• 대한기계학회논문집
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• 제16권1호
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• pp.156-161
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• 1992

본 연구에서는 이송축 직류 서보 모터의 전류신호와 NC정보를 이용해서 선삭 가공상태를 감시하는 시스템을 개발하였다. 모터 전류는 가공 부하의 상태를 잘 나 타내며, NC 장치에 내장되어 있기 때문에 신호 검출을 위한 별도의 센서가 필요 없어 서 공구가 수시로 바뀌는 NC작업 감시를 위한 유효한 신호이다. 또 NC 정보로부터 작업을 예측함으로써 감시 대상을 명확히 하고 신뢰성을 높이고자 하였다. 전체적인 감시 시스템의 프로그래밍 언어로는 C를 사용하여, 실시간 감시처리를 가능하게 하였 다.

• Journal of Radiation Protection and Research
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• 제29권1호
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• pp.41-48
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• 2004

A safety assessment code, called SAGE (Safety Assessment Groundwater Evaluation), has been developed to describe post-closure radionuclide releases and potential radiological doses for low- and intermediate-level radioactive waste (LILW) disposal in an engineered vault facility in Korea. The conceptual model implemented in the code is focused on the release of radionuclide from a gradually degrading engineered barrier system to an underlying unsaturated zone, thence to a saturated groundwater zone. The radionuclide transport equations are solved by spatially discretizing the disposal system into a series of compartments. Mass transfer between compartments is by diffusion/dispersion and advection. In all compartments, radionuclides ate decayed either as a single-member chain or as multi-member chains. The biosphere is represented as a set of steady-state, radionuclide-specific pathway dose conversion factors that are multiplied by the appropriate release rate from the far field for each pathway. The code has the capability to treat input parameters either deterministically or probabilistically. Parameter input is achieved through a user-friendly Graphical User Interface. An application is presented, which is compared against safety assessment results from the other computer codes, to benchmark the reliability of system-level conceptual modeling of the code.

• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 2002년도 Proceedings
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• pp.68-73
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• 2002

In standard teletherapy, a treatment plan is generated with the aid of a treatment planning system, but it is common to perform an independent monitor unit verification calculation (MUVC). In exact analogy, we propose and demonstrate that a simple and accurate MUVC in Intensity Modulated Radiotherapy (IMRT) is possible. We introduce a concept of Modified Clarkson Integration (MCI). In MCI, we exploit the rotational symmetry of scattering to simplify the dose calculation. For dose calculation along a central axis (CAX), we first replace the incident IMRT fluence by an azimuthally averaged fluence. Second, the Clarkson Integration is carried over annular sectors instead of over pie sectors. We wrote a computer code, implementing the MCI technique, in order to perform a MUVC for IMRT purposes. We applied the code to IMRT plans generated by CORVUS. The input to the code consists of CORVUS plan data (e.g., DMLC files, jaw settings, MU for each IMRT field, depth to isocenter for each IMRT field), and the output is dose contribution by individual IMRT field to the isocenter. The code uses measured beam data for Sc, Sp, TPR, (D/Mu)$\_$ref/ and includes effects from MLC transmission, and radiation field offset. On a 266 MHZ desktop computer, the code takes less than 15 sec to calculate a dose. The doses calculated with MCI algorithm agreed within +/- 3% with the doses calculated by CORVUS, which uses a 1cm x 1cm pencil beam in dose calculation. In the present version of MCI, skin contour variations and inhomogeneities were neglected.

• International Journal of Advanced Culture Technology
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• 제10권4호
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• pp.412-419
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• 2022

The amount of digital text data is growing exponentially, and many machine learning solutions are being used to monitor and manage this data. Artificial intelligence and machine learning are used in many areas of our daily lives, but the underlying processes and concepts are not easy for most people to understand. At a time when many experts are needed to run a machine learning solution, no-code machine learning tools are a good solution. No-code machine learning tools is a platform that enables machine learning functions to be performed without engineers or developers. The latest No-Code machine learning tools run in your browser, so you don't need to install any additional software, and the simple GUI interface makes them easy to use. Using these platforms can save you a lot of money and time because there is less skill and less code to write. No-Code machine learning tools make it easy to understand artificial intelligence and machine learning. In this paper, we examine No-Code machine learning tools and compare their features.

• 한국컴퓨터정보학회논문지
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• 제10권5호
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• pp.313-322
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• 2005

본 논문에서는 TMS302C6711을 기본 프로세서로 사용하는 DSP Starter Kit(DSK)를 이용하여 병렬신호처리시스템의 성능을 측정하는 성능 모니터를 구현하고 검증한다. 이 성능 모니터의 특징은 DSP/BIOS의 기능 및 실시간 데이터 전송을 위한 RTDX(Real Time Data Exchange)를 사용하여 DSP 작업부하, 메모리 이용률, 그리고 브릿지 트래픽 등과 같은 병렬신호처리시스템의 성능 평가 척도를 측정할 수 있다는 것이다. 시뮬레이션에서는 DSP 알고리즘에서 널리 사용하는 FFT, 2D FFT, Matrix Multiplication, Fir Filter를 사용한다. 하나의 웨이브 파일에서 각각 다른 주기와 데이터 크기, 버퍼크기에 따른 결과를 성능 모니터와 TI(Texas Instrument)사의 코드 컴포저 스투디오로 측정한다. 그리고 그 결과를 비교함으로써 본 논문에서 구현한 성능 모니터의 정확성을 검증한다.

• Journal of Radiation Protection and Research
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• 제36권4호
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• pp.200-208
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• 2011

Fluence monitor(F/M)는 조사 시편을 원자로의 노심에 넣은 후 방사화 된 조사 시편의 방사능을 측정한 후 역산하여 중성자의 선량을 계산하는 기법으로 원자로내의 중성자 분포를 조사하기 위하여 반드시 필요한 기술이다. 이 기술은 중성자에 대한 에너지 스펙트럼 측정이 간접적으로 가능하며, 현존하는 중성자 분포 측정 기법 중에서 우수한 정밀도를 지니고 있다. 하나로(HANARO)에서 수행하는 재료조사 시험에서의 중성자량 측정을 위하여 본 연구에서는 지름 0.1 mm, 길이 3 mm 미만의 질량 150~200 ${\mu}g$ 범위, 순도 99.9% 이상의 Fe, Ni, Ti 와이어를 F/M 시편으로 사용하였다. 이 시편은 알루미늄 캡슐에 봉입하여 30 MW 의 하나로 OR5공에 약 25일간 조사하였다. 조사를 마친 시편은 high purity germanium (HPGe) detector를 이용하여 감마선을 측정하였고, SAND-II code로 reaction rate와 중성자 cross-section등을 고려하여 fluence monitor 위치에서의 중성자 플루언스를 계산하였다. F/M이 장착 되었던 하나로 OR5공의 중성자 플루언스 값은 MCNP 코드를 이용하여 계산된 결과를 사용하였으며, SAND-II code로 장착된 F/M 위치에서의 중성자 플루언스를 계산하여 적용된 시편의 reaction에 따른 결과값의 차이를 비교 분석하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.894-899
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• 1991

GRAFCET is the program language for a sequential control and utilized in the description of sequence of a process. This study is to implement GRAFCET editor and compiler for personnel computer. The GRAFCET editor module is developed to use as menu-driven method based on the graphic screen and the graphic symbol. So, users can use it interactively. The GRAFCET compiler module analyzes the already drawed GRAFCET diagram, then translates it to Z80 assembly code. After generating Z80 machine code from assembly code, we can send the outputed machine code file to Z80 one-board computer through RS232C. We have developed the GRAFCET programming tool to utilize under IBM PC/AT with the VGA monitor, and it may be contribute to low cost automation system.

• 한국정밀공학회지
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• 제18권1호
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• pp.111-116
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• 2001

A practical scheme to reduce failure of the PCB(Printed Circuit Board) of a monitor is introduced using deformed mode shape under mechanical shock. When the monitor is given critical shock loads, cracks are commonly initiated at the tip of a hole on the PCB. Accordingly, a deformed mode shape of the PCB is obtained using a FEM code to define a weak point on the PCB under mechanical shock, and then the position and direction of the hole is determined to prevent the failure at the critical mode shape. Also, the stress intensity factor around the weak point on the PCB is calculated to check the possibility of fracture by normal tensile stress. In conclusion, present research is useful to assist the practical design of components-layout on the PCB.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권2호
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• pp.766-783
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• 2012

Recently, many malicious users have attacked web browsers using JavaScript code that can execute dynamic actions within the browsers. By forcing the browser to execute malicious JavaScript code, the attackers can steal personal information stored in the system, allow malware program downloads in the client's system, and so on. In order to reduce damage, malicious web pages must be located prior to general users accessing the infected pages. In this paper, a novel framework (JsSandbox) that can monitor and analyze the behavior of malicious JavaScript code using internal function hooking (IFH) is proposed. IFH is defined as the hooking of all functions in the modules using the debug information and extracting the parameter values. The use of IFH enables the monitoring of functions that API hooking cannot. JsSandbox was implemented based on a debugger engine, and some features were applied to detect and analyze malicious JavaScript code: detection of obfuscation, deobfuscation of the obfuscated string, detection of URLs related to redirection, and detection of exploit codes. Then, the proposed framework was analyzed for specific features, and the results demonstrate that JsSandbox can be applied to the analysis of the behavior of malicious web pages.

• Nuclear Engineering and Technology
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• 제44권4호
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• pp.393-404
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• 2012

After the Fukushima nuclear accident in 2011, there has been increasing concern regarding severe accidents in nuclear facilities. Severe accident scenarios are difficult for operators to monitor and identify. Therefore, accurate prediction of a severe accident is important in order to manage it appropriately in the unfavorable conditions. In this study, artificial intelligence (AI) techniques, such as support vector classification (SVC), probabilistic neural network (PNN), group method of data handling (GMDH), and fuzzy neural network (FNN), were used to monitor the major transient scenarios of a severe accident caused by three different initiating events, the hot-leg loss of coolant accident (LOCA), the cold-leg LOCA, and the steam generator tube rupture in pressurized water reactors (PWRs). The SVC and PNN models were used for the event classification. The GMDH and FNN models were employed to accurately predict the important timing representing severe accident scenarios. In addition, in order to verify the proposed algorithm, data from a number of numerical simulations were required in order to train the AI techniques due to the shortage of real LOCA data. The data was acquired by performing simulations using the MAAP4 code. The prediction accuracy of the three types of initiating events was sufficiently high to predict severe accident scenarios. Therefore, the AI techniques can be applied successfully in the identification and monitoring of severe accident scenarios in real PWRs.