• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.1-22
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• 2017

Analysis of future business or investment opportunities, such as business feasibility analysis and company or technology valuation, necessitate objective estimation on the relevant market and expected sales. While there are various ways to classify the estimation methods of these new sales or market size, they can be broadly divided into top-down and bottom-up approaches by benchmark references. Both methods, however, require a lot of resources and time. Therefore, we propose a data-based intelligent demand forecasting system to support evaluation of new business. This study focuses on analogical forecasting, one of the traditional quantitative forecasting methods, to develop sales forecasting intelligence systems for new businesses. Instead of simply estimating sales for a few years, we hereby propose a method of estimating the sales of new businesses by using the initial sales and the sales growth rate of similar companies. To demonstrate the appropriateness of this method, it is examined whether the sales performance of recently established companies in the same industry category in Korea can be utilized as a reference variable for the analogical forecasting. In this study, we examined whether the phenomenon of "mean reversion" was observed in the sales of start-up companies in order to identify errors in estimating sales of new businesses based on industry sales growth rate and whether the differences in business environment resulting from the different timing of business launch affects growth rate. We also conducted analyses of variance (ANOVA) and latent growth model (LGM) to identify differences in sales growth rates by industry category. Based on the results, we proposed industry-specific range and linear forecasting models. This study analyzed the sales of only 150,000 start-up companies in Korea in the last 10 years, and identified that the average growth rate of start-ups in Korea is higher than the industry average in the first few years, but it shortly shows the phenomenon of mean-reversion. In addition, although the start-up founding juncture affects the sales growth rate, it is not high significantly and the sales growth rate can be different according to the industry classification. Utilizing both this phenomenon and the performance of start-up companies in relevant industries, we have proposed two models of new business sales based on the sales growth rate. The method proposed in this study makes it possible to objectively and quickly estimate the sales of new business by industry, and it is expected to provide reference information to judge whether sales estimated by other methods (top-down/bottom-up approach) pass the bounds from ordinary cases in relevant industry. In particular, the results of this study can be practically used as useful reference information for business feasibility analysis or technical valuation for entering new business. When using the existing top-down method, it can be used to set the range of market size or market share. As well, when using the bottom-up method, the estimation period may be set in accordance of the mean reverting period information for the growth rate. The two models proposed in this study will enable rapid and objective sales estimation of new businesses, and are expected to improve the efficiency of business feasibility analysis and technology valuation process by developing intelligent information system. In academic perspectives, it is a very important discovery that the phenomenon of 'mean reversion' is found among start-up companies out of general small-and-medium enterprises (SMEs) as well as stable companies such as listed companies. In particular, there exists the significance of this study in that over the large-scale data the mean reverting phenomenon of the start-up firms' sales growth rate is different from that of the listed companies, and that there is a difference in each industry. If a linear model, which is useful for estimating the sales of a specific company, is highly likely to be utilized in practical aspects, it can be explained that the range model, which can be used for the estimation method of the sales of the unspecified firms, is highly likely to be used in political aspects. It implies that when analyzing the business activities and performance of a specific industry group or enterprise group there is political usability in that the range model enables to provide references and compare them by data based start-up sales forecasting system.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

• The Korean Journal of Emergency Medical Services
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• v.15 no.3
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• pp.31-44
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• 2011

Purpose : The purpose of emergency medical services(EMS) is to save human lives and assure the completeness of the body in emergency situations. Those who have been qualified on medical practice to perform such treatment as there is the risk of human life and possibility of major physical and mental injuries that could result from the urgency of time and invasiveness inflicted upon the body. In the emergency medical activities, 119 emergency medical technicians mainly perform the task but they are not able to perform such task independently and they are mandatory to receive medical direction. The purpose of this study is to examine the recognition and request for medical direction by 119 emergency medical technicians in order to provide basic information on the development of medical direction program suitable to the characteristics of EMS as well as for the studies on EMS for the sake of efficient operation of pre-hospital EMS. Method : Questionnaire via e-mail was conducted during July 1-31, 2010 for 675 participants who are emergency medical technicians, nurses and other emergency crews in Gyeongbuk. The effective 171 responses were used for the final analysis. In regards to the emergency medical technicians' scope of responsibilities defined in Attached Form 14, Enforcement regulations of EMS, t-test analysis was conducted by using the means and standard deviation of the level of request for medical direction on the scope of responsibilities of Level 1 & Level 2 emergency medical technicians as the scale of medical direction request. The general characteristics, experience result, the reason for necessity, emergency medical technicians & medical director request level, medical direction method, the place of work of the medical director, feedback content and improvement plan request level were analyzed through frequency and percentage. The level of experience in medical direction and necessity were analyzed through ${\chi}^2$ test. Results : In regards to the medical direction experience per qualification, the experience was the highest with 53.3% for Level 1 emergency medical technicians and 80.3% responded that experience was helpful. As for the recognition on the necessity of medical direction, 71.3% responded as "necessary" and it turned out to be the highest of 76.9% in nurses. As for the reason for responding "necessary", the reason for reducing the risk and side-effects from EMS for patients was the largest(75.4%), and the reason of EMS delay due to the request of medical direction was the highest(71.4%) for the reason for responding "not necessary". In regards to the request level of the task scope of emergency medical technicians, injection of certain amount of solution during a state of shock was the highest($3.10{\pm}.96$) for Level 1 emergency rescuers, and the endotracheal intubation was the highest($3.12{\pm}1.03$) for nurses, and the sublingual administration of nitroglycerine(NTG) during chest pain was the highest($2.62{\pm}1.02$) for Level 2 emergency medical technicians, and regulation of heartbeat using AED was the highest($2.76{\pm}.99$) for other emergency crews. For the revitalization of medical direction, the improvement in the capability of EMS(78.9%) was requested from emergency crew, and the ability to evaluate the medical state of patient was the highest(80.1%) in the level of request for medical director. The prehospital and direct medical direction was the highest(60.8%) for medical direction method, and the emergency medical facility was the highest(52.0%) for the placement of medical director, and the evaluation of appropriateness of EMS was the highest(66.1%) for the feedback content, and the reinforcement of emergency crew(emergency medical technicians) personnel was the highest(69.0%) for the improvement plan. Conclusion : The medical direction is an important policy in the prehospital EMS activity because 119 emergency medical technicians agreed the necessity of medical direction and over 80% of those who experienced medical direction said it was helpful. In addition, the simulation training program using algorithm and case study through feedback are necessary in order to enhance the technical capability of ambulance teams on the item of professional EMS with high level of request in the task scope of emergency medical technicians, and recognition of medical direction is the essence of the EMS field. In regards to revitalizing medical direction, the improvement of the task performance capability of 119 emergency medical technicians and medical directors, reinforcement of emergency medical activity personnel, assurance of trust between emergency medical technicians and the emergency physician, and search for professional operation plan of medical direction center are needed to expand the direct medical direction method for possible treatment beforehand through the participation by medical director even at the step in which emergency situation report is received.

• Journal of radiological science and technology
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• v.29 no.3
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• pp.167-175
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• 2006

With the recent prevalence of helical CT and multi-slice CT, which deliver higher radiation dose than conventional CT due to overbeaming effect in X-ray exposure and interpolation technique in image reconstruction. Although multi-detector and helical CT scanner provide a variety of opportunities for patient dose reduction, the potential risk for high radiation levels in CT examination can't be overemphasized in spite of acquiring more diagnostic information. So much more concerns is necessary about dose characteristics of CT scanner, especially dose efficient design as well as dose modulation software, because dose efficiency built into the scanner's design is probably the most important aspect of successful low dose clinical performance. This study was conducted to evaluate z-axis geometric dose efficiency in single detector CT and each level multi-detector CT, as well as to compare z-axis dose efficiency with change of technical scan parameters such as focal spot size of tube, beam collimation, detector combination, scan mode, pitch size, slice width and interval. The results obtained were as follows ; 1. SDCT was most highest and 4 MDCT was most lowest in z-axis geometric dose efficiency among SDCT, 4, 8, 16, 64 slice MDCT made by GE manufacture. 2. Small focal spot was 0.67-13.62% higher than large focal spot in z-axis geometric dose efficiency at MDCT. 3. Large beam collimation was 3.13-51.52% higher than small beam collimation in z-axis geometric dose efficiency at MDCT. 4. Z-axis geometric dose efficiency was same at 4 slice MDCT in all condition and 8 slice MDCT of large beam collimation with change of detector combination, but was changed irregularly at 8 slice MDCT of small beam collimation and 16 slice MDCT in all condition with change of detector combination. 5. There was no significant difference for z-axis geometric dose efficiency between conventional scan and helical scan, and with change of pitch factor, as well as change of slice width or interval for image reconstruction. As a conclusion, for reduction of patient radiation dose delivered from CT examination we are particularly concerned with dose efficiency of equipment and have to select proper scanning parameters which increase z-axis geometric dose efficiency within the range of preserving optimum clinical information in MDCT examination.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.12
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• pp.7367-7369
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• 2013

Background: Inoperable and metastatic hepatocellular carcinoma (HCC) is associated with a poor prognosis and low chemotherapeutic efficiency. Sorafenib is an oral multi-kinase inhibitor exerting its effects via the RAF/MEK/ERK pathway, vascular endothelial growth factor receptor (VEGFR) and platelet derived growth factor receptor beta (PDGFR-${\beta}$) tyrosine kinases. Randomized studies have shown a significant contribution of sorafenib to life expectancy and quality of life of cancer patients. The aim of the present study is to evaluate the efficacy and side effects of sorafenib therapy in Turkey. Materials and Methods: Data for 103 patients (82 males, 21 females) receiving sorafenib therapy in 13 centers from February 2008 to December 2012 were evaluated. Median age was 61 years and median ECOG performance status was 1 (range: 0-2). 60 patients (58%) had hepatitis B, 15 patients (15%) had hepatitis C infection and 12 patients (12%) had a history of alcohol consumption. All of the patients had Child scores meeting the utilization permit of the drug in our country (Child A). Results: A total of 571 cycles of sorafenib therapy were administered with a median of four per patient. Among the evaluable cases, there was partial response in 15 (15%), stable disease in 52 (50%), and progressive disease in 36 (35%). Median progression-free survival was 18 weeks and median overall survival was 48 weeks. The dose was reduced only in 6 patients and discontinued in 2 patients due to grade 3-4 toxicity, 18 patients (17%) suffering hand-foot syndrome, 7 (7%) diarrhea, and 2 (2%) vomiting. Conclusions: This retrospective study demonstrated better efficacy of sorafenib therapy in patients with advanced HCC compared to the literature while progression-free survival and overall survival findings were comparable. The side effect rates indicate that the drug was tolerated well. In conclusion, among the available treatment options, sorafenib is an efficient and tolerable agent in patients with inoperable or metastatic HCC.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• Journal of Science and Technology Studies
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• v.18 no.2
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• pp.135-179
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• 2018

How do robots interact with the elderly? In this paper, we analyze the contexts of interaction between robots and the elderly and the role of mediators in initiating, facilitating, and maintaining the interaction. We do not attempt to evaluate the robot's performance or measure the impact of robots on the elderly. Instead, we focus on the circumstances and contexts within which a robot is situated as it interacts with the elderly. Our premise is that the success of human-robot interaction does not depend solely on the robot's technical capability, but also on the pre-arranged settings and local contingencies at the site of interaction. We select three television shows that feature robots for the elderly and one "dementia-prevention" robot in a regional healthcare center as our sites for observing robot-elderly interaction: "Grandma's Robot"(tvN), "Co-existence Experiment''(JTBC), "Future Diary"(MBC), and the Silbot class in Suwon. By analyzing verbal and non-verbal interactions between the elderly and the robots in these programs, we point out that in most cases the robots and the elderly do not meet one-to-one; the interaction is usually mediated by an actor who is not an old person. These mediators are not temporary or secondary components in the robot-elderly interaction; they play a key role in the relationship by arranging the first meeting, triggering initial interactions, and carefully observing unfolding interactions. At critical moments, the mediators prevent the interaction from falling apart by intervening verbally or physically. Based on our observation of the robot-elderly interaction, we argue that we can better understand and evaluate the human-robot interaction in general by paying attention to the existence and role of the mediators. We suggest that researchers in human-robot interaction should expand their analytical focus from one-to-one interactions between humans and robots to human-robot-human interactions in diverse real-world situations.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.6
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• pp.96-106
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• 2013

The aim of this study was to reveal the advantages and disadvantages of Terelj Mongolian National Park based on the impressions of foreign and domestic travelers, and subsequently suggest supporting ideas to make this tourist attraction more enjoyable for travelers. A statistical program(SPSS 20.0) and an IPA matrix method were used to reveal the impressions of travelers and the results showed the following ideas. First, we made the technical analyses to demonstrate the characteristics of the current natural scenery which travelers want to see and the results indicated that both Korean and Mongolian travelers overall were not satisfied and the Park was not as they had imagined. The second part of the research highlighted the differences between the impressions held by Mongolian and Korean travelers, which showed dissimilarities in cultural resources, food, variety of events, cultural functions and parking, all of which were shown as important criteria in sightseeing. The variations were found in scenes of nature, variety of programs, and food, areas which revealed and were very important in the overall satisfaction of travelers. Third, the IPA method was used for analyze the advantages and disadvantages of Terelj National Park. The Mongolian travelers nominated the width of the road, cleanliness, variety of events and parking are the most essential things to feel satisfied, but Koreans selected safety of travel, accommodation, the width of the road and cleanliness. Finally, we analyzed the feelings of the travelers at the end of their trip. The Mongolian travelers preferred the area resource and environment convenience to feel satisfaction. For Korean travelers, the area resource is the most important when choosing travelling sights. Based on these results, if we take responsibility to protect the beauty of nature, and create a sightseeing place using natural sources, while also making more comfortable accommodations and improving the services, it can be a more unique place than others and lead to greater overall satisfaction for travelers.

• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.163-177
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• 2020

Purpose: While it is very important to maintain facilities recently, the introduction and its application of high technology in the facility maintenance industry has increased. It is necessary for high technology to secure reliability through the verification and certification system of diagnostic equipment to have an effective impact in the field, but there is difference between the industry's perspective and realistic level of technology apart from social demand for the system of the system. This paper dealt with the introduction of a verification and certification system for rational facility diagnostic equipment with the opinion survey on managers about the current situation. Method: Survey is carried out targeting managers in the maintenance and construction regarding the necessity and urgency of introducing a verification and certification system to promote the introduction and its application of high technology of diagnostic equipment and facility inspection. Also, the introduction to a verification and certification system was reviewed for advanced facility diagnostic equipment through foreign research about similar systems and comparative analysis of similar systems related to the certification of 21 domestic equipment. Result: It showed that, regarding the application of high technology, it is necessary for most managers to introduce high technology such as drones, robots, etc., in the maintenance industry, and when high technology is introduced, it will have a considerable effect in the field. On the other hand, the current technology level in Korea is relatively low, so it turned out to take a certain amount of time for the application of technology. Also, it was found that the management of reliable facility diagnostic equipment will be possible through the introduction of the verification and certification system for facility diagnosis equipment. Meanwhile, the survey is conducted on similar systems about foreign and domestic diagnosis and measuring equipment, etc., but there is no system to verify and certify equipment applied with high technology directly to facility diagnosis maintenance. However, because Japan has a system of verifying the performance of diagnostic equipment and South Korea has 21 similar inspection and diagnostic equipment certification systems among 186 certification systems, it is considered to be possible to design systems which utilize them. Conclusion: According to the managers' opinion, it seems that the introduction of the system supporting the application of 4th industrial technology for the equipment and the use of the equipment with high reliability has sufficient validity. However, because our high technology level is undervalued compared to the urgency, the system for checking high technology facilities and certifying diagnostic equipment should be to be implemented in form of escalation considering technical use and verification level. Apart from the introduction of the verification and certification system, it is necessary for special investment, support and efforts to promote advanced facility diagnostic equipment.