• Journal of the Korean Solar Energy Society
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• v.26 no.3
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• pp.89-97
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• 2006

Our Housing culture continuously changes for the correspondence to social development and changes of economy, and be developing. A massive apartment complex continuously increased, and According to this in our country heating energy consumption of a residential building is continuously increasing at country me whom was limited in order to raise efficient residential land use and diffusion ratio of house. If confirm an element to be able to reduce use of a heating energy, and there is saving possibility to parts of energy saving, this study will present the standard amount used with bases to the gas amount used for heating and Field Test data about room temperature. Execute simulation with building balance (public area, a plain), the gas amount useds such as incense of a building, indoor setting temperature ($^{\circ}C$), a position of an apartment house etc. to affect the energy amount used of a valuation object building of a variable through Field Test and research on the actual condition. Calculate the standard amount used of city gas for winter season heating of a comparative analysis apartment house to data value getting the above results through Field Test and simulations with bases.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.8 s.239
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• pp.1132-1138
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• 2005

Fatigue life of metal material can be predicted by the use of fracture theory and experimental database. Although prediction of fatigue life of rubber material uses the same way as metal, there are many reasons to make it almost impossible. One of the reasons is that there is not currently used fracture criteria for rubber material beacuse of non-standardization, various way of composition process of rubber and so on. Tearing energy is one of the fracture criteria which can be applied to a rubber. Even if tearing energy relaxes the restriction of rubber composition, it is also not currently used because of complication to apply in. Research material about failure process of rubber and tearing energy was reviewed to define the process of fatigue failure and the applicability of tearing energy in estimation of fatigue life for rubber. Also, 1file element formulation of tearing energy which can be used in FE analysis was developed.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.531-537
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• 1999

This paper presents the evaluaton procedures and the estimation model for DSM potential on commercial sector in Korea. In general, the evaluation process of the potential savings for DSM measures or programs consists of baseline electricity consumption forecast and potential evaluation such as technical potential(TP), economic potnetial(EP), and achievable potential(AP). A library of energy conservation measures applicable to each end-use or apparatus is developed, and energy savings and other factors are applied to the baseline demand estimates of consumption to produce potential savings estimates. The purpose of this paper is to establish the evaluation process of those DSM potential for commercial sector. In case study, we applied it to commercial sector for horizon years by end-use.

• Coupled systems mechanics
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• v.2 no.1
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• pp.23-51
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• 2013

An analytical algorithm for the estimation of the resistance forces exerted on the dipper of a cable shovel and the specific energy consumed in the cutting-loading process is presented. Forces due to payload and to cutting of geomaterials under given initial conditions, cutting trajectory of the bucket, bucket's design, and geomaterial properties are analytically computed. The excavation process has been modeled by means of a kinematical shovel model, as well as of dynamic payload and cutting resistance models. For the calculation of the cutting forces, a logsandwich passive failure mechanism of the geomaterial is considered, as has been found by considering that a slip surface propagates like a mixed mode crack. Subsequently, the Upper-Bound theorem of Limit Analysis Theory is applied for the approximate calculation of the maximum reacting forces exerted on the dipper of the cable shovel. This algorithm has been implemented into an Excel$^{TM}$ spreadsheet to facilitate user-friendly, "transparent" calculations and built-in data analysis techniques. Its use is demonstrated with a realistic application of a medium-sized shovel. It was found, among others, that the specific energy of cutting exhibits a size effect, such that it decreases as the (-1)-power of the cutting depth for the considered example application.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.367-378
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• 2021

This paper develops a dynamic regression model to quantify the contribution of key external factors to operational energy efficiency of ships. On this basis, kernel density estimation is applied to explore distribution patterns of fluctuations in operational performance. An empirical analysis based on these methods show that distribution of fluctuations in Energy Efficiency Operational Indicator (EEOI) is leptokurtic and fat tailed, rather than a normal one. Around 85% of fluctuations in EEOI can be jointly explained by capacity utilization and sailing speed, while the rest depend on other external factors largely beyond control. The variations in capacity utilization and sailing speed cannot be fully passed on to the energy efficiency performance of ships, due to complex interactions between various external factors. The application of the methods is demonstrated, showing a potential approach to develop a rating mechanism for use in the legally binding framework on operational energy efficiency of ships.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.303-309
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• 2012

Energy expenditure values were estimated based on the voice signals and body activities. Voice signals and body activities were obtained using PVDF contact vibration sensor and 3-axis accelerometer, respectively. Vibration caused by voices, activity signals, and actual energy consumption were acquired using data acquisition system and gas analyzer. With the use of power values from the voice signals and weight as independent variables, R-square of 0.918 appeared to show the highest value. For activity outputs, use of signal vector magnitude, body mass index, height, and age as independent variables revealed to provide the highest correlation with actual energy expenditure. Estimation of energy expenditure based on voice and activity provides more accurate results than based on activity only.

• Journal of the Korean Institute of Landscape Architecture
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• v.27 no.1
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• pp.64-78
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• 1999

Recently, new concept and paradigm of 'Environmental Sustainability' is taking a growing interest in environmental planning and design. This study is to establish the environmental sustainability principles, based on the concept of ESSD, and to develop the evaluation model of environmental sustainability for korean rural housing estates. A sustainability indices system, which is composed of 5 principles, 16 categories, an 37 estimation items, was finally established. Five principles of environmental sustainability for rural housing estate were. 'Sustainable Land Use', 'Interdependence of Men and Nature', 'Ecological Principles and Diversity', 'Efficient use of Energy and Recycling', and ' Minimizing Environmental Pollution'. And weighting values of each indicators, such as estimation items, categories, and principles, were estimated, based on the result of AHP etc. The questinnaire survey was conducted for experts of four related major fields. Finally, the validity and reliability of the sustainability indices system were verified.

• Journal of Korea Multimedia Society
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• v.13 no.6
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• pp.890-900
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• 2010

The Bayesian networks methods provide an efficient tool for performing information fusion and decision making under conditions of uncertainty. This paper proposes Bayes estimators for the system effectiveness in energy saving of the wireless sensor networks by use of the Bayesian method under the non-informative prior knowledge about means of active and sleep times based on time frames of sensor nodes in a wireless sensor network. And then, we conduct a case study on some Bayesian estimation models for the system energy saving effectiveness of a wireless sensor network, and evaluate and compare the performance of proposed Bayesian estimates of the system effectiveness in energy saving of the wireless sensor network. In the case study, we have recognized that the proposed Bayesian system energy saving effectiveness estimators are excellent to adapt in evaluation of energy efficiency using non-informative prior knowledge from previous experience with robustness according to given values of parameters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.907-923
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• 2020

For the severe haze situation in the Beijing-Tianjin-Hebei region, conventional fine particulate matter (PM2.5) concentration prediction methods based on pollutant data face problems such as incomplete data, which may lead to poor prediction performance. Therefore, this paper proposes a method of predicting the PM2.5 concentration based on image analysis technology that combines image data, which can reflect the original weather conditions, with currently popular machine learning methods. First, based on local parameter estimation, autoregressive (AR) model analysis and local estimation of the increase in image blur, we extract features from the weather images using an approach inspired by free energy and a no-reference robust metric model. Next, we compare the coefficient energy and contrast difference of each pixel in the AR model and then use the percentages to calculate the image sharpness to derive the overall mass fraction. Furthermore, the results are compared. The relationship between residual value and PM2.5 concentration is fitted by generalized Gauss distribution (GGD) model. Finally, nonlinear mapping is performed via the wavelet neural network (WNN) method to obtain the PM2.5 concentration. Experimental results obtained on real data show that the proposed method offers an improved prediction accuracy and lower root mean square error (RMSE).

• The KSFM Journal of Fluid Machinery
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• v.14 no.1
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• pp.34-41
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• 2011

Fire characteristics can be analyzed more realistically by using more accurate properties related to the fire dynamics and one way to acquire these fire properties is to use one of the inverse property estimation techniques. In this study two optimization algorithms which are frequently applied for the inverse heat transfer problems are selected to demonstrate the procedure of obtaining pyrolysis properties of charring material with relatively simple thermal decomposition. Thermal decomposition is occurred at the surface of the charring material heated by receiving the radiative energy from external heat sources and in this process the heat transfer through the charring material is simplified by an unsteady 1-dimensional problem. The basic genetic algorithm(GA) and repulsive particle swarm optimization(RPSO) algorithm are used to find the eight properties of a charring material; thermal conductivity(virgin, char), specific heat(virgin, char), char density, heat of pyrolysis, pre-exponential factor and activation energy by using the surface temperature and mass loss rate history data which are obtained from the calculated experiments. Results show that the RPSO algorithm has better performance in estimating the eight pyrolysis properties than the basic GA for problems considered in this study.