• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1104-1120
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• 2020

The chest X-rays are a common way to diagnose lung cancer or pneumonia. In particular, the finding of a lung nodule is the most important problem in the early detection of lung cancer. Recently, a lot of automatic diagnosis algorithms have been studied to find the lung nodules missed by doctors. The algorithms are typically based on segmentation network like U-Net. However, the occurrence of false positives that similar to lung nodules present outside the lungs can severely degrade performance. In this study, we propose a multi-task learning method that simultaneously learns the lung region and nodule-labeled data based on the prior knowledge that lung nodules exist only in the lung. The proposed method significantly reduces false positives outside the lung and improves the recognition rate of lung nodules to 83.8 F1 score compared to 66.6 F1 score of single task learning with U-net model. The experimental results on the JSRT public dataset demonstrate the effectiveness of the proposed method compared with other baseline methods.

• Journal of Sensor Science and Technology
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• v.25 no.3
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• pp.196-201
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• 2016

Rehabilitation exercises are the treatments designed to help patients who are in the process of recovery from injury or illness to restore their body functions back to the original status. However, many patients suffering from chronic diseases have found difficulties visiting hospitals for the rehabilitation program due to lack of transportation, cost of the program, their own busy schedules, etc. Also, the program usually contains a few medical check-ups which can cause patients to feel uncomfortable. In this paper, we develop a remote rehabilitation system with bio-signals by a stereo camera. A Kinect stereo camera manufactured by Microsoft corporation was used to recognize the body movement of a patient by using its infrared(IR) camera. Also, we detect the chest area of a user from the skeleton data and process to gain respiratory status. ROI coordinates are created on a user's face to detect photoplethysmography(PPG) signals to calculate heart rate values from its color sensor. Finally, rehabilitation exercises and bio-signal detecting features are combined into a Windows application for the cost effective and high performance remote rehabilitation system.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.2
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• pp.87-93
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• 1989

Squared-error Pattern Clustering algorithm used in unsupervised pattern recognition and image processing application demands substantial processing time for operation of feature vector matrix. So, this paper propose the fast squared-error Pattern Clustering Processor using the Residue Number System which have been the nature of parallel processing and pipeline. The proposed Squared-error Pattern Clustering Processor illustrate satisfiable error rate for Cluster number which can be divide meaningful region and about 200 times faster than 80287 coprocessor from experiments result of image segmentation. In this result, it is useful to real-time processing application for large data.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.639-647
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• 2020

Entrepreneurial intention is receiving immense recognition in entrepreneurship researches, as it motives an individual to become an entrepreneur. Still, the interplay between gender perspective and contextual factors (i.e., access to capital, business information, social network, educational support, structural support) are not fully investigated in understanding the entrepreneurial intention in developing countries like Bangladesh. Therefore, the paper aims to examine the gender difference and educational discipline difference in the university's students' entrepreneurial intention in relation to contextual factors in Bangladesh. In this study, sample has been particularly taken from the different disciplinary students of private universities. Five-point Likert scale-based survey questionnaire was developed based on past researches. 280 online survey forms were distributed among the university students and finally 225 students' response were found correct as the study sample size (final survey response rate = 80%), after eliminating the incorrect survey responses. For statistical analysis SPSS 23.0 version is used. One-way ANOVA is used to measure the gender and discipline difference on entrepreneurial intention among male and female students. The results show that business information and social network will have more influence on male students' entrepreneurial intention, and comparatively, business students have more willingness to become entrepreneurs than other departmental students.

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1729-1740
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• 2017

This paper describes a vision-based method that effectively recognize a traffic light. The method consists of two steps of traffic light detection and discrimination. Many related studies have used color information to detect traffic light, but color information is not robust to the varying illumination environment. This paper proposes a new method of traffic light detection based on intensity and saturation. When a traffic light is turned on, the light region usually shows values with high saturation and high intensity. However, when the light region is oversaturated, the region shows values of low saturation and high intensity. So this study proposes a method to be able to detect a traffic light under these conditions. After detecting a traffic light, it estimates the size of the body region including the traffic light and extracts the body region. The body region is compared with five models which represent specific traffic signals, then the region is discriminated as one of the five models or rejected as none of them. Experimental results show the performance of traffic light detection reporting the precision of 97.2%, the recall of 95.8%, and correct recognition rate of 94.3%. These results shows that the proposed method is effective.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.526-534
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• 2006

In this paper we propose a new algorithm to detect the irises of both eyes from a human face. Using the separability filter, the algorithm first extracts blobs(intensity valleys) as the candidates for the irises. Next, for each pair of blobs. the algorithm computes a cost usings Hough transform and separability later to measure the fit of the pair of blobs to the image. And then, the algorithm selects a pair of blobs with the smallest cost as the irises of both eyes. As the result of the experiment using 150 faces images without spectacles, the success rate of the proposed algorithm was 97.3% for the best case and 95.3% for the worst case.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.592-595
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• 2009

In this paper, we propose a face detection technique for still pictures which sequentially uses a skin-color model and a support vector machine (SVM). SVM is a learning algorithm for solving the classification problem. Some studies on face detection have reported superior results of SVM over neural networks. The SVM method searches for a face in a picture while changing the size of the window. The detection accuracy and the processing time of SVM vary largely depending on the complexity of the background of the picture or the size of the face. Therefore, we apply a face candidate area detection method using a skin-color model as a preprocessing technique. We compared the method using SVM alone with that of the proposed method in respect to face detection accuracy and processing time. As a result, the proposed method showed improved processing time while maintaining a high recognition rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.5
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• pp.332-339
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• 1986

This paper proposes a new method for the normalization of shape pattern based on Gaussian probability density function to increase automatic recognition rate of hand-written Hangul pattern. The sizes of hand-written Hangul pattern are detected from the input images, and pattern sizes are normalized by two variables interpolation. The pattrn shapes are noralized by letting correlation coefficients equal to zero. It is analyzed theoretically and verified through computer simulation for the relation between input image and normaized shape pattern. It is confirmed that this method is effective and reasonable for deformed hand-written Hangul pattern. Experimental resu results show that the declination. size and stroke width of hand-written Hangul patterns are mych improved.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1442-1447
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• 2014

This study examined the effect of the cold-warm color contrast of the learning-item on the learner's performance. To do this, experimental conditions were divided into three conditions: control condition, cold-warm contrast condition of background and figure, and cold-warm contrast condition of distracter and target. In addition, the OSPAN (operation span) task was used as the learning task. As a result, the rate of word recognition was higher in cold-warm contrast condition of distractor and target than any other condition. These results could be interpreted as enhancing effect.

• Korean Journal of Psychosomatic Medicine
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• v.19 no.1
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• pp.3-14
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• 2011

Delirium is a common psychiatric disorder and occurs in many hospitalized older patients and has serious consequences including increased mortality rate. Despite its importance, health care clinicians often fail to recognize delirium or misdiagnosed as other psychiatric illness. Awareness of the etiologies and risk factors of delirium should enable clinicians to focus on patients at risk and to recognize delirium symptoms early. To improve early recognition of delirium, emphasis should be given to terminology, psychopathology and knowledge regarding clinical rating scale for delirium in the specific medical and surgical clinical settings. In this study, authors introduce rating scales for delirium and knowledge of clinical diagnostic process for delirium and give rise to appropriate assessment of delirium in the clinical situation.