• 상하수도학회지
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• 제35권1호
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• pp.53-61
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• 2021

The quantified analysis of damages to wastewater treatment plants by natural disasters is essential to maintain the stability of wastewater treatment systems. However, studies on the quantified analysis of natural disaster effects on wastewater treatment systems are very rare. In this study, a total disaster index (DI) was developed to quantify the various damages to wastewater treatment systems from natural disasters using two statistical methods (i.e., AHP: analytic hierarchy process and PCA: principal component analysis). Typhoons, heavy rain, and earthquakes are considered as three major natural disasters for the development of the DI. A total of 15 input variables from public open-source data (e.g., statistical yearbook of wastewater treatment system, meteorological data and financial status in local governments) were used for the development of a DI for 199 wastewater treatment plants in Korea. The total DI was calculated from the weighted sum of the disaster indices of the three natural disasters (i.e., TI for typhoon, RI for heavy rain, and EI for earthquake). The three disaster indices of each natural disaster were determined from four components, such as possibility of occurrence and expected damages. The relative weights of the four components to calculate the disaster indices (TI, RI and EI) for each of the three natural disasters were also determined from AHP. PCA was used to determine the relative weights of the input variables to calculate the four components. The relative weights of TI, RI and EI to calculate total DI were determined as 0.547, 0.306, and 0.147 respectively.

• Journal of Korea Trade
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• 제25권4호
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• pp.17-36
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• 2021

Purpose - This study provides useful information to stakeholders by forecasting the tramp shipping market, which is a completely competitive market and has a huge fluctuation in freight rates due to low barriers to entry. Moreover, this study provides the most effective parameters for Baltic Dry Index (BDI) prediction and an optimal model by analyzing and comparing deep learning models such as the artificial neural network (ANN), recurrent neural network (RNN), and long short-term memory (LSTM). Design/methodology - This study uses various data models based on big data. The deep learning models considered are specialized for time series models. This study includes three perspectives to verify useful models in time series data by comparing prediction accuracy according to the selection of external variables and comparison between models. Findings - The BDI research reflecting the latest trends since 2015, using weekly data from 1995 to 2019 (25 years), is employed in this study. Additionally, we tried finding the best combination of BDI forecasts through the input of external factors such as supply, demand, raw materials, and economic aspects. Moreover, the combination of various unpredictable external variables and the fundamentals of supply and demand have sought to increase BDI prediction accuracy. Originality/value - Unlike previous studies, BDI forecasts reflect the latest stabilizing trends since 2015. Additionally, we look at the variation of the model's predictive accuracy according to the input of statistically validated variables. Moreover, we want to find the optimal model that minimizes the error value according to the parameter adjustment in the ANN model. Thus, this study helps future shipping stakeholders make decisions through BDI forecasts.

• 한국물환경학회지
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• 제26권5호
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• pp.796-801
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• 2010

Water quality index (WQI) can be a great tool that allows experts to translate large amount of complex water quality data into a format more easily understood by the public and policy makers. Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) can be calculated with the three factors (Scope: $F_1$, Frequency: $F_2$, Amplitude: $F_3$). After all, the WQI for a specific site is produced as a number between 0 to 100; the scale is also divided into five categories, i.e., Excellent, Good, Fair, Marginal and Poor. The WQI was found to be highly related to Chl-a, pH, temperature among the collected items. When the more input parameters were used, the range of variation generally became smaller. $F_3$ among the factors of WQI was influenced by algae. It showed a similar variation tendency between WQI and algal bloom in 2008.

• 수산경영론집
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• 제43권2호
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• pp.95-106
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• 2012

This study analyzed the changes in productivity growth of 291 regional fisheries cooperatives area from 2001 to 2010 selected as target. The productivity growth analysis of operating offices calculates Global-Malmquist productivity index. Input variables are number of the persons and the nettable area, output variables are deposit, loans and earnings. To improve the homogeneity of industry, the operating conditions were considered. Global Malmquist index of Operating offices was reduced between 2001~2010. The cause of increase and decrease of productivity are divided by efficiency change(EC) and best-practice change(BPC). Operating offices with increased productivity existed between 2001~2002 and between 2002~2003 and between 2006~2007. There were operating offices with increased productivity by EC. Global Malmquist index of Operating offices with locations was highest relatively in metropolitan. Operating offices with increased productivity existed between 2003~2004 and between 2007~2008 and between 2008~2009 in all locations. There were operating offices with decreased productivity by BPC.

• 산업경영시스템학회지
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• 제43권1호
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• pp.16-25
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• 2020

Vegetation segmentation in a field color image is a process of distinguishing vegetation objects of interests like crops and weeds from a background of soil and/or other residues. The performance of the process is crucial in automatic precision agriculture which includes weed control and crop status monitoring. To facilitate the segmentation, color indices have predominantly been used to transform the color image into its gray-scale image. A thresholding technique like the Otsu method is then applied to distinguish vegetation parts from the background. An obvious demerit of the thresholding based segmentation will be that classification of each pixel into vegetation or background is carried out solely by using the color feature of the pixel itself without taking into account color features of its neighboring pixels. This paper presents a new pixel-based segmentation method which employs a multi-layer perceptron neural network to classify the gray-scale image into vegetation and nonvegetation pixels. The input data of the neural network for each pixel are 2-dimensional gray-level values surrounding the pixel. To generate a gray-scale image from a raw RGB color image, a well-known color index called Excess Green minus Excess Red Index was used. Experimental results using 80 field images of 4 vegetation species demonstrate the superiority of the neural network to existing threshold-based segmentation methods in terms of accuracy, precision, recall, and harmonic mean.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권7호
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• pp.378-388
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• 2000

In this paper, we propose Fuzzy Polynomial Neural Networks(FPNN) based on Polynomial Neural Networks(PNN) and Fuzzy Neural Networks(FNN) for model identification of complex and nonlinear systems. The proposed FPNN is generated from the mutually combined structure of both FNN and PNN. The one and the other are considered as the premise part and consequence part of FPNN structure respectively. As the consequence part of FPNN, PNN is based on Group Method of Data Handling(GMDH) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and self-organizing networks that can be generated. FPNN is available effectively for multi-input variables and high-order polynomial according to the combination of FNN with PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get better output performance with superb predictive ability. As the premise part of FPNN, FNN uses both the simplified fuzzy inference as fuzzy inference method and error back-propagation algorithm as learning rule. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using genetic algorithms. And we use two kinds of FNN structure according to the division method of fuzzy space of input variables. One is basic FNN structure and uses fuzzy input space divided by each separated input variable, the other is modified FNN structure and uses fuzzy input space divided by mutually combined input variables. In order to evaluate the performance of proposed models, we use the nonlinear function and traffic route choice process. The results show that the proposed FPNN can produce the model with higher accuracy and more robustness than any other method presented previously. And also performance index related to the approximation and prediction capabilities of model is evaluated and discussed.

• 한국수자원학회논문집
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• 제33권5호
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• pp.647-658
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• 2000

본 연구에서는 공급측면 산업연관분석모형을 사용하여 물공급지장이 끼치는 산업의 전방효과를 분석하고자 하였다. 여기서 분석된 공급지장비용은 수도사업의 신뢰도 결정에 사용될수 있으며 물의 공급부족이 발생할 경우 물의 효율적 배분을 위한 정책적 기초를 제공할 수 있다. 따라서 산업연관분석을 이용하여 수도부문이 차지하는 국민경제적 위치를 확인하고 공급지장으로 인한 산업간 직·간접 피해를 분석하였다. 또한 가뭄시 중요한 공급우선 순위 결정을 위한 공급지장지수를 제안하였다. 한편 가뭄의 발생은 지역적인 특성을 가지고 있어서 전국산업연관표를 이용한 지역수준의 공급지장비용이 과대 도는 과소평가될 여지가 있다. 따라서 경남지역산업연관표를 통해 산정한 공급지장비용을 전국산업관표와 비교·분석하였다.

• 산경연구논집
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• 제10권7호
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• pp.71-82
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• 2019

Purpose - This study aims to identify the priorities of medical service quality improvement by customer satisfaction characteristics and potential customer satisfaction improvement (PCSI) index based on the dualistic quality classification of Kano Model (1984) for Comprehensive Health Screeening Center in General Hospitals and Centers only for Comprehensive Health Screening and suggest a direction for future improvement. Research design, data, and methodology - Through advanced research on health screening medical service quality, this study set four service quality factors, including tangible, human, process and supportive factors, and 39 measurement items. Based on these items, the study used 117 questions, which consist of dualistic quality factors, customer satisfaction coefficients, positive and negative questions for PCSI index and questions for current satisfaction. 300 effective samples were collected for adults in their 20s who experienced health screening service in Seoul, Gyeonggi-do and Incheon within the past two years. Collected data were input in the quality evaluation duality table to categorize quality factors and calculate customer satisfaction coefficients by Timko(1993). The study also analyzed PCSI index in comparison with current satisfaction and identified priorities in quality improvement. Results - It was found that the most urgent factors to improve the quality in both groups were adequate waiting hours and emergency response for complications, which are process factors classified as unitary quality. It is urgently needed to improve the quality as the PCSI index was high in supportive factors (complaint response team) as attractive quality in Comprehensive Health Screening Center in General Hospitals and in process factors (prevention of infection) as unitary quality in Centers only for Comprehensive Health Screening. As the PCSI index was low in space use as a tangible factor, it was found that the current level can be maintained instead of improvement. Conclusions - To improve the health screening medical service quality, it is required to focus on process factors (adequate waiting hours, emergency response for complications, prevention of infection) and supportive factors (complaint response team) among service qualities perceived by users. It is proposed to ensure continuous efforts to manage and reinforce priorities as a direction for future improvement in health screening service.

• 한국해양환경ㆍ에너지학회지
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• 제7권2호
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• pp.70-74
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• 2004

연안 퇴적물의 오염도 개선을 위해 수행되는 준설의 시행 여부 판단을 위해서는 합리적인 준설판단지수(Dredging Index: DI)설정이 필수적이다. 외국에서 사용되는 DI는 국가별 경제수준, 자연환경 특성, 해역의 이용 목적 등이 상이한 까닭에, 국내 환경에 직접 활용하는 것은 비합리적이다. 본 연구에서는 그 동안 축적된 국내 자료를 활용하여 DI를 개발하였고, 이를 오염 우심해역인 마산만의 준설 전·후 환경에 적용하였다. 적용 결과, 개발된 DI는 준설에 따른 퇴적물 환경변화를 잘 지시하는 것으로 판단되며, 준설에 필요한 사회 경제적 여건이 고려된 합리적 DI 값이 도출된다면 특정해역의 준설 범위와 깊이를 결정하는 도구로 사용될 수 있을 것으로 사료된다.

• 정보화정책
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• 제24권2호
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• pp.43-67
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• 2017

한국은 2015년 OECD에서 발표한 공공데이터 개방지수인 OUR Data Index에서 30개국 중에서 1위를 차지하였으나 같은 해 발표된 WWW 재단의 공공데이터 개방지수인 ODB에서는 86개국 중에서 17위를 차지하였다. 본 연구는 두 지표의 괴리된 평가결과와 OUR Data Index가 실제 한국의 공공데이터 개방수준을 제대로 평가하고 있는지에 대한 학술적 의구심에서 출발하였다. 이에 OUR Data Index의 국가 간 공공데이터 평가방식에 문제점이 있다고 보고 ODB와의 비교를 진행하였다. 두 지표에 대한 비교결과, 첫째, OUR Data Index와 ODB의 상관관계분석에서 두 지표는 상관성이 거의 없는 것으로 나타났다. 둘째, OUR Data Index는 ODB와 비교해서 평가체계가 모호하고, 평가 공공데이터도 부족하였다. ODB는 평가하는 공공데이터의 종류도 더 많고, 평가방식도 다양하였다. 셋째, OUR Data Index는 정부지원 항목이 평가지표상에 큰 비중을 차지하는데, 이것은 투입요소라는 한계를 가지고 있다. ODB는 이와 유사한 준비도라는 항목이 있으나 정부만이 아닌 다른 이해관계자의 역량도 평가한다는 차이가 있다. 넷째, OUR Data Index는 공공데이터 개방에 따른 효과에 대한 평가항목은 없었다. 반면 ODB는 정부, 경제, 사회 등 세 분야에 대한 공공데이터 개방의 파급효과를 하위항목으로 구성하였다.