• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.5
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• pp.21-30
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• 2008

The fuel cell generation convert fuel source, and gas directly to electricity in an electro-chemical process. Unlike traditional and conventional turbine engines, the process of fuel cell generation do not burn the fuel and run pistons or shafts, and it has not revolutionary machine, so have fewer efficiency losses, low emissions and no noisy moving parts. A high power density allows fuel cells to be relatively compact source of electric power, beneficial in application with space constraints. In this system, the fuel cell itself is nearly small-sized by other components of the system such as the fuel reformer and power inverter. So, the fuel cell energy's stationary fuel cells produce reliable electrical power for commercial and industrial companies as well as utilities. In this paper, a fuel cell system has been modeled using PSCAD/EMTDC to analyze its electric signals and characteristics. Also the power quality of the fuel cell system has been evaluated and the problems which can be occurred during its operation have been studied by modeling it more detailed. Particularly, we have placed great importance on its power quality and signal characteristics when it is connected with a power grid.

• The Journal of Bigdata
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• v.3 no.2
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• pp.19-33
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• 2018

Owing to the increase of FTA, food trade, and versatile preferences of consumers, food import has increased at tremendous rate every year. While the inspection check of imported food accounts for about 20% of the total food import, the budget and manpower necessary for the government's import inspection control is reaching its limit. The sudden import food accidents can cause enormous social and economic losses. Therefore, predictive system to forecast the compliance of food import with its preemptive measures will greatly improve the efficiency and effectiveness of import safety control management. There has already been a huge data accumulated from the past. The processed foods account for 75% of the total food import in the import food sector. The analysis of big data and the application of analytical techniques are also used to extract meaningful information from a large amount of data. Unfortunately, not many studies have been done regarding analyzing the import food and its implication with understanding the big data of food import. In this context, this study applied a variety of classification algorithms in the field of machine learning and suggested a data preprocessing method through the generation of new derivative variables to improve the accuracy of the model. In addition, the present study compared the performance of the predictive classification algorithms with the general base classifier. The Gaussian Naïve Bayes prediction model among various base classifiers showed the best performance to detect and predict the nonconformity of imported food. In the future, it is expected that the application of the abnormality detection model using the Gaussian Naïve Bayes. The predictive model will reduce the burdens of the inspection of import food and increase the non-conformity rate, which will have a great effect on the efficiency of the food import safety control and the speed of import customs clearance.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.143-159
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• 2017

Due to the rapid development of IT in recent years, not only personal information but also the key technologies and information leakage that companies have are becoming important issues. For the enterprise, the core technology that the company possesses is a very important part for the survival of the enterprise and for the continuous competitive advantage. Recently, there have been many cases of technical infringement. Technology leaks not only cause tremendous financial losses such as falling stock prices for companies, but they also have a negative impact on corporate reputation and delays in corporate development. In the case of SMEs, where core technology is an important part of the enterprise, compared to large corporations, the preparation for technological leakage can be seen as an indispensable factor in the existence of the enterprise. As the necessity and importance of Information Security Management (ISM) is emerging, it is necessary to check and prepare for the threat of technology infringement early in the enterprise. Nevertheless, previous studies have shown that the majority of policy alternatives are represented by about 90%. As a research method, literature analysis accounted for 76% and empirical and statistical analysis accounted for a relatively low rate of 16%. For this reason, it is necessary to study the management model and prediction model to prevent leakage of technology to meet the characteristics of SMEs. In this study, before analyzing the empirical analysis, we divided the technical characteristics from the technology value perspective and the organizational factor from the technology control point based on many previous researches related to the factors affecting the technology leakage. A total of 12 related variables were selected for the two factors, and the analysis was performed with these variables. In this study, we use three - year data of "Small and Medium Enterprise Technical Statistics Survey" conducted by the Small and Medium Business Administration. Analysis data includes 30 industries based on KSIC-based 2-digit classification, and the number of companies affected by technology leakage is 415 over 3 years. Through this data, we conducted a randomized sampling in the same industry based on the KSIC in the same year, and compared with the companies (n = 415) and the unaffected firms (n = 415) 1:1 Corresponding samples were prepared and analyzed. In this research, we will conduct an empirical analysis to search for factors influencing technology leakage, and propose an early warning system through data mining. Specifically, in this study, based on the questionnaire survey of SMEs conducted by the Small and Medium Business Administration (SME), we classified the factors that affect the technology leakage of SMEs into two factors(Technology Characteristics, Organization Characteristics). And we propose a model that informs the possibility of technical infringement by using Support Vector Machine(SVM) which is one of the various techniques of data mining based on the proven factors through statistical analysis. Unlike previous studies, this study focused on the cases of various industries in many years, and it can be pointed out that the artificial intelligence model was developed through this study. In addition, since the factors are derived empirically according to the actual leakage of SME technology leakage, it will be possible to suggest to policy makers which companies should be managed from the viewpoint of technology protection. Finally, it is expected that the early warning model on the possibility of technology leakage proposed in this study will provide an opportunity to prevent technology Leakage from the viewpoint of enterprise and government in advance.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.181-193
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• 2024

The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.

• Journal of Biosystems Engineering
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• v.5 no.1
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• pp.1-14
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• 1980

Threshing operation may be one of the most important processes in the paddy post-production system as far as the grain loss and labor requirement are concerned . head-feeding type threshers commercially available now in Korea originally were developed for threshing dry paddy in the range of 15 to 17 % in wet basis. However, threshing wet-paddy with the grain moisture content above 20 % has been strongly recommended, especially for new high-yielding Indica -type varieties ; (1) to reduce high grain loss incurred due to the handling operations, and (2) to prevent the quantitative and qualitative loss of milled -rice when unthreshed grains are rewetted due to the rainfall. The objective of this study were to investigate the adaptability of both a head-feeding type thresher and a throw-in type thresher to wet-paddy , and to find out the possiblilities of improving the components of these threshers threshing. Four varieties, Suweon 264 and Milyang 24 as Tongil sister line varieties, minehikari and Jinhueng as Japonica-type varieties, were used at the different levels of the moisture content of grains. Both the feed rate and the cylinder speed were varied for each material and each machine. The thresher output quality , composition of tailing return, and separating loss were analyzed from the sampels taken at each treatment. A separate experiment for measurement opf the power requirement of the head-feeding type thresher was also performed. The results are summarized as follows : 1. There was a difference in the thresher output quality between rice varieties. In case of wet-paddy threshing at 550 rpm , grains with branchlet and torn heads for the Suweon 264 were 12 % and 7 % of the total output in weight, respectively, and for the Minehikari 4.5 % and 2 % respectively. In case of dry paddy threshing , those for the Suweon 264 were 8 % and 5% , and for the Minehikari 4% and 1% respectively. However, those for the Milyang 23 , which is highly susceptable to shattering, were much lower with 1 % and 0.5% respectively, regardless of the moisture content of the paddy. Therefore, it is desirable to breed rice varieties of the same physical properties as well as to improve a thresher adaptable to all the varieties. Torn heads, which increased with the moisture content of rall the varieties except the Milyang 23 , decreased as the cylinder speed increased, but grains with branchlet didnt decrease. The damaged kernels increased with the cylinder speed. 3. The thresher output quality was not affected much by the feed rate. But grains with branchlet and torn heads increased slightly with the feed rate for the head-feeding type thresher since higher resistance lowered at the cylinder speed. 4. In order to reduce grains with branchlet and torn heads in wet-paddy threshing , it is desirable to improve the head-feeding type thresher by developing a new type of cylinder which to not give excess impact on kernels or a concave which has differenct sizes of holes at different locations along the cylinder. 5. For the head-feeding type thresher, there was a difference in separating loss between the varieties. At the cylinder speed of 600 rpm the separating losses for the Minehikari and the Suweon 264 were 1.2% and 0.6% respectively. The separating loss of the head-feeding type thresher was not affected by the moisture content of paddy while that of the Mini-aged thresher increased with the moisture content. 6. From the analysis of the tailings return , to appeared that the tailings return mechanism didn't function properly because lots of single grains and rubbishes were unnecessarily returned. 7. Adding a vibrating sieve to the head-feeding type thresher could increase the efficiency of separation. Consequently , the tailing return mechanism would function properly since unnecessary return could be educed greatly. 8. The power required for the head-feeding type thresher was not affected by the moisture content of paddy, but the average power increased linearly with the feed rate. The power also increased with the cylinder speed.