• Journal of The Korean Association For Science Education
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• v.26 no.1
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• pp.1-8
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• 2006

This study investigated the causal relationships between high school student multiple-choice algorithmic chemistry problem solving and 1) the motivational variables of achievement goal (task goal/performance goal/performance-avoidance) and perceived ability, and 2) the cognitive variables of learning strategy (deep learning/surface learning) and self-regulation. Path analysis supported a causal model in which perceived ability and task goal were found to positively influence algorithmic chemistry problem-solving ability via self-regulation. In particular it was found that perceived ability directly influenced algorithmic chemistry problem-solving ability. Moreover, deep learning was found to have been influenced by perceived ability and task goal, while surface learning was influenced by performance-avoidance goal. Lastly, there did not appear to be any causal relationship between learning strategy and algorithmic chemistry problem-solving ability.

• Computers and Concrete
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• v.26 no.4
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• pp.351-365
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• 2020

This work presents numerical and experimental analyses of the behavior of reinforced-concrete deep beams with unconventional geometries. The main goal here is to experimentally and numerically study these geometries to find possible new behaviors due to the material nonlinearity of reinforced concrete with complex geometries. Usually, unconventional geometries result from innovative designs; in general, studies of reinforced concrete structures are performed only on conventional members such as beams, columns, and labs. To achieve the goal, four reinforced-concrete deep beams with geometries not addressed in the literature were tested. The models were numerically analyzed with the Adaptive Micro Truss Model (AMTM), which is the proposed method, to address new geometries. This work also studied the main parameters of the constitutive model of concrete based on a statistical analysis of the finite element (FE) results. To estimate the ultimate loads, FE simulations were performed using the Monte Carlo method. Based on the obtained ultimate loads, a probabilistic distribution was created, and the final ultimate loads were computed.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1601-1604
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• 1997

The most important topic in research of mobile robot is path planning in order to avoid with obstacle. In this study the path planning algorithm using a neural network model is proposed. The inputs of neural network are range data which are acquired form laser range finderm and weights are based on difference with goal direction. The thresholds are made by consdiering the marginal distance between mobile robot and obstacle. Consequently the outputs are obtained by multiplying input and weight. The obtained heading directiion enables the mobile robot to approach the goal, without any collision with obstacles around. The effectiveness of the this method of real-time navigation of a mobile robot is estimated by computer simulation in complex environment.

• Journal of Korean Society for Quality Management
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• v.35 no.4
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• pp.38-51
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• 2007

The House of Quality(HOQ) is used in the development stage to identify important customer attributes and corresponding engineering characteristics. The importance of each customer attribute obtained in the HOQ affects to the quality of the final product or service. Traditionally, such importance is derived based on the assumption that customer satisfaction is linearly proportional to the product performance. In this paper, we propose a nonlinear function so as to relate the product performance with the customer satisfaction according to the Kano model. A performance goal is obtained by maximizing the total customer satisfaction under a cost constraint and the importance of each customer attribute is developed from the performance goal. Therefore, the proposed approach incorporates the Kano categories and the improvement cost in determining the importance of customer attributes.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.6
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• pp.386-394
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• 2016

In this research, in order to optimize the multi-objective function effectively, we suggested the optimization model to maximize the total destruction of ground targets and minimize the total damage of aircrafts and cost of air munitions by using goal programming. To satisfy the various variables and constraints of this mathematical model, the concept of air strike package is applied. As a consequence, effective attack can be possible by identifying the prior ground targets more quickly. This study can contribute to maximize the ROK air force's combat power and preservation of high value air asset in the war.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.431-434
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• 2003

This research developed a method for the estimation of groundwater recharge by yielding daily soil moisture content and watershed evapotranspiration from the water balance concept of the unsaturated and saturated layers in rainfall-runoff model called DAWAST. The goal of the research is to estimate the groundwater recharge fulfilling conditions of the safe discharge for any season. To meet this goal, the data of groundwater level and stream flow rate have been monitored in a study area and used to validate the model.

• The Journal of Information Systems
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• v.10 no.2
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• pp.5-32
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• 2001

The main goal of this research is at the development of a bundle product suggestion sub-system of an internet shopping mall for fishery products, which can reduce the search cost of user. To achieve the goal, we first study tie key factors of successful direct commerce for fishery products, and second, we design a bundle product suggestion module and its sub-module. For this, we identify the objectives of system, and write out the necessary functions of the system and models(process model, data model, dynamic model) through the analysis of user requirements. Based on the functions and models, we design user interfaces, database, processes, and knowledge base. In designing knowledge base and inferencing strategy, we consider two intelligent agent approach(optimal algorithms, heuristic rules) and suggest one more approach(case-based reasoning). The intelligent agent can be used in enhancing the suggestion of multiple fishery product simultaneously. The system analysis and design documents presented as the research results can be used to provide good guidelines to the companies who consider developing an production suggestion agents.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.10
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• pp.584-592
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• 2003

This paper presents a fuzzy-GA method for the allocation and operation of dispersed generator systems(DGs) based on load model in composite distribution systems. Groups of each individual load model consist of residential, industrial, commercial, official and agricultural load. The problem formulation considers an objective to reduce power loss of distribution systems and the constraints such as the number or total capacity of DGs and the deviation of the bus voltage. The main idea of solving fuzzy goal programming is to transform the original objective function and constraints into the equivalent multi-objectives functions with fuzzy sets to evaluate their imprecise nature for the criterion of power loss minimization, the number or total capacity of DGs and the bus voltage deviation, and then solve the problem using genetic algorithm. The method proposed is applied to IEEE 12 bus and 33 bus test systems to demonstrate its effectiveness. .

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.101-102
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• 2014

Results of Investment mean not results of procedure but the final goal of an organization. That is to say, results focus on success or failure of investment. So, cost effectiveness means financial cost that is affected in order to attain the output of organizational goal. Many enterprises are investing in developing and redeveloping various projects of information systems. But, it is not generally considered to check values with monitoring and evaluating their projects. We propose a new value model for information systems investment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.3
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• pp.98-108
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• 2005

The assembly line balancing problem has been focused by many research works because the efficient management of the assembly line might influence not only the quality of the products but also the working conditions for the workers. This paper deals with U-shape mixed-model assembly line balancing and considers both the processing time and the physical workloads. We suggest the goal programming approach for this situation and to overcome some difficulties of finding optimal solution, we adopt the genetic algorithm that is one of the most promising solution techniques. We tested several test problems and present the results that indicate some improvement for the line balancing as well as the stable performance of the algorithm.