• Communications of Mathematical Education
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• v.30 no.1
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• pp.85-99
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• 2016

The research was carried out to be part of a mathematics app stimulation that enables the elderly to learn mathematics by using Smart devices. Particularly appropriate method / function that leads to learning is very important for people who are not accustomed to Smart devices like the elderly. The research was conducted to build affordance strategy based on the consideration of characteristics of senior learners. It aims to achieve both the goals of education through mathematics learning materials provided by smart devices and also to improve user convenience. It suggests cognitive, physical and sensory features and factors to improve affordance of Smart learning system.

• Journal of Korea Multimedia Society
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• v.23 no.11
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• pp.1428-1434
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• 2020

Virtual reality (VR) and augmented reality (AR) technologies can interact intuitively using virtual 3D images. Information signs on buildings that are frequently used by the public play a very important role in conveying information. However, the current information sign has different understanding and interpretation, and it is difficult to communicate quickly and intuitively for interaction. The purpose of this study is to increase the efficiency of information signing through information provision using mobile augmented reality. The InfoAR app not only guides you to the destination of the building, but also acts as a marker for the logo image. The logo image created based on the feature points recognizes the information of the destination. It is converted to AR through a mobile app, allowing users to easily find their destination by obtaining specific information. In addition, it presents interactions that can enlarge, reduce, move, and rotate information about virtual objects augmented through a function called AR. In the future, if user convenience and usability of the interface are added, research is conducted, and the level of completion is improved, such as using VR contents and promotions and business cards, it is expected that highly useful contents will be produced.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.8
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• pp.3999-4005
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• 2013

We forecast that the scale of mobile market will be large scale according to the twenty million times of smart phone's user is arrived. The type of software development is being transferred into mobile-based App. or cloud computing-based service from web-based software. Currently both Google's android and Apple's IOS are known for two prominent platforms. Existing modeling techniques cannot be applied into the case of mobile application which is executed those platforms. Therefore, we suggest a modeling technique that is customized existing modeling techniques into android-based software development. That is, we propose an analysis and design techniques which are needed into android-based mobile smart environment.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1445-1452
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• 2016

Recently Mobile Software Applications are developed in various languages and stored in App Store. App Users selectively use appropriate apps for the owned hardware. In other words, it depends on the kinds of operating systems of the apps whether to use or not to use the applications in various languages. The apps should be differently implemented according to the kind of the user's device, though they provide the same functions. To solve these problems, it is necessary to define an independent function specification method which is not dependent to a specific system environment. In this paper, the Mobile Application Developing Framework is suggested, which incorporates all of the development process. Standardized models are proposed which can be used in the analysis and design steps. In implementation phase, a technique for cross framework design is suggested so as to implement a platform dependent mobile app.

• Journal of IKEEE
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• v.23 no.2
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• pp.448-453
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• 2019

Under the conflicting objectives of maximum user satisfaction and fast launching, there exist great needs for automated mobile app testing. In automated app testing, detection of usage-state changes is one of the most important issues for minimizing human intervention and testing of various usage scenarios. Because conventional approaches utilizing pre-collected training examples can not handle the rapid evolution of apps, we propose a novel method detecting changes in usage-state through graph-entropy. In the proposed method, widgets in a screen shot are recognized through DNNs and 'onverted graphs. We compared the performance of the proposed method with a SIFT (Scale-Invariant Feature Transform) based method on 20 real-world apps. In most cases, our method achieved superior results, but we found some situations where further improvements are required.

• 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.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.141-149
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• 2023

Repacked mobile apps constitute about 78% of all malware of Android, and it greatly affects the technical ecosystem of Android. Although many methods exist for repacked app detection, most of them suffer from performance issues. In this manuscript, a novel method using the Constant Key Point Selection and Limited Binary Pattern (CKPS: LBP) Feature extraction-based Hashing is proposed for the identification of repacked android applications through the visual similarity, which is a notable feature of repacked applications. The results from the experiment prove that the proposed method can effectively detect the apps that are similar visually even that are even under the double fold content manipulations. From the experimental analysis, it proved that the proposed CKPS: LBP method has a better efficiency of detecting 1354 similar applications from a repository of 95124 applications and also the computational time was 0.91 seconds within which a user could get the decision of whether the app repacked. The overall efficiency of the proposed algorithm is 41% greater than the average of other methods, and the time complexity is found to have been reduced by 31%. The collision probability of the Hashes was 41% better than the average value of the other state of the art methods.

• Smart Media Journal
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• v.13 no.6
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• pp.35-43
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• 2024

During the post-pandemic period, the interest in foreign language learning surged, leading to increased usage of language-learning apps. With the rising demand for these apps, analyzing app reviews becomes essential, as they provide valuable insights into user experiences and suggestions for improvement. This research focuses on extracting insights into users' opinions, sentiments, and overall satisfaction from reviews of HelloTalk, one of the most renowned language-learning apps. We employed topic modeling and emotion analysis approaches to analyze reviews collected from the Google Play Store. Several experiments were conducted to evaluate the performance of sentiment classification models with different settings. In addition, we identified dominant emotions and topics within the app reviews using feature importance analysis. The experimental results show that the Random Forest model with topics and emotions outperforms other approaches in accuracy, recall, and F1 score. The findings reveal that topics emphasizing language learning and community interactions, as well as the use of language learning tools and the learning experience, are prominent. Moreover, the emotions of 'admiration' and 'annoyance' emerge as significant factors across all models. This research highlights that incorporating emotion scores into the model and utilizing a broader range of emotion labels enhances model performance.

• Journal of Korea Port Economic Association
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• v.29 no.3
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• pp.73-94
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• 2013

The necessity of shipping market information services has been on the rise which emphasizes the relevance of transaction information and market information to parties both in and outside the shipping industry. However, previous related researches have been restricted to explorations limited by the offerings of existing shipping market information providers. Users today require effective information, an efficient contents management system, interfacing to help the information provider, graphing and spread sheets to facilitate and present the analyzed information through diverse formats, and reliable web and mobile services to provide information effectively with limited human resources. As a first step, service information has to be defined, so that it takes into account user utility, information retrieval and data development. Second, benchmark information and services must be provided from leading shipbrokers and research institutes. Third, a review of the latest technical trends is required to identify the most suitable technologies for servicing shipping market information. Finally, analysis is required on the implementation of a system with selected technologies, as well as the development of channels to post information which have been analyzed by users. Such a process would enable the continual redefinition of the shipping market information users actively need. The application of an X-Internet based WCMS, with a single-window dashboard providing user-customized information, and used to obtain and manage processes, add spread sheets to sustain calculations using the latest information, graph results, and to input additional information following predefined rules. Access to data and use of the system would require agreement that the system will incorporate user data and user-analyzed information into the market report, web portal, and hybrid app to provide current shipping market information appropriately and accurately to service users.

• The Journal of Society for e-Business Studies
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• v.21 no.3
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• pp.51-78
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• 2016

Online-to-offline (O2O) commerce is the new trend that merges online commerce with traditional industries in various fields. The primary purpose of this paper is to find out which factors influence customers' intention to switch from call-based driver-for-hire services to O2O app-based services. This study used variables and factors based on Theory of Switching Intention, and Extended Unified Theory of Acceptance and Use of Technology in order to design research questions. We surveyed 500 users of call-based driver-for-hire services. According to the result of this study, dissatisfaction with the current call-based driver-for-hire services is estimated to be a significant factor that strengthens customers' intention to switch from the call-based driver-for-hire services to the app-based services. Loyalty to the previous call-based driver-for-hire services was not seen as a crucial motivator that causes customers to switch to the new O2O driver service. Switching cost also did not play a key role in explaining the relationship between dissatisfaction with the current call-based service and the intention to use the new app-based service. Performance expectancy, easiness in use, the level of user's knowledge or available assistance in relation to the use of app-based services, and expectancy for reasonable price was found to have meaningful impacts on customers' intention to switch from the call-based driver-for-hire services to the app-based services. Age, gender and user experience on the new service were found incapable of moderating the relationship between aforementioned factors which influence customers' choice of the app-based driver-for-hire service, and customers' intent to switch to the app-based service.