• Journal of Korea Multimedia Society
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• v.8 no.2
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• pp.287-295
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• 2005

For a quick and easy way of writing Hangul in hand-held devices, we analyzed the combination rules of Hangul alphabets that we constructed a small set of Hangul alphabets that combines a whole set of Hangul alphabets. Hangul consonants are generated from base set of consonants with function keys and vowels are constructed from eight base set of vowels by combination rules and stroke-adding rules. Especially, we adopted an easy error-correction method to resolve the inconvenience of using a delete key for vowel harmony errors. Futhermore, we diversified the input method of diphthongs for user-friendliness by minimizing the efforts of teaming vowel combination rules. We compared our method with previous methods of 'Chon-Ji-In' and 'Na-Rat-Keul' that the proposed method is better than the previous methods in input speed and error correction functionality.

• Journal of Korea Multimedia Society
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• v.5 no.5
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• pp.538-551
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• 2002

Even though the distance education via Web has a great advantage to overcome time and space, its problem that the management of trainees is not efficient compared with classroom and group education. This problem is a great obstacle to the objects and achievement standards of distance education, giving controversial arguments to the advocators of distance education. Distance educators need to monitor the trainees 'participation and responses continuously and offer appropriate feedback to the trainees. However, the existing distance education system only focuses on teaching and teaming activities, and as a result, the efficient management function of distance education is not available. Accordingly, the study attempts to find out the appropriate managing elements of distance teacher training in order to effectively achieve the goals of teacher training and the efficient management of distance education. Also, it proposes distance teacher training system that offers appropriate feedback to trainees, applying the derived elements of distance teacher training to the training processes. To verify the efficiency of the system, hypotheses on related items of distance teacher education and learning types are suggested, and the achievement of learning and its relations are investigated through questionnaire of learning types.

• Journal of Korea Multimedia Society
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• v.9 no.3
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• pp.369-376
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• 2006

In this paper, we propose an improved fuzzy RBF network which dynamically adjusts the rate of learning by applying the Delta-bar-Delta algorithm in order to improve the learning performance of fuzzy RBF networks. The proposed learning algorithm, which combines the fuzzy C-Means algorithm with the generalized delta learning method, improves its learning performance by dynamically adjusting the rate of learning. The adjustment of the learning rate is achieved by self-generating middle-layered nodes and by applying the Delta-bar-Delta algorithm to the generalized delta learning method for the learning of middle and output layers. To evaluate the learning performance of the proposed RBF network, we used 40 identifiers extracted from a container image as the training data. Our experimental results show that the proposed method consumes less training time and improves the convergence of teaming, compared to the conventional ART2-based RBF network and fuzzy RBF network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.684-689
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• 2005

In this paper, we propose car license plate recognition using morphological information and an enhanced neural network. Morphological information on horizontal and vertical edges was used to extract the license plate from a car image. We used a contour tracking algorithm combined with the method of histogram and location information to extract individual characters in the extracted plate. The enhanced neural network is proposed for recognizing them, which has the method of combining the ART-1 and the supervised teaming method. The proposed method has applied to real world car images. The experimental results show that the proposed method has better the extraction rates than the methods with information of the thresholding, the RGB and the HSI, respectively. And the proposed neural network has better recognition performance than the conventional neural networks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.4
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• pp.883-889
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• 2005

Error backpropagation algorithm of multilayer perceptron may result in local-minima because of the insufficient nodes in the hidden layer, inadequate momentum set-up, and initial weights. In this paper, we proposed the ART-1 based fuzzy supervised learning algorithm which is composed of ART-1 and fuzzy single layer supervised learning algorithm. The Proposed fuzzy supervised learning algorithm using self-generation method applied not only ART-1 to creation of nodes from the input layer to the hidden layer, but also the winer-take-all method, modifying stored patterns according to specific patterns. to adjustment of weights. We have applied the proposed learning method to the problem of recognizing a resident registration number in resident cards. Our experimental result showed that the possibility of local-minima was decreased and the teaming speed and the paralysis were improved more than the conventional error backpropagation algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.802-805
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• 2008

With the rapid increase of a population, various problems arise from poor education environment and devalued quality of education. Internet cyber School, a new learning system may be one of the best methods to remedy the situation. We conducted a related questionnaire on the high school in PUSAN city for the study of the cyber learning system. Many high school student agreed that Internet cyber education hour should be matched up with the school hour. They must make a use of the cyber school Service to help the students study by themselves. And we also decide that the implemented service will increase the psychological effect spreading to other teaming fields.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.11
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• pp.935-943
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• 2020

This paper presents a methodology for evaluating suitability of a manned-unmanned aerial vehicle team for a complicated mission. The study identified vehicle performance, equipment performance and level of autonomy as the key factors that affect the mission effectiveness. A manned and an unmanned aircraft were compared, and their performance was quantized in these respects. SEAD was chosen as a representative manned-unmanned team mission. The SEAD mission was broken down to a sequence of tasks. Mission experts evaluated the importance of each mark item for the mission legs. Combining the results showed proper type of aircraft for each leg depending on the complexity, safety, and importance of the task. Finally, the whole mission plan was laid out as a time-based sequence which alleviate pilot workload significantly.

• Journal of the Korean School Mathematics Society
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• v.2 no.1
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• pp.15-30
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• 1999

For the purpose of turning learners' locus of control into internal-controllable variables, counseling materials were developed, and attribution counseling was given. The counseling effects were practically confirmed by way of teaching and evaluation in the actual classes, and furthermore the efforts to provide learners with successful experiences in learning were repeatedly made. As a result, the conclusions are as follows: 1. The procedure of Individual counseling for learning attribution based on individual standard grades and data of the variable order of merit apparently shows learners that if learners are to try their best in learning, they will surely go far in terms of learning in the near future. 2. The procedure of Individual counseling for teaming attribution based on achievement distribution in individual behavior-oriented fields suggests to learners that how to learn is as important as how much effort they make. Surely enough, learners are required to make more effective and efficient efforts, considering their own learning abilities. 3. With the above 1, 2 procedures involved, learners have attributed locus of causality in achievement to their internal-controllable causes. 4. With preparatory assignments according to learner's abilities provided, even slower learners came to be assured that their constant efforts could give rise to success in learning achievement. 5. Above all, it was confirmed that the learners' struggling attitude might well have a significant correlation with achievement success. The learners who are willing to attribute locus of causality in achievement to their internal-controllable causes or strenuous efforts and intrinsic motivation tend to be convinced that they can address themselves to whatever faces them, so they can set up specific learning goals fit for their abilities. Accordingly, they will bit by bit acquire successful experiences (often called 'Aha' experiences) and in turn, feeling the senses of self-efficacy and self-esteem enough to push their efforts even further, they can grow to form a positive self-concept. With one successful experience after another fed back into learners, they are gradually motivated to bring the oncoming achievement expectation to a higher level. To conclude, it is necessary that instruction leading to internal-controllable attribution should be provided, inducing learners to recognize success and failure in learning achievement as a result of their strenuous efforts.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.385-395
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• 2005

Long sentence analysis has been a critical problem in machine translation because of high complexity. The methods of intra-sentence segmentation have been proposed to reduce parsing complexity. This paper presents the intra-sentence segmentation method based on maximum entropy probability model to increase the coverage and accuracy of the segmentation. We construct the rules for choosing candidate segmentation positions by a teaming method using the lexical context of the words tagged as segmentation position. We also generate the model that gives probability value to each candidate segmentation positions. The lexical contexts are extracted from the corpus tagged with segmentation positions and are incorporated into the probability model. We construct training data using the sentences from Wall Street Journal and experiment the intra-sentence segmentation on the sentences from four different domains. The experiments show about $88\%$ accuracy and about $98\%$ coverage of the segmentation. Also, the proposed method results in parsing efficiency improvement by 4.8 times in speed and 3.6 times in space.

• The KIPS Transactions:PartB
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• v.13B no.6 s.109
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• pp.625-632
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• 2006

Collaborative filtering is a technology that aims at teaming predictive models of user preferences. Collaborative filtering systems have succeeded in Ecommerce market but they have shortcomings of high dimensionality and sparsity. In this paper we propose the nearest neighbor collaborative filtering method using non-negative matrix factorization(NNMF). We replace the missing values in the user-item matrix by using the user variance coefficient method as preprocessing for matrix decomposition and apply non-negative factorization to the matrix. The positive decomposition method using the non-negative decomposition represents users as semantic vectors and classifies the users into groups based on semantic relations. We compute the similarity between users by using vector similarity and selects the nearest neighbors based on the similarity. We predict the missing values of items that didn't rate by a new user based on the values that the nearest neighbors rated items.