• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.287-290
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• 2003

In recent years, one of the main trends of GIS is to construct and provide realistic and human-perceptible information of spatial object using video data. The rapid progress of wireless mobile technology makes the multimedia source using video data possible on mobile environment. Instead of traditional map-based service, video-based location services, that provide video data as location context, would be of interest in connection with various mobile applications requiring location service, such as telematics, LBS, etc. In this paper, we present the location service system using geo-referenced video on wireless mobile environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.1087-1104
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• 2015

An eye location based head posture recognition method is proposed in this paper. First, face is detected using skin color method, and eyebrow and eye areas are located based on gray gradient in face. Next, pupil circles are determined using edge detection circle method. Finally, head postures are recognized based on eye location information. The proposed method has high recognition precision and is robust for facial expressions and different head postures, and can be used in mouse operation. The experimental results reveal the validity of proposed method.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.91-96
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• 2016

In this paper, we propose the CRM service model for analyzing and managing location based data collected by Wi-Fi and BLE. As mobile devices became personalized, enterprises became interested in individual location, and location based mobile marketing started to stand on spotlight. Location based proximity marketing is developing along with contactless data transmission technology, and payment system that uses NFC, Beacon that utilizes BLE, as well as advertisement via Wi-Fi are being serviced. We suggest the model that mobile devices can be detected and identified by MAC address with the need of being connected to Wi-FI or Bluetooth interface. MAC addresses are not associated with any specific user account or mobile phone number. The idea is to be able to measure the amount of people which are present in a certain point at a specific time, allowing the study of the evolution of data analysis and offers effective information for decision-makings.

• Journal of Internet Computing and Services
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• v.2 no.5
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• pp.49-58
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• 2001

Mobile positioning measurement is the most important technology for Location Based Services in the cellular networks. Generally, we are expecting to use GPS to guarantee high accuracy of the mobile position, A CDMA network-based technique for the Mobile Station position calculation needs to be implemented in the cdma2000 network whether the handsets have GPS or not, The most reliable methods of the network-based location technologies are based on the estimation of time of signal traveling between MS and B18 in a network whose coordinates are identified, Other signal parameters such as the power of the received signal and the signal arrival direction cannot be used as main data for a location system because adoption of only the signal parameters will not meet the FCC requirements, In practice, the estimates of the time of signal propagation between MS and BTS always have errors resulting from low-resolution power of measurements and multi path signal propagation, This paper describes the combined network-based location technology in the cdma2000 1× necessary to meet US FCC requirements. The issues of a calibration table and statistic processing based on the pilot strength as well as combined network-based location technologies(TOA/ TDOA) will help to achieve higher location accuracy than specified in the US FCC Rule.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.4869-4874
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• 2011

In this paper, we defined constructivism and ontology theory and associate it in Location Based Service ubiquitous learning. And this paper aims to provide a clear vision about location based service (LBS) ubiquitous learning. The typical ubiquitous learning involving the Context Aware Intelligent system was presented. Also the Architecture for learning environment including the key idea and technical concept is being presented in this paper. Guided with these principles and with the advancement of information and communication technology the context-awareness based on Artificial intelligence for Location based Service for ubiquitous Learning was conceptualized. U-learning for Location Based Service is presented here and the concept behind this new learning paradigm. The learning environment architecture which comprises the entire component is illustrated here.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.10
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• pp.2345-2351
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• 2013

LBS(Location Based System) usually uses GPS technology to measure the exact position of the moving object. However, the method of managing location which utilizes the WiFi technology of mobile phone has not been introduced so far. The method of managing moving objects in view of the location of guardian has also not been proposed. In this paper, a new location management system of moving objects which take guardian's location into consideration is proposed. Specifically, the three methods of searching for missing child proposed in this paper are as follows : 1) a method based on an app for smart phone, 2) a method based on control server, 3) a method based on control server and fixed APs. Because the proposed system reflects the location of the guardian, the guardian is able to identify the state of child immediately and the workload can be reduced.

• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.41-45
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• 2023

Currently, the method of loading items in the warehouse, the worker directly decides the loading location, and the most used method is to load the product at the location closest to the entrance. This can be effective when there is no difference in the required amount for goods, but when there is a difference in the required amount for goods, it is inefficient because items with a small required amount are loaded near the entrance and occupy the corresponding space for a long time. Therefore, in order to minimize the release time of goods, it is essential to select an appropriate location when loading goods. In this study, a method for determining the loading location by predicting the required amount of goods was studied to select the optimal loading location. Deep learning based bidirectional long-term memory networks (Bi-LSTM) was used to predict the required amount for goods. This study compares and analyzes the release time of goods in the conventional method of loading close to the entrance and in the loading method using the required amount for goods using the Bi-LSTM model.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.3
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• pp.151-159
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• 2014

Recently, spread of large amount Smartphones made users to download location-based service applications, which provided by application developers. These location-based service applications are convenient tool for users. Location-based service use technology to find location of user and provide information of user's location. Leakage of information of user's location and expose of privacy life raised new controversy. In this thesis, it will analyze relations of increase of Smartphone market, usage of Location-based service and severity of personal information leakage. Also, it will analyze examples of user's case of damage which caused by leakage personal information and find solutions to reduce damage of personal information leakage. In research, it will find cases of damage that cause by Location-based service. Also it will analyze and research cases of damage and present with graph and chart. In conclusion, to reduce and prevent from damage which caused by leakage personal information, it is important that users and application developers to realize danger of private and personal information leakage. Also, user's personal information must deal with cautiously and application developers have to research and develop the application with powerful security.

• Journal of Korea Technology Innovation Society
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• v.1 no.3
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• pp.374-385
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• 1998

This study is estimates telephone service demand based on empirical studies of telecommunication service demand model. First, the telephone charge(call price index) by each location and subscription fee bring about a negative effect to telephone distribution rate: while the other explanatory variables bring about a positive effect. Second, the flexibility of telephone charge in A location(relevant location) and the flexibility between the distance of A location and B location are negative values, while the flexibility of other explanatory variables is represented in a positive value. This means that the long distance call numbers from A location to B location are in inverse proportion against the phone charge(call price index) of A location and against the distance between A location and the distance of other locations except A location, while they are in direct proportion with an average call number per minute from A location to other locations except A location, and also with subscription numbers of A location, other subscribers in locations other than A location, and the total expenditures of A location.

• ETRI Journal
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• v.30 no.3
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• pp.421-431
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• 2008

In this paper, we offer a new technique to discover frequent spatiotemporal patterns from a moving object database. Though the search space for spatiotemporal knowledge is extremely challenging, imposing spatial and timing constraints on moving sequences makes the computation feasible. The proposed technique includes two algorithms, AllMOP and MaxMOP, to find all frequent patterns and maximal patterns, respectively. In addition, to support the service provider in sending information to a user in a push-driven manner, we propose a rule-based location prediction technique to predict the future location of the user. The idea is to employ the algorithm AllMOP to discover the frequent movement patterns in the user's historical movements, from which frequent movement rules are generated. These rules are then used to estimate the future location of the user. The performance is assessed with respect to precision and recall. The proposed techniques could be quite efficiently applied in a location-based service (LBS) system in which diverse types of data are integrated to support a variety of LBSs.