• The Research Journal of the Costume Culture
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• v.14 no.3 s.62
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• pp.366-380
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• 2006

The purpose of this study was to examine the effect of shopping orientations on clothing purchasing behavior according to residence. The data was obtained from questionnaires filled out by 530 females living in Seoul and Jecheon. For data analysis, factor analysis, ANOVA, t-test, Cronbach's $\alpha$, Duncan's multiple range test and cluster analysis were used. For shopping orientation, five factors of orientation were found and labeled as hedonism, brand and store loyalty, conformity, economy and rationality factor. Based on five shopping orientation factors, women were classified into five clusters(self-centered and rational, recreational, economy and shopping low involvement, economical and conformative cluster). Each cluster showed significantly different clothing purchasing behaviors (problem recognition, information search and evaluative criteria) and had different demographic variables(age, income, marital status and school career). Finally, residence and shopping orientations have influenced various clothing purchasing behavior. In conclusion, residence was the important factor which influenced on shopping orientation and clothing purchasing behavior.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.327-336
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• 2002

Texture analysis is an important technique in many image understanding areas, such as perception of surface, object, shape and depth. But the previous works are intend to the issue of only texture segment, that is not capable of acquiring recognition information. No unsupervised method is basased on the recognition of texture in image. we propose a novel approach for efficient texture image analysis that uses unsupervised learning schemes for the texture recognition. The self-organization neural network for multiple texture image identification is based on block-based clustering and merging. The texture features used are the angle and magnitude in orientation-field that might be different from the sample textures. In order to show the performance of the proposed system, After we have attempted to build a various texture images. The final segmentation is achieved by using efficient edge detection algorithm applying to block-based dilation. The experimental results show that the performance of the system Is very successful.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.10
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• pp.2317-2328
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• 1997

The objective of this paper is to develop an algorithm for a real-time automatic fingerprint recognition system. The algorithm employs the wavelet transform(WT) and the dominat local orientation that derived from the gradient Gaussian(GoG) and coherence in determining the directions of ridges in fingerprint images. By using the WT, the algorithm does not require conventional preprocessing procedures such as smothing, binarization, thining and restoration. For recognition, two fingerprint images are compared in three different ST domains;one that represents the original image compressed to quarter(LL), another that shows vertical directional characteristic(LH), and third as the block that contains horizontal direction(HL) in WT domain. Each block has dominat local orientation that derived from the GoG and coherence. The proposed algorithm is imprlemented on a SunSparc-2 workstation under X-window environment. Our simulation results, in real-time have shown that while the rate of Type II error-Incorrect recognition of two identical fingerprints as the identical fingerprints-is held at 0%, the rate of Type I error-Incorrect recognitionof two identical fingerprints as the different ones-is 2.5%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2143-2149
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• 2007

Visual Cortex Stimulator is among artificial retina prosthesis for blind man, is the method that stimulate the brain cell directly without processing the information from retina to visual cortex. In this paper, we propose image construction and recognition model that is similar to human visual processing by recognizing the feature data with orientation information, that is, the characteristics of visual cortex. Back propagation algorithm based on Delta-bar delta is used to recognize after extracting image feature by Kirsh edge detector. Various numerical patterns are used to analyze the performance of proposed method. In experiment, the proposed recognition model to extract image characteristics with the orientation of information from retinal cells to visual cortex makes a little difference in a recognition rate but shows that it is not sensitive in a variety of learning rates similar to human vision system.

• Journal of The Korean Association For Science Education
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• v.32 no.7
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• pp.1222-1240
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• 2012

The purpose of this study was to compare the differences of the vocational values and the career orientation of science between middle school scientifically gifted students and non-gifted students. The subjects were 85 middle school scientifically gifted students and 139 middle school non-gifted students. For this purpose, the questionnaires about vocational values and science career orientation were administered. The results of this study were as follows: First, the vocational values between two groups were significantly different in 'diversity', 'reward', 'social recognition' and 'autonomy' among all 11 domains. 'Diversity' and 'autonomy' showed the highest scores for scientifically gifted students. On the other hand, for the non-gifted students, 'reward' and 'social recognition' showed the highest scores. Second, the grand mean of the science career orientation between two groups showed significant differences. The average of scientifically gifted students was significantly higher than that of the non-gifted students in all four sub-domains. Third, the main effect of the vocational values according to gender did not exist, but there were main effects, including diversity, reward, stability, social recognition and autonomy, between two groups. There was no interaction effect between group and gender in the vocational values. Fourth, there were interaction effects between group and gender in the science career orientation. The main effects existed in four sub-domains of science career orientation. However, according to gender, the main effect existed in the sub-domain 'job preference for science' between the male students and the female students.

• Knowledge Management Research
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• v.17 no.4
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• pp.77-104
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• 2016

The effective management of R&D employees is critical for a small or medium sized firm's sustainable growth. R&D employees have professional skills and choose expertise-oriented or management-oriented careers in the process of organizational socialization. This study synthetically verifies the direct and indirect effects of R&D employees' social network and self-esteem on their career orientation by organizational commitment based on social network theory and social recognition theory. The research model has been analyzed through structural equation modeling using survey responses from 220 R&D employees at small- and medium-sized firms in Korea. The analysis results show that internal network activities have direct and indirect impacts on organizational commitment and career orientation, but external network activities do not have significant effects on self-esteem, organizational commitment, or career orientation. There is no consensus in prior studies on whether expert orientation and management orientation are distinct concepts. In this study, these two types of orientation are verified as distinct concepts. It is also found that R&D employees' internal network activities are significant factors for a company's growth. A company should implement an educational system of roles and duties using which individuals can pursue career progression. In addition, it is necessary to provide career development programs such as job rotation, mentoring, and career counseling.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.17-20
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• 2000

This paper describes a shape-based object recognition algorithm using multiple distance images. For the images containing dense edge points and noise, previous Hausdorff distance (HD) measures yield a high ms error for object position and many false matchings for recognition. Extended version of HD measure considering edge position and orientation simultaneously is proposed for accurate matching. Multiple distance images are used to calculate proposed matching measure efficiently. Results are presented for visual images and infrared images.

• Journal of KIISE:Software and Applications
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• v.41 no.8
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• pp.586-597
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• 2014

The next generation mobile computing technology is recently attracting attention that smartphone and wearable device imbedded with various sensors are being deployed in the world. Existing activity and posture recognition research can be divided into two different ways considering feature of one's movement. While activity recognition focuses on catching distinct pattern according to continuous movement, posture recognition focuses on sudden change of posture and body orientation. There is a lack of research constructing a system mixing two separate patterns which could be applied in real world. In this paper, we propose a method to use both smartphone and wearable device to recognize activity and posture in the same time. To use smartphone and wearable sensor data together, we designed a pre-processing method and constructed recognition model mixing signal vector magnitude and orientation pattern features of vertical and horizontal. We considered cycling, fast/slow walking and running activities, and postures such as standing, sitting, and laying down. We confirmed the performance and validity by experiment, and proved the feasibility in real world.

• Korea Trade Review
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• v.46 no.2
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• pp.55-74
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• 2021

Despite the growing importance of the logistics industry, it has been socially recognized as a 3D job and is perceived as a field of lower professional identity since the workers themselves think that they are engaged in a less important job. According to the related researches, it shows that professional identity affects the quality of service to customers, and applying it to the workers who are engaged in the logistics industry should be a meaningful subject of research. Therefore, this study intends to look into the impact of professional identity by managers in logistics centers on their service orientation and job engagement. To this end, this study surveyed managers in logistics centers across the country and conducted exploratory factor analysis, confirmatory factor analysis, and path analysis through structural equation models. The results of this study are summarized as follows. First, among the sub-factors of professional identity, recognition of professionalism did not have a significant effect on service orientation and job engagement, while acquisition recognition and range cognition had significant effects on it. Second, service orientation had a significant effect on job engagement. It believes that this study suggested implications for educational institutions and logistics companies that develop human resources of logistics in the aspect of that it presented the importance of developing human resources of logistics as well as the directivity to where the working environment such as the autonomy in their works and the extension of their authority should take their way.

• Smart Media Journal
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• v.1 no.4
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• pp.18-26
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• 2012

The increase of the number of smartphone applications has enforced the importance of new user interface emergence and has raised the interest of research in the convergence of multiple sensors. In this paper, we propose a method for the convergence of acceleration, magnetic and gyro sensors to recognize the gesture from motion of user smartphone. The proposed method first obtain the 3D orientation of smartphone and recognize the gesture of hand motion by using HMM(Hidden Markov Model). The proposed method for the representation for 3D orientation of smartphone in spherical coordinate was used for quantization of smartphone orientation to be more sensitive in rotation axis. The experimental result shows that the success rate of our method is 93%.