• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.278-281
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• 2018

The early Web technology was to show text information through a browser. However, as web technology advances, it is possible to show large amounts of multimedia data through browsers. Web technologies are being applied in a variety of fields such as sensor network, hardware control, and data collection and analysis for big data and AI services. As a result, the standard has been prepared for the Internet of Things, which typically controls a sensor via HTTP communication and provides information to users, by installing a web browser on the interface of the Internet of Things. In addition, the recent development of web-assembly enabled 3D objects, virtual/enhancing real-world content that could not be run in web browsers through a native language of C-class. Factors that evaluate the performance of existing Web applications include performance, network resources, and security. However, since there are many areas in which web applications are applied, it is time to revisit and review these factors. In this thesis, we will conduct an analysis of the factors that assess the performance of a web application. We intend to establish an indicator of the development of web-based applications by reviewing the analysis of each element, its main points, and its needs to be supplemented.

• Korean Journal of Construction Engineering and Management
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• v.15 no.4
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• pp.11-19
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• 2014

Construction VE activities has occupies an important position as a key tool of the project in terms of budget and performance improvements. Reflecting this situation, VE application scope is being expanded than before. Thus, construction projects are required the continued research and development for effective use of construction VE. VE target choice method is the central part in the construction VE work. But, this has a problem with low utilization in practical terms. Accordingly, this study was developed the new methodology(PVTCM) for VE target selection of the construction VE work. Its contents are as follows: First, to analyze practical problem for VE target choice method through VE practical data. Second, to extract the high potential VE object based on the cost model and ideas similarity by excellent VE cases analysis. Third, to implement standardized VE object item by using affinity diagram for each construction type items. This research were conducted to experts interviews for comparison analysis with the cost model as one of a representative target selection method. As a result, proposed method were implemented significantly higher performance in terms of practical effectiveness than conventional method.

• The KIPS Transactions:PartD
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• v.11D no.6
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• pp.1247-1258
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• 2004

The LBS(Location-Based Service), which is based on individual's mobility, is required increasingly as mobile telecommunication and various infrastructures have developed rapidly. The technologies for LBS are location determination technology, service platform technology, contents provider technology and moving object database technology generally. Among these, service platform must be interoperable with location gate-way server and provide common function of billing, authentification, protect location information, privacy control, location trigger and intelligent acquisition and so on. The TTA(Telecommunications Technology Association) published specification that defines a standard protocol for safe and simple interface between LBS client and LBS platform and the OpenLS(Open Location Service) in OGC (Open GIS Consortium) released implementation specifications for providing Location based core services. In this paper, we implemented service platform for LBS which is able to interoperable with location gateway server and contents provider and is caracterized as follows. First, it could require and response location information from different types of location gateway server with same interface. Second, it complies with the standard interfaces with OpenLS 4 contents providers for core LBS. Third, it could provide location of wired phone as well as wireless mobile terminal compling with the standard protocol. Last, it could provide trajectorH information based past location as well as current location, because it is able to interoperable with moving object DBMS. This paper contributes to the construction and practical use of LBS by providing the method of implementation of service platform for LBS.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.635-645
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• 2007

Component technology has been widely accepted as an effective way for building software systems with reusable components, and Microsoft (MS) .NET is one of the recent representative component technologies. Model Driven Architecture (MDA) is a new development paradigm which generates software by transforming design models automatically and incrementally. Transformation of structural models in MDA has been successfully applied. However, transformation of dynamic models and pervasive services, such as transaction service, security service, synchronization service and object pooling are largely remains as an area for further research. The recent enterprise system has multi tier distributed architecture, and the functionality of early mentioned pervasive services is essential for this architecture. .NET platform can implement Component Object Model+ (COM+) component for supporting pervasive services by specify Attribute code. In this paper, we specify the functionalities of the COM+ component offering pervasive services, and then those functionalities are defined by UML profile. By using the profile, the Platform Specific Model (PSM) for .NET/C# is specified, and .NET components are automatically generated through our tool. The development productivity, extensibility, portability, and maintenance of software can be dramatically improved by using of the proposed methods.

• Journal of the Korean Geographical Society
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• v.38 no.6
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• pp.949-960
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• 2003

The marginal implicit price of air quality can be measured by taking a partial derivative of hedonic price function (HPF) with respect to the level of air quality. It has been pointed out that the size of the marginal implicit price varies with the use of different function forms, different estimation methods, and the different ways of measuring air quality level in estimating HPF. In addition to these factors, this study shows theoretically and empirically the way housing properties are represented on a digital map could differentiate the size of marginal implicit price of air quality when GIS is used to measure location attributes of the housing properties in the Korean apartment market. Furthermore, this study shows that the degree of difference in the marginal implicit price due to the manner in which housing properties are represented on a digital map can be larger than the degree of difference in the marginal implicit price due to using different function forms and estimation methods. The major implication from the results of this study is that one should carefully try diverse ways of representing housing properties in the Korean apartment market on a digital map in the process of estimating HPF, as he or she usually tries diverse function forms and estimation methods, to see if the value of the marginal implicit price of air quality varies substantially.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.593-603
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• 2010

Most spatial data acquisition systems employing a set of frame cameras may have suffered from their small fields of view and poor base-distance ratio. These limitations can be significantly reduced by employing an omni-directional camera that is capable of acquiring images in every direction. Bundle Block Adjustment (BBA) is one of the existing georeferencing methods to determine the exterior orientation parameters of two or more images. In this study, by extending the concept of the traditional BBA method, we attempt to develop a mathematical model of BBA for omni-directional images. The proposed mathematical model includes three main parts; observation equations based on the collinearity equations newly derived for omni-directional images, stochastic constraints imposed from GPS/INS data and GCPs. We also report the experimental results from the application of our proposed BBA to the real data obtained mainly in urban areas. With the different combinations of the constraints, we applied four different types of mathematical models. With the type where only GCPs are used as the constraints, the proposed BBA can provide the most accurate results, ${\pm}5cm$ of RMSE in the estimated ground point coordinates. In future, we plan to perform more sophisticated lens calibration for the omni-directional camera to improve the georeferencing accuracy of omni-directional images. These georeferenced omni-directional images can be effectively utilized for city modelling, particularly autonomous texture mapping for realistic street view.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.183-190
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• 2011

In this paper, we propose a prototype system for abnormal sound detection and identification which detects and recognizes the abnormal situations by means of analyzing audio information coming in real time from CCTV cameras under surveillance environment. The proposed system is composed of two layers: The first layer is an one-class support vector machine, i.e., support vector data description (SVDD) that performs rapid detection of abnormal situations and alerts to the manager. The second layer classifies the detected abnormal sound into predefined class such as 'gun', 'scream', 'siren', 'crash', 'bomb' via a sparse representation classifier (SRC) to cope with emergency situations. The proposed system is designed in a hierarchical manner via a mixture of SVDD and SRC, which has desired characteristics as follows: 1) By fast detecting abnormal sound using SVDD trained with only normal sound, it does not perform the unnecessary classification for normal sound. 2) It ensures a reliable system performance via a SRC that has been successfully applied in the field of face recognition. 3) With the intrinsic incremental learning capability of SRC, it can actively adapt itself to the change of a sound database. The experimental results with the qualitative analysis illustrate the efficiency of the proposed method.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.115-123
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• 2021

Pine nuts are Korea's representative nut forest products and profitable crops. However, pine nuts are harvested by climbing the trees themselves, thus the risk is high. In order to solve this problem, it is necessary to harvest pine nuts using a robot or an unmanned aerial vehicle(UAV). In this paper, we propose a deep learning based detection method for harvesting pine nut in UAV aerial images. For this, a video was recorded in a real pine forest using UAV, and a data augmentation technique was used to supplement a small number of data. As the data for 3D detection, Unity3D was used to model the virtual pine nut and the virtual environment, and the labeling was acquired using the 3D transformation method of the coordinate system. Deep learning algorithms for detection of pine nuts distribution area and 2D and 3D detection of pine nuts objects were used DeepLabV3+, YOLOv4, and CenterNet, respectively. As a result of the experiment, the detection rate of pine nuts distribution area was 82.15%, the 2D detection rate was 86.93%, and the 3D detection rate was 59.45%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.537-542
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• 2021

This paper improves the possibility of recognizing fast-moving objects through the YOLO (You Only Look Once) deep learning recognition model in an application environment for object recognition in images. The purpose was to study the method of collecting semantic data through processing. In the recognition model, the moving object recognition error was identified as unrecognized because of the difference between the frame rate of the camera and the moving speed of the object and a misrecognition due to the existence of a similar object in an environment adjacent to the object. To minimize the recognition errors by compensating for errors, such as unrecognized and misrecognized objects through the proposed data collection method, and applying vision processing technology for the causes of errors that may occur in images acquired for sports (tennis games) that can represent real similar environments. The effectiveness of effective secondary data collection was improved by research on methods and processing structures. Therefore, by applying the data collection method proposed in this study, ordinary people can collect and manage data to improve their health and athletic performance in the sports and health industry through the simple shooting of a smart-phone camera.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.463-476
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• 2022

After industrialization in the past, the automobile industry has continued to grow centered on internal combustion engines, but is facing a major change with the recent 4th industrial revolution. Most companies are preparing for the transition to electric vehicles and autonomous driving. Therefore, in this study, topic modeling was performed based on LDA algorithm by collecting 4,002 domestic papers and 68,372 overseas papers that contain keywords related to CASE (Connectivity, Autonomous, Sharing, Electrification), which represent future automobile trends. As a result of the analysis, it was found that domestic research mainly focuses on macroscopic aspects such as traffic infrastructure, urban traffic efficiency, and traffic policy. Through this, the government's technical support for MaaS (Mobility-as-a-Service) is required in the domestic shared car sector, and the need for data opening by means of transportation was presented. It is judged that these analysis results can be used as basic data for the future automobile industry.