• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.585-593
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• 2021

The service industry has become the driving force of economic development in recent years. With the current fierce competitive situation, competing businesses have continually provided a superior quality of service, and an excellent perceived brand image to gain customer satisfaction and customer loyalty. This study's current purpose is to empirical research the linking between service quality, brand image, customer satisfaction, and customer loyalty. We collect research data from 299 consumers who bought goods at supermarkets in Ho Chi Minh City, Vietnam, using a convenient sampling technique. We proposed the conceptual model from prior studies and considered it in Vietnam's context. PLS-SEM was conducted to test the relationships in the conceptual model. We have estimated the scale's reliability by Cronbach's alpha values and composite reliability values. Moreover, we have evaluated discriminant validity by the Fornell-Larcker standard. The findings showed that service quality positively affects the brand image, customer satisfaction, and customer loyalty. Likewise, the results also confirmed brand image had a positive impact on customer satisfaction and customer loyalty. Moreover, the outcomes also disclosed that customer satisfaction had a positive relationship with customer loyalty. The research suggested implications for managers, limitations, and directions for future research from the above findings.

• Journal of Broadcast Engineering
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• v.9 no.3
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• pp.207-213
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• 2004

The layered depth image (LDI) is an efficient approach to represent three-dimensional objects with complex geometry for image-based rendering (IBR). LDI contains several attribute values together with multiple layers at each pixel location. In this paper, we propose an efficient preprocessing algorithm to compress depth information of LDI. Considering each depth value as a point in the two-dimensional space, we compute the minimum distance between a straight line passing through the previous two values and the current depth value. Finally, the minimum distance replaces the current attribute value. The proposed algorithm reduces the variance of the depth information , therefore, It Improves the transform and coding efficiency.

• Nuclear Engineering and Technology
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• v.51 no.6
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• pp.1610-1615
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• 2019

Positron emission tomography (PET)/magnetic resonance (MR) scanning has the advantage of less additional exposure to radiation than does PET/computed tomography (CT). In particular, MR based attenuation correction (MR AC) can greatly affect the image quality of PET and is frequently obtained using various MR sequences. Thus, the purpose of the current study was to quantitatively compare the image quality between MR non-AC (MR NAC) and MR AC in PET images with three MR sequences. Percent image uniformity (PIU), percent contrast recovery (PCR), and percent background variability (PBV) were estimated to evaluate the quality of PET images with MR AC. Based on the results of PIU, 15.2% increase in the average quality was observed for PET images with MR AC than for PET images with MR NAC. In addition, 28.6% and 71.1% improvement in the average results of PCR and PBV respectively, was observed for PET images with MR AC compared with that with MR NAC. Moreover, no significant difference was observed among the average values using three MR sequences. In conclusion, the current study demonstrated that PET with MR AC improved the image quality and can be help diagnosis in all MR sequence cases.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.2
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• pp.177-184
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• 2013

This paper proposes an enhanced Simultaneous Localization and Mapping (SLAM) algorithm based on matching laser image and Extended Kalman Filter (EKF). In general, laser information is one of the most efficient data for localization of mobile robots and is more accurate than encoder data. For localization of a mobile robot, moving distance information of a robot is often obtained by encoders and distance information from the robot to landmarks is estimated by various sensors. Though encoder has high resolution, it is difficult to estimate current position of a robot precisely because of encoder error caused by slip and backlash of wheels. In this paper, the position and angle of the robot are estimated by comparing laser images obtained from laser scanner with high accuracy. In addition, Speeded Up Robust Features (SURF) is used for extracting feature points at previous laser image and current laser image by comparing feature points. As a result, the moving distance and heading angle are obtained based on information of available points. The experimental results using the proposed laser slam algorithm show effectiveness for the SLAM of robot.

• Current Industrial and Technological Trends in Aerospace
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• v.6 no.2
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• pp.90-98
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• 2008

In recent, image data compression method of high resolution satellite image is the important issue for its application and development. The CCSDS (Consultative Committee for Space Data Systems) published a standard for the high resolution image data compression, CCSDS 122.0-B-1, in the end of 2005, which is expected to be widely applied in process of compression for the high resolution satellite images. In this paper, it is explained that the current trends of image compression methods for high resolution satellites, and then the comparison results between CCSDS 122.0-B-1 standard and JPEG are described.

• Korean Journal of Remote Sensing
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• v.16 no.3
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• pp.199-209
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• 2000

This study improves the feature tracking method (FTM) in estimating the ocean current vectors from the sequential AVHRR satellite imageries by adding the objective algorithm in defining the edges and boundaries of the oceanic eddies and fronts. It was implemented by using the Sobel operator. The Sobel operator has been proved to be in effective filter in detecting the edges of any object on the image. In estimating the current vectors on the edges defined by the Sobel operator, center coordinates of the Pattern and Search tiles need to be determined by the investigator. The objective feature tracking method combined with maximum cross correlation method (MCC) is turned out to be very efficient and fast, since it uses only parts of the image containing the objects instead of searching the entire image. In the validation with the in situ ADCP measurements of currents in the East Sea, the estimated current speed values are around 35% lower than and current directions are deviated by $34^{\circ}$ from ADCP current vectors. The results are regarded as improved ones compared to the previous investigators'.

• Journal of the Korean Magnetics Society
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• v.13 no.2
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• pp.47-52
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• 2003

Ferromagnetic tunnel junctions were fabricated by dc magnetron sputtering and plasma oxidation process. The local transport properties of the ferromagnetic tunnel junctions were studied using contact-mode Atomic Force Microscopy (AFM) and the local current-voltage analysis. Tunnel junctions with the structure of sub./Ta/Cu/Ta/NiFe/Cu/Mn$\_$75/Ir$\_$25//Co$\_$70/Fe$\_$30//Al-oxide were prepared on thermally oxidized Si wafers. Al-oxide layers were formed with microwave excited plasma using radial line slot antenna (RLSA) for 5 and 7 sec. Kr gas was used as the inert gas mixed with $O_2$ gas for the plasma oxidization. No correlation between topography and current image was observed while they were measured simultaneously. The local current distribution was well identified with the distribution of local barrier height. Assuming the gaussian distribution of the local barrier height, the ferromagnetic tunnel junction with longer oxidation time was well fitted with the experimental results. As contrast, in the case of the shorter time oxidation junction, the current mainly flow through the low barrier height area for its insufficient oxygen. Such leakage current might result in the decrease of tunnel magnetoresistance (TMR) ratio.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.07a
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• pp.388-389
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• 2005

In this paper, the electric properties of mercury Iodide multi-layer samples has been investigated. We measured and analyzed their performance parameters such as the X-ray sensitivity and dark-current for a mercury Iodide multi-layer X-ray detector with a dielectric layer. The digital X-ray image detector can be constructed by integrating photoconduction multi-layer that dielectric layer has characteristics of low dark-current, high X-ray sensitivity. However this process has found to have complexity on the performance of the sample. We have investigate dielectric layer that it substitute dielectric layer for HgO(Mercury Oxide). We have employed two approaches for producing the mercury Iodide sample : 1) Physical Vapor Deposition(PVD) and 2) Particle-In-Binder(PIB). In this paper fabricated by PIB Method with thicknesses ranging from approximately 180um to 240um and we could produce high-quality samples for each technique particular application. As results, the dielectric materials such as HgO between the dielectric layer and the top electrode may reduce the dark-current of the samples. Mercury Iodide multi-layer having HgO has characteristics of low dark-current, high X-ray sensitivity and simple processing. So we can acquired a enhanced signal to noise ratio. In this paper offer the method can reduce the dark-current in the X-ray detector.

• Korean Journal of Community Nutrition
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• v.4 no.4
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• pp.554-560
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• 1999

This study was conducted to find adolescent females perception of body image. The survey was carried out by self-questionnaires with 463 female school and college students in Daegu. Analysis of data was done using t-test, and ANOVA with the SAS computer program. The average height, weight and BMI of the subjects were 161.2cm, 53.4kg and 20.51kg/$m^2$. It appeared that 33.3% of the subjects were off the normal range of body weight ; in particular 25.1% of the subjects were under weight. While the subjects’perception of their own current body image was not distorted, they were dissatisfied with their body image because they wanted a very thin figure. Subjects were divided into 3 groups -underweight, normal weight, overweight-according to their current body size. Their perceptions of ideal and desired figures differed significantly between the groups, but they thought a thinner figure than normal body image as ideal and desired body image even in overweight group. As a result, dissatisfaction of body image in the overweight group was significantly larger than the normal-weight group, and that of the normal-weight group was larger than the underweight group. Percentages of weight control attempt were 51.7% and 64.7% in the normal weight and underweight subjects, respectively. Subjects were divided into 2 groups according to their weight control experience : those who have attempted, and who have not attempted. Weight control attemptees had a higher level of dissatisfaction with their body image than non-attemptees, both because weight control attemptees were fatter, and they perceived a thinner figure as an ideal and as a desired body image thin non-attemptees. From the results of this study, we confirmed that one of reasons of excessive weight control behavior among adolescent females was distorted perception about ideal body image.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.525-528
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• 2009

Recently, image classification has been an important task in various fields. Generally, the performance of image classification is not good without the adjustment of image features. Therefore, it is desired that the way of automatic feature extraction. In this paper, we propose an image classification method which adjusts image features automatically. We assume that texture features are useful in image classification tasks because natural images are composed of several types of texture. Thus, the classification accuracy rate is improved by using distribution of texture features. We obtain texture features by calculating image features from a current considering pixel and its neighborhood pixels. And we calculate image features from distribution of textures feature. Those image features are adjusted to image classification tasks using Genetic Algorithm. We apply proposed method to classifying images into "head" or "non-head" and "male" or "female".