• Journal of Communications and Networks
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• v.17 no.2
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• pp.110-117
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• 2015

In mobile social network, it is a critical challenge to select an optimal set of devices to supply high quality service constantly under dynamic network topology and the limit of device capacity in mobile ad-hoc network (MANET). In this paper, a multi-devices composition and maintenance problem is proposed with ubiquitous service model and network model. In addition, a multi-devices composition and maintenance approach with dynamic planning is proposed to deal with this problem, consisting of service discovery, service composition, service monitor and service recover. At last, the simulation is implemented with OPNET and MATLAB and the result shows this mechanism is better applied to support complex ubiquitous service.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4054-4071
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• 2015

Named-Data Networking (NDN) is one of the promising approaches for the Future Internet to cope with the explosion and current usage pattern of Internet traffic. Content provider mobility in the NDN allows users to receive real-time traffic when the content providers are on the move. However, the current solutions for managing these mobile content providers suffer several issues such as long handover latency, high cost, and non-optimal routing path. In this paper, we survey main approaches for provider mobility in NDN and propose an optimal scheme to support the mobile content providers in the large-scale NDN domain. Our scheme predicts the movement of the provider and uses state information in the NDN forwarding plane to set up an optimal new routing path for mobile providers. By numerical analysis, our approach provides NDN users with better service access delay and lower total handover cost compared with the current solutions.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.27-39
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• 2018

Since the global positioning system (GPS) has been included in mobile devices (e.g., for car navigation, in smartphones, and in smart watches), the impact of personal GPS log data on daily life has been unprecedented. For example, such log data have been used to solve public problems, such as mass transit traffic patterns, finding optimum travelers' routes, and determining prospective business zones. However, a real-time analysis technique for GPS log data has been unattainable due to theoretical limitations. We introduced a machine learning model in order to resolve the limitation. In this paper presents a new, three-stage real-time prediction model for a person's daily route activity. In the first stage, a machine learning-based clustering algorithm is adopted for place detection. The training data set was a personal GPS tracking history. In the second stage, prediction of a new person's transient mode is studied. In the third stage, to represent the person's activity on those daily routes, inference rules are applied.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.924-928
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• 2005

Formative assessment of student progress and attitudes is important to our continuous improvement process, but collecting and compiling the data is burdensome without access to computer tools. This research is to set up a mobile computer based lab that will enable faculty who teach in rooms without computers to use testing and survey tools. The technologies necessary to develop such system including wireless communication, World Wide Web (WWW), database, and mobile computing are investigated in this research. The real-time based formative assessment of student is proposed. A hardware configuration for real-time assessment is also presented in the research.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1105-1108
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• 2003

Adaptation in dynamic environments gains a significant advantage by combining evolution and learning. We propose an on-line, realtime evolutionary learning mechanism to determine the structure and the synaptic weights of a neural network controller for mobile robot navigations. We support our method, based on (1+1) evolutionary strategy, which produces changes during the lifetime of an individual to increase the adaptability of the individual itself, with a set of experiments on evolutionary neural controller for physical robots behaviors.

• Information and Communications Magazine
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• v.14 no.11
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• pp.22-28
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• 1997

ETSI SMG plays a key role at the development of standards for the UMTS Universal Mobile Telecommunications System, a set of standards aimed at the global market. It will be a real Third Generation Global System for Mobile CommunlcaUons adding new features and Introducing relevant technological InnovaUons while evolving from both GSM and ISDN networks. UMTS Is based on the carefully selected market requirements and belongs to the IMT-2000 family. UMTS standardlsaUon Is a market driven process being developed In a close co-operatlon with the UMTS Forum and GSM MoU.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.141-148
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• 2012

Android that was made by Google and Open Handset Alliance is the open source software toolkit for mobile phone. Nowadays, Smart phone users have been rapidly increasing, by that reason a lot of application contents have been released and especially contents which focus on user convenience have been developed. In this paper, we develop a new application content smart alarm based on Google Android flatform. The features of the developed content are as follows. First, users set their day's schedules. So they can notify easily what they have to do at the moment. Second, when users set their alarms not to forget several sequential tasks, they can set their schedules by not only alarm method but also timer method. In the performance evaluation, we show the results of simulation using AVD(Android Virture Device).

• Journal of Digital Convergence
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• v.12 no.4
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• pp.85-92
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• 2014

In recent years, the government has pushed ahead with the convergence and innovation of science technology and information technology in order to realize the creative economy. So, a creative economy ecosystem has been set up to realize the creative economy for small businesses growth and small business happiness. According to proliferation of mobile area taking the lead in the recent IT transition, development of various convergence technologies related to mobile such as mobile Apps, SNS, and big data have been promoted. For realizing government's creative economy, systematic raising plan to create newly value-added market and occupation being considered with developing technology for mobile convergence based on imagination and creativity of small businesses is proposed in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1448-1451
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• 2004

Position estimation is one of the most important functions for the mobile robot navigating in the unstructured environment. Most of previous localization schemes estimate current position and pose of mobile robot by applying various localization algorithms with the information obtained from sensors which are set on the mobile robot, or by recognizing an artificial landmark attached on the wall, or objects of the environment as natural landmark in the indoor environment. Several drawbacks about them have been brought up. To compensate the drawbacks, a new localization method that estimates the absolute position of the mobile robot by using a fixed camera on the ceiling in the corridor is proposed. And also, it can improve the success rate for position estimation using the proposed method, which calculates the real size of an object. This scheme is not a relative localization, which decreases the position error through algorithms with noisy sensor data, but a kind of absolute localization. The effectiveness of the proposed localization scheme is demonstrated through the experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.875-878
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• 2004

Researching in text detection and segmentation has been done for a long period in the OCR area. However, there is some other area that the text detection and segmentation from images can be very useful. In this report, we first propose the design of a mobile translator system which helps non-native speakers to understand the foreign language using ubiquitous mobile network and camera mobile phones. The main focus of the paper will be the algorithm in detecting and segmenting texts embedded in the natural scenes from taken images. The image, which is captured by a camera mobile phone, is transmitted to a translator server. It is initially passed through some preprocessing processes to smooth the image as well as suppress noises. A threshold is applied to binarize the image. Afterward, an edge detection algorithm and connected component analysis are performed on the filtered image to find edges and segment the components in the image. Finally, the pre-defined layout relation constraints are utilized in order to decide which components likely to be texts in the image. A preliminary experiment was done and the system yielded a recognition rate of 94.44% on a set of 36 various natural scene images that contain texts.