• Knowledge Management Research
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• v.2 no.1
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• pp.65-81
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• 2001

The aim of this study is classify knowledge work style management for knowledge management. It is based on the knowledge creation model of Nonaka by subdividing types of knowledge workers. It was designed to create a model for application to the actual environment of management. Nonaka suggested the process of socialization, externalization, combination, internalization that the knowledge of a person creates new knowledge through the interaction of implicit knowledge and explicit knowledge. This research demonstrated that knowledge worker of 16 forms by applying SECI model to the main function and the subordinate functions again. This study aims at achieving a higher outcome by applying the ability of existing knowledge worker to subdivided expert field efficiently. Suggested styles of knowledge worker in this research are classified into craftsman style, pragmatic style, combination style, developed style knowledge worker who creates knowledge by selecting socialization as the function and again by selecting externalization combination, internalization as subordinate functions. And they were classified into creation style, insight style, strategy style according to practical application worker and function which is selecting externalization as the main function and socialization as the subordinate functions. They were classified into future style, innovation style, analysis style, judgement style knowledge worker who are selecting combination as the main function and experiment style, intuition style, research style, learning style worker who are selecting internalization as the main function. They suggested the characteristics and cases of each type.

• Journal of the Korean Society of Earth Science Education
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• v.5 no.3
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• pp.307-315
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• 2012

The purpose of this study was to examine the effects of small inquiry method on space perception ability and creative personality. Testees of this research are 36 elementary pre-service teachers taking an astronomical observation class. Doing inquiry activity after 36 elementary pre-service teachers are classified into 6 Jigsaw small inquiry. Learning activity was split into two groups, expert group and a population. To find out research outcome, pre-test was executed space perception ability test, creative personality test. Analysis of test result was accomplished with statistical package SPSS 18.0 paired t testing hypothesis. The results of this study are as follows. First, 'source of season change' class using Jigsaw small inquiry method has effect on space perception ability improvement. This was interpreted that space perception ability improvement was effective because characteristic of Jigsaw small inquiry is made up of lots of semin Second, 'source of season change' class using Jigsaw small inquiry method has no effect on creative personality. This was interpreted that experiment and discussion activity getting accomplished in a short time has no effect on qualitative characterizing Creative Personality improvement.

• Journal of Fisheries and Marine Sciences Education
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• v.8 no.1
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• pp.28-40
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• 1996

In the last 20 years, educators have made significant advances in their thinking about how students learn and what it is that teachers ought to teach. They attempted to teach thinking s kills and designed instructional programs to facilitate learning. The purpose of this study was to review metacognitive approaches in reading comprehension instruction, and to provide some practical implications to school teachers. First, this study reviewed the concept of metacognition. Metacognition can be divided by metacognitive knowledge and metacognitive experiences. Metacognitive knowledge consists of knowledge or beliefs about what factors interact to affect the outcome of cognitive enterprises. Metacognitive experiences are executive control of one's own cognitive process, which include planning, monitorning and evaluating. Second, this study attempted to investigate the processes of reading comprehension in the metacognitively based view. Third, this study reviewed three kinds of reading comprehension instruction. In the metacognitive approaches, instruction is viewed as constructive process in which teachers and students mediate and negotiate meaning from the instructional environment. In order to enhance reading comprehension, teachers should use examples, explicit instruction, modeling, and elaboration to provide sufficient scaffolding to students. The scaffolding gradually diminishes as students learn to use and apply the reading strategies on their own. Also, students should be encouraged to attribute successful reading to the use of appropriate strategies.

• PNF and Movement
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• v.16 no.1
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• pp.105-113
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• 2018

Purpose: The aim of this study was to explore the effects of dynamic balance training on pain, physical function, and dynamic balance in individuals with knee osteoarthritis. Methods: Fourteen patients with knee osteoarthritis participated in this study. The patients were randomly assigned to two groups: an experimental group (n=7) or a control group (n=7). All the patients took part in a lower extremity strength program for 30 min. In addition, the experimental group participated in a 30-min dynamic balance program. Both groups performed the program five times a week for 3 weeks. Outcomes, including the numeric rating scale (NRS), Western Ontario and MacMaster Universities Arthritis Index (WOMAC), and Community Balance and Mobility Scale (CB&M), were measured at baseline and after 3 weeks. Results: Both groups showed pre-to-post intervention improvements on all outcome measures (p<0.05). The experimental group showed a significant improvement in WOMAC (p = 0.00; Z = -2.82) and CB&M (p = 0.03; Z = -2.20) scores after the intervention as compared with those of the control group. Conclusion: The results revealed that dynamic balance training improved physical function, as well as balance ability, in patients with knee osteoarthritis as compared with that of a control group with no balance training.

• Journal of Elementary Mathematics Education in Korea
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• v.18 no.3
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• pp.519-537
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• 2014

Teacher efficacy influences teacher's own behaviors in class and students outcomes such as achievement, motivation and their own self-efficacy. In recent years, self efficacy and teacher efficacy are becoming more popular in many educational aspects. Teacher efficacy depends on him/her and each tasks and goals. Therefore, we need special instrument for measuring mathematics teacher efficacy. On this study, we derived educationally meaningful factors on mathematics teacher efficacy from previous literature. We developed Mathematics Teaching Efficacy Instrument(MTEI) consisted of 30 items with 6-point Likert scale. The six factors are as follows; mathematics teaching efficacy expectancy, mathematics teaching outcome expectancy, mathematics teaching content knowledge, teacher belief on their own students, the past mathematics learning experience for teacher own, influence from social-cultural environment.

• Journal of Information Processing Systems
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• v.7 no.4
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• pp.717-732
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• 2011

Classification in biomedical applications is an important task that predicts or classifies an outcome based on a given set of input variables such as diagnostic tests or the symptoms of a patient. Traditionally the classification algorithms would have to digest a stationary set of historical data in order to train up a decision-tree model and the learned model could then be used for testing new samples. However, a new breed of classification called stream-based classification can handle continuous data streams, which are ever evolving, unbound, and unstructured, for instance--biosignal live feeds. These emerging algorithms can potentially be used for real-time classification over biosignal data streams like EEG and ECG, etc. This paper presents a pioneer effort that studies the feasibility of classification algorithms for analyzing biosignals in the forms of infinite data streams. First, a performance comparison is made between traditional and stream-based classification. The results show that accuracy declines intermittently for traditional classification due to the requirement of model re-learning as new data arrives. Second, we show by a simulation that biosignal data streams can be processed with a satisfactory level of performance in terms of accuracy, memory requirement, and speed, by using a collection of stream-mining algorithms called Optimized Very Fast Decision Trees. The algorithms can effectively serve as a corner-stone technology for real-time classification in future biomedical applications.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1508-1520
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• 2018

In this paper, we propose an improved model to provide users with a better long-term prediction of waterworks operation data. The existing prediction models have been studied in various types of models such as multiple linear regression model while considering time, days and seasonal characteristics. But the existing model shows the rate of prediction for demand fluctuation and long-term prediction is insufficient. Particularly in the deep running model, the long-short-term memory (LSTM) model has been applied to predict data of water purification plant because its time series prediction is highly reliable. However, it is necessary to reflect the correlation among various related factors, and a supplementary model is needed to improve the long-term predictability. In this paper, convolutional neural network (CNN) model is introduced to select various input variables that have a necessary correlation and to improve long term prediction rate, thus increasing the prediction rate through the LSTM predictive value and the combined structure. In addition, a multiple linear regression model is applied to compile the predicted data of CNN and LSTM, which then confirms the data as the final predicted outcome.

• Journal of applied mathematics & informatics
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• v.40 no.5_6
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• pp.1151-1165
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• 2022

Key drive of information quarrying is to digest liked information starting possible information. With the colossal amount of realities kept in documents, information bases, and stores, in the medical care area, it's inexorably significant, assuming excessive, arising compelling resources aimed at examination besides comprehension like information on behalf of the withdrawal of gen that might assistance in independent direction. Classification is method in information mining; it's characterized as per private, passing on item toward a specific course established happening it is likeness toward past instances of different substances trendy the data collection. In pre-owned recycled four Classification algorithm that incorporate Multi-Layer perception, KSTAR, Bayesian Network and PART to fabricate the grouping replicas arranged the malaria data collection and analyze the replicas, degree their exhibition through Waikato Environment for Knowledge Analysis introduced to Java Development Kit 8, then utilizations outfit's technique trendy promoting presentation of the arrangement methodology. The outcome perceived that Bayesian Network return most elevated exactness of 50.05% when working on followed by Multi-Layer perception, with 49.9% when helping is half, then, at that point, Kstar with precision of 49.44%, 49.5% when supporting individually and PART have lesser precision of 48.1% when helping, The exploration recommended that Bayesian Network is awesome toward remain utilized on Malaria data collection in our sanatoriums.

• Journal of Distribution Science
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• v.21 no.2
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• pp.45-52
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• 2023

Purpose: The Malaysia Education Blueprint is primarily concerned with the transformation of students' minds through the curriculum offered at the school level (2013-2025). Diversity in the application of teaching and learning methods is one means of achieving the transformation of students' minds through the Secondary School Standard Curriculum. Consequently, the production of ExSheetLink's Module for Accounting Education is the primary outcome of this study, which had three objectives: the need for ExSheetLink's Module in the process of producing financial statements for Accounting Students in secondary school to the Accounting Teacher; and the design of ExSheetLink's Module that meets the entire process in the production of financial statements for Accounting Students in secondary school based on the Documents Curriculum and the Accounting Students' needs. Research design, data and methodology: This study outlines the research framework for module development in accordance with the Design and Development Research Method, which combines multiple research techniques (Mixed Method). Results: The development of ExSheetLink's Module is completed and can be used for the level of effectiveness purposes. Conclusion: The transformation of Accounting Students' minds is a success thanks to the ExSheetLink Module. Researchers also suggested that all Malaysian Secondary School accounting students test the ExSheetLink Module.

• Journal of The Korean Society of Inherited Metabolic disease
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• v.22 no.1
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• pp.15-20
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• 2022

The most common urea cycle disorder is ornithine transcarbamylase deficiency. More than 80 percent of patients with symptomatic ornithine transcarbamylase deficiency are late-onset, which can present various phenotypes from infancy to adulthood. With no regards to the severity of the disease, characteristic fluctuating courses due to hyperammonemia may develop unexpectedly, and can be precipitated by various metabolic stressors. Late-onset ornithine transcarbamylase deficiency is not merely related to a type of genetic variation, but also to the complex relationship between genetic and environmental factors that result in hyperammonemia; therefore, it is difficult to predict the prevalence of neurological symptoms in late-onset ornithine transcarbamylase deficiency. Most common acute neurological manifestations include psychological changes, seizures, cerebral edema, and death; subacute neurological manifestations include developmental delays, learning disabilities, intellectual disabilities, attention-deficit/hyperactivity disorder, executive function deficits, and emotional and behavioral problems. This review aims to increase awareness of late-onset ornithine transcarbamylase deficiency, allowing for an efficient use of biochemical and genetic tests available for diagnosis, ultimately leading to earlier treatment of patients.