• 한국전기전자재료학회논문지
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• 제11권10호
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• pp.940-945
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• 1998

In this paper, we obtained the data, which is required in training the neural network and diagnosing the degradation degree, by introducing the AE detection that is effective method in ordinary degradation diagnosis on activation. Aa the results of generalization tests by appling neural network to the unknown AE patterns obtained from two kinds of specimen, firstly as to evaluate an objective performance of neural network, the recognition ration for no-void specimen and 1[mm] -void specimen are appeared to be 98.9% and 92.5%, respectively. Also, in the evaluation of the adaptability of neural network with a new type of 0.2[mm] -void specimen, it is confirmed that the result appears to be 64% of recognition ratio at 94% of confidence interval coefficient in expectation output 0.2. On the other hand, the recognition capability of the neural network was confirmed by data from no-void and 1[mm] void specimen. The results prove the promising possibility of the application of ANN to discriminate specific void affecting as main degradation source at partial discharge condition in insulator containing multi-void by accummulated data base.

• 대한인간공학회지
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• 제31권4호
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• pp.551-556
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• 2012

Objective: This study presents the effect of visual feedback on one-hand gesture performance in vision-based gesture recognition system when people use gestures to control a screen device remotely. Backgroud: gesture interaction receives growing attention because it uses advanced sensor technology and it allows users natural interaction using their own body motion. In generating motion, visual feedback has been to considered critical factor affect speed and accuracy. Method: three types of visual feedback(arrow, star, and animation) were selected and 20 gestures were listed. 12 participants perform each 20 gestures while given 3 types of visual feedback in turn. Results: People made longer hand trace and take longer time to make a gesture when they were given arrow shape feedback than star-shape feedback. The animation type feedback was most preferred. Conclusion: The type of visual feedback showed statistically significant effect on the length of hand trace, elapsed time, and speed of motion in performing a gesture. Application: This study could be applied to any device that needs visual feedback for device control. A big feedback generate shorter length of motion trace, less time, faster than smaller one when people performs gestures to control a device. So the big size of visual feedback would be recommended for a situation requiring fast actions. On the other hand, the smaller visual feedback would be recommended for a situation requiring elaborated actions.

• 보건교육건강증진학회지
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• 제31권5호
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• pp.45-58
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• 2014

Objective: The purpose of this study was to analysis the determinants and trend of suicidal ideation the elderly in Korea. Methods: This study participants were selected the elderly over the age of 55 from the Korea National Health and Nutrition Examination Survey in 2001(n=1,122), 2005(n=2,098), and 2010(n=2,402). Statistical analysis methods used in this study were $x^2$-test, logistic regression analysis and other basic statistics such frequency, percentage using SPSS version 21.0. Results: In 2001, the influencing factors of suicidal ideation was spouses, subjective health status and stress recognition. In 2005, the influencing factors of suicidal ideation were spouses, subjective health status, chronic disease amount, activity limitation, depression experience and stress recognition. In 2010, the influencing factors of suicidal ideation were elderly, education level, subjective health status, activity limitation, depression experience and stress recognition. Conclusions: The health education considering the characteristics of each elderly group should be developed and applied to prevent adults' suicidal ideation because the factors influencing suicidal ideation were revealed differently between the elderly group.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권8호
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• pp.3962-3980
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• 2019

To deal with single sample face recognition, this paper presents a patch based semi-supervised linear regression (PSLR) algorithm, which draws facial variation information from unlabeled samples. Each facial image is divided into overlapped patches, and a regression model with mapping matrix will be constructed on each patch. Then, we adjust these matrices by mapping unlabeled patches to $[1,1,{\cdots},1]^T$. The solutions of all the mapping matrices are integrated into an overall objective function, which uses ${\ell}_{2,1}$-norm minimization constraints to improve discrimination ability of mapping matrices and reduce the impact of noise. After mapping matrices are computed, we adopt majority-voting strategy to classify the probe samples. To further learn the discrimination information between probe samples and obtain more robust mapping matrices, we also propose a multistage PSLR (MPSLR) algorithm, which iteratively updates the training dataset by adding those reliably labeled probe samples into it. The effectiveness of our approaches is evaluated using three public facial databases. Experimental results prove that our approaches are robust to illumination, expression and occlusion.

• 한국지형학회지
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• 제24권1호
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• pp.93-104
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• 2017

The objective of this study was two fold: firstly, we analyzed how the Geoparks have been run since the first one had been designated on December 31th, 2015. We then investigated how visitors' geographical and geological recognitions on the parks have changes. We visited geosites and investigated how well these sites accorded with the conditions for running Geoparks. In addition, scenery pictures and hashtags uploaded in Instagram between 2015 and 2016 were collected in order to analyze visitors preferences on the geosites along the, Hantan Imjingang River Geopark. Results showed that the hotspots were Bidulginang Waterall, Art Valley, and Jaein Waterfall. Compared to the ratio of geographical and geological references in 2015, the hashtags in all of these three geosites increased. The increases were as much as 3% in Bidulginang Falls, 0.6% in Art Valley, and 5% in Jaein Falls. In labelling the geographical and geological terms in Bidulginang Falls and Jaein Falls, the most frequently mentioned hashtags was "columnar joint", followed by "natural monument", "Geopark", and "basalt canyon". This study includes the study of visitors recognition which is one of the most important, but somehow neglected factor for the geopark's management.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.426-432
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• 2022

HVAC systems play a critical role in reducing energy consumption in buildings. Integrating occupants' thermal comfort evaluation into HVAC control strategies is believed to reduce building energy consumption while minimizing their thermal discomfort. Advanced technologies, such as visual sensors and deep learning, enable the recognition of occupants' discomfort-related actions, thus making it possible to estimate their thermal discomfort. Unfortunately, it remains unclear how accurate a deep learning-based classifier is to recognize occupants' discomfort-related actions in a working environment. Therefore, this research evaluates the classification performance of occupants' discomfort-related actions while sitting at a computer desk. To achieve this objective, this study collected RGB video data on nine college students' cold discomfort-related actions and then trained a deep learning-based classifier using the collected data. The classification results are threefold. First, the trained classifier has an average accuracy of 93.9% for classifying six cold discomfort-related actions. Second, each discomfort-related action is recognized with more than 85% accuracy. Third, classification errors are mostly observed among similar discomfort-related actions. These results indicate that using human action data will enable facility managers to estimate occupants' thermal discomfort and, in turn, adjust the operational settings of HVAC systems to improve the energy efficiency of buildings in conjunction with their thermal comfort levels.

• 한국실내디자인학회논문집
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• 제20권6호
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• pp.71-78
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• 2011

Although the recognition and emotion about space is subjective and individual, if standard is proposed through common factor, objective, quantified space image evaluation will be available. In addition, space image evaluation standard caused by recognitive-emotional factor can meet requests of space users and increase psychological satisfactions. The purpose of this study is to grasp the space image caused by recognitive-emotional factor in space with PAD model and analyze the evaluation of space image giving visual, recognitive and emotional effects. The analysis result revealed that 'joyfulness' and access-avoidance had a very similar distribution. The result means that space is evaluated with the degree of 'joyfulness' for space and it is led by approach-avoidance behavior. The recognition factor that forms and evaluates space image and decides approach-avoidance is expressed as adjective images such as 'fresh, joyful, light and static and its emotional factors are adjective images such as 'calm, allowable, joyful and quiet'.

• 센서학회지
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• 제26권2호
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• pp.128-134
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• 2017

Until now, neuropsychological tests can diagnose the brain dysfunction, however, cannot distinguish the objective data of experiment enough to distinguish the relationships between brain dysfunction and cerebropathia. In this paper, an automatic cognitive test equipment system with 6-axis motion sensors was proposed for the automation of neuropsychological tests. Fist-Edge-Palm(FEP) test and Go-no go test were used to evaluate motor programming of frontal lobe. The motion data from the specially designed motion glove are transmitted wirelessly to a computer to detect the gestures automatically. The healthy 20 and 11 persons are investigated for the FEP and Go-No go test, respectively. The recognition rates of gestures of FEP and Go-No go test are min. 91.38% and 89.09%. In conclusion, the automations of cognitive tests are successful to diagnose the brain diagnostics quantitatively.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1815-1821
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• 2015

Rapid increase in population growth has made the mankind to delve in appropriate identification of individuals through biometrics. Foot Print Recognition System is a new challenging area involved in the Personal recognition that is easy to capture and distinctive. Foot Print has its own dimensions, different in many ways and can be distinguished from one another. The main objective is to provide a novel efficient automated system Segmentation using Foot Print based on structural relations among the features in order to overcome the existing manual method. This system comprises of various statistical computations of various foot print parameters for identifying the factors like Instep-Foot Index, Ball-Foot Index, Heel- Index, Toe- Index etc. The input is naked footprint and the output result to an efficient segmentation system thereby leading to time complexity.

• 융합신호처리학회논문지
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• 제14권1호
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• pp.21-26
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• 2013

The objective of this study was to develop a system for handwriting recognition in three dimensions (3D) to authenticate users. While previous studies have used a stylus pen for two-dimensional input on a tablet, this study uses the Wii Remote controller because it can capture 3D human motion and could therefore be more effective means of recognition. The information obtained from a Wii Remote controller included x and y coordinates, acceleration (x, y, z), angular velocity (pitch, yaw, roll), twelve input buttons, and time. The proposed system calculates distances using six features extracted after preprocessing the data. In an experiment where 15 subjects wrote "AIZU" 10 times, we obtained a 94.8% identification rate using a combination of writing velocity, the peak value of pitch, and the peak value of yaw. This suggests that this system holds promise for handwriting-based authentication in the future.