• Journal of Korean Society on Water Environment
• /
• v.40 no.5
• /
• pp.243-257
• /
• 2024

Although lakes are an important part of freshwater, research on biological methods for assessing ecological integrity of Korean lakes is insufficient. Therefore, this study aimed to develop Lakes Benthic Macroinvertebrates Multi-Metric Index (LBMMI) to assess the ecological integrity of lakes in Korea to further understand Korean lake's ecosystem. We used biological data from 388 sampling units of national lake monitoring programs from 2022 to 2023 and water quality data from Water Environment Information System (WEIS). As a result, firstly, reference points and disturbed points were selected through Principal Component Analysis (PCA). Secondly, six core metric elements (Pielou's Evenness index (J), Total number of taxa (To.t), Percent of taxa in insecta (% I.t), Percent of individuals in Oligochaeta and chironomidae(tuble) (% OliCht.i), Percent of taxa in Predator (% Pe.t), and Percent of taxa in Clingers (% CL.t) were selected through discriminant analysis and relationship-test. Lastly, LBMMI was calculated for each sampling point by scoring using core metric elements and five grades were assigned for LBMMI scores using a Beta probability distribution model, with the suitability of LBMMI reviewed by comparing it with TSI_KO. LBMMI developed in this study is expected to appropriately assess ecological integrity of Korean lakes and provide a basis for further research on lake environment conservation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.17 no.2
• /
• pp.65-80
• /
• 2022

Despite the uncertainty and risky factors of startups, the special and critical role of accelerators in carrying out professional nurturing and investment for them is becoming increasingly significant in the startup social-system. However, academic research on investment determinants that have a profound impact on the survival of accelerators is lacking, and there are only a few empirical studies on the classification and importance of factors, and they do not enjoy the benefits of theoretical studies. This study proposes a business model innovation framework based on the business model innovation theory that reflects the nature and properties of startups that are investment targets of accelerators and derives 12 investment decision factors. The framework defines that the target, direction, and performable force of startup innovation are a business model, strategy, and dynamic capability. Besides, the framework analyzes the investment decision factors of the existing accelerators based on the business model innovation framework to verify the suitability and sufficiency of the composition. As a result of the analysis, first, most of the items were faithfully composed from a static point of view of business model innovation, but it was found that the factors related to the core activities to evaluate the activity and customer relationship were insufficient. Second, from the strategic point of view, the necessity of developing factors that can encompass the definition and content of core resources, which are internal strategic factors, was raised. Third, from the dynamic point of view, it was found that many of the investment determinants of accelerators were concentrated on the lower level of dynamic competencies. This can be judged as a result of reflecting the characteristics of a startup that needs to develop a solution with few resources and a small number of team members. In addition, the roles and interrelationships between each factor are not clear, thus it was found as a limiting point for startups to view and evaluate the direction and process in which startups dynamically innovate their business models. This study is considerably differentiated in that it provides a business model innovation framework and offers a theoretical basis for investment determinants by deriving the investment determinants of accelerators based on the framework and design the foundation for subsequent research. The business model innovation framework presented in this study has great implications in that it contributes to the achievement of startups, accelerators, and startup support organizations.

• The Journal of the Korea Contents Association
• /
• v.9 no.11
• /
• pp.432-442
• /
• 2009

This research had a look at what effect of the pursing benefit has on satisfaction, behavioral intention, and attitude of the visitors to the Gwangju Biennale. The survey was conducted for 320 visitors who finished their exhibition viewing schedule starting September 5 until September 19 [15 days]. 300 questionnaires excepting 20 unfaithfully responded copies among those collected from the surveyed were used for the analysis. As for the statistical disposal of the collected data, after going through the process of Data Coding, this research conducted an frequency analysis using SPSS 12.0 for window & statistics package program AMOS 5.0, an exploratory factor analysis to test the reliability and feasibility of the data, and reliability test of each factor; then, this research tested a hypothesis using structural equation model. The research results are as follows: First, as a result of factor analysis of the 15 pursuing benefits, 4 factors were elicited, such as pursuit of an intellectual experience, pursuit of a novel, exotic experience, pursuit of interpersonal, cultural exchange, and pursuit of internal fullness, etc.; as a result of factor analysis of the 10 attitudes, three factors were elicited, such as affective, cognitive, behavioral factors; as a result of factor analysis of 12 types of satisfaction, two factors, such as satisfaction with facilities and convenience matters, etc. were elicited. Second, as a result of the suitability of research model, suitability, its fidelity came out as $x^2=107.508$, d.f.=48, p=.000, Q=2.240, GFI=.942, AGFI=.906, RMR=.024, NFI=.952, TLI=.963, CFI=.973, RMSEA=.064. Third, pursuing benefit was found out to have a positive effect on satisfaction, attitude, and behavioral intention. Fourth, attitude was found out to have a positive significant effect on satisfaction. Fifth, attitude was found out to have a positive effect on behavioral intention. Sixth, satisfaction was found out to have a positive effect on behavioral intention.

• International Journal of Highway Engineering
• /
• v.12 no.4
• /
• pp.93-100
• /
• 2010

Trip generation is the first step in the conventional four-step model and has great effects on overall demand forecasting, so accuracy really matters at this stage. A linear regression model is widely used as a current trip generation model for such plans as urban transportation and SOC facilities, assuming that the relationship between each socio-economic index and trip generation stays linear. But when rapid urban development or an urban planning structure has changed, socio-economic index data for trip estimation may be lacking to bring many errors in estimated trip. Hence, instead of assuming that a socio-economic index widely used for a general purpose, this study aims to develop a new trip generation model by type based on the market separation for the variables to reflect the characteristics of various zones. The study considered the various characteristics (land use, socio-economic) of zones to enhance the forecasting accuracy of a trip generation model, the first-step in forecasting transportation demands. For a market separation methodology to improve forecasting accuracy, data mining (CART) on the basis of trip generation was used along with a regression analysis. Findings of the study indicated as follows : First, the analysis of zone characteristics using the CART analysis showed that trip production was under the influence of socio-economic factors (men-women relative proportion, age group (22 to 29)), while trip attraction was affected by land use factors (the relative proportion of business facilities) and the socio-economic factor (the relative proportion of third industry workers). Second, model development by type showed as a result that trip generation coefficients revealed 0.977 to 0.987 (trip/person) for "production" 0.692 to 3.256 (trip/person) for "attraction", which brought the necessity for type classifications. Third, a measured verification was conducted, where "production" and "attraction" showed a higher suitability than the existing model. The trip generation model by type developed in this study, therefore, turned out to be superior to the existing one.

• Journal of the Society of Disaster Information
• /
• v.17 no.3
• /
• pp.465-486
• /
• 2021

Purpose: Since most disaster information systems are centered on non-disabled people, the reality is that there is a lack of disaster information delivery systems for the vulnerable, such as the disabled, the elderly, and children, who are relatively vulnerable to disasters. The purpose of the service is to improve the safety of the disabled and the elderly by eliminating blind spots of informatization and establishing customized disaster information services to respond to disasters through IoT-based integrated control technology. Method: The model at the core of this study is the disaster alert propagation model and evacuation support model, and it shall be developed by reflecting the behavioral characteristics of the disabled and the elderly in the event of a disaster. The disaster alert propagation model spreads disaster situations collected using IoT technology, and the evacuation support model uses geomagnetic field-based measuring technology to identify the user's indoor location and help the disabled and the elderly evacuate safely. Results: Demonstration model demonstration resulted in an efficient qualitative evaluation of indoor location accuracy, such as the suitability of evacuation route guidance and satisfaction of services from the user's perspective. Conclusion: Disaster information and evacuation support services were established for the safety vulnerable groups of mobile app for model verification. The disaster situation was demonstrated through experts in the related fields and the disabled by limiting it to the fire situation. It was evaluated as "satisfaction" in the adequacy of disaster information delivery and evacuation support, and its functional satisfaction and user UI were evaluated as "normal" due to the nature of the pilot model. Through this, the disaster information and evacuation support services presented in this study were evaluated to support the safety vulnerable groups to a faster disaster evacuation without missing the golden time of disaster evacuation.

• Journal of Intelligence and Information Systems
• /
• v.21 no.1
• /
• pp.161-177
• /
• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.

• Journal of Korean Academy of Nursing
• /
• v.25 no.4
• /
• pp.617-632
• /
• 1995

Nowadays, most big hospitals have a computer system to manage their administration. For maxi mum effectiveness in managing the computer system, an analysis of the variables affecting its implementation is necessary from the beginning. This study was done to analyze the variables influencing the operation of a hospital information system (HIS). The theoretical base for this study considered the combined effects of user expectations of computerization, and computer-anxiety. The relationship between variables in the theoretical base were analyzed and the individual characteristics influencing each variable were also analyzed. This study was done in two steps. First, 344 nurses were given an initial questionnaire developed to evaluate the reliability of the items. Based on the results, a second revised questionnaire was administered to 88 nurses who had been working in the areas where HIS was applied. The results of the first and second steps of the study are as follows 1. The initial study was done with nurses who were trained on the computer system briefly before HIS was implemented. The individual characteristics influencing computer anxiety and expectation regarding computer system usage in that initial study included, length of career, type of degree or certification, previous experiences with a computer, training on a computer, desire for computer training, and level of acceptance of a computerized work environment. But in the second study with nurses working in areas of the hospital where HIS was introduced, the work site was the only influencing characteristics. There-fore, in applying a computer system, overcoming work-environment barriers will be more import-ant than any individual characteristics. 2. The computer anxiety of the nurses in both groups, before and after the computer system ap-plication, was below the average level but the expectation of the effects of computerization was above average. The nurses using the computer program showed an above average level of satis-faction with the computer system itself, and with its effect on their efficiency. Therefore, the ability of nurses operating HIS will be positively. predictive. 3. For the variables included in the theoretical framework of the study, all of the correlational coefficients were statistically significant in the analysis of variation correlation. Therefore, the theoretical base of the study, "expectation in con junction with computer anxiety" can be considered an model which can be evaluated. Accord-ing to our analysis, the higher the level of nurses' motivation to use the computer system and the lower the anxiety about computer usage, the higher the possibility of computer system acceptance by nurses. The results of this study showed that in applying a computer system in the hospital, the main characteristic influencing acceptance was where the individual worked rather than personal characteristics such as length of career, type of degree or certification, and previous experiences with a computer. Therefore, it is suggested that the first step in uncovering and eliminating hindrance factors in ap-plication of a computer system should be an analysis of working conditions in relation to the functional content of the computer system. The suitability of the theoretical model based on the hypothesis ap-plied in this study should be further tested.

• Journal of Digital Convergence
• /
• v.16 no.5
• /
• pp.85-95
• /
• 2018

With the scientists and the technicians of the small- and medium-sized enterprises who have been subscribing to the pension service as the subjects, this research took a look at the influences on the intention to continuously subscribe to the pension service and, finally, took a look at the differences between the subscribers of the safety type and the profit type which have been provided by the pension service. Through the questionnaire survey, which collected the data, an actual proof analysis was carried out. Through the statistical program, the degree of the reliability analysis and the feasibility analysis were carried out. And the degree of the suitability of the structural equation model was tested. And, finally, through the research model, the hypothesis was verified and the differences between the groups were analyzed. It appeared that the factors of the reliability and the responsiveness of the service quality factor have the positive influence on the perceived value, which is a parameter. And it appeared that the materiality and the perceptual openness factors cannot have any influence. And the stability and the usefulness, which are the attributed factors of the pension service, had the positive influences on the perceived value. Finally, it appeared that the perceived value of the pension service has a positive influence on the intention to subscribe continuously. Through the results of this research, it can contribute to the invigoration of the pension service. And it is thought that a pension service which is better than the preexistent pension service can be provided.

• Journal of Korean Society of Forest Science
• /
• v.105 no.3
• /
• pp.330-335
• /
• 2016

This study was conducted to derive merchantable volume ratio for 5 major species such as Pinus Densiflora (Central Region). The data used for this study was from at least more than 1,300 trees of research data throughout the country. the study applied two estimation equations, which were the estimation equation for wood volume ratio representing total wood volume to total tree stem volume and the estimation equation for merchantability representing ratio of merchantable volume to total wood volume. The merchantable volume ratio was derived by multiplying those two estimation equations. In order to gain wood volume ratio(W) from DBH, $W=\frac{a_1}{1+a_2/D}+\frac{b_1}{1+b_2/D}$ model was used. Fitness index of it was more than 99% by species, and other test statistics also indicated the suitability of this equation enough. Merchantability (M) for wood volume applied $M=e^{a_1\(\frac{d}{D}\)^{a_2}}-(b_0+b_1D+b_2D^2+b_3D^3)$ model and fitness index was more than 96% by species. Merchantable volume ratio was assessed using those two estimation equations by each 5 species, and constructed a merchantable volume ratio table. In result, merchuntable volume ratio was little difference between stand types, but there was slightly different with the existing standard such as conifers of 85% and non-conifers of 70%.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.5
• /
• pp.1797-1807
• /
• 2013

Dams always have the possibility of failure due to unexpected natural phenomena. In particular, dam failure can cause huge damage including damage for humans and properties when dam downstream regions are densely populated or have important national facilities. Although many studies have been conducted on the analysis of flood waves about single dam failure thus far, studies on the analysis of flood waves about the sequential failure of dams are lacking. Therefore, the purpose of this study was to calculate the peak discharge of sequential failure of dams through flood wave analysis of sequential failure of dams and this analysis techniques to predict flood wave propagation situation in downstream regions. To this end, failure flood wave analysis were conducted for Lawn Lake Dam which is a case of sequential failure of dams among actual failure cases using DAMBRK to test the suitability of the dam failure flood wave analysis model. Based on the results, flood wave analysis of sequential failure of dams were conducted for A dam in Korea assuming a virtual extreme flood to predict flood wave propagation situations and 2-dimensional flood wave analysis were conducted for major flooding points. Then, the 1, 2-dimensional flood wave analysis were compared and analyzed. The results showed goodness-of-fit values exceeding 90% and thus the accuracy of the 1-dimensional sequential failure of dams simulation could be identified. The results of this study are considered to be able to contribute to the provision of basic data for the establishment of disaster prevention measures for rivers related to sequential failure of dams.