• Proceedings of the KOR-KST Conference
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• 2000.02a
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• pp.25-47
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• 2000

In route guidance systems fastest-path routing has typically been adopted because of its simplicity. However, empirical studies on route choice behavior have shown that drivers use numerous criteria in choosing a route. The objective of this study is to develop computationally efficient algorithms for identifying a manageable subset of the nondominated (i.e. Pareto optimal) paths for real-time vehicle routing which reflect the drivers' preferences and route choice behaviors. We propose two pruning algorithms that reduce the search area based on a context-dependent linear utility function and thus reduce the computation time. The basic notion of the proposed approach is that ⅰ) enumerating all nondominated paths is computationally too expensive, ⅱ) obtaining a stable mathematical representation of the drivers' utility function is theoretically difficult and impractical, and ⅲ) obtaining optimal path given a nonlinear utility function is a NP-hard problem. Consequently, a heuristic two-stage strategy which identifies multiple routes and then select the near-optimal path may be effective and practical. As the first stage, we utilize the relaxation based pruning technique based on an entropy model to recognize and discard most of the nondominated paths that do not reflect the drivers' preference and/or the context-dependency of the preference. In addition, to make sure that paths identified are dissimilar in terms of links used, the number of shared links between routes is limited. We test the proposed algorithms in a large real-life traffic network and show that the algorithms reduce CPU time significantly compared with conventional multi-criteria shortest path algorithms while the attributes of the routes identified reflect drivers' preferences and generic route choice behaviors well.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.163-171
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• 2023

The intelligent transportation system has made a huge leap in the level of human services, which has had a positive impact on the quality of life of users. On the other hand, these services are becoming a new source of risk due to the use of data collected from vehicles, on which intelligent systems rely to create automatic contextual adaptation. Most of the popular privacy protection methods, such as Dummy and obfuscation, cannot be used with many services because of their impact on the accuracy of the service provided itself, they depend on changing the number of vehicles or their physical locations. This research presents a new approach based on the shuffling Nicknames of vehicles. It fully maintains the quality of the service and prevents tracking users permanently, penetrating their privacy, revealing their whereabouts, or discovering additional details about the nature of their behavior and movements. Our approach is based on creating a central Nicknames Pool in the cloud as well as distributed subpools in fog nodes to avoid intelligent delays and overloading of the central architecture. Finally, we will prove by simulation and discussion by examples the superiority of the proposed approach and its ability to adapt to new services and provide an effective level of protection. In the comparison, we will rely on the wellknown privacy criteria: Entropy, Ubiquity, and Performance.

• Proceedings of the KSR Conference
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• 2004.10a
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• pp.1718-1724
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• 2004

A station is not only the public space where socially diverse classes get together and cultural interchanges occur but also the personal and emotional space where the meeting and parting occur for each individual. Thus, it is necessity to consider this dual point from the beginning of the plan to make the simple, comfortable, intuitive and friendly environment for the users in the station. Also, it should be capable of active life style of moderner according to the change of the city environment. Furthermore, as a station is not just a single-purpose space anymore but the versatile space where fulfills the user's needs for the multi-function and the desire for diversity. As the station in these days opened 24 hours for users with the modern, commercial and cultural facilities, the interior design for a station needs to be designed to be easy to use, functional and able to vitalize the environment. In order to make a desirable interior environment in a station, first of all, it is required to grasp the characteristic of the space by analyzing the phenomena of an individual or a group act in a existing space formed by the interrelation between the human and the environment. To reduce the resistance against the new environment from the user, in other words, to increase the satisfaction, it is necessity to induce the behavior of the users to the desirable way toward to the new environment. Consequently, positive methodology with recognitive approach through cognitive psychology, spatial behavior research is required.

• Science of Emotion and Sensibility
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• v.20 no.2
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• pp.161-170
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• 2017

Emotion affects many parts of human life such as learning ability, behavior and judgment. It is important to understand human nature. Emotion can only be inferred from facial expressions or gestures, what it actually is. In particular, emotion is difficult to classify not only because individuals feel differently about emotion but also because visually induced emotion does not sustain during whole testing period. To solve the problem, we acquired bio-signals and extracted features from those signals, which offer objective information about emotion stimulus. The emotion pattern classifier was composed of unsupervised learning algorithm with hidden nodes and feature vectors. Restricted Boltzmann machine (RBM) based on probability estimation was used in the unsupervised learning and maps emotion features to transformed dimensions. The emotion was characterized by non-linear classifiers with hidden nodes of a multi layer neural network, named deep belief network (DBN). The accuracy of DBN (about 94 %) was better than that of back-propagation neural network (about 40 %). The DBN showed good performance as the emotion pattern classifier.

• Journal of the Korean Society of Costume
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• v.62 no.2
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• pp.87-102
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• 2012

The purpose of this study is to identify conceptual constructs of well-being consciousness and appearance management behaviors, and to examine the effects of these two variables on attitudes toward Korean herbal cosmetics for Korean and Japanese consumers. A survey was carried out among female consumers between the ages of 20 and 50, and a total of 500 responses were analyzed by descriptive analysis, reliability test, t-test, and confirmatory factor analysis, structural equation modeling and multi group analysis. The results of this study were as follows: 1) The result of CFA and the reliability test on well-being consciousness and appearance management of Korean and Japanese respondents clearly showed factorial structures on each of the variant assessments. 2) In regards to the well-being consciousness, Korean and Japanese respondents highly tended to perceive well-being as a benefit to the physical health and an eco-friendly lifestyle respectively. In the area of appearance management, Korean and Japanese respondents had similar patterns that showed high scores of skin care and weight control. Both Korean and Japanese consumers showed favorable attitudes toward Korean herbal cosmetic products. 3) The consumers' well-being consciousness revealed to have positive influences on appearance management behavior. Both well-being consciousness and appearance management positively influenced attitudes toward Korean herbal cosmetics. 4) As a result of MGA, the well-being consciousness had more positive impacts on Korean respondents' attitudes toward Korean herbal cosmetics than the appearance management variable when compared to the Japanese respondents. On the other hand, appearance management had more positive impacts on Japanese respondents' attitudes to-ward Korean herbal cosmetics than well-being consciousness when compared to the Korean respondents. These results suggest that differentiated marketing strategies for Korean herbal cosmetics are crucial when targeting Korean and Japanese consumers.

• Journal of Broadcast Engineering
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• v.25 no.5
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• pp.750-757
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• 2020

One of the basic tasks for robots to interact with humans is to quickly and accurately grasp human behavior. Therefore, it is necessary to increase the accuracy of human pose recognition when the robot is estimating the human pose and to recognize it as quickly as possible. However, when the human pose is estimated using deep learning, which is a representative method of artificial intelligence technology, recognition accuracy and speed are not satisfied at the same time. Therefore, it is common to select one of a top-down method that has high inference accuracy or a bottom-up method that has high processing speed. In this paper, we propose two methods that complement the disadvantages while including both the advantages of the two methods mentioned above. The first is to perform parallel inference on the server using multi GPU, and the second is to mix bottom-up and One-class Classification. As a result of the experiment, both of the methods presented in this paper showed improvement in speed. If these two methods are applied to the entertainment robot, it is expected that a highly reliable interaction with the audience can be performed.

• Journal of Distribution Science
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• v.15 no.3
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• pp.73-80
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• 2017

Purpose - Since Korean distribution market was opened, the domestic environment in department stores has been changed by the pattern of consumption and consumer need based on income classes. As multilateral Free Trade Agreement (FTA) accelerates opening markets, the scale of circulating capital has become bigger. Large-scale commercial facilities have developed quickly as a form of a large shopping center, thus, the matter of choice and securing market area became an important valuable in this trend. Moreover, multi-complex space has been proposed as the goal of successful business with promoting the public benefit. Research design, data, and methodology - This research studied consumer behavior using data about the life style and sales of consumers, not statistical data or survey as previous studies. This research tried to find the differentiation in complex cultural space with consumption behavior of department store. Results - As the structure of society and culture was getting diverse and complex, economic growth and development with such diversity and complexity improved consumers' quality of life. The changes of consumer life style are quite natural like human instinct. Department stores have activated retail business with the products of accumulated technology. Moreover, they have created the space of consumption and culture. Because of these social and environmental changes, department stores are being developed as Multi-functional spaces as well as sale places considering the strategies of department and the changes of consumers' purchasing behaviors. Conclusions - Urban culture complex is a landmark standing for the culture era of 21st century. It has provided an opportunity for consumers to enjoy culture, and has been an important factor to improve company images. Based on these roles and needs, expectancy effects are related with consumer preference and space preference, and the attitude toward companies. Moreover, the expectancy effects from those relationships are getting bigger and bigger. We should respect nature, a characteristic of Korean architecture, maintain visual continuity that harmonies with nature in the development of the complex space of the domestic department stores, and should take significance in the development of the complex cultural space in the direction of feeling the hierarchy of the space to obtain the visual pleasure with the artificial structure.

• Journal of the HCI Society of Korea
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• v.13 no.2
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• pp.31-44
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• 2018

In the IoT environment, various things could be connected. Those connected things learn and operate themselves, by acquiring data. As human being, they have self-learning and self-operating systems. In the field of IoT study, therefore, the key issue is to design communication system connecting both of the two different types of subjects, human being(user) and the things. With the advent of the IoT environment, much research has been done in the field of UI design. It can be seen that research has been conducted to take complex factors into account through keywords such as multi-modality and interusability. However, the existing UI design method has limitations in structuring or testing interaction between things and users of IoT environment. Therefore, this paper suggests a new UI prototyping method. In this paper, the major analysis and studies are as follows: (1) defined what is the behavior process of the things (2) analyzed the existing IoT product (3) built a new framework driving personality types (4) extracted three representative personality models (5) applied the three models to the smart home service and tested UI prototyping. It is meaningful with that this study can confirm user experience (UX) about IoT service in a more comprehensive way. Moreover, the concept of the personality of things will be utilized as a tool for establishing the identity of artificial intelligence (AI) services in the future.

• Environmental Analysis Health and Toxicology
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• v.11 no.1_2
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• pp.19-29
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• 1996

Human exposure to volatile compounds in tap water can occur from inhalation and dermal absorption as well as direct ingestion. The relative contribution to total human exposure from these pathways has been considered to be important especially for VOC's (volatile organic compounds). In an attempt to reduce the uncertainty of the risk assessment, it has been suggested that the exposure assessment process could be significantly improved by adopting Monte-Carlo simulation. However, there is no actual data in Korea for each exposure parameter to determine the level of exposure, and the distributional pattern. Therefore, we surveyed water use patterns and behavior related to multi-route exposure to VOC's in household tap water in Korea, and compared these values to the those in western countries. In the first survey, we calculated daily water intake using data from a sample of 1322 persons of several cities in Korea. In the second survey, we obtained questionnaire data on exposure time for showering, bathing and household activities, and tap water intake from 851households in Korea. In the last survey, we measured the exposure parameters (exposure time, water use rate etc.) related to showers, baths, toilets, dish washing, washing and cooking, and tap water intake was surveyed. Also, the subjects were measured their body weight, height and tidal volume, etc. A diary, a flow meter and a measuring cup were used to measure these values as precisely as possible. Average daily water intake was ranged 0.79-1.71 L/day for adults in three surveys. Tap water intake measured by log-sheet during one week in third survey was 1.26 (average), 1.98 L/day (90 percentlie), respectively. These results were comparable with results from EPA (1.4, 2L/day). The average amount of water used by housewives in the third survey was 515.0 $\pm$ 564.6L/day. In usual activity, the amount of water used in the bathroom, the laundry and the kitchen was 140.0 $\pm$ 538.9, 148.0 $\pm$ 174.5, 229.3 $\pm$ 205.4 L/day, respectively. Exposure parameters such as water intake rate, exposure duration, body weight, inhalation rates in surveyed data of Korean people differed from those published from western countries. This could be attributed to variations in lifestyle, dietary habits and physiological characteristics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.253-263
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• 2018

This paper examined the U-shape curvilinear relationship between team level conflict management and individual level turnover intention by using exit-voice theory, bandwagon effect, and social loafing theory. In addition to the non-linear relationship between team-level conflict management and individual-level turnover intentions, we also examined how trust in leaders has a moderating effect on this relationship. The samples were collected from a South Korean manufacturing company with 331 team members from 48 teams and items were measured twice to avoid common method biases. The intercepts-as-outcomes model of hierarchical linear modelling was conducted to verify the hypothesis. Results supported the cross-level curvilinear hypothesis which indicated that employees' turnover intention sharply decreased if the activeness of group conflict management was small and increases slightly, but this tendency moderated as activeness increases. After passing the lowest point, their turnover intention increased in the end. However, the moderation effect of trust in leader on this relationship was not statistically significant and hypothesis 2 was rejected. This paper explained the effects of group dynamics of conflict management on individual turnover intention. Such evidence may elucidate the importance of managing the social loafing behavior on conflict management process. This paper examined the sequential, multi-level, and curvilinear relationship between conflict management and turnover intention. Organizations and managers will benefit from avoiding the human resource loss by managing the conflict management process.