• IE interfaces
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• v.25 no.2
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• pp.178-186
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• 2012

The DRAM module is an important part of servers, workstations and personal computer. Its malfunction causes a lot of damage on customer system. Therefore, customers demand the highest quality products. The company applies DRAM module Outgoing Quality Assurance Inspection(OQA) to secures the highest quality. It is the key process to decides shipment of products through sample inspection method with customer oriented tests. High fraction of defectives entering to OQA causes inevitable high quality cost. This article proposes the application of ensemble learning to classify the lot status to minimize the ratio of wrong decision in OQA, observing a potential in reducing the wrong decision.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.1
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• pp.93-100
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• 2021

Forward osmosis (FO) process is a chemical potential driven process, where highly concentrated draw solution (DS) is used to take water through semi-permeable membrane from feed solution (FS) with lower concentration. Recently, commercial FO membrane modules have been developed so that full-scale FO process can be applied to seawater desalination or water reuse. In order to design a real-scale FO plant, the performance prediction of FO membrane modules installed in the plant is essential. Especially, the flux prediction is the most important task because the amount of diluted draw solution and concentrate solution flowing out of FO modules can be expected from the flux. Through a previous study, a theoretical based FO module model to predict flux was developed. However it needs an intensive numerical calculation work and a fitting process to reflect a complex module geometry. The idea of this work is to introduce deep learning to predict flux of FO membrane modules using 116 experimental data set, which include six input variables (flow rate, pressure, and ion concentration of DS and FS) and one output variable (flux). The procedure of optimizing a deep learning model to minimize prediction error and overfitting problem was developed and tested. The optimized deep learning model (error of 3.87%) was found to predict flux better than the theoretical based FO module model (error of 10.13%) in the data set which were not used in machine learning.

• Journal of the Korean earth science society
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• v.25 no.3
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• pp.176-184
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• 2004

The concept of 'the lunar and planetary phases' is very difficult to understand and students may have various misconceptions on this concept. A module drawing the lunar and planetary phases was developed with the application of the simplifying conditions method. The effects of instruction using the module drawing the lunar and planetary phases on the conceptual change and the achievement was investigated in the consideration of learners' characteristics (spatial perception ability, science inquiry ability, required pre-requested learning ability). Findings were as follows: 1) This module was effective for learners' conceptual change and achievement, 2) This module had a positive influence for development the learners' characteristics and conceptual change with the middle level of science inquiry ability, the middle and low level of required pre-requisite learning ability, and middle level of the spatial perception ability.

• The Journal of Korean Association of Computer Education
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• v.8 no.2
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• pp.33-40
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• 2005

It has been found that the learning method based on conventional CAI(Computer Assisted Instruction) to be inadequate and inefficient as it is designed without considering the individual learning characteristics of the learners. In order to rectify and remedy the problem, the development of an ITS(Intelligent Tutoring System) that is adequately equipped with an artificial intelligence that successfully interprets the individual learning ability characteristics through accumulated individual data is in order. This study attempts to verify the individual acquisition ability and the possible error committed by learners in the process of learning in order to present the elements to be considered for designing a successful student module that enables the effective learning through the 'learner ability grouping' for learning Electronic Calculator Architecture.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.9
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• pp.999-1004
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• 2014

This intelligent keyboard instrument self learning system developed in this study consists of smartphone based learning application and keyboard-instrument auxiliary module. The keyboard instrument auxiliary module receives playing information of the instrument through smartphone application and bluetooth communication. Then the module shows it through LED display so that the relationship between the keyboard and scale could be easily recognized even for beginners. Also, this system provides saving function and analyzing function of user's performance data, making learning more effective.

• Korean Journal of Computational Design and Engineering
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• v.2 no.2
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• pp.111-121
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• 1997

This study intends to develop a fixture planning module as a part of the planning system for cutting. The fixture module uses machine learning method to reuse previous failure results so that the system can reduce the repeated failures. Machine learning is one of efforts to incorporate human reasoning ability into a computerized system. A human expert designs better than a novice does because he has a wide experience in a specific area. This study implements the machine learning algorithm to have a wide experience in the fixture planning area as a human expert does. When the fixture planner finds a setup failure for the suggested operations by a process planner, it makes the process planner store its attributes and other information for the failed setup. Then the process planner applies the learned knowledge when it meets a similar case so that the planner can reduce possibility of setup failure. Also the system can teach a novice user by showing a failed setup with a modified setup.

• Speech Sciences
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• v.14 no.3
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• pp.31-46
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• 2007

This study attempts to investigate that the training of pitch manipulation would help Korean speakers reduce the intonation errors based on the review of many previous studies on Korean speakers' phonetic realization of intonation. The previous studies have indicated that Korean speakers have problems with pitch manipulation in their production of English word stress, sentence stress, and eventually intonation. To train Korean speakers phonetically realize English pitch patterns, a blended learning module was operated for two weeks: face-to-face instruction for six hours and e-learning instruction for three hours in total. This module was designed to help Korean speakers realize pitch as a distinctive phoneme. An acoustic assessment on five Korean female English speakers shows that the training of pitch manipulation helps Korean English speakers reduce the intonation errors indicated in the previous studies reviewed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.4
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• pp.133-140
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• 2007

This study aims to design and implement a learning evaluation system using .NET which is developed by Microsoft. .NET technology supports higher processing speed than ASP technology. The learning evaluation system is based on the web, consists of administrator module, questioner module and student module. The functions of the system, i.e., providing test questions, performing test, and evaluating result of test are achieving on the web in real time. Even when many users use this system, the system is stable and has a speed response time.

• The Journal of Natural Sciences
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• v.19 no.1
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• pp.11-25
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• 2008

An Adobe Connect Meeting Moodle activity module was developed for the Pai-Chai Moodle virtual learning environment. Professors can create online meeting room directly from their courses by using the Adobe Connect Meeting module. The web services from the server was utilized for the application integration.

• Journal of the Korean Society of Earth Science Education
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• v.10 no.1
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• pp.26-37
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• 2017

The purpose of this study was to investigate secondary pre-service science teachers' misconceptions of tide and to develop a learning module that can change misconceptions into scientific concepts and to examine the effect of the learning module for conceptual change. In order to achieve the purpose of the study, the researcher developed the test tool of tidal phenomena and the learning module using cognitive conflict strategy. The subjects of this study were 40 first year students who majored science education at a college of education in G metropolitan city. The results of this study are as follows. First, secondary pre-service science teachers had various misconceptions about tidal phenomena. Second, the developed learning module was effective in changing misconceptions about tide of pre-service science teachers into scientific concepts. However, some students had misconceptions about tidal phenomena after learning the developed module. The typical misconception was that they could not distinguish the centrifugal force generated when the earth and the moon revolve about the center of common mass as the center of rotation and the centrifugal force generated by the earth's rotation. And they did not know that they should not consider the earth's rotation while the earth was revolving around the center of common mass.