• Industrial Engineering and Management Systems
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• v.9 no.2
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• pp.88-96
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• 2010

This paper presents a two-phase quantitative framework to aid the decision making process for effective selection of an efficient freight logistics hub from 8 alternatives in Thailand on the North-South economic corridor. Phase 1 employs both multiple regression and Pearson Feature selection to find the important criteria, as defined by logistics hub score, and to reduce number of criteria by eliminating the less important criteria. The result of Pearson Feature selection indicated that only 5 of 15 criteria affected the logistics hub score. Moreover, Genetic Algorithm (GA) was constructed from original 15 criteria data set to find the relationship between logistics criteria and freight logistics hub score. As a result, the statistical tools are provided the same 5 important criteria, affecting logistics hub score from GA, and data mining tool. Phase 2 performs the fuzzy stochastic AHP analysis with the five important criteria. This approach could help to gain insight into how the imprecision in judgment ratios may affect their alternatives toward the best solution and how the best alternative may be identified with certain confidence. The main objective of the paper is to find the best alternative for selecting freight logistics hub under proper criteria. The experimental results show that by using this approach, Chiang Mai province is the best place with the confidence interval 95%.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.626-632
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• 2017

Since natural disaster occurs increasingly and becomes complicated, it causes deaths, disappearances, and damage to property. As a result, there is a growing interest in the development of ICT-based natural disaster response technology which can minimize economic and social losses. In this letter, we introduce the main functions of the forest fire management platform by using images from an UAV. In addition, we propose a disaster image analysis technology based on the deep learning which is a key element technology for disaster detection. The proposed deep learning based disaster image analysis learns repeatedly generated images from the past, then it is possible to detect the disaster situation of forest-fire similar to a person. The validity of the proposed method is verified through the experimental performance of the proposed disaster image analysis technique.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.557-567
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• 2005

The increasing complexity of the socio-economic environments makes it less and less possible for single decision-maker to consider all relevant aspects of problem. Therefore are, many organizations employ groups in decision making. In this paper, we present a multiperson decision making method using fuzzy logic with linguistic quantifier when each of group members specifies imprecise judgments possibly both on performance evaluations of alternatives with respect to the multiperson criteria and on the criteria. Inexact or vague preferences have appeared in the decision making literatures with a view to relaxing the burdens of preference specifications imposed to the decision-makers and thus taking into account the vagueness of human judgments. Allowing for the types of imprecise judgments in the model, however, makes more difficult a clear selection of alternative(s) that a group wants to make. So, further interactions with the decision-makers may proceed to the extent to compensate for the initial comforts of preference specifications. These interaction may not however guarantee the selection of the best alternative to implement. To circumvent this deadlock situation, we present a procedure for obtaining a satisfying solution by the use of linguistic quantifier guided aggregation which implies fuzzy majority. This is an approach to combine a prescriptive decision method via a mathematical programming and a well-established approximate solution method to aggregate multiple objects.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.4322-4327
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• 2015

Improper backfill materials and compaction controls under pipelines have become one of the major causes of failure in many sewage pipeline systems. A study on backfill materials and compaction controls has been considered for a long time. However, structural supporters under the pipe were recently concerned because of pipeline repair and maintenance. This paper presents a prefabricated plastic foundation for supporting a sewage pipe system and increasing the performance function of the pipes. Several analytical models for the plastic foundations were investigated using finite-element program, ABAQUS, for checking safety. Comparing with the results of analyses, some of economic design sections based on the sizes of pipe diameters, 600mm, 700 and 600mm, were evaluated. These results could be applied to a pipeline system with a prefabricated plastic foundation with respect to pipe diameters and buried depths.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.6168-6175
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• 2014

Several studies regarding the effects of academic achievement on mental health problems have been conducted in adolescents but not in elementary school students. Therefore, the aim of the current study was to examine the effects of school achievement on depression in Korean elementary school students. The participants were 1,048, 5th to 6th elementary students in Seoul, Korea. The Spearman correlations between school achievement and depression were -0.31 for boys and -0.37 for girls (p<0.001 for both). After controlling for grader, the family economic status and self-esteem, higher achiever group showed a significantly low risk for depression in boys and girls. This study suggests that the lower school achievement is associated with a depressive mood in Korean elementary students. Therefore, students with lower academic performance are a risk group for depression.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.1
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• pp.78-88
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• 2012

Although structural concrete is well known for its good economic efficiency, it has limits of structural performance due to the low tensile strength, for which new structural members utilizing various concrete composite materials have been developed. Steel Fiber-Reinforced Concrete(SFRC) has great tensile strength, which is the one of the excellent composite material to complement the weakness of concrete, and it is also considered as a good alternative to prevent the explosive failure of high strength concrete under fire. Also, prestressed concrete members are of great advantages to long span structures and have greater shear strength compared to conventional reinforced concrete members. In this research, thus, a total of 22 direct shear test specimens were fabricated and tested to understand the shear behavior of Steel Fiber-Reinforced Prestressed Concrete(SFR-PSC) members, in which SFRC members combined with prestressing method. Based on the test results, the constitutive equations of shear behavior at crack interfaces were proposed, which provided good estimation on the shear behavior of the SFR-PSC direct shear test specimens.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.138-144
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• 2019

In a modern society, people are concerned seriously about their travel destinations depending on time, economic problem. In this paper, we propose an non-hierarchical clustering based hybrid recommendation using context knowledge. The proposed method is personalized way of recommended knowledge about preferred travel places according to the user's location, place, and weather. Based on 14 attributes from the data collected through the survey, users with similar characteristics are grouped using a non-hierarchical clustering based hybrid recommendation. This makes more accurate recommendation by weighting implicit and explicit data. The users can be recommended a preferred travel destination without spending unnecessary time. The performance evaluation uses accuracy, recall, F-measure. The evaluation result was shown 0.636 accuracy, 0.723 recall, and 0.676 F-measure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.1083-1088
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• 2014

Recently, due to advances in both imaging technology and ICT, various types of image processing services became available and the application services of these two technologies are diversifying. Recognition of vehicle license plates is used in places where vehicle information is needed such as in parking management. However, existing systems have economic disadvantages like issuing parking tickets and attaching unnecessary equipment. In order to solve these problems, we designed and implemented automatic parking management system through recognition of vehicle license plates by using emguCV that is based on OpenCV. Additionally, we designed improved UI to handle the entire parking management situation which include information such as details of each parking vehicle, parking time and remaining parking spaces without screen movement. This improved UI is implemented with the use of WPF which is the latest technology in user program development. The emguCV used in this paper showed the most optimized performance in Intel based environment. With it, we obtained the result of within 0.5 seconds of recognition processing time and over 90% of recognition rate. Through improved UI, the manager could both simply and intuitively manage the entire system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.8
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• pp.1340-1346
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• 2016

Utilization of Distributed Generations (DGs) using Renewable Energy Sources (RESs) has been constantly increasing as they provide a lot of environmental, economic merits. In spite of these merits, some problems with respect to voltage profile, protection and its coordination system due to reverse power flow could happen. In order to analyze and solve the problems, accurate modeling of DG systems should be preceded as a fundamental research task. In this paper, we present a PhotoVoltaic (PV) generation system which consists of practical PV cells with series and parallel resistor and an inverter for interconnection with a main distribution system. The inverter is based on controllable current source which is capable of controlling power factors, active and reactive powers within a certain limit related to amount of PV generation. To verify performance of the model, a distribution system based on actual data is modeled by using ElectroMagnetic Transient Program (EMTP) software. Computer simulations according to various conditions are also performed and it is shown from simulation results that the model presented is very effective to study DG-related researches.

• International Journal of Highway Engineering
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• v.9 no.3
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• pp.91-100
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• 2007

The most important thing for driver's safety on the road is equipment of crash cushion as a vehicle protection safety facility. But development of crash cushion is defective because there's no rational and reality way of design. And also without an alternative plan, it rely on crash test hereby it suffers a great economic loss and wastes time. This study that uses data of cash test proves the suitability of single degree of freedom which considers the safety of passengers about three-dimensional complicated Crash Analysis. As the study analyzes the conduct of crash cushion, it want to develop the effective method of design on Single Degree of Freedom Crash Cushion. And it presents the way of crash cushion design through making a crash analysis model with single degree of freedom. To verify the validness of the crash cushion plan, with single degree of freedom plan, we make the level CC2 crash cushion and execute the crash test. A performance test brings satisfied result and a plan of single degree of freedom crash cushion is proven as an one of the way to be a good system which can design crash cushion.