• 한국IT서비스학회지
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• 제14권2호
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• pp.253-273
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• 2015

Cloud computing is provided on demand service via the internet, allowing users to pay for the service they actually use. Categorized as one kind of cloud computing, SaaS is computing resource and software sharing model with can be accessed via the internet. Based on virtualization technology, SaaS is expected to improve the efficiency and quality of the IT service level and performance in company. Therefore this research limited cloud services to SaaS especially focused on collaborative application service, and attempts to identify the factors which impact the performance of collaboration and intention to use. This study adopts technological factors of cloud SaaS services and factors of task characteristics to explore the determinants of collaborative performance and intention to use. An experimental study using student subjects with Google Apps provided empirical validation for our proposed model. Based on 337 data collected from respondents, the major findings are following. First, the characteristics of cloud computing services such as collaboration support, service reliability, and ease of use have positive effects on perceived usefulness of collaborative application while accessability, service reliability, and ease to use have positive effects on intention to use. Second, task interdependence has a positive effects on collaborative performance while task ambiguity factor has not. Third, perceived usefulness of collaborative application have positive effects on intention to use.

• 한국컴퓨터정보학회논문지
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• 제22권2호
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• pp.89-95
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• 2017

There are a variety of apps that are finding their way. And in car navigation, we launched a product that reflects Augmented Reality technology this year. However, existing apps have problems. It is implemented in 2D or 3D, has a large error range because it has been modified in most vehicles, is not updated in real time, and car augmented reality navigation is a vehicle, and a separate device is required, etc. In this study, we implemented a smartphone app for walking directions using augmented reality, and made it possible to intuitively use a route service from a user 's location to a destination. The Dijkstra algorithm is applied to calculate the shortest path to solve the problem of finding the route with the least cost. By using this application, it is possible to use the route search service even in a data-free environment, to solve the inconvenience of the language barrier, and to update in real time, so that the latest information can be always maintained. In the future, we want to develop an app that can be commercialized by using a character in the path to promote it.

• 정보보호학회논문지
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• 제28권3호
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• pp.617-623
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• 2018

본 연구는 안드로이드 정적분석을 기반으로 추출된 AndroidManifest 권한 특징을 통해 악성코드를 탐지하고자 한다. 특징들은 AndroidManifest의 권한을 기반으로 분석에 대한 자원과 시간을 줄였다. 악성코드 탐지 모델은 1500개의 정상어플리케이션과 500개의 악성코드들을 학습한 SVM(support vector machine), NB(Naive Bayes), GBC(Gradient Boosting Classifier), Logistic Regression 모델로 구성하여 98%의 탐지율을 기록했다. 또한, 악성앱 패밀리 식별은 알고리즘 SVM과 GPC (Gaussian Process Classifier), GBC를 이용하여 multi-classifiers모델을 구현하였다. 학습된 패밀리 식별 머신러닝 모델은 악성코드패밀리를 92% 분류했다.

• 디지털산업정보학회논문지
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• 제13권4호
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• pp.171-178
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• 2017

The controversy about the burger button triggered in 2013 is that it is difficult to know what the hamburger button itself means and that it is difficult to predict what will happen when the button is clicked, Could. This controversy was found to be fundamentally out of touch, and it could be seen that it caused conflict with Apple's navigation structure with iOS. Therefore, in the case of Apple, it is often used in the form of a tab at the bottom instead of using the slide menu, but it is preferable to be used for the purpose of the hamburger button. I've looked through a variety of documents and found that the amount of content you want to offer on your app or the web is large, and there are five or more categories. And if a sub-category needs to exist in the main category like a large shopping mall, the hamburger button could provide the best UI. Apps and webs that can be curated, such as news and pinterest, are better used to enhance the search filter than to place a hamburger button, and for apps or the web that has a longer amount of content on a page Scrolling was available as an alternative to the burger button. In other words, depending on the amount of content to be provided, it is possible to decide whether to use the hamburger menu from the time of designing the information architecture.

• 한국IT서비스학회지
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• 제17권2호
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• pp.111-128
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• 2018

About 3.9 million apps and 24 primary categories can be approved on Apple iTunes Store. Making accurate categorization can potentially receive many benefits for developers, app stores, and users, such as improving discoverability and receiving long-term revenue. However, current categorization problems may cause usage inefficiency and confusion, especially for cross-attribution, etc. This study focused on evaluating the reliability of app categorization on Apple iTunes Store by using several rounds of inter-rater reliability statistics, locating categorization problems based on Machine Learning, and making more accurate suggestions about representative functionality stems for each primary category. A mixed methods research was performed and total 4905 popular apps were observed. The original categorization was proved to be substantial reliable but need further improvement. The representative functionality stems for each category were identified. This paper may provide some fusion research experience and methodological suggestions in categorization research field and improve app store's categorization in discoverability.

• 한국정보시스템학회지:정보시스템연구
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• 제27권3호
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• pp.25-42
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• 2018

Purpose The purpose of this study focused on adopting production systems in cognitive psychology to improve the extraction process of persuasive design characteristics for healthcare-related mobile applications. Design/Methodology/Approach A research approach with four stages was developed. We developed and updated the evaluation guideline for persuasive design characteristics (PDC). We tried to summarize and analyze each of 28 PDC and prepared related production rules. Verification process for both guideline approach and production system approach were performed. Top one hundred apps from both medical category and health and Fitness category were selected and evaluated by two approaches. By comparing the results of the two approaches, we tried to explain the improvement and reliability of introducing the production system in the PDC extraction process. Findings Based on the updated guideline for healthcare-related mobile applications, a production system in cognitive psychology was developed. By comparing the PDC extraction results by two approaches, production system showed a better improvement for evaluation precision and efficiency for decision-making process. The findings of this study can be used for researchers and app developers to apply production system to analyze, evaluate, and develop better healthcare-related apps with persuasion.

• 한국인터넷방송통신학회논문지
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• 제12권5호
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• pp.177-183
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• 2012

스마트폰은 음성이나 문자를 주고받는 단순한 통신 기기에서 벗어나 현대인의 일상생활에서 최고의 필수품이 되었다. 스마트 폰의 성능 최적화를 위해 성능 향상과 여유 메모리 확보가 가장 많이 시도된다. 전체적인 성능 향상을 위해서는 컴퓨터 제조사에서 사용하는 CPU 오버 클락 기법을 사용하며, 앱들의 동작을 원활하게 해주는 여유 메모리 확보 기법 또한 흔히 시도된다. 이 논문에서 우리는 일반 사용자가 스마트폰 성능을 최적화할 수 있는 방법을 제시하고, 대중적인 앤드로이드 폰 모델을 대상으로 이 기법을 적용하는 실험을 하고 그 결과를 제시하였다.

• 전기전자학회논문지
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• 제22권3호
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• pp.693-699
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• 2018

CNN 기반의 객체 인식 성능은 매우 우수한 것으로 보고되고 있지만 모바일 기기의 앱 GUI와 같이 일반적으로 생각하기에 잡음이 적고 분명하게 인식될 수 있을 것으로 기대되는 환경에 적용해보면 인간의 관점에서 매우 유사한 GUI 입력 위젯들이 의외로 잘 인식되지는 않는다는 문제가 발생한다. 본 논문에서는 CNN의 입력 위젯 인식 성능을 향상시키기 위하여 모바일 앱의 GUI를 구성하는 객체들의 관계를 활용하는 방법을 제안한다. 제안 방법에서는 (1) CNN 기반의 객체 인식 도구인 Faster R-CNN을 이용하여 모바일 앱을 구성하는 입력 위젯을 1차 인식한 후 (2) 위젯 인식률 향상을 위하여 객체 간의 관계를 활용하는 방법을 결합하였다. 객체 간의 관계는 표현 공간상에서의 벡터의 평행 이동을 활용하여 표현되었으며, 총 323개의 앱에서 생성한 데이터에 적용한 결과 Faster R-CNN만을 사용한 경우와 비교하여 위젯 인식률을 상당히 개선할 수 있음을 확인하였다.

• 한국전자통신학회논문지
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• 제10권7호
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• pp.819-824
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• 2015

과거의 조형중심, 시스템 중심의 디자인에서 점차적으로 사용자를 배려하는 디자인 철학이 반영된 사용자 중심 디자인으로 패러다임이 변화하고, 특히 어떤 제품이나 서비스를 사용하는데 있어 최적의 경험을 제공하는 것을 목적으로 하는 UX디자인(User eXperience Design)의 중요성이 크게 인식되고 있다. 본 논문에서는 IoT시대에서 UX디자인이 고려해야할 변화 중에서 웨어러블의 기능에 영향이 적은 데이터를 기반으로 한 디자인 부분에 접근해 보았다. 다양하고 많은 데이터를 가진 기존 소셜커머스 앱의 레이아웃이 IoT디바이스의 인터페이스에서도 데이터 기반의 레이아웃과 유사하다고 생각하였다. 데이터 기반 앱을 모델로 레이아웃을 분석하여 UX디자인 의 구조를 정리하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권2호
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• pp.959-981
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• 2017

Existing Android malware detection approaches mostly have concentrated on superficial features such as requested or used permissions, which can't reflect the essential differences between benign apps and malware. In this paper, we propose a quantitative calculation model of application risks based on the key observation that the essential differences between benign apps and malware actually lie in the way how permissions are used, or rather the way how their corresponding permission methods are used. Specifically, we employ a fine-grained analysis on Android application risks. We firstly classify application risks into five specific categories and then introduce comprehensive risk, which is computed based on the former five, to describe the overall risk of an application. Given that users' risk preference and risk-bearing ability are naturally fuzzy, we design and implement a fuzzy logic system to calculate the comprehensive risk. On the basis of the quantitative calculation model, we propose a risk classification based approach for Android malware detection. The experiments show that our approach can achieve high accuracy with a low false positive rate using the RandomForest algorithm.