• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.18-31
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• 2023

Exploring artificial intelligence and machine learning for nuclear safety has witnessed increased interest in recent years. To contribute to this area of research, a machine learning model capable of accurately predicting nuclear power plant response with minimal computational cost is proposed. To develop a robust machine learning model, the Best Estimate Plus Uncertainty (BEPU) approach was used to generate a database to train three models and select the best of the three. The BEPU analysis was performed by coupling Dakota platform with the best estimate thermal hydraulics code RELAP/SCDAPSIM/MOD 3.4. The Code Scaling Applicability and Uncertainty approach was adopted, along with Wilks' theorem to obtain a statistically representative sample that satisfies the USNRC 95/95 rule with 95% probability and 95% confidence level. The generated database was used to train three models based on Recurrent Neural Networks; specifically, Long Short-Term Memory, Gated Recurrent Unit, and a hybrid model with Long Short-Term Memory coupled to Convolutional Neural Network. In this paper, the System Engineering approach was utilized to identify requirements, stakeholders, and functional and physical architecture to develop this project and ensure success in verification and validation activities necessary to ensure the efficient development of ML meta-models capable of predicting of the nuclear power plant response.

• Korean Journal of Radiology
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• v.22 no.10
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• pp.1697-1707
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• 2021

The recent introduction of various high-dimensional modeling methods, such as radiomics and deep learning, has created a much greater diversity in modeling approaches for survival prediction (or, more generally, time-to-event prediction). The newness of the recent modeling approaches and unfamiliarity with the model outputs may confuse some researchers and practitioners about the evaluation of the performance of such models. Methodological literacy to critically appraise the performance evaluation of the models and, ideally, the ability to conduct such an evaluation would be needed for those who want to develop models or apply them in practice. This article intends to provide intuitive, conceptual, and practical explanations of the statistical methods for evaluating the performance of survival prediction models with minimal usage of mathematical descriptions. It covers from conventional to deep learning methods, and emphasis has been placed on recent modeling approaches. This review article includes straightforward explanations of C indices (Harrell's C index, etc.), time-dependent receiver operating characteristic curve analysis, calibration plot, other methods for evaluating the calibration performance, and Brier score.

• Korean Chemical Engineering Research
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• v.45 no.1
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• pp.67-72
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• 2007

An efficient method for identification of MIMO state space model has been developed by combining partial least squares (PLS) regression, balanced realization, and balanced truncation. In the developed method, a MIMO system is decomposed into multiple MISO systems each of which is represented by a high-order ARX model and the parameters of the ARX models are estimated by PLS. Then, MISO state space models for respective MISO ARX transfer function are found through realization and combined to a MIMO state space model. Finally, a minimal balanced MIMO state space model is obtained through balanced realization and truncation. The proposed method was applied to the design of model predictive control for temperature control of a high pressure $CO_2$ solubility measurement system.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.87-93
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• 2022

Since 99% of PCs operating in the defense domain use the Windows operating system, detection and response of Window-based malware is very important to keep the defense cyberspace safe. This paper proposes a model capable of detecting malware in a Windows PE (Portable Executable) format. The detection model was designed with an emphasis on rapid update of the training model to efficiently cope with rapidly increasing malware rather than the detection accuracy. Therefore, in order to improve the training speed, the detection model was designed based on a Bidirectional LSTM (Long Short Term Memory) network that can detect malware with minimal sequence data without complicated pre-processing. The experiment was conducted using the EMBER2018 dataset, As a result of training the model with feature sets consisting of three type of sequence data(Byte-Entropy Histogram, Byte Histogram, and String Distribution), accuracy of 90.79% was achieved. Meanwhile, it was confirmed that the training time was shortened to 1/4 compared to the existing detection model, enabling rapid update of the detection model to respond to new types of malware on the surge.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.2
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• pp.115-124
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• 2024

To detect and prevent structural damage caused by various loads on marine structures and ships, structural health monitoring procedure is essential. Estimating loads acting on the structures which are measured by sensors that are mounted properly are crucial for structural health monitoring. However, attaching an excessive number of sensors to the structure without consideration can be inefficient due to the high costs involved and the potential for inducing structural instability. In this study, we introduce a method to determine the optimal number of sensors and their optimized locations for strain measurement sensors, allowing for accurate load estimation throughout the structure using model expansion method. To estimate the loads exerted on the entire structure with minimal sensors, we construct a strain-load interpolation matrix using the strain mode shapes of the finite element (FE) model and select the optimal sensor locations by applying D-Optimal Design and the row exchange algorithm. Finally, we estimate the loads exerted on the entire structure using the model expansion method. To validate the proposed method, we compare the results obtained by applying the optimal sensor placement and model expansion method to an FE model subjected to arbitrary loads with the loads exerted on the entire FE model, demonstrating efficiency and accuracy.

• The Korean Journal of Applied Statistics
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• v.26 no.1
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• pp.151-162
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• 2013

Due to a growing demand for the second-hand product, especially for the expensive one, the warranty and maintenance policies for such products have been studied to improve the product reliability of late. In this paper we study a periodic maintenance model for the second-hand product which is purchased by the customer at the age of $x$. When purchased, the dealer provides a warranty of a fixed length during which the product is maintained periodically to reduce the failure rate of the product and thus, to improve the reliability after each maintenance is served. If a failure occurs between two successive maintenances, only minimal repair is conducted. As for the warranty policy, we adopt free non-renewing repair action on each failure, in addition to the periodic maintenance service during the warranty period. Thus, under the given warranty policy, all the maintenance and repair costs incurred during the warranty period are charged to the dealer. For the proposed periodic maintenance scheme, we formulate a cost model to evaluate the expected total cost charged to the dealer during the warranty period and derive an optimal upgrade level of the failure rate at each maintenance to minimize the expected total warranty cost from the perspective of the dealer. We also present numerical results for an optimal upgrade level based on the proposed methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.637-637
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• 1997

In this paper, format conversion filters are proposed, which have advantages in hardware implementation compared to the ones proposed in MPEG-4 Video Verification Model. since each coefficients of the proposed filters is constrained to have less than two non-zero digits in minimal signed digit representation, multiplication of input and the coefficient can be implemented by a single adder. As a result, the proposed filters have advantages in hardware complexity and speed, compared to the filters which are usually implemented by integer multiplier or carry save adders. Six kinds of filters are proposed in MPEG-4 Video Verification Model for size conversion of 2:1, 4:1, 5:3 and 5:6. We design 5 filters for the same purpose and compare the performance. The remaining one is very simple to implement. For comparing the filtering performance, we first compare the results of sine wave frequency conversion as an indirect but meaningful comparison. Second. We compute the PSNR of the images obtained from the proposed filters and the ones proposed by MPEG, with reference to the images obtained by using double precision arithmetic and high order filter. The results show that the performance of the proposed filters is almost the same as that of the filters proposed by MPEG. In conclusion, the peroformance of the proposed filters is comparable to that of the ones in MPEG-4, while requiring lower hardware complexity and providing high operating speed.

• Journal of radiological science and technology
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• v.37 no.3
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• pp.203-209
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• 2014

Usefulness and clinical availability for surgery efficiency were evaluated by conducting pre-operative planning with a model manufactured by desktop 3D printer by using clavicle CT image. The patient-customized clavicle fracture model was manufactured by desktop 3D printer of FDM wire laminated processing method by converting the CT image into STL file in Open Source DICOM Viewer Osirix. Also, the model of the original shape before damaged was restored and manufactured by Mirror technique based on STL file of not fractured clavicle of the other side by using the symmetry feature of the human body. For the model, the position and size, degree of the fracture was equally printed out. Using the clavicle model directly manufactured with low cost and less time in Department of Radiology is considered to be useful because it can reduce secondary damage during surgery and increase surgery efficiency with Minimal invasive percutaneous plate osteosynthesis(MIPO).

• Journal of Korea Game Society
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• v.4 no.1
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• pp.58-66
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• 2004

This paper uses counterexamples for solving reachability games. An objective. of the game we consider here is to find out a minimal path from an initial state to the goal state. We represent initial states and game rules as finite state model and the goal state as temporal logic formula. Then, model checking is used to determine whether the model satisfies the formula. In case the model does not satisfy the formula, model checking generates a counterexample that shows how to reach the goal state from an initial state. In this way, we solve many of small-sized Push Push games. However, we cannot handle larger-sized games due to the state explosion problem. To mitigate the problem, abstraction is used to reduce the state space to be che cked. As a result, unsolved games are solved with the abstraction technique we propose inthis paper.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.208-221
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• 2019

The inference for this research was concentrated on client's data protection in cloud computing i.e. data storages protection problems and how to limit unauthenticated access to info by developing access control model then accessible preparations were introduce after that an access control model was recommend. Cloud computing might refer as technology base on internet, having share, adaptable authority that might be utilized as organization by clients. Compositely cloud computing is software's and hardware's are conveying by internet as a service. It is a remarkable technology get well known because of minimal efforts, adaptability and versatility according to client's necessity. Regardless its prevalence large administration, propositions are reluctant to proceed onward cloud computing because of protection problems, particularly client's info protection. Management have communicated worries overs info protection as their classified and delicate info should be put away by specialist management at any areas all around. Several access models were accessible, yet those models do not satisfy the protection obligations as per services producers and cloud is always under assaults of hackers and data integrity, accessibility and protection were traded off. This research presented a model keep in aspect the requirement of services producers that upgrading the info protection in items of integrity, accessibility and security. The developed model helped the reluctant clients to effectively choosing to move on cloud while considerate the uncertainty related with cloud computing.