• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.158-164
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• 2008

This study was conducted for raising the considering the dynamical context of mobile phone use environment in the mobile-phone research. For this I identified the characteristic of the mobile phone use. The first characteristic is that the mobile phone is the context sensitive device. Also, it reflects the user's life pattern because it is the very personal device. I defined the context of mobile phone use with the basis on this identification of those characteristics. I referenced the definition, 'situational context', defining the mobile phone use context. Also, I set up the research scope within the user task that is influential from the situational context, I named this kind of task as the 'contextual task'. I developed the Contextual Task Model in this study. I named the model as the 'ESR Model'. The reason that I developed this contextual task model is that this model can help novice designers and designers unfamiliar with an application domain understand the user behavior and user centered design. And also this model can be effective to communicate each other, I identified the user's contextual tasks three kinds of model. First, the Extend Model includes user tasks that related to extending from user physical working space to the virtual level. Second model is Synchronize Model, which includes issues that lesson the blocking when use several functions at a time or sequentially. Third model is Replace Model, which is come from the characteristic of user life pattern to use the mobile phone. Finally, I proposed an application of this model, CIQ. Through the process to make CIQ I proved the effectiveness of this ESR Model.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.74-78
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• 2003

In this paper, we have developed a technology-service relationship model which describes the diffusion process of a group of services and relevant technologies, and have applied the developed model to the prediction of the number of subscribers to the next generation mobile service. The technology-service relationship model developed in this paper incorporates the developing process of relevant technologies, a supply-side factor, into the diffusion process of specific services, while many diffusion models and multi-generation diffusion models in previous researches are mainly reflect the demand-side factors. So, the proposed model could effectively applied to the telecommunication services where the developing of the relevant technologies are very essential to the service penetration. In our application, the proposed model provides a competitive substitution between the next generation mobile service and the traditional mobile service.

• Asia pacific journal of information systems
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• v.16 no.4
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• pp.239-254
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• 2006

Location-based advertising or application has been one of the drivers of third-generation mobile operators' marketing efforts in the past few years. As a result, many studies on location-based marketing or advertising have been proposed for recent several years. However, these approaches have two common shortcomings. First. most of them just suggested the theoretical architectures, which were too abstract to apply it to the real-world cases. Second, many of these approaches only consider service provider (seller) rather than customers (buyers). Thus, the prior approaches fit to the automated sales or advertising rather than the implementation of CRM. To mitigate these limitations, this study presents a novel advertisement recommendation model for mobile users. We call our model MAR-CF (Mobile Advertisement Recommender using Collaborative Filtering). Our proposed model is based on traditional CF algorithm, but we adopt the multi-dimensional personalization model to conventional CF for enabling location-based advertising for mobile users. Thus, MAR-CF is designed to make recommendation results for mobile users by considering location, time, and needs type. To validate the usefulness of our recommendation model. we collect the real-world data for mobile advertisements, and perform an empirical validation. Experimental results show that MAR-CF generates more accurate prediction results than other comparative models.

• Journal of Korea Multimedia Society
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• v.22 no.2
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• pp.292-298
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• 2019

Mobile-based software development methodology has been vigorously researched from using object-oriented development methodology and component-based development methodology previous structural developing methodology. There are two types of OS in mobile platform which are android and iOS. There is a problem that the application to be developed is developed depending on the device type. To resolve this problem, first, the system structure and design method should be managed effectively. Second, a basic design guide that can be commonly adapted to the each project is required. In this paper, we define a mobile cross platform meta model based on MDA-development methodology, focusing on reusability, portability and interoperability about non - dependent part of the mobile platform. If the proposed meta-model is applied to manage the related information and all the types of Mobile-Apps become available through independent mobile app development process, henceforward, it will be much of help establishing formulaic mobile-app developmental methodology.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.402-409
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• 2007

Markov Chains has proven to be effective in predicting human behaviors in the areas of web site assess, multimedia educational system, and driving environment. In order to extend an application area of predicting human behaviors using Markov Chains, this study was conducted to investigate whether Markov Chains could be used to predict human behavior in selecting mobile phone menu item. Compared to the aforementioned application areas, this study has different aspects in using Markov Chains : m-order 1-step Markov Model and the concept of Power Law of Learning. The results showed that human behaviors in predicting mobile phone menu selection were well fitted into with m-order 1-step Markov Model and Power Law of Learning in allocating history path vector weights. In other words, prediction of mobile phone menu selection with Markov Chains was capable of user's actual menu selection.

• Journal of Internet Computing and Services
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• v.7 no.2
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• pp.81-92
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• 2006

Recently, the number of mobile phone and PDA users has been rapidly increased. Such monitoring and control applications as geographical and traffic information systems are being used widely with wireless devices. In this paper, we introduce the mobile M/VC application framework that supports the rapid constructions of mobile monitoring and control (M/VC) applications. The mobile M/VC application framework uses the mobile Observer/Observable pattern that extends the Java's Observer/Observable for automatic interactions of server and client objects in wireless environments. It also provides the Multiplexer and Demultiplexer classes that supports the assembly feature of Observer and Observable objects. To construct an application using the framework, developers just need to create necessary objects from the Observable and MobileObserver classes and inter-connect them structurally(like the plug-and-play style) through the Multiplexer and Demultiplexer objects. Then, the state change of Observable objects is notified to the connected Observer objects and user's input with Observer objects is propagated to Observable objects. These mechanism is the main process for monitoring and control applications. Therefore, the mobile M/VC application framework can improve the productivity of mobile applications and enhance the reusability of such components as Observer and Observable objects in wireless environments.

• The Journal of Society for e-Business Studies
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• v.16 no.4
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• pp.173-195
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• 2011

The ability of offering various and abundant mobile applications has emerged as the knowledge of the smartphone has grown in the smartphone market. The mobile application market has emerged as a competitive new market with enormous potential. Although many users download paid or free mobile applications through the app markets such as the Appstore, there is no significant research regarding customer's application purchase yet. Hence, we refer to the purchase motivation of mobile applications among experienced users who have bought paid applications. We conducted the interview with 30 users and suggest four categories of applications (productivity, entertainment, information, and social networking) and also classify the purchase intentions on each category based on the ground theory. The comparison analysis of the interview provides us what factors affect the application purchase. This framework may advance effective mobile application business model development, implicate the strategy for boosting mobile application market.

• Korean Management Science Review
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• v.33 no.2
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• pp.65-74
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• 2016

The present study applies the TAM (Technology Acceptance Model) to investigate the factors that affect the intention to use the mobile payment services. For this purpose five potential variables (perceived usefulness, perceived convenience, ubiquity, innovativeness, and safety risk) that are expected to affect the intention to use the mobile payment services were selected. An online survey was administered, and 339 questionnaires were analyzed. Structure Equation Model (SEM) Analysis revealed that TAM variables (perceived usefulness and perceived convenience) partially influenced the attitude. The perceived usefulness predicted the attitude while perceived convenience did not predict the attitude toward the mobile payment service. Personal characteristics variable (innovativeness) and mobile nature variables (ubiquity, and security risk) were identified as the predictors of the attitude toward the mobile payment service. While innovativeness and ubiquity affected the attitude positively, security risk affected the attitude negatively. Finally, the analysis substantiated the influence of attitude toward the mobile payment services on the intention to use the services. On the basis of findings, managerial implications and suggestions for further studies were discussed.

• Journal of the Semiconductor & Display Technology
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• v.18 no.1
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• pp.123-128
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• 2019

Currently mobile services are on the verge of full commercialization ahead of 5G mobile communication (5G). The first goal could be to preempt the 5G market through realistic media services utilizing VR (Virtual Reality) and AR (Augmented Reality) technologies that users can most easily experience. Basically this movement is based on the advanced development of smart devices and high quality graphics processing computing power of mobile application processors. Accordingly, the importance of mobile GPUs is emerging and the most concern issue becomes a model for predicting the power and performance for smooth operation of high quality mobile contents. In many cases, the performance of mobile GPUs has been introduced in terms of power consumption of mobile GPUs using dynamic voltage and frequency scaling and throttling functions for power consumption and heat management. This paper introduces several studies of mobile GPU performance prediction model with user-friendly methods not like conventional power centric performance prediction models.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.608-611
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• 2012

In this paper, a mobile cloud-based agent model is proposed in order to overcome the resource constraints and the difficulties of installing a variety of complex applications in mobile devices. The proposed software architecture overcomes the disadvantages of mobile devices and maximizes usage of cloud services by implementing the function of mobile agent concept. The significant portion of the cloud services is run in the cloud server and the client application implemented in the mobile device can call and control appropriate service from the cloud server. Thus, the inherent weakness of the mobile can be overcome by executing the target applications on cloud nodes.