• 시스템엔지니어링학술지
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• 제19권2호
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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.

• 한국컴퓨터정보학회논문지
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• 제15권8호
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• pp.23-30
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• 2010

플래시 메모리는 비휘발성이며 시스템에 전원이 없는 상태에서도 데이터를 유지할 수 있는 특성을 가지는 메모리이다. 게다가 빠른 접근 시간과 저전력 소비, 충격에 강하고, 작은 크기와 매우 가벼운 특성을 가진다. 가격이 점차 낮아 지고 용량이 증가함에 따라 플래시 메모리의 활용도는 가전제품, 내장형 시스템, 그리고 이동 단말기 등에 널리 사용되고 있는 추세이다. 이러한 플래시 메모리를 구동함에 있어서 필수적인 소프트웨어인 FLT이 필요하다. 본 연구에서는 기존의 블록 매핑 알고리즘의 가장 큰 단점을 극복하기 위한 새로운 FTL 알고리즘을 제안한다. 핵심적인 사항은 기존의 블록 매핑 테이블에 추가하여 작은 램 메모리를 이용하여 섹터 위치를 바로 알 수 있는 인텍스 블록 매핑 테이블을 제안하고자 한다. 시뮬레이션 결과에 따르면 제안된 FTL은기존의 하이브리드 매핑과 비교했을 때 수행 시간을 평균45%정도 줄이는 효과를 얻을 수 있었으며, 메모리 사상 요구량에 대해서 약 12% 줄이는 효과를 얻을 수 있었다.

• Journal of Advanced Marine Engineering and Technology
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• 제37권4호
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• pp.409-417
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• 2013

하이브리드 통신을 지원하는 하이브리드 통신 신호처리 제어보드는 저전력의 8-bit 마이크로콘트롤러인 ATxmega128A1으로 설계하였으며, 마이크로콘트롤러는 하이브리드 통신을 위한 모뎀과 GPS 모듈 등을 직렬 인터페이스하기 위해 8개의 UART 포트가 갖추어져 있으며, CLI(Command Line Interpreter) 프로그램은 각 포트의 인터페이스를 사용자 환경에 맞게 설정할 수 있으며, 내부에 2K 바이트의 프로그램 매개변수와 프로그램이 동작하는데 필요한 데이터를 저장할 수 있는 EEPROM과 128K 바이트의 플래시 메모리 및 프로그램이 실행되는 8K 바이트의 SRAM으로 구성되어 있다. 항로표지의 원격 관리를 VHF, CDMA, TRS 통신의 경로설정 최적화(Path Optimization) 기능을 갖는 하이브리드 통신을 이용하면 개별 통신 방식별로 음영지역이 존재하는 경우에도, 최적의 통신방식을 선택하여 통신을 수행하게 됨으로써, 통신 음영지역의 해소가 가능하다. 또한 통신장치마다 동일한 데이터 프레임을 사용함으로써 데이터의 호환성을 높였다. 실험은 30일 동안 각 부표에서 매 5분마다 데이터를 취득하였으며, 데이터 수신율은 99.4 % 이상을 보였다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
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• pp.1275-1281
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• 2011

Most of the railway traffic control systems are using in the DBMS(Database Management System)is a disk-based DBMS. When the train schedule and the event data is inputted and referred at real time on Disk-based DBMS, it is characteristic of the slow access time and the data is preserved permanently. For this reason, this paper suggests the way of improving for Railway Traffic Control System by the hybrid DBMS using a combination of memory and disk. We apply the Hybrid DBMS to Railway Traffic Control System and compare the existing method with suggested one using the same data. As a result of comparison, we have come to the conclusion that suggested method is far more performance to shorten data access time and process a mass information than the previous methods.

• 정보처리학회논문지A
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• 제11A권1호
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• pp.67-74
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• 2004

대부분의 병렬 알고리즘은 동기 알고리즘으로, 올바른 계산을 위해 작업을 일찍 끝낸 빠른 프로세서들은 동기점에서 느린 프로세서를 기다려야 하는데, 프로세서들의 성능이 다를 경우 연산 속도는 가장 느린 프로세서에 의해 결정된다. 본 논문에서는 거대 고유치 문제의 주요 고유쌍을 구하는 문제에 있어서 빠른 프로세서의 유휴 시간을 줄여 수렴 속도를 가속한 수 있는 동기/비동기 혼합 알고리즘을 고안하고 이를 MPMD 프로그래밍 방식을 사용하여 구현하였다.

• Structural Engineering and Mechanics
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• 제62권5호
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• pp.537-550
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• 2017

Structural sizing is a rewarding task due to its non-convex constrained nature in the design space. In order to provide both global exploration and proper search refinement, a hybrid method is developed here based on outstanding features of Evolutionary Computing and Teaching-Learning-Based Optimization. The new method introduces an observer phase for memory exploitation in addition to vector-sum movements in the original teacher and learner phases. Proper integer coding is suited and applied for structural size optimization together with a fly-to-boundary technique and an elitism strategy. Performance of the proposed method is further evaluated treating a number of truss examples compared with teaching-learning-based optimization. The results show enhanced capability of the method in efficient and stable convergence toward the optimum and effective capturing of high quality solutions in discrete structural sizing problems.

• 소음진동
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• 제2권4호
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• pp.265-272
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• 1992

The simplest method which has been used extensively for vibration analysis is the transfer matrix method introduced by Myklestad and was later extended by many researchers. The crude approximation results in considerable error on the predicted natural frequencies and to increase the accuracy the number of elements used in the analysis must be increased. In addition, numerical instability can occur as a result of matrix multiplication. Also the main disadvantage of the finite element method is the large computer memory requirements for complex systems. The new method proposed in this paper combines the transfer matrix and finite dynamic element techniques to form a powerful algorithm for vibration analysis of rotor system. It is shown that the accuracy improves significantly when the transfer matrix for each segment is obtained from finite dynamic element techniques.

• ETRI Journal
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• 제45권3호
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• pp.433-447
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• 2023

Critical issues such as connection congestion, long transmission delay, and packet loss become even worse during epidemic, disaster, and so on. In this study, a link load balancing method is proposed to address these issues on the data plane, a plane of the software-defined network (SDN) architecture. These problems are NP-complete, so a meta-heuristic approach, discrete particle swarm optimization, is used with a novel hybrid cost function. The superiority of the proposed method over existing methods in the literature is that it provides link and switch load balancing simultaneously. The goal is to choose a path that minimizes the connection load between the source and destination in multipath SDNs. Furthermore, the proposed work is dynamic, so selected paths are regularly updated. Simulation results prove that with the proposed method, streams reach the target with minimum time, no loss, low power consumption, and low memory usage.

• Journal of Information Processing Systems
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• 제20권2호
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• pp.159-172
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• 2024

The number of healthcare products available for pets has increased in recent times, which has prompted active research into wearable devices for pets. However, the data collected through such devices are limited by outliers and missing values owing to the anomalous and irregular characteristics of pets. Hence, we propose pet behavior recognition based on a hybrid one-dimensional convolutional neural network (CNN) and long short- term memory (LSTM) model using pet wearable devices. An Arduino-based pet wearable device was first fabricated to collect data for behavior recognition, where gyroscope and accelerometer values were collected using the device. Then, data augmentation was performed after replacing any missing values and outliers via preprocessing. At this time, the behaviors were classified into five types. To prevent bias from specific actions in the data augmentation, the number of datasets was compared and balanced, and CNN-LSTM-based deep learning was performed. The five subdivided behaviors and overall performance were then evaluated, and the overall accuracy of behavior recognition was found to be about 88.76%.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권9호
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• pp.531-538
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• 2005

This paper proposes an expert system which is able to enhance the accuracy and productivity by determining the test strategy based on heuristic rules for test of the hybrid electronic circuit board producted massively in production line. The test heuristic rules are obtained from test system designer, test experts and experimental results. The guarding method separating the tested device with circumference circuit of the device is adopted to enhance the accuracy of measurements in the test of analog devices. This guarding method can reduce the error occurring due to the voltage drop in both the signal input line and the measuring line by utilizing heuristic rules considering the device impedance and the parallel impedance. Also, PSA(Parallel Signature Analysis) technique Is applied for test of the digital devices and circuits. In the PSA technique, the real-time test of the high integrated device is possible by minimizing the test time forcing n bit output stream from the tested device to LFSR continuously. It is implemented in Visual C++ computer language for the purpose of the implementation of the inference engine using the dynamic memory allocation technique, the interface with the electronic circuit database and the hardware direct control. Finally, the effectiveness of the builded expert system is proved by simulating the several faults occurring in the mounting process the electronic devices to the surface of PCB for a typical hybrid electronic board and by identifying the results.