• The Journal of Korea Robotics Society
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• v.13 no.4
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• pp.265-271
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• 2018

The recent prosthetic technologies pursue to control multi-DOFs (degrees-of-freedom) hand and wrist. However, challenges such as high cost, wear-ability, and motion intent recognition for feedback control still remain for the use in daily living activities. The paper proposes a multi-channel knit band sensor to worn easily for surface EMG-based prosthetic control. The knitted electrodes were fabricated with conductive yarn, and the band except the electrodes are knitted using non-conductive yarn which has moisture wicking property. Two types of the knit bands are fabricated such as sixteen-electrodes for eight-channels and thirty-two electrodes for sixteen-channels. In order to substantiate the performance of the biopotential signal acquisition, several experiments are conducted. Signal to noise ratio (SNR) value of the knit band sensor was 18.48 dB. According to various forearm motions including hand and wrist, sixteen-channels EMG signals could be clearly distinguishable. In addition, the pattern recognition performance to control myoelectric prosthesis was verified in that overall classification accuracy of the RMS (root mean squares) filtered EMG signals (97.84%) was higher than that of the raw EMG signals (87.06%).

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.9-16
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• 2021

This study aims to develop a human activity recognition (HAR) system as a Deep-Learning (DL) classification model, distinguishing various human activities. We solely rely on the signals from a wristband accelerometer worn by a person for the user's convenience. 3-axis sequential acceleration signal data are gathered within a predefined time-window-slice, and they are used as input to the classification system. We are particularly interested in developing a Deep-Learning model that can outperform conventional machine learning classification performance. A total of 13 activities based on the laboratory experiments' data are used for the initial performance comparison. We have improved classification performance using the Convolutional Neural Network (CNN) combined with an auto-encoder feature reduction and parameter tuning. With various publically available HAR datasets, we could also achieve significant improvement in HAR classification. Our CNN model is also compared against Recurrent-Neural-Network(RNN) with Long Short-Term Memory(LSTM) to demonstrate its superiority. Noticeably, our model could distinguish both general activities and near-identical activities such as sitting down on the chair and floor, with almost perfect classification accuracy.

• Journal of the Korean Society of Costume
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• v.57 no.7
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• pp.108-121
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• 2007

The purpose of this study was to seek the means of enlarging the application of Saek-dong to fashion products by surveying and analysing the recognition and image of Saek-dong in college students. As a research procedure, the bibliographical survey on the meaning and history of Saek-dong was preceded in this study, and the students were examined on the recognition and image of Saek-dong through the questionnaires. The female students were more acquiesced with the Saek-dong and Saek-dong clothing than the male students. And the students thought that the Saek-dong was our original and traditional clothing because it was worn by our ancestors from the earliest years. The word Saek-dong reminded them of red, yellow, blue, green, white and red-brown colors in order of appearance. The most familiar color-arrange to them was red+yellow+dark-brown+green+blue, and the blue, purple, green, red, white color was thought as manly Saek-dong colors and the yellow, red, dark-brown, pink, white was regarded as feminine Saek-dong colors. Saek-dong was primarily associated with the image of Saek-dong clothing and most of the students expressed their feeling about the Saek-dong as 'cute.' Most of the students responded that the practical Hanbok was best illustrated as the most applied clothing of Saek-dong and that the attempt to apply the color and pattern of Saek-dong to other modern artistic products was likely to damage the worth of traditional Saek-dong. When it comes to the matter of applying the design of Saek-dong to the fashion products, male students thought that it could be best applied to the shirts, while female students thought that the design of Saek-dong could best be applied to the personal ornaments.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.723-730
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• 2023

Due to the recent development of battery technology, various types of means of transportation such as electric kickboards, Segways, and electric bicycles have emerged, which can be defined as Personal Mobility. In this paper, as the incidence of safety accidents increases due to the increase in the number of users of Personal Mobility, safety helmet devices that strengthen safety capabilities and peripheral recognition functions were studied. In order for the helmet to send a safety signal, Arduino was used as a base to set the value of the sensor according to changes in distance and angle using the ultrasonic sensor to minimize errors and ensure smooth recognition. In addition, a gyro sensor was used to turn on the direction indicator according to each slope. Using a CDS sensor, the LED is designed to turn on when it goes below 150 lux at night. Finally, it is possible to check whether a helmet is worn within 5cm, and when driving at an average speed, the direction indicator light is turned on at 10 degrees, and the LED is turned on at less than 150 lux.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.1
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• pp.29-36
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• 2017

In this paper, we propose a method for recognizing eating behavior with almost no motion acceleration. First, by using the acceleration of gravity acting on the wrist direction, we calculate the angle between the gravity and the wrist direction. After that, detect wrist reciprocating motion when peak and vally exist in specific angle band. And then, when accumulate the number of wrist reciprocating motion occurrences are up to 10, then regard as the meal time 5 minutes before the detection time. Also, estimate the meal time only if its duration is more than 7 minutes. Using the data of 2128 minutes, which was collected from four graduate student, the result of the meal time estimation shows 95.63% accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1486-1501
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• 2021

The removal of accessories from the face is one of the essential pre-processing stages in the field of face recognition. However, despite its importance, a robust solution has not yet been provided. This paper proposes a network and dataset construction methodology to remove only the glasses from facial images effectively. To obtain an image with the glasses removed from an image with glasses by the supervised learning method, a network that converts them and a set of paired data for training is required. To this end, we created a large number of synthetic images of glasses being worn using facial attribute transformation networks. We adopted the conditional GAN (cGAN) frameworks for training. The trained network converts the in-the-wild face image with glasses into an image without glasses and operates stably even in situations wherein the faces are of diverse races and ages and having different styles of glasses.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.6
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• pp.935-948
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• 2021

This study aimed to typify men's beliefs, perceptions, values, and attitudes, regarding foundation underwear, and examine the characteristics of each perception. Thirty-one statements on men's correctional underwear were selected, and Q classification was conducted with 20 men in their 30s and 40s as the P samples. Factors were extracted using principal component analysis and varimax rotation. Type 1 was the "fit improvement disadvantage cover type", which covered the target area, and improved the clothing fit. Type 2 was referred to as the "highlighting the advantages of chest correction" type, that was used to improve chest correction and exercise efficiency. "Positive wear for compensation of the abdomen", was listed as type 3, and was worn for abdominal correction. It was believed that type 3 could be used to correct body shape even if it was uncomfortable. Type 4, the "hip-up correction functional type", emphasized functionality based on its hip-up correction design.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.125-134
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• 2020

In this study, Q methodology was applied to investigate the subjective evaluation of department jumpers and characteristics of each type of recognition for college students. As a result of analyzing, they were classified into three types. Type 1 was recognized that the department jumper plays a role of giving a sense of belonging to the department and promoting the department. In addition, it was analyzed that wearing a department jumper would be cautious, but the activities were comfortable and people around me gave good evaluations and thought it had the effect of enhancing my confidence. In the case of type 2, the department jumper was satisfied because it was an easy-to-work and non-fashionable design, and was always worn when going to university. Type 3 was a type that gives a sense of belonging when wearing the department jumper, and that it was good for the department jumper to follow the fashion. It is thought that a department jumper with a good fit should be developed by reflecting the physical characteristics, showing the image or symbolism, so that the department jumper of college students can function as a uniform.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.21-31
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• 2018

Korean banknotes are similar in size, and their braille tend to worn out as they get old. These characteristics of Korean banknotes make the blind people, who mainly rely on the braille, even harder to distinguish the banknotes. Not only that, this can even lead to economic loss. There are already existing systems for recognizing the banknotes, but they don't support Korean banknotes. Furthermore, because they are developed as a mobile application, it is not easy for the blind people to use the system. Therefore, in this paper, we develop a Raspberry Pi-based banknote recognition system that not only recognizes the Korean banknotes but also are easily accessible by the blind people. Our system starts recognition with a very simple action of the user, and the blind people can hear the recognition results by sound. In order to choose the best feature extraction algorithm that directly affects the performance of the system, we compare the performance of SIFT, SURF, and ORB, which are representative feature extraction algorithms at present, in real environments. Through experiments in various real environments, we adopted SIFT to implement our system, which showed the highest accuracy of 95%.

• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.287-295
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• 2005

This paper describes user context awareness system, which is one of the most essential technologies in various application services of ubiquitous computing. The proposed system used two-akial accelerometer, embedded in SenseWear(R)PRO2 Armband (BodyMedia). When it was worn on the right upper arm of the experiment subjects, MAD (mean of absolute difference) value of the sensor data was calculated to quantify the amount of the wear's activity. Using this data, PC-based fuzzy inference system was realized to distinguish human motion states, such as, lying, sitting, walking and running and to recognize the restricted emergency situations. In laboratory experiment, the amount of activities for tying, sitting, walking and running were 0.204 g/s, 0.373 g/s, 2.808 g/s and 16.243 g/s respectively. The recognition rates of human motion states were 96.7 %, 93.0 %, 95.2 % and 98.4 % respectively for lying, sitting, walking and running. The recognition rate of restricted emergency situation was 100%.