• KIPS Transactions on Computer and Communication Systems
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• v.3 no.10
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• pp.383-392
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• 2014

The research for coatings is one of the most popular and active research in the polymer industry. For the coatings, electronics industry, medical and optical fields are growing more important. In particular, the trend is the increasing of the technical requirements for the performance and accuracy of the coatings by the development of automotive and electronic parts. In addition, the industry has a need of more intelligent and automated system in the industry is increasing by introduction of the IoT and big data analysis based on the environmental information and the context information. In this paper, we propose an optimization model for the design of experiments based coating formulation data objects using the Internet technologies and big data analytics. In this paper, the coating formulation was calculated based on the best data analysis is based on the experimental design, modify the operator with respect to the error caused based on the coating formulation used in the actual production site data and the corrected result data. Further optimization model to correct the reference value by leveraging big data analysis and Internet of things technology only existing coating formulation is applied as the reference data using a manufacturing environment and context information retrieval in color and quality, the most important factor in maintaining and was derived. Based on data obtained from an experiment and analysis is improving the accuracy of the combination data and making it possible to give a LOT shorter working hours per data. Also the data shortens the production time due to the reduction in the delivery time per treatment and It can contribute to cost reduction or the like defect rate reduced. Further, it is possible to obtain a standard data in the manufacturing process for the various models.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.885-901
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• 2021

This paper illustratesthe impact of the temporal gap between satellite images and targetsize in mesoscale atmospheric motion vector (AMV) algorithm. A test has been performed using GEO-KOMPSAT-2A (GK2A) rapid-scan data sets with a temporal gap varying between 2 and 10 minutes and a targetsize between 8×8 and 40×40. Resultsshow the variation of the number of AMVs produced, mean AMV speed, and validation scores as a function of temporal gap and target size. As a results, it was confirmed that the change in the number of vectors and the normalized root-mean squared vector difference (NRMSVD) became more pronounced when smaller targets are used. In addition, it was advantageous to use shorter temporal gap and smaller target size for the AMV calculation in the lower layer, where the average speed is low and the spatio-temporal scale of atmospheric phenomena is small. The temporal gap and the targetsize are closely related to the spatial and temporalscale of the atmospheric circulation to be observed with AMVs. Thus, selecting the target size and temporal gap for an optimum calculation of AMVsrequires considering them. This paper recommendsthat the optimized configuration to be used operationally for the near-real time analysis of mesoscale meteorological phenomena is 4-min temporal gap and 16×16 pixel target size, respectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.85-91
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• 2020

Recently, video-taping equipment such as CCTV have been seeing more use for crime prevention and general safety concerns. Since these video-taping equipment operates all throughout the day, the need for security personnel is lessened, and naturally costs incurred from managing such manpower should also decrease. However, technology currently used predominantly lacks self-sufficiency when given the task of searching for a specific object in the recorded video such as a person, and has to be done manually; current security-based video equipment is insufficient in an environment where real-time information retrieval is required. In this paper, we propose a technology that uses the latest deep-learning technology and OpenCV library to quickly search for a specific person in a video; the search is based on the clothing information that is inputted by the user and transmits the result in real time. We implemented our system to automatically recognize specific human objects in real time by using the YOLO library, whilst deep learning technology is used to classify human clothes into top/bottom clothes. Colors are also detected through the OpenCV library which are then all combined to identify the requested object. The system presented in this paper not only accurately and quickly recognizes a person object with a specific clothing, but also has a potential extensibility that can be used for other types of object recognition in a video surveillance system for various purposes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.433-435
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• 2022

In this paper, we introduce a computing resource standard metadata schema design plan for registering, retrieving, and managing computing resources used for research data analysis and utilization in the Korea Research Data Commons(KRDC). KRDC is a joint utilization system of research data and computing resources to maximize the sharing and utilization of research data. Computing resources refer to all resources in the computing environment, such as analysis infrastructure and analysis software, necessary to analyze and utilize research data used in the entire research process. The standard metadata schema for KRDC computing resource management is designed by considering common attributes for computing resource management and other attributes according to each computing resource feature. The standard metadata schema for computing resource management consists of a computing resource metadata schema and a computing resource provider metadata schema. In addition, the metadata schema of computing resources and providers was designed as a service schema and a system schema group according to their characteristics. The standard metadata schema designed in this paper is used for computing resource registration, retrieval, management, and workflow services for computing resource providers and computing resource users through the KRDC web service, and is designed in a scalable form for various computing resource links.

• Journal of KIISE:Databases
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• v.32 no.4
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• pp.452-472
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• 2005

We propose XIR-Branching, a novel method for processing partial match queries on heterogeneous XML documents using information retrieval(IR) techniques and novel instance join techniques. A partial match query is defined as the one having the descendent-or-self axis '//' in its path expression. In its general form, a partial match query has branch predicates forming branching paths. The objective of XIR-Branching is to efficiently support this type of queries for large-scale documents of heterogeneous schemas. XIR-Branching has its basis on the conventional schema-level methods using relational tables(e.g., XRel, XParent, XIR-Linear[21]) and significantly improves their efficiency and scalability using two techniques: an inverted index technique and a novel prefix match join. The former supports linear path expressions as the method used in XIR-Linear[21]. The latter supports branching path expressions, and allows for finding the result nodes more efficiently than containment joins used in the conventional methods. XIR-Linear shows the efficiency for linear path expressions, but does not handle branching path expressions. However, we have to handle branching path expressions for querying more in detail and general. The paper presents a novel method for handling branching path expressions. XIR-Branching reduces a candidate set for a query as a schema-level method and then, efficiently finds a final result set by using a novel prefix match join as an instance-level method. We compare the efficiency and scalability of XIR-Branching with those of XRel and XParent using XML documents crawled from the Internet. The results show that XIR-Branching is more efficient than both XRel and XParent by several orders of magnitude for linear path expressions, and by several factors for branching path expressions.

• Journal of Korea Multimedia Society
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• v.14 no.1
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• pp.54-75
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• 2011

PoC(Push-to-talk Over Cellular) is an integrated technology of group voice calls, video calls and internet based multimedia services. If a PoC user can not participate in the PoC session for various reasons such as an emergency situation, lack of battery capacity, then the user can use the PoC Box which has a similar functionality to the MM Box in the MMS(Multimedia Messaging Service). The RTSP(Real-Time Streaming Protocol) method is recommended to be used when there is a transmission session between the PoC box and a terminal. Since the existing VOD service uses a wired network, the packet size of RTSP-based VOD service is huge, however, the PoC service has wireless communication environments which have general characteristics to be used in RTSP method. Packet loss in a wired communication environments is relatively less than that in wireless communication environment, therefore, a buffering latency occurs in PoC service due to a play-out delay which means an asynchronous play of audio & video contents. Those problems make a user to be difficult to find the information they want when the media contents are played-out. In this paper, the following techniques and methods were proposed and their performance and superiority were verified through testing: cross-over dual reception buffering technique, advance partition multi-reception buffering technique, and on-demand multi-reception buffering technique, which are designed for effective picking up of information in media content being transmitted in short amount of time using RTSP when a user searches for media, as well as for reduction in playback delay; and same-priority packetization transmission method and priority-based packetization transmission method, which are media data packetization methods for transmission. From the simulation of functional evaluation, we could find that the proposed multiple receiving buffering and packetizing methods are superior, with respect to the media retrieval inclination, to the existing single receiving buffering method by 6-9 points from the viewpoint of effectiveness and excellence. Among them, especially, on-demand multiple receiving buffering technology with same-priority packetization transmission method is able to manage the media search inclination promptly to the requests of users by showing superiority of 3-24 points above compared to other combination methods. In addition, users could find the information they want much quickly since large amount of informations are received in a focused media retrieval period within a short time.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.183-194
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• 2004

The existing management job of research expenses has been divided into three parts： budget planning, budget draw-up, and exact settlement of budget. However, it caused some problems. Under this current circumstance it is required to obtain research expenses steadily, to operate efficiently and to use them clearly to solve such problems. As a result of a study on data warehouse development process of existing system integration company (Inmon, IBM) to reflect current trend described above, data warehouse development process of Inmon uses systematic and gradual access as a classical development cycle method. It causes overlap and feedback to the previous step in the process of each step Is requested. And another problem that it is difficult to toil what function refers and corrects data because functions and data are separated during performing development process at data warehouse development process of IBM is caused. Integrated management data warehouse development process of research expenses in the enterprise environment which applies UML at planning and analysis step, design step and implement and test step is suggested in this paper. Information retrieval agent uses existing budget plan DB, budget draw-up DB and budget settlement DB to find out information that a user wants to know. Information retrieval agent collects and saves information at integration database and information integration agent extracts, transports, transforms and loads the data. Information integration agent reduces a user's efforts to access to a number of information sources and check each of them. It also screens out data that a user may not need. As a result, integrated management data warehouse development process of research expenses in the enterprise environment reflects a user's requirements as much as possible and provides various types of information to make a decision which is needed to establish the policy of research expense management. It helps an end user approach his/her desired analysis information quickly and get various data from the comprehensive viewpoint rather than the fragmentary viewpoint. Furthermore, as it integrated three systems into one, it is possible to share data, to integrate the system, to reduce operating expenses and to simplify supporting environment for the decision making.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.137-152
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• 2012

In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.

• Journal of Digital Convergence
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• v.15 no.11
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• pp.261-269
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• 2017

The purpose of this paper is to provide a search system using a method of accessing the web in real time without using a database server in order to guarantee the up-to-date information in a single network, rather than using a plurality of bots connected by a wide area network Design. The method of the research is to design and analyze the system which can search the person and keyword quickly and accurately in crepe system. In the crepe server, when the user registers information, the body tag matching conversion process stores all the information as it is, since various styles are applied to each user, such as a font, a font size, and a color. The crepe server does not cause a problem of body tag matching. However, when executing the crepe retrieval system, the style and characteristics of users can not be formalized. This problem can be solved by using the html_img_parser function and the Go language html parser package. By applying queues and multiple threads to a general-purpose web crawler, rather than a web crawler design that targets a specific site, it is possible to utilize a multiplier that quickly and efficiently searches and collects various web sites in various applications.

• Journal of Internet Computing and Services
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• v.16 no.3
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• pp.59-69
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• 2015

Many users visit websites every day to perform information retrieval, shopping, and community activities. On the other hand, there is intense competition among sites which attempt to profit from the Internet users. Thus, the owners or marketing officers of each site try to design a variety of marketing strategies including cooperation with other sites. Through such cooperation, a site can share customers' information, mileage points, and hyperlinks with other sites. To create effective cooperation, it is crucial to choose an appropriate partner site that may have many potential customers. Unfortunately, it is exceedingly difficult to identify such an appropriate partner among the vast number of sites. In this paper, therefore, we devise a new methodology for recommending appropriate partner sites to each site. For this purpose, we perform site clustering from the perspective of visitors' similarities, and then identify a group of sites that has a number of common customers. We then analyze the potential for the practical use of the proposed methodology through its application to approximately 140 million actual site browsing histories.