• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.643-650
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• 2013

In this paper, we propose a novel method for enhancing the detection speed and rate by reducing the computation in Hough Circle Transform on real-time iris detection of smartphone camera image. First of all, we find a face and eyes from input image to detect iris and normalize the iris region into fixed size to prevent variation of size for iris region according to distance from camera lens. Moreover, we carry out histogram equalization to get regular image in bright and dark illumination from smartphone and calculate minimal iris range that contains iris with the distance between corner of the left eye and corner of the right eye on the image. Subsequently, we can minimize the computation of iris detection by applying Hough Circle Transform on the range including the iris only. The experiment is carried out in two case with bright and dark illumination. Our proposed method represents that detection speed is 40% faster and detection rate is 14% better than existing methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.586-589
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• 2015

A computer presentation system by using hand-motion identification rules is proposed. To identify hand motions of a presenter, a face region is extracted first using haar classifier. A motion status(patterns) and position of hands is discriminated using the center of gravities of user's face and hand after segmenting the hand area on the YCbCr color model. User's hand is applied to the motion detection rules and then presentation control command is then executed. The proposed system utilizes the motion identification rules without the use of additional equipment and it is then capable of controlling the presentation and does not depend on the complexity of the background. The proposed algorithm confirmed the stable control operation via the presentation of the experiment in the dark illumination range of indoor atmosphere (lx) 15-20-30.

• Korean Journal of Cognitive Science
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• v.8 no.4
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• pp.55-62
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• 1997

We proposed a method for locating of mouth using deformable templates, described by a parameterized template. An energy function is defined which links, edges, peaks, valleys in image intensity to corresponding properties of the template. The template deforms itself by altering its parameter values to minimize the energy function. The minimized energy function's parameter values can be used as descriptors for the feature. We propose a method for locating mouth fast, accurately by limiting a range of parameters' value and getting initial value of parameters' by preprocessing.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.609-616
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• 2017

In this paper, we propose an algorithm to obtain more stable and high recognition rate by using left and right rotation information of input image in order to obtain a stable recognition rate in face recognition. The proposed algorithm uses the facial image as the input information in the web camera environment to reduce the size of the image and normalize the information about the brightness and color to obtain the improved recognition rate. We apply Principal Component Analysis (PCA) to the detected candidate regions to obtain feature vectors and classify faces. Also, In order to reduce the error rate range of the recognition rate, a set of data with the left and right $45^{\circ}$ rotation information is constructed considering the directionality of the input face image, and each feature vector is obtained with PCA. In order to obtain a stable recognition rate with the obtained feature vector, it is after scattered in the eigenspace and the final face is recognized by comparing euclidean distant distances to each feature. The PCA-based feature vector is low-dimensional data, but there is no problem in expressing the face, and the recognition speed can be fast because of the small amount of calculation. The method proposed in this paper can improve the safety and accuracy of recognition and recognition rate faster than other algorithms, and can be used for real-time recognition system.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.18
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• pp.8479-8486
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• 2016

Background: Colorectal cancer (CRC) is the third most common cancer globally. In Jordan, it is the number one cancer among men and the second most common cancer among women, accounting for 15% and 9.4% respectively of all male and female diagnosed cancers. This study aimed to evaluate the knowledge and perceptions about colorectal cancer risk factors, signs and symptoms in Jordan and to provide useful data about the best modes of disseminating preventive messages about the disease. Materials and Methods: A stratified clustered random sampling technique was used to recruit 300 males and 300 females aged 30 to 65 years without a previous history of CRC from four governorates in Jordan. A semi-structured questionnaire and face to face interviews were employed. Descriptive and multivariate analysis was applied to assess knowledge and perceptions about CRC. Results: Both males and females perceived their CRC risk to be low. They had low knowledge scores about CRC with no significant gender association (P=0.47). From a maximum knowledge score of 18 points, the median scores of males and females were 4 points (SD=2.346, range 0-13) and 4 points (SD=2.329, range 0-11) respectively. Better knowledge scores were associated with governorate, higher educational level, older age, higher income, having a chronic disease, having a family history of CRC, previously knowing someone who had CRC and their doctor's knowledge about their family history of CRC. Conclusions: There is a low level of knowledge about CRC and underestimation of risk among the study participants. This underlines the need for public health interventions to create awareness about the illness. It also calls for further research to assess the knowledge and perceptions about CRC early detection examinations in Jordan.

• Journal of the Korean Electrochemical Society
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• v.17 no.1
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• pp.18-25
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• 2014

A Pt nanoparticle-decorated multiwall carbon nanotube (Pt-MWNT) electrode was prepared on Nafion by a hot-pressing at relatively low temperature. This electrode exhibited an intricate entangled, nanoporous structure as a result of gathering highly anisotropic Pt-MWNTs. Individual Pt nanoparticles were confirmed to have a polycrystalline face-centered cubic structure with an average crystal size of around 3.5 nm. From the cyclic voltammograms for hydrogen redox reactions, the Pt-MWNT electrode was found to have a similar electrochemical behavior to polycrystalline Pt, and a specific electrochemical surface area of $2170cm^2mg^{-1}$. Upon exposure to hydrogen analyte, the Pt-MWNT/Nafion electrode demon-strated a very high sensitivity of $3.60{\mu}A\;ppm^{-1}$ and an excellent linear response over the concentration range of 100-1000 ppm. Moreover, this electrode was also evaluated in terms of response and recovery times, reproducibility, and long-term stability. Obtained results revealed good sensing performance in hydrogen detection.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.1939-1951
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• 1994

This study introduces a new tool breakage detecting technology comprised of an unsupervised neural network combined with adaptive time series autoregressive(AR) model where parameters are estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(Recursive Least Square). Experiment indicates that AR parameters are good features for tool breakage, therefore it can be detected by tracking the evolution of the AR parameters during milling process. an ART 2(Adaptive Resonance Theory 2) neural network is used for clustering of tool states using these parameters and the network is capable of self organizing without supervised learning. This system operates successfully under the wide range of cutting conditions without a priori knowledge of the process, with fast monitoring time.

• Journal of Advanced Information Technology and Convergence
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• v.8 no.2
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• pp.47-58
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• 2018

In this paper, we propose a method for skin condition analysis using a camera module embedded in a smartphone without a separate skin diagnosis device. The type of skin disease detected in facial image taken by smartphone is acne, pigmentation, blemish and flush. Face features and regions were detected using Haar features, and skin regions were detected using YCbCr and HSV color models. Acne and flush were extracted by setting the range of a component image hue, and pigmentation was calculated by calculating the factor between the minimum and maximum value of the corresponding skin pixel in the component image R. Blemish was detected on the basis of adaptive thresholds in gray scale level images. As a result of the experiment, the proposed skin condition analysis showed that skin diseases of acne, pigmentation, blemish and flush were effectively detected.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.5
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• pp.25-32
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• 1995

In highly automated milling process, in-process monitoring of the malfunction is indispensable to ensure efficient cutting operation. Among many malfunctions in milling process, chatter vibration deteriorates surface finish, tool life and productivity. In this study, the monitoring system of chatter vibration for face milling process is proposed and experimentally estimated. The monitoring system employs two types of sensor such as cutting force and acceleration in sensory detection state. The RMS value and band frequency energy of the sensor signals are extracted in time domain for the input patterns of neural network to reduce time delay in signal processing state. The resultes of experimental evaluation show that the system works well over a wide range of cutting conditions.

• Archives of Plastic Surgery
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• v.35 no.4
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• pp.423-430
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• 2008

Purpose: Computed tomography theoretically should improve detection of foreign bodies and provide more information of adjacent soft tissues. And the CT scanner and PACS program proved to be an excellent instrument for detection and localization of most facial foreign bodies above certain minimum levels of detectability. The severity of injury in penetrating trauma to the face, it is often underestimated by physical examination. Diagnosis of a retained foreign object is always critical. Methods: From March, 2005 to February 2008 a study was done with 200 patients who had facial trauma. Axial and coronal CT images were obtained with a General Electric(Milwaukee, Wis) 9800 CT scanner at 130 kV, 90 mA, with a 2-mm section thickness and a $512{\times}512$ matrix. Results: Axial and coronal CT images at various window widths should be used as the first imaging modality to detect facial foreign bodies. The attenuation coefficients for the metallic and nonmetallic foreign bodies ranged from -437 to +3071 HU. As a general rule, metallic foreign bodies produced more Hounsfield artifacts than nonmetallic foreign bodies, thus providing a clue to their composition. All of the metallic foreign bodies were represented by a single peak and had a maximum attenuation coefficient of +3071 HU. Of the nonmetallic foreign bodies, glass had an attenuation coefficient that ranged from +105 to +2039, while plastic had a much lower coefficient that ranged from -62 to -35. wood had the lowest range of attenuation coefficients: -491 to -437. Conclusion: The PACS program allows one to distinguish metallic from nonmetallic foreign bodies and to individually identify the specific composition of many nonmetallic foreign bodies. This program does not, however, allow identification of the specific composition of a metallic foreign body. We recommend this type of software program for CT scanning of any patient with an injury to the face in which a foreign body is suspected.