• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.155-162
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• 2016

In recent years, hoping the interaction of individuals and rather than software development process and tools, and customers want software that works first, rather than a comprehensive document, in cooperation with the customer, rather than the developer negotiate a contract, to each other stick to the plan I think even more so than the value that corresponds to the change. In view of this, software development is given the autonomy and motivation to project team rather than process-oriented and have a passion and vision and human relations oriented management approach is required. In recent years, increasing the productivity benefits of agile development processes, improved quality, efficiency and customer satisfaction as is demonstrated in the methodology selected to promote the project, attention was given to the experts. Contemporary demands with regard to the methodology chosen to meet your needs, in this paper in the organization, and to solve the problems of product-based Cross functional team proposed methodology Feature Team model, this model is an organizational Cross functional team and the team is not the outcome (product) basis, were examined for the model that points to progress the development across multiple product as a functional unit, value-plan through the driven agile technique-based model and proposed a difference. And the domain analysis, required extraction by conventional JAD (joint application development) meeting the targets for the object-oriented modeling, in modeling and organize, review, aware in advance and the UML Structure and Behavior Diagrams and proposed to proceed with the project.

• Journal of Navigation and Port Research
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• v.28 no.1
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• pp.9-16
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• 2004

The purpose of this study is to examine the algorithm of ship collision avoidance system and to improve its performance. The study on the algorithm of ship collision avoidance system have been carried out by many researchers. We can divide the study according to the adopted theory into two category such as 'collision risk calculation method' and 'risk area method'. It is not so difficult to find heir merit and demerit in the respective method. This study suggested newly modified model, which can overcome a limit in the two method. The suggested model is based on collision risk calculation method and suggests how to solve the threshold value problem, that is, one of the unsolved issues in collision risk calculation method. To solve that problem this study proposed new system under which the users can select appropriate threshold value according to environments such as traffic situations and weathers conditions. Simulation results of new model is schematized using 'risk area method'to examine the relationships between the two method. In addition, in case of 'collision risk method', when TCPA and DCPA are used to determine collision risk, a problem happens, that is, two ships become too close in their stem area, therefore, partial function of 'risk area method'is adopted to solve the problem in suggested model.

• Journal of Broadcast Engineering
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• v.25 no.1
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• pp.94-104
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• 2020

Currently media consumption over fixed/mobile Internet is mostly conducted by adaptive media streaming technology such as DASH (Dynamic Adaptive Streaming over HTTP), which is an ISO/IEC MPEG (Moving Picture Experts Group) standard, or some other technologies similar to DASH. All these heavily depend on the HTTP caches that ISPs (Internet Service Providers) are obliged to provide sufficiently to make sure fast enough Web services. As a result, as the number of media streaming users increases, ISPs' burden for HTTP cache has been greatly increased rather than CDN (Content Delivery Network) providers' server burden. Hence ISPs charge traffic cost to CDN providers to compensate for the increased cost of HTTP caches. Recently in order to reduce the traffic cost of CDN providers, P2P (Peer-to-Peer)-assisted DASH system was proposed and a peer selection algorithm that maximally reduces CDN provides' traffic cost was investigated for this system. This algorithm, however, tends to concentrate the burden upon the selected peer. This paper proposes a new peer selection algorithm that distributes the burden among multiple peers while maintaining the proper reduction level of the CDN providers' cost. Through implementation of the new algorithm in a Web-based media streaming system using WebRTC (Web Real-Time Communication) standard APIs, it demonstrates its effectiveness with experimental results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.1
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• pp.1-9
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• 2020

ABL (Airborne Bathymetric LiDAR) is an advanced survey technology that uses green lasers to simultaneously measure the water depths and oceanic topography in coastal and river areas. Seabed point cloud extraction is an essential prerequisite to further utilizing the ABL data for various geographic data processing and applications. Conventional seabed detection approaches often use return waveforms. However, their limited accessibility often limits the broad use of the bathymetric LiDAR (Light Detection And Ranging) data. Further, it is often questioned if the waveform-based seabed extraction is reliable enough to extract seabed. Therefore, there is a high demand to extract seabed from the point cloud using other sources of information, such as geometric information. This study aimed to assess the feasibility of a ground filtering method to seabed extraction from geo-referenced point cloud data by using CSF (Cloth Simulation Filtering) method. We conducted a preliminary experiment with the RIGEL VQ 880 bathymetric data, and the results show that the CSF algorithm can be effectively applied to the seabed point segmentation.

• Spatial Information Research
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• v.22 no.5
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• pp.9-18
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• 2014

According to the recent development of the ubiquitous computing environment, the use of spatio-temporal data from sensors with GPS is increasing, and studies on the Semantic Sensor Web using spatio-temporal data for providing different kinds of services are being actively conducted. Especially, the W3C developed the SSNO(Semantic Sensor Network Ontology) which uses sensor-related standards such as the SWE(Sensor Web Enablement) of OGC and defines classes and properties for expressing sensor data. Since these studies are available for the query processing about non-spatio-temporal sensor data, it is hard to apply them to spatio-temporal sensor data processing which uses spatio-temporal data types and operators. Therefore, in this paper, we developed the SWE based on SSNO which supports the spatio-temporal sensor data types and operators expanding spatial data types and operators in "OpenGIS Simple Feature Specification for SQL" by OGC. The system receives SensorML(Sensor Model Language) and O&M (Observations and Measurements) Schema and converts the data into SSNO. It also performs the efficient query processing which supports spatio-temporal operators and reasoning rules. In addition, we have proved that this system can be utilized for the web service by applying it to a virtual scenario.

• Journal of Intelligence and Information Systems
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• v.12 no.2
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• pp.125-144
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• 2006

The development of mobile applications is fast in recent years. However, nearly all applications are for messaging, financial, locating services based on simple interactions with mobile users because of the limited screen size, narrow network bandwidth, and low computing power. Processing an algorithm for supporting a group decision process on mobile devices becomes impossible. In this paper, we introduce the mobile-oriented simple interactive procedure for support a group decision making process. The interactive procedure is developed for multiple objective linear programming problems to help the group select a compromising solution in the mobile Internet environment. Our procedure lessens the burden of group decision makers, which is one of necessary conditions of the mobile environment. Only the partial weak order preferences of variables and objectives from group decision makers are enough for searching the best compromising solution. The methodology is designed to avoid any assumption about the shape or existence of the decision makers' utility function. For the purpose of the experimental study of the procedure, we developed a group decision support system in the mobile Internet environment, MOBIGSS and applied to an allocation problem of investor assets.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.173-193
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• 2010

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component-based software development to promote application interaction and integration within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web services repositories not only be well-structured but also provide efficient tools for an environment supporting reusable software components for both service providers and consumers. As the potential of Web services for service-oriented computing is becoming widely recognized, the demand for an integrated framework that facilitates service discovery and publishing is concomitantly growing. In our research, we propose a framework that facilitates Web service discovery and publishing by combining clustering techniques and leveraging the semantics of the XML-based service specification in WSDL files. We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the Web service domain. We have developed a Web service discovery tool based on the proposed approach using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web services repositories. We believe that both service providers and consumers in a service-oriented computing environment can benefit from our Web service discovery approach.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.11
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• pp.1169-1174
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• 2015

Risk-Risk-based inspection (RBI) has been developed in order to identify risky equipments that can cause major accidents or damages in large-scale plants. This assessment evaluates the equipment's risk, categorizes their priorities based on risk level, and then determines the urgency of their maintenance or allocates maintenance resources. An earlier version of the risk-based assessment software is already installed within the equipment management system; however, the assessment is based on examination by an inspector, and the results can be influenced by his subjective judgment, rather than assessment being based on failure probability. Moreover, the system is housed within a server, which limits the inspector's work space and time, and such a system can be used only on site. In this paper, the development of independent risk-based assessment software is introduced; this software calculates the failure probability by an analytical method, and analyzes the field inspection results, as well as inspection effectiveness. It can also operate on site, since it can be installed on an independent platform, and has the ability to generate an I/O function for the field inspection results regarding the period for an optimum maintenance cycle. This program will provide useful information not only to the field users who are participating in maintenance, but also to the engineers who need to decide whether to extend the lifecycle of the power machinery or replace only specific components.

• Journal of the Korea Society of Computer and Information
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• v.19 no.2
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• pp.193-200
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• 2014

Due to the advent of ubiquitous computing environment, it is becoming a part of our common life style. And tremendous information is cumulated rapidly. In these trends, it is becoming a very important technology to find out exact information in a large data to present users. Collaborative filtering is the method based on other users' preferences, can not only reflect exact attributes of user but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. In this paper, we propose clustering method by user's features based on SOM for predicting purchase pattern in u-Commerce. it is necessary for us to make the cluster with similarity by user's features to be able to reflect attributes of the customer information in order to find the items with same propensity in the cluster rapidly. The proposed makes the task of clustering to apply the variable of featured vector for the user's information and RFM factors based on purchase history data. To verify improved performance of proposing system, we make experiments with dataset collected in a cosmetic internet shopping mall.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.33-54
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• 2010

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component based software development to promote application interaction both within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web service repositories not only be well-structured but also provide efficient tools for developers to find reusable Web service components that meet their needs. As the potential of Web services for service-oriented computing is being widely recognized, the demand for effective Web service discovery mechanisms is concomitantly growing. A number of public Web service repositories have been proposed, but the Web service taxonomy generation has not been satisfactorily addressed. Unfortunately, most existing Web service taxonomies are either too rudimentary to be useful or too hard to be maintained. In this paper, we propose a Web service taxonomy generation framework that combines an artificial neural network based clustering techniques with descriptive label generating and leverages the semantics of the XML-based service specification in WSDL documents. We believe that this is one of the first attempts at applying data mining techniques in the Web service discovery domain. We have developed a prototype system based on the proposed framework using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web service repositories. We report on some preliminary results demonstrating the efficacy of the proposed approach.