• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.155-169
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• 2014

With the rapid advances in technologies, organizations are more likely to depend on information systems in their decision-making processes. Business Intelligence (BI) systems, in particular, have become a mainstay in dealing with complex problems in an organization, partly because a variety of advanced computational methods from statistics, machine learning, and artificial intelligence can be applied to solve business problems such as demand forecasting. In addition to the ability to analyze past and present trends, these predictive analytics capabilities provide huge value to an organization's ability to respond to change in markets, business risks, and customer trends. While the performance effects of BI system use in organization settings have been studied, it has been little discussed on the use of predictive analytics technologies embedded in BI systems for forecasting tasks. Thus, this study aims to find important factors that can help to take advantage of the benefits of advanced technologies of a BI system. More generally, a BI system can be viewed as an advisor, defined as the one that formulates judgments or recommends alternatives and communicates these to the person in the role of the judge, and the information generated by the BI system as advice that a decision maker (judge) can follow. Thus, we refer to the findings from the advice-giving and advice-taking literature, focusing on the role of explanations of the system in users' advice taking. It has been shown that advice discounting could occur when an advisor's reasoning or evidence justifying the advisor's decision is not available. However, the majority of current BI systems merely provide a number, which may influence decision makers in accepting the advice and inferring the quality of advice. We in this study explore the following key factors that can influence users' advice taking within the setting of a BI system: explanations on how the box-office grosses are predicted, types of advisor, i.e., system (data mining technique) or human-based business advice mechanisms such as prediction markets (aggregated human advice) and human advisors (individual human expert advice), users' evaluations of the provided advice, and individual differences in decision-makers. Each subject performs the following four tasks, by going through a series of display screens on the computer. First, given the information of the given movie such as director and genre, the subjects are asked to predict the opening weekend box office of the movie. Second, in light of the information generated by an advisor, the subjects are asked to adjust their original predictions, if they desire to do so. Third, they are asked to evaluate the value of the given information (e.g., perceived usefulness, trust, satisfaction). Lastly, a short survey is conducted to identify individual differences that may affect advice-taking. The results from the experiment show that subjects are more likely to follow system-generated advice than human advice when the advice is provided with an explanation. When the subjects as system users think the information provided by the system is useful, they are also more likely to take the advice. In addition, individual differences affect advice-taking. The subjects with more expertise on advisors or that tend to agree with others adjust their predictions, following the advice. On the other hand, the subjects with more knowledge on movies are less affected by the advice and their final decisions are close to their original predictions. The advances in predictive analytics of a BI system demonstrate a great potential to support increasingly complex business decisions. This study shows how the designs of a BI system can play a role in influencing users' acceptance of the system-generated advice, and the findings provide valuable insights on how to leverage the advanced predictive analytics of the BI system in an organization's forecasting practices.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.81-88
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• 2015

Recently the Security fields is emerged as a important issue in the world, While a variety of techniques such as a Cloud Computing or a Internet Of Things appeared. In these circumstances, The domestic security fields are divided into the Information Security, the Physical Security and the Convergence Security. and among these security fields, Convergence security is attracted much attention from various industries. the classification systems of a new field Convergence Security has become a very important criteria such about the Statistics calculation, the Analysis of status industry sector and the Road maps. However, In the domestic, The related institutions classified each other differently the Convergence Security Classification. so it is urgently needed a domestic security fields systematic classification due to the problems such as lack of reliability of the accuracy, compatibility of a data. Therefore, this paper will be analyzed to the characteristics of the domestic security classification systems by the cases. and will be proposed the newly improved classification system, to be possible to addition or deletion of an classification entries, and to be easy expanded according to the new technology trends. this proposed to classification system is expected to be utilized as a basis for the construct of a domestic security classification system in a future.

• Journal of Korean Society of Transportation
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• v.14 no.2
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• pp.137-155
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• 1996

본 논문은 다이아몬드 인터체인지에서의 유고감지모형 개발을 위해 퍼지이론을 응용한 연구를 문서화 한 것이다. 지금까지의 교차로와 일반도로(고속도로가 아닌)에서의 유고감지에 관한 연구는 초기에 불과하다. 기존의 알고리즘들은 필요한 데이터 보존의 어 려움과 유고감지의 특성과 관련된 기술적 어려움을 효과적으로 극복하지 못하고 있다. 본 연구의 목적은 다이아몬드 인터체인지에서의 유고감지를 위한 새로운 모형을 개발하는데 있다. 이 연구를 통하여 개발된 유고감지 모형은 차량차단 유고(lane-blocking incidents) 를 감지하는데, 감지의 범위는 차량차단 유고의 경향이 교통 장황에 특정한 패턴을 형성 하고 그에 따른 신호제어전략의 조정이 요구될 때에 국한된다. 이 모형은 전통적인 통계 치를 이용한 유고감지감 고유의 문제를 해결하며, 보다 정확하고 신뢰성 있는 유고감지를 위해 다양한 교통변수를 이용하여 전체적인 유고의 경향을 포착한다. 또한 이 모형은 실 시간 교통대응 다이아몬드 인터체인지 신호제어 시스템 (real-time traffic adaptive diamond interchange control system)의 구성요소로써 사용되며, 그리고 더 큰 교차로 시스템에의 상용을 위하여 확장이 용역하도록 설계되었다. 본 연구를 통해 개발된 프로 토타입(prototype) 유고감지 모형은 실제의 다이아몬드 인터체인지에 적용되어, 감지율, 오보율, 평감지시간의 세 달로써 성능이 평가되었다. 모형의 성능평가 결과는 무적이었으 며, 퍼지이론은 유고감지에 효과적인 접근방법임을 확인할 수 있었다.투자의 타당성을 실증적으로 보여 주고 있다.산정 절차 정립에 엇갈림 알고리즘을 활용하는 방안을 제시하였다.자함수를 추정한 뒤 이를 이용해 업종, 기업규모, 상품유형별로 적합한 모델(Fixed Effects Model)을 결정하고, 각각에 해당하는 통계모형을 구축하였다. 이 결과 (1) 업종 및 기업규모별로 그룹간에 유의한 특성이 발견되었으며, (2) R&D 및 광고투자는 기업의 시장성과를 설명하는 중요한 변수이나, (3) R&D 투자의 경우는 광고에 비해 불확실성이 존재하는 것으로 나타났고, (4) 수리모형에서 도출된 한계원리가 통계모형에서도 유효한 것으로 드러났다.등을 토대로 한 10대 산업을 육성하기 위하여 과학기술부는 기술수요조사를 바탕으로 49개 주요기술을 도출하여, 과학기술 일류 국가 실현, 국민소득 2만불 달성이라는 국가적 슬로건을 내걸고 “차세대 성장동력” 창출을 위한 범정부차원의 기획과 연구비의 집중투자를 추진하고 있다.달성하기 위해서는 종합류류 전산망의 시급한 구축과 함께 화물차의 적재율을 높이고 공차율을 낮출 수 있는 운송체계의 수립이 필요한 것으로 판단된다. 그라나 이러한 화물전용차선의 효과는 단기적인 치유책일 수밖에 없기 때문에 물류유통 시설의 확충을 위한 사회간접자본의 구축을 서둘러 시행하여야 할 것이다.으로 처리한 Machine oil, Phenthoate EC 및 Trichlorfon WP는 비교적 약효가 낮았다.>$^{\circ}$E/$\leq$30$^{\circ}$NW 단열군이 연구지역 내에서 지하수 유동성이 가장 높은 단열군으로 추정된다. 이러한 사실은 3개 시추공을 대상으로 실시한

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2895-2905
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• 2018

We present a mixed multiplicative quantitative randomized response model which added a unrelated quantitative attribute and forced answer to the multiplicative model suggested by Bar-Lev et al. (2004). We also try to set up theoretical grounds for estimating sensitive quantitative attribute according to circumstances whether or not the information for unrelated quantitative attribute is known. We also extend it into the stratified mixed multiplicative quantitative randomized response model for stratified population along with two allocation methods, proportional and optimum allocation. We can see that the various quantitative randomized response models such as Eichhorn-Hayre's model (1983), Bar-Lev et al.'s model (2004), Gjestvang-Singh's model (2007) and Lee's model (2016a), are one of the special occasions of the suggested model. Finally, We compare the efficiency of our suggested model with Bar-Lev et al.'s (2004) and see that the bigger the value of $C_z$, the more the efficiency of the suggested model is obtained.

• Management & Information Systems Review
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• v.35 no.2
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• pp.99-118
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• 2016

With the development of Internet and popularization of smartphones over recent years, social network services are experiencing rapid growth. On top of this, smartphone gaming market is showing a rapid growth and the use of mobile social games is on the significant rise. The occurrence of game data manipulation targeting these services and personal information leakage is highlighting the importance of social gaming security. This study is intended to propose development plans effective and efficient in social game services by figuring out factors putting effects on security dependent behavior of social game users in Korea and carrying out a practical study on the casual relationship between factors influencing security dependent behavior through recognized behavioral control and attitudes for privacy infringement of these factors. To do this, proposed was a study model in which the HBM(Health Belief Model) allowing the social game user to influence security dependent behavior was expanded and applied as a major variable. To verify the study model of this study practically, a survey was conducted among university students in Seoul-based K University and S University who had experienced using social game services. According to the study findings, firstly, the perceived seriousness turned out to provide positive influence to trust. But, the perceived seriousness turned out not to put positive effects on self-efficacy. Secondly, the perceived probability turned out not to put positive effects on self-efficacy and trust. Thirdly, the perceived gain turned out to put positive effects on self-efficacy and trust. Fourthly, the perceived disorder turned out not to put positive effects on self-efficacy and trust. Fifthly, self-efficacy turned out to put positive effects on trust. But, self-efficacy turned out not to put positive effects on security dependent behavior. Sixthly, trust turned out not to put positive effects on security dependent behavior. This study is intended to make a strategic proposal so that social game users can raise awareness of their level of security perception and security willingness through this.

• Spatial Information Research
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• v.23 no.4
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• pp.57-66
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• 2015

At these day, owing to functional limitations and cost issues, used image map in web service have a problem which can not make exactly meet the user needs. This study aims to create an individual map for user suitable purposes using HTML5 technology that implement the vector map creation and its functions with services. The results of this study, the invisible problems of the tilting and rotation functions in image-based map utilizing the existing web environment were solved in HTML5 vector map. And to access the map information, by implementing the function of expressing the background and name data to selectively derive, various results were expressed in the map. Also, as a result of a comparison of performance the time required was measured at 0.88sec which comes in the range of the first loading time between 0.78sec and 7.56sec in a commercial map service, which showed the possibility of its commercialization. compared to 180GB of image maps for the production of a national map index system, the volume to produce a vector map was 2.5GB, a decrease by over 90%, which solved the issue of costs for a storage space. As a result, this study of HTML5 vector map design and implementation presented a plan for providing information suitable for the requirements of the users who use spatial information through utilizing a variety of information and expanding functions.

• Journal of Korea Spatial Information System Society
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• v.9 no.1
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• pp.45-57
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• 2007

Recently, the development of sensor devices has accelerated researches on advanced technologies like Wireless Sensor Networks. Moreover, spatial sensors using GPS lead to the era of the Ubiquitous Computing Environment which generally uses spatial information and non-spatial information together. In this new era, a real-time processing system for spatial sensor data is essential. In this reason, new data processing systems called DSMS(Data Stream Management System) are being developed by many researchers. However, since most of them do not support geometry types and spatial functions to process spatial sensor data, they are not suitable for the Ubiquitous Computing Environment. For these reasons, in this paper, we designed and implemented a spatial DSMS by extending STREAM which stands for STanford stREam datA Manager, to solve these problems. We added geometry types and spatial functions to STREAM in order to process spatial sensor data efficiently. In addition, we implemented a Spatial Object Manager to manage shared spatial objects within the system. Especially, we implemented the Simple Features Specification for SQL of OGC for interoperability and applied algorithms in GEOS to our system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.15-23
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• 2017

The person Re-identification is the most challenging part of computer vision due to the significant changes in human pose and background clutter with occlusions. The picture from non-overlapping cameras enhance the difficulty to distinguish some person from the other. To reach a better performance match, most methods use feature selection and distance metrics separately to get discriminative representations and proper distance to describe the similarity between person and kind of ignoring some significant features. This situation has encouraged us to consider a novel method to deal with this problem. In this paper, we proposed an enhanced recurrent neural network with three-tier hierarchical network for person re-identification. Specifically, the proposed recurrent neural network (RNN) model contain an iterative expectation maximum (EM) algorithm and three-tier Hierarchical network to jointly learn both the discriminative features and metrics distance. The iterative EM algorithm can fully use of the feature extraction ability of convolutional neural network (CNN) which is in series before the RNN. By unsupervised learning, the EM framework can change the labels of the patches and train larger datasets. Through the three-tier hierarchical network, the convolutional neural network, recurrent network and pooling layer can jointly be a feature extractor to better train the network. The experimental result shows that comparing with other researchers' approaches in this field, this method also can get a competitive accuracy. The influence of different component of this method will be analyzed and evaluated in the future research.

• Journal of the Korea Computer Industry Society
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• v.3 no.3
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• pp.331-340
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• 2002

The web world is getting so huge and untractable that without an intelligent information extractor we would get more and more helpless. Conventional web spidering techniques for general purpose search engine may be too slow for the specific search engines, which concentrate only on specific areas or keywords. In this paper a new model for improving web spidering capabilities is suggested and experimented. How to select adequate reference web pages from the initial web Page set relevant to a given specific area (or keywords) can be very important to reduce the spidering speed. Our reference web page selection method DOPS dynamically and orthogonally selects web pages, and it can also decide the appropriate number of reference pages, using a newly defined measure. Even for a very specific area, this method worked comparably well almost at the level of experts. If we consider that experts cannot work on a huge initial page set, and they still have difficulty in deciding the optimal number of the reference web pages, this method seems to be very promising. We also applied reinforcement learning to web environment, and DOPS-based reinforcement learning experiments shows that our method works quite favorably in terms of both the number of hyper links and time.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.5
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• pp.28-40
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• 2019

In order to resolve the imbalances in the supply of living SOCs according to socio-economic status, location, and population groups, the discussions on inclusive city policies are expanding. The purpose of this study is to propose an Index of Park Derivation (IPD) as an alternative indicator for the promotion of an inclusive urban park policy that can be applied in the 7 major metropolitan cities to select a region with a relatively high park needs. The main research results are as follows. First, the concept of an inclusive urban park policy is defined as "a policy to supply to manage high-quality park services with priority given to areas with low socio-economic and environmental status, such as a large amount of elderly, children, low-income families, areas vulnerable to disasters, such as heat and fine dust, and population groups." Second, we developed the index of park derivation (IPD), which is a combination of 17 variables including park service level, demographic characteristics, economic and educational level, health level, and environmental vulnerability. The variables that constitute the index of park deprivation (IPD) can be applied to SOC policies outside the parks, such as sports facilities, daycare centers, kindergartens, and public libraries. Third, applying index of park deprivation (IPD) to 1,148 Eup/Myeon/dong areas of the 7 metropolitan cities resulted in areas with relatively high park service needs. This study implies that the central and the local government suggest an alternative index to promote an inclusive urban park policy based on statistical and geographical information and data that can be easily accessed and utilized.