• Asia pacific journal of information systems
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• v.18 no.3
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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.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.360-376
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• 2020

Many heuristic attribute reduction algorithms have been proposed to find a single reduct that functions as the entire set of original attributes without loss of classification capability; however, the proposed reducts are not always perfect for these multiclass datasets. In this study, based on a probabilistic rough set model, we propose the class-oriented attribute reduction (COAR) algorithm, which separately finds a reduct for each target class. Thus, there is a strong dependence between a reduct and its target class. Consequently, we propose a type of ensemble constructed on a group of classifiers based on class-oriented reducts with a customized weighted majority voting strategy. We evaluated the performance of our proposed algorithm based on five real multiclass datasets. Experimental results confirm the superiority of the proposed method in terms of four general evaluation metrics.

• Proceedings of the Safety Management and Science Conference
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• 2008.11a
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• pp.505-515
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• 2008

This paper introduces six single and sequential acceptance sampling plans based on OC( Operating Characteristic) curve. Revised KS standards for acceptance sampling by attribute and by variable such as KSA 3102 : 1996, 3103 : 2005, KSA ISO 14560 : 2006, 8422 : 2001, 8423 : 2001 are presented.

• Proceedings of the Safety Management and Science Conference
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• 2008.11a
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• pp.517-526
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• 2008

This paper introduces fourteen single, double, multiple and sequential acceptance sampling plans based on switching rule. Revised KS standards for acceptance sampling by attribute and by variable such as KSA ISO 2859-0, 1:2001 2859-2:2001, 8422:2001, 3951:2006, 8423:2001, MIL-STD-105E:1989, 414:1968 and ANSI/ASQ Z1.4, Z1.9:2003 are presented.

• Proceedings of the Safety Management and Science Conference
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• 2008.11a
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• pp.161-165
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• 2008

This paper introduces three continuous sampling plans by attribute. Revised KS standards for acceptance samplings such as KSA ISO 2859-3, 4 : 2001 and 21247 : 2007 are presented. These plans are based on skip-lot, DQL(Declared Quality Level) and VL (Verification Level).

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.533-538
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• 2001

In this paper, we extend FARGs single mode attribute to multiple attributes for real image application and present a new CBIR using FMARG(Fuzzy Multiple Attribute Relational Graph), which can handle queries involving multiple attributes, not only object label, but also color, texture and spatial relation. In the experiment using the synthetic image database of 1,024 images and the natural image database of 1.026 images built from NETRA database and Corel Draw, the proposed approach shows 6~30% recall increase in the synthetic image database and a good performance, at the displacements and the retrieved number of similar images in the natural image database, compared with the single attribute approach.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.5100-5119
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• 2018

Most of existing privacy-preserving multi-authorities attribute-based encryption schemes (PP-MA-ABE) only considers the privacy of the user identity (ID). However, in many occasions information leakage is caused by the disclosing of his/her some sensitive attributes. In this paper, we propose a collusion-resisting ciphertext-policy PP-MA-ABE (CRPP-MACP-ABE) scheme with hiding both user's ID and attributes in the cloud storage system. We present a method to depict anonymous users and introduce a managerial role denoted by IDM for the management of user's anonymous identity certificate ($AID_{Cred}$). The scheme uses $AID_{Cred}$ to realize privacy-preserving of the user, namely, by verifying which attribute authorities (AAs) obtain the blinded public attribute keys, pseudonyms involved in the $AID_{Cred}$ and then distributes corresponding private keys for the user. We use different pseudonyms of the user to resist the collusion attack launched by viciousAAs. In addition, we utilize IDM to cooperate with multiple authorities in producing consistent private key for the user to avoid the collusion attack launched by vicious users. The proposed CRPP-MACP-ABE scheme is proved secure. Some computation and communication costs in our scheme are finished in preparation phase (i.e. user registration). Compared with the existing schemes, our scheme is more efficient.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.4028-4049
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• 2014

Attribute-based encryption (ABE) is a promising cryptographic primitive for implementing fine-grained data sharing in cloud computing. However, before ABE can be widely deployed in practical cloud storage systems, a challenging issue with regard to attributes and user revocation has to be addressed. To our knowledge, most of the existing ABE schemes fail to support flexible and direct revocation owing to the burdensome update of attribute secret keys and all the ciphertexts. Aiming at tackling the challenge above, we formalize the notion of ciphertext-policy ABE supporting flexible and direct revocation (FDR-CP-ABE), and present a concrete construction. The proposed scheme supports direct attribute and user revocation. To achieve this goal, we introduce an auxiliary function to determine the ciphertexts involved in revocation events, and then only update these involved ciphertexts by adopting the technique of broadcast encryption. Furthermore, our construction is proven secure in the standard model. Theoretical analysis and experimental results indicate that FDR-CP-ABE outperforms the previous revocation-related methods.

• Environmental and Resource Economics Review
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• v.10 no.3
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• pp.345-366
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• 2001

Evaluating environmental impacts of regional development projects has critical importance in environmental management aspect. This paper uses multi-attribute utility theory as a basis for obtaining a value index to assess the environmental impacts and applies the theory to a specific Korean case study. To structure and quantify basic values for the assessment, we elicited important attributes, then refined and structured them into a hierarchy. An environmental multi-attribute index is constructed as a multi-attribute utility function, based on value judgments provided by a group of technical experts, policy makers, and a decision-maker at Korean Ministry of Environment. The implications of the results are also discussed. We found that the work and results can provide valuable insights for assessment of environmental consequences.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2001.05a
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• pp.389-408
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• 2001

Evaluating the results of National Nuclear R&D projects has critical importance in nuclear management aspect. This paper uses multi-attribute utility theory as a basis for obtaining a value Index to assess the results of nuclear R&D projects and applies the theory to a specific Korean case study. To structure and quantify basic values for the . evaluation, we elicited important attributes, then refined and structured them into a hierarchy. A multi-attribute index is constructed as a multi-attribute utility function, based on value judgments provided by a group of technical experts, policy makers, and decision-makers. The implications of the results are also discussed. We found that the work and results can provide valuable insights for assessment of nuclear R&D consequences.