• Journal of KIISE:Software and Applications
• /
• v.32 no.4
• /
• pp.327-334
• /
• 2005

Recently, ICT has emerged as an indispensable tool for teaching a variety of subjects in education systems. In this paper, we examine the effect of the instructional models for ICT on the practical ability in the application of information with relation to the levels of self-regulated learning strategies. Students were divided into 3 groups, according to the instructional model for ICT which were problem search learning, problem solution learning, and discussion learning. As an experimental tools, we did pretest using self-regulated learning strategies measurement questionnaire and did pretest and posttest using practical ability in the application of information measurement questionnaire. The results show that higher level of self-regulated teaming strategies group has high practical ability in the application of information than lower level group. Other interesting results are also provided.

• Journal of Digital Convergence
• /
• v.14 no.2
• /
• pp.245-258
• /
• 2016

This paper aims to present the way to bring about significant results through performance improvement of learning algorithm in the research applying to machine learning. Research papers showing the results from machine learning methods were collected as data for this case study. In addition, suitable machine learning methods for each field were selected and suggested in this paper. As a result, SVM for engineering, decision-making tree algorithm for medical science, and SVM for other fields showed their efficiency in terms of their frequent use cases and classification/prediction. By analyzing cases of machine learning application, general characterization of application plans is drawn. Machine learning application has three steps: (1) data collection; (2) data learning through algorithm; and (3) significance test on algorithm. Performance is improved in each step by combining algorithm. Ways of performance improvement are classified as multiple machine learning structure modeling, $+{\alpha}$ machine learning structure modeling, and so forth.

• International Journal of Internet, Broadcasting and Communication
• /
• v.12 no.2
• /
• pp.120-126
• /
• 2020

Studies are being conducted regarding falling recognition using sensors on smartphonesto recognize falling in human daily life. These studies use a number of sensors, mostly acceleration sensors, gyro sensors, motion sensors, etc. Falling recognition system processes the values of sensor data by using a falling recognition algorithm and classifies behavior based on thresholds. If the threshold is ambiguous, the accuracy will be reduced. To solve this problem, Deep learning was introduced in the behavioral recognition system. Deep learning is a kind of machine learning technique that computers process and categorize input data rather than processing it by man-made algorithms. Thus, in this paper, we propose a falling recognition application system using deep learning based on smartphones. The proposed system is powered by apps on smartphones. It also consists of three layers and uses DataBase as a Service (DBaaS) to handle big data and address data heterogeneity. The proposed system uses deep learning to recognize the user's behavior, it can expect higher accuracy compared to the system in the general rule base.

• Journal of Korea Game Society
• /
• v.14 no.4
• /
• pp.95-104
• /
• 2014

In this research, we investigated the effect of arithmetic learning utilizing mathematical mobile application on arithmetic fluency and learning motivation of underachieving students in math. 24 4th grade math underachievers were divided into control and experimental groups. Arithmetic learning utilizing mathematical mobile application was conducted for experimental group and arithmetic learning utilizing learning worksheets was conducted for comparative group. After three weeks, the experimental group showed increase in math fluency and motivation compared to control group. Implications are discussed.

• Journal of Digital Contents Society
• /
• v.17 no.4
• /
• pp.265-272
• /
• 2016

Recently Chinese education market and social interest has been extended. Accordingly, smart learning based on smartphone applications became part of new educational paradigm. Also, there are more active research and development of applications for the Chinese language education. In this paper, we designed and implemented the smartphone functional application prototype for learning basic Chinese characters. Expression of Chinese characters, the comparison, listening in pronunciation, voice recording and listening, related content learning, and implement testing presented using casual user interface. In the future study, we will develop the prototype with user interface for learning Chinese conversation and individual index of evaluation can be effective learning Instrument without additional tools.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1995.10a
• /
• pp.1039-1042
• /
• 1995

In real time application such as motion control, it is hard to find the application of non-causal filtering due to its need for future position data, even though it shows wide usage in off-line digital signal processing. Recently, some of motion control areas such as learning and repetitive control use non-causal filtering technique in their application. these kinds of zero-lag non-causal filter application are very usful not only to reduce the machine vibration, but also to increase control accuracy with comparatively less work. In this paper, genuine method to implement zero-lag non-causal filter in a CNC is introduced. Also the variation of this implementation for the learning operation is suggested to give the NC better control performance for a specific job. By adopting the new NC architecture call Soft-NC, all these implementions are made possible here, and especially large memory requirement which hinders their usage for many years is no longer barrier in their real world application.

• International Journal of Contents
• /
• v.12 no.1
• /
• pp.54-59
• /
• 2016

The purpose of this paper is to discover how the use of digital applications can affect students' attitudes toward positive classroom participation and performance in learning a foreign language. Participants of this study were 128 students who took a foreign language class at a high school in central Korea. To find out students' perceptions and attitudes toward the effect of using a digital application for their foreign language study, online questionnaire and focus-group interview were conducted. Our research findings revealed that these students could engage in active language learning and experience learning improvement while studying a foreign language with digital applications. The improvement was possible by creating more interactive activities and quizzes. In addition, the digital application provided students immediate feedback. It gave students and teachers various motivations beyond the traditional 'chalk and talk' format of text-only-classes. This study provides an overview of the usefulness of digital application. In addition, it provides understanding for students' perceptions and involvement using digital application in a foreign language classroom.

• Smart Media Journal
• /
• v.11 no.2
• /
• pp.39-52
• /
• 2022

In the context of the evolution of automation and intelligence, deep learning and machine learning algorithms have been widely applied in aquaculture in recent years, providing new opportunities for the digital realization of aquaculture. Especially, water quality management deserves attention thanks to its importance to food organisms. In this study, we proposed an end-to-end deep learning-based TabNet model for water quality prediction. From major indexes of water quality assessment, we applied novel deep learning techniques and machine learning algorithms in innovative fish aquaculture to predict the number of water cells counting. Furthermore, the application of deep learning in aquaculture is outlined, and the obtained results are analyzed. The experiment on in-house data showed an optimistic impact on the application of artificial intelligence in aquaculture, helping to reduce costs and time and increase efficiency in the farming process.

• International Journal of Advanced Culture Technology
• /
• v.6 no.4
• /
• pp.262-265
• /
• 2018

Deep learning, a sub-field of machine learning changing the prospects of artificial intelligence (AI) because of its recent advancements and application in various field. Deep learning deals with algorithms inspired by the structure and function of the brain called artificial neural networks. This works reviews basic architecture and recent advancement of deep structured learning. It also describes contemporary applications of deep structured learning and its advantages over the treditional learning in artificial interlligence. This study is useful for the general readers and students who are in the early stage of deep learning studies.

• Korean Journal of Health Education and Promotion
• /
• v.21 no.3
• /
• pp.151-177
• /
• 2004

Recently, the educational community has attempted to implement the theory of multiple intelligences. In approaching multiple intelligences, teachers have applied the same structural approach which has been so successful with cooperative learning. Cooperative learning is easy to learn and implement, fun for teachers and students, and produce profoundly positive outcomes along a remarkable number of dimensions. Different structures are designed for different outcomes, including enhanced mastery of subject matter, improved thinking skills, team building, class building, development of social character and social skills, communication skills, classroom management, classroom discipline, and development of and engagement of each of the multiple intelligences. Cooperative learning is becoming an increasingly popular teaching strategy. In this study, it is aimed to clarify the application of cooperative learning in health education. Cooperative Learning in health education enhances student learning by: 1) providing a shared cognitive set of information between students, 2) motivating students to learn the material, 3) ensuring that students construct their own health knowledge, 4) providing formative feedback, 5) developing social and health group skills necessary for success outside the classroom, and 6) promoting positive interaction between members of different cultural and socio-economic groups. Cooperative Learning structures and techniques in health education are following. Flash Card, Focused Listing, Structured Problem-solving, Paired Annotations, Structured Learning Team Group Roles, Send-A-Problem, Value Line, Uncommon Commonalities, Team Expectations, Double Entry Journal, Guided Reciprocal Peer Questioning, What if. Because the purpose of health education is the practice, therefore health specialists have to guide powerful and effective teaching method The application of cooperative learning in health education may improve its effectiveness.