• Phonetics and Speech Sciences
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• v.14 no.2
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• pp.11-17
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• 2022

English vowels play an important role in verbal communication. However, Korean students tend to experience difficulty pronouncing a certain set of vowels despite extensive education in English. The aim of this study is to apply speech recognition software to evaluate Korean students' pronunciation of English vowels in minimal pair words and then to examine acoustic characteristics of the pairs in order to check their pronunciation problems. Thirty female Korean college students participated in the recording. Speech recognition rates were obtained to examine which English vowels were correctly pronounced. To compare and verify the recognition results, such acoustic analyses as the first and second formant trajectories and durations were also collected using Praat. The results showed an overall recognition rate of 54.7%. Some students incorrectly switched the tense and lax counterparts and produced the same vowel sounds for qualitatively different English vowels. From the acoustic analyses of the vowel formant trajectories, some of these vowel pairs were almost overlapped or exhibited slight acoustic differences at the majority of the measurement points. On the other hand, statistical analyses on the first formant trajectories of the three vowel pairs revealed significant differences throughout the measurement points, a finding that requires further investigation. Durational comparisons revealed a consistent pattern among the vowel pairs. The author concludes that speech recognition and analysis software can be useful to diagnose pronunciation problems of English-language learners.

• Culinary science and hospitality research
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• v.15 no.3
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• pp.324-343
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• 2009

The purpose of this study is to identify the effect of the risk communication of the food service industry on consumers' psychological response and attitude. The result is as follows. First, as for the relation between risk communication and information reliance, when the recognition of risk communication stability gets higher, information reliance rose; when the recognition of risk gets higher, information reliance rose with higher recognition of morality. Second, as for the relation between risk communication and risk recognition, when the recognition of risk communication stability gets higher, risk recognition rose; when the recognition of risk gets higher, risk recognition rose with higher recognition of environment and the information reliance rose with higher recognition of morality. Third, as for the relation between the information reliance of risk communication and risk recognition, when the information reliance of risk communication gets higher, risk recognition rose.

• Hwankyungkyoyuk
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• v.20 no.2
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• pp.93-107
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• 2007

Livestock agriculture plays an essential role Hongsung's economy. Unfortunately, if manure is manage properly it can contaminate water and pollute the air. The purposes of this study were to provide awareness of environmental impact and to design educational programs with sustainable agriculture. I used the specific steps of processes. First, collecting informations through survey on environmental awareness of livestock farmers in Hongsung-gun and recognizing the tendencies. Second, analyzing on educational status of livestock farmers. Third, finding objectives of environmental educational programs. At the end of processes, establishing programs which concerning on environmental education. I used two research methods to gather and analyze the data for developing an environmental education program. The first one is a general survey among 50 livestock farmers from Hongseong-gun, Chungcheongnam-do. The second one is the in-depth interviews with specialists in environmental education and government officials from the central government - the Ministry of Agriculture and Forestry - and the local government - Hongsung-gun who are in charge of livestock farming. I found the following results from this research. First, most livestock farmers replied with 'highly likely' to the five items on the recognition of the necessity of environment preservation, whereas only 38.7% answered with 'likely' to the item on the environmental pollution caused by livestock farming. This shows the tendency that they have less recognition of the reality than necessary. Second, most of the contents among 5 areas(knowledge, recognition, function, attitude, and participation) are the knowledge areas. That results are analyzed training materials for livestock farmers made by Hongsung-gun in 2004 and in 2005 by using goal categories suggested in the Tbilisi Resolution. Third, after analyzing the survey and in-depth interviews, I found that the need for education to recognize the environmental pollution, environmental protection and recycling of the livestock waste. We can summarize conclusions from this research. First, we need on educational program improve the livestock farmers' recognition of importance in environmental protection. Second, it is necessary to develop educational program with the viewpoint that livestock waste is not one of the culprits of the environmental pollution, but a recyclable resource. Third, contents of the environmental education program, should include all the educational elements, namely, knowledge, recognition, attitude, function and participation. The education for livestock farmers requires a research on the environmental education program that can be used with crop farmers who can use the resources recycled from the livestock waste from the viewpoint of recycling resources. This research is focused on the collection and analysis of the basic data for developing an environmental education program and the composition of the program. A further research on the implementation and assessment of this program is required.

• Journal of the Korea Fashion and Costume Design Association
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• v.16 no.1
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• pp.77-89
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• 2014

This study looked into the effect of the life style of single females in 20s and 30s on beauty behavior recognition, and spss 17.0 is used for data analysis method. As for the statistical analysis method in order to validate the measurement tools, reliability verification is conducted and life style groups are sampled using K-means taking into account factor scores by life style. To find out the difference between general beauty behavior recognition and life style, descriptive statistics and One Way ANOVA were carried out, and Duncan Test was implemented for the post examination method. Multiple regression analysis was also carried out to figure out the effect of life style on beauty behavior recognition. The result is as follows. First, according to the results of reliability verification and factor analysis for the lifestyle type and the recognition of the behavior for beauty, the types of the life style of the subjects were divided into Economic Utility, Convention Conservatism, Self Development, Showy Consumption, and Appearance Oriented, and the recognition of the behavior for beauty was named as Makeup and Hair, Cosmetic Surgery, Body Care, and Skin Care. Second, as to the recognition of the behavior for beauty based upon the lifestyle, the Appearance Oriented in Showy Consumption recorded the highest. Third, the analysis of the influence of the style on the recognition of the behavior for beauty showed that the behavior recognition for Makeup and Hair and for Skin Care was affected by the life style of Self Development, Showy Consumption, and Appearance Oriented; the behavior recognition for Cosmetic Surgery was affected by the life style of Conventional Conservatism, Showy Consumption, and Appearance Oriented; and again the behavior recognition for Body Care was by that of Economical Utility and Showy Consumption.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.455-458
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• 2001

In this paper, a new license plate recognition method using the morphological size distribution functions and color images is proposed. The proposed method consists of two steps. The first step is license plate extraction process using the plate color and step edge information in the license plate. The second step is the extraction of character feature vectors using the morphological size distribution functions and character recognition process using the MLP(multilayer perceptron). By the use of morphological size distributions functions, the error that may occur during the character region extraction process is lessened and the recognition performances are improved by the decrease of feature vector dimension.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1937-1943
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• 2005

The technology of emotion recognition is a crucial factor in day of ubiquitous that it provides various intelligent services for human. This paper intends to make the system which recognizes the human emotions based on 2-dimensional model with two bio signals, GSR and HRV. Since it is too difficult to make model the human's bio system analytically, as a statistical method, Hidden Markov Model(HMM) is used, which uses the transition probability among various states and measurable observation variance. As a result of experiments for each emotion, we can get average recognition rates of 64% for first HMM results and 55% for second HMM results

• The Journal of Korea Robotics Society
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• v.10 no.1
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• pp.16-23
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• 2015

This paper presents a method of improving the pose recognition accuracy of objects by using Kinect sensor. First, by using the SURF algorithm, which is one of the most widely used local features point algorithms, we modify inner parameters of the algorithm for efficient object recognition. The proposed method is adjusting the distance between the box filter, modifying Hessian matrix, and eliminating improper key points. In the second, the object orientation is estimated based on the homography. Finally the novel approach of Auto-scaling method is proposed to improve accuracy of object pose estimation. The proposed algorithm is experimentally tested with objects in the plane and its effectiveness is validated.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.195-198
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• 2003

The accuracy of automatic speech recognition system depends on the presence of background noise and speaker variability such as sex, intonation of speech, and speaking rate. Specially, the speaking rate of both inter-speaker and intra-speaker is a serious cause of mis-recognition. In this paper, we propose the compensation method of the speaking rate by the ratio of each vowel's length in a phrase. First the number of feature vectors in a phrase is estimated by the information of speaking rate. Second, the estimated number of feature vectors is assigned to each syllable of the phrase according to the ratio of its vowel length. Finally, the process of feature vector extraction is operated by the number that assigned to each syllable in the phrase. As a result the accuracy of automatic speech recognition was improved using the proposed compensation method of the speaking rate.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2327-2330
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• 2003

This paper deals with face detection and recognition using ellipsodal information and wavelet packet analysis. We proposed two methods. First, Face detection method uses general ellipsodal information of human face contour and we find eye position on wavelet transformed face images A novel method for recognition of views of human faces under roughly constant illumination is presented. Second, The proposed Face recognition scheme is based on the analysis of a wavelet packet decomposition of the face images. Each face image is first located and then, described by a subset of band filtered images containing wavelet coefficients. From these wavelet coefficients, which characterize the face texture, the Euclidian distance can be used in order to classify the face feature vectors into person classes. Experimental results are presented using images from the FERET and the MIT FACES databases. The efficiency of the proposed approach is analyzed according to the FERET evaluation procedure and by comparing our results with those obtained using the well-known Eigenfaces method. The proposed system achieved an rate of 97％(MIT data), 95.8％(FERET databace)

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2355-2358
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• 2003

The purpose of this paper is to investigate two major feature extraction techniques based on generic modular face recognition system. Detailed algorithms are described for principal component analysis (PCA) and independent component analysis (ICA). PCA and ICA ate statistical techniques for feature extraction and their incorporation into a face recognition system requires numerous design decisions. We explicitly state the design decisions by introducing a modular-based face recognition system since some of these decision are not documented in the literature. We explored different implementations of each module, and evaluate the statistical feature extraction algorithms based on the FERET performance evaluation protocol (the de facto standard method for evaluating face recognition algorithms). In this paper, we perform two experiments. In the first experiment, we report performance results on the FERET database based on PCA. In the second experiment, we examine performance variations based on ICA feature extraction algorithm. The experimental results are reported using four different categories of image sets including front, lighting, and duplicate images.