• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.541-550
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• 2019

An emergency generator is key equipment for fire-fighting to supply power to fire-fighting facilities, which protect property and people in cases of fire accidents. A rated load test for emergency generators must be carried out by connecting an emergency load to the generator in accordance with related regulations. However, a no-load test has been performed for emergency generators in general since serious problems can occur when the main power is cut off, including the damage of customer devices and shut down of critical loads. Therefore, this paper proposes a load test method for an emergency generator using energy storage system (ESS) without the interruption of main power. The emergency power system was also modeled based on PSCAD/EMTDC software, and a 200-kW scale ESS load test device was implemented. The simulation and test results show that the load test method is useful and practical for an emergency power supply system.

• Journal of Soil and Groundwater Environment
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• v.13 no.1
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• pp.77-91
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• 2008

In this study, we developed a technique of applying DRASTIC, which is the most widely used tool for estimation of groundwater vulnerability to the aqueous phase contaminant infiltrated from the surface, and a groundwater flow model jointly to assess groundwater contamination potential. The developed technique is then applied to Buyeo-eup area in Buyeo-gun, Chungcheongnam-do, Korea. The input thematic data of a depth to water required in DRASTIC model is known to be the most sensitive to the output while only a few observations at a few time schedules are generally available. To overcome this practical shortcoming, both steady-state and transient groundwater level distributions are simulated using a finite difference numerical model, MODFLOW. In the application for the assessment of groundwater vulnerability, it is found that the vulnerability results from the numerical simulation of a groundwater level is much more practical compared to cokriging methods. Those advantages are, first, the results from the simulation enable a practitioner to see the temporally comprehensive vulnerabilities. The second merit of the technique is that the method considers wide variety of engaging data such as field-observed hydrogeologic parameters as well as geographic relief. The depth to water generated through geostatistical methods in the conventional method is unable to incorporate temporally variable data, that is, the seasonal variation of a recharge rate. As a result, we found that the vulnerability out of both the geostatistical method and the steady-state groundwater flow simulation are in similar patterns. By applying the transient simulation results to DRASTIC model, we also found that the vulnerability shows sharp seasonal variation due to the change of groundwater recharge. The change of the vulnerability is found to be most peculiar during summer with the highest recharge rate and winter with the lowest. Our research indicates that numerical modeling can be a useful tool for temporal as well as spatial interpolation of the depth to water when the number of the observed data is inadequate for the vulnerability assessments through the conventional techniques.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.33-49
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• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.101-124
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• 2018

Recently, most of the technologies have been developed in various forms through the advancement of single technology or interaction with other technologies. Particularly, these technologies have the characteristic of the convergence caused by the interaction between two or more techniques. In addition, efforts in responding to technological changes by advance are continuously increasing through forecasting promising convergence technologies that will emerge in the near future. According to this phenomenon, many researchers are attempting to perform various analyses about forecasting promising convergence technologies. A convergence technology has characteristics of various technologies according to the principle of generation. Therefore, forecasting promising convergence technologies is much more difficult than forecasting general technologies with high growth potential. Nevertheless, some achievements have been confirmed in an attempt to forecasting promising technologies using big data analysis and social network analysis. Studies of convergence technology through data analysis are actively conducted with the theme of discovering new convergence technologies and analyzing their trends. According that, information about new convergence technologies is being provided more abundantly than in the past. However, existing methods in analyzing convergence technology have some limitations. Firstly, most studies deal with convergence technology analyze data through predefined technology classifications. The technologies appearing recently tend to have characteristics of convergence and thus consist of technologies from various fields. In other words, the new convergence technologies may not belong to the defined classification. Therefore, the existing method does not properly reflect the dynamic change of the convergence phenomenon. Secondly, in order to forecast the promising convergence technologies, most of the existing analysis method use the general purpose indicators in process. This method does not fully utilize the specificity of convergence phenomenon. The new convergence technology is highly dependent on the existing technology, which is the origin of that technology. Based on that, it can grow into the independent field or disappear rapidly, according to the change of the dependent technology. In the existing analysis, the potential growth of convergence technology is judged through the traditional indicators designed from the general purpose. However, these indicators do not reflect the principle of convergence. In other words, these indicators do not reflect the characteristics of convergence technology, which brings the meaning of new technologies emerge through two or more mature technologies and grown technologies affect the creation of another technology. Thirdly, previous studies do not provide objective methods for evaluating the accuracy of models in forecasting promising convergence technologies. In the studies of convergence technology, the subject of forecasting promising technologies was relatively insufficient due to the complexity of the field. Therefore, it is difficult to find a method to evaluate the accuracy of the model that forecasting promising convergence technologies. In order to activate the field of forecasting promising convergence technology, it is important to establish a method for objectively verifying and evaluating the accuracy of the model proposed by each study. To overcome these limitations, we propose a new method for analysis of convergence technologies. First of all, through topic modeling, we derive a new technology classification in terms of text content. It reflects the dynamic change of the actual technology market, not the existing fixed classification standard. In addition, we identify the influence relationships between technologies through the topic correspondence weights of each document, and structuralize them into a network. In addition, we devise a centrality indicator (PGC, potential growth centrality) to forecast the future growth of technology by utilizing the centrality information of each technology. It reflects the convergence characteristics of each technology, according to technology maturity and interdependence between technologies. Along with this, we propose a method to evaluate the accuracy of forecasting model by measuring the growth rate of promising technology. It is based on the variation of potential growth centrality by period. In this paper, we conduct experiments with 13,477 patent documents dealing with technical contents to evaluate the performance and practical applicability of the proposed method. As a result, it is confirmed that the forecast model based on a centrality indicator of the proposed method has a maximum forecast accuracy of about 2.88 times higher than the accuracy of the forecast model based on the currently used network indicators.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.125-148
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• 2018

Recently, as the demand for big data analysis increases, cases of analyzing unstructured data and using the results are also increasing. Among the various types of unstructured data, text is used as a means of communicating information in almost all fields. In addition, many analysts are interested in the amount of data is very large and relatively easy to collect compared to other unstructured and structured data. Among the various text analysis applications, document classification which classifies documents into predetermined categories, topic modeling which extracts major topics from a large number of documents, sentimental analysis or opinion mining that identifies emotions or opinions contained in texts, and Text Summarization which summarize the main contents from one document or several documents have been actively studied. Especially, the text summarization technique is actively applied in the business through the news summary service, the privacy policy summary service, ect. In addition, much research has been done in academia in accordance with the extraction approach which provides the main elements of the document selectively and the abstraction approach which extracts the elements of the document and composes new sentences by combining them. However, the technique of evaluating the quality of automatically summarized documents has not made much progress compared to the technique of automatic text summarization. Most of existing studies dealing with the quality evaluation of summarization were carried out manual summarization of document, using them as reference documents, and measuring the similarity between the automatic summary and reference document. Specifically, automatic summarization is performed through various techniques from full text, and comparison with reference document, which is an ideal summary document, is performed for measuring the quality of automatic summarization. Reference documents are provided in two major ways, the most common way is manual summarization, in which a person creates an ideal summary by hand. Since this method requires human intervention in the process of preparing the summary, it takes a lot of time and cost to write the summary, and there is a limitation that the evaluation result may be different depending on the subject of the summarizer. Therefore, in order to overcome these limitations, attempts have been made to measure the quality of summary documents without human intervention. On the other hand, as a representative attempt to overcome these limitations, a method has been recently devised to reduce the size of the full text and to measure the similarity of the reduced full text and the automatic summary. In this method, the more frequent term in the full text appears in the summary, the better the quality of the summary. However, since summarization essentially means minimizing a lot of content while minimizing content omissions, it is unreasonable to say that a "good summary" based on only frequency always means a "good summary" in its essential meaning. In order to overcome the limitations of this previous study of summarization evaluation, this study proposes an automatic quality evaluation for text summarization method based on the essential meaning of summarization. Specifically, the concept of succinctness is defined as an element indicating how few duplicated contents among the sentences of the summary, and completeness is defined as an element that indicating how few of the contents are not included in the summary. In this paper, we propose a method for automatic quality evaluation of text summarization based on the concepts of succinctness and completeness. In order to evaluate the practical applicability of the proposed methodology, 29,671 sentences were extracted from TripAdvisor 's hotel reviews, summarized the reviews by each hotel and presented the results of the experiments conducted on evaluation of the quality of summaries in accordance to the proposed methodology. It also provides a way to integrate the completeness and succinctness in the trade-off relationship into the F-Score, and propose a method to perform the optimal summarization by changing the threshold of the sentence similarity.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.150-161
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• 2018

Recently, unmanned aircraft EM (electromagnetic) survey based on ICT (Information and Communication Technology) has been widely utilized because of the efficiency in regional survey. We performed the theoretical study on the unmanned airship EM system developed by KIGAM (Korea Institute of Geoscience and Mineral resources) as part of the practical application of unmanned aircraft EM survey. Since this system has different configurations of transmitting and receiving loops compared to the conventional aircraft EM systems, a new technique is required for the appropriate interpretation of measured responses. Therefore, we proposed a method to calculate the EM field for the arbitrary shaped transmitter and verified its validity through the comparison with analytic solution for circular loop. In addition, to simulate the magnetic responses by three-dimensionally (3D) distributed anomalies, we have adapted our algorithm to 3D frequency-domain EM modeling algorithm based on the edge-FEM (finite element method). Though the analysis on magnetic field responses from a subsurface anomaly, it was found that the response decreases as the depth of the anomaly increases or the flight altitude increases. Also, it was confirmed that the response became smaller as the resistivity of the anomaly increases. However, a nonlinear trend of the out-of-phase component is shown depending on the depth of the anomaly and the used frequency, that makes it difficult to apply simple analysis based on the mapping of the magnitude of the responses and can cause the non-uniqueness problem in calculating the apparent resistivity. Thus, it is a prerequisite to analyze the appropriate frequency band and flight altitude considering the purpose of the survey and the site conditions when conducting a survey using the unmanned aircraft EM system.

• The Journal of Society for e-Business Studies
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• v.14 no.4
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• pp.229-253
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• 2009

The effect of knowledge sharing and its importance have been reported in the information systems literature. However, little has been learned about the impact of knowledgeexchange web sites. This study explores relationships between individual characteristics such as personal innovativeness in the domain of information technology (PIIT), computer selfefficacy (CSE), and computer anxiety (CA), user involvement (UI), and knowledge sharing in a knowledge.exchange website. In order to examine our research model, we adopted a survey research design based on the Structural Equation Modeling method. By analyzing 241 samples collected, we conclude that UI and CA are valuable to discuss in terms of their theoretical and practical implications. This study not only extends the research on personal innovativeness and knowledge sharing, but also suggests a need for focused research efforts to investigate real practices on knowledge sharing. This study initiates this kind of efforts to make a relevant tie between design of knowledge sharing applications and the success case in the commercial field to encourage users to share their knowledge.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.664-668
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• 2018

Free-standing structures that are especially high are more likely to receive brain attacks caused by lightning. Since special structures are generally part of national industrial structures, lightning strikes mostly cause socio-economic damage. Lightning protection facilities are installed to prevent such lightning damage, but in 2015, support cables on West Sea bridges were hit by lightning, causing a lot of economic damage. Accordingly, the design of a lightning protection system shall establish protective measures after analyzing the risk of debris falling onto the structure. In this thesis, lightning strikes are analyzed directly in relation to the modeling system that operates the actual information collection system for lightning strikes, depending on the location of the tall, free-standing structures, and practical lightning hazard information is provided by a meteorological station. In addition, we propose monitoring and applying a probability correction rate to the calculation of the lightning risk based on the number of lightning strikes directly reaching the ground in order to obtain an effective lightning risk assessment.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.9
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• pp.1305-1310
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• 2010

In a practical design process, the method of extracting the design space information of the complex system for verifying, improving, and optimizing the design process by taking into account the design variables and their shape tolerance is very important. Finite element analysis has been successfully implemented and integrated with design of experiment such as D-Optimal array; thus, a response surface model and optimization tools have been obtained, and design variables can be optimized by using the model and these tools. Then, to guarantee the robustness of the design variables, a robust design should be additionally performed by taking into account the statistical variation of the shape tolerance of the optimized design variables. In this study, a new approach based on the use of the response surface model is proposed; in this approach, the standard normal distribution of the shape tolerance is considered. By adopting this approach, it is possible to simultaneously optimize variables and perform a robust design. This approach can serve as a means of efficiently modeling the trade-off among many conflicting goals in the applications of finite element analysis. A case study on the robust optimal design of disc brakes under thermal loadings was carried out to solve multiple objective functions and determine the constraints of the design variables, such as a thermal deformation and weight.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.1
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• pp.35-41
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• 2000

This paper considers the consturction of 24/25 I-NRZI (Interleaved - Non Return to Zero Inverse) modulator designs for DVCR (Digital Video Cassette Recorder), and size of validity bit in order to store the amplitude value of square-wave and the standard data ( sine and cosine coefficients) at ROM Table that to acceptable the spectrum standard. The validity bit size of the standard data and the amplitude value of square-wave that to store at ROM Table are affected the size of pilot signal on the output spectrum, and the hardware size of modulator. At the designable 24/25 I-NRZI modulator, we simulated using random pattern (F0,F1,F2) that to verification the output data of the spectrum. Moreover, the resultant of the spectrum analysis, at the optimizing value, is 0.065 on the amplitude value of square-wave, and 3bit on the size of bit in order to store the standared data at ROM Table. In order to verify the hardware of designable 24/25 I-NRZI modulator, we perform to modeling of C-language firstly, and coding to Verilog HDL (Cadence Verilog XL) and synthesized using Synopsys (Library "Samsung KG75") tool as a base of spectrum results. In a foundation of this result, we are considered the size of hardware. In this paper, a considerable 24/25 I-NRZI modulator designable less than 10,000 gates as that is improved consturction as regards the path method of pre-coder etc, and able to application digital camcorders as now practical use.