• Journal of the Korean association of regional geographers
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• v.18 no.1
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• pp.118-127
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• 2012

Using GIS, animal clinic's spatial distribution characteristics were analyzed. Animal clinic location data was collected through the Internet's Open API service. Approximately 4,100 animal clinics are operated in South Korea in 2011. And 47 % of these are located in the Seoul area. Population, especially female population and apartment resident's ratio affects the location factor of the animal clinic. The number of 25~44 year-old woman and animal clinics are high correlation. In the animal clinic location, distance from the road is more important than the distance of the metro.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.2
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• pp.57-65
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• 2008

Wireless sensor networks achieve environment monitoring and controlling through use of small devices of low cost and low power. Such network is comprised of several sensor nodes, each having a microprocessor, sensor, actuator and wired/wireless transceiver inside a small device. In this paper, we employ the sensor networks in order to design and implement a real-time vehicle safety system. Such system can inform the safe velocity in a specific weather condition to drivers in advance through analyzing the weather data collected from sensor networks. As a result, the drivers can prevent effectively accidents by controlling their car speed.

• Journal of Korea Spatial Information System Society
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• v.10 no.1
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• pp.29-40
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• 2008

With the spread of mobile devices and advances in communication techknowledges, the needs of application which uses the movement patterns of moving objects in history trajectory data of moving objects gets Increasing. Especially, to design public transportation route or road network of the new city, we can use the similar patterns in the trajectories of moving objects that move on the spatial network such as road and railway. In this paper, we propose a spatio-temporal similar trajectory search algorithm for moving objects on road network. For this, we define a spatio-temporal similarity measure based on the real road network distance and propose a grid-based index structure for similar trajectory search. Finally, we analyze the performance of the proposed similar trajectory search algorithm in order to show its efficiency.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2006.11a
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• pp.261-264
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• 2006

지능형 차량정보 시스템은 21세기 교통체계로 기대를 모으고 있는 ITS(Intellligent Transport System)의 구축에 핵심이 되는 시스템이다. 이러한 시스템을 구현하기 위해서 종래의 네비게이션, 차량용 무선통신, 차량진단 등의 단일화된 시스템을 통합적으로 수행하며, 계측 또는 수집된 데이터를 분석하여 지능적으로 차량의 주행 상태를 분석 / 진단함으로써 차량에서의 안전한 운행과 운전자 및 승객들이 요구하는 정보 또는 다양한 서비스를 제공하기 위한 새로운 모듈의 개발이 절실히 필요한 실정이다. 따라서, 본 논문에서는 CAN(Controller Area Network) BUS을 이용한 차량의 상태수집 모듈과 능동 데이터베이스에 관해 기술하고 이를 통합하기 위한 임베디드 보드를 이용한 CAN BUS연계형 차량용 복합통신모듈의 프로토타입 H/W을 구성하여 실용화 가능성 및 유용성을 제시하고자 하였다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.439-444
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• 2015

The Social infrastructure systems such as communication, transportation, power and water supply systems are now facing various types of threats including component failures, security attacks and natural disasters, etc. Whenever such undesirable events occur, it is crucial to recover the system as quickly as possible because the downtime of social infrastructure causes catastrophic consequences in the society. Especially when there is a network link-failure, we need an automatic link-recovery method. This means that customers are aware of network failures that can be recovered before you say that service. In this paper, we analysis the relation between Auto-recovery performance and cost.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.246-248
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• 2017

Self-driving cars have three main functions. The first recognizes the surrounding environment, judge the risk, and lastly plans the drive path. Therefore, the driving operation is minimized. And it refers to a human friendly car capable of safe driving on its own. The reason for the need for self-driving car was to reduce traffic jams on limited roads and to reduce carbon dioxide emissions. Driving ahead of these self-driving car businesses can be expected to attract and expand the existing business and expand the new business and create new business opportunities for ICT firms. It is urgent for the concerned agencies to establish legal and institutional basis for self-driving cars. By doing so, new services could be provided to consumers. Therefore, this paper introduces the technological development trends for self-driving cars.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.927-930
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• 2010

Recently, continuous k-nearest neighbor query(CkNN) which is defined as a query to find the nearest points of interest to all the points on a given path is widely used in the LBS(Location Based Service) and ITS(Intelligent Transportation System) applications. It is necessary to acquire results quickly in the above applications and be applicable to spatial network databases. This paper proposes a new method to search nearest POIs(Point Of Interest) for moving query objects on the spatial networks. The method produces a set of split points and their corresponding k-POIs as results. There is no order between the POIs. The analysis show that the proposed method outperforms the existing methods.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Journal of the Korean Society of Hazard Mitigation
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• v.2 no.1 s.4
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• pp.153-159
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• 2002

Disasters are the phenomena that we have to prevent the occurrence in order to keep the safety to human lives and properties, and if occurred, we have to minimize the economic, social, and mental costs of the occurred disasters or incidents. This research analyzes the optimal location of fire stations in terms of served population maximization in Seoul. This research introduces "the maximal covering location problem(MCLP)," one of the optimization techniques, as the primary research method. This research also applies a geographic information system into spatial distribution analyses of existing fire stations and observed fire incidents. Results from the analyses show that the existing location of fire stations and branches need to be improved. The dispatch location of fire engines should be reconsidered for rapid services of fire fighting.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.6
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• pp.698-701
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• 2010

Recently, Vehicular Networks is being developed to provide variety of services such as email, ftp, and video streaming services. As IP mobility technology, Proxy Mobile IP is developed to provide these services for a VANET user. By adopting Proxy Mobile IPv6 (PMIPv6), Vehicular Networks can support IP mobility, but it may cause a proxy binding update (PBU) message when a vehicle moves from one MAG to another. In addition, if the density of vehicles on the road is high, significant PBU messages are generated. In this paper, we propose bulk PBU message to reduce signaling overhead by those PBU messages when a bunch of vehicles move from one MAG to another. When the vehicles move from one MAG to another, it generates only one bulk PBU message to update those vehicle's location. Through numerical and simulation results, we show that our proposed bulk registration reduces signaling overhead when the density of vehicles and the speed of them are high.