• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.59-65
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• 2017

In order to realize the operation of the creative modular toy, it is required to record the motion and to read and repeat the motion. At this time, a control potentiometer is used to read the absolute angle of rotation of the toy motion output shaft. However, the unstable part of the sensing area of the potentiometer is present in a certain region, which may lead to instability of the motor control. In this paper, we propose an algorithm to find the absolute angle of one rotation by reading two stable potentiometers on one axis and reading each stable region. We also describe the correction algorithm that is needed to perform multiple rotations. The proposed method is applied to Topobo modular toys to record the operation and perform iterative operation. In addition, multi-turn operation is recorded and operated to suggest the usefulness of the proposed method. In the future, we will expand the functions of recording and playback through various actions.

• Journal of The Korean Society of Integrative Medicine
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• v.7 no.1
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• pp.89-98
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• 2019

Purpose : The purpose of this study was to understand the correlations between occupational basic competencies, job searching efficacy and career preparation behavior of department on occupational therapy students. Methods : The subjects of this study were 103 occupational therapy students in D college. The data collection period was from July 1, 2018 to July 30, 2018. The collected data was processed using SPSS 21.0 and were analyzed using descriptive statistics, t-test, ANOVA, Scheffe's test and Pearson's correlation coefficient. Results : The mean scores for occupational basic competencies, job searching efficacy and career preparation behavior of the occupational therapy students were 3.61 (${\pm}0.59$), 3.58 (${\pm}0.61$) and 3.31 (${\pm}0.66$) respectively. The occupational basic competencies score of the Occupational Therapy students was significantly differed according to their age (t=-2.13, p=.03) and grade point average (F=15.01, p=.00). The job searching efficacy of the Occupational Therapy students was significantly different by grade point average (F=3.40, p=.02). There were no significant differences in job preparation behaviors among occupational therapy students according to gender, age, grade and grade point average. There was a positive correlation between occupational basic competencies and job searching efficacy (r=.675, p<.01), between occupational basic competencies and career preparation behavior (r=.455, p<.01), between job searching efficacy and career preparation behavior (r=.702, p<.01). Conclusion : The results of this study suggest the following: It is necessary to repeat this study with a greater number and range of subjects. In addition, it suggests that the progress of study should be developed and continued and refined in order to identify factors that affect the career preparation behavior of students of occupational therapy. In addition, the development of a program and the application of a curriculum to promote occupational basic competencies and job searching efficacy should be a priority.

• The Research Journal of the Costume Culture
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• v.30 no.1
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• pp.66-87
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• 2022

This study explores the possibility of creating new experimental hanbok designs by accommodating the latest world fashion trends and the changing needs of consumers, in order to attempt to overcome the limitations of traditional Korean fashion design. To do so, We analyze works by contemporary Korean fashion designers to investigate current developments in Korean fashion design and to identify areas of improvement within hanbok design. The results show that most contemporary hanbok designs repeat stereotypes of traditional hanbok with minor modifications. So there arises a need to create new hanbok designs that are clearly distinct from traditional hanbok but also maintain its core features. To develop such designs, I apply the techniques of deconstruction fashion, which allow making experiments with form, composition, and materials use to realize new aesthetics. The use of CLO 3D fashion design software also proves to be very efficient for developing experimental designs. The study results make meaningful contributions to the development of virtual clothing and 3D fashion for hanbok, particularly as metaBUS, a cloud-based research synthesis platform, is rapidly gaining ground, and reality and virtual reality are increasingly mixed in everyday life. This attempt at 3D design of hanbok is expected to trigger more creative experimentation in hanbok design.

• Transactions of Materials Processing
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• v.32 no.5
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• pp.239-246
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• 2023

To reduce the forming load due to the temperature drop, during the hot forging process, a reheating hot forging process design is required that to repeat heating and forging. However, if the critical strain required for recrystallization is not induced during forging and grain growth becomes dominant due to the reduction in dislocation density due to repeated heating, the mechanical properties may deteriorate. Therefore, in this study, Inconel 706 alloy was applied, and the grain refinement behavior was comparatively analyzed according to the number of reheating times and effective strain during reheating hot forging process. Reheating was carried out with a total compression rate of 40% up to 4 times. The Inconel 706 compression test specimens heated once showed finer grains as the effective strain increased due to the dynamic recrystallization phenomenon. However, as the number of heating increases, grain refinement was observed even in a low effective strain distribution of 0.43 due to static recrystallization during reheating. Moreover, grain growth occurs at a relatively low effective strain of 0.43 when the number of reheating is four or more. Therefore, it was effective to apply an effective strain of 0.43 or more during hot forging to Inconel 706 in order to induce crystallization through grain refinement and improve the properties of forged products. In addition, we could notice that up to three reheating times condition was appropriate to prevent grain growth and maintain fine grain size.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.139-147
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• 2009

The memory based reasoning just stores in the memory in the form of the training pattern of the representative pattern. And it classifies through the distance calculation with the test pattern. Because it uses the techniques which stores the training pattern whole in the memory or in which it replaces training patterns with the representative pattern. Due to this, the memory in which it is a lot for the other machine learning techniques is required. And as the moreover stored training pattern increases, the time required for a classification is very much required. In this paper, We propose the EAS(Evaluation And Selection) algorithm in order to minimize memory usage and to improve classification performance. After partitioning the training space, this evaluates each partitioned space as MDL and PM method. The partitioned space in which the evaluation result is most excellent makes into the representative pattern. Remainder partitioned spaces again partitions and repeat the evaluation. We verify the performance of Proposed algorithm using benchmark data sets from UCI Machine Learning Repository.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.655-662
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• 2023

Big data research plays a role of supplementing existing social science research methods. If the survey and experimental methods are somewhat inaccurate because they mainly rely on recall memories, big data are more accurate because they are real-time records. Social science research so far, which mainly conducts sample research for reasons such as time and cost, but big data research analyzes almost total data. However, it is not easy to repeat and reproduce social research because the social atmosphere can change and the subjects of research are not the same. While social science research has a strong triangular structure of 'theory-method-data', big data analysis shows a weak theory, which is a serious problem. Because, without the theory as a scientific explanation logic, even if the research results are obtained, they cannot be properly interpreted or fully utilized. Therefore, in order for big data research to become a methodological innovation, I proposed big thinking along with researchers' efforts to create new theories(black boxes).

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.6
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• pp.115-124
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• 2019

In a climate change environment where heat damage and drought occur during a rainy season such as in 2018, a vegetation-based LID system that enables disaster prevention as well as environment improvement is suggested in lieu of an installation-type LID system that is limited to the prevention of floods. However, the quantification of its performance as against construction cost is limited. This study aims to present an experiment environment and evaluation method on quantitative performance, which is required in order to disseminate the vegetation-based LID system. To this end, a 3^rd quartile huff time distribution mass curve was generated for 20-year frequency, 60-minute probable rainfall of 68mm/hr in Cheonan, and effluent was analyzed by recreating artificial rainfall. In order to assess the reliability of the rainfall event simulator, 10 repeat tests were conducted at one-minute intervals for 20 minutes with minimum rainfall intensity of 22.29mm/hr and the maximum rainfall intensity of 140.69mm/hr from the calculated probable rainfall. Effective rainfall as against influent flow was 21.83mm/hr (sd=0.17~1.36, n=20) on average at the minimum rainfall intensity and 142.27mm/hr (sd=1.02~3.25, n=20) on average at the maximum rainfall intensity. In artificial rainfall recreation experiments repeated for three times, the most frequent quartile was found to be the third quartile, which is around 40 minutes after beginning the experiment. The peak flow was observed 70 minutes after beginning the experiment in the experiment zone and after 50 minutes in the control zone. While the control zone recorded the maximum runoff intensity of 2.26mm/min(sd=0.25) 50 minutes after beginning the experiment, the experiment zone recorded the maximum runoff intensity of 0.77mm/min (sd=0.15) 70 minutes after beginning the experiment, which is 20 minutes later than the control zone. Also, the maximum runoff intensity of the experiment zone was 79.6% lower than that of the control zone, which confirmed that vegetation unit-type LID system had rainfall runoff reduction and delay effects. Based on the above findings, the reliability of a lab-level rainfall simulator for monitoring the vegetation-based LID system was reviewed, and maximum runoff intensity reduction and runoff time delay were confirmed. As a result, the study presented a performance evaluation method that can be applied to the pre-design of the vegetation-based LID system for rainfall events on a location before construction.

• Journal of KIISE:Databases
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• v.37 no.1
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• pp.1-11
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• 2010

Recently, there has been a growing interest in the processing of continuous queries over multiple data streams. When the arrival rates of tuples exceed the memory capacity of the system, a load shedding technique is used to avoid the system becoming overloaded by dropping some subset of input tuples. In this paper, we propose an effective load shedding algorithm for multi-way windowed joins over multiple data streams. Most previous load shedding algorithms estimate the productivity of each tuple, i.e., the number of join output tuples produced by the tuple, based on its "join attribute value" and drop tuples with the lowest productivity. However, the productivity of a tuple cannot be accurately estimated from its join attribute value when the join attribute values are unique and do not repeat, or the distribution of the join attribute values changes over time. For these cases, we estimate the productivity of a tuple based on its "arrival order" on data streams, rather than its join attribute value. The proposed method can effectively estimate the productivity of a tuple even when the productivity of a tuple cannot be accurately estimated from its join attribute value. Through extensive experiments and analysis, we show that our proposed method outperforms the previous methods in terms of effectiveness and efficiency.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.2
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• pp.103-116
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• 2017

In this paper, we present the design and implementation of a large-scale qualitative spatial reasoner, which can derive new qualitative spatial knowledge representing both topological and directional relationships between two arbitrary spatial objects in efficient way using Aparch Spark SQL. Apache Spark SQL is well known as a distributed parallel programming environment which provides both efficient join operations and query processing functions over a variety of data in Hadoop cluster computer systems. In our spatial reasoner, the overall reasoning process is divided into 6 jobs such as knowledge encoding, inverse reasoning, equal reasoning, transitive reasoning, relation refining, knowledge decoding, and then the execution order over the reasoning jobs is determined in consideration of both logical causal relationships and computational efficiency. The knowledge encoding job reduces the size of knowledge base to reason over by transforming the input knowledge of XML/RDF form into one of more precise form. Repeat of the transitive reasoning job and the relation refining job usually consumes most of computational time and storage for the overall reasoning process. In order to improve the jobs, our reasoner finds out the minimal disjunctive relations for qualitative spatial reasoning, and then, based upon them, it not only reduces the composition table to be used for the transitive reasoning job, but also optimizes the relation refining job. Through experiments using a large-scale benchmarking spatial knowledge base, the proposed reasoner showed high performance and scalability.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.134-143
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• 2009

In this paper, we propose a new relay selection algorithm for a two-way multiple relay channel. In the two-way multiple relay channel, two users exchange information with each other via multiple relays. The relays use a decode-and-forward or amplify-and-forward protocol, and exploit the combining process of the received packets to reduce the required channel resources. In the multiple relay network, diversity gain is achieved as the number of relays increases, and various schemes are proposed. In this paper, we propose a single best relay selection scheme based on instantaneous channel conditions. First of all, relays obtain the instantaneous channel state information in the handshaking process, and a single best relay is selected in a distributed methods prior to data transmissions. The relay selection metric is proposed so that the end-to-end channel condition is evaluated based on the intantaneous channel state informations. Simulation results show that the proposed relay selection algorithm achieve the increased throughput and diversity order when the number of potential relays is increased.