• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.558-558
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• 2015

하천 시설물은 홍수시 혹은 비상시 운영할 수 있는 경보시스템이나 관리지침 등의 마련이 필수적임에도 불구하고, 현재까지 가동보 시설물에 대한 비상시 운영 메뉴얼 및 경보시스템이 구축되지 못한 실정이다. 4대강 살리기 사업이나 하천정비사업과 같은 대표적인 하천관련 사업에서 단순한 하천 이 치수 목적뿐만 아니라 소수력 발전, 친수공간조성 등의 다목적 활용을 위하여 가동보 설치 사업이 다수 수행되었으며, 현재 국내 하천에 약 1,200여개의 가동보가 설치 운영되고 있다. 이와 같이 다목적 활용을 위하여 가동보의 수요가 급증하는데 반해, 각 설치 현장 상황에 적합한 가동보 운영지침이나 비상경보시스템이 구축되지 못한 실정이며, 적절한 지침 없이 관행적인 가동보 방류로 인한 물놀이 안전사고나 인명피해가 속출하고 있는 실정이다. 2012년 11월에는 하천 제수변 공사를 위해 전주천에 설치한 가동보를 임시적으로 방류하였는데, 하류측의 안전을 확인하지 않고 관행적으로 가동보를 방류하였고, 경보시스템의 부재로 인하여 가동보 하류측 징검다리를 건너는 유치원생들이 급류에 휩쓸리는 사고가 발생하였고, 최근 2014년 5월에는 수원시에 위치한 원천저수지 여수로 둑에 설치된 가로 34m 높이 1.6m 크기의 가동보가 공기압축기의 오작동으로 인하여 보 높이가 낮아지면서 약 30분 원천저수지 하류의 원천리천에 갑자기 무리 불어나 산책로가 침수되고 인근에 산책하던 주민들이 휩쓸려 떠내려가는 사고가 발생하였다. 해외에서도 가동보 운영 미숙으로 인하여 인명사고가 발생하는데, 2008년 11월 호주에서는 하류측 상황 점검이나 경고 방송 없이 가동보를 도복시켜 4살 여아가 급류에 사망하는 사고가 발생하였다. 국외의 경우에는, 상류측 홍수 수위나 하류측 역류 수위를 조절하기 위하여 가동보의 높이를 제어하는 시스템을 구비하고 있지만 이러한 시스템 역시 단순한 수위조절 기능으로서 가동보의 방류량을 제어하지 못하는 실정이다. 가동보를 운영하기 위한 조작시스템은 국내의 경우, 조작실의 조작판넬을 이용하여 가동보의 기립/도복 조작이나 원격 조작 기능과 같은 단순기능만을 구비하고 있어 가동보 방류시 하류측의 범람 피해를 야기하고 있다. 본 연구에서는 가동보 방류에 의한 하류측 범람 피해를 최소화하기 위하여 (1) 가동보 도복에 의한 방류량 산정 알고리즘을 개발하고, (2) 방류량에 따른 하류측 수위상승 범위 예측 기법을 개발하고, (3) 가동보 도복 속도를 제어하는 방류량 제어시스템을 개발하고, (4) 가동보 방류에 의한 비상경보시스템을 개발하였다.

• Journal of Korea Port Economic Association
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• v.23 no.2
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• pp.87-107
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• 2007

A rapid growth of interregional trade between China and Korea requires new development and expansion of ports. Currently, there is no rail-ferry system between China and Korea, however, a rapid growth of car-ferry industry shows possibilities. Several candidate cities and regions in East part of China and West part of Korea are selected. We identified times in clearance and station-to-station services as major benefits. We compared three transport modes including candidate cities and regions: container ships, car-ferry and rail-ferry. We used AHP (Analytic Hierarchy Process) as an evaluation method to select most competitive rail-ferry routes between two countries. We also used 7-point Likert scales to find out bottlenecks and factors to introduce rail-ferry services as other questionnaires. As a result, Rail Ferry System(RFS) is a little expensive due to wagon loading efficiency in cargo hold of the ship compared to Car Ferry System or Liner Shipping System. But RFS is recommendable in case of Block Train transport between Korea and EU area by may of TCR and TSR comparing Car Ferry System, because it can reduce total transport cost and connecting procedure at border lines of passing countries.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.245-245
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• 2017

하천 시설물은 홍수시 혹은 비상시 운영할 수 있는 경보시스템이나 관리지침 등의 마련이 필수적임에도 불구하고, 현재까지 가동보 시설물에 대한 비상시 운영 메뉴얼 및 경보시스템이 구축되지 못한 실정이다. 4대강 살리기 사업이나 하천정비사업과 같은 대표적인 하천관련 사업에서 단순한 하천 이 치수 목적뿐만 아니라 소수력 발전, 친수공간조성 등의 다목적 활용을 위하여 가동보 설치 사업이 다수 수행되었으며, 현재 국내 하천에 약 1,200여개의 가동보가 설치 운영되고 있다. 이와 같이 다목적 활용을 위하여 가동보의 수요가 급증하는데 반해, 각 설치 현장 상황에 적합한 가동보 운영지침이나 비상경보시스템이 구축되지 못한 실정이며, 적절한 지침 없이 관행적인 가동보 방류로 인한 물놀이 안전사고나 인명피해가 속출하고 있는 실정이다. 2012년 11월에는 하천 제수변 공사를 위해 전주천에 설치한 가동보를 임시적으로 방류하였는데, 하류측의 안전을 확인하지 않고 관행적으로 가동보를 방류하였고, 경보시스템의 부재로 인하여 가동보 하류측 징검다리를 건너는 유치원생들이 급류에 휩쓸리는 사고가 발생하였고, 최근 2014년 5월에는 수원시에 위치한 원천저수지 여수로 둑에 설치된 가로 34m 높이 1.6m 크기의 가동보가 공기압축기의 오작동으로 인하여 보 높이가 낮아지면서 약 30분 원천저수지 하류의 원천리천에 갑자기 무리 불어나 산책로가 침수되고 인근에 산책하던 주민들이 휩쓸려 떠내려가는 사고가 발생하였다. 해외에서도 가동보 운영 미숙으로 인하여 인명사고가 발생하는데, 2008년 11월 호주에서는 하류측 상황 점검이나 경고 방송 없이 가동보를 도복시켜 4살 여아가 급류에 사망하는 사고가 발생하였다. 국외의 경우에는, 상류측 홍수 수위나 하류측 역류 수위를 조절하기 위하여 가동보의 높이를 제어하는 시스템을 구비하고 있지만 이러한 시스템 역시 단순한 수위조절 기능으로서 가동보의 방류량을 제어하지 못하는 실정이다. 가동보를 운영하기 위한 조작시스템은 국내의 경우, 조작실의 조작판넬을 이용하여 가동보의 기립/도복 조작이나 원격 조작 기능과 같은 단순기능만을 구비하고 있어 가동보 방류시 하류측의 범람 피해를 야기하고 있다. 본 연구에서는 가동보 방류에 의한 하류측 범람 피해를 최소화하기 위하여 (1)가동보 도복에 의한 방류량 산정 알고리즘을 개발하고, (2) 방류량에 따른 하류측 수위상승 범위 예측 기법을 개발하고, (3) 가동보 도복 속도를 제어하는 방류량 제어시스템을 개발하고, (4) 가동보 방류에 의한 비상경보시스템을 개발하였다.

• Korean Journal of Construction Engineering and Management
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• v.22 no.2
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• pp.3-11
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• 2021

Myanmar is an undeveloped country with high development value among Asian countries. Therefore, various countries including the U.S. are considering entering the market. In this respect, demand for real estate development project is forecast to grow on increased inflow of foreigners and Myanmar's economic growth. However, Myanmar is a high-risk country in terms of overseas companies, including national risk. In this study, we conducted an in-depth interview with experts (law, finance, technology, and local experts) after analyzing data on Myanmar to extract risk-causing factors. Through this, 106 risk factors were extracted, and the final risk classification system was established by conducting three-time groupings using the affinity diagramming. And the relative importance of each factor was presented using the analytic hierarchy process (AHP) technique. As a result, the country-related risk, the fund-related risk, and the pre-sale-related risk were highly important. The research results are expected to provide risk management standards to companies entering the Myanmar real estate development type project.

• Journal of the Korean Geotechnical Society
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• v.38 no.4
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• pp.59-70
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• 2022

There is a growing interest in evaluating earthquake damage and determining disaster prevention measures due to the magnitude 5.8 earthquake in Pohang, Korea. Since the liquefaction phenomena occurred extensively in the residential area as a result of the earthquake, there was a demand for research on liquefaction phenomenon evaluation and liquefaction disaster prediction. Liquefaction is defined as a phenomenon where the strength of the ground is completely lost due to a sudden increase in excess pore water pressure caused due to large dynamic stress, such as an earthquake, acting on loose sand particles in a short period of time. The liquefaction potential index, which can identify the occurrence of liquefaction and predict the risk of liquefaction in a targeted area, can be used to create a liquefaction hazard map. However, since liquefaction assessment using existing field testing is predicated on a single borehole liquefaction assessment, there has been a representative issue for the whole targeted area. Spatial interpolation and geographic information systems can help to solve this issue to some extent. Therefore, in order to solve the representative problem of geotechnical information, this research uses the kriging method, one of the geostatistical spatial interpolation techniques, and constructs a geotechnical information database for liquefaction and spatial interpolation. Additionally, the liquefaction hazard map was created for each return period using the constructed geotechnical information database. Cross validation was used to confirm the accuracy of this liquefaction hazard map.

• Information Systems Review
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• v.25 no.1
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• pp.27-46
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• 2023

Research on restaurant recommender systems has been proposed due to the development of the food service industry and the increasing demand for restaurants. Existing restaurant recommendation studies extracted consumer preference information through quantitative information or online review sensitivity analysis, but there is a limitation that it cannot reflect consumer semantic preference information. In addition, there is a lack of recommendation research that reflects the detailed attributes of restaurants. To solve this problem, this study proposed a model that can learn the interaction between consumer preferences and restaurant attributes by applying deep learning techniques. First, the convolutional neural network was applied to online reviews to extract semantic preference information from consumers, and embedded techniques were applied to restaurant information to extract detailed attributes of restaurants. Finally, the interaction between consumer preference and restaurant attributes was learned through the element-wise products to predict the consumer preference rating. Experiments using an online review of Yelp.com to evaluate the performance of the proposed model in this study confirmed that the proposed model in this study showed excellent recommendation performance. By proposing a customized restaurant recommendation system using big data from the restaurant industry, this study expects to provide various academic and practical implications.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.687-692
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• 2024

The energy crisis is emerging as a serious problem around the world. In the case of Korea, there is great interest in energy efficiency research related to industrial complexes, which use more than 53% of total energy and account for more than 45% of greenhouse gas emissions in Korea. One of the studies is a study on saving energy through sharing facilities between factories using the same utility in an industrial complex called a virtual energy network plant and through transactions between energy producing and demand factories. In such energy-saving research, data collection is very important because there are various uses for data, such as analysis and prediction. However, existing systems had several shortcomings in reliably collecting time series data. In this study, we propose an intelligent IIoT platform to improve it. The intelligent IIoT platform includes a preprocessing system to identify abnormal data and process it in a timely manner, classifies abnormal and missing data, and presents interpolation techniques to maintain stable time series data. Additionally, time series data collection is streamlined through database optimization. This paper contributes to increasing data usability in the industrial environment through stable data collection and rapid problem response, and contributes to reducing the burden of data collection and optimizing monitoring load by introducing a variety of chatbot notification systems.

• Journal of Korea Water Resources Association
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• v.40 no.10
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• pp.769-781
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• 2007

Factor analysis has been usually employed in reducing quantity of data and summarizing information on a system or phenomenon. In this analysis methodology, variables are grouped into several factors by consideration of statistic characteristics, and the results are used for dropping variables which have lower weight than others. In this study, factor analysis was applied for extracting primary factors influencing multi-dam system operation in the Han River basin, where there are two multi-purpose dams such as Soyanggang Dam and Chungju Dam, and water has been supplied by integrating two dams in water use season. In order to fulfill factor analysis, first the variables related to two dams operation were gathered and divided into five groups (Soyanggang Dam: inflow, hydropower product, storage management, storage, and operation results of the past; Chungju Dam: inflow, hydropower product, water demand, storage, and operation results of the past). And then, considering statistic properties, in the gathered variables, some variables were chosen and grouped into five factors; hydrological condition, dam operation of the past, dam operation at normal season, water demand, and downstream dam operation. In order to check the appropriateness and applicability of factors, a multiple regression equation was newly constructed using factors as description variables, and those factors were compared with terms of objective function used in operation water resources optimally in a river basin. Reviewing the results through two check processes, it was revealed that the suggested approach provided satisfactory results. And, it was expected for extracted primary factors to be useful for making dam operation schedule considering the future situation and previous results.

• Journal of Korea Technology Innovation Society
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• v.10 no.1
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• pp.73-97
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• 2007

R&D into future technologies should be conducted in conjunction with technological innovation strategies that are linked to corporate survival within a framework of information and knowledge-based competitiveness. As such, future technology strategies should be ensured through open R&D organizations. The development of future technologies should not be conducted simply on the basis of future forecasts, but should take into account customer needs in advance and reflect them in the development of the future technologies or services. This research aims to select as segmentation variables the customers' attitude towards accepting future telecommunication technologies and their value orientation in their everyday life, as these factors wilt have the greatest effect on the demand for future telecommunication services and thus segment the future telecom service market. Likewise, such research seeks to segment the market from the stage of technology R&D activities and employ the results to formulate technology development strategies. Based on the customer attitude towards accepting new technologies, two groups were induced, and a hierarchical customer segmentation model was provided to conduct secondary segmentation of the two groups on the basis of their respective customer value orientation. A survey was conducted in June 2006 on 800 consumers aged 15 to 69, residing in Seoul and five other major South Korean cities, through one-on-one interviews. The samples were divided into two sub-groups according to their level of acceptance of new technology; a sub-group demonstrating a high level of technology acceptance (39.4%) and another sub-group with a comparatively lower level of technology acceptance (60.6%). These two sub-groups were further divided each into 5 smaller sub-groups (10 total smaller sub-groups) through two rounds of segmentation. The ten sub-groups were then analyzed in their detailed characteristics, including general demographic characteristics, usage patterns in existing telecom services such as mobile service, broadband internet and wireless internet and the status of ownership of a computing or information device and the desire or intention to purchase one. Through these steps, we were able to statistically prove that each of these 10 sub-groups responded to telecom services as independent markets. We found that each segmented group responds as an independent individual market. Through correspondence analysis, the target segmentation groups were positioned in such a way as to facilitate the entry of future telecommunication services into the market, as well as their diffusion and transferability.

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