• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.3
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• pp.465-479
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• 2016

Some groups do ethical activities (such as ethical slogan t-shirt campaigns) only to complete the requirements for ethical duty; consequently, some people question the effectiveness of those products. The attributes of ethical slogan t-shirts should be considered seriously to reduce skepticism when planning a campaign. Researchers can also suggest a new purpose for ethical t-shirts using an ethical message. In study 1, we conduct a conjoint analysis that suggests realistic multi-attribute choice decisions. The suggested multi-attributes wear design aesthetic (high/low), price (high/low), where we donate (close/far), and the size of firm (big/small). In addition, participations were divided into two groups according to eco-friendly attitudes to confirm differences in choices between two groups. Study 1 showed that price is the most important attribute, but design aesthetic also remains important. In addition, a group that has a high eco-friendly attitude thought "where we donate" was more important than other groups. In study 2, a pre-post approach investigated wearers' attitude changes. We also divided participants into two groups and one group wear high level design aesthetic t-shirts (and vice-versa) to measure the attitude change difference. As a result of study 2, the wearers partially changed their eco-friendly attitudes. The group that wore high design aesthetic t-shirts showed a greater difference than other groups. Through this study, we conclude that customers seriously considered the design aesthetic. Finally, wearing ethical slogan t-shirts can change the attitudes of wearers.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.235-242
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• 2015

Social network technology has been increasing interest in the big data service and development. However, the data stored in the distributed server and not on the central server technology is easy enough to find and extract. In this paper, we propose a big data management techniques to minimize the processing time of information you want from the content server and the management server that provides big data services. The proposed method is to link the in-group data, classified data and groups according to the type, feature, characteristic of big data and the attribute information applied to a hash chain. Further, the data generated to extract the stored data in the distributed server to record time for improving the data index information processing speed of the data classification of the multi-attribute information imparted to the data. As experimental result, The average seek time of the data through the number of cluster groups was increased an average of 14.6% and the data processing time through the number of keywords was reduced an average of 13%.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.981-997
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• 2020

Blockchain technology can provide a high level security based on a decentralized distributed ledger and consensus-based structure. In order to increase the utilization of blockchain technology, it is necessary to find a way to use it in fields that require personal data processing such as health care and e-commerce. To achieve this goal, the blockchain based system should be able to comply with data privacy regulations represented by European Union(EU)'s GDPR(General Data Protection Regulation). However, because of the properties of the blockchain like the immutability and decentralized recorded data, it is difficult to technically implement the requirements of the existing privacy regulations on the blockchain. In this paper, we propose a multi-chain based access control system that can guarantee the rights of the personal data subject required by GDPR by utilizing Chameleon Hash and Attribute Based Encryption (ABE). Finally, we will show through security analysis that our system can handle personal data while maintaining confidentiality and integrity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2550-2572
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• 2023

Epidemiological survey is an important means for the prevention and control of infectious diseases. Due to the particularity of the epidemic survey, 1) epidemiological survey in epidemic prevention and control has a wide range of people involved, a large number of data collected, strong requirements for information disclosure and high timeliness of data processing; 2) the epidemiological survey data need to be disclosed at different institutions and the use of data has different permission requirements. As a result, it easily causes personal privacy disclosure. Therefore, traditional access control technologies are unsuitable for the privacy protection of epidemiological survey data. In view of these situations, we propose a black box-assisted fine-grained hierarchical access control scheme for epidemiological survey data. Firstly, a black box-assisted multi-attribute authority management mechanism without a trusted center is established to avoid authority deception. Meanwhile, the establishment of a master key-free system not only reduces the storage load but also prevents the risk of master key disclosure. Secondly, a sensitivity classification method is proposed according to the confidentiality degree of the institution to which the data belong and the importance of the data properties to set fine-grained access permission. Thirdly, a hierarchical authorization algorithm combined with data sensitivity and hierarchical attribute-based encryption (ABE) technology is proposed to achieve hierarchical access control of epidemiological survey data. Efficiency analysis and experiments show that the scheme meets the security requirements of privacy protection and key management in epidemiological survey.

• Proceedings of the Technology Innovation Conference
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• 1999.06a
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• pp.245-265
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• 1999

MAUT and AHP are widely used for quantification of subjective judgements in various fields of decision making. This study focuses on the introduction and application of MAUT/AHP method which is a hybrid of MAUT and AHP techniques in R&D project priority setting. This hybrid model can clarify each factors' contribution using MAUT method and can reduce the number of pairwise comparisons of AHP method. This study applies AMUT/AHP method to the evaluation of R&D projects in a Government - funded research institute. To evaluate R&D projects, six evaluation factors are derived. SMART(Simple MultiAttribute Rating Technique) and DVM(Difference Value Measurement ) out of many MAUT methods are used to design the utility function ad AHP is used to allocate the weights among evaluation factors. The major findings of this study can be summarized as follows. First, the SMART/AHP and the DVM/AHP have the same results with the SMART and the DVM, and they are different results with AHP. It is very hard to decide which one is better. Second, MAUT/AHP's strength is analyzed. MAUT reflects utility values of evaluators to alternatives and AHP results objective and consistent weights of factors through pariwise comparisons. Third, its possible application fields are proposed. It is applicable to subjective decision making problems with high complexity and inter-independent factors.

• Korean Journal of Organic Agriculture
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• v.17 no.4
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• pp.413-439
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• 2009

This study conducts a survey and test to understand U.S. public's perception about multifunctionality. The questionnaire suggests seven alternative way of providing questions about intangible benefits provided by agriculture in the U.S. The final questionnaire was administered as an e-mail survey in June 2008 to a nationally representative household panel maintained in the U.S. by the Ipsos Observer. Data analysis shows that 64 percent of respondents considered the multifunctionality of agriculiture as an important issue and 45 percent of respondents were in favor of increasing government expenditure to support farmland preservation. Using Fishbein's multi-attribute model as a theoretical background, this paper develops an empirical model to assess and attributes of multifunctionality. For the analysis, bivariate orderd probit model was set up to reflect respondent's attitude. Regression analyses show that two questions (how much you agree with agriculture's intangible benefit and increasing government expenditure to support agriculture) are shaped by different sets of facts.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.855-861
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• 2005

Every public agency governing infrastructure has to plan effectively for rehabilitation of existing facilities within the constraints of the capital program. Numerous technical, social, political, financial, and management constraints govern the decision to rehabilitate a facility. However, without a systematic procedure for selecting facilities for rehabilitation, within the prevailing constraints, it is possible that the funds available for rehabilitation might be suboptimized. Therefore, a decision support system that assists the user in selecting facilities for rehabilitation while considering the technical, social, financial, and political and management constraints will be useful in the decision-making process. This paper compares the Analytical Hierarchy Process (AHP) with the Swing Weight method used to prioritize functional criteria for suburban station rehabilitation. This paper also contains a brief discussion about the relevance of the Multi Attribute utility theory in developing a decision model for the problem at hand. The results of this paper provides the user with a decision support system that would prioritize the stations in order of their weights obtained by a systematic evaluation of various criteria and sub-criteria involved in the decision making process

• Journal of Intelligence and Information Systems
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• v.11 no.1
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• pp.107-121
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• 2005

Recently, many researches on recommendation systems and collaborative filtering have been proceeding in both research and practice. However, although product items may have multi-valued attributes, previous studies did not reflect the multi-valued attributes. To overcome this limitation, this paper proposes new methodology for recommendation system. The proposed methodology uses multi-valued attributes based on clustering technique for items and applies the collaborative filtering to provide accurate recommendations. In the proposed methodology, both user clustering-based CBR and item attribute clustering-based CBR technique have been applied to the collaborative filtering to consider correlation of item to item as well as correlation of user to user. By using multi-valued attribute-based clustering technique for items, characteristics of items are identified clearly. Extensive experiments have been performed with MovieLens data to validate the proposed methodology. The results of the experiment show that the proposed methodology outperforms the benchmarked methodologies: Case Based Reasoning Collaborative Filtering (CBR_CF) and User Clustering Case Based Reasoning Collaborative Filtering (UC_CBR_CF).

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.3
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• pp.91-101
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• 2010

As global warming has caused the number of abnormal changes in climate to increase throughout the world, much damage has occurred recently in Korean Peninsula which results from unexpected heavy rains, landslides, and floods from typhoons. To prevent and cope with these annually repeated natural hazards, the overall improvements are needed, including systematic management of the existing natural hazard information and improvement of hazard information. In this study, multi-purpose hazard information map based on digital image was constructed as an effective way to enhance hazard management considering regional characteristics and hazard response capabilities in the field. Multi-purpose hazard information map with a new concept by fusion of geospatial information and hazard attribute information is able to support quick decision for hazard management making and development of hazard information system.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.151-154
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• 2008

Dramatic price increases of fossil fuels and the economic development of emerging nations accelerates the transformation of forest lands into monocultures, e.g. for biofuel production. On this account, cost efficient methods to enable the monitoring of land resources has become a vital ambition. The application of remote sensing techniques has become an integral part of forest attribute estimation and mapping. The aim of this study was to evaluate the potentials of the kNN method by combining terrestrial with remotely sensed data for the development of a pixel-based monitoring system for the small scaled mosaic of different land use types of the off-reserve forests of the Goaso forest district in Ghana, West Africa. For this reason, occurrence and distribution of land use types like cocoa and non-timber forest resources, such as bamboo and raphia palms, were estimated, applying the kNN method to ASTER satellite data. Averaged overall accuracies, ranging from 79% for plantain, to 83% for oil palms, were found for single-attribute classifications, whereas a multi-attribute approach showed overall accuracies of up to 70%. Values of k between 3 and 6 seem appropriate for mapping bamboo. Optimisation of spectral bands improves results considerably.