• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.244-250
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• 2015

Survivability is avoidance and tolerance ability of combat systems for accomplishing mission in battle field. Therefore, the combat system has to protect or minimize any damage from threats. For this reason, many modeling and simulation based studies which analyze vulnerability of the combat system by threats, are in progress to improve survivability of the combat system. In this paper, we developed a 3D penetration analysis program for survivability analysis of combat system. To do this, we applied the penetration analysis equation to threat and protection performance of tank. Also we implemented simple tank models based on 3D CAD, and tested the developed program using the implemented tank models. As a result, we verified the developed program that is possible to analyze penetration by threat and protection performance of tank and to visualize its result, based on scenarios.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6297-6304
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• 2015

Nuclear power plant decommissioning has attracted attention according to the shutdown decision of Kori 1 which is Korea's first nuclear power plant. Nuclear power plant decommissioning is the one who never experienced ever in our country. So, its process is difficult and time-consuming. In addition, it is difficult to determine the decommissioning quantity. This study proposed the plan that can be used in quantity take-off for nuclear power plant decommissioning using BIM technology being utilized in recent construction industry. As a result, we suggested the method of BIM-based quantity take-off such as the selection decommissioning method and process, setting up of BIM modeling environment, establishment of OBS & WBS, integrated BIM modeling, the definition of quantity property. The proposed plan can be utilized usefully from when permanent stopping nuclear power plant occurs intensively. Furthermore, the overseas nuclear power plant decommissioning project order also are expected through technology securement based on this plan.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.2
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• pp.112-123
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• 2005

The latest E-commerce sites provide personalized services to maximize user satisfaction for Internet user The collaborative filtering is an algorithm for personalized item real-time recommendation. Various supplementary methods are provided for improving the accuracy of prediction and performance. It is important to consider these two things simultaneously to implement a useful recommendation system. However, established studies on collaborative filtering technique deal only with the matter of accuracy improvement and overlook the matter of performance. This study considers representative attribute-neighborhood, recommendation textile set, and similarity grouping that are expected to improve performance to the recommendation agent system. Ultimately, this paper suggests empirical applications to verify the adequacy and the validity on this system with the development of Fashion Design Recommendation Agent System (FDRAS ).

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.27 no.4
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• pp.303-312
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• 1991

This paper describes the general formulation for the in-plane flexural free vibration analysis of two layered structure by the transfer influence coefficient method. The structure is regared as a distributed mass system with lumped mass and inertia moments, massless linear and rotational springs, and joints elements of releases and rolls at which the displacements are discontinuous in each layer. The results of the simple numerical examples on a personal computer demonstrate the validity of the present method, that is, the numerical high accuracy, the high speed, the flexibility for programming of the present algorithm, compared with the transfer matrix method.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.12
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• pp.455-462
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• 2014

In recent years, various services in mobile environments due to the growth of mobile devices and related techniques like wireless networks. Furthermore, as the increasing communication traffic in cellular networks has become a new significant issue, many studies for device-to-device(D2D) communication and D2D-based cooperative services have been performed recently. In this paper, we design a smart agent system for D2D-based cooperative services and propose a dynamic service binding method based on service ontology. We classify roles of mobile devices for cooperative services by defining three types of smart agents, and construct a knowledge base in order to describe properties of 'service' unit. The proposed knowledge model, D2D cooperative service ontology, can enable a autonomous cooperative services between mobile devices by binding a requested service to the appropriate member device according to the real-time context in mobile environments.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.161-168
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• 2019

The purpose of this study analyze consumer usage characteristics and product development guide of electronic pen based on TAM theory(Davies, 1989). Research methods apply contents analysis(qualitative research) and Activity/Inactivity analysis of main consumer participation. Research results are as follows. Active consumer indicated 30-49 age, male, office job and research fellow. And they suggested stable power supply system, App connected pen function extension, add the modified pen function, advanced data recognition of pen, advanced take note ability and stable grip feeling of pen, selected line width, synchronization improvement with other smart device and charging function. These result indicated the importance product improvement diffusion factor of early market to main market. The future research of electric pen focused on different product strategy between electric pen and smart device connected electric pen.

• Journal of the Korea Society of Computer and Information
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• v.26 no.8
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• pp.229-237
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• 2021

This paper aims to study the using motivation and influencing factors of Chinese users' participation in live stream shopping through theoretical and empirical analysis, so as to evaluate the change in users' needs and improve marketing strategies. In doing so, I conducted a questionnaire survey for Chinese live stream shopping users and collected the required data. For empirical analysis, I used SPSS and AMOS software to carry out descriptive analysis, reliability and validity analysis and structural equation model analysis (SEM) to test the hypothesis. The results of the analysis showed that core competency and brand personality of the short video industry have a significant impact on user and customer perceived value, thus influencing users' using motivation. That is, users do not blindly follow live stream shopping but make their active choice. Therefore, it is suggested that live stream shopping platform should strengthen the e-commerce attributes and eradicate "the sense of false satisfaction", in order to achieve the effective communication of information. On the other hand, to stimulate the purchase motivation of users, the brand should build up its personality, and enhance user and customer perceived value in cyber marketing.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.5
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• pp.71-81
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• 2008

In the paper, we designed a context aware task-role based access control system(CAT-RACS) which can control access and prevent illegal access efficiently for various information systems in ubiquitous computing environment. CAT-RACS applied CA-TRBAC, which adds context-role concept for achieve policy composition by context information and security level attribute to be kept confidentiality of information. CA-TRBAC doesn't permit access when context isn't coincident with access control conditions, or role and task's security level aren't accord with object's security level or their level is a lower level, even if user's role and task are coincident with access control conditions. It provides security services of user authentication and access control, etc. by a context-aware security manager, and provides context-aware security services and manages context information needed in security policy configuration by a context information fusion manager. Also, it manages CA-TRBAC policy, user authentication policy, and security domain management policy by a security policy manager.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.533-539
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• 2020

Real-time service (RTS) provided by IGS provides correction for GNSS orbit and clock via internet, so it is widely used in fields that require real-time precise positioning. However, the RTS signal may be lost due to an unstable Internet environment. When signal disconnection occurs, signal prediction can be performed using polynomial models. However, the RTS changes rapidly after the GNSS navigation message issue of data (IOD) changes, so it is difficult to predict when signal loss occurs at that point. In this study, we proposed an algorithm to generate continuous RTS correction information by applying the difference in navigation trajectory according to IOD change. The use of this algorithm can improve the accuracy of RTS prediction at IOD changes. After performing optimization studies to improve RTS prediction performance, the predicted RTS trajectory information was applied to precision positioning (PPP). Compared to the conventional method, the position error is significantly reduced, and the error increase along with the signal loss interval increase is reduced.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1462-1468
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• 2022

Among the data used for the diagnosis of calf disease, feces play an important role in disease diagnosis. In the image of calf feces, the health status can be known by the shape, color, and texture. For the fecal image that can identify the health status, data of 207 normal calves and 158 calves with diarrhea were pre-processed according to fecal status and used. In this paper, images of fecal variables are detected among the collected calf data and images are trained by applying GLCM-CNN, which combines the properties of CNN and GLCM, on a dataset containing disease symptoms using convolutional network technology. There was a significant difference between CNN's 89.9% accuracy and GLCM-CNN, which showed 91.7% accuracy, and GLCM-CNN showed a high accuracy of 1.8%.