• Journal of Digital Convergence
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• v.9 no.1
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• pp.61-70
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• 2011

Ultimately, this research will focus on the activity traits of future customers in the convergence age. To accomplish that, firstly, researcher develop measures for assessing the convergence level of digital devices and digital services. Next, this will investigate the behavioral traits of people who use specific devices or services on the internet or mobile networks. This study proposed five convergence measures each for devices and services. For digital devices, measures such as converged functions, accessibility to network, portability, immediate communicability, and expandibility of functions were utilized. For digital measures such as scope of users, newness, social network level, ease-of use on mobile networks, and expandibility of information were used. We believe that the research results can provide insights for those wishing to explore the convergence level of devices and services and those developing high-level converged devices and digital services.

• Electronics and Telecommunications Trends
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• v.34 no.6
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• pp.133-144
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• 2019

Although deep learning-based visual image recognition technology has evolved rapidly, most of the commonly used methods focus solely on recognition accuracy. However, the demand for low latency and low power consuming image recognition with an acceptable accuracy is rising for practical applications in edge devices. For example, most Internet of Things (IoT) devices have a low computing power requiring more pragmatic use of these technologies; in addition, drones or smartphones have limited battery capacity again requiring practical applications that take this into consideration. Furthermore, some people do not prefer that central servers process their private images, as is required by high performance serverbased recognition technologies. To address these demands, the object and scene recognition technologies for mobile/embedded devices that enable optimized neural networks to operate in mobile and embedded environments are gaining attention. In this report, we briefly summarize the recent trends and issues of object and scene recognition technologies for mobile and embedded devices.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.717-720
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• 2007

With the convergence of mobile devices and the Internet ubiquitous computing promises to revolutionalize the way that we access services and run application. However, ubiquitous computing environments, in particular, mobile and wireless environments interfaced with the Internet, currently possess security vulnerabilities that are ripe for attack from cyber-threats. Thus, this paper discusses the Limitation of current security mechanisms in ubiquitous computing environments

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.2
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• pp.359-373
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• 2011

Demand for rich media services is rapidly increasing and, as a result, several technologies are competing to deliver rich media services to mobile, resource-constrained devices. In this paper, we explore the existing rich media technologies and analyze their key features. In addition, in order to accommodate the new requirements introduced by emerging service models, such as service convergence, these technologies must evolve from their current status. We examine how the community intends to achieve this.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.441-447
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• 2020

In a situation in which around 50 million metric tons of electrical and electronic products is generated globally per year, the total installed base of Internet of Things (IoT) devices is projected to amount to around 75 billion worldwide by 2025. However, there is very little research on identification schemes for end-of-life treatment (EoLT) of IoT devices. To address this issue, this paper proposes new identifiers including EoLT information such as recyclability rate (Rcyc) and recoverability rate (Rcov) of an IoT device, recycling rate (RCR) and recovery rate (RVR) of each part in the IoT device, etc. and implements them by using object identifier (OID), mobile radio frequency identification (RFID) and quick response (QR) code. The implemented OID and mobile RFID can be used with cooperation of a remote server via communication networks and the implemented QR code can be used simply with a smartphone app.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.77-84
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• 2011

Following the increase in the supply of smartphones and the increase in the use of wireless Internet, the online shopping environment is also changing into mobile shopping. However, the domestic mobile shopping services fall short of people's expectations compared to desktop Internet shopping malls. These are mainly due to the restricted screen size and inconvenient data entry of mobile devices, the slow Internet speed, and other restrictive conditions. Accordingly, in this paper, the usability of three main domestic mobile shopping malls was evaluated using a heuristic evaluation method. The factors that must be considered when producing a mobile website, the consideration for the mobile users, and the main functions of a shopping mall, were considered to define an evaluation form. The results of the evaluation were then analyzed to propose the problems of mobile shopping malls and the directions for their improvement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.2
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• pp.174-190
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• 2010

In ubiquitous computing, invisible devices and software are connected to one another to provide convenient services to users [1][2]. Users hope to obtain a personalized service which is composed of customized devices among sharable devices in a ubiquitous smart space (which is called USS in this paper). However, the situations of each user are different and user preferences also are various. Although users request the same service in the same USS, the most suitable devices for composing the service are different for each user. For these user requirements, this paper proposes a device recommender system which infers and recommends customized devices for composing a user required service. The objective of this paper is the development of the systems for recommending devices through context-aware inference in peer-to-peer environments. For this goal, this paper considers the context and user preference. Also I implement a prototype system and test performance on the real ubiquitous mobile object (UMO).

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.180-187
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• 2020

Security threats are increasing with interest due to the mass spread of smart devices, and vulnerabilities in developed applications are being exposed while mobile malicious codes are spreading. The government and companies provide various applications for the public, and for reliability and security of applications, security checks are required during application development. In this paper, among the security threats that can occur in the mobile service environment, we set up the vulnerability analysis items to respond to security threats when developing Android-based applications. Based on the set analysis items, vulnerability analysis was performed by examining three applications of public institutions and private companies currently operating as mobile applications. As a result of application security checks used by three public institutions and companies, authority management and open module stability management were well managed. However, it was confirmed that many security vulnerabilities were found in input value verification, outside transmit data management, and data management. It is believed that it will contribute to improving the safety of mobile applications through the case of vulnerability analysis for Android application security.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4098-4116
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• 2020

Mobile devices such as smartphones are very attractive targets for augmented reality (AR) services, but their limited resources make it difficult to increase the number of objects to be recognized. When the recognition process is scaled to a large number of objects, it typically requires significant computation time and memory. Therefore, most large-scale mobile AR systems rely on a server to outsource recognition process to a high-performance PC, but this limits the scenarios available in the AR services. As a part of realizing large-scale standalone mobile AR, this paper presents a solution to the problem of accuracy, memory, and speed for large-scale object recognition. To this end, we design our own basic feature and realize spatial locality, selective feature extraction, rough pose estimation, and selective feature matching. Experiments are performed to verify the appropriateness of the proposed method for realizing large-scale standalone mobile AR in terms of efficiency and accuracy.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.71-76
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• 2019

In this paper, we propose a simple one-click marketing solution for mobile devices which can advertise a product which is embedded in a mobile video while watching the video on a smartphone. If a specific product of interest appears in the video to the user, one can simply click on the product in the video and a pop-up window with information about the product is proposed. The implementation of the system is expected to enable users to gain real-time information about the product while watching the video without having to search for the product again after watching the movie, and thereby facilitating more mobile commerce. We use a two-fold system to prevent the failure of tracking which often occurs on a single online tracking system, so that the user cannot always get the commercial product information.