• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.63-68
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• 2022

Given the competition between different tourist destinations to attract domestic and international tourists it is absolutely vital to examine their website efficacy on specific attributes. This study employs one of the recently developed multi-criteria decision-making method the Best-Worst Method to assess the state government official tourism website across four Indian states known for their tourism potential- Himachal Pradesh, Uttrakhand, Uttar Pradesh and Rajasthan on specific attributes provided by the widely acknowledged WebQual instrument. Information Fit-to-Task and Trust emerged as the most important criterion. Relative advantage and Innovation the least important. The results of the study are easily interpretable and visual. They offer both an individual and comparative analysis of the perceived website efficacy on specific attributes to facilitate tourism stakeholders and website administrators to strategize and make their digital presence effective and competitive.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.145-164
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• 2014

Network virtualization provides a promising tool to allow multiple heterogeneous virtual networks to run on a shared substrate network simultaneously. A long-standing challenge in network virtualization is the Virtual Network Embedding (VNE) problem: how to embed virtual networks onto specific physical nodes and links in the substrate network effectively. Recent research presents several heuristic algorithms that only consider single topological attribute of networks, which may lead to decreased utilization of resources. In this paper, we introduce six complementary characteristics that reflect different topological attributes, and propose three topology-aware VNE algorithms by leveraging the respective advantages of different characteristics. In addition, a new KS-core decomposition algorithm based on two characteristics is devised to better disentangle the hierarchical topological structure of virtual networks. Due to the overall consideration of topological attributes of substrate and virtual networks by using multiple characteristics, our study better coordinates node and link embedding. Extensive simulations demonstrate that our proposed algorithms improve the long-term average revenue, acceptance ratio, and revenue/cost ratio compared to previous algorithms.

• Journal of Information Technology Applications and Management
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• v.14 no.3
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• pp.137-149
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• 2007

Most of hospitals, especially small-scale hospitals, have tried to get customers through the Internet as what companies have done recently. There are various attempts that increase visits to one's web-site in plastic surgery hospitals. However, in plastic surgery, there have been few studies on which an attribute contributes to increase the number of web-site visit. In order to derive the important attributes on the number of visit, we compared functional attributes of 30 high-visit plastic surgery web-sites with those of 30 low-visit web-sites using statistical and data mining methods. For analysis, three methods have conducted including Multiple Discriminant Analysis (statistical method), Decision Trees (data mining method), and Artificial Neural Network (data mining method). Furthermore, results of each method have been evaluated one another. The result of this study shows that a few attributes like 'Simulating cyber plastic surgery program', 'recommendation of information' explain the number of the visitors between high and low visit web-site. The methodology employed in this study provides an efficient way of improving satisfaction of visitors of plastic surgery website.

• Journal of Information Technology Services
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• v.15 no.4
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• pp.153-174
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• 2016

On account of multiple causes, including prolonged global economic crisis, addressing environmental pollution and the advent of hyper-connected society, a new paradigm called 'sharing economy' has rapidly emerged. Many startups have attempted to build promising business model based on the sharing economy concept. Nevertheless, successful cases are still very rare in the global level, except for Uber and Airbnb cases. Therefore, this study analyzes necessary causes and sufficient causes for successful settlements in the market through a comparative case analysis on digital matching firms in the sharing economy businesses. For the case study, we compare five successful cases (Uber, Airbnb, Kickstarter, TaskRabbit and DogVacay), three failure cases (Homejoy, Ridejoy and Tuterspree) and a platform cooperativism case (Juno) in accordance with six value attributes of business model including value proposition, market segment, value chain, cost structure and profit potential, value network and competitive strategy. We apply Boolean method to support controlled comparison and eliminate unnecessary attributes. The Boolean analysis result shows that value proposition, cost structure and profit potential, value network and competitive strategy are the essential attributes. Furthermore, the result indicates that each attribute is a necessary condition, where all four conditions should be met simultaneously in order to be successful. With this result, we discuss essential consideration for those who are planning startup based on the sharing economy business model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3685-3707
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• 2021

In recent years, facial attribute editing has been successfully used to effectively change face images of various attributes based on generative adversarial networks and encoder-decoder models. However, existing models have a limitation in that they may change an unintended part in the process of changing an attribute or may generate an unnatural result. In this paper, we propose a model that improves the learning of the attention mask by adding a spatial attention mechanism based on the unified selective transfer network (referred to as STGAN) using semi-supervised learning. The proposed model can edit multiple attributes while preserving details independent of the attributes being edited. This study makes two main contributions to the literature. First, we propose an encoder-decoder model structure that learns and edits multiple facial attributes and suppresses distortion using an attention mask. Second, we define guide masks and propose a method and an objective function that use the guide masks for multiple facial attribute editing through semi-supervised learning. Through qualitative and quantitative evaluations of the experimental results, the proposed method was proven to yield improved results that preserve the image details by suppressing unintended changes than existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1071-1090
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• 2016

Most of scheduling methods in the Grid only consider one special attribute of the resource or one aspect of QoS (Quality of Service) of the job. In this paper, we focus on the problem that how to consider two aspects simultaneously. Based on the requirements of the jobs and the attributes of the resources, jobs are categorized into three kinds: CPU-overload, memory-overload, and bandwidth-overload jobs. One job may belong to different kinds according to different attributes. We schedule the jobs in different categories in different orders, and then propose a scheduling method-MTS (multiple attributes scheduling method) to schedule Grid resources. Based on the comparisons between our method, Min-min, ASJS (Adaptive Scoring Job Scheduling), and MRS (Multi-dimensional Scheduling) show: (1) MTS reduces the execution time more than 15% to other methods, (2) MTS improves the number of the finished jobs before the deadlines of the jobs, and (3) MTS enhances the file size of transmitted files (input files and output files) and improves the number of the instructions of the finished jobs.

• Journal of Korea Technology Innovation Society
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• v.7 no.1
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• pp.89-110
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• 2004

Home networks consist of two or more home appliances or communication devices enabling the mutual data communication between appliances such as personal computers, refrigerators, phones, television sets, personal digital assistants(PDA), etc. There are three factors that create demand for the home network services. The first factor is development of technology. Second, on the demand side, consumer demand for the home appliances having access to the Internet is in the increase. Finally, producers need a strategy to deal with the problem of market saturation. Home networks are emerging markets. They are unique in that they unite information technologies with home appliances that provide new services. in this paper we study the main attributes of home network services and analyze consumers' preferences for them. However, it is not quite possible to use the revealed preference approach since the home network market is still at an incipient stage. We therefore use the conjoint analysis method using stated preference data. conjoint analysis has been widely use in the area of marketing for evaluating consumer preferences for new products and services. it presents a hypothetical product to the respondents along with the product's attributes and their levels. The respondents are asked to either rank each alternative or choose between several hypothetical products. By estimating consumers' willingness to pay for the attributes of the home network services and analyzing consumers' preferences, we predict the pattern of the development of the home network services and related technologies along various quality dimensions. Based on the estimation results, we draw policy implications for the national- and company-level strategy.

• International Journal of Highway Engineering
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• v.15 no.3
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• pp.93-101
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• 2013

PURPOSES : This study is to investigate the relationship of socioeconomic characteristics and road network structure with traffic growth patterns. The findings is to be used to tweak traffic forecast provided by traditional four step process using relevant socioeconomic and road network data. METHODS: Comprehensive statistical analysis is used to identify key explanatory variables using historical observations on traffic forecast, actual traffic counts and surrounding environments. Based on statistical results, a multiple regression model is developed to predict the effects of socioeconomic and road network attributes on traffic growth patterns. The validation of the proposed model is also performed using a different set of historical data. RESULTS : The statistical analysis results indicate that several socioeconomic characteristics and road network structure cleary affect the tendency of over- and under-estimation of road traffics. Among them, land use is a key factor which is revealed by a factor that traffic forecast for urban road tends to be under-estimated while rural road traffic prediction is generally over-estimated. The model application suggests that tweaking the traffic forecast using the proposed model can reduce the discrepancies between the predicted and actual traffic counts from 30.4% to 21.9%. CONCLUSIONS : Prediction of road traffic growth patterns based on surrounding socioeconomic and road network attributes can help develop the optimal strategy of road construction plan by enhancing reliability of traffic forecast as well as tendency of traffic growth.

• Journal of the Korea Society for Simulation
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• v.9 no.3
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• pp.77-89
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• 2000

This paper suggests a multi-attribute dispatching rule for an automated guided vehicle(AGV). The attributes to be considered are the number of queues in outgoing buffers of workstations, distance between an idle AGV and a workstation with a job waiting for the service of vehicle, and the number of queues in input buffers of the destination workstation of a job. The suggested rule is based on the simple additive weighting method using a normalized score for each attribute. A neural network approach is applied to obtain an appropriate weight vector of attributes based on the current status of the manufacturing system. Backpropagation algorithm is used to train the neural network model. The proposed dispatching rules and some single attribute rules are compared and analyzed by simulation technique. A number of simulation runs are executed under different experimental conditions to compare the several performance measures of the suggested rules and some existing single attribute dispatching rules each other.

• Convergence Security Journal
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• v.11 no.3
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• pp.55-66
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• 2011

This research focus on the value of smart phones for university students in Korea, considering on the correlations between the main causes influencing intrinsic value(price attributes, function attributes), network value(learning effects attributes, externalities attributes) user satisfaction, and intentions of repurchase of the smart phones market in Korea. Through the statistical analyses on the 8 hypotheses from a research model, we found that intrinsic value and network value gave an attentive influence on user satisfaction and repurchase intention. Call charge and Liquid crystal display and Design of smart phone have an influenced user satisfaction and repurchase intention.