• Smart Media Journal
• /
• v.12 no.11
• /
• pp.154-164
• /
• 2023

The Construction Technology Information System collects, processes, and provides the public with free of charge 16 types of construction technology-related texts or index information, such as construction standards, construction practices, and construction reports, required at construction sites to enhance domestic construction technology. This study judged that user satisfaction could be increased if the budget was allocated first to the most effective construction technology information DB establishment. For each type of construction technology information, the level of satisfaction felt by the population for the quantity provided and the value of use according to the acquisition and utilization of information were investigated. Reliability between independent variables and dependent variables through a multiple regression analysis process to identify how the demographic characteristics of the population affect user satisfaction and the factors that affect the use value of information for each type of construction technology information. and the correlation was analyzed. The correlation between the demographic characteristics of respondents and users' satisfaction with the provided quantity was generally low, but construction experience, age, etc. were found to have an effect on satisfaction with the provided quantity. In particular, among the demographic measurement items of respondents, the more construction experience they had, the higher their satisfaction level with the quantity provided of low-level technical standards, and it was analyzed that older age had an impact on satisfaction with the quantity provided for small and medium-sized business support information.

• Journal of Korean society of Dental Hygiene
• /
• v.11 no.2
• /
• pp.197-211
• /
• 2011

Objectives : OHIP-14 and EQ-5D were used, targeting the residents of farming communities to identify the elements that influence oral cavity's health and quality of life due to health and to identify the importance of oral cavity's health in order to increase health of adults' oral cavity and quality of life via improved health. Methods : This research was conducted from July 17th, 2010 to August 16th, 2010 targeting 600 residents in Goryeong-gun, Gyeongsangbuk-do, aging over 40. The data has been analyzed using Mann-Whitney U test, Kruskal-Wallis test and hierarchical multiple regression through SPSS Win Program 18.0 version. Results : 1. OHIP-14 and EQ-5D based on general characteristics showed lower oral health-related quality of life and health-related quality of life on the following cases: women (p=0.004, p<0.001), older (p<0.001, p<0.001), lower scholastic ability (p<0.001, p<0.001), lower average of average spending money (p<0.001, p<0.001), higher number of chronic disease (p<0.001, p<0.001), less drinking (p=0.012, p=0.008), lower perceived oral health and health status (p<0.001, p<0.001) and non smoking showed only EQ-5D (p<0.001). 2. OHIP-14 and EQ-5D based on oral health behavior showed lower oral health-related quality of life and health-related quality of life on the following cases: no periodic oral check-up (p<0.001, p<0.001), less experience of oral health education (p<0.001, p<0.001), horizontal tooth-brushing method(p<0.001, p<0.001) and lower frequency of tooth-brushing showed only OHIP-14 (p=0.042). OHIP-14 and EQ-5D based on oral health status and subjective oral symptom showed lower oral health-related quality of life and health-related quality of life on following cases: number of existing tooth less than 20 (p<0.001, p<0.001), the number of missing teeth more than 9 (p<0.001, p=0.044), DMFT (Decay, Missing, Filling Teeth) index more than 18 (p<0.001, p<0.001), wears denture (p<0.001, p<0.001), edentulous (p<0.001, p=0.002), have xerostomia (p<0.001, p<0.001) and have chewing discomfort (p<0.001, p<0.001). 3. Factors affecting OHIP-14 were gender, age, perceived oral health status, perceived health status, number of existing teeth, dental status, xerostomia and chewing discomfort, and the of reliability (how well it explains) the final model was 48.7%. EQ-5D showed relevance on gender, age, presence of chronic disease, perceived health status, xerostomia, chewing discomfort and oral health-related quality of life, and the reliability of the final model was 42.9%. Conclusions : In order to improve the quality of life of ruralists, oral health needs to be improved or remained by increasing the rate of possession of the existing teeth and preventing the loss of teeth. In order to do so, improvement of accessibility of dental clinic, change of direction from treatment-centered to prevention-centered health care system, development of oral health education program and various oral health care policies which would vitalize continuous oral health care system are considered to be necessary.

• Journal of Gifted/Talented Education
• /
• v.23 no.1
• /
• pp.109-128
• /
• 2013

The purpose of this study is to verify the validity of KEDI Leadership Inventory (Simplified) for elementary and secondary school student. The existing Leadership Inventory is outdated by excessive or insufficient items. To verify reliability and validity of this KEDI Leadership Inventory (Simplified), we analyze internal consistency of scale for reliability and construct validity, convergent and discriminative validity. criterion-related validity. The internal consistency of the scale is relatively high from .610 to .838 for elementary school student, and from .734 to .936 for secondary school student To verify construct validity, we analyze a confirmatory factor analysis using AMOS whether revealed that the structural equation model including 5 construct validity in KEDI Leadership Inventory(Simplified) showed fit index at a satisfactory level as follows. The major fit indexes are showed as follows; CFI (.954), TLI (.943), RMSEA (.068) in the scale for elementary school student, CFI (.935), TLI (.915), RMSEA (.070) in the scale for secondary school student. Futhermore, to secure criterion-related validity, this KEDI Leadership Inventory(Simplified) showed significant correlations with student's leader position in their classroom for r=.358 (p<.01), and gifted education students are significantly higher .50 than no gifted student. This KEDI Leadership Inventory (Sim'plified) is made up of parsimonious 20 items, so that teachers can be convenient to identify intra-inter personal leadership characteristics of a student and recommend the student for gifted education institution.

• Land and Housing Review
• /
• v.9 no.3
• /
• pp.1-8
• /
• 2018

In Europe and the United States, the use of limit states design has almost been established for pile foundation design. According to the global trend, the Ministry of Land, Transport and Maritime Affairs has established the basic design criteria of the bridge under the limit state design method. However, it is difficult to reflect on the design right now because of lack of research on resistance coefficient of the pile method and ground condition. In this study, to obtain the resistance coefficient of PHC bored pile which is widely used in Korea, the bearing capacity calculated by the LH design standard and the bridge design standard method, the static load test(21 times) and the dynamic load test(EOID 21 times, Restrike 21) The reliability analysis was performed on the results. The analysis of the resistance coefficient of PHC bored pile by loading test was analyzed by adding more than two times data. As a result, the resistance coefficient obtained from the static load test(ultimate bearing capacity) was 0.64 ~ 0.83 according to the design formula and the target reliability index, and the resistance coefficient obtained from the dynamic load test(ultimate bearing capacity) was 0.42~0.55. Respectively. The resistance coefficient obtained from the modified bearing capacity of dynamic load test(EOID's ultimate end bearing capacity + restrike's ultimate skin bearing capacity) was 0.55~0.71, which was reduced to about 14% when compared with the resistance coefficient obtained by the static load test(ultimate bearing capacity). As a result of the addition of the data, the resistivity coefficient was not changed significantly, even if the data were increased more than 2 times by the same value or 0.04 as the previous resistance coefficient. In conclusion, the overall resistance coefficient calculated by the static load test and dynamic load tests in this study is larger than the resistance coefficient of 0.3 suggested by the bridge design standard(2015).

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.139-161
• /
• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• Journal of Intelligence and Information Systems
• /
• v.21 no.2
• /
• pp.113-129
• /
• 2015

Location branding is a very important income making activity, by giving special meanings to a specific location while producing identity and communal value which are based around the understanding of a place's location branding concept methodology. Many other areas, such as marketing, architecture, and city construction, exert an influence creating an impressive brand image. A place brand which shows great recognition to both native people of S. Korea and foreigners creates significant economic effects. There has been research on creating a strategically and detailed place brand image, and the representative research has been carried out by Anholt who surveyed two million people from 50 different countries. However, the investigation, including survey research, required a great deal of effort from the workforce and required significant expense. As a result, there is a need to make more affordable, objective and effective research methods. The purpose of this paper is to find a way to measure the intensity of the image of the brand objective and at a low cost through text mining purposes. The proposed method extracts the keyword and the factors constructing the location brand image from the related web documents. In this way, we can measure the brand image intensity of the specific location. The performance of the proposed methodology was verified through comparison with Anholt's 50 city image consistency index ranking around the world. Four methods are applied to the test. First, RNADOM method artificially ranks the cities included in the experiment. HUMAN method firstly makes a questionnaire and selects 9 volunteers who are well acquainted with brand management and at the same time cities to evaluate. Then they are requested to rank the cities and compared with the Anholt's evaluation results. TM method applies the proposed method to evaluate the cities with all evaluation criteria. TM-LEARN, which is the extended method of TM, selects significant evaluation items from the items in every criterion. Then the method evaluates the cities with all selected evaluation criteria. RMSE is used to as a metric to compare the evaluation results. Experimental results suggested by this paper's methodology are as follows: Firstly, compared to the evaluation method that targets ordinary people, this method appeared to be more accurate. Secondly, compared to the traditional survey method, the time and the cost are much less because in this research we used automated means. Thirdly, this proposed methodology is very timely because it can be evaluated from time to time. Fourthly, compared to Anholt's method which evaluated only for an already specified city, this proposed methodology is applicable to any location. Finally, this proposed methodology has a relatively high objectivity because our research was conducted based on open source data. As a result, our city image evaluation text mining approach has found validity in terms of accuracy, cost-effectiveness, timeliness, scalability, and reliability. The proposed method provides managers with clear guidelines regarding brand management in public and private sectors. As public sectors such as local officers, the proposed method could be used to formulate strategies and enhance the image of their places in an efficient manner. Rather than conducting heavy questionnaires, the local officers could monitor the current place image very shortly a priori, than may make decisions to go over the formal place image test only if the evaluation results from the proposed method are not ordinary no matter what the results indicate opportunity or threat to the place. Moreover, with co-using the morphological analysis, extracting meaningful facets of place brand from text, sentiment analysis and more with the proposed method, marketing strategy planners or civil engineering professionals may obtain deeper and more abundant insights for better place rand images. In the future, a prototype system will be implemented to show the feasibility of the idea proposed in this paper.

• Journal of the HCI Society of Korea
• /
• v.8 no.1
• /
• pp.1-9
• /
• 2013

This is to develop a new way of testing self-esteem by adopting DAP(Draw a Person) test and to make a platform to digitalize it for young people in the adolescent stage. This approach is to get high effectiveness of the self-esteem measurement using DAP test, including some personal inner situations which can be easily missed in the large statistical analysis. The other objective of this study is digitalize to recover limits of DAP test in the subjective rating standard. It is based on the distribution of the figure drawing expressed numerically by the anxiety index of Handler. For these two examinations, we made experiment through 4 stages with second grade middle school 73 students from July 30th to October 31th in 2009 during 4 months. Firstly, we executed 'Self Values Test' for all 73 people, and divided them into two groups; one is high self-esteem group of 36 people, the other is low self-esteem group of 37 people. Secondly, we regrouped them following D (Depression), Pd (Psychopathic Deviate), Sc (Schizophrenia) scales of MMPI; one is high self-esteem group of 7 people, the other is low self-esteem group of 13 people. Thirdly, we conducted DAP test separately for these 20 people. We intended to verify necessity and appropriateness of direction of 'Digitalizing Measurement System' by comparing and analyzing relation between DAP and Self-esteem following evaluation criteria which has similarity in 3 tests, after executing DAP to reflect peculiarity of adolescents sufficiently. We compared and analyzed result abstracted by sampling DAP test of two groups; One is high self-esteem group of 2 people, the other is low self-esteem group of 2 people; to confirm whether we can improve limitation that original psychological testing has by comparing mutual reliance of measurement test. Finally, with DAP test gained from correlations between self-esteem and melancholia following as above-mentioned steps, we discovered possibility of realization to get a concrete and individual criteria of evaluation based on Expert System as a way of enhancing accessibility in quantitative manner. 'Digitalizing Measurement Program' of DAP test suggested in this study promote results' reliability based on existing tests and measurement.

• Journal of Intelligence and Information Systems
• /
• v.16 no.3
• /
• pp.163-179
• /
• 2010

Recentlythe concept of fast fashion is drawing attention as customer needs are diversified and supply lead time is getting shorter in fashion industry. It is emphasized as one of the critical success factors in the fashion industry how quickly and efficiently to satisfy the customer needs as the competition has intensified. Because the fast fashion is inherently susceptible to trend, it is very important for fashion retailers to make quick decisions regarding items to launch, quantity based on demand prediction, and the time to respond. Also the planning decisions must be executed through the business processes of procurement, production, and logistics in real time. In order to adapt to this trend, the fashion industry urgently needs supports from intelligent quick response(QR) system. However, the traditional functions of QR systems have not been able to completely satisfy such demands of the fast fashion industry. This paper proposes an intelligent quick response system for the fast fashion(IQRS-FF). Presented are models for QR process, QR principles and execution, and QR quantity and timing computation. IQRS-FF models support the decision makers by providing useful information with automated and rule-based algorithms. If the predefined conditions of a rule are satisfied, the actions defined in the rule are automatically taken or informed to the decision makers. In IQRS-FF, QRdecisions are made in two stages: pre-season and in-season. In pre-season, firstly master demand prediction is performed based on the macro level analysis such as local and global economy, fashion trends and competitors. The prediction proceeds to the master production and procurement planning. Checking availability and delivery of materials for production, decision makers must make reservations or request procurements. For the outsourcing materials, they must check the availability and capacity of partners. By the master plans, the performance of the QR during the in-season is greatly enhanced and the decision to select the QR items is made fully considering the availability of materials in warehouse as well as partners' capacity. During in-season, the decision makers must find the right time to QR as the actual sales occur in stores. Then they are to decide items to QRbased not only on the qualitative criteria such as opinions from sales persons but also on the quantitative criteria such as sales volume, the recent sales trend, inventory level, the remaining period, the forecast for the remaining period, and competitors' performance. To calculate QR quantity in IQRS-FF, two calculation methods are designed: QR Index based calculation and attribute similarity based calculation using demographic cluster. In the early period of a new season, the attribute similarity based QR amount calculation is better used because there are not enough historical sales data. By analyzing sales trends of the categories or items that have similar attributes, QR quantity can be computed. On the other hand, in case of having enough information to analyze the sales trends or forecasting, the QR Index based calculation method can be used. Having defined the models for decision making for QR, we design KPIs(Key Performance Indicators) to test the reliability of the models in critical decision makings: the difference of sales volumebetween QR items and non-QR items; the accuracy rate of QR the lead-time spent on QR decision-making. To verify the effectiveness and practicality of the proposed models, a case study has been performed for a representative fashion company which recently developed and launched the IQRS-FF. The case study shows that the average sales rateof QR items increased by 15%, the differences in sales rate between QR items and non-QR items increased by 10%, the QR accuracy was 70%, the lead time for QR dramatically decreased from 120 hours to 8 hours.

• Journal of Intelligence and Information Systems
• /
• v.27 no.3
• /
• pp.75-94
• /
• 2021

The low birth rate and shortened military service period are causing concerns about selecting excellent military officers. The Republic of Korea entered a low birth rate society in 1984 and an aged society in 2018 respectively, and is expected to be in a super-aged society in 2025. In addition, the troop-oriented military is changed as a state-of-the-art weapons-oriented military, and the reduction of the military service period was implemented in 2018 to ease the burden of military service for young people and play a role in the society early. Some observe that the application rate for military officers is falling due to a decrease of manpower resources and a preference for shortened mandatory military service over military officers. This requires further consideration of the policy of securing excellent military officers. Most of the related studies have used social scientists' methodologies, but this study applies the methodology of text mining suitable for large-scale documents analysis. This study extracts words of discriminative characteristics from the Republic of Korea Air Force Non-Commissioned Officer Applicant cover letters and analyzes the polarity of pass and fail. It consists of three steps in total. First, the application is divided into general and technical fields, and the words characterized in the cover letter are ordered according to the difference in the frequency ratio of each field. The greater the difference in the proportion of each application field, the field character is defined as 'more discriminative'. Based on this, we extract the top 50 words representing discriminative characteristics in general fields and the top 50 words representing discriminative characteristics in technology fields. Second, the number of appropriate topics in the overall cover letter is calculated through the LDA. It uses perplexity score and coherence score. Based on the appropriate number of topics, we then use LDA to generate topic and probability, and estimate which topic words of discriminative characteristic belong to. Subsequently, the keyword indicators of questions used to set the labeling candidate index, and the most appropriate index indicator is set as the label for the topic when considering the topic-specific word distribution. Third, using L-LDA, which sets the cover letter and label as pass and fail, we generate topics and probabilities for each field of pass and fail labels. Furthermore, we extract only words of discriminative characteristics that give labeled topics among generated topics and probabilities by pass and fail labels. Next, we extract the difference between the probability on the pass label and the probability on the fail label by word of the labeled discriminative characteristic. A positive figure can be seen as having the polarity of pass, and a negative figure can be seen as having the polarity of fail. This study is the first research to reflect the characteristics of cover letters of Republic of Korea Air Force non-commissioned officer applicants, not in the private sector. Moreover, these methodologies can apply text mining techniques for multiple documents, rather survey or interview methods, to reduce analysis time and increase reliability for the entire population. For this reason, the methodology proposed in the study is also applicable to other forms of multiple documents in the field of military personnel. This study shows that L-LDA is more suitable than LDA to extract discriminative characteristics of Republic of Korea Air Force Noncommissioned cover letters. Furthermore, this study proposes a methodology that uses a combination of LDA and L-LDA. Therefore, through the analysis of the results of the acquisition of non-commissioned Republic of Korea Air Force officers, we would like to provide information available for acquisition and promotional policies and propose a methodology available for research in the field of military manpower acquisition.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.4
• /
• pp.251-267
• /
• 2021

Remotely sensed vegetation indices (VIs) are empirically related with gross primary productivity (GPP) in various spatio-temporal scales. The uncertainties in GPP-VI relationship increase with temporal resolution. Uncertainty also exists in the eddy covariance (EC)-based estimation of GPP, arising from the partitioning of the measured net ecosystem CO2 exchange (NEE) into GPP and ecosystem respiration (RE). For two forests and two agricultural sites, we correlated the EC-derived GPP in various time scales with three different near-surface remotely sensed VIs: (1) normalized difference vegetation index (NDVI), (2) enhanced vegetation index (EVI), and (3) near infrared reflectance from vegetation (NIRv) along with NIRvP (i.e., NIRv multiplied by photosynthetically active radiation, PAR). Among the compared VIs, NIRvP showed highest correlation with half-hourly and monthly GPP at all sites. The NIRvP was used to test the reliability of GPP derived by two different NEE partitioning methods: (1) original KoFlux methods (GPP_Ori) and (2) machine-learning based method (GPP_ANN). GPP_ANN showed higher correlation with NIRvP at half-hourly time scale, but there was no difference at daily time scale. The NIRvP-GPP correlation was lower under clear sky conditions due to co-limitation of GPP by other environmental conditions such as air temperature, vapor pressure deficit and soil moisture. However, under cloudy conditions when photosynthesis is mainly limited by radiation, the use of NIRvP was more promising to test the credibility of NEE partitioning methods. Despite the necessity of further analyses, the results suggest that NIRvP can be used as the proxy of GPP at high temporal-scale. However, for the VIs-based GPP estimation with high temporal resolution to be meaningful, complex systems-based analysis methods (related to systems thinking and self-organization that goes beyond the empirical VIs-GPP relationship) should be developed.