• Asia pacific journal of information systems
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• v.17 no.1
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• pp.33-58
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• 2007

Quiet often, an organization tries to grapple with inconsistent and partial information to generate relevant information to support decision making and action. As such, an organization scans the environment interprets scanned data, executes actions, and learns from feedback of actions, which boils down to computational interpretations and learning in terms of machine learning, statistics, and database. The ExOM proposed in this paper is geared to facilitate such knowledge discovery found in large databases in a most flexible manner. It supports a broad range of learning and classification styles and integrates them with traditional database functions. The learning and classification components of the ExOM are tightly integrated so that learning and classification of objects is less burdensome to ordinary users. A brief sketch of a strategy as to the expressiveness of terminological language is followed by a description of prototype implementation of the learning and classification components of the ExOM.

• The Korean Journal of Physiology and Pharmacology
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• v.24 no.2
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• pp.129-135
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• 2020

SHP2 is an unusual protein phosphatase that functions as an activator for several signaling pathways, including the RAS pathway, while most other phosphatases suppress their downstream signaling cascades. The physiological and pathophysiological roles of SHP2 have been extensively studied in the field of cancer research. Mutations in the PTPN11 gene which encodes SHP2 are also highly associated with developmental disorders, such as Noonan syndrome (NS), and cognitive deficits including learning disabilities are common among NS patients. However, the molecular and cellular mechanism by which SHP2 is involved in cognitive functions is not well understood. Recent studies using SHP2 mutant mice or pharmacological inhibitors have shown that SHP2 plays critical role in learning and memory and synaptic plasticity. Here, we review the recent studies demonstrating that SHP2 is involved in synaptic plasticity, and learning and memory, by the regulation of the expression and/or function of glutamate receptors. We suggest that each cell type may have distinct paths connecting the dots between SHP2 and glutamate receptors, and these paths may also change with aging.

• Journal of the Korean School Mathematics Society
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• v.25 no.1
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• pp.79-104
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• 2022

It is very important to help students learn by examining how well students solve math problems. Therefore, in this study, four methods(error analysis by problem type, schematization analysis, area graph analysis, and broken line graph analysis) were constructed to analyze how the connectivity between concepts of middle school functions affects the problem solving results. The students' learning situation was visually expressed to enable intuitive understanding. This analysis method makes it easy to understand the evaluation results of students. It can help students learn by understanding their learning situation. It will be useful in mathematics teaching and learning as it can help students to monitor their own problems and make a self-directed learning plan.

• Journal of Korean Physical Therapy Science
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• v.19 no.3
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• pp.23-30
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• 2012

The purpose of this study was to apply treadmill training through motor learning to cerebral palsy children and examine its effects on their Gross Motor Functions. The subjects of this study were 13 spastic diplegia children who had difficulty in independent gait, and GMFCS level III, IV. We performed treadmill gait training using the principle of weight bearing, based on 4times a week for 30 minutes before and after each session physical therapy we gave weight bearing treadmill training 5 to 10 minutes, during 7 weeks(April 9, 2012~May 26, 2012) fittingly for the children's gait characteristics. In order to test how the weight bearing treadmill training affects spastic diplegia children's gross motor functions, we measured body mobility with Gross Motor Function Measure (GMFM). These data were collected before and after the experiment and analyzed through comparison. Data collected from the 13 spastic diplegia children the results were as follows. For evaluating with regard to change in body mobility, significant difference was observed between before and after the experiment in measured gross motor functions, which were crawling, kneeling, standing, walking, jumping and running(p<0.05). According to the results of this study, when gait training through motor learning was applied to spastic cerebral palsy children, it made significant changes in their body mobility. Accordingly, for the effective application of gait training through motor learning to cerebral palsy children, it is considered necessary to make research from different angle on how such training affects children's mobility, activity of muscles in the lower limbs, and gait characteristics.

• International Journal of Contents
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• v.10 no.3
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• pp.26-34
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• 2014

Mobile learning is a practical learning method for busy adult learners because the mobility of digital devices can overcome the drawbacks of e-learning. However, research is strongly lacking in the theoretical exploration of mobile learning effects and functions and its empirical research. Moreover, the research of learning characteristics and learners' requirements must be considered before applying and disseminating mobile learning into the educational field. To address this shortcoming, this study conducted an online survey with 1,542 officers of the Ministry of Health and Welfare Affairs (MHWA) regarding learner recognition to mobile learning. The analysis of learners' attitudes toward mobile learning, based on age and position, indicated that subordinate workers appeared to place more value on mobile learning. Many participants preferred mobile learning because of its mobility and the effectiveness of anywhere and anytime. However, some participants continue to misunderstand mobile learning and its necessity. Therefore, consideration of learning effectiveness, the form of the content, and learner-centered learning must be reviewed in advance. This study could lead to practical implications of mobile learning.

• Educational Technology International
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• v.15 no.2
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• pp.71-88
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• 2014

A variety of studies to predict students' performance have been conducted since educational data such as web-log files traced from Learning Management System (LMS) are increasingly used to analyze students' learning behaviors. However, it is still challenging to predict students' learning achievement in blended learning environment where online and offline learning are combined. In higher education, diverse cases of blended learning can be formed from simple use of LMS for administrative purposes to full usages of functions in LMS for online distance learning class. As a result, a generalized model to predict students' academic success does not fulfill diverse cases of blended learning. This study compares two blended learning classes with each prediction model. The first blended class which involves online discussion-based learning revealed a linear regression model, which explained 70% of the variance in total score through six variables including total log-in time, log-in frequencies, log-in regularities, visits on boards, visits on repositories, and the number of postings. However, the second case, a lecture-based class providing regular basis online lecture notes in Moodle show weaker results from the same linear regression model mainly due to non-linearity of variables. To investigate the non-linear relations between online activities and total score, RF (Random Forest) was utilized. The results indicate that there are different set of important variables for the two distinctive types of blended learning cases. Results suggest that the prediction models and data-mining technique should be based on the considerations of diverse pedagogical characteristics of blended learning classes.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.290-293
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• 2021

In this paper, we implement a learning efficiency verification system to inspire learning motivation and help improve concentration by detecting the situation of the user studying. To this aim, data on learning attitude and concentration are measured by extracting the movement of the user's face or body through a real-time camera. The Jetson board was used to implement the real-time embedded system, and a convolutional neural network (CNN) was implemented for image recognition. After detecting the feature part of the object using a CNN, motion detection is performed. The captured image is shown in a GUI written in PYQT5, and data is collected by sending push messages when each of the actions is obstructed. In addition, each function can be executed on the main screen made with the GUI, and functions such as a statistical graph that calculates the collected data, To do list, and white noise are performed. Through learning efficiency checking system, various functions including data collection and analysis of targets were provided to users.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.1-6
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• 2009

One of the most important problems in bioinformatics is how to extract the useful information from a huge amount of data, and make a decision in diagnosis, prognosis, and medical treatment applications. This paper proposes a weighted kernel function for support vector machine and its learning method with a fast convergence and a good classification performance. We defined the weighted kernel function as the weighted sum of a set of different types of basis kernel functions such as neural, radial, and polynomial kernels, which are trained by a learning method based on genetic algorithm. The weights of basis kernel functions in proposed kernel are determined in learning phase and used as the parameters in the decision model in classification phase. The experiments on several clinical datasets such as colon cancer indicate that our weighted kernel function results in higher and more stable classification performance than other kernel functions.

• Journal of The Korean Association of Information Education
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• v.20 no.2
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• pp.189-196
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• 2016

The PATROL instructional model only uses digital textbooks. PATROL is an acronym for Planning, Action, Tracking, Recommending, Ordering, and Leading. Teachers have a difficult time using current digital textbooks to determine how much time students spend using course materials. This is because current digital textbooks can only show the content of paper textbooks and display additional multimedia materials. In this study, digital textbook functions were designed based on the PATROL model in order to analyze students' learning situations, diagnose problems, and offer solutions. Digital textbook are based on learning analytics named SEE-PAD. SEE-PAD is composed of the following: Social network analysis; Evaluation and assEssment analysis; Predictive analysis; Adaptive learning analysis; and the analysis Dashboard. I drew and showed the use case and sequence diagrams of SEE-PAD to help design digital textbook functions.

• The Journal of Korean Association of Computer Education
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• v.14 no.3
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• pp.37-49
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• 2011

A user can use resources on the Semantic Web using a Semantic Web browser. In order to utilize the functions of Semantic Web browsers in education, we compared the functions of well-known Semantic Web browsers such as Tabulator, Contextual Search Browser (CSB), Magpie, and Piggy Bank. In order to utilize Semantic Web browsers in education, a user needs to understand the features of each Semantic Web browser and our work can help both teachers and students. Tabulator is an RDF browser that can help to check whether resources can be used for learning and relevance of resources. CSB can be used to search educational resources using a conrtext file that contains the subjects of learning. It can also help learning by showing semantic web resources in the form of triple set as well as by supporting highlighting function. Magpie can help learners without basic knowledge on learning materials by providing interpretation based on a glossary file and related background knowledge. Piggy Bank supports conversion of web resources into semantic web resources and allows to browse semantic web resources in various views as well as to share semantic web resources.