• Asian Pacific Journal of Cancer Prevention
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• 제15권3호
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• pp.1435-1440
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• 2014

Background: It has been found that support given to women with breast cancer has a positive effect upon their reactions to the illness and may even prolong their survival. Perceived support needs assessment in breast cancer women could be considered as a necessary part of nursing function. Aim: The purpose of this study was to translate and culturally adapt the self-assessed support needs (SASN) questionnaire into Persian language and to investigate its psychometric properties. Materials and Methods: After forward-backward translation of the questionnaire and making appropriate changes, we selected 160 women with breast cancer as our study sample. The psychometric properties of the SASN, including its internal consistency, test retest reliability, and construct validity were evaluated through the known-groups technique. Results: The calculated Kaiser Meyer Olkin was 0.756, indicating that the sample was sufficiently large to perform a satisfactory factor analysis. The six factors all together explained 50.7% of the variance; the first factor (diagnosing) explaining the biggest part of variance (10.9). Internal consistency reliability was 0.83 for the whole scale and the stability of test was 0.78. For the first factor, Cronbach's alpha was 0.90 and factor loadings of scale's items were found to deal with diagnosis subscale. The domains described patients' diagnosis, treatment, support, femininity and body image, family and friends and information. Conclusions: The reliability and validity of the adapted version of the SASN was shown to be satisfactory. Thus, it can be used to investigate self-assessed support needs of Iranian women suffering from breast cancer since the SASN is a multi-domain scale.

• The KIPS Transactions:PartB
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• 제9B권5호
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• pp.653-662
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• 2002

Fingerprint recognition is a task to find a matching pattern in a database for a specific persons fingerprint. To accomplish this task, preprocessing, classification, and matching steps are taken for a large-scale fingerprint database but only the matching step is taken without classification for a small-scale database. The primary matching method is based on minutiae (ridge ending point, bifurcation). This matching method, however, requires a very complex computation to extract minutiae and match minutiae-to-minutiae accurately due to translation, rotation, nonlinear deformation of fingerprint and occurrence of spurious minutiae. In addition, this method requires a laborious preprocessing step in order to improve the quality of fingerprint Images. This paper proposes a new simple method to eliminate these problems. With this method, Gabor variance is used instead of minutiae for fingerprint recognition. The Gabor variance is computed from Gabor features that result from filtering a fingerprint image through Gabor filter. In this paper, this method is described and its test result is shown, demonstrating the potential of using this new method for fingerprint recognition.

• Journal of the Institute of Electronics Engineers of Korea SP
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• 제39권4호
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• pp.370-380
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• 2002

This paper proposes an ATR (Automatic Target Recognition) algorithm for identifying non-occluded and occluded military vehicles in natural FLIR (Forward Looking InfraRed) images. After segmenting a target, a radial function is defined from the target boundary to extract global shape features. Also, to extract local shape features of upper region of a target, a distance function is defined from boundary points and a line between two extreme points. From two functions and target contour, four global and four local shape features are proposed. They are much more invariant to translation, rotation and scale transform than traditional feature sets. In the experiments, we show that the proposed feature set is superior to the traditional feature sets with respect to the similarity-transform invariance and recognition performance.

• Investigative Magnetic Resonance Imaging
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• 제21권4호
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• pp.223-232
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• 2017

Purpose: To report the use of multiband accelerated echo-planar imaging (EPI) for resting-state functional MRI (rs-fMRI) to achieve rapid high temporal resolution at 3T compared to conventional EPI. Materials and Methods: rs-fMRI data were acquired from 20 healthy right-handed volunteers by using three methods: conventional single-band gradient-echo EPI acquisition (Data 1), multiband gradient-echo EPI acquisition with 240 volumes (Data 2) and 480 volumes (Data 3). Temporal signal-to-noise ratio (tSNR) maps were obtained by dividing the mean of the time course of each voxel by its temporal standard deviation. The resting-state sensorimotor network (SMN) and default mode network (DMN) were estimated using independent component analysis (ICA) and a seed-based method. One-way analysis of variance (ANOVA) was performed between the tSNR map, SMN, and DMN from the three data sets for between-group analysis. P < 0.05 with a family-wise error (FWE) correction for multiple comparisons was considered statistically significant. Results: One-way ANOVA and post-hoc two-sample t-tests showed that the tSNR was higher in Data 1 than Data 2 and 3 in white matter structures such as the striatum and medial and superior longitudinal fasciculus. One-way ANOVA revealed no differences in SMN or DMN across the three data sets. Conclusion: Within the adapted metrics estimated under specific imaging conditions employed in this study, multiband accelerated EPI, which substantially reduced scan times, provides the same quality image of functional connectivity as rs-fMRI by using conventional EPI at 3T. Under employed imaging conditions, this technique shows strong potential for clinical acceptance and translation of rs-fMRI protocols with potential advantages in spatial and/or temporal resolution. However, further study is warranted to evaluate whether the current findings can be generalized in diverse settings.

• Journal of Korea Multimedia Society
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• 제13권5호
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• pp.710-721
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• 2010

Recently, for the advancement of embedded technology about mobile device, a new kind of service, mash-up is appeared. It is service or application combining multimedia content making tool or device and web-GIS(geographic information system) service in the mobile environment. This service can be ease to use for casual user and can apply in various ways. So, It is served in web 2.0 environment actively. But, in the mashup service, because generated multimedia contents linked with web map are new type of multimedia contents which include user's migration routes in the space such as GPS coordinates. Thus, there are no protection ways for intellectual property created by GIS web-map service users and user's privacy. In this paper, we proposed a location and user information hiding scheme for GIS web-map service. This scheme embeds location and user information into a picture that is taken by camera module on the mobile phone. It is not only protecting way for user's privacy but is also tracing way against illegal photographer who is peeping person through hidden camera. And than, we also realized proposed scheme on the mobile smart phone. For minimizing margin of error about location coordinate value against contents manipulating attacks, GPS information is embedded into chrominance signal of contents considering weight of each digit about binary type of GPS coordinate value. And for tracing illegal photographer, user information such as serial number of mobile phone, phone number and photographing date is embedded into frequency spectrum of contents luminance signal. In the experimental results, we confirmed that the error of extracted information against various image processing attacks is within reliable tolerance. And after file format translation attack, we extracted embedded information from the attacked contents without no damage. Using similarity between extracted one and original templete, we also extracted whole information from damaged chrominance signal of contents by various image processing attacks.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제32권3C호
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• pp.278-286
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• 2007

In this paper, an efficient algorithm is proposed for the interpolation of interlaced images. First of all, by efficiently estimating the directional spatial correlations of neighboring pixels, increased interpolation accuracy can be achieved. And then using the gradient vector which was obtained by Sobel operation, enables to consider the fine directional edges and make it possible to estimate the accurate direction of edges. In other words, it is possible to interpolate the interlaced images with considering the characteristics of images. In addition, by altering the conventional edge detector for the purpose of a easy De-interlacing and multiplying the optimal translation coefficients to each of the gradient vectors, an efficient interpolation for images can be achieved. Comparing with the conventional De-interlacing algorithms, proposed algorithm not only reduced the complexity but also estimated the accurate edge direction and the proposed scheme have been clearly verified that it enhances the objective and subjective image quality by the extensive simulations for various images.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제14권11호
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• pp.5385-5391
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• 2013

As on-line purchases is activated, customers' demand increases for the realistic and accurate digital information of a product design. In this paper, we propose a practical method that can generate a realistic 3D model of a real product using a 3D geometry obtained by a 3D scanner and its photographic images. In order to register images to the 3D geometry, the camera focal length, the CCD scanning aspect ratio and the transformation matrix between the camera coordinate and the 3D object coordinate must be determined. To perform this 2D-3D registration with consideration of computational complexity, a three-step method is applied, which consists of camera calibration, determination of a temporary optimum translation vector (TOTV) and nonlinear optimization for three rotational angles. A case study for a metallic coated industrial part, of which the colour appearance is hardly obtained by a 3D colour scanner has performed to demonstrate the effectiveness of the proposed method.

• Journal of Broadcast Engineering
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• 제24권4호
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• pp.580-591
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• 2019

This paper focuses on to improving object detection performance using the camera and LiDAR on autonomous vehicle platforms by fusing detected objects from individual sensors through a late fusion approach. In the case of object detection using camera sensor, YOLOv3 model was employed as a one-stage detection process. Furthermore, the distance estimation of the detected objects is based on the formulations of Perspective matrix. On the other hand, the object detection using LiDAR is based on K-means clustering method. The camera and LiDAR calibration was carried out by PnP-Ransac in order to calculate the rotation and translation matrix between two sensors. For Sensor fusion, intersection over union(IoU) on the image plane with respective to the distance and angle on world coordinate were estimated. Additionally, all the three attributes i.e; IoU, distance and angle were fused using logistic regression. The performance evaluation in the sensor fusion scenario has shown an effective 5% improvement in object detection performance compared to the usage of single sensor.

• The KIPS Transactions:PartB
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• 제9B권3호
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• pp.369-374
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• 2002

In this paper, we propose the react-time car license plate recognition algorithm using intensity variation and geometric pattern vector. Generally, difference of car license plate region between character and background is more noticeable than other regions. And also, car license plate region usually shows high density values as well as constant intensity variations. Based on these characteristics, we first extract car license plate region using intensity variations. Secondly, lightness compensation process is performed on the considerably dark and brightness input images to acquire constant extraction efficiency. In the proposed recognition step, we first pre-process noise reduction and thinning steps. And also, we use geometric pattern vector to extract features which independent on the size, translation, and rotation of input values. In the experimental results, the proposed method shows better computation times than conventional circular pattern vector and better extraction results regardless of irregular environment lighting conditions as well as noise, size, and location of plate.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제29권4C호
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• pp.494-504
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• 2004

The researches about gaze detection have been much developed with many applications. Most previous researches only rely on image processing algorithm, so they take much processing time and have many constraints. In our work, we implement it with a computer vision system setting a IR-LED based single camera. To detect the gaze position, we locate facial features, which is effectively performed with IR-LED based camera and SVM(Support Vector Machine). When a user gazes at a position of monitor, we can compute the 3D positions of those features based on 3D rotation and translation estimation and affine transform. Finally, the gaze position by the facial movements is computed from the normal vector of the plane determined by those computed 3D positions of features. In addition, we use a trained neural network to detect the gaze position by eye's movement. As experimental results, we can obtain the facial and eye gaze position on a monitor and the gaze position accuracy between the computed positions and the real ones is about 4.2 cm of RMS error.