• Journal of Magnetics
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• v.22 no.1
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• pp.34-42
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• 2017

Material defects in the Steam Generator Tubes (SGT) of sodium cooled fast breeder reactor (PFBR) can lead to leakage of water into sodium. The water and sodium reaction will lead to major accidents. Therefore, the examination of steam generator tubes for the early detection of defects is an important requirement for safety and economic considerations. In this work, the Magnetic Flux Leakage (MFL) based Non Destructive Testing (NDT) technique is used to perform the defect detection process. The rectangular notch defects on the outer surface of steam generator tubes are modeled using COMSOL multiphysics 4.3a software. The obtained MFL images are de-noised to improve the integrity of flaw related information. Grey Level Co-occurrence Matrix (GLCM) features are extracted from MFL images and taken as input parameter to train the neural network. A comparative study on characterization have been carried out using feed-forward back propagation (FFBP) and cascade-forward back propagation (CFBP) algorithms. The results of both algorithms are evaluated with Mean Square Error (MSE) as a prediction performance measure. The average percentage error for length, depth and width are also computed. The result shows that the feed-forward back propagation network model performs better in characterizing the defects.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.972-988
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• 2021

At present, DevOps environments are getting popular in software organizations due to better collaboration and software productivity over traditional software process models. Software artefacts in DevOps environments are vulnerable to frequent changes at any phase of the software development life cycle that create a continuous integration continuous delivery pipeline. Therefore, software artefact traceability management is challenging in DevOps environments due to the continual artefact changes; often it makes the artefacts to be inconsistent. The existing software traceability related research shows limitations such as being limited to few types of artefacts, lack of automation and inability to cope with continuous integrations. This paper attempts to overcome those challenges by providing traceability support for heterogeneous artefacts in DevOps environments using a prototype named SAT-Analyser. The novel contribution of this work is the proposed traceability process model consists of artefact change detection, change impact analysis, and change propagation. Moreover, this tool provides multi-user accessibility and is integrated with a prominent DevOps tool stack to enable collaborations. The case study analysis has shown high accuracy in SAT-Analyser generated results and have obtained positive feedback from industry DevOps practitioners for its efficacy.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.2
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• pp.95-101
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• 2020

In this paper, we consider a group testing (GT) framework which is to find a set of defective samples out of a large number of samples. To handle this framework, we propose a maximum product detection algorithm (MPDA) which is based on maximum a posteriori probability (MAP). The key idea of this algorithm exploits iterative detection to propagate belief to neighbor samples by exchanging marginal probabilities between samples and output results. The belief propagation algorithm as a conventional approach has been used to detect defective samples, but it has computational complexity to obtain the marginal probability in the output nodes which combine other marginal probabilities from the sample nodes. We show that the our proposed MPDA provides a benefit to reduce computational complexity up to 12% in runtime, while its performance is only slightly degraded compared to the belief propagation algorithm. And we verify the simulations to compare the difference of performance.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.4
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• pp.462-468
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• 2016

In this paper, we present the results of the numerical analysis employing CONWEP, LS-DYNA FSI(Fluid Structure Interaction), AUTODYN FSI, LS-DYNA ALE(Arbitrary Lagrange Eulerian) and combination of CONWEP and LS-DYNA ALE for blast door fracture and wave propagation through the tunnel by the external explosion. We compared the numerical analysis results with the subscale test data and selected combination of CONWEP and LS-DYNA ALE method as adequate data generation method for the FRM(Fast Running Model) software development. It is expected to save much time and costs by using the numerical simulation data for the various test conditions.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.235-245
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• 2011

Early criticality prediction models that determine whether a design entity is fault-prone or not are becoming more and more important as software development projects are getting larger. Effective predictions can reduce the system development cost and improve software quality by identifying trouble-spots at early phases and proper allocation of effort and resources. Many prediction models have been proposed using statistical and machine learning methods. This paper builds a prediction model using Support Vector Machine(SVM) which is one of the most popular modern classification methods and compares its prediction performance with a well-known prediction model, BackPropagation neural network Model(BPM). SVM is known to generalize well even in high dimensional spaces under small training data conditions. In prediction performance evaluation experiments, dimensionality reduction techniques for data set are not used because the dimension of input data is too small. Experimental results show that the prediction performance of SVM model is slightly better than that of BPM and polynomial kernel function achieves better performance than other SVM kernel functions.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1143-1155
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• 1999

셀룰러 방식의 이동통신 시스템에서 전파의 유효신호 도달범위를 예측하기 위해서는 전파전파 모델을 이용한 예측기법이 주로 사용된다. 그러나, 전파과정에서 주변 지형지물에 의해 발생하는 전파손실은 매우 복잡한 비선형적인 특성을 가지며 수식으로는 정확한 표현이 불가능하다. 본 논문에서는 신경회로망의 함수 근사화 능력을 이용하여 전파손실 예측모델을 생성하는 방법을 제안한다. 즉, 전파손실을 송수신 안테나간의 거리, 송신안테나의 특성, 장애물 투과영향, 회절특성, 도로, 수면에 의한 영향 등과 같은 전파환경 변수들의 함수로 가정하고, 신경회로망 학습을 통하여 함수를 근사화한다. 전파환경 변수들이 신경회로망 입력으로 사용되기 위해서는 3차원 지형도와 벡터지도를 이용하여 전파의 반사, 회절, 산란 등의 물리적인 특성이 고려된 특징 추출을 통해 정량적인 수치들을 계산한다. 이와 같이 얻어진 훈련데이타를 이용한 신경회로망 학습을 통해 전파손실 모델을 완성한다. 이 모델을 이용하여 서울 도심 지역의 실제 서비스 환경에 대한 타 모델과의 비교실험결과를 통해 제안하는 모델의 우수성을 보인다.Abstract In cellular mobile communication systems, wave propagation models are used in most cases to predict cell coverage. The amount of propagation loss induced by the obstacles in the propagation path, however, is a highly non-linear function, which cannot be easily represented mathematically. In this paper, we introduce the method of producing propagation loss prediction models by function approximation using neural networks. In this method, we assume the propagation loss is a function of the relevant parameters such as the distance from the base station antenna, the specification of the transmitter antenna, obstacle profile, diffraction effect, road, and water effect. The values of these parameters are produced from the field measurement data, 3D digital terrain maps, and vector maps as its inputs by a feature extraction process, which takes into account the physical characteristics of electromagnetic waves such as reflection, diffraction and scattering. The values produced are used as the input to the neural network, which are then trained to become the propagation loss prediction model. In the experimental study, we obtain a considerable amount of improvement over COST-231 model in the prediction accuracy using this model.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.135-144
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• 2022

Electromagnetic topology (EMT) technique is a method to analyze each component of the electromagnetic propagation environment and combine them in the form of a network in order to effectively model the complex propagation environment. In a typical commercial communication channel model, since the propagation environment is complex and difficult to predict, a probabilistic propagation channel model that utilizes an average solution, although with low accuracy, is used. However, modeling techniques using EMT technique are considered for application of propagation and coupling analysis of threat electromagnetic waves such as electromagnetic pulses, radio wave models used in electronic warfare, local communication channel models used in 5G and 6G communications that require relatively high accuracy electromagnetic wave propagation characteristics. This paper describes the effective implementation method, algorithm, and program implementation of the electromagnetic topology (EMT) method analyzed in the frequency domain. Also, a method of deriving a response in the time domain to an arbitrary applied signal source with respect to the EMT analysis result in the frequency domain will be discussed.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.133-138
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• 2011

In IP-based wireless sensor networks (WSNs), it might be necessary to distribute application updates to the sensor nodes in order to fix bugs or add new functionality. However, physical access to nodes is in many cases extremely limited following deployment. Therefore, network reprogramming protocols have recently emerged as a way to distribute application updates without requiring physical access to sensor nodes. In order to solve the network reprogramming problem over the air interface, this thesis presents a new scheme for new update code propagation using fragmentation scheme and network coding. The proposed code propagation method roughly shows reduced performance improvement in terms of the number of data exchange compared with the previously proposed pipelining scheme. Further, It is shows enhanced reliability for update code propagation and reduced overhead in terms of the number of data exchange. As a result, we can efficiently perform the software update from the viewpoint of speed, energy, and network congestion when the proposed code propagation system is applied. In addition, the proposed system solves overhearing problems of network coding such as the loss of original messages and decoding error using the predefined message. Therefore, our system allows a software update system to exchange reliable data in wireless sensor networks.

• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.622-632
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• 1999

As the complexity of software development is increasing due to networking, multimedia, and diverse system architecture, the need for effective software development methodology is increasing. Especially, due to software standard and internalization of software market, it is necessary to accept international quality such as ISO 9000-3. In addition, object oriented development methodology is required due to rapid propagation of OO technology and standardization. Recently, UML was accepted by the OMG as standard object-oriented modeling language for distributed environment. When we UML was accepted by the OMG as standard object-oriented modeling language for distributed environment. When we develop Java and CORBA-based software, often UML is applied to Java and CORBA-based projects. However, current structural or OMT-based object-oriented methodologies. In this paper, we proposed UML-based development and concrete guidelines for each phase in order to apply UML to software development practically and effectively. Also, we define the transition guidelines and semantics between various development tasks. In addition, the analysis and design techniques of user interface and system development techniques needed in Web application development are presented.

• Advances in Computational Design
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• v.4 no.2
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• pp.141-153
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• 2019

This research is comprised of virtually simulating behavior while experiencing low gravity effects in advance of real world testing in low gravity aboard Zero Gravity Corporation's (Zero-G) research aircraft (727-200F). The experiment simulated a drill rig penetrating a regolith simulant. Regolith is a layer of loose, heterogeneous superficial deposits covering solid rock on surfaces of the Earth' moon, asteroids and Mars. The behavior and propagation of space debris when drilled in low gravity was tested through simulations and visualization in a leading dynamic simulation software as well as discrete element modeling software and in preparation for comparing to real world results from flying the experiment aboard Zero-G. The study of outer space regolith could lead to deeper scientific knowledge of extra-terrestrial surfaces, which could lead us to breakthroughs with respect to space mining or in-situ resource utilization (ISRU). These studies aimed to test and evaluate the drilling process in low to zero gravity environments and to determine static stress analysis on the drill when tested in low gravity environments. These tests and simulations were conducted by a team from Texas A&M University's Department of Construction Science, the United States Air Force Academy's Department of Astronautical Engineering, and Crow Industries