• Asia pacific journal of information systems
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• v.25 no.3
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• pp.548-562
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• 2015

The growing popularity of mobile application has led to researchers and practitioners needing to understand users' mobile application download behaviors. Using large-scale transaction data obtained from a leading Korean telecommunications company, we empirically explore how application download rank, which appears to users when they decide to download a new application, affects their extended mobile application download. This terminology refers to downloading an additional application in the same category as those that they have already downloaded. We also consider IT characteristics, user characteristics, and application type that might be associated with the extended application download. The analysis generates the following result. Overall, a higher rank of a new application encourages the extended application download, but the linear relationship between the rank and the extended application download disappears when critical rank points are incorporated into the model. Further, no quadratic effect of rank is found in the extended application download. Based on the results, we suggest theoretical and managerial implications.

• The Pure and Applied Mathematics
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• v.10 no.2
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• pp.103-118
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• 2003

We estimate the stable rank of twisted crossed products of $C^{*}-algebras$ by topological Abelian groups. As an application we estimate the stable rank of twisted crossed products of $C^{*}-algebras$ by solvable Lie groups. In particular, we obtain the stable rank estimate of twisted group $C^{*}-algebras$ of solvable Lie groups by the (reduced) dimension and (generalized) rank of groups.

• Journal of the Korean Statistical Society
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• v.26 no.3
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• pp.319-332
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• 1997

The application of multivariate linear rank statistics to data with item nonresponse is considered. Only a modest extension of the complete data techniques is required when the missing data may be thought of as a random sample, and an appropriate modification of the covariances is derived. A proof of the asymptotic multivariate normality is given. A review of some related results in the literature is presented and applications including longitudinal and repeated measures designs are discussed.

• The korean journal of orthodontics
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• v.38 no.3
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• pp.159-174
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• 2008

Objective: The purpose of this study was to investigate whether cortical punching could stimulate the expression of OPG, RANK, and RANKL during tooth movement by immunohistochemistry. Methods: 34 sprague-dawley rats (15 weeks old) were allocated into 3 groups: TMC group (experimental group; Tooth Movement with Corticotomy, n = 16), TM group (control group; Tooth Movement only group, n = 16), and non-treatment group (n = 2). 20 gm of orthodontic force was applied to rat incisors by inserting elastic bands. The duration of force application was 1, 4, 7 and 14 days. A microscrew (diameter 1.2 mm) was used for cortical punching of the palatal side of the upper incisors in the TMC group. Results: Distributions of OPG, RANK, and RANKL were evaluated by immunohistochemistry. OPG, RANK and RANKL were observed on experimental and control groups. On the compression side, the degree of the expression of OPG decreased in both groups. The expression of RANK was most prominent in the experimental group of day 4. The expression of RANKL was most intensive and extensive in the experimental group of day 7. However, the expression of OPG was decreased in the experimental and control groups compared to the non treatment group. The expression of OPG, RANK and RANKL after force application were decreased at day 14. Conclusions: These findings suggested that cortical punching might stimulate remodeling of alveolar bone during a 2 week period of tooth movement without any pathologic change.

• Genomics & Informatics
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• v.5 no.3
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• pp.95-101
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• 2007

In this paper, we consider the variable selection methods in the Cox model when a large number of gene expression levels are involved with survival time. Deciding which genes are associated with survival time has been a challenging problem because of the large number of genes and relatively small sample size (n<

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4604-4623
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• 2014

Authentication mechanisms coupled with strong encryption techniques are used for network security purposes; however, given sufficient time, well-equipped intruders are successful for compromising system security. The authentication protocols often fail when they are analysed critically. Formal approaches have emerged to analyse protocol failures. In this study, Communicating Sequential Processes (CSP) which is an abstract language designed especially for the description of communication patterns is employed. Rank functions are also used for verification and analysis which are helpful to establish that some critical information is not available to the intruder. In order to establish this, by assigning a value or rank to each critical information, it is shown that all the critical information that can be generated within the network have a particular characterizing property. This paper presents an application of rank functions approach to an authentication protocol that combines delaying the decryption process with timed authentication while keys are dynamically renewed under pseudo-secure situations. The analysis and verification of authentication properties and results are presented and discussed.

• Journal of applied mathematics & informatics
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• v.8 no.2
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• pp.627-634
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• 2001

Under contamination, Bahadur representations with a strong remainder term are derived for random central order statistics with a prescribed limiting rank, and asymptotic normalities for these statistics of truncated and contaminated data are proved, with a suitable limiting rank. From these results, an application to the fixed-width confidence interval problem is available.

• Journal of Korean society of Dental Hygiene
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• v.19 no.5
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• pp.859-871
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• 2019

Objectives: The present study aimed to evaluate the usability, quality, and usefulness of the mobile application, CAMBRA-kids, for caries management in preschoolers. Methods: Ninety-one caregivers and preschoolers participated in the user evaluation of CAMBRA-kids. The evaluators assessed the usability, quality, and usefulness of CAMBRA-kids. The collected data were analyzed using R studio 1.2.1335 for Windows (RStudio Inc. 2018, Boston, MA, USA). The evaluations for usability, quality, and usefulness were analyzed with descriptive statistics, Kruskal-Wallis rank sum test, and Wilcoxon rank sum test. Results: On user evaluation, the quality and usefulness of the application scored >3 points, and majority of the users rated the quality and usefulness of the application as high. The quality of the application's system was the highest at 3.68 points, and the actual usage of the application was the lowest at 3.10 points. The application had the highest technological aspect score of 3.20, whereas the content related to oral health information had the lowest score of 3.10/5. Although the application showed no statistically significant differences in the quality and usefulness according to general characteristics, there was a statistically significant difference (p<0.05) between the two when compared between the caries risk group. For all items, the protector of the high-risk group evaluated the quality and usefulness of the application highly. The moderate risk group gave the lowest evaluation score for the application's quality and usefulness. The usability score of the application, according to the user version of the mobile application rating scale (uMARS), was 3.25, and the average engagement score was 2.82 (56.31%). The highest subscale score was 3.63. Conclusions: In this study, we found suitable quality, usability, and usefulness of the mobile application, CAMBRA-kids. In future, the use of this application will contribute to the prevention of dental caries among preschoolers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3723-3737
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• 2022

Google Play is one of the largest Android phone app markets and it contains both free and paid apps. It provides a variety of categories for every target user who has different needs and purposes. The customer's rate every product based on their experience of apps and based on the average rating the position of an app in these arch varies. Fraudulent behaviors emerge in those apps which incorporate search rank maltreatment and malware proliferation. To distinguish the fraudulent behavior, a novel framework is structured that finds and uses follows left behind by fraudsters, to identify both malware and applications exposed to the search rank fraud method. This strategy correlates survey exercises and remarkably joins identified review relations with semantic and behavioral signals produced from Google Play application information, to distinguish dubious applications. The proposed model accomplishes 90% precision in grouping gathered informational indexes of malware, fakes, and authentic apps. It finds many fraudulent applications that right now avoid Google Bouncers recognition technology. It also helped the discovery of fake reviews using the reviewer relationship amount of reviews which are forced as positive reviews for each reviewed Google play the android app.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.834-837
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• 2009

There is a growing need for ad-hoc analysis of extremely large data sets, especially at e-Commerce companies which depend on recommender application. Nowadays, as the number of e-Commerce web pages grow to a tremendous proportion; vertical recommender services can help customers to find what they need. Recommender application is one of the reasons for e-Commerce success in today's world. Compared with general e-Commerce recommender application, obviously, general e-Commerce recommender application's processing scope is greatly narrowed down. MapReduce is emerging as an important programming model for large-scale data-parallel applications such as web indexing, data mining, and scientific simulation. The objective of this paper is to explore MapReduce framework for the e-Commerce recommender application on major general and dedicated link analysis for e-Commerce recommender application, and thus the responding time has been decreased and the recommender application's accuracy has been improved.