• Journal of Digital Contents Society
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• v.19 no.6
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• pp.1213-1218
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• 2018

Recently introduced Mask R - CNN presents a conceptually simple, flexible, general framework for instance segmentation of objects. In this paper, we propose an algorithm for efficiently searching objects of images, while creating a segmentation mask of heat generation part for an instance which is a heating element in a heat sensed image acquired from a thermal infrared camera. This method called a mask R - CNN is an algorithm that extends Faster R - CNN by adding a branch for predicting an object mask in parallel with an existing branch for recognition of a bounding box. The mask R - CNN is added to the high - speed R - CNN which training is easy and fast to execute. Also, it is easy to generalize the mask R - CNN to other tasks. In this research, we propose an infrared image detection algorithm based on R - CNN and detect heating elements which can not be distinguished by RGB images. As a result of the experiment, a heat-generating object which can not be discriminated from Mask R-CNN was detected normally.

• The Journal of Society for e-Business Studies
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• v.20 no.4
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• pp.41-59
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• 2015

Information systems has been developed and used in various business area, therefore there are abundance of history data (log data) stored, and subsequently, it is required to analyze those log data. Previous studies have been focusing on the discovering of relationship between events and no identification of anomaly instances. Previously, anomaly instances are treated as noise and simply ignored. However, this kind of anomaly instances can occur repeatedly. Hence, a new methodology to detect the anomaly instances is needed. In this paper, we propose a methodology of LAPID (Local Anomaly Process Instance Detection) for discriminating an anomalous process instance from the log data. We specified a distance metric from the activity relation matrix of each instance, and use it to detect API (Anomaly Process Instance). For verifying the suggested methodology, we discovered characteristics of exceptional situations from log data. To demonstrate our proposed methodology, we performed our experiment on real data from a domestic port terminal.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1802-1807
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• 2015

The cloud computing service provides physical IT resources to VM instances to users using virtual technique and the users pay cost of VM instances to service provider. The auction model based on cloud computing provides available resources of service provider to users through auction mechanism. The users bid spot instances to process their a job until its deadline time. If the bidding price of users is higher than the spot price, the user will be provided the spot instances by service provider. In this paper, we propose a new bidding strategy to minimize the total cost for job completion. Typically, the users propose bidding price as high as possible to get the spot instances and the spot price get high. we lower the spot price using proposed strategy and minimize the total cost for job completion. To evaluate the performance of our strategy, we compare the spot price and the total cost for job completion with real workload data.

• The Journal of Information Technology and Database
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• v.2 no.2
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• pp.25-34
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• 1995

In this paper, we present design philosophy and implementation issues of a functionality testing tool for object-oriented database systems. A testing tool has been developed to validate UniSQL/X functionalities with C++ interface. A testing tool is designed under consideration of scaleability, simplicity and extendibility. The schema is deliberately constructed to verify the object-oriented functionalities such as abstraction, inheritance and aggregation. Each test item has been derived under various black box techniques such as equivalent partitioning and boundary-value analysis. The testing tool consists of six phases, namely, database creation, database population, construction of testindex, compilation and link, execution and result reporting, and final cleanup. The prototype provides more than 140 test items at 90 programs.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.2
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• pp.429-436
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• 2018

Electronic documents are efficient to be created and managed, but they are liable to lose their originality because copies are created during distribution and delivery. For this reason, various security technologies for electronic documents have been applied. However, most security technologies currently used are for document management such as file access privilege control, file version and history management, and therefore can not be used in environments where authenticity is absolutely required, such as confidential documents. In this paper, we propose a method to detect document forgery and tampering through analysis of file system without installing an agent inside the instance operating system in cloud computing environment. BubbleDoc monitors the minimum amount of virtual volume storage in an instance, so it can efficiently detect forgery and tampering of documents. Experimental results show that the proposed technique has 0.16% disk read operation overhead when it is set to 1,000ms cycle for monitoring for document falsification and modulation detection.

• Journal of Internet Computing and Services
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• v.13 no.5
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• pp.33-43
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• 2012

Semantic web is utilized to construct advanced information service by using semantic relationships between entities. Text mining can be applied to generate semantic relationships from unstructured data resources. In this study, ontology schema guideline, ontology instance generation, disambiguation of same name by text mining and advanced historical people finding service by reasoning have been proposed. Various relationships between historical event, organization, people, which are created by domain experts, are linked to literatures of National Institute of Korean History (NIKH). It improves the effectiveness of user access and proposes advanced people finding service based on relationships. In order to distinguish between people with the same name, we compares the structure and edge, nodes of personal social network. To provide additional information, external resources including thesaurus and web are linked to all of internal related resources as well.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.165-171
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• 2013

Coding patterns that appeared frequently in the source code is a typical piece of code. The functionality that difficult to modularize, such as logging or synchronization processing, and the useful sentences in programming is extracted in software as codding pattern. Large-scale software could not be analyzed fully because the number of coding pattern that can be manually investigated is limited. In this paper, the characteristics of coding patterns perform the evaluation. The goal is to extract for codding-pattern to analyzed by developer. We was selected 6 indicators and performed analysis of 4 open-source. Matrix relations between the values and characteristics of the actual pattern analysis, pattern instances, the width of the distribution of instances, the pattern repeating structure of the elements included in the rates should be analyzed for patterns and indicators that help in choosing was confirmed.

• Journal of the Korean Society for Library and Information Science
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• v.32 no.3
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• pp.157-177
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• 1998

The 21st century will be the advanced Information society era. The management of very large quantity of electronic documents is important because new applications such as Digital Libraries, CSCW (Computer-Supported Cooperative Work) in Intranet, CALS (Commerce At the Light Speed) are emerging, which require the functionalities of efficient storing, searching and managing a bulk of electronic documents. SGML(Standard Generalized Markup Language) is an ISO Standard for representing structure information of electronic documents. This paper proposes an effective data model for storing and managing SGML documents. We also describe the design and implementation details of SGML document management system, which has capabilities of storing SGML instances, generating schema dynamically, and retrieving structure elements efficiently.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.3
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• pp.26-33
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• 2017

Recently container technologies have been receiving attention for efficient use of the cloud platform. Container virtualization technology has the advantage of a highly portable, high density when compared with the existing hypervisor. Container virtualization technology, however, uses a virtualization technology at the operating system level, which is shared by a single kernel to run multiple instances. For this reason, the feature of container is that the attacker can obtain the root privilege of the host operating system internal the container. Due to the characteristics of the container, the attacker can attack the root privilege of the host operating system in the container utilizing the vulnerability of the kernel. In this paper, we propose a framework for efficiently detecting and responding to root privilege attacks of a host operating system in a container. This framework uses a memory trap technique to detect changes in a specific memory area of a container and to suspend the operation of the container when it is detected.

• Convergence Security Journal
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• v.22 no.2
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• pp.21-26
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• 2022

Wearing face masks is an effective measure to prevent COVID-19 infection. Infrared thermal image based temperature measurement and identity recognition system has been widely used in many large enterprises and universities in China, so it is totally necessary to research the face mask detection of thermal infrared imaging. Recently introduced MTCNN (Multi-task Cascaded Convolutional Networks)presents a conceptually simple, flexible, general framework for instance segmentation of objects. In this paper, we propose an algorithm for efficiently searching objects of images, while creating a segmentation of heat generation part for an instance which is a heating element in a heat sensed image acquired from a thermal infrared camera. This method called a mask MTCNN is an algorithm that extends MTCNN by adding a branch for predicting an object mask in parallel with an existing branch for recognition of a bounding box. It is easy to generalize the R-CNN to other tasks. In this paper, we proposed an infrared image detection algorithm based on R-CNN and detect heating elements which can not be distinguished by RGB images.