• Journal of the Korea Institute of Building Construction
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• v.20 no.6
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• pp.505-514
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• 2020

This research introduces the method of developing Korea BIM standard (KBIMS) architectural and structural element library and the methodology of converting KBIMS IFC property names with special characters. Diverse BIM tools are utilizing in project, however BIM library researches lack diversity on BIM tool selection. This research described the method to generate twelve categories and seven hundred and ninety-three elements library containing geometrical and numerical data in CATIA V6. KBIMS has its special property data naming systems which was the challenge inputting to ENOVIA IFC database. Three mapping methods for special naming characters had been developed and the ASCII code method was applied. In addition, the convertor prototype had been developed for searching and replacing the ASCII codes into the original KBIMS IFC property names. The methodology was verified by exporting 2,443 entities without data loss in the sample model conversion test. This research would provide a wider choice of BIM tool selection for applying KBIMS. Furthermore, the research would help on the reduction of data interoperability issues in projects. The developed library would be open to the public, however the continuous update and maintenance would be necessary.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.616-625
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• 2021

Deep neural networks are an approximation method that approximates an arbitrary function to a linear model and then repeats additional approximation using a nonlinear active function. In this process, the method of evaluating the performance of approximation uses the loss function. Existing in-depth learning methods implement approximation that takes into account loss functions in the linear approximation process, but non-linear approximation phases that use active functions use non-linear transformation that is not related to reduction of loss functions of loss. This study proposes parametric activation functions that introduce scale parameters that can change the scale of activation functions and location parameters that can change the location of activation functions. By introducing parametric activation functions based on scale and location parameters, the performance of nonlinear approximation using activation functions can be improved. The scale and location parameters in each hidden layer can improve the performance of the deep neural network by determining parameters that minimize the loss function value through the learning process using the primary differential coefficient of the loss function for the parameters in the backpropagation. Through MNIST classification problems and XOR problems, parametric activation functions have been found to have superior performance over existing activation functions.

• Smart Media Journal
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• v.11 no.2
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• pp.77-83
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• 2022

The neuromorphic architecture uses a spiking neural network (SNN) model to derive more accurate results as more spike values are accumulated through inference experiments. When the inference result converges to a specific value, even if the inference experiment is further performed, the change in the result is smaller and power consumption may increase. In particular, in an AI-based IoT environment, power consumption can be a big problem. Therefore, in this paper, we propose a technique to reduce the power consumption of AI-based IoT by reducing the inference time by adjusting the inference image exposure time in the neuromorphic architecture environment. The proposed technique calculates the next inferred image exposure time by reflecting the change in inference accuracy. In addition, the rate of reflection of the change in inference accuracy can be adjusted with a coefficient value, and an optimal coefficient value is found through a comparison experiment of various coefficient values. In the proposed technique, the inference image exposure time corresponding to the target accuracy is greater than that of the linear technique, but the overall power consumption is less than that of the linear technique. As a result of measuring and evaluating the performance of the proposed method, it is confirmed that the inference experiment applying the proposed method can reduce the final exposure time by about 90% compared to the inference experiment applying the linear method.

• Journal of Korean Society of Transportation
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• v.24 no.1 s.87
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• pp.29-38
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• 2006

After the first opening of the KTX in April 2004, travel time between major cities has been dramatically reduced. The reduction rates range from 32% to 47%. Considering travel time reduction between major cities, this study concerned about the intercity travel impact of the KTX operation. This study aimed to analyze intercity mode choice behavior of Daegu Citizens according to the first opening of the KTX. This study takes place in two sections. These are (i) the section of KTX between Daegu and Seoul, and (ii) the section of KTX between Daegu and Daejeon. This study estimated empirical models for analyzing intercity mode choice behavior according to the first opening of the KTX. This study makes use of the data from travel survey from Daegu metropolitan area. The main part of the survey was carried out in the KTX Dong-Daegu station. The survey data includes the information on travel from Daegu to Daejeon and from Daegu to Seoul. In order to analyze intercity choice behavior according to the frist opening of the KTX, multinomial model structure is used. For the model specification, a variety of behavioral assumptions about the factors which affect the mode choice, were considered. From the empirical model estimation, it is found that OVTT(Out-of-Vehicle Travel Time), OVTC(Out-of-Vehicle Travel Cost), IVTT(In-Vehicle Travel Time), IVTC(In-Vehicle Travel Cost), travel frequency, travel purpose, sex, age, occupation. household income, individual income are significant in choosing intercity travel mode. However, it is found that the intercity nde choice behavior is different between (i) the section of KTX between Daegu and Seoul, and (ii) the section of KTX between Daegu and Daejeon. Furthermore, some policy implications are discussed in conclusion.

• The Korean Journal of Pesticide Science
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• v.16 no.3
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• pp.261-266
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• 2012

It is common to use many experiment animals to evaluate the toxicity of chemicals including pesticides. For protecting animal, the concepts of 3R (Reduction, Replacement, Refinement) were introduced and in vitro alternatives methods actively have been developed all over the world. Many experimental animals for toxicological tests have been used, so that it is important to establish the alternative methods. In this study, the alternative method using reconstituted human skin model (Keraskin$^{TM}$) was conducted for classification of skin irritation on pesticides. Sixteen formulations selected on the basis of the degree of irritation were treated by Keraskin$^{TM}$ test. The percent of cell viability was measured into the culture medium collected after treatment of the pesticides for 24-72 hrs. The skin irritations of formulations were evaluated by the cell viability. In this study, The 4 formulations with mild irritation in rabbits were evaluated as nonirritant, the 6 formulations with moderate and severe irritation were evaluated as irritant in human skin model test. We suggest that the alternative test using Keraskin$^{TM}$ model could be used as toxicity evaluation for primary irritation index (P.I.I.) score of greater than or equal to 2.1 of pesticides. The further studies should be required to apply for hazardous assessment of pesticides on alternative skin irritation methods because of the interindividual variability of the sensitivity of skin irritation on pesticides.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.233-241
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• 2016

Experiments were carried out to quantify the topographic effects on attenuation of sunshine in complex terrain and the results are expected to help convert the coarse resolution sunshine duration information provided by the Korea Meteorological Administration (KMA) into a detailed map reflecting the terrain characteristics of mountainous watershed. Hourly shaded relief images for one year, each pixel consisting of 0 to 255 brightness value, were constructed by applying techniques of shadow modeling and skyline analysis to the 3m resolution digital elevation model for an experimental watershed on the southern slope of Mt. Jiri in Korea. By using a bimetal sunshine recorder, sunshine duration was measured at three points with different terrain conditions in the watershed from May 15, 2015 to May 14, 2016. The brightness values of the 3 corresponding pixel points on the shaded relief map were extracted and regressed to the measured sunshine duration, resulting in a brightness-sunshine duration response curve for a clear day. We devised a method to calibrate this curve equation according to sky condition categorized by cloud amount and used it to derive an empirical model for estimating sunshine duration over a complex terrain. When the performance of this model was compared with a conventional scheme for estimating sunshine duration over a horizontal plane, the estimation bias was improved remarkably and the root mean square error for daily sunshine hour was 1.7hr, which is a reduction by 37% from the conventional method. In order to apply this model to a given area, the clear-sky sunshine duration of each pixel should be produced on hourly intervals first, by driving the curve equation with the hourly shaded relief image of the area. Next, the cloud effect is corrected by 3-hourly 'sky condition' of the KMA digital forecast products. Finally, daily sunshine hour can be obtained by accumulating the hourly sunshine duration. A detailed sunshine duration distribution of 3m horizontal resolution was obtained by applying this procedure to the experimental watershed.

• Journal of Korean Society of Transportation
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• v.19 no.4
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• pp.7-18
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• 2001

This study represents a first attempt in Korea to develop the simultaneous freight supply-demand model which considers the relationship between freight supply and demand. As the existing study was limited in one area, or the supply and the demand was separated and assumed not to affect each other, this study take it into consideration the fact that the demand affects supply and simultaneously vice versa. This approach allows us to diagnose a policy carried on and helps us to make a resonable alternative for the effectiveness of freight transportation system. To find a relationship between them, we use a method of econometrics. a structural equation theory and two stage least-squares(2SLS) estimation technique, to get rid of bias which involves two successive applications of OLS. Based on the domestic freight data, this study consider as explanatory variables a number of population(P), industry(IN), the amount of production of the mining and manufacturing industries(MMI), the rate of the effectiveness of freight capacity(LE) and the distance of an empty carriage operation(VC). This study describes well the simultaneous process of freight supply-demand system in that the increase of VC from the decrease of VC raises the cargo capacity and cargo capacity also augments VC. By the way. it is analyzed that the increment of VC due to the increase of the cargo capacity is larger than the reduction of VC owing to the increase of the quantify of goods. Therefore an alternative policy is needed in a short and long run point of view. That is to say, to promote the effectiveness of the freight transportation system, a short term supply control and a long run logistic infrastructure are urgent based on the restoration of market economy by successive deregulation. So we are able to conclude that gradual deregulation is more desirable to build effective freight market.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.27 no.4
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• pp.340-360
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• 1982

Because of the continuing rapid increase in pesticide usage in Taiwan, much attention has been focus on pesticide contamination of food and effect of pesticides on human and environmental health. The Plant Protection Center (PPC) conducts safety evaluation of pesticides usee! in Taiwan. The pesticides are classified into different groups based on their acute toxicities. Pesticides which are classified into extremely toxic group are not allow to used on short term crops or the continuously harvest crops. The acute toxicity of pesticides to the beneficial insects are also studied, special attention has been paid to the two predators of rice brown planthopper. 60% of cultivated land in Taiwan are paddy field; therefore, acute fish toxicity was taken into consideration when a pesticide was applied for registration to be used in the paddy. Fish toxicities were evaluated by the dangerous rating value which is the amount of pesticide residue in the field water over the TLM value. Mutagenicity of pesticides was continuously evaluated by using Arne's microbial testing method. Island wide survey of residual levels of pesticides of known pollutants such as chlorinated hydrocarbon . insecticides, mercurial compounds in soil, water and biological samples were carried out constantly. The potential of a new1y Imported esticides to pollute the environment were studied by using model ecosystem. Ecological magnification (EM) of a chemical was calculated from model ecosystem. A chemical was considered as a pollutant when its EM value over 5000. In order to ensure the levels of pesticides residue of the crop within the safety limit. The 'tolerance' of pesticides on different crop groupings were established base on 1) acceptable daily intake value of individual pesticides, 2) average daily consumption of each crop groupings by Chinese person, 3) Actual residues of pesticides. on different crops obtained from supervised trials. Total about 79 pesticides for which the tolerances have been established on different crop groupings. Because the intensive agricultural system was adopted in Taiwan. The phytotoxicity of pesticides to the non-target crops was therefore become one of the important factor in the safety evaluation of pesticide usage. These will include 1) direct injury, 2) injury caused by pesticide polluted irrigation water, 3) injury caused by the pesticide polluted soil, 4) reduction of growth caused by the effect of pesticide on the soil microorganisms. This paper will reviewed all the aspects mentioned in the previous .paragraphs. Most the works have done in Taiwan by the PPC.y the PPC.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.6
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• pp.635-641
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• 2019

Domestic southwest offshore wind farms have problems such as the reduction in fishing rights by prohibiting vessel traffic, which delays their development. As such, there is a need to develop offshore windfarms in Europe to permit the passage of vessels and fishing operations in specific offshore windfarm areas. In this study, we used the environmental stress (ES model) and the IALA Waterway Risk Assessment Program (IWRAP) to determine the ratio of risk to the route type (cross pattern, grid pattern) and traffic volume (present, 3 times, 5 times and 10 times) to derive the risk factors of specific vessels for offshore windfarms. As a result, ship operators' risk related to offshore windfarms did not rise in both route types and there was no significant difference in the annual probability of collision in the present traffic volume. In conditions that increased traffic volume by 3 times, 5 times and 10 times, the risk ratio increased as ship operator risk and collision probability increased at the crossing points. Furthermore, when the traffic volume of the ship increased, the risk could be more effectively distributed in the grid route compared to the cross route. The results of this study are expected to apply to the operation type, route operation method, safety measures, etc. in offshore wind farms.

• Journal of the Korean Institute of Gas
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• v.2 no.4
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• pp.60-66
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• 1998

The hot stove system is a process that is continuously and constantly generating the hot combustion air required for the blast furnace. The hot stove process is considered as a main energy consumption process because it consumes about $20\%$ of the total energy in steel making works. So, many researchers have interested in the improvement of the heat efficiency of the hot stove to reduce the energy consumption. But they have difficulties in improving the heat efficiency of the hot stove because there is no precise information on heat transformation occurring during the heating period. In order to model the relationship between the operating conditions and heat efficiencies, we propose a neural network using feature extraction as one of experimental modeling methods. In order to show the performance of the model, we compare it with Partial Least Square (PLS) method. Both methods have similarities in using the dimension reduction technique. And then we present the simulation results on the prediction of the heat efficiency of the hot stove.