• International journal of advanced smart convergence
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• v.9 no.3
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• pp.36-41
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• 2020

In this study, a nursing management application for fourth-year students majoring in nursing at university was developed and practically applied in lectures. The application consists of an introduction, learning contents, and quiz contents. Nursing students downloaded and used it on their smartphones, such as iPhones and Android phones. The learning contents of a nursing management application include theoretical contents related to courses on nursing management and quiz contents comprising basic, advanced, and mixed quizzes based on the learning contents. Nursing students had access to this application on their smartphones and studied the contents provided regardless of time and space. Moreover, they were allowed to check their scores as soon as they selected and answered the questions included in the quiz contents. Nursing students used a nursing management application during and after lectures. We confirmed their learning process and learning results anytime and provided relevant feedback.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.7
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• pp.82-91
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• 1997

In this paper, we analyze the dynamics of langevine competitive learning neural network based on its fokker-plank equation. From the viewpont of the stochastic differential equation (SDE), langevine competitive learning equation is one of langevine stochastic differential equation and has the diffusin equation on the topological space (.ohm., F, P) with probability measure. We derive the fokker-plank equation from the proposed algorithm and prove by introducing a infinitestimal operator for markov semigroups, that the weight vector in the particular simplex can converge to the globally optimal point under the condition of some convex or pseudo-convex performance measure function. Experimental resutls for pattern recognition of the remote sensing data indicate the superiority of langevine competitive learning neural network in comparison to the conventional competitive learning neural network.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.216-221
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• 2004

This paper describes an optimal synthesis method of binary neural network for pattern recognition. Our objective is to minimize the number of connections and the number of neurons in hidden layer by using a Newly Expanded and Truncated Learning Algorithm (NETLA) for the multilayered neural networks. The synthesis method in NETLA uses the Expanded Sum of Product (ESP) of the boolean expressions and is based on the multilayer perceptron. It has an ability to optimize a given binary neural network in the binary space without any iterative learning as the conventional Error Back Propagation (EBP) algorithm. Furthermore, NETLA can reduce the number of the required neurons in hidden layer and the number of connections. Therefore, this learning algorithm can speed up training for the pattern recognition problems. The superiority of NETLA to other learning algorithms is demonstrated by an practical application to the approximation problem of a circular region.

• Journal of Distribution Science
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• v.13 no.6
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• pp.25-33
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• 2015

Purpose - This paper's goal is to assess and promote several good teaching product designs and several learning environments. The paper discusses research product design learning and management. Research design, data, and methodology - As part of information science and technology, a school uses several teaching networks for auxiliary teaching, taking several designs as the teaching foundation, and creating multimedia curricula. Results - The results indicate that in the best learning designs and environments, the learner can maintain a high interest, which not only attracts all levels in the schools, but also has a pivotal influence on teaching around the world. The research study answers the question, was the atmosphere already luxurious? Conclusions - This study introduces several methodologies that are widely used for experimental processes. Using multi-criterion decision-making technology in studies of language product evaluation systems, the language teaching quality and space design is developed, and the language classroom learning system, the machine operation, the classroom environment design method, etc., conform to specifics of the study, the best choices, the most effective utilization, and are the most efficient.

• 한국정보컨버전스학회:학술대회논문집
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• 2008.06a
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• pp.205-208
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• 2008

Contents application from contents development of web technical base and with the operation different environment information of the educational resources integration the importance and necessity of the management central chain e-Learning system will be able to operate are raising its head with base. Is the actual condition which develops the development process where but, the education application currently is not standardized in base. Approaches with an educational domain from the present paper consequently, and defines MDA(Model Driven Architecture) coats e-Learning System. Also uses a studying contents standard metadata and about the contents storage space analyzes and plans the core property which uses MDA automatic tools leads and under developing boil e-Learning System will be able to provide the contents which does in actual professor own necessity.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.2
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• pp.113-120
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• 2021

The Distance Measuring Equipment (DME) is a ground-based aircraft navigation system and is considered as an infrastructure that ensures resilient aircraft navigation capability during the event of a Global Navigation Satellite System (GNSS) outage. The main problem of DME as a GNSS back up is a poor positioning accuracy that often reaches over 100 m. In this paper, a novel approach of applying deep reinforcement learning to a DME pulse design is introduced to improve the DME distance measuring accuracy. This method is designed to develop multipath-resistant DME pulses that comply with current DME specifications. In the research, a Markov Decision Process (MDP) for DME pulse design is set using pulse shape requirements and a timing error. Based on the designed MDP, we created an Environment called PulseEnv, which allows the agent representing a DME pulse shape to explore continuous space using the Soft Actor Critical (SAC) reinforcement learning algorithm.

• Tunnel and Underground Space
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• v.30 no.6
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• pp.540-550
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• 2020

Machine learning has been actively used in the field of automation due to the development and establishment of AI technology. The important thing in utilizing machine learning is that appropriate algorithms exist depending on data characteristics, and it is needed to analysis the datasets for applying machine learning techniques. In this study, advance rate is predicted using geotechnical and machine data of TBM tunnel section passing through the soil ground below the stream. Although there were no problems of application of statistical technology in the linear regression model, the coefficient of determination was 0.76. While, the ensemble model and support vector machine showed the predicted performance of 0.88 or higher. it is indicating that the model suitable for predicting advance rate of the EPB Shield TBM was the support vector machine in the analyzed dataset. As a result, it is judged that the suitability of the prediction model using data including mechanical data and ground information is high. In addition, research is needed to increase the diversity of ground conditions and the amount of data.

• The Journal of Sustainable Design and Educational Environment Research
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• v.21 no.2
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• pp.11-24
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• 2022

The purpose of this study is to derive a curriculum environment for operating various student-centered teaching and learning methods, and the following results were derived: First, most of the lectures, discussions and consultations, data search, report preparation, presentation, work exhibition, and others were commonly derived, regardless of the types of long-term and short-term project classes for each subject. In particular, the necessity of operating various classes at the same time was suggested, indicating the need for an integrated teaching and learning operation environment in the unit subject class. Second, considering that practical classes are linked concurrently to lectures and discussion classes to conduct one subject class, it is necessary to switch to a specialized curriculum system that allows various classes such as lectures to be carried out at the same time. Third, as a result of grasping the appropriateness of the space size of the subject class for realizing different class types in the future, it can be seen that the space size of the practice room, including the space for practice and the area for exhibition, should be expanded. Based on the research results, the spatial environment for the operation of future teaching and learning classes is based on the public curriculum classroom system, and whether professional curriculum classes, such as lecture rooms and discussion and presentation rooms, are secured according to the number of students.

• Journal of Internet Computing and Services
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• v.9 no.6
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• pp.141-153
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• 2008

E-learning is a new paradigm of education using Internet media. E-learning is rapidly expanding, since it is not restricted by time and space. However, due to the lack of standardization in e-learning, learning contents are developed redundantly. SCORM has been proposed to address this standardization problems. The mere learning contents are shared, the higher the reusability of contents becomes. Therefore, it is needed to develop methods or tools to help educators or content producers to create a learning course easily. In this paper, we propose an association method that could help educators or content producers to efficiently generate learning courses for a subject. The association method, a learning course generation method suggested by this paper, makes use of existing learning courses and learning contents to create new learning courses suitable to a subject. The association method analyzes statistical information of leaning objects derived from existing learning courses and measures coherence between learning objects to create a learning course. The association method suggested by this paper not only supports educators or content producers for easy generation of learning course but also offers a guideline for developing learning courses.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.295-303
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• 2022

This study compares two cases in which flipped learning is applied in the active learning classroom (ALC) and fixed classroom of advanced engineering education. To this end, the difference in pre-learning, academic achievement, and class satisfaction between ALC and fixed classroom flipped learning were compared. The results revealed that students in ALC flipped learning watched more video lectures for pre-learning than those in the fixed classroom flipped learning and achieved higher scores on final tests, though they obtained lower points on midterm exam. In addition, examination of class satisfaction with questions about class factors, instructor factors, and overall satisfaction revealed that ALC flipped learning showed higher satisfaction in all factors than the fixed classroom flipped learning. This case study suggests that the ALC environment, a learning space built to facilitate learner-centered activities, is more effective for flipped learning that requires active interaction in the classroom.