• Journal of the Korean Solar Energy Society
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• v.31 no.2
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• pp.37-46
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• 2011

The GWNU (Gangnung-Wonju national university) solar radiation model was developed with radiative transfer theory by Iqbal and it is applied the NREL (National Research Energy Laboratory). Input data were collected and accomplished from the model prediction data from RDAPS (Regional Data Assimilated Prediction Model), satellite data and ground observations. And GWNU solar model calculates not only horizontal surface but also complicated terrain surface. Also, We collected the statistical data related on photovoltaic power generation of the Korean Peninsula and analyzed about photovoltaic power efficiency of the Gangwon region. Finally, the solar energy resource and photovoltaic generation possibility map established up with 4 km, 1 km and 180 m resolution on Gangwon region based on actual equipment from Shinan solar plant,statistical data for photovoltaic and complicated topographical effect.

• The Journal of Information Systems
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• v.31 no.1
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• pp.115-146
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• 2022

Purpose The purpose of this study is to find meaningful insights using regression analysis to resolve the digital divide between generations. In the analysis process of this study, social network analysis was applied to approach it with a perspective differentiated from the existing statistical techniques. Design/methodology/approach This study used a social network analysis methodology that transforms and analyzes government-led survey data into relational data. First, the cross-sectional data were converted into relational data, and a continuous core-periphery model and multidimensional scaling method were applied. Afterwards, the relationship between various factors affecting the digital divide and the difference in influence were analyzed by generation. Findings According to the network analysis results, it can be seen that all generations commonly use 'information and news search' and 'living information service'. However, it can be seen that the centrally used services of each generation are clearly different from each other, and the degree of linkage between the services is also clearly different. In addition, it can be seen that the relationship between factors influencing the digital divide by generation is also different.

• Water for future
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• v.18 no.1
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• pp.75-83
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• 1985

The applicability of ARMA(1, 1) multiseason model, which is in the beginning stage of active researches in the field of synthetic generation is evaluated with the streamflow data at the Nakdong stage gauging station on the main stem of the Nakdong River. The method of parameter estimation for the modelis reviewed and the statistical analysis of the generated seasonal streamflows such as corrlogram analysis and the computation of moments is made. The results obtained by ARMA(1, 1) multiseason model are compared with the historical streamflow data and also with those by two other multiseason models, namely, Thomas-Fiering model and Matalas AR(1) multiseason model. The seasonal streamflows grnerated by three multiseason models were annually summed up to form respective annual flow series whose statistics were compared with those of the annual flow series generated by three annual models, namely, AR(1), Matalas AR(1), and ARMA(1, 1) annual models. The possibility of ARMA(1, 1) multiseason model for the simultaneous generation of seasonal and annual streamflows is also evaluated.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1177-1179
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• 2003

Recently, the ground-based laser profiler is used for acquisition of 3D spatial information of a rchaeological objects. However, it is very difficult to measure complicated objects, because of a relatively low-resolution. On the other hand, texture mapping can be a solution to complement the low resolution, and to generate 3D model with higher fidelity. But, a huge cost is required for the construction of textured 3D model, because huge labor is demanded, and the work depends on editor's experiences and skills . Moreover, the accuracy of data would be lost during the editing works. In this research, using the laser profiler and a non-calibrated digital camera, a method is proposed for the automatic generation of 3D model by integrating these data. At first, region segmentation is applied to laser range data to extract geometric features of an object in the laser range data. Various information such as normal vectors of planes, distances from a sensor and a sun-direction are used in this processing. Next, an image segmentation is also applied to the digital camera images, which include the same object. Then, geometrical relations are determined by corresponding the features extracted in the laser range data and digital camera’ images. By projecting digital camera image onto the surface data reconstructed from laser range image, the 3D texture model was generated automatically.

• Journal of the Korean Solar Energy Society
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• v.26 no.1
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• pp.41-47
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• 2006

Moisture in a building is one of the most important variables influencing building performance, human health, and comfort of indoor environment. However, there are still lacks in the knowledge of understanding the moisture problem well and controlling moisture. Accordingly, in order to provide the fundamental data to control moisture contents in the indoor air, this study was to predict moisture contents transferred through building envelopes and indoor moisture generation rate. Moisture transfer model was made by physical relations in each node, and the indoor moisture generation rate was gained by comparing the model with experimental analyses. From the study, we found out that moisture generation rate was critical and day-periodic, so that we predicted the indoor moisture content by substituting the constant value gained from the average in a day for the moisture generation rate.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.2
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• pp.329-338
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• 2021

This study predicts the amount of wind power generation for rational operation plan of wind power generation and capacity calculation of ESS. For forecasting, we present a method of predicting wind power generation by combining a physical approach and a statistical approach. The factors of wind power generation are analyzed and variables are selected. By collecting historical data of the selected variables, the amount of wind power generation is predicted using deep learning. The model used is a hybrid model that combines a bidirectional long short term memory (LSTM) and a convolution neural network (CNN) algorithm. To compare the prediction performance, this model is compared with the model and the error which consist of the MLP(:Multi Layer Perceptron) algorithm, The results is presented to evaluate the prediction performance.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.809-812
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• 2007

Automatic generation method of structural analysis model data for a truss bridge is presented through 3-D bridge information modeling based on Industry Foundation Classes(IFC). The mapping schema is proposed between a steel bridge information model based on STEP and a truss bridge information model based on the IFC. The geometry information from mapping is presented by IFC model, and SAP 2000 that can import the IFC file performs the structural analysis. Numerical analysis for a truss bridge is performed in this paper.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.6
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• pp.1-9
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• 2009

Watershed topographical data is essential for the management for water resources and watershed management in terms of hydrology analysis. Collecting watershed topographical and meteorological data is the first step for simulating hydrological models and calculating hydrological components. This study describes a specialized Web-based Geographic Information Systems, Soil Water Assessment Tool model data generation system, which was developed to support SWAT model operation using Web-GIS capability for map browsing, online watershed delineation and topographical and meteorological data extraction. This system tested its operability extracting watershed topographical and meteorological data in real time and the extracted spatial and weather data were seamlessly imported to ArcSWAT system demonstrating its usability. The Web-GIS would be useful to users who are willing to operate SWAT models for the various watershed management purposes in terms of spatial and weather preparing.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.840-842
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• 2005

Since 2001, Korea government has been purchasing the generation from renewable generation facilities with the higher incentive prices than market price in order to increase the penetration of renewable energies. Generally, the incentive purchase tariff is calculated on the base of the generation cost of renewable power facilities. This paper constructs the input data for economic analysis and evaluates the generation cost of PV, wind power, LFG and small hydro power using LCCA model.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.8
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• pp.341-354
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• 2023

The title of a document is the brief summarization of the document. Readers can easily understand a document if we provide them with its title in their preferred styles and the languages. In this research, we propose a cross-lingual and style-based title generation model using multiple adapters. To train the model, we need a parallel corpus in several languages with different styles. It is quite difficult to construct this kind of parallel corpus; however, a monolingual title generation corpus of the same style can be built easily. Therefore, we apply a zero-shot strategy to generate a title in a different language and with a different style for an input document. A baseline model is Transformer consisting of an encoder and a decoder, pre-trained by several languages. The model is then equipped with multiple adapters for translation, languages, and styles. After the model learns a translation task from parallel corpus, it learns a title generation task from monolingual title generation corpus. When training the model with a task, we only activate an adapter that corresponds to the task. When generating a cross-lingual and style-based title, we only activate adapters that correspond to a target language and a target style. An experimental result shows that our proposed model is only as good as a pipeline model that first translates into a target language and then generates a title. There have been significant changes in natural language generation due to the emergence of large-scale language models. However, research to improve the performance of natural language generation using limited resources and limited data needs to continue. In this regard, this study seeks to explore the significance of such research.