• Title/Summary/Keyword: Detector Optimization

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Calculation of Detector Positions for a Source Localizing Radiation Portal Monitor System Using a Modified Iterative Genetic Algorithm

  • Jeon, Byoungil;Kim, Jongyul;Lim, Kiseo;Choi, Younghyun;Moon, Myungkook
    • Journal of Radiation Protection and Research
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    • v.42 no.4
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    • pp.212-221
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    • 2017
  • Background: This study aims to calculate detector positions as a design of a radioactive source localizing radiation portal monitor (RPM) system using an improved genetic algorithm. Materials and Methods: To calculate of detector positions for a source localizing RPM system optimization problem is defined. To solve the problem, a modified iterative genetic algorithm (MIGA) is developed. In general, a genetic algorithm (GA) finds a globally optimal solution with a high probability, but it is not perfect at all times. To increase the probability to find globally optimal solution rather, a MIGA is designed by supplementing the iteration, competition, and verification with GA. For an optimization problem that is defined to find detector positions that maximizes differences of detector signals, a localization method is derived by modifying the inverse radiation transport model, and realistic parameter information is suggested. Results and Discussion: To compare the MIGA and GA, both algorithms are implemented in a MATLAB environment. The performance of the GA and MIGA and that of the procedures supplemented in the MIGA are analyzed by computer simulations. The results show that the iteration, competition, and verification procedures help to search for globally optimal solutions. Further, the MIGA is more robust against falling into local minima and finds a more reliably optimal result than the GA. Conclusion: The positions of the detectors on an RPM for radioactive source localization are optimized using the MIGA. To increase the contrast of the measurements from each detector, a relationship between the source and the detectors is derived by modifying the inverse transport model. Realistic parameters are utilized for accurate simulations. Furthermore, the MIGA is developed to achieve a reliable solution. By utilizing results of this study, an RPM for radioactive source localization has been designed and will be fabricated soon.

Impulse Noise Removal Using Noise Detector and Total Variation Optimization (잡음 검출기와 총변량 최적화를 이용한 영상의 임펄스 잡음제거)

  • Lee Im-Geun
    • The Journal of the Korea Contents Association
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    • v.6 no.4
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    • pp.11-18
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    • 2006
  • A new algorithm for removing salt and pepper impulse noise in image using impulse noise detector and total variation optimization is presented. The proposed two types of noise detectors which are based on the adaptive median filter, can detect impulse noise with high accuracy while reducing the probability of detecting image details as impulses. And the detectors maintain its performance independent of noise density. For removing impulses, total variation optimization is applied only to those detected noise candidate to reduces unnecessary computation. The proposed approach successfully remove impulse noise while preserving image details.

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DIntrusion Detection in WSN with an Improved NSA Based on the DE-CMOP

  • Guo, Weipeng;Chen, Yonghong;Cai, Yiqiao;Wang, Tian;Tian, Hui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.11
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    • pp.5574-5591
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    • 2017
  • Inspired by the idea of Artificial Immune System, many researches of wireless sensor network (WSN) intrusion detection is based on the artificial intelligent system (AIS). However, a large number of generated detectors, black hole, overlap problem of NSA have impeded further used in WSN. In order to improve the anomaly detection performance for WSN, detector generation mechanism need to be improved. Therefore, in this paper, a Differential Evolution Constraint Multi-objective Optimization Problem based Negative Selection Algorithm (DE-CMOP based NSA) is proposed to optimize the distribution and effectiveness of the detector. By combining the constraint handling and multi-objective optimization technique, the algorithm is able to generate the detector set with maximized coverage of non-self space and minimized overlap among detectors. By employing differential evolution, the algorithm can reduce the black hole effectively. The experiment results show that our proposed scheme provides improved NSA algorithm in-terms, the detectors generated by the DE-CMOP based NSA more uniform with less overlap and minimum black hole, thus effectively improves the intrusion detection performance. At the same time, the new algorithm reduces the number of detectors which reduces the complexity of detection phase. Thus, this makes it suitable for intrusion detection in WSN.

Design and Manufacture of an Electron Detector for Scanning Electron Microscope (주사전자현미경용 전자검출기의 설계 및 제작)

  • Jeon, Jong-Up;Kim, Ji-Won
    • Journal of the Korean Society for Precision Engineering
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    • v.25 no.4
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    • pp.53-60
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    • 2008
  • Electron detectors used in scanning electron microscope accept electrons emitted from the specimen and convert them to an electrical signal that, after amplification, is used to modulate the gray-level intensities on a cathode ray tube, producing an image of the specimen. Electron detector is one of the key components dominating the performance of scanning electron microscope so that the development of electron detectors having high performance is indispensable to acquire high quality images using scanning electron microscope. In this paper, we designed and manufactured an electron detector and conducted a couple of image capture experiments using it. In particular, scintillator which generates light photons when it is struck by high-energy electrons was manufactured and experimental studies on the optimization of manufacturing condition was carried out. From experiments to evaluate the performance of our detector, it was verified that the performance of our detector is equivalent to or better than that of the conventional one.

IMPROVING REGIONAL OVERPOWER PROTECTION TRIP SET POINT VIA CHANNEL OPTIMIZATION

  • Kastanya, Doddy
    • Nuclear Engineering and Technology
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    • v.44 no.7
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    • pp.799-806
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    • 2012
  • In recent years, a new algorithm has been introduced to perform the regional overpower protection (ROP) detector layout optimization for $CANDU^{(R)}$ reactors. This algorithm is called DETPLASA. This algorithm has been shown to successfully come up with a detector layout which meets the target trip set point (TSP) value. Knowing that these ROP detectors are placed in a number of safety channels, one expects that there is an optimal placement of the candidate detectors into these channels. The objective of the present paper is to show that a slight improvement to the TSP value can be realized by optimizing the channelization of these ROP detectors. Depending on the size of the ROP system, based on numerical experiments performed in this study, the range of additional TSP improvement is from 0.16%FP (full power) to 0.56%FP.

Development of Analytical Model for Optimization of Dual Layer Phoswich Detector Length for PET

  • Chung Yong Hyun;Choi Yong;Choe Yearn Seong;Lee Kyung-Han;Kim Byung-Tae
    • Journal of Biomedical Engineering Research
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    • v.26 no.1
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    • pp.17-22
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    • 2005
  • Small animal PET using a dual layer phoswich detector has been developed to obtain high and uniform spatial resolution. In this study, a simple analytic model to optimize the lengths of a dual layer phoswich detector was derived and validated by Monte Carlo simulation. For a small animal PET scanner with a 10㎝ ring diameter, the optimal length of the phoswich detector consisting of various crystal materials, such as LSO and LuYAP, were calculated analytically and validated using GATE. The detector module consisted of 8×8 arrays of crystals, with each phoswich detector element having a 2㎜×2㎜ sensitive area. The total crystal length was fixed to 20㎜. The optimal lengths of the phoswich detector layers, as functions of the crystal materials and order, conveniently derived by the analytic equation, showed good agreement with those estimated by the time consuming simulation. The simple analytical model can be used for the fast and accurate design of an optimal phoswich detector for small animal PET to achieve high spatial resolution and uniformity.

Signal Detection Based on a Decreasing Exponential Function in Alpha-Stable Distributed Noise

  • Luo, Jinjun;Wang, Shilian;Zhang, Eryang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.1
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    • pp.269-286
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    • 2018
  • Signal detection in symmetric alpha-stable ($S{\alpha}S$) distributed noise is a challenging problem. This paper proposes a detector based on a decreasing exponential function (DEF). The DEF detector can effectively suppress the impulsive noise and achieve good performance in the presence of $S{\alpha}S$ noise. The analytical expressions of the detection and false alarm probabilities of the DEF detector are derived, and the parameter optimization for the detector is discussed. A performance analysis shows that the DEF detector has much lower computational complexity than the Gaussian kernelized energy detector (GKED), and it performs better than the latter in $S{\alpha}S$ noise with small characteristic exponent values. In addition, the DEF detector outperforms the fractional lower order moment (FLOM)-based detector in $S{\alpha}S$ noise for most characteristic exponent values with the same order of magnitude of computational complexity.

Optimization of Blind Adaptive Decorrelating PIC Detector Performance in DS-CDMA System

  • Sirijiamrat, S.;Benjangkaprasert, C.;Sangaroon, O.
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1962-1965
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    • 2004
  • In this paper, the new algorithm for blind adaptive decorrelating parallel interference canceller detector in direct-sequence code division multiple access (DS-CDMA) synchronous communication systems is proposed. The goal of this paper is to improve the performance of the blind adaptive decorrelating parallel interference cancellation detector (BAD/PIC). The proposed blind adaptive decorrelating detector is using optimum step-size technique bootstrap algorithm as an initial stage of PIC, which does not require a training sequence. Therefore, this algorithm has a superior view of utilizing bandwidth and reduces the complexity of computation of inversion cross-correlation matrix. The computer simulation results show that the bit error rate performance of the proposed algorithm for the new structure of detector is better than that of the other detectors such as matched filters, the conventional PIC, and the blind adaptive decorrelating PIC detector.

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Optimization of airborne alpha beta detection system modeling using MCNP simulation

  • Sung, Si Hyeong;Kim, Hee Reyoung
    • Nuclear Engineering and Technology
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    • v.52 no.4
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    • pp.841-845
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    • 2020
  • An airborne alpha beta detection system using passivated implanted planar silicon (PIPS) detector was modeled with the MCNP6 code and its resolution and detection efficiency were analyzed. Simulation of the resolution performed using the Gaussian energy broadening (GEB) function showed that the full width at half maximum (FWHM) of 35.214 keV for alpha particles was within 34-38 KeV, which is the FWHM range of the actual detector, and the FWHM of 15.1 keV for beta particles was constructed with a similar model to 17 keV, which is the FWHM range of an actual detector. In addition, the detection efficiency and the resolution were simulated according to the distance between the detector and the air filter. When the distance was decreased to 0.2 cm from 0.8 cm, the efficiency of the alpha and beta particles detection decreased from 5.33% to 4.89% and from 5.64% to 4.27%, respectively, and the FWHM of the alpha and beta particles improved from 40.9 KeV to 29.84 keV and 25.76 keV-13.27 keV, respectively.