• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.1-6
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• 2020

Road movement pollutant air environment big data is a link between real-time traffic data such as vehicle type, speed, and load using AVC, VDS, WIM, and DTG, which are always traffic volume survey equipment, and road shape (uphill, downhill, turning section) data using GIS. It consists of traffic flow data. Also, unlike general data, a lot of data per unit time is generated and has various formats. In particular, since about 7.4 million cases/hour or more of large-scale real-time data collected as detailed traffic flow information are collected, stored and processed, a system that can efficiently process data is required. Therefore, in this study, an open source-based data parallel processing performance optimization study is conducted for the visualization of big data in the air environment of road transport pollution.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1495-1502
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• 2015

Dashboard camera is important system to store the variable data that not only video but also non-visual information that state of vehicle such as accelerometer, speed, direction. Non-visual information include variable data that can't visualization, so it used important evidence to figure out the situation in accident. It could be missed to non-visual information what can be prove the case in the just digital video forensic procedure. In this paper, We proposal the digital forensic analysis procedure for dashboard camera to all data in dashboard camera extract and analysis data for investigating traffic accident case. And I analyze to some products in with this digital forensic analysis procedure.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.4
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• pp.375-384
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• 2005

Three dimensional urban models are being increasingly applied for various purposes such as city planning, telecommunication cell planning, traffic analysis, environmental monitoring and disaster management. In recent years, technologies from CAD and GIS are being merged to find optimal solutions in three dimensional modeling of urban buildings. These solutions include modeling of the interior building space as well as its exterior shape visualization. Research and development effort in this area has been performed by scientists and engineers from Computer Graphics, CAD and GIS. Computer Graphics and CAD focussed on precise and efficient visualization, where as GIS emphasized on topology and spatial analysis. Complementary research effort is required for an effective model to serve both visualization and spatial analysis purposes. This study presents an efficient way of using the CAD plans included in the building register documents to reconstruct the internal space of buildings. Topological information was built in the geospatial database and merged with the geometric information of CAD plans. as well as other attributal data from the building register. The GIS network modeling method introduced in this study is expected to enable an effective 3 dimensional spatial analysis of building interior which is developing with increasing complexity and size.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.233-254
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• 2017

The purpose of this study is to analyze the main factors influencing the severity of traffic accidents and to visualize spatiotemporal characteristics of traffic accidents in Seoul. To do this, we collected the traffic accident data that occurred in Seoul for four years from 2012 to 2015, and classified as slight, serious, and death traffic accidents according to the severity of traffic accidents. The analysis of spatiotemporal characteristics of traffic accidents was performed by kernel density analysis, hotspot analysis, space time cube analysis, and Emerging HotSpot Analysis. The factors affecting the severity of traffic accidents were analyzed using decision tree model. The results show that traffic accidents in Seoul are more frequent in suburbs than in central areas. Especially, traffic accidents concentrated in some commercial and entertainment areas in Seocho and Gangnam, and the traffic accidents were more and more intense over time. In the case of death traffic accidents, there were statistically significant hotspot areas in Yeongdeungpo-gu, Guro-gu, Jongno-gu, Jung-gu and Seongbuk. However, hotspots of death traffic accidents by time zone resulted in different patterns. In terms of traffic accident severity, the type of accident is the most important factor. The type of the road, the type of the vehicle, the time of the traffic accident, and the type of the violation of the regulations were ranked in order of importance. Regarding decision rules that cause serious traffic accidents, in case of van or truck, there is a high probability that a serious traffic accident will occur at a place where the width of the road is wide and the vehicle speed is high. In case of bicycle, car, motorcycle or the others there is a high probability that a serious traffic accident will occur under the same circumstances in the dawn time.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1431-1438
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• 2014

We analyzed the articles from "Kukje Shinmun" and "Busan Ilbo", which are two local newpapers of Busan Metropolitan City. The articles cover from January 1, 2013 to December 31, 2013. Meaningful pattern inherent in 2889 articles of which the title includes "Busan" and "Traffic" and related data was analyzed. Textmining method, which is a part of datamining, was used for the social network analysis (SNA). HDFS and MapReduce (from Hadoop ecosystem), which is open-source framework based on JAVA, were used with Linux environment (Uubntu-12.04LTS) for the construction of unstructured data and the storage, process and the analysis of big data. We implemented new algorithm that shows better visualization compared with the default one from R package, by providing the color and thickness based on the weight from each node and line connecting the nodes.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.55-68
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• 2014

Some infrastructure these days is usually constructed under the ground for it to not interfere the foot-traffic of pedestrians, and thus, it is difficult to visually confirm the accurate location of the site where the establishments must be buried. These technical difficulties increase the magnitude of the problems that could arise from over-reliance on the experience of the worker or a mere blueprint. Such problems include exposure to flood and collapse. This paper proposes a constructor-oriented visualization system via mobile gadgets in general construction sites with occluded structures. This proposal is consisted with three stages. First, "Stage of detecting manhole and extracting features" detects and extracts the basis point of occluded structures which is unoccluded manhole. Next, "Stage of tracking features" tracks down the extracted features in the previous stage. Lastly, "Stage of visualizing occluded constructions" analyzes and synthesizes the GPS data and 3D objects obtained from mobile gadgets in the previous stages. This proposal implemented ideal method through parallel analysis of manhole detection, feature extraction, and tracking techniques in indoor environment, and confirmed the possibility through occluded water-pipe augmentation in real environment. Also, it offers a practical constructor-oriented environment derived from the augmented 3D results of occluded water-pipings.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1930-1936
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• 2007

Electronic Navigational Charts(ENCs) are official nautical charts which are equivalent to paper charts with supplementary information. Although their main purpose is to be used for the safe navigation of ships, they also contain much information on coasts and seas which may be interesting to ordinary people. However, there is no easy way to access them because of their specialized data format, access method and visualization. This paper proposes m implementation of SVG for the access and services of ENCs. SVG(Scalable Vector Graphic) makes it possible to make use of Vector graphics for map services in basic internet browsing environment. Implementation of SVG for ENC applications by this research is free of special server side GIS mapping system and client side extra technology. The Implementation of SVG for ENC Applications can be summarized as follows: Firstly, SVG provides spatial information to possess searching engine to embody SVG map. Secondly SVG can provide high-quality vector map graphics and interactive facility without special Internet GIS system. It makes it possible to use services with very low cost. Thirdly, SVG information service targeting on maritime transportation can be used as template, so it can be used dynamically any other purpose such as traffic management and vessel monitoring. Many good characteristics of SVG in mapping at computer screen and reusability of SVG document provide new era of visualization of marine geographic information.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.133-138
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• 2006

Electronic Navigational Charts(ENCs) are official nautical charts which are equivalent to paper charts with supplementary information. Although their main purpose is to be used for the safe navigation of ships, they also contain much information on coasts and seas which may be interesting to ordinary people. However, there is no easy way to access them because of therir specialized data format, access method and visualization. This paper proposes on implementation of SVG for the access and services of ENCs. SVG(Scalable Vector Graphic) makes it possible to make use of Vector graphics for servicing maps in basic internet browsing environment. Implement of SVG for ENC applications by this research is free of special server side GIS mapping system and client side extra technology. The implementation of SVG for ENC Applications can be summarized as follows: Firstly, SVG provides spatial information to possess searching engine to embody SVG map. Secondly, SVG can provide high-quality vector map graphics and interactive facility without special Internet GIS system. It makes it possible to use services with very low cost. Thirdly, SVG information service targeting on maritime transportation can be used as template, so it can be used dynamically any other purpose such as traffic management and vessel monitoring. Many good characteristics of SVG in mapping at computer screen and reusability of SVG document provide new era of visualization of marine geographic information.

• Journal of KIISE:Information Networking
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• v.36 no.3
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• pp.173-183
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• 2009

We present a real-time monitoring system for detecting anomalous network events using the entropy. The entropy accounts for the effects of disorder in the system. When an abnormal factor arises to agitate the current system the entropy must show an abrupt change. In this paper we deliberately model the Internet to measure the entropy. Packets flowing between these two networks may incur to sustain the current value. In the proposed system we keep track of the value of entropy in time to pinpoint the sudden changes in the value. The time-series data of entropy are transformed into the two-dimensional domains to help visually inspect the activities on the network. We examine the system using network traffic traces containing notorious worms and DoS attacks on the testbed. Furthermore, we compare our proposed system of time series forecasting method, such as EWMA, holt-winters, and PCA in terms of sensitive. The result suggests that our approach be able to detect anomalies with the fairly high accuracy. Our contributions are two folds: (1) highly sensitive detection of anomalies and (2) visualization of network activities to alert anomalies.