the government. This study will suggest an effective direction for the support policy of the defense industry exportation through analysis on factors behind the success of the T-50 exportation to indonesia in the view of policy network. Policy network theory has its efficacy and workability in analyzing what kind of results are yielded from each policy actor's attributes and their interaction during the execution and establishment of the support policy for the defense exportation. The type of policy network of the T-50 exportation to Indonesia was a policy community. Many governmental ministries, defense industry which is the group of interest, and experts from the research institutes have established the Korea Defense Trade Support Center(KODITS) for accomplishing common policy goal with mutually shared sentiment, and sought for a strategy for the success of the defense industry exportation having official and unofficial meeting centering around the KODITS. Although there were oppositions and conflicts among major actors, though forming a cooperative relationship among majority of the actors, policy-wise decision making for the exportation of the T-50 to Indonesia was efficiently carried out. The cooperative relationship was the key in the success of the T-50 exportation. Considering that the policy community from cooperative mutual interaction is efficient in reaching the goal of the defense industry exportation support policy, this study suggests operating government-wise temporary Task Force(TF) to succeed in big exportation projects such as the T-X exportation to the U.S. In addition, institutional and procedural supplementation such as regular meetings among the head of related governmental ministries and etc. are required in order to enhance the mutually cooperative relationship withing the TF.