• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.360-364
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• 2009

Analyzing information diffusion in a blog world is a very useful research issue, which can be used for predicting information diffusion, abnormally detection, marketing, and revitalizing the blog world. Existing studies on information diffusion in blog networks establish explicit relationship between blogs, and analyze only the word-of-mouth effect through such explicit relationships. However, we observed that more than 85% of all information diffusion in a blog world occurs through non-explicit relationships. In this paper, we propose a new model that considers both explicit and non-explicit relationships between blogs in order to explain all information diffusion phenomena in a blog world. We verify the superiority of our proposed models through extensive experiments of information diffusions at a real blog net-work.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.45-50
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• 2004

In this paper, we propose a new PCA-based LDA Mixture Algorithm(PLMA) for real-time face recognition system. This system greatly consists of the two parts: 1) face extraction part; 2) face recognition part. In the face extraction part we applied subtraction image, color filtering, eyes and mouth region detection, and normalization method, and in the face recognition part we used the method mixing PCA and LDA in extracted face candidate region images. The existing recognition system using only PCA showed low recognition rates, and it is hard in the recognition system using only LDA to apply LDA to the input images as it is when the number of image pixels ire small as compared with the training set. To overcome these shortcomings, we reduced dimension as we apply PCA to the normalized images, and apply LDA to the compressed images, therefore it is possible for us to do real-time recognition, and we are also capable of improving recognition rates. We have experimented using self-organized DAUface database to evaluate the performance of the proposed system. The experimental results show that the proposed method outperform PCA, LDA and ICA method within the framework of recognition accuracy.

• Korean Journal of Computational Design and Engineering
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• v.13 no.6
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• pp.403-411
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• 2008

The alignment of facial images is crucial for 2D face recognition. This is the same to facial meshes for 3D face recognition. Most of the 3D face recognition methods refer to 3D alignment but do not describe their approaches in details. In this paper, we focus on describing an automatic 3D alignment in viewpoint of quantitative analysis. This paper presents a framework of 3D face alignment and normalization based on feature points obtained by Active Shape Models (ASMs). The positions of eyes and mouth can give possibility of aligning the 3D face exactly in three-dimension space. The rotational transform on each axis is defined with respect to the reference position. In aligning process, the rotational transform converts an input 3D faces with large pose variations to the reference frontal view. The part of face is flopped from the aligned face using the sphere region centered at the nose tip of 3D face. The cropped face is shifted and brought into the frame with specified size for normalizing. Subsequently, the interpolation is carried to the face for sampling at equal interval and filling holes. The color interpolation is also carried at the same interval. The outputs are normalized 2D and 3D face which can be used for face recognition. Finally, we carry two sets of experiments to measure aligning errors and evaluate the performance of suggested process.

• The Journal of the Korea Contents Association
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• v.13 no.1
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• pp.1-8
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• 2013

The accuracy of a real facial recognition system can be varied according to the accuracy of the eye detection algorithm when we design and implement a semi-automatic facial recognition algorithm depending on the eye position of a database. In this paper, a fully automatic facial recognition algorithm is proposed such that Gabor and LBP features are extracted from fiducial points of a face graph which was created by using fiducial points based on the eyes, nose, mouth and border lines of a face, fitted on the face image. In this algorithm, the recognition performance could be increased because a face graph can be fitted on a face image automatically and fiducial points based LPB features are implemented with the basic Gabor features. The simulation results show that the proposed algorithm can be used in real-time recognition for more than 1,000 faces and produce good recognition performance for each data set.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.2
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• pp.859-864
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• 2013

Aim: To compare the effectiveness of self-examination, clinical examination and screening methods using 1% toluidine blue and Lugol's iodine in estimating the prevalence of lesions at risk of malignancy and oral malignant disease amongst the male inmates of Yerwada Central Jail, Pune. Material and Methods: Study was carried out on male inmates in two phases. In the first phase self-examination and clinical examination was carried out on 2,257 male inmates. 164 suspicious cases were subjected to phase II of the study out of whom, 82 participants were screened with 1% toluidine blue and 2% Lugol's iodine followed by biopsy procedure. Results: Sensitivity and specificity for self-examination with clinical examination was 92.2% and 96.6% respectively. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) and positive (+LR) and negative likelihood ratio (-LR) for Toluidine Blue were 88.1%, 66.6% 97.1%, 30%, 2.63 and 0.17 respectively while for Lugol's Iodine they were 94.7%, 83.8%, 98.6%, 55.5%, 5.67 and 0.06 respectively. Conclusions: Prevalence of lesions at risk of malignancy and oral malignant disease by self-examination was 7.8% and by clinical examination was 6.3%. Self-examination is an effective tool in early detection of oral cancer. Use of Lugol's iodine as a screening tool for oral lesions is highly effective in inmate populations.

• The KIPS Transactions:PartA
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• v.16A no.4
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• pp.255-262
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• 2009

We present an autonomous entertainment dolphin robot system based on ubiquitous sensor networks(USN). Generally, It is impossible to apply to USN and GPS in underwater bio-mimetic robots. But An Entertainment dolphin robot which presented in this paper operates on the water not underwater. Navigation of the underwater robot in a given area is based on GPS data and the acquired position information from deployed USN motes with emphasis on user interaction. Body structures, sensors and actuators, governing microcontroller boards, and swimming and interaction features are described for a typical entertainment dolphin robot. Actions of mouth-opening, tail splash or water blow through a spout hole are typical responses of interaction when touch sensors on the body detect users' demand. Dolphin robots should turn towards people who demand to interact with them, while swimming autonomously. The functions that are relevant to human-robot interaction as well as robot movement such as path control, obstacle detection and avoidance are managed by microcontrollers on the robot for autonomy. Distance errors are calibrated periodically by the known position data of the deployed USN motes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.247-257
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• 2020

Livestock epidemics, such as foot and mouth disease, are causing enormous economic losses due to their strong infectious power. Early detection of infectious diseases in livestock is very important, but it is difficult to diagnose early in individual farms, and there are frequent cases of transmission through inter-farm movement such as veterinarians and feeding vehicles. In this study, we studied the technology that enables rapid diagnosis without veterinarian farm visits and prevents further spread by automatically monitoring the body temperature of livestock using ubiquitous-based information and communication technology in the early stage of onset and sending it in real time. We have presented a technique for systematically managing livestock epidemics at the farm level, regional level, and national level by using the community mapping technique by using the remote medical treatment system linked to the automatically collected information. In this process, community mapping items for each step and stakeholders were derived for crowd sourcing based spatial information technology.

• Journal of Genetic Medicine
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• v.15 no.2
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• pp.92-96
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• 2018

Chronic mucocutaneous candidiasis (CMC) is characterized by increased susceptibility to chronic and recurrent infections of the skin, mucous membranes, and nails by Candida species. It is a primary immunodeficiency disorder that is difficult to diagnose because of its heterogeneous clinical manifestations and genetic background. A 20-month-old boy who did not grow in height for 3 months was diagnosed as having hypothyroidism and he had hepatitis which was found at 5 years old. He presented with persistent oral thrush and vesicles on the body, the cause of which could not be identified from laboratory findings. No microorganism was detected in the throat culture; however, the oral thrush persisted. Immunological tests showed that immunoglobulin (Ig) subclass IgG and cluster of differentiation (CD)3, CD4, and CD8 levels were within normal limits. We prescribed oral levothyroxine and fluconazole mouth rinse. The patient was examined using diagnostic exome sequencing at the age of 6 years, and a c.1162A>G (p.K388E) STAT1 gene mutation was identified. A diagnosis of CMC based on the STAT1 gene mutation was, thus, made. At the age of 8 years, the boy developed a malar-like rash on his face. We conducted tests for detection of antinuclear antibodies and anti-dsDNA antibodies, which showed positive results; therefore, systemic lupus erythematosus (SLE) was also suspected. Whole exome sequencing is important to diagnose rare diseases in children. A STAT1 gene mutation should be suspected in patients with chronic fungal infections with a thyroid disease and/or SLE.

• Journal of Oral Medicine and Pain
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• v.44 no.3
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• pp.103-111
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• 2019

Purpose: Patients with taste complaints presenting with various abnormal perceptions and alterations in gustatory function are often encountered in dental clinics. Since taste perception is thought to be influenced by numerous factors including neurological and psychological factors, the gustatory profiles of patients complaining of taste abnormalities should be very different. However, the gustatory profiles based on the clinical subtypes of taste complaints have not been fully studied. This study aimed to better understand the gustatory profiles depending on the clinical subtypes of taste complaints. Methods: Clinical data from 169 patients with complaints of altered taste were retrospectively collected to analyse their clinical and gustatory profiles. These complaints were subdivided into hypergeusia, hypogeusia, and dysgeusia for each taste quality according to the clinical types of these complaints. The gustatory profiles were then established by analysing the detection and recognition thresholds for each taste quality depending on the clinical subtypes of taste complaints. Results: Clinical analysis revealed that patients with taste complaints had widely diverse clinical profiles. There were significant differences between males and females with taste complaints in the prevalence rates of symptoms like dry mouth, tongue coating, and burning sensation. While hypogeusia (76.3%) was the most frequent type of taste complaint, it was revealed that the taste thresholds were not always consistent with the patient's description of gustatory symptoms. Conclusions: Patients with taste complaints exhibited diverse clinical profiles with sex differences. Considering the diversity of the taste complaints, the quantitative gustatory testing methods can be valuable to differentially evaluate the presence and intensity of altered taste in patients with these complaints.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.132-142
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• 2021

The purpose of this study is to present an effective methodology that can measure heart rate, heart rate variability, oxygen saturation, respiration rate, mental stress level, and blood pressure using mobile front camera that can be accessed most in real life. Face recognition was performed in real-time using Blaze Face to acquire facial image data, and the forehead was designated as ROI (Region Of Interest) using feature points of the eyes, nose, and mouth, and ears. Representative values for each channel of the ROI were generated and aligned on the time axis to measure vital signs. The vital signs measurement method was based on Fourier transform, and noise was removed and filtered according to the desired vital signs to increase the accuracy of the measurement. To verify the results, vital signs measured using facial image data were compared with pulse oximeter contact sensor, and TI non-contact sensor. As a result of this work, the possibility of extracting a total of six vital signs (heart rate, heart rate variability, oxygen saturation, respiratory rate, stress, and blood pressure) was confirmed through facial images.