• Korean Institute of Interior Design Journal
• /
• v.26 no.6
• /
• pp.97-105
• /
• 2017

Korea is promoted STEAM education since 2011. Furthermore, in high school education, based on the in-depth elective course's teaching and learning contents of science. The STEAM program can improve students' competence because it encourages to self-directed learning through the vocational project performance. Therefore, in this study, we researched a design education program for the experience of fusion and complex design based on STEAM education concept. We developed an education program to design insulation wall systems using up-cycling concepts to increase energy efficiency. As a result, the characteristics of the fusion education and the theoretical study about the learner-centered education curriculum, the analysis of the high school curriculum, the STEAM elements, The program was revised and supplemented through consultation with STEAM experts. In addition, the developed program was applied to high school students, and each step were analyzed based on the educational method theory. The following results were obtained. First, this study presented a program to cope with the needs of high school intensive education. Second, it provided learning motivation by combining flipped-learning as a way to train STEAM education contents. Third, it is required to develop differentiated and continuous program development and data sharing Fourth, in order to operate and promote the future environment design STEAM school, it is necessary to expand educational programs for high school students in the region through linkage with various universities.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38C no.2
• /
• pp.213-218
• /
• 2013

One of the most popular approaches to parameter adaptation in hidden Markov model (HMM) based systems is the maximum likelihood linear regression (MLLR) technique. In our previous study, we proposed factored MLLR (FMLLR) where each MLLR parameter is defined as a function of a control vector. We presented a method to train the FMLLR parameters based on a general framework of the expectation-maximization (EM) algorithm. Using the proposed algorithm, supplementary information which cannot be included in the models is effectively reflected in the adaptation process. In this paper, we apply the FMLLR algorithm to a pitch sequence as well as spectrum parameters. In a series of experiments on artificial generation of expressive speech, we evaluate the performance of the FMLLR technique and also compare with other approaches to parameter adaptation in HMM-based speech synthesis.

• Management & Information Systems Review
• /
• v.32 no.3
• /
• pp.43-59
• /
• 2013

The most important thing in training of organization is that how effectively it can be made most of the performance among the staff. It will be useless if the knowledge which gaining after training can not be applied. Therefore the transfer of learning is studied since it is important for decision of training. We studied the factors of transfer of learning and carried out a survey targeting the public officials of Gangwon province with the factors we made a study. We define the factor of both promoted and interrupted in training and suggest the way of improving it. The first, the modeling of competency can stimulate the desire of achievement and complete a course of training among staff of organizations. The second, the construction of training program and organizational culture just for Gangwon province can increase the satisfaction of training among the learners. The third, the establishment of management system after training can reinforce the capability making use of train. The sharing of each information with boss at the office can help to stimulate the function of feedback after training as well.

• Journal of the Ergonomics Society of Korea
• /
• v.29 no.6
• /
• pp.907-914
• /
• 2010

Cognitive model, that is cognitive architecture, is the model expressed with computer program to show the process how human solve a certain problem and it is continuously under investigation through various fields of study such as cognitive engineering, computer engineering, and cognitive psychology. In addition, the much extensive applicability of cognitive model usually helps it to be used for quantitative prediction of human Behavior or Natural programming of human performance in many HCI areas including User Interface Usability, artificial intelligence, natural programming language and also Robot engineering. Meanwhile, when a system designed, an usability test about conceptual design of interface is needed and in this case, analysis evaluation using cognitive model like GOMS or ACT-R is much more effective than empirical evaluation which naturally needs products and subjects. In particular, if we consider the recent trend of very short-end term between a previous technology development and the next new one, it would take time and much efforts to choose subjects and train them in order to conduct usability test which is repeatedly followed in the process of a system development and this finally would bring delays of development of a new system. In this study, we predicted quantitatively the human behavior processes which contains cognitive processes for menu selection in touch screen interface through ACT-R, one of the common method of usability test. Throughout the study, it was shown that the result using cognitive model was equal with the result using existing empirical evaluation. And it is expected that cognitive model has a possibility not only to be used as an effective methodology for evaluation of HCI products or system but also to contribute the activation of HCI cognitive modeling in Korea.

• Journal of Convergence for Information Technology
• /
• v.8 no.2
• /
• pp.203-208
• /
• 2018

This study is concerned with the introduction and operation of smart factories. In order to accomplish the purpose of research, we made a standard system of smart factory and investigated the recognition system. This study was conducted as a grounded theory methodology among qualitative research methodologies. The results of the study are the necessity of a tool to appropriately evaluate the new manufacturing process management system and related management activities to achieve the successful introduction of smart factories and the management performance of the organization. In order to successfully implement the Smart Factory Certification System, it is necessary to establish a certification organization system, enact relevant laws and amendments, operate government-led pilot projects, train professional workers, and establish incentive policies.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.3
• /
• pp.312-318
• /
• 2012

Recently, although the need of marine robots being raised in extreme areas, the basis is very deficient. Fortunately, as the robot competition is vitalizing and the need of the robot education is increasing, it is desirable to establish the basis of the R&D and industrialization of marine robots and to train professionals through the development and diffusion of marine robot kits. However, in conventional case, there is no underwater-type autonomous marine robot kit for the marine robot competition, which has the abilities of the underwater locomotion and target detection and avoidance. To solve this problem, a marine robot kit which has the abilities of the underwater locomotion, the waterproof and the weight adjustment, is developed. To verify the performance of the developed kit, test and evaluation such as surge, pitch, yaw, obstacle avoidance is performed. The test and evaluation results show that the possibility of the real applications of the developed kit.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2013.06a
• /
• pp.270-272
• /
• 2013

In order to protect coastal facilities mainly from wave and current actions, the self-locking bio blocks constituting component elements of protecting structures against scouring were designed. These blocks are adapted to the sloping bottom, coastal dunes, and submerged coastal base counteracting the destructive and erosive impulse action. A series of laboratory experiments is necessary to investigate the reflection of water waves over and against a train of protruded or submerged shore structures and compare the reflecting capabilities of incident waves including wave forces. In this study the hydraulic model experiment was conducted to identify the performance of newly designed water affinity bio blocks to keep the coast slope and bottom mound from scouring by reduction of the reflection coefficient and to convince stability of the placements. Revised design of each element of blocks were also tested for field conditions. From the result of experiment, the field applicability of the developed blocks and placement is to be discussed afterward.

• Journal of the Institute of Convergence Signal Processing
• /
• v.5 no.3
• /
• pp.190-197
• /
• 2004

This paper presents automated prediction of transient ischemic episodes using neural networks(NN) based pattern matching method. The learning algorithm used to train the multilayer networks is a modified backpropagation algorithm. The algorithm updates parameters of nonlinear function in a neuron as well as connecting weights between neurons to improve learning speed. The performance of the method was evaluated using ECG signals of the MIT/BIH long-term database. Experimental results for 15 records(237 ischemic episodes) show that the average sensitivity and specificity of ischemic episode prediction are 85.71% and 71.11%, respectively. It is also found that the proposed method predicts an average of 45.53［sec］ ahead real ischemia. These results indicate that the NN approach as the pattern matching classifier can be a useful tool for the prediction of transient ischemic episodes.

• Journal of Intelligence and Information Systems
• /
• v.19 no.2
• /
• pp.87-99
• /
• 2013

Massive increases in data available to an organization are creating a new opportunity for competitive advantage. In this era of big data, developing analytics capabilities, therefore, becomes critical to take advantage of internal and external data and gain insights for data-driven decision making. However, the use of data in education is in its infancy, in comparison with business and government, and the potential for data analytics to impact education services is growing. In this paper, I survey how universities are currently using education data to improve students' performance and administrative efficiency, and propose new ways of extending the current use. In addition, with the so-called data scientist shortage, universities should be able to train professionals with data analytics skills. This paper discusses which skills are valuable to data scientists and introduces various training and certification programs offered by universities and industry. I finally conclude the paper by exploring new curriculums where students, by themselves, can learn how to find and use relevant data even in any courses.

• Journal of KIISE
• /
• v.42 no.9
• /
• pp.1124-1132
• /
• 2015

In order to train a supervised machine learning algorithm, it is necessary to have non-biased labels and a sufficient amount of training data. However, it is difficult to collect the required non-biased labels and a sufficient amount of training data to develop an automatic English Composition scoring system. In addition, an English writing assessment is carried out using a multi-faceted evaluation of the overall level of the answer. Therefore, it is difficult to choose an appropriate machine learning algorithm for such work. In this paper, we show that it is possible to alleviate these problems through ensemble learning. The results of the experiment indicate that the ensemble technique exhibited an overall performance that was better than that of other algorithms.