• Journal of Multimedia Information System
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• v.2 no.2
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• pp.223-232
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• 2015

In this system, mobile devices are not independent, they can communicate with each other, one device's change can affect the whole system or other devices. To achieve the above mentioned A Self-Reconfigurable System of Contents, through discover the device and connect process, to establish the connection between the mobile devices. After user assigns two dimension display type, the user can select content to input the system, contents are portioning and broadcast to devices. The system can self-reconfigure contents rapidly and exactly. This technique supports contents self-reconfiguration for devices remove, addition and position exchange. In this paper, when the user uses the hand contacts device, the device sends a signal to assist the system to detection device's position. The system does not need to get accurate devices moving direction, just according to all changed devices position to judge where the devices destination is. This research develops an application according to this technique, and the real machine tests the application using Android platform. Some communication protocols and mathematical modeling methods are proposed. These methods can also be used in other Internet of Things (IoT) fields, such as Drones Navigation, Smart Home, and Informational City management.

• Journal of Korean Society for Geospatial Information Science
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• v.5 no.1 s.9
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• pp.41-55
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• 1997

An improved model of 'use' or 'region' districting(or regional zoning) scheme has been proposed. GIS based prototype model of managing the semi-agricultural region is implemented in a PC based platform focusing the Yongin, Kyonggi-Do area. Throughout the process of users' requirement analysis, database design, and user interface design, it has been shown that the integrated system may shed light on the prospective usage by the city or county government officials regardless of the short functionalities and user interface. This study aims first at identifying the needs in the area of districting at local level and at suggesting a basic framework of database design and system implementation in regard to region districting. The ARC/INFO, ArcView/Avenue based PC-based decision supports system presented herein is hoped to be supplemented with the inclusion of time factor in its database to cover and reflect the temporal variations associated with the plans.

• Korea Trade Review
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• v.46 no.2
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• pp.263-280
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• 2021

With the advent of the era of the 4th Industrial Revolution, various support policies and programs are being introduced as the promotion of startups related to the 4th industry is promoted as a core policy of the government. Based on major technologies such as Artificial Intelligence(AI), Big Data, Internet of Things(IoT), Blockchain, and Automation leading the 4th industrial revolution, logistics and distribution companies are expanding the range of markets and services provided. The purpose of this study is to examine the current status of startups in the logistics field based on major technologies of the 4th Industrial Revolution, which are rapidly growing at home and abroad, and suggest implications for revitalizing logistics startups through a policy demand survey. As a result of the study, in order to foster domestic logistics startups, we propose policy support for integration of logistics startups, integrated management of information, provision of physical space, network platform, and practical education and mentoring.

• Journal of Digital Convergence
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• v.18 no.8
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• pp.37-48
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• 2020

This study aimed at understanding trends of living lab studies and deriving implications for directions of the studies by utilizing text mining. The study included network analysis and topic modelling based on keywords and abstracts from total 166 thesis published between 2011 and November 2019. Centrality analysis showed that living lab studies had been conducted focusing on keywords like innovation, society, technology, development, user and so on. From the topic modelling, 5 topics such as "regional innovation and user support", "social policy program of government", "smart city platform building", "technology innovation model of company" and "participation in system transformation" were extracted. Since the foundation of KNoLL in 2017, the diversification of living lab study subjects has been made. Quantitative analysis using text mining provides useful results for development of living lab studies.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.45-52
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• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.7
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• pp.169-177
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• 2015

This paper described a fuzzy comprehensive evaluation method and implemented assessment system for multi-layer decision making. The proposed method is a assessment before bidding through the key questions using fuzzy comprehensive evaluation method and the entropy weights. The key questions are given by the wider investigation of major sports event organizers. The paper carried out evaluation of single factor and fuzzy comprehensive evaluation from low layer to high layer step by step. In order to verify the effectiveness of proposed method, we built the sports event management service platform (SEMSP) for assessment of applicant city. This method represents a unified one of the quantitative results and the qualitative results based on the judgment of experts.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.25-31
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• 2019

Because of its physical characteristics, earthquake has a great impact on a wide area in a short time, so it needs a resilience based seismic countermeasures to restore the community function. For this reason, in this study, the seismic damages of urban buildings were assessed stochastically by virtual earthquakes using public data information and disaster management program(Ergo-EQ). A geographical map reflecting geological characteristics of the target area was created with the buildings and topographic data in Dalseo-gu, Daegu City. In addition, an integrated database including building characteristics was modified to be linked with the Ergo-EQ program. The seismic damages for the buildings were evaluated through the exceedance probability of four different damage levels. From the damage results, it can be identified not only the seismic damage of each building, but also the major factors affecting earthquake damage.

• Journal of Environmental Impact Assessment
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• v.32 no.5
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• pp.305-317
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• 2023

This study suggested a citizen science based model to enhance the efficacy of the managing invasive alien plants and examined whose applicability in 3 Wetland Protected Areas (Jangrok of Gwangju metropolitan city, Madongho of Goseong in South Gyeongsang Province, and Ungok of Gochang in North Jeolla Province). The process consists of (a) collecting citizen scientist including local residents of 3 protected areas and piling up information on the 4 species of invasive alien plants (Sicyos angulatus L., Solanum carolinense L., Ambrosia artemisiifolia L. and Solidago altissima L) in a information platform Ecological Information Bank (EcoBank) from September 18th to October 31th, (b) constructing distribution map containing the location and density (3 phases: individual-population-community) of target plants, (c) providing distribution map to Environment Agency and local government who is principal agent of managing invasive alien plants in 3 protected areas, and from whom (d) surveying applications of the distribution map and opinion for future supplement. As a result, citizen science based monitoring should be continued to complement the nationwide information for the field management of invasive alien plants with the expansion of target species (total 17 plants species that Ministry of Environment in South Korea designated) and period of monitoring in a year to increase the usability of surveyed information from citizen science. In the long run, effectiveness of the management of invasive alien species applied by citizen science should be reviewed including efficacy of field management process from citizen's participating in elimination project of invasive alien plants and time series distribution followed by the management of the species.

• Spatial Information Research
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• v.19 no.3
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• pp.83-93
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• 2011

Since urban facilities have a signigicant meaning that represents the degree of development of nations and cities, it is very important to effectively manage and operate the facilities. In this paper, we propose a context-awareness system for managing urban underground facilities intelligently and develop its algorithm and prototype. The algorithm of the suggested system includes the period from the point when various sensors set up in USN environments sense abnormal signals and make alarms to the point when the context-awareness system analyzes the alarm and sends the analysis results to integrated platform and related modules. We then implement the prototype of the proposed context awareness system and verify the effectiveness of the system by performing unit tests. Our developed prototype will become the basis of actual system development. We expect that the suggested system will be used as a good reference model of related systems managing various types of urban facilities.

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.15-27
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• 2020

Accurate knowledge of land use/land cover (LULC) features and their relative changes over upon the time are essential for sustainable urban management. Urban sprawl growth has been always also a worldwide concern that needs to carefully monitor particularly in a developing country where unplanned building constriction has been expanding at a high rate. Recently, remotely sensed imageries with a very high spatial/spectral resolution and state of the art machine learning approaches sent the urban classification and growth monitoring to a higher level. In this research, we classified the Quickbird satellite imagery by object-based image analysis of Dempster-Shafer (OBIA-DS) for the years of 2002 and 2015 at Karbala-Iraq. The real LULC changes including, residential sprawl expansion, amongst these years, were identified via change detection procedure. In accordance with extracted features of LULC and detected trend of urban pattern, the future LULC dynamic was simulated by using land transformation model (LTM) in geospatial information system (GIS) platform. Both classification and prediction stages were successfully validated using ground control points (GCPs) through accuracy assessment metric of Kappa coefficient that indicated 0.87 and 0.91 for 2002 and 2015 classification as well as 0.79 for prediction part. Detail results revealed a substantial growth in building over fifteen years that mostly replaced by agriculture and orchard field. The prediction scenario of LULC sprawl development for 2030 revealed a substantial decline in green and agriculture land as well as an extensive increment in build-up area especially at the countryside of the city without following the residential pattern standard. The proposed method helps urban decision-makers to identify the detail temporal-spatial growth pattern of highly populated cities like Karbala. Additionally, the results of this study can be considered as a probable future map in order to design enough future social services and amenities for the local inhabitants.