• Journal of Digital Convergence
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• v.18 no.2
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• pp.1-12
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• 2020

This study aimed to select and evaluate policy priorities for the expansion of public and semi-public systems for coastwise passenger transport services. For research methodology, the Consistent Fuzzy Preference Relations (CFPR) method was used to effectively extract expert knowledge. First, the result of the analysis on policy tasks for expanding the semi-public system for coastwise passenger transport services showed that "the establishment of public transportation fare system" was the most important task at 0.160. Second, "conversion of the subsidiary routes to a public system by the central government" was ranked next at the importance of 0.136. The factor named "support through proper allocation of budgets between national and local governments" are ranked third (0.119). The results of this study have practical implications in that it proposed the policy priorities for the expansion of the public semi-public systems for coastwise passenger transport services.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.59-71
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• 2019

This research is aimed to identify the building factors and deriving the importance of each factor for establishing the smart distribution center in the fourth industrial revolution era. The research methodology used CFPR(Consistent Fuzzy Preference Relations) to effectively extract expert knowledge. Research has shown as principle factors that "Service" is the first factor to be considered as 0.271, followed by "Infra(Warehouse)"(0.254), "Information System"(0.247), and "Equipment"(0.228). And as detailed factors, "Reliability" showed the highest importance as 0.091, followed "Visibility of Information System"(0.076), "Space Advancement"(0.075), "Location"(0.074) and "Satisfaction of service"(0.073). This study has implications in that it has presented an establishment direction for the smart distribution center.

• The Journal of Korean Institute of Information Technology
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• v.18 no.5
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• pp.55-64
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• 2020

Estimating the state of charge (SOC) of a battery is essential for increasing the stability and reliability of a photovoltaic system. In this study, battery SOC estimation methods were proposed using artificial neural networks (ANNs) with gradient descent (GD), Levenberg-Marquardt (LM), and scaled conjugate gradient (SCG), and an adaptive neuro-fuzzy inference system (ANFIS). The charge start voltage and the integrated charge current were used as input data and the SOC was used as output data. Four models (ANN-GD, ANN-LM, ANN-SCG, and ANFIS) were implemented for battery SOC estimation and compared using MATLAB. The experimental results revealed that battery SOC estimation using the ANFIS model had both the highest accuracy and highest convergence speed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.295-304
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• 2020

The IPCC (Intergovernmental Panel on Climate Change) recommended the importance of preventive measures against extreme weather, and heat waves are one of the main themes for establishing preventive measures. In this study, we tried to analyze the heat vulnerable areas by considering not only spatial characteristics but also social characteristics. Energy consumption, popu lation density, normalized difference vegetation index, waterfront distance, solar radiation, and road distribution were examined as variables. Then, by selecting a suitable model, SLM (Spatial Lag Model), available variables were extracted. Then, based on the Fuzzy theory, the degree of vulnerability to heat waves was analyzed for each variable, and six variables were superimposed to finally derive the heat vulnerable area. The study site was selected as the Daegu area where the effects of the heat wave were high. In the case of vulnerable areas, it was confirmed that the existing urban areas are mainly distributed in Seogu, Namgu, and Dalseogu of Daegu, which are less affected by waterside and vegetation. It was confirmed that both spatial and social characteristics should be considered in policy support for reducing heat waves in Daegu.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.123-132
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• 2017

In order to identify the factor and effect of shippers' inland transportation decision in North China and the Republic of Korea, the determinants of shipping liners, shippers and forwarders when selecting ports were extracted through previous studies and then analyzed using factor analysis and Fuzzy-AHP. As a result of analyzing the importance between groups, it can be found that while logistics costs at port and accessibility to hinterland are the most important factors for shipping liners, shippers and forwarders. Transportation cost by feeder is the most important sub factors for shipping liners. Inland transportation cost is the most important sub factors for shippers and forwarders. Through this study, it was recognized that one of the biggest concerns of shippers was reduction of inland transportation cost In addition, it was confirmed that the main factor of shifting the decision of the port selection from the shipping liners to the shipper is the reduction of inland transportation cost.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.91-100
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• 2016

The purpose of this study was to draw out success factors of port operation for New International Passenger Terminal(NIPT) in Incheon Port using the fuzzy method. In this study, the success factors of port operation were firstly selected by literature review and finally adopted them by in-depth interview with experts who had working experiences over 15 years in the field of Korea-China Carferry shipping business and stevedoring business. Success factors of port operation of the NIPT have been classified into four principal factors such as 'land's use side', 'productivity side', 'cost side' and 'services side', and the comparative analysis was conducted among success factors of port operation. According to the results of analysis, in terms of "land's use side", securing CY space of full-empty containers(0.857) was the most important factor. Among detailed factors of "productivity side", building terminal automation system(0.806) was significantly needed. In the factors of "cost side" and "service side", land rental costs(0.861) and schedule management of berth operation(0.798) were selected as the most important factors. Consequently, new international passenger terminal has implications that the main port operations should focus on reasonable rents calculation, ensuring proper space of CY, and building automation system of terminal, There is a need to proceed to conduct a comparative study of the same operating mode of an international passenger terminal.

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.49-53
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• 2017

Breast cancer is the sccond most female cancer patient in the entire female cancer patient, and has emerged as the highest contributor to female cancer deaths. If breast cancer id detected early, the cure rate is 92 percent. However, if early detection fails, breast cancer has a very high rate of metastasis. The transition from cancer to cancer has become more successful as cancer progresses. Early diagnosis of cancer is an important factor in improving quality of life. Examples of breast cancer include Mammograph, ultrasound, and Momotome. Mommography is not only painful for the examiner, but also for easy access to breast cancer exam inations. In this paper, breast cancer diagnosis data mammograph data was used. In addition, the Neural Network were classified for early diagnosis of breast cancer early using NEWFM. After learning of data using NEWFM, the accuracy of the breast cancer data classification was 84.4391%.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.217-222
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• 2011

Genetic algorithms are one of the most important methods used to solve the Traveling Salesman Problem. Therefore, many researchers have tried to improve the Genetic Algorithm by using different methods and operations in order to find the optimal solution within reasonable time. This paper intends to find a new approach that adopts an improved genetic algorithm to solve the Traveling Salesman Problem, and compare with the well known heuristic method, namely, Kohonen Self-Organizing Map by using different data sets of symmetric TSP from TSPLIB. In order to improve the search process for the optimal solution, the proposed approach consists of three strategies: two separate tour segments sets, the improved crossover operator, and the improved mutation operator. The two separate tour segments sets are construction heuristic which produces tour of the first generation with low cost. The improved crossover operator finds the candidate fine tour segments in parents and preserves them for descendants. The mutation operator is an operator which can optimize a chromosome with mutation successfully by altering the mutation probability dynamically. The two improved operators can be used to avoid the premature convergence. Simulation experiments are executed to investigate the quality of the solution and convergence speed by using a representative set of test problems taken from TSPLIB. The results of a comparison between the new approach using the improved genetic algorithm and the Kohonen Self-Organizing Map show that the new approach yields better results for problems up to 200 cities.

• Journal of Convergence for Information Technology
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• v.8 no.5
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• pp.131-135
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• 2018

The heart disease taking the second place of the cause of the death of modern people is a terrible disease that makes sudden death without noticing. To judge the aortic valve disease of heart diseases a name of disease was diagnosed using psychological data provided from physioNet. Aortic valve is a valve of the area that blood is spilled from left ventricle to aorta. Aortic stenosis of heart troubles is a disease when the valve does not open appropriately in contracting the left ventricle to aorta due to narrowed aortic valve. In this paper, 3126 samples of cardiac sound data were used as an experiment data composed of 180 characteristics including normal people and aortic valve stenosis patients. To diagnose normal and aortic valve stenosis patients, NEWFM was utilized. By using an average method of weight as an feature selection method of NEWFM, the result shows 91.0871% accuracy.

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.173-179
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• 2010

Over recent years, much research attention has been devoted to a two-factor authentication mechanism which integrates both tokenized pseudorandom numbers with user specific biometric features for biometric verification, known as Biohash. The main advantage of Biohash over sole biometrics is that Biohash is able to achieve a zero equal error rate and provide a clean separation of the genuine and imposter populations, thereby allowing elimination of false accept rates without imperiling the false reject rates. Nonetheless, when the token of a user is compromised, the recognition performance of a biometric system drops drastically. As such, a few solutions have been proposed to improve the degraded performance but such improvements appear to be insignificant. In this paper, we investigate and pinpoint the basis of such deterioration. Subsequently, we propose a two-level approach by utilizing strong inner products and fuzzy logic weighting strategies accordingly to increase the original performance of Biohash under this scenario.