• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.131-146
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• 2011

It is becoming more essential than ever for office professionals to become competent in information collection/gathering and problem solving in today's global business society. In particular, office professionals do not only assist simple chores but are also forced to make decisions as quickly and efficiently as possible in problematic situations that can end in either profit or loss to their company. Since office professionals rely heavily on their tacit knowledge to solve problems that arise in everyday business situations, it is truly helpful and efficient to refer to similar business cases from the past and share or reuse such previous business knowledge for better performance results. Case-based reasoning(CBR) is a problem-solving method which utilizes previous similar cases to solve problems. Through CBR, the closest case to the current business situation can be searched and retrieved from the case or knowledge base and can be referred to for a new solution. This reduces the time and resources needed and increase success probability. The main purpose of this study is to design a system called COKRS(Case-based reasoning Office Knowledge Recommender System) and develop a prototype for it. COKRS manages cases and their meta data, accepts key words from the user and searches the casebase for the most similar past case to the input keyword, and communicates with users to collect information about the quality of the case provided and continuously apply the information to update values on the similarity table. Core concepts like system architecture, definition of a case, meta database, similarity table have been introduced, and also an algorithm to retrieve all similar cases from past work history has also been proposed. In this research, a case is best defined as a work experience in office administration. However, defining a case in office administration was not an easy task in reality. We surveyed 10 office professionals in order to get an idea of how to define a case in office administration and found out that in most cases any type of office work is to be recorded digitally and/or non-digitally. Therefore, we have defined a record or document case as for COKRS. Similarity table was composed of items of the result of job analysis for office professionals conducted in a previous research. Values between items of the similarity table were initially set to those from researchers' experiences and literature review. The results of this study could also be utilized in other areas of business for knowledge sharing wherever it is necessary and beneficial to share and learn from past experiences. We expect this research to be a reference for researchers and developers who are in this area or interested in office knowledge recommendation system based on CBR. Focus group interview(FGI) was conducted with ten administrative assistants carefully selected from various areas of business. They were given a chance to try out COKRS in an actual work setting and make some suggestions for future improvement. FGI has identified the user-interface for saving and searching cases for keywords as the most positive aspect of COKRS, and has identified the most urgently needed improvement as transforming tacit knowledge and knowhow into recorded documents more efficiently. Also, the focus group has mentioned that it is essential to secure enough support, encouragement, and reward from the company and promote positive attitude and atmosphere for knowledge sharing for everybody's benefit in the company.

• 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.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 Korean Society of Transportation
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• v.20 no.5
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• pp.113-130
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• 2002

In this paper, we developed DNL(Dynamic Network Loading) model based on Moving cell theory to analyze the dynamic characteristics of traffic flow in congested network. In this paper vehicles entered into link at same interval would construct one cell, and the cells moved according to Cell following rule. In the past researches relating to DNL model a continuous single link is separated into two sections such as running section and queuing section to describe physical queue so that various dynamic states generated in real link are only simplified by running and queuing state. However, the approach has some difficulties in simulating various dynamic flow characteristics. To overcome these problems, we present Moving cell theory which is developed by combining Car following theory and Lagrangian method mainly using for the analysis of air pollutants dispersion. In Moving cell theory platoons are represented by cells and each cell is processed by Cell following theory. This type of simulation model is firstly presented by Cremer et al(1999). However they did not develop merging and diverging model because their model was applied to basic freeway section. Moreover they set the number of vehicles which can be included in one cell in one interval so this formulation cant apply to signalized intersection in urban network. To solve these difficulties we develop new approach using Moving cell theory and simulate traffic flow dynamics continuously by movement and state transition of the cells. The developed model are played on simple network including merging and diverging section and it shows improved abilities to describe flow dynamics comparing past DNL models.

• Journal of Technology Innovation
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• v.20 no.2
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• pp.75-107
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• 2012

Previous researches on technological innovation have several limitations such as lack of general mechanism for technological innovation(inputs, throughputs and outputs of technological innovation), large company oriented studies, and ignoring importance of technology management capabilities. So, this study suggested a new model using resource-based theory and system theory, and empirically applied that to SMEs. Structural equation model analysis by using 223 SMEs in Daegu region provided a support for most of hypotheses. Research results showed that all of factors on technological innovation were significantly and positively related with each other: inputs(R&D leadership, innovation strategy, R&D investment, R&D human resource management, external network), throughputs(portfolio management, project management, technology commercialization) and output(technological innovation). In case of technological innovation inputs, R&D leadership influenced on innovation strategy positively and significantly. And R&D leadership and innovation strategy had positive and significant effects on R&D investment, R&D human resource management and external network. R&D human resource management and external network exerted positive and significant influences on technological innovation throughputs such as portfolio management and project management. But R&D investment did not significant impacts on technological innovation throughputs. Among technological innovation throughputs, both portfolio management and project management had positive and significant effect on technology commercialization. In addition, technology commercialization acted positively and significantly technological innovation output. This study suggests necessary of efforts to implement innovation strategy and manage R&D human resource effectively based on CEO's innovativeness and entrepreneurship. Also, if SMEs want to develop technology and commercialize it, they have to cooperate with external technology resources and informations. Research results revealed that proper level of R&D investment, internal and external communication, information sharing, and learning and cooperative culture were very important for improvement of technological innovation performance in SMEs. Especially, this research suggested that if SMEs manage technological innovation process effectively based on resource-based and system approaches, then they can overcome their resource limitations and gain high technological innovation performance. Also, useful policy support for technological innovation of central or regional government by this research model is important factor for SMEs' technological innovation performance.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.2
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• pp.107-117
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• 2004

If doubtlessly contributes much to agriculture and rural development. The roles can be summarized as; 1. to activate rural areas and to provide more comfortable and safe rural life with equivalent services to those in urban areas, facilitating distance education, tole-medicine, remote public services, remote entertainment etc. 2. To initiate new agricultural and rural business such as e-commerce, real estate business for satellite officies, rural tourism and virtual corporation of small-scale farms. 3. To support policy-making and evaluation on optimal farm production, disaster management, effective agro-environmental resource management etc., providing tools such as GIS. 4. To improve farm management and farming technologies by efficient farm management, risk management, effective information or knowledge transfer etc., realizing competitive and sustainable farming with safe products. 5. To provide systems and tools to secure food traceability and reliability that has been an emerging issue concerning farm products since serious contamination such as BSE and chicken flu was detected. 6. To take an important and key role for industrialization of farming or lam business enterprise, combining the above roles.

• Journal of the Korean Geographical Society
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• v.51 no.5
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• pp.613-632
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• 2016

The recent diagnosis of the Anthropocene challenges public understanding of nature as a pure and singular entity removed from society, as the diagnosis confirms the earth-changing force of humans. In geography, the nature-society divide has been critically interrogated long before the diagnosis of the Anthropocene, developing several ways of theorizing nature-society relations. This paper introduces a new frontier for such theoretical endeavors: more-than-human geography. Inspired by the material and performative turn in geography and the social sciences around the 2000s, more-than-human geographers have sought to re-engage with the livingness of the world in the study of nature-society relations. Drawing on actor-network theory, non-representational theory (NRT) and vitalism, they have developed innovative ways of thinking about and relating to nature through the key concepts of 'nonhuman agency' and 'affect'. While more-than-human geography has been extensively debated and developed in recent Euro-American scholarship on cultural and economic geography, it has so far received limited attention in Korean geographical studies on nature. This paper aims to address this gap by discussing the key concepts and seminal work of more-than-human geography. I first outline four theoretical strands through which nature-society relations are perceived in geography. I then offer an overview of more-than-human geography, discussing its theoretical foundations and considering ontologies, epistemologies, politics and ethics associated with nature-society relations. Then, I compare more-than-human geography with political ecology, which is the mainstream critical approach in contemporary environmental social sciences. I would argue that more-than-human geography further challenges and develops political ecology through its heightened attention to the affective capacity of nonhumans and the methodological ethos of doing a careful political ecology. I conclude by reflecting on the implications of more-than-human geography for Korean studies on nature-society relations.

• Journal of Life Science
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• v.23 no.11
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• pp.1325-1335
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• 2013

Working dogs, such as rescue dogs, military watch dogs, guide dogs, and search dogs, are selected by in-training examination of desired traits, including concentration, possessiveness, and boldness. In recent years, genetic information has been considered to be an important factor for the outstanding abilities of working dogs. To characterize the molecular features of the canine genes related to phenotypes for working dogs, we investigated the 24 previously reported genes (AR, BDNF, DAT, DBH, DGCR2, DRD4, MAOA, MAOB, SLC6A4, TH, TPH2, IFT88, KCNA3, TBR2, TRKB, ACE, GNB1, MSTN, PLCL1, SLC25A22, WFIKKN2, APOE, GRIN2B, and PIK3CG) that were categorized to personality, olfactory sense, and athletic/learning ability. We analyzed the chromosomal location, gene-gene interactions, Gene Ontology, and expression patterns of these genes using bioinformatic tools. In addition, variable numbers of tandem repeat (VNTR) or microsatellite (MS) polymorphism in the AR, MAOA, MAOB, TH, DAT, DBH, and DRD4 genes were reviewed. Taken together, we suggest that the genetic background of the canine genes associated with various working dog behaviors and skill performance attributes could be used for proper selection of superior working dogs.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1245-1257
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• 2021

GOCI-II, succeeding the mission of GOCI, was launched in February 2020 and has been in regular operation since October 2020. Korea Institute of Ocean Science and Technology (KIOST) processes and produces in real time Level-1B and 26 Level-2 outputs, which then are provided by Korea Hydrographic and Oceanographic Agency (KHOA). We introduced current status of regular GOCI-II operation and showed future improvement. Basic GOCI-II products including chlorophyll-a, total suspended materials, and colored dissolved organic matter concentration, are induced by OC4 and YOC algorithms, which were described in detail. For the full disk (FD), imaging schedule was established considering solar zenith angle and sun glint during the in-orbital test, but improved by further considering satellite zenith angle. The number of slots satisfying the condition 'Best Ocean' significantly increased from 15 to 78. GOCI-II calibration requirements were presented based on that by European Space Agency (ESA) and candidate fixed locations for calibrating local observation area were. The quality management of FD uses research ships and overseas bases of KIOST, but it is necessary to establish an international calibration/validation network. These results are expected to enhance the understanding of users for output processing and help establish detailed plans for future quality management tasks.

• Journal of Family Resource Management and Policy Review
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• v.25 no.3
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• pp.87-102
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• 2021

Child abuse and neglect are recently increasing in Korea, and although the government has actively improved the child protection system, the number of abused children and the rate of cases judged as abuse have continuously risen. Given that 75% of child abusers are parents, child abuse and neglect are expected to recur. To prevent such a recurrence, various intervention programs for abused children and their parents are required. The purpose of this study were to design a recovery support service process and investigate the effectiveness of pilot program for families of origin, including neglected(protected) children, to improve the system by which these programs are operated, and formulate policy alternatives that reinforce "family preservation" principles. The pilot program was implemented from June to November 2020 in 4-local healthy family support center. The number of program participants and the frequency of participation in each other differed, because of the difference in number of confirmed coronavirus cases in each region and the requirement for social distancing. Through the program, a community-based service process was developed for neglected(protected) children and their parents, and cooperative networks between related facilities and institutions were established. The study formulated the following recommendations: First, a cooperation system among government departments mandated to provide different services to neglected(protected) children is needed. Second, wider and various channels through which abused children can avail of protective services should be developed within communities. Third, more stable environments for program operation should be cultivated, and cooperative partnerships should be sought for knowledge sharing among relevant government departments. Another necessary measure is for a center to develop its own business model, in which the duplication of services provided by involved organizations is avoided. Finally, clear guidelines, administrative standards, and specific plans for program operation should be arranged. Also regional characteristics are maintained, but services should be standardized.