• Journal of Service Research and Studies
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• v.14 no.1
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• pp.63-76
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• 2024

Multi-family housing plays a crucial role as a living and experiencing space, and its environment has a direct impact on the well-being and stability of its residents. Therefore, Crime Prevention Design (CPTED) for multi-family housing is of utmost importance. However, crime-related data in China is not disclosed to the public because of its specificity, making it difficult for researchers to conduct further in-depth studies based on accurate crime data. As a result, the establishment and application of CPTED theory in terms of crime prevention is limited and delayed. This study aims to explore three aspects of CPTED in multi-family housing as perceived by home-buying consumers. It investigated consumer perception of the CPTED, the importance of each element and ways to increase awareness of CPTED in multifamily housing in order to effectively improve multifamily crime prevention design principles and further enhance public safety. This study examined the current state and future trends of CPTED in China by analyzing relevant research reports and literature, aiming to gain insights into the crime prevention awareness of Chinese homeowners. In addition, a survey was conducted on Chinese consumers to unravel the importance of CPTED and increase awareness of its various elements in multifamily-family. This study used a Likert scale and SPSS reliability analysis to determine the cognitive status of multi-family CPTED, the importance of each element, and proposed an improvement plan based on the analysis results. As this study was limited by the difficulty of implementation and the lack of validation of its practical effectiveness, it is recommended that future research needs to validate the effectiveness of crime prevention designs and produce more practical results. Furthermore, it is crucial to utilize this study to inform the implementation of security solutions that are tailored to the unique characteristics of each district. Additionally, it is important to offer guidance on how to enhance community safety by increasing residents' awareness of security through education and information dissemination. The author hopes that the representative multi-family CPTED awareness, the importance of each element, and plans for improvement shall be summarized from this study, and provide foundational data for the future development of CPTED based on the Chinese region.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.9-18
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• 2024

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.387-396
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• 2024

Most very high-resolution (VHR) satellite images provide rational polynomial coefficients (RPC) data to facilitate the transformation between ground coordinates and image coordinates. However, initial RPC often contains geometric errors, necessitating correction through matching with ground control points (GCPs). A GCP chip is a small image patch extracted from an orthorectified image together with height information of the center point, which can be directly used for geometric correction. Many studies have focused on area-based matching methods to accurately align GCP chips with VHR satellite images. In cases with seasonal differences or changed areas, edge-based algorithms are often used for matching due to the difficulty of relying solely on pixel values. However, traditional edge extraction algorithms,such as canny edge detectors, require appropriate threshold settings tailored to the spectral characteristics of satellite images. Therefore, this study utilizes deep learning-based edge information that is insensitive to the regional characteristics of satellite images for matching. Specifically,we use a pretrained pixel difference network (PiDiNet) to generate the edge maps for both satellite images and GCP chips. These edge maps are then used as input for normalized cross-correlation (NCC) and relative edge cross-correlation (RECC) to identify the peak points with the highest correlation between the two edge maps. To remove mismatched pairs and thus obtain the bias-compensated RPC, we iteratively apply the data snooping. Finally, we compare the results qualitatively and quantitatively with those obtained from traditional NCC and RECC methods. The PiDiNet network approach achieved high matching accuracy with root mean square error (RMSE) values ranging from 0.3 to 0.9 pixels. However, the PiDiNet-generated edges were thicker compared to those from the canny method, leading to slightly lower registration accuracy in some images. Nevertheless, PiDiNet consistently produced characteristic edge information, allowing for successful matching even in challenging regions. This study demonstrates that improving the robustness of edge-based registration methods can facilitate effective registration across diverse regions.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.384-395
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• 2023

Since transpiration plays a key role in optimal irrigation management, knowledge of the irrigation demand of crops like tomatoes, which are highly susceptible to water stress, is necessary. One way to determine irrigation demand is to measure transpiration, which is affected by environmental factor or growth stage. This study aimed to estimate the transpiration amount of tomatoes and find a suitable model using mathematical and deep learning models using minute-by-minute data. Pearson correlation revealed that observed environmental variables significantly correlate with crop transpiration. Inside air temperature and outside radiation positively correlated with transpiration, while humidity showed a negative correlation. Multiple Linear Regression (MLR), Polynomial Regression model, Artificial Neural Network (ANN), Long short-term Memory (LSTM), and Gated Recurrent Unit (GRU) models were built and compared their accuracies. All models showed potential in estimating transpiration with R² values ranging from 0.770 to 0.948 and RMSE of 0.495 mm/min to 1.038 mm/min in the test dataset. Deep learning models outperformed the mathematical models; the GRU demonstrated the best performance in the test data with 0.948 R² and 0.495 mm/min RMSE. The LSTM and ANN closely followed with R² values of 0.946 and 0.944, respectively, and RMSE of 0.504 m/min and 0.511, respectively. The GRU model exhibited superior performance in short-term forecasts while LSTM for long-term but requires verification using a large dataset. Compared to the FAO56 Penman-Monteith (PM) equation, PM has a lower RMSE of 0.598 mm/min than MLR and Polynomial models degrees 2 and 3 but performed least among all models in capturing variability in transpiration. Therefore, this study recommended GRU and LSTM models for short-term estimation of tomato transpiration in greenhouses.

• Journal of radiological science and technology
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• v.31 no.1
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• pp.17-23
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• 2008

Purpose : Because there is a difference depending on the environment as for an inspection equipment the important part of bone density scan and the precision/accuracy of a tester, the management of quality must be made systematically. The equipment failure caused by overload effect due to the aged equipment and the increase of a patient was made frequently. Thus, the replacement of equipment and additional purchases of new bonedensity equipment caused a compatibility problem in tracking patients. This study wants to know whether the clinical changes of patient's bonedensity can be accurately and precisely reflected when used it compatiblly like the existing equipment after equipment replacement and expansion. Materials and methods : Two equipments of GE Lunar Prodigy Advance(P1 and P2) and the Phantom HOLOGIC Spine Road(HSP) were used to measure equipment precision. Each device scans 20 times so that precision data was acquired from the phantom(Group 1). The precision of a tester was measured by shooting twice the same patient, every 15 members from each of the target equipment in 120 women(average age 48.78, 20-60 years old)(Group 2). In addition, the measurement of the precision of a tester and the cross-calibration data were made by scanning 20 times in each of the equipment using HSP, based on the data obtained from the management of quality using phantom(ASP) every morning (Group 3). The same patient was shot only once in one equipment alternately to make the measurement of the precision of a tester and the cross-calibration data in 120 women(average age 48.78, 20-60 years old)(Group 4). Results : It is steady equipment according to daily Q.C Data with $0.996\;g/cm^2$, change value(%CV) 0.08. The mean${\pm}$SD and a %CV price are ALP in Group 1(P1 : $1.064{\pm}0.002\;g/cm^2$, $%CV=0.190\;g/cm^2$, P2 : $1.061{\pm}0.003\;g/cm^2$, %CV=0.192). The mean${\pm}$SD and a %CV price are P1 : $1.187{\pm}0.002\;g/cm^2$, $%CV=0.164\;g/cm^2$, P2 : $1.198{\pm}0.002\;g/cm^2$, %CV=0.163 in Group 2. The average error${\pm}$2SD and %CV are P1 - (spine: $0.001{\pm}0.03\;g/cm^2$, %CV=0.94, Femur: $0.001{\pm}0.019\;g/cm^2$, %CV=0.96), P2 - (spine: $0.002{\pm}0.018\;g/cm^2$, %CV=0.55, Femur: $0.001{\pm}0.013\;g/cm^2$, %CV=0.48) in Group 3. The average error${\pm}2SD$, %CV, and r value was spine : $0.006{\pm}0.024\;g/cm^2$, %CV=0.86, r=0.995, Femur: $0{\pm}0.014\;g/cm^2$, %CV=0.54, r=0.998 in Group 4. Conclusion: Both LUNAR ASP CV% and HOLOGIC Spine Phantom are included in the normal range of error of ${\pm}2%$ defined in ISCD. BMD measurement keeps a relatively constant value, so showing excellent repeatability. The Phantom has homogeneous characteristics, but it has limitations to reflect the clinical part including variations in patient's body weight or body fat. As a result, it is believed that quality control using Phantom will be useful to check mis-calibration of the equipment used. A value measured a patient two times with one equipment, and that of double-crossed two equipment are all included within 2SD Value in the Bland - Altman Graph compared results of Group 3 with Group 4. The r value of 0.99 or higher in Linear regression analysis(Regression Analysis) indicated high precision and correlation. Therefore, it revealed that two compatible equipment did not affect in tracking the patients. Regular testing equipment and capabilities of a tester, then appropriate calibration will have to be achieved in order to calculate confidential BMD.

• Journal of Sasang Constitutional Medicine
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• v.11 no.2
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• pp.119-150
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• 1999

In spite of recent remarkable recent development in both western and oriental medical sciences, there is still only a shallow understanding of individual differences for various prognoses of incurable diseases and immunopathy diseases. Nevertheless, the care, cure and prevention methods of Sasang Constitutional Medicine are broadly used as an effective treatment of incurable diseases like immunopathy diseases and stress-related diseases and diseases due to aging. In this sense, the establishment of classification norms is urgent and essential for the worldwide application of Sasang Constitutional Medicine(SCM). This study began with the confirmation process of whether Sasang Constitutional types exist in Americans. To accomodate for cultural differences, the distinguishing tool was readjusted so that Sasang Constitutional Types in Americans could be determined. Hence, the selected tool is the new QSCCII+, which is a newly revised English version of the QSCCII. QSCCII was made and standardized by Dept. of SCM in Kyung Hee Medical Center and Dr. Kim7). The evaluation methods of the old version were improved in the new QSCCII+ through necessary statistical manipulation. The original QSCCII was officially authorized by the Korean Society of Sasang Constitutional Medicine as the only computerized version of Sasang diagnostics. This study is the first attempt to design a new diagnostic tool for the classification of Sasang Constitutional types in North Americans with the revision of QSCCII. The subjects of this study were selected from the cooperative people among the students and staffs of the University of Bridgeport and the patients who visited the Clinic in the Health Science Center. This study takes for about 1 year from 1998. 8 to 1999. 8 The conclusions of the study can be summarized as follows: 1. Sasang constitutional types also exist in Americans. It can also naturally be inferred that Sasang Constitutional types exist in all human beings, for there are many different human races in America. 2. There are more So-Yang In's than any other types in American white people. This result confirms the hypothesis that there also exist Sasang Constitutional types in westerners. 3. The result of repetitive tests suggests that the new QSCCII+ is an effective diagnostic tool for westerners when we consider the constant diagnostic results of the QSCCII+. 4. Sasang Constitutional types exit in the sample group regardless of racial difference. 5. The question items that were not often checked by Americans need to be modified into more understandable expressions. 6. The standardization of diagnosis for Americans should be established by use of the QSCCII+ 7. It can be guessed that there are many Tae-yang In's among the 71 persons who could not be clearly classified by the QSCCII+. Due to the scarcity of Tae-yang-In in general, it is important to improve upon the discernability of the QSCC II+. 8. The results of the Sasang Constitutional distribution in North Americans are as follows: The percentage of So-yang In distribution in the sample group is 36.25%(87persons), that of Tae-eum In is 13.75%(33persons), and that of So-eum In is 20.41%(49persons).

• Tuberculosis and Respiratory Diseases
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• v.42 no.3
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• pp.277-294
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• 1995

Background: The prevalence of tuberculosis in Korea decreased remarkably for the past 30 years, while the incidence of disease caused by mycobacteria other than tuberculosis is unknown. Korean Academy of Tuberculosis and Respiratory Diseases performed national survey to estimate the incidence of mycobacterial diseases other than tuberculosis in Korea. We analyzed the clinical data of confirmed cases for the practice of primary care physicians and pulmonary specialists. Methods: The period of study was from January 1981 to October 1994. We collected the data retrospectively by correspondence with physicians in the hospitals that referred the specimens to Korean Institute of Tuberculosis, The Korean National Tuberculosis Association for the detection of mycobacteria other than tuberculosis. In confirmed cases, we obtained the records for clinical, laboratory and radiological findings in detail using protocols. Results: 1) Mycobacterial diseases other than tuberculosis were confirmed that 1 case was in 1981, 2 cases in 1982, 4 cases in 1983, 2 cases in 1984, 5 cases in 1985, 1 case in 1986, 3 cases in 1987, 1 case in 1988, 6 cases in 1989, 9 cases in 1990, 14 cases in 1990, 10 cases in 1992, 4 cases in 1993, and 96 cases in 1994. Cases since 1990 were 133 cases(84.2%) of a total. 2) Fifty seven percent of patients were in the age group of over 60 years. The ratio of male to female patients was 2.6:1. 3) The distribution of hospitals in Korea showed that 61 cases(38.6%) were referred from Double Cross Clinic, 42 cases(26.6%) from health centers, 21 cases(13.3%) from tertiary referral hospitals, 15 cases(9.5%) from secondary referral hospitals, and 10 cases(6.3%) from primary care hospitals. The area distribution in Korea revealed that 98 cases(62%) were in Seoul, 17 cases(10.8%) in Gyeongsangbuk-do, 12 cases(7.6%) in Kyongki-do, 8 cases(5.1%) in Chungchongnam-do, each 5 cases(3.2%) in Gyeongsangnam-do and Chungchongbuk-do, 6 cases(3.8%) in other areas. 4) In the species of isolated mycobacteria other than tuberculosis, M. avium-intracellulare was found in 104 cases(65.2%), M. fortuitum in 20 cases(12.7%), M. chelonae in 15 cases(9.5%), M. gordonae in 7 cases(4.4%), M. terrae in 5 cases(3.2%), M. scrofulaceum in 3 cases(1.9%), M. kansasii and M. szulgai in each 2 cases(1.3%), and M. avium-intracellulare coexisting with M. terrae in 1 case(0.6%). 5) In pre-existing pulmonary diseases, pulmonary tuberculosis was 113 cases(71.5%), bronchiectasis 6 cases(3.8%), chronic bronchitis 10 cases(6.3%), and pulmonary fibrosis 6 cases(3.8%). The timing of diagnosis as having pulmonary tuberculosis was within 1 year in 7 cases(6.2%), 2~5 years ago in 32 cases(28.3%), 6~10 years ago in 29 cases(25.7%), 11~15 years ago in 16 cases(14.2%), 16~20 years ago in 15 cases (13.3%), and 20 years ago in 14 cases(12.4%). Duration of anti-tuberculous treatment was within 3 months in 6 cases(5.3%), 4~6 months in 17 cases(15%), 7~9 months in 16 cases(14.2%), 10~12 months in 11 cases(9.7%), 1~2 years in 21 cases(18.6%), and over 2 years in 8 cases(7.1%). The results of treatment were cure in 44 cases(27.9%) and failure in 25 cases(15.8%). 6) Associated extra-pulmonary diseases were chronic liver disease coexisting with chronic renal failure in 1 case(0.6%), diabetes mellitus in 9 cases(5.7%), cardiovascular diseases in 2 cases(1.3%), long-term therapy with steroid in 2 cases(1.3%) and chronic liver disease, chronic renal failure, colitis and pneumoconiosis in each 1 case(0.6%). 7) The clinical presentations of mycobacterial diseases other than tuberculosis were 86 cases (54.4%) of chronic pulmonary infections, 1 case(0.6%) of cervical or other site lymphadenitis, 3 cases(1.9%) of endobronchial tuberculosis, and 1 case(0.6%) of intestinal tuberculosis. 8) The symptoms of patients were cough(62%), sputum(61.4%), dyspnea(30.4%), hemoptysis or blood-tinged sputum(20.9%), weight loss(13.3%), fever(6.3%), and others(4.4%). 9) Smear negative with culture negative cases were 24 cases(15.2%) in first examination, 27 cases(17.1%) in second one, 22 cases(13.9%) in third one, and 17 cases(10.8%) in fourth one. Smear negative with culture positive cases were 59 cases(37.3%) in first examination, 36 cases (22.8%) in second one, 24 cases(15.2%) in third one, and 23 cases(14.6%) in fourth one. Smear positive with culture negative cases were 1 case(0.6%) in first examination, 4 cases(2.5%) in second one, 1 case (0.6%) in third one, and 2 cases(1.3%) in fourth one. Smear positive with culture positive cases were 48 cases(30.4%) in first examination, 34 cases(21.5%) in second one, 34 cases(21.5%) in third one, and 22 cases(13.9%) in fourth one. 10) The specimens isolated mycobacteria other than tuberculosis were sputum in 143 cases (90.5%), sputum and bronchial washing in 4 cases(2.5%), bronchial washing in 1 case(0.6%). 11) Drug resistance against all species of mycobacteria other than tuberculosis were that INH was 62%, EMB 55.7%, RMP 52.5%, PZA 34.8%, OFX 29.1%, SM 36.7%, KM 27.2%, TUM 24.1%, CS 23.4%, TH 34.2%, and PAS 44.9%. Drug resistance against M. avium-intracellulare were that INH was 62.5%, EMB 59.6%, RMP 51.9%, PZA 29.8%, OFX 33.7%, SM 30.8%, KM 20.2%, TUM 17.3%, CS 14.4%, TH 31.7%, and PAS 38.5%. Drug resistance against M. chelonae were that INH was 66.7%, EMB 66.7%, RMP 66.7%, PZA 40%, OFX 26.7%, SM 66.7%, KM 53.3%, TUM 53.3%, CS 60%, TH 53.3%, and PAS 66.7%. Drug resistance against M. fortuitum were that INH was 65%, EMB 55%, RMP 65%, PZA 50%, OFX 25%, SM 55%, KM 45%, TUM 55%, CS 65%, TH 45%, and PAS 60%. 12) The activities of disease on chest roentgenogram showed that no active disease was 7 cases(4.4%), mild 20 cases(12.7%), moderate 67 cases(42.4%), and severe 47 cases(29.8%). Cavities were found in 43 cases(27.2%) and pleurisy in 18 cases(11.4%). 13) Treatment of mycobacterial diseases other than tuberculosis was done in 129 cases(81.7%). In cases treated with the first line anti-tuberculous drugs, combination chemotherapy including INH and RMP was done in 86 cases(66.7%), INH or RMP in 30 cases(23.3%), and not including INH and RMP in 9 cases(7%). In 65 cases treated with the second line anti-tuberculous drugs, combination chemotherapy including below 2 drugs were in 2 cases(3.1%), 3 drugs in 15 cases(23.1%), 4 drugs in 20 cases(30.8%), 5 drugs in 9 cases(13.8%), and over 6 drugs in 19 cases (29.2%). The results of treatment were improvement in 36 cases(27.9%), no interval changes in 65 cases(50.4%), aggravation in 4 cases(3.1%), and death in 4 cases(3.1%). In improved 36 cases, 34 cases(94.4%) attained negative conversion of mycobacteria other than tuberculosis on cultures. The timing in attaining negative conversion on cultures was within 1 month in 2 cases(1.3%), within 3 months in 11 cases(7%), within 6 months in 14 eases(8.9%), within 1 year in 2 cases(1.3%) and over 1 year in 1 case(0.6%). Conclusion: Clinical, laboratory and radiological findings of mycobacterial diseases other than tuberculosis were summarized. This collected datas will assist in the more detection of mycobacterial diseases other than tuberculosis in Korea in near future.

• Advances in pediatric surgery
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• v.8 no.2
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• pp.143-155
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• 2002

A survey on biliary atresia was made among 26 members of the Korean Association of Pediatric Surgeons. The members were required to complete a questionnaire and a case registration form for each patient during the twentyone-year period of 1980-2000. Three hundred and eighty patients were registered from 18 institutions. The average number of patients per surgeon was one to two every year. The male to female ratio was 1:1.3. The age of patients on diagnosis with biliary atresia was on average $65.4{\pm} 36.2$ days old. The national distribution was 32.8% in Seoul, 25.3% in Gyoungki-Do, 21.6% in Gyoungsang-Do, 9.27% in Choongchung-Do, etc. in order. The most common clinical presentation was jaundice (98.4%) and change of stool color (86.2%) was second. Two hundred eighty (74.7%) of 375 patients were operated by 80 days of age. Three hundred thirty six (9 1.9%) of 366 patients were operated on by the original Kasai procedure, and 305 (84.3%) of 362 patients were observed by bile-drainage postoperatively. The overall postoperative complication rate was 18.5% and the overall postoperative mortality rate was 6.8%. The associated anomalies were observed in 72 cases (22.5%). One hundred ninty five (64.7%) of 302 patients have been alive in follow-up and 49 (25.1%) have survived over 5 years without problem after operation. Ascending cholangitis, varices and ascites affected survival significantly, and the important long-term prognostic factor was the occurrence of complications.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.1-23
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• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.

• 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.