• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2021년도 하계학술대회
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• pp.105-108
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• 2021

Generative adversarial networks (GANs) have reached a great result at creating the synthesis image, especially in the face generation task. Unlike other deep learning tasks, the input of GANs is usually the random vector sampled by a probability distribution, which leads to unstable training and unpredictable output. One way to solve those problems is to employ the label condition in both the generator and discriminator. CelebA and FFHQ are the two most famous datasets for face image generation. While CelebA contains attribute annotations for more than 200,000 images, FFHQ does not have attribute annotations. Thus, in this work, we introduce a method to learn the attributes from CelebA then predict both soft and hard labels for FFHQ. The evaluated result from our model achieves 0.7611 points of the metric is the area under the receiver operating characteristic curve.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2007년도 추계학술대회 및 정기총회
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• pp.121-129
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• 2007

Recently a multi-attribute structure analysis method is one of the evident areas of important points in the decision support system analysis. This research developed an internet/intranet-based solution builder for a three-step decision support system using fuzzy-AHP in the view of 1) brainstorming far the idea generation, 2) fuzzy-AHP (fuzzy analytic hierarchy process) as a multi-attribute structured analysis method and 3) aggregation logic model to integrate the results of individual analysis. We applied this decision support system to the make-or-buy decision problem for school foodservice system considering the multi-attributes in the decision making. A computer program is developed and demonstrated it internet/intranet-based decision problem. It was known that this solution builder provides decision makers a good tool for mate-of-buy group decision making.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1998년도 추계학술대회 논문집
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• pp.103-106
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• 1998

본 연구는 연구·개발 프로젝트의 평가를 위하여 연구·개발 프로젝트의 다-속성(Multi-attributes)을 고려하한 평가 모델의 연구이다. 이를 위하여 우선 평가구조를 구축하고 각 속성별 평가를 종합하기 위한 종합성과도(Total Preference Index)로 단일 측정치로 평가 할 수 있도록 종합하기 위한 적절한 효용함수를 도입하여 사용하였다. 이러한 평가 과정을 다-속성 의사결정 모델(Multi-attribute Utility Model)로 통합하였으며 연구·개발프로젝트의 특성을 고려하여 각 연구실의 책임자(Laboratory Directors)의 평가체계를 개발하여 본 평가모델에 포함하였다. 본 평가모델의 시험 적용을 위하여 특정 연구소에 시험적용하고 그 결과를 보였으며, 부분적으로 보완 연구될 경우 일반적인 프로젝트의 평가모델로 활용될 수 있으리라 생각된다.

• Asia pacific journal of information systems
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• 제16권4호
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• pp.1-25
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• 2006

This research approached the negotiation problem from the seller's perspective in the make-to-order manufacturing industry in order to solve the multi-attribute automated negotiation problem. To this end, more than 'two negotiation attributes are defined and a preferred value of each negotiation alternative is calculated based on the entropy value of each attribute. And then, the best option is selected according to the utility function of each negotiator, a penalty of negotiation delay, and conviction of possibility of negotiation success. The suggested automated negotiation methods in this study can be employed for the development of advanced automated negotiation systems.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1999년도 춘계학술대회 논문집
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• pp.184-188
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• 1999

The performance of an AGV varies with the applied AGV dispatching rule in the operation of AGVS. This study proposes a multi-attribute AGV dispatching rule. The suggested dispatching rule considers the output queue of a workstation, distance between an idle AGV and a workstation to be served, the input queue of the destination and the remaining job process of a part. This study suggests two types of and the remaining job process of a part. This study suggests two types of multi-attribute dispatching rules. One is an one-stage rule which selects the part to be served considering four attributes simultaneously. The other is a two-stage rule by which a workstation is selected and a part is chosen from the selected workstation. The simulation runs were executed under different experimental conditions to obtain preliminary statistics on the several performance measures.

• 한국조리학회지
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• 제6권1호
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• pp.79-102
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• 2000

This study aims at providing restaurant marketers and decision-makers both the brand differentiation information and the useful clues to achieve the high market share through the various brand differentiation opportunities in multi-chain family restaurants. Sample surveys were conducted to 245 persons who had frequent using multi-chain family restaurants in Seoul. Method of survey used are telephone interviewing. The result of analysis was shown the marketer's performances on differentiation marketing, but that there were a lot of opportunities of differentiating the brand from others. Therefore, restaurant marketers and decision-makers should try to differentiate their brand along the lines of physical attributes, service, food quality, personnel, location, or image, in order to win the guest and then get the succession of their business.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권12호
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• pp.3836-3854
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• 2022

The student group division is benefit for universities to do the student management based on the group profile. With the widespread use of student smart cards on campus, especially where students living in campus residence halls, students' daily activities on campus are recorded with information such as smart card swiping time and location. Therefore, it is feasible to depict the students with the daily activity data and accordingly group students based on objective measuring from their campus behavior with some regular student attributions collected in the management system. However, it is challenge in feature representation due to diverse forms of the student data. To effectively and comprehensively represent students' behaviors for further student group division, we proposed to adopt activity data from student smart cards and student attributes as input data with taking account of activity and attribution relationship types from different perspective. Specially, we propose a novel student group division method based on a multi-view student attribute heterogeneous information network (MSA-HIN). The network nodes in our proposed MSA-HIN represent students with their multi-dimensional attribute information. Meanwhile, the edges are constructed to characterize student different relationships, such as co-major, co-occurrence, and co-borrowing books. Based on the MSA-HIN, embedded representations of students are learned and a deep graph cluster algorithm is applied to divide students into groups. Comparative experiments have been done on a real-life campus dataset collected from a university. The experimental results demonstrate that our method can effectively reveal the variability of student attributes and relationships and accordingly achieves the best clustering results for group division.

• 한국의류산업학회지
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• 제25권1호
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• pp.11-23
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• 2023

With the proliferation of the "Untact" culture (non-face-to-face society), advanced technologies have accelerated the cashierless systems in the retail context. Cashierless fashion stores are expected to grow rapidly in the same way automated convenience stores grew in popularity. Applying the extended technology acceptance theory, this study aims to investigate how the attributes of cashierless fashion store influence consumers' acceptance of it and to examine how consumer's technology readiness moderates the model. Two online surveys-preliminary and secondary-were conducted to collect data from consumers in their 20s and 30s who had experienced cashierless stores over the past year. To analyze a total of 423 responses, this study conducted a confirmatory factor analysis, a multi-group factor analysis, a multi-group structure equation modeling, and a descriptive analysis. The results demonstrate that convenience, trustworthiness, and price had a positive impact on perceived ease of use, while service quality had a negative one. Enjoyment, convenience, trustworthiness, and price positively influenced perceived usefulness. Both perceived ease of use and usefulness increased the intention to use. Furthermore, the multi-group comparison confirmed that the positive dimensions of consumer's technology readiness played a moderating role in the model. This study provides a research foundation for consumer acceptance of technologically advanced stores and offers practical implications to companies planning cashierless fashion stores.

• Asia pacific journal of information systems
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• 제18권3호
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• pp.1-20
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• 2008

Based on the multi-attribute utility theory (MAUT), we present a survey method to measure consumer preferences. The multi-attribute utility theory has been used to make decisions in OR/MS field; however, we show that the method can be effectively used to estimate the demand for new services by measuring individual level utility function. Because conjoint method has been widely used to measure consumer preferences for new products and services, we compare the pros and cons of two consumer preference survey methods. Further, we illustrate how swing weighing method can be effectively used to elicit customer preferences especially for new telecommunications services, Multi-attribute utility theory is a compositional approach for modeling customer preference, in which researchers calculate overall service utility by summing up the evaluation results for each attribute. On the contrary, conjoint method is a decompositional approach, which requires holistic evaluations for profiles. Partworth for each attribute is derived or estimated based on the evaluation, and finally consumer preferences for each profile are calculated. However, if the profiles are quite new and unfamiliar to the survey respondents, they will find it very difficult to accurately evaluate the profiles. We believe that the multi-attribute utility theory-based survey method is more appropriate than the conjoint method, because respondents only need to assess attribute level preferences and not holistic assessment. We chose swing weighting method among many weight assessment methods in multi-attribute utility theory, because it is designed to perform in a simple and fast manner. As illustrated in Clemen and Reilly (2001), to assess swing weights, the first step is to create the worst possible outcome as a benchmark by setting the worst level on each of the attributes. Then, each of the succeeding rows "swings" one of the attributes from worst to best. Upon constructing the swing table, respondents rank order the outcomes (rows). The next step is to rate the outcomes in which the rating for the benchmark is set to be 0 and the rating for the best outcome to be 100, and the ratings for other outcomes are determined in the ranges between 0 and 100. In calculating weight for each attribute, ratings are normalized by the total sum of all ratings. To demonstrate the applicability of the approach, we elicited and analyzed individual-level customer preference for new telecommunication services-WiBro and HSDPA. We began with a randomly selected 800 interviewees, and reduced them to 432 because other remaining ones were related to the people who did not show strong intention for subscription to new telecommunications services. For each combination of content and handset, number of responses which favored WiBro and HSDPA were counted, respectively. It was assumed that interviewee favors a specific service when expected utility is greater than that of competing service(s). Then, the market share of each service was calculated by normalizing the total number of responses which preferred each service. Holistic evaluation of new and unfamiliar service is a tough challenge for survey respondents. We have developed a simple and easy method to assess individual level preference by estimating weight of each attribute. Swing method was applied for this purpose. We believe that estimating individual level preference will be quite flexibly used to predict market performance of new services in many different business environments.

• Asia pacific journal of information systems
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• 제20권1호
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• pp.57-79
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• 2010

In a virtual community, one can possess multiple identities and pretend to be different by creating self-identity in contrast with his or her actual self. Does false identity undermine the qualitative growth of a virtual community by reducing members' accountability? Or does it stimulate their contributive behaviors by ensuring freedom of speech? It is imperative to understand the effects of multi-identity considering the distinct properties of a virtual community in which people easily change their identities at little or no cost. To answer these questions, we adopted the concept of self-discrepancy from the social psychology theory rooted in the concept of the self and developed a theoretical model to predict quality of contribution of the individual member in virtual communities. Based on the self-discrepancy theory, we first identified two different domains of the self: (1) an "actual self" that consists of attributes that the person believes he or she currently possesses in real life and (2) a "cyber self" that consists of attributes the person believes he or she possesses in a virtual community. Next, we derived an index for two different types of self-discrepancy by using the differences between the actual and the cyber identities: Personal Self-discrepancy and Social Self-discrepancy. Personal Self-discrepancy reflects the degree of discrepancy between actual and cyber identity regarding a person's intelligence, education, and expertise. Social Self-discrepancy reflects the degree of discrepancy between actual and cyber identity regarding a person's morality, sociability, and accordance with social norms. Finally, we linked them with sense of virtual community, perceived privacy rights, and quality of contribution to examine how having a multi-identity influences an individual's psychological state and contributive behaviors in a virtual community. The results of the analysis based on 266 respondents showed that Social Self-discrepancy negatively influenced both the Sense of Virtual Community and Perceived Privacy Rights, while Personal Self-discrepancy negatively influenced only Perceived Privacy Rights, thereby resulting in reduced quality of contribution in virtual communities. Based on the results of this analysis, we can explain the dysfunctions of multi-identity in virtual communities. First, people who pretend to be different by engaging in socially undesirable behaviors under their alternative identities are more likely to suffer lower levels of psychological wellbeing and thus experience lower levels of sense of virtual community than others. Second, people do not perceive a high level of privacy rights reflecting catharsis, recovery, or autonomy, even though they create different selves and engage in socially undesirable behaviors in a virtual community. Third, people who pretend to be different persons in terms of their intelligence, education, or expertise also indirectly debase the quality of contribution by decreasing perceived privacy rights. The results suggest that virtual community managers should pay more attention to the negative influences exercised by multi-identity on the quality of contribution, thereby controlling the need to create alternative identities in virtual communities. We hope that more research will be conducted on this underexplored area of multi-identity and that our theoretical framework will serve as a useful conceptual tool for all endeavors.