• Journal of Computational Design and Engineering
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• v.2 no.3
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• pp.157-164
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• 2015

This paper discusses an optimization-based approach for the design of a product platform for industrial three-axis linear-type robots, which are widely used for handling objects in manufacturing lines. Since the operational specifications of these robots, such as operation speed, working distance and orientation, weight and shape of loads, etc., will vary for different applications, robotic system vendors must provide various types of robots efficiently and effectively to meet a range of market needs. A promising step toward this goal is the concept of a product platform, in which several key elements are commonly used across a series of products, which can then be customized for individual requirements. However the design of a product platform is more complicated than that of each product, due to the need to optimize the design across many products. This paper proposes an optimization-based fundamental framework toward the design of a product platform for industrial three-axis linear-type robots; this framework allows the solution of a complicated design problem and builds an optimal design method of fundamental features of robot frames that are commonly used for a wide range of robots. In this formulation, some key performance metrics of the robot are estimated by a reducedorder model which is configured with beam theory. A multi-objective optimization problem is formulated to represent the trade-offs among key design parameters using a weighted-sum form for a single product. This formulation is integrated into a mini-max type optimization problem across a series of robots as an optimal design formulation for the product platform. Some case studies of optimal platform design for industrial three-axis linear-type robots are presented to demonstrate the applications of a genetic algorithm to such mathematical models.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.489-496
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• 2006

The random-based cleaning algorithm is a simple algorithm widely used in commercial vacuum cleaning robots. This algorithm has two limitations, that is, cleaning takes a long time and there is no guarantee that the cleaning will cover the whole cleaning area. This has lead to customer dissatisfaction. Thus, in recent years, many intelligent cleaning algorithms that takes into consideration information gathered from the cleaning area environment have been proposed. The plowing-based algorithm, which is the most efficient algorithm known to date when there are no obstacles in the cleaning area, has a deficiency that when obstacle prevail, its performance is not guaranteed. In this paper, we propose the Group-k algorithm that is efficient for that situation, that is, when obstacle prevail. The goal is not to complete the cleaning as soon as possible, but to clean the majority of the cleaning area as fast as possible. The motivation behind this is that areas close to obstacles are usually difficult for robots to handle, and hence, many require human assistance anyway In our approach, obstacles are grouped by the complexity of the obstacles, which we refer to as 'complex rank', and then decide the cleaning route based on this complex rank. Results from our simulation-based experiments show that although the cleaning completion time takes longer than the plowing-based algorithm, the Group-k algorithm cleans the majority of the cleaning area faster than the plowing algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.133-140
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• 2018

In this study, a correlation between execution of quality management activities and their results was verified by applying the Malcolm Baldrige model (hereafter referred to as the MB model) as a quality management performance measurement indicator for small and medium enterprises (SMEs) in South Korea. To achieve this goal, we need to determine whether the categorical requirements in the MB model are recognized consistently in SMEs, as a prerequisite. To this end, factor analysis was conducted for measurement variables in each category, which revealed that the process indicator was made up of six factors and the outcome indicator was made up of five factors, like those configured in the MB model. This result can be interpreted to mean that the requirements in each category of the MB model were well produced and recognized consistently throughout SMEs in South Korea. In addition, the analysis of causality between the process indicator (quality management activities) and the outcome indicator (management results) showed high causality between them. Although the quality management levels of SMEs in South Korea are inferior to those of conglomerates or other national quality award-winning companies, this study is significant in that the causality between quality management activities and results was verified, since this study targeted SMEs in South Korea as the target of investigation. Thus, it is empirically proven that the MB model can contribute to improved management results for SMEs in Korea.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.56-63
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• 2015

Several fields of science have demanded large-scale workflow support, which requires thousands of CPU cores or more. In order to support such large-scale scientific workflows, high capacity parallel systems such as supercomputers are widely used. In order to increase the utilization of these systems, most schedulers use backfilling policy: Small jobs are moved ahead to fill in holes in the schedule when large jobs do not delay. Since an estimate of the runtime is necessary for backfilling, most parallel systems use user's estimated runtime. However, it is found to be extremely inaccurate because users overestimate their jobs. Therefore, in this paper, we propose a novel system for the runtime prediction based on workload-aware clustering with the goal of improving prediction performance. The proposed method for runtime prediction of parallel applications consists of three main phases. First, a feature selection based on factor analysis is performed to identify important input features. Then, it performs a clustering analysis of history data based on self-organizing map which is followed by hierarchical clustering for finding the clustering boundaries from the weight vectors. Finally, prediction models are constructed using support vector regression with the clustered workload data. Multiple prediction models for each clustered data pattern can reduce the error rate compared with a single model for the whole data pattern. In the experiments, we use workload logs on parallel systems (i.e., iPSC, LANL-CM5, SDSC-Par95, SDSC-Par96, and CTC-SP2) to evaluate the effectiveness of our approach. Comparing with other techniques, experimental results show that the proposed method improves the accuracy up to 69.08%.

• Journal of Practical Engineering Education
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• v.11 no.1
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• pp.25-31
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• 2019

The purpose of this study is to investigate the difference between motivation and learning strategies of students who have received academic probation and who have not while attending engineering college. The subjects of this study were engineering college students in Seoul and they participated in the learning strategy test at the teaching and learning center. The subjects of this study were 553 students, 22 of whom received academic probation and 531 didn't. In order to achieve the purpose of this study, we used MLST (Multi-dimensional Learning Strategy test) learning strategy checklists of Korea Guidance, which is a standardized test. A t-test was conducted to compare motivational and learning strategies between students with and without academic probation. As a result, the motivation score of the students with the academic probation was lower than that of those without the academic probation, and the score of the time management and note taking factors of the students with the academic probation were lower than those of the students without the academic probation.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.140-140
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• 2021

Urban flood management is a crucial and challenging task, particularly in developed cities. Therefore, accurate prediction of urban flooding under heavy precipitation is critically important to address such a challenge. In recent years, machine learning techniques have received considerable attention for their strong learning ability and suitability for modeling complex and nonlinear hydrological processes. Moreover, a survey of the published literature finds that hybrid computational intelligent methods using nature-inspired algorithms have been increasingly employed to predict or simulate the streamflow with high reliability. The present study is aimed to propose a novel approach, an ensemble tree, Bayesian Additive Regression Trees (BART) model incorporating a nature-inspired algorithm to predict hourly multi-step ahead streamflow. For this reason, a hybrid intelligent model was developed, namely GA-BART, containing BART model integrating with Genetic algorithm (GA). The Jungrang urban basin located in Seoul, South Korea, was selected as a case study for the purpose. A database was established based on 39 heavy rainfall events during 2003 and 2020 that collected from the rain gauges and monitoring stations system in the basin. For the goal of this study, the different step ahead models will be developed based in the methods, including 1-hour, 2-hour, 3-hour, 4-hour, 5-hour, and 6-hour step ahead streamflow predictions. In addition, the comparison of the hybrid BART model with a baseline model such as super vector regression models is examined in this study. It is expected that the hybrid BART model has a robust performance and can be an optional choice in streamflow forecasting for urban basins.

• (The) Research of the performance art and culture
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• no.41
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• pp.5-38
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• 2020

The current state of performance halls in South Korea is closely related to the performance art and culture of the nation as the culture of putting on and enjoying a performance is deeply rooted in public culture and arts halls representing each area at the local government level. Today, public culture and arts halls have multiple management purposes, and the subjects of their management are in the public domain including the central and local governments or investment and donation foundations in overwhelming cases. Public culture and arts halls thus have close correlations with the institutional aspect of cultural policies as the objects of culture and art policies at the central and local government level. The full-blown era of public culture and arts halls opened up in the 1980s~1990s, during which multi-purpose performance halls of a similar structure became universal around the nation. Public culture and arts halls of the uniform shape were distributed around the nation with no premise of genre characteristics or local environments for arts, and this was attributed to the cultural policies of the military regime. The Park Chung-hee regime proclaimed Yusin that was beyond the Constitution and enacted the Culture and Arts Promotion Act(September, 1972), which was the first culture and arts act in the nation. Based on the act, a five-year plan for the promotion of culture and arts(1973) was made and led to the construction of cultural facilities. "Public culture and arts" halls or "culture" halls were built to serve multiple purposes around the nation because the Culture and Arts Promotion Act, which is called the starting point of the nation's legal system for culture and arts, defined "culture and arts" as "matters regarding literature, art, music, entertainment, and publications." The definition became a ground for the current "multi-purpose" concept. The organization of Ministry of Culture and Public Information set up a culture and administration system to state its supervision of "culture and arts" and distinguish popular culture from the promotion of arts. During the period, former President Park exhibited his perception of "culture=arts=culture and arts" in his speeches. Arts belonged to the category of culture, but it was considered as "culture and arts." There was no department devoted to arts policies when the act was enacted with a broad scope of culture accepted. This ambiguity worked as a mechanism to mobilize arts in ideological utilizations as a policy. Against this backdrop, the Sejong Center for the Performing Arts, a multi-purpose performance hall, was established in 1978 based on the Culture and Arts Promotion Act under the supervision of Ministry of Culture and Public Information. There were, however, conflicts of value over the issue of accepting the popular music among the "culture and arts = multiple purposes" of the system, "culture ≠ arts" of the cultural organization that pushed forward its establishment, and "culture and arts = arts" perceived by the powerful class. The new military regime seized power after Coup d'état of December 12, 1979 and failed at its culture policy of bringing the resistance force within the system. It tried to differentiate itself from the Park regime by converting the perception into "expansion of opportunities for the people to enjoy culture" to gain people's supports both from the side of resistance and that of support. For the Chun Doo-hwan regime, differentiating itself from the previous regime was to secure legitimacy. Expansion of opportunities to enjoy culture was pushed forward at the level of national distribution. This approach thus failed to settle down as a long-term policy of arts development, and the military regime tried to secure its legitimacy through the symbolism of hardware. During the period, the institutional ground for public culture and arts halls was based on the definition of "culture and arts" in the Culture and Arts Promotion Act enacted under the Yusin system of the Park regime. The "multi-purpose" concept, which was the management goal of public performance halls, was born based on this. In this context of the times, proscenium performance halls of a similar structure and public culture and arts halls with a similar management goal were established around the nation, leading to today's performance art and culture in the nation.

• Journal of dental hygiene science
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• v.12 no.4
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• pp.375-382
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• 2012

This research will target the Dental Hygienics students to identify the level and type of the $2{\times}2$ achievement target orientation, and will study how this achievement target orientation is related to the Self-Regulated Learning, as well as the effect on the each sub elements of the Self-Regulated Learning (SRL). Among the $2{\times}2$ achievement target orientation of all the female university students, the skillful approach was found to be highest. In case of the adjustment of the motivation following grade, intrinsic value of the 1st grader was higher than the intrinsic value of the 2nd and 3rd graders. As for the behavior adjustment, the 3rd grader's time and studying adjustment were found to be higher. Mean while, pursuit of the cooperation was found to be high compared to the time and studying adjustment of the1st and 2nd graders. Second, intrinsic value, overt goal orientation, and studying environment adjustment among the SRL's subelements, manifested significant correlation with all the sub elements of the $2{\times}2$ achievement target orientation. As for the elements that affected cognition adjustment, grade and skillful approach were found to exert significant effect on the performance adjustment. As for the element that affects behavior adjustment, grade and skillful approach exerted significant effect on the sub elements of the behavior adjustment. Analysis on the effect of the achievement target orientation and SRL implies that the direction of the students' learning goal can be modified and that they can learn effectively by using the SRL appropriately. When the two elements are factored in carefully, the key findings could serve as a base data that can motivate the students, inducing effective learning process.

• Journal of KIISE:Databases
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• v.35 no.6
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• pp.505-517
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• 2008

This paper proposes a rewriting algorithm of OWL-DL ontology query in SPARQL. Currently, to obtain inference results of given SPARQL queries, Web ontology repositories construct inference ontology models and match the SPARQL queries with the models. However, an inference model requires much larger space than its original base model, and reusability of the model is not available for other inferrable SPARQL queries. Therefore, the aforementioned approach is not suitable for large scale SPARQL query processing. To resolve tills issue, this paper proposes a novel SPARQL query rewriting algorithm that can obtain results by rewriting SPARQL queries and accomplishing query operations against the base ontology model. To achieve this goal, we first define OWL-DL inference rules and apply them on rewriting graph pattern in queries. The paper categorizes the inference rules and discusses on how these rules affect the query rewriting. To show the advantages of our proposal, a prototype system based on lena is implemented. For comparative evaluation, we conduct an experiment with a set of test queries and compare of our proposal with the previous approach. The evaluation result showed the proposed algorithm supports an improved performance in efficiency of the inferrable SPARQL query processing without loss of completeness and soundness.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.3
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• pp.281-285
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• 2008

Wireless sensor networks are closely related with the geometric environment in which they are deployed. We consider the probable case when a routing protocol runs on an environment with many complex obstacles like downtown surroundings. In addition, there are no unrealistic assumptions in order to increase practicality of the protocol. Our goal is to find a routing protocol for maximizing network lifetime by using only connectivity information in the complex sensor network environment. We propose a topology-based routing algorithm that accomplishes good performance in terms of network lifetime and routing complexity as measures. Our routing algorithm makes routing decision based on a weighted graph as topological abstraction of the complex network. The graph conduces to lifetime enhancement by giving alternative paths, distributing the skewed burden. An energy estimation method is used so as to maintain routing information without any additional cost. We show how our approach can be used to maximize network lifetime and by extensive simulation we prove that out approach gives good results in terms of both measures-network lifetime and routing complexity.