• Proceedings of the KWS Conference
• /
• 2009.11a
• /
• pp.14-14
• /
• 2009

자동차 차체와 같은 박판을 접합하기 위해서 인버터 DC 저항 점 용접공정은 매우 널리 사용되어지고 있다. 이는 교류 용접에 비해 적은 전류로 용접이 가능하고, 더 넓은 적정 용접 영역을 가지며, 보다 적은 전극마모를 가지는 인버터 DC 저항 점용접의 특성에 기인한다. 아울러 최근에는 파워 소자와 같은 인버터 구성에 필요한 구성 요소의 가격이 낮아져, 전반적으로 용접기의 가격이 하락하였고, 구성 장치에 대한 신뢰성이 증가하였으며, 기존보다 전력의 사용량이 감소하여 인버터 DC 저항점 용접공정의 사용이 더욱 증가하고 있는 상황이다. 또한 차량의 경량화에 대한 요구가 증가함에 따라 고 장력 강판의 적용이 확대되고 있다. 이러한 재료의 우수한 용접을 위해 인버터 DC 저항 점 용접시스템의 개발이 더욱 활발하게 이루어지고 있다. 하지만 인버터 DC 저항 점용접 시스템을 구성하더라도 모재의 특성이 전류 파형에 영향을 주게 되어, 정 전류 제어가 적용되지 못하면 전류 파형이 불안정해지게 되고 원하는 전류가 발생되지 않게 되어 스패터가 발생하거나, 용접 품질에 영향을 줄 수 있게 된다. 본 연구에서는 인버터 DC 저항 점용접 시스템을 구성하고, 정 전류의 제어를 위한 퍼지 제어 알고리즘을 개발하여 적용하였다. 퍼지제어기의 환산 계수를 최적화하기 위해서 유전 알고리즘을 적용하였으며, 실험에는 고장력강을 대상으로 정 전류 용접 공정을 수행하였다.

• Journal of Internet Computing and Services
• /
• v.8 no.1
• /
• pp.1-14
• /
• 2007

IF handoff events are occurred during the transmission of multimedia traffic, the efficient resource allocation and handoff procedures are necessary to maintain the same QoS of transmitted multimedia traffic because the QoS may be defected by some delay and information loss, This paper proposes a handoff scheme to accommodate multimedia traffic based on the resource reservation procedure using direction estimation, This scheme uses a novel mobile tracking method based on Fuzzy Multi Criteria Decision Making, in which uncertain parameters such as PSS (Pilot Signal Strength), the distance between the mobile and the base station, the moving direction, and the previous location are used in the decision process using the aggregation function in fuzzy set theory, With the position information, the moving direction is determined, The handoff requests for real time sessions are handled based on the direction prediction and the resource reservation scheme, The resources in the estimated adjacent cells should be reserved and allocated to guarantee the continuity of the real time sessions, Through simulation results, we show that our proposed resource reservation method provides a better performance than that of the conventional method.

• Journal of Navigation and Port Research
• /
• v.27 no.5
• /
• pp.569-576
• /
• 2003

Although the Free Trade Zone(FTZ) are actually competing with various strategies, the definition and structural understanding of activation strategies are not known very much Therefore this study has launched from this fact, and has the objective of obtaining the structural model for activation strategies in Gunsan FTZ, and understanding the components of activation in these region The process began by abstracting the components that composed the success factors in FTZ through recent research, and grouping it by the most core components. Also, by using the FSM(Fuzzy Structural Modeling) method to understand the structure of the grouped components, and the structural model for activation of FTZ was able to obtain as the result. When analyzing the obtained structural model, expansion of tax reduction, flexibility of law systems and good business environment came out to be the most important component groups, and especially flexibility of law systems and good business environment were the most effective component that effected all the other components overall.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.11
• /
• pp.1049-1057
• /
• 2020

The shift from elite education to mass education in Vietnam has met the demand for education for everybody as well as for quality human resource talent for an emerging nation. Under the resource constraint, understanding the quality dimensions of education and its priority level is important for effective and efficient policies. This study was carried out using both qualitative and quantitative methodologies to develop quality criteria and a ranking model. Two rounds of in-depth interviews were conducted with fifteen experts in the field, who were rectors, employers, and recruitment specialists to develop the quality framework applied in Vietnamese universities under total quality management (TQM), starting from the input of the senior secondary school leavers, through a teaching process to the output. The first round of interviews were unstructured questionnaires designed to explore the main factors in quality assessment model. The second round affirmed the experts' agreement on the assessment model. Then, fuzzy logic was applied to rank eight criteria in the quality assessment model into priority order: cost, teaching and administrative staff, leadership, curriculum, student-related factors, internationalization, admissions, and campus. The results are critical for identifying the necessary actions to enhance the education quality and to further research on the optimal quality model.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.5
• /
• pp.437-443
• /
• 2015

This paper presents face recognition based on the fusion of visible image and thermal infrared (IR) texture estimated from the face image in the visible spectrum. The proposed face recognition scheme uses a multi- layer neural network to estimate thermal texture from visible imagery. In the training process, a set of visible and thermal IR image pairs are used to determine the parameters of the neural network to learn a complex mapping from a visible image to its thermal texture in the low-dimensional feature space. The trained neural network estimates the principal components of the thermal texture corresponding to the input visible image. Extensive experiments on face recognition were performed using two popular face recognition algorithms, Eigenfaces and Fisherfaces for NIST/Equinox database for benchmarking. The fusion of visible image and thermal IR texture demonstrated improved face recognition accuracies over conventional face recognition in terms of receiver operating characteristics (ROC) as well as first matching performances.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.49 no.2
• /
• pp.38-43
• /
• 2012

It is necessary to measure cracks on concrete slab surface accurately in concrete structure maintenance for the stability of the structure. However, in real world, the process is done by time consuming and ineffective manual inspection. Although there have been some studies to provide computerized inspection methods, they are vulnerable to rugged surface or noise due to the influence of the light or environmental reasons. In this paper, we propose a new method that extracts not only undistorted cracks but minute cracks that were often regarded as noise. We extract candidate crack areas by applying fuzzy method with R, G, and B channel values of concrete slab structure. Then further refinement processes are performed with SOM algorithm and density based cutoff to remove noise. Experiment verifies that the proposed method is sufficiently useful in various crack images.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.2
• /
• pp.436-444
• /
• 2010

In this study, we introduce and discuss a concept of a granular-oriented radial basis function neural networks (GRBF NNs). In contrast to the typical architectures encountered in radial basis function neural networks(RBF NNs), our main objective is to develop a design strategy of GRBF NNs as follows : (a) The architecture of the network is fully reflective of the structure encountered in the training data which are granulated with the aid of clustering techniques. More specifically, the output space is granulated with use of K-Means clustering while the information granules in the multidimensional input space are formed by using a so-called context-based Fuzzy C-Means which takes into account the structure being already formed in the output space, (b) The innovative development facet of the network involves a dynamic reduction of dimensionality of the input space in which the information granules are formed in the subspace of the overall input space which is formed by selecting a suitable subset of input variables so that the this subspace retains the structure of the entire space. As this search is of combinatorial character, we use the technique of genetic optimization to determine the optimal input subspaces. A series of numeric studies exploiting some nonlinear process data and a dataset coming from the machine learning repository provide a detailed insight into the nature of the algorithm and its parameters as well as offer some comparative analysis.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.1
• /
• pp.11-19
• /
• 2013

For an autonomous multi-mobile robot system, path planning and collision avoidance are important functions used to perform a given task collaboratively and cooperatively. This study considers these important and challenging problems. The proposed approach is based on a potential field method and fuzzy logic system. First, a global path planner selects the paths of the robots that minimize the cost function from each robot to its own target using a potential field. Then, a local path planner modifies the path and orientation from the global planner to avoid collisions with static and dynamic obstacles using a fuzzy logic system. In this paper, each robot independently selects its destination and considers other robots as dynamic obstacles, and there is no need to predict the motion of obstacles. This process continues until the corresponding target of each robot is found. To test this method, an autonomous multi-mobile robot simulator (AMMRS) is developed, and both simulation-based and experimental results are given. The results show that the path planning and collision avoidance strategies are effective and useful for multi-mobile robot systems.

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

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.9
• /
• pp.2183-2188
• /
• 2009

This paper describes an automatic mesh generation system for finite element analysis of three-dimensional cracks. It is consisting of fuzzy knowledge processing, bubble meshing and solid geometry modeler. This novel mesh generation process consists of three sub-processes: (a) definition of geometric model, i.e. analysis model, (b) generation of bubbles, and (c) generation of elements. One of commercial solid modelers is employed for three-dimensional crack structures. Bubble is generated if its distance from existing bubble points is similar to the bubble spacing function at the point. The bubble spacing function is well controlled by the fuzzy knowledge processing. The Delaunay method is introduced as a basic tool for element generation. Practical performances of the present system are demonstrated through several mesh generations for 3D cracks.