• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.280-282
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• 2004

According as IT environment changes from client/server system to the open system based on web service technologies, the exchange of data and services between independent applications and service servers in web environment is observed Recently. In this points, it is necessary that Geographic Information Systems, Spatial Imagery Information Systems, Intelligent Transportation Systems, and Global Navigation Satellite Systems based on the location and geometry information are inter-related each other. But, the inter-relation of these systems is very difficult because of the closed system architecture, different information format, and the absence of interoperability technologies. In this Paper, we describe 4S integration system based web service technologies that accept the international standard as WFS, WCS, WRS of OGC (OpenGIS Consortium) and UDDI, SOAP, WSDL of W3C. In detail, we study the system architecture design and implementation of traffic information service, routing service, and tracing service. These services are consisting of the data schema based on XML and GML, various functions of each layered service, each server platform, and web server. Specially, we represent that GML is being applied to a wide range of location-based services, telematics, and intelligent transportation

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.659-679
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• 2015

Distributed applications are composed of multiple nodes, which exchange information with individual nodes through message passing. Compared with traditional applications, distributed applications have more complex behavior patterns because a large number of interactions and concurrent behaviors exist among their distributed nodes. Thus, it is difficult to detect anomalous behaviors and determine the location and scope of abnormal nodes, and some attacks and misuse cannot be detected. To address this problem, we introduce a method for detecting anomalous behaviors based on process algebra. We specify the architecture of the behavior detection model and the detection algorithm. The anomalous behavior detection and analysis demonstrate that our method is a good discriminator between normal and anomalous behavior characteristics of distributed applications. Performance evaluation shows that the proposed method enhances efficiency without security degradation.

• Journal of People, Plants, and Environment
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• v.22 no.1
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• pp.75-89
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• 2019

This study aimed to examine the current status of mobile applications for garden design and extract valuable contents for the development of garden design programs for future reference. Mobile applications released in Korean or English on Google Play App Market as of July, 2018 were analyzed in this study (1 application in Korea and 14 applications overseas). The purposes of this study are to analyze the components of the programs for those who actually intend to create a garden and to use it as a resource for developing mobile applications for garden design. Thus, program components and contents were analyzed for garden design applications based on real space (1 application in Korea and 3 applications overseas) that could actually help users. The analysis of mobile applications for garden design shows that while overseas garden programs are rapidly developing in various fields, the number of garden design mobile applications developed in Korea and the amount of information platforms are significantly insufficient. This study suggested flowchart for garden design mobile applications based on the analysis results of existing garden design application. This flowchart includes a series of processes from planning/designing gardens to purchasing plants and facilities to constructing/maintaining gardens for users who intend to design and create a real garden. Furthermore, this study proposed a freemium business model based on 4R(Reflex, Reality, Real place, Real communication) marketing strategies for mobile applications. Realistic experiences can be increased through graphics and information about gardens and plants provided in this study, and location-based information services as well as the creation of systems connected with vendors and suppliers of products related to gardens can induce consumers' purchasing behaviors. Additionally PR activities through various garden-related cultural events are expected to attract more users.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1812-1824
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• 2019

The location and human activity are usually used as one of the important parameters to monitor the health status in healthcare devices. However, nearly all existing location and monitoring systems have the limitation of short-range communication and high power consumption. In this paper, we propose a new mechanism to collect and transmit monitoring information based on LoRa technology. The monitoring device with sensors can collect the real-time activity and location information and transmit them to the cloud server through LoRa gateway. The user can check all his history and current information through the specific designed mobile applications. Experiment was carried out to verify the communication, power consumption and monitoring performance of the entire system. Experimental results demonstrate that this system can collect monitoring and activity information accurately and provide the long rang coverage with low power consumption.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.135-142
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• 2021

Estimating the locations of workers in a shipyard is beneficial for a variety of applications such as selecting potential forwarders for transferring data in IoT services and quickly rescuing workers in the event of industrial disasters or accidents. In this work, we propose a human movement stream processing system for estimating worker locations in shipyards based on Apache Spark and TensorFlow serving. First, we use Apache Spark to process location data streams. Then, we design a worker location prediction model to estimate the locations of workers. TensorFlow serving manages and executes the worker location prediction model. When there are requirements from clients, Apache Spark extracts input data from the processed data for the prediction model and then sends it to TensorFlow serving for estimating workers' locations. The worker movement data is needed to evaluate the proposed system but there are no available worker movement traces in shipyards. Therefore, we also develop a mobility model for generating the workers' movements in shipyards. Based on synthetic data, the proposed system is evaluated. It obtains a high performance and could be used for a variety of tasksin shipyards.

• Journal of Korea Multimedia Society
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• v.21 no.5
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• pp.583-591
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• 2018

With the development of ICT(Information and Communication Technology), the number of smart devices is rapidly increasing. LBS(Location Based Service) applications that provide user's location based service are used in various fields. There is also a growing demand for indoor precision positioning technology to provide seamless services. In this paper, we propose an indoor positioning system that estimates the location of a smartphone user. The proposed algorithm determines whether the received signal is LOS(Line-of-Sight) or NLOS(Non-Line of-Sight) in order to decrease multipath effect by the indoor environment. The proposed positioning algorithm is very simple and requires only the AP(Access Point) coordinates. In addition, it requires only two APs for estimating the location of a smartphone user. The proposed algorithm is a practically applicable technology without any additional hardware and kernel modification in the smartphone. In the experiment results, the reliability of the positioning system was found to be within 0.83 m.

• Proceedings of the Korea Contents Association Conference
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• 2004.05a
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• pp.522-528
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• 2004

Mobile internet service based on CDMA network evolution and multifunction mobile terminal is popular in Korea. Mobile internet service is classified as the information service using browser and mobile multimedia service using download platform. Killer applications based on multifunction mobile terminals have been developed for new business in mobile internet services. One of killer applications is location based seurvice (LBS) using mobile location information. In this paper, we develop mobile map browser using WIPI platform that is the main function in LBS. Mobile map browser interworking with GIS server provides the map information. The developed mobile map browser can be working on PDA and telematics terminals when WIPI is porting on these devices.

• Tribology and Lubricants
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• v.29 no.2
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• pp.91-97
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• 2013

Quantifying the nanoscale force between the atomic force microscopy (AFM) probe of a force-sensing cantilever and the sample is one of the challenges faced by AFM researchers. The normal force calibration is straightforward; however, the lateral force is complicated due to the twisting motion of the cantilever. Force measurement in a liquid environment is often needed for biological applications; however, calibrating the force of the AFM probes for those applications is more difficult owing to the limitations of conventional calibration methods. In this work, an accurate nondestructive lateral force calibration method using multiple pivot loading was proposed for liquid environment. The torque sensitivity at the location of the integrated probe was extrapolated based on accurately measured torque sensitivities across the cantilever width along a few cantilever lengths. The uncertainty of the torque sensitivity at the location of the integrated tip was about 13%, which is significantly smaller than those for other calibration methods in a liquid environment.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.5
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• pp.9-20
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• 2005

In this paper, we propose ubiTrack, a system which tracks users' location in indoor environments by employing infrared-based proximity method. Most of recently developed systems have focussed on performance and accuracy. For this reason, they adopted the idea of centralized management, which gathers all information in a main system to monitor users' location. However, these systems raise privacy concerns in ubiquitous computing environments where tons of sensors are seamlessly embedded into environments. In addition, centralized systems also need high computational power to support multiple users. The proposed ubiTrack is designed as a passive mobile architecture to relax privacy problems. Moreover, ubiTrack utilizes appropriate area as a unit to efficiently track users. To achieve this, ubiTrack overlaps each sensing area by utilizing the TDM (Time-Division Multiplexing) method. Additionally, ubiTrack exploits various filtering methods at each receiver and utilization module. The filtering methods minimize unexpected noise effect caused by external shock or intensity weakness of ID signal at the boundary of sensing area. ubiTrack can be applied not only to location-based applications but also to context-aware applications because of its associated module. This module is a part of middleware to support communication between heterogeneous applications or sensors in ubiquitous computing environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.204-226
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• 2018

Big data processing applications have been migrated into cloud gradually, due to the advantages of cloud computing. Hadoop Distributed File System (HDFS) is one of the fundamental support systems for big data processing on MapReduce-like frameworks, such as Hadoop and Spark. Since HDFS is not aware of the co-location of virtual machines in the cloud, the default scheme of block allocation in HDFS does not fit well in the cloud environments behaving in two aspects: data reliability loss and performance degradation. In this paper, we present a novel location-aware data block allocation strategy (LDBAS). LDBAS jointly optimizes data reliability and performance for upper-layer applications by allocating data blocks according to the locations and different processing capacities of virtual nodes in the cloud. We apply LDBAS to two stages of data allocation of HDFS in the cloud (the initial data allocation and data recovery), and design the corresponding algorithms. Finally, we implement LDBAS into an actual Hadoop cluster and evaluate the performance with the benchmark suite BigDataBench. The experimental results show that LDBAS can guarantee the designed data reliability while reducing the job execution time of the I/O-intensive applications in Hadoop by 8.9% on average and up to 11.2% compared with the original Hadoop in the cloud.