• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.8
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• pp.1596-1603
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• 2007

In this paper, we experimented by three kind of method for feature parameter, training method and recognition algorithm of most suitable for speech recognition system and considered. We decided speech recognition system of most suitable through two kind of experiment after we make speech recognizer. First, we did an experiment about three kind of feature parameter to evaluate recognition performance of it in speech recognizer using existent MFCC and MFCC new feature parameter that change characteristic space using PCA and ICA. Second, we experimented recognition performance or HMM, SVM and RVM by studying data number. By an experiment until now, feature parameter by ICA showed performance improvement of average 1.5% than MFCC by high linear discrimination from characteristic space. RVM showed performance improvement of maximum 3.25% than HMM in an experiment by decrease of studying data. As such result, effective method for speech recognition system to propose in this paper derives feature parameters using ICA and un recognition using RVM.

• Journal of Forest and Environmental Science
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• v.32 no.2
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• pp.164-172
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• 2016

This study examined the recognition differences between local residents and national park managers on the adjustment of national parks which are conducted every ten years for the purpose of providing basic information for the park management, according to the Natural Parks Act. Both local residents and national park managers positively perceived the adjustment of national parks, but park managers showed concern towards the damage of natural resources resulting from the cancellation and adjustment of restricted development districts in Korean national parks. Local residents are more likely than park managers to recommend boundary adjustment in other national parks regarding the influence of parks adjustment on local change. While local residents recognized that the boundary adjustment of national parks improves the level of community management, park managers focused on damages on the local environment and the park landscape adjacent to the areas. The result shows the recognition differences of local residents and park managers. Further research into adjustment of national parks is necessary to diminish perception gaps among stakeholders and develop prediction indicators of cancellation effect in response to the future cancellation areas of national parks through the characteristics of cancellation communities, revitalization of local economy, and environmental change of local community.

• Journal of Korean Elementary Science Education
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• v.30 no.3
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• pp.340-352
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• 2011

The purpose of this study was to analyze effects of teaching materials for elementary science gifted conception about object recognition. Elementary science gifted have misconceptions that they can see in lightness. They can not explain how a shadow is made. This paper reports in-depth investigation on elementary science gifted's understanding of object recognition focusing on process of light. A program is developed to elementary science gifted in the subject matter. The tutorial emphasizing the process of light consists of pre-test, worksheet, and post-test. The Tutorial has 4 steps; darkness and light, light on things, light reached eyes, structure of the eyes. Each steps has 2~4 experiments. Through the tutorial, we expect their misconceptions can be changed into scientific conceptions. For the research and analysis, a questionnaire is posed to 39 elementary science gifted at M Elementary School in D Metropolitan City. The first method of product analysis makes a comparative study of pre-test, post-test score, and hake gain each test. As a result, total score of all student was raised. And hake gain of pre-test(II) is 0.6, hake gain of post-test is 0.68. It is Medium gain. Also, elementary science gifted could understand how we see through the tutorial emphasizing process of light. And their misconceptions can be changed into scientific conceptions.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.9
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• pp.801-806
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• 2001

According as many people use a computer newly, damage of computer virus and hacking is rapidly increasing by the crucial users A computer virus is one of program in computer and has abilities of self reproduction ad destruction like a virus of biology. And hacking is to rob a person's data in a intruded computer and to delete data in a person s computer from the outside. To block hacking that is intrusion of a person s computer and the computer virus that destroys data, a study for intrusion-detection of system and virus detection using a biological immune system is in progress. In this paper, we make a model of positive selection and negative selection of self-recognition process that is ability of T-cytotoxic cell that plays an important part in biological immune system. So we embody a self-nonself distinction algorithm in computer, which is an important part when we detect an infected data by computer virus and a modified data by intrusion from the outside. The composed self-recognition process distinguishes self-file from the changed files. To prove the efficacy of self-recognition algorithm, we use simulation by a cell change and a string change of self file.

• Convergence Security Journal
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• v.19 no.1
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• pp.67-78
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• 2019

Most existing facial expression recognition methods use a uniform grid method that divides the entire facial image into uniform blocks when describing facial features. The problem of this method may include non-face backgrounds, which interferes with discrimination of facial expressions, and the feature of a face included in each block may vary depending on the position, size, and orientation of the face in the input image. In this paper, we propose a variable-size block method which determines the size and position of a block that best represents meaningful facial expression change. As a part of the effort, we propose the way to determine the optimal number, position and size of each block based on the facial feature points. For the evaluation of the proposed method, we generate the facial feature vectors using LDTP and construct a facial expression recognition system based on SVM. Experimental results show that the proposed method is superior to conventional uniform grid based method. Especially, it shows that the proposed method can adapt to the change of the input environment more effectively by showing relatively better performance than exiting methods in the images with large shape and orientation changes.

• Communications of Mathematical Education
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• v.29 no.3
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• pp.513-532
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• 2015

In order to suggest desirable management of college mathematics for freshmen in middle level engineering college, we analyse the change of mathematics recognition between 2011 year and 2015 year freshmen who took college scholastic ability test which are based on the national mathematics curriculum 7th and 7th revision, respectively. In A university, 2011 year and 2015 year engineering freshmen were taken basic mathematical ability test and given the survey for the recognition of mathematics and college mathematics. Research results are as follows: First of all, middle level engineering freshmen were poor at basic mathematical ability. The change of mathematics recognition appeared in the level of mathematics ability and the effort for college mathematics class. Moreover middle level engineering freshmen recognize college mathematics as a basic subject for engineering and hope teacher-directed learning in college mathematics class. For the success of college mathematics in engineering college, this study suggests basic mathematical ability test and the survey for the recognition of mathematics and college mathematics. We also suggest that college mathematics class must be focused on basic mathematical ability improvement and self-directed learning.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.3
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• pp.344-355
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• 2002

Having a variety of good characteristics against other pattern recognition techniques, Multilayer Perceptron (MLP) has been used in wide applications. But, it is known that Error Backpropagation (EBP) algorithm which MLP uses in learning has a defect that requires relatively long leaning time. Because learning data in pattern recognition contain abundant redundancies, in order to increase learning speed it is very effective to use online-based teaming methods, which update parameters of MLP pattern by pattern. Typical online EBP algorithm applies fixed learning rate for each update of parameters. Though a large amount of speedup with online EBP can be obtained by choosing an appropriate fixed rate, fixing the rate leads to the problem that the algorithm cannot respond effectively to different leaning phases as the phases change and the learning pattern areas vary. To solve this problem, this paper defines learning as three phases and proposes a Instant Learning by Varying Rate and Skipping (ILVRS) method to reflect only necessary patterns when learning phases change. The basic concept of ILVRS is as follows. To discriminate and use necessary patterns which change as learning proceeds, (1) ILVRS uses a variable learning rate which is an error calculated from each pattern and is suppressed within a proper range, and (2) ILVRS bypasses unnecessary patterns in loaming phases. In this paper, an experimentation is conducted for speaker verification as an application of pattern recognition, and the results are presented to verify the performance of ILVRS.

• Journal of the Korean Society of Earth Science Education
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• v.9 no.3
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• pp.323-340
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• 2016

The purpose of this study is to investigate the effect of observing material on the phase change of moon considering the orbits of earth and moon for elementary school students. For this study, the material which shows the orbit of moon tilted at $5^{\circ}$ with the orbit of earth is developed. 110 6th grade students in an elementary school are sampled. They are divided into the experimental group and the control group. The lessons using the material developed in this study are implemented to the experimental group, and the lessons using the material proposed in ordinary textbook are implemented to the control group. The pre, post, delayed concept tests on the phase change of moon are administered to the students of the experimental group and the control group, and semi-structured interviews are conducted for each concept level. According to students' responses, the concept levels are divided into 'Phase recognition', 'Space viewpoint', 'Earth viewpoint', and 'No recognition'. The experimental group and the control group are homogeneous in the pre-test. The result of this study shows that the experimental group gains significantly more scores than the control group in the post and delayed tests. Also, in the post and delayed tests, more students of the experimental group are in the highest level 'Phase recognition' than the control group. Finally, students of the experimental group who were in the 'Phase recognition' and 'Space viewpoint' explain more scientifically than the students of the control group. Therefore the results of this study show that the observing material on the phase change of moon considering the orbits of earth and moon is effective.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.587-598
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• 2022

To increase building change recognition accuracy, we present a deep learning-based building change detection using remote sensing images. In the proposed approach, by merging pixel-level and object-level information of multitemporal remote sensing images, we create the difference image (DI), and the frequency-domain significance technique is used to generate the DI saliency map. The fuzzy C-means clustering technique pre-classifies the coarse change detection map by defining the DI saliency map threshold. We then extract the neighborhood features of the unchanged pixels and the changed (buildings) from pixel-level and object-level feature images, which are then used as valid deep neural network (DNN) training samples. The trained DNNs are then utilized to identify changes in DI. The suggested strategy was evaluated and compared to current detection methods using two datasets. The results suggest that our proposed technique can detect more building change information and improve change detection accuracy.

• Journal of Fashion Business
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• v.21 no.4
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• pp.61-72
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• 2017

The purpose of this study was to analyze the impact of climate change cognition on clothing behavior of fashion consumers to understand the impact of climate change on the fashion system. An online survey was conducted of 385 people in their 20s-50s working in the fashion industry as well as general consumers. Data collected from surveys were analyzed by factor analysis and t-test. Results are as follow: First, climate change cognition consists of four sub-dimensions, which are 'knowledge of climate change' and 'recognition of climate change in Korea'. Second, clothing behavior related with climate change consists of six sub-dimensions, which are 'environmentally-friendly fashion purchases', 'new clothes-wearing style affected by climate change', 'ethical fashion consumption', 'pursuit of functional fashion', 'pursuit of seasonless fashion', and 'clothes-wearing in response to climate change.' Last, the group with higher cognition of climate change than the group with lesser cognition had significantly higher degree of trying new styles created because of climate change, making ethical fashion purchases, pursuing functional fashion, and wearing clothes in response to climate change.