WorldWideScience

Sample records for based correlation detection

  1. Vehicle detection and tracking based on phase-correlation

    Institute of Scientific and Technical Information of China (English)

    Yi He(何毅); Xin Yang(杨新)

    2004-01-01

    This paper presents vehicle detection and tracking algorithms based on real-time background (RTB) and phase-correlation (PC) in the video sequence of urban highway with fixed camera. Firstly moving objects are obtained by subtracting RTB from serial images. After classification, PC is used to determine corresponding regions of moving objects between consecutive frames. The problems of vehicles' merging and splitting, sudden stop, and restart are also considered. Experiments show that the method is practical and can realize real-time detection and tracking of vehicles on highway.

  2. An Eavesdropping Detecting Approach Based on Mode-Mode Correlation

    Institute of Scientific and Technical Information of China (English)

    XIONG Jin; ZENG Gui-Hua; ZHOU Nan-Run

    2005-01-01

    @@ We find that second-order coherence as well as a Hanbury-Brown-Twiss intensity interferometer may provide an optimal approach for eavesdropping detection in the quantum key distribution based on two-mode squeezed'vacuum states. With this approach, eavesdropping can be easily detected without sacrificing extra secret bits as the test key. In addition, the efficiency of the quantum key distribution protocol is enhanced greatly.

  3. Correlation based efficient face recognition and color change detection

    Science.gov (United States)

    Elbouz, M.; Alfalou, A.; Brosseau, C.; Alam, M. S.; Qasmi, S.

    2013-01-01

    Identifying the human face via correlation is a topic attracting widespread interest. At the heart of this technique lies the comparison of an unknown target image to a known reference database of images. However, the color information in the target image remains notoriously difficult to interpret. In this paper, we report a new technique which: (i) is robust against illumination change, (ii) offers discrimination ability to detect color change between faces having similar shape, and (iii) is specifically designed to detect red colored stains (i.e. facial bleeding). We adopt the Vanderlugt correlator (VLC) architecture with a segmented phase filter and we decompose the color target image using normalized red, green, and blue (RGB), and hue, saturation, and value (HSV) scales. We propose a new strategy to effectively utilize color information in signatures for further increasing the discrimination ability. The proposed algorithm has been found to be very efficient for discriminating face subjects with different skin colors, and those having color stains in different areas of the facial image.

  4. Stochastic quantum Zeno-based detection of noise correlations

    Science.gov (United States)

    Müller, Matthias M.; Gherardini, Stefano; Caruso, Filippo

    2016-12-01

    A system under constant observation is practically freezed to the measurement subspace. If the system driving is a random classical field, the survival probability of the system in the subspace becomes a random variable described by the Stochastic Quantum Zeno Dynamics (SQZD) formalism. Here, we study the time and ensemble average of this random survival probability and demonstrate how time correlations in the noisy environment determine whether the two averages do coincide or not. These environment time correlations can potentially generate non-Markovian dynamics of the quantum system depending on the structure and energy scale of the system Hamiltonian. We thus propose a way to detect time correlations of the environment by coupling a quantum probe system to it and observing the survival probability of the quantum probe in a measurement subspace. This will further contribute to the development of new schemes for quantum sensing technologies, where nanodevices may be exploited to image external structures or biological molecules via the surface field they generate.

  5. Intrusion detection method based on nonlinear correlation measure

    NARCIS (Netherlands)

    Ambusaidi, Mohammed A.; Tan, Zhiyuan; He, Xiangjian; Nanda, Priyadarsi; Lu, Liang Fu; Jamdagni, Aruna

    2014-01-01

    Cyber crimes and malicious network activities have posed serious threats to the entire internet and its users. This issue is becoming more critical, as network-based services, are more widespread and closely related to our daily life. Thus, it has raised a serious concern in individual internet user

  6. Performance of Narrowband Signal Detection under Correlated Rayleigh Fading Based on Synthetic Array

    Directory of Open Access Journals (Sweden)

    Ali Broumandan

    2009-01-01

    design parameters of probability of detection (Pd and probability of false alarm (Pfa. An optimum detector based on Estimator-Correlator (EC is developed, and its performance is compared with that of suboptimal Equal-Gain (EG combiner in different channel correlation scenarios. It is shown that in moderate channel correlation scenarios the detection performance of EC and EG is identical. The sensitivity of the proposed method to knowledge of motion parameters is also investigated. An extensive set of measurements based on CDMA-2000 pilot signals using the static antenna and synthetic array are used to experimentally verify these theoretical findings.

  7. A correlation based fault detection method for short circuits in battery packs

    Science.gov (United States)

    Xia, Bing; Shang, Yunlong; Nguyen, Truong; Mi, Chris

    2017-01-01

    This paper presents a fault detection method for short circuits based on the correlation coefficient of voltage curves. The proposed method utilizes the direct voltage measurements from the battery cells, and does not require any additional hardware or effort in modeling during fault detection. Moreover, the inherent mathematical properties of the correlation coefficient ensure the robustness of this method as the battery pack ages or is imbalanced in real applications. In order to apply this method online, the recursive moving window correlation coefficient calculation is adopted to maintain the detection sensitivity to faults during operation. An additive square wave is designed to prevent false positive detections when the batteries are at rest. The fault isolation can be achieved by identifying the overlapped cell in the correlation coefficients with fault flags. Simulation and experimental results validated the feasibility and demonstrated the advantages of this method.

  8. Correlation Coefficient Based DVB-T Continual Pilot Detection to Identify Spectrum Hole for CR Application

    Directory of Open Access Journals (Sweden)

    Mohammad Mizanur RAHMAN

    2016-06-01

    Full Text Available Digital terrestrial television (DTV covers an area with radius as large as 60 km. Federal Communications Commission (FCC and Office of Communications (Ofcom suggests detection of DTV signal at signal strength of as low as -114 dBm and -120 dBm respectively. Thus, detection of DTV signals in low signal-to-noise ratio (SNR is vital. Continual pilot (CP positions in all the DTV signals are fixed. Digital Video Broadcasting Terrestrial (DVB-T, a DTV standard, is followed by most of the countries of the world. In this paper we propose a correlation based CP detection which can detect a DVB-T signal at low SNR. One CP carrier was generated at the receiver which was correlated with the received orthogonal frequency division multiplexing (OFDM signal sequence. The correlation coefficient was then compared with a threshold correlation coefficient to identify the existence of the CP to detect the presence of a DVB-T signal and thereby spectrum hole. It was found from the simulation study for additive white Gaussian noise (AWGN channel that signal detection at low SNR is possible compared to the time domain symbol cross-correlation (TDSC method.

  9. Data-driven fault detection for industrial processes canonical correlation analysis and projection based methods

    CERN Document Server

    Chen, Zhiwen

    2017-01-01

    Zhiwen Chen aims to develop advanced fault detection (FD) methods for the monitoring of industrial processes. With the ever increasing demands on reliability and safety in industrial processes, fault detection has become an important issue. Although the model-based fault detection theory has been well studied in the past decades, its applications are limited to large-scale industrial processes because it is difficult to build accurate models. Furthermore, motivated by the limitations of existing data-driven FD methods, novel canonical correlation analysis (CCA) and projection-based methods are proposed from the perspectives of process input and output data, less engineering effort and wide application scope. For performance evaluation of FD methods, a new index is also developed. Contents A New Index for Performance Evaluation of FD Methods CCA-based FD Method for the Monitoring of Stationary Processes Projection-based FD Method for the Monitoring of Dynamic Processes Benchmark Study and Real-Time Implementat...

  10. Harmonic detection an AC excited generation system based on in-phase correlation filtering

    Institute of Scientific and Technical Information of China (English)

    贺益康; 孙丹; 王文举; 石赟

    2002-01-01

    The paper reports results of investigation on the harmonic detection technique of a complicated power supply system such as an AC excited generation system, which has a variable fundamental frequency and low order harmonics with rich sub-harmonics whose frequencies are lower than the fundamental one. The in-phase correlation filtering technique, based on the frequency shifting principle, is proposed in this paper.Theoretical analysis and experimental results validate the effectiveness of this technique for the harmonic detections of AC excited generation systems.

  11. Harmonic detection an AC excited generation system based on in-phase correlation filtering

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The paper reports results of investigation on the harmonic detection technique of a complicated power supply system such as an AC excited generation system, which has a variable fundamental frequency and low order harmonics with rich sub-harmonics whose frequencies are lower than the fundamental one. The in-phase correlation filtering technique, based on the frequency shifting principle, is proposed in this paper. Theoretical analysis and experimental results validate the effectiveness of this technique for the harmonic detections of AC excited generation systems.

  12. Denial-of-service attack detection based on multivariate correlation analysis

    NARCIS (Netherlands)

    Tan, Zhiyuan; Jamdagni, Aruna; He, Xiangjian; Nanda, Priyadarsi; Liu, Ren Ping; Lu, Bao-Liang; Zhang, Liqing; Kwok, James

    2011-01-01

    The reliability and availability of network services are being threatened by the growing number of Denial-of-Service (DoS) attacks. Effective mechanisms for DoS attack detection are demanded. Therefore, we propose a multivariate correlation analysis approach to investigate and extract second-order s

  13. Damage Detection of Structures for Ambient Loading Based on Cross Correlation Function Amplitude and SVM

    Directory of Open Access Journals (Sweden)

    Lin-sheng Huo

    2016-01-01

    Full Text Available An effective method for the damage detection of skeletal structures which combines the cross correlation function amplitude (CCFA with the support vector machine (SVM is presented in this paper. The proposed method consists of two stages. Firstly, the data features are extracted from the CCFA, which, calculated from dynamic responses and as a representation of the modal shapes of the structure, changes when damage occurs on the structure. The data features are then input into the SVM with the one-against-one (OAO algorithm to classify the damage status of the structure. The simulation data of IASC-ASCE benchmark model and a vibration experiment of truss structure are adopted to verify the feasibility of proposed method. The results show that the proposed method is suitable for the damage identification of skeletal structures with the limited sensors subjected to ambient excitation. As the CCFA based data features are sensitive to damage, the proposed method demonstrates its reliability in the diagnosis of structures with damage, especially for those with minor damage. In addition, the proposed method shows better noise robustness and is more suitable for noisy environments.

  14. Baseline-free fatigue crack detection based on spectral correlation and nonlinear wave modulation

    Science.gov (United States)

    Liu, Peipei; Sohn, Hoon; Yang, Suyoung; Lim, Hyung Jin

    2016-12-01

    By generating ultrasonic waves at two different frequencies onto a cracked structure, modulations due to crack-induced nonlinearity can be observed in the corresponding ultrasonic response. This nonlinear wave modulation phenomenon has been widely studied and proven capable of detecting a fatigue crack at a very early stage. However, under field conditions, other exogenous vibrations exist and the modulation components can be buried under ambient noises, making it difficult to extract the modulation components simply by using a spectral density function. In this study, the nonlinear modulation components in the ultrasonic response were extracted using a spectral correlation function (the double Fourier transform) with respect to time and time lag of a signal’s autocorrelation. Using spectral correlation, noise or interference, which is spectrally overlapped with the nonlinear modulation components in the ultrasonic response, can be effectively removed or reduced. Only the nonlinear modulation components are accentuated at specific coordinates of the spectral correlation plot. A damage feature is defined by comparing the spectral correlation value between nonlinear modulation components with other spectral correlation values among randomly selected frequencies. Then, by analyzing the statistical characteristics of the multiple damage feature values obtained from different input frequency combinations, fatigue cracks can be detected without relying on baseline data obtained from the pristine condition of the target structure. In the end, an experimental test was conducted on aluminum plates with a real fatigue crack and the test signals were contaminated by simulated noises with varying signal-to-noise ratios. The results validated the proposed technique.

  15. Staff line detection and revision algorithm based on subsection projection and correlation algorithm

    Science.gov (United States)

    Yang, Yin-xian; Yang, Ding-li

    2013-03-01

    Staff line detection plays a key role in OMR technology, and is the precon-ditions of subsequent segmentation 1& recognition of music sheets. For the phenomena of horizontal inclination & curvature of staff lines and vertical inclination of image, which often occur in music scores, an improved approach based on subsection projection is put forward to realize the detection of original staff lines and revision in an effect to implement staff line detection more successfully. Experimental results show the presented algorithm can detect and revise staff lines fast and effectively.

  16. Spatial correlation coefficient images for ultrasonic detection.

    Science.gov (United States)

    Cepel, Raina; Ho, K C; Rinker, Brett A; Palmer, Donald D; Lerch, Terrence P; Neal, Steven P

    2007-09-01

    In ultrasonics, image formation and detection are generally based on signal amplitude. In this paper, we introduce correlation coefficient images as a signal-amplitude independent approach for image formation. The correlation coefficients are calculated between A-scans digitized at adjacent measurement positions. In these images, defects are revealed as regions of high or low correlation relative to the background correlations associated with noise. Correlation coefficient and C-scan images are shown to demonstrate flat-bottom-hole detection in a stainless steel annular ring and crack detection in an aluminum aircraft structure.

  17. Microevent Detection Based on Waveform Cross-correlation in the Dogye Mining Area, Korea

    Science.gov (United States)

    Son, M.; Shin, J. S.; Kim, G.

    2015-12-01

    We have studied induced seismicity associated with Dogye coal mine located in the eastern part of Korea. From May 2009 to March 2014, 222 events that occurred at the mining area were reported in our catalog with local magnitudes ranging from 0.6 to 2.4. For 67 events we can observe that the epicenters relocated by the double difference technique with Lg waveform cross-correlation image location of the six clusters classified according to waveform similarity. On May 2014 a broadband seismometer is installed in the mine office to understand seismicity of the mining area. We cross-correlate continuous data of the installed station recorded from May 2014 to April 2015 with a comb-like waveform observed regularly. The comb-like waveform with length of 30 to 60 minutes is a signal train composed of a blast every 30 seconds. We consider the comb-like signal related directly to mining activity from the fact that the signal train appears averagely four times a day on weekdays with its monotonic amplitude. Besides the comb-like signal, events with an irregular occurrence time and amplitude is detected from the one-year continuous record of the installed station. We suggests that most of the undefined events are formed from fracturing in response to stress-perturbation on an active mining face or represent slip in existing shear zones such as a fault or dike.

  18. A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis

    Science.gov (United States)

    Wang, Fang

    2016-06-01

    In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρ D X A , contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

  19. A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis.

    Science.gov (United States)

    Wang, Fang

    2016-06-01

    In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρDXA, contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

  20. Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method

    Directory of Open Access Journals (Sweden)

    Yang Zhang

    2016-10-01

    Full Text Available Ultra-wideband (UWB radar has been widely used for detecting human physiological signals (respiration, movement, etc. in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc., the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.

  1. Temperature-Corrected Oxygen Detection Based on Multi-Mode Diode Laser Correlation Spectroscopy

    Directory of Open Access Journals (Sweden)

    Xiutao Lou

    2013-01-01

    Full Text Available Temperature-corrected oxygen measurements were performed by using multi-mode diode laser correlation spectroscopy at temperatures ranging between 300 and 473 K. The experiments simulate in situ monitoring of oxygen in coal-combustion exhaust gases at the tail of the flue. A linear relationship with a correlation coefficient of −0.999 was found between the evaluated concentration and the gas temperature. Temperature effects were either auto-corrected by keeping the reference gas at the same conditions as the sample gas, or rectified by using a predetermined effective temperature-correction coefficient calibrated for a range of absorption wavelengths. Relative standard deviations of the temperature-corrected oxygen concentrations obtained by different schemes and at various temperatures were estimated, yielding a measurement precision of 0.6%.

  2. Unbiased community detection for correlation matrices

    CERN Document Server

    MacMahon, Mel

    2013-01-01

    A challenging problem in the study of large complex systems is that of resolving, without prior information, the emergent mesoscopic organization determined by groups of units whose dynamical activity is more strongly correlated internally than with the rest of the system. The existing techniques to filter correlations are not explicitly oriented at identifying such modules and suffer from an unavoidable information loss. A promising alternative is that of employing community detection techniques developed in network theory. Unfortunately, the attempts made so far have merely replaced network data with correlation matrices, a procedure that we show to be fundamentally biased due to its inconsistency with the null hypotheses underlying the existing algorithms. Here we introduce, via a consistent redefinition of null models based on Random Matrix Theory, the unbiased correlation-based counterparts of the most popular community detection techniques. After successfully benchmarking our methods, we apply them to s...

  3. An automated cross-correlation based event detection technique and its application to surface passive data set

    Science.gov (United States)

    Forghani-Arani, Farnoush; Behura, Jyoti; Haines, Seth S.; Batzle, Mike

    2013-01-01

    In studies on heavy oil, shale reservoirs, tight gas and enhanced geothermal systems, the use of surface passive seismic data to monitor induced microseismicity due to the fluid flow in the subsurface is becoming more common. However, in most studies passive seismic records contain days and months of data and manually analysing the data can be expensive and inaccurate. Moreover, in the presence of noise, detecting the arrival of weak microseismic events becomes challenging. Hence, the use of an automated, accurate and computationally fast technique for event detection in passive seismic data is essential. The conventional automatic event identification algorithm computes a running-window energy ratio of the short-term average to the long-term average of the passive seismic data for each trace. We show that for the common case of a low signal-to-noise ratio in surface passive records, the conventional method is not sufficiently effective at event identification. Here, we extend the conventional algorithm by introducing a technique that is based on the cross-correlation of the energy ratios computed by the conventional method. With our technique we can measure the similarities amongst the computed energy ratios at different traces. Our approach is successful at improving the detectability of events with a low signal-to-noise ratio that are not detectable with the conventional algorithm. Also, our algorithm has the advantage to identify if an event is common to all stations (a regional event) or to a limited number of stations (a local event). We provide examples of applying our technique to synthetic data and a field surface passive data set recorded at a geothermal site.

  4. Investigation of a Cross-Correlation Based Optical Strain Measurement Technique for Detecting radial Growth on a Rotating Disk

    Science.gov (United States)

    Clem, Michelle M.; Woike, Mark R.

    2013-01-01

    The Aeronautical Sciences Project under NASA`s Fundamental Aeronautics Program is extremely interested in the development of novel measurement technologies, such as optical surface measurements in the internal parts of a flow path, for in situ health monitoring of gas turbine engines. In situ health monitoring has the potential to detect flaws, i.e. cracks in key components, such as engine turbine disks, before the flaws lead to catastrophic failure. In the present study, a cross-correlation imaging technique is investigated in a proof-of-concept study as a possible optical technique to measure the radial growth and strain field on an already cracked sub-scale turbine engine disk under loaded conditions in the NASA Glenn Research Center`s High Precision Rotordynamics Laboratory. The optical strain measurement technique under investigation offers potential fault detection using an applied high-contrast random speckle pattern and imaging the pattern under unloaded and loaded conditions with a CCD camera. Spinning the cracked disk at high speeds induces an external load, resulting in a radial growth of the disk of approximately 50.0-im in the flawed region and hence, a localized strain field. When imaging the cracked disk under static conditions, the disk will be undistorted; however, during rotation the cracked region will grow radially, thus causing the applied particle pattern to be .shifted`. The resulting particle displacements between the two images will then be measured using the two-dimensional cross-correlation algorithms implemented in standard Particle Image Velocimetry (PIV) software to track the disk growth, which facilitates calculation of the localized strain field. In order to develop and validate this optical strain measurement technique an initial proof-of-concept experiment is carried out in a controlled environment. Using PIV optimization principles and guidelines, three potential speckle patterns, for future use on the rotating disk, are developed

  5. A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines

    Directory of Open Access Journals (Sweden)

    Qiyang Xiao

    2016-12-01

    Full Text Available In this study, a small leak detection method based on variational mode decomposition (VMD and ambiguity correlation classification (ACC is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF, an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM and back propagation neural network (BP methods.

  6. A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines.

    Science.gov (United States)

    Xiao, Qiyang; Li, Jian; Bai, Zhiliang; Sun, Jiedi; Zhou, Nan; Zeng, Zhoumo

    2016-12-13

    In this study, a small leak detection method based on variational mode decomposition (VMD) and ambiguity correlation classification (ACC) is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF), an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM) and back propagation neural network (BP) methods.

  7. Progress of a cross-correlation based optical strain measurement technique for detecting radial growth on a rotating disk

    Science.gov (United States)

    Clem, Michelle M.; Woike, Mark R.; Abdul-Aziz, Ali

    2014-04-01

    The Aeronautical Sciences Project under NASA's Fundamental Aeronautics Program is interested in the development of novel measurement technologies, such as optical surface measurements for the in situ health monitoring of critical constituents of the internal flow path. In situ health monitoring has the potential to detect flaws, i.e. cracks in key components, such as engine turbine disks, before the flaws lead to catastrophic failure. The present study, aims to further validate and develop an optical strain measurement technique to measure the radial growth and strain field of an already cracked disk, mimicking the geometry of a sub-scale turbine engine disk, under loaded conditions in the NASA Glenn Research Center's High Precision Rotordynamics Laboratory. The technique offers potential fault detection by imaging an applied high-contrast random speckle pattern under unloaded and loaded conditions with a CCD camera. Spinning the cracked disk at high speeds (loaded conditions) induces an external load, resulting in a radial growth of the disk of approximately 50.0-μm in the flawed region and hence, a localized strain field. When imaging the cracked disk under static conditions, the disk will be undistorted; however, during rotation the cracked region will grow radially, thus causing the applied particle pattern to be `shifted'. The resulting particle displacements between the two images is measured using the two-dimensional cross-correlation algorithms implemented in standard Particle Image Velocimetry (PIV) software to track the disk growth, which facilitates calculation of the localized strain field. A random particle distribution is adhered onto the surface of the cracked disk and two bench top experiments are carried out to evaluate the technique's ability to measure the induced particle displacements. The disk is shifted manually using a translation stage equipped with a fine micrometer and a hotplate is used to induce thermal growth of the disk, causing the

  8. Spatial Correlation Coefficient Images for Ultrasonic Detection (Preprint)

    Science.gov (United States)

    2006-07-01

    for image formation and detection based on the similarity of adjacent signals. Signal similarity is quantified in terms of the correlation coefficient calculated...between A-scans digitized at adjacent measurement positions. Correlation coefficient images are introduced for visualizing the similarity...beam field with the defect. Correlation coefficient and C-scan images are shown to demonstrate flat-bottom-hole detection in a stainless steel annular

  9. Efficiency of using correlation function for estimation of probability of substance detection on the base of THz spectral dynamics

    Science.gov (United States)

    Trofimov, Vyacheslav A.; Peskov, Nikolay V.; Kirillov, Dmitry A.

    2012-10-01

    One of the problems arising in Time-Domain THz spectroscopy for the problem of security is the developing the criteria for assessment of probability for the detection and identification of the explosive and drugs. We analyze the efficiency of using the correlation function and another functional (more exactly, spectral norm) for this aim. These criteria are applied to spectral lines dynamics. For increasing the reliability of the assessment we subtract the averaged value of THz signal during time of analysis of the signal: it means deleting the constant from this part of the signal. Because of this, we can increase the contrast of assessment. We compare application of the Fourier-Gabor transform with unbounded (for example, Gaussian) window, which slides along the signal, for finding the spectral lines dynamics with application of the Fourier transform in short time interval (FTST), in which the Fourier transform is applied to parts of the signals, for the same aim. These methods are close each to other. Nevertheless, they differ by series of frequencies which they use. It is important for practice that the optimal window shape depends on chosen method for obtaining the spectral dynamics. The probability enhancements if we can find the train of pulses with different frequencies, which follow sequentially. We show that there is possibility to get pure spectral lines dynamics even under the condition of distorted spectrum of the substance response on the action of the THz pulse.

  10. 基于相关性分析的硬件木马检测方法%Hardware Trojan Detection Method Based on Correlation Analysis

    Institute of Scientific and Technical Information of China (English)

    刘长龙; 赵毅强; 史亚峰; 冯紫竹

    2013-01-01

    为提高硬件木马检测的准确率,提出一种基于相关性分析的检测方法。在完成木马功耗建模的基础上,提出并分析利用经典相关系数进行木马检测的可行性以及存在的缺点,根据木马检测的特点,优化检测系数,给出利用区间重叠比作为木马判定依据的检测方法。实验结果表明,与采用经典相关系数的方法相比,该方法在降低约6%检测准确率的前提下,能使鲁棒性提高1倍以上。%To improve the accuracy of the hardware trojan detection, a method based on the correlation analysis is presented. After a power modeling of the trojan, the feasibility and defect of the detection method by using the classical correlation coefficient are analyzed, the detection coefficient is optimized according to the characteristics of trojan detection, and the detection method depended on the region overlap ratio is presented. Experimental results show that this method can provide more than two times of robustness when the detection accuracy declined about 6%compared with the classical correlation coefficient.

  11. Immunity Based Worm Detection System

    Institute of Scientific and Technical Information of China (English)

    HONG Zheng; WU Li-fa; WANG Yuan-yuan

    2007-01-01

    Current worm detection methods are unable to detect multi-vector polymorphic worms effectively.Based on negative selection mechanism of the immune system,a local network worm detection system that detects worms was proposed.Normal network service requests were represented by self-strings,and the detection system used self-strings to monitor the network for anomaly.According to the properties of worm propagation,a control center correlated the anomalies detected in the form of binary trees to ensure the accuracy of worm detection.Experiments show the system to be effective in detecting the traditional as well as multi-vector polymorphic worms.

  12. Local correlation detection with linearity enhancement in streaming data

    KAUST Repository

    Xie, Qing

    2013-01-01

    This paper addresses the challenges in detecting the potential correlation between numerical data streams, which facilitates the research of data stream mining and pattern discovery. We focus on local correlation with delay, which may occur in burst at different time in different streams, and last for a limited period. The uncertainty on the correlation occurrence and the time delay make it diff cult to monitor the correlation online. Furthermore, the conventional correlation measure lacks the ability of ref ecting visual linearity, which is more desirable in reality. This paper proposes effective methods to continuously detect the correlation between data streams. Our approach is based on the Discrete Fourier Transform to make rapid cross-correlation calculation with time delay allowed. In addition, we introduce a shape-based similarity measure into the framework, which ref nes the results by representative trend patterns to enhance the signif cance of linearity. The similarity of proposed linear representations can quickly estimate the correlation, and the window sliding strategy in segment level improves the eff ciency for online detection. The empirical study demonstrates the accuracy of our detection approach, as well as more than 30% improvement of eff ciency. Copyright 2013 ACM.

  13. Correlation methods in fingerprint detection studies

    Energy Technology Data Exchange (ETDEWEB)

    Santer, B.D.; Wigley, T.M.L.; Jones, P.D. (Lawrence Livermore National Laboratory, Livermore, CA (United States))

    1993-07-01

    This investigation addresses two general issues regarding the role of pattern similarity statistics in greenhouse warming detection studies: normalization, and the relative merits of centered versus uncentered statistics. A pattern correlation statistic is used to search for the greenhouse warming signals predicted by five different models in the observed records of land and ocean surface temperature changes. Two forms of this statistic were computed: R(t), which makes use of non-normalized data, and R(t), which employs point-wise normalized data in order to focus the search on regions where the signal-to-noise ratio is large. While there are no trends in the R(t) time series, the time series of R(t) show large positive trends. However, it is not possible to infer from the R(t) results that the observed pattern of temperature change is, in fact, becoming increasingly similar to the model-predicted signal. It is shown that trends in R(t) must arise almost completely from the observed data, and cannot be an indicator of increasing observed data/signal similarity. The most informative pattern correlation statistic for detection purposes is R(t), the standard product-moment correlation coefficient between the observed and model fields. Our failure to find meaningful trends in R(t) may be due to the fact that the signal is being obscured by the background noise of natural variability, and/or because of incorrect model signals or sensitivities.

  14. Cluster identification based on correlations.

    Science.gov (United States)

    Schulman, L S

    2012-04-01

    The problem addressed is the identification of cooperating agents based on correlations created as a result of the joint action of these and other agents. A systematic method for using correlations beyond second moments is developed. The technique is applied to a didactic example, the identification of alphabet letters based on correlations among the pixels used in an image of the letter. As in this example, agents can belong to more than one cluster. Moreover, the identification scheme does not require that the patterns be known ahead of time.

  15. Time-resolved single-photon detection module based on silicon photomultiplier: A novel building block for time-correlated measurement systems

    Science.gov (United States)

    Martinenghi, E.; Di Sieno, L.; Contini, D.; Sanzaro, M.; Pifferi, A.; Dalla Mora, A.

    2016-07-01

    We present the design and preliminary characterization of the first detection module based on Silicon Photomultiplier (SiPM) tailored for single-photon timing applications. The aim of this work is to demonstrate, thanks to the design of a suitable module, the possibility to easily exploit SiPM in many applications as an interesting detector featuring large active area, similarly to photomultipliers tubes, but keeping the advantages of solid state detectors (high quantum efficiency, low cost, compactness, robustness, low bias voltage, and insensitiveness to magnetic field). The module integrates a cooled SiPM with a total photosensitive area of 1 mm2 together with the suitable avalanche signal read-out circuit, the signal conditioning, the biasing electronics, and a Peltier cooler driver for thermal stabilization. It is able to extract the single-photon timing information with resolution better than 100 ps full-width at half maximum. We verified the effective stabilization in response to external thermal perturbations, thus proving the complete insensitivity of the module to environment temperature variations, which represents a fundamental parameter to profitably use the instrument for real-field applications. We also characterized the single-photon timing resolution, the background noise due to both primary dark count generation and afterpulsing, the single-photon detection efficiency, and the instrument response function shape. The proposed module can become a reliable and cost-effective building block for time-correlated single-photon counting instruments in applications requiring high collection capability of isotropic light and detection efficiency (e.g., fluorescence decay measurements or time-domain diffuse optics systems).

  16. Papanicolaou test in the detection of high-grade cervical lesions: a re-evaluation based on cytohistologic non-correlation rates in 356 concurrently obtained samples.

    Science.gov (United States)

    Carns, Bhavini; Fadare, Oluwole

    2008-01-01

    Studies evaluating the routine Papanicolaou (Pap) test have traditionally used as the reference gold standard, the diagnoses on the follow-up histologic samples. Since the latter are typically obtained days to weeks after the Pap test, the accuracy of the resultant comparison may be affected by interim factors, such as regression of human papillomavirus, new lesion acquisitions or colposcopy-associated variability. A subset of our clinicians have routinely obtained cervical cytology samples immediately prior to their colposcopic procedures, which presented a unique opportunity to re-evaluate the test performance of liquid-based cervical cytology in detecting the most clinically significant lesions (i.e. cervical intraepithelial neoplasia 2 or worse: CIN2+), using as gold standard, diagnoses on cervical biopsies that were essentially obtained simultaneously. For each patient, cytohistologic non-correlation between the Pap test and biopsy was considered to be present when either modality displayed a high-grade squamous intraepithelial lesion (HGSIL)/CIN2+ while the other displayed a less severe lesion. Therefore, HGSIL/CIN2+ was present in both the Pap test and biopsy in true positives, and absent in both modalities in true negatives. In false positives, the Pap test showed HGSIL while the biopsy showed less than a CIN2+. In false negatives, Pap tests displaying less than a HGSIL were associated with biopsies displaying CIN2+. Combinations associated with "atypical" interpretations were excluded. A cytohistologic non-correlation was present in 17 (4.8%) of the 356 combinations reviewed. The non-correlation was attributed, by virtue of having the less severe interpretation, to the Pap test in all 17 cases. There were 17, 322, 0, and 17 true positives, true negatives, false positives and false negatives respectively. The sensitivity, specificity, positive predictive value and negative predictive value of the Pap test, at a diagnostic threshold of HGSIL, in identifying

  17. Joint Transform Correlation for face tracking: elderly fall detection application

    Science.gov (United States)

    Katz, Philippe; Aron, Michael; Alfalou, Ayman

    2013-03-01

    In this paper, an iterative tracking algorithm based on a non-linear JTC (Joint Transform Correlator) architecture and enhanced by a digital image processing method is proposed and validated. This algorithm is based on the computation of a correlation plane where the reference image is updated at each frame. For that purpose, we use the JTC technique in real time to track a patient (target image) in a room fitted with a video camera. The correlation plane is used to localize the target image in the current video frame (frame i). Then, the reference image to be exploited in the next frame (frame i+1) is updated according to the previous one (frame i). In an effort to validate our algorithm, our work is divided into two parts: (i) a large study based on different sequences with several situations and different JTC parameters is achieved in order to quantify their effects on the tracking performances (decimation, non-linearity coefficient, size of the correlation plane, size of the region of interest...). (ii) the tracking algorithm is integrated into an application of elderly fall detection. The first reference image is a face detected by means of Haar descriptors, and then localized into the new video image thanks to our tracking method. In order to avoid a bad update of the reference frame, a method based on a comparison of image intensity histograms is proposed and integrated in our algorithm. This step ensures a robust tracking of the reference frame. This article focuses on face tracking step optimisation and evalutation. A supplementary step of fall detection, based on vertical acceleration and position, will be added and studied in further work.

  18. MR detection of retinal hemorrhages: correlation with graded ophthalmologic exam

    Energy Technology Data Exchange (ETDEWEB)

    Beavers, Angela J.; Allbery, Sandra M. [University of Nebraska Medical Center, Department of Radiology, Omaha, NE (United States); Children' s Hospital and Medical Center, Department of Radiology, Omaha, NE (United States); Stagner, Anna M.; Hejkal, Thomas W. [University of Nebraska Medical Center, Department of Ophthalmology, Omaha, NE (United States); Children' s Hospital and Medical Center, Department of Ophthalmology, Omaha, NE (United States); Lyden, Elizabeth R. [University of Nebraska Medical Center, College of Public Health, Omaha, NE (United States); Haney, Suzanne B. [Children' s Hospital and Medical Center, Department of Pediatrics, Omaha, NE (United States); University of Nebraska Medical Center, Department of Pediatrics, Omaha, NE (United States)

    2015-08-15

    Dilated fundoscopic exam is considered the gold standard for detecting retinal hemorrhage, but expertise in obtaining this exam is not always immediately available. MRI can detect retinal hemorrhages, but correlation of the grade or severity of retinal hemorrhage on dilated fundoscopic exam with retinal hemorrhage visibility on MRI has not been described. To determine the value of standard brain protocol MRI in detecting retinal hemorrhage and to determine whether there is any correlation with MR detection of retinal hemorrhage and the dilated fundoscopic exam grade of hemorrhage. We conducted a retrospective chart review of 77 children <2 years old who were seen for head trauma from April 2007 to July 2013 and had both brain MRI and dilated fundoscopic exam or retinal camera images. A staff pediatric radiologist and radiology resident reviewed the MR images. Retinal hemorrhages were graded by a chief ophthalmology resident on a 12-point scale based on the retinal hemorrhage type, size, location and extent as seen on review of retinal camera images and detailed reports by ophthalmologists. Higher scores indicated increased severity of retinal hemorrhages. There was a statistically significant difference in the median grade of retinal hemorrhage examination between children who had retinal hemorrhage detected on MRI and children who did not have retinal hemorrhage detected on MRI (P = 0.02). When examination grade was categorized as low-grade (1-4), moderate-grade (5-8) or high-grade (>8) hemorrhage, there was a statistically significant association between exam grade and diagnosis based on MRI (P = 0.008). For example, only 14% of children with low-grade retinal hemorrhages were identified on MRI compared to 76% of children with high-grade hemorrhages. MR detection of retinal hemorrhage demonstrated a sensitivity of 61%, specificity of 100%, positive predictive value of 100% and negative predictive value of 63%. Retinal hemorrhage was best seen on the gradient

  19. Neural correlates of humor detection and appreciation.

    Science.gov (United States)

    Moran, Joseph M; Wig, Gagan S; Adams, Reginald B; Janata, Petr; Kelley, William M

    2004-03-01

    Humor is a uniquely human quality whose neural substrates remain enigmatic. The present report combined dynamic, real-life content and event-related functional magnetic resonance imaging (fMRI) to dissociate humor detection ("getting the joke") from humor appreciation (the affective experience of mirth). During scanning, subjects viewed full-length episodes of the television sitcoms Seinfeld or The Simpsons. Brain activity time-locked to humor detection moments revealed increases in left inferior frontal and posterior temporal cortices, whereas brain activity time-locked to moments of humor appreciation revealed increases in bilateral regions of insular cortex and the amygdala. These findings provide evidence that humor depends critically upon extant neural systems important for resolving incongruities (humor detection) and for the expression of affect (humor appreciation).

  20. Detection Performance of the Circular Correlation Coefficient Receiver,

    Science.gov (United States)

    of the squared modulus of the circular serial correlation coefficient is found when no signal is present, allowing computation of the detection...threshold. For small data records, as is typical in radar applications, the performance of the correlation coefficient detector is compared to a standard... Correlation Coefficient , Autoregressive, CFAR, Autocorrelation Estimation, Radar Receiver, and Digital Signal Processing.

  1. Correlations Between 48 Human Actions Improve Their Detection

    NARCIS (Netherlands)

    Burghouts, G.J.; Schutte, K.

    2012-01-01

    Many human actions are correlated, because of compound and/or sequential actions, and similarity. Indeed, human actions are highly correlated in human annotations of 48 actions in the 4,774 videos from visint.org. We exploit such correlations to improve the detection of these 48 human actions, rangi

  2. Detecting Positive Correlations in a Multivariate Sample

    CERN Document Server

    Castro, Ery Arias; Lugosi, Gábor

    2012-01-01

    We consider the problem of testing whether a correlation matrix of a multivariate normal population is the identity matrix. We focus on sparse classes of alternatives where only a few entries are nonzero and, in fact, positive. We derive a general lower bound applicable to various classes and study the performance of some near-optimal tests. We pay special attention to computational feasibility and construct near-optimal tests that can be computed efficiently. Finally, we apply our results to prove new lower bounds for the clique number of high-dimensional random geometric graphs.

  3. Cross-correlation-based detection and characterisation of microseismicity adjacent to the locked, late-interseismic Alpine Fault, South Westland, New Zealand

    Science.gov (United States)

    Chamberlain, Calum J.; Boese, Carolin M.; Townend, John

    2017-01-01

    The Alpine Fault is inferred on paleoseismological grounds to produce magnitude 8 earthquakes approximately every 330 yrs and to have last ruptured almost 300 yrs ago in 1717 AD. Despite approximately 90% of its typical interseismic period having elapsed since the last major earthquake, the Alpine Fault exhibits little present-day microseismicity and no geodetic evidence for shallow creep. Determining the mechanical state of the fault ahead of a future earthquake is a key objective of several studies, including the Deep Fault Drilling Project (DFDP). Here we use a network of borehole seismometers installed in conjunction with DFDP to detect and characterise low-magnitude seismicity adjacent to the central section of the Alpine Fault. We employ matched-filter detection techniques, automated cross-correlation phase picking, and singular value decomposition-derived magnitude estimation to construct a high-precision catalogue of 283 earthquakes within 5 km of the fault trace in an otherwise seismically quiet zone. The newly recognised seismicity occurs in non-repeating, spatially and temporally limited sequences, similar to sequences previously documented using standard methods but at significantly lower magnitudes of ML < 1.8. These earthquakes are not clustered on a single distinctive structure, and we infer that they are distributed throughout a highly fractured zone surrounding the Alpine Fault. Focal mechanisms computed for 13 earthquakes using manual polarity picks exhibit predominantly strike-slip faulting, consistent with focal mechanisms observed further from the fault. We conclude that the Alpine Fault is locked and accumulating strain throughout the seismogenic zone at this location.

  4. Correlation studies on surface particle detection methods

    Science.gov (United States)

    Peterson, Ronald V.; White, James C.

    1988-01-01

    The accurate determination of dust levels on optical surfaces is necessary to assess sensor system performance. A comparison study was made on several particle measurement methods including those based on direct imaging and light scattering. The effectiveness of removing the particles from the surface prior to determining particle size distributions was also assessed. These studies revealed that some methods, especially those requiring particle removal before analysis, are subject to large systematic errors affecting particle size distributions. Thus, an understanding of the particle measurement methods employed is necessary before any surface cleanliness or obstruction value assignments are accepted as true representations of an optical surface contamination condition.

  5. The Prevalence, Correlates, Detection and Control of Diabetes among Older People in Low and Middle Income Countries. A 10/66 Dementia Research Group Population-Based Survey

    Science.gov (United States)

    Salas, Aquiles; Acosta, Daisy; Ferri, Cleusa P.; Guerra, Mariella; Huang, Yueqin; Jacob, K. S.; Jimenez-Velazquez, Ivonne Z.; Llibre Rodriguez, Juan J.; Sosa, Ana L.; Uwakwe, Richard; Williams, Joseph D.; Jotheeswaran, A. T.; Liu, Zhaorui; Lopez Medina, A. M.; Salinas-Contreras, Rosa Maria; Prince, Martin J.

    2016-01-01

    Background Little is known of the epidemiology of diabetes among older people in low and middle income countries. We aimed to study and compare prevalence, social patterning, correlates, detection, treatment and control of diabetes among older people in Latin America, India, China and Nigeria. Methods Cross-sectional surveys in 13 catchment area sites in nine countries. Diagnosed diabetes was assessed in all sites through self-reported diagnosis. Undiagnosed diabetes was assessed in seven Latin American sites through fasting blood samples (glucose > = 7mmol/L). Results Total diabetes prevalence in catchment sites in Cuba (prevalence 24.2%, SMR 116), Puerto Rico (43.4%, 197), and urban (27.0%, 125), and rural Mexico (23.7%, 111) already exceeds that in the USA, while that in Venezuela (20.9%, 100) is similar. Diagnosed diabetes prevalence varied very widely, between low prevalences in sites in rural China (0.9%), rural India (6.6%) and Nigeria (6.0%). and 32.1% in Puerto Rico, explained mainly by access to health services. Treatment coverage varied substantially between sites. Diabetes control (40 to 61% of those diagnosed) was modest in the Latin American sites where this was studied. Diabetes was independently associated with less education, but more assets. Hypertension, central obesity and hypertriglyceridaemia, but not hypercholesterolaemia were consistently associated with total diabetes. Conclusions Diabetes prevalence is already high in most sites. Identifying undiagnosed cases is essential to quantify population burden, particularly in least developed settings where diagnosis is uncommon. Metabolic risk factors and associated lifestyles may play an important part in aetiology, but this requires confirmation with longitudinal data. Given the high prevalence among older people, more population research is indicated to quantify the impact of diabetes, and to monitor the effect of prevention and health system strengthening on prevalence, treatment and control

  6. The Prevalence, Correlates, Detection and Control of Diabetes among Older People in Low and Middle Income Countries. A 10/66 Dementia Research Group Population-Based Survey.

    Directory of Open Access Journals (Sweden)

    Aquiles Salas

    Full Text Available Little is known of the epidemiology of diabetes among older people in low and middle income countries. We aimed to study and compare prevalence, social patterning, correlates, detection, treatment and control of diabetes among older people in Latin America, India, China and Nigeria.Cross-sectional surveys in 13 catchment area sites in nine countries. Diagnosed diabetes was assessed in all sites through self-reported diagnosis. Undiagnosed diabetes was assessed in seven Latin American sites through fasting blood samples (glucose > = 7 mmol/L.Total diabetes prevalence in catchment sites in Cuba (prevalence 24.2%, SMR 116, Puerto Rico (43.4%, 197, and urban (27.0%, 125, and rural Mexico (23.7%, 111 already exceeds that in the USA, while that in Venezuela (20.9%, 100 is similar. Diagnosed diabetes prevalence varied very widely, between low prevalences in sites in rural China (0.9%, rural India (6.6% and Nigeria (6.0%. and 32.1% in Puerto Rico, explained mainly by access to health services. Treatment coverage varied substantially between sites. Diabetes control (40 to 61% of those diagnosed was modest in the Latin American sites where this was studied. Diabetes was independently associated with less education, but more assets. Hypertension, central obesity and hypertriglyceridaemia, but not hypercholesterolaemia were consistently associated with total diabetes.Diabetes prevalence is already high in most sites. Identifying undiagnosed cases is essential to quantify population burden, particularly in least developed settings where diagnosis is uncommon. Metabolic risk factors and associated lifestyles may play an important part in aetiology, but this requires confirmation with longitudinal data. Given the high prevalence among older people, more population research is indicated to quantify the impact of diabetes, and to monitor the effect of prevention and health system strengthening on prevalence, treatment and control.

  7. WAVELET BASED SPECTRAL CORRELATION METHOD FOR DPSK CHIP RATE ESTIMATION

    Institute of Scientific and Technical Information of China (English)

    Li Yingxiang; Xiao Xianci; Tai Hengming

    2004-01-01

    A wavelet-based spectral correlation algorithm to detect and estimate BPSK signal chip rate is proposed. Simulation results show that the proposed method can correctly estimate the BPSK signal chip rate, which may be corrupted by the quadratic characteristics of the spectral correlation function, in a low SNR environment.

  8. Multitarget analysis of CFAR detection of partially-correlated χ2 targets

    OpenAIRE

    El Mashade, Mohamed Bakry

    2016-01-01

    The goal of this paper is to treat the problem of detecting the partially-correlated χ2 fluctuating targets with two and four degrees of freedom. We analyze the detection performance in general terms of the more generalized version, which is known as GTM, of the CFAR processors when the operating environment is contaminated with outlying target returns and the radar receiver carries its processing based on post-detection integration of M exponentially correlated pulses. Analytical formulas fo...

  9. Markov chaotic sequences for correlation based watermarking schemes

    Energy Technology Data Exchange (ETDEWEB)

    Tefas, A.; Nikolaidis, A.; Nikolaidis, N.; Solachidis, V.; Tsekeridou, S.; Pitas, I. E-mail: pitas@zeus.csd.auth.gr

    2003-07-01

    In this paper, statistical analysis of watermarking schemes based on correlation detection is presented. Statistical properties of watermark sequences generated by piecewise-linear Markov maps are exploited, resulting in superior watermark detection reliability. Correlation/spectral properties of such sequences are easily controllable, a fact that affects the watermarking system performance. A family of chaotic maps, namely the skew tent map family, is proposed for use in watermarking schemes.

  10. Manifold Outlier Detection Algorithm Based on Local-Correlation Dimension%基于局部相关维度的流形离群点检测算法

    Institute of Scientific and Technical Information of China (English)

    黄添强; 李凯; 郭躬德

    2011-01-01

    传统的离群点检测算法不适合检测流形离群点,目前专门针对流形离群点检测的算法报道较少.为此,基于实验观察的启示,提出用流形局部相关维度检测流形离群点的算法.首先探讨内在维度的性质,并基于实验观察提出用流形局部相关维度来度量流形离群点,然后证明流形局部相关维度可表征数据样本离群的性质,最后基于此性质提出流形离群点检测算法.在人工数据与真实数据上的实验表明本算法可检测流形离群点,且本算法比最近报道的流形除噪算法具有更优的性能.%Traditional outlier detection algorithm is not suitable for detection of manifold outlier. There are reports of denoising algorithm for manifold learning, but fewer reports of manifold outlier detection algorithms. Therefore, the manifold outlier detection algorithm is proposed based on the local-correlation dimension according to experimental observations. Firstly, the nature of the intrinsic dimension is discussed, and the local-correlation dimension is used to measure the manifold outlier, which is based on experimental observations. And then it is proved that the nature of outliers on manifolds can be characterized by local-correlation dimension. Finally, the manifold outlier detection algorithm based on local-correlation dimension is proposed according to the nature. The performance evaluation of the artificial data and the real data shows that the algorithm can detect manifold outliers and it has better performance than the recently reported manifold blurry mean shif algorithm.

  11. A correlation method of detecting and estimating interactions of QTLs

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    More and more studies demonstrate that a great deal of interactions among the quantitative trait loci (QTLs) are far more than those detected by single markers. A correlation method was proposed for estimating the interactions of multiple QTLs detected by multi-markers in several mapping populations. Genetic implication of this method and usage were discussed.

  12. Spatial- and Time-Correlated Detection of Fission Fragments

    Directory of Open Access Journals (Sweden)

    Platkevic M.

    2012-02-01

    Full Text Available With the goal to measure angular correlations of fission fragments in rare fission decay (e.g. ternary and quaternary fission, a multi-detector coincidence system based on two and up to four position sensitive pixel detectors Timepix has been built. In addition to the high granularity, wide dynamic range and per pixel signal threshold, these devices are equipped with per pixel energy and time sensitivity providing more information (position, energy, time, enhances particle-type identification and selectivity of event-by-event detection. Operation of the device with the integrated USB 2.0 based readout interface FITPix and the control and data acquisition software tool Pixelman enables online visualization and flexible/adjustable operation for a different type of experiments. Spatially correlated fission fragments can be thus registered in coincidence. Similarly triggered measurements are performed using an integrated spectrometric module with analogue signal chain electronics. The current status of development together with demonstration of the technique with a 252Cf source is presented.

  13. A Correlation-Based Fingerprint Verification System

    NARCIS (Netherlands)

    Bazen, Asker M.; Verwaaijen, Gerben T.B.; Gerez, Sabih H.; Veelenturf, Leo P.J.; Zwaag, van der Berend Jan

    2000-01-01

    In this paper, a correlation-based fingerprint verification system is presented. Unlike the traditional minutiae-based systems, this system directly uses the richer gray-scale information of the fingerprints. The correlation-based fingerprint verification system first selects appropriate templates i

  14. An Immune Inspired Network Intrusion Detection System Utilising Correlation Context

    CERN Document Server

    Tedesco, Gianni

    2009-01-01

    Network Intrusion Detection Systems (NIDS) are computer systems which monitor a network with the aim of discerning malicious from benign activity on that network. While a wide range of approaches have met varying levels of success, most IDSs rely on having access to a database of known attack signatures which are written by security experts. Nowadays, in order to solve problems with false positive alerts, correlation algorithms are used to add additional structure to sequences of IDS alerts. However, such techniques are of no help in discovering novel attacks or variations of known attacks, something the human immune system (HIS) is capable of doing in its own specialised domain. This paper presents a novel immune algorithm for application to the IDS problem. The goal is to discover packets containing novel variations of attacks covered by an existing signature base.

  15. 基于相关滤波技术的SO2气体浓度监测系统设计%Detection System of SO2 Concentration Based on Gas Filter Correlation Technology

    Institute of Scientific and Technical Information of China (English)

    姚娜; 张记龙; 王志斌; 王相如; 张跃国

    2011-01-01

    A method of non-dispersion infrared absorption technology based on gas filter correlation technology for measuring SO2 is described in this paper. Based on the correlation operation principle and the gas characteristics absorption in infrared region, the method combining correlation technology and gas filter correlation (GFC) technology effectively solves the problems that SO2 air pollution in china is serious in recent years and atmosphere SO2 detection with non-dispersion Infrared system faces the problem of high noise interference. It brings about modulation and detection for feeble spectrum signal. And it realizes the new monitor design of SO2 concentration in the eventual. The experiment results show that the detection sensitivity of system can reach lppm.%介绍一种基于相关滤波技术的非分散红外SO2气体浓度测量方法.该方法是在相关运算原理和SO2红外吸收特性基础上,结合相关检测和气体滤波技术,有效解决了近年来空气中SO2污染严重且在非分散红外SO2检测系统中噪声干扰大的问题,实现了对微弱光信号的调制和检测,并实现了新型SO2浓度监测仪的设计.试验表明,系统有10(-6)的检测灵敏度.

  16. Canonical Correlation Analysis for Feature-Based Fusion of Biomedical Imaging Modalities and Its Application to Detection of Associative Networks in Schizophrenia.

    Science.gov (United States)

    Correa, Nicolle M; Li, Yi-Ou; Adalı, Tülay; Calhoun, Vince D

    2008-12-01

    Typically data acquired through imaging techniques such as functional magnetic resonance imaging (fMRI), structural MRI (sMRI), and electroencephalography (EEG) are analyzed separately. However, fusing information from such complementary modalities promises to provide additional insight into connectivity across brain networks and changes due to disease. We propose a data fusion scheme at the feature level using canonical correlation analysis (CCA) to determine inter-subject covariations across modalities. As we show both with simulation results and application to real data, multimodal CCA (mCCA) proves to be a flexible and powerful method for discovering associations among various data types. We demonstrate the versatility of the method with application to two datasets, an fMRI and EEG, and an fMRI and sMRI dataset, both collected from patients diagnosed with schizophrenia and healthy controls. CCA results for fMRI and EEG data collected for an auditory oddball task reveal associations of the temporal and motor areas with the N2 and P3 peaks. For the application to fMRI and sMRI data collected for an auditory sensorimotor task, CCA results show an interesting joint relationship between fMRI and gray matter, with patients with schizophrenia showing more functional activity in motor areas and less activity in temporal areas associated with less gray matter as compared to healthy controls. Additionally, we compare our scheme with an independent component analysis based fusion method, joint-ICA that has proven useful for such a study and note that the two methods provide complementary perspectives on data fusion.

  17. Robust Statistical Detection of Power-Law Cross-Correlation

    Science.gov (United States)

    Blythe, Duncan A. J.; Nikulin, Vadim V.; Müller, Klaus-Robert

    2016-06-01

    We show that widely used approaches in statistical physics incorrectly indicate the existence of power-law cross-correlations between financial stock market fluctuations measured over several years and the neuronal activity of the human brain lasting for only a few minutes. While such cross-correlations are nonsensical, no current methodology allows them to be reliably discarded, leaving researchers at greater risk when the spurious nature of cross-correlations is not clear from the unrelated origin of the time series and rather requires careful statistical estimation. Here we propose a theory and method (PLCC-test) which allows us to rigorously and robustly test for power-law cross-correlations, correctly detecting genuine and discarding spurious cross-correlations, thus establishing meaningful relationships between processes in complex physical systems. Our method reveals for the first time the presence of power-law cross-correlations between amplitudes of the alpha and beta frequency ranges of the human electroencephalogram.

  18. Fluorescence correlation spectroscopy: Ultrasensitive detection in clear and turbid media

    Science.gov (United States)

    Tahari, Abdel Kader

    In this work, I describe the development of a simple, inexpensive, and powerful alternative technique to detect and analyze, without enrichment, extremely low concentrations of cells, bacteria, viruses, and protein aggregates in turbid fluids for clinical and biotechnological applications. The anticipated applications of this technique are many. They range from the determination of the somatic cell count in milk for the dairy industry, to the enumeration and characterization of microorganisms in environmental microbiology and the food industry, and to the fast and ultrasensitive detection of protein aggregates for the diagnosis of Alzheimer's and other neurodegenerative diseases in clinical medicine. A prototype instrument has been built and allowed the detection and quantification of particles down to a few per milliliter in short scanning times. It consists of a small microscope that has a horizontal geometry and a mechanical instrument that holds a cylindrical cuvette (1 cm in diameter) with two motors that provide a rotational and a slower vertical inversion motions. The illumination focus is centered about 200 mum from the wall of the cuvette inside the sample. The total volume that is explored is large (˜1ml/min for bright particles). The data is analyzed with a correlation filter program based on particle passage pattern recognition. I will also describe further work on improving the sensitivity of the technique, expanding it for multiple-species discrimination and enumeration, and testing the prototype device in actual clinical and biotechnological applications. The main clinical application of this project seeks to establish conditions and use this new technique to quantify and size-analyze oligomeric complexes of the Alzheimer's disease beta-peptide in cerebrospinal fluid and other body fluids as a molecular biomarker for persons at risk of Alzheimer's disease dementia. The technology could potentially be extended to the diagnosis and therapeutic

  19. Interevent Correlations from Avalanches Hiding Below the Detection Threshold

    Science.gov (United States)

    Janićević, Sanja; Laurson, Lasse; Mâløy, Knut Jørgen; Santucci, Stéphane; Alava, Mikko J.

    2016-12-01

    Numerous systems ranging from deformation of materials to earthquakes exhibit bursty dynamics, which consist of a sequence of events with a broad event size distribution. Very often these events are observed to be temporally correlated or clustered, evidenced by power-law-distributed waiting times separating two consecutive activity bursts. We show how such interevent correlations arise simply because of a finite detection threshold, created by the limited sensitivity of the measurement apparatus, or used to subtract background activity or noise from the activity signal. Data from crack-propagation experiments and numerical simulations of a nonequilibrium crack-line model demonstrate how thresholding leads to correlated bursts of activity by separating the avalanche events into subavalanches. The resulting temporal subavalanche correlations are well described by our general scaling description of thresholding-induced correlations in crackling noise.

  20. Intrinsic Correlations for Flaring Blazars Detected by Fermi

    Science.gov (United States)

    Fan, J. H.; Yang, J. H.; Xiao, H. B.; Lin, C.; Constantin, D.; Luo, G. Y.; Pei, Z. Y.; Hao, J. M.; Mao, Y. W.

    2017-02-01

    Blazars are an extreme subclass of active galactic nuclei. Their rapid variability, luminous brightness, superluminal motion, and high and variable polarization are probably due to a beaming effect. However, this beaming factor (or Doppler factor) is very difficult to measure. Currently, a good way to estimate it is to use the timescale of their radio flares. In this Letter, we use multiwavelength data and Doppler factors reported in the literature for a sample of 86 flaring blazars detected by Fermi to compute their intrinsic multiwavelength data and intrinsic spectral energy distributions and investigate the correlations among observed and intrinsic data. Quite interestingly, intrinsic data show a positive correlation between luminosity and peak frequency, in contrast with the behavior of observed data, and a tighter correlation between γ-ray luminosity and the lower-energy ones. For flaring blazars detected by Fermi, we conclude that (1) observed emissions are strongly beamed; (2) the anti-correlation between luminosity and peak frequency from the observed data is an apparent result, the correlation between intrinsic data being positive; and (3) intrinsic γ-ray luminosity is strongly correlated with other intrinsic luminosities.

  1. Evolution of worldwide stock markets, correlation structure, and correlation-based graphs.

    Science.gov (United States)

    Song, Dong-Ming; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N

    2011-08-01

    We investigate the daily correlation present among market indices of stock exchanges located all over the world in the time period January 1996 to July 2009. We discover that the correlation among market indices presents both a fast and a slow dynamics. The slow dynamics reflects the development and consolidation of globalization. The fast dynamics is associated with critical events that originate in a specific country or region of the world and rapidly affect the global system. We provide evidence that the short term time scale of correlation among market indices is less than 3 trading months (about 60 trading days). The average values of the nondiagonal elements of the correlation matrix, correlation-based graphs, and the spectral properties of the largest eigenvalues and eigenvectors of the correlation matrix are carrying information about the fast and slow dynamics of the correlation of market indices. We introduce a measure of mutual information based on link co-occurrence in networks in order to detect the fast dynamics of successive changes of correlation-based graphs in a quantitative way.

  2. Detection of aggressiveness in immature rats and study of partly modified passive avoidance reaction based on negative emotion according to Buresh method and neurochemical correlates

    Directory of Open Access Journals (Sweden)

    M.Nikolaishvili

    2016-05-01

    Full Text Available Based on these facts, noradrenalin must be considered the main endogenous inductor of aggressive behavior. It takes part in behavior genesis and at the same time it synthesis increasesright when aggressive behavior is essential in order to adapt to environmental factors. Thus Noradrenalin could be the stimulating factor for aggressive behavior , although we should note that specific aggressive agent is not discovered yet. And it seems that the component carrying only this function is not produced in organism. Hence, anatomical, behavioral and pharmacological studies showed, that CNS structures such as almond-shapes structure , hippocampus, prefrontal cortex influence on the decrease of memory based on negative emotions that was more shown in less aggressive animals, than is non-aggressive. We can conclude that the difference in both aggressive animals is very little than in non aggressive. That suggests the high quality of memory and consolidation of aggressive animal.

  3. Symmetry Detection in Visual Impairment: Behavioral Evidence and Neural Correlates

    Directory of Open Access Journals (Sweden)

    Zaira Cattaneo

    2014-05-01

    Full Text Available Bilateral symmetry is an extremely salient feature for the human visual system. An interesting issue is whether the perceptual salience of symmetry is rooted in normal visual development. In this review, we discuss empirical work on visual and tactile symmetry detection in normally sighted and visually impaired individuals. On the one hand, available evidence suggests that efficient visual symmetry detection may need normal binocular vision development. On the other hand, converging evidence suggests that symmetry can develop as a principle of haptic perceptual organization in individuals lacking visual experience. Certain features of visual symmetry detection, however, such as the higher salience of the patterns containing a vertical axis of symmetry, do not systematically apply to the haptic modality. The neural correlates (revealed with neuroimaging associated with visual and haptic symmetry detection are also discussed.

  4. 基于流量相关性和数据融合的P2Pbotnet检测%P2P botnet detection based on correlation of flow and information fusion theory

    Institute of Scientific and Technical Information of China (English)

    宋元章; 陈媛; 王安邦

    2014-01-01

    提出了一种基于网络流量相关性和数据融合理论的实时检测P2P botnet方法,该方法主要关注P2P botnet的命令与控制机制(C&C)机制产生的本质流量---UDP流,它不会受P2P botnet的网络结构、协议和攻击类型的影响。首先分别用自相似性和信息熵来刻画UDP流的相关性特征,利用非参数CUSUM (cumula-tive sum )算法检测上述特征的变化以得到检测结果,然后利用Dempster-Shafer证据理论融合上述特征的检测结果。同时,采用TCP流量特征在一定程度上消除P2P应用程序对P2P botnet检测的影响。实验表明所提出的方法可有效检测新型P2P botnet 。%A real-time detection method-based on correlation of flow and information fusion theory was proposed .It focused on UDP (user datagram protocol) flow ,which was used to build the com-mand and control mechanism of P2P (peer-to-peer) botnet .So the abnormalities of UDP flow are the essential abnormalities of P2P botnet ,which will not change with structures of P2P network ,P2P protocols and attacks .The correlation features of UDP flow was described accurately with the self-similarity and the entropy theory .Two detection results were got separately by disposing abnormali-ties of the above features with the nonparametric CUSUM (cumulative sum) algorithm ,and the final decision detection result was achieved by fusing the above detection results with the Dempster-Shafer evidence theory .Considering that the traffic flow of web applications was likely to affect the detection result ,the features of TCP (transmission control protocol) flow were used to solve the problem .The experiments show that the proposed method can detect P2P botnet with a relatively lower false nega-tive and false positive rate .

  5. Optical correlation recognition based on LCOS

    Science.gov (United States)

    Tang, Mingchuan; Wu, Jianhong

    2013-08-01

    Vander-Lugt correlator[1] plays an important role in optical pattern recognition due to the characteristics of accurate positioning and high signal-to-noise ratio. The ideal Vander-Lugt correlator should have the ability of outputting strong and sharp correlation peak in allusion to the true target, in the existing Spatial Light Modulators[2], Liquid Crystal On Silicon(LCOS) has been the most competitive candidate for the matched filter owing to the continuous phase modulation peculiarity. Allowing for the distortions of the target to be identified including rotations, scaling changes, perspective changes, which can severely impact the correlation recognition results, herein, we present a modified Vander-Lugt correlator based on the LCOS by means of applying an iterative algorithm to the design of the filter so that the correlator can invariant to the distortions while maintaining good performance. The results of numerical simulation demonstrate that the filter could get the similar recognition results for all the training images. And the experiment shows that the modified correlator achieves the 180° rotating tolerance significantly improving the recognition efficiency of the correlator.

  6. Machine Learning Based Malware Detection

    Science.gov (United States)

    2015-05-18

    A TRIDENT SCHOLAR PROJECT REPORT NO. 440 Machine Learning Based Malware Detection by Midshipman 1/C Zane A. Markel, USN...public release and sale; its distribution is limited. U.S.N.A. --- Trident Scholar project report; no. 440 (2015) MACHINE LEARNING BASED MALWARE...COVERED (From - To) 4. TITLE AND SUBTITLE Machine Learning Based Malware Detection 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM

  7. Generalized Correlation Coefficient Based on Log Likelihood Ratio Test Statistic

    Directory of Open Access Journals (Sweden)

    Liu Hsiang-Chuan

    2016-01-01

    Full Text Available In this paper, I point out that both Joe’s and Ding’s strength statistics can only be used for testing the pair-wise independence, and I propose a novel G-square based strength statistic, called Liu’s generalized correlation coefficient, it can be used to detect and compare the strength of not only the pair-wise independence but also the mutual independence of any multivariate variables. Furthermore, I proved that only Liu’s generalized correlation coefficient is strictly increasing on its number of variables, it is more sensitive and useful than Cramer’s V coefficient, in other words, Liu generalized correlation coefficient is not only the G-square based strength statistic, but also an improved statistic for detecting and comparing the strengths of deferent associations of any two or more sets of multivariate variables, moreover, this new strength statistic can also be tested by G2.

  8. 基于吉布斯抽样的相关观测异常值检测的贝叶斯方法%Bayesian Method for Outlier Detection of Correlated Observation Based on Gibbs Sampling

    Institute of Scientific and Technical Information of China (English)

    魏萌; 王靳辉; 衡广辉

    2012-01-01

    相关观测的异常值检测是测量数据处理的难题之一.在系统总结和分析前人研究成果的基础上,运用贝叶斯统计推断理论,提出了相关观测异常值检测的贝叶斯方法.首先,基于识别变量的后验概率,提出了相关观测异常值定位的贝叶斯方法;然后设计和构建了计算后验概率的吉布斯抽样方法,基于最大后验估计原理,推导和建立了计算异常值参数的贝叶斯公式;最后对某GPS网相连进行了计算和分析.结果表明,在相关观测条件下,使用新方法能够对多个异常值同时进行检测,有效地消除异常值的不良影响.%Outlier of correlated observation are one of the difficult and important problems in data processing. According to systemically reviewing research history of the puzzle, Bayesian detection method was put forward and applied in the GPS network utilizing the modern Bayesian theories and methods. First of all, on the basis of posterior probabilities of classification variables, the Bayesian methods for positioning outlier of correlated observations was proposed, and based on Gibbs sampling, the algorithm for calculating the posterior probability of classification variables was designed. Secondly, modern Bayesian statistical theory was appliedy to deduce Bayesian estimations for outlier. Then, those new methods in a GPS network adjustment was applied. These numerical examples demonstrated that the new methods were effective. In condition of correlated observations, the methods can detect multiple outliers of correlated observation and eliminate the influence of outlier effectively at the same time.

  9. Features Based Text Similarity Detection

    CERN Document Server

    Kent, Chow Kok

    2010-01-01

    As the Internet help us cross cultural border by providing different information, plagiarism issue is bound to arise. As a result, plagiarism detection becomes more demanding in overcoming this issue. Different plagiarism detection tools have been developed based on various detection techniques. Nowadays, fingerprint matching technique plays an important role in those detection tools. However, in handling some large content articles, there are some weaknesses in fingerprint matching technique especially in space and time consumption issue. In this paper, we propose a new approach to detect plagiarism which integrates the use of fingerprint matching technique with four key features to assist in the detection process. These proposed features are capable to choose the main point or key sentence in the articles to be compared. Those selected sentence will be undergo the fingerprint matching process in order to detect the similarity between the sentences. Hence, time and space usage for the comparison process is r...

  10. 基于随机振动响应互相关函数的结构损伤识别试验分析%Structural damage detection method based on correlation function analysis of vibration measurement data

    Institute of Scientific and Technical Information of China (English)

    雷家艳; 姚谦峰; 雷鹰; 刘朝

    2011-01-01

    提出了基于结构振动响应互相关函数分析的损伤识别方法.通过八层剪切型钢框架结构模型在模拟白噪声随机激励作用下的试验,利用相邻测点响应的互相关函数幅值向量变化,构造损伤识别因子进行结构损伤判定、定位及程度量化,结果表明该方法对结构损伤识别的简易性及有效性,并为结构在线监测和分散式检测提供方法参考.%A structural damage identification technique based on correlation function analysis of vibration measurement data was proposed. An 8-storey steel shear building model was chosen as example in the case verification. The results demonstrate that accident magnitude change of correlation function can be used to locate the damage by comparing the shape changes between damaged and undamaged samples. The value of CVAC is effective to determinate whether the damage has happened or not, and it can be used as a reference method even for on-line structural health monitoring. The parameter K, defined to detect damage severity, corresponds to the theoretical damage level in different cases.

  11. Behavioural Correlation for Detecting P2P Bots

    CERN Document Server

    Al-Hammadi, Yousof

    2010-01-01

    In the past few years, IRC bots, malicious programs which are remotely controlled by the attacker through IRC servers, have become a major threat to the Internet and users. These bots can be used in different malicious ways such as issuing distributed denial of services attacks to shutdown other networks and services, keystrokes logging, spamming, traffic sniffing cause serious disruption on networks and users. New bots use peer to peer (P2P) protocols start to appear as the upcoming threat to Internet security due to the fact that P2P bots do not have a centralized point to shutdown or traceback, thus making the detection of P2P bots is a real challenge. In response to these threats, we present an algorithm to detect an individual P2P bot running on a system by correlating its activities. Our evaluation shows that correlating different activities generated by P2P bots within a specified time period can detect these kind of bots.

  12. 基于信号互相关的低速率拒绝服务攻击检测方法%Detecting Low-Rate DoS Attacks Based on Signal Cross-Correlation

    Institute of Scientific and Technical Information of China (English)

    吴志军; 李光; 岳猛

    2014-01-01

    低速率拒绝服务LDoS (Low-rate Denial of Service )攻击是一种基于TCP/IP协议漏洞,采用密集型周期性脉冲的攻击方式。本文针对分布式LDoS攻击脉冲到达目标端的时序关系,提出基于互相关的LDoS攻击检测方法。该方法通过计算构造的检测序列与采样得到的网络流量序列的相关性,得到相关序列,采用基于循环卷积的互相关算法来计算攻击脉冲经过不同传输通道在特定的攻击目标端的精确时间,利用无周期单脉冲预测技术估计LDoS攻击的周期参数,提取LDoS攻击的脉冲持续时间的相关性特征,并设计判决门限规则。实验结果表明基于信号互相关的LDoS攻击检测方法具有较好的检测性能。%Low-rate Denial of Service (LDoS ) attack is TCP-targeted attack ,which attempts to deny bandwidth of TCP flows .LDoS attacks send intensive periodic pulses at sufficiently low average rate to elude detection of DoS defense system .Based on the sequence relation between the distributed LDoS attack pulses arriving at the destination ,a cross-correlation LDoS attack de-tection method is proposed by using cyclic convolution .This method builds a detection sequence for the purpose of exploring the timing relationship for distributed LDoS attack pulses arriving at the specific destination .Through computing the relation between the constructed detection sequence and sampled network flow sequence ,the cross sequence is obtained .The cyclic convolution cross-re-lation algorithm is utilized to compute the precise time that the attack pulses arriving at the specific destination through different transferring channels .With nonperiodic monopulse prediction technology ,the periodic parameters of LDoS attack are estimated ,the relation characteristic of the pulse durations of LDoS attacks is extracted ,and the threshold rules are designed .Experimental results show that the proposed algorithm of LDoS attack detection based

  13. Correlation of calculated CNR and signal detectability on MR images

    Energy Technology Data Exchange (ETDEWEB)

    Ogura, Akio [Kyoto City Hospital (Japan); Higashida, Mitsuji; Yamazaki, Masaru; Inoue, Hiroshi

    1998-06-01

    To calculate the contrast-to-noise ratio (CNR) on magnetic resonance images, an equation selected to match each study is commonly used. The CNR values calculated using these equations may have their own characteristics. Therefore, the characteristics of four commonly calculated CNRs were evaluated in comparison with signal detectability. For the calculation of CNR, a phantom with five different solutions of CuSO{sub 4} was imaged using various scan sequences with different TR and NEX. These images, which had different levels of noise and contrast, were measured for averaged signal intensity and standard deviation of noise in the same ROIs (regions of interest). To define signal detectability, Burger`s phantom soaked in the CuSO{sub 4} solution was imaged with the same pulse sequences used to evaluate CNR. Burger`s phantom images were evaluated by five observers with a 50% confidence level. The characteristics of each CNR value were evaluated by correlating them with signal detectability. The results showed that some calculated CNRs indicated the noise element, but contrast element. From the point of view of signal detectability, the equation using the average of local variance and global variance with respect to coarse pixels was superior to others. (author)

  14. Fission Multiplicity Detection with Temporal Gamma-Neutron Discrimination from Higher-Order Time Correlation Statistics

    Energy Technology Data Exchange (ETDEWEB)

    Oberer, R.B.

    2002-11-12

    The current practice of nondestructive assay (NDA) of fissile materials using neutrons is dominated by the {sup 3}He detector. This has been the case since the mid 1980s when Fission Multiplicity Detection (FMD) was replaced with thermal well counters and neutron multiplicity counting (NMC). The thermal well counters detect neutrons by neutron capture in the {sup 3}He detector subsequent to moderation. The process of detection requires from 30 to 60 {micro}s. As will be explained in Section 3.3 the rate of detecting correlated neutrons (signal) from the same fission are independent of this time but the rate of accidental correlations (noise) are proportional to this time. The well counters are at a distinct disadvantage when there is a large source of uncorrelated neutrons present from ({alpha}, n) reactions for example. Plastic scintillating detectors, as were used in FMD, require only about 20 ns to detect neutrons from fission. One thousandth as many accidental coincidences are therefore accumulated. The major problem with the use of fast-plastic scintillation detectors, however, is that both neutrons and gamma rays are detected. The pulses from the two are indistinguishable in these detectors. For this thesis, a new technique was developed to use higher-order time correlation statistics to distinguish combinations of neutron and gamma ray detections in fast-plastic scintillation detectors. A system of analysis to describe these correlations was developed based on simple physical principles. Other sources of correlations from non-fission events are identified and integrated into the analysis developed for fission events. A number of ratios and metric are identified to determine physical properties of the source from the correlations. It is possible to determine both the quantity being measured and detection efficiency from these ratios from a single measurement without a separate calibration. To account for detector dead-time, an alternative analytical technique

  15. VEHICLE LOCALIZATION BY LIDAR POINT CORRELATION IMPROVED BY CHANGE DETECTION

    Directory of Open Access Journals (Sweden)

    A. Schlichting

    2016-06-01

    Full Text Available LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or even construction sites could lead to wrong localization results, we use a change detection algorithm to detect these objects in the reference data. If an object occurs in a certain number of measurements at the same position, we mark it and every containing point as static. In the next step, we merge the data of the single measurement epochs to one reference dataset, whereby we only use static points. Further, we also use a classification algorithm to detect trees. For the online localization of the vehicle, we use simulated data of a vertical aligned automotive LiDAR sensor. As we only want to use static objects in this case as well, we use a random forest classifier to detect dynamic scan points online. Since the automotive data is derived from the LiDAR Mobile Mapping System, we are able to use the labelled objects from the reference data generation step to create the training data and further to detect dynamic objects online. The localization then can be done by a point to image correlation method using only static objects. We achieved a localization standard deviation of about 5 cm (position and 0.06° (heading, and were able to successfully localize the vehicle in about 93 % of the cases along a trajectory of 13 km in Hannover, Germany.

  16. Vehicle Localization by LIDAR Point Correlation Improved by Change Detection

    Science.gov (United States)

    Schlichting, A.; Brenner, C.

    2016-06-01

    LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or even construction sites could lead to wrong localization results, we use a change detection algorithm to detect these objects in the reference data. If an object occurs in a certain number of measurements at the same position, we mark it and every containing point as static. In the next step, we merge the data of the single measurement epochs to one reference dataset, whereby we only use static points. Further, we also use a classification algorithm to detect trees. For the online localization of the vehicle, we use simulated data of a vertical aligned automotive LiDAR sensor. As we only want to use static objects in this case as well, we use a random forest classifier to detect dynamic scan points online. Since the automotive data is derived from the LiDAR Mobile Mapping System, we are able to use the labelled objects from the reference data generation step to create the training data and further to detect dynamic objects online. The localization then can be done by a point to image correlation method using only static objects. We achieved a localization standard deviation of about 5 cm (position) and 0.06° (heading), and were able to successfully localize the vehicle in about 93 % of the cases along a trajectory of 13 km in Hannover, Germany.

  17. Tools for Multimode Quantum Information: Modulation, Detection, and Spatial Quantum Correlations

    DEFF Research Database (Denmark)

    Lassen, Mikael Østergaard; Delaubert, Vincent; Janousek, Jirí

    2007-01-01

    We present here all the tools required for continuous variable parallel quantum information protocols based on spatial multi-mode quantum correlations and entanglement. We describe techniques for encoding and detecting this quantum information with high efficiency in the individual modes. We use ...

  18. Detecting and Correcting Based on Correlation for Ultrasonic by Image Phase Jitter%基于相关函数的超声图像方位跳变检测和校正

    Institute of Scientific and Technical Information of China (English)

    涂继辉; 李长文; 余厚全; 谢凯; 邹伟

    2011-01-01

    In order to solve the problem of appearing the phase jitter phenomenon on the television logging image, a method of detecting the phase jitter logging image is proposed, which is based on correlative feature. The correlative feature of ultrasound image logging between adjacent rows is used to automatically search the jumping position and phase difference, then the image according to the jumping position and phase difference cyclically moved, and ultimately the goal of correcting the image is achieved. The experimental results show that the algorithm can very accurately auto-correct the azimuth jump image, which has very important practical significance on processing the well logging data.%为了解决超声电视测井成像图像中出现的方位跳变问题,提出了一种利用相关特征来检测方位跳变测井图像的方法.该方法利用超声测井图像相邻行之间相关性来自动搜索图像出现方位跳变的深度位置和方位差,根据跳变深度位置和方位差来循环平移图像,最终实现校正图像的目标.实验结果证明,该方法能准确地自动校正方位跳变的图像.对实际测井资料的处理过程具有重要的实际意义.

  19. Gait Correlation Analysis Based Human Identification

    Directory of Open Access Journals (Sweden)

    Jinyan Chen

    2014-01-01

    Full Text Available Human gait identification aims to identify people by a sequence of walking images. Comparing with fingerprint or iris based identification, the most important advantage of gait identification is that it can be done at a distance. In this paper, silhouette correlation analysis based human identification approach is proposed. By background subtracting algorithm, the moving silhouette figure can be extracted from the walking images sequence. Every pixel in the silhouette has three dimensions: horizontal axis (x, vertical axis (y, and temporal axis (t. By moving every pixel in the silhouette image along these three dimensions, we can get a new silhouette. The correlation result between the original silhouette and the new one can be used as the raw feature of human gait. Discrete Fourier transform is used to extract features from this correlation result. Then, these features are normalized to minimize the affection of noise. Primary component analysis method is used to reduce the features’ dimensions. Experiment based on CASIA database shows that this method has an encouraging recognition performance.

  20. Correlation measure to detect time series distances, whence economy globalization

    Science.gov (United States)

    Miśkiewicz, Janusz; Ausloos, Marcel

    2008-11-01

    An instantaneous time series distance is defined through the equal time correlation coefficient. The idea is applied to the Gross Domestic Product (GDP) yearly increments of 21 rich countries between 1950 and 2005 in order to test the process of economic globalisation. Some data discussion is first presented to decide what (EKS, GK, or derived) GDP series should be studied. Distances are then calculated from the correlation coefficient values between pairs of series. The role of time averaging of the distances over finite size windows is discussed. Three network structures are next constructed based on the hierarchy of distances. It is shown that the mean distance between the most developed countries on several networks actually decreases in time, -which we consider as a proof of globalization. An empirical law is found for the evolution after 1990, similar to that found in flux creep. The optimal observation time window size is found ≃15 years.

  1. Adaptive, Model-Based Monitoring and Threat Detection

    Science.gov (United States)

    Valdes, Alfonso; Skinner, Keith

    2002-09-01

    We explore the suitability of model-based probabilistic techniques, such as Bayes networks, to the field of intrusion detection and alert report correlation. We describe a network intrusion detection system (IDS) using Bayes inference, wherein the knowledge base is encoded not as rules but as conditional probability relations between observables and hypotheses of normal and malicious usage. The same high-performance Bayes inference library was employed in a component of the Mission-Based Correlation effort, using an initial knowledge base that adaptively learns the security administrator's preference for alert priority and rank. Another major effort demonstrated probabilistic techniques in heterogeneous sensor correlation. We provide results for simulated attack data, live traffic, and the CyberPanel Grand Challenge Problem. Our results establish that model-based probabilistic techniques are an important complementary capability to signature-based methods in detection and correlation.

  2. Long-term visual tracking based on correlation filters

    Science.gov (United States)

    Wei, Quanlu; Lao, Songyang; Bai, Liang

    2017-03-01

    In order to accomplish the long term visual tracking task in complex scenes, solve problems of scale variation, appearance variation and tracking failure, a long term tracking algorithm is given based on the framework of collaborative correlation tracking. Firstly, we integrate several powerful features to boost the represent ability based on the kernel correlation filter, and extend the filter by embedding a scale factor into the kernelized matrix to handle the scale variation. Then, we use the Peak-Sidelobe Ratio to decide whether the object is tracked successfully, and a CUR filter for re-detection the object in case of tracking failure is learnt with random sampling. Corresponding experiment is performed on 17 challenging benchmark video sequences. Compared with the 8 existing state-of-the-art algorithms based on discriminative learning method, the results show that the proposed algorithm improves the tracking performance on several indexes, and is robust to complex scenes for long term visual tracking.

  3. Phase Correlation Based Iris Image Registration Model

    Institute of Scientific and Technical Information of China (English)

    Jun-Zhou Huang; Tie-Niu Tan; Li Ma; Yun-Hong Wang

    2005-01-01

    Iris recognition is one of the most reliable personal identification methods. In iris recognition systems, image registration is an important component. Accurately registering iris images leads to higher recognition rate for an iris recognition system. This paper proposes a phase correlation based method for iris image registration with sub-pixel accuracy.Compared with existing methods, it is insensitive to image intensity and can compensate to a certain extent the non-linear iris deformation caused by pupil movement. Experimental results show that the proposed algorithm has an encouraging performance.

  4. Theoretical NMR correlations based Structure Discussion

    Directory of Open Access Journals (Sweden)

    Junker Jochen

    2011-07-01

    Full Text Available Abstract The constitutional assignment of natural products by NMR spectroscopy is usually based on 2D NMR experiments like COSY, HSQC, and HMBC. The actual difficulty of the structure elucidation problem depends more on the type of the investigated molecule than on its size. The moment HMBC data is involved in the process or a large number of heteroatoms is present, a possibility of multiple solutions fitting the same data set exists. A structure elucidation software can be used to find such alternative constitutional assignments and help in the discussion in order to find the correct solution. But this is rarely done. This article describes the use of theoretical NMR correlation data in the structure elucidation process with WEBCOCON, not for the initial constitutional assignments, but to define how well a suggested molecule could have been described by NMR correlation data. The results of this analysis can be used to decide on further steps needed to assure the correctness of the structural assignment. As first step the analysis of the deviation of carbon chemical shifts is performed, comparing chemical shifts predicted for each possible solution with the experimental data. The application of this technique to three well known compounds is shown. Using NMR correlation data alone for the description of the constitutions is not always enough, even when including 13C chemical shift prediction.

  5. COMBINED TRANSMIT ANTENNA SELECTION AND DETECTION OVER SPATIAL CORRELATED MIMO SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    In this paper a method that combines transmit antenna selection and reduced-constellation detection in spatially correlated Multi-Input Multi-Output (MIMO) fading channels is presented. To mitigate the performance degradation caused by the use of antenna selection that is based on correlation among columns, an iterative receiver scheme that uses only a subset of the constellation points close to the expected symbol value estimated in the previous iteration is proposed. The size of the subset can adapt to the maximum correlation of the sub-matrix after the simple antenna selection. Furthermore, the error rate performance of the scheme under linear Minimum Mean Square Error (MMSE) or Ordered Successive Interference Cancellation (OSIC) for the first run detection and different interleaver lengths is investigated while the transmit antenna selection is considered. The simulation results show a significant advantage both for implementation complexity and for error rate performance under a fixed data rate.

  6. Detection of Impaired Cerebral Autoregulation Using Selected Correlation Analysis: A Validation Study

    Science.gov (United States)

    Brawanski, Alexander

    2017-01-01

    Multimodal brain monitoring has been utilized to optimize treatment of patients with critical neurological diseases. However, the amount of data requires an integrative tool set to unmask pathological events in a timely fashion. Recently we have introduced a mathematical model allowing the simulation of pathophysiological conditions such as reduced intracranial compliance and impaired autoregulation. Utilizing a mathematical tool set called selected correlation analysis (sca), correlation patterns, which indicate impaired autoregulation, can be detected in patient data sets (scp). In this study we compared the results of the sca with the pressure reactivity index (PRx), an established marker for impaired autoregulation. Mean PRx values were significantly higher in time segments identified as scp compared to segments showing no selected correlations (nsc). The sca based approach predicted cerebral autoregulation failure with a sensitivity of 78.8% and a specificity of 62.6%. Autoregulation failure, as detected by the results of both analysis methods, was significantly correlated with poor outcome. Sca of brain monitoring data detects impaired autoregulation with high sensitivity and sufficient specificity. Since the sca approach allows the simultaneous detection of both major pathological conditions, disturbed autoregulation and reduced compliance, it may become a useful analysis tool for brain multimodal monitoring data. PMID:28255331

  7. Detection of Impaired Cerebral Autoregulation Using Selected Correlation Analysis: A Validation Study

    Directory of Open Access Journals (Sweden)

    Martin A. Proescholdt

    2017-01-01

    Full Text Available Multimodal brain monitoring has been utilized to optimize treatment of patients with critical neurological diseases. However, the amount of data requires an integrative tool set to unmask pathological events in a timely fashion. Recently we have introduced a mathematical model allowing the simulation of pathophysiological conditions such as reduced intracranial compliance and impaired autoregulation. Utilizing a mathematical tool set called selected correlation analysis (sca, correlation patterns, which indicate impaired autoregulation, can be detected in patient data sets (scp. In this study we compared the results of the sca with the pressure reactivity index (PRx, an established marker for impaired autoregulation. Mean PRx values were significantly higher in time segments identified as scp compared to segments showing no selected correlations (nsc. The sca based approach predicted cerebral autoregulation failure with a sensitivity of 78.8% and a specificity of 62.6%. Autoregulation failure, as detected by the results of both analysis methods, was significantly correlated with poor outcome. Sca of brain monitoring data detects impaired autoregulation with high sensitivity and sufficient specificity. Since the sca approach allows the simultaneous detection of both major pathological conditions, disturbed autoregulation and reduced compliance, it may become a useful analysis tool for brain multimodal monitoring data.

  8. Spectral Correlation of Multicarrier Modulated Signals and Its Application for Signal Detection

    Science.gov (United States)

    Zhang, Haijian; Le Ruyet (Eurasipmember), Didier; Terré, Michel

    2009-12-01

    Spectral correlation theory for cyclostationary time-series signals has been studied for decades. Explicit formulas of spectral correlation function for various types of analog-modulated and digital-modulated signals are already derived. In this paper, we investigate and exploit the cyclostationarity characteristics for two kinds of multicarrier modulated (MCM) signals: conventional OFDM and filter bank based multicarrier (FBMC) signals. The spectral correlation characterization of MCM signal can be described by a special linear periodic time-variant (LPTV) system. Using this LPTV description, we have derived the explicit theoretical formulas of nonconjugate and conjugate cyclic autocorrelation function (CAF) and spectral correlation function (SCF) for OFDM and FBMC signals. According to theoretical spectral analysis, Cyclostationary Signatures (CS) are artificially embedded into MCM signal and a low-complexity signature detector is, therefore, presented for detecting MCM signal. Theoretical analysis and simulation results demonstrate the efficiency and robustness of this CS detector compared to traditionary energy detector.

  9. Spectral Correlation of Multicarrier Modulated Signals and Its Application for Signal Detection

    Directory of Open Access Journals (Sweden)

    Zhang Haijian

    2010-01-01

    Full Text Available Spectral correlation theory for cyclostationary time-series signals has been studied for decades. Explicit formulas of spectral correlation function for various types of analog-modulated and digital-modulated signals are already derived. In this paper, we investigate and exploit the cyclostationarity characteristics for two kinds of multicarrier modulated (MCM signals: conventional OFDM and filter bank based multicarrier (FBMC signals. The spectral correlation characterization of MCM signal can be described by a special linear periodic time-variant (LPTV system. Using this LPTV description, we have derived the explicit theoretical formulas of nonconjugate and conjugate cyclic autocorrelation function (CAF and spectral correlation function (SCF for OFDM and FBMC signals. According to theoretical spectral analysis, Cyclostationary Signatures (CS are artificially embedded into MCM signal and a low-complexity signature detector is, therefore, presented for detecting MCM signal. Theoretical analysis and simulation results demonstrate the efficiency and robustness of this CS detector compared to traditionary energy detector.

  10. An edge-adaptive demosaicking method based on image correlation

    Institute of Scientific and Technical Information of China (English)

    贾晓芬; 赵佰亭; 周孟然; 陈兆权

    2015-01-01

    To reduce the cost, size and complexity, a consumer digital camera usually uses a single sensor overlaid with a color filter array (CFA) to sample one of the red−green−blue primary color values, and uses demosaicking algorithm to estimate the missing color values at each pixel. A novel image correlation and support vector machine (SVM) based edge-adaptive algorithm was proposed, which can reduce edge artifacts and false color artifacts, effectively. Firstly, image pixels were separated into edge region and smooth region with an edge detection algorithm. Then, a hybrid approach switching between a simple demosaicking algorithm on the smooth region and SVM based demosaicking algorithm on the edge region was performed. Image spatial and spectral correlations were employed to create middle planes for the interpolation. Experimental result shows that the proposed approach produced visually pleasing full-color result images and obtained higher CPSNR and smaller S-CIELAB *abDE than other conventional demosaicking algorithms.

  11. Detecting Nanodomains in Living Cell Membrane by Fluorescence Correlation Spectroscopy

    Science.gov (United States)

    He, Hai-Tao; Marguet, Didier

    2011-05-01

    Cell membranes actively participate in numerous cellular functions. Inasmuch as bioactivities of cell membranes are known to depend crucially on their lateral organization, much effort has been focused on deciphering this organization on different length scales. Within this context, the concept of lipid rafts has been intensively discussed over recent years. In line with its ability to measure diffusion parameters with great precision, fluorescence correlation spectroscopy (FCS) measurements have been made in association with innovative experimental strategies to monitor modes of molecular lateral diffusion within the plasma membrane of living cells. These investigations have allowed significant progress in the characterization of the cell membrane lateral organization at the suboptical level and have provided compelling evidence for the in vivo existence of raft nanodomains. We review these FCS-based studies and the characteristic structural features of raft nanodomains. We also discuss the findings in regards to the current view of lipid rafts as a general membrane-organizing principle.

  12. Detecting long-range correlation with detrended fluctuation analysis: Application to BWR stability

    Energy Technology Data Exchange (ETDEWEB)

    Espinosa-Paredes, Gilberto [Departamento de Ingenieria de Procesos e Hidraulica, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico, DF 09340 (Mexico)]. E-mail: gepe@xanum.uam.mx; Alvarez-Ramirez, Jose [Departamento de Ingenieria de Procesos e Hidraulica, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico, DF 09340 (Mexico); Vazquez, Alejandro [Departamento de Ingenieria de Procesos e Hidraulica, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico, DF 09340 (Mexico)

    2006-11-15

    The aim of this paper is to explore the application of detrended fluctuation analysis (DFA) to study boiling water reactor stability. DFA is a scaling method commonly used for detecting long-range correlations in non-stationary time series. This method is based on the random walk theory and was applied to neutronic power signal of Forsmark stability benchmark. Our results shows that the scaling properties breakdown during unstable oscillations.

  13. Ionizing particle detection based on phononic crystals

    Science.gov (United States)

    Aly, Arafa H.; Mehaney, Ahmed; Eissa, Mostafa F.

    2015-08-01

    Most conventional radiation detectors are based on electronic or photon collections. In this work, we introduce a new and novel type of ionizing particle detector based on phonon collection. Helium ion radiation treats tumors with better precision. There are nine known isotopes of helium, but only helium-3 and helium-4 are stable. Helium-4 is formed in fusion reactor technology and in enormous quantities during Big Bang nucleo-synthesis. In this study, we introduce a technique for helium-4 ion detection (sensing) based on the innovative properties of the new composite materials known as phononic crystals (PnCs). PnCs can provide an easy and cheap technique for ion detection compared with conventional methods. PnC structures commonly consist of a periodic array of two or more materials with different elastic properties. The two materials are polymethyl-methacrylate and polyethylene polymers. The calculations showed that the energies lost to target phonons are maximized at 1 keV helium-4 ion energy. There is a correlation between the total phonon energies and the transmittance of PnC structures. The maximum transmission for phonons due to the passage of helium-4 ions was found in the case of making polyethylene as a first layer in the PnC structure. Therefore, the concept of ion detection based on PnC structure is achievable.

  14. Ionizing particle detection based on phononic crystals

    Energy Technology Data Exchange (ETDEWEB)

    Aly, Arafa H., E-mail: arafa16@yahoo.com, E-mail: arafa.hussien@science.bsu.edu.eg; Mehaney, Ahmed; Eissa, Mostafa F. [Physics Department, Faculty of Science, Beni-Suef University, Beni-Suef (Egypt)

    2015-08-14

    Most conventional radiation detectors are based on electronic or photon collections. In this work, we introduce a new and novel type of ionizing particle detector based on phonon collection. Helium ion radiation treats tumors with better precision. There are nine known isotopes of helium, but only helium-3 and helium-4 are stable. Helium-4 is formed in fusion reactor technology and in enormous quantities during Big Bang nucleo-synthesis. In this study, we introduce a technique for helium-4 ion detection (sensing) based on the innovative properties of the new composite materials known as phononic crystals (PnCs). PnCs can provide an easy and cheap technique for ion detection compared with conventional methods. PnC structures commonly consist of a periodic array of two or more materials with different elastic properties. The two materials are polymethyl-methacrylate and polyethylene polymers. The calculations showed that the energies lost to target phonons are maximized at 1 keV helium-4 ion energy. There is a correlation between the total phonon energies and the transmittance of PnC structures. The maximum transmission for phonons due to the passage of helium-4 ions was found in the case of making polyethylene as a first layer in the PnC structure. Therefore, the concept of ion detection based on PnC structure is achievable.

  15. Detection System for Neutron $\\beta$ Decay Correlations in the UCNB and Nab experiments

    CERN Document Server

    Broussard, L J; Adamek, E R; Baeßler, S; Birge, N; Blatnik, M; Bowman, J D; Brandt, A E; Brown, M; Burkhart, J; Callahan, N B; Clayton, S M; Crawford, C; Cude-Woods, C; Currie, S; Dees, E B; Ding, X; Fomin, N; Frlez, E; Fry, J; Gray, F E; Hasan, S; Hickerson, K P; Hoagland, J; Holley, A T; Ito, T M; Klein, A; Li, H; Liu, C -Y; Makela, M F; McGaughey, P L; Mirabal-Martinez, J; Morris, C L; Ortiz, J D; Pattie, R W; Penttilä, S I; Plaster, B; Počanić, D; Ramsey, J C; Salas-Bacci, A; Salvat, D J; Saunders, A; Seestrom, S J; Sjue, S K L; Sprow, A P; Tang, Z; Vogelaar, R B; Vorndick, B; Wang, Z; Wei, W; Wexler, J; Wilburn, W S; Womack, T L; Young, A R

    2016-01-01

    We describe a detection system designed for precise measurements of angular correlations in neutron $\\beta$ decay. The system is based on thick, large area, highly segmented silicon detectors developed in collaboration with Micron Semiconductor, Ltd. The prototype system meets specifications for $\\beta$ electron detection with energy thresholds below 10 keV, energy resolution of $\\sim$3 keV FWHM, and rise time of $\\sim$50 ns with 19 of the 127 detector pixels instrumented. Using ultracold neutrons at the Los Alamos Neutron Science Center, we have demonstrated the coincident detection of $\\beta$ particles and recoil protons from neutron $\\beta$ decay. The fully instrumented detection system will be implemented in the UCNB and Nab experiments, to determine the neutron $\\beta$ decay parameters $B$, $a$, and $b$.

  16. Detection system for neutron β decay correlations in the UCNB and Nab experiments

    Science.gov (United States)

    Broussard, L. J.; Zeck, B. A.; Adamek, E. R.; Baeßler, S.; Birge, N.; Blatnik, M.; Bowman, J. D.; Brandt, A. E.; Brown, M.; Burkhart, J.; Callahan, N. B.; Clayton, S. M.; Crawford, C.; Cude-Woods, C.; Currie, S.; Dees, E. B.; Ding, X.; Fomin, N.; Frlez, E.; Fry, J.; Gray, F. E.; Hasan, S.; Hickerson, K. P.; Hoagland, J.; Holley, A. T.; Ito, T. M.; Klein, A.; Li, H.; Liu, C.-Y.; Makela, M. F.; McGaughey, P. L.; Mirabal-Martinez, J.; Morris, C. L.; Ortiz, J. D.; Pattie, R. W.; Penttilä, S. I.; Plaster, B.; Počanić, D.; Ramsey, J. C.; Salas-Bacci, A.; Salvat, D. J.; Saunders, A.; Seestrom, S. J.; Sjue, S. K. L.; Sprow, A. P.; Tang, Z.; Vogelaar, R. B.; Vorndick, B.; Wang, Z.; Wei, W.; Wexler, J.; Wilburn, W. S.; Womack, T. L.; Young, A. R.

    2017-03-01

    We describe a detection system designed for precise measurements of angular correlations in neutron β decay. The system is based on thick, large area, highly segmented silicon detectors developed in collaboration with Micron Semiconductor, Ltd. The prototype system meets specifications for β electron detection with energy thresholds below 10 keV, energy resolution of ∼3 keV FWHM, and rise time of ∼50 ns with 19 of the 127 detector pixels instrumented. Using ultracold neutrons at the Los Alamos Neutron Science Center, we have demonstrated the coincident detection of β particles and recoil protons from neutron β decay. The fully instrumented detection system will be implemented in the UCNB and Nab experiments to determine the neutron β decay parameters B, a, and b.

  17. Bacteriophage-Based Pathogen Detection

    Science.gov (United States)

    Ripp, Steven

    Considered the most abundant organism on Earth, at a population approaching 1031, bacteriophage, or phage for short, mediate interactions with myriad bacterial hosts that has for decades been exploited in phage typing schemes for signature identification of clinical, food-borne, and water-borne pathogens. With over 5,000 phage being morphologically characterized and grouped as to susceptible host, there exists an enormous cache of bacterial-specific sensors that has more recently been incorporated into novel bio-recognition assays with heightened sensitivity, specificity, and speed. These assays take many forms, ranging from straightforward visualization of labeled phage as they attach to their specific bacterial hosts to reporter phage that genetically deposit trackable signals within their bacterial hosts to the detection of progeny phage or other uniquely identifiable elements released from infected host cells. A comprehensive review of these and other phage-based detection assays, as directed towards the detection and monitoring of bacterial pathogens, will be provided in this chapter.

  18. Detection of correlated fragments in a sequence of images by superimposed Fourier holograms

    Science.gov (United States)

    Pavlov, A. V.

    2016-08-01

    The problem of detecting correlated fragments in a sequence of images recorded by the superimposing holograms within the Fourier holography scheme with angular multiplication of a spatially modulated reference beam is considered. The approach to the solution of this problem is based on the properties of the variance of the image sum. It is shown that this problem can be solved by providing a constant distance between the signal and reference images when recording superimposed holograms and a partial mutual correlatedness of reference images. The detection efficiency is analysed from the point of view of estimated image data capacity, the degree of mutual correlation of reference images, and the hologram recording conditions. The results of a numerical experiment under the most complicated conditions (representation of images by realisations of homogeneous random fields) confirm the theoretical conclusions.

  19. Coincidence detection of spatially correlated photon pairs with a monolithic time-resolving detector array

    CERN Document Server

    Unternährer, Manuel; Gasparini, Leonardo; Stoppa, David; Stefanov, André

    2016-01-01

    We demonstrate coincidence measurements of spatially entangled photons by means of a novel type of multi-pixel based detection array. The adopted sensor is a fully digital 8$\\times$16 silicon photomultiplier array allowing not only photon counting but also per-pixel time stamping of the arrived photons with a resolution of 65 ps. Together with a frame rate of 500 kfps, this property exceeds the capabilities of conventional charge-coupled device cameras which have become of growing interest for the detection of transversely correlated photon pairs. The sensor is used to measure a second-order correlation function for various non-collinear configurations of entangled photons generated by spontaneous parametric down-conversion. The experimental results are compared to theory.

  20. Trace gas detection and monitoring with the Digital Array Gas-correlation Radiometer (DAGR)

    Science.gov (United States)

    Gordley, Larry L.; Hervig, Mark E.; Fish, Chad; McHugh, Martin J.

    2011-05-01

    We present the first results from a Digital Array Gas-correlation Radiometer (DAGR) prototype sensor, and discuss applications in remote sensing of trace gases. The sensor concept is based on traditional and reliable Gas Filter Correlation Radiometry (GFCR), but overcomes the limitations in solar backscatter applications. The DAGR sensor design can be scaled to the size of a digital camera and is ideal for downlooking detection of gases in the boundary layer, where solar backscatter measurements are needed to overcome the lack of thermal contrast in the IR. Ground-based portable DAGR sensors can monitor carbon sequestration sites or industrial facilities. Aircraft or UAV deployment can quickly survey large areas and are particularly well suited for gas leak detection or carbon monitoring. From space-based platforms, Doppler modulation can be exploited to produce an extremely fine spectral resolution with effective resolving power exceeding 100,000. Such space-based DAGR observations could provide near-global sensing of climatically important species such as such as CO2, CO, CH4, O3 and N2O. Planetary science applications include detection and mapping of biomarkers in the Martian atmosphere.

  1. Circle Detection Based on HSI Color Space

    Institute of Scientific and Technical Information of China (English)

    MAOXia; LIXing-xin; XUEYu-li

    2005-01-01

    A method based on HSI color space is presented to solve the problem of circle detection from color images. In terms of the evaluation to the edge detection method based on intensity, the edge detection based on hue is chosen to process the color image, and the simplified calculation of hue transform is discussed. Then the algorithm of circle detection based on Canny edge detection is proposed. Due to the dispersive distribution of the detected result, Hough transformation and template smooth are used in circle detection, and the proposed method gives a quite good result.

  2. Application of detecting algorithm based on network

    Institute of Scientific and Technical Information of China (English)

    张凤斌; 杨永田; 江子扬; 孙冰心

    2004-01-01

    Because currently intrusion detection systems cannot detect undefined intrusion behavior effectively,according to the robustness and adaptability of the genetic algorithms, this paper integrates the genetic algorithms into an intrusion detection system, and a detection algorithm based on network traffic is proposed. This algorithm is a real-time and self-study algorithm and can detect undefined intrusion behaviors effectively.

  3. Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations

    Science.gov (United States)

    Kwapień, Jarosław; Oświecimka, Paweł; DroŻdŻ, Stanisław

    2015-11-01

    The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρDCCA works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρDCCA that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρq not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρq works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q -dependent counterpart of the correlation matrices and then to the network representation.

  4. Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations

    CERN Document Server

    Kwapien, Jaroslaw; Drozdz, Stanislaw

    2015-01-01

    The detrended cross-correlation coefficient $\\rho_{\\rm DCCA}$ has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, non-stationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analogue of the Pearson coefficient in the case of the fluctuation analysis. The coefficient $\\rho_{\\rm DCCA}$ works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of $\\rho_{\\rm DCCA}$ that exploits the multifractal versions of DFA and DCCA: MFDFA and MFCCA, respectively. The resulting new coefficient $\\rho_q$ not only is able to quantify the strength of correlations, but ...

  5. Edge detection in the potentialfi eld using the correlation coeffi cients of multidirectional standard deviations

    Institute of Scientific and Technical Information of China (English)

    Xu Meng-Long; Yang Chang-Bao; Wu Yan-Gang; Chen Jing-Yi; Huan Heng-Fei

    2015-01-01

    Most edge-detection methods rely on calculating gradient derivatives of the potential field, a process that is easily affected by noise and is therefore of low stability. We propose a new edge-detection method named correlation coeffi cient of multidirectional standard deviations (CCMS) that is solely based on statistics. First, we prove the reliability of the proposed method using a single model and then a combination of models. The proposed method is evaluated by comparing the results with those obtained by other edge-detection methods. The CCMS method offers outstanding recognition, retains the sharpness of details, and has low sensitivity to noise. We also applied the CCMS method to Bouguer anomaly data of a potash deposit in Laos. The applicability of the CCMS method is shown by comparing the inferred tectonic framework to that inferred from remote sensing (RS) data.

  6. Improved maximum average correlation height filter with adaptive log base selection for object recognition

    Science.gov (United States)

    Tehsin, Sara; Rehman, Saad; Awan, Ahmad B.; Chaudry, Qaiser; Abbas, Muhammad; Young, Rupert; Asif, Afia

    2016-04-01

    Sensitivity to the variations in the reference image is a major concern when recognizing target objects. A combinational framework of correlation filters and logarithmic transformation has been previously reported to resolve this issue alongside catering for scale and rotation changes of the object in the presence of distortion and noise. In this paper, we have extended the work to include the influence of different logarithmic bases on the resultant correlation plane. The meaningful changes in correlation parameters along with contraction/expansion in the correlation plane peak have been identified under different scenarios. Based on our research, we propose some specific log bases to be used in logarithmically transformed correlation filters for achieving suitable tolerance to different variations. The study is based upon testing a range of logarithmic bases for different situations and finding an optimal logarithmic base for each particular set of distortions. Our results show improved correlation and target detection accuracies.

  7. Are Eurozone Fixed Income Markets Integrated? An Analysis Based on Wavelet Multiple Correlation and Cross Correlation

    Directory of Open Access Journals (Sweden)

    Arif Billah Dar

    2014-01-01

    Full Text Available This paper investigates the synchronization of fixed income markets within Eurozone countries using the new wavelet based methodology. Conventional wavelet methods that use multivariate set of variables to calculate pairwise correlation and cross correlation lead to spurious correlation due to possible relationships with other variables, amplification of type-1 errors, and results, in the form of large set of erroneous graphs. Given these disadvantages of conventional wavelet based pairwise correlation and cross-correlation method, we avoid these limitations by using wavelet multiple correlation and multiple cross correlations to analyze the relationships in Eurozone fixed income markets. Our results based on this methodology indicate that Eurozone fixed income markets are highly integrated and this integration grows with timescales, and hence there is almost no scope for independent monetary policy and bond diversification in these countries.

  8. A new technique for the detection of large scale landslides in glacio-lacustrine deposits using image correlation based upon aerial imagery: A case study from the French Alps

    Science.gov (United States)

    Fernandez, Paz; Whitworth, Malcolm

    2016-10-01

    Landslide monitoring has benefited from recent advances in the use of image correlation of high resolution optical imagery. However, this approach has typically involved satellite imagery that may not be available for all landslides depending on their time of movement and location. This study has investigated the application of image correlation techniques applied to a sequence of aerial imagery to an active landslide in the French Alps. We apply an indirect landslide monitoring technique (COSI-Corr) based upon the cross-correlation between aerial photographs, to obtain horizontal displacement rates. Results for the 2001-2003 time interval are presented, providing a spatial model of landslide activity and motion across the landslide, which is consistent with previous studies. The study has identified areas of new landslide activity in addition to known areas and through image decorrelation has identified and mapped two new lateral landslides within the main landslide complex. This new approach for landslide monitoring is likely to be of wide applicability to other areas characterised by complex ground displacements.

  9. A Correlated Microwave-Acoustic Imaging method for early-stage cancer detection.

    Science.gov (United States)

    Gao, Fei; Zheng, Yuanjin

    2012-01-01

    Microwave-based imaging technique shows large potential in detecting early-stage cancer due to significant dielectric contrast between tumor and surrounding healthy tissue. In this paper, we present a new way named Correlated Microwave-Acoustic Imaging (CMAI) of combining two microwave-based imaging modalities: confocal microwave imaging(CMI) by detecting scattered microwave signal, and microwave-induced thermo-acoustic imaging (TAI) by detecting induced acoustic signal arising from microwave energy absorption and thermal expansion. Necessity of combining CMI and TAI is analyzed theoretically, and by applying simple algorithm to CMI and TAI separately, we propose an image correlation approach merging CMI and TAI together to achieve better performance in terms of resolution and contrast. Preliminary numerical simulation shows promising results in case of low contrast and large variation scenarios. A UWB transmitter is designed and tested for future complete system implementation. This preliminary study inspires us to develop a new medical imaging modality CMAI to achieve real-time, high resolution and high contrast simultaneously.

  10. DSN Beowulf Cluster-Based VLBI Correlator

    Science.gov (United States)

    Rogstad, Stephen P.; Jongeling, Andre P.; Finley, Susan G.; White, Leslie A.; Lanyi, Gabor E.; Clark, John E.; Goodhart, Charles E.

    2009-01-01

    The NASA Deep Space Network (DSN) requires a broadband VLBI (very long baseline interferometry) correlator to process data routinely taken as part of the VLBI source Catalogue Maintenance and Enhancement task (CAT M&E) and the Time and Earth Motion Precision Observations task (TEMPO). The data provided by these measurements are a crucial ingredient in the formation of precision deep-space navigation models. In addition, a VLBI correlator is needed to provide support for other VLBI related activities for both internal and external customers. The JPL VLBI Correlator (JVC) was designed, developed, and delivered to the DSN as a successor to the legacy Block II Correlator. The JVC is a full-capability VLBI correlator that uses software processes running on multiple computers to cross-correlate two-antenna broadband noise data. Components of this new system (see Figure 1) consist of Linux PCs integrated into a Beowulf Cluster, an existing Mark5 data storage system, a RAID array, an existing software correlator package (SoftC) originally developed for Delta DOR Navigation processing, and various custom- developed software processes and scripts. Parallel processing on the JVC is achieved by assigning slave nodes of the Beowulf cluster to process separate scans in parallel until all scans have been processed. Due to the single stream sequential playback of the Mark5 data, some ramp-up time is required before all nodes can have access to required scan data. Core functions of each processing step are accomplished using optimized C programs. The coordination and execution of these programs across the cluster is accomplished using Pearl scripts, PostgreSQL commands, and a handful of miscellaneous system utilities. Mark5 data modules are loaded on Mark5 Data systems playback units, one per station. Data processing is started when the operator scans the Mark5 systems and runs a script that reads various configuration files and then creates an experiment-dependent status database

  11. Trinocular Stereo Matching Based on Correlations Between Baselines and Disparities

    Institute of Scientific and Technical Information of China (English)

    GUANYepeng; GUWeikang

    2004-01-01

    Gray correlation technique is utilized to take the multi-peak feature points with gray correlation coefficients less than a certain range of maximal correlation coefficient as a potential candidate matching set. There exists the maximal correlation between the correct disparities and their corresponding baselines. A trinocular stereo matching algorithm is proposed based on correlations between the baselines and disparities. After computing the correlations between the baselines and disparities, the unique matches can be determined by maximal correlation coefficient. It is proved that the algorithm proposed is valid and credible by 3-D reconstruction on two pairs of actual natural stereo images.

  12. Reliability Distribution of Numerical Control Lathe Based on Correlation Analysis

    Institute of Scientific and Technical Information of China (English)

    Xiaoyan Qi; Guixiang Shen; Yingzhi Zhang; Shuguang Sun; Bingkun Chen

    2016-01-01

    Combined Reliability distribution with correlation analysis, a new method has been proposed to make Reliability distribution where considering the elements about structure correlation and failure correlation of subsystems. Firstly, we make a sequence for subsystems by means of TOPSIS which comprehends the considerations of Reliability allocation, and introducing a Copula connecting function to set up a distribution model based on structure correlation, failure correlation and target correlation, and then acquiring reliability target area of all subsystems by Matlab. In this method, not only the traditional distribution considerations are concerned, but also correlation influences are involved, to achieve supplementing information and optimizing distribution.

  13. Subspace decomposition-based correlation matrix multiplication

    Institute of Scientific and Technical Information of China (English)

    Cheng Hao; Guo Wei; Yu Jingdong

    2008-01-01

    The correlation matrix, which is widely used in eigenvalue decomposition (EVD) or singular value decomposition (SVD), usually can be denoted by R = E[yiy'i]. A novel method for constructing the correlation matrix R is proposed. The proposed algorithm can improve the resolving power of the signal eigenvalues and overcomes the shortcomings of the traditional subspace methods, which cannot be applied to low SNR. Then the proposed method is applied to the direct sequence spread spectrum (DSSS) signal's signature sequence estimation.The performance of the proposed algorithm is analyzed, and some illustrative simulation results are presented.

  14. Edge detection based on morphological amoebas

    CERN Document Server

    Lee, Won Yeol; Kim, Se Yun; Lim, Jae Young; Lim, Dong Hoon

    2011-01-01

    Detecting the edges of objects within images is critical for quality image processing. We present an edge-detecting technique that uses morphological amoebas that adjust their shape based on variation in image contours. We evaluate the method both quantitatively and qualitatively for edge detection of images, and compare it to classic morphological methods. Our amoeba-based edge-detection system performed better than the classic edge detectors.

  15. Cross-Correlation Detection of Point Sources in the WMAP First Year Data

    Institute of Scientific and Technical Information of China (English)

    Jian-Yin Nie; Shuang-Nan Zhang

    2007-01-01

    We apply a Cross-Correlation (CC) method developed previously for detecting gamma-ray point sources to the WMAP first year data by using the Point-Spread Function of WMAP and obtain a full sky CC coefficient map. We find that the CC method is a powerful tool to examine the WMAP foreground residuals which can be further cleaned accordingly. Evident foreground signals are found in the WMAP foreground cleaned maps and the Tegmark cleaned map. In this process 101 point sources are detected, and 26 of them are new sources additional to the originally listed WMAP 208 sources. We estimate the flux of these new sources and verify them by another method. As a result, a revised mask file based on the WMAP first year data is produced by including these new sources.

  16. An attempt to determine the effect of increase of observation correlations on detectability and identifiability of a single gross error

    Science.gov (United States)

    Prószyński, Witold; Kwaśniak, Mieczysław

    2016-12-01

    The paper presents the results of investigating the effect of increase of observation correlations on detectability and identifiability of a single gross error, the outlier test sensitivity and also the response-based measures of internal reliability of networks. To reduce in a research a practically incomputable number of possible test options when considering all the non-diagonal elements of the correlation matrix as variables, its simplest representation was used being a matrix with all non-diagonal elements of equal values, termed uniform correlation. By raising the common correlation value incrementally, a sequence of matrix configurations could be obtained corresponding to the increasing level of observation correlations. For each of the measures characterizing the above mentioned features of network reliability the effect is presented in a diagram form as a function of the increasing level of observation correlations. The influence of observation correlations on sensitivity of the w-test for correlated observations (Förstner 1983, Teunissen 2006) is investigated in comparison with the original Baarda's w-test designated for uncorrelated observations, to determine the character of expected sensitivity degradation of the latter when used for correlated observations. The correlation effects obtained for different reliability measures exhibit mutual consistency in a satisfactory extent. As a by-product of the analyses, a simple formula valid for any arbitrary correlation matrix is proposed for transforming the Baarda's w-test statistics into the w-test statistics for correlated observations.

  17. Searching non-impulsive earthquakes using a full-waveform, cross-correlation detection method.

    Science.gov (United States)

    alinne solano, ericka; Hjorleifsdottir, Vala

    2016-04-01

    Some seismic events, which have low P-wave amplitude, pass undetected by regional or global networks. A subset of these events occur due to fast mass movement as in the case of rapid glacial movements (Ekström, et al., 2003; Ekström, et al., 2006) or landslides (Ekstrom and Stark, 2013). Some other events depleted in high frequencies are related to volcanic activity (e.g. Schuler and Ekstrom, 2009) or to non-volcanic tremors (Obara, 2002). Furthermore, non-impulsive earthquakes have been located on oceanic transform faults (OTF) (Abercrombie and Ekstrom, 2001). A suite of methods can be used to detect these non-impulsive events. Correlation, matched filter, or template event methods (e.g. Schaff and Waldhauser 2010; Rubinstein & Beroza 2007) are very efficient for detecting smaller events occurring in a similar place and with the same mechanism as a larger template event. One such method (Ekström, 2006), that is applied on the scale of the globe, routinely detects events with magnitudes around Mw 5 and larger. In this work we want to lower the detection threshold by using shorter period records registered by regional networks together with a full-waveform detection method based on time reversal schemes (Solano, et al., in prep.). The method uses continuous observed seismograms, together with moment tensor responses calculated for a 3D structure. Looking for events on the East Pacific Rise (EPR) around 9 N in one month of data from the National Seismological broadband Network (Servicio Sismologico Nacional, SSN), we found one new event. However, we also had 435 false detections due to high noise levels at several stations, gaps in the data or detection of teleseismic phases. To manually discard these events is a time consuming task that should be automated. We are working on several strategies, including weighting the input traces by their signal to noise ratio, correlation of a template peak associated to the detection function and the coincidence in time of the

  18. Exploring the limits of waveform correlation event detection as applied to three earthquake aftershock sequences.

    Energy Technology Data Exchange (ETDEWEB)

    Resor, Megan E.; Carr, Dorthe Bame; Young, Christopher John

    2010-05-01

    Swarms of earthquakes and/or aftershock sequences can dramatically increase the level of seismicity in a region for a period of time lasting from days to months, depending on the swarm or sequence. Such occurrences can provide a large amount of useful information to seismologists. For those who monitor seismic events for possible nuclear explosions, however, these swarms/sequences are a nuisance. In an explosion monitoring system, each event must be treated as a possible nuclear test until it can be proven, to a high degree of confidence, not to be. Seismic events recorded by the same station with highly correlated waveforms almost certainly have a similar location and source type, so clusters of events within a swarm can quickly be identified as earthquakes. We have developed a number of tools that can be used to exploit the high degree of waveform similarity expected to be associated with swarms/sequences. Dendro Tool measures correlations between known events. The Waveform Correlation Detector is intended to act as a detector, finding events in raw data which correlate with known events. The Self Scanner is used to find all correlated segments within a raw data steam and does not require an event library. All three techniques together provide an opportunity to study the similarities of events in an aftershock sequence in different ways. To comprehensively characterize the benefits and limits of waveform correlation techniques, we studied 3 aftershock sequences, using our 3 tools, at multiple stations. We explored the effects of station distance and event magnitudes on correlation results. Lastly, we show the reduction in detection threshold and analyst workload offered by waveform correlation techniques compared to STA/LTA based detection. We analyzed 4 days of data from each aftershock sequence using all three methods. Most known events clustered in a similar manner across the toolsets. Up to 25% of catalogued events were found to be a member of a cluster. In

  19. Nonlocality in many-body quantum systems detected with two-body correlators

    Energy Technology Data Exchange (ETDEWEB)

    Tura, J., E-mail: jordi.tura@icfo.es [ICFO—Institut de Ciencies Fotoniques, Mediterranean Technology Park, 08860 Castelldefels (Barcelona) (Spain); Augusiak, R.; Sainz, A.B. [ICFO—Institut de Ciencies Fotoniques, Mediterranean Technology Park, 08860 Castelldefels (Barcelona) (Spain); Lücke, B.; Klempt, C. [Institut für Quantenoptik, Leibniz Universität Hannover, Welfengarten 1, D-30167 Hannover (Germany); Lewenstein, M.; Acín, A. [ICFO—Institut de Ciencies Fotoniques, Mediterranean Technology Park, 08860 Castelldefels (Barcelona) (Spain); ICREA—Institució Catalana de Recerca i Estudis Avançats, Lluis Campanys 3, 08010 Barcelona (Spain)

    2015-11-15

    Contemporary understanding of correlations in quantum many-body systems and in quantum phase transitions is based to a large extent on the recent intensive studies of entanglement in many-body systems. In contrast, much less is known about the role of quantum nonlocality in these systems, mostly because the available multipartite Bell inequalities involve high-order correlations among many particles, which are hard to access theoretically, and even harder experimentally. Standard, “theorist- and experimentalist-friendly” many-body observables involve correlations among only few (one, two, rarely three...) particles. Typically, there is no multipartite Bell inequality for this scenario based on such low-order correlations. Recently, however, we have succeeded in constructing multipartite Bell inequalities that involve two- and one-body correlations only, and showed how they revealed the nonlocality in many-body systems relevant for nuclear and atomic physics [Tura et al., Science 344 (2014) 1256]. With the present contribution we continue our work on this problem. On the one hand, we present a detailed derivation of the above Bell inequalities, pertaining to permutation symmetry among the involved parties. On the other hand, we present a couple of new results concerning such Bell inequalities. First, we characterize their tightness. We then discuss maximal quantum violations of these inequalities in the general case, and their scaling with the number of parties. Moreover, we provide new classes of two-body Bell inequalities which reveal nonlocality of the Dicke states—ground states of physically relevant and experimentally realizable Hamiltonians. Finally, we shortly discuss various scenarios for nonlocality detection in mesoscopic systems of trapped ions or atoms, and by atoms trapped in the vicinity of designed nanostructures.

  20. Vision-based Vehicle Detection Survey

    Directory of Open Access Journals (Sweden)

    Alex David S

    2016-03-01

    Full Text Available Nowadays thousands of drivers and passengers were losing their lives every year on road accident, due to deadly crashes between more than one vehicle. There are number of many research focuses were dedicated to the development of intellectual driver assistance systems and autonomous vehicles over the past decade, which reduces the danger by monitoring the on-road environment. In particular, researchers attracted towards the on-road detection of vehicles in recent years. Different parameters have been analyzed in this paper which includes camera placement and the various applications of monocular vehicle detection, common features and common classification methods, motion- based approaches and nighttime vehicle detection and monocular pose estimation. Previous works on the vehicle detection listed based on camera poisons, feature based detection and motion based detection works and night time detection.

  1. Collaborative Filtering Algorithms Based on Kendall Correlation in Recommender Systems

    Institute of Scientific and Technical Information of China (English)

    YAO Yu; ZHU Shanfeng; CHEN Xinmeng

    2006-01-01

    In this work, Kendall correlation based collaborative filtering algorithms for the recommender systems are proposed. The Kendall correlation method is used to measure the correlation amongst users by means of considering the relative order of the users' ratings. Kendall based algorithm is based upon a more general model and thus could be more widely applied in e-commerce. Another discovery of this work is that the consideration of only positive correlated neighbors in prediction, in both Pearson and Kendall algorithms, achieves higher accuracy than the consideration of all neighbors, with only a small loss of coverage.

  2. PILOT-BASED FREQUENCY OFFSET DETECTION SCHEME IN OFDM SYSTEM

    Institute of Scientific and Technical Information of China (English)

    Du Zheng; Zhu Jinkang

    2003-01-01

    The frequency offset information is extracted from local pilot amplitude characteristics, which suffer much less distortion in frequency-selective fading channels than those utilizing frequency domain correlation techniques. Simulation shows that the performance of this scheme has better performance than the existing frequency domain pilot-based frequency offset detection scheme.

  3. Linear feature detection based on ridgelet

    Institute of Scientific and Technical Information of China (English)

    HOU; Biao; (侯彪); LIU; Fang; (刘芳); JIAO; Licheng; (焦李成)

    2003-01-01

    Linear feature detection is very important in image processing. The detection efficiency will directly affect the perfomance of pattern recognition and pattern classification. Based on the idea of ridgelet, this paper presents a new discrete localized ridgelet transform and a new method for detecting linear feature in anisotropic images. Experimental results prove the efficiency of the proposed method.

  4. Asymptotic distributions in the projection pursuit based canonical correlation analysis

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    In this paper, associations between two sets of random variables based on the projection pursuit (PP) method are studied. The asymptotic normal distributions of estimators of the PP based canonical correlations and weighting vectors are derived.

  5. Detecting Bots Based on Keylogging Activities

    CERN Document Server

    Al-Hammadi, Yousof

    2010-01-01

    A bot is a piece of software that is usually installed on an infected machine without the user's knowledge. A bot is controlled remotely by the attacker under a Command and Control structure. Recent statistics show that bots represent one of the fastest growing threats to our network by performing malicious activities such as email spamming or keylogging. However, few bot detection techniques have been developed to date. In this paper, we investigate a behavioural algorithm to detect a single bot that uses keylogging activity. Our approach involves the use of function calls analysis for the detection of the bot with a keylogging component. Correlation of the frequency of a specified time-window is performed to enhance he detection scheme. We perform a range of experiments with the spybot. Our results show that there is a high correlation between some function calls executed by this bot which indicates abnormal activity in our system.

  6. DETECTING TECHNIQUE OF WEAK PERIODIC PULSE SIGNAL VIA SYNTHESIS OF CROSS-CORRELATION AND CHAOTIC SYSTEM

    Institute of Scientific and Technical Information of China (English)

    Li Yue; Yang Baojun; Lu Peng; Li Shizhe

    2003-01-01

    In this letter, with the synthesis of usual cross-correlation detecting method andchaotic detecting method, a new detecting system for the weak periodic pulse signal is constituted,in which the two methods can play respective preponderance. Theoretical analyses and simulationstudies have shown that the detecting system is very sensitive to the periodic pulse signal understrong noise background and has exceedingly powerful capability of suppressing complex noise.

  7. Image Edge Detection Based on Oscillation

    Institute of Scientific and Technical Information of China (English)

    FAN Hong; WANG Zhi-jie

    2005-01-01

    A new method for image edge detection based on a pulse neural network is proposed in this paper. The network is locally connected. The external input of each neuron of the network is gray value of the corresponding pixel. The synchrony of the neuron and its neighbors is detected by detection neurons. The edge of the image can be read off at minima of the total activity of the detection neurons.

  8. Signature Based Intrusion Detection System Using SNORT

    Directory of Open Access Journals (Sweden)

    Vinod Kumar

    2012-11-01

    Full Text Available Now a day’s Intrusion Detection systems plays very important role in Network security. As the use of internet is growing rapidly the possibility of attack is also increasing in that ratio. People are using signature based IDS’s. Snort is mostly used signature based IDS because of it is open source software. World widely it is used in intrusion detection and prevention domain. Basic analysis and security engine (BASE is also used to see the alerts generated by Snort. In the paper we have implementation the signature based intrusion detection using Snort. Our work will help to novel user to understand the concept of Snort based IDS.

  9. The application of the multifractal cross-correlation analysis methods in radar target detection within sea clutter

    Science.gov (United States)

    Xi, Caiping; Zhang, Shuning; Xiong, Gang; Zhao, Huichang; Yang, Yonghong

    2017-02-01

    Many complex systems generate multifractal time series which are long-range cross-correlated. This paper introduces three multifractal cross-correlation analysis methods, such as multifractal cross-correlation analysis based on the partition function approach (MFXPF), multifractal detrended cross-correlation analysis (MFDCCA) methods based on detrended fluctuation analysis (MFXDFA) and detrended moving average analysis (MFXDMA), which only consider one moment order. We do comparative analysis of the artificial time series (binomial multiplicative cascades and Cantor sets with different probabilities) by these methods. Then we do a feasibility test of the fixed threshold target detection within sea clutter by applying the multifractal cross-correlation analysis methods to the IPIX radar sea clutter data. The results show that it is feasible to use the method of the fixed threshold based on the multifractal feature parameter Δf(α) by the MFXPF and MFXDFA-1 methods. At last, we give the main conclusions and provide a valuable reference on how to choose the multifractal algorithms, the detection parameters and the target detection methods within sea clutter in practice.

  10. Automatic microseismic event detection by band-limited phase-only correlation

    Science.gov (United States)

    Wu, Shaojiang; Wang, Yibo; Zhan, Yi; Chang, Xu

    2016-12-01

    Identification and detection of microseismic events is a significant issue in source locations and source mechanism analysis. The number of the records is notably large, especially in the case of some real-time monitoring, and while the majority of microseismic events are highly weak and sparse, automatic algorithms are indispensable. In this study, we introduce an effective method for the identification and detection of microseismic events by judging whether the P-wave phase exists in a local segment from a single three-component microseismic records. The new judging algorithm consists primarily of the following key steps: 1) transform the waveform time series into time-varying spectral representations using the S-transform; 2) calculate the similarity of the frequency content in the time-frequency domain using the phase-only correlation function; and 3) identify the P-phase by the combination analysis between any two components. The proposed algorithm is compared to a similar approach using the cross-correlation in the time domain between any two components and later tested with synthetic microseismic datasets and real field-recorded datasets. The results indicate that the proposed algorithm is able to distinguish similar and dissimilar waveforms, even for low signal noise ratio and emergent events, which is important for accurate and rapid selection of microseismic events from a large number of records. This method can be applied to other geophysical analyses based on the waveform data.

  11. Acoustic signal detection through the cross-correlation method in experiments with different signal to noise ratio and reverberation conditions

    CERN Document Server

    Adrián-Martínez, S; Bou-Cabo, M; Felis, I; Llorens, C; Martínez-Mora, J A; Saldaña, M

    2015-01-01

    The study and application of signal detection techniques based on cross-correlation method for acoustic transient signals in noisy and reverberant environments are presented. These techniques are shown to provide high signal to noise ratio, good signal discernment from very close echoes and accurate detection of signal arrival time. The proposed methodology has been tested on real data collected in environments and conditions where its benefits can be shown. This work focuses on the acoustic detection applied to tasks of positioning in underwater structures and calibration such those as ANTARES and KM3NeT deep-sea neutrino telescopes, as well as, in particle detection through acoustic events for the COUPP/PICO detectors. Moreover, a method for obtaining the real amplitude of the signal in time (voltage) by using cross correlation has been developed and tested and is described in this work.

  12. Miniaturized Hollow-Waveguide Gas Correlation Radiometer (GCR) for Trace Gas Detection in the Martian Atmosphere

    Science.gov (United States)

    Wilson, Emily L.; Georgieva, E. M.; Melroy, H. R.

    2012-01-01

    Gas correlation radiometry (GCR) has been shown to be a sensitive and versatile method for detecting trace gases in Earth's atmosphere. Here, we present a miniaturized and simplified version of this instrument capable of mapping multiple trace gases and identifying active regions on the Mars surface. Reduction of the size and mass of the GCR instrument has been achieved by implementing a lightweight, 1 mm inner diameter hollow-core optical fiber (hollow waveguide) for the gas correlation cell. Based on a comparison with an Earth orbiting CO2 gas correlation instrument, replacement of the 10 meter mUltipass cell with hollow waveguide of equivalent pathlength reduces the cell mass from approx 150 kg to approx 0.5 kg, and reduces the volume from 1.9 m x 1.3 m x 0.86 m to a small bundle of fiber coils approximately I meter in diameter by 0.05 m in height (mass and volume reductions of >99%). This modular instrument technique can be expanded to include measurements of additional species of interest including nitrous oxide (N2O), hydrogen sulfide (H2S), methanol (CH3OH), and sulfur dioxide (SO2), as well as carbon dioxide (CO2) for a simultaneous measure of mass balance.

  13. Non Correlation DWT Based Watermarking Behavior in Different Color Spaces

    Directory of Open Access Journals (Sweden)

    Mehdi Khalili

    2016-01-01

    Full Text Available There are two digital watermarking techniques. Digital watermarking techniques based on correlation and digital watermarking techniques that are not based on correlation. In previous work, we proposed a DWT2 based CDMA image watermarking scheme to study the effects of using eight color spaces RGB, YCbCr, JPEG-YCbCr, YIQ, YUV, HSI, HSV and CIELab, on watermarking algorithms based on correlation techniques. This paper proposes a non correlation based image watermarking scheme in wavelet transform domain and tests it in the same color spaces, to develop studying, reach a comprehensive analysis and focus on satisfying the requirements of based non coloration watermarking algorithms. To achieve more security, imperceptibility and robustness of the proposed scheme, first, the binary watermark image encodes by applying ATM, CCM and exclusive OR. Then, the scrambled watermark embeds into intended quantized approximation coefficients of wavelet transform by LSB insertion technique.

  14. A correlation consistency based multivariate alarm thresholds optimization approach.

    Science.gov (United States)

    Gao, Huihui; Liu, Feifei; Zhu, Qunxiong

    2016-11-01

    Different alarm thresholds could generate different alarm data, resulting in different correlations. A new multivariate alarm thresholds optimization methodology based on the correlation consistency between process data and alarm data is proposed in this paper. The interpretative structural modeling is adopted to select the key variables. For the key variables, the correlation coefficients of process data are calculated by the Pearson correlation analysis, while the correlation coefficients of alarm data are calculated by kernel density estimation. To ensure the correlation consistency, the objective function is established as the sum of the absolute differences between these two types of correlations. The optimal thresholds are obtained using particle swarm optimization algorithm. Case study of Tennessee Eastman process is given to demonstrate the effectiveness of proposed method.

  15. Post detection Integration Analysis of Adaptive Detection of Partially-Correlated χ2 Targets in The Presence of Interferers

    Directory of Open Access Journals (Sweden)

    B., Mohamed

    2014-12-01

    Full Text Available The moderately fluctuating Rayleigh and 2 targets represent an important class of practical targets. The illumination of this class by a coherent pulse train will return a train of correlated pulses with a correlation coefficient in the range 01 (intermediate between SWII and SWI models in the case of Rayleigh targets.and (intermediate between SWIV and SWIII models in the case of 2 targets. Therefore, it is interesting to adaptively detect this class of partially-correlated targets. On the other hand, the constant false alarm rate in the presence of variable levels of noise is usually a requirement placed on any modern radar. The CA and OS schemes are the most familiar candidates in this category of detection techniques. Our goal in this paper is to analyze their detection performances for the case where the radar receiver post-detection integrates M pulses of an exponentially correlated signal from targets which exhibit 2 statistics with two and four degrees of freedom. Exact formulas for the detection probabilities are derived, in the absence as well as in the presence of spurious targets. As predicted, the CA detector has the best homogeneous performance while the OS scheme gives the best target multiplicity performance when the number of outlying targets is within its allowable values.

  16. Technical Note: Detection of gas bubble leakage via correlation of water column multibeam images

    Directory of Open Access Journals (Sweden)

    J. Schneider von Deimling

    2012-03-01

    Full Text Available Hydroacoustic detection of natural gas release from the seafloor has been conducted in the past by using singlebeam echosounders. In contrast, modern multibeam swath mapping systems allow much wider coverage, higher resolution, and offer 3-D spatial correlation. Up to the present, the extremely high data rate hampers water column backscatter investigations and more sophisticated visualization and processing techniques are needed. Here, we present water column backscatter data acquired with a 50 kHz prototype multibeam system over a period of 75 seconds. Display types are of swath-images as well as of a "re-sorted" singlebeam presentation. Thus, individual and/or groups of gas bubbles rising from the 24 m deep seafloor clearly emerge in the acoustic images, making it possible to estimate rise velocities. A sophisticated processing scheme is introduced to identify those rising gas bubbles in the hydroacoustic data. We apply a cross-correlation technique adapted from particle imaging velocimetry (PIV to the acoustic backscatter images. Temporal and spatial drift patterns of the bubbles are assessed and are shown to match very well to measured and theoretical rise patterns. The application of this processing to our field data gives clear results with respect to unambiguous bubble detection and remote bubble rise velocimetry. The method can identify and exclude the main source of misinterpretations, i.e. fish-mediated echoes. Although image-based cross-correlation techniques are well known in the field of fluid mechanics for high resolution and non-inversive current flow field analysis, we present the first application of this technique as an acoustic bubble detector.

  17. Optical flow based finger stroke detection

    Science.gov (United States)

    Zhu, Zhongdi; Li, Bin; Wang, Kongqiao

    2010-07-01

    Finger stroke detection is an important topic in hand based Human Computer Interaction (HCI) system. Few research studies have carried out effective solutions to this problem. In this paper, we present a novel approach for stroke detection based on mono vision. Via analyzing the optical flow field within the finger area, our method is able to detect finger stroke under various camera position and visual angles. We present a thorough evaluation for each component of the algorithm, and show its efficiency and effectiveness on solving difficult stroke detection problems.

  18. Post detection Integration Analysis of Adaptive Detection of Partially-Correlated χ2 Targets in The Presence of Interferers

    OpenAIRE

    B., Mohamed; El Mashade

    2014-01-01

    The moderately fluctuating Rayleigh and 2 targets represent an important class of practical targets. The illumination of this class by a coherent pulse train will return a train of correlated pulses with a correlation coefficient in the range 01 (intermediate between SWII and SWI models in the case of Rayleigh targets).and (intermediate between SWIV and SWIII models in the case of 2 targets). Therefore, it is interesting to adaptively detect this class of partially-correlated targets. On...

  19. Detection of microcalcifications by characteristic magnetic susceptibility effects using MR phase image cross-correlation analysis

    Energy Technology Data Exchange (ETDEWEB)

    Baheza, Richard A. [Department of Biomedical Engineering and Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee 37232-2310 (United States); Welch, E. Brian [Institute of Imaging Science and Departments of Radiology and Radiological Sciences and Biomedical Engineering, Vanderbilt University, Nashville, Tennessee 37232-2310 (United States); Gochberg, Daniel F. [Institute of Imaging Science and Departments of Radiology and Radiological Sciences, and Physics and Astronomy, Vanderbilt University, Nashville, Tennessee 37232-2310 (United States); Sanders, Melinda [Department of Pathology, Vanderbilt University, Nashville, Tennessee 37232-2310 (United States); Harvey, Sara [Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, Tennessee 37232-2310 (United States); Gore, John C. [Institute of Imaging Science and Departments of Biomedical Engineering, Radiology and Radiological Sciences, Physics and Astronomy, and Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee 37232-2310 (United States); Yankeelov, Thomas E., E-mail: thomas.yankeelov@vanderbilt.edu [Institute of Imaging Science and Departments of Radiology and Radiological Sciences, Biomedical Engineering, Physics and Astronomy, and Cancer Biology, Vanderbilt University, Nashville, Tennessee 37232-2310 (United States)

    2015-03-15

    Purpose: To develop and evaluate a new method for detecting calcium deposits using their characteristic magnetic susceptibility effects on magnetic resonance (MR) images at high fields and demonstrate its potential in practice for detecting breast microcalcifications. Methods: Characteristic dipole signatures of calcium deposits were detected in magnetic resonance phase images by computing the cross-correlation between the acquired data and a library of templates containing simulated phase patterns of spherical deposits. The influence of signal-to-noise ratio and various other MR parameters on the results were assessed using simulations and validated experimentally. The method was tested experimentally for detection of calcium fragments within gel phantoms and calcium-like inhomogeneities within chicken tissue at 7 T with optimized MR acquisition parameters. The method was also evaluated for detection of simulated microcalcifications, modeled from biopsy samples of malignant breast cancer, inserted in silico into breast magnetic resonance imaging (MRIs) of healthy subjects at 7 T. For both assessments of calcium fragments in phantoms and biopsy-based simulated microcalcifications in breast MRIs, receiver operator characteristic curve analyses were performed to determine the cross-correlation index cutoff, for achieving optimal sensitivity and specificity, and the area under the curve (AUC), for measuring the method’s performance. Results: The method detected calcium fragments with sizes of 0.14–0.79 mm, 1 mm calcium-like deposits, and simulated microcalcifications with sizes of 0.4–1.0 mm in images with voxel sizes between (0.2 mm){sup 3} and (0.6 mm){sup 3}. In images acquired at 7 T with voxel sizes of (0.2 mm){sup 3}–(0.4 mm){sup 3}, calcium fragments (size 0.3–0.4 mm) were detected with a sensitivity, specificity, and AUC of 78%–90%, 51%–68%, and 0.77%–0.88%, respectively. In images acquired with a human 7 T scanner, acquisition times below 12

  20. Correlating intrusion detection alerts on bot malware infections using neural network

    DEFF Research Database (Denmark)

    Kidmose, Egon; Stevanovic, Matija; Pedersen, Jens Myrup

    2016-01-01

    Millions of computers are infected with bot malware, form botnets and enable botmaster to perform malicious and criminal activities. Intrusion Detection Systems are deployed to detect infections, but they raise many correlated alerts for each infection, requiring a large manual investigation effo...

  1. Quantum Encryption Protocol Based on Continuous Variable EPR Correlations

    Institute of Scientific and Technical Information of China (English)

    HE Guang-Qiang; ZENG Gui-Hua

    2006-01-01

    A quantum encryption protocol based on Gaussian-modulated continuous variable EPR correlations is proposed. The security is guaranteed by continuous variable EPR entanglement correlations produced by nondegenerate optical parametric amplifier (NOPA). For general beam splitter eavesdropping strategy, the mutual information Ⅰ(α, ε)between Alice and Eve is calculated by employing Shannon information theory. Finally the security analysis is presented.

  2. Frontal Face Detection using Haar Wavelet Coefficients and Local Histogram Correlation

    Directory of Open Access Journals (Sweden)

    Iwan Setyawan

    2011-12-01

    Full Text Available Face detection is the main building block on which all automatic systems dealing with human faces is built. For example, a face recognition system must rely on face detection to process an input image and determine which areas contain human faces. These areas then become the input for the face recognition system for further processing. This paper presents a face detection system designed to detect frontal faces. The system uses Haar wavelet coefficients and local histogram correlation as differentiating features. Our proposed system is trained using 100 training images. Our experiments show that the proposed system performed well during testing, achieving a detection rate of 91.5%.

  3. Detection of a periodic structure embedded in surface roughness, for various correlation functions

    Indian Academy of Sciences (India)

    V C Vani; S Chatterjee

    2011-10-01

    This paper deals with surface profilometry, where we try to detect a periodic structure, hidden in randomness using the matched filter method of analysing the intensity of light, scattered from the surface. From the direct problem of light scattering from a composite rough surface of the above type, we find that the detectability of the periodic structure can be hindered by the randomness, being dependent on the correlation function of the random part. In our earlier works, we had concentrated mainly on the Cauchy-type correlation function for the rough part. In the present work, we show that this technique can determine the periodic structure of different kinds of correlation functions of the roughness, including Cauchy, Gaussian etc. We study the detection by the matched filter method as the nature of the correlation function is varied.

  4. Daytime Water Detection Based on Sky Reflections

    Science.gov (United States)

    Rankin, Arturo; Matthies, Larry; Bellutta, Paolo

    2011-01-01

    A water body s surface can be modeled as a horizontal mirror. Water detection based on sky reflections and color variation are complementary. A reflection coefficient model suggests sky reflections dominate the color of water at ranges > 12 meters. Water detection based on sky reflections: (1) geometrically locates the pixel in the sky that is reflecting on a candidate water pixel on the ground (2) predicts if the ground pixel is water based on color similarity and local terrain features. Water detection has been integrated on XUVs.

  5. Image edge detection based on beamlet transform

    Institute of Scientific and Technical Information of China (English)

    Li Jing; Huang Peikang; Wang Xiaohu; Pan Xudong

    2009-01-01

    Combining beamlet transform with steerable filters, a new edge detection method based on line gra-dient is proposed. Compared with operators based on point local properties, the edge-detection results with this method achieve higher SNR and position accuracy, and are quite helpful for image registration, object identification, etc. Some edge-detection experiments on optical and SAR images that demonstrate the significant improvement over classical edge operators are also presented. Moreover, the template matching result based on edge information of optical reference image and SAR image also proves the validity of this method.

  6. Continuous detection of weak sensory signals in afferent spike trains: the role of anti-correlated interspike intervals in detection performance.

    Science.gov (United States)

    Goense, J B M; Ratnam, R

    2003-10-01

    An important problem in sensory processing is deciding whether fluctuating neural activity encodes a stimulus or is due to variability in baseline activity. Neurons that subserve detection must examine incoming spike trains continuously, and quickly and reliably differentiate signals from baseline activity. Here we demonstrate that a neural integrator can perform continuous signal detection, with performance exceeding that of trial-based procedures, where spike counts in signal- and baseline windows are compared. The procedure was applied to data from electrosensory afferents of weakly electric fish (Apteronotus leptorhynchus), where weak perturbations generated by small prey add approximately 1 spike to a baseline of approximately 300 spikes s(-1). The hypothetical postsynaptic neuron, modeling an electrosensory lateral line lobe cell, could detect an added spike within 10-15 ms, achieving near ideal detection performance (80-95%) at false alarm rates of 1-2 Hz, while trial-based testing resulted in only 30-35% correct detections at that false alarm rate. The performance improvement was due to anti-correlations in the afferent spike train, which reduced both the amplitude and duration of fluctuations in postsynaptic membrane activity, and so decreased the number of false alarms. Anti-correlations can be exploited to improve detection performance only if there is memory of prior decisions.

  7. A measurement-based technique for incipient anomaly detection

    KAUST Repository

    Harrou, Fouzi

    2016-06-13

    Fault detection is essential for safe operation of various engineering systems. Principal component analysis (PCA) has been widely used in monitoring highly correlated process variables. Conventional PCA-based methods, nevertheless, often fail to detect small or incipient faults. In this paper, we develop new PCA-based monitoring charts, combining PCA with multivariate memory control charts, such as the multivariate cumulative sum (MCUSUM) and multivariate exponentially weighted moving average (MEWMA) monitoring schemes. The multivariate control charts with memory are sensitive to small and moderate faults in the process mean, which significantly improves the performance of PCA methods and widen their applicability in practice. Using simulated data, we demonstrate that the proposed PCA-based MEWMA and MCUSUM control charts are more effective in detecting small shifts in the mean of the multivariate process variables, and outperform the conventional PCA-based monitoring charts. © 2015 IEEE.

  8. Photonic crystal fiber based antibody detection

    DEFF Research Database (Denmark)

    Duval, A; Lhoutellier, M; Jensen, J B

    2004-01-01

    An original approach for detecting labeled antibodies based on strong penetration photonic crystal fibers is introduced. The target antibody is immobilized inside the air-holes of a photonic crystal fiber and the detection is realized by the means of evanescent-wave fluorescence spectroscopy...

  9. Immune based computer virus detection approaches

    Institute of Scientific and Technical Information of China (English)

    TAN Ying; ZHANG Pengtao

    2013-01-01

    The computer virus is considered one of the most horrifying threats to the security of computer systems worldwide.The rapid development of evasion techniques used in virus causes the signature based computer virus detection techniques to be ineffective.Many novel computer virus detection approaches have been proposed in the past to cope with the ineffectiveness,mainly classified into three categories:static,dynamic and heuristics techniques.As the natural similarities between the biological immune system (BIS),computer security system (CSS),and the artificial immune system (AIS) were all developed as a new prototype in the community of anti-virus research.The immune mechanisms in the BIS provide the opportunities to construct computer virus detection models that are robust and adaptive with the ability to detect unseen viruses.In this paper,a variety of classic computer virus detection approaches were introduced and reviewed based on the background knowledge of the computer virus history.Next,a variety of immune based computer virus detection approaches were also discussed in detail.Promising experimental results suggest that the immune based computer virus detection approaches were able to detect new variants and unseen viruses at lower false positive rates,which have paved a new way for the anti-virus research.

  10. Photonic crystal fiber based antibody detection

    OpenAIRE

    Duval, A.; Lhoutellier, M; Jensen, J. B.; Hoiby, P E; Missier, V; Pedersen, L. H.; Hansen, Theis Peter; Bjarklev, Anders Overgaard; Bang, Ole

    2004-01-01

    An original approach for detecting labeled antibodies based on strong penetration photonic crystal fibers is introduced. The target antibody is immobilized inside the air-holes of a photonic crystal fiber and the detection is realized by the means of evanescent-wave fluorescence spectroscopy and the use of a transversal illumination setup.

  11. Sociolect-Based Community Detection

    Energy Technology Data Exchange (ETDEWEB)

    Reynolds, William N.; Salter, William J.; Farber, Robert M.; Corley, Courtney D.; Dowling, Chase P.; Beeman, William O.; Smith-Lovin, Lynn; Choi, Joon Nak

    2013-06-06

    "Sociolects" are specialized vocabularies used by social subgroups defined by common interests or origins. We applied methods to retrieve large quantities of Twitter data based on expert-identified sociolects and then applied and developed network-analysis methods to relate sociolect use to network (sub-) structure. We show that novel methods including consideration of node populations, as well as edge counts, provide substantially enhanced performance compared to standard assortativity. We explain these methods, show their utility in analyzing large corpora of social media data, and discuss their further extensions and potential applications.

  12. Correlating nuclear frequencies by two-dimensional ELDOR-detected NMR spectroscopy.

    Science.gov (United States)

    Kaminker, Ilia; Wilson, Tiffany D; Savelieff, Masha G; Hovav, Yonatan; Zimmermann, Herbert; Lu, Yi; Goldfarb, Daniella

    2014-03-01

    ELDOR (Electron Double Resonance)-detected NMR (EDNMR) is a pulse EPR experiment that is used to measure the transition frequencies of nuclear spins coupled to electron spins. These frequencies are further used to determine hyperfine and quadrupolar couplings, which are signatures of the electronic and spatial structures of paramagnetic centers. In recent years, EDNMR has been shown to be particularly useful at high fields/high frequencies, such as W-band (∼95 GHz, ∼3.5 T), for low γ quadrupolar nuclei. Although at high fields the nuclear Larmor frequencies are usually well resolved, the limited resolution of EDNMR still remains a major concern. In this work we introduce a two dimensional, triple resonance, correlation experiment based on the EDNMR pulse sequence, which we term 2D-EDNMR. This experiment allows circumventing the resolution limitation by spreading the signals in two dimensions and the observed correlations help in the assignment of the signals. First we demonstrate the utility of the 2D-EDNMR experiment on a nitroxide spin label, where we observe correlations between (14)N nuclear frequencies. Negative cross-peaks appear between lines belonging to different MS electron spin manifolds. We resolved two independent correlation patterns for nuclear frequencies arising from the EPR transitions corresponding to the (14)N mI=0 and mI=-1 nuclear spin states, which severely overlap in the one dimensional EDNMR spectrum. The observed correlations could be accounted for by considering changes in the populations of energy levels that S=1/2, I=1 spin systems undergo during the pulse sequence. In addition to these negative cross-peaks, positive cross-peaks appear as well. We present a theoretical model based on the Liouville equation and use it to calculate the time evolution of populations of the various energy levels during the 2D-EDNMR experiment and generated simulated 2D-EDMR spectra. These calculations show that the positive cross-peaks appear due to

  13. Correlating nuclear frequencies by two-dimensional ELDOR-detected NMR spectroscopy

    Science.gov (United States)

    Kaminker, Ilia; Wilson, Tiffany D.; Savelieff, Masha G.; Hovav, Yonatan; Zimmermann, Herbert; Lu, Yi; Goldfarb, Daniella

    2014-03-01

    ELDOR (Electron Double Resonance)-detected NMR (EDNMR) is a pulse EPR experiment that is used to measure the transition frequencies of nuclear spins coupled to electron spins. These frequencies are further used to determine hyperfine and quadrupolar couplings, which are signatures of the electronic and spatial structures of paramagnetic centers. In recent years, EDNMR has been shown to be particularly useful at high fields/high frequencies, such as W-band (∼95 GHz, ∼3.5 T), for low γ quadrupolar nuclei. Although at high fields the nuclear Larmor frequencies are usually well resolved, the limited resolution of EDNMR still remains a major concern. In this work we introduce a two dimensional, triple resonance, correlation experiment based on the EDNMR pulse sequence, which we term 2D-EDNMR. This experiment allows circumventing the resolution limitation by spreading the signals in two dimensions and the observed correlations help in the assignment of the signals. First we demonstrate the utility of the 2D-EDNMR experiment on a nitroxide spin label, where we observe correlations between 14N nuclear frequencies. Negative cross-peaks appear between lines belonging to different MS electron spin manifolds. We resolved two independent correlation patterns for nuclear frequencies arising from the EPR transitions corresponding to the 14N mI = 0 and mI = -1 nuclear spin states, which severely overlap in the one dimensional EDNMR spectrum. The observed correlations could be accounted for by considering changes in the populations of energy levels that S = 1/2, I = 1 spin systems undergo during the pulse sequence. In addition to these negative cross-peaks, positive cross-peaks appear as well. We present a theoretical model based on the Liouville equation and use it to calculate the time evolution of populations of the various energy levels during the 2D-EDNMR experiment and generated simulated 2D-EDMR spectra. These calculations show that the positive cross-peaks appear due

  14. Collaborative regression-based anatomical landmark detection

    Science.gov (United States)

    Gao, Yaozong; Shen, Dinggang

    2015-12-01

    Anatomical landmark detection plays an important role in medical image analysis, e.g. for registration, segmentation and quantitative analysis. Among the various existing methods for landmark detection, regression-based methods have recently attracted much attention due to their robustness and efficiency. In these methods, landmarks are localised through voting from all image voxels, which is completely different from the classification-based methods that use voxel-wise classification to detect landmarks. Despite their robustness, the accuracy of regression-based landmark detection methods is often limited due to (1) the inclusion of uninformative image voxels in the voting procedure, and (2) the lack of effective ways to incorporate inter-landmark spatial dependency into the detection step. In this paper, we propose a collaborative landmark detection framework to address these limitations. The concept of collaboration is reflected in two aspects. (1) Multi-resolution collaboration. A multi-resolution strategy is proposed to hierarchically localise landmarks by gradually excluding uninformative votes from faraway voxels. Moreover, for informative voxels near the landmark, a spherical sampling strategy is also designed at the training stage to improve their prediction accuracy. (2) Inter-landmark collaboration. A confidence-based landmark detection strategy is proposed to improve the detection accuracy of ‘difficult-to-detect’ landmarks by using spatial guidance from ‘easy-to-detect’ landmarks. To evaluate our method, we conducted experiments extensively on three datasets for detecting prostate landmarks and head & neck landmarks in computed tomography images, and also dental landmarks in cone beam computed tomography images. The results show the effectiveness of our collaborative landmark detection framework in improving landmark detection accuracy, compared to other state-of-the-art methods.

  15. Power Consumption Based Android Malware Detection

    Directory of Open Access Journals (Sweden)

    Hongyu Yang

    2016-01-01

    Full Text Available In order to solve the problem that Android platform’s sand-box mechanism prevents security protection software from accessing effective information to detect malware, this paper proposes a malicious software detection method based on power consumption. Firstly, the mobile battery consumption status information was obtained, and the Gaussian mixture model (GMM was built by using Mel frequency cepstral coefficients (MFCC. Then, the GMM was used to analyze power consumption; malicious software can be classified and detected through classification processing. Experiment results demonstrate that the function of an application and its power consumption have a close relationship, and our method can detect some typical malicious application software accurately.

  16. Existence problem of optical correlation based pattern recognition

    Institute of Scientific and Technical Information of China (English)

    ZHANG; Yanxin(张延炘); LI; Sumei(李素梅)

    2003-01-01

    The existence problem of optical correlation based pattern recognition, namely its range of validity and its limitation, is discussed in this paper conjointly with the function approximation theory of neural networks. The conclusion is that only if the sets to be recognized are linearly separable (which is rare) or the subsets, in which a segmental sample of the targets is involved,are linearly separable, can the classical 4f optical correlation system carry out the task of recognition inerrably. The recognition principle of a joint transform correlator is the same as that of a 4f system, and so is its range of validities. Based on the demonstration of the existence problem of optical correlation based pattern recognition an evaluation on some important problems that were studied in this field over the past 40 years is presented explicitly.

  17. Anomaly Detection in Electroencephalogram Signals Using Unconstrained Minimum Average Correlation Energy Filter

    Directory of Open Access Journals (Sweden)

    Aini Hussain

    2009-01-01

    Full Text Available Problem statement: Electroencepharogram (EEG is an extremely complex signal with very low signal to noise ratio and these attributed to difficulty in analyzing the signal. Hence for detecting abnormal segment, a distinctive method is required to train the technologist to distinguish the anomalous in EEG data. The objective of this study was to create a framework to analyze EEG signals recorded from epileptic patients by evaluating the potential of UMACE filter to detect changes in single-channel EEG data during routine epilepsy monitoring. Approach: Normally, the peak to side lobe ratio (PSR of a UMACE filter was employed as an indicator if a test data is similar to an authentic class or vice versa, however in this study, the consistent changes of the correlation output known as Region Of Interest (ROI was plotted and monitored. Based on this approach, a novel method to analyze and distinguish variances in scalp EEG as well as comparing both normal and abnormal regions of the patient’s EEG was assessed. The performance of the novelty detection was examined based on the onset and end time of each seizure in the ROI plot. Results: Results showed that using ROI plot of variances one can distinguish irregularities in the EEG data. The advantage of the proposed technique was that it did not require large amount of data for training. Conclusion: As such, it was feasible to perform seizure analysis as well as localizing seizure onsets. In short, the technique can be used as a guideline for faster diagnosis in a lengthy EEG recording.

  18. Partially-Correlated χ2 Targets Detection Analysis of GTM-Adaptive Processor in the Presence of Outliers

    Directory of Open Access Journals (Sweden)

    Mohamed B. El Mashade

    2014-10-01

    Full Text Available This paper addresses the problem of detecting the partially-correlated χ2 fluctuating targets with two and four degrees of freedom. It presents the performance analysis, in its exact form, of GTM-CFAR processor when the operating environment is contaminated with extraneous targets and the radar receiver post-detection integrates M pulses of exponentially correlated targets. Mathematical formulas for the detection and false alarm probabilities are derived, in the absence as well as in the presence of spurious targets which are fluctuating in accordance with the so-called moderately fluctuating χ2 targets. A thorough performance assessment by several numerical examples, which has considered the role that each parameter can play in the processor performance, is also given. The results show that the processor performance improves, for weak SNR of the primary target, as the correlation coefficient ρs increases and this occurs either in the absence or in the presence of outlying targets. As the strength of the target return increases, the processor tends to invert this behavior. The SWI & SWII and SWIII & SWIV models enclose the correlated target cases when the target correlation follows χ2 fluctuation models with two and four degrees of freedom, respectively, and this behavior is common for all GTM based detectors.

  19. EFFICIENT IRIS SEGMENTATION BASED ON EYELID DETECTION

    Directory of Open Access Journals (Sweden)

    ABDULJALIL RADMAN

    2013-08-01

    Full Text Available This paper proposes a computationally efficient eyelid detection algorithm for detecting eyelid boundaries in iris images acquired under less constrained imaging conditions. The proposed eyelid detection algorithm is developed based on the live-wire technique. The major advantage of the proposed algorithm is its computational simplicity as compared to the prior eyelid detection algorithms. The saturation color features of the sclera region of the HSI color space of the iris image are exploited to determine the two intersection points between each eyelid and the outer iris boundary. The strongly connected edges between these two points are detected using the live wire technique that is likely to be the eyelid boundary. The experimental results obtained from UBIRIS.v1 database reveal that the eyelid detection algorithm which proposed in this paper improves the segmentation accuracy for the less constrained iris images.

  20. Grey-theory based intrusion detection model

    Institute of Scientific and Technical Information of China (English)

    Qin Boping; Zhou Xianwei; Yang Jun; Song Cunyi

    2006-01-01

    To solve the problem that current intrusion detection model needs large-scale data in formulating the model in real-time use, an intrusion detection system model based on grey theory (GTIDS) is presented. Grey theory has merits of fewer requirements on original data scale, less limitation of the distribution pattern and simpler algorithm in modeling.With these merits GTIDS constructs model according to partial time sequence for rapid detect on intrusive act in secure system. In this detection model rate of false drop and false retrieval are effectively reduced through twice modeling and repeated detect on target data. Furthermore, GTIDS framework and specific process of modeling algorithm are presented. The affectivity of GTIDS is proved through emulated experiments comparing snort and next-generation intrusion detection expert system (NIDES) in SRI international.

  1. Experimental detection of non-classical correlations in mixed state quantum computation

    CERN Document Server

    Passante, G; Trottier, D A; Laflamme, R

    2011-01-01

    We report on an experiment to detect non-classical correlations in a highly mixed state. The correlations are characterized by the quantum discord and are observed using four qubits in a liquid state nuclear magnetic resonance quantum information processor. The state analyzed is the output of a DQC1 computation, whose input is a single quantum bit accompanied by n maximally mixed qubits. This model of computation outperforms the best known classical algorithms, and although it contains vanishing entanglement it is known to have quantum correlations characterized by the quantum discord. This experiment detects non-vanishing quantum discord, ensuring the existence of non-classical correlations as measured by the quantum discord.

  2. [Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

    Science.gov (United States)

    Zhou, Jinzhi; Tang, Xiaofang

    2015-08-01

    In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.

  3. Pedestrian detection based on redundant wavelet transform

    Science.gov (United States)

    Huang, Lin; Ji, Liping; Hu, Ping; Yang, Tiejun

    2016-10-01

    Intelligent video surveillance is to analysis video or image sequences captured by a fixed or mobile surveillance camera, including moving object detection, segmentation and recognition. By using it, we can be notified immediately in an abnormal situation. Pedestrian detection plays an important role in an intelligent video surveillance system, and it is also a key technology in the field of intelligent vehicle. So pedestrian detection has very vital significance in traffic management optimization, security early warn and abnormal behavior detection. Generally, pedestrian detection can be summarized as: first to estimate moving areas; then to extract features of region of interest; finally to classify using a classifier. Redundant wavelet transform (RWT) overcomes the deficiency of shift variant of discrete wavelet transform, and it has better performance in motion estimation when compared to discrete wavelet transform. Addressing the problem of the detection of multi-pedestrian with different speed, we present an algorithm of pedestrian detection based on motion estimation using RWT, combining histogram of oriented gradients (HOG) and support vector machine (SVM). Firstly, three intensities of movement (IoM) are estimated using RWT and the corresponding areas are segmented. According to the different IoM, a region proposal (RP) is generated. Then, the features of a RP is extracted using HOG. Finally, the features are fed into a SVM trained by pedestrian databases and the final detection results are gained. Experiments show that the proposed algorithm can detect pedestrians accurately and efficiently.

  4. Color-image retrieval based on fuzzy correlation

    Institute of Scientific and Technical Information of China (English)

    ZHAI Hongchen; LIANG Yanmei; MU Guoguang

    2004-01-01

    We report a method of color-image retrieval based on fuzzy correlation, in which α-cut relations in fuzzy set theory are applied to defining color match and height match of color peaks for synthesizing fuzzy correlation of two color histograms, and RGB space is partitioned into six sub-regions in the experiment for the regional color comparisons. Experimental results show that the efficiency of the color-image retrieval can be effectively improved by this approach.

  5. Detecting Distributed Network Traffic Anomaly with Network-Wide Correlation Analysis

    Directory of Open Access Journals (Sweden)

    Yang Dan

    2008-12-01

    Full Text Available Distributed network traffic anomaly refers to a traffic abnormal behavior involving many links of a network and caused by the same source (e.g., DDoS attack, worm propagation. The anomaly transiting in a single link might be unnoticeable and hard to detect, while the anomalous aggregation from many links can be prevailing, and does more harm to the networks. Aiming at the similar features of distributed traffic anomaly on many links, this paper proposes a network-wide detection method by performing anomalous correlation analysis of traffic signals' instantaneous parameters. In our method, traffic signals' instantaneous parameters are firstly computed, and their network-wide anomalous space is then extracted via traffic prediction. Finally, an anomaly is detected by a global correlation coefficient of anomalous space. Our evaluation using Abilene traffic traces demonstrates the excellent performance of this approach for distributed traffic anomaly detection.

  6. Study of a theoretical model for the measured gate moments resulting from correlated detection events and an extending dead time

    Energy Technology Data Exchange (ETDEWEB)

    Hauck, Danielle K., E-mail: hauck@lanl.gov [Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Croft, Stephen; Evans, Louise G. [Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Favalli, Andrea; Santi, Peter A.; Dowell, Jonathan [Los Alamos National Laboratory, Los Alamos, NM 87545 (United States)

    2013-08-11

    Neutron emissions from fissioning nuclear material are temporally correlated. The detection of these correlated neutrons is frequently used to quantify plutonium (Pu) and other fissile materials for international nuclear safeguards and related activities. However, detector dead time affects the observed rates of correlated neutrons in a non-trivial manner, and must be accounted for to obtain accurate results. A major simplification made in the most widely used dead time corrections is that the neutron detections are occurring randomly in time. A few previous attempts at providing a dead time model for correlated neutrons have been limited in scope, have made simplifying assumptions early in the derivation, and have, in general, not been implemented in the broader safeguards community. This paper provides an exact dead time model for correlated neutron detections in a single channel system assuming an updating dead time, and therefore a paralyzable system. This dead time model includes the assumption that a single exponential, with one characteristic decay constant, can describe the system neutron die-away profile. An exact model for the effects of dead time on measured gate moments is derived which is extendable to an arbitrary order of neutron correlation. This dead time model predicts the measured gate moments based on the dead time and underlying detection rates, including the effects from detection rates with an arbitrarily high order of correlation. The effects of dead time on the apparent singles, doubles, triples and quadruples rates using either event triggered, random or mixed gate structure is also derived. Either the equations for the measured gate moments or the apparent multiplicity rates can be numerically inverted to find the dead time corrected multiplicity rates. Although the model has been explicitly solved for rates up to and including quadruples, it is directly extendable to any order of correlation. This model is presented from the perspective

  7. Dictionary based Approach to Edge Detection

    CERN Document Server

    Chandra, Nitish

    2015-01-01

    Edge detection is a very essential part of image processing, as quality and accuracy of detection determines the success of further processing. We have developed a new self learning technique for edge detection using dictionary comprised of eigenfilters constructed using features of the input image. The dictionary based method eliminates the need of pre or post processing of the image and accounts for noise, blurriness, class of image and variation of illumination during the detection process itself. Since, this method depends on the characteristics of the image, the new technique can detect edges more accurately and capture greater detail than existing algorithms such as Sobel, Prewitt Laplacian of Gaussian, Canny method etc which use generic filters and operators. We have demonstrated its application on various classes of images such as text, face, barcodes, traffic and cell images. An application of this technique to cell counting in a microscopic image is also presented.

  8. Recent advances in biosensor based endotoxin detection.

    Science.gov (United States)

    Das, A P; Kumar, P S; Swain, S

    2014-01-15

    Endotoxins also referred to as pyrogens are chemically lipopolysaccharides habitually found in food, environment and clinical products of bacterial origin and are unavoidable ubiquitous microbiological contaminants. Pernicious issues of its contamination result in high mortality and severe morbidities. Standard traditional techniques are slow and cumbersome, highlighting the pressing need for evoking agile endotoxin detection system. The early and prompt detection of endotoxin assumes prime importance in health care, pharmacological and biomedical sectors. The unparalleled recognition abilities of LAL biosensors perched with remarkable sensitivity, high stability and reproducibility have bestowed it with persistent reliability and their possible fabrication for commercial applicability. This review paper entails an overview of various trends in current techniques available and other possible alternatives in biosensor based endotoxin detection together with its classification, epidemiological aspects, thrust areas demanding endotoxin control, commercially available detection sensors and a revolutionary unprecedented approach narrating the influence of omics for endotoxin detection.

  9. Web Based Cross Language Plagiarism Detection

    CERN Document Server

    Kent, Chow Kok

    2009-01-01

    As the Internet help us cross language and cultural border by providing different types of translation tools, cross language plagiarism, also known as translation plagiarism are bound to arise. Especially among the academic works, such issue will definitely affect the student's works including the quality of their assignments and paper works. In this paper, we propose a new approach in detecting cross language plagiarism. Our web based cross language plagiarism detection system is specially tuned to detect translation plagiarism by implementing different techniques and tools to assist the detection process. Google Translate API is used as our translation tool and Google Search API, which is used in our information retrieval process. Our system is also integrated with the fingerprint matching technique, which is a widely used plagiarism detection technique. In general, our proposed system is started by translating the input documents from Malay to English, followed by removal of stop words and stemming words, ...

  10. Cluster based Intrusion Detection System for Manets

    Directory of Open Access Journals (Sweden)

    Nisha Dang

    2012-07-01

    Full Text Available Manets are the ad hoc networks that are build on demand or instantly when some mobile nodes come in the mobility range of each other and decide to cooperate for data transfer and communication. Therefore there is no defined topology for Manets. They communicate in dynamic topology which continuously changes as nodes are not stable. Due to this lack of infrastructure and distributed nature they are more vulnerable for attacks and provide a good scope to malicious users to become part of the network. To prevent the security of mobile ad hoc networks many security measures are designed such as encryption algorithms, firewalls etc. But still there is some scope of malicious actions. So, Intrusion detection systems are proposed to detect any intruder in the network and its malicious activities. Cluster based intrusion detection system is also designed to restrict the intruders activities in clusters of mobile nodes. In clusters each node run some intrusion detection code to detect local as well as global intrusion. In this paper we have taken insight of intrusion detection systems and different attacks on Manet security. Then we proposed how overhead involved in cluster based intrusion detection system can be reduced.

  11. Spatio-activity based object detection

    CERN Document Server

    Springett, Jarrad

    2008-01-01

    We present the SAMMI lightweight object detection method which has a high level of accuracy and robustness, and which is able to operate in an environment with a large number of cameras. Background modeling is based on DCT coefficients provided by cameras. Foreground detection uses similarity in temporal characteristics of adjacent blocks of pixels, which is a computationally inexpensive way to make use of object coherence. Scene model updating uses the approximated median method for improved performance. Evaluation at pixel level and application level shows that SAMMI object detection performs better and faster than the conventional Mixture of Gaussians method.

  12. Correlation theory-based signal processing method for CMF signals

    Science.gov (United States)

    Shen, Yan-lin; Tu, Ya-qing

    2016-06-01

    Signal processing precision of Coriolis mass flowmeter (CMF) signals affects measurement accuracy of Coriolis mass flowmeters directly. To improve the measurement accuracy of CMFs, a correlation theory-based signal processing method for CMF signals is proposed, which is comprised of the correlation theory-based frequency estimation method and phase difference estimation method. Theoretical analysis shows that the proposed method eliminates the effect of non-integral period sampling signals on frequency and phase difference estimation. The results of simulations and field experiments demonstrate that the proposed method improves the anti-interference performance of frequency and phase difference estimation and has better estimation performance than the adaptive notch filter, discrete Fourier transform and autocorrelation methods in terms of frequency estimation and the data extension-based correlation, Hilbert transform, quadrature delay estimator and discrete Fourier transform methods in terms of phase difference estimation, which contributes to improving the measurement accuracy of Coriolis mass flowmeters.

  13. Effective information spreading based on local information in correlated networks

    Science.gov (United States)

    Gao, Lei; Wang, Wei; Pan, Liming; Tang, Ming; Zhang, Hai-Feng

    2016-12-01

    Using network-based information to facilitate information spreading is an essential task for spreading dynamics in complex networks. Focusing on degree correlated networks, we propose a preferential contact strategy based on the local network structure and local informed density to promote the information spreading. During the spreading process, an informed node will preferentially select a contact target among its neighbors, basing on their degrees or local informed densities. By extensively implementing numerical simulations in synthetic and empirical networks, we find that when only consider the local structure information, the convergence time of information spreading will be remarkably reduced if low-degree neighbors are favored as contact targets. Meanwhile, the minimum convergence time depends non-monotonically on degree-degree correlation, and a moderate correlation coefficient results in the most efficient information spreading. Incorporating the local informed density information into contact strategy, the convergence time of information spreading can be further reduced, and be minimized by an moderately preferential selection.

  14. Effective information spreading based on local information in correlated networks

    CERN Document Server

    Gao, Lei; Pan, Liming; Tang, Ming; Zhang, Hai-Feng

    2016-01-01

    Using network-based information to facilitate information spreading is an essential task for spreading dynamics in complex networks, which will benefit the promotion of technical innovations, healthy behaviors, new products, etc. Focusing on degree correlated networks, we propose a preferential contact strategy based on the local network structure and local informed density to promote the information spreading. During the spreading process, an informed node will preferentially select a contact target among its neighbors, basing on their degrees or local informed densities. By extensively implementing numerical simulations in synthetic and empirical networks, we find that when only consider the local structure information, the convergence time of information spreading will be remarkably reduced if low-degree neighbors are favored as contact targets. Meanwhile, the minimum convergence time depends non-monotonically on degree-degree correlation, and moderate correlation coefficients result in most efficient info...

  15. Correlation coefficient mapping in fluorescence spectroscopy: tissue classification for cancer detection.

    Science.gov (United States)

    Crowell, Ed; Wang, Gufeng; Cox, Jason; Platz, Charles P; Geng, Lei

    2005-03-01

    Correlation coefficient mapping has been applied to intrinsic fluorescence spectra of colonic tissue for the purpose of cancer diagnosis. Fluorescence emission spectra were collected of 57 colonic tissue sites in a range of 4 physiological conditions: normal (29), hyperplastic (2), adenomatous (5), and cancerous tissues (21). The sample-sample correlation was used to examine the ability of correlation coefficient mapping to determine tissue disease state. The correlation coefficient map indicates two main categories of samples. These categories were found to relate to disease states of the tissue. Sensitivity, selectivity, predictive value positive, and predictive value negative for differentiation between normal tissue and all other categories were all above 92%. This was found to be similar to, or higher than, tissue classification using existing methods of data reduction. Wavelength-wavelength correlation among the samples highlights areas of importance for tissue classification. The two-dimensional correlation map reveals absorption by NADH and hemoglobin in the samples as negative correlation, an effect not obvious from the one-dimensional fluorescence spectra alone. The integrity of tissue was examined in a time series of spectra of a single tissue sample taken after tissue resection. The wavelength-wavelength correlation coefficient map shows the areas of significance for each fluorophore and their relation to each other. NADH displays negative correlation to collagen and FAD, from the absorption of emission or fluorescence resonance energy transfer. The wavelength-wavelength correlation map for the decay set also clearly shows that there are only three fluorophores of importance in the samples, by the well-defined pattern of the map. The sample-sample correlation coefficient map reveals the changes over time and their impact on tissue classification. Correlation coefficient mapping proves to be an effective method for sample classification and cancer

  16. Seizure detection algorithms based on EMG signals

    DEFF Research Database (Denmark)

    Conradsen, Isa

    Background: the currently used non-invasive seizure detection methods are not reliable. Muscle fibers are directly connected to the nerves, whereby electric signals are generated during activity. Therefore, an alarm system on electromyography (EMG) signals is a theoretical possibility. Objective...... on the amplitude of the signal. The other algorithm was based on information of the signal in the frequency domain, and it focused on synchronisation of the electrical activity in a single muscle during the seizure. Results: The amplitude-based algorithm reliably detected seizures in 2 of the patients, while......: to show whether medical signal processing of EMG data is feasible for detection of epileptic seizures. Methods: EMG signals during generalised seizures were recorded from 3 patients (with 20 seizures in total). Two possible medical signal processing algorithms were tested. The first algorithm was based...

  17. Repeat Sequences and Base Correlations in Human Y Chromosome Palindromes

    Institute of Scientific and Technical Information of China (English)

    Neng-zhi Jin; Zi-xian Liu; Yan-jiao Qi; Wen-yuan Qiu

    2009-01-01

    On the basis of information theory and statistical methods, we use mutual information, n-tuple entropy and conditional entropy, combined with biological characteristics, to analyze the long range correlation and short range correlation in human Y chromosome palindromes. The magnitude distribution of the long range correlation which can be reflected by the mutual information is P5>P5a>P5b (P5a and P5b are the sequences that replace solely Alu repeats and all interspersed repeats with random uncorrelated sequences in human Y chromosome palindrome 5, respectively); and the magnitude distribution of the short range correlation which can be reflected by the n-tuple entropy and the conditional entropy is P5>P5a>P5b>random uncorrelated sequence. In other words, when the Alu repeats and all interspersed repeats replace with random uncorrelated sequence, the long range and short range correlation decrease gradually. However, the random uncorrelated sequence has no correlation. This research indicates that more repeat sequences result in stronger correlation between bases in human Y chromosome. The analyses may be helpful to understand the special structures of human Y chromosome palindromes profoundly.

  18. Sella size and jaw bases - Is there a correlation???

    Directory of Open Access Journals (Sweden)

    Neha

    2016-01-01

    Full Text Available Introduction: Sella turcica is an important cephalometric structure and attempts have been made in the past to correlate its dimensions to the malocclusion. However, no study has so far compared the size of sella to the jaw bases that determine the type of malocclusion. The present study was undertaken to find out any such correlation if it exists. Materials and Methods: Lateral cephalograms of 110 adults consisting of 40 Class I, 40 Class II, and 30 Class III patients were assessed for the measurement of sella length, width, height, and area. The maxillary length, mandibular ramus height, and body length were also measured. The sella dimensions were compared among three malocclusion types by one-way ANOVA. Pearson correlation was calculated between the jaw size and sella dimensions. Furthermore, the ratio of jaw base lengths and sella area were calculated. Results and Conclusion: Mean sella length, width and area were found to be greatest in Class III, followed by Class I and least in Class II though the results were not statistically significant. 3 out of 4 measured dimensions of sella, correlated significantly with mandibular ramus and body length each. However, only one dimension of sella showed significant correlation with maxilla. The mandibular ramus and body length show a nearly constant ratio to sella area (0.83–0.85, 0.64–0.65, respectively in all the three malocclusions. Thus, mandible has a definite and better correlation to the size of sella turcica.

  19. CTA in the detection and quantification of vertebral artery pathologies: a correlation with color Doppler sonography

    Energy Technology Data Exchange (ETDEWEB)

    Puchner, Stefan; Rand, Thomas; Reiter, Markus; Lammer, Johannes; Bucek, Robert A. [Medical University Vienna, Department of Cardiovascular and Interventional Radiology, Vienna (Austria); Haumer, Markus; Minar, Erich [Medical University Vienna, Department of Angiology, Vienna (Austria)

    2007-08-15

    We evaluated the feasibility of multidetector CT angiography (MDCTA) in the examination of vertebral artery (VA) pathologies and correlated the results with those of color Doppler sonography (CDS). In this retrospective cohort analysis, we identified 65 patients with suspected cerebrovascular disease, who underwent MDCTA and CDS of the supraaortic vessels within a maximum period of 1 month. We evaluated the feasibility and image quality of MDCTA in this indication, compared the value of reformatted images and axial source images in the grading of stenoses and correlated these results with those of CDS. The image quality of the MDCTA examination was classified as good in 64 patients (98.5%) and as moderate in 1 patient (1.5%). Axial source images and reformatted images agreed perfectly in terms of stenosis detection and grading as well as the detection of hypoplastic VAs ({kappa} = 1). The correlation between MDCTA and CDS was moderate ({kappa} = 0.56) in terms of stenosis detection and quantification and poor ({kappa} = 0.35) in terms of detection of hypoplasia of the VA. MDCTA is a feasible method for the evaluation of VA pathologies providing a good image quality. Image reformatting does not add any diagnostic value to the interpretation of axial source images. The correlation between MDCTA and CDS is only moderate, reflecting the clinically important limitations of CDS in this indication. (orig.)

  20. US correlation for MRI-detected breast lesions in women with familial risk of breast cancer.

    NARCIS (Netherlands)

    Sim, L.S.; Hendriks, J.H.C.L.; Bult, P.; Fook-Chong, S.M.

    2005-01-01

    AIM: To examine the value of US correlation for MRI-detected breast lesions in women with familial risk of breast cancer. METHODS: From an initial dataset of 245 women with positive family history who had breast cancer surveillance involving mammography or MRI between November 1994 and February 2001

  1. Improved biosensor-based detection system

    DEFF Research Database (Denmark)

    2015-01-01

    Described is a new biosensor-based detection system for effector compounds, useful for in vivo applications in e.g. screening and selecting of cells which produce a small molecule effector compound or which take up a small molecule effector compound from its environment. The detection system...... comprises a protein or RNA-based biosensor for the effector compound which indirectly regulates the expression of a reporter gene via two hybrid proteins, providing for fewer false signals or less 'noise', tuning of sensitivity or other advantages over conventional systems where the biosensor directly...

  2. Detectability of trace gases in the Martian atmosphere using gas correlation filter radiometry

    Science.gov (United States)

    Sinclair, J.; Irwin, P. G. J.; Wilson, E.; Calcutt, S.

    2015-10-01

    We present the results of radiative transfer simulations of a gas correlation filter radiometer (GCFR) in the detection of trace species in the Martian atmosphere. We investigated two scenarios: 1) nadir and/or limb sounding from a Mars orbiter in the thermal infrared, 2) solar occultation measurements in the near-infrared from the Martian surface. In both scenarios, a GCFR would allow detection of trace gases at a lower concentration than that detectable by a conventional filter radiometer. In nadir/limb sounding, we find that CH4, SO2, N2O, C2H2 and CH3OH are detectable at concentrations lower than previously-derived upper limits. From solar occultation measurements, we find that CH4, SO2, C2H2, C2H6 are detectable at concentrations lower than previously-derived upper limits but only in low dust conditions.

  3. Anti-correlations in the degree distribution increase stimulus detection performance in noisy spiking neural networks.

    Science.gov (United States)

    Martens, Marijn B; Houweling, Arthur R; E Tiesinga, Paul H

    2017-02-01

    Neuronal circuits in the rodent barrel cortex are characterized by stable low firing rates. However, recent experiments show that short spike trains elicited by electrical stimulation in single neurons can induce behavioral responses. Hence, the underlying neural networks provide stability against internal fluctuations in the firing rate, while simultaneously making the circuits sensitive to small external perturbations. Here we studied whether stability and sensitivity are affected by the connectivity structure in recurrently connected spiking networks. We found that anti-correlation between the number of afferent (in-degree) and efferent (out-degree) synaptic connections of neurons increases stability against pathological bursting, relative to networks where the degrees were either positively correlated or uncorrelated. In the stable network state, stimulation of a few cells could lead to a detectable change in the firing rate. To quantify the ability of networks to detect the stimulation, we used a receiver operating characteristic (ROC) analysis. For a given level of background noise, networks with anti-correlated degrees displayed the lowest false positive rates, and consequently had the highest stimulus detection performance. We propose that anti-correlation in the degree distribution may be a computational strategy employed by sensory cortices to increase the detectability of external stimuli. We show that networks with anti-correlated degrees can in principle be formed by applying learning rules comprised of a combination of spike-timing dependent plasticity, homeostatic plasticity and pruning to networks with uncorrelated degrees. To test our prediction we suggest a novel experimental method to estimate correlations in the degree distribution.

  4. Indirectly detected chemical shift correlation NMR spectroscopy in solids under fast magic angle spinning

    Energy Technology Data Exchange (ETDEWEB)

    Mao, Kanmi [Iowa State Univ., Ames, IA (United States)

    2011-01-01

    The development of fast magic angle spinning (MAS) opened up an opportunity for the indirect detection of insensitive low-γ nuclei (e.g., 13C and 15N) via the sensitive high-{gamma} nuclei (e.g., 1H and 19F) in solid-state NMR, with advanced sensitivity and resolution. In this thesis, new methodology utilizing fast MAS is presented, including through-bond indirectly detected heteronuclear correlation (HETCOR) spectroscopy, which is assisted by multiple RF pulse sequences for 1H-1H homonuclear decoupling. Also presented is a simple new strategy for optimization of 1H-1H homonuclear decoupling. As applications, various classes of materials, such as catalytic nanoscale materials, biomolecules, and organic complexes, are studied by combining indirect detection and other one-dimensional (1D) and two-dimensional (2D) NMR techniques. Indirectly detected through-bond HETCOR spectroscopy utilizing refocused INEPT (INEPTR) mixing was developed under fast MAS (Chapter 2). The time performance of this approach in 1H detected 2D 1H{l_brace}13C{r_brace} spectra was significantly improved, by a factor of almost 10, compared to the traditional 13C detected experiments, as demonstrated by measuring naturally abundant organic-inorganic mesoporous hybrid materials. The through-bond scheme was demonstrated as a new analytical tool, which provides complementary structural information in solid-state systems in addition to through-space correlation. To further benefit the sensitivity of the INEPT transfer in rigid solids, the combined rotation and multiple-pulse spectroscopy (CRAMPS) was implemented for homonuclear 1H decoupling under fast MAS (Chapter 3). Several decoupling schemes (PMLG5m$\\bar{x}$, PMLG5mm$\\bar{x}$x and SAM3) were analyzed to maximize the performance of through-bond transfer based

  5. Distinct frontal and amygdala correlates of change detection for facial identity and expression.

    Science.gov (United States)

    Achaibou, Amal; Loth, Eva; Bishop, Sonia J

    2016-02-01

    Recruitment of 'top-down' frontal attentional mechanisms is held to support detection of changes in task-relevant stimuli. Fluctuations in intrinsic frontal activity have been shown to impact task performance more generally. Meanwhile, the amygdala has been implicated in 'bottom-up' attentional capture by threat. Here, 22 adult human participants took part in a functional magnetic resonance change detection study aimed at investigating the correlates of successful (vs failed) detection of changes in facial identity vs expression. For identity changes, we expected prefrontal recruitment to differentiate 'hit' from 'miss' trials, in line with previous reports. Meanwhile, we postulated that a different mechanism would support detection of emotionally salient changes. Specifically, elevated amygdala activation was predicted to be associated with successful detection of threat-related changes in expression, over-riding the influence of fluctuations in top-down attention. Our findings revealed that fusiform activity tracked change detection across conditions. Ventrolateral prefrontal cortical activity was uniquely linked to detection of changes in identity not expression, and amygdala activity to detection of changes from neutral to fearful expressions. These results are consistent with distinct mechanisms supporting detection of changes in face identity vs expression, the former potentially reflecting top-down attention, the latter bottom-up attentional capture by stimulus emotional salience.

  6. Distinct frontal and amygdala correlates of change detection for facial identity and expression

    Science.gov (United States)

    Achaibou, Amal; Loth, Eva

    2016-01-01

    Recruitment of ‘top-down’ frontal attentional mechanisms is held to support detection of changes in task-relevant stimuli. Fluctuations in intrinsic frontal activity have been shown to impact task performance more generally. Meanwhile, the amygdala has been implicated in ‘bottom-up’ attentional capture by threat. Here, 22 adult human participants took part in a functional magnetic resonance change detection study aimed at investigating the correlates of successful (vs failed) detection of changes in facial identity vs expression. For identity changes, we expected prefrontal recruitment to differentiate ‘hit’ from ‘miss’ trials, in line with previous reports. Meanwhile, we postulated that a different mechanism would support detection of emotionally salient changes. Specifically, elevated amygdala activation was predicted to be associated with successful detection of threat-related changes in expression, over-riding the influence of fluctuations in top-down attention. Our findings revealed that fusiform activity tracked change detection across conditions. Ventrolateral prefrontal cortical activity was uniquely linked to detection of changes in identity not expression, and amygdala activity to detection of changes from neutral to fearful expressions. These results are consistent with distinct mechanisms supporting detection of changes in face identity vs expression, the former potentially reflecting top-down attention, the latter bottom-up attentional capture by stimulus emotional salience. PMID:26245835

  7. Detection of land surface memory by correlations between thickness of colluvial deposits and morphometric variables

    Science.gov (United States)

    Mitusov, A. V.; Dreibrodt, S.; Mitusova, O. E.; Khamnueva, S. V.; Bork, H.-R.

    2013-06-01

    Some morphometric variables store information about past land surfaces longer than others. This property of morphometric variables is recognised as land surface memory. Slope deposits, soils, and vegetation also have this memory. In this study, a memory effect was quantitatively detected by Spearman correlations between thickness of colluvium and morphometric variables of the modern land surface. During long-term sedimentation, the sign of horizontal curvature (kh) may be inverted from minus to plus, suggesting that locations with positive kh values are not accumulation zones. However, the thickness of colluvial deposits at such locations in our study area indicates sediment accumulation. The sign of minimal curvature (kmin) tends to be more stable and remains negative. This difference provides the stronger correlation of colluvial layer thickness with kmin than with kh. The strongest correlation was found for total thickness of the colluvial deposits of the Neolithic and Iron Age with kmin (- 0.84); the correlation with kh was weaker (- 0.71).

  8. On the detectability of trace chemical species in the martian atmosphere using gas correlation filter radiometry

    Science.gov (United States)

    Sinclair, J. A.; Irwin, P. G. J.; Calcutt, S. B.; Wilson, E. L.

    2015-11-01

    The martian atmosphere is host to many trace gases including water (H2O) and its isotopologues, methane (CH4) and potentially sulphur dioxide (SO2), nitrous oxide (N2O) and further organic compounds, which would serve as indirect tracers of geological, chemical and biological processes on Mars. With exception of the recent detection of CH4 by Curiosity, previous detections of these species have been unsuccessful or considered tentative due to the low concentrations of these species in the atmosphere (∼10-9 partial pressures), limited spectral resolving power and/or signal-to-noise and the challenge of discriminating between telluric and martian features when observing from the Earth. In this study, we present radiative transfer simulations of an alternative method for detection of trace gas species - the gas correlation radiometry method. Two potential observing scenarios were explored where a gas correlation filter radiometer (GCFR) instrument: (1) performs nadir and/or limb sounding of the martian atmosphere in the thermal infrared (200-2000 cm-1 from an orbiting spacecraft or (2) performs solar occultation measurements in the near-infrared (2000-5000 cm-1) from a lander on the martian surface. In both scenarios, simulations of a narrowband filter radiometer (without gas correlation) were also generated to serve as a comparison. From a spacecraft, we find that a gas correlation filter radiometer, in comparison to a filter radiometer (FR), offers a greater discrimination between temperature and dust, a greater discrimination between H2O and HDO, and would allow detection of N2O and CH3OH at concentrations of ∼10 ppbv and ∼2 ppbv, respectively, which are lower than previously-derived upper limits. However, the lowest retrievable concentration of SO2 (approximately 2 ppbv) is comparable with previous upper limits and CH4 is only detectable at concentrations of approximately 10 ppbv, which is an order of magnitude higher than the concentration recently measured

  9. Water Detection Based on Object Reflections

    Science.gov (United States)

    Rankin, Arturo L.; Matthies, Larry H.

    2012-01-01

    Water bodies are challenging terrain hazards for terrestrial unmanned ground vehicles (UGVs) for several reasons. Traversing through deep water bodies could cause costly damage to the electronics of UGVs. Additionally, a UGV that is either broken down due to water damage or becomes stuck in a water body during an autonomous operation will require rescue, potentially drawing critical resources away from the primary operation and increasing the operation cost. Thus, robust water detection is a critical perception requirement for UGV autonomous navigation. One of the properties useful for detecting still water bodies is that their surface acts as a horizontal mirror at high incidence angles. Still water bodies in wide-open areas can be detected by geometrically locating the exact pixels in the sky that are reflecting on candidate water pixels on the ground, predicting if ground pixels are water based on color similarity to the sky and local terrain features. But in cluttered areas where reflections of objects in the background dominate the appearance of the surface of still water bodies, detection based on sky reflections is of marginal value. Specifically, this software attempts to solve the problem of detecting still water bodies on cross-country terrain in cluttered areas at low cost.

  10. Community detection based on network communicability

    Science.gov (United States)

    Estrada, Ernesto

    2011-03-01

    We propose a new method for detecting communities based on the concept of communicability between nodes in a complex network. This method, designated as N-ComBa K-means, uses a normalized version of the adjacency matrix to build the communicability matrix and then applies K-means clustering to find the communities in a graph. We analyze how this method performs for some pathological cases found in the analysis of the detection limit of communities and propose some possible solutions on the basis of the analysis of the ratio of local to global densities in graphs. We use four different quality criteria for detecting the best clustering and compare the new approach with the Girvan-Newman algorithm for the analysis of two "classical" networks: karate club and bottlenose dolphins. Finally, we analyze the more challenging case of homogeneous networks with community structure, for which the Girvan-Newman completely fails in detecting any clustering. The N-ComBa K-means approach performs very well in these situations and we applied it to detect the community structure in an international trade network of miscellaneous manufactures of metal having these characteristics. Some final remarks about the general philosophy of community detection are also discussed.

  11. Wafer weak point detection based on aerial images or WLCD

    Science.gov (United States)

    Ning, Guoxiang; Philipp, Peter; Litt, Lloyd C.; Ackmann, Paul; Crell, Christian; Chen, Norman

    2015-10-01

    Aerial image measurement is a key technique for model based optical proximity correction (OPC) verification. Actual aerial images obtained by AIMS (aerial image measurement system) or WLCD (wafer level critical dimension) can detect printed wafer weak point structures in advance of wafer exposure and defect inspection. Normally, the potential wafer weak points are determined based on optical rule check (ORC) simulation in advance. However, the correlation to real wafer weak points is often not perfect due to the contribution of mask three dimension (M3D) effects, actual mask errors, and scanner lens effects. If the design weak points can accurately be detected in advance, it will reduce the wafer fab cost and improve cycle time. WLCD or AIMS tools are able to measure the aerial images CD and bossung curve through focus window. However, it is difficult to detect the wafer weak point in advance without defining selection criteria. In this study, wafer weak points sensitive to mask mean-to-nominal values are characterized for a process with very high MEEF (normally more than 4). Aerial image CD uses fixed threshold to detect the wafer weak points. By using WLCD through threshold and focus window, the efficiency of wafer weak point detection is also demonstrated. A novel method using contrast range evaluation is shown in the paper. Use of the slope of aerial images for more accurate detection of the wafer weak points using WLCD is also discussed. The contrast range can also be used to detect the wafer weak points in advance. Further, since the mean to nominal of the reticle contributes to the effective contrast range in a high MEEF area this work shows that control of the mask error is critical for high MEEF layers such as poly, active and metal layers. Wafer process based weak points that cannot be detected by wafer lithography CD or WLCD will be discussed.

  12. Plagiarism Detection Based on SCAM Algorithm

    DEFF Research Database (Denmark)

    Anzelmi, Daniele; Carlone, Domenico; Rizzello, Fabio

    2011-01-01

    Plagiarism is a complex problem and considered one of the biggest in publishing of scientific, engineering and other types of documents. Plagiarism has also increased with the widespread use of the Internet as large amount of digital data is available. Plagiarism is not just direct copy but also...... paraphrasing, rewording, adapting parts, missing references or wrong citations. This makes the problem more difficult to handle adequately. Plagiarism detection techniques are applied by making a distinction between natural and programming languages. Our proposed detection process is based on natural language...

  13. Detection of rheumatoid arthritis by evaluation of normalized variances of fluorescence time correlation functions

    Science.gov (United States)

    Dziekan, Thomas; Weissbach, Carmen; Voigt, Jan; Ebert, Bernd; MacDonald, Rainer; Bahner, Malte L.; Mahler, Marianne; Schirner, Michael; Berliner, Michael; Berliner, Birgitt; Osel, Jens; Osel, Ilka

    2011-07-01

    Fluorescence imaging using the dye indocyanine green as a contrast agent was investigated in a prospective clinical study for the detection of rheumatoid arthritis. Normalized variances of correlated time series of fluorescence intensities describing the bolus kinetics of the contrast agent in certain regions of interest were analyzed to differentiate healthy from inflamed finger joints. These values are determined using a robust, parameter-free algorithm. We found that the normalized variance of correlation functions improves the differentiation between healthy joints of volunteers and joints with rheumatoid arthritis of patients by about 10% compared to, e.g., ratios of areas under the curves of raw data.

  14. Resolved target detection in clutter using correlated, dual-band imagery

    Science.gov (United States)

    Stotts, Larry B.

    2015-10-01

    This paper develops a log-likelihood ratio test statistic for resolved target detection in dual-band imagery because the previous work indicates that most of the processing gains come from processing just two bands. Simple, closed-form equations for the closed-form probabilities of false alarm and detection are given. A computer simulation validates the theory. A constant false alarm rate version of the theory is applied to real available multiband data with quasi-resolved target sets and fixed clutter noise. The results show very reasonable performance in target detectability using three sets of correlated dual-band images. Finally, this paper shows that the resolved target detection problem depends on the weighted difference between the dual-band target contrasts. The theoretical development reaffirms that the signal-to-noise ratio or contrast-to-noise ratio is approximately the weighted difference squared, divided by the normalized total image noise variance.

  15. GPU Based Software Correlators - Perspectives for VLBI2010

    Science.gov (United States)

    Hobiger, Thomas; Kimura, Moritaka; Takefuji, Kazuhiro; Oyama, Tomoaki; Koyama, Yasuhiro; Kondo, Tetsuro; Gotoh, Tadahiro; Amagai, Jun

    2010-01-01

    Caused by historical separation and driven by the requirements of the PC gaming industry, Graphics Processing Units (GPUs) have evolved to massive parallel processing systems which entered the area of non-graphic related applications. Although a single processing core on the GPU is much slower and provides less functionality than its counterpart on the CPU, the huge number of these small processing entities outperforms the classical processors when the application can be parallelized. Thus, in recent years various radio astronomical projects have started to make use of this technology either to realize the correlator on this platform or to establish the post-processing pipeline with GPUs. Therefore, the feasibility of GPUs as a choice for a VLBI correlator is being investigated, including pros and cons of this technology. Additionally, a GPU based software correlator will be reviewed with respect to energy consumption/GFlop/sec and cost/GFlop/sec.

  16. Sodium boiling detection in LMFBRs by acoustic-neutronic cross correlation

    Energy Technology Data Exchange (ETDEWEB)

    Wright, S.A.

    1977-01-01

    The acoustic and neutronic noise signals caused by boiling are the signals primarily considered likely to detect sodium boiling in an LMFBR. Unfortunately, these signals may have serious signal-to-noise problems due to strong background noise sources. Neutronic-acoustic cross correlation techniques are expected to provide a means of improving the signal-to-noise ratio. This technique can improve the signal-to-noise ratio because the neutronic and acoustic signals due to boiling are highly correlated near the bubble repetition frequency, while the background noise sources are expected to be uncorrelated (or at most weakly correlated). An experiment was designed to show that the neutronic and acoustic noise signals are indeed highly correlated. The experiment consisted of simulating the void and pressure effects of local sodium boiling in the core of a zero-power reactor (ARK). The analysis showed that the neutronic and acoustic noise signals caused by boiling are almost perfectly correlated in a wide frequency band about the bubble repetition frequency. The results of the experiments were generalized to full-scale reactors to compare the inherent effectiveness of the methods which use the neutronic or acoustic signals alone with a hybrid method, which cross correlates the neutronic and acoustic signals. It was concluded that over a zone of the reactor where the void coefficient is sufficiently large (approximately 85 percent the core volume), the cross correlation method can provide a more rapid detection system for a given signal-to-noise ratio. However, where the void coefficient is small, one must probably rely on the acoustic method alone.

  17. Correlates of gender and achievement in introductory algebra based physics

    Science.gov (United States)

    Smith, Rachel Clara

    The field of physics is heavily male dominated in America. Thus, half of the population of our country is underrepresented and underserved. The identification of factors that contribute to gender disparity in physics is necessary for educators to address the individual needs of students, and, in particular, the separate and specific needs of female students. In an effort to determine if any correlations could be established or strengthened between sex, gender identity, social network, algebra skill, scientific reasoning ability, and/or student attitude, a study was performed on a group of 82 students in an introductory algebra based physics course. The subjects each filled out a survey at the beginning of the semester of their first semester of algebra based physics. They filled out another survey at the end of that same semester. These surveys included physics content pretests and posttests, as well as questions about the students' habits, attitudes, and social networks. Correlates of posttest score were identified, in order of significance, as pretest score, emphasis on conceptual learning, preference for male friends, number of siblings (negatively correlated), motivation in physics, algebra score, and parents' combined education level. Number of siblings was also found to negatively correlate with, in order of significance, gender identity, preference for male friends, emphasis on conceptual learning, and motivation in physics. Preference for male friends was found to correlate with, in order of significance, emphasis on conceptual learning, gender identity, and algebra score. Also, gender identity was found to correlate with emphasis on conceptual learning, the strongest predictor of posttest score other than pretest score.

  18. DATA-MINING BASED FAULT DETECTION

    Institute of Scientific and Technical Information of China (English)

    Ma Hongguang; Han Chongzhao; Wang Guohua; Xu Jianfeng; Zhu Xiaofei

    2005-01-01

    This paper presents a fault-detection method based on the phase space reconstruction and data mining approaches for the complex electronic system. The approach for the phase space reconstruction of chaotic time series is a combination algorithm of multiple autocorrelation and Γ-test, by which the quasi-optimal embedding dimension and time delay can be obtained.The data mining algorithm, which calculates the radius of gyration of unit-mass point around the centre of mass in the phase space, can distinguish the fault parameter from the chaotic time series output by the tested system. The experimental results depict that this fault detection method can correctly detect the fault phenomena of electronic system.

  19. Regional principal color based saliency detection.

    Directory of Open Access Journals (Sweden)

    Jing Lou

    Full Text Available Saliency detection is widely used in many visual applications like image segmentation, object recognition and classification. In this paper, we will introduce a new method to detect salient objects in natural images. The approach is based on a regional principal color contrast modal, which incorporates low-level and medium-level visual cues. The method allows a simple computation of color features and two categories of spatial relationships to a saliency map, achieving higher F-measure rates. At the same time, we present an interpolation approach to evaluate resulting curves, and analyze parameters selection. Our method enables the effective computation of arbitrary resolution images. Experimental results on a saliency database show that our approach produces high quality saliency maps and performs favorably against ten saliency detection algorithms.

  20. Pollution detection by digital correlation of multispectral, stero-image pairs.

    Science.gov (United States)

    Krause, F. R.; Betz, H. T.; Lysobey, D. H.

    1971-01-01

    Remote detection of air pollution circulation patterns is proposed to eventually predict the accumulation of hazardous surface concentrations in time for preventive emission control operations. Earth observations from space platforms will contain information on the height, mean velocity and lateral mixing scales of inversion layers and pollution plumes. Although this information is often not visible on photographs, it could conceivably be retrieved through a digital cross-correlation of multispectral stereo image pairs. Laboratory and field test results are used to illustrate the detection of non-visual inversion layers, the reduction of dominant signal interference, and the spectroscopic identification of combustion products.

  1. Water Detection Based on Color Variation

    Science.gov (United States)

    Rankin, Arturo L.

    2012-01-01

    This software has been designed to detect water bodies that are out in the open on cross-country terrain at close range (out to 30 meters), using imagery acquired from a stereo pair of color cameras mounted on a terrestrial, unmanned ground vehicle (UGV). This detector exploits the fact that the color variation across water bodies is generally larger and more uniform than that of other naturally occurring types of terrain, such as soil and vegetation. Non-traversable water bodies, such as large puddles, ponds, and lakes, are detected based on color variation, image intensity variance, image intensity gradient, size, and shape. At ranges beyond 20 meters, water bodies out in the open can be indirectly detected by detecting reflections of the sky below the horizon in color imagery. But at closer range, the color coming out of a water body dominates sky reflections, and the water cue from sky reflections is of marginal use. Since there may be times during UGV autonomous navigation when a water body does not come into a perception system s field of view until it is at close range, the ability to detect water bodies at close range is critical. Factors that influence the perceived color of a water body at close range are the amount and type of sediment in the water, the water s depth, and the angle of incidence to the water body. Developing a single model of the mixture ratio of light reflected off the water surface (to the camera) to light coming out of the water body (to the camera) for all water bodies would be fairly difficult. Instead, this software detects close water bodies based on local terrain features and the natural, uniform change in color that occurs across the surface from the leading edge to the trailing edge.

  2. Spectral methods and cluster structure in correlation-based networks

    Science.gov (United States)

    Heimo, Tapio; Tibély, Gergely; Saramäki, Jari; Kaski, Kimmo; Kertész, János

    2008-10-01

    We investigate how in complex systems the eigenpairs of the matrices derived from the correlations of multichannel observations reflect the cluster structure of the underlying networks. For this we use daily return data from the NYSE and focus specifically on the spectral properties of weight W=|-δ and diffusion matrices D=W/sj-δ, where C is the correlation matrix and si=∑jW the strength of node j. The eigenvalues (and corresponding eigenvectors) of the weight matrix are ranked in descending order. As in the earlier observations, the first eigenvector stands for a measure of the market correlations. Its components are, to first approximation, equal to the strengths of the nodes and there is a second order, roughly linear, correction. The high ranking eigenvectors, excluding the highest ranking one, are usually assigned to market sectors and industrial branches. Our study shows that both for weight and diffusion matrices the eigenpair analysis is not capable of easily deducing the cluster structure of the network without a priori knowledge. In addition we have studied the clustering of stocks using the asset graph approach with and without spectrum based noise filtering. It turns out that asset graphs are quite insensitive to noise and there is no sharp percolation transition as a function of the ratio of bonds included, thus no natural threshold value for that ratio seems to exist. We suggest that these observations can be of use for other correlation based networks as well.

  3. The Detection of Defects in Optical Fibers Using a Hybrid Opto-electronic Correlator

    Institute of Scientific and Technical Information of China (English)

    LIU Yange; LIU Wei; ZHANG Yimo; ZHOU Ge

    2000-01-01

    A hybrid opto-electronic correlator for detecting defects in optical fibers is proposed. After the light from a He-Ne laser being expanded and filtered it is not collimated but directly passes a Fourier transform lens and illuminates a reference fiber and a test fiber at the same input plane. The Fourier transform spectrum of the two fibers is therefore obtained at the rear focal plane of the lens, where it is sampled via a CCD array connected with a computer through a frame grabber. The computer performs filter, inverse Fourier transform and setting threshold operation on classification. The system is an equivalent of joint transform correlator with a Fourier lens of long focal length. The experiment results for optical fibers having incoordinate defects are presented. The results indicate that the system can be used for fiber defect detection, and has the advantages of high identification, compact configuration, easy adjustment and flexible manipulation.

  4. Detectability of Pore Defect in Wind Turbine Blade Composites Using Image Correlation Technique

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jong Il; Huh, Yong Hak; Lee, Gun Chang [Korea Research institute of Standard and Science, Daejeon (Korea, Republic of)

    2013-10-15

    Defects that occur during the manufacturing process or operation of a wind turbine blade have a great influence on its life and safety. Typically, defects such as delamination, pore, wrinkle and matrix crack are found in a blade. In this study, the detectability of the pores, a type of defect that frequently occur during manufacturing, was examined from the full field strain distribution determined with the image correlation technique. Pore defects were artificially introduced in four-ply laminated GFRP composites with 0 .deg/{+-}45 .deg fiber direction. The artificial pores were introduced in consideration of their size and location. Three different-sized pores with diameter of 1, 2 and 3 mm were located on the top and bottom surface and embedded. By applying static loads of 0-200 MPa, the strain distributions over the specimen with the pore defects were determined using image correlation technique. It was found the pores with diameter exceeding 2 mm can be detected in diameter.

  5. An FPGA-Based People Detection System

    Directory of Open Access Journals (Sweden)

    James J. Clark

    2005-05-01

    Full Text Available This paper presents an FPGA-based system for detecting people from video. The system is designed to use JPEG-compressed frames from a network camera. Unlike previous approaches that use techniques such as background subtraction and motion detection, we use a machine-learning-based approach to train an accurate detector. We address the hardware design challenges involved in implementing such a detector, along with JPEG decompression, on an FPGA. We also present an algorithm that efficiently combines JPEG decompression with the detection process. This algorithm carries out the inverse DCT step of JPEG decompression only partially. Therefore, it is computationally more efficient and simpler to implement, and it takes up less space on the chip than the full inverse DCT algorithm. The system is demonstrated on an automated video surveillance application and the performance of both hardware and software implementations is analyzed. The results show that the system can detect people accurately at a rate of about 2.5 frames per second on a Virtex-II 2V1000 using a MicroBlaze processor running at 75 MHz, communicating with dedicated hardware over FSL links.

  6. IMAGE ANALYSIS BASED ON EDGE DETECTION TECHNIQUES

    Institute of Scientific and Technical Information of China (English)

    纳瑟; 刘重庆

    2002-01-01

    A method that incorporates edge detection technique, Markov Random field (MRF), watershed segmentation and merging techniques was presented for performing image segmentation and edge detection tasks. It first applies edge detection technique to obtain a Difference In Strength (DIS) map. An initial segmented result is obtained based on K-means clustering technique and the minimum distance. Then the region process is modeled by MRF to obtain an image that contains different intensity regions. The gradient values are calculated and then the watershed technique is used. DIS calculation is used for each pixel to define all the edges (weak or strong) in the image. The DIS map is obtained. This help as priority knowledge to know the possibility of the region segmentation by the next step (MRF), which gives an image that has all the edges and regions information. In MRF model,gray level l, at pixel location i, in an image X, depends on the gray levels of neighboring pixels. The segmentation results are improved by using watershed algorithm. After all pixels of the segmented regions are processed, a map of primitive region with edges is generated. The edge map is obtained using a merge process based on averaged intensity mean values. A common edge detectors that work on (MRF) segmented image are used and the results are compared. The segmentation and edge detection result is one closed boundary per actual region in the image.

  7. Time correlation measurements from extensive air showers detected by the EEE telescopes

    CERN Document Server

    Abbrescia, M; Fabbri, F L; Gnesi, I; Bressan, E; Tosello, F; Librizzi, F; Coccia, E; Paoletti, R; Yanez, G; Li, S; Votano, L; Scribano, A; Avanzini, C; Piragino, G; Perasso, L; Regano, A; Ferroli, R Baldini; De Gruttola, D; Sartorelli, G; Siddi, E; Cifarelli, L; Di Giovanni, A; Frolov, V; Serci, S; Selvi, M; Zouyevski, R; Dreucci, M; Squarcia, S; Righini, G C; Agocs, A; Zichichi, A; La Rocca, P; Pilo, F; Miozzi, S; Massai, M; Cicalo, C; D'Incecco, M; Panareo, M; Gemme, G; Garbini, M; Aiola, S; Riggi, F; Hatzifotiadou, D; Scapparone, E; Chiavassa, A; Maggiora, A; Bencivenni, G; Gustavino, C; Spandre, G; Taiuti, M; Williams, M C S; Bossini, E; De Pasquale, S

    2013-01-01

    Time correlated events due to cosmic muons from extensive air showers have been detected by means of telescope pairs of the EEE (Extreme Energy Events) Project array. The coincidence rate, properly normalized for detector acceptance, efficiency and altitude location, has been extracted as a function of the relative distance between the telescopes. The results have been also compared with additional measurements carried out by small scintillator detectors at various distances.

  8. Time correlation measurements from extensive air showers detected by the EEE telescopes

    Science.gov (United States)

    Abbrescia, M.; Agocs, A.; Aiola, S.; Antolini, R.; Avanzini, C.; Baldini Ferroli, R.; Bencivenni, G.; Bossini, E.; Bressan, E.; Chiavassa, A.; Cicalò, C.; Cifarelli, L.; Coccia, E.; De Gruttola, D.; De Pasquale, S.; Di Giovanni, A.; D'Incecco, M.; Dreucci, M.; Fabbri, F. L.; Frolov, V.; Garbini, M.; Gemme, G.; Gnesi, I.; Gustavino, C.; Hatzifotiadou, D.; La Rocca, P.; Li, S.; Librizzi, F.; Maggiora, A.; Massai, M.; Miozzi, S.; Panareo, M.; Paoletti, R.; Perasso, L.; Pilo, F.; Piragino, G.; Regano, A.; Riggi, F.; Righini, G. C.; Sartorelli, G.; Scapparone, E.; Scribano, A.; Selvi, M.; Serci, S.; Siddi, E.; Spandre, G.; Squarcia, S.; Taiuti, M.; Tosello, F.; Votano, L.; Williams, M. C. S.; Yanez, G.; Zichichi, A.; Zouyevski, R.

    2013-12-01

    Time correlated events due to cosmic muons from extensive air showers have been detected by means of telescope pairs of the EEE (Extreme Energy Events) Project array. The coincidence rate, properly normalized for detector acceptance, efficiency and altitude location, has been extracted as a function of the relative distance between the telescopes. The results have been also compared with additional measurements carried out by small scintillator detectors at various distances.

  9. Semiautomated tremor detection using a combined cross-correlation and neural network approach

    Science.gov (United States)

    Horstmann, Tobias; Harrington, Rebecca M.; Cochran, Elizabeth S.

    2013-01-01

    Despite observations of tectonic tremor in many locations around the globe, the emergent phase arrivals, low‒amplitude waveforms, and variable event durations make automatic detection a nontrivial task. In this study, we employ a new method to identify tremor in large data sets using a semiautomated technique. The method first reduces the data volume with an envelope cross‒correlation technique, followed by a Self‒Organizing Map (SOM) algorithm to identify and classify event types. The method detects tremor in an automated fashion after calibrating for a specific data set, hence we refer to it as being “semiautomated”. We apply the semiautomated detection algorithm to a newly acquired data set of waveforms from a temporary deployment of 13 seismometers near Cholame, California, from May 2010 to July 2011. We manually identify tremor events in a 3 week long test data set and compare to the SOM output and find a detection accuracy of 79.5%. Detection accuracy improves with increasing signal‒to‒noise ratios and number of available stations. We find detection completeness of 96% for tremor events with signal‒to‒noise ratios above 3 and optimal results when data from at least 10 stations are available. We compare the SOM algorithm to the envelope correlation method of Wech and Creager and find the SOM performs significantly better, at least for the data set examined here. Using the SOM algorithm, we detect 2606 tremor events with a cumulative signal duration of nearly 55 h during the 13 month deployment. Overall, the SOM algorithm is shown to be a flexible new method that utilizes characteristics of the waveforms to identify tremor from noise or other seismic signals.

  10. Detection of weak gravitational lensing magnification from Galaxy-QSO cross-correlation in the SDSS

    CERN Document Server

    Gaztañaga, E

    2003-01-01

    We report a detection of galaxy-QSO cross-correlation w_{GQ} in the Sloan Digital Sky Survey (SDSS) Early Data Release (EDR) over 0.2-30 arc-minute scales. We cross-correlate galaxy samples of different mean depths r'=19-22 (z_G =0.15-0.35) with the main QSO population (i'_Q <19.2) at \\zbar_Q \\simeq 1.6. We find positive detection in most cases (except for the faintest QSOs as expeceted) with up to 8-sigma significance. The amplitude of the signal on arc-minute scales is about 20% at z_G=0.15 decreasing to 10% at z_G =0.35 This is a few times larger than currently expected from structure formation LCDM models o but confirms, at a higher significance, previous measurements by several groups. The shape and redshift evolution agrees well with being a lensing signal. We also find a 3-sigma detection for the (pseudo) skewness (galaxy-galaxy-QSO correlation): S_3 = 18.6 \\pm 5.7$ The data indicates very strong non-linear amplitude for the underlaying matter fluctuations scales of 0.2$ Mpc/h, in apparent contradic...

  11. Wenchuan Event Detection And Localization Using Waveform Correlation Coupled With Double Difference

    Science.gov (United States)

    Slinkard, M.; Heck, S.; Schaff, D. P.; Young, C. J.; Richards, P. G.

    2014-12-01

    The well-studied Wenchuan aftershock sequence triggered by the May 12, 2008, Ms 8.0, mainshock offers an ideal test case for evaluating the effectiveness of using waveform correlation coupled with double difference relocation to detect and locate events in a large aftershock sequence. We use Sandia's SeisCorr detector to process 3 months of data recorded by permanent IRIS and temporary ASCENT stations using templates from events listed in a global catalog to find similar events in the raw data stream. Then we take the detections and relocate them using the double difference method. We explore both the performance that can be expected with using just a small number of stations, and, the benefits of reprocessing a well-studied sequence such as this one using waveform correlation to find even more events. We benchmark our results against previously published results describing relocations of regional catalog data. Before starting this project, we had examples where with just a few stations at far-regional distances, waveform correlation combined with double difference did and impressive job of detection and location events with precision at the few hundred and even tens of meters level.

  12. Design and implementation of random noise radar with spectral-domain correlation for moving target detection

    Science.gov (United States)

    Kim, Jeong Phill; Jeong, Chi Hyun; Kim, Cheol Hoo

    2011-06-01

    A correlation processing algorithm in the spectral domain is proposed for detecting moving targets with random noise radar. AD converted reference and Rx signals are passed through FFT block, and they are multiplied after the reference signal is complex conjugated. Now inverse FFT yields the sub-correlation results, and range and velocity information can be accurately extracted by an additional FFT processing. In this design procedure, specific considerations have to be made for correlation length, averaging number, and number of sub-correlation data for Doppler processing. The proposed algorithm was verified by Simulink (Mathworks) simulation, and its logic was implemented with Xilinx FPGA device (Vertex5 series) by System Generator block sets (Xilinx) in the Simulink environment. A CW X-band random-FM noise radar prototype with an instantaneous bandwidth of 100 MHz was designed and implemented, and laboratory and field tests were conducted to detect moving targets, and the observed results showed the validity of the proposed algorithm and the operation of implemented FPGA logics.

  13. NO2 Detection Using Microcantilever Based Potentiometry

    Directory of Open Access Journals (Sweden)

    Goutam Koley

    2008-11-01

    Full Text Available A highly sensitive and novel sensor platform for gases and volatile chemicals using microcantilever based potentiometry is reported. A resonant cantilever is used to detect the changes in surface work functions of functionalized substrates caused by adsorption of target gas molecules. Surface work function (SWF changes were measured for different functionalization layers made of transition metal oxide thin films with the flow of NO2. The rate of change in SWF for In2O3 and SnO2 were found to be ~80 and ~100 μV/sec, respectively, for 70 ppm NO2. A sensitivity of 64 μV/sec for SWF change was also found for 70 ppm NO2 concentration for isolated clusters of ZnO nanowires, indicating that this technique is applicable even for nano-clusters of sensing materials where amperometric detection is impossible due to material discontinuity. NO2 detection as low as 400 ppb was possible using highly insulating In2O3 and SnO2 thin films (resistivity > 1 TΩ/⎕. Two different forms of nano scale graphite were compared with the transition oxide based functionalization layer for sensing sub-ppm NO2 sensing. It was observed that nanostructured graphite (NG shows much higher sensitivity and lower response time than transition metal oxides.

  14. Bacteriophage based probes for pathogen detection.

    Science.gov (United States)

    Singh, Amit; Arutyunov, Denis; Szymanski, Christine M; Evoy, Stephane

    2012-08-01

    Rapid and specific detection of pathogenic bacteria is important for the proper treatment, containment and prevention of human, animal and plant diseases. Identifying unique biological probes to achieve a high degree of specificity and minimize false positives has therefore garnered much interest in recent years. Bacteriophages are obligate intracellular parasites that subvert bacterial cell resources for their own multiplication and production of disseminative new virions, which repeat the cycle by binding specifically to the host surface receptors and injecting genetic material into the bacterial cells. The precision of host recognition in phages is imparted by the receptor binding proteins (RBPs) that are often located in the tail-spike or tail fiber protein assemblies of the virions. Phage host recognition specificity has been traditionally exploited for bacterial typing using laborious and time consuming bacterial growth assays. At the same time this feature makes phage virions or RBPs an excellent choice for the development of probes capable of selectively capturing bacteria on solid surfaces with subsequent quick and automatic detection of the binding event. This review focuses on the description of pathogen detection approaches based on immobilized phage virions as well as pure recombinant RBPs. Specific advantages of RBP-based molecular probes are also discussed.

  15. Correlation-based temperature and emissivity separation algorithm

    Institute of Scientific and Technical Information of China (English)

    CHENG Jie; LIU QinHuo; LI XiaoWen; XIAO Qing; LIU Qiang; DU YongMing

    2008-01-01

    Based on analyzing the relationship between the atmospheric downward radiance and surface emissivity, this paper proposes a correlation criterion to optimize surface temperature during the process of temperature and emissivity separation from thermal infrared hyperspectral data, and puts forward the correlation-based temperature and emissivity separation algorithm (CBTES). The algorithm uses the correlation between the atmospheric downward radiance and surface emissivity to optimize surface temperature, and obtains surface emissivity with this temperature. The accuracy of CBTES was evaluated by the simulated thermal infrared hyperspectral data. The simulated results show that the CBTES can achieve high accuracy of temperature and emissivity inversion. CBTES has been compared with the iterative spectrally smooth temperature/emissivity separation (ISSTES), and the comparison results show that they have relative accuracy. Besides, CBTES is insensitive to the instrumental random noise and the change of atmospheric downward radiance during the measurements. As regards the nonisothermal pixel, its radiometric temperature changes slowly with the wavenumber when its emissivity is defined as r-emissivity. The CBTES can be used to derive the equivalent temperature of nonisothermal pixel in a narrow spectral region when we assumed that the radiometric temperature is invariable in the narrow spectral region. The derived equivalent temperatures in multi-spectral regions in 714-250cm-1 can characterize the change trend of nonisothermal pixel's radiometric temperature.

  16. Correlation-based temperature and emissivity separation algorithm

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Based on analyzing the relationship between the atmospheric downward radiance and surface emis- sivity, this paper proposes a correlation criterion to optimize surface temperature during the process of temperature and emissivity separation from thermal infrared hyperspectral data, and puts forward the correlation-based temperature and emissivity separation algorithm (CBTES). The algorithm uses the correlation between the atmospheric downward radiance and surface emissivity to optimize surface temperature, and obtains surface emissivity with this temperature. The accuracy of CBTES was evalu- ated by the simulated thermal infrared hyperspectral data. The simulated results show that the CBTES can achieve high accuracy of temperature and emissivity inversion. CBTES has been compared with the iterative spectrally smooth temperature/emissivity separation (ISSTES), and the comparison results show that they have relative accuracy. Besides, CBTES is insensitive to the instrumental random noise and the change of atmospheric downward radiance during the measurements. As regards the noniso- thermal pixel, its radiometric temperature changes slowly with the wavenumber when its emissivity is defined as r-emissivity. The CBTES can be used to derive the equivalent temperature of nonisothermal pixel in a narrow spectral region when we assumed that the radiometric temperature is invariable in the narrow spectral region. The derived equivalent temperatures in multi-spectral regions in 714―1250 cm?1 can characterize the change trend of nonisothermal pixel’s radiometric temperature.

  17. Cross correlation calculations and neutron scattering analysis for a portable solid state neutron detection system

    Science.gov (United States)

    Saltos, Andrea

    In efforts to perform accurate dosimetry, Oakes et al. [Nucl. Intrum. Mehods. (2013)] introduced a new portable solid state neutron rem meter based on an adaptation of the Bonner sphere and the position sensitive long counter. The system utilizes high thermal efficiency neutron detectors to generate a linear combination of measurement signals that are used to estimate the incident neutron spectra. The inversion problem associated to deduce dose from the counts in individual detector elements is addressed by applying a cross-correlation method which allows estimation of dose with average errors less than 15%. In this work, an evaluation of the performance of this system was extended to take into account new correlation techniques and neutron scattering contribution. To test the effectiveness of correlations, the Distance correlation, Pearson Product-Moment correlation, and their weighted versions were performed between measured spatial detector responses obtained from nine different test spectra, and the spatial response of Library functions generated by MCNPX. Results indicate that there is no advantage of using the Distance Correlation over the Pearson Correlation, and that weighted versions of these correlations do not increase their performance in evaluating dose. Both correlations were proven to work well even at low integrated doses measured for short periods of time. To evaluate the contribution produced by room-return neutrons on the dosimeter response, MCNPX was used to simulate dosimeter responses for five isotropic neutron sources placed inside different sizes of rectangular concrete rooms. Results show that the contribution of scattered neutrons to the response of the dosimeter can be significant, so that for most cases the dose is over predicted with errors as large as 500%. A possible method to correct for the contribution of room-return neutrons is also assessed and can be used as a good initial estimate on how to approach the problem.

  18. PCR-free detection of genetically modified organisms using magnetic capture technology and fluorescence cross-correlation spectroscopy.

    Directory of Open Access Journals (Sweden)

    Xiaoming Zhou

    Full Text Available The safety of genetically modified organisms (GMOs has attracted much attention recently. Polymerase chain reaction (PCR amplification is a common method used in the identification of GMOs. However, a major disadvantage of PCR is the potential amplification of non-target DNA, causing false-positive identification. Thus, there remains a need for a simple, reliable and ultrasensitive method to identify and quantify GMO in crops. This report is to introduce a magnetic bead-based PCR-free method for rapid detection of GMOs using dual-color fluorescence cross-correlation spectroscopy (FCCS. The cauliflower mosaic virus 35S (CaMV35S promoter commonly used in transgenic products was targeted. CaMV35S target was captured by a biotin-labeled nucleic acid probe and then purified using streptavidin-coated magnetic beads through biotin-streptavidin linkage. The purified target DNA fragment was hybridized with two nucleic acid probes labeled respectively by Rhodamine Green and Cy5 dyes. Finally, FCCS was used to detect and quantify the target DNA fragment through simultaneously detecting the fluorescence emissions from the two dyes. In our study, GMOs in genetically engineered soybeans and tomatoes were detected, using the magnetic bead-based PCR-free FCCS method. A detection limit of 50 pM GMOs target was achieved and PCR-free detection of GMOs from 5 microg genomic DNA with magnetic capture technology was accomplished. Also, the accuracy of GMO determination by the FCCS method is verified by spectrophotometry at 260 nm using PCR amplified target DNA fragment from GM tomato. The new method is rapid and effective as demonstrated in our experiments and can be easily extended to high-throughput and automatic screening format. We believe that the new magnetic bead-assisted FCCS detection technique will be a useful tool for PCR-free GMOs identification and other specific nucleic acids.

  19. PCR-free detection of genetically modified organisms using magnetic capture technology and fluorescence cross-correlation spectroscopy.

    Science.gov (United States)

    Zhou, Xiaoming; Xing, Da; Tang, Yonghong; Chen, Wei R

    2009-11-26

    The safety of genetically modified organisms (GMOs) has attracted much attention recently. Polymerase chain reaction (PCR) amplification is a common method used in the identification of GMOs. However, a major disadvantage of PCR is the potential amplification of non-target DNA, causing false-positive identification. Thus, there remains a need for a simple, reliable and ultrasensitive method to identify and quantify GMO in crops. This report is to introduce a magnetic bead-based PCR-free method for rapid detection of GMOs using dual-color fluorescence cross-correlation spectroscopy (FCCS). The cauliflower mosaic virus 35S (CaMV35S) promoter commonly used in transgenic products was targeted. CaMV35S target was captured by a biotin-labeled nucleic acid probe and then purified using streptavidin-coated magnetic beads through biotin-streptavidin linkage. The purified target DNA fragment was hybridized with two nucleic acid probes labeled respectively by Rhodamine Green and Cy5 dyes. Finally, FCCS was used to detect and quantify the target DNA fragment through simultaneously detecting the fluorescence emissions from the two dyes. In our study, GMOs in genetically engineered soybeans and tomatoes were detected, using the magnetic bead-based PCR-free FCCS method. A detection limit of 50 pM GMOs target was achieved and PCR-free detection of GMOs from 5 microg genomic DNA with magnetic capture technology was accomplished. Also, the accuracy of GMO determination by the FCCS method is verified by spectrophotometry at 260 nm using PCR amplified target DNA fragment from GM tomato. The new method is rapid and effective as demonstrated in our experiments and can be easily extended to high-throughput and automatic screening format. We believe that the new magnetic bead-assisted FCCS detection technique will be a useful tool for PCR-free GMOs identification and other specific nucleic acids.

  20. Robust Reservoir Generation by Correlation-Based Learning

    Directory of Open Access Journals (Sweden)

    Tadashi Yamazaki

    2009-01-01

    Full Text Available Reservoir computing (RC is a new framework for neural computation. A reservoir is usually a recurrent neural network with fixed random connections. In this article, we propose an RC model in which the connections in the reservoir are modifiable. Specifically, we consider correlation-based learning (CBL, which modifies the connection weight between a given pair of neurons according to the correlation in their activities. We demonstrate that CBL enables the reservoir to reproduce almost the same spatiotemporal activity patterns in response to an identical input stimulus in the presence of noise. This result suggests that CBL enhances the robustness in the generation of the spatiotemporal activity pattern against noise in input signals. We apply our RC model to trace eyeblink conditioning. The reservoir bridged the gap of an interstimulus interval between the conditioned and unconditioned stimuli, and a readout neuron was able to learn and express the timed conditioned response.

  1. Optimization of integer wavelet transforms based on difference correlation structures.

    Science.gov (United States)

    Li, Hongliang; Liu, Guizhong; Zhang, Zhongwei

    2005-11-01

    In this paper, a novel lifting integer wavelet transform based on difference correlation structure (DCCS-LIWT) is proposed. First, we establish a relationship between the performance of a linear predictor and the difference correlations of an image. The obtained results provide a theoretical foundation for the following construction of the optimal lifting filters. Then, the optimal prediction lifting coefficients in the sense of least-square prediction error are derived. DCCS-LIWT puts heavy emphasis on image inherent dependence. A distinct feature of this method is the use of the variance-normalized autocorrelation function of the difference image to construct a linear predictor and adapt the predictor to varying image sources. The proposed scheme also allows respective calculations of the lifting filters for the horizontal and vertical orientations. Experimental evaluation shows that the proposed method produces better results than the other well-known integer transforms for the lossless image compression.

  2. An immune based dynamic intrusion detection model

    Institute of Scientific and Technical Information of China (English)

    LI Tao

    2005-01-01

    With the dynamic description method for self and antigen, and the concept of dynamic immune tolerance for lymphocytes in network-security domain presented in this paper, a new immune based dynamic intrusion detection model (Idid) is proposed. In Idid, the dynamic models and the corresponding recursive equations of the lifecycle of mature lymphocytes, and the immune memory are built. Therefore, the problem of the dynamic description of self and nonself in computer immune systems is solved, and the defect of the low efficiency of mature lymphocyte generating in traditional computer immune systems is overcome. Simulations of this model are performed, and the comparison experiment results show that the proposed dynamic intrusion detection model has a better adaptability than the traditional methods.

  3. Frequency Based Fault Detection in Wind Turbines

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob

    2014-01-01

    In order to obtain lower cost of energy for wind turbines fault detection and accommodation is important. Expensive condition monitoring systems are often used to monitor the condition of rotating and vibrating system parts. One example is the gearbox in a wind turbine. This system is operated...... in parallel to the control system, using different computers and additional often expensive sensors. In this paper a simple filter based algorithm is proposed to detect changes in a resonance frequency in a system, exemplified with faults resulting in changes in the resonance frequency in the wind turbine...... gearbox. Only the generator speed measurement which is available in even simple wind turbine control systems is used as input. Consequently this proposed scheme does not need additional sensors and computers for monitoring the condition of the wind gearbox. The scheme is evaluated on a wide-spread wind...

  4. An SPR based sensor for allergens detection.

    Science.gov (United States)

    Ashley, J; Piekarska, M; Segers, C; Trinh, L; Rodgers, T; Willey, R; Tothill, I E

    2017-02-15

    A simple, sensitive and label-free optical sensor method was developed for allergens analysis using α-casein as the biomarker for cow's milk detection, to be used directly in final rinse samples of cleaning in place systems (CIP) of food manufacturers. A Surface Plasmon Resonance (SPR) sensor chip consisting of four sensing arrays enabling the measurement of samples and control binding events simultaneously on the sensor surface was employed in this work. SPR offers several advantages in terms of label free detection, real time measurements and superior sensitivity when compared to ELISA based techniques. The gold sensor chip was used to immobilise α-casein-polyclonal antibody using EDC/NHS coupling procedure. The performance of the assay and the sensor was first optimised and characterised in pure buffer conditions giving a detection limit of 58ngmL(-1) as a direct binding assay. The assay sensitivity can be further improved by using sandwich assay format and amplified with nanoparticles. However, at this stage this is not required as the detection limit achieved exceeded the required allergens detection levels of 2µgmL(-1) for α-S1-casein. The sensor demonstrated good selectivity towards the α-casein as the target analyte and adequate recoveries from CIP final rinse wash samples. The sensor would be useful tool for monitoring allergen levels after cleaning procedures, providing additional data that may better inform upon wider food allergen risk management decision(s) that are made by food manufacturer. In particular, this sensor could potentially help validate or optimise cleaning practices for a given food manufacturing process.

  5. 3D shape measurement with phase correlation based fringe projection

    Science.gov (United States)

    Kühmstedt, Peter; Munckelt, Christoph; Heinze, Matthias; Bräuer-Burchardt, Christian; Notni, Gunther

    2007-06-01

    Here we propose a method for 3D shape measurement by means of phase correlation based fringe projection in a stereo arrangement. The novelty in the approach is characterized by following features. Correlation between phase values of the images of two cameras is used for the co-ordinate calculation. This work stands in contrast to the sole usage of phase values (phasogrammetry) or classical triangulation (phase values and image co-ordinates - camera raster values) for the determination of the co-ordinates. The method's main advantage is the insensitivity of the 3D-coordinates from the absolute phase values. Thus it prevents errors in the determination of the co-ordinates and improves robustness in areas with interreflections artefacts and inhomogeneous regions of intensity. A technical advantage is the fact that the accuracy of the 3D co-ordinates does not depend on the projection resolution. Thus the achievable quality of the 3D co-ordinates can be selectively improved by the use of high quality camera lenses and can participate in improvements in modern camera technologies. The presented new solution of the stereo based fringe projection with phase correlation makes a flexible, errortolerant realization of measuring systems within different applications like quality control, rapid prototyping, design and CAD/CAM possible. In the paper the phase correlation method will be described in detail. Furthermore, different realizations will be shown, i.e. a mobile system for the measurement of large objects and an endoscopic like system for CAD/CAM in dental industry.

  6. Automated Signature Creator for a Signature Based Intrusion Detection System with Network Attack Detection Capabilities (Pancakes

    Directory of Open Access Journals (Sweden)

    Frances Bernadette C. De Ocampo

    2015-05-01

    Full Text Available Signature-based Intrusion Detection System (IDS helps in maintaining the integrity of data in a network controlled environment. Unfortunately, this type of IDS depends on predetermined intrusion patterns that are manually created. If the signature database of the Signature-based IDS is not updated, network attacks just pass through this type of IDS without being noticed. To avoid this, an Anomaly-based IDS is used in order to countercheck if a network traffic that is not detected by Signature-based IDS is a true malicious traffic or not. In doing so, the Anomaly-based IDS might come up with several numbers of logs containing numerous network attacks which could possibly be a false positive. This is the reason why the Anomaly-based IDS is not perfect, it would readily alarm the system that a network traffic is an attack just because it is not on its baseline. In order to resolve the problem between these two IDSs, the goal is to correlate data between the logs of the Anomaly-based IDS and the packet that has been captured in order to determine if a network traffic is really malicious or not. With the supervision of a security expert, the malicious network traffic would be verified as malicious. Using machine learning, the researchers can identify which algorithm is better than the other algorithms in classifying if a certain network traffic is really malicious. Upon doing so, the creation of signatures would follow by basing the automated creation of signatures from the detected malicious traffic.

  7. Partially-Correlated χ2 Targets Detection Analysis of GTM-Adaptive Processor in the Presence of Outliers

    OpenAIRE

    Mohamed B. El Mashade

    2014-01-01

    This paper addresses the problem of detecting the partially-correlated χ2 fluctuating targets with two and four degrees of freedom. It presents the performance analysis, in its exact form, of GTM-CFAR processor when the operating environment is contaminated with extraneous targets and the radar receiver post-detection integrates M pulses of exponentially correlated targets. Mathematical formulas for the detection and false alarm probabilities are derived, in the absence as well as in the pres...

  8. Plagiarism Detection Using Graph-Based Representation

    CERN Document Server

    Osman, Ahmed Hamza; Binwahlan, Mohammed Salem

    2010-01-01

    Plagiarism of material from the Internet is a widespread and growing problem. Several methods used to detect the plagiarism and similarity between the source document and suspected documents such as fingerprint based on character or n-gram. In this paper, we discussed a new method to detect the plagiarism based on graph representation; however, Preprocessing for each document is required such as breaking down the document into its constituent sentences. Segmentation of each sentence into separated terms and stop word removal. We build the graph by grouping each sentence terms in one node, the resulted nodes are connected to each other based on order of sentence within the document, all nodes in graph are also connected to top level node "Topic Signature". Topic signature node is formed by extracting the concepts of each sentence terms and grouping them in such node. The main advantage of the proposed method is the topic signature which is main entry for the graph is used as quick guide to the relevant nodes. ...

  9. Dramatyping: a generic algorithm for detecting reasonable temporal correlations between drug administration and lab value alterations.

    Science.gov (United States)

    Newe, Axel

    2016-01-01

    According to the World Health Organization, one of the criteria for the standardized assessment of case causality in adverse drug reactions is the temporal relationship between the intake of a drug and the occurrence of a reaction or a laboratory test abnormality. This article presents and describes an algorithm for the detection of a reasonable temporal correlation between the administration of a drug and the alteration of a laboratory value course. The algorithm is designed to process normalized lab values and is therefore universally applicable. It has a sensitivity of 0.932 for the detection of lab value courses that show changes in temporal correlation with the administration of a drug and it has a specificity of 0.967 for the detection of lab value courses that show no changes. Therefore, the algorithm is appropriate to screen the data of electronic health records and to support human experts in revealing adverse drug reactions. A reference implementation in Python programming language is available.

  10. Dramatyping: a generic algorithm for detecting reasonable temporal correlations between drug administration and lab value alterations

    Directory of Open Access Journals (Sweden)

    Axel Newe

    2016-03-01

    Full Text Available According to the World Health Organization, one of the criteria for the standardized assessment of case causality in adverse drug reactions is the temporal relationship between the intake of a drug and the occurrence of a reaction or a laboratory test abnormality. This article presents and describes an algorithm for the detection of a reasonable temporal correlation between the administration of a drug and the alteration of a laboratory value course. The algorithm is designed to process normalized lab values and is therefore universally applicable. It has a sensitivity of 0.932 for the detection of lab value courses that show changes in temporal correlation with the administration of a drug and it has a specificity of 0.967 for the detection of lab value courses that show no changes. Therefore, the algorithm is appropriate to screen the data of electronic health records and to support human experts in revealing adverse drug reactions. A reference implementation in Python programming language is available.

  11. SVM multiuser detection based on heuristic kernel

    Institute of Scientific and Technical Information of China (English)

    Yang Tao; Hu Bo

    2007-01-01

    A support vector machine (SVM) based multiuser detection (MUD) scheme in code-division multiple-access (CDMA) system is proposed. In this scheme, the equivalent support vector (SV) is obtained through a kernel sparsity approximation algorithm, which avoids the conventional costly quadratic programming (QP) procedure in SVM. Besides, the coefficient of the SV is attained through the solution to a generalized eigenproblem. Simulation results show that the proposed scheme has almost the same bit error rate (BER) as the standard SVM and is better than minimum mean square error (MMSE) scheme. Meanwhile, it has a low computation complexity.

  12. IMU Fault Detection Based on 2-CUSUM

    Directory of Open Access Journals (Sweden)

    Élcio Jeronimo de Oliveira

    2012-01-01

    IMU strapdown platforms using fiber optic gyros (FOG or micro electro mechanical systems (MEMSs. A way to solve this problem makes use of sensor redundancy and parity vector (PV analysis. However, the actual sensor outputs can include some anomalies, as impulsive noise which can be associated with the sensors itself or data acquisition process, committing the elementary threshold criteria as commonly used. Therefore, to overcome this problem, in this work, it is proposed an algorithm based on median filter (MF for prefiltering and chi-square cumulative sum (2-CUSUM only for fault detection (FD applied to an IMU composed by four FOGs.

  13. Global contrast based salient region detection

    KAUST Repository

    Cheng, Ming-Ming

    2011-08-25

    Reliable estimation of visual saliency allows appropriate processing of images without prior knowledge of their contents, and thus remains an important step in many computer vision tasks including image segmentation, object recognition, and adaptive compression. We propose a regional contrast based saliency extraction algorithm, which simultaneously evaluates global contrast differences and spatial coherence. The proposed algorithm is simple, efficient, and yields full resolution saliency maps. Our algorithm consistently outperformed existing saliency detection methods, yielding higher precision and better recall rates, when evaluated using one of the largest publicly available data sets. We also demonstrate how the extracted saliency map can be used to create high quality segmentation masks for subsequent image processing.

  14. Mobile Recommendation Based on Link Community Detection

    Directory of Open Access Journals (Sweden)

    Kun Deng

    2014-01-01

    Full Text Available Since traditional mobile recommendation systems have difficulty in acquiring complete and accurate user information in mobile networks, the accuracy of recommendation is not high. In order to solve this problem, this paper proposes a novel mobile recommendation algorithm based on link community detection (MRLD. MRLD executes link label diffusion algorithm and maximal extended modularity (EQ of greedy search to obtain the link community structure, and overlapping nodes belonging analysis (ONBA is adopted to adjust the overlapping nodes in order to get the more accurate community structure. MRLD is tested on both synthetic and real-world networks, and the experimental results show that our approach is valid and feasible.

  15. Neutron Detection Using Gadolinium-Based Diodes

    Science.gov (United States)

    2011-03-01

    U Uranium UNL The University of Nebraska, Lincoln XRD X-Ray Diffraction 1 NEUTRON DETECTION USING GADOLINIUM-BASED DIODES I...detector volume of approximately 3.46x10-6 cm3. 6 4 2 0 2 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Applied BiasV De ple tio nW idt hm  Si SiC 22...Layer deposition on the SiC substrate was confirmed by x-ray diffraction ( XRD ), however, no ellipsometry or other characterization measurements were

  16. Matrix-based concordance correlation coefficient for repeated measures.

    Science.gov (United States)

    Hiriote, Sasiprapa; Chinchilli, Vernon M

    2011-09-01

    In many clinical studies, Lin's concordance correlation coefficient (CCC) is a common tool to assess the agreement of a continuous response measured by two raters or methods. However, the need for measures of agreement may arise for more complex situations, such as when the responses are measured on more than one occasion by each rater or method. In this work, we propose a new CCC in the presence of repeated measurements, called the matrix-based concordance correlation coefficient (MCCC) based on a matrix norm that possesses the properties needed to characterize the level of agreement between two p× 1 vectors of random variables. It can be shown that the MCCC reduces to Lin's CCC when p= 1. For inference, we propose an estimator for the MCCC based on U-statistics. Furthermore, we derive the asymptotic distribution of the estimator of the MCCC, which is proven to be normal. The simulation studies confirm that overall in terms of accuracy, precision, and coverage probability, the estimator of the MCCC works very well in general cases especially when n is greater than 40. Finally, we use real data from an Asthma Clinical Research Network (ACRN) study and the Penn State Young Women's Health Study for demonstration.

  17. DNA & Protein detection based on microbead agglutination

    KAUST Repository

    Kodzius, Rimantas

    2012-06-06

    We report a simple and rapid room temperature assay for point-of-care (POC) testing that is based on specific agglutination. Agglutination tests are based on aggregation of microparticles in the presence of a specific analyte thus enabling the macroscopic observation. Agglutination-based tests are most often used to explore the antibody-antigen reactions. Agglutination has been used for mode protein assays using a biotin/streptavidin two-component system, as well as a hybridization based two-component assay; however, as our work shows, two-component systems are prone to self-termination of the linking analyte and thus have a lower sensitivity. Three component systems have also been used with DNA hybridization, as in our work; however, their assay requires 48 hours for incubation, while our assay is performed in 5 minutes making it a real candidate for POC testing. We demonstrate three assays: a two-component biotin/streptavidin assay, a three-component hybridization assay using single stranded DNA (ssDNA) molecules and a stepped three-component hybridization assay. The comparison of these three assays shows our simple stepped three-component agglutination assay to be rapid at room temperature and more sensitive than the two-component version by an order of magnitude. An agglutination assay was also performed in a PDMS microfluidic chip where agglutinated beads were trapped by filter columns for easy observation. We developed a rapid (5 minute) room temperature assay, which is based on microbead agglutination. Our three-component assay solves the linker self-termination issue allowing an order of magnitude increase in sensitivity over two–component assays. Our stepped version of the three-component assay solves the issue with probe site saturation thus enabling a wider range of detection. Detection of the agglutinated beads with the naked eye by trapping in microfluidic channels has been shown.

  18. Point pattern match-based change detection in a constellation of previously detected objects

    Science.gov (United States)

    Paglieroni, David W.

    2016-06-07

    A method and system is provided that applies attribute- and topology-based change detection to objects that were detected on previous scans of a medium. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, detection strength, size, elongation, orientation, etc. The locations define a three-dimensional network topology forming a constellation of previously detected objects. The change detection system stores attributes of the previously detected objects in a constellation database. The change detection system detects changes by comparing the attributes and topological consistency of newly detected objects encountered during a new scan of the medium to previously detected objects in the constellation database. The change detection system may receive the attributes of the newly detected objects as the objects are detected by an object detection system in real time.

  19. Overlapping Community Detection based on Network Decomposition

    Science.gov (United States)

    Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin

    2016-04-01

    Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms.

  20. Waveguide-Based Biosensors for Pathogen Detection

    Directory of Open Access Journals (Sweden)

    Nile Hartman

    2009-07-01

    Full Text Available Optical phenomena such as fluorescence, phosphorescence, polarization, interference and non-linearity have been extensively used for biosensing applications. Optical waveguides (both planar and fiber-optic are comprised of a material with high permittivity/high refractive index surrounded on all sides by materials with lower refractive indices, such as a substrate and the media to be sensed. This arrangement allows coupled light to propagate through the high refractive index waveguide by total internal reflection and generates an electromagnetic wave—the evanescent field—whose amplitude decreases exponentially as the distance from the surface increases. Excitation of fluorophores within the evanescent wave allows for sensitive detection while minimizing background fluorescence from complex, “dirty” biological samples. In this review, we will describe the basic principles, advantages and disadvantages of planar optical waveguide-based biodetection technologies. This discussion will include already commercialized technologies (e.g., Corning’s EPIC® Ô, SRU Biosystems’ BIND™, Zeptosense®, etc. and new technologies that are under research and development. We will also review differing assay approaches for the detection of various biomolecules, as well as the thin-film coatings that are often required for waveguide functionalization and effective detection. Finally, we will discuss reverse-symmetry waveguides, resonant waveguide grating sensors and metal-clad leaky waveguides as alternative signal transducers in optical biosensing.

  1. Network Intrusion Detection based on GMKL Algorithm

    Directory of Open Access Journals (Sweden)

    Li Yuxiang

    2013-06-01

    Full Text Available According to the 31th statistical reports of China Internet network information center (CNNIC, by the end of December 2012, the number of Chinese netizens has reached 564 million, and the scale of mobile Internet users also reached 420 million. But when the network brings great convenience to people's life, it also brings huge threat in the life of people. So through collecting and analyzing the information in the computer system or network we can detect any possible behaviors that can damage the availability, integrity and confidentiality of the computer resource, and make timely treatment to these behaviors which have important research significance to improve the operation environment of network and network service. At present, the Neural Network, Support Vector machine (SVM and Hidden Markov Model, Fuzzy inference and Genetic Algorithms are introduced into the research of network intrusion detection, trying to build a healthy and secure network operation environment. But most of these algorithms are based on the total sample and it also hypothesizes that the number of the sample is infinity. But in the field of network intrusion the collected data often cannot meet the above requirements. It often shows high latitudes, variability and small sample characteristics. For these data using traditional machine learning methods are hard to get ideal results. In view of this, this paper proposed a Generalized Multi-Kernel Learning method to applied to network intrusion detection. The Generalized Multi-Kernel Learning method can be well applied to large scale sample data, dimension complex, containing a large number of heterogeneous information and so on. The experimental results show that applying GMKL to network attack detection has high classification precision and low abnormal practical precision.

  2. Traffic Sign Recognition System based on Cambridge Correlator Image Comparator

    OpenAIRE

    J. Turan; L. Ovsenik; T. Harasthy

    2012-01-01

    Paper presents basic information about application of Optical Correlator (OC), specifically Cambridge Correlator, in system to recognize of traffic sign. Traffic Sign Recognition System consists of three main blocks, Preprocessing, Optical Correlator and Traffic Sign Identification. The Region of Interest (ROI) is defined and chosen in preprocessing block and then goes to Optical Correlator, where is compared with database of Traffic Sign. Output of Optical Correlation is correlation plane, w...

  3. A Correlation-Based Joint CFAR Detector Using Adaptively-Truncated Statistics in SAR Imagery.

    Science.gov (United States)

    Ai, Jiaqiu; Yang, Xuezhi; Zhou, Fang; Dong, Zhangyu; Jia, Lu; Yan, He

    2017-03-27

    Traditional constant false alarm rate (CFAR) detectors only use the contrast information between ship targets and clutter, and they suffer probability of detection (PD) degradation in multiple target situations. This paper proposes a correlation-based joint CFAR detector using adaptively-truncated statistics (hereafter called TS-2DLNCFAR) in SAR images. The proposed joint CFAR detector exploits the gray intensity correlation characteristics by building a two-dimensional (2D) joint log-normal model as the joint distribution (JPDF) of the clutter, so joint CFAR detection is realized. Inspired by the CFAR detection methodology, we design an adaptive threshold-based clutter truncation method to eliminate the high-intensity outliers, such as interfering ship targets, side-lobes, and ghosts in the background window, whereas the real clutter samples are preserved to the largest degree. A 2D joint log-normal model is accurately built using the adaptively-truncated clutter through simple parameter estimation, so the joint CFAR detection performance is greatly improved. Compared with traditional CFAR detectors, the proposed TS-2DLNCFAR detector achieves a high PD and a low false alarm rate (FAR) in multiple target situations. The superiority of the proposed TS-2DLNCFAR detector is validated on the multi-look Envisat-ASAR and TerraSAR-X data.

  4. Attribute and topology based change detection in a constellation of previously detected objects

    Energy Technology Data Exchange (ETDEWEB)

    Paglieroni, David W.; Beer, Reginald N.

    2016-01-19

    A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.

  5. Detection of Target ssDNA Using a Microfabricated Hall Magnetometer with Correlated Optical Readout

    Directory of Open Access Journals (Sweden)

    Steven M. Hira

    2012-01-01

    Full Text Available Sensing biological agents at the genomic level, while enhancing the response time for biodetection over commonly used, optics-based techniques such as nucleic acid microarrays or enzyme-linked immunosorbent assays (ELISAs, is an important criterion for new biosensors. Here, we describe the successful detection of a 35-base, single-strand nucleic acid target by Hall-based magnetic transduction as a mimic for pathogenic DNA target detection. The detection platform has low background, large signal amplification following target binding and can discriminate a single, 350 nm superparamagnetic bead labeled with DNA. Detection of the target sequence was demonstrated at 364 pM (<2 target DNA strands per bead target DNA in the presence of 36 μM nontarget (noncomplementary DNA (<10 ppm target DNA using optical microscopy detection on a GaAs Hall mimic. The use of Hall magnetometers as magnetic transduction biosensors holds promise for multiplexing applications that can greatly improve point-of-care (POC diagnostics and subsequent medical care.

  6. Texture orientation-based algorithm for detecting infrared maritime targets.

    Science.gov (United States)

    Wang, Bin; Dong, Lili; Zhao, Ming; Wu, Houde; Xu, Wenhai

    2015-05-20

    Infrared maritime target detection is a key technology for maritime target searching systems. However, in infrared maritime images (IMIs) taken under complicated sea conditions, background clutters, such as ocean waves, clouds or sea fog, usually have high intensity that can easily overwhelm the brightness of real targets, which is difficult for traditional target detection algorithms to deal with. To mitigate this problem, this paper proposes a novel target detection algorithm based on texture orientation. This algorithm first extracts suspected targets by analyzing the intersubband correlation between horizontal and vertical wavelet subbands of the original IMI on the first scale. Then the self-adaptive wavelet threshold denoising and local singularity analysis of the original IMI is combined to remove false alarms further. Experiments show that compared with traditional algorithms, this algorithm can suppress background clutter much better and realize better single-frame detection for infrared maritime targets. Besides, in order to guarantee accurate target extraction further, the pipeline-filtering algorithm is adopted to eliminate residual false alarms. The high practical value and applicability of this proposed strategy is backed strongly by experimental data acquired under different environmental conditions.

  7. Expectation-based and data-based illusory correlation : The effects of confirming versus disconfirming evidence

    NARCIS (Netherlands)

    Berndsen, M; VanderPligt, J; Spears, R

    1996-01-01

    The present study (n = 154) examines the effects of expectations and stimulus information on the perception of illusory correlation. There have been few studies attempting to integrate expectation-based and data- (distinctiveness-) based processes. These studies suggest that data-based illusory corr

  8. Methods of estrus detection and correlates of the reproductive cycle in the sun bear (Helarctos malayanus).

    Science.gov (United States)

    Frederick, Cheryl; Kyes, Randall; Hunt, Kathleen; Collins, Darin; Durrant, Barbara; Wasser, Samuel K

    2010-10-15

    The objective was to explore multiple methods for detecting and characterizing the reproductive cycle of the sun bear (Helarctos malayanus). Thirteen H. m. euryspilus females, loaned from the Malaysian government to US zoos, were used. Fecal metabolite concentrations of estrogen and progesterone were compared to vaginal cytology, changes in genital appearance, and behavior (videotapes and zookeeper observations). Cytology and video behavior were characterized during five hormonally defined states: high, low, and baseline progesterone, estrus, and high estrogen. Among states, there were significant differences in cytology and behavior. Sexual, affiliative, and stereotypic behaviors were highest during estrus, whereas affiliative and social behaviors were lowest during high progesterone. In this captive breeding population, 30.8% of females cycled two or three times a year, 30.8% cycled once a year, and 38.5% did not cycle during this study. Inter-estrus intervals were (mean ± SEM) 115.7 ± 6.3 d (range, 101-131). Spearman rank correlations were significant between both ordinal sexual and affiliative behaviors and vulva swelling and color. Sexual behavior was significantly positively correlated with superficial and keratinized cells, but negatively correlated with parabasal and basophilic cells in cycling females (opposite pattern for appetitive behavior). In conclusion, data for cytology, vulva changes and behavior were consistent with, and complementary to, hormonal data; collectively, they delineated estrus and identified specific reproductive types.

  9. Detection of spatial correlations of fundamental plane residuals, and cosmological implications

    CERN Document Server

    Joachimi, Benjamin; Mandelbaum, Rachel

    2015-01-01

    The fundamental plane (FP) is a widely used tool to investigate the properties of early-type galaxies, and the tight relation between its parameters has spawned several cosmological applications, including its use as a distance indicator for peculiar velocity surveys and as a means to suppress intrinsic noise in cosmic size magnification measurements. Systematic trends with the large-scale structure across the FP could cause serious biases for these cosmological probes, but may also yield new insights into the early-type population. Here we report the first detection of spatial correlations among offsets in galaxy size from an FP that explicitly accounts for redshift trends, using a sample of about $95,000$ elliptical galaxies from the Sloan Digital Sky Survey. We show that these offsets correlate with the density field out to at least $10h^{-1}$Mpc at $4\\sigma$ significance in a way that cannot be explained by systematic errors in galaxy size estimates. We propose a physical explanation for the correlations ...

  10. Reionization on Large Scales II: Detecting Patchy Reionization through Cross Correlation of the Cosmic Microwave Background

    CERN Document Server

    Natarajan, Aravind; Trac, Hy; Pen, Ue Li; Loeb, Abraham

    2012-01-01

    We investigate the effect of patchy reionization on the cosmic microwave background temperature. An anisotropic optical depth tau (theta) alters the TT power spectrum on small scales l > 2000. We make use of the correlation between the matter density and the reionization redshift fields to construct full sky maps of tau(theta). Patchy reionization transfers CMB power from large scales to small scales, resulting in a non-zero cross correlation between large and small angular scales. We show that the patchy tau correlator is sensitive to small root mean square values tau_rms ~ 0.003 seen in our maps. We include other secondary anisotropies such as CMB lensing, kinetic and thermal Sunyaev-Zel'dovich terms, as well as the infrared and point source background, and show that patchy reionization may be detected in the low frequency channels ~ 90 GHz, particularly for extended reionization histories. If frequency dependent secondaries can be minimized by a multi-frequency analysis, we show that even small degrees of ...

  11. Long-range vibration sensor based on correlation analysis of optical frequency-domain reflectometry signals.

    Science.gov (United States)

    Ding, Zhenyang; Yao, X Steve; Liu, Tiegen; Du, Yang; Liu, Kun; Han, Qun; Meng, Zhuo; Chen, Hongxin

    2012-12-17

    We present a novel method to achieve a space-resolved long- range vibration detection system based on the correlation analysis of the optical frequency-domain reflectometry (OFDR) signals. By performing two separate measurements of the vibrated and non-vibrated states on a test fiber, the vibration frequency and position of a vibration event can be obtained by analyzing the cross-correlation between beat signals of the vibrated and non-vibrated states in a spatial domain, where the beat signals are generated from interferences between local Rayleigh backscattering signals of the test fiber and local light oscillator. Using the proposed technique, we constructed a standard single-mode fiber based vibration sensor that can have a dynamic range of 12 km and a measurable vibration frequency up to 2 kHz with a spatial resolution of 5 m. Moreover, preliminarily investigation results of two vibration events located at different positions along the test fiber are also reported.

  12. Edge detection based on directional space

    Institute of Scientific and Technical Information of China (English)

    YUAN Wei-qi; LI De-sheng

    2006-01-01

    A new method for edge detection based on directional space is proposed.The principle is that:firstly,the directional differential space is set up in which the ridge edge pixels and valley edge pixels are abstracted with the help of the method of logical judgments along the direction of differential function,forming a directional roof edge map;secondly,step edge pixels are abstracted between the neighboring directional ridge edge and directional valley edge along the direction of differential function;finally,the ridge edge map,valley edge map and step edge map gained along different directions are combined into corresponding ridge edge map,valley edge map and step edge map.This method is different from classical algorithms in which the gray differential values of the mutual vertical direction are combined into one gradient value.The experiment of edge detection is made for the images of nature scenery,human body and accumulative raw material,whose result is compared with the one of classical algorithms and showing the robustness of the proposed method.

  13. Detection of gravitational waves in Michelson interferometer by the use of second order correlation functions

    CERN Document Server

    Ben-Aryeh, Y

    2006-01-01

    The possibility of measuring the second order correlation function of the gravitational waves detectors' currents or photonumbers, and the observation of the gravitational signals by using a spectrum analyzer is discussed. The method is based on complicated data processing and is expected to be efficient for coherent periodic gravitational waves. It is suggested as an alternative method to the conventional one which is used now in the gravitational waves observatories.

  14. Detecting Soft Errors in Stencil based Computations

    Energy Technology Data Exchange (ETDEWEB)

    Sharma, V. [Univ. of Utah, Salt Lake City, UT (United States); Gopalkrishnan, G. [Univ. of Utah, Salt Lake City, UT (United States); Bronevetsky, G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-05-06

    Given the growing emphasis on system resilience, it is important to develop software-level error detectors that help trap hardware-level faults with reasonable accuracy while minimizing false alarms as well as the performance overhead introduced. We present a technique that approaches this idea by taking stencil computations as our target, and synthesizing detectors based on machine learning. In particular, we employ linear regression to generate computationally inexpensive models which form the basis for error detection. Our technique has been incorporated into a new open-source library called SORREL. In addition to reporting encouraging experimental results, we demonstrate techniques that help reduce the size of training data. We also discuss the efficacy of various detectors synthesized, as well as our future plans.

  15. Comic image understanding based on polygon detection

    Science.gov (United States)

    Li, Luyuan; Wang, Yongtao; Tang, Zhi; Liu, Dong

    2013-01-01

    Comic image understanding aims to automatically decompose scanned comic page images into storyboards and then identify the reading order of them, which is the key technique to produce digital comic documents that are suitable for reading on mobile devices. In this paper, we propose a novel comic image understanding method based on polygon detection. First, we segment a comic page images into storyboards by finding the polygonal enclosing box of each storyboard. Then, each storyboard can be represented by a polygon, and the reading order of them is determined by analyzing the relative geometric relationship between each pair of polygons. The proposed method is tested on 2000 comic images from ten printed comic series, and the experimental results demonstrate that it works well on different types of comic images.

  16. Error detection based on MB types

    Institute of Scientific and Technical Information of China (English)

    FANG Yong; JEONG JeChang; WU ChengKe

    2008-01-01

    This paper proposes a method of error detection based on macroblock (MB) types for video transmission. For decoded inter MBs, the absolute values of received residues are accumulated. At the same time, the intra textural complexity of the current MB is estimated by that of the motion compensated reference block. We compare the inter residue with the intra textural complexity. If the inter residue is larger than the intra textural complexity by a predefined threshold, the MB is con-sidered to be erroneous and errors are concealed. For decoded intra MBs, the connective smoothness of the current MB with neighboring MBs is tested to find erroneous MBs. Simulation results show that the new method can remove those seriously-corrupted MBs efficiently. Combined with error concealment, the new method improves the recovered quality at the decoder by about 0.5-1 dB.

  17. Aptamer Based Microsphere Biosensor for Thrombin Detection

    Directory of Open Access Journals (Sweden)

    Xudong Fan

    2006-08-01

    Full Text Available We have developed an optical microsphere resonator biosensor using aptamer asreceptor for the measurement of the important biomolecule thrombin. The sphere surface ismodified with anti-thrombin aptamer, which has excellent binding affinity and selectivityfor thrombin. Binding of the thrombin at the sphere surface is monitored by the spectralposition of the microsphere’s whispering gallery mode resonances. A detection limit on theorder of 1 NIH Unit/mL is demonstrated. Control experiments with non-aptameroligonucleotide and BSA are also carried out to confirm the specific binding betweenaptamer and thrombin. We expect that this demonstration will lead to the development ofhighly sensitive biomarker sensors based on aptamer with lower cost and higher throughputthan current technology.

  18. Parametric Roll Resonance Detection using Phase Correlation and Log-likelihood Testing Techniques

    DEFF Research Database (Denmark)

    Galeazzi, Roberto; Blanke, Mogens; Poulsen, Niels Kjølstad

    2009-01-01

    Real-time detection of parametric roll is still an open issue that is gathering an increasing attention. A first generation warning systems, based on guidelines and polar diagrams, showed their potential to face issues like long-term prediction and risk assessment. This paper presents a second...... generation warning system the purpose of which is to provide the master with an onboard system able to trigger an alarm when parametric roll is likely to happen within the immediate future. A detection scheme is introduced, which is able to issue a warning within five roll periods after a resonant motion...

  19. The use of waveform cross correlation at a three-component seismic array for detection, location, and magnitude estimation

    Science.gov (United States)

    Kitov, Ivan; Sanina, Irina

    2016-04-01

    Using the waveform cross-correlation technique, we have re-estimated relative locations and magnitudes of 200 events detected by an array consisting of seven 3-C sensors. All these events were quarry blasts conducted at several local/regional mines, which were detected and identified in the course of regional seismotectonic monitoring. From all detected signals we selected those having the highest quality and created a set of three-component templates for further cross correlation study. By changing the length of correlation window and the frequency band of the templates we selected optimal parameters for robust estimates of cross correlation coefficients and relative amplitudes/magnitudes of all signals. The relative locations and magnitude estimates obtained by cross correlation are compared to those in the catalog created in standard interactive analysis.

  20. Detection of EMI4-ALK fusion gene in non-small cell lung cancer and its clinicopathologic correlation

    Institute of Scientific and Technical Information of China (English)

    钟山

    2013-01-01

    Objective To investigate the frequency of EML4-ALK fusion gene in non small-cell lung cancer NSCLC patients,and its correlation with clinicopathologic features.Methods Real-time PCR was used to detect

  1. Use of MR arthrography in detecting tears of the ligamentum teres with arthroscopic correlation

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Connie Y.; Gill, Corey M.; Huang, Ambrose J.; Simeone, Frank J.; Torriani, Martin; Bredella, Miriam A. [Massachusetts General Hospital, Division of Musculoskeletal Imaging and Intervention, Department of Radiology, Boston, MA (United States); McCarthy, Joseph C. [Massachusetts General Hospital, Department of Orthopedics, Boston, MA (United States)

    2014-12-20

    To demonstrate the normal appearance of the ligamentum teres on MR arthrography (MRA) and evaluate the accuracy of MRA in detecting ligamentum teres tears with arthroscopic correlation. Institutional Review Board approval was obtained with a waiver for informed consent because of the retrospective study design. A total of 165 cases in 159 patients (111 females, 48 males; mean age 41 ± 12 years) who underwent both MRA and hip arthroscopy were evaluated for appearance of the ligamentum teres, including the size, number of bundles, and ligamentum teres tears. Marrow edema of the fovea capitis adjacent to the ligamentum teres insertion and the presence of hip plicae were also recorded. The mean thickness and length of the ligamentum teres were 3.5 ± 1.5 mm and 25.2 ± 3.8 mm, respectively. Sensitivity, specificity, positive and negative predictive value, and accuracy of MRA for the detection of ligamentum teres tears were 78, 97, 74, 97, and 95 %, respectively. MRA is an accurate method to evaluate the normal morphology and to detect tears of the ligamentum teres. (orig.)

  2. Spanning Trees and bootstrap reliability estimation in correlation based networks

    CERN Document Server

    Tumminello, M; Lillo, F; Micciché, S; Mantegna, R N

    2006-01-01

    We introduce a new technique to associate a spanning tree to the average linkage cluster analysis. We term this tree as the Average Linkage Minimum Spanning Tree. We also introduce a technique to associate a value of reliability to links of correlation based graphs by using bootstrap replicas of data. Both techniques are applied to the portfolio of the 300 most capitalized stocks traded at New York Stock Exchange during the time period 2001-2003. We show that the Average Linkage Minimum Spanning Tree recognizes economic sectors and sub-sectors as communities in the network slightly better than the Minimum Spanning Tree does. We also show that the average reliability of links in the Minimum Spanning Tree is slightly greater than the average reliability of links in the Average Linkage Minimum Spanning Tree.

  3. Windows Volatile Memory Forensics Based on Correlation Analysis

    Directory of Open Access Journals (Sweden)

    Xiaolu Zhang

    2014-03-01

    Full Text Available In this paper, we present an integrated memory forensic solution for multiple Windows memory images. By calculation, the method can find out the correlation degree among the processes of volatile memory images and the hidden clues behind the events of computers, which is usually difficult to be obtained and easily ignored by analyzing one single memory image and forensic investigators. In order to test the validity, we performed an experiment based on two hosts' memory image which contains criminal incidents. According to the experimental result, we find that the event chains reconstructed by our method are similar to the actual actions in the criminal scene. Investigators can review the digital crime scenario which is contained in the data set by analyzing the experimental results. This paper is aimed at finding the valid actions with illegal attempt and making the memory analysis not to be utterly dependent on the operating system and relevant experts.

  4. Traffic Prediction Based on Correlation of Road Sections

    Directory of Open Access Journals (Sweden)

    Xiaodan Huang

    2013-10-01

    Full Text Available Road section data packet is very necessary for the estimation and prediction in short-time traffic condition. However, previous researches on this problem are lack of quantitative analysis. A section correlation analyzing method with traffic flow microwave data is proposed for this problem. It is based on the metric multidimensional scaling theory. With a dissimilarity matrix, scalar product matrix can be calculated. Subsequently, a reconstructing matrix of section traffic flow could be got with principal components factor analysis, which could display section groups in low dimension. It is verified that the new method is reliable and effective. After that, Auto Regressive Moving Average (A RMA model is used for forecasting traffic flow and lane occupancy. Finally, a simulated example has shown that the technique is effective and exact. The theoretical analysis indicates that the forecasting model and algorithms have a broad prospect for practical application.  

  5. Preserving Differential Privacy in Degree-Correlation based Graph Generation.

    Science.gov (United States)

    Wang, Yue; Wu, Xintao

    2013-08-01

    Enabling accurate analysis of social network data while preserving differential privacy has been challenging since graph features such as cluster coefficient often have high sensitivity, which is different from traditional aggregate functions (e.g., count and sum) on tabular data. In this paper, we study the problem of enforcing edge differential privacy in graph generation. The idea is to enforce differential privacy on graph model parameters learned from the original network and then generate the graphs for releasing using the graph model with the private parameters. In particular, we develop a differential privacy preserving graph generator based on the dK-graph generation model. We first derive from the original graph various parameters (i.e., degree correlations) used in the dK-graph model, then enforce edge differential privacy on the learned parameters, and finally use the dK-graph model with the perturbed parameters to generate graphs. For the 2K-graph model, we enforce the edge differential privacy by calibrating noise based on the smooth sensitivity, rather than the global sensitivity. By doing this, we achieve the strict differential privacy guarantee with smaller magnitude noise. We conduct experiments on four real networks and compare the performance of our private dK-graph models with the stochastic Kronecker graph generation model in terms of utility and privacy tradeoff. Empirical evaluations show the developed private dK-graph generation models significantly outperform the approach based on the stochastic Kronecker generation model.

  6. Combining Correlation-Based and Reward-Based Learning in Neural Control for Policy Improvement

    DEFF Research Database (Denmark)

    Manoonpong, Poramate; Kolodziejski, Christoph; Wörgötter, Florentin;

    2013-01-01

    Classical conditioning (conventionally modeled as correlation-based learning) and operant conditioning (conventionally modeled as reinforcement learning or reward-based learning) have been found in biological systems. Evidence shows that these two mechanisms strongly involve learning about...... associations. Based on these biological findings, we propose a new learning model to achieve successful control policies for artificial systems. This model combines correlation-based learning using input correlation learning (ICO learning) and reward-based learning using continuous actor–critic reinforcement...... learning (RL), thereby working as a dual learner system. The model performance is evaluated by simulations of a cart-pole system as a dynamic motion control problem and a mobile robot system as a goal-directed behavior control problem. Results show that the model can strongly improve pole balancing control...

  7. Dynamically reconfigurable multiple beam illumination based on optical correlation

    DEFF Research Database (Denmark)

    Glückstad, Jesper; Palima, Darwin; Dam, Jeppe Seidelin

    2009-01-01

    We adapt concepts from optical correlation and optical pattern recognition to propose a method for generating reconfigurable multiple spots with high efficiency. The generated spots correspond to the correlation spikes in optical pattern recognition. In pattern recognition, optimizing the correla...

  8. Miniaturized Gas Correlation Radiometer for the Detection of Trace Gases in the Martian Atmosphere

    Science.gov (United States)

    Melroy, H.; Wilson, E. L.; Georgieva, E.

    2012-12-01

    We present a miniaturized and simplified version of a gas correlation radiometer (GCR) capable of simultaneously mapping multiple trace gases and identifying active regions on the Mars surface. Gas correlation radiometry (GCR) has been shown to be a sensitive and versatile method for detecting trace gases in Earth's atmosphere. Reduction of the size and mass of the GCR was achieved by implementing compact, light-weight 1 mm inner diameter hollow-core optical fibers (hollow waveguides) as the gas correlation cells. In a comparison with an Earth orbiting CO2 GCR instrument, exchanging the 10 m multipass cells with hollow waveguide gas correlation cells of equivalent pathlength reduces the mass from ~150 kg to ~0.5 kg, and reduces the volume from 1.9 m x 1.3 m x 0.86 m to a small bundle of fiber coils approximately 1 meter in diameter by 0.05 m in height (mass and volume reductions of >99%). A unique feature of this instrument is its stackable module design, with a single module for each trace gas. Each of the modules is self-contained, and fundamentally identical; differing by the bandpass filter wavelength range and gas mixtures inside the hollow-waveguide absorption cells. The current configuration contains four stacked modules for simultaneous measurements of methane (CH4), formaldehyde (H2CO), water vapor (H2O), and deuterated water vapor (HDO) but could easily be expanded to include measurements of additional species of interest including nitrous oxide (N2O), hydrogen sulfide (H2S), methanol (CH3OH), and sulfur dioxide (SO2), as well as carbon dioxide (CO2) for a simultaneous measure of mass balance. Preliminary results indicate that a 1 ppb detection limit is possible for both formaldehyde and methane with one second of averaging. Using non-optimized components, we have demonstrated an instrument sensitivity equivalent to ~30 ppb for formaldehyde, and ~500 ppb for methane. We expect custom bandpass filters and 6 m long waveguides to significantly improve these

  9. Miniaturized Gas Correlation Radiometer for the Detection of Trace Gases in the Martian Atmosphere

    Science.gov (United States)

    Melroy, Hilary R.; Wilson, Emily L.; Georgieva, Elena

    2012-01-01

    We present a miniaturized and simplified version of a gas correlation radiometer (GCR) capable of simultaneously mapping multiple trace gases and identifying active regions on the Mars surface. Gas correlation radiometry (GCR) has been shown to be a sensitive and versatile method for detecting trace gases in Earth's atmosphere. Reduction of the size and mass of the GCR was achieved by implementing compact, light-weight 1 mm inner diameter hollow-core optical fibers (hollow waveguides) as the gas correlation cells. In a comparison with an Earth orbiting CO2 GCR instrument, exchanging the 10 m multipass cells with hollow waveguide gas correlation cells of equivalent path length reduces the mass from approximately 150 kg to approximately 0.5 kg, and reduces the volume from 1.9 m x 1.3 m x 0.86 m to a small bundle of fiber coils approximately 1 meter in diameter by 0.05 m in height (mass and volume reductions of greater than 99%). A unique feature of this instrument is its stackable module design, with a single module for each trace gas. Each of the modules is self-contained, and fundamentally identical; differing by the bandpass filter wavelength range and gas mixtures inside the hollow-waveguide absorption cells. The current configuration contains four stacked modules for simultaneous measurements of methane (CH4), formaldehyde (H2CO), water vapor (H2O), and deuterated water vapor (HDO) but could easily be expanded to include measurements of additional species of interest including nitrous oxide (N2O), hydrogen sulfide (H2S), methanol (CH3OH), and sulfur dioxide (SO2), as well as carbon dioxide (CO2) for a simultaneous measure of mass balance. Preliminary results indicate that a 1 ppb detection limit is possible for both formaldehyde and methane with one second of averaging. Using non-optimized components, we have demonstrated an instrument sensitivity equivalent to approximately 30 ppb for formaldehyde, and approximately 500 ppb for methane. We expect custom

  10. Optical coherent detection Brillouin distributed optical fiber sensor based on orthogonal polarization diversity reception

    Institute of Scientific and Technical Information of China (English)

    Muping Song; Bin Zhao; Xianmin Zhang

    2005-01-01

    In Brillouin distributed optical fiber sensor, using optical coherent detection to detect Brillouin scattering optical signal is a good method, but there exists the polarization correlated detection problem. A novel detecting scheme is presented and demonstrated experimentally, which adopts orthogonal polarization diversity reception to resolve the polarization correlated detection problem. A laser is used as pump and reference light sources, a microwave electric-optical modulator (EOM) is adopted to produce frequency shift reference light, a polarization controller is used to control the polarization of the reference light which is changed into two orthogonal polarization for two adjacent acquisition periods. The Brillouin scattering light is coherently detected with the reference light, and the Brillouin scattering optical signal is taken out based on Brillouin frequency shift. After electronic processing, better Brillouin distributed sensing signal is obtained. A 25-km Brillouin distributed optical fiber sensor is achieved.

  11. Lesion area detection using source image correlation coefficient for CT perfusion imaging.

    Science.gov (United States)

    Fan Zhu; Rodriguez Gonzalez, David; Carpenter, Trevor; Atkinson, Malcolm; Wardlaw, Joanna

    2013-09-01

    Computer tomography (CT) perfusion imaging is widely used to calculate brain hemodynamic quantities such as cerebral blood flow, cerebral blood volume, and mean transit time that aid the diagnosis of acute stroke. Since perfusion source images contain more information than hemodynamic maps, good utilization of the source images can lead to better understanding than the hemodynamic maps alone. Correlation-coefficient tests are used in our approach to measure the similarity between healthy tissue time-concentration curves and unknown curves. This information is then used to differentiate penumbra and dead tissues from healthy tissues. The goal of the segmentation is to fully utilize information in the perfusion source images. Our method directly identifies suspected abnormal areas from perfusion source images and then delivers a suggested segmentation of healthy, penumbra, and dead tissue. This approach is designed to handle CT perfusion images, but it can also be used to detect lesion areas in magnetic resonance perfusion images.

  12. Automatic detection and classification of damage zone(s) for incorporating in digital image correlation technique

    Science.gov (United States)

    Bhattacharjee, Sudipta; Deb, Debasis

    2016-07-01

    Digital image correlation (DIC) is a technique developed for monitoring surface deformation/displacement of an object under loading conditions. This method is further refined to make it capable of handling discontinuities on the surface of the sample. A damage zone is referred to a surface area fractured and opened in due course of loading. In this study, an algorithm is presented to automatically detect multiple damage zones in deformed image. The algorithm identifies the pixels located inside these zones and eliminate them from FEM-DIC processes. The proposed algorithm is successfully implemented on several damaged samples to estimate displacement fields of an object under loading conditions. This study shows that displacement fields represent the damage conditions reasonably well as compared to regular FEM-DIC technique without considering the damage zones.

  13. Community detection in temporal multilayer networks, and its application to correlation networks

    CERN Document Server

    Bazzi, Marya; Williams, Stacy; McDonald, Mark; Fenn, Daniel J; Howison, Sam D

    2015-01-01

    Networks are a convenient way to represent complex systems of interacting entities. Many networks contain "communities" of nodes that are more densely connected to each other than to nodes in the rest of the network. In this paper, we investigate the detection of communities in temporal networks represented as multilayer networks. As a focal example, we study time-dependent financial-asset correlation networks. We first argue that the use of the "modularity" quality function---which is defined by comparing edge weights in an observed network to expected edge weights in a "null network"---is application-dependent. We differentiate between "null networks" and "null models" in our discussion of modularity maximization, and we highlight that the same null network can correspond to different null models. We then investigate a multilayer modularity-maximization problem to identify communities in temporal networks. Our multilayer analysis only depends on the form of the maximization problem and not on the specific q...

  14. High correlation of double Debye model parameters in skin cancer detection.

    Science.gov (United States)

    Truong, Bao C Q; Tuan, H D; Fitzgerald, Anthony J; Wallace, Vincent P; Nguyen, H T

    2014-01-01

    The double Debye model can be used to capture the dielectric response of human skin in terahertz regime due to high water content in the tissue. The increased water proportion is widely considered as a biomarker of carcinogenesis, which gives rise of using this model in skin cancer detection. Therefore, the goal of this paper is to provide a specific analysis of the double Debye parameters in terms of non-melanoma skin cancer classification. Pearson correlation is applied to investigate the sensitivity of these parameters and their combinations to the variation in tumor percentage of skin samples. The most sensitive parameters are then assessed by using the receiver operating characteristic (ROC) plot to confirm their potential of classifying tumor from normal skin. Our positive outcomes support further steps to clinical application of terahertz imaging in skin cancer delineation.

  15. Traffic Sign Recognition System based on Cambridge Correlator Image Comparator

    Directory of Open Access Journals (Sweden)

    J. Turan

    2012-06-01

    Full Text Available Paper presents basic information about application of Optical Correlator (OC, specifically Cambridge Correlator, in system to recognize of traffic sign. Traffic Sign Recognition System consists of three main blocks, Preprocessing, Optical Correlator and Traffic Sign Identification. The Region of Interest (ROI is defined and chosen in preprocessing block and then goes to Optical Correlator, where is compared with database of Traffic Sign. Output of Optical Correlation is correlation plane, which consist of highly localized intensities, know as correlation peaks. The intensity of spots provides a measure of similarity and position of spots, how images (traffic signs are relatively aligned in the input scene. Several experiments have been done with proposed system and results and conclusion are discussed.

  16. CFHTLenS and RCSLenS Cross-Correlation with Planck Lensing Detected in Fourier and Configuration Space

    CERN Document Server

    Harnois-Déraps, Joachim; Hojjati, Alireza; van Waerbeke, Ludovic; Asgari, Marika; Choi, Ami; Erben, Thomas; Heymans, Catherine; Hildebrandt, Hendrik; Kitching, Thomas D; Miller, Lance; Nakajima, Reiko; Viola, Massimo; Arnouts, Stéphane; Coupon, Jean; Moutard, Thibaud

    2016-01-01

    We measure the cross-correlation signature between the Planck CMB lensing map and the weak lensing observations from both the Red-sequence Cluster Lensing Survey (RCSLenS) and the Canada-France-Hawai Telescope Lensing Survey (CFHTLenS). In addition to a Fourier analysis, we include the first configuration-space detection, based on the estimators $\\langle \\kappa_{\\rm CMB} \\kappa_{\\rm gal} \\rangle$ and $\\langle \\kappa_{\\rm CMB} \\gamma_{t} \\rangle$. Combining 747.2 deg$^2$ from both surveys, we find a detection significance that exceeds $4.2\\sigma$ in both Fourier- and configuration-space analyses. Scaling the predictions by a free parameter $A$, we obtain $A^{\\rm Planck}_{\\rm CFHT}= 0.68\\pm 0.31 $ and $A^{\\rm Planck}_{\\rm RCS}= 1.31\\pm 0.33$. In preparation for the next generation of measurements similar to these, we quantify the impact of different analysis choices on these results. First, since none of these estimators probes the exact same dynamical range, we improve our detection by combining them. Second, ...

  17. CFHTLenS and RCSLenS cross-correlation with Planck lensing detected in fourier and configuration space

    Science.gov (United States)

    Harnois-Déraps, Joachim; Tröster, Tilman; Hojjati, Alireza; van Waerbeke, Ludovic; Asgari, Marika; Choi, Ami; Erben, Thomas; Heymans, Catherine; Hildebrandt, Hendrik; Kitching, Thomas D.; Miller, Lance; Nakajima, Reiko; Viola, Massimo; Arnouts, Stéphane; Coupon, Jean; Moutard, Thibaud

    2016-07-01

    We measure the cross-correlation signature between the Planck cosmic microwave background (CMB) lensing map and the weak lensing observations from both the Red-sequence Cluster Lensing Survey and the Canada-France-Hawaii Telescope Lensing Survey. In addition to a Fourier analysis, we include the first configuration-space detection, based on the estimators and . Combining 747.2 deg2 from both surveys, we find a detection significance that exceeds 4.2σ in both Fourier- and configuration-space analyses. Scaling the predictions by a free parameter A, we obtain A^Planck_CFHT= 0.68± 0.31 and A^Planck_RCS= 1.31± 0.33. In preparation for the next generation of measurements similar to these, we quantify the impact of different analysis choices on these results. First, since none of these estimators probes the exact same dynamical range, we improve our detection by combining them. Secondly, we carry out a detailed investigation on the effect of apodization, zero-padding and mask multiplication, validated on a suite of high-resolution simulations, and find that the latter produces the largest systematic bias in the cosmological interpretation. Finally, we show that residual contamination from intrinsic alignment and the effect of photometric redshift error are both largely degenerate with the characteristic signal from massive neutrinos, however the signature of baryon feedback might be easier to distinguish. The three lensing data sets are publicly available.

  18. Estimating genetic correlations based on phenotypic data: a simulation-based method

    Indian Academy of Sciences (India)

    Elias Zintzaras

    2011-04-01

    Knowledge of genetic correlations is essential to understand the joint evolution of traits through correlated responses to selection, a difficult and seldom, very precise task even with easy-to-breed species. Here, a simulation-based method to estimate genetic correlations and genetic covariances that relies only on phenotypic measurements is proposed. The method does not require any degree of relatedness in the sampled individuals. Extensive numerical results suggest that the propose method may provide relatively efficient estimates regardless of sample sizes and contributions from common environmental effects.

  19. 3D Detection, Quantification and Correlation of Slope Failures with Geologic Structure in the Mont Blanc massif

    Science.gov (United States)

    Allan, Mark; Dunning, Stuart; Lim, Michael; Woodward, John

    2016-04-01

    A thorough understanding of supply from landslides and knowledge of their spatial distribution is of fundamental importance to high-mountain sediment budgets. Advances in 3D data acquisition techniques are heralding new opportunities to create high-resolution topographic models to aid our understanding of landscape change through time. In this study, we use a Structure-from-Motion Multi-View Stereo (SfM-MVS) approach to detect and quantify slope failures at selected sites in the Mont Blanc massif. Past and present glaciations along with its topographical characteristics have resulted in a high rate of geomorphological activity within the range. Data for SfM-MVS processing were captured across variable temporal scales to examine short-term (daily), seasonal and annual change from terrestrial, Unmanned Aerial Vehicle (UAV) and helicopter perspectives. Variable spatial scales were also examined ranging from small focussed slopes (~0.01 km2) to large valley-scale surveys (~3 km2). Alignment and registration were conducted using a series of Ground Control Points (GCPs) across the surveyed slope at various heights and slope aspects. GCPs were also used to optimise data and reduce non-linear distortions. 3D differencing was performed using a multiscale model-to-model comparison algorithm (M3C2) which uses variable thresholding across each slope based on local surface roughness and model alignment quality. Detected change was correlated with local slope structure and 3D discontinuity analysis was undertaken using a plane-detection and clustering approach (DSE). Computation of joint spacing was performed using the classified data and normal distances. Structural analysis allowed us to assign a Slope Mass Rating (SMR) and assess the stability of each slope relative to the detected change and determine likely failure modes. We demonstrate an entirely 3D workflow which preserves the complexity of alpine slope topography to compute volumetric loss using a variable threshold. A

  20. A cross-correlation based fiber optic white-light interferometry with wavelet transform denoising

    Science.gov (United States)

    Wang, Zhen; Jiang, Yi; Ding, Wenhui; Gao, Ran

    2013-09-01

    A fiber optic white-light interferometry based on cross-correlation calculation is presented. The detected white-light spectrum signal of fiber optic extrinsic Fabry-Perot interferometric (EFPI) sensor is firstly decomposed by discrete wavelet transform for denoising before interrogating the cavity length of the EFPI sensor. In measurement experiment, the cross-correlation algorithm with multiple-level calculations is performed both for achieving the high measurement resolution and for improving the efficiency of the measurement. The experimental results show that the variation range of the measurement results was 1.265 nm, and the standard deviation of the measurement results can reach 0.375 nm when an EFPI sensor with cavity length of 1500 μm was interrogated.

  1. Improving SVDD classification performance on hyperspectral images via correlation based ensemble technique

    Science.gov (United States)

    Uslu, Faruk Sukru; Binol, Hamidullah; Ilarslan, Mustafa; Bal, Abdullah

    2017-02-01

    Support Vector Data Description (SVDD) is a nonparametric and powerful method for target detection and classification. The SVDD constructs a minimum hypersphere enclosing the target objects as much as possible. It has advantages of sparsity, good generalization and using kernel machines. In many studies, different methods have been offered in order to improve the performance of the SVDD. In this paper, we have presented ensemble methods to improve classification performance of the SVDD in remotely sensed hyperspectral imagery (HSI) data. Among various ensemble approaches we have selected bagging technique for training data set with different combinations. As a novel technique for weighting we have proposed a correlation based weight coefficients assignment. In this technique, correlation between each bagged classifier is calculated to give coefficients to weighted combinators. To verify the improvement performance, two hyperspectral images are processed for classification purpose. The obtained results show that the ensemble SVDD has been found to be significantly better than conventional SVDD in terms of classification accuracy.

  2. Vibration measurement based on the optical cross-correlation technique with femtosecond pulsed laser

    Science.gov (United States)

    Han, Jibo; Wu, Tengfei; Zhao, Chunbo; Li, Shuyi

    2016-10-01

    Two vibration measurement methods with femtosecond pulsed laser based on the optical cross-correlation technique are presented independently in this paper. The balanced optical cross-correlation technique can reflect the time jitter between the reference pluses and measurement pluses by detecting second harmonic signals using type II phase-matched nonlinear crystal and balanced amplified photo-detectors. In the first method, with the purpose of attaining the vibration displacement, the time difference of the reference pulses relative to the measurement pluses can be measured using single femtosecond pulsed laser. In the second method, there are a couple of femtosecond pulsed lasers with high pulse repetition frequency. Vibration displacement associated with cavity length can be calculated by means of precisely measuring the pulse repetition frequency. The results show that the range of measurement attains ±150μm for a 500fs pulse. These methods will be suited for vibration displacement measurement, including laboratory use, field testing and industrial application.

  3. Lagrangian based methods for coherent structure detection

    Energy Technology Data Exchange (ETDEWEB)

    Allshouse, Michael R., E-mail: mallshouse@chaos.utexas.edu [Center for Nonlinear Dynamics and Department of Physics, University of Texas at Austin, Austin, Texas 78712 (United States); Peacock, Thomas, E-mail: tomp@mit.edu [Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States)

    2015-09-15

    There has been a proliferation in the development of Lagrangian analytical methods for detecting coherent structures in fluid flow transport, yielding a variety of qualitatively different approaches. We present a review of four approaches and demonstrate the utility of these methods via their application to the same sample analytic model, the canonical double-gyre flow, highlighting the pros and cons of each approach. Two of the methods, the geometric and probabilistic approaches, are well established and require velocity field data over the time interval of interest to identify particularly important material lines and surfaces, and influential regions, respectively. The other two approaches, implementing tools from cluster and braid theory, seek coherent structures based on limited trajectory data, attempting to partition the flow transport into distinct regions. All four of these approaches share the common trait that they are objective methods, meaning that their results do not depend on the frame of reference used. For each method, we also present a number of example applications ranging from blood flow and chemical reactions to ocean and atmospheric flows.

  4. Biomimetic visual detection based on insect neurobiology

    Science.gov (United States)

    O'Carroll, David C.

    2001-11-01

    With a visual system that accounts for as much as 30% of the lifted mass, flying insects such as dragonflies and hoverflies invest more in vision than any other animal. Impressive visual performance is subserved by a surprisingly simple visual system. In a typical insect eye, between 2,000 and 30,000 pixels in the image are analyzed by fewer than 200,000 neurons in underlying neural circuits. The combination of sophisticated visual processing with an approachable level of complexity has made the insect visual system a leading model for biomimetic approaches to computer vision. Much neurobiological research has focused on neural circuits used for detection of moving patterns (e.g. optical flow during flight) and moving targets (e.g. prey). Research from several labs has led to great advances in our understanding of the neural mechanisms involved, and has spawned neuromorphic hardware based on key processes identified in neurobiological experiments. Despite its attractions, the highly non-linear nature of several key stages in insect visual processing presents a challenge to understanding. I will describe examples of adaptive elements of neural circuits in the fly visual system which analyze the direction and velocity of wide-field optical flow patterns and the result of experiments that suggest that these non-linearities may contribute to robust responses to natural image motion.

  5. Code-Aided Estimation and Detection on Time-Varying Correlated Mimo Channels: A Factor Graph Approach

    Directory of Open Access Journals (Sweden)

    Simoens Frederik

    2006-01-01

    Full Text Available This paper concerns channel tracking in a multiantenna context for correlated flat-fading channels obeying a Gauss-Markov model. It is known that data-aided tracking of fast-fading channels requires a lot of pilot symbols in order to achieve sufficient accuracy, and hence decreases the spectral efficiency. To overcome this problem, we design a code-aided estimation scheme which exploits information from both the pilot symbols and the unknown coded data symbols. The algorithm is derived based on a factor graph representation of the system and application of the sum-product algorithm. The sum-product algorithm reveals how soft information from the decoder should be exploited for the purpose of estimation and how the information bits can be detected. Simulation results illustrate the effectiveness of our approach.

  6. Heat shock-induced interactions among nuclear HSFs detected by fluorescence cross-correlation spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Pack, Chan-Gi, E-mail: changipack@amc.seoul.kr [Asan Institute for Life Sciences, University of Ulsan, College of Medicine, Asan Medical Center, Seoul 138-736 (Korea, Republic of); Ahn, Sang-Gun [Dept. of Pathology, College of Dentistry, Chosun University, Seosuk-dong, Dong-gu, Gwangju 501-759 (Korea, Republic of)

    2015-07-31

    The cellular response to stress is primarily controlled in cells via transcriptional activation by heat shock factor 1 (HSF1). HSF1 is well-known to form homotrimers for activation upon heat shock and subsequently bind to target DNAs, such as heat-shock elements, by forming stress granules. A previous study demonstrated that nuclear HSF1 and HSF2 molecules in live cells interacted with target DNAs on the stress granules. However, the process underlying the binding interactions of HSF family in cells upon heat shock remains unclear. This study demonstrate for the first time that the interaction kinetics among nuclear HSF1, HSF2, and HSF4 upon heat shock can be detected directly in live cells using dual color fluorescence cross-correlation spectroscopy (FCCS). FCCS analyses indicated that the binding between HSFs was dramatically changed by heat shock. Interestingly, the recovery kinetics of interaction between HSF1 molecules after heat shock could be represented by changes in the relative interaction amplitude and mobility. - Highlights: • The binding interactions among nuclear HSFs were successfully detected. • The binding kinetics between HSF1s during recovery was quantified. • HSF2 and HSF4 strongly formed hetero-complex, even before heat shock. • Nuclear HSF2 and HSF4 bound to HSF1 only after heat shock.

  7. Study on correlations of modal frequencies and environmental factors for a suspension bridge based on improved neural networks

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    By using of long-term monitoring data of Runyang Suspension Bridge,the improved back-propagation neural networks (BPNNs) are formulated for modeling the correlations between modal frequencies and environmental conditions including wind,temperature and vehicle load.Then,with the correlation models the environmental effects on modal frequencies are quantified and the abnormal changes of measured frequencies are detected by means of the hypothesis tests.Analysis results reveal that BPNN-based correlation models improved by both early stopping and Bayesian regularization techniques exhibit excellent generalization capability.And the developed correlation models can effectively reduce the environmental variability in modal frequencies.The t-test method provides a good capability to detect the damage-induced 0.16% and 0.12% abnormal changes of the 5th and 6th modal frequencies,respectively.Hence,the proposed method is suitable for real-time monitoring of suspension bridge conditions.

  8. Ground-Based Detection of Exoatmospheric Calcium

    Science.gov (United States)

    Rojo, Patricio M.; Astudillo-Defru, Nicola

    2014-11-01

    Data acquired with HDS@Subaru for HD209458b is re-analyzed. A new pipeline performs an automated search for the exoatmospheric presence of several elements without any a-priori assumptions on its existence or strength. We analyzed thousands of lines in the full spectral range of this optical echelle spectrograph using a robust method to correct for the telluric contamination. We recover previous detections of Sodium and Halpha, and present the first strong detection of Calcium in an Extrasolar Atmosphere as well as the tentative detection of other elements. The Calcium detection is in disagreement with theoretical thermal-equilibrium models.

  9. A Case Study Correlating Innovative Gamma Ray Scanning Detection Systems Data to Surface Soil Gamma Spectrometry Results - 13580

    Energy Technology Data Exchange (ETDEWEB)

    Thompson, Shannon; Rodriguez, Rene; Billock, Paul [HydroGeoLogic, Inc., 11107 Sunset Hills Road, Suite 400, Reston, VA 20190 (United States); Lit, Peter [Nomad Science Group, 7738 Nautilus Shell Street, Las Vegas, NV 89139 (United States)

    2013-07-01

    HydroGeoLogic (HGL), Inc. completed a United States Environmental Protection Agency (USEPA) study to characterize radiological contamination at a site near Canoga Park, California. The characterized area contained 470 acres including the site of a prototype commercial nuclear reactor and other nuclear design, testing, and support operations from the 1950's until 1988 [1]. The site history included radiological releases during operation followed by D and D activities. The characterization was conducted under an accelerated schedule and the results will support the project remediation. The project has a rigorous cleanup to background agenda and does not allow for comparison to risk-based guidelines. To target soil sample locations, multiple lines of evidence were evaluated including a gamma radiation survey, geophysical surveys, historical site assessment, aerial photographs, and former worker interviews. Due to the time since production and decay, the primary gamma emitting radionuclide remaining is cesium-137 (Cs-137). The gamma ray survey covered diverse, rugged terrain using custom designed sodium iodide thallium-activated (NaI(Tl)) scintillation detection systems. The survey goals included attaining 100% ground surface coverage and detecting gamma radiation as sensitively as possible. The effectiveness of innovative gamma ray detection systems was tested by correlating field Cs-137 static count ratios to Cs-137 laboratory gamma spectrometry results. As a case study, the area encompassing the former location of the first nuclear power station in the U. S. was scanned, and second by second global positioning system (GPS)-linked gamma spectral data were evaluated by examining total count rate and nuclide-specific regions of interest. To compensate for Compton scattering from higher energy naturally occurring radionuclides (U-238, Th-232 and their progeny, and K-40), count rate ratios of anthropogenic nuclide-specific regions of interest to the total count rate

  10. Atlas-based diffusion tensor imaging correlates of executive function

    Science.gov (United States)

    Nowrangi, Milap A.; Okonkwo, Ozioma; Lyketsos, Constantine; Oishi, Kenichi; Mori, Susumu; Albert, Marilyn; Mielke, Michelle M.

    2015-01-01

    Impairment in executive function (EF) is commonly found in Alzheimer’s Dementia (AD) and Mild Cognitive Impairment (MCI). Atlas-based Diffusion Tensor Imaging (DTI) methods may be useful in relating regional integrity to EF measures in MCI and AD. 66 participants (25 NC, 22 MCI, and 19 AD) received DTI scans and clinical evaluation. DTI scans were applied to a pre-segmented atlas and fractional anisotropy (FA) and mean diffusivity (MD) were calculated. ANOVA was used to assess group differences in frontal, parietal, and cerebellar regions. For regions differing between groups (p<0.01), linear regression examined the relationship between EF scores and regional FA and MD. Anisotropy and diffusivity in frontal and parietal lobe white matter (WM) structures were associated with EF scores in MCI and only frontal lobe structures in AD. EF was more strongly associated with FA than MD. The relationship between EF and anisotropy and diffusivity was strongest in MCI. These results suggest that regional WM integrity is compromised in MCI and AD and that FA may be a better correlate of EF than MD. PMID:25318544

  11. STOCK Market Differences in Correlation-Based Weighted Network

    Science.gov (United States)

    Youn, Janghyuk; Lee, Junghoon; Chang, Woojin

    We examined the sector dynamics of Korean stock market in relation to the market volatility. The daily price data of 360 stocks for 5019 trading days (from January, 1990 to August, 2008) in Korean stock market are used. We performed the weighted network analysis and employed four measures: the average, the variance, the intensity, and the coherence of network weights (absolute values of stock return correlations) to investigate the network structure of Korean stock market. We performed regression analysis using the four measures in the seven major industry sectors and the market (seven sectors combined). We found that the average, the intensity, and the coherence of sector (subnetwork) weights increase as market becomes volatile. Except for the "Financials" sector, the variance of sector weights also grows as market volatility increases. Based on the four measures, we can categorize "Financials," "Information Technology" and "Industrials" sectors into one group, and "Materials" and "Consumer Discretionary" sectors into another group. We investigated the distributions of intrasector and intersector weights for each sector and found the differences in "Financials" sector are most distinct.

  12. A study of combined evaluation of suppliers based on correlation

    Directory of Open Access Journals (Sweden)

    Heting Qiu

    2013-03-01

    Full Text Available Purpose: The Selection of logistics service providers is an important issue in supply chain management. But different evaluation methods may lead to different results, which could cause inconsistent conclusions. This paper makes use of a new perspective to combine with a variety of methods to eliminate the deviation of different single evaluation methods. Design/methodology/approach: This paper expounds the application of the combined evaluation method based on correlation. Entropy method, factor analysis, grey colligation evaluation and AHP have been used for research. Findings: According to the evaluate result, the ranking of suppliers obtained by each method have obvious differences. The result shows that combined evaluation method can eliminate the deviation of different single evaluation methods. Originality/value: The combined evaluation method makes up for the defects of single evaluation methods and obtains a result that is more stable and creditable with smaller deviation. This study can provide the enterprise leaders with more scientific method to select their cooperative companies. 

  13. Effective Steganography Detection Based On Data Compression

    CERN Document Server

    Nechta, Ivan

    2011-01-01

    This article describes novel text steganalysis method. The archiver "Bzip2" used for detection stegotext generated by Texto stegosystem. Experiments show that proposed approach gets better performance than typical existing methods. The detection accuracy exceeds 99.98% for text segments with size 400 bytes.

  14. Dependence-Based Anomaly Detection Methodologies

    Science.gov (United States)

    2012-08-16

    tricks the user to enter their Netflix login. Detecting it is out of our scope and requires site authentication (i.e., certification verification... Netflix login. Detecting it is out of our scope and requires site authentication (i.e., certification verification) and user education. The preliminary

  15. Video quality assessment based on correlation between spatiotemporal motion energies

    Science.gov (United States)

    Yan, Peng; Mou, Xuanqin

    2016-09-01

    Video quality assessment (VQA) has been a hot research topic because of rapid increase of huge demand of video communications. From the earliest PSNR metric to advanced models that are perceptual aware, researchers have made great progress in this field by introducing properties of human vision system (HVS) into VQA model design. Among various algorithms that model the property of HVS perceiving motion, the spatiotemporal energy model has been validated to be high consistent with psychophysical experiments. In this paper, we take the spatiotemporal energy model into VQA model design by the following steps. 1) According to the pristine spatiotemporal energy model proposed by Adelson et al, we apply the linear filters, which are oriented in space-time and tuned in spatial frequency, to filter the reference and test videos respectively. The outputs of quadrature pairs of above filters are then squared and summed to give two measures of motion energy, which are named rightward and leftward energy responses, respectively. 2) Based on the pristine model, we calculate summation of the rightward and leftward energy responses as spatiotemporal features to represent perceptual quality information for videos, named total spatiotemporal motion energy maps. 3) The proposed FR-VQA model, named STME, is calculated with statistics based on the pixel-wise correlation between the total spatiotemporal motion energy maps of the reference and distorted videos. The STME model was validated on the LIVE VQA Database by comparing with existing FR-VQA models. Experimental results show that STME performs with excellent prediction accuracy and stays in state-of-the-art VQA models.

  16. Network Anomaly Detection Based on Wavelet Analysis

    Directory of Open Access Journals (Sweden)

    Ali A. Ghorbani

    2008-11-01

    Full Text Available Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

  17. Correlation methods of base-level cycle based on wavelet neural network

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The authors discussed the method of wavelet neural network (WNN) for correlation of base-level cycle. A new vectored method of well log data was proposed. Through the training with the known data set, the WNN can remenber the cycle pattern characteristic of the well log curves. By the trained WNN to identify the cycle pattern in the vectored log data, the ocrrelation process among the well cycles was completed. The application indicates that it is highly efficient and reliable in base-level cycle correlation.

  18. Effect of the degree of phase-correlation of laser sources on the transmission and optical coherent detection in radio-over-fibre systems

    Science.gov (United States)

    Maldonado-Basilio, Ramón; Li, Ran; Abdul-Majid, Sawsan; Nikkhah, Hamdam; Leong, Kin-Wai; Hall, Trevor J.

    2013-01-01

    The deployment of high capacity Radio-over-Fiber (RoF) systems rely, among many aspects, on the capability to efficiently generate, transport, and detect millimeter-wave carriers modulated at high data rates. Photonic approaches based on the heterodyne beating of two free-running laser sources have been proposed as an alternative to generate multi-Gbps quadrature phase modulated signals imposed on millimeter wave carriers. Implementing photonic approaches in the down-link avoids the need for electronic generation of high frequency carriers and decreases the requirements at the base band electronics. In addition, implementing complex modulation formats overcomes some of the typical issues found in intensity modulation direct detection approaches such as non­ linearity, receiver sensitivity and dynamic range. In this work, the performance improvement of a coherent RoF system carrying 10 Gbps QPSK signals is numerically analyzed in terms of both the frequency linewidth and the degree of phase correlation between the lasers utilised at the down-link (for the optical heterodyne beating) and at the up-link (for the optical coherent detection). Relative to phase correlated lasers featuring linewidths of 5 MHz, the peak power of the 60 G Hz carrier generated at the down-link is reduced by 8 dB for un-correlated lasers. In addition, the error vector magnitude of the received signal at the up-link is improved from over 20% (for un-correlated lasers and linewidths of 5 MHz) to around 15% (for correlated lasers) at an optical received power of -30 dBm. The results obtained reinforce the idea of using coherent comb laser sources with phase correlated modes located at the Central Office. It also motivates the eventual deployment of techniques to control the degree of phase correlation between the lasers used as signal and local oscillator at the optical coherent receivers.

  19. Correlation between theoretical anatomical patterns of lymphatic drainage and lymphoscintigraphy findings during sentinel node detection in head and neck melanomas

    Energy Technology Data Exchange (ETDEWEB)

    Vidal, Monica; Ruiz, Diana Milena [Hospital Clinic de Barcelona, Nuclear Medicine Department, Barcelona (Spain); Vidal-Sicart, Sergi; Paredes, Pilar; Pons, Francesca [Hospital Clinic de Barcelona, Nuclear Medicine Department, Barcelona (Spain); Institut d' Investigacions Biomediques Agusti Pi i Sunyer (IDIBAPS), Barcelona (Spain); Torres, Ferran [Hospital Clinic Barcelona, Statistical of Biostatistics and Data Management Core Facility, IDIBAPS, Barcelona (Spain); Universitat Autonoma de Barcelona, Biostatistics Unit, Faculty of Medicine, Barcelona (Spain)

    2016-04-15

    In the diagnosis of head and neck melanoma, lymphatic drainage is complex and highly variable. As regional lymph node metastasis is one of the most important prognostic factors, lymphoscintigraphy can help map individual drainage patterns. The aim of this study was to compare the results of lymphoscintigraphy and sentinel lymph node (SLN) detection with theoretical anatomical patterns of lymphatic drainage based on the location of the primary tumour lesion in patients with head and neck melanoma. We also determined the percentage of discrepancies between our lymphoscintigraphy and the theoretical location of nodal drainage predicted by a large lymphoscintigraphic database, in order to explain recurrence and false-negative SLN biopsies. In this retrospective study of 152 patients with head and neck melanoma, the locations of the SLNs on lymphoscintigraphy and detected intraoperatively were compared with the lymphatic drainage predicted by on-line software based on a large melanoma database. All patients showed lymphatic drainage and in all patients at least one SLN was identified by lymphoscintigraphy. Of the 152 patients, 4 had a primary lesion in areas that were not described in the Sydney Melanoma Unit database, so agreement could only be evaluated in 148 patients. Agreement between lymphoscintigraphic findings and the theoretical lymphatic drainage predicted by the software was completely concordant in 119 of the 148 patients (80.4 %, 95 % CI 73.3 - 86 %). However, this concordance was partial (some concordant nodes and others not) in 18 patients (12.2 %, 95 % CI 7.8 - 18.4 %). Discordance was complete in 11 patients (7.4 %, 95 % CI 4.2 - 12.8 %). In melanoma of the head and neck there is a high correlation between lymphatic drainage found by lymphoscintigraphy and the predicted drainage pattern and basins provided by a large reference database. Due to unpredictable drainage, preoperative lymphoscintigraphy is essential to accurately detect the SLNs in head and

  20. Anomica: Fast Support Vector Based Novelty Detection

    Data.gov (United States)

    National Aeronautics and Space Administration — In this paper we propose ν-Anomica, a novel anomaly detection technique that can be trained on huge data sets with much reduced running time compared to the...

  1. BER analysis of MPSK space-time code with differential detection over correlated block-fading Rayleigh channel

    Institute of Scientific and Technical Information of China (English)

    ZOU Yu-long; ZHENG Bao-yu

    2008-01-01

    MIMO technology proposed in recent years can effectively combat the multipath fading of wireless channel and can considerably enlarge the channel capacity, which has been investigated widely by researchers. However, its performance analysis over correlated block-fading Rayleigh channel is still an open and challenging objective. In this article, an analytic expression of bit error rate (BER) is presented for multiple phase shift keying (MPSK) space-time code, with differential detection over correlated block-fading Rayleigh channel. Through theoretical analysis of BER, it can be found that the differential space-time scheme without the need for channel state information (CSI) at receiver achieves distinct performance gain compared with the traditional nonspace-time system. And then, the system simulation is complimented to verify the above result, showing that the diversity system based on the differential space-time block coding (DSTBC) outperforms the traditional nonspace- time system with diversity gain in terms of BER. Furthermore, the numerical results also demonstrate that the error floor of the differential space-time system is much lower than that of the differential nonspace-time system.

  2. Detection of Atmospheric Composition Based on Lidar

    Energy Technology Data Exchange (ETDEWEB)

    Zhang Jinye; Tong Yala; Yang Xiaoling; Gong Jiaoli [School of science, Hubei University of Technology, Wuhan 430068 (China); Gong Wei, E-mail: yezi.zh@163.com [State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079 (China)

    2011-02-01

    A summary overview about the types of lidar and their own applications on atmosphere detection is presented. Measurement of atmospheric aerosols by Mie lidar and Raman lidar is focused. The vertical profiles of aerosols in the atmosphere are retrieved. And at the same time, through analyzing aerosol vertical content distribution, the atmosphere boundary layer and the cloud are also observed. All the results show that the lidar has good performance on detecting the atmospheric composition.

  3. Performance of VBLAST Systems Based on Spatial Correlated MIMO Channels

    Institute of Scientific and Technical Information of China (English)

    WANG Zhong-peng; QIU Zhong-yuan; WU Wei-ling

    2004-01-01

    Vertically-layered Bell Laboratories Layered Space-Time (VBLAST) is one of the most promising techniques for realizing high spectral efficiencies over wireless link. In previously published work, the performance of VBLAST has been primarily investigated in uncorrelated Rayleigh fading channels. However in real environments some correlation between antenna elements can be presented. In this paper, we study the impact of transmit correlation on the performance of VBLAST systems. Finally we provide simulation results demonstrating the impact of spatial fading correlation on the symbol error rate of VBLAST.

  4. Aerobic plate counts and ATP levels correlate with Listeria monocytogenes detection in retail delis.

    Science.gov (United States)

    Hammons, Susan R; Stasiewicz, Matthew J; Roof, Sherry; Oliver, Haley F

    2015-04-01

    Listeria monocytogenes is a foodborne pathogen that causes an estimated 1,591 cases of illness and 255 deaths annually in the United States, the majority of which are attributed to ready-to-eat deli meats processed in retail delis. Because retail delis distribute product directly to consumers, rapid methods to validate cleaning and sanitation are needed to improve retail food safety. This study investigated the relationships among ATP levels, standard aerobic plate count (APC), and L. monocytogenes presence in fully operational delis. Fifteen full-service delis were concurrently sampled for ATP, APC, and L. monocytogenes during preoperational hours once monthly for 3 months. Fifteen additional delis were recruited for 6 months of operational sampling (n = 30). A 1-log increase in APC was equivalent to a 3.3-fold increase in the odds of detecting L. monocytogenes (P < 0.001) and a 1.9-log increase in L monocytogenes population (P = 0.03). An ATP level increase of 1 log relative light unit correlated to a 0.22-log increase in APC (P < 0.001). A preoperational ATP level mean increase by 1 log relative light unit increased the odds of detecting L. monocytogenes concurrently fourfold. A 0.5-log increase in mean ATP level during preoperational sampling corresponded to a 2% increase in the predicted L. monocytogenes prevalence during operation (P < 0.01). Additionally, 10 statistically representative sites were identified and recommended for use in sanitation monitoring programs. Our data support the use of ATP as a rapid method to validate effective cleaning and sanitation to reduce L. monocytogenes in retail delis.

  5. Correlation between localization, age, and chromosomal imbalances in ependymal tumours as detected by CGH.

    Science.gov (United States)

    Jeuken, Judith W M; Sprenger, Sandra H E; Gilhuis, Job; Teepen, Hans L J M; Grotenhuis, Andre J; Wesseling, Pieter

    2002-06-01

    Ependymal tumours (ETs) are gliomas that arise from the ependymal lining of the cerebral ventricles and from the remnants of the central canal of the spinal cord. Both clinical and genetic studies suggest that distinct genetic subtypes of ETs exist, the subtypes being correlated with patient age and/or tumour site. In the present study, the tumour genome of 20 ETs (15 adult and five paediatric cases) was screened for chromosomal imbalances by comparative genomic hybridization (CGH). The most frequently detected imbalances were -22q (75%), -10q (65%), -21 (50%), -16p (50%), -1p (45%), +4q (45%), -10p (45%), -2q (40%), -6 (40%), -19 (40%), -2p (35%), -3p (35%), and -16q (35%). Comparison of the chromosomal imbalances detected in ETs with those previously reported in oligodendroglial and astrocytic tumours revealed that in this respect ETs show similarities to these other gliomas. By combining these results with those of a recent study of Zheng et al. and Hirose et al., it was found that although ETs from different sites and from adult and paediatric patients show overlap at the CGH level, some chromosomal imbalances occur predominantly in a certain category. In adult patients, spinal ETs relatively often showed +2, +7, +12, and -14q; infratentorial ETs -22; and supratentorial ETs -9. In addition, in posterior fossa ETs, -6 and +9 were much more frequent in adults than in children. It is concluded that the genetic background of ETs is complex and partly determined by tumour site, histopathological subtype, and age of the patient.

  6. Neural correlates of own name and own face detection in autism spectrum disorder.

    Directory of Open Access Journals (Sweden)

    Hanna B Cygan

    Full Text Available Autism spectrum disorder (ASD is a heterogeneous neurodevelopmental condition clinically characterized by social interaction and communication difficulties. To date, the majority of research efforts have focused on brain mechanisms underlying the deficits in interpersonal social cognition associated with ASD. Recent empirical and theoretical work has begun to reveal evidence for a reduced or even absent self-preference effect in patients with ASD. One may hypothesize that this is related to the impaired attentional processing of self-referential stimuli. The aim of our study was to test this hypothesis. We investigated the neural correlates of face and name detection in ASD. Four categories of face/name stimuli were used: own, close-other, famous, and unknown. Event-related potentials were recorded from 62 electrodes in 23 subjects with ASD and 23 matched control subjects. P100, N170, and P300 components were analyzed. The control group clearly showed a significant self-preference effect: higher P300 amplitude to the presentation of own face and own name than to the close-other, famous, and unknown categories, indicating preferential attentional engagement in processing of self-related information. In contrast, detection of both own and close-other's face and name in the ASD group was associated with enhanced P300, suggesting similar attention allocation for self and close-other related information. These findings suggest that attention allocation in the ASD group is modulated by the personal significance factor, and that the self-preference effect is absent if self is compared to close-other. These effects are similar for physical and non-physical aspects of the autistic self. In addition, lateralization of face and name processing is attenuated in ASD, suggesting atypical brain organization.

  7. Vision-based vehicle detection and tracking algorithm design

    Science.gov (United States)

    Hwang, Junyeon; Huh, Kunsoo; Lee, Donghwi

    2009-12-01

    The vision-based vehicle detection in front of an ego-vehicle is regarded as promising for driver assistance as well as for autonomous vehicle guidance. The feasibility of vehicle detection in a passenger car requires accurate and robust sensing performance. A multivehicle detection system based on stereo vision has been developed for better accuracy and robustness. This system utilizes morphological filter, feature detector, template matching, and epipolar constraint techniques in order to detect the corresponding pairs of vehicles. After the initial detection, the system executes the tracking algorithm for the vehicles. The proposed system can detect front vehicles such as the leading vehicle and side-lane vehicles. The position parameters of the vehicles located in front are obtained based on the detection information. The proposed vehicle detection system is implemented on a passenger car, and its performance is verified experimentally.

  8. Seismic wave detection system based on fully distributed acoustic sensing

    Science.gov (United States)

    Jiang, Yue; Xu, Tuanwei; Feng, Shengwen; Huang, Jianfen; Yang, Yang; Guo, Gaoran; Li, Fang

    2016-11-01

    This paper presents a seismic wave detection system based on fully distributed acoustic sensing. Combined with Φ- OTDR and PGC demodulation technology, the system can detect and acquire seismic wave in real time. The system has a frequency response of 3.05 dB from 5 Hz to 1 kHz, whose sampling interval of each channel of 1 meter on total sensing distance up to 10 km. By comparing with the geophone in laboratory, the data show that in the time domain and frequency domain, two waveforms coincide consistently, and the correlation coefficient could be larger than 0.98. Through the analysis of the data of the array experiment and the oil well experiment, DAS system shows a consistent time domain and frequency domain response and a clearer trail of seismic wave signal as well as a higher signal-noise rate which indicate that the system we proposed is expected to become the next generation of seismic exploration equipment.

  9. Cavitating vortex characterization based on acoustic signal detection

    Science.gov (United States)

    Digulescu, A.; Murgan, I.; Candel, I.; Bunea, F.; Ciocan, G.; Bucur, D. M.; Dunca, G.; Ioana, C.; Vasile, G.; Serbanescu, A.

    2016-11-01

    In hydraulic turbines operating at part loads, a cavitating vortex structure appears at runner outlet. This helical vortex, called vortex rope, can be cavitating in its core if the local pressure is lower that the vaporization pressure. An actual concern is the detection of the cavitation apparition and the characterization of its level. This paper presents a potentially innovative method for the detection of the cavitating vortex presence based on acoustic methods. The method is tested on a reduced scale facility using two acoustic transceivers positioned in ”V” configuration. The received signals were continuously recorded and their frequency content was chosen to fit the flow and the cavitating vortex. Experimental results showed that due to the increasing flow rate, the signal - vortex interaction is observed as modifications on the received signal's high order statistics and bandwidth. Also, the signal processing results were correlated with the data measured with a pressure sensor mounted in the cavitating vortex section. Finally it is shown that this non-intrusive acoustic approach can indicate the apparition, development and the damping of the cavitating vortex. For real scale facilities, applying this method is a work in progress.

  10. Chord Recognition Based on Temporal Correlation Support Vector Machine

    OpenAIRE

    Zhongyang Rao; Xin Guan; Jianfu Teng

    2016-01-01

    In this paper, we propose a method called temporal correlation support vector machine (TCSVM) for automatic major-minor chord recognition in audio music. We first use robust principal component analysis to separate the singing voice from the music to reduce the influence of the singing voice and consider the temporal correlations of the chord features. Using robust principal component analysis, we expect the low-rank component of the spectrogram matrix to contain the musical accompaniment and...

  11. Sampling of general correlators in worm-algorithm based simulations

    Science.gov (United States)

    Rindlisbacher, Tobias; Åkerlund, Oscar; de Forcrand, Philippe

    2016-08-01

    Using the complex ϕ4-model as a prototype for a system which is simulated by a worm algorithm, we show that not only the charged correlator , but also more general correlators such as or , as well as condensates like , can be measured at every step of the Monte Carlo evolution of the worm instead of on closed-worm configurations only. The method generalizes straightforwardly to other systems simulated by worms, such as spin or sigma models.

  12. Sampling of General Correlators in Worm Algorithm-based Simulations

    CERN Document Server

    Rindlisbacher, Tobias; de Forcrand, Philippe

    2016-01-01

    Using the complex $\\phi^4$-model as a prototype for a system which is simulated by a (bosonic) worm algorithm, we show that not only the charged correlator $$, but also more general correlators such as $$ or $$ as well as condensates like $$ can be measured at every step of the Monte Carlo evolution of the worm instead of on closed-worm configurations only. The method generalizes straightforwardly to other systems simulated by (bosonic) worms, such as spin or sigma models.

  13. Detection and localization of deep endometriosis by means of MRI and correlation with the ENZIAN score

    Energy Technology Data Exchange (ETDEWEB)

    Di Paola, V., E-mail: dipaola.valerio@libero.it; Manfredi, R.; Castelli, F.; Negrelli, R.; Mehrabi, S.; Pozzi Mucelli, R.

    2015-04-15

    %, 95%, 99%, 86%, respectively. The highest accuracy was for adenomyosis (100%) and endometriosis of utero-sacral ligaments (USLs) (98%), slightly lower for vagina-rectovaginal septum an colo-rectal walls (96%), and the lowest for bladder endometriosis (92%). The concordance between histopathological and MRI ENZIAN score was excellent (k = 0.824); in particular it was 0.812 for lesions in vagina-rectovaginal space, 0.890 for lesions in USL, 0.822 for lesions in rectum–sigmoid colon, 1.000 for uterine adenomyosis, and 0.367 for lesions located in the bladder wall. Conclusion: MRI correlates with the ENZIAN score and has an accuracy of 95% in the detection and localization of deep endometriosis, allowing to minimize false negative results (4%) in patients with deep endometriosis and to obtain a correct preoperative staging.

  14. Functional cine MR imaging for the detection and mapping of intraabdominal adhesions: method and surgical correlation

    Energy Technology Data Exchange (ETDEWEB)

    Buhmann-Kirchhoff, Sonja; Reiser, Maximilian; Lienemann, Andreas [University Hospital Grosshadern, Ludwig-Maximilians-University Munich, Department of Clinical Radiology, Munich (Germany); Lang, Reinhold; Steitz, Heinrich O.; Jauch, Karl W. [University Hospital Munich-Grosshadern, Department of Surgery, Munich (Germany); Kirchhoff, Chlodwig [University Hospital Munich-Innenstadt, Department of Surgery, Munich (Germany)

    2008-06-15

    The purpose of this study was to evaluate the presence and localization of intraabdominal adhesions using functional cine magnetic resonance imaging (MRI) and to correlate the MR findings with intraoperative results. In a retrospective study, patients who had undergone previous abdominal surgery with suspected intraabdominal adhesions were examined. A true fast imaging with steady state precession sequence in transverse/sagittal orientation was used for a section-by-section dynamic depiction of visceral slide on a 1.5-Tesla system. After MRI, all patients underwent anew surgery. A nine-segment abdominal map was used to document the location and type of the adhesions. The intraoperative results were taken as standard of reference. Ninety patients were enrolled. During surgery 71 adhesions were detected, MRI depicted 68 intraabdominal adhesions. The most common type of adhesion in MRI was found between the anterior abdominal wall and small bowel loops (n = 22, 32.5%) and between small bowel loops and pelvic organs (n = 14, 20.6%). Comparing MRI with the intraoperative findings, sensitivity varied between 31 and 75% with a varying specificity between 65 and 92% in the different segments leading to an overall MRI accuracy of 89%. Functional cine MRI proved to be a useful examination technique for the identification of intraabdominal adhesions in patients with acute or chronic pain and corresponding clinical findings providing accurate results. However, no differentiation for symptomatic versus asymptomatic adhesions is possible. (orig.)

  15. A NOVEL THRESHOLD BASED EDGE DETECTION ALGORITHM

    Directory of Open Access Journals (Sweden)

    Y. RAMADEVI,

    2011-06-01

    Full Text Available Image segmentation is the process of partitioning/subdividing a digital image into multiple meaningful regions or sets of pixels regions with respect to a particular application. Edge detection is one of the frequently used techniques in digital image processing. The level to which the subdivision is carried depends on theproblem being viewed. Edges characterize boundaries and are therefore a problem of fundamental importance in image processing. There are many ways to perform edge detection. In this paper different Edge detection methods such as Sobel, Prewitt, Robert, Canny, Laplacian of Gaussian (LOG are used for segmenting the image. Expectation-Maximization (EM algorithm, OSTU and Genetic algorithms are also used. A new edge detection technique is proposed which detects the sharp and accurate edges that are not possible with the existing techniques. The proposed method with different threshold values for given input image is shown that ranges between 0 and 1 and it are observed that when the threshold value is 0.68 the sharp edges are recognised properly.

  16. Biosensor based on Butyrylcholinesterase for Detection of Carbofuran

    Science.gov (United States)

    Dey, Mousumi; Bhuvanagayathri, R.; Daniel, David K.

    2015-04-01

    Esterase enzymes play an important role in biology because they are responsible for the hydrolysis of choline esters. In their absence, the original state of the post synaptic membranes cannot be reestablished. Therefore, the aim of the work is to study the inhibiting action exerted by the group of compounds on these enzymes. Among these class of inhibiting compounds, pesticides are important because of the potential danger as a result of their large scale use in agriculture. Pesticides are generally determined using liquid or gas chromatography methods with various detection techniques. These methods are very sensitive and discriminating, however they require sample pretreatment such as extraction, preconcentration and clean up, which are skilled techniques and high cost treatment and also time consuming. In this study, acetyl cholinesterase and butyrylcholinesterase based biosensors have emerged as a promising tool for the detection and characterization of pesticides which are inhibitors of these enzymes. Although the physiological function of butyrylcholinesterase in comparison with acetyl cholinesterase is ambiguous, it has larger substrate specificity towards choline esters. Therefore, the development of a more selective electrode against choline, can lead to more sensitive determination of the inhibitor being investigated. Hence in the present work, a method based on inhibition of butyrylcholinesterase was attempted for quantification of carbofuran on the basis of cholinesterase inhibition. Butyrylcholinesterase with an activity of 10.2 units/mg was immobilized on a solid surface by cross linking with glutaraldehyde. The immobilized system was calibrated by correlating the inhibition of the butyrylcholinesterase activity with varying concentrations of the butyryl choline chloride and carbofuran. The sensing mechanism was investigated for its response to carbofuran concentrations ranging from 125 to 1,000 ppm. The effects of butyryl choline chloride

  17. Detecting Outlier Microarray Arrays by Correlation and Percentage of Outliers Spots

    Directory of Open Access Journals (Sweden)

    Song Yang

    2006-01-01

    Full Text Available We developed a quality assurance (QA tool, namely microarray outlier filter (MOF, and have applied it to our microarray datasets for the identification of problematic arrays. Our approach is based on the comparison of the arrays using the correlation coefficient and the number of outlier spots generated on each array to reveal outlier arrays. For a human universal reference (HUR dataset, which is used as a technical control in our standard hybridization procedure, 3 outlier arrays were identified out of 35 experiments. For a human blood dataset, 12 outlier arrays were identified from 185 experiments. In general, arrays from human blood samples displayed greater variation in their gene expression profiles than arrays from HUR samples. As a result, MOF identified two distinct patterns in the occurrence of outlier arrays. These results demonstrate that this methodology is a valuable QA practice to identify questionable microarray data prior to downstream analysis.

  18. Adaptive skin detection based on online training

    Science.gov (United States)

    Zhang, Ming; Tang, Liang; Zhou, Jie; Rong, Gang

    2007-11-01

    Skin is a widely used cue for porn image classification. Most conventional methods are off-line training schemes. They usually use a fixed boundary to segment skin regions in the images and are effective only in restricted conditions: e.g. good lightness and unique human race. This paper presents an adaptive online training scheme for skin detection which can handle these tough cases. In our approach, skin detection is considered as a classification problem on Gaussian mixture model. For each image, human face is detected and the face color is used to establish a primary estimation of skin color distribution. Then an adaptive online training algorithm is used to find the real boundary between skin color and background color in current image. Experimental results on 450 images showed that the proposed method is more robust in general situations than the conventional ones.

  19. Antibody-based biological toxin detection

    Energy Technology Data Exchange (ETDEWEB)

    Menking, D.E.; Goode, M.T. [Army Edgewood Research, Development and Engineering Center, Aberdeen Proving Ground, MD (United States)

    1995-12-01

    Fiber optic evanescent fluorosensors are under investigation in our laboratory for the study of drug-receptor interactions for detection of threat agents and antibody-antigen interactions for detection of biological toxins. In a direct competition assay, antibodies against Cholera toxin, Staphylococcus Enterotoxin B or ricin were noncovalently immobilized on quartz fibers and probed with fluorescein isothiocyanate (FITC) - labeled toxins. In the indirect competition assay, Cholera toxin or Botulinum toxoid A was immobilized onto the fiber, followed by incubation in an antiserum or partially purified anti-toxin IgG. These were then probed with FITC-anti-IgG antibodies. Unlabeled toxins competed with labeled toxins or anti-toxin IgG in a dose dependent manner and the detection of the toxins was in the nanomolar range.

  20. Community Detection Based on Link Prediction Methods

    CERN Document Server

    Cheng, Hui-Min

    2016-01-01

    Community detection and link prediction are both of great significance in network analysis, which provide very valuable insights into topological structures of the network from diffrent perspectives. In this paper, we propose a novel community detection algorithm with inclusion of link prediction, motivated by the question whether link prediction can be devoted to improve the accuracy of community partition. For link prediction, we propose two novel indices to compute the similarity between each pair of nodes, one of which aims to add missing links, and the other tries to remove spurious edges. Extensive experiments are conducted on benchmark data sets, and the results of our proposed algorithm are compared with two classes of baselines. In conclusion, our proposed algorithm is competitive, revealing that link prediction does improve the precision of community detection.

  1. Memory detection 2.0: the first web-based memory detection test.

    Science.gov (United States)

    Kleinberg, Bennett; Verschuere, Bruno

    2015-01-01

    There is accumulating evidence that reaction times (RTs) can be used to detect recognition of critical (e.g., crime) information. A limitation of this research base is its reliance upon small samples (average n = 24), and indications of publication bias. To advance RT-based memory detection, we report upon the development of the first web-based memory detection test. Participants in this research (Study1: n = 255; Study2: n = 262) tried to hide 2 high salient (birthday, country of origin) and 2 low salient (favourite colour, favourite animal) autobiographical details. RTs allowed to detect concealed autobiographical information, and this, as predicted, more successfully so than error rates, and for high salient than for low salient items. While much remains to be learned, memory detection 2.0 seems to offer an interesting new platform to efficiently and validly conduct RT-based memory detection research.

  2. Memory detection 2.0: the first web-based memory detection test.

    Directory of Open Access Journals (Sweden)

    Bennett Kleinberg

    Full Text Available There is accumulating evidence that reaction times (RTs can be used to detect recognition of critical (e.g., crime information. A limitation of this research base is its reliance upon small samples (average n = 24, and indications of publication bias. To advance RT-based memory detection, we report upon the development of the first web-based memory detection test. Participants in this research (Study1: n = 255; Study2: n = 262 tried to hide 2 high salient (birthday, country of origin and 2 low salient (favourite colour, favourite animal autobiographical details. RTs allowed to detect concealed autobiographical information, and this, as predicted, more successfully so than error rates, and for high salient than for low salient items. While much remains to be learned, memory detection 2.0 seems to offer an interesting new platform to efficiently and validly conduct RT-based memory detection research.

  3. Image automatic mosaics based on contour phase correlation

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jing; HU Zhiping; LIU Zhitai; OU Zongying

    2007-01-01

    The image planar mosaics is studied,and an image automatic mosaics algorithm on the basis of contour phase correlation is proposed in this paper.To begin with,by taking into account mere translations and rotations between images,a contour phase correlation algorithm is used to realize the preliminary alignments of images,and the initial projective transformation matrices are obtained.Then,an optimization algorithm is used to optimize the initial projective transformation matrices,and complete the precise image mosaics.The contour phase correlation is an improvement on the conventional phase correlation in two aspects:First,the contours of images are extracted,and the phase correlation is applied to the contours of images instead of the whole original images;Second,when there are multiple peak values approximate to the maximum peak value in the δ function array,their corresponding translations can be regarded as candidate translations and calculated separately,and the best translation can be determined by the optimization of conformability of two images in the overlapping area.The running results show that the proposed algorithm can consistently yield high-quality mosaics,even in the cases of poor or differential lighting conditions,existences of minor rotations,and other complicated displacements between images.

  4. Coupled-cluster based basis sets for valence correlation calculations

    Science.gov (United States)

    Claudino, Daniel; Gargano, Ricardo; Bartlett, Rodney J.

    2016-03-01

    Novel basis sets are generated that target the description of valence correlation in atoms H through Ar. The new contraction coefficients are obtained according to the Atomic Natural Orbital (ANO) procedure from CCSD(T) (coupled-cluster singles and doubles with perturbative triples correction) density matrices starting from the primitive functions of Dunning et al. [J. Chem. Phys. 90, 1007 (1989); ibid. 98, 1358 (1993); ibid. 100, 2975 (1993)] (correlation consistent polarized valence X-tuple zeta, cc-pVXZ). The exponents of the primitive Gaussian functions are subject to uniform scaling in order to ensure satisfaction of the virial theorem for the corresponding atoms. These new sets, named ANO-VT-XZ (Atomic Natural Orbital Virial Theorem X-tuple Zeta), have the same number of contracted functions as their cc-pVXZ counterparts in each subshell. The performance of these basis sets is assessed by the evaluation of the contraction errors in four distinct computations: correlation energies in atoms, probing the density in different regions of space via (-3 ≤ n ≤ 3) in atoms, correlation energies in diatomic molecules, and the quality of fitting potential energy curves as measured by spectroscopic constants. All energy calculations with ANO-VT-QZ have contraction errors within "chemical accuracy" of 1 kcal/mol, which is not true for cc-pVQZ, suggesting some improvement compared to the correlation consistent series of Dunning and co-workers.

  5. Model Based Fault Detection in a Centrifugal Pump Application

    DEFF Research Database (Denmark)

    Kallesøe, Carsten; Cocquempot, Vincent; Izadi-Zamanabadi, Roozbeh

    2006-01-01

    A model based approach for fault detection in a centrifugal pump, driven by an induction motor, is proposed in this paper. The fault detection algorithm is derived using a combination of structural analysis, observer design and Analytical Redundancy Relation (ARR) design. Structural consideration...... is capable of detecting four different faults in the mechanical and hydraulic parts of the pump.......A model based approach for fault detection in a centrifugal pump, driven by an induction motor, is proposed in this paper. The fault detection algorithm is derived using a combination of structural analysis, observer design and Analytical Redundancy Relation (ARR) design. Structural considerations...

  6. A microfluidic based optical particle detection method

    Science.gov (United States)

    Dou, James; Chen, Lu; Nayyar, Rakesh; Aitchison, Stewart

    2012-03-01

    An optical particle detection and analysis method is presented. This method combines the capillary microfluidics, integrated optics and novel image acquisition and analysis algorithms to form the basis of a portable or handheld cytometer instrument. Experimental results provided shows the testing results are closely matched with conventional flow cytometer data.

  7. On Bitstream Based Edge Detection Techniques

    Science.gov (United States)

    2009-01-01

    Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing , Addison-Wesley...Longman Publishing Co., Inc., Boston, MA, USA, 2001. [6] William K Pratt, Digital image processing , Wiley, New York :, 1991. [7] Miguel Segui Prieto and...bitstream processing 1. INTRODUCTION Edge detection is a vital part of image processing , which is used for extracting important features from an image

  8. Flow-based detection of DNS tunnels

    NARCIS (Netherlands)

    Ellens, W.; Zuraniewski, P.W.; Sperotto, A.; Schotanus, H.A.; Mandjes, M.; Meeuwissen, H.B.

    2013-01-01

    DNS tunnels allow circumventing access and security policies in firewalled networks. Such a security breach can be misused for activities like free web browsing, but also for command & control traffic or cyber espionage, thus motivating the search for effective automated DNS tunnel detection techniq

  9. Effective analysis of cloud based intrusion detection system

    Directory of Open Access Journals (Sweden)

    Sanjay Ram

    2012-08-01

    Full Text Available The goal of IDS is to analyze events on the network and identify attacks. The increasing number of network security related incidents makes it necessary for organizations to actively protect their sensitive data with the installation of intrusion detection systems (IDS. People are paid more attention on intrusion detection which as an important computer network security technology. According to the development trend of intrusion detection, detecting all kinds of intrusions effectively requires a global view of the monitored network, Here, discuss about new intrusion detection mechanism based on cloud computing, which can make up for the deficiency of traditional intrusion detection, and proved to be great scalable.

  10. A Novel Chip-based Spectrophotometer for Online Detection

    Institute of Scientific and Technical Information of China (English)

    Haoyuan Cai; Min-Hsien Wu; Zheng Cui

    2006-01-01

    A chip-based spectrophotometer integrated with optical fiber is successfully demonstrated. Grade concentration of lactate solution flowed through the chip to perform an online detection. The response time (100s) and Limit of Detection (LOD,50mg/L) of the device were measured. This device shows comparable performance with traditional commercial instrument,while greatly decreases the sample requirement per detection and reduces the size of total system, introducing a novel method for real-time detection.

  11. A wavelet-based method to discriminate internal faults from inrush currents using correlation coefficient

    Energy Technology Data Exchange (ETDEWEB)

    Vahidi, B.; Ghaffarzadeh, N.; Hosseinian, S.H. [Dept. of Electrical Engineering, Amirkabir University of Technology, Tehran (Iran)

    2010-09-15

    In this paper a new method based on discrete wavelet transform and correlation coefficient is presented for digital differential protection. The algorithm includes offline and online operations. In offline operation, discrete wavelet transform is used to decompose typical three-phase differential currents for inrush current. Then an index is defined and computed. The index is based on the sum of the energy of detail coefficients at level 5 of three-phase differential currents at each half cycle. The online operation consists of capturing the three-phase differential currents using 10 kHz sampling rate, decomposing it by db1. Finally, the inrush current and internal fault is detected based on correlation coefficients of the computed index of pre-stored typical inrush current and a recorded indistinct signal. The effectiveness of the approach is tested using numerous inrush and internal fault currents. Simulations are used to confirm the aptness and the capability of the proposed method to discriminate inrush current from internal fault. (author)

  12. Sampling of general correlators in worm-algorithm based simulations

    Directory of Open Access Journals (Sweden)

    Tobias Rindlisbacher

    2016-08-01

    Full Text Available Using the complex ϕ4-model as a prototype for a system which is simulated by a worm algorithm, we show that not only the charged correlator 〈ϕ⁎(xϕ(y〉, but also more general correlators such as 〈|ϕ(x||ϕ(y|〉 or 〈arg⁡(ϕ(xarg⁡(ϕ(y〉, as well as condensates like 〈|ϕ|〉, can be measured at every step of the Monte Carlo evolution of the worm instead of on closed-worm configurations only. The method generalizes straightforwardly to other systems simulated by worms, such as spin or sigma models.

  13. Hybrid Collision Detection Algorithm based on Image Space

    Directory of Open Access Journals (Sweden)

    XueLi Shen

    2013-07-01

    Full Text Available Collision detection is an important application in the field of virtual reality, and efficiently completing collision detection has become the research focus. For the poorly real-time defect of collision detection, this paper has presented an algorithm based on the hybrid collision detection, detecting the potential collision object sets quickly with the mixed bounding volume hierarchy tree, and then using the streaming pattern collision detection algorithm to make an accurate detection. With the above methods, it can achieve the purpose of balancing load of the CPU and GPU and speeding up the detection rate. The experimental results show that compared with the classic Rapid algorithm, this algorithm can effectively improve the efficiency of collision detection.

  14. Experimental damage detection in a wind turbine blade model using principal components of response correlation functions

    Science.gov (United States)

    Hoell, S.; Omenzetter, P.

    2015-07-01

    The utilization of vibration signals for structural damage detection (SDD) is appealing due to the strong theoretical foundation of such approaches, ease of data acquisition and processing efficiency. Different methods are available for defining damage sensitive features (DSFs) based on vibrations, such as modal analysis or time series methods. The present paper proposes the use of partial autocorrelation coefficients of acceleration responses as DSFs. Principal component (PC) analysis is used to transform the initial DSFs to scores. The resulting scores from the healthy and damaged states are used to select the PCs which are most sensitive to damage. These are then used for making decisions about the structural state by means of statistical hypothesis testing conducted on the scores. The approach is applied to experiments with a laboratory scale wind turbine blade (WTB) made of glass-fibre reinforced epoxy composite. Damage is non-destructively simulated by attaching small masses and the WTB is excited with the help of an electrodynamic shaker using band-limited white noise. The SDD results for the selected subsets of PCs show a clear improvement of the detectability of early damages compared to other DSF selections.

  15. Effects of model-based physiological noise correction on default mode network anti-correlations and correlations.

    Science.gov (United States)

    Chang, Catie; Glover, Gary H

    2009-10-01

    Previous studies have reported that the spontaneous, resting-state time course of the default-mode network is negatively correlated with that of the "task-positive network", a collection of regions commonly recruited in demanding cognitive tasks. However, all studies of negative correlations between the default-mode and task-positive networks have employed some form of normalization or regression of the whole-brain average signal ("global signal"); these processing steps alter the time series of voxels in an uninterpretable manner as well as introduce spurious negative correlations. Thus, the extent of negative correlations with the default mode network without global signal removal has not been well characterized, and it is has recently been hypothesized that the apparent negative correlations in many of the task-positive regions could be artifactually induced by global signal pre-processing. The present study aimed to examine negative and positive correlations with the default-mode network when model-based corrections for respiratory and cardiac noise are applied in lieu of global signal removal. Physiological noise correction consisted of (1) removal of time-locked cardiac and respiratory artifacts using RETROICOR (Glover, G.H., Li, T.Q., Ress, D., 2000. Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR. Magn. Reson. Med. 44, 162-167), and (2) removal of low-frequency respiratory and heart rate variations by convolving these waveforms with pre-determined transfer functions (Birn et al., 2008; Chang et al., 2009) and projecting the resulting two signals out of the data. It is demonstrated that negative correlations between the default-mode network and regions of the task-positive network are present in the majority of individual subjects both with and without physiological noise correction. Physiological noise correction increased the spatial extent and magnitude of negative correlations, yielding negative

  16. Anomaly-based Network Intrusion Detection Methods

    Directory of Open Access Journals (Sweden)

    Pavel Nevlud

    2013-01-01

    Full Text Available The article deals with detection of network anomalies. Network anomalies include everything that is quite different from the normal operation. For detection of anomalies were used machine learning systems. Machine learning can be considered as a support or a limited type of artificial intelligence. A machine learning system usually starts with some knowledge and a corresponding knowledge organization so that it can interpret, analyse, and test the knowledge acquired. There are several machine learning techniques available. We tested Decision tree learning and Bayesian networks. The open source data-mining framework WEKA was the tool we used for testing the classify, cluster, association algorithms and for visualization of our results. The WEKA is a collection of machine learning algorithms for data mining tasks.

  17. Tests of Fit Based on the Correlation Coefficient

    Science.gov (United States)

    1990-10-04

    function. Regional Conference Series in Appl. Math., 9. Philadelphia: SIAM. 2. Gerlach, B., (1979). A consistent correlation-type goodness-of-fit test; with...the distribution of quadratic forms in normal variables. Biometrika, 48, 419-426. 4. Sarkadi, K., (1975). The consistency of the Shapiro- Francia test

  18. CHAOTIC CONTROL OF NONLINEAR SYSTEMS BASED ON IMPROVED CORRELATIVITY

    Institute of Scientific and Technical Information of China (English)

    Zhou Xiaoan; Zhang Jihong

    2003-01-01

    Chaotic sequences are basically ergodic random sequences. By improving correlativity of a chaotic signal, the chaotic dynamic system can be controlled to converge to its equilibrium point and, more significantly, to its multi-periodic orbits. Mathematical theory analysis is carried out and some computer simulation results are provided to support such controllability of the chaotic Henon system and the discrete coupled map lattice.

  19. Automatic hearing loss detection system based on auditory brainstem response

    Energy Technology Data Exchange (ETDEWEB)

    Aldonate, J; Mercuri, C; Reta, J; Biurrun, J; Bonell, C; Gentiletti, G; Escobar, S; Acevedo, R [Laboratorio de Ingenieria en Rehabilitacion e Investigaciones Neuromusculares y Sensoriales (Argentina); Facultad de Ingenieria, Universidad Nacional de Entre Rios, Ruta 11 - Km 10, Oro Verde, Entre Rios (Argentina)

    2007-11-15

    Hearing loss is one of the pathologies with the highest prevalence in newborns. If it is not detected in time, it can affect the nervous system and cause problems in speech, language and cognitive development. The recommended methods for early detection are based on otoacoustic emissions (OAE) and/or auditory brainstem response (ABR). In this work, the design and implementation of an automated system based on ABR to detect hearing loss in newborns is presented. Preliminary evaluation in adults was satisfactory.

  20. Method for detecting software anomalies based on recurrence plot analysis

    OpenAIRE

    Michał Mosdorf

    2012-01-01

    Presented paper evaluates method for detecting software anomalies based on recurrence plot analysis of trace log generated by software execution. Described method for detecting software anomalies is based on windowed recurrence quantification analysis for selected measures (e.g. Recurrence rate - RR or Determinism - DET). Initial results show that proposed method is useful in detecting silent software anomalies that do not result in typical crashes (e.g. exceptions).

  1. Method for detecting software anomalies based on recurrence plot analysis

    Directory of Open Access Journals (Sweden)

    Michał Mosdorf

    2012-03-01

    Full Text Available Presented paper evaluates method for detecting software anomalies based on recurrence plot analysis of trace log generated by software execution. Described method for detecting software anomalies is based on windowed recurrence quantification analysis for selected measures (e.g. Recurrence rate - RR or Determinism - DET. Initial results show that proposed method is useful in detecting silent software anomalies that do not result in typical crashes (e.g. exceptions.

  2. Automatic hearing loss detection system based on auditory brainstem response

    Science.gov (United States)

    Aldonate, J.; Mercuri, C.; Reta, J.; Biurrun, J.; Bonell, C.; Gentiletti, G.; Escobar, S.; Acevedo, R.

    2007-11-01

    Hearing loss is one of the pathologies with the highest prevalence in newborns. If it is not detected in time, it can affect the nervous system and cause problems in speech, language and cognitive development. The recommended methods for early detection are based on otoacoustic emissions (OAE) and/or auditory brainstem response (ABR). In this work, the design and implementation of an automated system based on ABR to detect hearing loss in newborns is presented. Preliminary evaluation in adults was satisfactory.

  3. Poseidon: a 2-tier anomaly-based intrusion detection system

    NARCIS (Netherlands)

    Bolzoni, Damiano; Zambon, Emmanuele; Etalle, Sandro; Hartel, Pieter

    2005-01-01

    We present Poseidon, a new anomaly based intrusion detection system. Poseidon is payload-based, and presents a two-tier architecture: the first stage consists of a Self-Organizing Map, while the second one is a modified PAYL system. Our benchmarks on the 1999 DARPA data set show a higher detection r

  4. Parkinson's disease detection based on dysphonia measurements

    Science.gov (United States)

    Lahmiri, Salim

    2017-04-01

    Assessing dysphonic symptoms is a noninvasive and effective approach to detect Parkinson's disease (PD) in patients. The main purpose of this study is to investigate the effect of different dysphonia measurements on PD detection by support vector machine (SVM). Seven categories of dysphonia measurements are considered. Experimental results from ten-fold cross-validation technique demonstrate that vocal fundamental frequency statistics yield the highest accuracy of 88 % ± 0.04. When all dysphonia measurements are employed, the SVM classifier achieves 94 % ± 0.03 accuracy. A refinement of the original patterns space by removing dysphonia measurements with similar variation across healthy and PD subjects allows achieving 97.03 % ± 0.03 accuracy. The latter performance is larger than what is reported in the literature on the same dataset with ten-fold cross-validation technique. Finally, it was found that measures of ratio of noise to tonal components in the voice are the most suitable dysphonic symptoms to detect PD subjects as they achieve 99.64 % ± 0.01 specificity. This finding is highly promising for understanding PD symptoms.

  5. Goal-dependent modulation of declarative memory: neural correlates of temporal recency decisions and novelty detection.

    Science.gov (United States)

    Dudukovic, Nicole M; Wagner, Anthony D

    2007-06-18

    Declarative memory allows an organism to discriminate between previously encountered and novel items, and to place past encounters in time. Numerous imaging studies have investigated the neural processes supporting item recognition, whereas few have examined retrieval of temporal information. In the present study, functional magnetic resonance imaging (fMRI) was conducted while subjects engaged in temporal recency and item novelty decisions. Subjects encountered three-alternative forced-choice retrieval trials, each consisting of two words from a preceding study phase and one novel word, and were instructed to either identify the novel item (Novelty trials) or the more recently presented study item (Recency trials). Relative to correct Novelty decisions, correct Recency decisions elicited greater activation in a network of left-lateralized regions, including frontopolar and dorsolateral prefrontal cortex and intraparietal sulcus. A conjunction analysis revealed that these left-lateralized regions overlapped with those previously observed to be engaged during source recollection versus novelty detection, suggesting that during Recency trials subjects attempted to recollect event details. Consistent with this interpretation, correct Recency decisions activated posterior hippocampus and parahippocampal cortex, whereas incorrect Recency decisions elicited greater anterior cingulate activation. The magnitude of this latter effect positively correlated with activation in right dorsolateral prefrontal cortex. Finally, correct Novelty decisions activated the anterior medial temporal lobe to a greater extent than did correct Recency decisions, suggesting that medial temporal novelty responses are not obligatory but rather can be modulated by the goal-directed allocation of attention. Collectively, these findings advance understanding of how subjects strategically engage frontal and parietal mechanisms in the service of attempting to remember the temporal order of events

  6. Preliminary measurement results of biotinylated BSA detection of a low cost optical cavity based biosensor using differential detection

    Science.gov (United States)

    Cowles, Peter; Joy, Cody; Bujana, Antonio; Rho, DongGee; Kim, Seunghyun

    2016-03-01

    We report an optical cavity based biosensor using a novel differential detection method for point-of-care applications. Two laser diodes allow for multiplexing capability along with the ability to enhance the responsivity using differential detection. The laser wavelengths are chosen so that the optical intensities of two lasers change monotonically with opposite slopes upon the adsorption of desired biomarkers. The cavity width, PMMA thickness, and silver thickness have been optimized to achieve a large change in scaled differential value. We chose biotinylated BSA detection with Avidin as a receptor molecule to demonstrate the proposed design. Avidin is attached directly to the PMMA layer by physisorption. Then, biotinylated BSA is introduced to the sample and the intensities of the laser diodes are measured by a sCMOS camera. A change in the scaled differential value will correlate to the binding of biotinylated BSA. In this presentation, we will discuss simulation results, fabrication procedures, and preliminary measurement results.

  7. Analysis of quantitative EEG detection results of patients with Alzheimerˊs disease and its correlation with serum index

    Institute of Scientific and Technical Information of China (English)

    Ming-Mei Sun; Fu-Ying Jiao

    2015-01-01

    Objective: To study the quantitative EEG detection results of patients with Alzheimer's disease and its correlation with serum index. Methods: 50 patients with Alzheimer's disease diagnosed in our hospital from May 2012 to August 2014 were enrolled in the observation group; healthy people who received physical examination in our hospital during the same period were enrolled in the control group. Then quantitative EEG detection was conducted and serum was collected to detect contents of inflammatory factors and serum neuron injury related molecules. Results: (1)quantitative EEG: ( +θ)/( +β) ratios of whole brain, frontal lobe, temporal lobe, parietal lobe and occipital lobe of the observation group were higher than those of the control group; (2)inflammatory factors: serum TNF- , IL-1β, IL-6, MMP2, MMP9 and ET contents of the observation group were higher than those of the control group and were positively correlated with ( +θ)/( +β) ratios;(3) neuron injury related molecules: serum Hcy, Aβ1-42, Tau, Glu, Aap and Gly contents of the observation group were higher than those of the control group and were positively correlated with ( +θ)/( +β) ratios. Conclusion: ( +θ)/( +β) ratios of quantitative EEG detection of patients with Alzheimer's disease abnormally increase and have good correlation with abnormality of serum inflammatory factors and neuron injury related molecules; it’s an ideal method to evaluate the severity degree ofAlzheimer's disease.

  8. Gaussian Belief Propagation Based Multiuser Detection

    CERN Document Server

    Bickson, Danny; Shental, Ori; Siegel, Paul H; Wolf, Jack K

    2008-01-01

    In this work, we present a novel construction for solving the linear multiuser detection problem using the Gaussian Belief Propagation algorithm. Our algorithm yields an efficient, iterative and distributed implementation of the MMSE detector. We compare our algorithm's performance to a recent result and show an improved memory consumption, reduced computation steps and a reduction in the number of sent messages. We prove that recent work by Montanari et al. is an instance of our general algorithm, providing new convergence results for both algorithms.

  9. Malfunction diagnosis of sensors based on correlation of measurements

    Science.gov (United States)

    Lu, Wei; Teng, Jun; Wen, Runfa; Zhu, Jiayi; Li, Chao

    2017-02-01

    Structural health monitoring (SHM) is a type of on-site characterization of a real-world full-scale structure that is subjected to the real-world load cases. The fundamental element of SHM is the structural response measurements by sensors, the reliability of which is significant for safety assessment and other SHM applications. The paper proposed a method to diagnosis the fault in sensors using the correlation of measurements. The correlation of the variations of the measurements is examined using the sliding time windows, which is the principle to determine the fault in the sensors. The strain measurements from the SHM system of a real world structure, Shenzhen Bay Stadium, are performed to simulate the faults in sensors and to verify the effectiveness of the proposed method.

  10. NIRS-BASED CORTICAL ACTIVATION ANALYSIS BY TEMPORAL CROSS CORRELATION

    Directory of Open Access Journals (Sweden)

    Raul Fernandez-Rojas

    2016-02-01

    Full Text Available In this study we present a method of signal processing to determine dominant channels in near infrared spectroscopy (NIRS. To compare measuring channels and identify delays between them, cross correlation is computed. Furthermore, to find out possible dominant channels, a visual inspection was performed. The outcomes demonstrated that the visual inspection exhibited evoked-related activations in the primary somatosensory cortex (S1 after stimulation which is consistent with comparable studies and the cross correlation study discovered dominant channels on both cerebral hemispheres. The analysis also showed a relationship between dominant channels and adjacent channels. For that reason, our results present a new method to identify dominant regions in the cerebral cortex using near-infrared spectroscopy. These findings have also implications in the decrease of channels by eliminating irrelevant channels for the experiment.

  11. GLRT Based Anomaly Detection for Sensor Network Monitoring

    KAUST Repository

    Harrou, Fouzi

    2015-12-07

    Proper operation of antenna arrays requires continuously monitoring their performances. When a fault occurs in an antenna array, the radiation pattern changes and can significantly deviate from the desired design performance specifications. In this paper, the problem of fault detection in linear antenna arrays is addressed within a statistical framework. Specifically, a statistical fault detection method based on the generalized likelihood ratio (GLR) principle is utilized for detecting potential faults in linear antenna arrays. The proposed method relies on detecting deviations in the radiation pattern of the monitored array with respect to a reference (fault-free) one. To assess the abilities of the GLR based fault detection method, three case studies involving different types of faults have been performed. The simulation results clearly illustrate the effectiveness of the GLR-based fault detection method in monitoring the performance of linear antenna arrays.

  12. A Vehicle Detection Algorithm Based on Deep Belief Network

    Directory of Open Access Journals (Sweden)

    Hai Wang

    2014-01-01

    Full Text Available Vision based vehicle detection is a critical technology that plays an important role in not only vehicle active safety but also road video surveillance application. Traditional shallow model based vehicle detection algorithm still cannot meet the requirement of accurate vehicle detection in these applications. In this work, a novel deep learning based vehicle detection algorithm with 2D deep belief network (2D-DBN is proposed. In the algorithm, the proposed 2D-DBN architecture uses second-order planes instead of first-order vector as input and uses bilinear projection for retaining discriminative information so as to determine the size of the deep architecture which enhances the success rate of vehicle detection. On-road experimental results demonstrate that the algorithm performs better than state-of-the-art vehicle detection algorithm in testing data sets.

  13. Extracting Coherent Information from Noise Based Correlation Processing

    Science.gov (United States)

    2015-09-30

    LONG-TERM GOALS The goal of this research is to establish methodologies to utilize ambient noise in the ocean and to determine what scenarios...None PUBLICATIONS [1] “ Monitoring deep-ocean temperatures using acoustic ambinet noise,”K. W. Woolfe, S. Lani, K.G. Sabra, W. A. Kuperman...Geophys. Res. Lett., 42,2878–2884, doi:10.1002/2015GL063438 (2015). [2] “Optimized extraction of coherent arrivals from ambient noise correlations in

  14. CHAOTIC CONTROL OF NONLINEAR SYSTEMS BASED ON IMPROVED CORRELATIVITY

    Institute of Scientific and Technical Information of China (English)

    ZhouZiaoan; ZhangJihong

    2003-01-01

    Chaotic sequences are basically ergodic random esquences.By improving correlativity of a chaotic signal,the chaotic dynamic system can be controlled to converge to its equilibrium point and,more significantly,to its multi-periodic orbits.Mathematical theory analysis is carried out and some computer simulation results are provided to support such controllability of the chaotic Henon system and the discrete coupled map lattice.

  15. Chord Recognition Based on Temporal Correlation Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Zhongyang Rao

    2016-05-01

    Full Text Available In this paper, we propose a method called temporal correlation support vector machine (TCSVM for automatic major-minor chord recognition in audio music. We first use robust principal component analysis to separate the singing voice from the music to reduce the influence of the singing voice and consider the temporal correlations of the chord features. Using robust principal component analysis, we expect the low-rank component of the spectrogram matrix to contain the musical accompaniment and the sparse component to contain the vocal signals. Then, we extract a new logarithmic pitch class profile (LPCP feature called enhanced LPCP from the low-rank part. To exploit the temporal correlation among the LPCP features of chords, we propose an improved support vector machine algorithm called TCSVM. We perform this study using the MIREX’09 (Music Information Retrieval Evaluation eXchange Audio Chord Estimation dataset. Furthermore, we conduct comprehensive experiments using different pitch class profile feature vectors to examine the performance of TCSVM. The results of our method are comparable to the state-of-the-art methods that entered the MIREX in 2013 and 2014 for the MIREX’09 Audio Chord Estimation task dataset.

  16. Multi-features Based Approach for Moving Shadow Detection

    Institute of Scientific and Technical Information of China (English)

    ZHOU Ning; ZHOU Man-li; XU Yi-ping; FANG Bao-hong

    2004-01-01

    In the video-based surveillance application, moving shadows can affect the correct localization and detection of moving objects. This paper aims to present a method for shadow detection and suppression used for moving visual object detection. The major novelty of the shadow suppression is the integration of several features including photometric invariant color feature, motion edge feature, and spatial feature etc. By modifying process for false shadow detected, the averaging detection rate of moving object reaches above 90% in the test of Hall-Monitor sequence.

  17. A fast and accurate FPGA based QRS detection system.

    Science.gov (United States)

    Shukla, Ashish; Macchiarulo, Luca

    2008-01-01

    An accurate Field Programmable Gate Array (FPGA) based ECG Analysis system is described in this paper. The design, based on a popular software based QRS detection algorithm, calculates the threshold value for the next peak detection cycle, from the median of eight previously detected peaks. The hardware design has accuracy in excess of 96% in detecting the beats correctly when tested with a subset of five 30 minute data records obtained from the MIT-BIH Arrhythmia database. The design, implemented using a proprietary design tool (System Generator), is an extension of our previous work and uses 76% resources available in a small-sized FPGA device (Xilinx Spartan xc3s500), has a higher detection accuracy as compared to our previous design and takes almost half the analysis time in comparison to software based approach.

  18. P2P worm detection based on application identification

    Institute of Scientific and Technical Information of China (English)

    XIA Chunhe; SHI Yunping; LI Xiaojian; GAO Wei

    2007-01-01

    P2P worm exploits common vulnerabilities and spreads through peer-to-peer networks.Despite being recognized as a potential and deadly threat to the Internet recently,few relevant countermeasures are found in extant literature.Once it breaks out,a P2P worm could result in unpredictable losses.Based on propagation characteristics of the worm,this paper presents a detection method called PWD (P2P Worm Detection),which is designed based on application identification and unknown worm detection.Simulation result and LAN-environment experiment result both indicate that PWD is an effective method to detect and block P2P worms.

  19. Color pattern recognition based on the joint fractional Fourier transform correlator

    Institute of Scientific and Technical Information of China (English)

    Weimin Jin; Yupei Zhang

    2007-01-01

    A new system of multi-channel single-output joint fractional Fourier transform correlator (JFRTC) for color pattern recognition is proposed based on the conventional system of multi-channel single-output joint transform correlator (JTC). The theoretical analysis and optical experiments are performed. With this method, one can obtain three correlation peaks at the output plane which show a pair of desired cross-correlation peaks and one auto-correlation peak. In comparison, the conventional system leads to more correlation peaks playing a noise role in color pattern recognition.

  20. Correlation technique and least square support vector machine combine for frequency domain based ECG beat classification.

    Science.gov (United States)

    Dutta, Saibal; Chatterjee, Amitava; Munshi, Sugata

    2010-12-01

    The present work proposes the development of an automated medical diagnostic tool that can classify ECG beats. This is considered an important problem as accurate, timely detection of cardiac arrhythmia can help to provide proper medical attention to cure/reduce the ailment. The proposed scheme utilizes a cross-correlation based approach where the cross-spectral density information in frequency domain is used to extract suitable features. A least square support vector machine (LS-SVM) classifier is developed utilizing the features so that the ECG beats are classified into three categories: normal beats, PVC beats and other beats. This three-class classification scheme is developed utilizing a small training dataset and tested with an enormous testing dataset to show the generalization capability of the scheme. The scheme, when employed for 40 files in the MIT/BIH arrhythmia database, could produce high classification accuracy in the range 95.51-96.12% and could outperform several competing algorithms.

  1. Minimum variance imaging based on correlation analysis of Lamb wave signals.

    Science.gov (United States)

    Hua, Jiadong; Lin, Jing; Zeng, Liang; Luo, Zhi

    2016-08-01

    In Lamb wave imaging, MVDR (minimum variance distortionless response) is a promising approach for the detection and monitoring of large areas with sparse transducer network. Previous studies in MVDR use signal amplitude as the input damage feature, and the imaging performance is closely related to the evaluation accuracy of the scattering characteristic. However, scattering characteristic is highly dependent on damage parameters (e.g. type, orientation and size), which are unknown beforehand. The evaluation error can degrade imaging performance severely. In this study, a more reliable damage feature, LSCC (local signal correlation coefficient), is established to replace signal amplitude. In comparison with signal amplitude, one attractive feature of LSCC is its independence of damage parameters. Therefore, LSCC model in the transducer network could be accurately evaluated, the imaging performance is improved subsequently. Both theoretical analysis and experimental investigation are given to validate the effectiveness of the LSCC-based MVDR algorithm in improving imaging performance.

  2. Sequential backbone assignment based on dipolar amide-to-amide correlation experiments.

    Science.gov (United States)

    Xiang, ShengQi; Grohe, Kristof; Rovó, Petra; Vasa, Suresh Kumar; Giller, Karin; Becker, Stefan; Linser, Rasmus

    2015-07-01

    Proton detection in solid-state NMR has seen a tremendous increase in popularity in the last years. New experimental techniques allow to exploit protons as an additional source of information on structure, dynamics, and protein interactions with their surroundings. In addition, sensitivity is mostly improved and ambiguity in assignment experiments reduced. We show here that, in the solid state, sequential amide-to-amide correlations turn out to be an excellent, complementary way to exploit amide shifts for unambiguous backbone assignment. For a general assessment, we compare amide-to-amide experiments with the more common (13)C-shift-based methods. Exploiting efficient CP magnetization transfers rather than less efficient INEPT periods, our results suggest that the approach is very feasible for solid-state NMR.

  3. Sequential backbone assignment based on dipolar amide-to-amide correlation experiments

    Energy Technology Data Exchange (ETDEWEB)

    Xiang, ShengQi; Grohe, Kristof; Rovó, Petra; Vasa, Suresh Kumar; Giller, Karin; Becker, Stefan; Linser, Rasmus, E-mail: rali@nmr.mpibpc.mpg.de [Max Planck Institute for Biophysical Chemistry, Department for NMR-Based Structural Biology (Germany)

    2015-07-15

    Proton detection in solid-state NMR has seen a tremendous increase in popularity in the last years. New experimental techniques allow to exploit protons as an additional source of information on structure, dynamics, and protein interactions with their surroundings. In addition, sensitivity is mostly improved and ambiguity in assignment experiments reduced. We show here that, in the solid state, sequential amide-to-amide correlations turn out to be an excellent, complementary way to exploit amide shifts for unambiguous backbone assignment. For a general assessment, we compare amide-to-amide experiments with the more common {sup 13}C-shift-based methods. Exploiting efficient CP magnetization transfers rather than less efficient INEPT periods, our results suggest that the approach is very feasible for solid-state NMR.

  4. Feature-based alert correlation in security systems using self organizing maps

    Science.gov (United States)

    Kumar, Munesh; Siddique, Shoaib; Noor, Humera

    2009-04-01

    The security of the networks has been an important concern for any organization. This is especially important for the defense sector as to get unauthorized access to the sensitive information of an organization has been the prime desire for cyber criminals. Many network security techniques like Firewall, VPN Concentrator etc. are deployed at the perimeter of network to deal with attack(s) that occur(s) from exterior of network. But any vulnerability that causes to penetrate the network's perimeter of defense, can exploit the entire network. To deal with such vulnerabilities a system has been evolved with the purpose of generating an alert for any malicious activity triggered against the network and its resources, termed as Intrusion Detection System (IDS). The traditional IDS have still some deficiencies like generating large number of alerts, containing both true and false one etc. By automatically classifying (correlating) various alerts, the high-level analysis of the security status of network can be identified and the job of network security administrator becomes much easier. In this paper we propose to utilize Self Organizing Maps (SOM); an Artificial Neural Network for correlating large amount of logged intrusion alerts based on generic features such as Source/Destination IP Addresses, Port No, Signature ID etc. The different ways in which alerts can be correlated by Artificial Intelligence techniques are also discussed. . We've shown that the strategy described in the paper improves the efficiency of IDS by better correlating the alerts, leading to reduced false positives and increased competence of network administrator.

  5. Comparison of Subset-Based Local and Finite Element-Based Global Digital Image Correlation

    KAUST Repository

    Pan, Bing

    2015-02-12

    Digital image correlation (DIC) techniques require an image matching algorithm to register the same physical points represented in different images. Subset-based local DIC and finite element-based (FE-based) global DIC are the two primary image matching methods that have been extensively investigated and regularly used in the field of experimental mechanics. Due to its straightforward implementation and high efficiency, subset-based local DIC has been used in almost all commercial DIC packages. However, it is argued by some researchers that FE-based global DIC offers better accuracy because of the enforced continuity between element nodes. We propose a detailed performance comparison between these different DIC algorithms both in terms of measurement accuracy and computational efficiency. Then, by measuring displacements of the same calculation points using the same calculation algorithms (e.g., correlation criterion, initial guess estimation, subpixel interpolation, optimization algorithm and convergence conditions) and identical calculation parameters (e.g., subset or element size), the performances of subset-based local DIC and two FE-based global DIC approaches are carefully compared in terms of measurement error and computational efficiency using both numerical tests and real experiments. A detailed examination of the experimental results reveals that, when subset (element) size is not very small and the local deformation within a subset (element) can be well approximated by the shape function used, standard subset-based local DIC approach not only provides better results in measured displacements, but also demonstrates much higher computation efficiency. However, several special merits of FE-based global DIC approaches are indicated.

  6. Large range rotation distortion measurement for remote sensing images based on volume holographic optical correlator

    Science.gov (United States)

    Zheng, Tianxiang; Cao, Liangcai; Zhao, Tian; He, Qingsheng; Jin, Guofan

    2012-10-01

    Volume holographic optical correlator can compute the correlation results between images at a super-high speed. In the application of remote imaging processing such as scene matching, 6,000 template images have been angularly multiplexed in the photorefractive crystal and the 6,000 parallel processing channels are achieved. In order to detect the correlation pattern of images precisely and distinguishingly, an on-off pixel inverted technology of images is proposed. It can fully use the CCD's linear range for detection and expand the normalized correlation value differences as the target image rotates. Due to the natural characteristics of the remote sensing images, the statistical formulas between the rotation distortions and the correlation results can be estimated. The rotation distortion components can be estimated by curve fitting method with the data of correlation results. The intensities of the correlation spots are related to the distortion between the two images. The rotation distortion could be derived from the intensities in the post processing procedure. With 18 rotations of the input image and sending them into the volume holographic system, the detection of the rotation variation in the range of 180° can be fulfilled. So the large range rotation distortion detection is firstly realized. It offers a fast, large range rotation measurement method for image distortions.

  7. Model Based Incipient Fault Detection for Gear Drives

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper presents the method of model based incipient fault detection for gear drives,this method is based on parity space method. It can generate the robust residual that is maximally sensitive to the fault caused by the change of the parameters. The example of simulation shows the application of the method, and the residual waves have different characteristics due to different parameter changes; one can detect and isolate the fault based on the different characteristics.

  8. Muon Detection Based on a Hadronic Calorimeter

    CERN Document Server

    Ciodaro, T; Abreu, R; Achenbach, R; Adragna, P; Aharrouche, M; Aielli, G; Al-Shabibi, A; Aleksandrov, I; Alexandrov, E; Aloisio, A; Alviggi, M G; Amorim, A; Amram, N; Andrei, V; Anduaga, X; Angelaszek, D; Anjos, N; Annovi, A; Antonelli, S; Anulli, F; Apolle, R; Aracena, I; Ask, S; Åsman, B; Avolio, G; Baak, M; Backes, M; Backlund, S; Badescu, E; Baines, J; Ballestrero, S; Banerjee, S; Bansil, H S; Barnett, B M; Bartoldus, R; Bartsch, V; Batraneanu, S; Battaglia, A; Bauss, B; Beauchemin, P; Beck, H P; Bee, C; Begel, M; Behera, P K; Bell, P; Bell, W H; Bellagamba, L; Bellomo, M; Ben Ami, S; Bendel, M; Benhammou, Y; Benslama, K; Berge, D; Bernius, C; Berry, T; Bianco, M; Biglietti, M; Blair, R E; Bogaerts, A; Bohm, C; Boisvert, V; Bold, T; Bondioli, M; Borer, C; Boscherini, D; Bosman, M; Bossini, E; Boveia, A; Bracinik, J; Brandt, A G; Brawn, I P; Brelier, B; Brenner, R; Bressler, S; Brock, R; Brooks, W K; Brown, G; Brunet, S; Bruni, A; Bruni, G; Bucci, F; Buda, S; Burckhart-Chromek, D; Buscher, V; Buttinger, W; Calvet, S; Camarri, P; Campanelli, M; Canale, V; Canelli, F; Capasso, L; Caprini, M; Caracinha, D; Caramarcu, C; Cardarelli, R; Carlino, G; Casadei, D; Casado, M P; Cattani, G; Cerri, A; Cerrito, L; Chapleau, B; Childers, J T; Chiodini, G; Christidi, I; Ciapetti, G; Cimino, D; Ciobotaru, M; Coccaro, A; Cogan, J; Collins, N J; Conde Muino, P; Conidi, C; Conventi, F; Corradi, M; Corso-Radu, A; Coura Torres, R; Cranmer, K; Crescioli, F; Crone, G; Crupi, R; Cuenca Almenar, C; Cummings, J T; Curtis, C J; Czyczula, Z; Dam, M; Damazio, D; Dao, V; Darlea, G L; Davis, A O; De Asmundis, R; De Pedis, D; De Santo, A; de Seixas, J M; Degenhardt, J; Della Pietra, M; Della Volpe, D; Demers, S; Demirkoz, B; Di Ciaccio, A; Di Mattia, A; Di Nardo, R; Di Simone, A; Diaz, M A; Dietzsch, T A; Dionisi, C; Dobson, E; Dobson, M; dos Anjos, A; Dotti, A; Dova, M T; Drake, G; Dufour, M-A; Dumitru, I; Eckweiler, S; Ehrenfeld, W; Eifert, T; Eisenhandler, E; Ellis, K V; Ellis, N; Emeliyanov, D; Enoque Ferreira de Lima, D; Ermoline, Y; Ernst, J; Etzion, E; Falciano, S; Farrington, S; Farthouat, P; Faulkner , P J W; Fedorko, W; Fellmann, D; Feng, E; Ferrag, S; Ferrari, R; Ferrer, M L; Fiorini, L; Fischer, G; Flowerdew, M J; Fonseca Martin, T; Francis, D; Fratina, S; French, S T; Front, D; Fukunaga, C; Gadomski, S; Garelli, N; Garitaonandia Elejabarrieta, H; Gaudio, G; Gee, C N P; George, S; Giagu, S; Giannetti, P; Gillman, A R; Giorgi, M; Giunta, M; Giusti, P; Goebel, M; Gonçalo, R; Gonzalez Silva, L; Göringer, C; Gorini, B; Gorini, E; Grabowska-Bold, I; Green, B; Groll, M; Guida, A; Guler, H; Haas, S; Hadavand, H; Hadley, D R; Haller, J; Hamilton, A; Hanke, P; Hansen, J R; Hasegawa, S; Hasegawa, Y; Hauser, R; Hayakawa, T; Hayden, D; Head, S; Heim, S; Hellman, S; Henke, M; Hershenhorn, A; Hidvégi, A; Hillert, S; Hillier, S J; Hirayama, S; Hod, N; Hoffmann, D; Hong, T M; Hryn'ova, T; Huston, J; Iacobucci, G; Igonkina, O; Ikeno, M; Ilchenko, Y; Ishikawa, A; Ishino, M; Iwasaki, H; Izzo, V; Jez, P; Jimenez Otero, S; Johansen, M; Johns, K; Jones, G; Joos, M; Kadlecik, P; Kajomovitz, E; Kanaya, N; Kanega, F; Kanno, T; Kapliy, A; Kaushik, V; Kawagoe, K; Kawamoto, T; Kazarov, A; Kehoe, R; Kessoku, K; Khomich, A; Khoriauli, G; Kieft, G; Kirk, J; Klemetti, M; Klofver, P; Klous, S; Kluge, E-E; Kobayashi, T; Koeneke, K; Koletsou, I; Koll, J D; Kolos, S; Kono, T; Konoplich, R; Konstantinidis, N; Korcyl, K; Kordas, K; Kotov, V; Kowalewski, R V; Krasznahorkay, A; Kraus, J; Kreisel, A; Kubota, T; Kugel, A; Kunkle, J; Kurashige, H; Kuze, M; Kwee, R; Laforge, B; Landon, M; Lane, J; Lankford, A J; Laranjeira Lima, S M; Larner, A; Leahu, L; Lehmann Miotto, G; Lei, X; Lellouch, D; Levinson, L; Li, S; Liberti, B; Lilley, J N; Linnemann, J T; Lipeles, E; Lohse, T; Losada, M; Lowe, A; Luci, C; Luminari, L; Lundberg, J; Lupu, N; Machado Miguéns, J; Mackeprang, R; Maettig, S; Magnoni, L; Maiani, C; Maltrana, D; Mangeard, P-S; Männer, R; Mapelli, L; Marchese, F; Marino, C; Martin, B; Martin, B T; Martin, T; Martyniuk, A; Marzano, F; Masik, J; Mastrandrea, P; Matsushita, T; McCarn, A; Mechnich, J; Medinnis, M; Meier, K; Melachrinos, C; Mendoza Nava, L M; Merola, L; Messina, A; Meyer, C P; Middleton, R P; Mikenberg, G; Mills, C M; Mincer, A; Mineev, M; Misiejuk, A; Moa, T; Moenig, K; Monk, J; Monticelli, F; Mora Herrera, C; Morettini, P; Morris, J D; Müller, F; Munwes, Y; Murillo Garcia, R; Nagano, K; Nagasaka, Y; Navarro, G A; Negri, A; Nelson, S; Nemethy, P; Neubauer, M S; Neusiedl, A; Newman, P; Nisati, A; Nomoto, H; Nozaki, M; Nozicka, M; Nurse, E; Ochando, C; Ochi, A; Oda, S; Oh, A; Ohm, C; Okumura, Y; Olivito, D; Omachi, C; Osculati, B; Oshita, H; Ospanov, R; Owen, M A; Özcan, V E; Ozone, K; Padilla, C; Panes, B; Panikashvili, N; Paramonov, A; Parodi, F; Pasqualucci, E; Pastore, F; Patricelli, S; Pauly, T; Perera, V J O; Perez, E; Petcu, M; Petersen, B A; Petersen, J; Petrolo, E; Phan, A; Piegaia, R; Pilkington, A; Pinder, A; Poddar, S; Polini, A; Pope, B G; Potter, C T; Primavera, M; Prokoshin, F; Ptacek, E; Qian, W; Quinonez, F; Rajagopalan, S; Ramos Dos Santos Neves, R; Reinherz-Aronis, E; Reinsch, A; Renkel, P; Rescigno, M; Rieke, S; Riu, I; Robertson, S H; Robinson, M; Rodriguez, D; Roich, A; Romeo, G; Romero, R; Roos, L; Ruiz Martinez, A; Ryabov, Y; Ryan, P; Saavedra, A; Safai Tehrani, F; Sakamoto, H; Salamanna, G; Salamon, A; Saland, J; Salnikov, A; Salvatore, F; Sankey, D P C; Santamarina, C; Santonico, R; Sarkisyan-Grinbaum, E; Sasaki, O; Savu, D; Scannicchio, D A; Schäfer, U; Scharf, V L; Scheirich, D; Schiavi, C; Schlereth, J; Schmitt, K; Schroder, C; Schroer, N; Schultz-Coulon, H-C; Schwienhorst, R; Sekhniaidze, G; Sfyrla, A; Shamim, M; Sherman, D; Shimojima, M; Shochet, M; Shooltz, D; Sidoti, A; Silbert, O; Silverstein, S; Sinev, N; Siragusa, G; Sivoklokov, S; Sjoen, R; Sjölin, J; Slagle, K; Sloper, J E; Smith, B C; Soffer, A; Soloviev, I; Spagnolo, S; Spiwoks, R; Staley, R J; Stamen, R; Stancu, S; Steinberg, P; Stelzer, J; Stockton, M C; Straessner, A; Strauss, E A; Strom, D; Su, D; Sugaya, Y; Sugimoto, T; Sushkov, S; Sutton, M R; Suzuki, Y; Taffard, A; Taiblum, N; Takahashi, Y; Takeda, H; Takeshita, T; Tamsett, M; Tan, C L A; Tanaka, S; Tapprogge, S; Tarem, S; Tarem, Z; Taylor, C; Teixeira-Dias, P; Thomas, J P; Thompson, P D; Thomson, M A; Tokushuku, K; Tollefson, K; Tomoto, M; Topfel, C; Torrence, E; Touchard, F; Traynor, D; Tremblet, L; Tricoli, A; Tripiana, M; Triplett, N; True, P; Tsiakiris, M; Tsuno, S; Tuggle, J; Ünel, G; Urquijo, P; Urrejola, P; Usai, G; Vachon, B; Vallecorsa, S; Valsan, L; Vandelli, W; Vari, R; Vaz Gil Lopes, L; Veneziano, S; Ventura, A; Venturi, N; Vercesi, V; Vermeulen, J C; Volpi, G; Vorwerk, V; Wagner, P; Wang, M; Warburton, A; Watkins, P M; Watson, A T; Watson, M; Weber, P; Weidberg, A R; Wengler, T; Werner, P; Werth, M; Wessels, M; White, M; Whiteson, D; Wickens, F J; Wiedenmann, W; Wielers, M; Winklmeier, F; Woods, K S; Wu, S-L; Wu, X; Xaplanteris Karampatsos, L; Xella, S; Yakovlev, A; Yamazaki, Y; Yang, U; Yasu, Y; Yuan, L; Zaitsev, A; Zanello, L; Zhang, H; Zhang, J; Zhao, L; Zobernig, H; zur Nedden, M

    2010-01-01

    The ATLAS Tile hadronic calorimeter (TileCal) provides highly-segmented energy measurements of incoming particles. The information from TileCal's last segmentation layer can assist in muon tagging and it is being considered for a near future upgrade of the level-one trigger, mainly for rejecting triggers due to cavern background at the barrel region. A muon receiver for the TileCal muon signals is being designed in order to interface with the ATLAS level-one trigger. This paper addresses the preliminary studies concerning the muon discrimination capability for the muon receiver. Monte Carlo simulations for single muons from the interaction point were used to study the effectiveness of hadronic calorimeter information on muon detection.

  9. Intrusion Detection Systems Based On Packet Sniffing

    Directory of Open Access Journals (Sweden)

    Ushus Maria Joseph

    2013-01-01

    Full Text Available In the present era of networks, security of network systems is becoming increasingly important, as more and more sensitive information is being stored and manipulated online. The paper entitled ’Packet Sniffing’ is a IDS where it monitors packets on the network wire and attempts to the discovery of hacker/cracker who is attempting to break into system. Packet Sniffing also finds the contents and tracks the data packet in the network system. This sniffing is being performed by comparing the captured packet with the intruder details stored in the database .If the packet is found to be an intruder it is then forwarded to the firewall with the respective message for blocking. The Emotional Ants module contains the sender and receiver .The sender will inform all the other Ants running in other machines about the detection of intruder through his pheromone (Messages. The receiver in Ants will listen for the messages from other Ants

  10. Aptamer-Based Technologies in Foodborne Pathogen Detection

    Science.gov (United States)

    Teng, Jun; Yuan, Fang; Ye, Yingwang; Zheng, Lei; Yao, Li; Xue, Feng; Chen, Wei; Li, Baoguang

    2016-01-01

    Aptamers are single stranded DNA or RNA ligands, which can be selected by a method called systematic evolution of ligands by exponential enrichment (SELEX); and they can specifically recognize and bind to their targets. These unique characteristics of aptamers offer great potentials in applications such as pathogen detection and biomolecular screening. Pathogen detection is the critical means in detecting and identifying the problems related to public health and food safety; and only the rapid, sensitive and efficient detection technologies can enable the users to make the accurate assessments on the risks of infections (humans and animals) or contaminations (foods and other commodities) caused by various pathogens. This article reviews the development in the field of the aptamer-based approaches for pathogen detection, including whole-cell SELEX and Genomic SELEX. Nowadays, a variety of aptamer-based biosensors have been developed for pathogen detection. Thus, in this review, we also cover the development in aptamer-based biosensors including optical biosensors for multiple pathogen detection by multiple-labeling or label-free models such as fluorescence detection and surface plasmon resonance, electrochemical biosensors and lateral chromatography test strips, and their applications in pathogen detection and biomolecular screening. While notable progress has been made in the field in the last decade, challenges or drawbacks in their applications such as pathogen detection and biomolecular screening remain to be overcome. PMID:27672383

  11. Aptamer-Based Technologies in Foodborne Pathogen Detection

    Directory of Open Access Journals (Sweden)

    Jun Teng

    2016-09-01

    Full Text Available Aptamers are single stranded DNA or RNA ligands, which can be selected by a method called systematic evolution of ligands by exponential enrichment (SELEX; and they can specifically recognize and bind to their targets. These unique characteristics of aptamers offer great potentials in applications such as pathogen detection and biomolecular screening. Pathogen detection is the first and critical means in detecting and identifying the problems related to public health and food safety; and only the rapid, sensitive and efficient detection technologies can enable the users to make to accurate assessments on the risk of infections (humans and animals or contaminations (foods and other commodities caused by various pathogens. This article reviews the developments in the field of the aptamer-based approaches for pathogen detection, including whole-cell SELEX and Genomic SELEX. Nowadays, a variety of aptamer-based biosensors have been developed for pathogen detection. Thus, in this review, we also cover the development of aptamer-based biosensors including optical biosensors for multiple pathogen detection in multiple-labeling or label-free models such as fluorescence detection and surface plasmon resonance, electrochemical biosensors, and lateral chromatography test strips, and their applications in the pathogen detection and biomolecular screening. While notable progress has been made in the field in the last decade, challenges or drawbacks in their applications such as pathogen detection and biomolecular screening, remain to be overcome.

  12. Laser Spot Detection Based on Reaction Diffusion

    Science.gov (United States)

    Vázquez-Otero, Alejandro; Khikhlukha, Danila; Solano-Altamirano, J. M.; Dormido, Raquel; Duro, Natividad

    2016-01-01

    Center-location of a laser spot is a problem of interest when the laser is used for processing and performing measurements. Measurement quality depends on correctly determining the location of the laser spot. Hence, improving and proposing algorithms for the correct location of the spots are fundamental issues in laser-based measurements. In this paper we introduce a Reaction Diffusion (RD) system as the main computational framework for robustly finding laser spot centers. The method presented is compared with a conventional approach for locating laser spots, and the experimental results indicate that RD-based computation generates reliable and precise solutions. These results confirm the flexibility of the new computational paradigm based on RD systems for addressing problems that can be reduced to a set of geometric operations. PMID:26938537

  13. Laser Spot Detection Based on Reaction Diffusion

    Directory of Open Access Journals (Sweden)

    Alejandro Vázquez-Otero

    2016-03-01

    Full Text Available Center-location of a laser spot is a problem of interest when the laser is used for processing and performing measurements. Measurement quality depends on correctly determining the location of the laser spot. Hence, improving and proposing algorithms for the correct location of the spots are fundamental issues in laser-based measurements. In this paper we introduce a Reaction Diffusion (RD system as the main computational framework for robustly finding laser spot centers. The method presented is compared with a conventional approach for locating laser spots, and the experimental results indicate that RD-based computation generates reliable and precise solutions. These results confirm the flexibility of the new computational paradigm based on RD systems for addressing problems that can be reduced to a set of geometric operations.

  14. Digital image restoration based on pixel simultaneous detection probabilities

    CERN Document Server

    Grabskii, V

    2008-01-01

    Here an image restoration on the basis of pixel simultaneous detection probabilities (PSDP) is proposed. These probabilities can be precisely determined by means of correlations measurement [NIMA 586 (2008) 314-326]. The proposed image restoration is based on the solution of matrix equation. Non-zero elements of Toeplitz block matrix with ones on the main diagonal, is determined using PSDP. The number of non zero descending diagonals depends on the detector construction and is not always smaller than 8. To solve the matrix equation, the Gaussian elimination algorithm is used. The proposed restoration algorithm is studied by means of the simulated images (with and without additive noise using PSDP for General Electric Senographe 2000D mammography device detector) and a small area (160x160 pixels) of real images acquired by the above mentioned device. The estimation errors of PSDP and the additive noise magnitude permits to restore images with the precision better than 2% for the above mentioned detector. The a...

  15. Conductometric biosensor for ethanol detection based on whole yeast cells.

    Science.gov (United States)

    Korpan, Y I; Dzyadevich, S V; Zharova, V P; El'skaya, A V

    1994-01-01

    The quantification of ethanol in alcoholic beverages was performed by yeast cell-based conductometric biosensor. A membrane with yeast cells immobilized in 2% Ca-alginate gel was attached on gold planar electrodes. Changes in conductivity due to the specific consumption of ethanol by yeast cells were registered by the computer-controlled sensor system. The response time of the constructed microbial sensor was less than 5 min, linearity (in a logarithmic scale) was observed in the range of 5-100 mM alcohol concentration. It was established that pH value in their region from 5 to 8 did not influence the levels of initial signal. The increase of a buffer capacity in the sample results in the decrease of the biosensor output. The minimal detectable level of ethanol was 1 mM and the relative standard deviation appeared to be 10-12% for 15 repeated assays. When the system was operated and stored at 20-25 degrees C, the biosensor response was stable for only 3 days. However, when the microbial sensor was stored at 4 degrees C, the system was stable up to 12 days. Good correlation between the results obtained by a conductometric cell-biosensor and gas chromatograph was observed.

  16. Nonlinear ultrasonic measurements based on cross-correlation filtering techniques

    Science.gov (United States)

    Yee, Andrew; Stewart, Dylan; Bunget, Gheorghe; Kramer, Patrick; Farinholt, Kevin; Friedersdorf, Fritz; Pepi, Marc; Ghoshal, Anindya

    2017-02-01

    Cyclic loading of mechanical components promotes the formation of dislocation dipoles in metals, which can serve as precursors to crack nucleation and ultimately lead to failure. In the laboratory setting, an acoustic nonlinearity parameter has been assessed as an effective indicator for characterizing the progression of fatigue damage precursors. However, the need to use monochromatic waves of medium-to-high acoustic energy has presented a constraint, making it problematic for use in field applications. This paper presents a potential approach for field measurement of acoustic nonlinearity by using general purpose ultrasonic pulser-receivers. Nonlinear ultrasonic measurements during fatigue testing were analyzed by the using contact and immersion pulse-through method. A novel cross-correlation filtering technique was developed to extract the fundamental and higher harmonic waves from the signals. As in the case of the classic harmonic generation, the nonlinearity parameters of the second and third harmonics indicate a strong correlation with fatigue cycles. Consideration was given to potential nonlinearities in the measurement system, and tests have confirmed that measured second harmonic signals exhibit a linear dependence on the input signal strength, further affirming the conclusion that this parameter relates to damage precursor formation from cyclic loading.

  17. GNSS Spoofing Detection Based on Signal Power Measurements: Statistical Analysis

    Directory of Open Access Journals (Sweden)

    V. Dehghanian

    2012-01-01

    Full Text Available A threat to GNSS receivers is posed by a spoofing transmitter that emulates authentic signals but with randomized code phase and Doppler values over a small range. Such spoofing signals can result in large navigational solution errors that are passed onto the unsuspecting user with potentially dire consequences. An effective spoofing detection technique is developed in this paper, based on signal power measurements and that can be readily applied to present consumer grade GNSS receivers with minimal firmware changes. An extensive statistical analysis is carried out based on formulating a multihypothesis detection problem. Expressions are developed to devise a set of thresholds required for signal detection and identification. The detection processing methods developed are further manipulated to exploit incidental antenna motion arising from user interaction with a GNSS handheld receiver to further enhance the detection performance of the proposed algorithm. The statistical analysis supports the effectiveness of the proposed spoofing detection technique under various multipath conditions.

  18. Shape-Based Plagiarism Detection for Flowchart Figures in Texts

    Directory of Open Access Journals (Sweden)

    Senosy Arrish

    2014-02-01

    Full Text Available Plagiarism detection is well known phenomenon in the academic arena. Copying other people is considered as serious offence that needs to be checked. There are many plagiarism detection systems such as turn-it-in that has been developed to provide this checks. Most, if not all, discard the figures and charts before checking for plagiarism. Discarding the figures and charts results in look holes that people can take advantage. That means people can plagiarized figures and charts easily without the current plagiarism systems detecting it. There are very few papers which talks about flowcharts plagiarism detection. Therefore, there is a need to develop a system that will detect plagiarism in figures and charts. This paper presents a method for detecting flow chart figure plagiarism based on shape-based image processing and multimedia retrieval. The method managed to retrieve flowcharts with ranked similarity according to different matching sets.

  19. Intrusion detection based on system calls and homogeneous Markov chains

    Institute of Scientific and Technical Information of China (English)

    Tian Xinguang; Duan Miyi; Sun Chunlai; Li Wenfa

    2008-01-01

    A novel method for detecting anomalous program behavior is presented, which is applicable to hostbased intrusion detection systems that monitor system call activities. The method constructs a homogeneous Markov chain model to characterize the normal behavior of a privileged program, and associates the states of the Markov chain with the unique system calls in the training data. At the detection stage, the probabilities that the Markov chain model supports the system call sequences generated by the program are computed. A low probability indicates an anomalous sequence that may result from intrusive activities. Then a decision rule based on the number of anomalous sequences in a locality frame is adopted to classify the program's behavior. The method gives attention to both computational efficiency and detection accuracy, and is especially suitable for on-line detection. It has been applied to practical host-based intrusion detection systems.

  20. Two-Dimensional UV Absorption Correlation Spectroscopy as a Method for the Detection of Thiamethoxam Residue in Tea

    Science.gov (United States)

    Zhang, J.; Zhao, Zh.; Wang, L.; Zhu, X.; Shen, L.; Yu, Y.

    2015-05-01

    Two-dimensional correlation spectroscopy (2D-COS) combined with UV absorption spectroscopy was evaluated as a technique for the identification of spectral regions associated with the residues of thiamethoxam in tea. There is only one absorption peak at 275 nm in the absorption spectrum of a mixture of thiamethoxam and tea, which is the absorption peak of tea. Based on 2D-COS, the absorption peak of thiamethoxam at 250 nm is extracted from the UV spectra of the mixture. To determine the residue of thiamethoxam in tea, 250 nm is selected as the measured wavelength, at which the fitting result is as follows: the residual sum of squares is 0.01375, standard deviation R2 is 0.99068, and F value is 426. Statistical analysis shows that there is a significant linear relationship between the concentration of thiamethoxam in tea and the absorbance at 250 nm in the UV spectra of the mixture. Moreover, the average prediction error is 0.0033 and the prediction variance is 0.1654, indicating good predictive result. Thus, the UV absorption spectrum can be used as a measurement method for rapid detection of thiamethoxam residues in tea.

  1. Evidence-based detection of pulmonary arterial hypertension in systemic sclerosis: the DETECT study

    NARCIS (Netherlands)

    Coghlan, J.G.; Denton, C.P.; Grunig, E.; Bonderman, D.; Distler, O.; Khanna, D.; Muller-Ladner, U.; Pope, J.E.; Vonk, M.C.; Doelberg, M.; Chadha-Boreham, H.; Heinzl, H.; Rosenberg, D.M.; McLaughlin, V.V.; Seibold, J.R.

    2014-01-01

    OBJECTIVE: Earlier detection of pulmonary arterial hypertension (PAH), a leading cause of death in systemic sclerosis (SSc), facilitates earlier treatment. The objective of this study was to develop the first evidence-based detection algorithm for PAH in SSc. METHODS: In this cross-sectional, intern

  2. Change detection of built-up land: A framework of combining pixel-based detection and object-based recognition

    Science.gov (United States)

    Xiao, Pengfeng; Zhang, Xueliang; Wang, Dongguang; Yuan, Min; Feng, Xuezhi; Kelly, Maggi

    2016-09-01

    This study proposed a new framework that combines pixel-level change detection and object-level recognition to detect changes of built-up land from high-spatial resolution remote sensing images. First, an adaptive differencing method was designed to detect changes at the pixel level based on both spectral and textural features. Next, the changed pixels were subjected to a set of morphological operations to improve the completeness and to generate changed objects, achieving the transition of change detection from the pixel level to the object level. The changed objects were further recognised through the difference of morphological building index in two phases to indicate changed objects on built-up land. The transformation from changed pixels to changed objects makes the proposed framework distinct with both the pixel-based and the object-based change detection methods. Compared with the pixel-based methods, the proposed framework can improve the change detection capability through the transformation and successive recognition of objects. Compared with the object-based method, the proposed framework avoids the issue of multitemporal segmentation and can generate changed objects directly from changed pixels. The experimental results show the effectiveness of the transformation from changed pixels to changed objects and the successive object-based recognition on improving the detection accuracy, which justify the application potential of the proposed change detection framework.

  3. Unsupervised abnormality detection using saliency and Retinex based color enhancement.

    Science.gov (United States)

    Deeba, Farah; Mohammed, Shahed K; Bui, Francis M; Wahid, Khan A

    2016-08-01

    An efficient and automated abnormality detection method can significantly reduce the burden of screening of the enormous visual information resulting from capsule endoscopic procedure. As a pre-processing stage, color enhancement could be useful to improve the image quality and the detection performance. Therefore, in this paper, we have proposed a two-stage automated abnormality detection algorithm. In the first stage, an adaptive color enhancement method based on Retinex theory is applied on the endoscopic images. In the second stage, an efficient salient region detection algorithm is applied to detect the clinically significant regions. The proposed algorithm is applied on a dataset containing images with diverse pathologies. The algorithm can successfully detect a significant percentage of the abnormal regions. From our experiment, it was evident that color enhancement method improves the performance of abnormality detection. The proposed algorithm can achieve a sensitivity of 97.33% and specificity of 79%, higher than state-of-the-art performance.

  4. SVM Intrusion Detection Model Based on Compressed Sampling

    Directory of Open Access Journals (Sweden)

    Shanxiong Chen

    2016-01-01

    Full Text Available Intrusion detection needs to deal with a large amount of data; particularly, the technology of network intrusion detection has to detect all of network data. Massive data processing is the bottleneck of network software and hardware equipment in intrusion detection. If we can reduce the data dimension in the stage of data sampling and directly obtain the feature information of network data, efficiency of detection can be improved greatly. In the paper, we present a SVM intrusion detection model based on compressive sampling. We use compressed sampling method in the compressed sensing theory to implement feature compression for network data flow so that we can gain refined sparse representation. After that SVM is used to classify the compression results. This method can realize detection of network anomaly behavior quickly without reducing the classification accuracy.

  5. QRS Detection Based on an Advanced Multilevel Algorithm

    OpenAIRE

    Wissam Jenkal; Rachid Latif; Ahmed Toumanari; Azzedine Dliou; Oussama El B’charri; Fadel Mrabih Rabou Maoulainine

    2016-01-01

    This paper presents an advanced multilevel algorithm used for the QRS complex detection. This method is based on three levels. The first permits the extraction of higher peaks using an adaptive thresholding technique. The second allows the QRS region detection. The last level permits the detection of Q, R and S waves. The proposed algorithm shows interesting results compared to recently published methods. The perspective of this work is the implementation of this method on an embedded system ...

  6. A real time vehicles detection algorithm for vision based sensors

    CERN Document Server

    Płaczek, Bartłomiej

    2011-01-01

    A vehicle detection plays an important role in the traffic control at signalised intersections. This paper introduces a vision-based algorithm for vehicles presence recognition in detection zones. The algorithm uses linguistic variables to evaluate local attributes of an input image. The image attributes are categorised as vehicle, background or unknown features. Experimental results on complex traffic scenes show that the proposed algorithm is effective for a real-time vehicles detection.

  7. Diffusion Geometry Based Nonlinear Methods for Hyperspectral Change Detection

    Science.gov (United States)

    2010-05-12

    Schaum and A. Stocker, “Hyperspectral change detection and supervised matched filtering based on covariance equalization,” Proceedings of the SPIE, vol...5425, pp. 77- 90 (2004). 10. A. Schaum and A. Stocker, “Linear chromodynamics models for hyperspectral target detection,” Proceedings of the IEEE...Aerospace Conference (February 2003). 11. A. Schaum and A. Stocker, “Linear chromodynamics models for hyperspectral target detection

  8. An optimized, universal hardware-based adaptive correlation receiver architecture

    Science.gov (United States)

    Zhu, Zaidi; Suarez, Hernan; Zhang, Yan; Wang, Shang

    2014-05-01

    The traditional radar RF transceivers, similar to communication transceivers, have the basic elements such as baseband waveform processing, IF/RF up-down conversion, transmitter power circuits, receiver front-ends, and antennas, which are shown in the upper half of Figure 1. For modern radars with diversified and sophisticated waveforms, we can frequently observe that the transceiver behaviors, especially nonlinear behaviors, are depending on the waveform amplitudes, frequency contents and instantaneous phases. Usually, it is a troublesome process to tune an RF transceiver to optimum when different waveforms are used. Another issue arises from the interference caused by the waveforms - for example, the range side-lobe (RSL) caused by the waveforms, once the signals pass through the entire transceiver chain, may be further increased due to distortions. This study is inspired by the two existing solutions from commercial communication industry, digital pre-distortion (DPD) and adaptive channel estimation and Interference Mitigation (AIM), while combining these technologies into a single chip or board that can be inserted into the existing transceiver system. This device is then named RF Transceiver Optimizer (RTO). The lower half of Figure 1 shows the basic element of RTO. With RTO, the digital baseband processing does not need to take into account the transceiver performance with diversified waveforms, such as the transmitter efficiency and chain distortion (and the intermodulation products caused by distortions). Neither does it need to concern the pulse compression (or correlation receiver) process and the related mitigation. The focus is simply the information about the ground truth carried by the main peak of correlation receiver outputs. RTO can be considered as an extension of the existing calibration process, while it has the benefits of automatic, adaptive and universal. Currently, the main techniques to implement the RTO are the digital pre- or -post

  9. Nondestructive Damage Detection Based on Modal Analysis

    Directory of Open Access Journals (Sweden)

    T. Plachý

    2004-01-01

    Full Text Available Three studies of damage identification and localization based on methods using experimentally estimated modal characteristics are presented. The results of an experimental investigation of simple structural elements (three RC-beams and three RC-slabs obtained in the laboratory are compared with the results obtained on a real structure (a composite bridge – a concrete deck supported by steel girders in situ. 

  10. Developing nucleic acid-based electrical detection systems

    Directory of Open Access Journals (Sweden)

    Gabig-Ciminska Magdalena

    2006-03-01

    Full Text Available Abstract Development of nucleic acid-based detection systems is the main focus of many research groups and high technology companies. The enormous work done in this field is particularly due to the broad versatility and variety of these sensing devices. From optical to electrical systems, from label-dependent to label-free approaches, from single to multi-analyte and array formats, this wide range of possibilities makes the research field very diversified and competitive. New challenges and requirements for an ideal detector suitable for nucleic acid analysis include high sensitivity and high specificity protocol that can be completed in a relatively short time offering at the same time low detection limit. Moreover, systems that can be miniaturized and automated present a significant advantage over conventional technology, especially if detection is needed in the field. Electrical system technology for nucleic acid-based detection is an enabling mode for making miniaturized to micro- and nanometer scale bio-monitoring devices via the fusion of modern micro- and nanofabrication technology and molecular biotechnology. The electrical biosensors that rely on the conversion of the Watson-Crick base-pair recognition event into a useful electrical signal are advancing rapidly, and recently are receiving much attention as a valuable tool for microbial pathogen detection. Pathogens may pose a serious threat to humans, animal and plants, thus their detection and analysis is a significant element of public health. Although different conventional methods for detection of pathogenic microorganisms and their toxins exist and are currently being applied, improvements of molecular-based detection methodologies have changed these traditional detection techniques and introduced a new era of rapid, miniaturized and automated electrical chip detection technologies into pathogen identification sector. In this review some developments and current directions in

  11. Multifeature Fusion Vehicle Detection Algorithm Based on Choquet Integral

    Directory of Open Access Journals (Sweden)

    Wenhui Li

    2014-01-01

    Full Text Available Vision-based multivehicle detection plays an important role in Forward Collision Warning Systems (FCWS and Blind Spot Detection Systems (BSDS. The performance of these systems depends on the real-time capability, accuracy, and robustness of vehicle detection methods. To improve the accuracy of vehicle detection algorithm, we propose a multifeature fusion vehicle detection algorithm based on Choquet integral. This algorithm divides the vehicle detection problem into two phases: feature similarity measure and multifeature fusion. In the feature similarity measure phase, we first propose a taillight-based vehicle detection method, and then vehicle taillight feature similarity measure is defined. Second, combining with the definition of Choquet integral, the vehicle symmetry similarity measure and the HOG + AdaBoost feature similarity measure are defined. Finally, these three features are fused together by Choquet integral. Being evaluated on public test collections and our own test images, the experimental results show that our method has achieved effective and robust multivehicle detection in complicated environments. Our method can not only improve the detection rate but also reduce the false alarm rate, which meets the engineering requirements of Advanced Driving Assistance Systems (ADAS.

  12. Weak Signal Frequency Detection Method Based on Generalized Duffing Oscillator

    Institute of Scientific and Technical Information of China (English)

    SHI Si-Hong; YUAN Yong; WANG Hui-Qi; LUO Mao-Kang

    2011-01-01

    @@ The sensitive characteristic to the initial value of chaos system sufficiently demonstrates the superiority in weak signal parameters detection.Analyzing the current chaos-based frequency detection method, a novel generalized Duffing equation is proposed to detect weak signal frequency.By choosing a suitable adjusting factor, when the outside driving force frequency is equal to that of the detected signal, the generalized Duffing oscillator is in great period state, which can obtain the frequency information of the detected signal.The simulation results indicate this method is rapidly convenient and shows better accuracy.%The sensitive characteristic to the initial value of chaos system sufficiently demonstrates the superiority in weak signal parameters detection. Analyzing the current chaos-based frequency detection method, a novel generalized Duffing equation is proposed to detect weak signal frequency. By choosing a suitable adjusting factor, when the outside driving force frequency is equal to that of the detected signal, the generalized Duffing oscillator is in great period state, which can obtain the frequency information of the detected signal. The simulation results indicate this method is rapidly convenient and shows better accuracy.

  13. Detecting shake-off electron-ion coincidences to measure {beta}-decay correlations in laser trapped {sup 21}Na

    Energy Technology Data Exchange (ETDEWEB)

    Scielzo, N.D. [University of California and Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); Freedman, S.J. [University of California and Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); Fujikawa, B.K. [Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); Kominis, I. [Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); Maruyama, R. [Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); Vetter, P.A. [Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); Vieregg, J.R. [University of California and Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States)

    2004-12-27

    The properties of a neutral atom trap are nearly ideal for precise measurements of nuclear {beta}-decay correlation coefficients. Following a radioactive decay, all particles emerge from the trap volume unperturbed and are available for study. However, for measurements online at existing accelerators, sufficient statistics will be difficult to acquire if precision significantly better than 0.01 in the correlation coefficients is desired. We have investigated the feasibility of detecting shake-off electrons in coincidence with the recoiling ions to decrease the statistical uncertainty of some measurements by nearly an order of magnitude.

  14. Statistical Outlier Detection for Jury Based Grading Systems

    DEFF Research Database (Denmark)

    Thompson, Mary Kathryn; Clemmensen, Line Katrine Harder; Rosas, Harvey

    2013-01-01

    This paper presents an algorithm that was developed to identify statistical outliers from the scores of grading jury members in a large project-based first year design course. The background and requirements for the outlier detection system are presented. The outlier detection algorithm and the f...

  15. Active Fault Detection Based on a Statistical Test

    DEFF Research Database (Denmark)

    Sekunda, André Krabdrup; Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2016-01-01

    In this paper active fault detection of closed loop systems using dual Youla-Jabr-Bongiorno-Kucera(YJBK) parameters is presented. Until now all detector design for active fault detection using the dual YJBK parameters has been based on CUSUM detectors. Here a method for design of a matched filter...

  16. Revisiting anomaly-based network intrusion detection systems

    NARCIS (Netherlands)

    Bolzoni, Damiano

    2009-01-01

    Intrusion detection systems (IDSs) are well-known and widely-deployed security tools to detect cyber-attacks and malicious activities in computer systems and networks. A signature-based IDS works similar to anti-virus software. It employs a signature database of known attacks, and a successful match

  17. A new benchmark for stereo-based pedestrian detection

    NARCIS (Netherlands)

    C.G. Keller; M. Enzweiler; D.M. Gavrila

    2011-01-01

    Pedestrian detection is a rapidly evolving area in the intelligent vehicles domain. Stereo vision is an attractive sensor for this purpose. But unlike for monocular vision, there are no realistic, large scale benchmarks available for stereo-based pedestrian detection, to provide a common point of re

  18. Detection and correction of blinking bias in image correlation transport measurements of quantum dot tagged macromolecules

    DEFF Research Database (Denmark)

    Durisic, Nela; Bachir, Alexia I; Kolin, David L;

    2007-01-01

    Semiconductor nanocrystals or quantum dots (QDs) are becoming widely used as fluorescent labels for biological applications. Here we demonstrate that fluorescence fluctuation analysis of their diffusional mobility using temporal image correlation spectroscopy is highly susceptible to systematic e...

  19. Error analysis in cross-correlation of sky maps: application to the ISW detection

    CERN Document Server

    Cabre, A; Manera, E G M; Cabre, Anna; Fosalba, Pablo; Manera, Enrique Gaztanaga & Marc

    2007-01-01

    Constraining cosmological parameters from measurements of the Integrated Sachs-Wolfe effect requires developing robust and accurate methods for computing statistical errors in the cross-correlation between maps. This paper presents a detailed comparison of such error estimation applied to the case of cross-correlation of Cosmic Microwave Background (CMB) and large-scale structure data. We compare theoretical models for error estimation with montecarlo simulations where both the galaxy and the CMB maps vary around a fiducial auto-correlation and cross-correlation model which agrees well with the current concordance LCDM cosmology. Our analysis compares estimators both in harmonic and configuration (or real) space, quantifies the accuracy of the error analysis and discuss the impact of partial sky survey area and the choice of input fiducial model on dark-energy constraints. We show that purely analytic approaches yield accurate errors even in surveys that cover only 10% of the sky and that parameter constraint...

  20. Polypyrrole based gas sensor for ammonia detection

    Science.gov (United States)

    Dunst, K. J.; Cysewska, K.; Kalinowski, P.; Jasiński, P.

    2016-01-01

    The nature of polypyrrole response to toxic gases does not allow using the sensor in a conventional way. The main aim of this study is to acquire the information about the concentration using different approaches: a linear approximation, a non-linear approximation and a tangent method. In this paper a two-steps procedure for sensor response measurements has been utilized. Polypyrrole films were electrochemically synthesized on the interdigitated electrodes. Gas sensing measurements of polypyrrole based sensor were carried out at room temperature. The influence of the flow rate on the sensing performance to NH3 were investigated. The preliminary studies of aging of the sensor were also explored.

  1. Scintillation particle detection based on microfluidics

    CERN Document Server

    Mapelli, A; Renaud, P; Gorini, B; Trivino, N Vico; Jiguet, S; Vandelli, W; Haguenauer, M

    2010-01-01

    A novel type of particle detector based on scintillation, with precise spatial resolution and high radiation hardness, is being studied. It consists of a single microfluidic channel filled with a liquid scintillator and is designed to define an array of scintillating waveguides each independently coupled to a photodetector. Prototype detectors built using an SU-8 epoxy resin have been tested with electrons from a radioactive source. The experimental results show a light yield compatible with the theoretical expectations and confirm the validity of the approach. (C) 2010 Elsevier B.V. All rights reserved.

  2. Raman spectroscopy-based detection of chemical contaminants in food powders

    Science.gov (United States)

    Chao, Kuanglin; Dhakal, Sagar; Qin, Jianwei; Kim, Moon; Bae, Abigail

    2016-05-01

    Raman spectroscopy technique has proven to be a reliable method for qualitative detection of chemical contaminants in food ingredients and products. For quantitative imaging-based detection, each contaminant particle in a food sample must be detected and it is important to determine the necessary spatial resolution needed to effectively detect the contaminant particles. This study examined the effective spatial resolution required for detection of maleic acid in tapioca starch and benzoyl peroxide in wheat flour. Each chemical contaminant was mixed into its corresponding food powder at a concentration of 1% (w/w). Raman spectral images were collected for each sample, leveled across a 45 mm x 45 mm area, using different spatial resolutions. Based on analysis of these images, a spatial resolution of 0.5mm was selected as effective spatial resolution for detection of maleic acid in starch and benzoyl peroxide in flour. An experiment was then conducted using the 0.5mm spatial resolution to demonstrate Raman imaging-based quantitative detection of these contaminants for samples prepared at 0.1%, 0.3%, and 0.5% (w/w) concentrations. The results showed a linear correlation between the detected numbers of contaminant pixels and the actual concentrations of contaminant.

  3. A versatile microparticle-based immunoaggregation assay for macromolecular biomarker detection and quantification.

    Directory of Open Access Journals (Sweden)

    Haiyan Wu

    Full Text Available The rapid, sensitive and low-cost detection of macromolecular biomarkers is critical in clinical diagnostics, environmental monitoring, research, etc. Conventional assay methods usually require bulky, expensive and designated instruments and relative long assay time. For hospitals and laboratories that lack immediate access to analytical instruments, fast and low-cost assay methods for the detection of macromolecular biomarkers are urgently needed. In this work, we developed a versatile microparticle (MP-based immunoaggregation method for the detection and quantification of macromolecular biomarkers. Antibodies (Abs were firstly conjugated to MP through streptavidin-biotin interaction; the addition of macromolecular biomarkers caused the aggregation of Ab-MPs, which were subsequently detected by an optical microscope or optical particle sizer. The invisible nanometer-scale macromolecular biomarkers caused detectable change of micrometer-scale particle size distributions. Goat anti-rabbit immunoglobulin and human ferritin were used as model biomarkers to demonstrate MP-based immunoaggregation assay in PBS and 10% FBS to mimic real biomarker assay in the complex medium. It was found that both the number ratio and the volume ratio of Ab-MP aggregates caused by biomarker to all particles were directly correlated to the biomarker concentration. In addition, we found that the detection range could be tuned by adjusting the Ab-MP concentration. We envision that this novel MP-based immunoaggregation assay can be combined with multiple detection methods to detect and quantify macromolecular biomarkers at the nanogram per milliliter level.

  4. Unsupervised Approaches for Post-Processing in Computationally Efficient Waveform-Similarity-Based Earthquake Detection

    Science.gov (United States)

    Bergen, K.; Yoon, C. E.; OReilly, O. J.; Beroza, G. C.

    2015-12-01

    Recent improvements in computational efficiency for waveform correlation-based detections achieved by new methods such as Fingerprint and Similarity Thresholding (FAST) promise to allow large-scale blind search for similar waveforms in long-duration continuous seismic data. Waveform similarity search applied to datasets of months to years of continuous seismic data will identify significantly more events than traditional detection methods. With the anticipated increase in number of detections and associated increase in false positives, manual inspection of the detection results will become infeasible. This motivates the need for new approaches to process the output of similarity-based detection. We explore data mining techniques for improved detection post-processing. We approach this by considering similarity-detector output as a sparse similarity graph with candidate events as vertices and similarities as weighted edges. Image processing techniques are leveraged to define candidate events and combine results individually processed at multiple stations. Clustering and graph analysis methods are used to identify groups of similar waveforms and assign a confidence score to candidate detections. Anomaly detection and classification are applied to waveform data for additional false detection removal. A comparison of methods will be presented and their performance will be demonstrated on a suspected induced and non-induced earthquake sequence.

  5. How to detect Edgar Allan Poe's 'purloined letter,' or cross-correlation algorithms in digitized video images for object identification, movement evaluation, and deformation analysis

    Science.gov (United States)

    Dost, Michael; Vogel, Dietmar; Winkler, Thomas; Vogel, Juergen; Erb, Rolf; Kieselstein, Eva; Michel, Bernd

    2003-07-01

    Cross correlation analysis of digitised grey scale patterns is based on - at least - two images which are compared one to each other. Comparison is performed by means of a two-dimensional cross correlation algorithm applied to a set of local intensity submatrices taken from the pattern matrices of the reference and the comparison images in the surrounding of predefined points of interest. Established as an outstanding NDE tool for 2D and 3D deformation field analysis with a focus on micro- and nanoscale applications (microDAC and nanoDAC), the method exhibits an additional potential for far wider applications, that could be used for advancing homeland security. Cause the cross correlation algorithm in some kind seems to imitate some of the "smart" properties of human vision, this "field-of-surface-related" method can provide alternative solutions to some object and process recognition problems that are difficult to solve with more classic "object-related" image processing methods. Detecting differences between two or more images using cross correlation techniques can open new and unusual applications in identification and detection of hidden objects or objects with unknown origin, in movement or displacement field analysis and in some aspects of biometric analysis, that could be of special interest for homeland security.

  6. Mouse V1 population correlates of visual detection rely on heterogeneity within neuronal response patterns

    NARCIS (Netherlands)

    J.S. Montijn; P.M. Goltstein; C.M.A. Pennartz

    2015-01-01

    Previous studies have demonstrated the importance of the primary sensory cortex for the detection, discrimination and awareness of visual stimuli, but it is unknown how neuronal populations in this area process detected and undetected stimuli differently. Critical differences may reside in the mean

  7. A Multistep Framework for Vision Based Vehicle Detection

    Directory of Open Access Journals (Sweden)

    Hai Wang

    2014-01-01

    Full Text Available Vision based vehicle detection is a critical technology that plays an important role in not only vehicle active safety but also road video surveillance application. In this work, a multistep framework for vision based vehicle detection is proposed. In the first step, for vehicle candidate generation, a novel geometrical and coarse depth information based method is proposed. In the second step, for candidate verification, a deep architecture of deep belief network (DBN for vehicle classification is trained. In the last step, a temporal analysis method based on the complexity and spatial information is used to further reduce miss and false detection. Experiments demonstrate that this framework is with high true positive (TP rate as well as low false positive (FP rate. On road experimental results demonstrate that the algorithm performs better than state-of-the-art vehicle detection algorithm in testing data sets.

  8. Algorithms for Speeding up Distance-Based Outlier Detection

    Data.gov (United States)

    National Aeronautics and Space Administration — The problem of distance-based outlier detection is difficult to solve efficiently in very large datasets because of potential quadratic time complexity. We address...

  9. Design and implementation of photon correlator based on C8051F

    Science.gov (United States)

    Shen, Jin; Li, Yuming; Liu, Wei; Yang, Yan; Cheng, Yanting

    2008-02-01

    Correlation techniques are widely used to extract spectral information from light scattering and other stochastic processes. Within the photon correlation system, the correlating operation must work at a high speed. In this paper, a photon correlator based on microcontroller C8051F was developed. In the photon correlator, the work of counting and scratch is completed by the two 4-bits binary adder 74F161, which is connected to form an 8-bits adder., and the correlation operation of every channel is carried out by the software of C8051F. By probably choosing high speed devices counting of 10ns in width pulses can be counted. The correlation operations including multiplying and addition operation of 56 channels with the circulation program within 3μs were made in interrupt service routine of the C8051F. The work in this paper can be applied in the ultra-fine particle sizing with photon correlation spectroscopy.

  10. Vibration Based Sun Gear Damage Detection

    Science.gov (United States)

    Hood, Adrian; LaBerge, Kelsen; Lewicki, David; Pines, Darryll

    2013-01-01

    Seeded fault experiments were conducted on the planetary stage of an OH-58C helicopter transmission. Two vibration based methods are discussed that isolate the dynamics of the sun gear from that of the planet gears, bearings, input spiral bevel stage, and other components in and around the gearbox. Three damaged sun gears: two spalled and one cracked, serve as the focus of this current work. A non-sequential vibration separation algorithm was developed and the resulting signals analyzed. The second method uses only the time synchronously averaged data but takes advantage of the signal/source mapping required for vibration separation. Both algorithms were successful in identifying the spall damage. Sun gear damage was confirmed by the presence of sun mesh groups. The sun tooth crack condition was inconclusive.

  11. Voltage Sag Source Location Based on Instantaneous Energy Detection

    DEFF Research Database (Denmark)

    Chen, Zhe; Kong, Wei; Dong, Xinzhou

    2008-01-01

    Voltage sag is a major power quality problem, which could disrupt the operation of voltage-sensitive equipment. This paper presents the method based on variation components-based instantaneous energy for voltage sag source detection. Simulations have been performed to provide the thorough analysi...... for system with distributed generation units. The studies show that the presented method can effectively detect the location of voltage sag source....

  12. Abnormal traffic flow data detection based on wavelet analysis

    Directory of Open Access Journals (Sweden)

    Xiao Qian

    2016-01-01

    Full Text Available In view of the traffic flow data of non-stationary, the abnormal data detection is difficult.proposed basing on the wavelet analysis and least squares method of abnormal traffic flow data detection in this paper.First using wavelet analysis to make the traffic flow data of high frequency and low frequency component and separation, and then, combined with least square method to find abnormal points in the reconstructed signal data.Wavelet analysis and least square method, the simulation results show that using wavelet analysis of abnormal traffic flow data detection, effectively reduce the detection results of misjudgment rate and false negative rate.

  13. USING MORPHLET-BASED IMAGE REPRESENTATION FOR OBJECT DETECTION

    Directory of Open Access Journals (Sweden)

    V. S. Gorbatsevich

    2016-06-01

    Full Text Available In this paper, we propose an original method for objects detection based on a special tree-structured image representation – the trees of morphlets. The method provides robust detection of various types of objects in an image without employing a machine learning procedure. Along with a bounding box creation on a detection step, the method makes pre-segmentation, which can be further used for recognition purposes. Another important feature of the proposed approach is that there are no needs to use a running window as well as a features pyramid in order to detect the objects of different sizes.

  14. Ensemble-based Malware Detection with Different Voting Schemes

    Directory of Open Access Journals (Sweden)

    Ms. Jyoti H. Landage

    2014-10-01

    Full Text Available Now a day’s computer security is the field which attempts to keep information on the computer safe and secure. Security means permitting things you do want, while preventing things you don’t want from happening. Malware represents a serious threat to security of computer system. Traditional anti-malware products use the signature-based, heuristic-based detection techniques to detect the malware. These techniques detect the known malware accurately but can’t detect the new, unknown malware. This paper presents a malware detection system based on the data mining and machine learning technique. The proposed method consists of disassemble process, feature extraction process and feature selection process. Three classification algorithms are employed on dataset to generate and train the classifiers named as Ripper, C4.5, IBk. The ensemble method Voting is used to improve the accuracy of results. Here majority voting and veto voting are implemented; the expected output is decided on the basis of majority and veto voting. The decision strategy of veto is improved by introducing the trust-based veto voting. The results of majority voting, veto voting and trust-based veto voting are compared. The experimental results show that the trust-based veto voting can accurately detect known and unknown malware instances better than majority voting and can identify the benign files better than veto voting.

  15. ENSEMBLE-BASED MALWARE DETECTION WITH DIFFERENT VOTING SCHEMES

    Directory of Open Access Journals (Sweden)

    Jyoti H. Landage

    2015-10-01

    Full Text Available Now a day’s computer security is the field which attempts to keep information on the computer safe and secure. Security means permitting things you do want, while preventing things you don't want from happening. Malware represents a serious threat to security of computer system. Traditional anti-malware products use the signature-based, heuristic-based detection techniques to detect the malware. These techniques detect the known malware accurately but can't detect the new, unknown malware. This paper presents a malware detection system based on the data mining and machine learning technique. The proposed method consists of disassemble process, feature extraction process and feature selection process. Three classification algorithms are employed on dataset to generate and train the classifiers named as Ripper, C4.5, IBk. The ensemble method Voting is used to improve the accuracy of results. Here majority voting and veto voting are implemented; the expected output is decided on the basis of majority and veto voting. The decision strategy of veto is improved by introducing the trust-based veto voting. The results of majority voting, veto voting and trust-based veto voting are compared. The experimental results show that the trust-based veto voting can accurately detect known and unknown malware instances better than majority voting and can identify the benign files better than veto voting.

  16. An Algorithm for Detection of DVB-T Signals Based on Their Second-Order Statistics

    Directory of Open Access Journals (Sweden)

    Jallon Pierre

    2008-01-01

    Full Text Available Abstract We propose in this paper a detection algorithm based on a cost function that jointly tests the correlation induced by the cyclic prefix and the fact that this correlation is time-periodic. In the first part of the paper, the cost function is introduced and some analytical results are given. In particular, the noise and multipath channel impacts on its values are theoretically analysed. In a second part of the paper, some asymptotic results are derived. A first exploitation of these results is used to build a detection test based on the false alarm probability. These results are also used to evaluate the impact of the number of cycle frequencies taken into account in the cost function on the detection performances. Thanks to numerical estimations, we have been able to estimate that the proposed algorithm detects DVB-T signals with an SNR of  dB. As a comparison, and in the same context, the detection algorithm proposed by the 802.22 WG in 2006 is able to detect these signals with an SNR of  dB.

  17. An Algorithm for Detection of DVB-T Signals Based on Their Second-Order Statistics

    Directory of Open Access Journals (Sweden)

    Pierre Jallon

    2008-03-01

    Full Text Available We propose in this paper a detection algorithm based on a cost function that jointly tests the correlation induced by the cyclic prefix and the fact that this correlation is time-periodic. In the first part of the paper, the cost function is introduced and some analytical results are given. In particular, the noise and multipath channel impacts on its values are theoretically analysed. In a second part of the paper, some asymptotic results are derived. A first exploitation of these results is used to build a detection test based on the false alarm probability. These results are also used to evaluate the impact of the number of cycle frequencies taken into account in the cost function on the detection performances. Thanks to numerical estimations, we have been able to estimate that the proposed algorithm detects DVB-T signals with an SNR of −12 dB. As a comparison, and in the same context, the detection algorithm proposed by the 802.22 WG in 2006 is able to detect these signals with an SNR of −8 dB.

  18. Fuzzy logic and optical correlation-based face recognition method for patient monitoring application in home video surveillance

    Science.gov (United States)

    Elbouz, Marwa; Alfalou, Ayman; Brosseau, Christian

    2011-06-01

    Home automation is being implemented into more and more domiciles of the elderly and disabled in order to maintain their independence and safety. For that purpose, we propose and validate a surveillance video system, which detects various posture-based events. One of the novel points of this system is to use adapted Vander-Lugt correlator (VLC) and joint-transfer correlator (JTC) techniques to make decisions on the identity of a patient and his three-dimensional (3-D) positions in order to overcome the problem of crowd environment. We propose a fuzzy logic technique to get decisions on the subject's behavior. Our system is focused on the goals of accuracy, convenience, and cost, which in addition does not require any devices attached to the subject. The system permits one to study and model subject responses to behavioral change intervention because several levels of alarm can be incorporated according different situations considered. Our algorithm performs a fast 3-D recovery of the subject's head position by locating eyes within the face image and involves a model-based prediction and optical correlation techniques to guide the tracking procedure. The object detection is based on (hue, saturation, value) color space. The system also involves an adapted fuzzy logic control algorithm to make a decision based on information given to the system. Furthermore, the principles described here are applicable to a very wide range of situations and robust enough to be implementable in ongoing experiments.

  19. A Smartphone Malware Detection Framework Based on Artificial Immunology

    Directory of Open Access Journals (Sweden)

    Min Zhao

    2013-02-01

    Full Text Available With the sharp increase in the number of smartphones, the Android platform pose to becoming a market leader that makes the need for malware analysis on this platform an urgent issue. The current Artificial Immune-Based malware detection systems research focus on traditional computers that uses information from OS or network, but the smartphone software behavior has its own structure and semantics. Current research cannot detect malware in smartphone exactly and efficiently. To address these problems, in this paper, we capitalize on earlier approaches for dynamic analysis of application behavior as a means for detecting malware in the smartphone. An Artificial Immune-Based Smartphone Malware Detection Framework is brought forwards and a prototype system is implemented, the experiment result show that the system can obtain higher detection rate and decrease the false positive rate.

  20. Transistor-based particle detection systems and methods

    Science.gov (United States)

    Jain, Ankit; Nair, Pradeep R.; Alam, Muhammad Ashraful

    2015-06-09

    Transistor-based particle detection systems and methods may be configured to detect charged and non-charged particles. Such systems may include a supporting structure contacting a gate of a transistor and separating the gate from a dielectric of the transistor, and the transistor may have a near pull-in bias and a sub-threshold region bias to facilitate particle detection. The transistor may be configured to change current flow through the transistor in response to a change in stiffness of the gate caused by securing of a particle to the gate, and the transistor-based particle detection system may configured to detect the non-charged particle at least from the change in current flow.

  1. Outlier Mining Based Abnormal Machine Detection in Intelligent Maintenance

    Institute of Scientific and Technical Information of China (English)

    ZHANG Lei; CAO Qi-xin; LEE Jay

    2009-01-01

    Assessing machine's performance through comparing the same or similar machines is important to implement intelligent maintenance for swarm machine. In this paper, an outlier mining based abnormal machine detection algorithm is proposed for this purpose. Firstly, the outlier mining based on clustering is introduced and the definition of cluster-based global outlier factor (CBGOF) is presented. Then the modified swarm intelligence clustering(MSIC) algorithm is suggested and the outlier mining algorithm based on MSIC is proposed. The algorithm can not only cluster machines according to their performance but also detect possible abnormal machines. Finally, a comparison of mobile soccer robots' performance proves the algorithm is feasible and effective.

  2. Caption detection from video sequence based on fuzzy neural networks

    Science.gov (United States)

    Gao, Xinbo; Xin, Hong; Li, Jie

    2001-09-01

    Caption graphically superimposed in video frames can provide important indexing information. The automatic detection and recognition of video captions can be of great help in querying topics of interest in digital news library. To detect the caption from video sequence, we present algorithms based on fuzzy clustering neural networks. Since neural networks have the capabilities of learning and self-organizing and parallel computing mechanism, with the great increasing of digital images and video databases, neural networks based techniques become more efficient and popular tools for multimedia processing. Experimental results show that our caption detection scheme is effective and robust.

  3. Detection of non-classical space-time correlations with a novel type of single-photon camera

    CERN Document Server

    Just, Felix; Cavanna, Andrea; Michel, Thilo; Gleixner, Thomas; Taheri, Michael; Vallerga, John; Campbell, Michael; Tick, Timo; Anton, Gisela; Chekhova, Maria V; Leuchs, Gerd

    2014-01-01

    During the last decades, multi-pixel detectors have been developed capable of registering single photons. The newly developed Hybrid Photon Detector camera has a remarkable property that it has not only spatial but also temporal resolution. In this work, we use this device for the detection of non-classical light from spontaneous parametric down-conversion and use two-photon correlations for the absolute calibration of its quantum efficiency.

  4. Image Fakery Detection Based on Singular Value Decomposition

    Directory of Open Access Journals (Sweden)

    T. Basaruddin

    2009-11-01

    Full Text Available The growing of image processing technology nowadays make it easier for user to modify and fake the images. Image fakery is a process to manipulate part or whole areas of image either in it content or context with the help of digital image processing techniques. Image fakery is barely unrecognizable because the fake image is looking so natural. Yet by using the numerical computation technique it is able to detect the evidence of fake image. This research is successfully applied the singular value decomposition method to detect image fakery. The image preprocessing algorithm prior to the detection process yields two vectors orthogonal to the singular value vector which are important to detect fake image. The result of experiment to images in several conditions successfully detects the fake images with threshold value 0.2. Singular value decomposition-based detection of image fakery can be used to investigate fake image modified from original image accurately.

  5. Spectral evolution of gamma-ray bursts detected by the SIGNE experiment. 1: Correlation between intensity and spectral hardness

    Science.gov (United States)

    Kargatis, Vincent E.; Liang, Edison P.; Hurley, Kevin C.; Barat, C.; Eveno, E.; Niel, M.

    1994-01-01

    We study the continuum spectral evolution of 16 gamma-ray bursts detected by the Franco-Soviet SIGNE experiment in 1981-1982 by fitting time resolved (0.5 s) spectra in count space with simple thermal bremsstrahlung and synchrotron models. We find that there is no single characteristic of spectral evolution: we see hard-to-soft, soft-to-hard, luminosity-hardness tracking, and chaotic evolution. We perform correlation studies between instantaneous burst intensity and spectral temperature for seven bursts. While we basically confirm the existence of a correlation between these variables as originally claimed by Golenetskii et al. (1983) we find higher values and a broader range of correlation indices.

  6. Learning-Based Detection of Harmful Data in Mobile Devices

    Directory of Open Access Journals (Sweden)

    Seok-Woo Jang

    2016-01-01

    Full Text Available The Internet has supported diverse types of multimedia content flowing freely on smart phones and tablet PCs based on its easy accessibility. However, multimedia content that can be emotionally harmful for children is also easily spread, causing many social problems. This paper proposes a method to assess the harmfulness of input images automatically based on an artificial neural network. The proposed method first detects human face areas based on the MCT features from the input images. Next, based on color characteristics, this study identifies human skin color areas along with the candidate areas of nipples, one of the human body parts representing harmfulness. Finally, the method removes nonnipple areas among the detected candidate areas using the artificial neural network. The experimental results show that the suggested neural network learning-based method can determine the harmfulness of various types of images more effectively by detecting nipple regions from input images robustly.

  7. Detection of infrastructure manipulation with knowledge-based video surveillance

    Science.gov (United States)

    Muench, David; Hilsenbeck, Barbara; Kieritz, Hilke; Becker, Stefan; Grosselfinger, Ann-Kristin; Huebner, Wolfgang; Arens, Michael

    2016-10-01

    We are living in a world dependent on sophisticated technical infrastructure. Malicious manipulation of such critical infrastructure poses an enormous threat for all its users. Thus, running a critical infrastructure needs special attention to log the planned maintenance or to detect suspicious events. Towards this end, we present a knowledge-based surveillance approach capable of logging visual observable events in such an environment. The video surveillance modules are based on appearance-based person detection, which further is used to modulate the outcome of generic processing steps such as change detection or skin detection. A relation between the expected scene behavior and the underlying basic video surveillance modules is established. It will be shown that the combination already provides sufficient expressiveness to describe various everyday situations in indoor video surveillance. The whole approach is qualitatively and quantitatively evaluated on a prototypical scenario in a server room.

  8. A new approach toward object-based change detection

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Object-based change detection has been the hotspot in remote sensing image processing.A new approach toward object-based change detection is proposed.The two different temporal images are unitedly segmented using the mean shift procedure to obtain corresponding objects.Then change detection is implemented based on the integration of corresponding objects’ intensity and texture differences.Experiments are conducted on both panchromatic images and multispectral images and the results show that the integrated measure is robust with respect to illumination changes and noise.Supplementary color detection is conducted to determine whether the color of the unchanged objects changes or not when dealing with multispectral images.Some verification work is carried out to show the accuracy of the proposed approach.

  9. Detection of heavy metal by paper-based microfluidics.

    Science.gov (United States)

    Lin, Yang; Gritsenko, Dmitry; Feng, Shaolong; Teh, Yi Chen; Lu, Xiaonan; Xu, Jie

    2016-09-15

    Heavy metal pollution has shown great threat to the environment and public health worldwide. Current methods for the detection of heavy metals require expensive instrumentation and laborious operation, which can only be accomplished in centralized laboratories. Various microfluidic paper-based analytical devices have been developed recently as simple, cheap and disposable alternatives to conventional ones for on-site detection of heavy metals. In this review, we first summarize current development of paper-based analytical devices and discuss the selection of paper substrates, methods of device fabrication, and relevant theories in these devices. We then compare and categorize recent reports on detection of heavy metals using paper-based microfluidic devices on the basis of various detection mechanisms, such as colorimetric, fluorescent, and electrochemical methods. To finalize, the future development and trend in this field are discussed.

  10. An Efficient Fuzzy Clustering-Based Approach for Intrusion Detection

    CERN Document Server

    Nguyen, Huu Hoa; Darmont, Jérôme

    2011-01-01

    The need to increase accuracy in detecting sophisticated cyber attacks poses a great challenge not only to the research community but also to corporations. So far, many approaches have been proposed to cope with this threat. Among them, data mining has brought on remarkable contributions to the intrusion detection problem. However, the generalization ability of data mining-based methods remains limited, and hence detecting sophisticated attacks remains a tough task. In this thread, we present a novel method based on both clustering and classification for developing an efficient intrusion detection system (IDS). The key idea is to take useful information exploited from fuzzy clustering into account for the process of building an IDS. To this aim, we first present cornerstones to construct additional cluster features for a training set. Then, we come up with an algorithm to generate an IDS based on such cluster features and the original input features. Finally, we experimentally prove that our method outperform...

  11. Correlation between localization, age, and chromosomal imbalances in ependymal tumours as detected by CGH.

    NARCIS (Netherlands)

    Jeuken, J.W.M.; Sprenger, S.H.; Gilhuis, H.J.; Teepen, J.L.; Grotenhuis, J.A.; Wesseling, P.

    2002-01-01

    Ependymal tumours (ETs) are gliomas that arise from the ependymal lining of the cerebral ventricles and from the remnants of the central canal of the spinal cord. Both clinical and genetic studies suggest that distinct genetic subtypes of ETs exist, the subtypes being correlated with patient age and

  12. DEFECTS IN CDS - IN DETECTED BY PERTURBED ANGULAR-CORRELATION SPECTROSCOPY (PAC)

    NARCIS (Netherlands)

    MAGERLE, R; DEICHER, M; DESNICA, U; KELLER, R; PFEIFFER, W; PLEITER, F; SKUDLIK, H; WICHERT, T

    1991-01-01

    The local lattice environment of the donor In in CdS is investigated measuring the electric-field gradient at the site of the radioactive probe atom In-111 by the perturbed gamma-gamma angular correlation technique. It is shown that implantation of In into CdS with subsequent annealing drives 100% o

  13. Detectability of the 21-cm CMB cross-correlation from the epoch of reionization

    NARCIS (Netherlands)

    Tashiro, Hiroyuki; Aghanim, Nabila; Langer, Mathieu; Douspis, Marian; Zaroubi, Saleem; Jelic, Vibor

    2010-01-01

    The 21-cm line fluctuations and the cosmic microwave background (CMB) are powerful probes of the epoch of reionization of the Universe. We study the potential of the cross-correlation between 21-cm line fluctuations and CMB anisotropy to obtain further constraints on the reionization history. We ana

  14. Kullback-Leibler distance-based enhanced detection of incipient anomalies

    KAUST Repository

    Harrou, Fouzi

    2016-09-09

    Accurate and effective anomaly detection and diagnosis of modern engineering systems by monitoring processes ensure reliability and safety of a product while maintaining desired quality. In this paper, an innovative method based on Kullback-Leibler divergence for detecting incipient anomalies in highly correlated multivariate data is presented. We use a partial least square (PLS) method as a modeling framework and a symmetrized Kullback-Leibler distance (KLD) as an anomaly indicator, where it is used to quantify the dissimilarity between current PLS-based residual and reference probability distributions obtained using fault-free data. Furthermore, this paper reports the development of two monitoring charts based on the KLD. The first approach is a KLD-Shewhart chart, where the Shewhart monitoring chart with a three sigma rule is used to monitor the KLD of the response variables residuals from the PLS model. The second approach integrates the KLD statistic into the exponentially weighted moving average monitoring chart. The performance of the PLS-based KLD anomaly-detection methods is illustrated and compared to that of conventional PLS-based anomaly detection methods. Using synthetic data and simulated distillation column data, we demonstrate the greater sensitivity and effectiveness of the developed method over the conventional PLS-based methods, especially when data are highly correlated and small anomalies are of interest. Results indicate that the proposed chart is a very promising KLD-based method because KLD-based charts are, in practice, designed to detect small shifts in process parameters. © 2016 Elsevier Ltd

  15. Multicriteria Similarity-Based Anomaly Detection Using Pareto Depth Analysis.

    Science.gov (United States)

    Hsiao, Ko-Jen; Xu, Kevin S; Calder, Jeff; Hero, Alfred O

    2016-06-01

    We consider the problem of identifying patterns in a data set that exhibits anomalous behavior, often referred to as anomaly detection. Similarity-based anomaly detection algorithms detect abnormally large amounts of similarity or dissimilarity, e.g., as measured by the nearest neighbor Euclidean distances between a test sample and the training samples. In many application domains, there may not exist a single dissimilarity measure that captures all possible anomalous patterns. In such cases, multiple dissimilarity measures can be defined, including nonmetric measures, and one can test for anomalies by scalarizing using a nonnegative linear combination of them. If the relative importance of the different dissimilarity measures are not known in advance, as in many anomaly detection applications, the anomaly detection algorithm may need to be executed multiple times with different choices of weights in the linear combination. In this paper, we propose a method for similarity-based anomaly detection using a novel multicriteria dissimilarity measure, the Pareto depth. The proposed Pareto depth analysis (PDA) anomaly detection algorithm uses the concept of Pareto optimality to detect anomalies under multiple criteria without having to run an algorithm multiple times with different choices of weights. The proposed PDA approach is provably better than using linear combinations of the criteria, and shows superior performance on experiments with synthetic and real data sets.

  16. Physicochemical properties determining the detection probability of tryptic peptides in Fourier transform mass spectrometry. A correlation study

    DEFF Research Database (Denmark)

    Nielsen, Michael L; Savitski, Mikhail M; Kjeldsen, Frank

    2004-01-01

    Sequence verification and mapping of posttranslational modifications require nearly 100% sequence coverage in the "bottom-up" protein analysis. Even in favorable cases, routine liquid chromatography-mass spectrometry detects from protein digests peptides covering 50-90% of the sequence. Here we...... investigated the reasons for limited peptide detection, considering various physicochemical aspects of peptide behavior in liquid chromatography-Fourier transform mass spectrometry (LC-FTMS). No overall correlation was found between the detection probability and peptide mass. In agreement with literature data...... between pI and signal response. An explanation of this paradoxal behavior was found through the observation that more acidic tryptic peptide lengths tend to be longer. Longer peptides tend to acquire higher average charge state in positive mode electrospray ionization than more basic but shorter...

  17. Eigenvoice-based MAP adaptation within correlation subspace

    Institute of Scientific and Technical Information of China (English)

    LUO Jun; OU Zhi-jian; WANG Zuo-ying

    2006-01-01

    In recent years,the eigenvoice approach has proven to be an efficient method for rapid speaker adaptation,which directs the adaptation according to the analysis of full speaker vector space.In this article,we developed a new algorithm for eigenspace-based adaptation restricting eigenvoices in clustered subspaces, and maximum likelihood (ML) criterion was replaced with maximum aposteriori (MAP) criterion for better parameter estimation.Experiments show that even with one sentence adaptation data this algorithm would result in 6.45 % error ratio reduction relatively,which overcomes the instability of maximum likelihood linear regression (MLLR) with limited data and is much faster than traditional MAP method.This algorithm is not highly-dependent on subspace number of division,thus it proved to be a robust adaptation algorithm.

  18. Cavity enhanced detection methods for probing the dynamics of spin correlated radical pairs in solution

    Science.gov (United States)

    Neil, Simon R. T.; Maeda, Kiminori; Henbest, Kevin B.; Goez, Martin; Hemmens, Robert; Timmel, Christiane R.; Mackenzie, Stuart R.

    2010-04-01

    Cavity enhanced absorption spectroscopy (CEAS) combined with phase-sensitive detection is employed to study the effects of static magnetic fields on radical recombination reactions. The chemical system comprises the photochemically generated thionine semiquinone radical and a 1,4-diazabicyclo[2.2.2]octane (DABCO) cationic radical in a micellar solution of sodium dodecyl sulphate. Data obtained using the modulated CEAS technique, describing the magnetic field effect (MFE) on reaction yields, are shown to be superior to those obtained using conventional transient absorption (TA) flash photolysis methods typically employed for these measurements. The high sensitivity afforded by modulated CEAS detection is discussed in terms of the new possibilities it offers such as the measurement of magnetic field effects in real biological systems which have hitherto been largely beyond the detection capabilities of existing techniques.

  19. Infrared Image Small Target Detection Based on Bi-orthogonal Wavelet and Morphology

    Institute of Scientific and Technical Information of China (English)

    CHI Jian-nan; ZHANG Zhao-hui; WANG Dong-shu; HAO Yan-shuang

    2007-01-01

    An image multi-scale edge detection method based on anti-symmetrical bi-orthogonal wavelet is given in theory. Convolution operation property and function as a differential operator are analyzed,which anti-symmetrical bi-orthogonal wavelet transform have. An algorithm for wavelet reconstruction in which multi-scale edge can be detected is put forward. Based on it, a detection method for small target in infrared image with sea or sky background based on the anti-symmetrical bi-orthogonal wavelet and morphology is proposed. The small target detection is considered as a process in which structural background is removed, correlative background is suppressed, and noise is restrained. In this approach, the multi-scale edge is extracted by means of the anti-symmetrical bi-orthogonal wavelet decomposition. Then, module maximum chains formed by complicated background of clouds, sea wave and sea-sky-line are removed, and the image background becomes smoother. Finally, the morphology based edge detection method is used to get small target and restrain undulate background and noise. Experiment results show that the approach can suppress clutter background and detect the small target effectively.

  20. Subpixel edge detection method based on low-frequency filtering

    Science.gov (United States)

    Bylinsky, Yosip Y.; Kotyra, Andrzej; Gromaszek, Konrad; Iskakova, Aigul

    2016-09-01

    A method of edge detection in images is proposed basing that based on low-frequency filtering. The method uses polynomial interpolation to determine the coordinates of the edge point with subpixel accuracy. Some experiments have been results also have been provided.

  1. Noise analysis for sensitivity-based structural damage detection

    Institute of Scientific and Technical Information of China (English)

    YIN Tao; ZHU Hong-ping; YU Ling

    2007-01-01

    As vibration-based structural damage detection methods are easily affected by environmental noise, a new statistic-based noise analysis method is proposed together with the Monte Carlo technique to investigate the influence of experimental noise of modal data on sensitivity-based damage detection methods. Different from the commonly used random perturbation technique, the proposed technique is deduced directly by Moore-Penrose generalized inverse of the sensitivity matrix, which does not only make the analysis process more efficient but also can analyze the influence of noise on both frequencies and mode shapes for three commonly used sensitivity-based damage detection methods in a similar way. A one-story portal frame is adopted to evaluate the efficiency of the proposed noise analysis technique.

  2. Automatic Vehicle License Recognition Based on Video Vehicular Detection System

    Institute of Scientific and Technical Information of China (English)

    YANG Zhaoxuan; CHEN Yang; HE Yinghua; WU Jun

    2006-01-01

    Traditional methods of license character extraction cannot meet the requirements of recognition accuracy and speed rendered by the video vehicular detection system.Therefore, a license plate localization method based on multi-scale edge detection and a character segmentation algorithm based on Markov random field model is presented.Results of experiments demonstrate that the method yields more accurate license character extraction in contrast to traditional localization method based on edge detection by difference operator and character segmentation based on threshold.The accuracy increases from 90% to 94% under preferable illumination, while under poor condition, it increases more than 5%.When the two improved algorithms are used, the accuracy and speed of automatic license recognition meet the system's requirement even under the noisy circumstance or uneven illumination.

  3. Automated Contour Detection for Intravascular Ultrasound Image Sequences Based on Fast Active Contour Algorithm

    Institute of Scientific and Technical Information of China (English)

    DONG Hai-yan; WANG Hui-nan

    2006-01-01

    Intravascular ultrasound can provide high-resolution real-time crosssectional images about lumen, plaque and tissue. Traditionally, the luminal border and medial-adventitial border are traced manually. This process is extremely timeconsuming and the subjective difference would be large. In this paper, a new automated contour detection method is introduced based on fast active contour model.Experimental results found that lumen and vessel area measurements after automated detection showed good agreement with manual tracings with high correlation coefficients (0.94 and 0.95, respectively) and small system difference ( -0.32 and 0.56, respectively). So it can be a reliable and accurate diagnostic tool.

  4. Multi-core Processors based Network Intrusion Detection Method

    Directory of Open Access Journals (Sweden)

    Ziqian Wan

    2012-09-01

    Full Text Available It is becoming increasingly hard to build an intrusion detection system (IDS, because of the higher traffic throughput and the rising sophistication of attacking. Scale will be an important issue to address in the intrusion detection area. For hardware, tomorrow’s performance gains will come from multi-core architectures in which a number of CPU executes concurrently. We take the advantage of multi-core processors’ full power for intrusion detection in this work. We present an intrusion detection system based on the Snort open-source IDS that exploits the computational power of MIPS multi-core architecture to offload the costly pattern matching operations from the CPU, and thus increase the system’s processing throughput. A preliminary experiment demonstrates the potential of this system. The experiment results indicate that this method can be used effectively to speed up intrusion detection systems.

  5. Distributed intrusion detection system based on fuzzy rules

    Science.gov (United States)

    Qiao, Peili; Su, Jie; Liu, Yahui

    2006-04-01

    Computational Intelligence is the theory and method solving problems by simulating the intelligence of human using computer and it is the development of Artificial Intelligence. Fuzzy Technique is one of the most important theories of computational Intelligence. Genetic Fuzzy Technique and Neuro-Fuzzy Technique are the combination of Fuzzy Technique and novel techniques. This paper gives a distributed intrusion detection system based on fuzzy rules that has the characters of distributed parallel processing, self-organization, self-learning and self-adaptation by the using of Neuro-Fuzzy Technique and Genetic Fuzzy Technique. Specially, fuzzy decision technique can be used to reduce false detection. The results of the simulation experiment show that this intrusion detection system model has the characteristics of distributed, error tolerance, dynamic learning, and adaptation. It solves the problem of low identifying rate to new attacks and hidden attacks. The false detection rate is low. This approach is efficient to the distributed intrusion detection.

  6. Nanomaterial-Based Biosensors for Detection of Pesticides and Explosives

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Jun; Lin, Yuehe

    2009-01-01

    In this chapter, we describe nanomaterial-based biosensors for detecting OP pesticides and explosives. CNTs and functionalized silica nanoparticles have been chosen for this study. The biosensors were combined with the flow-injection system, providing great advantages for onsite, real-time, and continuous detection of environmental pollutants such as OPs and TNT. The sensors take advantage of the electrocatalytic properties of CNTs, which makes it feasible to achieve a sensitive electrochemical detection of the products from enzymatic reactions at low potential. This approach uses a large aspect ratio of silica nanoparticles, which can be used as a carrier for loading a large amount of electroactive species, such as poly(guanine), for amplified detection of explosives. These methods offer a new environmental monitoring tool for rapid, inexpensive, and highly sensitive detection of OPs or TNT compounds.

  7. Proton magnetic resonance spectroscopy detection of neurotransmitters in dorsomedial medulla correlate with spontaneous baroreceptor reflex function.

    Science.gov (United States)

    Garcia-Espinosa, Maria A; Shaltout, Hossam A; Olson, John; Westwood, Brian M; Robbins, Mike E; Link, Kerry; Diz, Debra I

    2010-02-01

    Control of heart rate variability via modulation of sympathovagal balance is a key function of nucleus tractus solitarii and the dorsal motor nucleus of the vagus localized in the dorsomedial medulla oblongata. Normal blood pressure regulation involves precise balance of glutamate (Glu)-glutamine-gamma-aminobutyric acid transmitter systems, and angiotensin II modulates these transmitters to produce tonic suppression of reflex function. It is not known, however, whether other brain transmitters/metabolites are indicators of baroreflex function. This study establishes the concept that comprehensive baseline transmitter/metabolite profiles obtained using in vivo (1)H magnetic resonance spectroscopy in rats with well-characterized differences in resting blood pressure and baroreflex function can be used as indices of autonomic balance or baroreflex sensitivity. Transgenic rats with over-expression of renin [m(Ren2)27] or under-expression of glial-angiotensinogen (ASrAogen) were compared with Sprague-Dawley rats. Glu concentration in the dorsal medulla is significantly higher in ASrAogen rats compared with either Sprague-Dawley or (mRen2)27 rats. Glu levels and the ratio of Glu:glutamine correlated positively with indices of higher vagal tone consistent with the importance of these neurotransmitters in baroreflex function. Interestingly, the levels of choline-containing metabolites showed a significant positive correlation with spontaneous baroreflex sensitivity and a negative correlation with sympathetic tone. Thus, we demonstrate the concept that noninvasive assessment of neurochemical biomarkers may be used as an index of baroreflex sensitivity.

  8. Correlation between automatic detection of malaria on thin film and experts' parasitaemia scores

    Science.gov (United States)

    Sunarko, Budi; Williams, Simon; Prescott, William R.; Byker, Scott M.; Bottema, Murk J.

    2017-03-01

    An algorithm was developed to diagnose the presence of malaria and to estimate the depth of infection by automatically counting individual normal and infected erythrocytes in images of thin blood smears. During the training stage, the parameters of the algorithm were optimized to maximize correlation with estimates of parasitaemia from expert human observers. The correlation was tested on a set of 1590 images from seven thin film blood smears. The correlation between the results from the algorithm and expert human readers was r = 0.836. Results indicate that reliable estimates of parasitaemia may be achieved by computational image analysis methods applied to images of thin film smears. Meanwhile, compared to biological experiments, the algorithm fitted well the three high parasitaemia slides and a mid-level parasitaemia slide, and overestimated the three low parasitaemia slides. To improve the parasitaemia estimation, the sources of the overestimation were identified. Emphasis is laid on the importance of further research in order to identify parasites independently of their erythrocyte hosts

  9. Enhancing Community Detection By Affinity-based Edge Weighting Scheme

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Andy [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sanders, Geoffrey [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Henson, Van [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Vassilevski, Panayot [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-10-05

    Community detection refers to an important graph analytics problem of finding a set of densely-connected subgraphs in a graph and has gained a great deal of interest recently. The performance of current community detection algorithms is limited by an inherent constraint of unweighted graphs that offer very little information on their internal community structures. In this paper, we propose a new scheme to address this issue that weights the edges in a given graph based on recently proposed vertex affinity. The vertex affinity quantifies the proximity between two vertices in terms of their clustering strength, and therefore, it is ideal for graph analytics applications such as community detection. We also demonstrate that the affinity-based edge weighting scheme can improve the performance of community detection algorithms significantly.

  10. a Uav-Based ROE Deer Fawn Detection System

    Science.gov (United States)

    Israel, M.

    2011-09-01

    This paper presents a UAV based remote sensing system for the detection of fawns in the meadows. There is a high demand because during pasture mowing many wild animals, especially roe deer fawns are killed by mowing machines. The system was tested in several real situations especially with differing weather and iluminating conditions. Its primary sensor is a lightweight thermal infrared camera. The images are captured onboard of the flight system and also transmitted as analog video stream to the ground station, where the user can follow the camera live stream on a monitor for manual animal detection. Beside a high detection rate a fast workflow is another very important objective for this application. Therefore a waypoint planning software was developed that accelerates the workflow. At adequate illuminating and weather conditions the presented UAV-based fawn detection via thermal imaging is a comfortable, fast and reliable method.

  11. Using Case-Based Reasoning for detecting computer virus

    Directory of Open Access Journals (Sweden)

    Abdellatif Berkat

    2011-07-01

    Full Text Available The typical antivirus approach consists of waiting for a number of computers to be infected, detecting the virus, designing a solution, delivering and deploying a solution. In such a situation, it is very difficult to prevent every machine from being compromised by viruses. In this paper, we propose a new method, for detecting computer viruses, that is based on the technique of Case-Based Reasoning (CBR. In this method: (1 even new viruses that do not exist in the database can be detected (2 The updating of the virus database is done automatically without connecting to the Internet. Whenever a new virus is detected, it will be automatically added to the database used by our application. This presents a major advantage

  12. The Unknown Computer Viruses Detection Based on Similarity

    Science.gov (United States)

    Liu, Zhongda; Nakaya, Naoshi; Koui, Yuuji

    New computer viruses are continually being generated and they cause damage all over the world. In general, current anti-virus software detects viruses by matching a pattern based on the signature; thus, unknown viruses without any signature cannot be detected. Although there are some static analysis technologies that do not depend on signatures, virus writers often use code obfuscation techniques, which make it difficult to execute a code analysis. As is generally known, unknown viruses and known viruses share a common feature. In this paper we propose a new static analysis technology that can circumvent code obfuscation to extract the common feature and detect unknown viruses based on similarity. The results of evaluation experiments demonstrated that this technique is able to detect unknown viruses without false positives.

  13. A Detection Scheme for Cavity-based Dark Matter Searches

    CERN Document Server

    Bukhari, M H S

    2016-01-01

    We present here proposal of a scheme and some useful ideas for resonant cavity-based detection of cold dark matter axions with hope to improve the existing endeavors. The scheme is based upon our idea of a detector, which incorporates an integrated tunnel diode and a GaAs HEMT or HFET, High Electron Mobility Transistor or Heterogenous FET, for resonance detection and amplification from a resonant cavity (in a strong transverse magnetic field from a cylindrical array of halbach magnets). The idea of a TD-oscillator-amplifier combination could possibly serve as a more sensitive and viable resonance detection regime while maintaining an excellent performance with low noise temperature, whereas the halbach magnets array may offer a compact and permanent solution replacing the conventional electromagnets scheme. We believe that all these factors could possibly increase the sensitivity and accuracy of axion detection searches and reduce complications (and associated costs) in the experiments, in addition to help re...

  14. Stratification-Based Outlier Detection over the Deep Web.

    Science.gov (United States)

    Xian, Xuefeng; Zhao, Pengpeng; Sheng, Victor S; Fang, Ligang; Gu, Caidong; Yang, Yuanfeng; Cui, Zhiming

    2016-01-01

    For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribution of this paper is to develop a new data mining method for outlier detection over deep web. In our approach, the query space of a deep web data source is stratified based on a pilot sample. Neighborhood sampling and uncertainty sampling are developed in this paper with the goal of improving recall and precision based on stratification. Finally, a careful performance evaluation of our algorithm confirms that our approach can effectively detect outliers in deep web.

  15. Arduino-based noise robust online heart-rate detection.

    Science.gov (United States)

    Das, Sangita; Pal, Saurabh; Mitra, Madhuchhanda

    2017-04-01

    This paper introduces a noise robust real time heart rate detection system from electrocardiogram (ECG) data. An online data acquisition system is developed to collect ECG signals from human subjects. Heart rate is detected using window-based autocorrelation peak localisation technique. A low-cost Arduino UNO board is used to implement the complete automated process. The performance of the system is compared with PC-based heart rate detection technique. Accuracy of the system is validated through simulated noisy ECG data with various levels of signal to noise ratio (SNR). The mean percentage error of detected heart rate is found to be 0.72% for the noisy database with five different noise levels.

  16. Moving object detection in aerial video based on spatiotemporal saliency

    Institute of Scientific and Technical Information of China (English)

    Shen Hao; Li Shuxiao; Zhu Chengfei; Chang Hongxing; Zhang Jinglan

    2013-01-01

    In this paper, the problem of moving object detection in aerial video is addressed. While motion cues have been extensively exploited in the literature, how to use spatial information is still an open problem. To deal with this issue, we propose a novel hierarchical moving target detection method based on spatiotemporal saliency. Temporal saliency is used to get a coarse segmentation, and spatial saliency is extracted to obtain the object’s appearance details in candidate motion regions. Finally, by combining temporal and spatial saliency information, we can get refined detec-tion results. Additionally, in order to give a full description of the object distribution, spatial sal-iency is detected in both pixel and region levels based on local contrast. Experiments conducted on the VIVID dataset show that the proposed method is efficient and accurate.

  17. Statistical detection of structural damage based on model reduction

    Institute of Scientific and Technical Information of China (English)

    Tao YIN; Heung-fai LAM; Hong-ping ZHU

    2009-01-01

    This paper proposes a statistical method for damage detection based on the finite element (FE) model reduction technique that utilizes measured modal data with a limited number of sensors.A deterministic damage detection process is formulated based on the model reduction technique.The probabilistic process is integrated into the deterministic damage detection process using a perturbation technique,resulting in a statistical structural damage detection method.This is achieved by deriving the firstand second-order partial derivatives of uncertain parameters,such as elasticity of the damaged member,with respect to the measurement noise,which allows expectation and covariance matrix of the uncertain parameters to be calculated.Besides the theoretical development,this paper reports numerical verification of the proposed method using a portal frame example and Monte Carlo simulation.

  18. Stratification-Based Outlier Detection over the Deep Web

    Directory of Open Access Journals (Sweden)

    Xuefeng Xian

    2016-01-01

    Full Text Available For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribution of this paper is to develop a new data mining method for outlier detection over deep web. In our approach, the query space of a deep web data source is stratified based on a pilot sample. Neighborhood sampling and uncertainty sampling are developed in this paper with the goal of improving recall and precision based on stratification. Finally, a careful performance evaluation of our algorithm confirms that our approach can effectively detect outliers in deep web.

  19. a Enzyme-Based Electrochemical Sensor for Sensitive Detection of Organophosphorus Pesticides

    Science.gov (United States)

    Zhou, Nong; Li, Chengyong; Mo, Rijian; Zhang, Peng; He, Lei; Nie, Fanghong; Su, Weiming; Liu, Shucheng; Gao, Jing; Shao, Haiyan; Qian, Zhong-Ji; Ji, Hongwu

    2016-12-01

    A sensitive and fast sensor for quantitative detection of organophosphorus pesticides (OPs) is obtained using acetylcholinesterase (AChE) biosensor based on graphene oxide (GO)-chitosan (CS) composite film. This new biosensor is prepared via depositing GO-CS composite film on glassy carbon electrode (GCE) and then assembling AChE on the composite film. The GO-CS composite film shows an excellent biocompatibility with AChE and enhances immobilization efficiency of AChE. GO homogeneously disperses in the GO-CS composite films and exhibits excellent electrocatalytic activity to thiocholine oxidation, which is from acetylthiocholine catalyzed by AChE. The results show that the inhibition of carbaryl/trichlorfon on AChE activity is proportional to the concentration of carbaryl/trichlorfon. The detection of linear range for carbaryl is from 10nM to 100nM and the correlation coefficients of 0.993. The detection limit for carbaryl is calculated to be about 2.5nM. In addition, the detection of linear range for trichlorfon is from 10nM to 60nM and the correlation coefficients of 0.994. The detection limit for trichlorfon is calculated to be about 1.2nM. This biosensor provides a new promising tool for trace organophosphorus pesticide detection.

  20. A GPU-based Real-time Software Correlation System for the Murchison Widefield Array Prototype

    Science.gov (United States)

    Wayth, Randall B.; Greenhill, Lincoln J.; Briggs, Frank H.

    2009-08-01

    Modern graphics processing units (GPUs) are inexpensive commodity hardware that offer Tflop/s theoretical computing capacity. GPUs are well suited to many compute-intensive tasks including digital signal processing. We describe the implementation and performance of a GPU-based digital correlator for radio astronomy. The correlator is implemented using the NVIDIA CUDA development environment. We evaluate three design options on two generations of NVIDIA hardware. The different designs utilize the internal registers, shared memory, and multiprocessors in different ways. We find that optimal performance is achieved with the design that minimizes global memory reads on recent generations of hardware. The GPU-based correlator outperforms a single-threaded CPU equivalent by a factor of 60 for a 32-antenna array, and runs on commodity PC hardware. The extra compute capability provided by the GPU maximizes the correlation capability of a PC while retaining the fast development time associated with using standard hardware, networking, and programming languages. In this way, a GPU-based correlation system represents a middle ground in design space between high performance, custom-built hardware, and pure CPU-based software correlation. The correlator was deployed at the Murchison Widefield Array 32-antenna prototype system where it ran in real time for extended periods. We briefly describe the data capture, streaming, and correlation system for the prototype array.

  1. [Quantitative specific detection of Staphylococcus aureus based on recombinant lysostaphin and ATP bioluminescence].

    Science.gov (United States)

    Li, Yuyuan; Mi, Zhiqiang; An, Xiaoping; Zhou, Yusen; Tong, Yigang

    2014-08-01

    Quantitative specific detection of Staphylococcus aureus is based on recombinant lysostaphin and ATP bioluminescence. To produce recombinant lysostaphin, the lysostaphin gene was chemically synthesized and inserted it into prokaryotic expression vector pQE30, and the resulting expression plasmid pQE30-Lys was transformed into E. coli M15 for expressing lysostaphin with IPTG induction. The recombinant protein was purified by Ni(2+)-NTA affinity chromatography. Staphylococcus aureus was detected by the recombinant lysostaphin with ATP bioluminescence, and plate count method. The results of the two methods were compared. The recombinant lysostaphin was successfully expressed, and a method of quantitative specific detection of S. aureus has been established, which showed a significant linear correlation with the colony counting. The detection method developed has good perspective to quantify S. aureus.

  2. Adaptive stochastic resonance method for weak signal detection based on particle swarm optimization

    Institute of Scientific and Technical Information of China (English)

    XING; Hongyan; ZHANG; Qiang; LU; Chunxia

    2015-01-01

    In order to solve the parameter adjustment problems of adaptive stochastic resonance system in the areas of weak signal detection,this article presents a new method to enhance the detection efficiency and availability in the system of two-dimensional Duffing based on particle swarm optimization.First,the influence of different parameters on the detection performance is analyzed respectively.The correlation between parameter adjustment and stochastic resonance effect is also discussed and converted to the problem of multi-parameter optimization.Second,the experiments including typical system and sea clutter data are conducted to verify the effect of the proposed method.Results show that the proposed method is highly effective to detect weak signal from chaotic background,and enhance the output SNR greatly.

  3. The Unknown Computer Viruses Detection Based on Similarity

    OpenAIRE

    Liu, Zhongda; NAKAYA, Naoshi; KOUI, Yuuji

    2009-01-01

    New computer viruses are continually being generated and they cause damage all over the world. In general, current anti-virus software detects viruses by matching a pattern based on the signature; thus, unknown viruses without any signature cannot be detected. Although there are some static analysis technologies that do not depend on signatures, virus writers often use code obfuscation techniques, which make it difficult to execute a code analysis. As is generally known, unknown viruses and k...

  4. Compressive sensing holography based on optical heterodyne detection

    Science.gov (United States)

    Hu, Youjun; Zhou, Dingfu; Yuan, Sheng; Wei, Yayun; Wang, Mengting; Zhou, Xin

    2016-12-01

    In this paper, compressive sensing holography based on optical heterodyne detection is presented, which can photograph the hologram of an object. The complex hologram is composed of a sine-hologram and a cosine-hologram. A single pixel photoelectric conversion element is used to detect the time-varying optical field which contains the amplitude and phase information of the transmitted light, and a simulation result is demonstrated further by recording the Fresnel hologram of a complex amplitude object.

  5. Fabric Defect Detection Based on Regional Growing PCNN

    OpenAIRE

    2012-01-01

    This paper presents an adaptive image segmentation method based on a new Regional Growing Pulse Coupled Neural Network (PCNN) model for detecting fabric defects. In this method, the pixels of analyzed image are mapped on the neurons in a pulse coupled neural network. Improved PCNN model and regional growing theory are combined in the light of the requirements for fabric defect detection. And the mean and variance value of the defect-free images are introduced into this model. The validation t...

  6. Edge Detection of Concrete Mesostructure Based on DIS Operator

    OpenAIRE

    Feng, Bin; Xu, Zicheng; Xia, Jin; Jin, Shijie; Jin, Weiliang

    2016-01-01

    Aggregate edge detection is the basis of creating concrete mesoscale model, which is applied to analyze concrete mesoscale characteristics. A concrete digital image edge detection method using DIS operator is presented in this paper. Mean filter, multi-scale filter, and Gaussian filter are compared on the effect of concrete image noise reduction. Based on the result, Gaussian filter is the most optimum method to reduce image noise and remain aggregate edge distinct. Sobel operator, Laplacian ...

  7. Polarization-Based Radar Detection in Sea Clutter

    Science.gov (United States)

    2015-02-27

    Report 3. DATES COVERED (From - To) 01-04-2012 to 28-02-2015 4. TITLE AND SUBTITLE Polarization -Based Radar Detection in Sea Clutter 5a...14. ABSTRACT The goal of the proposed research is to characterize and model polarization -related behaviors of sea clutter and to use these models...that is to be exploited in this new form of detection is termed polarization mode dispersion (PMD), which is characterized by a spread in the received

  8. Inverse Problem Solution in Landmines Detection Based on Active Thermography

    Directory of Open Access Journals (Sweden)

    B. Szymanik

    2014-12-01

    Full Text Available Landmines still affect numerous territories in the whole world and pose a serious threat, mostly to civilians. Widely used non-metallic landmines are undetectable using metal detector. Therefore, there is an urging need to improve methods of detecting such objects. In the present study we introduce relatively new method of landmines' detection: active infrared thermography with microwave excitation. In this paper we present the optimization based method of solving inverse problem for microwave heating. This technique will be used in the reconstruction of detected landmines geometric and material properties.

  9. Image edge detection based on multi-fractal spectrum analysis

    Institute of Scientific and Technical Information of China (English)

    WANG Shao-yuan; WANG Yao-nan

    2006-01-01

    In this paper,an image edge detection method based on multi-fractal spectrum analysis is presented.The coarse grain H(o)lder exponent of the image pixels is first computed,then,its multi-fractal spectrum is estimated by the kernel estimation method.Finally,the image edge detection is done by means of different multi-fractal spectrum values.Simulation results show that this method is efficient and has better locality compared with the traditional edge detection methods such as the Sobel method.

  10. QRS Detection Based on an Advanced Multilevel Algorithm

    Directory of Open Access Journals (Sweden)

    Wissam Jenkal

    2016-01-01

    Full Text Available This paper presents an advanced multilevel algorithm used for the QRS complex detection. This method is based on three levels. The first permits the extraction of higher peaks using an adaptive thresholding technique. The second allows the QRS region detection. The last level permits the detection of Q, R and S waves. The proposed algorithm shows interesting results compared to recently published methods. The perspective of this work is the implementation of this method on an embedded system for a real time ECG monitoring system.

  11. MIXED SCHEME FOR IMAGE EDGE DETECTION BASED ON WAVELET TRANSFORM

    Institute of Scientific and Technical Information of China (English)

    Xie Hongmei; Yu Bianzhang; Zhao Jian

    2004-01-01

    A mixed scheme based on Wavelet Transformation (WT) is proposed for image edge detection. The scheme combines the wavelet transform and traditional Sobel and LoG (Laplacian of Gaussian) operator edge-detection algorithms. The precise theory analysis is given to show that the wavelet transformation has an advantage for signal processing. Simulation results show that the new scheme is better than only using the Sobel or LoG methods. Complexity analysis is also given and the conclusion is acceptable, therefore the proposed scheme is effective for edge detection.

  12. INTRUSION DETECTION BASED ON THE SECOND-ORDER STOCHASTIC MODEL

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    This paper presents a new method based on a second-order stochastic model for computer intrusion detection. The results show that the performance of the second-order stochastic model is better than that of a first-order stochastic model. In this study, different window sizes are also used to test the performance of the model. The detection results show that the second-order stochastic model is not so sensitive to the window size, comparing with the first-order stochastic model and other previous researches. The detection result of window sizes 6 and 10 is the same.

  13. Research and Implementation of Unsupervised Clustering-Based Intrusion Detection

    Institute of Scientific and Technical Information of China (English)

    LuoMin; ZhangHuan-guo; WangLi-na

    2003-01-01

    An unsupervised clustering-based intrusion detection algorithm is discussed in this paper. The basic idea of the algorithm is to produce the cluster by comparing the distances of unlabeled training data sets. With the classified data instances, anomaly data clusters can be easily identified by normal duster ratio and the identified cluster can be used in real data detection. The benefit of the algorithm is that it doesn't need labeled training data sets. The experiment coneludes that this approach can detect unknown intrusions efficiently in the real network connections via using the data sets of KDD99.

  14. Vision-Based People Detection System for Heavy Machine Applications

    Directory of Open Access Journals (Sweden)

    Vincent Fremont

    2016-01-01

    Full Text Available This paper presents a vision-based people detection system for improving safety in heavy machines. We propose a perception system composed of a monocular fisheye camera and a LiDAR. Fisheye cameras have the advantage of a wide field-of-view, but the strong distortions that they create must be handled at the detection stage. Since people detection in fisheye images has not been well studied, we focus on investigating and quantifying the impact that strong radial distortions have on the appearance of people, and we propose approaches for handling this specificity, adapted from state-of-the-art people detection approaches. These adaptive approaches nevertheless have the drawback of high computational cost and complexity. Consequently, we also present a framework for harnessing the LiDAR modality in order to enhance the detection algorithm for different camera positions. A sequential LiDAR-based fusion architecture is used, which addresses directly the problem of reducing false detections and computational cost in an exclusively vision-based system. A heavy machine dataset was built, and different experiments were carried out to evaluate the performance of the system. The results are promising, in terms of both processing speed and performance.

  15. Cell-based detection of microbial biomaterial contaminations.

    Science.gov (United States)

    Roch, Toralf; Ma, Nan; Kratz, Karl; Lendlein, Andreas

    2015-01-01

    A major challenge in biomaterial synthesis and functionalization is the prevention of microbial contaminations such as endotoxins (lipopolysaccharides (LPS)). In addition to LPS, which are exclusively expressed by Gram negative bacteria, also other microbial products derived from fungi or Gram positive bacteria can be found as contaminations in research laboratories. Typically, the Limulus amebocyte lysate (LAL)-test is used to determine the endotoxin levels of medical devices. However, this test fails to detect material-bound LPS and other microbial contaminations and, as demonstrated in this study, detects LPS from various bacterial species with different sensitivities.In this work, a cell-based assay using genetically engineered RAW macrophages, which detect not only soluble but also material-bound microbial contaminations is introduced.The sensitivity of this cell-line towards different LPS species and different heat-inactivated microbes was investigated. As proof of principle a soft hydrophobic poly(n-butyl acrylate) network (cPnBA), which may due to adhesive properties strongly bind microbes, was deliberately contaminated with heat-inactivated bacteria. While the LAL-test failed to detect the microbial contamination, the cell-based assay clearly detected material-bound microbial contaminations. Our data demonstrate that a cell-based detection system should routinely be used as supplement to the LAL-test to determine microbial contaminations of biomaterials.

  16. Deceiving entropy-based DoS detection

    Science.gov (United States)

    Özçelik, Ä.°lker; Brooks, Richard R.

    2014-06-01

    Denial of Service (DoS) attacks disable network services for legitimate users. A McAfee report shows that eight out of ten Critical Infrastructure Providers (CIPs) surveyed had a significant Distributed DoS (DDoS) attack in 2010.1 Researchers proposed many approaches for detecting these attacks in the past decade. Anomaly based DoS detection is the most common. In this approach, the detector uses statistical features; such as the entropy of incoming packet header fields like source IP addresses or protocol type. It calculates the observed statistical feature and triggers an alarm if an extreme deviation occurs. However, intrusion detection systems (IDS) using entropy based detection can be fooled by spoofing. An attacker can sniff the network to collect header field data of network packets coming from distributed nodes on the Internet and fuses them to calculate the entropy of normal background traffic. Then s/he can spoof attack packets to keep the entropy value in the expected range during the attack. In this study, we present a proof of concept entropy spoofing attack that deceives entropy based detection approaches. Our preliminary results show that spoofing attacks cause significant detection performance degradation.

  17. Vision Based Obstacle Detection mechanism of a Fixed Wing UAV

    Directory of Open Access Journals (Sweden)

    S.N. Omkar

    2014-03-01

    Full Text Available In this paper we have developed a vision based navigation and obstacle detection mechanism for unmanned aerial vehicles (UAVs which can be used effectively in GPS denied regions as well as in regions where remote controlled UAV navigation is impossible thus making the UAV more versatile and fully autonomous. We used a fixed single onboard video camera on the UAV that extracts images of the environment of a UAV. These images are then processed and detect an obstacle in the path if any. This method is effective in detecting dark as well as light coloured obstacles in the vicinity of the UAV. We developed two algorithms. The first one is to detect the horizon and land in the images extracted from the camera and to detect an obstacle in its path. The second one is specifically to detect a light coloured obstacle in the environment thus making our method more precise. The time taken for processing of the images and generating a result is very small thus this algorithm is also fit to be used in real time applications. These Algorithms are more effective than previously developed in this field because this algorithm does the detection of any obstacle without knowing the size of it beforehand. This algorithm is also capable of detecting light coloured obstacles in the sky which otherwise might be missed by an UAV or even a human pilot sometimes. Thus it makes the navigation more precise.

  18. THE CONSTRUCTIONS OF ALMOST BINARY SEQUENCE PAIRS WITH THREE-LEVEL CORRELATION BASED ON CYCLOTOMY

    Institute of Scientific and Technical Information of China (English)

    Peng Xiuping; Xu Chengqian

    2012-01-01

    In this paper,a new class of almost binary sequence pair with a single zero element is presented.The almost binary sequence pairs with three-level correlation are constructed based on cyclotomic numbers of order 2,4,and 6.Most of them have good correlation and balance property,whose maximum nontrivial correlation magnitudes are 2 and the difference between the numbers of occurrence of +1's and -1's are 0 or 1.In addition,the corresponding binary sequence pairs are investigated as well and we can also get some kinds of binary sequence pairs with optimum balance and good correlation.

  19. Aptamer-based microcantilever biosensor for ultrasensitive detection of tumor marker nucleolin.

    Science.gov (United States)

    Li, Huiyan; Bai, Xiaojing; Wang, Nan; Chen, Xuejuan; Li, Jing; Zhang, Zhe; Tang, Jilin

    2016-01-01

    We present an aptamer-based microcantilever biosensor for label-free detection of nucleolin. The sensor cantilevers in the microcantilever array were functionalized with nucleolin aptamer (AS1411) while the reference cantilevers were modified by 6-mercapto-1-hexanol (MCH) to eliminate environmental disturbances. The interaction between nucleolin and AS1411 induced surface stress changes, resulting in a differential deflection between sensor and reference cantilevers. The amplitude of differential cantilever deflection had a good linear relationship with the nucleolin concentration ranging from 10 nM to 250 nM with a correlation coefficient of 0.999. The detection limit was about 1.0 nM, at a signal-to-noise ratio of 3. The aptamer-based microcantilever sensor demonstrated good selectivity and was facile, rapid, and reagentless. Our results show the potential for the application of microcantilever biosensor system as a powerful tool to detect tumor markers with high sensitivity and specificity.

  20. MIrExpress: A Database for Gene Coexpression Correlation in Immune Cells Based on Mutual Information and Pearson Correlation

    OpenAIRE

    Luman Wang; Qiaochu Mo; Jianxin Wang

    2015-01-01

    Most current gene coexpression databases support the analysis for linear correlation of gene pairs, but not nonlinear correlation of them, which hinders precisely evaluating the gene-gene coexpression strengths. Here, we report a new database, MIrExpress, which takes advantage of the information theory, as well as the Pearson linear correlation method, to measure the linear correlation, nonlinear correlation, and their hybrid of cell-specific gene coexpressions in immune cells. For a given ge...

  1. Detection of luminescent single ultrasmall silicon nanoparticles using fluctuation correlation spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Akcakir, O. [Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States); Therrien, J. [Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States); Belomoin, G. [Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States); Barry, N. [Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States); Muller, J. D. [Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States); Gratton, E. [Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States); Nayfeh, M. [Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States)

    2000-04-03

    We dispersed electrochemical etched Si into a colloid of ultrasmall blue luminescent nanoparticles, observable with the naked eye, in room light. We use two-photon near-infrared femtosecond excitation at 780 nm to record the fluctuating time series of the luminescence, and determine the number density, brightness, and size of diffusing fluorescent particles. The luminescence efficiency of particles is high enough such that we are able to detect a single particle, in a focal volume, of 1 pcm3. The measurements yield a particle size of 1 nm, consistent with direct imaging by transmission electron microscopy. They also yield an excitation efficiency under two-photon excitation two to threefold larger than that of fluorescein. Detection of single particles paves the way for their use as labels in biosensing applications. (c) 2000 American Institute of Physics.

  2. SUSY-QCD corrections for direct detection of neutralino dark matter and correlations with relic density

    Science.gov (United States)

    Klasen, M.; Kovařík, K.; Steppeler, P.

    2016-11-01

    In this paper, we perform a full next-to-leading order (NLO) QCD calculation of neutralino scattering on protons or neutrons in the minimal supersymmetric standard model. We match the results of the NLO QCD calculation to the scalar and axial-vector operators in the effective field theory approach. These govern the spin-independent and spin-dependent detection rates, respectively. The calculations have been performed for general bino, wino and higgsino decompositions of neutralino dark matter and required a novel tensor reduction method of loop integrals with vanishing relative velocities and Gram determinants. Numerically, the NLO QCD effects are shown to be of at least of similar size and sometimes larger than the currently estimated nuclear uncertainties. We also demonstrate the interplay of the direct detection rate with the relic density when consistently analyzed with the program dm@nlo.

  3. Analysis of Vehicle Detection with WSN-Based Ultrasonic Sensors

    Directory of Open Access Journals (Sweden)

    Youngtae Jo

    2014-08-01

    Full Text Available Existing traffic information acquisition systems suffer from high cost and low scalability. To address these problems, the application of wireless sensor networks (WSNs has been studied, as WSN-based systems are highly scalable and have a low cost of installing and replacing the systems. Magnetic, acoustic and accelerometer sensors have been considered for WSN-based traffic surveillance, but the use of ultrasonic sensors has not been studied. The limitations of WSN-based systems make it necessary to employ power saving methods and vehicle detection algorithms with low computational complexity. In this paper, we model and analyze optimal power saving methodologies for an ultrasonic sensor and present a computationally-efficient vehicle detection algorithm using ultrasonic data. The proposed methodologies are implemented and evaluated with a tiny microprocessor on real roads. The evaluation results show that the low computational complexity of our algorithm does not compromise the accuracy of vehicle detection.

  4. Analysis of vehicle detection with WSN-based ultrasonic sensors.

    Science.gov (United States)

    Jo, Youngtae; Jung, Inbum

    2014-08-04

    Existing traffic information acquisition systems suffer from high cost and low scalability. To address these problems, the application of wireless sensor networks (WSNs) has been studied, as WSN-based systems are highly scalable and have a low cost of installing and replacing the systems. Magnetic, acoustic and accelerometer sensors have been considered for WSN-based traffic surveillance, but the use of ultrasonic sensors has not been studied. The limitations of WSN-based systems make it necessary to employ power saving methods and vehicle detection algorithms with low computational complexity. In this paper, we model and analyze optimal power saving methodologies for an ultrasonic sensor and present a computationally-efficient vehicle detection algorithm using ultrasonic data. The proposed methodologies are implemented and evaluated with a tiny microprocessor on real roads. The evaluation results show that the low computational complexity of our algorithm does not compromise the accuracy of vehicle detection.

  5. Early Detection of Breast Cancer via Multi-plane Correlation Breast Imaging

    Science.gov (United States)

    2008-04-01

    outcome of this task was published in two articles the journal of Medical Physics in 2007 and 2008: Chawla A., Samei E., Saunders R., Abbey C...Delong D., Effect of dose reduction on the detection of mammographic lesions: A mathematical observer model analysis, Medical Physics 34: 3385-3398... Medical Physics 35: 1337-1345, 2008. Task 1.3: Apply the observer model on the image dataset to determine the optimum set of acquisition parameters

  6. The detection of bulk explosives using nuclear-based techniques

    Energy Technology Data Exchange (ETDEWEB)

    Morgado, R.E.; Gozani, T.; Seher, C.C.

    1988-01-01

    In 1986 we presented a rationale for the detection of bulk explosives based on nuclear techniques that addressed the requirements of civil aviation security in the airport environment. Since then, efforts have intensified to implement a system based on thermal neutron activation (TNA), with new work developing in fast neutron and energetic photon reactions. In this paper we will describe these techniques and present new results from laboratory and airport testing. Based on preliminary results, we contended in our earlier paper that nuclear-based techniques did provide sufficiently penetrating probes and distinguishable detectable reaction products to achieve the FAA operational goals; new data have supported this contention. The status of nuclear-based techniques for the detection of bulk explosives presently under investigation by the US Federal Aviation Administration (FAA) is reviewed. These include thermal neutron activation (TNA), fast neutron activation (FNA), the associated particle technique, nuclear resonance absorption, and photoneutron activation. The results of comprehensive airport testing of the TNA system performed during 1987-88 are summarized. From a technical point of view, nuclear-based techniques now represent the most comprehensive and feasible approach for meeting the operational criteria of detection, false alarms, and throughput. 9 refs., 5 figs., 2 tabs.

  7. Perceptual detection as a dynamical bistability phenomenon: A neurocomputational correlate of sensation

    Science.gov (United States)

    Deco, Gustavo; Pérez-Sanagustín, Mar; de Lafuente, Victor; Romo, Ranulfo

    2007-01-01

    Recent studies that combined psychophysical/neurophysiological experiments [de Lafuente V, Romo R (2005) Nat Neurosci 8:1698–1703] analyzed the responses from single neurons, recorded in several cortical areas of parietal and frontal lobes, while trained monkeys reported the presence or absence of a mechanical vibration of varying amplitude applied to skin of one fingertip. The analysis showed that the activity of primary somatosensory cortex neurons covaried with the stimulus strength but did not covary with the animal's perceptual reports. In contrast, the activity of medial premotor cortex (MPC) neurons did not covary with the stimulus strength but did covary with the animal's perceptual reports. Here, we address the question of how perceptual detection is computed in MPC. In particular, we regard perceptual detection as a bistable neurodynamical phenomenon reflected in the activity of MPC. We show that the activity of MPC is consistent with a decision-making-like scenario of fluctuation-driven computation that causes a probabilistic transition between two bistable states, one corresponding to the case in which the monkey detects the sensory input, the other corresponding to the case in which the monkey does not. Moreover, the high variability activity of MPC neurons both within and between trials reflects stochastic fluctuations that may play a crucial role in the monkey's probabilistic perceptual reports. PMID:18077434

  8. Detecting Chemically Modified DNA Bases Using Surface Enhanced Raman Spectroscopy.

    Science.gov (United States)

    Barhoumi, Aoune; Halas, Naomi J

    2011-12-15

    Post-translational modifications of DNA- changes in the chemical structure of individual bases that occur without changes in the DNA sequence- are known to alter gene expression. They are believed to result in frequently deleterious phenotypic changes, such as cancer. Methylation of adenine, methylation and hydroxymethylation of cytosine, and guanine oxidation are the primary DNA base modifications identified to date. Here we show it is possible to use surface enhanced Raman spectroscopy (SERS) to detect these primary DNA base modifications. SERS detection of modified DNA bases is label-free and requires minimal additional sample preparation, reducing the possibility of additional chemical modifications induced prior to measurement. This approach shows the feasibility of DNA base modification assessment as a potentially routine analysis that may be further developed for clinical diagnostics.

  9. Longitudinal correlation of 3D OCT to detect early stage erosion in bovine enamel

    Science.gov (United States)

    Aden, Abdirahman; Anderson, Paul; Burnett, Gary R.; Lynch, Richard J. M.; Tomlins, Peter H.

    2017-01-01

    Erosive tissue-loss in dental enamel is of significant clinical concern because the net loss of enamel is irreversible, however, initial erosion is reversible. Micro-hardness testing is a standard method for measuring initial erosion, but its invasive nature has led to the investigation of alternative measurement techniques. Optical coherence tomography (OCT) is an attractive alternative because of its ability to non-invasively image three-dimensional volumes. In this study, a four-dimensional OCT system is used to longitudinally measure bovine enamel undergoing a continuous erosive challenge. A new method of analyzing 3D OCT volumes is introduced that compares intensity projections of the specimen surface by calculating the slope of a linear regression line between corresponding pixel intensities and the associated correlation coefficient. The OCT correlation measurements are compared to micro-hardness data and found to exhibit a linear relationship. The results show that this method is a sensitive technique for the investigation of the formation of early stage erosive lesions.

  10. Longitudinal correlation of 3D OCT to detect early stage erosion in bovine enamel.

    Science.gov (United States)

    Aden, Abdirahman; Anderson, Paul; Burnett, Gary R; Lynch, Richard J M; Tomlins, Peter H

    2017-02-01

    Erosive tissue-loss in dental enamel is of significant clinical concern because the net loss of enamel is irreversible, however, initial erosion is reversible. Micro-hardness testing is a standard method for measuring initial erosion, but its invasive nature has led to the investigation of alternative measurement techniques. Optical coherence tomography (OCT) is an attractive alternative because of its ability to non-invasively image three-dimensional volumes. In this study, a four-dimensional OCT system is used to longitudinally measure bovine enamel undergoing a continuous erosive challenge. A new method of analyzing 3D OCT volumes is introduced that compares intensity projections of the specimen surface by calculating the slope of a linear regression line between corresponding pixel intensities and the associated correlation coefficient. The OCT correlation measurements are compared to micro-hardness data and found to exhibit a linear relationship. The results show that this method is a sensitive technique for the investigation of the formation of early stage erosive lesions.

  11. Obstacle detection of mobile robot based on data fusion

    Institute of Scientific and Technical Information of China (English)

    YUAN Xin; SU Li; SUN Li-ning

    2009-01-01

    To study the problem of obstacle detection based on multi-sensors data fusion, the multi-target track-ing theory and techniques are introduced into obstacle detection systems, and the exact position of obstacle can be determined. Data fusion problems are discussed directly based on achievable data from some sensors without considering the specific structure of each individual sensor. With respect to normal linear systems and nonlinear systems, the corresponding algorithms are proposed. The validity of the method is confirmed by simulation re-suits.

  12. Nanobiosensors Based on Localized Surface Plasmon Resonance for Biomarker Detection

    Directory of Open Access Journals (Sweden)

    Yoochan Hong

    2012-01-01

    Full Text Available Localized surface plasmon resonance (LSPR is induced by incident light when it interacts with noble metal nanoparticles that have smaller sizes than the wavelength of the incident light. Recently, LSPR-based nanobiosensors were developed as tools for highly sensitive, label-free, and flexible sensing techniques for the detection of biomolecular interactions. In this paper, we describe the basic principles of LSPR-based nanobiosensing techniques and LSPR sensor system for biomolecule sensing. We also discuss the challenges using LSPR nanobiosensors for detection of biomolecules as a biomarker.

  13. 3D face recognition algorithm based on detecting reliable components

    Institute of Scientific and Technical Information of China (English)

    Huang Wenjun; Zhou Xuebing; Niu Xiamu

    2007-01-01

    Fisherfaces algorithm is a popular method for face recognition. However, there exist some unstable components that degrade recognition performance. In this paper, we propose a method based on detecting reliable components to overcome the problem and introduce it to 3D face recognition. The reliable components are detected within the binary feature vector, which is generated from the Fisherfaces feature vector based on statistical properties, and is used for 3D face recognition as the final feature vector. Experimental results show that the reliable components feature vector is much more effective than the Fisherfaces feature vector for face recognition.

  14. An Improved Retransmission-based Network Steganography: Design and Detection

    Directory of Open Access Journals (Sweden)

    Jiangtao Zhai

    2013-01-01

    Full Text Available Network steganography is a covert communication technique that uses redundancies in network protocols to transfer secret information. The retransmission-based steganography (RSTEG embeds covert messages into the payload field of the intentionally retransmission packets. So its capacity is higher than most of the existing methods. Because TCP checksum field of the original packet is different from that of the retransmitted packet, RSTEG is not stealthy in fact. An improved method named IRSTEG is presented to resolve the flaw by introducing the payload compensation. Further, a method is proposed to detect IRSTEG based the payload segment comparison. Experiments show that the method can detect IRSTEG well.

  15. DNA methylation detection based on difference of base content

    Science.gov (United States)

    Sato, Shinobu; Ohtsuka, Keiichi; Honda, Satoshi; Sato, Yusuke; Takenaka, Shigeori

    2016-04-01

    Methylation frequently occurs in cytosines of CpG sites to regulate gene expression. The identification of aberrant methylation of certain genes is important for cancer marker analysis. The aim of this study was to determine the methylation frequency in DNA samples of unknown length and/or concentration. Unmethylated cytosine is known to be converted to thymine following bisulfite treatment and subsequent PCR. For this reason, the AT content in DNA increases with an increasing number of methylation sites. In this study, the fluorescein-carrying bis-acridinyl peptide (FKA) molecule was used for the detection of methylation frequency. FKA contains fluorescein and two acridine moieties, which together allow for the determination of the AT content of double-stranded DNA fragments. Methylated and unmethylated human genomes were subjected to bisulfide treatment and subsequent PCR using primers specific for the CFTR, CDH4, DBC1, and NPY genes. The AT content in the resulting PCR products was estimated by FKA, and AT content estimations were found to be in good agreement with those determined by DNA sequencing. This newly developed method may be useful for determining methylation frequencies of many PCR products by measuring the fluorescence in samples excited at two different wavelengths.

  16. VoIP attacks detection engine based on neural network

    Science.gov (United States)

    Safarik, Jakub; Slachta, Jiri

    2015-05-01

    The security is crucial for any system nowadays, especially communications. One of the most successful protocols in the field of communication over IP networks is Session Initiation Protocol. It is an open-source project used by different kinds of applications, both open-source and proprietary. High penetration and text-based principle made SIP number one target in IP telephony infrastructure, so security of SIP server is essential. To keep up with hackers and to detect potential malicious attacks, security administrator needs to monitor and evaluate SIP traffic in the network. But monitoring and following evaluation could easily overwhelm the security administrator in networks, typically in networks with a number of SIP servers, users and logically or geographically separated networks. The proposed solution lies in automatic attack detection systems. The article covers detection of VoIP attacks through a distributed network of nodes. Then the gathered data analyze aggregation server with artificial neural network. Artificial neural network means multilayer perceptron network trained with a set of collected attacks. Attack data could also be preprocessed and verified with a self-organizing map. The source data is detected by distributed network of detection nodes. Each node contains a honeypot application and traffic monitoring mechanism. Aggregation of data from each node creates an input for neural networks. The automatic classification on a centralized server with low false positive detection reduce the cost of attack detection resources. The detection system uses modular design for easy deployment in final infrastructure. The centralized server collects and process detected traffic. It also maintains all detection nodes.

  17. In-pipe leak detection by Minimum Residual complexity: A Robust time Delay Estimation method against correlated noise

    CERN Document Server

    Ahmadi, A M; Bahrampour, A R; Ravanbod, H

    2013-01-01

    In this work, the residual complexity (RC) similarity measure, is employed for time delay estimation (TDE) in gas pipe leak localization. The result of TDE by RC is compared with those of Cross Correlation(CC) and Mutual Information(MI) similarity measures based on our experimental data. The comparison confirms the advantages of RC relative to CC and MI, in robustness against both correlated noises and reduction of number of samples. These advantages originate from not only its mathematical nature of RC similarity measure which considers interdependency but also from broadband frequency of acoustic waves propagating during gas pipes.

  18. Using frame correlation algorithm in a duration distribution based hidden Markov model

    Institute of Scientific and Technical Information of China (English)

    王作英; 崔小东

    2000-01-01

    The assumption of frame independence is a widely known weakness of traditional hidden Markov model (HMM). In this paper, a frame correlation algorithm based on the duration distribution based hidden Markov model (DDBHMM) is proposed. In the algorithm, an AR model is used to depict the low pass effect of vocal tract from which stems the inertia leading to frame correlation. In the preliminary experiment of middle vocabulary speaker dependent isolated word recognition, our frame correlation algorithm outperforms the frame independent one. The average error reduction is about 20% .

  19. Real-time fault detection method based on belief rule base for aircraft navigation system

    Institute of Scientific and Technical Information of China (English)

    Zhao Xin; Wang Shicheng; Zhang Jinsheng; Fan Zhiliang; Min Haibo

    2013-01-01

    Real-time and accurate fault detection is essential to enhance the aircraft navigation system's reliability and safety.The existent detection methods based on analytical model draws back at simultaneously detecting gradual and sudden faults.On account of this reason,we propose an online detection solution based on non-analytical model.In this article,the navigation system fault detection model is established based on belief rule base (BRB),where the system measuring residual and its changing rate are used as the inputs of BRB model and the fault detection function as the output.To overcome the drawbacks of current parameter optimization algorithms for BRB and achieve online update,a parameter recursive estimation algorithm is presented for online BRB detection model based on expectation maximization (EM) algorithm.Furthermore,the proposed method is verified by navigation experiment.Experimental results show that the proposed method is able to effectively realize online parameter evaluation in navigation system fault detection model.The output of the detection model can track the fault state very well,and the faults can be diagnosed in real time and accurately.In addition,the detection ability,especially in the probability of false detection,is superior to offline optimization method,and thus the system reliability has great improvement.

  20. Analysis of Android Device-Based Solutions for Fall Detection.

    Science.gov (United States)

    Casilari, Eduardo; Luque, Rafael; Morón, María-José

    2015-07-23

    Falls are a major cause of health and psychological problems as well as hospitalization costs among older adults. Thus, the investigation on automatic Fall Detection Systems (FDSs) has received special attention from the research community during the last decade. In this area, the widespread popularity, decreasing price, computing capabilities, built-in sensors and multiplicity of wireless interfaces of Android-based devices (especially smartphones) have fostered the adoption of this technology to deploy wearable and inexpensive architectures for fall detection. This paper presents a critical and thorough analysis of those existing fall detection systems that are based on Android devices. The review systematically classifies and compares the proposals of the literature taking into account different criteria such as the system architecture, the employed sensors, the detection algorithm or the response in case of a fall alarms. The study emphasizes the analysis of the evaluation methods that are employed to assess the effectiveness of the detection process. The review reveals the complete lack of a reference framework to validate and compare the proposals. In addition, the study also shows that most research works do not evaluate the actual applicability of the Android devices (with limited battery and computing resources) to fall detection solutions.