• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.51-56
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• 2007

Feature functions were used for the classification of music. The spectral roll-off, variance, average peak level, and class were chosen to make up a feature function vector. Among these, it is the spectral roll-off function that has a low-frequency to high-frequency ratio. To find the optimal roll-off point, the roll-off points from 0.05 to 0.95 were swept. The classification success rate was monitored as the roll-off point was being changed. The data that were used for the experiments were taken from the sounds made by a modern violin and a baroque one. Their shapes and sounds are similar, but they differ slightly in sound texture. As such, the data obtained from the sounds of these two kinds of violin can be useful in finding an adequate roll-off point. The optimal roll-off point, as determined through the experiment, was 0.85. At this point, the classification success rate was 85%, which was the highest.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.384-390
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• 2020

The reverberation effect on the sound when producing movies or VR contents is a very important factor in the realism and liveliness. The reverberation time depending the space is recommended in a standard called RT60(Reverberation Time 60 dB). In this paper, we propose a scene recognition technique for automatic reverberation editing. To this end, we devised a classification model that independently trains color images and predicted depth images in the same model. Indoor scene classification is limited only by training color information because of the similarity of internal structure. Deep learning based depth information extraction technology is used to use spatial depth information. Based on RT60, 10 scene classes were constructed and model training and evaluation were conducted. Finally, the proposed SCR + DNet (Scene Classification for Reverb + Depth Net) classifier achieves higher performance than conventional CNN classifiers with 92.4% accuracy.

• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.689-698
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• 2006

Pattern recognition is the study of how machines can observe the environment, learn to distinguish patterns of interest from their background, and make sound and reasonable decisions about the categories of the patterns. Color image consists of various color patterns. And most pattern recognition methods use the information of color which has been trained and extract the feature of the color. This thesis extracts adaptively specific color feature from images with several limited colors. Because the number of the color patterns is limited, the distribution of the color in the image is similar. But, when there are some noises and distortions in the image, its distribution can be various. Therefore we cannot extract specific color regions in the standard image that is well expressed in special color patterns to extract, and special color regions of the image to test. We suggest new method to reduce the error of recognition by extracting the specific color feature adaptively for images with the low distortion, and six test images with some degree of noises and distortion. We consequently found that proposed method shouws more accurate results than those of statistical pattern recognition.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.225-233
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• 2024

Active sonar transmits sound waves to detect covertly maneuvering underwater objects and detects the signals reflected back from the target. However, in addition to the target's echo, the active sonar's received signal is mixed with seafloor, sea surface reverberation, biological noise, and other noise, making target recognition difficult. Conventional techniques for detecting signals above a threshold not only cause false detections or miss targets depending on the set threshold, but also have the problem of having to set an appropriate threshold for various underwater environments. To overcome this, research has been conducted on automatic calculation of threshold values through techniques such as Constant False Alarm Rate (CFAR) and application of advanced tracking filters and association techniques, but there are limitations in environments where a significant number of detections occur. As deep learning technology has recently developed, efforts have been made to apply it in the field of underwater target detection, but it is very difficult to acquire active sonar data for discriminator learning, so not only is the data rare, but there are only a very small number of targets and a relatively large number of non-targets. There are difficulties due to the imbalance of data. In this paper, the image of the energy distribution of the detection signal is used, and a classifier is learned in a way that takes into account the imbalance of the data to distinguish between targets and non-targets and added to the existing technique. Through the proposed technique, target misclassification was minimized and non-targets were eliminated, making target recognition easier for active sonar operators. And the effectiveness of the proposed technique was verified through sea experiment data obtained in the East Sea.

• Journal of the Korean Society of Fashion and Beauty
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• v.5 no.1 s.12
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• pp.34-50
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• 2007

This study was designed to measure customer awareness about their own scalp and hair treatment based on survey, through the theoretical background of scalp physiology field by considering scalp and hair treatment. This was to provide a principal data about scalp and hair treatment for the beauty industry. Also, the data about the awareness of customers will be used to search for a direction far basic beauty services in the scalp and hair treatment field. Four hundred customers in beauty parlors, dermatology clinics, skin care institutes, and scalp institutes, living in the North Cheolla Province were surveyed. They were 25 years old and over. The surveys were performed over a period of ten days from November 18th to 28th in 2005. The collected data was analyzed by SPSS. Frequency and percentage were used to draw typical feature of subjects. Chi-square test, frequencies, t-test and One-way ANOVA were performed to consider awareness of customers for hair treatment as well as hair character and scalp hair. This study was able to estimate the awareness of customers by putting together between the recognition of scalp based on the special quality of hair and the recognition of hair and scalp treatment. In conclusion, the scalp and hair did not act independently. In order to have healthy hair, one must posses a healthy, and physiologically sound scalp. In order for beauticians to properly serve their clientele who require hair and scalp treatment, one must be able to comprehend and understand the field of scalp and hair treatment.

• Culinary science and hospitality research
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• v.19 no.2
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• pp.76-92
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• 2013

This study aimed to investigate major satisfaction and career maturity according to the values of college students majoring in food management and culinary arts. To do this, frequency analysis, factor analysis, correlation analysis, and multiple regression were conducted and analyzed using SPSS18.0 program. Analysis results indicate that the values of the college students majoring in dining and culinary education have effects on major satisfaction and career maturity. In particular, pragmatic value is a very important factor in increasing major satisfaction and career maturity, and social recognition and curriculum factors are very significant for students to make career decisions. Therefore, in order to enhance college students' major satisfaction and career maturity, it's necessary to teach sound values so that they can build self-esteem value. Also, it's essential to organize subject contents and curriculums in which theory and practice are allocated properly so that students can be interested in their majors and have new experience as well as the community's right recognition for college students majoring in dinning and culinary education and their active interest as the study suggests.

• Health Policy and Management
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• v.26 no.4
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• pp.256-264
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• 2016

Equity-focused public health policy has solid theoretical and practical basis, in addition to ethical one. In the Republic of Korea (hereafter Korea), however, equity in health has not had a high priority in policy goals, regardless of policy areas and particular actors or approaches. Equitable health has been only a minor concern in most public health issues and their decision-making. Generic public health policies are needed to reduce inequity in health, but the importance of a firm basis for sound policy-making cannot be overemphasized. Health equity should be 'mainstreamed' in all public health policies. Potential approaches include intersectoral collaboration, health impact assessment, and 'Health in All Policies.' Public policy agendas for equitable health cannot be formulated without measurement and recognition of the problem. Korea is still suffering from the lack of reliable information on the current status of health inequity, resulting in a relatively weak awareness of the problem among both the general public and policy-makers. More information is needed to increase recognition and awareness that will increase intervention and actions. The absence of decision-making and actions should not be justified even by the lack of information on determinants and pathways of health inequities. Generic plausible solutions can often work in the real world according to political and social commitment. I have discussed several aspects of public health policy from the perspective of health equity, focusing on current status and plausible explanation. Policy process, agenda setting in particular, is highlighted and theories and concepts are presented along with analysis and description of current situation.

• Journal of Science and Technology Studies
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• v.1 no.2 s.2
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• pp.399-422
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• 2001

Models for human cognition currently discussed in cognitive science cannot be appropriate ones. The symbolic model of the traditional artificial intelligence works for reasoning and problem-solving tasks, but doesn't fit for pattern recognition such as letter/sound cognition. Connectionism shows the contrary phenomena to those of the traditional artificial intelligence. Connectionist systems has been shown to be very strong in the tasks of pattern recognition but weak in most of logical tasks. Brooks' situated action theory denies the. notion of representation which is presupposed in both the traditional artificial intelligence and connectionism and suggests a subsumption model which is based on perceptions coming from real world. However, situated action theory hasn't also been well applied to human cognition so far. In emphasizing those characteristics of models I refer those models 'left-brain model', 'right-brain model', and 'robot model' respectively. After I examine those models in terms of substantial items of cognitions- mental state, mental procedure, basic element of cognition, rule of cognition, appropriate level of analysis, architecture of cognition, I draw three arguments of embodiment. I suggest a way of unifying those existing models by examining their theoretical compatability which is found in those arguments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1397-1406
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• 2019

In everyday mobile phone calls between the disabled and non-disabled people due to neurological impairment, the communication accuracy is often hindered by combining the accuracy of pronunciation due to the neurological impairment and the pronunciation features of the disabled. In order to improve this problem, the limiting method is MEMS (micro electro mechanical systems), which includes an induction line that artificially corrects difficult vocalization according to the oral characteristics of the language impaired by improving the word of out of vocabulary. mechanical System) Microphone device improvement. S/W improvement is decision tree with invert function, and improved matrix-vector rnn method is proposed considering continuous word characteristics. Considering the characteristics of H/W and S/W, a similar dictionary was created, contributing to the improvement of speech intelligibility for smooth communication.

• Journal of Audiology & Otology
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• v.24 no.4
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• pp.180-190
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• 2020

Background and Objectives: Although many studies have evaluated the effect of the digital noise reduction (DNR) algorithm of hearing aids (HAs) on speech recognition, there are few studies on the effect of DNR on music perception. Therefore, we aimed to evaluate the effect of DNR on music, in addition to speech perception, using objective and subjective measurements. Subjects and Methods: Sixteen HA users participated in this study (58.00±10.44 years; 3 males and 13 females). The objective assessment of speech and music perception was based on the Korean version of the Clinical Assessment of Music Perception test and word and sentence recognition scores. Meanwhile, for the subjective assessment, the quality rating of speech and music as well as self-reported HA benefits were evaluated. Results: There was no improvement conferred with DNR of HAs on the objective assessment tests of speech and music perception. The pitch discrimination at 262 Hz in the DNR-off condition was better than that in the unaided condition (p=0.024); however, the unaided condition and the DNR-on conditions did not differ. In the Korean music background questionnaire, responses regarding ease of communication were better in the DNR-on condition than in the DNR-off condition (p=0.029). Conclusions: Speech and music perception or sound quality did not improve with the activation of DNR. However, DNR positively influenced the listener's subjective listening comfort. The DNR-off condition in HAs may be beneficial for pitch discrimination at some frequencies.