• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.190-194
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• 2023

By looking the importance of communication, data delivery and access in various sectors including governmental, business and individual for any kind of data, it becomes mandatory to identify faults and flaws during cyber communication. To protect personal, governmental and business data from being misused from numerous advanced attacks, there is the need of cyber security. The information security provides massive protection to both the host machine as well as network. The learning methods are used for analyzing as well as preventing various attacks. Machine learning is one of the branch of Artificial Intelligence that plays a potential learning techniques to detect the cyber-attacks. In the proposed methodology, the Decision Tree (DT) which is also a kind of supervised learning model, is combined with the different cross-validation method to determine the accuracy and the execution time to identify the cyber-attacks from a very recent dataset of different network attack activities of network traffic in the UNSW-NB15 dataset. It is a hybrid method in which different types of attributes including Gini Index and Entropy of DT model has been implemented separately to identify the most accurate procedure to detect intrusion with respect to the execution time. The different DT methodologies including DT using Gini Index, DT using train-split method and DT using information entropy along with their respective subdivision such as using K-Fold validation, using Stratified K-Fold validation are implemented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1564-1570
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• 2013

In this paper, we propose a robust pupil detection method using rank order filter and cross-correlation. Potential pupil candidates are detected using rank order filter. Eye region is binarized using variable threshold to find eyebrow, and pupil candidates at the eyebrow are removed. The positions of pupil candidates are corrected, the pupil candidates are grouped into pairs based on geometric constraints. A similarity measure is obtained for two eye of each pair using cross-correlation, we select a pair with the largest similarity measure as a final pupil. The experiments have been performed for 500 images of the BioID face database. The results show that it achieves the high detection rate of 96.8% and improves about 11.6% than existing method.

• Journal of Contemporary Eastern Asia
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• v.13 no.1
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• pp.19-37
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• 2014

In an attempt to develop comprehensive evidence-based methods for evaluation of the R&D performance of cross-disciplinary projects, a joint bibliometric analysis of patents and publications was performed for two industry-university-government collaborative projects aimed at commercialization: Hokkaido University Research & Business Park Project (2003-2007; 63 inventors; 176 patents; 853 papers), and Matching Program for Innovations in Future Drug Discovery and Medical Care - phase I (2006-2010; 46 inventors; 235 patents; 733 papers). Besides the simple output indicators (for five years period), and citations (from the publication date to the end of 2012), science maps based on the network analysis of words and co-authorship relations were generated to identify the prominent research themes and teams. Our joint analysis of publications and patents yields objective and mutually complementing information, which provides better insights on research and commercialization performance of the large-scale projects. Hence, such analysis has potential for use in the industry-university project's performance evaluation.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.115-125
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• 2021

Simulation-based hull form optimization is a typical HEB (high-dimensional, expensive computationally, black-box) problem. Conventional optimization algorithms easily fall into the "curse of dimensionality" when dealing with HEB problems. A recently proposed Cross-Entropy (CE) optimization algorithm is an advanced stochastic optimization algorithm based on a probability model, which has the potential to deal with high-dimensional optimization problems. Currently, the CE algorithm is still in the theoretical research stage and rarely applied to actual engineering optimization. One reason is that the Monte Carlo (MC) method is used to estimate the high-dimensional integrals in parameter update, leading to a large sample size. This paper proposes an improved CE algorithm based on quasi-Monte Carlo (QMC) estimation using high-dimensional truncated Sobol subsequence, referred to as the QMC-CE algorithm. The optimization performance of the proposed algorithm is better than that of the original CE algorithm. With a set of identical control parameters, the tests on six standard test functions and a hull form optimization problem show that the proposed algorithm not only has faster convergence but can also apply to complex simulation optimization problems.

• Journal of Periodontal and Implant Science
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• v.45 no.1
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• pp.2-7
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• 2015

A fundamental problem in analyzing complex multilevel-structured periodontal data is the violation of independency among the observations, which is an assumption in traditional statistical models (e.g., analysis of variance and ordinary least squares regression). In many cases, aggregation (i.e., mean or sum scores) has been employed to overcome this problem. However, the aggregation approach still exhibits certain limitations, such as a loss of power and detailed information, no cross-level relationship analysis, and the potential for creating an ecological fallacy. In order to handle multilevel-structured data appropriately, mixed effects models have been introduced and employed in dental research using periodontal data. The use of mixed effects models might account for the potential bias due to the violation of the independency assumption as well as provide accurate estimates.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.904-907
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• 2019

Nuclear energy remains one of the world's major energy sources, making up over 10% of global electricity generation in 2017. Public acceptance of nuclear energy is essential for its adoption. From a practical perspective, it is beneficial to have a simple indicator that can predict the actual adoption of nuclear energy. Based on practical experience, the authors suggest tolerance and self-sufficiency as potential indicators that may predict the adoption of nuclear energy. By evaluating the cross-sectional data of 18 countries in 2013, this research assesses the actual impact of tolerance and self-sufficiency on public acceptance in order to identify the validity of the two variables. The results indicate that the two variables are statistically significant, while public acceptance is insignificant in explaining national adoption of nuclear energy. This may be because tolerance reflects national willingness to accept potential risk, while self-sufficiency explains a government's likelihood of developing non-carbon energy sources.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.292-298
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• 2022

Femtocell networks can be a potential method for increasing the capacity of LTE networks, especially in indoor areas. However, unplanned deployment of femtocells results in co-tier interference and cross-tier interference problems. The interference reduces the advantages of implementing femtocell networks to a certain extent. The notion of Fractional Frequency Reuse (FFR) is proposed in order to reduce the impact of interference on the system's performance. In this paper, a dynamic approach for efficiently partitioning the spectrum is suggested. The goal is to enhance the capacity of femtocells, which will improve the performance of the system. The suggested strategy allocates less resources to the macrocell portion of the network, which has a greater number of femtocells deployed to maximize the utilization of available resources for femtocell users. The spectrum division would be dynamic. The proposed strategy is evaluated through a simulation using MATLAB tool. In conclusion, the results showed that the proposed scheme has the potential to boost the system's capacity.

• Fourth Industrial Review
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• v.2 no.1
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• pp.33-43
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• 2022

Purpose - With the rapid development of information technology, the digital economy has become an important grip of the new development pattern, and the digital transformation of enterprises is a major trend. As SMEs are the mainstay of the economy and employment, it is important to study the digital transformation of SMEs to promote the development of the digital economy. Research design, data, and methodology - Based on a resource-based view, this report analyses the current situation and issues of digital transformation of SMEs from the perspective of digital orientation as well as the breadth and depth of technological capabilities of enterprises, using data from a survey of 200 manufacturing enterprises in China. Result - The results show that SMEs generally have a digital transformation mindset, but a weak digital foundation. In order to execute a digital strategy, companies need digital transformation capabilities. These behavioral capabilities are guided by the strategic direction of the business, and companies with strong capabilities are always trying to tap into the full digital potential. Conclusion - In order to effectively promote the digital transformation of SMEs, we suggest that SMEs pay attention to digital capability building, make good use of digital platforms and network resources, and lay a solid foundation for digital transformation; meanwhile, we suggest that government departments play a guiding and supporting role to build a cross-industry and cross-sector digital synergy system to help promote the development of SMEs' digital transformation. This paper presents some suggestions from both the internal and external environment of the enterprise, with the expectation of contributing to the digital transformation practices of SMEs.

• ETRI Journal
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• v.24 no.2
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• pp.97-108
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• 2002

Optical Border Gateway Protocol (OBGP) is an extension to BGP for Optical Cross Connects (OXCs) to automatically setup multiple direct optical lightpaths between many different autonomous domains. With OBGP, the routing component of a network may be distributed to the edge of the network while the packet classification and forwarding is done in the core. However, it is necessary to analyze the stable convergence functions of OBGP in case of lightpath failures. In this paper, we first describe the architecture of the OBGP model and analyze the potential problems of OBGP, e.g., virtual BGP router convergence behavior in the presence of lightpath failure. We then propose an OBGP convergence model derived from an inter-AS (Autonomous System) relationship. The evaluation results show that the proposed model can be used for a stable OBGP routing policy and OBGP routing convergence under lightpath failures of the optical Internet.

• Management & Information Systems Review
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• v.34 no.1
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• pp.191-209
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• 2015

Electronic word-of-mouth (eWOM) in social media has been recognized as one of the most influential marketing tools across various businesses. Understanding eWOM in social media is critical to reach potential global consumers easily and quickly in the hospitality industry. However, few empirical studies in hospitality attempted to evaluate the effectiveness of eWOM in social media from a global perspective. Given the competitive climate of the hospitality market, it is meaningful for hospitality marketers to evaluate the effectiveness of eWOM in social media and the influence of cultural factors to promote customers and increase profitability globally. The main purpose of this study was to examine the influence of cultural values on social media eWOM in the hospitality industry in China, Korea, and the USA. The result of this study indicates Chinese and American people engage more than Korean people when they try to purchase hospitality product and service This study particularly provided a cross-cultural study of comparison among these countries and the findings of this study are expected to provide important practical assistance for global marketing strategies in social media.