• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.109-131
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• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

• Cartoon and Animation Studies
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• s.33
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• pp.223-246
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• 2013

Even though cartoons and narration comics were born from different origin, they have been called by names such as 'cartoons' or 'comics'. The reason can be found in the similarity of cartoons and narration comics. The similarity of cartoons and narration comics is the genre consisting of writing and drawing. Writing can be the format of expression and it can represent the story. Such story is present as a component of 'narration'. Sub genre of comics includes cartoons and narration comics. It includes animation in a broad range. In cases of narration comics and animation, it is thought that narration is present with continuity of time. However, in case of cartoon, because one or two cuts without continuity of writing are frequently expressed, it is being asked whether narration is present. It is easy to be reminded of epic or chanson de geste whenever you hear 'narration'. Since it deals with a biography of the character, we think the concept of 'narration' with temporality. However, narration provides a certain event in a broad range. Thus, cartoons presenting one event with the image may have the existence of narration, because description of multiple scenes of narrative comics can be implicitly represented in cartoons. As such implications leave a space, the empty space can be filled by active reasoning of recipients. However, nevertheless, it is very difficult to find studies as well as mentions of narration in cartoons. Thus, in this paper, we investigate the concept and structure of narration and demonstrate the presence of narration in cartoons. First of all, we looked at the narration theory in literature before studying narration in cartoons. The reason is that we thought the approach to the literary theory was required in order to investigate the basic elements, since cartoons are a collection of writing and drawing. We were focused on the prerequisites of narration presented in "story and discourse" of s. Chatman. If the prerequisites of narration are present, we can assume that the narration is present. The prerequisites are 'narration reasoning', 'screening', 'consistency', 'process statements' and 'stasis statement'. As s. Chatman described them as prerequisites of narration, he analyzed the narration structures of films and novels. In addition, we revealed that the narrations were present in cartoons as we identified how prerequisites of narration presented by Chatman were presented and expressed through "vocabulary of comics", "Timeframe" and "life in the line" described in "understanding comics" by Scott McCloud.

• Journal of Service Research and Studies
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• v.5 no.1
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• pp.91-103
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• 2015

We examine the information transmission between the KT Spot and the KT Futures Index, the SK Telecom Spot and the SK Telecom Futures Index, based on the returns data offered by the Korea Exchange. The data includes daily return data from 1 January 2012 to 31 December 2014. Utilizing a dynamic analytical tool-the VAR model, Granger Causality test, Impulse Response Function and Variance Decomposition have been implemented. The results of the analysis are as follows. Firstly, results of Granger Causality test suggests the existence of mutual causality the KT Futures Index and the SK Telecom Futures Index precede and have explanatory power the KT Spot and the SK Telecom Spot However the results also identified a greater causality and explanatory power of the KT Spot and the SK Telecom Spot over the KT Futures Index and the SK Telecom Futures Index. Secondly, the results of impulse response function suggest that the KT Futures Index show immediate response to the KT Spot and are influenced by till time 4. From time 2, the impact gradually disappears. Also the SKT Futures Index show immediate response to the SKT Spot and are influenced by till time 4. From time 2, the impact gradually disappears. Lastly, the variance decomposition analysis shows that the changes of return of the KT Spot and SKT Spot are dependent on those of the KT Futures Index and the SK Telecom Futures Index. This implies that returns on the KT Spot and SKT Spot have a significant influence over returns on the KT Futures Index and the SK Telecom Futures Index. It contributes to the understanding of market price formation function through analysis of detached the KT Spot and the KT Futures Index, the SK Telecom Spot and the SK Telecom Futures Index.

• Health Policy and Management
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• v.34 no.3
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• pp.293-308
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• 2024

Background: Assessing the change in mental health status of quarantined patients in community treatment centers at the time of admission and discharge, and inferring the influencing factors. Methods: The study was conducted on a sample of 1,941 quarantined patients from three community treatment centers. Changes in anxiety, psychological distress, post-traumatic stress, depression, and self-harm ideation between admission and discharge were categorized as either "improved" or "worsened." Inference was performed to determine the probability of worsening in mental health status. Results: The mental health status of quarantined patients, such as anxiety and depression, was relatively higher than that of the general population. Anxiety (84.3% improved) and psychological distress (79.0% improved) were reduced during quarantine treatment. However, some patients continued to experience moderate to severe levels of anxiety (11.2%) and psychological distress (11.0%) at discharge. As for depression, the depression of moderate or higher level was increased at the time of discharge (28.7%→36.7%) compared to admission. The deterioration of anxiety and psychological distress was found to be the most significant factor influencing the worsening of depression at discharge (odds ratio [OR] for anxiety deterioration, 2.04; OR for psychological distress deterioration, 3.56). These effects were also observed similarly in post-traumatic stress and self-injury ideation. Conclusion: Improving anxiety and psychological distress among quarantined patients in community treatment centers can reduce the worsening of post-traumatic stress, depression, and self-injury ideation at the time of discharge. These findings provide evidence for the need for active mental health management from the initial stages of quarantine treatment.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.37-44
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• 2008

Data entered into RFID tags are used for saving costs and enhancing competitiveness in the development of applications in various industrial areas. RFID readers perform the identification and search of hundreds of objects, which are tags. RFID technology that identifies objects on request of dynamic linking and tracking is composed of application components supporting information infrastructure. Despite their many advantages, existing applications, which do not consider elements related to real.time data communication among remote RFID devices, cannot support connections among heterogeneous devices effectively. As different network devices are installed in applications separately and go through different query analysis processes, there happen the delays of monitoring or errors in data conversion. The present study implements a RFID database handling system in semantic Web environment for integrated management of information extracted from RFID tags regardless of application. Users’ RFID tags are identified by a RFID reader mounted on an application, and the data are sent to the RFID database processing system, and then the process converts the information into a semantic Web language. Data transmitted on the standardized semantic Web base are translated by a smart browser and displayed on the screen. The use of a semantic Web language enables reasoning on meaningful relations and this, in turn, makes it easy to expand the functions by adding modules.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.2
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• pp.74-93
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• 2010

Nowadays, the navigation system is very popular to general public and the study of landmarks has an important role to develop the cognitive systems for regional navigation. The city image is composed of landmarks that are well-known to regional community and they are the reference frame for place recognition in urban navigation. In general, the case of navigation can be categorized as two kinds. The first is to explore the new region and the second is to navigate the familiar region. In case of latter, the city image has a critical role in place recognition for regional community. Place recognition of a community might be a knowledge-based inference on the basis of city image which is composed of the systematically connected places. In this study, the mental structure of urban image is regarded as a hierarchical knowledge and represents it as domain ontology for the regional navigation of a community. The city image of a community is assumed as the collection of landmarks, which are categorized as anchor, distant and local according to spatial familiarity of community. Representing city image as a regional knowledge using ontology modeling method is an essential step to make the geographical assumption of a regional community explicit and reusable for the regional agents who will provide the regional guide in LBS age.

• Journal of the Korean earth science society
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• v.35 no.3
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• pp.192-202
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• 2014

The purpose of this study was to investigate high school students' conception of conservation of mass through the scenario of carbon emission in terms of carbon cycle. Seventy six high school students of 11th grade were participated in this study. Participants were provided with two scenarios that showed a gradual increase and decrease of atmospheric $CO_2$ amount from the level recorded in 2013 up to 450 ppm and to 340 ppm by 2110, which is the changes of around 15%. We asked participants to explain the reason after having them draw the emissions trajectory of $CO_2$ according to scenario. Most participants thought that carbon emission would continue to increase despite the two scenarios of carbon emission making sense in terms of conservation of mass between emissions and the natural removal of carbon dioxide. This implies that participants came to think of pattern matching that carbon emission would continue to increase as they used correlation graphs of carbon emission: that is, the graphs of the evolution of anthropogenic emissions, of atmospheric $CO_2$, and of global mean temperature, from the beginning of the Industrial Revolution up to date, all of which are shown in high school earth science textbooks.

• The Journal of Society for e-Business Studies
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• v.20 no.4
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• pp.151-175
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• 2015

Although three types of the information security measures (technical, physical and managerial ones) are all together critical to maintaining information security in the organizations and should be implemented at the same time, this study aims at providing theoretical basis of establishing and implementing effective managerial security measures. The rationale behind this research objective is that it is very important to effectively perform the managerial security measures to achieve the target performance level of the technical and the physical security measures because main agents of practicing the information security measures in the organizations are staff members even though the technical and the physical ones are well constructed and implemented. In particular, this study intends to develop and propose the theoretical model applicable to providing the way of improving organizational members' intention to use information security technologies since the very intention to use them is essential to effectively establishing and promoting managerial security measures. In order to achieve the objective of this study, the factors critical to influencing upon the intention to use information security technologies are derived through systematically reviewing related theories and previous studies, and then the research model and hypotheses are proposed by logically reasoning the casual relationship among the these factors. Also, the empirical analyses are performed by conducting the survey of the organization members of domestic large companies and analyzing the structural equation model by PLS (Partial Least Squares) method. The significant results of this study can contribute to expanding the research area of managerial information security and can be applied to suggesting the practical guidelines for effectively establishing and implementing the managerial security measures in various organizations.