• Asian Pacific Journal of Cancer Prevention
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• v.14 no.9
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• pp.4961-4964
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• 2013

Greater use of mobile phone devices seems inevitable because the health industry and cancer care are facing challenges such as resource constraints, rising care costs, the need for immediate access to healthcare data of types such as audio video texts for early detection and treatment of patients and increasing remote aids in telemedicine. Physicians, in order to study the causes of cancer, detect cancer earlier, act in prevention measures, determine the effectiveness of treatment and specify the reasons for the treatment ineffectiveness, need to access accurate, comprehensive and timely cancer data. Mobile devices provide opportunities and can play an important role in consulting, diagnosis, treatment, and quick access to health information. There easy carriage make them perfect tools for healthcare providers in cancer care management. Key factors in cancer care management systems through a mobile phone health approach must be considered such as human resources, confidentiality and privacy, legal and ethical issues, appropriate ICT and provider infrastructure and costs in general aspects and interoperability, human relationships, types of mobile devices and telecommunication related points in specific aspects. The successful implementation of mobile-based systems in cancer care management will constantly face many challenges. Hence, in applying mobile cancer care, involvement of users and considering their needs in all phases of project, providing adequate bandwidth, preparation of standard tools that provide maximum mobility and flexibility for users, decreasing obstacles to interrupt network communications, and using suitable communication protocols are essential. It is obvious that identifying and reducing barriers and strengthening the positive points will have a significant role in appropriate planning and promoting the achievements of mobile cancer care systems. The aim of this article is to explain key points which should be considered in designing appropriate mobile health systems in cancer care as an approach for improving cancer care management.

• Journal of The Korean Association of Information Education
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• v.12 no.1
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• pp.57-63
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• 2008

This study uses the identification which is one of the critical components of psychological mechanism and enables replacing one's own self because of the needs of self-expression(disclosure) and creation. The study aims to improve educational effects using the realistic by increasing sense of the virtual reality and the attention. After the computer-based contents were developed and converted to be applied into robot, and then the contents were combined the student's photo and the avatar using automatic loading. Finally each one of the contents was applied to the students. The results of the investigation indicated that there were significant effects of the contents based on identification. In other words, the contents effect on student's attention, but not their academic achievement. The study could find the effect of the identification's application using the educational robot. We suggested that improving technical ability of the augmented virtuality as a face-detection and sensitive interaction may lead to the specific suggestions for educational effects for further research.

• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.185-195
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• 2013

In this paper, we propose a video summarization technique on a smartphone, based on spatiotemporal saliency. The proposed technique detects scene changes by computing the difference of the color histogram, which is robust to camera and object motion. Then the similarity between adjacent frames, face region, and frame saliency are computed to analyze the spatiotemporal saliency in a video clip. Over-segmented hierarchical tree is created using scene changes and is updated iteratively using mergence and maintenance energies computed during the analysis procedure. In the updated hierarchical tree, segmented frames are extracted by applying a greedy algorithm on the node with high saliency when it satisfies the reduction ratio and the minimum interval requested by the user. Experimental result shows that the proposed method summaries a 2 minute-length video in about 10 seconds on a commercial smartphone. The summarization quality is superior to the commercial video editing software, Muvee.

• Journal of Broadcast Engineering
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• v.22 no.2
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• pp.182-192
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• 2017

In this paper, we propose hand tracking system combined with color and motion information. Most of hand detection and tracking systems are performed by modeling skin color. However, in this approach, since it is highly influenced by light or surrounding objects, accurate values cannot be derived constantly. Also, depending on the skin color, hand tracking may be interrupted by not only the hand but also the background with a color similar to that of the face and skin. Therefore, we design the hand tracking that can effectively track a hand by using motion history image(MHI) and combining it with CamShift. The proposed system is implemented based on C/C++, and the experiments proved that the proposed method shows stable and excellent performance.

• Journal of KIISE
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• v.45 no.1
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• pp.15-21
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• 2018

Low-Rank Representation (LRR) based methods are widely used in many practical applications, such as face clustering and object detection, because they can guarantee high prediction accuracy when used to constructing graphs in graph - based semi-supervised learning. However, in order to solve the LRR problem, it is necessary to perform singular value decomposition on the square matrix of the number of data points for each iteration of the algorithm; hence the calculation is inefficient. To solve this problem, we propose an improved and faster LRR method based on the recently published Fast LRR (FaLRR) and suggests ways to introduce and optimize additional constraints on the underlying optimization goals in order to address the fact that the FaLRR is fast but actually poor in classification problems. Our experiments confirm that the proposed method finds a better solution than LRR does. We also propose Fast MLRR (FaMLRR), which shows better results when the goal of minimizing is added.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.6
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• pp.600-606
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• 2012

Upon investigation of the damaged wheels for high speed train it was determined that the damage was caused by rolling contact fatigue during operation of train. The major problems that railway vehicle system using wheel-rail has to face during operation of railway vehicle are rolling contact fatigue, cracks in wheels, cracks in rails and wheel-rail profile wear. If these deficiencies are not controlled at early stages the huge economical problems due to unexpected maintenance cost in railway vehicle can be happened. Also, If the accurate knowledge of contact conditions between wheel and rail can be evaluated, the damage of wheel can be prevented and the maintenance operation can save money. This paper presents the applicability of electro-magnetic technique to the detection and sizing of defects in wheel. Under the condition of continuous rolling contact fatigue the damage of wheel has continuously monitored using the applied sensor. It was shown that the usefulness of the applied sensor was verified by twin disc test and the measured damaged sizes showed good agreement with the damaged sizes estimated by electro-magnetic technique.

• Journal of the Korean Society of Safety
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• v.21 no.2 s.74
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• pp.138-142
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• 2006

Occupational asthma is commonly known to be induced by isocyanate exposure. Spray painters generally use isocyanates for 2-pack spray painting to coat wooden panel surfaces in the furniture industry in South Australia. Due to a lack of actual exposure data, this study conducted environmental and dermal/ocular monitoring from a company in the furniture industry. According to this study, there was no significant airborne contamination, due to the use of high volume low pressure (HVLP) spray guns, low concentration of hardener in paint solutions and appropriate respirator like full face-air line respirator. There was no significant HDI detection in the general work area around the spray booths. Owing to the use of disposable nitrile gloves during the spray painting, no significant dermal exposure was found. According to color monitoring, there was a possible dermal exposure from surfaces in the workplace, unless either protective gloves were worn or appropriate working practices like clean-up process and storage in a secure places. No eye contamination was detected from the spray painters. No significant exposure levels from inhalational, dermal, ocular were found. The area of most concern was work practices.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.9-18
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• 2011

In this paper, we propose a method which recognizes human activity using model-based gaze direction estimation in an indoor environment. The method consists of two steps. First, we detect a head region and estimate its gaze direction as prior information in the human activity recognition. We use color and shape information for the detection of head region and use Bayesian Network model representing relationships between a head and a face for the estimation of gaze direction. Second, we recognize event and scenario describing the human activity. We use change of human state for the event recognition and use a rule-based method with combination of events and some constraints. We define 4 types of scenarios related to the gaze direction. We show performance of the gaze direction estimation and human activity recognition with results of experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.251-256
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• 2008

Many researchers are studying about human Brain-Computer Interface(BCI) that it based on electroencephalogram(EEG) signals of multichannel. The researches of EEG signals are used for detection of a seizure or a epilepsy and as a lie detector. The researches about an interface between Brain and Computer have been studied robots control and game of using human brain as engineering recently. Especially, a field of brain studies used EEG signals is put emphasis on EEG artifacts elimination for correct signals. In this paper, we measure EEG signals as human emotions and divide it into five frequence parts. They are calculated related the percentage of selecting range to total range. the calculating values are compared standard values by Bayesian Network. lastly, we show the human face avatar as human Emotion.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.2
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• pp.349-356
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• 2020

This paper introduces the implementation of a driver's condition warning system using eye aspect ratio to prevent a car accident. The proposed driver's condition warning system using eye aspect ratio consists of a camera, that is required to detect eyes, the Raspberrypie that processes information on eyes from the camera, buzzer and vibrator, that are required to warn the driver. In order to detect and recognize driver's eyes, the histogram of oriented gradients and face landmark estimation based on deep-learning are used. Initially the system calculates the eye aspect ratio of the driver from 6 coordinates around the eye and then gets each eye aspect ratio values when the eyes are opened and closed. These two different eye aspect ratio values are used to calculate the threshold value that is necessary to determine the eye state. Because the threshold value is adaptively determined according to the driver's eye aspect ratio, the system can use the optimal threshold value to determine the driver's condition. In addition, the system synthesizes an input image from the gray-scaled and LAB model images to operate in low lighting conditions.