• Journal of Korea Multimedia Society
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• v.9 no.10
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• pp.1332-1343
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• 2006

This paper proposes an educational community service system that manages information of good quality intensively without overlapping, and that provides an effective searching function by using a personal community with many user layers. This system raises the efficiency of searching and management by using Metadata and Category. It is a self-leading educational community system that brings merits into relief and improves weak points. We constructed an autogenous Blog chain service as a tool which verifies this system, which is called 'EduLOG(Educational Blog) service' Especially we extracted Metadata suitable for this service, which is on the basis of worldfamous Dublin Core Metadata. And we made a new category on the basis of categories which were proposed by some educational community sites and public educational authorities, and we applied it to this system. To ascertain whether this service system provide adequate function or not, we made a questionnaire on the basis of the appraisal table in websites, and evaluated it at the request of experts. In view of the results so far achieved, it returned good scores (above 3.5/5.0) in accuracy of evaluation, low-end reappearance ratio, easiness of registering and approaching information, and intensive management of a categorical information, confirming the efficiency of the ECSS system. Therefore we believe firmly that the ECSS system will play a efficient information storing and searching roles in the near future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.568-573
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• 2018

UAV(Unmanned Aerial Vehicle) is widely used in space information construction, agriculture, fisheries, weather observation, communication, and entertainment fields because they are cheaper and easier to operate than manned aircraft. In particular, UAV have attracted much attention due to the speed and cost of data acquisition in the field of spatial information construction. However, ortho image images produced using UAVs are distorted in buildings and forests. It is necessary to solve these problems in order to utilize the geospatial information field. In this study, fixed wing, rotary wing, vertical take off and landing type UAV were used to detect distortions of ortho image of UAV under various conditions, and various object areas such as construction site, urban area, and forest area were captured and analysed. Through the research, it was found that the redundancy of the unmanned aerial vehicle image is the biggest factor of the distortion phenomenon, and the higher the flight altitude, the less the distortion phenomenon. We also proposed a method to reduce distortion of orthoimage by lowering the resolution of original image using DTM (Digital Terrain Model) to improve distortion. Future high-quality unmanned aerial vehicles without distortions will contribute greatly to the application of UAV in the field of precision surveying.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.565-572
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• 2018

Recently, UAVs (Unmanned Aerial Vehicles) or drones have gained popularity for the engineering surveying and mapping because they enable the rapid data acquisition and processing as well as their operation cost is low. The applicable fields become much wider including the topographic monitoring, agriculture, and forestry. It is reported that the high geospatial accuracy is achievable with the drone photogrammetry for many applications. However most studies reported the best achievable mapping results using well-distributed ground control points though some studies investigated the impact of control points on the accuracy. In this study, we focused on the drone mapping of corridors such as roads and pipelines. The distribution and the number of control points along the corridor were diversified for the accuracy assessment. In addition, the effects of the camera self-calibration and the number of the image strips were also studied. The experimental results showed that the biased distribution of ground control points has more negative impact on the accuracy compared to the density of points. The prior camera calibration was favored than the on-the-fly self-calibration that may produce poor positional accuracy for the case of less or biased control points. In addition, increasing the number of strips along the corridor was not helpful to increase the positional accuracy.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2007.05a
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• pp.300-320
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• 2007

정보기술의 발달과 함께 소프트웨어 제품은 모든 산업에 필수요소가 되었고, 품질과 평가에 대한 관심도 점차 증가되고 있다. 하지만 일부 산업에서는 소프트웨어 품질 평가에 대한 사용자들의 만병 통치적 기대, 품질 표준의 부족, 측정을 위한 양질의 데이터 부족, 소프트웨어 분석과 디자인에 대한 공학적 한계로 소프트웨어 품질 평가에 대해 많은 문제점이 지적되고 있다. 국내에서도 의료산업 관련 정보시스템의 오류 및 사용자들의 운영 미숙은 매년 많은 금액의 사회적 비용을 증가시켰고, 병원정보시스템의 품질에 대한 관심을 초래하였다. 특히, 산업적 특성이 강한 병원정보시스템은 성공적 구축을 위해 사용자 중심의 소프트웨어 디자인과 다양한 전문가들의 지식 통합이 필요하며, 정보시스템 품질 측정으로 연구자들과 개발자들의 시스템 설계 혼란을 감소시키는 방법론이 필요하다는 연구들이 등장하고 있다. 대부분의 병원정보시스템이 단편적인 업무처리 위주로 개발 운영되고 있고, 장기적 경영전략이나 임상연구를 위한 분석적 정보처리 기능들은 결여되어 있다. 또한 소프트웨어 재설계나 추가적 개발 에 활용될 수 있는 객관적 품질 기준이 부족하고, 사용자들의 요구사항에 대해 소프트웨어 설계에 있어서 효율적으로 반영되지 못하고 있다. 이에 본 연구는 최근 발표된 병원정보시스템 품질 평가에 대한 연구 경향을 종합하고, 품질 평가에 대 해 효율적으로 활용되고 있는 사용성(Usability)을 기준으로 병원산업의 특수성을 포함한 품질 평가 방법과 품질척도를 제안하고자 한다. 국제표준기구(ISO:International Standards Organization)에서는 품질 특성을 기능성, 신뢰성, 사용성, 효율성, 유지 보수성과 이식성의 특성을 제시하고 있다. 특히 Folmer & Bosch(2004)가 정리한 ISO9126에서는 품질의 특성을 배움의 용이성, 운영의 용이성, 이해성과 매력성으로 분류하였고, ISO9241-11는 효과성, 효율성과 만족성으로 분류하였다. 또한 Shackel(1991)은 배움의 용이성(배움과 시간, 기억력), 효과성(오류, 직무시간), 유연성과 마음가짐으로 분류하고 있다(Shackel, 1991). Nielsen(1997)은 배움의 용이성, 기억의 용이성, 오류, 효율성, 만족성으로 분류하고 있고(Nielsen, 1997), Shneiderman(1998)는 효과성(직무시간, 배움의 시간), 효율성(기억의 지속시간, 오류), 만족도를 품질의 특성으로 분류하였다. 이와 같은 소프트웨어의 품질은 소프트웨어 계획, 개발, 성장과 쇠퇴의 모든 과정에 적용되며, 환경적 변화에 따라 사용자들의 정보욕구를 적절하게 반영하여 만족도를 높이 는 것이라고 요약할 수 있다. 그러나 현재까지 소프트웨어 품질 평가에 대한 연구들 은 보편적인 평가 항목들을 대상으로 측정하여 일반적인 품질기준을 제시하고 있고, 유사한 측정 내용들이 중복되어 있다. 이러한 경향은 산업별 특수성이 강한 소프트웨어에 대해서는 정확한 품질측정이 어려웠고, 품질측정에 대한 신뢰성을 떨어뜨리는 계기가 되었다. 이러한 한계를 극복하고자 나타난 방법론이 최종사용자들의 요구사항을 얼마나 적절하게 시스템에 반영했는지에 대한 사용성(Usability) 측정이다. 사용성에 대한 정의는 사용자들이 실질적으로 일하는 장소에서 직접 사용자들의 시스템 운용실태를 파악하여 문제점을 개선하는 것으로 요약할 수 있다. ISO9124-11에서는 사용성을 "어떤 제품이 구체적인 사용자들에 의해 구체적인 목적을 달성하기 위한 구체적인 사용의 맥락에서 효율성, 효과성을 만족함으로 사용될 수 있는 정도"로 정의하고 있다. 지난 10년간 병원정보시스템 평가에 대한 문헌들을 고찰한 결과 품질 측정의 효과는 정보화에 대한 동기유발과 의료품질을 높이는 게기가 되었으며, 질병에 대한 예방효과도 높은 것으로 조사되었다. 그러나 평가에 대한 인식의 문제, 평가 방법의 신뢰성 부족, 평가 지침과 부분적 평가에 따른 인증의 어려움 평가 결과에 대한 확산과 단편적 연구의 한계 등으로 연구결과에 대한 신뢰도와 활용도는 낮은 것으로 조사되었고, HIS에 대한 연구 빈도와 범위 가 매우 미약하였다. 특히, 품질속성은 같은 용어이지만 연구자에 따라 전혀 다른 측정 내용을 제시하고 있어 효율적인 품질 지표를 제시하는데 많은 혼란을 초래하고 있다. 이러한 품질 평가의 경향은 시스템 설계 및 개발자들에게 필요한 사용자들의 구체적이고 독특한 욕구나 병원정보시스템 환경의 특수성 파악에 한계를 보였으며, 평가 범위도 부분적으로 이루어져 전사적 시스템 설계 및 개발에 중요한 자료를 제공하지 못하고 있다. 이러한 문제점과 한계를 극복하고자 ISO와 같은 품질 표준 속성과 컨텍스트(Context)를 중심으로 사용자에 의한 평가 척도의 설정은 구체적이고 실용적이며 신뢰성 있는 평가 방법이 될 것이다.

• The Journal of the Petrological Society of Korea
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• v.13 no.4
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• pp.179-190
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• 2004

Precambrian metamorphic rocks of Yeongyang-Uljin area, which is located in the eastern part of Sobaegsan Massif, Korea, are composed of Pyeonghae, Giseong, Wonnam Formations and Hada leuco granite gneisses. These show a zonal distribution of WNW-ESE trend, and are intruded by Mesozoic igneous rocks and are unconformably overlain by Mesozoic sedimentary rocks. This study clarifies the deformation history of Precambrian metamorphic rocks after the formation of gneissosity or schistosity on the basis of the geometric and kinematic features and the forming sequence of multi-deformed rock structures, and suggests that the geological structures of this area experienced at least four phases of deformation i.e. ductile shear deformation, one deformation before that, at least two deformations after that. (1) The first phase of deformation formed regional foliations and WNW-trending isoclinal folds with subhorizontal axes and steep axial planes dipping to the north. (2) The second phase of deformation occurred by dextral ductile shear deformation of top-to-the east movement, forming stretching lineations of E-W trend, S-C mylonitic structure foliations, and Z-shaped asymmetric folds. (3) The third phase deformation formed I-W trending open- or kink-type recumbent folds with subhorizontal axes and gently dipping axial planes. (4) The fourth phase deformation took place under compression of NNW-SSE direction, forming ENE-WSW trending symmetric open upright folds and asymmetric conjugate kink folds with subhorizontal axes, and conjugate faults thrusting to the both NNW and SSE with drag folds related to it. These four phases of deformation are closely connected with the orientation of regional foliation in the Yeongyang-Uljin area. 1st deformation produced regional foliation striking WNW and steeply dipping to the north, 2nd deformation locally change the strike of regional foliation into N-S direction, and 3rd and 4th deformations locally change dip-angle and dip-direction of regional foliation.

• Journal of KIISE:Information Networking
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• v.30 no.3
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• pp.329-342
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• 2003

Most of the existing multicast routing protocols for ad-hoc networks do not take into account the efficiency of the protocol for the cases when there are large number of sources in the multicast group, resulting in either large overhead or poor data delivery ratio when the number of sources is large. In this paper, we propose a multicast routing protocol for ad-hoc networks, which particularly considers the scalability of the protocol in terms of the number of sources in the multicast groups. The proposed protocol designates a set of sources as the core sources. Each core source is a root of each tree that reaches all the destinations of the multicast group. The union of these trees constitutes the data delivery mesh, and each of the non-core sources finds the nearest core source in order to delegate its data delivery. For the efficient operation of the proposed protocol, it is important to have an appropriate number of core sources. Having too many of the core sources incurs excessive control and data packet overhead, whereas having too little of them results in a vulnerable and overloaded data delivery mesh. The data delivery mesh is optimally reconfigured through the periodic control message flooding from the core sources, whereas the connectivity of the mesh is maintained by a persistent local mesh recovery mechanism. The simulation results show that the proposed protocol achieves an efficient multicast communication with high data delivery ratio and low communication overhead compared with the other existing multicast routing protocols when there are multiple sources in the multicast group.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.137-152
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• 2017

The decline in the price of IT devices and the development of the Internet have created a new field called Internet of Things (IoT). IoT, which creates new services by connecting all the objects that are in everyday life to the Internet, is pioneering new forms of business that have not been seen before in combination with Big Data. The prospect of IoT can be said to be unlimited in its utilization. In addition, studies of standardization organizations for smooth connection of these IoT devices are also active. However, there is a part of this study that we overlook. In order to control IoT equipment or acquire information, it is necessary to separately develop interworking issues (IP address, Wi-Fi, Bluetooth, NFC, etc.) and related application software or apps. In order to solve these problems, existing research methods have been conducted on augmented reality using GPS or markers. However, there is a disadvantage in that a separate marker is required and the marker is recognized only in the vicinity. In addition, in the case of a study using a GPS address using a 2D-based camera, it was difficult to implement an active interface because the distance to the target device could not be recognized. In this study, we use 3D Depth recognition camera to be installed on smartphone and calculate the space coordinates automatically by linking the distance measurement and the sensor information of the mobile phone without a separate marker. Coordination inquiry finds equipment of IoT and enables information acquisition and control of corresponding IoT equipment. Therefore, from the user's point of view, it is possible to reduce the burden on the problem of interworking of the IoT equipment and the installation of the app. Furthermore, if this technology is used in the field of public services and smart glasses, it will reduce duplication of investment in software development and increase in public services.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.