• Korean Management Science Review
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• v.21 no.2
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• pp.191-213
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• 2004

This study addresses the evaluation criteria of multimedia authoring tools(MATs), the way which decision-maker can exclude outlier matrix from group using the concept of the compatibility index, and how AHP can be applied to the selection of MATs in a group decision-making environment. The AHP technique allows an evaluator to quantify the relative importance of elements at each hierarchy and to calculate the composite relative weights for each product(i.e. MATs). This decision process allows setting to priority of the MATs based on the AHP. The results indicated that technical ability of MATs was the most significant factor in affecting their decision, trailed by managerial efficiency and vendor support. To the experts, multimedia data support was the less important than development interface. Also, the results indicated that product A(0.510) was their first choice, trailed by product C(0.286) and B(0.204). Assessing the composite relative weights revealed that expert group's members were consistent with the rankings of decision variables(evaluation criteria variables) statistically in selecting their MATs. Therefore, we believed that expert group's members have achieved sufficient agreement to permit the use of geometric mean to average the group's preference without obscuring the differences of individual opinions.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.496-500
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• 2015

International construction projects are inherently more risky than domestic projects with multi-dimensional uncertainties that require complementary risk management at both the country and project levels. However, despite a growing need for systematic country evaluations, most studies have focused on project-level decisions and lack country-based approaches for firms in the construction industry. Accordingly, this study suggests data-driven approaches for evaluating countries using two quantitative models. The first is a two-stage country segmentation model that not only screens negative countries based on country attractiveness (macro-segmentation) but also identifies promising countries based on the level of past project performance in a given country (micro-segmentation). The second is a multi-criteria country segmentation model that combines a firm's business objective with the country evaluation process based on Kraljic's matrix and fuzzy preference relations (FPR). These models utilize not only secondary data from internationally reputable institutions but also performance data on Korean firms from 1990 to 2014 to evaluate 29 countries. The proposed approaches enable firms to enhance their decision-making capacity for evaluating and selecting countries at the early stage of corporate strategy development.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3030-3049
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• 2023

With the development and wide application of hybrid network computing modes like cloud computing, edge computing and fog computing, the customer service requests and the collaborative optimization of various computing resources face huge challenges. Considering the characteristics of network environment resources, the optimized deployment of service resources is a feasible solution. So, in this paper, the optimal goals for deploying service resources are customer experience and service cost. The focus is on the system impact of deploying services on load, fault tolerance, service cost, and quality of service (QoS). Therefore, the alternate node filtering algorithm (ANF) and the adjustment factor of cost matrix are proposed in this paper to enhance the system service performance without changing the minimum total service cost, and corresponding theoretical proof has been provided. In addition, for improving the fault tolerance of system, the alternate node preference factor and algorithm (ANP) are presented, which can effectively reduce the probability of data copy loss, based on which an improved cost-efficient replica deployment strategy named ICERD is given. Finally, by simulating the random occurrence of cloud node failures in the experiments and comparing the ICERD strategy with representative strategies, it has been validated that the ICERD strategy proposed in this paper not only effectively reduces customer access latency, meets customers' QoS requests, and improves system service quality, but also maintains the load balancing of the entire system, reduces service cost, enhances system fault tolerance, which further confirm the effectiveness and reliability of the ICERD strategy.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.1-10
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• 2013

Personalization aims to provide customized contents to each user by using the user's personal preferences. In this sense, the core parts of personalization are regarded as recommendation technologies, which can recommend the proper contents or products to each user according to his/her preference. Prior studies have proposed novel recommendation technologies because they recognized the importance of recommender systems. Among several recommendation technologies, collaborative filtering (CF) has been actively studied and applied in real-world applications. The CF, however, often suffers sparsity or scalability problems. Prior research also recognized the importance of these two problems and therefore proposed many solutions. Many prior studies, however, suffered from problems, such as requiring additional time and cost for solving the limitations by utilizing additional information from other sources besides the existing user-item matrix. This study proposes a novel implicit rating approach for collaborative filtering in order to mitigate the sparsity problem as well as to enhance the performance of recommender systems. In this study, we propose the methods of reducing the sparsity problem through supplementing the user-item matrix based on the implicit rating approach, which measures the trust level among users via the existing user-item matrix. This study provides the preliminary experimental results for testing the usefulness of the proposed model.

• Phonetics and Speech Sciences
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• v.13 no.2
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• pp.27-35
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• 2021

This study investigated the status of the wh-island constraint in Seoul Korean. The syntactic movement of a wh-phrase out of an embedded sentence so as to have wide scope at LF is known to be invalid as it violates the wh-island constraint, but there have been studies in which such a movement was possible when the sentence is read with a wh-intonation. We conducted perceptual tests in which subjects were asked to select an answer after listening to each of the four types of interrogative sentences. Three of them were with 'Nugu-leul', which is an accusative form of the wh-phrase 'who' as well as an indefinite form. The fourth sentence contained the name of a person. 'Nugu-leul' and the noun were positioned in the same embedded sentence to see whether the subjects accepted a matrix scope interpretation of the wh-phrases. Response time was transformed to normalized log response time and checked to find any differences in the time taken to select the answers depending on different types of interrogative sentences. The results showed the subjects had a definite preference for the matrix scope interpretation for the sentences with a wh-intonation. The response time required to select the matrix scope interpretation was longer than for any other type of interrogative sentence. We concluded that the wh-island constraint in Seoul Korean is weak.

• Journal of Practical Agriculture & Fisheries Research
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• v.20 no.2
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• pp.5-11
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• 2018

There is a need to breed and distribute domestic varieties for Lilium Asiatic hybrids because most of the lily bulbs cultivated in Korea imported from foreign country. The genetic resources of Lilium Asiatic hybrids, 'Buff Pixie', 'Orange Matrix' and 'Tiny Puppet', which were collected from 2001, had been self-pollinated from 2004 to 2012. In 2012, Lilium Asiatic 'Lovely LiASong' as an F₁ hybrid was bred through crossing 'L₂-12-1' and 'L₂-35-4' obtained by 4th self-fertilization. 'Lovely LiASong' had a bowl shaped single flower with a few spots and medium-sized flower, 8.7cm in flower diameter. The number of flowers per plant was 4.9, which was relatively more flowers than other cultivars. And the flower inflorescence had umbellate and racemose while the attitude of longitudinal axis was erect. The plant height was 33.4cm with 30.4 leaves per plant and 7.2cm in leaf length. The 'Lovely LiASong' showed a high consumer preference because it had a relatively longer flowering period, larger flower diameter and number of flowers than those of the control, 'Tiny Ghost'.

• Journal of Life Science
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• v.33 no.8
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• pp.605-611
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• 2023

Recently, sporadic cases of human infection by genetic reassortants of H7Nx influenza A viruses have been reported; such viruses have also been continuously isolated from avian species. In this study, A/wild bird/South Korea/sw-anu/2023, a novel reassortant of the H7N1 avian influenza virus, was analyzed using full-genome sequencing and molecular characterization. Phylogenetic analysis showed that A/wild bird/South Korea/sw-anu/2023 belonged to the Eurasian lineage of H7Nx viruses. The polymerase basic (PB)2, PB1, polymerase acidic (PA), and nucleoprotein (NP) genes of these viruses were found to be closely related to those of avian influenza viruses isolated from wild birds, while the hemagglutinin (HA), neuraminidase (NA), matrix (M), and nonstructural (NS) genes were similar to those of avian influenza viruses isolated from domestic ducks. In addition, A/wild bird/South Korea/sw-anu/2023 also had a high binding preference for avian-specific glycans in the solid-phase direct binding assay. These results suggest the presence of a new generation of H7N1 avian influenza viruses in wild birds and highlight the reassortment of avian influenza viruses found along the East Asian-Australasian flyway. Overall, H7Nx viruses circulate worldwide, and mutated H7N1 avian viruses may infect humans, which emphasizes the requirement for continued surveillance of the H7N1 avian influenza virus in wild birds and poultry.

• Journal of Digital Convergence
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• v.10 no.5
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• pp.67-78
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• 2012

Recently, the interesting of customers in online auto insurance is rapidly increasing. The one of major reasons is economical benefit. offline auto insurance products as a service formed high price. However, online auto insurance relatively formed low price. Thanks to these characteristics of online auto insurance has gained great popularity. Therefore, in purchasing online auto insurance, consumers carefully buy products of auto insurance. In this study, we classified the $2{\times}2$ matrix (online preference group, economic pursuit group, convenience oriented group, and carefulness approach group) in online auto insurance consumers focusing on the perceived benefits and price acceptance. From an economic point of view of consumers around the perceived benefits and price acceptance, we analyzed the relationships among easy of use, usefulness, attitude, and purchase intention in automobile e-shopping mall. The results of this study will provide the useful implications for the planing CRM(customer relationship management) strategy for improving purchase intention of customers to online insurance companies.

• Journal of Digital Contents Society
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• v.18 no.4
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• pp.707-712
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• 2017

As the amount of data increases exponentially, the recommender system is attracting interest in various industries such as movies, books, and music, and is being studied. The recommendation system aims to propose an appropriate item to the user based on the user's past preference and click stream. Typical examples include Netflix's movie recommendation system and Amazon's book recommendation system. Previous studies can be categorized into three types: collaborative filtering, content-based recommendation, and hybrid recommendation. However, existing recommendation systems have disadvantages such as sparsity, cold start, and scalability problems. To improve these shortcomings and to develop a more accurate recommendation system, we have designed a recommendation system as a factorization machine using actual online product purchase data.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.64-75
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• 2018

With the development of location-aware technologies and the activation of smart phones, location based social networks(LBSN) have been activated to allow people to easily share their location. In particular, studies on recommending the location of user interests by using the user check-in function in LBSN have been actively conducted. In this paper, we propose a location recommendation scheme considering time and user activities in LBSN. The proposed scheme considers user preference changes over time, local experts, and user interest in rare places. In other words, it uses the check-in history over time and distinguishes the user activity area to identify local experts. It also considers a rare place to give a weight to the user preferred place. It is shown through various performance evaluations that the proposed scheme outperforms the existing schemes.