• The Mathematical Education
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• v.63 no.2
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• pp.273-294
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• 2024

Recently, interest in Edu-Tech, which applies new technologies to the educational field, is growing. Edu-Tech is now being naturally used in schools, allowing both teachers and students to adapt to these changes. Particularly, there's significant attention on using Edu-Tech to bridge the educational gap through various teaching and learning strategies. This study focuses on the importance of self-directed task management by students for supplementary learning. It developed and utilized a math learning platform that enables teachers to easily provide and manage necessary tasks for students. Initially, the study developed "Sussam-MathTeacher" a problem-based learning application for middle school students, aimed at enhancing problem-solving abilities. This platform operates as a task management system, allowing teachers to assign or recommend problems to either the entire class or individual students. It aims to improve students' problem-solving abilities through a process that includes presenting necessary tasks, monitoring their own progress in solving problems, and self-assessing growth. Through this study, students demonstrated improved problem-solving skills by tackling tasks suited to their levels using "Sussam" highlighting the critical role of teachers in the digital educational environment.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.1
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• pp.62-66
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the learning control field was learning in robots doing repetitive tasks such as an assembly line works. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Some techniques will show up in the numerical simulation for vertical dynamic robot. The methods of learning system are shown for the iterative precision of each link.

• ETRI Journal
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• v.42 no.1
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• pp.90-100
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• 2020

Named entity recognition (NER) continues to be an important task in natural language processing because it is featured as a subtask and/or subproblem in information extraction and machine translation. In Urdu language processing, it is a very difficult task. This paper proposes various deep recurrent neural network (DRNN) learning models with word embedding. Experimental results demonstrate that they improve upon current state-of-the-art NER approaches for Urdu. The DRRN models evaluated include forward and bidirectional extensions of the long short-term memory and back propagation through time approaches. The proposed models consider both language-dependent features, such as part-of-speech tags, and language-independent features, such as the "context windows" of words. The effectiveness of the DRNN models with word embedding for NER in Urdu is demonstrated using three datasets. The results reveal that the proposed approach significantly outperforms previous conditional random field and artificial neural network approaches. The best f-measure values achieved on the three benchmark datasets using the proposed deep learning approaches are 81.1%, 79.94%, and 63.21%, respectively.

• The Journal of Korea Robotics Society
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• v.13 no.3
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• pp.164-173
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• 2018

This paper proposes functional test methods of first-aid gadgets which are special end-effectors, for relief robot. In recent years, researches have been actively conducted on robots that can perform rescue operations on behalf of rescue workers in dangerous areas such as disasters and wars. These special robots mainly perform the task of finding or transporting injured people. However, it is sometimes they necessary to provide first aid in the field. Among the various first-aid operations, gadgets are being developed for oxygen supply, injection, and hemostasis operations that can be used in a defense/civilian area by using robot technology. Previous studies have proposed first-aid gadgets that are suitable for onsite situations and enable robots to perform the given task quickly and accurately. In this paper, we design a test procedure suitable for the functions of first-aid gadgets, summarize the results, and introduce future research directions.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.4
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• pp.92-98
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• 2005

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized teaming control based on adaptive control method. The original motivation of the teaming control field was loaming in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Some techniques will show up in the numerical simulation for vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.556-560
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• 2002

In this paper, we propose a remote controller for robot manipulator using local area network(LAN) and internet. To do this, we develope a server-client system as used in the network field. The client system is in any computer in remote place for the user to log-in the server and manage the remote factory. the server system is a computer which controls the manipulator and waits for a access from client. The server system consists of several control algorithms which is needed to drive the manipulator and networking system to transfer images that shows states of the work place, and to receive a Tmp data to run the manipulator The client system consists of 3D(dimension) graphic user interface for teaching and off-line task like simulation, external hardware interface which makes it easier for the user to teach. Using this server-client system, the user who is on remote place can edit the work schedule of manipulator, then run the machine after it is transferred and monitor the results of the task.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.9-12
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• 1999

This paper presents the development of a control architecture for the autonomous underwater vehicle (AUV) with VARIVEC (variable vector) propeller. Moreover this paper also describes the new technique of controlling the servomotors using the Field Programmable Gate Array (FPGA). The AUVs are being currently used fur various work assignments. For the daily measuring task, conventional AUV are too large and too heavy. A small AUV will be necessary for efficient exploration and investigation of a wide range of a sea. AUVs are in the phase of research and development at present and there are still many problems to be solved such as power resources and underwater data transmission. Further, another important task is to make them smaller and lighter for excellent maneuverability and low power. Our goal is to develop a compact and light AUV having the intelligent capabilities. We employed the VARIVEC propeller system utilizing the radio control helicopter elements, which are swash plate and DC servomotors. The VARIVEC propeller can generate six components including thrust, lateral force and moment by changing periodically the blade angle of the propeller during one revolution. It is possible to reduce the number of propellers, mechanism and hence power sources. Our control tests were carried out in an anechoic tank which suppress the reflecting effects of the wall surface. We tested the developed AUV with required performance. Experimental results indicate the effectiveness of our approach. Control of VARIVEC propeller was realized without any difficulty.

• Journal of the Ergonomics Society of Korea
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• v.29 no.1
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• pp.121-128
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• 2010

The purpose of this study is to confirm the impact of noise on subject accomplishment as well as physical/mental load, and evaluates the effects of noise-masking and earplug. 15 college students participate in the test, and the comparison is performed by executing four projects according to conditional categories of noise environments; control condition, noise condition, earplug condition, and noise-masking condition. Noise in the field site of the H manufacturer was used as the noise source, the general job aptitude test which consist of linguistic ability, math ability, perception ability, reasoning ability was used as the task of this project. To estimate physical/mental load evaluation, we used the heart rate R-R interval, Criteria flicker fusion frequency(CFF) and measured NASA-TLX workload for subjective evaluation. As the research outcome, it is shown that there is a meaningful difference for the project task score, dropping rate of CFF, the heart rate, and NASA-TLX subjective evaluation score according to conditions of noise environment. Therefore, the impact of noise on capability of subject accomplishment as well as physical/mental load was confirmed along with the effects of using earplug and noise-masking.

• Journal of Korean Elementary Science Education
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• v.39 no.4
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• pp.494-505
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• 2020

In this study, we surveyed characteristics of the science related collaborative problem solving competency of pre-service elementary teachers, especially required in the digital age. The participants in online survey were 119 pre-service elementary teachers of National University of Education located in Gangwon province. The analyzed results of survey were as follows: First, pre-service teachers performed their task responsibly in collaborative problem solving context related to science. However, they lacked competencies in making rubrics for problem solving processes or outcomes, and setting up rules about team activities. Second, in using ICT technology, the competencies of utilizing tools such as app and software lacked compared with the competencies of searching data in online and using ppt. Third, there was no statistically significant difference among groups by their intensive major in university or selective subject in high school. Nevertheless, pre-service teachers majoring in natural science showed more persistence than those majoring in humanities in problem solving context. Finally, there was no significant gender difference except 'clear communication and accomplishment'. That is, female pre-service teachers performed more responsible in their task and showed more fluency in communication and presentation within their group than male counterparts. Based on these results, implications in the field of pre-service teacher education were discussed.

• Journal of Computing Science and Engineering
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• v.10 no.2
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• pp.58-67
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• 2016

With the large amount of complex network data that is increasingly available on the Web, link prediction has become a popular data-mining research field. The focus of this paper is on a link-prediction task that can be formulated as a binary classification problem in complex networks. To solve this link-prediction problem, a sparse-classification algorithm called "Truncated Kernel Projection Machine" that is based on empirical-feature selection is proposed. The proposed algorithm is a novel way to achieve a realization of sparse empirical-feature-based learning that is different from those of the regularized kernel-projection machines. The algorithm is more appealing than those of the previous outstanding learning machines since it can be computed efficiently, and it is also implemented easily and stably during the link-prediction task. The algorithm is applied here for link-prediction tasks in different complex networks, and an investigation of several classification algorithms was performed for comparison. The experimental results show that the proposed algorithm outperformed the compared algorithms in several key indices with a smaller number of test errors and greater stability.