• Journal of radiological science and technology
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• 제27권3호
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• pp.51-58
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• 2004

The gel, which is stained on probe after ultrasonography, is a good circumstances for proliferation of microbe. This study is to investigate into the actual state of sanitary management, recognition degree and infection level of ultrasonographic probes. We had performed a question with telephone to 42 hospitals in Seoul area from December in 2003. We also cultured to obtained a sample from three ultrasonographic units to investigate infection level of the probes. Sanitary management of the probes was performed in 21 hospitals with alcohol cotton. Sanitary management was performed daily in 14 hospitals. Most hospitals used cotton towel for clearing of gel stained on probes. Preventive management against infection was performed in 32 hospitals with vinyl cover, surgical glove, or alcohol sterilization etc. In the recognition degree on infection, the response that using method of ultrasonographic probes is insanitary were in 78.6%(33 hospitals), and 54.8%(23 hospitals) responded that bacteria can be infected through the probes. In the results of germiculture, bacteria and fungi were detected too number of to count, but escherichia coli was not detected. In conclusion, The gel stained on probe after ultrasonography must be cleared completely, and it is necessary that change of recognition on sanitary management.

• Journal of Korea Multimedia Society
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• 제23권12호
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• pp.1464-1475
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• 2020

Due to the spread of COVID-19, the online lecture has become more prevalent. However, it was found that a lot of students and professors are experiencing lack of communication. This study is therefore designed to improve interactive communication between professors and students in real-time online lectures. To do so, we explore deep learning approaches for automatic recognition of students' facial expressions and classification of their understanding into 3 classes (Understand / Neutral / Not Understand). We use 'BlazeFace' model for face detection and 'ResNet-GRU' model for facial expression recognition (FER). We name this entire process 'Degree of Understanding (DoU)' algorithm. DoU algorithm can analyze a multitude of students collectively and present the result in visualized statistics. To our knowledge, this study has great significance in that this is the first study offers the statistics of understanding in lectures using FER. As a result, the algorithm achieved rapid speed of 0.098sec/frame with high accuracy of 94.3% in CPU environment, demonstrating the potential to be applied to real-time online lectures. DoU Algorithm can be extended to various fields where facial expressions play important roles in communications such as interactions with hearing impaired people.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제18권7호
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• pp.935-943
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• 1993

In this paper, robust recognition system for tilted facial image was developed. At first, standard facial image and lilted facial image are captured by CCTV camera and then transformed into binary image. The binary image is processed in order to obtain contour image by Laplacian edge operator. We trace and delete outermost edge line and use inner contour lines. We label four inner contour lines in order among the inner lines, and then we extract left and right eye with known distance relationship and with two eyes coordinates, and calculate slope information. At last, we rotate the tilted image in accordance with slope information and then calculate the ten distance features between element and element. In order to make the system invariant to image scale, we normalize these features with distance between left and righ eye. Experimental results show 88% recognition rate for twenty five face images when tilted degree is considered and 60% recognition rate when tilted degree is not considered.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제24권12B호
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• pp.2359-2368
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• 1999

In this paper we propose a 2D FLIR image-based 3D target recognition system which performs group-to-ground vehicle recognition using the target contour and its degree of reliability extracted from FLIR image. First we extract target from background in FLIR image. Then we define contour points of the extracted target which have high edge gradient magnitude and brightness value as reliable contour point and make reliable contour by grouping all reliable contour points. After that we extract corresponding reliable contours from model contour image and perform comparison between scene and model features which are calculated by DST(discrete sine transform) of reliable contours. Experiment shows that the proposed algorithm work well and even in case of imperfect target extraction it showed better performance then conventional 2D contour-based matching algorithms.

• Journal of the Korean Home Economics Association
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• 제44권3호
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• pp.1-11
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• 2006

Although the personal credit rating has become more important than ever before in our era, a significant number of social problems have occurred due to the rising number of individuals and households with low credit ratings. The main objectives of this research are to determine effective policies of social remedies through an investigation of recognition, expectation, and utilization levels of relevant public policies available to assist individuals with low credit ratings. The sample population was taken from the credit defaulters who had visited the Credit Recovery Commission. The research was undertaken from April 28 to May 4, 2004. This study focused on the related variables concerning the degree of utilization of remedial public policies. The results showed that females, less educated individuals, and those with higher levels of expectation and recognition were more likely to utilize remedial policies. Based on the research, conclusions regarding the usage of public remedial policies for credit defaulters are as stated below. Education for households should be conducted in order to increase the expectation and recognition levels of relevant policies.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제16권1호
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• pp.23-34
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• 1991

This paper is studied for the recognition of occluded objects by fuzzy inference. The images are transformed a group of linear line segments, which is formed local features extracted from curvature points, using polygonal approximation. The features extracted from images are representes to the fuzzified data which is mapped into fuzzy concepts to represent the fuzziness, and the recognition of a model from scenes is performed by fuzzy inference using the production rulse which is generated from the model image. It is considered that the recognition results according to the change of degree of fuzziness in the experiments, and the experimental results for 30 scenes contained 120 models is obtained 92.5% of recognition rate.

• International journal of advanced smart convergence
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• 제8권4호
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• pp.104-112
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• 2019

This study proposed a robust detection algorithm. It detects face more stably with respect to changes in light and rotation forthe identification of a face shape. The proposed algorithm uses face shape asinput information in a single camera environment and divides only face area through preprocessing process. However, it is not easy to accurately recognize the face area that is sensitive to lighting changes and has a large degree of freedom, and the error range is large. In this paper, we separated the background and face area using the brightness difference of the two images to increase the recognition rate. The brightness difference between the two images means the difference between the images taken under the bright light and the images taken under the dark light. After separating only the face region, the face shape is recognized by using the self-organization feature map (SOFM) algorithm. SOFM first selects the first top neuron through the learning process. Second, the highest neuron is renewed by competing again between the highest neuron and neighboring neurons through the competition process. Third, the final top neuron is selected by repeating the learning process and the competition process. In addition, the competition will go through a three-step learning process to ensure that the top neurons are updated well among neurons. By using these SOFM neural network algorithms, we intend to implement a stable and robust real-time face shape recognition system in face shape recognition.

• The Journal of Korean Physical Therapy
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• 제33권2호
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• pp.69-75
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• 2021

Purpose: This study examined the recognition of rehabilitative robots for treatment in physical therapists. Methods: This study surveyed 100 physical therapists in Seoul and Gyeonggi-do using Google Form, an online survey tool. The questionnaire consisted of 21 questions, including eight questions on the general characteristics, 13 questions on the recognition of rehabilitative robots. Results: The general characteristics of the physical therapists showed differences and influences on recognition of rehabilitative robots, and there were statistically significant differences. There were significant differences in the recognition of rehabilitation robots according to general characteristics in gender, age, education degree, type of hospital, average weekly working time, and treatment field. Multiple regression analysis found that gender and the type of hospital influenced the recognition of rehabilitation robots. Conclusion: Physical therapists showed differences in recognition of rehabilitative robots according to their general characteristics, and gender and the type of hospital influence the recognition of rehabilitation robots. Sufficient systematic education programs should be provided, and physical therapists require policy adjustments to increase their accessibility to rehabilitation robots through continuing education.

• Journal of Korean Home Economics Education Association
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• 제4권1호
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• pp.17-30
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• 1992

This study aims at finding a new home economics education with will include male students as its teaching objects, and then providing home economics teachers with useful materials. For this purpose I examined the curriculum of foreign home economics education and analized male and female secondary school students’and their recognition and demand to the home economics education. Investigated persons are male and female students of the first year of 3 sendary schools and their parents in Seoul, who are choosen by menas of random sampling. The items analysis of questionnaires was performed by means of random sampling. The items analysis of questionnaires was performed by means of SPSS. The results are marked with percentage and the significance level is verified by t and X(sup)2 analysis methods. The results obtained from the items analysis are as follows：1 According to the increasing number of female employees, the mechanization of household affaires, and so on, male students and male parents got to realize the necessity of home economics education and the importance of men and women’s cooperation to lead a family life. 2. It is shown that the goal of home economics deucation must be to form a right value point of the family life and family. This fact implies that many examinees regards the home economics education in the moral point of view. 3. In the necessity degree according to each field of the home economics education curriculum, moral and social aspects such as family relationship, home management & economics, human development and bringing up are regarded more important than household affairs and the related technical aspects. 4. In the difference between groups to the necessity degree according to each field of the home economics education curriculum, there are few differences between male and female parents, but there are many differences between male and female students. Male students regards the contents of the home economics education curriculum less necessary than female students. Especially in the field of clothing, residence, human development and bringing up, the difference between male and female students is obvious. 5. The necessity degree of the contents related to environmental pollution, saving of energy and resources, utilizing of computer, etc. is very high.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제16권5호
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• pp.892-898
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• 2012

Rough classification methods are used to improving the recognition speed in many character recognition problems. In this case, some irreversible result can occur by an error in rough classification. Methods for duplicating each model in several classes are used in order to reduce this risk. But the errors by rough classfication can not be completely ruled out by these methods. In this paper, an recognition method is proposed to increase speed that matches models selectively without any increase in error. This method constructs a model graph using similarity between models. Then a search process begins from a particular point in the model graph. In this process, matching of unnecessary models are reduced that are not similar to the input pattern. In this paper, the proposed method is applied to the recognition problem of handwriting numbers and upper/lower cases of English alphabets. In the experiments, the proposed method was compared with the basic method that matches all models with input pattern. As a result, the same recognition rate, which has shown as the basic method, was obtained by controlling the out-degree of the model graph and the number of maintaining candidates during the search process thereby being increased the recognition speed to 2.45 times.