• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.43-48
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• 2022

Recently, due to the rapid performance improvement of smartphones and the increase in background executions of mobile apps, multitasking has become common on mobile platforms. Unlike traditional desktop and server apps, response time is important in most mobile apps as they are interactive tasks, and some apps are classified as real-time tasks with deadlines. In this paper, we discuss how to meet the requirements of heterogeneous multitasking in managing memory of real-time and interactive tasks when they are executed together on a smartphone. To do so, we analyze the memory requirement of real-time tasks, and propose a model that has the ability of allocating memory to multitasking tasks on a smartphone. Trace-driven simulations with real-world storage access traces captured by heterogeneous apps show that the proposed model provides reasonable performance for interactive tasks while guaranteeing the requirement of real-time tasks.

• Journal of Digital Convergence
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• v.10 no.5
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• pp.339-349
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• 2012

Smartphones which represent to the Mobile convergence, is the rapid spread, more than half of Korean are using. Accordingly, mobile apps that run on smartphone market is growing at a rapid pace. However, most studies on smartphone and mobile apps are focusing on the technology acceptance and improvement of function. So, this study is to suggest promotion strategy to each mobile apps, analyzed through three phases. First phase is the frequency analysis that deduct most frequently used mobile apps. Second phase is association rules that found to associate between mobile apps. Finally, to analyze deduction techniques for acquired 5 mobile apps to target variable in pre-2 phase use total 35 variables of 20 mobile apps categories, demographic variables, amount of PC, movie, music, book, game usage and fees per month.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.6
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• pp.835-844
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• 2018

Recently, as the number of smartphone users has been increasing worldwide, various services such as electronic payment, internet use, and financial settlement are being used as a smartphone. In addition, researches for home appliance control and automobile control using smartphone are conducted. As such, smartphone users can enjoy a more convenient life, but by hacking smartphones, tapping texts and conversations on smartphones, tracking location through spy apps, DDoS attacks using smartphones, and malicious apps When a message is received at a specific telephone number when using a micropayment, the corresponding text message is transmitted to a remote server, thereby increasing the risk of leakage of personal information and the like. Therefore, in this paper, we define the risk factors of the smartphone that are caused by the internal and external environmental, physical, contents (apps) of the smartphone through the smartphone that we use in real life, We propose a method to check vulnerability of smartphone security solution such as CC evaluation and the most effective response technique for each risk of smartphone by defining the technique.

• International journal of advanced smart convergence
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• v.6 no.1
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• pp.44-49
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• 2017

In the modern technology era, it is possible to connect objects and the internet anytime and anywhere through IoT of hyper-connected society. Accordingly, a smart shopping cart was designed and realized by applying IoT. Therefore, this paper builds the IoT shopping cart system according to the trend of IoT environment.. When RFID is installed in the Arduino and the tagged item is inserted into the IoT shopping cart, the product information and price are displayed on the Arduino linked Raspberry Pi. We built a web server on the Raspberry Pi to handle this data, and built an App on the smartphone to implement the IoT shopping cart environment. Consumers can receive pricing and product information through smartphone apps through raspberry pie, can make quick calculations through smartphone, and provide various information to consumers through apps.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.101-108
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• 2015

This study paid attention to the notable increase of the use of diet/exercise apps on smartphones. Based on channel expansion theory and technology acceptance model (TAM), this study investigated how three predictors-Internet information use efficacy, Internet information credibility, smartphone use efficacy-affected one's attitude toward and intention to use diet/exercise apps. Results from a path analysis indicated that Internet information use efficacy and smartphone use efficacy positively predict the perceived ease of use of diet/exercise apps. Internet information credibility positively predicts the perceived usefulness of such apps. Moreover, there were gender differences in the effects of both Internet information use efficacy and Internet information credibility on the perceived usefulness of diet/exercise apps.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1049-1055
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• 2013

Smartphones are rapidly growing because of easy installation of the apps (application software) that users actually want. There are increasingly many apps that require cryptographic suites to be installed, for instance, for protecting account and financial data. Android platform provides protection mechanisms for memory and storage based on Linux kernel, but they are vulnerable to rooting attacks. In this paper, we analyze security mechanisms of Android platform and point out security problems. We show the security vulnerabilities of several commercial apps and suggest appropriate countermeasures.

• International Journal of Contents
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• v.10 no.3
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• pp.1-8
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• 2014

In this paper, we collect and analyze the status of mobile phone applications (hereafter apps) in the healthcare and fitness category of the Apple iTunes App Store and Google Play Store. We determine the number of apps and analyze statistical aspects such as classifications, age rating, fees, and user evaluation of the popular items. As of September 30, 2013, there were 236 popular apps available from iTunes. Google Play offered 720 apps. We discover that apps for healthcare and fitness are diverse. Apps for physical exercise have the greatest popularity. The proportions of apps that are suitable for all ages among the Google and iTunes popular apps are 55.8% and 89.4%, respectively. The user evaluation of apps in iTunes is relatively less positive. We determine that the proportion of paid apps to free apps in Google is higher than that of the apps in iTunes. We perform hypothesis tests and find statistically significant differences in age rating and perceived satisfaction between the apps of the Apple iTunes App Store and Google Play Store. However, we find no meaningful differences in the classification and price of the apps between the two app stores. We perform hypothesis tests to verify the differences in age rating and perceived satisfaction between the paid and free apps within and across the Google Play Store and iTunes App Store. There are statistically significant differences in the age rating between the paid and free apps in the Google play store, between the Google free and iTunes free apps, between the Google paid and iTunes paid apps, between the Google free and iTunes paid apps, and between the Google paid and iTunes free apps. There are statistically significant differences in the perceived satisfaction between the Google free and iTunes free apps, between the Google paid and iTunes paid apps, between the Google free and iTunes paid apps, and between the Google paid and iTunes free apps.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.41-54
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• 2020

In this paper, it will study various problems such as personal information infringement from when using various useful Apps in the Smartphone environment. It also researched the vulnerabilities Mobile Apps and the risks of personal information leakage when using Smartphone information to decrease threat and find solution. In the second chapter, it will check the existing Mobile App related Apps. In the third chapter, it will check the threats and major factors that caused by the leakage of personal information which related to the app. Then it will suggest solution and end with conclusion. This paper also looked at various problems that caused by illegal adverse effect from illegal personal information collection. Then it researched and made suggestion to make consideration on safety of personal information and privacy infringement that threat to personal information For safety of mobile banking, it proposed a safety method to separate and manage the code which has the core logic which required to run the App. For safety of direction App, when running the direction App, even if the information is collected, location information for unauthorized accessed will encrypt and store in DB, so that access to personal information is difficult. For delivery App environment, by using the national deliver order call center's representative phone to receive a telephone order then, the customer information is delivered to the branch office when it receive order and it will automatically delete information from the server when the delivery is completed by improving DB server of order. For the smart work app environment, the security solution operates automatically by separating and make independent private and work areas. Then it will suggest initialization for company's confidential business information and personal information to safe from danger even if loss.

• Fashion & Textile Research Journal
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• v.18 no.6
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• pp.825-832
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• 2016

The purposes of this study was to investigate effects of fashion brand apps on smartphones flow and consumer satisfaction in mobile shopping. These findings provide new information to marketers for the marketing strategy for dealing with mobile shopping mall. A total of 233 usable questionnaires were obtained from men and women ages 20-30 who have mobile shopping purchasing experience. Data were analyzed by frequency analysis, factor analysis using SPSS for Window 22.0 and confirmatory factor analysis and structural equation model analysis by AMOS 22.0. The results were as follows. First, the analysis of fashion brand apps factors showed that it consist of 2 kinds of dimensions of basic information type and additional information type. Second, basic information type of fashion brand apps have had a direct impact on consumer satisfaction and did not affect the smartphones flow. Additional information type influence consumer satisfaction through a smartphones flow. Basic information type of fashion brand apps showed a greater impact on consumer satisfaction than a smartphone flow. A managerial implication was discussed for fashion brand marketers to develop strategies on fashion brand apps that could stimulate and increase the consumer flow and satisfaction.

• Knowledge Management Research
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• v.20 no.3
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• pp.139-154
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• 2019

With the increasing use of smartphone apps, many apps are coming out in various fields. In order to analyze the current status and trends of apps in a specific field, it is necessary to establish a classification scheme. Various schemes considering users' behavior and characteristics of apps have been proposed, but there is a problem in that many apps are released and a fixed classification scheme must be updated according to the passage of time. Although it is necessary to consider many aspects in establishing classification scheme, it is possible to grasp the trend of the app through the proposal of a classification scheme according to the characteristic of the app. This research proposes a method of establishing an app classification scheme through the description of the app written by the app developers. For this purpose, we collected explanations about apps in the tourism field and identified major categories through topic modeling. Using only the apps corresponding to the topic, we construct a network of words contained in the explanatory text and identify subcategories based on the networks of words. Six topics were selected, and Clauset Newman Moore algorithm was applied to each topic to identify subcategories. Four or five subcategories were identified for each topic.