• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.18 no.10
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• pp.965-975
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• 2005

In the case of the fault in stator windings of a high voltage motor. it facilitates certain destructive characteristics in insulations. This will result in a decreased reliability in power supplies and will prevent the generation of electricity, which will result in huge economic losses. This study simulates motor windings using normal windings and four faulty windings for an actual fault in stator winding of a high voltage motor. The partial discharge signals produced in each faulty winding were measured using an 80 PF epoxy/mica coupler sensor. In order to quantified signal waves its a way of feature extraction for each faulty signal, the signal wave of winding was quantified to measure the degree of skewness shape and kurtosis, which are both types of statistical parameters, using a discrete wavelet transformation method for each faulty type. Wave types present different types lot each faulty type, and the skewness and kurtosis also present different quantified values. The result of feature extraction was used as a preprocessing stage to identify a certain fault in stater windings. It is evident that the type of faulty signals can be classified from the test results using faulty signals that were randomly selected from the signal, which was not applied in the training after the training and learning period, by applying it to a back-propagation algorithm due to the supervising and learning method in a neural network in order to classify the faulty type. This becomes an important basis for studying diagnosis methods using the classification of faulty signals with a feature extraction algorithm, which can diagnose the fault of stator windings in the future.

• The Mathematical Education
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• v.56 no.2
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• pp.161-175
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• 2017

The purpose of this study is to compare and analyze the impact on low-achievers in mathematics who studied mathematics using Blended e-learning and Personalized system of instruction after school. Blended e-learning is defined as the management of e-learning using the e-study run by the education office in local. Personalized system of instruction was proceeded as follows; (1) all students are given a syllabicated learning task and a study guide, (2) students study the material autonomously according to their own pace for a certain period of time, (3) the teacher strengthens the students' motivation through grading and feedback after students study a subject and solve the evaluation problem. The learning materials for Personalized system of instruction are re-edited the offline education contents provided by the blended e-learning to the level of students. The 118 $7^{th}$ grade students from the D middle school participated in this study. The results were verified by achievement tests before and after the study, as well as survey regarding their attitude toward mathematics. The results are as follows. First, Blended e-learning has more positive impacts than Personalized system of instruction in mathematics achievement. Second, there was no difference in mathematics achievement according to their self-directed learning between Blended e-learning and Personalized system of instruction. Third, both types utilizing Blended e-learning and Personalized system of instruction have positive effect on attitude toward mathematics, and there is not their difference between two methods of teaching and learning mathematics.

• Korean Journal of Cognitive Science
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• v.13 no.3
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• pp.47-60
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• 2002

The study investigated the effects of types of presentation and cognitive load on multimedia learning. In experiment 1, subject were 90 elementary school students. The subject were assigned in three conditions: Narration and Text (NT) condition, Animation and Narration(AN) condition, Animation and Text(AT) condition. The result showed that AN condition improved the learning performances in comparison with AT condition, NT condition. Experiment 2 was administrated to 87 undergraduate students. They were participated in three conditions, also. The conditions were Animation and Text (AT) condition, Animation and Narration (AN) condition, Animation, Narration and Text (ANT) condition. the results showed that AN condition was greater in AT, ANT condition. The results from a series of these experiments imply that varying the types of presentation of identical learning materials had influences on the performances. Multimedia presentation(animation and verbal conditions) improved the learning performances in comparison with monomedia presentation(verbal condition), and the advantage was raised when learners were provided the learning material in the multimodal and multimedia environment(AN condition). Also, it came out that redundant text identical to narration disrupted learning when learners were in the picture (either animation or illustration) and narration conditions. Likewise, also for adults, performances were improved in the multimodal conditions and redundant text identical to narration was not helpful for learning. These results are evidences for the dual-coding theory and the cognitive load theory.

• Journal of the Korean association of regional geographers
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• v.5 no.1
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• pp.163-185
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• 1999

The purpose of this study is to develop the model of constructivist multimedia-assisted instruction(CMAI) and to analyze the effect of it in the secondary school geography. The main results are as follows : (1) The conceptual model of CMAI can be defined as an instruction aiming at making a person who has self-directed learning ability through constructivism and multimedia. The procedural model of CMAI based on PIDA instructional strategy is divided into four stages : prediction & explanation, inquiry activity, discussion & fixation, application & synthesis stage. (2) CMAI is typed by offline CMAI and online CMAI. that is, O/WCMAI(online CMAI by web-based courseware). Offline CMAI is subdivided into P/TCMAI(offline CMAI by presentation-based courseware) and C/RCMAI(offline CMAI by cd-rom based courseware) according to authoring tool and function. (3) Offline constructivist multimedia course-ware(offline courseware) was developed for 2 periods as the material to analyze the effect of CMAI. Offline courseware is received development level of it. (4) After offline courseware being applied to the class, the effect of it according the types of the CMAI instruction(lecture instruction, whole teaching, individualized learning, cooperative learning) was analyzed. As the result of analyzing the descriptive statistics of the level of learning achievement and instruction response, there isn't big relationship between them. As the result of analyzing the inferential statistics of the level of learning achievement, there wasn't significant difference between the types of CMAI instruction in whole student of the classes and certain students who improved their grades. But as the result of analyzing of the level of instruction response, there was significant difference between lecture instruction and other types of the CMAI instruction(whole teaching, individualized learning, cooperative learning).

• Composites Research
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• v.35 no.5
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• pp.303-308
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• 2022

PIC (Piecewise Integrated Composite) is a new concept for designing a composite structure with mosaically assigning various types of stacking sequences in order to improve mechanical properties of laminated composites. Also, machine learning is a sub-category of artificial intelligence, that refers to the process by which computers develop the ability to continuously learn from and make predictions based on data, then make adjustments without further programming. In the present study, the tapered box beam type PIC robot arm for carrying and transferring wide and thin LCD display was designed based on the machine learning in order to increase structural stiffness. Essential training data were collected from the reference elements, which were intentionally designated elements among finite element models, during preliminary FE analysis. Additionally, triaxiality values for each finite element were obtained for judging the dominant external loading type, such as tensile, compressive or shear. Training and evaluating machine learning model were conducted using the training data and loading types of elements were predicted in case the level accuracy was fulfilled. Three types of stacking sequences, which were to be known as robust toward specific loading types, were mosaically assigned to the PIC robot arm. Henceforth, the bending type FE analysis was carried out and its result claimed that the PIC robot arm showed increased stiffness compared to conventional uni-stacking sequence type composite robot arm.

• Journal of the Korean Institute of Rural Architecture
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• v.21 no.4
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• pp.37-44
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• 2019

A reduction in the number of high school students in Eup and Myeon districts is very severe. This issue leads to the problem with educational programs of school and an academic achievement gap. Therefore, the purpose of this study is to analyze the characteristics of areas and layout types of the floor plan of high school facilities in Eup and Myeon districts of Jeju Island where the number of students reduces and to provide a fundamental material for establishing school environments. The floor plan of school facilities was categorized into learning, support, common, and other areas and the characteristics of each area were analyzed. As a result, it was necessary to make spatial and facility improvements in common area and support area. The layout type of each area was classified into centralized type, distributed type, and mixed type, and then each type was analyzed. As a result, the main building had low points of the floor plan for learning area and common area. In order to respond to the number of students, it is required to establish reasonable spatial plan criteria and guidelines under the supervision of Office of Education and furthermore to make an effort to create futuristic educational facilities.

• Journal of the Earthquake Engineering Society of Korea
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• v.27 no.4
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• pp.171-180
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• 2023

This study proposed a seismic reinforcement of RC columns with non-seismic details, a fiber reinforcement method of aramid sheets and MLCP (high elasticity aromatic polyester fiber material) with different characteristics, and 4 full-size column specimens and conducted experiments. The results show that a non-seismic specimen (RC-Orig) rapidly lost its load-bearing capacity after reaching the maximum load, and shear failure occurred. The RC column reinforced with three types of aramid did not show an apparent increase in strength compared to the unreinforced specimen but showed a ductile behavior supporting the load while receiving a lateral displacement at least 1.57 to 1.95 times higher than the unreinforced specimen. The fracture mode of the specimen, according to the application of lateral load, also changed from shear to ductile fracture through aramid-based reinforcement. In addition, when examining the energy dissipation ability of the reinforced specimens, a ductile behavior dissipating seismic energy performed 4 times greater and more stably than the existing specimens.

• Journal of Soil and Groundwater Environment
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• v.21 no.3
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• pp.21-34
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• 2016

In the present study, we applied various machine learning techniques comparatively for prediction of subsurface structures based on multiple secondary information (i.e., well-logging data). The machine learning techniques employed in this study are Naive Bayes classification (NB), artificial neural network (ANN), support vector machine (SVM) and logistic regression classification (LR). As an alternative model, conventional hidden Markov model (HMM) and modified hidden Markov model (mHMM) are used where additional information of transition probability between primary properties is incorporated in the predictions. In the comparisons, 16 boreholes consisted with four different materials are synthesized, which show directional non-stationarity in upward and downward directions. Futhermore, two types of the secondary information that is statistically related to each material are generated. From the comparative analysis with various case studies, the accuracies of the techniques become degenerated with inclusion of additive errors and small amount of the training data. For HMM predictions, the conventional HMM shows the similar accuracies with the models that does not relies on transition probability. However, the mHMM consistently shows the highest prediction accuracy among the test cases, which can be attributed to the consideration of geological nature in the training of the model.

• Journal of the Semiconductor & Display Technology
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• v.18 no.2
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• pp.48-52
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• 2019

Virtual metrology, which is one of APC techniques, is a method to predict characteristics of manufactured films using machine learning with saving time and resources. As the photoresist is no longer a mask material for use in high aspect ratios as the CD is reduced, hard mask is introduced to solve such problems. Among many types of hard mask materials, amorphous carbon layer(ACL) is widely investigated due to its advantages of high etch selectivity than conventional photoresist, high optical transmittance, easy deposition process, and removability by oxygen plasma. In this study, VM using different machine learning algorithms is applied to predict the thickness of ACL and trained models are evaluated which model shows best prediction performance. ACL specimens are deposited by plasma enhanced chemical vapor deposition(PECVD) with four different process parameters(Pressure, RF power, $C_3H_6$ gas flow, $N_2$ gas flow). Gradient boosting regression(GBR) algorithm, random forest regression(RFR) algorithm, and neural network(NN) are selected for modeling. The model using gradient boosting algorithm shows most proper performance with higher R-squared value. A model for predicting the thickness of the ACL film within the abovementioned conditions has been successfully constructed.

• Journal of the Korean earth science society
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• v.25 no.7
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• pp.545-557
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• 2004

The purpose of this study is to classify types of preconception on the seasonal change to middle school students and to find out how the developed multimedia material changes their conception in the seasonal change. The questionnaire about the variation of season consisted of 10 items. Questions are given to 80 ninth graders. Control and experimental group was 23 and 57 students, respectively and they were instructed for two class periods. A learning method using multimedia was applied to the experimental group. On the other hand, traditional teaching-learning method was used for the control group. A learning method using multimedia in this study had an effect on the conceptual changes (p$<$0.01). Data in this study was divided into six levels to classify the changes of concepts in detail. As a result, it showed that a learning method using multimedia was effective for students to make progress from unscientific to scientific concepts, to build up scientific concepts, to build up scientific concepts, and to elaborate scientific concepts as compared with traditional method.