• Journal of Korea Society of Industrial Information Systems
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• v.6 no.2
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• pp.63-73
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• 2001

An alternative approach to formulating a special class of linear goal programming (LGP) models is presented. We propose a formulation of the LGP model that can include the decision variables in the objective function. We specifically propose that the position of the decision variables in the objective function be used to eliminate goal constraints whose sole purpose is to indirectly optimize decision variables. For the select group of LGP problems wherever indirect optimization of decision variables are sought, the alternative LGP model formulation is able to reduce the size of these LGP models and in turn the computational effort required for their solution.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.235-244
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• 2022

Many new techniques have been adopted in HEVC (High efficiency video coding) standard, such as quadtree-structured coding unit (CU), prediction unit (PU) partition, 35 intra-mode, and so on. To reduce computational complexity, the paper proposes two optimization algorithms which include fast CU depth range decision and fast PU partition mode decision. Firstly, depth range of CU is predicted according to spatial-temporal correlation. Secondly, we utilize the depth difference between the current CU and CU corresponding to the same position of adjacent frame for PU mode range selection. The number of traversal candidate modes is reduced. The experiment result shows the proposed algorithm obtains a lot of time reducing, and the loss of coding efficiency is inappreciable.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.81-96
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• 2007

The headline of advertisements holds the important position in advertisement recognition and receptivity. In this paper, we classified the headlines as several types with measuring the response effects for purpose of understanding the customer's behavior. Also we conducted the decision tree analysis and correspondence analysis. The decision tree shows the difference between responders and non-responders, and the correspondence analysis shows the relationship between the sales and the customer's demographic information.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.1
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• pp.201-206
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• 1994

The linear search problem is concerned with finding a hiden target on the real line R. The position of the target governed by some probability distribution. It is desired to find the target in the least expected search time. This problem has been formulated as an optimization problem by a number of authors without making use of Markov Decision Process (MDP) theory. It is the aim of the paper to give a (MDP) formulation to the search problem which we feel is both natural and easy to follow.

• Smart Media Journal
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• v.13 no.1
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• pp.24-35
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• 2024

The combination of Artificial Intelligence and the Internet of Things (AIoT) has gained significant popularity. Deep neural networks (DNNs) have demonstrated remarkable success in various applications. However, deploying complex AI models on embedded boards can pose challenges due to computational limitations and model complexity. This paper presents an AIoT-based system for smart parking lots using edge devices. Our approach involves developing a detection model and a decision tree for occupancy status classification. Specifically, we utilize YOLOv5 for car license plate (LP) detection by verifying the position of the license plate within the parking space.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.5
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• pp.766-776
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• 2008

The purpose of this study was 1) to identify the reasons for delay of decision making and the shopping information in internet shopping, 2) to classify consumers based on the clothing benefits, 3) and to examine the differences among consumer groups in the reasons for delay of decision making and the shopping information. The data were collected from a sample of 500 internet shopper aged from 20 to 40. This study used factor analysis, multiple regression analysis, Pearson's correlation analysis, cluster analysis and ANOVA. The results showed that the reasons for delay of decision making consisted of eight factors: Performance risk, Comparison shopping, Economic shopping, Social risk, Uncertainty, Expecting of market change, Product unsatisfaction, Passive shopping. The shopping information consisted of three factors: Product variety, Product information, Additional information. Five factors of clothing benefits were Economy, Figure compensation, Social position, Individuality, and Comfort. The respondents were classified into four groups by five factors of clothing benefits; Individuality seeking group, Low-benefits seeking group, Economy seeking group, Figure compensation/comfort seeking group. There were significant differences among groups in the reasons for delay of decision making and the shopping information among groups. Therefore, marketers need to provide different shopping information for delay closure by target groups.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.4
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• pp.113-131
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• 2015

Decision effectiveness depends on type of knowledge within team members generated by decision making process. Thus, organization in accordance with teams' experience and capability ultimately achieve their desired outcome. However, previous research has not addressed a mediating role between different knowledge type in decision making and product competitive advantages(pioneering advantage and product quality superiority). Based on the knowledge-based view, we model how different knowledge characteristics in decision making affect to acquire each of knowledge in decision making effectively and then to apply acquired knowledge in decision making. Anchored in a source-position-performance (SPP) framework (Day and Wensley's, 1988), we shed light on the effects of three knowledge characteristics dimensions in decision making process on knowledge management competences in decision making for a new product project. We also examine the relationship between two dimensions of NPD knowledge management competences, and product competitive advantages which consist of market pioneering advantage and product quality superiority. To test the relationships, the empirical analyses are conducted using a sample of team managers who participated in NPD projects. This study suggest that managers should increase their acquirability and applicability of knowledge by integrating complexity of diverse and new knowledge, developing codifiability of well-documented knowledge, and creating the sharing common knowledge among NPD team members. Thus, they are able to outrun major competitors in terms of pioneering advantage and product quality superiority perspective.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.181-183
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• 1996

Generally, While position type fuzzy controller has good performance in transient period, it has uniform steady state error of response. While velocity type fuzzy controller is capable of reducing steady state error of response, it is hard to develop the performance in transient period. In order to have both good performance in transient period and ability to reduce the steady state error of response, weighting fuzzy controller, which is composed of these two fuzzy controllers, is proposed. For the decision of weight to each fuzzy controller, Weighting fuzzy set is established according to the system state variables and applied to each fuzzy controller. The proposed weighted fuzzy controller has the merits of both position type fuzzy controller and velocity type fuzzy controller simultaneously.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.164-167
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• 2004

In the paper is proposed a hierarchical adaptive fuzzy controller for balancing and position control of the inverted pendulum system. Because balancing control rules of the pendulum and position control rules of the cart can be opposite, it is difficult to design an adaptive fuzzy controller that satisfy both objectives. To stabilize the pendulum at a specified position, the hierarchical adaptive fuzzy controller consists of a robust indirect adaptive fuzzy controller for balancing, a forced disturbance generator which emulates heuristic control strategy, and a supervisory decision maker for the arbitration of two control objectives It is proved that all the signals in the overall system are bounded. Simulation results are given to verify the proposed adapt i ye fuzzy control method.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.3
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• pp.313-324
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• 1996

A new policy to determine the waiting position of an idle Automated Guided Vehicle(AGV) is proposed and its performance is compared with the existing waiting position policies. Unlike the existing policies, the queue length in the input buffer is considered in the new policy. As a result, the waiting position based on the new policy depends on the status of the system. The simulation result indicates that the proposed policy reduces the waiting time in both the input and the output buffers significantly, regardless of the number of AGVs in the system. Therefore, the manufacturing lead time can be minimized.