• Journal of Energy Engineering
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• v.21 no.1
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• pp.109-117
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• 2012

The climate industry could be defined as the group of industries responding to world climate change compacts. This study confined it to renewable energy and analyzed the economic impacts of Korean renewable industry, using 2009 Input-Output Table. This study estimated that Korean renewable industry made the production-induced impact of 1.1644 won(Korean money), and the value-added-induced impact of 0.3544 won through an increase in output growth of 1 won. Its job-creation impact is analyzed to correspond to 10.065 labors through an increase in output growth of 1 billion won. And its industrial linkage effects including forward and backward ones are analyzed not to be so great as expected. According to these results, some policies vitalizing Korean renewable industry and relating industries to its value-chain as new growth engines are recommended.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.1
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• pp.55-64
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• 1995

This paper presents analytic results of energy sequestered for the forcing cultural Cu- cumber and the others production system with the input-output tables method in the suthern parts of Korea. In this study an attempt is made to evaluate input of direct and indirect energy, output of yield energy and net energy in order to achieve increased energy productivity under P E greenhouse. Cultural practices were grouped soil and soilless with perlite for vegetable production. The results from this study are summarized as follows : 1. Total energy inputs in cucumber production were calculated to be 510 GJ/l0a(di- rect energy : 480 GJ/lOa, indirect energy : 30 GJ/lOa) from soil culture and 440 GJ/ 10a(direct energy : 420 GJ/lOa, indirect energy : 20 GJ/lOa) from soilless culture in perlite hydroponics. 2. Energy outputs from cucumber and biomass were 7 GJ/lOa and 120 GJ/lOa at a uniform rate respectively. 3. Heating fuel as diesel is a major energy inputs approaching 90% of the total energy requirements for cucumber production. 4. Net energy in cucumber production was calculated to be 503 GJ/lOa from soil cul- ture and 431 GJ/lOa from soilless culture. Net energy productivity was maintained costantly as 0.98. 5. Energy productivity in cucumber was calculated to be 0.029 kg/MJ from soil culture and 0.043kg/MJ from soilless culture, while energy efficiency was 0.012 and 0.015 respectively. It is expected that a soilless cultural production system seems to be reduc- tive in seguestered energy input by 13%.

• Journal of the Korean Solar Energy Society
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• v.23 no.4
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• pp.11-20
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• 2003

This study aims to develop the program for active solar heating system design & analysis. The program, named ASOLis, is consisted of three user's interface like as system input/output, library, and utilities and used TRNSYS as a calculation engine for the system analysis. ASOLis simplifies user's input data through the database and can design 37 different types of solar systems. Solar system is configurated by two separated parts "solar thermal collecting part" and "load supplying part". Due to the user-friendly layout, all design parameters can be changed quickly and easily for the influence on system efficiency. For the reliability, ASOLis compared with experimental result. As a result, ASOLis is expected to be used as a vital tool for the design and analysis of active solar heating system.

• Nutrition Research and Practice
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• v.17 no.6
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• pp.1255-1266
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• 2023

BACKGROUND/OBJECTIVES: This study aimed to predict the association between nutritional intake and diabetes mellitus (DM) by developing an artificial neural network (ANN) model for older adults. SUBJECTS/METHODS: Participants aged over 65 years from the 7th (2016-2018) Korea National Health and Nutrition Examination Survey were included. The diagnostic criteria of DM were set as output variables, while various nutritional intakes were set as input variables. An ANN model comprising one input layer with 16 nodes, one hidden layer with 12 nodes, and one output layer with one node was implemented in the MATLAB^® programming language. A sensitivity analysis was conducted to determine the relative importance of the input variables in predicting the output. RESULTS: Our DM-predicting neural network model exhibited relatively high accuracy (81.3%) with 11 nutrient inputs, namely, thiamin, carbohydrates, potassium, energy, cholesterol, sugar, vitamin A, riboflavin, protein, vitamin C, and fat. CONCLUSIONS: In this study, the neural network sensitivity analysis method based on nutrient intake demonstrated a relatively accurate classification and prediction of DM in the older population.

• Environmental and Resource Economics Review
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• v.20 no.2
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• pp.255-289
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• 2011

This study made linked Energy IO Table 00-05-08 of 76 sectors in intermediate sectors and analyzed structural decomposition analysis in energy consumption change in industrial sector with both by aggregate data and micro data. Structural decomposition analysis focused value added level change, value added share change of each industry, output structural change of each industry and energy intensity change of each industry as factors. Supply side model based on Ghosh inverse matrix was applied as empirical model because Korea has export driven industrial structure. Empirical results with aggregate data showed that value added change increased energy consumption and output structural change of each industry decreased energy consumption in both 2000~2005 and 2005~2008. However value added share change and energy intensity change caused opposite direction in energy consumption change with time. Policy based on aggregate data can not evaluate effort of each industry in energy efficiency and make effective results because aggregate data delete character of each industry.

• Journal of Energy Engineering
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• v.8 no.2
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• pp.317-324
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• 1999

This study suggests the effectiveness of an "extended" power system evaluation methodology based on LCA and energy input-output analysis techniques. This "extended" evaluation methodology is designed to incorporate total energy system costs through fuel cycle and external costs, including CO$_2$abatement cost. As an empirical test, we applied the methodology to orimulsion-fired power generation technology and found that orimulsion could be considered as in attractive base-load power generation fuel in terms of economic and environmental aspects, compared to conventional coal-fired power plant.

• Journal of the Korean Solar Energy Society
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• v.28 no.6
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• pp.64-69
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• 2008

In this study the thermal performance and economic analysis program of solar heating system for district heating was developed. This program, named SOLAN-DHS and based on TRNSYS, consisted of four modules like as user's interface for system input/output, library, and utilities and a calculating engine. SOLAN-DHS simplifies user's input data through the database of most system engineering data including weather data of 17 areas in Korea. Five different types of solar systems which can be applicable to district heating system were presented in this program. Due to the user-friendly layout, all design parameters can be changed quickly and easily for the influence on system efficiency. The reliability of SOLAN-DHS was finally verified by the experiments.

• Ocean and Polar Research
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• v.38 no.1
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• pp.59-70
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• 2016

Establishing the strategic plans to foster the oceans and fisheries (O&F) industry as an engine for national sustainable economic growth has become an important task for developing countries as well as developed countries. The first step to do so is to identify O&F industry and analyze its economic effects. Therefore, the prime purposes of the paper are two-fold. The first is to identify O&F industry and estimate its market size using 2012 Input-Output (I-O) table published by the Bank of Korea. The second purpose is to obtain some quantitative information on production-inducing effect, value-added creation effect, and employment-inducing effect of the O&F industry. To this end, we apply an IO analysis using exogenous specification of the O&F industry. The results show that the O&F industry covers 4.1% and 3.0% of national output and gross domestic product, respectively. Moreover, we found that 1.0 won of production or investment in the O&F industry induces 1.7363 won of production and 0.4759 won of value-added in the national economy. One billion won of production or investment in the O&F industry touches off 7.5569 persons of employment. This information can be utilized in the O&F industry-related policy-making.

• Journal of Communications and Networks
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• v.12 no.4
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• pp.358-365
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• 2010

We develop a low complexity cooperative diversity protocol for low energy adaptive clustering hierarchy (LEACH) based wireless sensor networks. A cross layer approach is used to obtain spatial diversity in the physical layer. In this paper, a simple modification in clustering algorithm of the LEACH protocol is proposed to exploit virtual multiple-input multiple-output (MIMO) based user cooperation. In lieu of selecting a single cluster-head at network layer, we proposed M cluster-heads in each cluster to obtain a diversity order of M in long distance communication. Due to the broadcast nature of wireless transmission, cluster-heads are able to receive data from sensor nodes at the same time. This fact ensures the synchronization required to implement a virtual MIMO based space time block code (STBC) in cluster-head to sink node transmission. An analytical method to evaluate the energy consumption based on BER curve is presented. Analysis and simulation results show that proposed cooperative LEACH protocol can save a huge amount of energy over LEACH protocol with same data rate, bit error rate, delay and bandwidth requirements. Moreover, this proposal can achieve higher order diversity with improved spectral efficiency compared to other virtual MIMO based protocols.

• KIEAE Journal
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• v.15 no.4
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• pp.105-110
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• 2015

Purpose: This study aimed at finding the optimal input variables of the artificial neural network-based predictive model for the optimal controls of the indoor temperature environment. By applying the optimal input variables to the predictive model, the required time for restoring the current indoor temperature during the setback period to the normal setpoint temperature can be more precisely calculated for the cooling season. The precise prediction results will support the advanced operation of the cooling system to condition the indoor temperature comfortably in a more energy-efficient manner. Method: Two major steps employing the numerical computer simulation method were conducted for developing an ANN model and finding the optimal input variables. In the first process, the initial ANN model was intuitively determined to have input neurons that seemed to have a relationship with the output neuron. The second process was conducted for finding the statistical relationship between the initial input variables and output variable. Result: Based on the statistical analysis, the optimal input variables were determined.