• Journal of KIISE:Computing Practices and Letters
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• v.5 no.6
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• pp.758-770
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• 1999

최근 급속한 네트워크 기술의 발달로 이들에 대한 관리의 필요성이 제기되었고 이를 위해 SNMP와 CMIP등과 같은 표준이 등장하여 사용되어 왔다. 그러나 점점 더 다양하고 복잡한 네트워크가 형성되자 이들에 대한 효율적인 관리가 필요하게 되었다. 현재, TMN은 개념에 있어서 보편성 및 가장 일반화된 관리개념이며 최종적으로 도달할 네트워크 관리 개념을 포함하고 있다. CORBA는 분산환경에서 응용프로그램을 쉽게 구현할 수 있는 기반을 제공하고 있다. 따라서 이러한 두 가지 기술을 접목한 CORBA와 TMN을 통합하고자 하는 많은 연구가 진행되고 있다. 본 논문에서는 현재의 CORBA/TMN 통합에 대한 연구를 바탕으로 효율적인 네트워크 통합 관리 구조를 정의하고 TMN의 기능중 Alarm Surveillance를 구조에 맞춰 구현하였다. 구현된 Alarm Surveillance System은 다양한 대리자들로부터 보고되는 여러 형태의 Alarm 정보에 대해, 처리 및 운용자에 대한 보고수행 등을 일관성 있게 처리하고 있는 것을 보여주고 있다. 따라서 제시된 Alarm Surveillance System은 사용자에게 일관성 있는 관리행위를 제공함으로써 다양한 관리구조가 적용된 복잡한 네트워크 관리를 제공할 수 있다. 또한 전체 네트워크로부터 필요한 통계분석을 위한 자료 수집 등의 편의를 제공할 것이다.Abstract Recently, due to the rapid development of network technology, the need for the network management appeared. So two representative standardards, SNMP and CMIP, have been applied to many network management system. But the more complex and vaious network are constructed, the demand for more efficient network management technology grew bigger. Currently, TMN technology is beginning to be widely applied to the management of networks. CORBA has been widely adopted for developing distributed systems in many areas of information technology. CORBA provides the infrastructure for the interoperability of various object-oriented management applications in a distributed environment, and, recently there have been world-wide research for the integration of CORBA within a TMN framework. Many attempts have been made to enable network management using CORBA techonology and some are working on already. This paper defines the architecture for integrated network management based on current CORBA/TMN integration technologies and then presents the design and implementation for alarm surveillance system which was applied to the defined architecture. The prototype implementation was done using IONA orbix. The proposed integrated network management framework will provide users with consistent management operations and ability to manage complex and various networks and to gather statistical data from those networks.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.329-334
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• 2018

Web services are standardized software technologies that enable interoperability of operating systems and programming languages through networks and related standards. Web services are distributed computing services that provide and discover services making it possible to access various services. Since the search method of web service considers only the functional aspect, it has a limitation on user-oriented search when selecting a service. In order to solve these problems, this study proposes an automatic IoT information generation tool, and provides IoT extension information when searching a web service, thereby improving the problem so that a suitable service can be selected for a user. Automatic IoT extension information generation tool proposed in this study collects and stores various information generated in the process of sensing, networking, and information processing by collaborating autonomously in a distributed environment of user, object, and service. The proposed method supports the service search suitable for the user by providing the information generated by the user as extended information when searching the web service. The proposed method can be applied to the 4th industry sector to provide a customized service that meets various environment requirements.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.313-322
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• 2020

The recognition of the risk hazards is a vital step to effectively prevent accidents on a construction site. The advanced development in computer vision systems and the availability of the large visual database related to construction site made it possible to take quick action in the event of human error and disaster situations that may occur during management supervision. Therefore, it is necessary to analyze the risk factors that need to be managed at the construction site and review appropriate and effective technical methods for each risk factor. This research focuses on analyzing Occupational Safety and Health Agency (OSHA) related to risk zone identification rules that can be adopted by the image recognition technology and classify their risk factors depending on the effective technical method. Therefore, this research developed a pattern-oriented classification of OSHA rules that can employ a large scale of safety hazard recognition. This research uses joint reasoning of risk zone Identification and numeric input by utilizing a stereo camera integrated with an image detection algorithm such as (YOLOv3) and Pyramid Stereo Matching Network (PSMNet). The research result identifies risk zones and raises alarm if a target object enters this zone. It also determines numerical information of a target, which recognizes the length, spacing, and angle of the target. Applying image detection joint logic algorithms might leverage the speed and accuracy of hazard detection due to merging more than one factor to prevent accidents in the job site.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.1C
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• pp.21-35
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• 2002

Nowadays, in accordance with increasing expectations of multimedia stream service on the internet, a lot of distributed applications are being required and developed. But the models of the existing systems have the problems that cannot support the extensibility and the reusability, when the QoS relating functions are being developed as an integrated modules which are suited on the centralized controlled specific-purpose application services. To cope with these problems, it is suggested in this paper to a distributed QoS management system on CORBA, an object-oriented middleware compliance. This systems we suggested can provides not only for efficient control of resources, various service QoS, and QoS control functions as the existing functions, but also QoS control real-time negotiation and dynamic adaptation in addition. This system consists of QoS Control Management Module(QoS CMM) in client side and QoS Management Module(QoS MM) in server side, respectively. These distributed modules are interfacing with each other via CORBA on different systems for distributed QoS management while serving distributed streaming applications. In phase of design of our system, we use UML(Unified Modeling Language) for designing each component in modules, their method calls and various detailed functions for controlling QoS of stream services. For implementation of our system, we used OrbixWeb 3.1c following CORBA specification on Solaris 2.5/2.7, Java language, Java Media Framework API 2.0 beta2, Mini-SQL 1.0.16 and the multimedia equipments, such as SunVideoPlus/Sun Video capture board and Sun Camera. Finally, we showed a numerical data controlled by real-time negotiation and adaptation procedures based on QoS map information to GUIs on client and server dynamically, while our distributed QoS management system is executing a given streaming service.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.31-59
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• 2007

We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.145-154
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• 2022

Automatic Target Recognition (ATR) technology is emerging as a core technology of Future Combat Systems (FCS). Conventional ATR is performed based on IMINT (image information) collected from the SAR sensor, and various image-based deep learning models are used. However, with the development of IT and sensing technology, even though data/information related to ATR is expanding to HUMINT (human information) and SIGINT (signal information), ATR still contains image oriented IMINT data only is being used. In complex and diversified battlefield situations, it is difficult to guarantee high-level ATR accuracy and generalization performance with image data alone. Therefore, we propose a knowledge graph-based ATR method that can utilize image and text data simultaneously in this paper. The main idea of the knowledge graph and deep model-based ATR method is to convert the ATR image and text into graphs according to the characteristics of each data, align it to the knowledge graph, and connect the heterogeneous ATR data through the knowledge graph. In order to convert the ATR image into a graph, an object-tag graph consisting of object tags as nodes is generated from the image by using the pre-trained image object recognition model and the vocabulary of the knowledge graph. On the other hand, the ATR text uses the pre-trained language model, TF-IDF, co-occurrence word graph, and the vocabulary of knowledge graph to generate a word graph composed of nodes with key vocabulary for the ATR. The generated two types of graphs are connected to the knowledge graph using the entity alignment model for improvement of the ATR performance from images and texts. To prove the superiority of the proposed method, 227 documents from web documents and 61,714 RDF triples from dbpedia were collected, and comparison experiments were performed on precision, recall, and f1-score in a perspective of the entity alignment..

• Journal of KIISE:Software and Applications
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• v.31 no.8
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• pp.1027-1042
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• 2004

A Software Component is a module that is reused among a lot of projects, systems, and companies rather than a single application. Components can be reused in various systems if they provide not only the common functionalities required in many applications but also the diverse aspects to be customized for being suitable for customers' demands. From the development phase, components should be designed and developed considering the variable aspects they have for convenient customization. Easily customized components can be frequently reused in lots of applications. In the literature, there are some modeling and customizing techniques. But they suggested only conceptual or basic methods based on Object-Oriented. And the practical instructions for reusing component were not provided sufficiently. Moreover, there are few techniques that consider the proper variability types components have. Thus, those techniques are not appropriate for applying to black box component completely developed and released. In this paper, we classify variabilities that components have in functional aspect into two categories. The one is logic variability, and the other is workflow variability. For each classified variability, we propose the three kind of modeling techniques, which are selection, plug in and externalization. Also detailed instructions for practical design and application are provided.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4B
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• pp.323-338
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• 2003

The main memory database systems (MMDBMS) efficiently supports various database applications that require high performance since it employs main memory rather than disk as a primary storage. Recently, it has been increased needs that have the fast data processing as well as the efficient modeling of application requiring for a complicated structure, and conformity to applications that need the strict dta consistency. In MMDBMS, because all the data is located in the main memory, it can support the usable expression methods of data satisfying their needs without performance overhead. The method has the operation to manipulate the data and the constraint such as referential integrity in more detail. The data model consists of this methods is an essential component to decide the expression power of DBMS. In this paper, we discuss about various requests to provide the communication services and propose the data model that support it. The mainly discussed issues are 1) definition of the relationship between tables using the pointer, 2) navigation of the data using the relationship, 3) support of the referential integrity for pointer, 4) support of the uniform processing time for the join, 5) support of the object-oriented concepts, and 6) sharing of an index on multi-tables. We discuss the pointer-based data model that designed to include these issues to efficiently support complication environments.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.4
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• pp.208-220
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• 2011

Korean traditional practice that gets a gravesite for burial and reckless grave establishment not only obstructs systematic national land management and reasonable urban development, but also causes a serious factor which has a harmful effect on natural environment and residential space in reality that our country is limited in area and national and social bases for use and establishment of graves are still inadequite. Though government and local governments have tried to cope with these problems by enacting legislation on funeral and others and so forth, they still have a variety of problems due to the shortage of grave management systems and information of accumulated individual graves. This study describes about the development of a GIS-based grave management system for making administrative management for individual cemeteries the prime object. As a result of application to a pilot area, the system developed in this study was able to be applied for supporting the time-limited burial system and managing cemeteries for those who left no relatives behind by constructing the database with grave-related position/attribute information which are collected by administrative system or direct survey. In addition, it is expected that this system will be utilized as a systematic management method that can be handed down the present or the future descendants under the tradition of the family-oriented funeral culture.

• The KIPS Transactions:PartD
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• v.8D no.2
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• pp.154-165
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• 2001

A number of attempts to develop methods for measuring software effort have been focused on the area of software engineering and many models have also been suggested to estimate the effort of software projects. Almost all current models use algorithmic or statistical mechanisms, but the existing algorithmic effort estimation models have failed to produce accurate estimates. Furthermore, they are unable to reflect the rapidly changing technical environment of software development such as module reuse, 4GL, CASE tool, etc. In addition, these models do not consider the paradigm shift of software engineering and information systems(i.e., Object Oriented system, Client-Server architecture, Internet/Intranet based system etc.). Thus, a new approach to software effort estimation is needed. After reviewing and analyzing the problems of the current estimation models, we have developed a model and a system architecture that will improve estimation performance. In this paper, we have adopted a neural network model to overcome some drawbacks and to increase estimation performance. We will also address the efficient system architecture and estimation procedure by a similar case-based approach and finally suggest the heuristic search method to find the best estimate of target project through empirical experiments. According to our experiment with the optimally parsimonious neural network model the mean error rate was significantly reduced to 14.3%.