• The Mathematical Education
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• v.62 no.2
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• pp.211-236
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• 2023

The purpose of this study is to derive implications of preservice mathematics teacher education in Korea by analyzing the case of edTPA used in the preservice teacher training process in the United States. Recently, there has been a growing interest in promoting professional competencies considering not only the cognitive dimension related to knowledge development of preservice mathematics teachers but also the situational dimension considering reality in the classroom. The edTPA in the United States is a performance-based assessment based on lessons conducted by preservice teachers at school. This study analyzes the professional competencies required of preservice mathematics teachers by analyzing handbooks that described the case of edTPA in which preservice mathematics teachers in the United States participate. The edTPA includes planning, instruction, and assessment tasks, and continuous tasks are performed in connection with classes. Thus, the analysis is conducted on the points of linkage between the description of evaluation items and criteria in the planning, instruction, and assessment tasks, as well as the professional competencies required from that linkage. As a result of analyzing the edTPA handbooks, the professional competencies required of preservice mathematics teachers in the edTPA assessment were the competency to focus on and implement specific mathematics lessons, the competency to reflectively understand the implementation and assessment of specific mathematics lessons, and the competency to make a progressive determination of students' achievement related to their learning and their uses of language and representations. The results of this analysis can be used as constructs for competencies that can be assessed in the preservice in the organization of the preservice mathematics teacher curriculum and practice training semester system in Korea.

• Therapeutic Science for Rehabilitation
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• v.12 no.2
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• pp.69-83
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• 2023

Objective : This study, as a preliminary study, applied an Information & Communication Technology (ICT) home-based program to elderly people aged 65 years or older to confirm the effect of the cognitive enhancement program and to find the possibility of remote rehabilitation. Methods : This study from August to October 2022, three subjects were selected and the intervention was conducted for about 2 months. This intervention was conducted using Korean version of Mini-Mental State Examination, Korean version of Montreal Cognitive Assessment (MoCA-K), Computer Cognitive Senior Assessment System, and the Center for Epidemiologic Studies Depression scale to evaluate cognitive improvement before and after the program. The therapist remotely set the level of cognitive training according to the subject's level through weekly feedback. Results : After the intervention, all subjects showed improved scores in most items of the MoCA-K conducted before and after the intervention. In addition, among the items of Cotras-pro, upper cognition, language ability, attention, visual perception, and memory were improved. Conclusion : Cognitive rehabilitation training using an ICT home-based program not only prevented dementia but also made it habitual. Through this study, it was confirmed that remote rehabilitation for the elderly could be possible.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.127-142
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• 2016

Deep learning model is a kind of neural networks that allows multiple hidden layers. There are various deep learning architectures such as convolutional neural networks, deep belief networks and recurrent neural networks. Those have been applied to fields like computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics where they have been shown to produce state-of-the-art results on various tasks. Among those architectures, convolutional neural networks and recurrent neural networks are classified as the supervised learning model. And in recent years, those supervised learning models have gained more popularity than unsupervised learning models such as deep belief networks, because supervised learning models have shown fashionable applications in such fields mentioned above. Deep learning models can be trained with backpropagation algorithm. Backpropagation is an abbreviation for "backward propagation of errors" and a common method of training artificial neural networks used in conjunction with an optimization method such as gradient descent. The method calculates the gradient of an error function with respect to all the weights in the network. The gradient is fed to the optimization method which in turn uses it to update the weights, in an attempt to minimize the error function. Convolutional neural networks use a special architecture which is particularly well-adapted to classify images. Using this architecture makes convolutional networks fast to train. This, in turn, helps us train deep, muti-layer networks, which are very good at classifying images. These days, deep convolutional networks are used in most neural networks for image recognition. Convolutional neural networks use three basic ideas: local receptive fields, shared weights, and pooling. By local receptive fields, we mean that each neuron in the first(or any) hidden layer will be connected to a small region of the input(or previous layer's) neurons. Shared weights mean that we're going to use the same weights and bias for each of the local receptive field. This means that all the neurons in the hidden layer detect exactly the same feature, just at different locations in the input image. In addition to the convolutional layers just described, convolutional neural networks also contain pooling layers. Pooling layers are usually used immediately after convolutional layers. What the pooling layers do is to simplify the information in the output from the convolutional layer. Recent convolutional network architectures have 10 to 20 hidden layers and billions of connections between units. Training deep learning networks has taken weeks several years ago, but thanks to progress in GPU and algorithm enhancement, training time has reduced to several hours. Neural networks with time-varying behavior are known as recurrent neural networks or RNNs. A recurrent neural network is a class of artificial neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Unlike feedforward neural networks, RNNs can use their internal memory to process arbitrary sequences of inputs. Early RNN models turned out to be very difficult to train, harder even than deep feedforward networks. The reason is the unstable gradient problem such as vanishing gradient and exploding gradient. The gradient can get smaller and smaller as it is propagated back through layers. This makes learning in early layers extremely slow. The problem actually gets worse in RNNs, since gradients aren't just propagated backward through layers, they're propagated backward through time. If the network runs for a long time, that can make the gradient extremely unstable and hard to learn from. It has been possible to incorporate an idea known as long short-term memory units (LSTMs) into RNNs. LSTMs make it much easier to get good results when training RNNs, and many recent papers make use of LSTMs or related ideas.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.372-381
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• 2009

Recently, the number of children of multi-cultural family is increasing and the achievement gap between city and farming village is getting larger. It will be alternatives to develop e-learning contents which students can study by themselves where there are internet connected computers. As one of the solutions to improve students' writing ability, we developed animation e-learning contents about manuscript paper usage and sentence signs. As a result of applying e-learning contents to students, we can make sure that e-learning contents are more effective than existing means such as workbook-centered education and web contents persuaded by text in academic interesting, satisfaction and achievement. Consequently, we offer this training methods as alternatives which can increase academic performance for multi-cultural family and Korean students who are behind the other students in language ability.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.35 no.6
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• pp.437-447
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• 2013

The fibula is one of the most useful sources for harvest of a vascularized bone graft. The fibula is a straight, long, tubed bone, much stronger than any other available bone that can currently be used for a vascularized graft. It has a reliable peroneal vascular pedicle with a large diameter and moderate length. There is a definite nutrient artery that enters the medullary cavity, as well as multiple arcade vessels, which add to the supply of the bone through periosteal circulation. The vascularized fibula graft is used mainly for long segment defects of the long tubed bone of the upper and lower extremities. It can provide a long, straight length up to 25 cm in an adult. The fibula can be easily osteotomized and can be used in reconstruction of the curved mandible. Since the first description as a vascularized free fibula bone graft by Taylor in 1975 and as a mandibular reconstruction by Hidalgo in 1989, the fibula has continued to replace the bone and soft tissue reconstruction options in the field of maxillofacial reconstruction. For the better understanding of a fibular free flap, the constant anatomical findings must be learned and memorized by young doctors during the specialized training course for the Korean National Board of Oral and Maxillofacial Surgery. This article reviews the anatomical basis of a fibular free flap with Korean language.

• The Journal of Industrial Distribution & Business
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• v.11 no.2
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• pp.33-39
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• 2020

Purpose: The purpose of this study is that victims of technology leaks and people concerned about leaks complain of stress over security concerns. However, there are no psychological treatments among the government's comprehensive plans to prevent technology leaks. Therefore, the government intends to present education methods using the NLP (Neuro Linguistic Program), a collective counseling technique, to heal the psychological injury of the victims. Psychological counseling methods include cognitive behavioral therapy, psychoanalytic behavioral therapy, humanism therapy, art therapy, and other psychological therapies. Among them, NLP (Neuro Linguistic Programming) method was used. NLP has three concepts: neuron, language, and programming, and is used as a general method for group counseling. Research design, data and methodology: In relation to composition, Chapter 1 explained the purpose and necessity of the study, Chapter 2 explained the types of psychological counseling and NLPs to help understand the study, introduced the prior study related to the development of collective counseling programs through NLP, and Chapter 3 developed a security psychological counseling education program. In addition, FGI(Focus Group Interview) was conducted for professionals. Results: Corporate counseling considered most in this study should satisfy client, counselor and manager differently from individual counseling. For this purpose, the result was composed of 11 times. In order to derive personal problems for clients, they consisted of finding, loving, expressing, and emancipating self. And, It solved the leakage anxiety to suggest a professional solution for the counselor. In addition, this course helps them become familiar with counseling techniques for becoming a good security administrator. Lastly, it was configured to leave the result for the manager to suggest the organizational development method through this training. The implication of this study is to derive psychological counseling methods for security officers. Most companies in the field of security counseling complain about technology leakage stress. There is currently no psychotherapy support project under the policy. And It was developed because it can expect sales improvement from security consultation. Conclusions: In conclusion, the results were organized to be left to the manager so that he could suggest how to develop the organization through this time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.7
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• pp.4798-4804
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• 2015

The aim of this study is evaluate the effect of a cognitive occupational therapy program on cognitive function, depression and hands function for patients with dementia living in a local community. A cognitive rehabilitation program of 10 weeks focusing on the occupational therapy is conducted from September to December 2012 on 21 patents (experimental group: 12, control group: 9) with dementia who are admitted to nursing homes in a metropolitan region. In the experimental group, the cognitive function, depression level, hand strength, and hand coordination ability is significantly improved after the application of the cognitive program (p<.05). In conclusion, the cognitive occupational therapy program may be a useful intervention for dementia. Because the therapeutic goal for dementia treatment is mainly concentrated on the amelioration of dementia symptoms, thus it is necessary to develop a various cognition training program that can be maintained the patient's residual functional capacity and returned to the social community through the early detection and the early intervention.

• International Commerce and Information Review
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• v.17 no.2
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• pp.307-327
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• 2015

Trade education methods that combine practical knowledge and on-site job training have significantly contributed in improving abilities of trade experts. For instance, GTEP and LINC have contributed to a substantial expansion of SME export performane. Moreover, students' cooperation experience have led to employment outcomes as SMEs can employ customized trade workers. I have conducted a survey to 100 students about university-industry collaboration. Results show that ICT skills and foreign language ability are the highest required conditions of employment while production and technology knowledge are the lowest. Furthermore, 50 companies operating in foreign markets responded that through industry-university cooperation, capabilities of university graduates have improved and trade education cooperation scheme is a success.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.85-94
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• 2017

In this paper, I proposed a sound model generation and a most frequent model search algorithm for recognizing animal vocalization. The sound model generation algorithm generates a optimal set of models through repeating processes such as the training process, the Viterbi Search process, and the most frequent model search process while adjusting HMM(Hidden Markov Model) structure to improve global recognition rate. The most frequent model search algorithm searches the list of models produced by Viterbi Search Algorithm for the most frequent model and makes it be the final decision of recognition process. It is implemented using MFCC(Mel Frequency Cepstral Coefficient) for the sound feature, HMM for the model, and C# programming language. To evaluate the algorithm, a set of animal sounds for 27 species were prepared and the experiment showed that the sound model generation algorithm generates 27 HMM models with 97.29 percent of recognition rate.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.292-295
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• 2006

As Chinese characters occupies more than 70% of words we currently use, the education of Chinese characters is becoming important day by day to accurately deliver the meaning of words in our language life. In recent, there are increasing concerns on writing Chinese characters correctly as well as reciting, books and Internet contents on Chinese character writing is emerging. However, currently available Internet media on the Chinese characters education only illuminates recitation and interpretation. Moreover, the writing part is merely provided in the form of paper by printing the characters, thus, writing materials are insufficient. In this paper, we propose a design and implementation of Web based Chinese characters writing system. Using the system, a user can write Chinese characters with mouse device. The learning progress is accordingly managed for the user. In addition, the proposed system can be used any place in where Internet is connected.