• The Journal of the Korea Contents Association
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• v.11 no.11
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• pp.413-423
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• 2011

Service environments are known to have effects on quality recognition in fine-dining and family type restaurants. The current study explores that the effects are also likely in the fast-food type ones. To verify the research method factor and reliability analysis of SPSS version 18.0 are applied. The program is also used to test the influences among variables. With multiple regression analysis the study finds that there is a significant effect of service environment on quality recognition in fast-food type restaurants. The study also finds that employees' uniform and cleanliness are more influential than waiting time which is generally known as a key factor in fast food service restaurants.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.2
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• pp.219-231
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• 2022

This study sought to typify incontinence symptoms and how women over sixty perceive incontinence panties and pads. The study uses Q methodology to analyze the perception of these products by type. The research utilized Q methodology and the QUANL pc program for analysis. Type 1 was a type of depression and anxiety due to incontinence. Type 1 was a type of thinking that incontinence was hidden from others. Type 2 was a smell-sensitive reclusion. Type 2 was most concerned about smell, as people sometimes avoid interpersonal relationships because of urinary incontinence. Type 3 was function-oriented toilet frequently. Type 3 was recognizing that the absorption function of incontinence products is important, as the toilet is frequently used. Type 3 mainly wore underwear among incontinence products and thought that incontinence was not hidden from others. In the case of incontinent women, products that prevent others from feeling the smell of urine were considered important. Future studies should expand on this study's work to analyze practical, currently-existing incontinence products.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1421-1429
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• 2017

Human activity recognition has been studied using various sensors and algorithms. Human activity recognition can be divided into sensor based and vision based on the method. In this paper, we proposed an activity recognition system using acceleration sensor and gyroscope sensor in smartphone among sensor based methods. We used Deep Belief Network (DBN), which is one of the most popular deep learning methods, to improve an accuracy of human activity recognition. DBN uses the entire input set as a common input. However, because of the characteristics of different time window depending on the type of human activity, the RBMs, which is a component of DBN, are configured hierarchically by combining them from different time windows. As a result of applying to real data, The proposed human activity recognition system showed stable precision.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.2
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• pp.130-135
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• 2016

Gait recognition has advantage of non-contact type recognition. But It has disadvantage of low recognition rate when the pedestrian silhouette is changed due to bag or coat. In this paper, we proposed new method using combination of gait energy image feature and thermal face image feature. First, we extracted a face image which has optimal focusing value using human body rate and Tenengrad algorithm. Second step, we extracted features from gait energy image and thermal face image using linear discriminant analysis. Third, calculate euclidean distance between train data and test data, and optimize weights using genetic algorithm. Finally, we compute classification using nearest neighbor classification algorithm. So the proposed method shows a better result than the conventional method.

• KIEE International Transaction on Systems and Control
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• v.12D no.1
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• pp.27-32
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• 2002

In this paper, we would study the applicability of neural networks to the recognition process of Korean stenographic character image, applying the classification function, which is the greatest merit of those of neural networks applied to the various parts so far, to the stenographic character recognition, relatively simple classification work. Korean stenographic recognition algorithms, which recognize the characters by using some methods, have a quantitative problem that despite the simplicity of the structure, a lot of basic characters are impossible to classify into a type. They also have qualitative one that It Is not easy to classify characters fur the delicacy of the character farms. Even though this is the result of experiment under the limited environment of the basic characters, this shows the possibility that the stenographic characters can be recolonized effectively by neural network system. In this system, we got 90.86% recognition rate as an average.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.6
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• pp.51-61
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• 2007

In this paper, Air-interface protocols of ISO 18000-6 Types and EPCglobal Classes applied to RFID system in UHF band are analyzed, and those anticollision algorithms are realized. Also, the each algorithm which improves the performance of standard protocol is proposed, and the performance is compared when clock period of link timing is a identical condition on $12.5{\mu}s$. As the result, when 500 tags exist simultaneously inside reader interrogation zone, the tag recognition performance of a standard protocol is better in preceding order of Class-1 Generation-1, Type B, Type A, Class-0 and Class-1 Generation-2. And also the performance of improved protocol is better in ascending order of Type B, Type A, Class-1 Generation-1, Class-0 and Class-1 Generation-2. Therefore, performance of tag recognition remarkably depends on the regulated clock period in the protocol and link timing between a reader and a tag.

• Journal of the Korea Society of Computer and Information
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• v.24 no.2
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• pp.85-93
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• 2019

The purpose of this study is to provide basic data for the development of clothing which can improve the satisfaction of male university students' body shape by classifying the perception of body shape and examining characteristics by type. The types of recognition of body shape of male college students were classified into five types: developed upper body with protruding under abdomen, normal body with long legs, developed under body with big skeleton, skinny body, and ladder type normal body. The actual body shape was classified into three. The Y type had a long chest length and a shoulder developed, and the lower body silhouette was plain and short. Type H was flat with little protrusion from the chest to the hip. Type X has a larger hip and longer hip length than the waist. Body type was classified based on bust, waist, and hip circumference, but recognition body type was classified based on visual characteristics. It is thought that ergonomic consideration is needed to cover the disadvantages of each body type considering the aesthetic part as well as wearing comfort in accordance with the trend of the fashion market nowadays that the slim fit is generalized. This study was limited to male university students in their early 20s in Chungbuk province. Therefore, we could not grasp attitudes and perceptions of male university students living in other provinces. Therefore, we should pay attention to the generalization of the results of this study.

• Journal of the Korea Convergence Society
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• v.9 no.8
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• pp.87-94
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• 2018

This study was conducted to determine the recognition and behavior of female workers on irradiated food. A total of 326 surveys have been analyzed. The results of the study showed that the level of knowledge was 3.411 points and the level of recognition was 2.542 points. There was a significant difference in purchase of irradiated food by level of education, affiliation, and job type; in consumption of irradiated food by affiliation, level of education, job type and work experience; in preventive behavior of irradiated food by affiliation, work experience and job type. In a correlation analysis on the factors of irradiated food, those with more knowledge and better recognition had more experience of purchase and consumption. However, preventive behavior had no significant correlation with knowledge, recognition, purchase and consumption. Therefore, for a rational selection of irradiated food, it is important to provide information and safety training on them.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.9-16
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• 2019

The goal of this study is to propose an efficient model for recognizing and classifying tree images to measure the accuracy that can be applied to smart devices during class. From the 2009 revised textbook to the 2015 revised textbook, the learning objective to the fourth-grade science textbook of elementary schools was added to the plant recognition utilizing smart devices. In this study, we compared the recognition rates of trees before and after retraining using a pre-trained inception V3 model, which is the support of the Google Inception V3. In terms of tree recognition, it can distinguish several features, including shapes, bark, leaves, flowers, and fruits that may lead to the recognition rate. Furthermore, if all the leaves of trees may fall during winter, it may challenge to identify the type of tree, as only the bark of the tree will remain some leaves. Therefore, the effective tree classification model is presented through the combination of the images by tree type and the method of combining the model for the accuracy of each tree type. I hope that this model will apply to smart devices used in educational settings.

• MALSORI
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• no.62
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• pp.85-96
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• 2007

In this paper, we carried out recognition experiments for noisy speech having various levels of car noise and output of an audio system using the speech interface. The speech interface consists of three parts: pre-processing, acoustic echo canceller, post-processing. First, a high pass filter is employed as a pre-processing part to remove some engine noises. Then, an echo canceller implemented by using an FIR-type filter with an NLMS adaptive algorithm is used to remove the music or speech coming from the audio system in a car. As a last part, the MMSE-STSA based speech enhancement method is applied to the out of the echo canceller to remove the residual noise further. For recognition experiments, we generated test signals by adding music to the car noisy speech from Aurora 2 database. The HTK-based continuous HMM system is constructed for a recognition system. Experimental results show that the proposed speech interface is very promising for robust speech recognition in a noisy car environment.