• Journal of Korean Society of Transportation
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• v.25 no.3
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• pp.99-109
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• 2007

Variable message signs (VMS), which are used for providing real-time information on traffic conditions and accident occurrences, are one of the important components of intelligent transportation systems VMS messages need to meet human factor requirements: messages should be readable and understandable while driving. Lab-controlled experiments on VMS messages were conducted to obtain useful data for analyzing drivers' responsive characteristics for VMS messages. Binary logistic regression (BLR) modeling techniques were applied to explore the relationships among drivers' message perceptions, message reading time, and amount of VMS messages. Probabilistic outcomes of the proposed BLR-based perception model could be greatly utilized to design VMS messages considering drivers' legibility performance. The major contribution of this study is to develop invaluable statistical models that can be used in designing VMS messages more effectively from the human factor point of view. The results could be further applied to establish the scheme of VMS message phase and duration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2938-2956
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• 2020

Objective image quality assessment (IQA) models have been developed by effective features to imitate the characteristics of human visual system (HVS). Actually, HVS is extremely sensitive to color degradation and complex texture changes. In this paper, we firstly reveal that many existing full reference image quality assessment (FR-IQA) methods can hardly measure the image quality with contrast and masking texture changes. To solve this problem, considering texture masking effect, we proposed a novel FR-IQA method, called Texture and Color Quality Index (TCQI). The proposed method considers both in the masking effect texture and color visual perceptual threshold, which adopts three kinds of features to reflect masking texture, color difference and structural information. Furthermore, random forest (RF) is used to address the drawbacks of existing pooling technologies. Compared with other traditional learning-based tools (support vector regression and neural network), RF can achieve the better prediction performance. Experiments conducted on five large-scale databases demonstrate that our approach is highly consistent with subjective perception, outperforms twelve the state-of-the-art IQA models in terms of prediction accuracy and keeps a moderate computational complexity. The cross database validation also validates our approach achieves the ability to maintain high robustness.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.18-29
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• 2019

In the field of Human-Computer Interaction design, persuasive design has gradually been applied to the system development and design process, especially for mobile application design. However, most mobile applications have hitherto a very short using lifecycle. Especially, design features with long-term persuasive effectiveness remain to be further researched and developed. In this study, we focused on investigating and identifying the durative persuasive design characteristics through a data mining process and evaluating the durative effectiveness through a long-term observation process. Total five hundred healthcare-related mobile applications were selected from Apple iTunes Store and a mixed method was conducted to extract the most common persuasive design characteristics. Based on the results of extraction, a representative healthcare-related mobile application was selected as experimental subject. Total one hundred and twenty participants were observed during a six-months experiment and the monitoring data of app usage of all participants was collected once a week. According to the evaluation model for behavior change identification process, participants with habit formation features were proved to have a significant long-term perception level for ten persuasive design characteristics. Further interview research was performed to investigate the participant's long-term perceptions on those characteristics for the purpose of identifying the durative persuasions. The results indicated that a long-term durative effectiveness can be observed and healthcare-related apps designed with those characteristics could have durative effectiveness. This study may contribute to the improvement of future mobile application designs in user experience and durative persuasion, as well as bringing future benefits for both mobile application developers and users.

• Journal of the Daesoon Academy of Sciences
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• v.49
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• pp.1-52
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• 2024

One notable characteristic of Daesoon Jinrihoe's view of time, is its perception of time as a passive entity. This signifies that, in the context of Daesoon Jinrihoe, time is subject to influence through experience, specifically undergoing re-calibration or governance. The summary of this perspective is as follows: Firstly, Daesoon Jinrihoe's understanding of time incorporates a historical viewpoint characterized by the law of entropy, which posits that disorder increases as time progresses. Secondly, within the world established by Daesoon Jinrihoe, time experiences transformation before and after the Great Opening. Prior to this event, time follows a helical model characterized by increasing chaotic disorder, whereas in the Later World, the helical model reflects only Mutual Beneficence, symbolizing progress and development in the era. Thirdly, the Great Opening re-calibrates time, serving as the criterion for determining human life. Prior to the Great Opening, time recorded human life in a manner marked by Mutual Contention, whereas afterward, it will record human life as being characterized by Mutual Beneficence. This re-calibration of time leads precisely to directional (spatial) re-calibration. Fourthly, the Great Opening re-calibrates the order of time and space. In the Former World, space held precedence over time. However, the Great Opening changes this dynamic, with time assuming precedence over space in the Later World. In this context, the integration of time and space establishes a worldview. Fifthly, in the worldview of Daesoon Jinrihoe, time serves as a vehicle for the governance of the Supreme God. The Supreme God governs all things by controlling time, orchestrating changes spanning birth (saeng, 生), growth (jang, 長), harvest (yeom, 斂), and storage (jang, 藏), much like how problems are resolved through natural progress without requiring deliberate action. Lastly, time functions as a medium through which entities that strive to achieve unification with the Dao come to govern all things. For this reason, achieving unification with the Dao in Daesoon Jinrihoe specifically refers to the governance of time.

• Korea journal of population studies
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• v.33 no.2
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• pp.33-59
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• 2010

This paper intends to find the determinants of the occupational aspirations of college students in Korea. According to Wisconsin model, the occupational aspiration of youth has a statistically significant influence on his or her actual education level and occupation choice implying that the more motivated with high-level occupational aspiration will obtain the higher level of occupation. The analysis for this study is based on the survey of undergraduate students' perception, attitude and lifestyle in Korea 2004, which was conducted against 1,947 respondents, and multiple regression model was utilized. The dependent variable for occupational aspirations was measured by the Standard International Occupational Prestige Scale (SIOPS) of Donald J. Treiman. Independent variables include social capital and cultural capital as well as demographic variables, socio-economic status, and human capital variables. Social capital variable was measured by the position generator scale of Nan Lin and Mary Dumin, and cultural capital variable was done to our original index. This study shows that social and cultural capitals are factors having significant influence on occupational aspiration, in addition to the well-known factors such as gender, human capital and the occupation of father.

• Journal of KIISE
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• v.42 no.5
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• pp.609-620
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• 2015

Viewers of videos are likely to absorb more information from the part of the screen that attracts visual attention. This fact has led to the visual attention models that are being used in producing and evaluating videos. In this paper, we investigate the factors that are significant to visual attention and the mathematical form of the visual attention model. We then estimated the visual attention probability using the statistical design of experiments. The analysis of variance (ANOVA) verifies that the motion velocity, distance from the screen, and amount of defocus blur affect human visual attention significantly. Using the response surface modeling (RSM), we created a visual attention score model that concerns the three factors, from which we calculate the visual attention probabilities (VAPs) of image pixels. The VAPs are directly applied to existing gradient based 3D effect perception measurement. By giving weights according to our VAPs, our algorithm achieves more accurate measurement than the existing method. The performance of the proposed measurement is assessed by comparing them with subjective evaluation as well as with existing methods. The comparison verifies that the proposed measurement outperforms the existing ones.

• Fashion & Textile Research Journal
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• v.22 no.5
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• pp.570-583
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• 2020

The fashion industry is accountable for labor and environment-related issues. With such issues raised, consumers' social responsibility for environmental and labor issues has become an important factor that shapes the perception of companies. This study investigates the relationship between consumer values, concerns regarding social issues, and willingness to pay a premium for ethical fashion products. This study included two exogenous variables of altruistic value and egocentric value. In the conceptual model, consumers' social responsibility was conceptualized as two constructs of environmental consciousness and labor-issue consciousness. It was then analyzed as mediating variables. Willingness to pay a premium for ethical fashion products was the endogenous variable. Data was collected and analyzed with PLS-SEM from 600 consumers. The assessment of discriminant validity and construct validity using CFA were conducted before analyzing the model. Structural equation modeling results revealed that altruistic value directly influenced environmental consciousness and labor-issue consciousness. However, egocentric value was directly and significantly influenced only by labor-issue consciousness. Both environmental and labor issue consciousness directly influenced customers' willingness to pay a premium, but did not significantly change their willingness to pay a premium. Two-stage serial mediation analysis results indicated that the constructs did not have a significant mediation effect on the exogenous variables (altruistic value and egocentric value) and the endogenous variable (willingness to pay a premium) for ethical fashion products. This study found the influence of consumer's personal values on their willingness to pay a higher price for ethical fashion products.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.288-307
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• 2016

Image distortions are typically characterized by degradations of structures. Dictionaries learned from natural images can capture the underlying structures in images, which are important for image quality assessment (IQA). This paper presents a general-purpose no-reference image quality metric using a GRadient-Induced Dictionary (GRID). A dictionary is first constructed based on gradients of natural images using K-means clustering. Then image features are extracted using the dictionary based on Euclidean-norm coding and max-pooling. A distortion classification model and several distortion-specific quality regression models are trained using the support vector machine (SVM) by combining image features with distortion types and subjective scores, respectively. To evaluate the quality of a test image, the distortion classification model is used to determine the probabilities that the image belongs to different kinds of distortions, while the regression models are used to predict the corresponding distortion-specific quality scores. Finally, an overall quality score is computed as the probability-weighted distortion-specific quality scores. The proposed metric can evaluate image quality accurately and efficiently using a small dictionary. The performance of the proposed method is verified on public image quality databases. Experimental results demonstrate that the proposed metric can generate quality scores highly consistent with human perception, and it outperforms the state-of-the-arts.

• Smart Media Journal
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• v.3 no.2
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• pp.20-28
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• 2014

The issues of generation, delivery, and processing of information which have been treated importantly in information design field have evolved along with the evolution of the humankind. In the modern society, the vast amount of, complex, and artificial forms of information such as big-data is accounted for the majority and claims of interest focusing on how to effectively design those kinds of information are being increased. This study explored the visualization methods applied with the natural objects as motives as one of the ways for users to easily get their perception and cognition to the information. Nature has long influenced on the human figural activities. The natural objects take the optimum visual shapes and provide the diverse inspiration and emotion to the designers in the various design fields such as product design, architecture design, and so on. Through the literature studies, we suggested the compositional principles of natural objects and the principles for observing and analysing natural objects as a principle to use the natural objects for information design domain. We, also, suggested the information design approach model which is inspired the natural objects by linking those two kinds of principles to the information design's visual realization factors and explored the possibilities of utilizing of the approach model by the case studies.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.193-204
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• 2021

Based on risk-benefit theory, this study examined a structural equation model accounting for the mechanisms through which affective perceptions of AI predicting individuals' support for the government's Ai policies. Four perceived characteristics of AI (i.e., usefulness, entertainment value, privacy concern, threat of human replacement) were investigated in relation to perceived benefits/risks, attitudes toward AI, and AI policy support, based on a nationwide sample of South Korea (N=352). The hypothesized model was well supported by the data: Perceived usefulness was a strong predictor of perceived benefit, which in turn predicted attitude and support. Perceived benefit and attitude played significant roles as mediators. Perceived entertainment value along with perceived usefulness and privacy concern predicted attitude, not perceived benefit. Neither attitude nor support was significantly associated with perceived risk which was predicted by privacy concern. Theoretical and practical implications of the results are discussed.