• Proceedings of the Korean Society of Computer Information Conference
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• 2015.07a
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• pp.333-334
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• 2015

2012년 12월 협동조합기본법이 시행된 이래, 2015년 6월 현재 전국적으로 약 7,300여개의 협동조합이 설립되어 조합원들의 유기적인 공동활동을 통해 공동사업을 수행하고 있다. 소상공인협동조합, 사회적협동조합 등 다양한 형태의 협동조합은 자신들의 공동목적을 달성하기 위한 요소로 업무정보 공유에 기반한 협업이 필수적이라고 인식하고 있다. 기획재정부의 분류에 따르면 21개의 업종으로 다양한 산업군에 걸쳐 협동조합은 하나의 기업처럼 사업활동을 하고 있다. 하지만, 일반기업과는 달리 협동조합은 수직적인 경영구조가 아닌 조합원들 간의 수평적 경영조직을 갖는다. 본 논문에서는 공동사업 수행과 공동이익 창출이라는 협동조합의 특수한 사업모델과 전국에 산발적으로 분산되어 있는 조합원들 간의 공동업무 활동을 위한 협업 시스템을 제안한다.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.6
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• pp.365-371
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• 2008

Condensing gas boiler units may make a big role for the reduction of energy consumption in heating industries. In order to decrease the energy consumption of a condensing gas boiler unit, effective operations of the system are necessary. In this study, mathematical models of a condensing gas boiler system were developed in order to develop control algorithms of the system. These include dynamic models of a blower, a gas valve, a pump, a burner, a boiler heat exchanger, and a hot water heat exchanger. Control algorithms of a blower, a gas valve, and a pump were also assumed. Simulation results showed good predictions of dynamic behaviors of a boiler system. Therefore, the simulation program developed for this study may be effectively used for the development of control algorithms of a boiler system.

• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.1-6
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• 2021

The purpose of this study is to improve the performance of the artificial neural network system for facial image analysis through the image landmark selection technique. For landmark selection, a CNN-based multi-layer ResNet model for classification of facial image age is required. From the configured ResNet model, a heat map that detects the change of the output node according to the change of the input node is extracted. By combining a plurality of extracted heat maps, facial landmarks related to age classification prediction are created. The importance of each pixel location can be analyzed through facial landmarks. In addition, by removing the pixels with low weights, a significant amount of input data can be reduced.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.309-328
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• 2022

This study empirically analyzed a Korean pre-trained language models (PLMs) designed for natural language generation. The performance of two PLMs - BART and GPT - at the task of abstractive text summarization was compared. To investigate how performance depends on the characteristics of the inference data, ten different document types, containing six types of informational content and creation content, were considered. It was found that BART (which can both generate and understand natural language) performed better than GPT (which can only generate). Upon more detailed examination of the effect of inference data characteristics, the performance of GPT was found to be proportional to the length of the input text. However, even for the longest documents (with optimal GPT performance), BART still out-performed GPT, suggesting that the greatest influence on downstream performance is not the size of the training data or PLMs parameters but the structural suitability of the PLMs for the applied downstream task. The performance of different PLMs was also compared through analyzing parts of speech (POS) shares. BART's performance was inversely related to the proportion of prefixes, adjectives, adverbs and verbs but positively related to that of nouns. This result emphasizes the importance of taking the inference data's characteristics into account when fine-tuning a PLMs for its intended downstream task.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.4
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• pp.189-196
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• 2017

BIS(Bus Information System) provides the different information related to buses including predictions of arriving times at stations. BIS have been deployed almost all cities in our country and played active roles to improve the convenience of public transportation systems. Moving average filters, Kalman filter and regression models have been representative in forecasting the arriving times of buses in current BIS. The accuracy in prediction of arriving times depends largely on the forecasting algorithms and traffic conditions considered when forecasting in BIS. In present BIS, the simple prediction algorithms are used only considering the passage times and distances between stations. The forecasting of arrivals, however, have been influenced by the traffic conditions such as traffic signals, traffic accidents and pedestrians ets., and missing data. To improve the accuracy of bus arriving estimates, there are big troubles in building models including the above problems. Hidden Markov Models have been effective algorithms considering various restrictions above. So, we have built the HMM forecasting models for bus arriving times in the current BIS. When building models, the data collected from Sunchean City at 2015 have been utilized. There are about 2298 stations and 217 routes in Suncheon city. The models are developed differently week days and weekend. And then the models are conformed with the data from different districts and times. We find that our HMM models can provide more accurate forecasting than other existing methods like moving average filters, Kalmam filters, or regression models. In this paper, we propose Hidden Markov Model to obtain more precise and accurate model better than Moving Average Filter, Kalman Filter and regression model. With the help of Hidden Markov Model, two different sections were used to find the pattern and verified using Bootstrap process.

• Journal of the Korean Geographical Society
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• v.49 no.6
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• pp.917-934
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• 2014

Geographically weighted regression(GWR) model has been widely used to estimate spatially heterogeneous real estate prices. The GWR model, however, has some limitations of the selection of different price determinants over space and the restricted number of observations for local estimation. Alternatively, the geographically weighted LASSO(GWL) model has been recently introduced and received a growing interest. In this paper, we attempt to explore various local price determinants for the real estate by utilizing the GWL and its applicability to forecasting the real estate price. To do this, we developed the three hedonic models of OLS, GWR, and GWL focusing on the sales price of apartments in Seoul and compared those models in terms of model fit, prediction, and multicollinearity. As a result, local models appeared to be better than the global OLS on the whole, and in particular, the GWL appeared to be more explanatory and predictable than other models. Moreover, the GWL enabled to provide spatially different sets of price determinants which no multicollinearity exists. The GWL helps select the significant sets of independent variables from a high dimensional dataset, and hence will be a useful technique for large and complex spatial big data.

• Journal of Biomedical Engineering Research
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• v.23 no.6
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• pp.437-449
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• 2002

Coronary arteries are subjected to very different flow conditions compared to other arteries in systemic blood circulation. We Performed a computational fluid dynamic research to investigate influence of such flow conditions in coronary arteries on development and progress of atherosclerosis in the same. The results showed big differences in the flow field of the coronary artery compared to the abdominal and femoral arteries. The coronary artery showed higher wall shear stresses due to the small vessel diameter. On the other hand, it showed only one vortex distal to the stenosis throat during a whole pulse cycle. However. several vortices were observed in the abdominal and femoral arteries in both proximal and distal sides of the stenosis throat The wall shear stresses and extent of recirculation area were increased with impedance phase angle increasing toward more negative values. Therefore, cardiac contraction and the negative impedance phase angle as large as -110。 may induce a flow field that accelerates atherosclerosis.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.284-288
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• 2009

With explosively growing PPI databases, the computational approach for a prediction and configuration of PPI network has been a big stream in the bioinformatics area. Recent researches gradually consider physicochemical properties of proteins and support high resolution results with integration of experimental results. With regard to current research trend, it is very close future to complete a PPI network configuration of each organism. However, direct applying the PPI network to real field is complicated problem because PPI network is only a set of co-expressive proteins or gene products, and its network link means simple physical binding rather than in-depth knowledge of biological process. In this paper, we suggest a protein functional flow model which is a directed network based on a protein functions' relation of signaling transduction pathway. The vertex of the suggested model is a molecular function annotated by gene ontology, and the relations among the vertex are considered as edges. Thus, it is easy to trace a specific function's transition, and it can be a constraint to extract a meaningful sub-path from whole PPI network. To evaluate the model, 11 functional flow models of Homo sapiens were built from KEGG, and Cronbach's alpha values were measured (alpha=0.67). Among 1023 functional flows, 765 functional flows showed 0.6 or higher alpha values.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.2
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• pp.72-79
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• 2003

A numerical calculation was conducted to estimate and to elucidate the role of the radiative heat flux from metal particles(Al, $Al_2O_3$) on the dynamic extinction of solid propellant rocket where the rapid depressurization took place. Anon-linear flame modeling implemented by the residence time modeling for metalized propellant was adopted to evaluate conductive heat flux to the propellant surface. The radiative heat feed back was calculated with the aid of a modified comvustion-flow model as well. The calculation results with the propellant of AP:Al:CTPB=76:10:14 had revealed that the radiative heat flux is approximately 5~6% of total flux at the critical depressurization rate regardless of chamber geometry (open or confined chamber). It was also found that the dynamic extinction in open geometry could be predicted at the depressurization rate about 45% larger with radiative heat feedback than without radiation. Thus, it should be claimed that even a small amount of radiative flux 5~6% could produce a big error in predicting the critical depressurization rate of the metalized propellant combustion.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.79-98
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• 2018

The purpose of this study is to suggest a model analysing spatio-temporal characteristics of the civil complaints for the officially assessed land price based on big data mining. Specifically, in this study, the underlying reasons for the civil complaints were found from the spatio-temporal perspectives, rather than the institutional factors, and a model was suggested monitoring a trend of the occurrence of such complaints. The official documents of 6,481 civil complaints for the officially assessed land price in the district of Jung-gu of Incheon Metropolitan City over the period from 2006 to 2015 along with their temporal and spatial poperties were collected and used for the analysis. Frequencies of major key words were examined by using a text mining method. Correlations among mafor key words were studied through the social network analysis. By calculating term frequency(TF) and term frequency-inverse document frequency(TF-IDF), which correspond to the weighted value of key words, I identified the major key words for the occurrence of the civil complaint for the officially assessed land price. Then the spatio-temporal characteristics of the civil complaints were examined by analysing hot spot based on the statistics of Getis-Ord $Gi^*$. It was found that the characteristic of civil complaints for the officially assessed land price were changing, forming a cluster that is linked spatio-temporally. Using text mining and social network analysis method, we could find out that the occurrence reason of civil complaints for the officially assessed land price could be identified quantitatively based on natural language. TF and TF-IDF, the weighted averages of key words, can be used as main explanatory variables to analyze spatio-temporal characteristics of civil complaints for the officially assessed land price since these statistics are different over time across different regions.