• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1789-1804
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• 1999

This paper presents a simulation-based system for verification and validation(V&V) of design implication of the Visual Real-time Object Model which is produced by existing object's behavior design method. This system can simulate the dynamic interactions using the executable Ada simulation machine, and can detect various logical and temporal problems in the visual real-time object model prior to the real implementation of the application systems. Also, the system can generate the Ada prototype code from the validated specification. This system is implemented by Visual C++ version 4.2. For simulation, this system is using the Ada language because Ada's real-time expression capabilities such as concurrent processes, rendezvous, temporal behavior expression, and etc, are competent compared to other languages. This work contributes to a tightly coupling of methodology-based visual models and formal-based simulation systems, and also contributes to a realization of automated specification V&V.

• Korean Journal of Clinical Laboratory Science
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• v.54 no.2
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• pp.79-94
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• 2022

Due to the highly contagious nature and severity of the respiratory diseases caused by COVID-19, economical and accurate tests are required to better monitor and prevent the spread of this contagion. As the structural and molecular properties of SARS-CoV-2 were being revealed during the early stage of the COVID-19 pandemic, many manufacturers of COVID-19 diagnostic kits actively invested in the design, development, validation, verification, and implementation of diagnostic tests. Currently, diagnostic tests for SARS-CoV-2 are the most widely used and validated techniques for rapid antigen, and immuno-serological assays for specific IgG and IgM antibody tests and molecular diagnostic tests. Molecular diagnostic assays are the gold standard for direct detection of viral RNA in individuals suspected to be infected with SARS-CoV-2. Antibody-based serological tests are indirect tests applied to determine COVID-19 prevalence in the community and identify individuals who have obtained immunity. In the future, it is necessary to explore technical problems encountered in the early stages of global or regional outbreaks of pandemics and provide future directions for better diagnostic tests. This article evaluates the commercially available and FDA-approved molecular and immunological diagnostic assays and analyzes their performance characteristics.

• Nuclear Engineering and Technology
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• v.40 no.5
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• pp.397-408
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• 2008

This paper describes the application of a software fault tree analysis (FTA) as one of the analysis techniques for a software safety analysis (SSA) at the design phase and its analysis results for the safety-critical software of a digital reactor protection system, which is called the KNICS RPS, being developed in the KNICS (Korea Nuclear Instrumentation & Control Systems) project. The software modules in the design description were represented by function blocks (FBs), and the software FTA was performed based on the well-defined fault tree templates for the FBs. The SSA, which is part of the verification and validation (V&V) activities, was activated at each phase of the software lifecycle for the KNICS RPS. At the design phase, the software HAZOP (Hazard and Operability) and the software FTA were employed in the SSA in such a way that the software HAZOP was performed first and then the software FTA was applied. The software FTA was applied to some critical modules selected from the software HAZOP analysis.

• Advances in nano research
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• v.7 no.6
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• pp.419-429
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• 2019

The effect of an increasing percentage of nanofiller (glass cenosphere) with Glass/Epoxy hybrid composite curved panels modeled mathematically using the multiscale concept and subsequent numerical eigenvalues of different geometrical configurations (cylindrical, spherical, elliptical, hyperboloid and flat) predicted in this research article. The numerical model of Glass/Epoxy/Cenosphere is derived using the higher-order polynomial type of kinematic theory in association with isoparametric finite element technique. The multiscale mathematical model utilized for the customized computer code for the evaluation of the frequency data. The numerical model validation and consistency verified with experimental frequency data and convergence test including the experimental elastic properties. The experimental frequencies of the multiscale nano filler-reinforced composite are recorded through the impact hammer frequency test rig including CDAQ-9178 (National Instruments) and LABVIEW virtual programming. Finally, the nano cenosphere filler percentage and different design associated geometrical parameters on the natural frequency data of hybrid composite structural configurations are illustrated through a series of numerical examples.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.11a
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• pp.191-196
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• 1996

The potential value of the Application Specific Integrated Circuits(ASIC's) in safety systems of Nuclear Power Plants(NPP's) is being increasingly recognized because they are essentially hardwired circuitry on a chip, the reliability of the system can be proved more easily than that of software based systems which is difficult in point of software V&V(Verification and Validation). There are two types of ASIC, one is a full customized type, the other is a half customized type. PLD(Programmable Logic Device) used in this paper is a half customized ASIC which is a device consisting of blocks of logic connected with programmable interconnections that are customized in the package by end users. This paper describes the RPS(Reactor Protection System) composed of ASICs which provides emergency shutdown of the reactor to protect the core and the pressure boundary of RCS(Reactor Coolant System) in NPP's. The RPS is largely composed of five logic blocks, each of them was implemented in one PLD, as the followings. A). Bistable Logic B). Matrix Logic C).Initiation Logic D). MMI(Man Machine Interface) Logic E). Test Logic.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.500-503
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• 2016

소프트웨어의 개발 단계에서는 검증을 위한 V&V(Verification & Validation) 프로세스를 통해 체계적인 개발 활동이 가능하도록 지원하고 있다. 이에 반해 소프트웨어 요구사항 분석 이전에 수행되는 연구 단계는 그렇지 못하며, 또한 소프트웨어 연구 사업의 평가 시 구체적인 기준의 부재, 평가 시간과 수집된 자료의 부족 등의 문제가 제기 되었다. 따라서 본 논문에서는 연구자의 연구 활동과 연구 평가자의 연구 평가 활동을 지원하기 위해 소프트웨어 관련 국제 표준에서 추출한 요구사항을 바탕으로 하여 목표 구조, 평가 메트릭을 도출하고, 평가 시나리오와 그것을 해설해주는 가이드라인을 생성하는 방법을 제안한다. 우리의 연구는 연구 평가를 위한 메트릭 가이드라인인 라이덴 선언에 일부 부합하는 것을 확인하였다. 연구 결과는 연구 평가의 효율화와 자동화를 위한 향후 연구의 기초가 될 것이다.

• Journal of the Korean Society of Radiology
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• v.14 no.6
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• pp.773-780
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• 2020

With the development of the 4th industrial, research is being conducted to prevent diseases and reduce damage in various fields of science and technology such as medicine, health, and bio. As a result, artificial intelligence technology has been introduced and researched for image analysis of radiological examinations. In this paper, we will directly apply a deep learning model for classification and detection of pneumonia using chest X-ray images, and evaluate whether the deep learning model of the Inception series is a useful model for detecting pneumonia. As the experimental material, a chest X-ray image data set provided and shared free of charge by Kaggle was used, and out of the total 3,470 chest X-ray image data, it was classified into 1,870 training data sets, 1,100 validation data sets, and 500 test data sets. I did. As a result of the experiment, the result of metric evaluation of the Inception V3 deep learning model was 94.80% for accuracy, 97.24% for precision, 94.00% for recall, and 95.59 for F1 score. In addition, the accuracy of the final epoch for Inception V3 deep learning modeling was 94.91% for learning modeling and 89.68% for verification modeling for pneumonia detection and classification of chest X-ray images. For the evaluation of the loss function value, the learning modeling was 1.127% and the validation modeling was 4.603%. As a result, it was evaluated that the Inception V3 deep learning model is a very excellent deep learning model in extracting and classifying features of chest image data, and its learning state is also very good. As a result of matrix accuracy evaluation for test modeling, the accuracy of 96% for normal chest X-ray image data and 97% for pneumonia chest X-ray image data was proven. The deep learning model of the Inception series is considered to be a useful deep learning model for classification of chest diseases, and it is expected that it can also play an auxiliary role of human resources, so it is considered that it will be a solution to the problem of insufficient medical personnel. In the future, this study is expected to be presented as basic data for similar studies in the case of similar studies on the diagnosis of pneumonia using deep learning.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.75.2-76
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• 2021

MESSIER is a science satellite project to observe the Low Surface Brightness (LSB) sky at UV and optical wavelengths. The wide-field, optical system of MESSIER is optimized minimizing optical aberrations through the use of a Linear Astigmatism Free - Three Mirror System (LAF-TMS) combined with freeform mirrors. One of the key factors in observations of the LSB is the shape and spatial variability of the Point Spread Function (PSF) produced by scatterings and diffraction effects within the optical system and beyond (baffle). To assess the various factors affecting the PSF in this design, we use PhoSim, the Photon simulator, which is a fast photon Monte Carlo code designed to include all these effects, and also atmospheric effects (for ground-based telescopes) and phenomena occurring inside of the sensor. PhoSim provides very realistic simulations results and is suitable for simulations of very weak signals. Before the application to the MESSIER optics system, PhoSim had not been validated for confocal off-axis reflective optics (LAF-TMS). As a verification study for the LAF-TMS design, we apply Phosim sequentially. First, we use a single parabolic mirror system and compare the PSF results of the central field with the results from Zemax, CODE V, and the theoretical Airy pattern. We then test a confocal off-axis Cassegrain system and check PhoSim through cross-validation with CODE V. At the same time, we describe the shapes of the freeform mirrors with XY and Zernike polynomials. Finally, we will analyze the LAF-TMS design for the MESSIER optical system.

• Analytical Science and Technology
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• v.37 no.2
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• pp.98-113
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• 2024

The current investigation entails the characterization of five degradation products (DPs) formed under different stress conditions of loteprednol using liquid chromatography-tandem mass spectrometry (LC-MS/MS). In addition, this study developed a stable high-performance liquid chromatography (HPLC) method for evaluating loteprednol along with impurities. The method conditions were meticulously fine-tuned which involved the exploration of the appropriate solvent, pH, flow of the mobile phase, columns, and wavelength. The method conditions were carefully chosen to successfully resolve the impurities of loteprednol and were employed in subsequent validation procedures. The stability profile of loteprednol was exposed to stress degradation experiments conducted under five conditions, and DPs were structurally characterized by employing LC-MS/MS. The chromatographic resolution of loteprednol and its impurities along with DPs was effectively achieved using a Phenomenex Luna 250 mm C18 column using 0.1 % phosphoric acid, methanol, and acetonitrile in 45:25:30 (v/v) pumped isocratically at 0.8 mL/min with 243 nm wavelength. The method produces an accurate fit calibration curve in 50-300 ㎍/mL for loteprednol and LOQ (0.05 ㎍/mL) - 0.30 ㎍/mL for its impurities with acceptable precision, accuracy, and recovery. The stress-induced degradation study revealed the degradation of loteprednol under basic, acidic, and photolytic conditions, resulting in the formation of seven distinct DPs. The efficacy of this method was validated through LC-MS/MS, which allowed for the verification of the chemical structures of the newly generated DPs of loteprednol. This method was appropriate for assessing the impurities of loteprednol and can also be appropriate for structural and quantitative assessment of its degradation products.

• Journal of the Korean Society of Safety
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• v.27 no.5
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• pp.219-223
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• 2012

For an off-site consequence analysis at nuclear power plant, MELCOR Accident Consequence Code System(MACCS) II code is widely used as a software tool. In this study, the algorithm of web-based off-site consequence analysis program(OSCAP) using the MACCS II code was developed for an Integrated Leak Rate Test (ILRT) interval extension and Level 3 probabilistic safety assessment(PSA), and verification and validation(V&V) of the program was performed. The main input data for the MACCS II code are meteorological, population distribution and source term information. However, it requires lots of time and efforts to generate the main input data for an off-site consequence analysis using the MACCS II code. For example, the meteorological data are collected from each nuclear power site in real time, but the formats of the raw data collected are different from each site. To reduce the efforts and time for risk assessments, the web-based OSCAP has an automatic processing module which converts the format of the raw data collected from each site to the input data format of the MACCS II code. The program also provides an automatic function of converting the latest population data from Statistics Korea, the National Statistical Office, to the population distribution input data format of the MACCS II code. For the source term data, the program includes the release fraction of each source term category resulting from modular accident analysis program(MAAP) code analysis and the core inventory data from ORIGEN. These analysis results of each plant in Korea are stored in a database module of the web-based OSCAP, so the user can select the defaulted source term data of each plant without handling source term input data.