Kernel-based noise filtering of neutron detector signals

International Nuclear Information System (INIS)

Park, Moon Ghu; Shin, Ho Cheol; Lee, Eun Ki

2007-01-01

This paper describes recently developed techniques for effective filtering of neutron detector signal noise. In this paper, three kinds of noise filters are proposed and their performance is demonstrated for the estimation of reactivity. The tested filters are based on the unilateral kernel filter, unilateral kernel filter with adaptive bandwidth and bilateral filter to show their effectiveness in edge preservation. Filtering performance is compared with conventional low-pass and wavelet filters. The bilateral filter shows a remarkable improvement compared with unilateral kernel and wavelet filters. The effectiveness and simplicity of the unilateral kernel filter with adaptive bandwidth is also demonstrated by applying it to the reactivity measurement performed during reactor start-up physics tests

Responses of diode detectors to radiation beams from teletherapy machines

International Nuclear Information System (INIS)

Malinda, Lora; Nasukha

2003-01-01

Responses of diode detectors to radiation beams from teletherapy machines. It has been carried out responses to two sets of diode detector by using the beams of teletherapy Co-60 and medical linear accelerator. Each set of consist of 8 diode detectors was irradiated by using gamma beams from teletherapy Co-60 machines and 6 MV and 10 MV foron beams from medical linear accelerator and 6.9.12.16. and 20 MeV electron beams from medical linear accelerator. The detectors were positioned on the phantom circularly and radially and electronic equilibrium condition for all type and energy beams. It was found that every detectors had own individual response and it is not to be uniformity, since the fluctuation in between 16.6 % to 30.9 %. All detectors responses are linear to gamma and foron beams, and also for energy above 6 MeV for electron beams. Nonlinearity response occurs for 6 MeV electron beam, it is probably from the assumption of electronic equilibrium

Machine Learning Method Applied in Readout System of Superheated Droplet Detector

Science.gov (United States)

Liu, Yi; Sullivan, Clair Julia; d'Errico, Francesco

2017-07-01

Direct readability is one advantage of superheated droplet detectors in neutron dosimetry. Utilizing such a distinct characteristic, an imaging readout system analyzes image of the detector for neutron dose readout. To improve the accuracy and precision of algorithms in the imaging readout system, machine learning algorithms were developed. Deep learning neural network and support vector machine algorithms are applied and compared with generally used Hough transform and curvature analysis methods. The machine learning methods showed a much higher accuracy and better precision in recognizing circular gas bubbles.

Supervised machine learning algorithms to diagnose stress for vehicle drivers based on physiological sensor signals.

Science.gov (United States)

Barua, Shaibal; Begum, Shahina; Ahmed, Mobyen Uddin

2015-01-01

Machine learning algorithms play an important role in computer science research. Recent advancement in sensor data collection in clinical sciences lead to a complex, heterogeneous data processing, and analysis for patient diagnosis and prognosis. Diagnosis and treatment of patients based on manual analysis of these sensor data are difficult and time consuming. Therefore, development of Knowledge-based systems to support clinicians in decision-making is important. However, it is necessary to perform experimental work to compare performances of different machine learning methods to help to select appropriate method for a specific characteristic of data sets. This paper compares classification performance of three popular machine learning methods i.e., case-based reasoning, neutral networks and support vector machine to diagnose stress of vehicle drivers using finger temperature and heart rate variability. The experimental results show that case-based reasoning outperforms other two methods in terms of classification accuracy. Case-based reasoning has achieved 80% and 86% accuracy to classify stress using finger temperature and heart rate variability. On contrary, both neural network and support vector machine have achieved less than 80% accuracy by using both physiological signals.

K-mean clustering algorithm for processing signals from compound semiconductor detectors

International Nuclear Information System (INIS)

Tada, Tsutomu; Hitomi, Keitaro; Wu, Yan; Kim, Seong-Yun; Yamazaki, Hiromichi; Ishii, Keizo

2011-01-01

The K-mean clustering algorithm was employed for processing signal waveforms from TlBr detectors. The signal waveforms were classified based on its shape reflecting the charge collection process in the detector. The classified signal waveforms were processed individually to suppress the pulse height variation of signals due to the charge collection loss. The obtained energy resolution of a 137 Cs spectrum measured with a 0.5 mm thick TlBr detector was 1.3% FWHM by employing 500 clusters.

Signal generation in gas detectors

International Nuclear Information System (INIS)

Stillman, A.

1993-01-01

This tutorial describes the generation of electrical signals in gas detectors. Ionization of the gas by the passage of charged particles generates these signals. Starting with the Bethe-Bloch equation, the treatment is a general introduction to the production of ion-pairs in gas devices. I continue with the characterization of the ionization as an electrical signal, and calculate the signal current in a simple example. Another example demonstrates the effect of space charge on the design of a detector. The AGS Booster ionization profile monitor is a model for this calculation

CCD-based vertex detectors

CERN Document Server

Damerell, C J S

2005-01-01

Over the past 20 years, CCD-based vertex detectors have been used to construct some of the most precise 'tracking microscopes' in particle physics. They were initially used by the ACCMOR collaboration for fixed target experiments in CERN, where they enabled the lifetimes of some of the shortest-lived charm particles to be measured precisely. The migration to collider experiments was accomplished in the SLD experiment, where the original 120 Mpixel detector was later upgraded to one with 307 Mpixels. This detector was used in a range of physics studies which exceeded the capability of the LEP detectors, including the most precise limit to date on the Bs mixing parameter. This success, and the high background hit densities that will inevitably be encountered at the future TeV-scale linear collider, have established the need for a silicon pixel-based vertex detector at this machine. The technical options have now been broadened to include a wide range of possible silicon imaging technologies as well as CCDs (mon...

Signal development in irradiated silicon detectors

CERN Document Server

Kramberger, Gregor; Mikuz, Marko

2001-01-01

This work provides a detailed study of signal formation in silicon detectors, with the emphasis on detectors with high concentration of irradiation induced defects in the lattice. These defects give rise to deep energy levels in the band gap. As a consequence, the current induced by charge motion in silicon detectors is signifcantly altered. Within the framework of the study a new experimental method, Charge correction method, based on transient current technique (TCT) was proposed for determination of effective electron and hole trapping times in irradiated silicon detectors. Effective carrier trapping times were determined in numerous silicon pad detectors irradiated with neutrons, pions and protons. Studied detectors were fabricated on oxygenated and non-oxygenated silicon wafers with different bulk resistivities. Measured effective carrier trapping times were found to be inversely proportional to fuence and increase with temperature. No dependence on silicon resistivity and oxygen concentration was observ...

B-meson factories: Physics, machines and detectors

International Nuclear Information System (INIS)

Kolanoski, H.

1990-10-01

This report gives a short survey of the present status of B-meson factory plans and discussions at different laboratories. The physics motivation for an e + e - machine running with the highest possible luminosity in the Γ(4S) energy region is outlined emphasizing the possibility to observe CP violation in the B-meson system. The technical concepts for such machines together with the basic luminosity limitations are discussed. Finally, the requirements on a detector which is able to cover the rich physics program are presented. (orig.)

Machines vs. ensembles: effective MAPK signaling through heterogeneous sets of protein complexes.

Directory of Open Access Journals (Sweden)

Ryan Suderman

Full Text Available Despite the importance of intracellular signaling networks, there is currently no consensus regarding the fundamental nature of the protein complexes such networks employ. One prominent view involves stable signaling machines with well-defined quaternary structures. The combinatorial complexity of signaling networks has led to an opposing perspective, namely that signaling proceeds via heterogeneous pleiomorphic ensembles of transient complexes. Since many hypotheses regarding network function rely on how we conceptualize signaling complexes, resolving this issue is a central problem in systems biology. Unfortunately, direct experimental characterization of these complexes has proven technologically difficult, while combinatorial complexity has prevented traditional modeling methods from approaching this question. Here we employ rule-based modeling, a technique that overcomes these limitations, to construct a model of the yeast pheromone signaling network. We found that this model exhibits significant ensemble character while generating reliable responses that match experimental observations. To contrast the ensemble behavior, we constructed a model that employs hierarchical assembly pathways to produce scaffold-based signaling machines. We found that this machine model could not replicate the experimentally observed combinatorial inhibition that arises when the scaffold is overexpressed. This finding provides evidence against the hierarchical assembly of machines in the pheromone signaling network and suggests that machines and ensembles may serve distinct purposes in vivo. In some cases, e.g. core enzymatic activities like protein synthesis and degradation, machines assembled via hierarchical energy landscapes may provide functional stability for the cell. In other cases, such as signaling, ensembles may represent a form of weak linkage, facilitating variation and plasticity in network evolution. The capacity of ensembles to signal effectively

A novel human-machine interface based on recognition of multi-channel facial bioelectric signals

International Nuclear Information System (INIS)

Razazadeh, Iman Mohammad; Firoozabadi, S. Mohammad; Golpayegani, S.M.R.H.; Hu, H.

2011-01-01

Full text: This paper presents a novel human-machine interface for disabled people to interact with assistive systems for a better quality of life. It is based on multichannel forehead bioelectric signals acquired by placing three pairs of electrodes (physical channels) on the Fron-tails and Temporalis facial muscles. The acquired signals are passes through a parallel filter bank to explore three different sub-bands related to facial electromyogram, electrooculogram and electroencephalogram. The root mean features of the bioelectric signals analyzed within non-overlapping 256 ms windows were extracted. The subtractive fuzzy c-means clustering method (SFCM) was applied to segment the feature space and generate initial fuzzy based Takagi-Sugeno rules. Then, an adaptive neuro-fuzzy inference system is exploited to tune up the premises and consequence parameters of the extracted SFCMs. rules. The average classifier discriminating ratio for eight different facial gestures (smiling, frowning, pulling up left/right lips corner, eye movement to left/right/up/down is between 93.04% and 96.99% according to different combinations and fusions of logical features. Experimental results show that the proposed interface has a high degree of accuracy and robustness for discrimination of 8 fundamental facial gestures. Some potential and further capabilities of our approach in human-machine interfaces are also discussed. (author)

Fast digitizing and digital signal processing of detector signals

International Nuclear Information System (INIS)

Hannaske, Roland

2008-01-01

A fast-digitizer data acquisition system recently installed at the neutron time-of-flight experiment nELBE, which is located at the superconducting electron accelerator ELBE of Forschungszentrum Dresden-Rossendorf, is tested with two different detector types. Preamplifier signals from a high-purity germanium detector are digitized, stored and finally processed. For a precise determination of the energy of the detected radiation, the moving-window deconvolution algorithm is used to compensate the ballistic deficit and different shaping algorithms are applied. The energy resolution is determined in an experiment with γ-rays from a 22 Na source and is compared to the energy resolution achieved with analogously processed signals. On the other hand, signals from the photomultipliers of barium fluoride and plastic scintillation detectors are digitized. These signals have risetimes of a few nanoseconds only. The moment of interaction of the radiation with the detector is determined by methods of digital signal processing. Therefore, different timing algorithms are implemented and tested with data from an experiment at nELBE. The time resolutions achieved with these algorithms are compared to each other as well as to reference values coming from analog signal processing. In addition to these experiments, some properties of the digitizing hardware are measured and a program for the analysis of stored, digitized data is developed. The analysis of the signals shows that the energy resolution achieved with the 10-bit digitizer system used here is not competitive to a 14-bit peak-sensing ADC, although the ballistic deficit can be fully corrected. However, digital methods give better result in sub-ns timing than analog signal processing. (orig.)

Intelligent sensor networks the integration of sensor networks, signal processing and machine learning

CERN Document Server

Hu, Fei

2012-01-01

Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, incl

Human-machine interface based on muscular and brain signals applied to a robotic wheelchair

International Nuclear Information System (INIS)

Ferreira, A; Silva, R L; Celeste, W C; Filho, T F Bastos; Filho, M Sarcinelli

2007-01-01

This paper presents a Human-Machine Interface (HMI) based on the signals generated by eye blinks or brain activity. The system structure and the signal acquisition and processing are shown. The signals used in this work are either the signal associated to the muscular movement corresponding to an eye blink or the brain signal corresponding to visual information processing. The variance is the feature extracted from such signals in order to detect the intention of the user. The classification is performed by a variance threshold which is experimentally determined for each user during the training stage. The command options, which are going to be sent to the commanded device, are presented to the user in the screen of a PDA (Personal Digital Assistant). In the experiments here reported, a robotic wheelchair is used as the device being commanded

Human-machine interface based on muscular and brain signals applied to a robotic wheelchair

Energy Technology Data Exchange (ETDEWEB)

Ferreira, A; Silva, R L; Celeste, W C; Filho, T F Bastos; Filho, M Sarcinelli [Electrical Engineering Department, Federal University of Espirito Santo (UFES), Av. Fernando Ferrari, 514, Vitoria, 29075-910 (Brazil)

2007-11-15

This paper presents a Human-Machine Interface (HMI) based on the signals generated by eye blinks or brain activity. The system structure and the signal acquisition and processing are shown. The signals used in this work are either the signal associated to the muscular movement corresponding to an eye blink or the brain signal corresponding to visual information processing. The variance is the feature extracted from such signals in order to detect the intention of the user. The classification is performed by a variance threshold which is experimentally determined for each user during the training stage. The command options, which are going to be sent to the commanded device, are presented to the user in the screen of a PDA (Personal Digital Assistant). In the experiments here reported, a robotic wheelchair is used as the device being commanded.

Parametric Adaptive Radar Detector with Enhanced Mismatched Signals Rejection Capabilities

Directory of Open Access Journals (Sweden)

Liu Bin

2010-01-01

Full Text Available We consider the problem of adaptive signal detection in the presence of Gaussian noise with unknown covariance matrix. We propose a parametric radar detector by introducing a design parameter to trade off the target sensitivity with sidelobes energy rejection. The resulting detector merges the statistics of Kelly's GLRT and of the Rao test and so covers Kelly's GLRT and the Rao test as special cases. Both invariance properties and constant false alarm rate (CFAR behavior for this detector are studied. At the analysis stage, the performance of the new receiver is assessed and compared with several traditional adaptive detectors. The results highlight better rejection capabilities of this proposed detector for mismatched signals. Further, we develop two two-stage detectors, one of which consists of an adaptive matched filter (AMF followed by the aforementioned detector, and the other is obtained by cascading a GLRT-based Subspace Detector (SD and the proposed adaptive detector. We show that the former two-stage detector outperforms traditional two-stage detectors in terms of selectivity, and the latter yields more robustness.

The Design and Research of the Operation Status Detector for Marine Engine Room Power Plant Based on Noise

Directory of Open Access Journals (Sweden)

Li Hang

2016-01-01

Full Text Available Designed in this paper, based on the noise of ship engine room power plant running status of detector, is mainly used in the operation of the power plant of acoustic shell size to determine when the machine running state, this device is composed of signal disposal and alarm display adjustment part of two parts. Detector that can show the size of the voice, if exceed the set limit alarm value, the detector can sound an alarm, to remind staff equipment fails, it shall timely inspection maintenance, improve the safety of the operation of the ship.

Summary of the snowmass working group on machine-detector interface

International Nuclear Information System (INIS)

Bharadwaj, V.; Colestock, P.; Cooper, J.; Goderre, G.; Holt, J.

1993-01-01

From the detector point of view, what experimenters need is an outline of the EXPECTED machine parameters tempered with some indication of the POSSIBLE machine parameters. Given guidance from accelerator physicists on the machine, experimenters may get the germ of an idea of how to exploit a particular machine property. Similarly, given some indication of what is important to the experimenters, accelerator physicists may have ideas of how to modify the machine appropriately. The authors discuss a list of machine parameters from the perspective of experimentalists. These include: luminosity; number of bunches/bunch spacing; beam energy; luminosity lifetime; β * /longitudinal emittance; transverse emittance. They also include a summary of tevatron performance - past, present, and projected

Vibration of signal wires in wire detectors under irradiation

International Nuclear Information System (INIS)

Bojko, I.R.; Shelkov, G.A.; Dodonov, V.I.; Ignatenko, M.A.; Nikolenko, M.Yu.

1995-01-01

Radiation-induced vibration of signal wires in wire detectors is found and explained. The phenomenon is based on repulsion of a signal wire with a positive potential and a cloud of positive ions that remains after neutralization of the electron part of the avalanche formed in the course of gas amplification. Vibration with a noticeable amplitude may arise from fluctuations of repulsive forces, which act on the wire and whose sources are numerous ion clusters. A formula is obtained which allows wire oscillations to be estimated for all types of wire detectors. Calculation shows that oscillations of signal wires can be substantial for the coordinate accuracy of a detector working in the limited streamer mode at fluxes over 10 5 particles per second per wire. In the proportional mode an average oscillation amplitude can be as large as 20-30 μm at some detector parameters and external radiation fluxes over 10 5 . The experimental investigations show that the proposed model well describes the main features of the phenomenon. 6 refs., 8 figs

Signal Attenuation Curve for Different Surface Detector Arrays

Science.gov (United States)

Vicha, J.; Travnicek, P.; Nosek, D.; Ebr, J.

2014-06-01

Modern cosmic ray experiments consisting of large array of particle detectors measure the signals of electromagnetic or muon components or their combination. The correction for an amount of atmosphere passed is applied to the surface detector signal before its conversion to the shower energy. Either Monte Carlo based approach assuming certain composition of primaries or indirect estimation using real data and assuming isotropy of arrival directions can be used. Toy surface arrays of different sensitivities to electromagnetic and muon components are assumed in MC simulations to study effects imposed on attenuation curves for varying composition or possible high energy anisotropy. The possible sensitivity of the attenuation curve to the mass composition is also tested for different array types focusing on a future apparatus that can separate muon and electromagnetic component signals.

Correction of rhodium detector signals for comparison to design calculations

International Nuclear Information System (INIS)

Judd, J.L.; Chang, R.Y.; Gabel, C.W.

1989-01-01

Rhodium detectors are used in many commercial pressurized water reactors PWRs [pressurized water reactor] as in-core neutron detectors. The signals from the detectors are the result of neutron absorption in 103 Rh and the subsequent beta decay of 104 Rh to 104 Pd. The rhodium depletes ∼1% per full-power month, so corrections are necessary to the detector signal to account for the effects of the rhodium depletion. These corrections result from the change in detector self-shielding with rhodium burnup and the change in rhodium concentration itself. Correction for the change in rhodium concentration is done by multiplication of the factor N(t)/N 0 , where N(t) is the rhodium concentration at time t and N 0 is the initial rhodium concentration. The calculation of the self-shielding factor is more complicated and is presented. A self-shielding factor based on the fraction of rhodium remaining was calculated with the CASMO-3 code. The results obtained from our comparisons of predicted and measured in-core detector signals show that the CASMO-3/SIMULATE-3 code package is an effective tool for estimating pin peaking and power distributions

Proceedings of the IEEE Machine Learning for Signal Processing XVII

DEFF Research Database (Denmark)

The seventeenth of a series of workshops sponsored by the IEEE Signal Processing Society and organized by the Machine Learning for Signal Processing Technical Committee (MLSP-TC). The field of machine learning has matured considerably in both methodology and real-world application domains and has...... become particularly important for solution of problems in signal processing. As reflected in this collection, machine learning for signal processing combines many ideas from adaptive signal/image processing, learning theory and models, and statistics in order to solve complex real-world signal processing......, and two papers from the winners of the Data Analysis Competition. The program included papers in the following areas: genomic signal processing, pattern recognition and classification, image and video processing, blind signal processing, models, learning algorithms, and applications of machine learning...

Confirmation of Thermal Images and Vibration Signals for Intelligent Machine Fault Diagnostics

Directory of Open Access Journals (Sweden)

Achmad Widodo

2012-01-01

Full Text Available This paper deals with the maintenance technique for industrial machinery using the artificial neural network so-called self-organizing map (SOM. The aim of this work is to develop intelligent maintenance system for machinery based on an alternative way, namely, thermal images instead of vibration signals. SOM is selected due to its simplicity and is categorized as an unsupervised algorithm. Following the SOM training, machine fault diagnostics is performed by using the pattern recognition technique of machine conditions. The data used in this work are thermal images and vibration signals, which were acquired from machine fault simulator (MFS. It is a reliable tool and is able to simulate several conditions of faulty machine such as unbalance, misalignment, looseness, and rolling element bearing faults (outer race, inner race, ball, and cage defects. Data acquisition were conducted simultaneously by infrared thermography camera and vibration sensors installed in the MFS. The experimental data are presented as thermal image and vibration signal in the time domain. Feature extraction was carried out to obtain salient features sensitive to machine conditions from thermal images and vibration signals. These features are then used to train the SOM for intelligent machine diagnostics process. The results show that SOM can perform intelligent fault diagnostics with plausible accuracies.

Machine implications for detectors and physics

International Nuclear Information System (INIS)

Tauchi, Toshiaki

2001-01-01

Future linear colliders are very different at many aspects because of low repetition rate (5∼200 Hz) and high accelerating gradient (22∼150 MeV/m). For high luminosity, the beam sizes must be squeezed in extremely small region at interaction point (IP). We briefly describe new phenomena at the IP, i.e. beamstrahlung process, creations of e + e - pairs and minijets. We also report machine implications related to the energy spread, beamstrahlung, bunch-train structure, beam polarizations and backgrounds for detectors and physics

Optoelectronic analogue signal transfer for LHC detectors, 1991

CERN Document Server

Dowell, John D; Homer, R J; Jovanovic, P; Kenyon, I; Staley, R; Webster, K; Da Via, C; Feyt, J; Nappey, P; Stefanini, G; Dwir, B; Reinhart, F K; Davies, J; Green, N; Stewart, W; Young, T; Hall, G; Akesson, T; Jarlskog, G; Kröll, S; Nickerson, R; Jaroslawski, S; CERN. Geneva. Detector Research and Development Committee

1991-01-01

We propose to study and develop opto-electronic analogue front-ends based on electro-optic intensity modulators. These devices translate the detector electrical analogue signals into optical signals which are then transferred via optical fibres to photodetector receivers at the remote readout. In comparison with conventional solutions based on copper cables, this technique offers the advantages of high speed, very low power dissipation and transmission losses, compactness and immunity to electromagnetic interference. The linearity and dynamic range that can be obtained are more than adequate for central tracking detectors, and the proposed devices have considerable radiation- hardness capabilities. The large bandwidth and short transit times offer possibilities for improved triggering schemes. The proposed R&D programme is aimed at producing multi-channel "demonstrator" units for evaluation both in laboratory and beam tests. This will allow the choice of the most effective technology. A detailed study wil...

Gravity Spy: integrating advanced LIGO detector characterization, machine learning, and citizen science

Science.gov (United States)

Zevin, M; Coughlin, S; Bahaadini, S; Besler, E; Rohani, N; Allen, S; Cabero, M; Crowston, K; Katsaggelos, A K; Larson, S L; Lee, T K; Lintott, C; Littenberg, T B; Lundgren, A; Østerlund, C; Smith, J R; Trouille, L; Kalogera, V

2018-01-01

With the first direct detection of gravitational waves, the advanced laser interferometer gravitational-wave observatory (LIGO) has initiated a new field of astronomy by providing an alternative means of sensing the universe. The extreme sensitivity required to make such detections is achieved through exquisite isolation of all sensitive components of LIGO from non-gravitational-wave disturbances. Nonetheless, LIGO is still susceptible to a variety of instrumental and environmental sources of noise that contaminate the data. Of particular concern are noise features known as glitches, which are transient and non-Gaussian in their nature, and occur at a high enough rate so that accidental coincidence between the two LIGO detectors is non-negligible. Glitches come in a wide range of time-frequency-amplitude morphologies, with new morphologies appearing as the detector evolves. Since they can obscure or mimic true gravitational-wave signals, a robust characterization of glitches is paramount in the effort to achieve the gravitational-wave detection rates that are predicted by the design sensitivity of LIGO. This proves a daunting task for members of the LIGO Scientific Collaboration alone due to the sheer amount of data. In this paper we describe an innovative project that combines crowdsourcing with machine learning to aid in the challenging task of categorizing all of the glitches recorded by the LIGO detectors. Through the Zooniverse platform, we engage and recruit volunteers from the public to categorize images of time-frequency representations of glitches into pre-identified morphological classes and to discover new classes that appear as the detectors evolve. In addition, machine learning algorithms are used to categorize images after being trained on human-classified examples of the morphological classes. Leveraging the strengths of both classification methods, we create a combined method with the aim of improving the efficiency and accuracy of each individual

Gravity Spy: integrating advanced LIGO detector characterization, machine learning, and citizen science

International Nuclear Information System (INIS)

Zevin, M; Coughlin, S; Larson, S L; Trouille, L; Kalogera, V; Bahaadini, S; Besler, E; Rohani, N; Katsaggelos, A K; Allen, S; Cabero, M; Lundgren, A; Crowston, K; Østerlund, C; Lee, T K; Lintott, C; Littenberg, T B; Smith, J R

2017-01-01

With the first direct detection of gravitational waves, the advanced laser interferometer gravitational-wave observatory (LIGO) has initiated a new field of astronomy by providing an alternative means of sensing the universe. The extreme sensitivity required to make such detections is achieved through exquisite isolation of all sensitive components of LIGO from non-gravitational-wave disturbances. Nonetheless, LIGO is still susceptible to a variety of instrumental and environmental sources of noise that contaminate the data. Of particular concern are noise features known as glitches , which are transient and non-Gaussian in their nature, and occur at a high enough rate so that accidental coincidence between the two LIGO detectors is non-negligible. Glitches come in a wide range of time-frequency-amplitude morphologies, with new morphologies appearing as the detector evolves. Since they can obscure or mimic true gravitational-wave signals, a robust characterization of glitches is paramount in the effort to achieve the gravitational-wave detection rates that are predicted by the design sensitivity of LIGO. This proves a daunting task for members of the LIGO Scientific Collaboration alone due to the sheer amount of data. In this paper we describe an innovative project that combines crowdsourcing with machine learning to aid in the challenging task of categorizing all of the glitches recorded by the LIGO detectors. Through the Zooniverse platform, we engage and recruit volunteers from the public to categorize images of time-frequency representations of glitches into pre-identified morphological classes and to discover new classes that appear as the detectors evolve. In addition, machine learning algorithms are used to categorize images after being trained on human-classified examples of the morphological classes. Leveraging the strengths of both classification methods, we create a combined method with the aim of improving the efficiency and accuracy of each individual

Proceedings of IEEE Machine Learning for Signal Processing Workshop XVI

DEFF Research Database (Denmark)

Larsen, Jan

These proceedings contains refereed papers presented at the sixteenth IEEE Workshop on Machine Learning for Signal Processing (MLSP'2006), held in Maynooth, Co. Kildare, Ireland, September 6-8, 2006. This is a continuation of the IEEE Workshops on Neural Networks for Signal Processing (NNSP......). The name of the Technical Committee, hence of the Workshop, was changed to Machine Learning for Signal Processing in September 2003 to better reflect the areas represented by the Technical Committee. The conference is organized by the Machine Learning for Signal Processing Technical Committee...... the same standard as the printed version and facilitates the reading and searching of the papers. The field of machine learning has matured considerably in both methodology and real-world application domains and has become particularly important for solution of problems in signal processing. As reflected...

SPECT detector system design based on embedded system

International Nuclear Information System (INIS)

Zhang Weizheng; Zhao Shujun; Zhang Lei; Sun Yuanling

2007-01-01

A single-photon emission computed tomography detector system based on embedded Linux designed. This system is composed of detector module, data acquisition module, ARM MPU module, network interface communication module and human machine interface module. Its software uses multithreading technology based on embedded Linux. It can achieve high speed data acquisition, real-time data correction and network data communication. It can accelerate the data acquisition and decrease the dead time. The accuracy and the stability of the system can be improved. (authors)

Response of resonant gravitational wave detectors to damped sinusoid signals

International Nuclear Information System (INIS)

Pai, A; Celsi, C; Pallottino, G V; D'Antonio, S; Astone, P

2007-01-01

Till date, the search for burst signals with resonant gravitational wave (GW) detectors has been done using the δ-function approximation for the signal, which was reasonable due to the very small bandwidth of these detectors. However, now with increased bandwidth (of the order of 10 or more Hz) and with the possibility of comparing results with interferometric GW detectors (broad-band), it is very important to exploit the resonant detectors' capability to detect also signals with specific wave shapes. As a first step, we present a study of the response of resonant GW detectors to damped sinusoids with given frequency and decay time and report on the development of a filter matched to these signals. This study is a preliminary step towards the comprehension of the detector response and of the filtering for signals such as the excitation of stellar quasi-normal modes

Financial signal processing and machine learning

CERN Document Server

Kulkarni,Sanjeev R; Dmitry M. Malioutov

2016-01-01

The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analy...

Digital signal processors for cryogenic high-resolution x-ray detector readout

International Nuclear Information System (INIS)

Friedrich, Stephan; Drury, Owen B.; Bechstein, Sylke; Hennig, Wolfgang; Momayezi, Michael

2003-01-01

We are developing fast digital signal processors (DSPs) to read out superconducting high-resolution X-ray detectors with on-line pulse processing. For superconducting tunnel junction (STJ) detector read-out, the DSPs offer online filtering, rise time discrimination and pile-up rejection. Compared to analog pulse processing, DSP readout somewhat degrades the detector resolution, but improves the spectral purity of the detector response. We discuss DSP performance with our 9-channel STJ array for synchrotron-based high-resolution X-ray spectroscopy. (author)

IEEE International Workshop on Machine Learning for Signal Processing: Preface

DEFF Research Database (Denmark)

Tao, Jianhua

The 21st IEEE International Workshop on Machine Learning for Signal Processing will be held in Beijing, China, on September 18–21, 2011. The workshop series is the major annual technical event of the IEEE Signal Processing Society's Technical Committee on Machine Learning for Signal Processing...

Machine-Learning-Based Future Received Signal Strength Prediction Using Depth Images for mmWave Communications

OpenAIRE

Okamoto, Hironao; Nishio, Takayuki; Nakashima, Kota; Koda, Yusuke; Yamamoto, Koji; Morikura, Masahiro; Asai, Yusuke; Miyatake, Ryo

2018-01-01

This paper discusses a machine-learning (ML)-based future received signal strength (RSS) prediction scheme using depth camera images for millimeter-wave (mmWave) networks. The scheme provides the future RSS prediction of any mmWave links within the camera's view, including links where nodes are not transmitting frames. This enables network controllers to conduct network operations before line-of-sight path blockages degrade the RSS. Using the ML techniques, the prediction scheme automatically...

Integrated circuit for processing a low-frequency signal from a seismic detector

Energy Technology Data Exchange (ETDEWEB)

Malashevich, N. I.; Roslyakov, A. S.; Polomoshnov, S. A., E-mail: S.Polomoshnov@tsen.ru; Fedorov, R. A. [Research and Production Complex ' Technological Center' of the Moscow Institute of Electronic Technology (Russian Federation)

2011-12-15

Specific features for the detection and processing of a low-frequency signal from a seismic detector are considered in terms of an integrated circuit based on a large matrix crystal of the 5507 series. This integrated circuit is designed for the detection of human movements. The specific features of the information signal, obtained at the output of the seismic detector, and the main characteristics of the integrated circuit and its structure are reported.

Improving detector signal processing with pulse height analysis in Moessbauer spectrometers

International Nuclear Information System (INIS)

Pechousek, Jiri; Mashlan, Miroslav; Frydrych, Jiri; Jancik, Dalibor; Prochazka, Roman

2007-01-01

A plenty of different programming techniques and instrument solutions are used in the development of Moessbauer spectrometers. Each of them should provide a faster spectrum accumulation process, increased productivity of measurements, decreased nonlinearity of the velocity scale, etc. The well known virtual instrumentation programming method has been used to design a computer-based Moessbauer spectrometer. Hardware solution was based on two commercially-available PCI modules produced by National Instruments Co. Virtual Moessbauer spectrometer is implemented by the graphical programming language LabVIEW 7 Express. This design environment allows to emulate the multichannel analyzer on the digital oscilloscope platform. This is a novel method based on Waveform Peak Detection function which allows detailed analysis of the acquired signal. The optimal treatment of the detector signal from various detector types is achieved by mathematical processing only. As a result, the possibility of an increase of signal/noise ratio is presented.

SU-C-304-07: Are Small Field Detector Correction Factors Strongly Dependent On Machine-Specific Characteristics?

International Nuclear Information System (INIS)

Mathew, D; Tanny, S; Parsai, E; Sperling, N

2015-01-01

Purpose: The current small field dosimetry formalism utilizes quality correction factors to compensate for the difference in detector response relative to dose deposited in water. The correction factors are defined on a machine-specific basis for each beam quality and detector combination. Some research has suggested that the correction factors may only be weakly dependent on machine-to-machine variations, allowing for determinations of class-specific correction factors for various accelerator models. This research examines the differences in small field correction factors for three detectors across two Varian Truebeam accelerators to determine the correction factor dependence on machine-specific characteristics. Methods: Output factors were measured on two Varian Truebeam accelerators for equivalently tuned 6 MV and 6 FFF beams. Measurements were obtained using a commercial plastic scintillation detector (PSD), two ion chambers, and a diode detector. Measurements were made at a depth of 10 cm with an SSD of 100 cm for jaw-defined field sizes ranging from 3×3 cm 2 to 0.6×0.6 cm 2 , normalized to values at 5×5cm 2 . Correction factors for each field on each machine were calculated as the ratio of the detector response to the PSD response. Percent change of correction factors for the chambers are presented relative to the primary machine. Results: The Exradin A26 demonstrates a difference of 9% for 6×6mm 2 fields in both the 6FFF and 6MV beams. The A16 chamber demonstrates a 5%, and 3% difference in 6FFF and 6MV fields at the same field size respectively. The Edge diode exhibits less than 1.5% difference across both evaluated energies. Field sizes larger than 1.4×1.4cm2 demonstrated less than 1% difference for all detectors. Conclusion: Preliminary results suggest that class-specific correction may not be appropriate for micro-ionization chamber. For diode systems, the correction factor was substantially similar and may be useful for class-specific reference

SU-C-304-07: Are Small Field Detector Correction Factors Strongly Dependent On Machine-Specific Characteristics?

Energy Technology Data Exchange (ETDEWEB)

Mathew, D; Tanny, S; Parsai, E; Sperling, N [University of Toledo Medical Center, Toledo, OH (United States)

2015-06-15

Purpose: The current small field dosimetry formalism utilizes quality correction factors to compensate for the difference in detector response relative to dose deposited in water. The correction factors are defined on a machine-specific basis for each beam quality and detector combination. Some research has suggested that the correction factors may only be weakly dependent on machine-to-machine variations, allowing for determinations of class-specific correction factors for various accelerator models. This research examines the differences in small field correction factors for three detectors across two Varian Truebeam accelerators to determine the correction factor dependence on machine-specific characteristics. Methods: Output factors were measured on two Varian Truebeam accelerators for equivalently tuned 6 MV and 6 FFF beams. Measurements were obtained using a commercial plastic scintillation detector (PSD), two ion chambers, and a diode detector. Measurements were made at a depth of 10 cm with an SSD of 100 cm for jaw-defined field sizes ranging from 3×3 cm{sup 2} to 0.6×0.6 cm{sup 2}, normalized to values at 5×5cm{sup 2}. Correction factors for each field on each machine were calculated as the ratio of the detector response to the PSD response. Percent change of correction factors for the chambers are presented relative to the primary machine. Results: The Exradin A26 demonstrates a difference of 9% for 6×6mm{sup 2} fields in both the 6FFF and 6MV beams. The A16 chamber demonstrates a 5%, and 3% difference in 6FFF and 6MV fields at the same field size respectively. The Edge diode exhibits less than 1.5% difference across both evaluated energies. Field sizes larger than 1.4×1.4cm2 demonstrated less than 1% difference for all detectors. Conclusion: Preliminary results suggest that class-specific correction may not be appropriate for micro-ionization chamber. For diode systems, the correction factor was substantially similar and may be useful for class

Current signal of silicon detectors facing charged particles and heavy ions

International Nuclear Information System (INIS)

Hamrita, H.

2005-07-01

This work consisted in collecting and studying for the first time the shapes of current signals obtained from charged particles or heavy ions produced by silicon detectors. The document is divided into two main parts. The first consisted in reducing the experimental data obtained with charged particles as well as with heavy ions. These experiments were performed at the Orsay Tandem and at GANIL using LISE. These two experiments enabled us to create a data base formed of current signals with various shapes and various times of collection. The second part consisted in carrying out a simulation of the current signals obtained from the various ions. To obtain this simulation we propose a new model describing the formation of the signal. We used the data base of the signals obtained in experiments in order to constrain the three parameters of our model. In this model, the charge carriers created are regarded as dipoles and their density is related to the dielectric polarization in the silicon detector. This phenomenon induces an increase in permittivity throughout the range of the incident ion and consequently the electric field between the electrodes of the detector is decreased inside the trace. We coupled with this phenomenon a dissociation and extraction mode of the charge carriers so that they can be moved in the electric field. (author)

Man/machine interface algorithm for advanced delayed-neutron signal characterization system

International Nuclear Information System (INIS)

Gross, K.C.

1985-01-01

The present failed-element rupture detector (FERD) at Experimental Breeder Reactor II (EBR-II) consists of a single bank of delayed-neutron (DN) detectors at a fixed transit time from the core. Plans are currently under way to upgrade the FERD in 1986 and provide advanced DN signal characterization capability that is embodied in an equivalent-recoil-area (ERA) meter. The new configuration will make available to the operator a wealth of quantitative diagnostic information related to the condition and dynamic evolution of a fuel breach. The diagnostic parameters will include a continuous reading of the ERA value for the breach; the transit time, T/sub tr/, for DN emitters traveling from the core to the FERD; and the isotopic holdup time, T/sub h/, for the source. To enhance the processing, interpretation, and display of these parameters to the reactor operator, a man/machine interface (MMI) algorithm has been developed to run in the background on EBR-II's data acquisition system (DAS). The purpose of this paper is to describe the features and implementation of this newly developed MMI algorithm

SU-E-T-113: Dose Distribution Using Respiratory Signals and Machine Parameters During Treatment

International Nuclear Information System (INIS)

Imae, T; Haga, A; Saotome, N; Kida, S; Nakano, M; Takeuchi, Y; Shiraki, T; Yano, K; Yamashita, H; Nakagawa, K; Ohtomo, K

2014-01-01

Purpose: Volumetric modulated arc therapy (VMAT) is a rotational intensity-modulated radiotherapy (IMRT) technique capable of acquiring projection images during treatment. Treatment plans for lung tumors using stereotactic body radiotherapy (SBRT) are calculated with planning computed tomography (CT) images only exhale phase. Purpose of this study is to evaluate dose distribution by reconstructing from only the data such as respiratory signals and machine parameters acquired during treatment. Methods: Phantom and three patients with lung tumor underwent CT scans for treatment planning. They were treated by VMAT while acquiring projection images to derive their respiratory signals and machine parameters including positions of multi leaf collimators, dose rates and integrated monitor units. The respiratory signals were divided into 4 and 10 phases and machine parameters were correlated with the divided respiratory signals based on the gantry angle. Dose distributions of each respiratory phase were calculated from plans which were reconstructed from the respiratory signals and the machine parameters during treatment. The doses at isocenter, maximum point and the centroid of target were evaluated. Results and Discussion: Dose distributions during treatment were calculated using the machine parameters and the respiratory signals detected from projection images. Maximum dose difference between plan and in treatment distribution was −1.8±0.4% at centroid of target and dose differences of evaluated points between 4 and 10 phases were no significant. Conclusion: The present method successfully evaluated dose distribution using respiratory signals and machine parameters during treatment. This method is feasible to verify the actual dose for moving target

Proceedings of IEEE Machine Learning for Signal Processing Workshop XV

DEFF Research Database (Denmark)

Larsen, Jan

These proceedings contains refereed papers presented at the Fifteenth IEEE Workshop on Machine Learning for Signal Processing (MLSP’2005), held in Mystic, Connecticut, USA, September 28-30, 2005. This is a continuation of the IEEE Workshops on Neural Networks for Signal Processing (NNSP) organized...... by the NNSP Technical Committee of the IEEE Signal Processing Society. The name of the Technical Committee, hence of the Workshop, was changed to Machine Learning for Signal Processing in September 2003 to better reflect the areas represented by the Technical Committee. The conference is organized...... by the Machine Learning for Signal Processing Technical Committee with sponsorship of the IEEE Signal Processing Society. Following the practice started two years ago, the bound volume of the proceedings is going to be published by IEEE following the Workshop, and we are pleased to offer to conference attendees...

2015 International Conference on Machine Learning and Signal Processing

CERN Document Server

Woo, Wai; Sulaiman, Hamzah; Othman, Mohd; Saat, Mohd

2016-01-01

This book presents important research findings and recent innovations in the field of machine learning and signal processing. A wide range of topics relating to machine learning and signal processing techniques and their applications are addressed in order to provide both researchers and practitioners with a valuable resource documenting the latest advances and trends. The book comprises a careful selection of the papers submitted to the 2015 International Conference on Machine Learning and Signal Processing (MALSIP 2015), which was held on 15–17 December 2015 in Ho Chi Minh City, Vietnam with the aim of offering researchers, academicians, and practitioners an ideal opportunity to disseminate their findings and achievements. All of the included contributions were chosen by expert peer reviewers from across the world on the basis of their interest to the community. In addition to presenting the latest in design, development, and research, the book provides access to numerous new algorithms for machine learni...

Self-Sustained Operation of Radiation Detectors Based on Embedded Signal Processing

International Nuclear Information System (INIS)

Talnishnikh, Elena; Paganini, Lucia; Stegenga, Jan; Woertche, Heinrich; Limburgy, Han

2013-06-01

Radiation detectors featuring long term stability, self-sustained operation and low power consumption are crucial for long-term environmental monitoring (e.g. nuclear waste disposals and mining activities) and provide enhanced applications of nuclear fingerprinting e.g. in farming and geological surveying. INCAS3 is developing a compact modular system consisting of four functional modules, namely analogue conditioning and signal digitalization, dead-time-free real-time signal processing, embedded high level analysis of the processed signal, and wireless communication. The modules are organized such that they can be interchanged and modified independently. For the input module one can choose an ADC sampling frequency to be either 100 MHz with 14 bit precision or 1 GHz with reduced precision (10 bit). The main focus of the signal processing section, based on an FPGA, is on providing dead-time-free signal handling in real time. Other useful features such as base line correction, pulse shape analysis (energy, decay and arrival time) are being developed as (VHDL) library functions. Additional modules, e.g. anomaly detection in the incoming signal, pile-up correction if operated at high rates and advanced signal shape processing, can be included in the processing if required and can be applied to autonomously generate the information necessary to control the sensor parameters and stabilize energy spectra and sensitivity. At present we operate the system in conjunction with inorganic scintillators (NaI, CsI) read out by a photomultiplier in order to provide a system capable of long term quantification of nuclear contaminations in natural environments. The underlying technology is based on detecting natural or anthropogenic gamma radiation and generating corresponding energy spectra in real time. The generated spectra are analyzed either in a standard way by any suitable desktop software in a lab or, as it is described in this work, by the ENSA (Embedded Nuclear Spectra

Signal Formation Processes in Micromegas Detectors and Quality Control for large size Detector Construction for the ATLAS New Small Wheel

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00387450; Rembser, Christoph

2017-08-04

The Micromegas technology is one of the most successful modern gaseous detector concepts and widely utilized in nuclear and particle physics experiments. Twenty years of R & D rendered the technology sufficiently mature to be selected as precision tracking detector for the New Small Wheel (NSW) upgrade of the ATLAS Muon spectrometer. This will be the first large scale application of Micromegas in one of the major LHC experiments. However, many of the fundamental microscopic processes in these gaseous detectors are still not fully understood and studies on several detector aspects, like the micromesh geometry, have never been addressed systematically. The studies on signal formation in Micromegas, presented in the first part of this thesis, focuses on the microscopic signal electron loss mechanisms and the amplification processes in electron gas interaction. Based on a detailed model of detector parameter dependencies, these processes are scrutinized in an iterating comparison between exper- imental result...

Machine Learning Techniques for Optical Performance Monitoring from Directly Detected PDM-QAM Signals

DEFF Research Database (Denmark)

Thrane, Jakob; Wass, Jesper; Piels, Molly

2017-01-01

Linear signal processing algorithms are effective in dealing with linear transmission channel and linear signal detection, while the nonlinear signal processing algorithms, from the machine learning community, are effective in dealing with nonlinear transmission channel and nonlinear signal...... detection. In this paper, a brief overview of the various machine learning methods and their application in optical communication is presented and discussed. Moreover, supervised machine learning methods, such as neural networks and support vector machine, are experimentally demonstrated for in-band optical...

Clustering method to process signals from a CdZnTe detector

International Nuclear Information System (INIS)

Zhang, Lan; Takahashi, Hiroyuki; Fukuda, Daiji; Nakazawa, Masaharu

2001-01-01

The poor mobility of holes in a compound semiconductor detector results in the imperfect collection of the primary charge deposited in the detector. Furthermore the fluctuation of the charge loss efficiency due to the change in the hole collection path length seriously degrades the energy resolution of the detector. Since the charge collection efficiency varies with the signal waveform, we can expect the improvement of the energy resolution through a proper waveform signal processing method. We developed a new digital signal processing technique, a clustering method which derives typical patterns containing the information on the real situation inside a detector from measured signals. The obtained typical patterns for the detector are then used for the pattern matching method. Measured signals are classified through analyzing the practical waveform variation due to the charge trapping, the electric field and the crystal defect etc. Signals with similar shape are placed into the same cluster. For each cluster we calculate an average waveform as a reference pattern. Using these reference patterns obtained from all the clusters, we can classify other measured signal waveforms from the same detector. Then signals are independently processed according to the classified category and form corresponding spectra. Finally these spectra are merged into one spectrum by multiplying normalization coefficients. The effectiveness of this method was verified with a CdZnTe detector of 2 mm thick and a 137 Cs gamma-ray source. The obtained energy resolution as improved to about 8 keV (FWHM). Because the clustering method is only related to the measured waveforms, it can be applied to any type and size of detectors and compatible with any type of filtering methods. (author)

Classifier for gravitational-wave inspiral signals in nonideal single-detector data

Science.gov (United States)

Kapadia, S. J.; Dent, T.; Dal Canton, T.

2017-11-01

We describe a multivariate classifier for candidate events in a templated search for gravitational-wave (GW) inspiral signals from neutron-star-black-hole (NS-BH) binaries, in data from ground-based detectors where sensitivity is limited by non-Gaussian noise transients. The standard signal-to-noise ratio (SNR) and chi-squared test for inspiral searches use only properties of a single matched filter at the time of an event; instead, we propose a classifier using features derived from a bank of inspiral templates around the time of each event, and also from a search using approximate sine-Gaussian templates. The classifier thus extracts additional information from strain data to discriminate inspiral signals from noise transients. We evaluate a random forest classifier on a set of single-detector events obtained from realistic simulated advanced LIGO data, using simulated NS-BH signals added to the data. The new classifier detects a factor of 1.5-2 more signals at low false positive rates as compared to the standard "reweighted SNR" statistic, and does not require the chi-squared test to be computed. Conversely, if only the SNR and chi-squared values of single-detector events are available, random forest classification performs nearly identically to the reweighted SNR.

A LabVIEWTM-based detector testing system

International Nuclear Information System (INIS)

Yang Haori; Li Yuanjing; Wang Yi; Li Yulan; Li Jin

2003-01-01

The construction of a LabVIEW-based detector testing system is described in this paper. In this system, the signal of detector is magnified and digitized, so amplitude or time spectrum can be obtained. The Analog-to-Digital Converter is a peak-sensitive ADC based on VME bus. The virtual instrument constructed by LabVIEW can be used to acquire data, draw spectrum and save testing results

Non-stationary signal analysis based on general parameterized time-frequency transform and its application in the feature extraction of a rotary machine

Science.gov (United States)

Zhou, Peng; Peng, Zhike; Chen, Shiqian; Yang, Yang; Zhang, Wenming

2018-06-01

With the development of large rotary machines for faster and more integrated performance, the condition monitoring and fault diagnosis for them are becoming more challenging. Since the time-frequency (TF) pattern of the vibration signal from the rotary machine often contains condition information and fault feature, the methods based on TF analysis have been widely-used to solve these two problems in the industrial community. This article introduces an effective non-stationary signal analysis method based on the general parameterized time-frequency transform (GPTFT). The GPTFT is achieved by inserting a rotation operator and a shift operator in the short-time Fourier transform. This method can produce a high-concentrated TF pattern with a general kernel. A multi-component instantaneous frequency (IF) extraction method is proposed based on it. The estimation for the IF of every component is accomplished by defining a spectrum concentration index (SCI). Moreover, such an IF estimation process is iteratively operated until all the components are extracted. The tests on three simulation examples and a real vibration signal demonstrate the effectiveness and superiority of our method.

An Analysis of Delay-based and Integrator-based Sequence Detectors for Grid-Connected Converters

DEFF Research Database (Denmark)

Khazraj, Hesam; Silva, Filipe Miguel Faria da; Bak, Claus Leth

2017-01-01

-signal cancellation operators are the main members of the delay-based sequence detectors. The aim of this paper is to provide a theoretical and experimental comparative study between integrator and delay based sequence detectors. The theoretical analysis is conducted based on the small-signal modelling......Detecting and separating positive and negative sequence components of the grid voltage or current is of vital importance in the control of grid-connected power converters, HVDC systems, etc. To this end, several techniques have been proposed in recent years. These techniques can be broadly...... classified into two main classes: The integrator-based techniques and Delay-based techniques. The complex-coefficient filter-based technique, dual second-order generalized integrator-based method, multiple reference frame approach are the main members of the integrator-based sequence detector and the delay...

Acoustic monitoring of rotating machine by advanced signal processing technology

International Nuclear Information System (INIS)

Kanemoto, Shigeru

2010-01-01

The acoustic data remotely measured by hand held type microphones are investigated for monitoring and diagnosing the rotational machine integrity in nuclear power plants. The plant operator's patrol monitoring is one of the important activities for condition monitoring. However, remotely measured sound has some difficulties to be considered for precise diagnosis or quantitative judgment of rotating machine anomaly, since the measurement sensitivity is different in each measurement, and also, the sensitivity deteriorates in comparison with an attached type sensor. Hence, in the present study, several advanced signal processing methods are examined and compared in order to find optimum anomaly monitoring technology from the viewpoints of both sensitivity and robustness of performance. The dimension of pre-processed signal feature patterns are reduced into two-dimensional space for the visualization by using the standard principal component analysis (PCA) or the kernel based PCA. Then, the normal state is classified by using probabilistic neural network (PNN) or support vector data description (SVDD). By using the mockup test facility of rotating machine, it is shown that the appropriate combination of the above algorithms gives sensitive and robust anomaly monitoring performance. (author)

A new ion detector array and digital-signal-processor-based interface

International Nuclear Information System (INIS)

Langstaff, D.P.; McGinnity, T.M.; Forbes, D.M.; Birkinshaw, K.; Lawton, M.W.

1994-01-01

A new one-dimensional ion detector array on a silicon chip has been developed for use in mass spectrometry. It is much smaller and simpler than electro-optical arrays currently in use and in addition has a higher resolution and a zero noise level. The array consists of a one-dimensional array of metal strips (electrodes) with a pitch of 25 μm on the top surface of a silicon chip, each electrode having its own charge pulse sensor, 8-bit counter and control/interface circuitry. The chip is mounted on a ceramic substrate and is preceded by a micro-channel plate electron multiplier. Chips are butted to give a longer array. Test results show a stable operating region. A digital-signal-processor-based interface is described, which controls the mode of operation and reads the accumulated array data at the maximum rate to avoid counter overflow. (author)

A new ion detector array and digital-signal-processor-based interface

Energy Technology Data Exchange (ETDEWEB)

Langstaff, D.P.; McGinnity, T.M.; Forbes, D.M.; Birkinshaw, K. (University Coll. of Wales, Aberystwyth (United Kingdom). Dept. of Physics); Lawton, M.W. (University of Wales Aberystwyth (United Kingdom). Dept. of Computer Science)

1994-04-01

A new one-dimensional ion detector array on a silicon chip has been developed for use in mass spectrometry. It is much smaller and simpler than electro-optical arrays currently in use and in addition has a higher resolution and a zero noise level. The array consists of a one-dimensional array of metal strips (electrodes) with a pitch of 25 [mu]m on the top surface of a silicon chip, each electrode having its own charge pulse sensor, 8-bit counter and control/interface circuitry. The chip is mounted on a ceramic substrate and is preceded by a micro-channel plate electron multiplier. Chips are butted to give a longer array. Test results show a stable operating region. A digital-signal-processor-based interface is described, which controls the mode of operation and reads the accumulated array data at the maximum rate to avoid counter overflow. (author).

Delivering key signals to the machine: seeking the electric signal that muscles emanate

International Nuclear Information System (INIS)

Hashim, A Y Bani; Maslan, M N; Izamshah, R; Mohamad, I S

2014-01-01

Due to the limitation of electric power generation in the human body, present human-machine interfaces have not been successful because of the nature of standard electronics circuit designs, which do not consider the specifications of signals that resulted from the skin. In general, the outcomes and applications of human-machine interfaces are limited to custom-designed subsystems, such as neuroprosthesis. We seek to model the bio dynamical of sub skin into equivalent mathematical definitions, descriptions, and theorems. Within the human skin, there are networks of nerves that permit the skin to function as a multi dimension transducer. We investigate the nature of structural skin. Apart from multiple networks of nerves, there are other segments within the skin such as minute muscles. We identify the segments that are active when there is an electromyography activity. When the nervous system is firing signals, the muscle is being stimulated. We evaluate the phenomena of biodynamic of the muscles that is concerned with the electromyography activity of the nervous system. In effect, we design a relationship between the human somatosensory and synthetic systems sensory as the union of a complete set of the new domain of the functional system. This classifies electromyogram waveforms linked to intent thought of an operator. The system will become the basis for delivering key signals to machine such that the machine is under operator's intent, hence slavery

Detectors and signal processing for high-energy physics

International Nuclear Information System (INIS)

Rehak, P.

1981-01-01

Basic principles of the particle detection and signal processing for high-energy physics experiments are presented. It is shown that the optimum performance of a properly designed detector system is not limited by incidental imperfections, but solely by more fundamental limitations imposed by the quantum nature and statistical behavior of matter. The noise sources connected with the detection and signal processing are studied. The concepts of optimal filtering and optimal detector/amplifying device matching are introduced. Signal processing for a liquid argon calorimeter is analyzed in some detail. The position detection in gas counters is studied. Resolution in drift chambers for the drift coordinate measurement as well as the second coordinate measurement is discussed

Analysis of photogenerated random telegraph signal in single electron detector (photo-SET).

Science.gov (United States)

Troudi, M; Sghaier, Na; Kalboussi, A; Souifi, A

2010-01-04

In this paper, we analyzed slow single traps, situated inside the tunnel oxide of small area single electron photo-detector (photo-SET or nanopixel). The relationship between excitation signal (photons) and random-telegraph-signal (RTS) was evidenced. We demonstrated that photoinduced RTS observed on a photo-detector is due to the interaction between single photogenerated charges that tunnel from dot to dot and current path. Based on RTS analysis for various temperatures, gate bias and optical power we determined the characteristics of these single photogenerated traps: the energy position within the silicon bandgap, capture cross section and the position within the Si/SiO(x = 1.5) interfaces.

Development of a new signal processor for tetralateral position sensitive detector based on single-chip microcomputer

International Nuclear Information System (INIS)

Huang Meizhen; Shi Longzhao; Wang Yuxing; Ni Yi; Li Zhenqing; Ding Haifeng

2006-01-01

An inherently nonlinear relation between the output current of the tetralateral position sensitive detector (PSD) and the position of the incident light spot has been found theoretically. Based on single-chip microcomputer and the theoretical relation between output current and position, a new signal processor capable of correcting nonlinearity and reducing position measurement deviation of tetralateral PSD was developed. A tetralateral PSD (S1200, 13x13 mm 2 , Hamamatsu Photonics K.K.) was measured with the new signal processor, a linear relation between the output position of the PSD, and the incident position of the light spot was obtained. In the 60% range of a 13x13 mm 2 active area, the position nonlinearity (rms) was 0.15% and the position measurement deviation (rms) was ±20 μm. Compared with traditional analog signal processor, the new signal processor is of better compatibility, lower cost, higher precision, and easier to be interfaced

Searching for gravitational-wave signals emitted by eccentric compact binaries using a non-eccentric template bank: implications for ground-based detectors

Energy Technology Data Exchange (ETDEWEB)

Cokelaer, T; Pathak, D, E-mail: Thomas.Cokelaer@astro.cf.ac.u, E-mail: Devanka.Pathak@astro.cf.ac.u [School of Physics and Astronomy, Cardiff University, Cardiff CF24 3AA (United Kingdom)

2009-02-21

Most of the inspiralling compact binaries are expected to be circularized by the time their gravitational-wave signals enter the frequency band of ground-based detectors such as LIGO or VIRGO. However, it is not excluded that some of these binaries might still possess a significant eccentricity at a few tens of hertz. Despite this possibility, current search pipelines-based on matched filtering techniques-consider only non-eccentric templates. The effect of such an approximation on the loss of signal-to-noise ratio (SNR) has been investigated by Martel and Poisson (1999 Phys. Rev. D 60 124008) in the context of initial LIGO detector. They ascertained that non-eccentric templates will be successful at detecting eccentric signals. We revisit their work by incorporating current and future ground-based detectors and precisely quantify the exact loss of SNR. In order to be more faithful to an actual search, we maximized the SNR over a template bank, whose minimal match is set to 95%. For initial LIGO detector, we claim that the initial eccentricity does not need to be taken into account in our searches for any system with total mass M element of [2-45]M{sub o-dot} if e{sub 0} approx< 0.05 because the loss of SNR (about 5%) is consistent with the discreteness of the template bank. Similarly, this statement is also true for systems with M element of [6-35]M{sub o-dot} and e{sub 0} approx< 0.10. However, by neglecting the eccentricity in our searches, significant loss of detection (larger than 10%) may arise as soon as e{sub 0} >= 0.05 for neutron-star binaries. We also provide exhaustive results for VIRGO, Advanced LIGO and Einstein Telescope detectors. It is worth noting that for Einstein Telescope, neutron star binaries with e{sub 0} >= 0.02 lead to a 10% loss of detection.

An information-theoretical approach to image resolution applied to neutron imaging detectors based upon individual discriminator signals

International Nuclear Information System (INIS)

Clergeau, Jean-Francois; Ferraton, Matthieu; Guerard, Bruno; Khaplanov, Anton; Piscitelli, Francesco; Platz, Martin; Rigal, Jean-Marie; Van Esch, Patrick; Daulle, Thibault

2013-06-01

1D or 2D neutron imaging detectors with individual wire or strip readout using discriminators have the advantage of being able to treat several neutron impacts partially overlapping in time, hence reducing global dead time. A single neutron impact usually gives rise to several discriminator signals. In this paper, we introduce an information-theoretical definition of image resolution. Two point-like spots of neutron impacts with a given distance between them act as a source of information (each neutron hit belongs to one spot or the other), and the detector plus signal treatment is regarded as an imperfect communication channel that transmits this information. The maximal mutual information obtained from this channel as a function of the distance between the spots allows to define a calibration-independent measure of resolution. We then apply this measure to quantify the power of resolution of different algorithms treating these individual discriminator signals which can be implemented in firmware. The method is then applied to different detectors existing at the ILL. Center-of-gravity methods usually improve the resolution over best-wire algorithms which are the standard way of treating these signals. (authors)

An information-theoretical approach to image resolution applied to neutron imaging detectors based upon individual discriminator signals

Energy Technology Data Exchange (ETDEWEB)

Clergeau, Jean-Francois; Ferraton, Matthieu; Guerard, Bruno; Khaplanov, Anton; Piscitelli, Francesco; Platz, Martin; Rigal, Jean-Marie; Van Esch, Patrick [Institut Laue Langevin, Neutron Detector Service, Grenoble (France); Daulle, Thibault [PHELMA Grenoble - INP Grenoble (France)

2013-06-15

1D or 2D neutron imaging detectors with individual wire or strip readout using discriminators have the advantage of being able to treat several neutron impacts partially overlapping in time, hence reducing global dead time. A single neutron impact usually gives rise to several discriminator signals. In this paper, we introduce an information-theoretical definition of image resolution. Two point-like spots of neutron impacts with a given distance between them act as a source of information (each neutron hit belongs to one spot or the other), and the detector plus signal treatment is regarded as an imperfect communication channel that transmits this information. The maximal mutual information obtained from this channel as a function of the distance between the spots allows to define a calibration-independent measure of resolution. We then apply this measure to quantify the power of resolution of different algorithms treating these individual discriminator signals which can be implemented in firmware. The method is then applied to different detectors existing at the ILL. Center-of-gravity methods usually improve the resolution over best-wire algorithms which are the standard way of treating these signals. (authors)

New estimates of extensive-air-shower energies on the basis of signals in scintillation detectors

Energy Technology Data Exchange (ETDEWEB)

Anyutin, N. V.; Dedenko, L. G., E-mail: ddn@dec1.sinp.msu.ru [Moscow State University, Faculty of Physics (Russian Federation); Roganova, T. M.; Fedorova, G. F. [Moscow State University, Skobeltsyn Institute of Nuclear Physics (Russian Federation)

2017-03-15

New formulas for estimating the energy of inclined extensive air showers (EASs) on the basis of signals in detectors by means of an original method and detailed tables of signals induced in scintillation detectors by photons, electrons, positrons, and muons and calculated with the aid of the GEANT4 code package were proposed in terms of the QGSJETII-04, EPOS LHC, and GHEISHA models. The parameters appearing in the proposed formulas were calculated by employing the CORSIKA code package. It is shown that, for showers of zenith angles in the range of 20◦–45◦, the standard constant-intensity-cut method, which is used to interpret data from the Yakutsk EAS array, overestimates the shower energy by a factor of 1.2 to 1.5. It is proposed to employ the calculated VEM (Vertical Equivalent Muon) signal units of 10.8 and 11.4 MeV for, respectively, ground-based and underground scintillation detectors and to take into account the dependence of signals on the azimuthal angle of the detector position and fluctuations in the development of showers.

The Data Acquisition System for a Kinetic Inductance Detector

International Nuclear Information System (INIS)

Branchini, P; Budano, A; Capasso, L; Marchetti, D

2015-01-01

The Data Acquisition System (DAQ) and the Front-End electronics for an array of Kinetic Inductance Detectors (KIDs) are described. KIDs are superconductive detectors, in which electrons are organized in Cooper pairs. Any incident radiation could break a pair generating a couple of quasi-particles that increase the inductance of the detector. The DAQ system we developed is a hardware/software co-design, based on state machines and on a microprocessor embedded into an FPGA. A commercial DAC/ADC board is used to interface the FPGA to the array of KIDs. The DAQ system generates a Stimulus signal suitable for an array of up to 128 KIDs. Such signal is up-mixed with a 3 GHz carrier wave and it then excites the KIDs array. The read-out signal from the detector is down-mixed with respect to the 3 GHz sine wave and recovered Stimulus is read back by the ADC device. The microprocessor stores read out data via a PCI express bus (PCIe) into an external disk. It also computes the Fast Fourier Transform of the acquired read out signal: this allows extrapolating which KID interacted and the energy of the impinging radiation. Simulations and tests have been performed successfully and experimental results are presented. (paper)

Reconstruction of Micropattern Detector Signals using Convolutional Neural Networks

Science.gov (United States)

Flekova, L.; Schott, M.

2017-10-01

Micropattern gaseous detector (MPGD) technologies, such as GEMs or MicroMegas, are particularly suitable for precision tracking and triggering in high rate environments. Given their relatively low production costs, MPGDs are an exemplary candidate for the next generation of particle detectors. Having acknowledged these advantages, both the ATLAS and CMS collaborations at the LHC are exploiting these new technologies for their detector upgrade programs in the coming years. When MPGDs are utilized for triggering purposes, the measured signals need to be precisely reconstructed within less than 200 ns, which can be achieved by the usage of FPGAs. In this work, we present a novel approach to identify reconstructed signals, their timing and the corresponding spatial position on the detector. In particular, we study the effect of noise and dead readout strips on the reconstruction performance. Our approach leverages the potential of convolutional neural network (CNNs), which have recently manifested an outstanding performance in a range of modeling tasks. The proposed neural network architecture of our CNN is designed simply enough, so that it can be modeled directly by an FPGA and thus provide precise information on reconstructed signals already in trigger level.

A new kind of metal detector based on chaotic oscillator

Science.gov (United States)

Hu, Wenjing

2017-12-01

The sensitivity of a metal detector greatly depends on the identification ability to weak signals from the probe. In order to improve the sensitivity of metal detectors, this paper applies the Duffing chaotic oscillator to metal detectors based on its characteristic which is very sensitive to weak periodic signals. To make a suitable Duffing system for detectors, this paper computes two Lyapunov characteristics exponents of the Duffing oscillator, which help to obtain the threshold of the Duffing system in the critical state accurately and give quantitative criteria for chaos. Meanwhile, a corresponding simulation model of the chaotic oscillator is made by the Simulink tool box of Matlab. Simulation results shows that Duffing oscillator is very sensitive to sinusoidal signals in high frequency cases. And experimental results show that the measurable diameter of metal particles is about 1.5mm. It indicates that this new method can feasibly and effectively improve the metal detector sensitivity.

A benefit assessment of using in-core neutron detector signals in core protection calculator system (CPCS)

International Nuclear Information System (INIS)

Han, S.; Park, S.J.; Seong, P.H.

1997-01-01

A Core Protection Calculator System (CPCS) is a digital computer based safety system generating trip signals based on the calculation of Departure from Nucleate Boiling Ratio (DNBR) and Local Power Density (LPD). Currently, CPCS uses ex-core detector signals for core power calculation and it has some uncertainties. In this study, in-core detector signals which directly measure inside flux of core are applied to CPCS to get more accurate power distribution profile, DNBR and LPD. In order to improve axial power distribution calculation, piece-wise cubic Spline method is applied; from the 40 nodes of expanded signals, more accurate and detailed core information can be provided. Simulation is carried out to verify its applicability to power distribution calculation. Simulation result shows that the improved method reduces the calculational uncertainties significantly and it allows larger operational margin. It is also expected that no power reduction is required while Core Operating Limit Supervisory System (COLSS) is out-of-service due to reduced uncertainties when the improved method is applied. In this study, a quantitative economic benefit assessment of using in-core neutron detector signals is also carried out. (authors)

A benefit assessment of using in-core neutron detector signals in core protection calculator system(CPCS)

International Nuclear Information System (INIS)

Han, Seung

1996-02-01

A Core Protection Calculator System(CPCS) is a digital computer based safety system generating trip signals based on the calculation of Departure from Nucleate Boiling Ratio(DNBR) and Local Power Density(LPD). Currently, CPCS uses ex-core detector signals for core power calculation and it has some uncertainties. In this study, In-core detector signals which directly measure inside flux of core are applied to CPCS to get more accurate power distribution profile, DNBR and LPD. In order to improve axial power distribution calculation, piecewise cubic spline method is applied: From the 40 nodes of expanded signals, more accurate and detailed core information can be provided. Simulation is carried out to verify its applicability to power distribution calculation. Simulation result shows that the improved method reduces the calculational uncertainties significantly and it allows larger operational margin. It is also expected that no power reduction is required while Core Operating Limit Supervisory System(COLSS) is out-of-service due to reduced uncertainties when the improved method is applied. In this study, a quantitative economic benefit assessment of using in-core neutron detector signals is also carried out

Improved fabrication of HgI2 nuclear radiation detectors by machine-cleaving

International Nuclear Information System (INIS)

Levi, A.; Burger, A.; Schieber, M.; Vandenberg, L.; Yellon, W.B.; Alkire, R.W.

1982-01-01

The perfection of machine-cleaved sections from HgI 2 bulk crystals was examined. The perfection of the machine-cleaved sections as established by gamma diffraction rocking curves was found to be much better than the perfection of hand-cleaved sections or as grown thin platelets, reaching a perfection similar to that of the wire-sawn sections of HgI 2 . A correlation between the perfection and the thickness of the machine-cleaved section was also found, i.e., the thicker the cleaved-section the more perfect it is. The reproducibility of the fabrication was significantly improved by using machine cleaving in the process of fabrication. Large single crystals of HgI 2 weighing 20 to 200 g, can be grown from the vapor phase using the TOM Technique. In order to fabricate nuclear radiation detectors from these single crystals, thin sections of about 0.4 to 0.8 mm thickness have to be prepared. Up till now, the state-of-the-art of fabricating HgI 2 nuclear radiation detectors involved two methods to get thin sections from the large single crystals: (1) hand-cleaving using a razor-blade and (2) solution wire sawing. The chemical wire sawing method involves a loss of about 50% of the crystal volume and is usually followed by a chemical polishing process which involves a significant loss of volume of the original volume. This procedure is complicated and wasteful. The traditional fabrication method, i.e., hand-cleaving followed by rapid nonselective chemical etching, is simpler and less wasteful

The desktop muon detector: A simple, physics-motivated machine- and electronics-shop project for university students

Science.gov (United States)

Axani, S. N.; Conrad, J. M.; Kirby, C.

2017-12-01

This paper describes the construction of a desktop muon detector, an undergraduate-level physics project that develops machine-shop and electronics-shop technical skills. The desktop muon detector is a self-contained apparatus that employs a plastic scintillator as the detection medium and a silicon photomultiplier for light collection. This detector can be battery powered and is used in conjunction with the provided software. The total cost per detector is approximately 100. We describe physics experiments we have performed, and then suggest several other interesting measurements that are possible, with one or more desktop muon detectors.

Machine learning based Intelligent cognitive network using fog computing

Science.gov (United States)

Lu, Jingyang; Li, Lun; Chen, Genshe; Shen, Dan; Pham, Khanh; Blasch, Erik

2017-05-01

In this paper, a Cognitive Radio Network (CRN) based on artificial intelligence is proposed to distribute the limited radio spectrum resources more efficiently. The CRN framework can analyze the time-sensitive signal data close to the signal source using fog computing with different types of machine learning techniques. Depending on the computational capabilities of the fog nodes, different features and machine learning techniques are chosen to optimize spectrum allocation. Also, the computing nodes send the periodic signal summary which is much smaller than the original signal to the cloud so that the overall system spectrum source allocation strategies are dynamically updated. Applying fog computing, the system is more adaptive to the local environment and robust to spectrum changes. As most of the signal data is processed at the fog level, it further strengthens the system security by reducing the communication burden of the communications network.

Signal and noise analysis of a-Si:H radiation detector-amplifier system

International Nuclear Information System (INIS)

Cho, Gyuseong.

1992-03-01

Hydrogenated amorphous silicon (a-Si:H) has potential advantages in making radiation detectors for many applications because of its deposition capability on a large-area substrate and its high radiation resistance. Position-sensitive radiation detectors can be made out of a 1d strip or a 2-d pixel array of a Si:H pin diodes. In addition, signal processing electronics can be made by thin-film transistors on the same substrate. The calculated radiation signal, based on a simple charge collection model agreed well with results from various wave length light sources and 1 MeV beta particles on sample diodes. The total noise of the detection system was analyzed into (a) shot noise and (b) 1/f noise from a detector diode, and (c) thermal noise and (d) 1/f noise from the frontend TFT of a charge-sensitive preamplifier. the effective noise charge calculated by convoluting these noise power spectra with the transfer function of a CR-RC shaping amplifier showed a good agreement with the direct measurements of noise charge. The derived equations of signal and noise charge can be used to design an a-Si:H pixel detector amplifier system optimally. Signals from a pixel can be readout using switching TFTs, or diodes. Prototype tests of a double-diode readout scheme showed that the storage time and the readout time are limited by the resistances of the reverse-biased pixel diode and the forward biased switching diodes respectively. A prototype charge-sensitive amplifier was made using poly-Si TFTs to test the feasibility of making pixel-level amplifiers which would be required in small-signal detection. The measured overall gain-bandwidth product was ∼400 MHz and the noise charge ∼1000 electrons at a 1 μsec shaping time. When the amplifier is connected to a pixel detector of capacitance 0.2 pF, it would give a charge-to-voltage gain of ∼0.02 mV/electron with a pulse rise time less than 100 nsec and a dynamic range of 48 dB

Signal and noise analysis of a-Si:H radiation detector-amplifier system

Energy Technology Data Exchange (ETDEWEB)

Cho, Gyuseong [Univ. of California, Berkeley, CA (United States)

1992-03-01

Hydrogenated amorphous silicon (a-Si:H) has potential advantages in making radiation detectors for many applications because of its deposition capability on a large-area substrate and its high radiation resistance. Position-sensitive radiation detectors can be made out of a 1d strip or a 2-d pixel array of a Si:H pin diodes. In addition, signal processing electronics can be made by thin-film transistors on the same substrate. The calculated radiation signal, based on a simple charge collection model agreed well with results from various wave length light sources and 1 MeV beta particles on sample diodes. The total noise of the detection system was analyzed into (a) shot noise and (b) 1/f noise from a detector diode, and (c) thermal noise and (d) 1/f noise from the frontend TFT of a charge-sensitive preamplifier. the effective noise charge calculated by convoluting these noise power spectra with the transfer function of a CR-RC shaping amplifier showed a good agreement with the direct measurements of noise charge. The derived equations of signal and noise charge can be used to design an a-Si:H pixel detector amplifier system optimally. Signals from a pixel can be readout using switching TFTs, or diodes. Prototype tests of a double-diode readout scheme showed that the storage time and the readout time are limited by the resistances of the reverse-biased pixel diode and the forward biased switching diodes respectively. A prototype charge-sensitive amplifier was made using poly-Si TFTs to test the feasibility of making pixel-level amplifiers which would be required in small-signal detection. The measured overall gain-bandwidth product was ~400 MHz and the noise charge ~1000 electrons at a 1 μsec shaping time. When the amplifier is connected to a pixel detector of capacitance 0.2 pF, it would give a charge-to-voltage gain of ~0.02 mV/electron with a pulse rise time less than 100 nsec and a dynamic range of 48 dB.

Signal and noise analysis of a-Si:H radiation detector-amplifier system

Energy Technology Data Exchange (ETDEWEB)

Cho, Gyuseong.

1992-03-01

Hydrogenated amorphous silicon (a-Si:H) has potential advantages in making radiation detectors for many applications because of its deposition capability on a large-area substrate and its high radiation resistance. Position-sensitive radiation detectors can be made out of a 1d strip or a 2-d pixel array of a Si:H pin diodes. In addition, signal processing electronics can be made by thin-film transistors on the same substrate. The calculated radiation signal, based on a simple charge collection model agreed well with results from various wave length light sources and 1 MeV beta particles on sample diodes. The total noise of the detection system was analyzed into (a) shot noise and (b) 1/f noise from a detector diode, and (c) thermal noise and (d) 1/f noise from the frontend TFT of a charge-sensitive preamplifier. the effective noise charge calculated by convoluting these noise power spectra with the transfer function of a CR-RC shaping amplifier showed a good agreement with the direct measurements of noise charge. The derived equations of signal and noise charge can be used to design an a-Si:H pixel detector amplifier system optimally. Signals from a pixel can be readout using switching TFTs, or diodes. Prototype tests of a double-diode readout scheme showed that the storage time and the readout time are limited by the resistances of the reverse-biased pixel diode and the forward biased switching diodes respectively. A prototype charge-sensitive amplifier was made using poly-Si TFTs to test the feasibility of making pixel-level amplifiers which would be required in small-signal detection. The measured overall gain-bandwidth product was {approximately}400 MHz and the noise charge {approximately}1000 electrons at a 1 {mu}sec shaping time. When the amplifier is connected to a pixel detector of capacitance 0.2 pF, it would give a charge-to-voltage gain of {approximately}0.02 mV/electron with a pulse rise time less than 100 nsec and a dynamic range of 48 dB.

Beam Collimation and Machine-Detector Interface at the International Linear Collider

CERN Document Server

Mokhov, Nikolai V; Kostin, Mikhail A

2005-01-01

Synchrotron radiation, spray from the dumps and extraction lines, beam-gas and beam halo interactions with collimators and other components in the ILC beam delivery system create fluxes of muons and other secondaries which can exceed the tolerable levels at a detector by a few orders of magnitude. It is shown that with a multi-stage collimation system, magnetized iron spoilers which fill the tunnel and a set of masks in the detector, one can hopefully meet the design goals. Results of modeling with the STRUCT and MARS15 codes of beam loss and energy deposition effects are presented in this paper. We concentrate on collimation system and mask design and optimization, short- and long-term survivability of the critical components (spoilers, absorbers, magnets, separators, dumps), dynamic heat loads and radiation levels in magnets and other components, machine-related backgrounds and damage in collider detectors, and environmental aspects (prompt dose, ground-water and air activation).

Improved method for SNR prediction in machine-learning-based test

NARCIS (Netherlands)

Sheng, Xiaoqin; Kerkhoff, Hans G.

2010-01-01

This paper applies an improved method for testing the signal-to-noise ratio (SNR) of Analogue-to-Digital Converters (ADC). In previous work, a noisy and nonlinear pulse signal is exploited as the input stimulus to obtain the signature results of ADC. By applying a machine-learning-based approach,

A design of energy detector for ArF excimer lasers

Science.gov (United States)

Feng, Zebin; Han, Xiaoquan; Zhou, Yi; Bai, Lujun

2017-08-01

ArF excimer lasers with short wavelength and high photon energy are widely applied in the field of integrated circuit lithography, material processing, laser medicine, and so on. Excimer laser single pulse energy is a very important parameter in the application. In order to detect the single pulse energy on-line, one energy detector based on photodiode was designed. The signal processing circuit connected to the photodiode was designed so that the signal obtained by the photodiode was amplified and the pulse width was broadened. The amplified signal was acquired by a data acquisition card and stored in the computer for subsequent data processing. The peak of the pulse signal is used to characterize the single pulse energy of ArF excimer laser. In every condition of deferent pulse energy value levels, a series of data about laser pulses energy were acquired synchronously using the Ophir energy meter and the energy detector. A data set about the relationship between laser pulse energy and the peak of the pulse signal was acquired. Then, by using the data acquired, a model characterizing the functional relationship between the energy value and the peak value of the pulse was trained based on an algorithm of machine learning, Support Vector Regression (SVR). By using the model, the energy value can be obtained directly from the energy detector designed in this project. The result shows that the relative error between the energy obtained by the energy detector and by the Ophir energy meter is less than 2%.

Non-linear dynamical signal characterization for prediction of defibrillation success through machine learning

Directory of Open Access Journals (Sweden)

Shandilya Sharad

2012-10-01

Full Text Available Abstract Background Ventricular Fibrillation (VF is a common presenting dysrhythmia in the setting of cardiac arrest whose main treatment is defibrillation through direct current countershock to achieve return of spontaneous circulation. However, often defibrillation is unsuccessful and may even lead to the transition of VF to more nefarious rhythms such as asystole or pulseless electrical activity. Multiple methods have been proposed for predicting defibrillation success based on examination of the VF waveform. To date, however, no analytical technique has been widely accepted. We developed a unique approach of computational VF waveform analysis, with and without addition of the signal of end-tidal carbon dioxide (PetCO2, using advanced machine learning algorithms. We compare these results with those obtained using the Amplitude Spectral Area (AMSA technique. Methods A total of 90 pre-countershock ECG signals were analyzed form an accessible preshosptial cardiac arrest database. A unified predictive model, based on signal processing and machine learning, was developed with time-series and dual-tree complex wavelet transform features. Upon selection of correlated variables, a parametrically optimized support vector machine (SVM model was trained for predicting outcomes on the test sets. Training and testing was performed with nested 10-fold cross validation and 6–10 features for each test fold. Results The integrative model performs real-time, short-term (7.8 second analysis of the Electrocardiogram (ECG. For a total of 90 signals, 34 successful and 56 unsuccessful defibrillations were classified with an average Accuracy and Receiver Operator Characteristic (ROC Area Under the Curve (AUC of 82.2% and 85%, respectively. Incorporation of the end-tidal carbon dioxide signal boosted Accuracy and ROC AUC to 83.3% and 93.8%, respectively, for a smaller dataset containing 48 signals. VF analysis using AMSA resulted in accuracy and ROC AUC of 64

The Effect of Personalization on Smartphone-Based Fall Detectors

Directory of Open Access Journals (Sweden)

Carlos Medrano

2016-01-01

Full Text Available The risk of falling is high among different groups of people, such as older people, individuals with Parkinson's disease or patients in neuro-rehabilitation units. Developing robust fall detectors is important for acting promptly in case of a fall. Therefore, in this study we propose to personalize smartphone-based detectors to boost their performance as compared to a non-personalized system. Four algorithms were investigated using a public dataset: three novelty detection algorithms—Nearest Neighbor (NN, Local Outlier Factor (LOF and One-Class Support Vector Machine (OneClass-SVM—and a traditional supervised algorithm, Support Vector Machine (SVM. The effect of personalization was studied for each subject by considering two different training conditions: data coming only from that subject or data coming from the remaining subjects. The area under the receiver operating characteristic curve (AUC was selected as the primary figure of merit. The results show that there is a general trend towards the increase in performance by personalizing the detector, but the effect depends on the individual being considered. A personalized NN can reach the performance of a non-personalized SVM (average AUC of 0.9861 and 0.9795, respectively, which is remarkable since NN only uses activities of daily living for training.

OPTICALLY BASED CHARGE INJECTION SYSTEM FOR IONIZATION DETECTORS

International Nuclear Information System (INIS)

CHEN, H.; CITTERIO, M.; LANNI, F.; LEITE, M.A.L.; RADEKA, V.; RESCIA, S.; TAKAI, H.

2001-01-01

An optically coupled charge injection system for ionization based radiation detectors which allows a test charge to be injected without the creation of ground loops has been developed. An ionization like signal from an external source is brought into the detector through an optical fiber and injected into the electrodes by means of a photodiode. As an application example, crosstalk measurements on a liquid Argon electromagnetic calorimeter readout electrodes were performed

Noise and signal processing in a microstrip detector with a time variant readout system

International Nuclear Information System (INIS)

Cattaneo, P.W.

1995-01-01

This paper treats the noise and signal processing by a time variant filter in a microstrip detector. In particular, the noise sources in the detector-electronics chain and the signal losses that cause a substantial decrease of the original signal are thoroughly analyzed. This work has been motivated by the analysis of the data of the microstrip detectors designed for the ALEPH minivertex detector. Hence, even if the discussion will be kept as general as possible, concrete examples will be presented referring to the specific ALEPH design. (orig.)

Coherent search of continuous gravitational wave signals: extension of the 5-vectors method to a network of detectors

International Nuclear Information System (INIS)

Astone, P; Colla, A; Frasca, S; Palomba, C; D'Antonio, S

2012-01-01

We describe the extension to multiple datasets of a coherent method for the search of continuous gravitational wave signals, based on the computation of 5-vectors. In particular, we show how to coherently combine different datasets belonging to the same detector or to different detectors. In the latter case the coherent combination is the way to have the maximum increase in signal-to-noise ratio. If the datasets belong to the same detector the advantage comes mainly from the properties of a quantity called coherence which is helpful (in both cases, in fact) in rejecting false candidates. The method has been tested searching for simulated signals injected in Gaussian noise and the results of the simulations are discussed.

Prediction of Machine Tool Condition Using Support Vector Machine

International Nuclear Information System (INIS)

Wang Peigong; Meng Qingfeng; Zhao Jian; Li Junjie; Wang Xiufeng

2011-01-01

Condition monitoring and predicting of CNC machine tools are investigated in this paper. Considering the CNC machine tools are often small numbers of samples, a condition predicting method for CNC machine tools based on support vector machines (SVMs) is proposed, then one-step and multi-step condition prediction models are constructed. The support vector machines prediction models are used to predict the trends of working condition of a certain type of CNC worm wheel and gear grinding machine by applying sequence data of vibration signal, which is collected during machine processing. And the relationship between different eigenvalue in CNC vibration signal and machining quality is discussed. The test result shows that the trend of vibration signal Peak-to-peak value in surface normal direction is most relevant to the trend of surface roughness value. In trends prediction of working condition, support vector machine has higher prediction accuracy both in the short term ('One-step') and long term (multi-step) prediction compared to autoregressive (AR) model and the RBF neural network. Experimental results show that it is feasible to apply support vector machine to CNC machine tool condition prediction.

Application for vibration monitoring of aspheric surface machining based on wireless sensor networks

Science.gov (United States)

Han, Chun Guang; Guo, Yin Biao; Jiang, Chen

2010-05-01

Any kinds of tiny vibration of machine tool parts will have a great influence on surface quality of the workpiece at ultra-precise machining process of aspheric surface. At present the major way for decreasing influence of vibration is machining compensation technology. Therefore it is important for machining compensation control to acquire and transmit these vibration signals effectively. This paper presents a vibration monitoring system of aspheric surface machining machine tool based on wireless sensor networks (WSN). Some key issues of wireless sensor networks for vibration monitoring system of aspheric surface machining are discussed. The reliability of data transmission, network communication protocol and synchronization mechanism of wireless sensor networks are studied for the vibration monitoring system. The proposed system achieves multi-sensors vibration monitoring involving the grinding wheel, the workpiece and the workbench spindle. The wireless transmission of vibration signals is achieved by the combination with vibration sensor nodes and wireless network. In this paper, these vibration sensor nodes are developed. An experimental platform is structured which employs wireless sensor networks to the vibration monitoring system in order to test acquisition and wireless transmission of vibration signal. The test results show that the proposed system can achieve vibration data transmission effectively and reliability and meet the monitoring requirements of aspheric surface machining machine tool.

Evaluation of different time domain peak models using extreme learning machine-based peak detection for EEG signal.

Science.gov (United States)

Adam, Asrul; Ibrahim, Zuwairie; Mokhtar, Norrima; Shapiai, Mohd Ibrahim; Cumming, Paul; Mubin, Marizan

2016-01-01

Various peak models have been introduced to detect and analyze peaks in the time domain analysis of electroencephalogram (EEG) signals. In general, peak model in the time domain analysis consists of a set of signal parameters, such as amplitude, width, and slope. Models including those proposed by Dumpala, Acir, Liu, and Dingle are routinely used to detect peaks in EEG signals acquired in clinical studies of epilepsy or eye blink. The optimal peak model is the most reliable peak detection performance in a particular application. A fair measure of performance of different models requires a common and unbiased platform. In this study, we evaluate the performance of the four different peak models using the extreme learning machine (ELM)-based peak detection algorithm. We found that the Dingle model gave the best performance, with 72 % accuracy in the analysis of real EEG data. Statistical analysis conferred that the Dingle model afforded significantly better mean testing accuracy than did the Acir and Liu models, which were in the range 37-52 %. Meanwhile, the Dingle model has no significant difference compared to Dumpala model.

A 64-channel integrated circuit for signal readout from coordinate detectors

International Nuclear Information System (INIS)

Aulchenko, V.; Shekhtman, L.; Zhulanov, V.

2017-01-01

A specialized integrated circuit was developed for the readout of signal from coordinate detectors of different types, including gas micro-pattern detectors and silicon microstrip detectors. The ASIC includes 64 channels, each containing a low-noise charge-sensitive amplifier with a connectable feedback capacitor and resistor, and fast reset of the feedback capacitor. Each channel of the ASIC also contains 100 cells of analogue memory where the signal can be stored at a rate of 10 MHz. The pitch of input pads is 50 μm and the chip size is 5× 5 mm 2 . The equivalent noise charge of the ASIC channel is about 2000 electrons with 10 pF capacitance at the input and maximal signal before saturation corresponds to 2× 10 6 electrons. The first application for this ASIC is the detector for imaging of explosions at a synchrotron radiation beam (DIMEX), where it has to substitute the old and slower APC128 ASIC. The full-size electronics including 8 ASICs for 512 channels was assembled and tested.

Double gated-integrator for shaping nuclear radiation detector signals

International Nuclear Information System (INIS)

Gal, J.

2001-01-01

A new shaper, the double gated-integrator, for shaping nuclear radiation detector signals is investigated both theoretically and experimentally. The double gated-integrator consists of a pre-filter and two cascaded gated integrators. Two kinds of pre-filters were considered: a rectangular one and an exponential one. The results of the theoretical calculation show that the best figure of demerit for the double gated-integrator with exponential pre-filter is 1.016. This means that its noise to signal ratio is only 1.6% worse than that it is for infinite cusp shaping. The practical realization of the exponential pre-filter and that of the double gated integrator, both in analogue and in digital way, is very simple. Therefore, the double gated-integrator with exponential pre-filter could be a promising solution for shaping nuclear radiation detector signals

Signal formation and active edge studies of 3D silicon detector technology

CERN Document Server

Kok, Angela

3D detectors and devices with an ‘active edge’ were fabricated at the Stanford Nanofabrication Facility. Characteristics such as time response and edge sensitivity were studied. The induced signals from a 3D detector were studied using a fast, low-noise transimpedance amplifier. The rise time of the output signal obtained for a minimum ionising particle was faster than 4 ns at room temperature and 2 ns at 130K. This is in agreement with earlier calculations of 3D detectors that predicted the charge collection time to be between one to two ns. The first understanding of signal formation in a 3D detector was achieved by comparing measurements with a full system simulation. The differences in collection behaviour between electrons and holes were also understood and verified by measurement. Edge sensitivity was measured at the CERN SPS, using a high energy muon beam and a silicon telescope. The detector was measured to be efficient up to less than 4 μm from its physical edge. This confirmed that active edge ...

Machine learning approaches for the prediction of signal peptides and otherprotein sorting signals

DEFF Research Database (Denmark)

Nielsen, Henrik; Brunak, Søren; von Heijne, Gunnar

1999-01-01

Prediction of protein sorting signals from the sequence of amino acids has great importance in the field of proteomics today. Recently,the growth of protein databases, combined with machine learning approaches, such as neural networks and hidden Markov models, havemade it possible to achieve...

GELATIO: a general framework for modular digital analysis of high-purity Ge detector signals

International Nuclear Information System (INIS)

Agostini, M; Pandola, L; Zavarise, P; Volynets, O

2011-01-01

GELATIO is a new software framework for advanced data analysis and digital signal processing developed for the GERDA neutrinoless double beta decay experiment. The framework is tailored to handle the full analysis flow of signals recorded by high purity Ge detectors and photo-multipliers from the veto counters. It is designed to support a multi-channel modular and flexible analysis, widely customizable by the user either via human-readable initialization files or via a graphical interface. The framework organizes the data into a multi-level structure, from the raw data up to the condensed analysis parameters, and includes tools and utilities to handle the data stream between the different levels. GELATIO is implemented in C++. It relies upon ROOT and its extension TAM, which provides compatibility with PROOF, enabling the software to run in parallel on clusters of computers or many-core machines. It was tested on different platforms and benchmarked in several GERDA-related applications. A stable version is presently available for the GERDA Collaboration and it is used to provide the reference analysis of the experiment data.

GELATIO: a general framework for modular digital analysis of high-purity Ge detector signals

Science.gov (United States)

Agostini, M.; Pandola, L.; Zavarise, P.; Volynets, O.

2011-08-01

GELATIO is a new software framework for advanced data analysis and digital signal processing developed for the GERDA neutrinoless double beta decay experiment. The framework is tailored to handle the full analysis flow of signals recorded by high purity Ge detectors and photo-multipliers from the veto counters. It is designed to support a multi-channel modular and flexible analysis, widely customizable by the user either via human-readable initialization files or via a graphical interface. The framework organizes the data into a multi-level structure, from the raw data up to the condensed analysis parameters, and includes tools and utilities to handle the data stream between the different levels. GELATIO is implemented in C++. It relies upon ROOT and its extension TAM, which provides compatibility with PROOF, enabling the software to run in parallel on clusters of computers or many-core machines. It was tested on different platforms and benchmarked in several GERDA-related applications. A stable version is presently available for the GERDA Collaboration and it is used to provide the reference analysis of the experiment data.

Fission signal detection using helium-4 gas fast neutron scintillation detectors

Energy Technology Data Exchange (ETDEWEB)

Lewis, J. M., E-mail: lewisj@ufl.edu; Kelley, R. P.; Jordan, K. A. [Nuclear Engineering Program, University of Florida, Gainesville, Florida 32611 (United States); Murer, D. [Arktis Radiation Detectors Ltd., 8045 Zurich (Switzerland)

2014-07-07

We demonstrate the unambiguous detection of the fission neutron signal produced in natural uranium during active neutron interrogation using a deuterium-deuterium fusion neutron generator and a high pressure {sup 4}He gas fast neutron scintillation detector. The energy deposition by individual neutrons is quantified, and energy discrimination is used to differentiate the induced fission neutrons from the mono-energetic interrogation neutrons. The detector can discriminate between different incident neutron energies using pulse height discrimination of the slow scintillation component of the elastic scattering interaction between a neutron and the {sup 4}He atom. Energy histograms resulting from this data show the buildup of a detected fission neutron signal at higher energies. The detector is shown here to detect a unique fission neutron signal from a natural uranium sample during active interrogation with a (d, d) neutron generator. This signal path has a direct application to the detection of shielded nuclear material in cargo and air containers. It allows for continuous interrogation and detection while greatly minimizing the potential for false alarms.

Modelling of scintillator based flat-panel detectors with Monte-Carlo simulations

International Nuclear Information System (INIS)

Reims, N; Sukowski, F; Uhlmann, N

2011-01-01

Scintillator based flat panel detectors are state of the art in the field of industrial X-ray imaging applications. Choosing the proper system and setup parameters for the vast range of different applications can be a time consuming task, especially when developing new detector systems. Since the system behaviour cannot always be foreseen easily, Monte-Carlo (MC) simulations are keys to gain further knowledge of system components and their behaviour for different imaging conditions. In this work we used two Monte-Carlo based models to examine an indirect converting flat panel detector, specifically the Hamamatsu C9312SK. We focused on the signal generation in the scintillation layer and its influence on the spatial resolution of the whole system. The models differ significantly in their level of complexity. The first model gives a global description of the detector based on different parameters characterizing the spatial resolution. With relatively small effort a simulation model can be developed which equates the real detector regarding signal transfer. The second model allows a more detailed insight of the system. It is based on the well established cascade theory, i.e. describing the detector as a cascade of elemental gain and scattering stages, which represent the built in components and their signal transfer behaviour. In comparison to the first model the influence of single components especially the important light spread behaviour in the scintillator can be analysed in a more differentiated way. Although the implementation of the second model is more time consuming both models have in common that a relatively small amount of system manufacturer parameters are needed. The results of both models were in good agreement with the measured parameters of the real system.

An instrumentation amplifier based readout circuit for a dual element microbolometer infrared detector

Science.gov (United States)

de Waal, D. J.; Schoeman, J.

2014-06-01

The infrared band is widely used in many applications to solve problems stretching over very diverse fields, ranging from medical applications like inflammation detection to military, security and safety applications employing thermal imaging in low light conditions. At the heart of these optoelectrical systems lies a sensor used to detect incident infrared radiation, and in the case of this work our focus is on uncooled microbolometers as thermal detectors. Microbolometer based thermal detectors are limited in sensitivity by various parameters, including the detector layout and design, operating temperature, air pressure and biasing that causes self heating. Traditional microbolometers use the entire membrane surface for a single detector material. This work presents the design of a readout circuit amplifier where a dual detector element microbolometer is used, rather than the traditional single element. The concept to be investigated is based on the principle that both elements will be stimulated with a similar incoming IR signal and experience the same resistive change, thus creating a common mode signal. However, such a common mode signal will be rejected by a differential amplifier, thus one element is placed within a negative resistance converter to create a differential mode signal that is twice the magnitude of the comparable single mode signal of traditional detector designs. An instrumentation amplifier is used for the final stage of the readout amplifier circuit, as it allows for very high common mode rejection with proper trimming of the Wheatstone bridge to compensate for manufacturing tolerance. It was found that by implementing the above, improved sensitivity can be achieved.

Simulation of medical irradiation and X-ray detector signals

Energy Technology Data Exchange (ETDEWEB)

Kreisler, Bjoern

2010-02-08

This thesis aims for an improved understanding of medical irradiation. Two major parts are investigated: the beam shaping components of a medical linear accelerator, i.e. the source of the radiation, and the signal generation inside semiconductor sensors, i.e. the detection of the radiation. The direct measurement of the spatial and spectral particle distribution in the irradiation beam is not possible with state of the art detectors due to the high particle flux. The development of new advanced detectors is the goal of the first part of this thesis. The focus is set on the signal generation inside the sensor volume of a semiconductor detector. Incoming particles interact with the sensor material and generate clouds of electron hole pairs. These pairs get separated by an applied bias voltage. The motion of the charge clouds is simulated with a finite element programme taking into account the drift and diffusion. Mirror charges are induced on the electrodes which move due to the motion of the charge cloud. The motion of the induced mirror charges leads to the signal that is detected. The transient calculation of the signals is based on Ramo's theorem. The efficient adjoint formulation of the induction solution is adjusted to doped materials, as for example the electric bias field and hence the motion of the charge cloud is changing with the doping level. The effect of the doping of the material on the signal shape is shown together with influences of different voltages and pixel geometries. Smaller pixels and higher bias voltages can lead to shorter signals which is preferable for high flux measurements. Possible count rate improvements are limited by electric break through, high dark current across the sensor layer and charge sharing. Another option to shorten the signals is the use of steering grid electrodes which modify the electric and the weighting field. This results in shorter signals and thus in a higher possible rate. The detailed Monte

Simulation of medical irradiation and X-ray detector signals

International Nuclear Information System (INIS)

Kreisler, Bjoern

2010-01-01

This thesis aims for an improved understanding of medical irradiation. Two major parts are investigated: the beam shaping components of a medical linear accelerator, i.e. the source of the radiation, and the signal generation inside semiconductor sensors, i.e. the detection of the radiation. The direct measurement of the spatial and spectral particle distribution in the irradiation beam is not possible with state of the art detectors due to the high particle flux. The development of new advanced detectors is the goal of the first part of this thesis. The focus is set on the signal generation inside the sensor volume of a semiconductor detector. Incoming particles interact with the sensor material and generate clouds of electron hole pairs. These pairs get separated by an applied bias voltage. The motion of the charge clouds is simulated with a finite element programme taking into account the drift and diffusion. Mirror charges are induced on the electrodes which move due to the motion of the charge cloud. The motion of the induced mirror charges leads to the signal that is detected. The transient calculation of the signals is based on Ramo's theorem. The efficient adjoint formulation of the induction solution is adjusted to doped materials, as for example the electric bias field and hence the motion of the charge cloud is changing with the doping level. The effect of the doping of the material on the signal shape is shown together with influences of different voltages and pixel geometries. Smaller pixels and higher bias voltages can lead to shorter signals which is preferable for high flux measurements. Possible count rate improvements are limited by electric break through, high dark current across the sensor layer and charge sharing. Another option to shorten the signals is the use of steering grid electrodes which modify the electric and the weighting field. This results in shorter signals and thus in a higher possible rate. The detailed Monte-Carlo simulation of

Gravity Spy - Integrating LIGO detector characterization, citizen science, and machine learning

Science.gov (United States)

Zevin, Michael; Gravity Spy

2016-06-01

On September 14th 2015, the Advanced Laser Interferometer Gravitational-wave Observatory (aLIGO) made the first direct observation of gravitational waves and opened a new field of observational astronomy. However, being the most complicated and sensitve experiment ever undertaken in gravitational physics, aLIGO is susceptible to various sources of environmental and instrumental noise that hinder the search for more gravitational waves.Of particular concern are transient, non-Gaussian noise features known as glitches. Glitches can mimic true astrophysical gravitational waves, occur at a high enough frequency to be coherent between the two detectors, and generally worsen aLIGO's detection capabilities. The proper classification and charaterization of glitches is paramount in optimizing aLIGO's ability to detect gravitational waves. However, teaching computers to identify and morphologically classify these artifacts is exceedingly difficult.Human intuition has proven to be a useful tool in classifcation probelms such as this. Gravity Spy is an innovative, interdisciplinary project hosted by Zooniverse that combines aLIGO detector characterization, citizen science, machine learning, and social science. In this project, citizen scientists and computers will work together in a sybiotic relationship that leverages human pattern recognition and the ability of machine learning to process large amounts of data systematically: volunteers classify triggers from the aLIGO data steam that are constantly updated as aLIGO takes in new data, and these classifications are used to train machine learning algorithms which proceed to classify the bulk of aLIGO data and feed questionable glithces back to the users.In this talk, I will discuss the workflow and initial results of the Gravity Spy project with regard to aLIGO's future observing runs and highlight the potential of such citizen science projects in promoting nascent fields such as gravitational wave astrophysics.

Digital signal processing for a thermal neutron detector using ZnS(Ag):{sup 6}LiF scintillating layers read out with WLS fibers and SiPMs

Energy Technology Data Exchange (ETDEWEB)

Mosset, J.-B., E-mail: jean-baptiste.mosset@psi.ch; Stoykov, A.; Greuter, U.; Hildebrandt, M.; Schlumpf, N.

2016-07-11

We present a digital signal processing system based on a photon counting approach which we developed for a thermal neutron detector consisting of ZnS(Ag):{sup 6}LiF scintillating layers read out with WLS fibers and SiPMs. Three digital filters have been evaluated: a moving sum, a moving sum after differentiation and a digital CR-RC{sup 4} filter. The performances of the detector with these filters are presented. A full analog signal processing using a CR-RC{sup 4} filter has been emulated digitally. The detector performance obtained with this analog approach is compared with the one obtained with the best performing digital approach. - Highlights: • Application of digital signal processing for a SiPM-based ZnS:6LiF neutron detector. • Optimisation of detector performances with 3 different digital filters. • Comparison with detector performances with a full analog signal processing.

Signal formation processes in Micromegas detectors and quality control for large size detector construction for the ATLAS new small wheel

Energy Technology Data Exchange (ETDEWEB)

Kuger, Fabian

2017-07-31

The Micromegas technology is one of the most successful modern gaseous detector concepts and widely utilized in nuclear and particle physics experiments. Twenty years of R and D rendered the technology sufficiently mature to be selected as precision tracking detector for the New Small Wheel (NSW) upgrade of the ATLAS Muon spectrometer. This will be the first large scale application of Micromegas in one of the major LHC experiments. However, many of the fundamental microscopic processes in these gaseous detectors are still not fully understood and studies on several detector aspects, like the micromesh geometry, have never been addressed systematically. The studies on signal formation in Micromegas, presented in the first part of this thesis, focuses on the microscopic signal electron loss mechanisms and the amplification processes in electron gas interaction. Based on a detailed model of detector parameter dependencies, these processes are scrutinized in an iterating comparison between experimental results, theory prediction of the macroscopic observables and process simulation on the microscopic level. Utilizing the specialized detectors developed in the scope of this thesis as well as refined simulation algorithms, an unprecedented level of accuracy in the description of the microscopic processes is reached, deepening the understanding of the fundamental process in gaseous detectors. The second part is dedicated to the challenges arising with the large scale Micromegas production for the ATLAS NSW. A selection of technological choices, partially influenced or determined by the herein presented studies, are discussed alongside a final report on two production related tasks addressing the detectors' core components: For the industrial production of resistive anode PCBs a detailed quality control (QC) and quality assurance (QA) scheme as well as the therefore required testing tools have been developed. In parallel the study on micromesh parameter optimization

Signal formation processes in Micromegas detectors and quality control for large size detector construction for the ATLAS new small wheel

International Nuclear Information System (INIS)

Kuger, Fabian

2017-01-01

The Micromegas technology is one of the most successful modern gaseous detector concepts and widely utilized in nuclear and particle physics experiments. Twenty years of R and D rendered the technology sufficiently mature to be selected as precision tracking detector for the New Small Wheel (NSW) upgrade of the ATLAS Muon spectrometer. This will be the first large scale application of Micromegas in one of the major LHC experiments. However, many of the fundamental microscopic processes in these gaseous detectors are still not fully understood and studies on several detector aspects, like the micromesh geometry, have never been addressed systematically. The studies on signal formation in Micromegas, presented in the first part of this thesis, focuses on the microscopic signal electron loss mechanisms and the amplification processes in electron gas interaction. Based on a detailed model of detector parameter dependencies, these processes are scrutinized in an iterating comparison between experimental results, theory prediction of the macroscopic observables and process simulation on the microscopic level. Utilizing the specialized detectors developed in the scope of this thesis as well as refined simulation algorithms, an unprecedented level of accuracy in the description of the microscopic processes is reached, deepening the understanding of the fundamental process in gaseous detectors. The second part is dedicated to the challenges arising with the large scale Micromegas production for the ATLAS NSW. A selection of technological choices, partially influenced or determined by the herein presented studies, are discussed alongside a final report on two production related tasks addressing the detectors' core components: For the industrial production of resistive anode PCBs a detailed quality control (QC) and quality assurance (QA) scheme as well as the therefore required testing tools have been developed. In parallel the study on micromesh parameter optimization

Digital signal processing for CdTe detectors using VXIbus data collection systems

Energy Technology Data Exchange (ETDEWEB)

Fukuda, Daiji; Takahashi, Hiroyuki; Kurahashi, Tomohiko; Iguchi, Tetsuo; Nakazawa, Masaharu

1996-07-01

Recently fast signal digitizing technique has been developed, and signal waveforms with very short time periods can be obtained. In this paper, we analyzed each measured pulse which was digitized by an apparatus of this kind, and tried to improve an energy resolution of a CdTe semiconductor detector. The result of the energy resolution for {sup 137}Cs 662 keV photopeak was 13 keV. Also, we developed a fast data collection system based on VXIbus standard, and the counting rate on this system was obtained about 50 counts per second. (author)

The BEAST II Experiment at Belle II. Characterization of the commissioning detector system for SuperKEKB

Energy Technology Data Exchange (ETDEWEB)

Ahlburg, Patrick; Eyring, Andreas; Filimonov, Viacheslav; Krueger, Hans; Mari, Laura; Marinas, Carlos; Pohl, David-Leon; Wermes, Norbert; Dingfelder, Jochen [University of Bonn (Germany)

2016-07-01

Before the upgraded vertex detector for the Belle II experiment at the SuperKEKB collider in Japan will be installed, a dedicated detector system for machine commissioning (BEAST II) will be employed. One of its main objectives is to measure and characterize the different background types in order to ensure a safe environment before the installation of the actual silicon detector systems close to the interaction point. FANGS, a detector system at BEAST II, based on ATLAS-IBL front-end electronics and planar silicon sensors is currently being developed for this purpose. The unique feature of this detector system is the high energy resolution achieved by using an external FPGA clock to sample the time-over-threshold signal, while keeping the excellent timing properties. The complete detector system is presented in this talk.

Radiation imaging with optically read out GEM-based detectors

Science.gov (United States)

Brunbauer, F. M.; Lupberger, M.; Oliveri, E.; Resnati, F.; Ropelewski, L.; Streli, C.; Thuiner, P.; van Stenis, M.

2018-02-01

Modern imaging sensors allow for high granularity optical readout of radiation detectors such as MicroPattern Gaseous Detectors (MPGDs). Taking advantage of the high signal amplification factors achievable by MPGD technologies such as Gaseous Electron Multipliers (GEMs), highly sensitive detectors can be realised and employing gas mixtures with strong scintillation yield in the visible wavelength regime, optical readout of such detectors can provide high-resolution event representations. Applications from X-ray imaging to fluoroscopy and tomography profit from the good spatial resolution of optical readout and the possibility to obtain images without the need for extensive reconstruction. Sensitivity to low-energy X-rays and energy resolution permit energy resolved imaging and material distinction in X-ray fluorescence measurements. Additionally, the low material budget of gaseous detectors and the possibility to couple scintillation light to imaging sensors via fibres or mirrors makes optically read out GEMs an ideal candidate for beam monitoring detectors in high energy physics as well as radiotherapy. We present applications and achievements of optically read out GEM-based detectors including high spatial resolution imaging and X-ray fluorescence measurements as an alternative readout approach for MPGDs. A detector concept for low intensity applications such as X-ray crystallography, which maximises detection efficiency with a thick conversion region but mitigates parallax-induced broadening is presented and beam monitoring capabilities of optical readout are explored. Augmenting high resolution 2D projections of particle tracks obtained with optical readout with timing information from fast photon detectors or transparent anodes for charge readout, 3D reconstruction of particle trajectories can be performed and permits the realisation of optically read out time projection chambers. Combining readily available high performance imaging sensors with compatible

Units of signals in the surface and underground scintillation detectors of the Yakutsk array

International Nuclear Information System (INIS)

Dedenko, L G; Fedorova, G F; Roganova, T M

2013-01-01

Signals in the surface and underground scintillation detectors from the extensive air shower particles at the Yakutsk array are measured in some practical units. These units are signals in detectors caused by the near vertical muons. These signals from the near vertical muons in the surface and underground detectors have been simulated with the help of the GEANT4 package. These simulations follow up the real experimental calibration of the surface and underground detectors carried out at the Yakutsk array. Results of simulations show the noticeable difference of ∼5% in energies deposited in these two types of detectors. This difference should be taken into account to interpret correctly data on the fraction of muons observed at the Yakutsk array and to make real conclusions about the composition of the primary cosmic radiation at ultra-high energies.

Persymmetric Adaptive Detectors of Subspace Signals in Homogeneous and Partially Homogeneous Clutter

Directory of Open Access Journals (Sweden)

Ding Hao

2015-08-01

Full Text Available In the field of adaptive radar detection, an effective strategy to improve the detection performance is to exploit the structural information of the covariance matrix, especially in the case of insufficient reference cells. Thus, in this study, the problem of detecting multidimensional subspace signals is discussed by considering the persymmetric structure of the clutter covariance matrix, which implies that the covariance matrix is persymmetric about its cross diagonal. Persymmetric adaptive detectors are derived on the basis of the one-step principle as well as the two-step Generalized Likelihood Ratio Test (GLRT in homogeneous and partially homogeneous clutter. The proposed detectors consider the structural information of the covariance matrix at the design stage. Simulation results suggest performance improvement compared with existing detectors when reference cells are insufficient. Moreover, the detection performance is assessed with respect to the effects of the covariance matrix, signal subspace dimension, and mismatched performance of signal subspace as well as signal fluctuations.

Evaluation of high performance data acquisition boards for simultaneous sampling of fast signals from PET detectors

International Nuclear Information System (INIS)

Judenhofer, Martin S; Pichler, Bernd J; Cherry, Simon R

2005-01-01

Detectors used for positron emission tomography (PET) provide fast, randomly distributed signals that need to be digitized for further processing. One possibility is to sample the signals at the peak initiated by a trigger from a constant fraction discriminator (CFD). For PET detectors, simultaneous acquisition of many channels is often important. To develop and evaluate novel PET detectors, a flexible, relatively low cost and high performance laboratory data acquisition (DAQ) system is therefore required. The use of dedicated DAQ systems, such as a multi-channel analysers (MCAs) or continuous sampling boards at high rates, is expensive. This work evaluates the suitability of well-priced peripheral component interconnect (PCI)-based 8-channel DAQ boards (PD2-MFS-8 2M/14 and PD2-MFS-8-500k/14, United Electronic Industries Inc., Canton, MA, USA) for signal acquisition from novel PET detectors. A software package was developed to access the board, measure basic board parameters, and to acquire, visualize, and analyse energy spectra and position profiles from block detectors. The performance tests showed that the boards input linearity is >99.2% and the standard deviation is 22 Na source was 14.9% (FWHM) at 511 keV and is slightly better than the result obtained with a high-end single channel MCA (8000A, Amptek, USA) using the same detector (16.8%). The crystals (1.2 x 1.2 x 12 mm 3 ) within a 9 x 9 LSO block detector could be clearly separated in an acquired position profile. Thus, these boards are well suited for data acquisition with novel detectors developed for nuclear imaging

Machine Learning Multi-Stage Classification and Regression in the Search for Vector-like Quarks and the Neyman Construction in Signal Searches

CERN Document Server

Leone, Robert Matthew

A search for vector-like quarks (VLQs) decaying to a Z boson using multi-stage machine learning was compared to a search using a standard square cuts search strategy. VLQs are predicted by several new theories beyond the Standard Model. The searches used 20.3 inverse femtobarns of proton-proton collisions at a center-of-mass energy of 8 TeV collected with the ATLAS detector in 2012 at the CERN Large Hadron Collider. CLs upper limits on production cross sections of vector-like top and bottom quarks were computed for VLQs produced singly or in pairs, Tsingle, Bsingle, Tpair, and Bpair. The two stage machine learning classification search strategy did not provide any improvement over the standard square cuts strategy, but for Tpair, Bpair, and Tsingle, a third stage of machine learning regression was able to lower the upper limits of high signal masses by as much as 50%. Additionally, new test statistics were developed for use in the Neyman construction of confidence regions in order to address deficiencies in c...

Optoelectronic~Analogue~Signal~Transfer~for~LHC~Detectors

CERN Multimedia

Stefanini, G; Reinhart, F K; Batten, J C

2002-01-01

% RD23 \\\\ \\\\ \\\\ \\\\The main goal of the RD23 project is to develop optical fiber links for volume application in the analog signal transfer of tracking detectors at LHC. Key requirements were radiation hardness, low power dissipation and affordable cost. The technique proposed initially was based on external modulation, and the project was targeted at the development of electro-optic intensity modulators as transmitters. In 1996, this approach was abandoned in favor of a system based on directly modulated semiconductor laser transmitters. This configuration was subsequently adopted as baseline choice by the CMS experiment for its tracker readout system. \\\\ \\\\In view of qualifying the radiation hardness of all optical link components to be installed at LHC front-ends, extensive validation tests took place in 1997 and 1998. Irradiations of lasers, pin-diodes, optical fibers and connectors were carried out with neutrons ($\\sim$6MeV) and $^{60}$Co gamma rays. In addition, lasers and pin-diodes in die as well as pa...

A Support Vector Machine-Based Gender Identification Using Speech Signal

Science.gov (United States)

Lee, Kye-Hwan; Kang, Sang-Ick; Kim, Deok-Hwan; Chang, Joon-Hyuk

We propose an effective voice-based gender identification method using a support vector machine (SVM). The SVM is a binary classification algorithm that classifies two groups by finding the voluntary nonlinear boundary in a feature space and is known to yield high classification performance. In the present work, we compare the identification performance of the SVM with that of a Gaussian mixture model (GMM)-based method using the mel frequency cepstral coefficients (MFCC). A novel approach of incorporating a features fusion scheme based on a combination of the MFCC and the fundamental frequency is proposed with the aim of improving the performance of gender identification. Experimental results demonstrate that the gender identification performance using the SVM is significantly better than that of the GMM-based scheme. Moreover, the performance is substantially improved when the proposed features fusion technique is applied.

Signal generation in highly irradiated silicon microstrip detectors for the ATLAS experiment

International Nuclear Information System (INIS)

Ruggiero, Gennaro

2003-01-01

Silicon detectors are the most diffused tracking devices in High Energy Physics (HEP). The reason of such success can be found in the characteristics of the material together with the existing advanced technology for the fabrication of these devices. Nevertheless in many modem HEP experiments the observation of vary rare events require data taking at high luminosity with a consequent extremely intense hadron radiation field that damages the silicon and degrades the performance of these devices. In this thesis work a detailed study of the signal generation in microstrip detectors has been produced with a special care for the ATLAS semiconductor tracker geometry. This has required a development of an appropriate setup to perform measurements with Transient Current/ Charge Technique. This has allowed studying the evolution of the signal in several microstrips detector samples irradiated at fluences covering the range expected in the ATLAS Semiconductor Tracker. For a better understanding of these measurements a powerful software package that simulates the signal generation in these devices has been developed. Moreover in this thesis it has been also shown that the degradation due to radiation in silicon detectors can be strongly reduced if the data taking is done with detectors operated at 130 K. This makes low temperature operation that benefits of the recovery of the charge collection efficiency in highly irradiated silicon detectors (also known as Lazarus effect) an optimal option for future high luminosity experiments. (author)

Electric fields, weighting fields, signals and charge diffusion in detectors including resistive materials

International Nuclear Information System (INIS)

Riegler, W.

2016-01-01

In this report we discuss static and time dependent electric fields in detector geometries with an arbitrary number of parallel layers of a given permittivity and weak conductivity. We derive the Green's functions i.e. the field of a point charge, as well as the weighting fields for readout pads and readout strips in these geometries. The effect of 'bulk' resistivity on electric fields and signals is investigated. The spreading of charge on thin resistive layers is also discussed in detail, and the conditions for allowing the effect to be described by the diffusion equation is discussed. We apply the results to derive fields and induced signals in Resistive Plate Chambers, MICROMEGAS detectors including resistive layers for charge spreading and discharge protection as well as detectors using resistive charge division readout like the MicroCAT detector. We also discuss in detail how resistive layers affect signal shapes and increase crosstalk between readout electrodes.

Electric fields, weighting fields, signals and charge diffusion in detectors including resistive materials

CERN Document Server

Riegler, Werner

2016-11-07

In this report we discuss static and time dependent electric fields in detector geometries with an arbitrary number of parallel layers of a given permittivity and weak conductivity. We derive the Green's functions i.e. the field of a point charge, as well as the weighting fields for readout pads and readout strips in these geometries. The effect of 'bulk' resistivity on electric fields and signals is investigated. The spreading of charge on thin resistive layers is also discussed in detail, and the conditions for allowing the effect to be described by the diffusion equation is discussed. We apply the results to derive fields and induced signals in Resistive Plate Chambers, Micromega detectors including resistive layers for charge spreading and discharge protection as well as detectors using resistive charge division readout like the MicroCAT detector. We also discuss in detail how resistive layers affect signal shapes and increase crosstalk between readout electrodes.

EMD-Based Symbolic Dynamic Analysis for the Recognition of Human and Nonhuman Pyroelectric Infrared Signals.

Science.gov (United States)

Zhao, Jiaduo; Gong, Weiguo; Tang, Yuzhen; Li, Weihong

2016-01-20

In this paper, we propose an effective human and nonhuman pyroelectric infrared (PIR) signal recognition method to reduce PIR detector false alarms. First, using the mathematical model of the PIR detector, we analyze the physical characteristics of the human and nonhuman PIR signals; second, based on the analysis results, we propose an empirical mode decomposition (EMD)-based symbolic dynamic analysis method for the recognition of human and nonhuman PIR signals. In the proposed method, first, we extract the detailed features of a PIR signal into five symbol sequences using an EMD-based symbolization method, then, we generate five feature descriptors for each PIR signal through constructing five probabilistic finite state automata with the symbol sequences. Finally, we use a weighted voting classification strategy to classify the PIR signals with their feature descriptors. Comparative experiments show that the proposed method can effectively classify the human and nonhuman PIR signals and reduce PIR detector's false alarms.

Machine listening intelligence

Science.gov (United States)

Cella, C. E.

2017-05-01

This manifesto paper will introduce machine listening intelligence, an integrated research framework for acoustic and musical signals modelling, based on signal processing, deep learning and computational musicology.

Detector Control System for the ATLAS Forward Proton detector

CERN Document Server

Czekierda, Sabina; The ATLAS collaboration

2017-01-01

The ATLAS Forward Proton (AFP) is a forward detector using a Roman Pot technique, recently installed in the LHC tunnel. It is aiming at registering protons that were diffractively or electromagnetically scattered in soft and hard processes. Infrastructure of the detector consists of hardware placed both in the tunnel and in the control room USA15 (about 330 meters from the Roman Pots). AFP detector, like the other detectors of the ATLAS experiment, uses the Detector Control System (DCS) to supervise the detector and to ensure its safe and coherent operation, since the incorrect detector performance may influence the physics results. The DCS continuously monitors the detector parameters, subset of which is stored in data bases. Crucial parameters are guarded by alarm system. A detector representation as a hierarchical tree-like structure of well-defined subsystems built with the use of the Finite State Machine (FSM) toolkit allows for overall detector operation and visualization. Every node in the hierarchy is...

Optimal Signal Quality Index for Photoplethysmogram Signals

Directory of Open Access Journals (Sweden)

Mohamed Elgendi

2016-09-01

Full Text Available A photoplethysmogram (PPG is a noninvasive circulatory signal related to the pulsatile volume of blood in tissue and is typically collected by pulse oximeters. PPG signals collected via mobile devices are prone to artifacts that negatively impact measurement accuracy, which can lead to a significant number of misleading diagnoses. Given the rapidly increased use of mobile devices to collect PPG signals, developing an optimal signal quality index (SQI is essential to classify the signal quality from these devices. Eight SQIs were developed and tested based on: perfusion, kurtosis, skewness, relative power, non-stationarity, zero crossing, entropy, and the matching of systolic wave detectors. Two independent annotators annotated all PPG data (106 recordings, 60 s each and a third expert conducted the adjudication of differences. The independent annotators labeled each PPG signal with one of the following labels: excellent, acceptable or unfit for diagnosis. All indices were compared using Mahalanobis distance, linear discriminant analysis, quadratic discriminant analysis, and support vector machine with leave-one-out cross-validation. The skewness index outperformed the other seven indices in differentiating between excellent PPG and acceptable, acceptable combined with unfit, and unfit recordings, with overall F 1 scores of 86.0%, 87.2%, and 79.1%, respectively.

Optimal Signal Quality Index for Photoplethysmogram Signals.

Science.gov (United States)

Elgendi, Mohamed

2016-09-22

A photoplethysmogram (PPG) is a noninvasive circulatory signal related to the pulsatile volume of blood in tissue and is typically collected by pulse oximeters. PPG signals collected via mobile devices are prone to artifacts that negatively impact measurement accuracy, which can lead to a significant number of misleading diagnoses. Given the rapidly increased use of mobile devices to collect PPG signals, developing an optimal signal quality index (SQI) is essential to classify the signal quality from these devices. Eight SQIs were developed and tested based on: perfusion, kurtosis, skewness, relative power, non-stationarity, zero crossing, entropy, and the matching of systolic wave detectors. Two independent annotators annotated all PPG data (106 recordings, 60 s each) and a third expert conducted the adjudication of differences. The independent annotators labeled each PPG signal with one of the following labels: excellent, acceptable or unfit for diagnosis. All indices were compared using Mahalanobis distance, linear discriminant analysis, quadratic discriminant analysis, and support vector machine with leave-one-out cross-validation. The skewness index outperformed the other seven indices in differentiating between excellent PPG and acceptable, acceptable combined with unfit, and unfit recordings, with overall F 1 scores of 86.0%, 87.2%, and 79.1%, respectively.

Classifying BCI signals from novice users with extreme learning machine

Directory of Open Access Journals (Sweden)

Rodríguez-Bermúdez Germán

2017-07-01

Full Text Available Brain computer interface (BCI allows to control external devices only with the electrical activity of the brain. In order to improve the system, several approaches have been proposed. However it is usual to test algorithms with standard BCI signals from experts users or from repositories available on Internet. In this work, extreme learning machine (ELM has been tested with signals from 5 novel users to compare with standard classification algorithms. Experimental results show that ELM is a suitable method to classify electroencephalogram signals from novice users.

Twin target self-amplification-based DNA machine for highly sensitive detection of cancer-related gene.

Science.gov (United States)

Xu, Huo; Jiang, Yifan; Liu, Dengyou; Liu, Kai; Zhang, Yafeng; Yu, Suhong; Shen, Zhifa; Wu, Zai-Sheng

2018-06-29

The sensitive detection of cancer-related genes is of great significance for early diagnosis and treatment of human cancers, and previous isothermal amplification sensing systems were often based on the reuse of target DNA, the amplification of enzymatic products and the accumulation of reporting probes. However, no reporting probes are able to be transformed into target species and in turn initiate the signal of other probes. Herein we reported a simple, isothermal and highly sensitive homogeneous assay system for tumor suppressor p53 gene detection based on a new autonomous DNA machine, where the signaling probe, molecular beacon (MB), was able to execute the function similar to target DNA besides providing the common signal. In the presence of target p53 gene, the operation of DNA machine can be initiated, and cyclical nucleic acid strand-displacement polymerization (CNDP) and nicking/polymerization cyclical amplification (NPCA) occur, during which the MB was opened by target species and cleaved by restriction endonuclease. In turn, the cleaved fragments could activate the next signaling process as target DNA did. According to the functional similarity, the cleaved fragment was called twin target, and the corresponding fashion to amplify the signal was named twin target self-amplification. Utilizing this newly-proposed DNA machine, the target DNA could be detected down to 0.1 pM with a wide dynamic range (6 orders of magnitude) and single-base mismatched targets were discriminated, indicating a very high assay sensitivity and good specificity. In addition, the DNA machine was not only used to screen the p53 gene in complex biological matrix but also was capable of practically detecting genomic DNA p53 extracted from A549 cell line. This indicates that the proposed DNA machine holds the potential application in biomedical research and early clinical diagnosis. Copyright © 2018 Elsevier B.V. All rights reserved.

DNA-based machines.

Science.gov (United States)

Wang, Fuan; Willner, Bilha; Willner, Itamar

2014-01-01

The base sequence in nucleic acids encodes substantial structural and functional information into the biopolymer. This encoded information provides the basis for the tailoring and assembly of DNA machines. A DNA machine is defined as a molecular device that exhibits the following fundamental features. (1) It performs a fuel-driven mechanical process that mimics macroscopic machines. (2) The mechanical process requires an energy input, "fuel." (3) The mechanical operation is accompanied by an energy consumption process that leads to "waste products." (4) The cyclic operation of the DNA devices, involves the use of "fuel" and "anti-fuel" ingredients. A variety of DNA-based machines are described, including the construction of "tweezers," "walkers," "robots," "cranes," "transporters," "springs," "gears," and interlocked cyclic DNA structures acting as reconfigurable catenanes, rotaxanes, and rotors. Different "fuels", such as nucleic acid strands, pH (H⁺/OH⁻), metal ions, and light, are used to trigger the mechanical functions of the DNA devices. The operation of the devices in solution and on surfaces is described, and a variety of optical, electrical, and photoelectrochemical methods to follow the operations of the DNA machines are presented. We further address the possible applications of DNA machines and the future perspectives of molecular DNA devices. These include the application of DNA machines as functional structures for the construction of logic gates and computing, for the programmed organization of metallic nanoparticle structures and the control of plasmonic properties, and for controlling chemical transformations by DNA machines. We further discuss the future applications of DNA machines for intracellular sensing, controlling intracellular metabolic pathways, and the use of the functional nanostructures for drug delivery and medical applications.

Effect of uncompensated SPN detector cables on neutron noise signals measured in VVER-440 reactors

Energy Technology Data Exchange (ETDEWEB)

Kiss, S. E-mail: kisss@sunserv.kfki.hu; Lipcsei, S. E-mail: lipcsei@sunserv.kfki.hu; Hazi, G. E-mail: gah@sunserv.kfki.hu

2003-03-01

The Self Powered Neutron Detector (SPND) noise measurements of an operating VVER-440 nuclear reactor are described and characterised. Signal characteristics may be radically influenced by the geometrical properties of the detector and the cable, and by the measuring arrangement. Simulator is used as a means of studying the structure of those phase spectra that show propagating perturbations measured on uncompensated SPN detectors. The paper presents measurements with detectors of very different sizes (i.e. 20 cm length SPNDs and the 200 cm length compensation cables), where the ratios of the global and local component differ significantly for the different detector sizes. This phenomenon is used up for signal compensation.

Real-Time Accumulative Computation Motion Detectors

Directory of Open Access Journals (Sweden)

Saturnino Maldonado-Bascón

2009-12-01

Full Text Available The neurally inspired accumulative computation (AC method and its application to motion detection have been introduced in the past years. This paper revisits the fact that many researchers have explored the relationship between neural networks and finite state machines. Indeed, finite state machines constitute the best characterized computational model, whereas artificial neural networks have become a very successful tool for modeling and problem solving. The article shows how to reach real-time performance after using a model described as a finite state machine. This paper introduces two steps towards that direction: (a A simplification of the general AC method is performed by formally transforming it into a finite state machine. (b A hardware implementation in FPGA of such a designed AC module, as well as an 8-AC motion detector, providing promising performance results. We also offer two case studies of the use of AC motion detectors in surveillance applications, namely infrared-based people segmentation and color-based people tracking, respectively.

Joint preprocesser-based detector for cooperative networks with limited hardware processing capability

KAUST Repository

Abuzaid, Abdulrahman I.

2015-02-01

In this letter, a joint detector for cooperative communication networks is proposed when the destination has limited hardware processing capability. The transmitter sends its symbols with the help of L relays. As the destination has limited hardware, only U out of L signals are processed and the energy of the remaining relays is lost. To solve this problem, a joint preprocessing based detector is proposed. This joint preprocessor based detector operate on the principles of minimizing the symbol error rate (SER). For a realistic assessment, pilot symbol aided channel estimation is incorporated for this proposed detector. From our simulations, it can be observed that our proposed detector achieves the same SER performance as that of the maximum likelihood (ML) detector with all participating relays. Additionally, our detector outperforms selection combining (SC), channel shortening (CS) scheme and reduced-rank techniques when using the same U. Our proposed scheme has low computational complexity.

Time resolution improvement of Schottky CdTe PET detectors using digital signal processing

International Nuclear Information System (INIS)

Nakhostin, M.; Ishii, K.; Kikuchi, Y.; Matsuyama, S.; Yamazaki, H.; Torshabi, A. Esmaili

2009-01-01

We present the results of our study on the timing performance of Schottky CdTe PET detectors using the technique of digital signal processing. The coincidence signals between a CdTe detector (15x15x1 mm 3 ) and a fast liquid scintillator detector were digitized by a fast digital oscilloscope and analyzed. In the analysis, digital versions of the elements of timing circuits, including pulse shaper and time discriminator, were created and a digital implementation of the Amplitude and Rise-time Compensation (ARC) mode of timing was performed. Owing to a very fine adjustment of the parameters of timing measurement, a good time resolution of less than 9.9 ns (FWHM) at an energy threshold of 150 keV was achieved. In the next step, a new method of time pickoff for improvement of timing resolution without loss in the detection efficiency of CdTe detectors was examined. In the method, signals from a CdTe detector are grouped by their rise-times and different procedures of time pickoff are applied to the signals of each group. Then, the time pickoffs are synchronized by compensating the fixed time offset, caused by the different time pickoff procedures. This method leads to an improved time resolution of ∼7.2 ns (FWHM) at an energy threshold of as low as 150 keV. The methods presented in this work are computationally fast enough to be used for online processing of data in an actual PET system.

CVD diamond based soft X-ray detector with fast response

International Nuclear Information System (INIS)

Li Fang; Hou Lifei; Su Chunxiao; Yang Guohong; Liu Shenye

2010-01-01

A soft X-ray detector has been made with high quality chemical vapor deposited (CVD) diamond and the electrical structure of micro-strip. Through the measurement of response time on a laser with the pulse width of 10 ps, the full width at half maximum of the data got in the oscilloscope was 115 ps. The rise time of the CVD diamond detector was calculated to be 49 ps. In the experiment on the laser prototype facility, the signal got by the CVD diamond detector was compared with that got by a soft X-ray spectrometer. Both signals coincided well. The detector is proved to be a kind of reliable soft X-ray detector with fast response and high signal-to-noise ratio. (authors)

Physics and Detectors at CLIC

CERN Multimedia

CERN. Geneva

2012-01-01

CLIC represents an attractive option for the future particle physics programme at the energy frontier. CLIC is a proposed electron-positron linear collider, based on a novel two beam accelerating structure, with the capability of operating at centre-of-mass energies of up to 3 TeV. The Physics and Detector volume of the CLIC conceptual design report was recently published as a CERN yellow report. In this seminar, I will review the conclusions of this report, focussing on four main areas. Firstly, I will give an overview of the physics potential at CLIC, and will place this in the context of a possible scenario for the staged construction of the machine. Secondly, I will discuss the challenges for a detector operating in the CLIC machine environment. I will then present detailed studies of possible detector concepts, based on high granularity particle flow calorimetry, which demonstrate that the required detector performance goals at CLIC can be met. Finally, I will highlight the main issues for the future R&a...

Noninvasive extraction of fetal electrocardiogram based on Support Vector Machine

Science.gov (United States)

Fu, Yumei; Xiang, Shihan; Chen, Tianyi; Zhou, Ping; Huang, Weiyan

2015-10-01

The fetal electrocardiogram (FECG) signal has important clinical value for diagnosing the fetal heart diseases and choosing suitable therapeutics schemes to doctors. So, the noninvasive extraction of FECG from electrocardiogram (ECG) signals becomes a hot research point. A new method, the Support Vector Machine (SVM) is utilized for the extraction of FECG with limited size of data. Firstly, the theory of the SVM and the principle of the extraction based on the SVM are studied. Secondly, the transformation of maternal electrocardiogram (MECG) component in abdominal composite signal is verified to be nonlinear and fitted with the SVM. Then, the SVM is trained, and the training results are compared with the real data to ensure the effect of the training. Meanwhile, the parameters of the SVM are optimized to achieve the best performance so that the learning machine can be utilized to fit the unknown samples. Finally, the FECG is extracted by removing the optimal estimation of MECG component from the abdominal composite signal. In order to evaluate the performance of FECG extraction based on the SVM, the Signal-to-Noise Ratio (SNR) and the visual test are used. The experimental results show that the FECG with good quality can be extracted, its SNR ratio is significantly increased as high as 9.2349 dB and the time cost is significantly decreased as short as 0.802 seconds. Compared with the traditional method, the noninvasive extraction method based on the SVM has a simple realization, the shorter treatment time and the better extraction quality under the same conditions.

An assesment of the characteristics of the GM detectors and iodine remote detectors of the Paks environmental monitoring system based on the data measured from 1982 to 1985

International Nuclear Information System (INIS)

Nagy, Gy.; Lang, Edit; Deme, S.; Feher, I.

1986-03-01

Measurements performed at the GM detectors and iodine remote detectors of the continuous environmental monitoring system of the Paks NPP can be used for estimating the effect of atmospheric releases. Based on the investigations carried out from Sep. 1982 to July 1985, a good correlation between the signals and the background radioactivity levels could be established. It was further stated that radon fallout during raining was responsible for significant signal changes of both types of detectors. (V.N.)

Relevancies of multiple-interaction events and signal-to-noise ratio for Anger-logic based PET detector designs

Science.gov (United States)

Peng, Hao

2015-10-01

A fundamental challenge for PET block detector designs is to deploy finer crystal elements while limiting the number of readout channels. The standard Anger-logic scheme including light sharing (an 8 by 8 crystal array coupled to a 2×2 photodetector array with an optical diffuser, multiplexing ratio: 16:1) has been widely used to address such a challenge. Our work proposes a generalized model to study the impacts of two critical parameters on spatial resolution performance of a PET block detector: multiple interaction events and signal-to-noise ratio (SNR). The study consists of the following three parts: (1) studying light output profile and multiple interactions of 511 keV photons within crystal arrays of different crystal widths (from 4 mm down to 1 mm, constant height: 20 mm); (2) applying the Anger-logic positioning algorithm to investigate positioning/decoding uncertainties (i.e., "block effect") in terms of peak-to-valley ratio (PVR), with light sharing, multiple interactions and photodetector SNR taken into account; and (3) studying the dependency of spatial resolution on SNR in the context of modulation transfer function (MTF). The proposed model can be used to guide the development and evaluation of a standard Anger-logic based PET block detector including: (1) selecting/optimizing the configuration of crystal elements for a given photodetector SNR; and (2) predicting to what extent additional electronic multiplexing may be implemented to further reduce the number of readout channels.

Fault Severity Estimation of Rotating Machinery Based on Residual Signals

Directory of Open Access Journals (Sweden)

Fan Jiang

2012-01-01

Full Text Available Fault severity estimation is an important part of a condition-based maintenance system, which can monitor the performance of an operation machine and enhance its level of safety. In this paper, a novel method based on statistical property and residual signals is developed for estimating the fault severity of rotating machinery. The fast Fourier transformation (FFT is applied to extract the so-called multifrequency-band energy (MFBE from the vibration signals of rotating machinery with different fault severity levels in the first stage. Usually these features of the working conditions with different fault sensitivities are different. Therefore a sensitive features-selecting algorithm is defined to construct the feature matrix and calculate the statistic parameter (mean in the second stage. In the last stage, the residual signals computed by the zero space vector are used to estimate the fault severity. Simulation and experimental results reveal that the proposed method based on statistics and residual signals is effective and feasible for estimating the severity of a rotating machine fault.

Effect of SiO$_{2}$ passivating layer in segmented silicon planar detectors on the detector response

CERN Document Server

Verbitskaya, Elena; Eremin, Vladimir; Golubkov, S; Konkov, K; Roe, Shaun; Ruggiero, G; Sidorov, A; Weilhammer, Peter

2004-01-01

Silicon detectors with a fine segmentation (micropixel and microstrip) are the main type of detectors used in the inner trackers of LHC experiments. Due to the high luminosity of the LHC machines they are required to have a fast response to fit the short shaping time of 25 ns and to be radiation hard. Evaluation of silicon microstrip detectors developed for the ATLAS silicon tracker and carried out under collaboration of CERN and PTI has shown the reversal of the pulse polarity in the detector response to short- range radiation. Since the negative signal is of about 30% of the normal positive one, the effect strongly reduces the charge collection efficiency in irradiated detectors. The investigation presents the consideration on the origin of a negative response in Si microstrip detectors and the experimental proof of the model. The study of the effect has been carried out using "baby" strip detectors with a special design: each strip has a window in a metallization, which covers the p/sup +/ implant. The sca...

A Computer- Based Digital Signal Processing for Nuclear Scintillator Detectors

International Nuclear Information System (INIS)

Ashour, M.A.; Abo Shosha, A.M.

2000-01-01

In this paper, a Digital Signal Processing (DSP) Computer-based system for the nuclear scintillation signals with exponential decay is presented. The main objective of this work is to identify the characteristics of the acquired signals smoothly, this can be done by transferring the signal environment from random signal domain to deterministic domain using digital manipulation techniques. The proposed system consists of two major parts. The first part is the high performance data acquisition system (DAQ) that depends on a multi-channel Logic Scope. Which is interfaced with the host computer through the General Purpose Interface Board (GPIB) Ver. IEEE 488.2. Also, a Graphical User Interface (GUI) has been designed for this purpose using the graphical programming facilities. The second of the system is the DSP software Algorithm which analyses, demonstrates, monitoring these data to obtain the main characteristics of the acquired signals; the amplitude, the pulse count, the pulse width, decay factor, and the arrival time

Origin of a signal detected with the LSD detector after the accident at the chernobyl nuclear power plant

Energy Technology Data Exchange (ETDEWEB)

Agafonova, N. Yu., E-mail: natagafonova@gmail.com; Malgin, A. S., E-mail: malgin@lngs.infn.it [Russian Academy of Sciences, Institute for Nuclear Research (Russian Federation); Fulgione, W. [Istituto Nazionale di Fisica Nucleare, and Osservatorio Astrofisico di Torino, Istituto di Fisica dello Spazio Interplanetario (Italy)

2013-08-15

A rare signal was detected at 23:53 Moscow time on April 27, 1986 with the LSD low-background scintillation detector located under Mont Blanc at a distance of 1820 km from Chernobyl. To reveal the origin of this signal, we discuss the results obtained with other instruments operating within a similar program, as well as analyze the characteristics of the pulses of the signal and facts referring to the explosion of the Chernobyl reactor. A hypothesis based on detection with the LSD of gamma-quanta from {beta} decays of {sup 135}I nuclei ejected into atmosphere by the reactor explosion and carried in the underground detector camera with air of positive ventilation is considered. The explosion origin of the LSD signal indicates a new technogenic source of the background in the search for neutrino bursts from cores of collapsing stars.

Demonstration and comparison of tuned and detuned signal recycling in a large-scale gravitational wave detector

International Nuclear Information System (INIS)

Hild, S; Grote, H; Hewtison, M; Lueck, H; Smith, J R; Strain, K A; Willke, B; Danzmann, K

2007-01-01

The British/German gravitational wave detector GEO 600 located near Hannover in Germany is the first large-scale gravitational-wave detector using the advanced technique of signal recycling. Currently the instrument operates in detuned signal recycling mode. Several problems arise due to the fact that the signal recycling cavity changes amplitude and phase of all light fields (carrier and sidebands) present at the dark-port. In addition, in the case of detuned signal recycling this leads to unbalanced sideband fields at the detector output. The large amplitude modulation caused by this asymmetry does not carry any gravitational wave information, but might be the cause of saturation and nonlinearities on the main photodiode. We developed and demonstrated a new control method to realize tuned signal recycling operation in a large-scale gravitational wave detector. A detailed comparison of tuned and detuned signal recycling operation is given. The response function of the system (optical gain) was measured and compared, as was the size of amplitude modulation on the main photodiode. Some important noise couplings were measured and partly found to be strongly reduced in the case of tuned signal recycling operation

Electronic readout for THGEM detectors based on FPGA TDCs

Energy Technology Data Exchange (ETDEWEB)

Baumann, Tobias; Buechele, Maximilian; Fischer, Horst; Gorzellik, Matthias; Grussenmeyer, Tobias; Herrmann, Florian; Joerg, Philipp; Koenigsmann, Kay; Kremser, Paul; Kunz, Tobias; Michalski, Christoph; Schopferer, Sebastian; Szameitat, Tobias [Physikalisches Institut, Freiburg Univ. (Germany); Collaboration: COMPASS-II RICH upgrade Group

2013-07-01

In the framework of the RD51 programme the characteristics of a new detector design, called THGEM, which is based on multi-layer arrangements of printed circuit board material, is investigated. The THGEMs combine the advantages for covering gains up to 10{sup 6} in electron multiplication at large detector areas and low material budget. Studies are performed by extending the design to a hybrid gas detector by adding a Micromega layer, which significantly improves the ion back flow ratio of the chamber. With the upgrade of the COMPASS experiment at CERN a MWPC plane of the RICH-1 detector will be replaced by installing THGEM chambers. This summarizes to 40k channels of electronic readout, including amplification, discrimination and time-to-digital conversion of the anode signals. Due to the expected hit rate of the detector we design a cost-efficient TDC, based on Artix7 FPGA technology, with time resolution below 100 ps and sufficient hit buffer depth. To cover the large readout area the data is transferred via optical fibres to a central readout system which is part of the GANDALF framework.

An SVM-Based Classifier for Estimating the State of Various Rotating Components in Agro-Industrial Machinery with a Vibration Signal Acquired from a Single Point on the Machine Chassis

Directory of Open Access Journals (Sweden)

Ruben Ruiz-Gonzalez

2014-11-01

Full Text Available The goal of this article is to assess the feasibility of estimating the state of various rotating components in agro-industrial machinery by employing just one vibration signal acquired from a single point on the machine chassis. To do so, a Support Vector Machine (SVM-based system is employed. Experimental tests evaluated this system by acquiring vibration data from a single point of an agricultural harvester, while varying several of its working conditions. The whole process included two major steps. Initially, the vibration data were preprocessed through twelve feature extraction algorithms, after which the Exhaustive Search method selected the most suitable features. Secondly, the SVM-based system accuracy was evaluated by using Leave-One-Out cross-validation, with the selected features as the input data. The results of this study provide evidence that (i accurate estimation of the status of various rotating components in agro-industrial machinery is possible by processing the vibration signal acquired from a single point on the machine structure; (ii the vibration signal can be acquired with a uniaxial accelerometer, the orientation of which does not significantly affect the classification accuracy; and, (iii when using an SVM classifier, an 85% mean cross-validation accuracy can be reached, which only requires a maximum of seven features as its input, and no significant improvements are noted between the use of either nonlinear or linear kernels.

Machine learning based global particle indentification algorithms at LHCb experiment

CERN Multimedia

Derkach, Denis; Likhomanenko, Tatiana; Rogozhnikov, Aleksei; Ratnikov, Fedor

2017-01-01

One of the most important aspects of data processing at LHC experiments is the particle identification (PID) algorithm. In LHCb, several different sub-detector systems provide PID information: the Ring Imaging CHerenkov (RICH) detector, the hadronic and electromagnetic calorimeters, and the muon chambers. To improve charged particle identification, several neural networks including a deep architecture and gradient boosting have been applied to data. These new approaches provide higher identification efficiencies than existing implementations for all charged particle types. It is also necessary to achieve a flat dependency between efficiencies and spectator variables such as particle momentum, in order to reduce systematic uncertainties during later stages of data analysis. For this purpose, "flat” algorithms that guarantee the flatness property for efficiencies have also been developed. This talk presents this new approach based on machine learning and its performance.

Process signal selection method to improve the impact mitigation of sensor broken for diagnosis using machine learning

International Nuclear Information System (INIS)

Minowa, Hirotsugu; Gofuku, Akio

2014-01-01

Accidents of industrial plants cause large loss on human, economic, social credibility. In recent, studies of diagnostic methods using techniques of machine learning are expected to detect early and correctly abnormality occurred in a plant. However, the general diagnostic machines are generated generally to require all process signals (hereafter, signals) for plant diagnosis. Thus if trouble occurs such as process sensor is broken, the diagnostic machine cannot diagnose or may decrease diagnostic performance. Therefore, we propose an important process signal selection method to improve impact mitigation without reducing the diagnostic performance by reducing the adverse effect of noises on multi-agent diagnostic system. The advantage of our method is the general-purpose property that allows to be applied to various supervised machine learning and to set the various parameters to decide termination of search. The experiment evaluation revealed that diagnostic machines generated by our method using SVM improved the impact mitigation and did not reduce performance about the diagnostic accuracy, the velocity of diagnosis, predictions of plant state near accident occurrence, in comparison with the basic diagnostic machine which diagnoses by using all signals. This paper reports our proposed method and the results evaluated which our method was applied to the simulated abnormal of the fast-breeder reactor Monju. (author)

LUCID A Cherenkov Tube Based Detector for Monitoring the ATLAS Experiment Luminosity

CERN Document Server

Sbrizzi, A

2007-01-01

The LUCID (LUminosity Cherenkov Integrating Detector) apparatus is composed by two symmetric arms deployed at about 17 m from the ATLAS interaction point. The purpose of this detector, which will be installed in january 2008, is to monitor the luminosity delivered by the LHC machine to the ATLAS experiment. An absolute luminosity calibration is needed and it will be provided by a Roman Pot type detector with the two arms placed at about 240 m from the interaction point. Each arm of the LUCID detector is based on an aluminum vessel containing 20 Cherenkov tubes, 15 mm diameter and 1500 mm length, filled with C4F10 radiator gas at 1.5 bar. The Cherenkov light generated by charged particles above the threshold is collected by photomultiplier tubes (PMT) directly placed at the tubes end. The challenging aspect of this detector is its readout in an environment characterized by the high dose of radiation (about 0.7 Mrad/year at 10^33cm^2 s^-1) it must withstand. In order to fulfill these radiation hardness requirem...

refining of scintillation detector signals relying on interpolated wavelets on a FPGA prototype

International Nuclear Information System (INIS)

Aboshosha, A.; Sayed, M.; Ashour, M.; Safwat, A.

2010-01-01

in this article, a signal processing core based on field programmable gate arrays (FPGAs) is developed for processing of scintillation detector signals. this core is implemented to apply the forward wavelet transfrom and interpolation technique. the main purpose of that is to de-noise, compress and reconstruct these signals by which the processing speed and storage will be optimized. moreover, this technique gives us all important features of the acquired signals such as counting, shaping and pulse height. A new contribution of our framework arises from employing the interpolation techniques to reconstruct the signal where the mother wavelet and details are not required. The hardware design is implemented using hardware description language (HDL) and is implemented practically on the FPGA. The performance of the design has been tested in simulation mode on Model sim benchmark and in real time mode on XC2S 50 spartan- II FPGA.

A Framework for Diagnosing the Out-of-Control Signals in Multivariate Process Using Optimized Support Vector Machines

Directory of Open Access Journals (Sweden)

Tai-fu Li

2013-01-01

Full Text Available Multivariate statistical process control is the continuation and development of unitary statistical process control. Most multivariate statistical quality control charts are usually used (in manufacturing and service industries to determine whether a process is performing as intended or if there are some unnatural causes of variation upon an overall statistics. Once the control chart detects out-of-control signals, one difficulty encountered with multivariate control charts is the interpretation of an out-of-control signal. That is, we have to determine whether one or more or a combination of variables is responsible for the abnormal signal. A novel approach for diagnosing the out-of-control signals in the multivariate process is described in this paper. The proposed methodology uses the optimized support vector machines (support vector machine classification based on genetic algorithm to recognize set of subclasses of multivariate abnormal patters, identify the responsible variable(s on the occurrence of abnormal pattern. Multiple sets of experiments are used to verify this model. The performance of the proposed approach demonstrates that this model can accurately classify the source(s of out-of-control signal and even outperforms the conventional multivariate control scheme.

Fabrication of Gamma Detectors Based on Magnetic Ag:Er Microcalorimeters

Energy Technology Data Exchange (ETDEWEB)

Friedrich, Stephan [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Boyd, Stephen [Univ. of New Mexico, Albuquerque, NM (United States); Cantor, Robin [STAR Cryoelectronics, Santa Fe, NM (United States)

2015-11-25

This report discusses the photolithographic fabrication of ultra-high resolution gamma-ray detectors based on magnetic microcalorimeters (MMCs). The MMC uses a novel Er-doped silver sensor (Ag:Er) that is expected to have higher sensitivity than the Er-doped gold (Au:Er) sensors currently in use. The MMC also integrates the first-stage SQUID preamplifier on the same chip as the MMC gamma detector to increase its signal-to-noise ratio. In addition, the MMC uses a passive Ta-Nb heat switch to replace one of the common long-term failure points in earlier detectors. This report discusses the fabrication process we have developed to implement the proposed improvements.

Fabrication of Gamma Detectors Based on Magnetic Ag:Er Microcalorimeters

Energy Technology Data Exchange (ETDEWEB)

Friedrich, Stephan [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Boyd, Stephen [Univ. of New Mexico, Albuquerque, NM (United States); Cantor, Robin [STAR Cryoelectronics, Santa Fe, NM (United States)

2016-05-06

This report discusses the photolithographic fabrication of ultra-high resolution gamma-ray detectors based on magnetic microcalorimeters (MMCs). The MMC uses a novel Er-doped silver sensor (Ag:Er) that is expected to have higher sensitivity than the Er-doped gold (Au:Er) sensors currently in use. The MMC also integrates the first-stage SQUID preamplifier on the same chip as the MMC gamma detector to increase its signal-to-noise ratio. In addition, the MMC uses a passive Ta-Nb heat switch to replace one of the common long-term failure points in earlier detectors. This report discusses the fabrication process we have developed to implement the proposed improvements.

Fabrication of Gamma Detectors Based on Magnetic Ag:Er Microcalorimeters

International Nuclear Information System (INIS)

Friedrich, Stephan; Boyd, Stephen; Cantor, Robin

2016-01-01

This report discusses the photolithographic fabrication of ultra-high resolution gamma-ray detectors based on magnetic microcalorimeters (MMCs). The MMC uses a novel Er-doped silver sensor (Ag:Er) that is expected to have higher sensitivity than the Er-doped gold (Au:Er) sensors currently in use. The MMC also integrates the first-stage SQUID preamplifier on the same chip as the MMC gamma detector to increase its signal-to-noise ratio. In addition, the MMC uses a passive Ta-Nb heat switch to replace one of the common long-term failure points in earlier detectors. This report discusses the fabrication process we have developed to implement the proposed improvements.

Fabrication of Gamma Detectors Based on Magnetic Ag:Er Microcalorimeters

International Nuclear Information System (INIS)

Friedrich, Stephan; Boyd, Stephen; Cantor, Robin

2015-01-01

This report discusses the photolithographic fabrication of ultra-high resolution gamma-ray detectors based on magnetic microcalorimeters (MMCs). The MMC uses a novel Er-doped silver sensor (Ag:Er) that is expected to have higher sensitivity than the Er-doped gold (Au:Er) sensors currently in use. The MMC also integrates the first-stage SQUID preamplifier on the same chip as the MMC gamma detector to increase its signal-to-noise ratio. In addition, the MMC uses a passive Ta-Nb heat switch to replace one of the common long-term failure points in earlier detectors. This report discusses the fabrication process we have developed to implement the proposed improvements.

Faster method for the calculation of the chattering signal at the ct-detector by monte-carlo-method

International Nuclear Information System (INIS)

Schmidt, B.; Kalender, W.A.

2003-01-01

Multislice spiral CT scanners allow to acquire multiple slices simultaneously. With increasing numbers of slices, not only the total extent of slice collimation increases, but also the contribution of scatter radiation to the detector signal. A fast method for calculating the scatter signal would offer the possibility to correct the measured detector signal. Monte Carlo methods allow to simulate the paths of photons through a 3D volume, both in a patient- and scanner-specific fashion. If a scatter photon leaves the volume, its path can be followed and its interaction with an element of the detector be checked. This conventional way of calculating the scatter signal is time-consuming. In order to reduce the calculation time, a more efficient method was developed (Method of Weights). Every time an interaction occurs inside of the 3D volume, the probability of a detector hit due to photon scattering is calculated for each detector channel. The respective value is added to the scatter signal per detector with the corresponding weight. Simulated values of scatter-to-primary-signal ratios were confirmed by data available in the literature. Both the conventional and fast methods for the calculation of scatter signals yielded identical values within the range of statistical accuracy. Assuming the same computing time, the standard deviation for the conventional method was 5 times higher than for the fast one. The presented method allows to significantly reduce the computation time. It may therefore provide a basis for ''real time'' methods to correct for the scatter signal, especially in case of increasing numbers of slices. (orig.) [de

Investigation of new vehicle detectors for high-speed signalized intersections.

Science.gov (United States)

2015-09-01

Early indications from the use of the newest vehicle detectors for high-speed signalized intersections : suggested that they perform well as replacements for the Texas Department of Transportations : (TxDOTs) legacy systems, but this early conc...

Characterization and modelling of signal dynamics in 3D-DDTC detectors

International Nuclear Information System (INIS)

Zoboli, A.; Boscardin, M.; Bosisio, L.; Dalla Betta, G.-F.; Gabos, P.; Piemonte, C.; Ronchin, S.; Zorzi, N.

2010-01-01

In the past few years we have developed 3D detector technologies within a collaboration between INFN and FBK-irst aiming at a simplification of the fabrication technology with respect to the original 3D design. These detectors are the object of an increasing interest from the HEP community because of their intrinsic radiation hardness, making them appealing for innermost layers of tracking at the foreseen upgrades of the large hadron collider. In this paper we evaluate the signal shape in response to localized and uniform charge deposition both by solving Ramo's theorem and with the aid of TCAD simulations. Signals observed in 3D diodes, stimulated by lasers at different wavelengths, are compared with simulations results.

Characterization and modelling of signal dynamics in 3D-DDTC detectors

Energy Technology Data Exchange (ETDEWEB)

Zoboli, A., E-mail: zoboli@disi.unitn.i [INFN, Sezione di Padova (Gruppo Collegato di Trento), and Dipartimento di Ingegneria e Scienza dell' Informazione, Universita di Trento, Via Sommarive, 14, I-38050 Povo (Trento) (Italy); Boscardin, M. [Fondazione Bruno Kessler, Centro per i Materiali e i Microsistemi, Via Sommarive, 18, I-38050 Povo (Trento) (Italy); Bosisio, L. [INFN, Sezione di Trieste, e Dipartimento di Fisica, Universita di Trieste, I-34127 Trieste (Italy); Dalla Betta, G.-F.; Gabos, P. [INFN, Sezione di Padova (Gruppo Collegato di Trento), and Dipartimento di Ingegneria e Scienza dell' Informazione, Universita di Trento, Via Sommarive, 14, I-38050 Povo (Trento) (Italy); Piemonte, C.; Ronchin, S.; Zorzi, N. [Fondazione Bruno Kessler, Centro per i Materiali e i Microsistemi, Via Sommarive, 18, I-38050 Povo (Trento) (Italy)

2010-05-21

In the past few years we have developed 3D detector technologies within a collaboration between INFN and FBK-irst aiming at a simplification of the fabrication technology with respect to the original 3D design. These detectors are the object of an increasing interest from the HEP community because of their intrinsic radiation hardness, making them appealing for innermost layers of tracking at the foreseen upgrades of the large hadron collider. In this paper we evaluate the signal shape in response to localized and uniform charge deposition both by solving Ramo's theorem and with the aid of TCAD simulations. Signals observed in 3D diodes, stimulated by lasers at different wavelengths, are compared with simulations results.

Smile detectors correlation

Science.gov (United States)

Yuksel, Kivanc; Chang, Xin; Skarbek, Władysław

2017-08-01

The novel smile recognition algorithm is presented based on extraction of 68 facial salient points (fp68) using the ensemble of regression trees. The smile detector exploits the Support Vector Machine linear model. It is trained with few hundreds exemplar images by SVM algorithm working in 136 dimensional space. It is shown by the strict statistical data analysis that such geometric detector strongly depends on the geometry of mouth opening area, measured by triangulation of outer lip contour. To this goal two Bayesian detectors were developed and compared with SVM detector. The first uses the mouth area in 2D image, while the second refers to the mouth area in 3D animated face model. The 3D modeling is based on Candide-3 model and it is performed in real time along with three smile detectors and statistics estimators. The mouth area/Bayesian detectors exhibit high correlation with fp68/SVM detector in a range [0:8; 1:0], depending mainly on light conditions and individual features with advantage of 3D technique, especially in hard light conditions.

Modeling the impact of preflushing on CTE in proton irradiated CCD-based detectors

Science.gov (United States)

Philbrick, R. H.

2002-04-01

A software model is described that performs a "real world" simulation of the operation of several types of charge-coupled device (CCD)-based detectors in order to accurately predict the impact that high-energy proton radiation has on image distortion and modulation transfer function (MTF). The model was written primarily to predict the effectiveness of vertical preflushing on the custom full frame CCD-based detectors intended for use on the proposed Kepler Discovery mission, but it is capable of simulating many other types of CCD detectors and operating modes as well. The model keeps track of the occupancy of all phosphorous-silicon (P-V), divacancy (V-V) and oxygen-silicon (O-V) defect centers under every CCD electrode over the entire detector area. The integrated image is read out by simulating every electrode-to-electrode charge transfer in both the vertical and horizontal CCD registers. A signal level dependency on the capture and emission of signal is included and the current state of each electrode (e.g., barrier or storage) is considered when distributing integrated and emitted signal. Options for performing preflushing, preflashing, and including mini-channels are available on both the vertical and horizontal CCD registers. In addition, dark signal generation and image transfer smear can be selectively enabled or disabled. A comparison of the charge transfer efficiency (CTE) data measured on the Hubble space telescope imaging spectrometer (STIS) CCD with the CTE extracted from model simulations of the STIS CCD show good agreement.

Using convolutional neural networks to estimate time-of-flight from PET detector waveforms

Science.gov (United States)

Berg, Eric; Cherry, Simon R.

2018-01-01

Although there have been impressive strides in detector development for time-of-flight positron emission tomography, most detectors still make use of simple signal processing methods to extract the time-of-flight information from the detector signals. In most cases, the timing pick-off for each waveform is computed using leading edge discrimination or constant fraction discrimination, as these were historically easily implemented with analog pulse processing electronics. However, now with the availability of fast waveform digitizers, there is opportunity to make use of more of the timing information contained in the coincident detector waveforms with advanced signal processing techniques. Here we describe the application of deep convolutional neural networks (CNNs), a type of machine learning, to estimate time-of-flight directly from the pair of digitized detector waveforms for a coincident event. One of the key features of this approach is the simplicity in obtaining ground-truth-labeled data needed to train the CNN: the true time-of-flight is determined from the difference in path length between the positron emission and each of the coincident detectors, which can be easily controlled experimentally. The experimental setup used here made use of two photomultiplier tube-based scintillation detectors, and a point source, stepped in 5 mm increments over a 15 cm range between the two detectors. The detector waveforms were digitized at 10 GS s-1 using a bench-top oscilloscope. The results shown here demonstrate that CNN-based time-of-flight estimation improves timing resolution by 20% compared to leading edge discrimination (231 ps versus 185 ps), and 23% compared to constant fraction discrimination (242 ps versus 185 ps). By comparing several different CNN architectures, we also showed that CNN depth (number of convolutional and fully connected layers) had the largest impact on timing resolution, while the exact network parameters, such as convolutional

MRTD: man versus machine

Science.gov (United States)

van Rheenen, Arthur D.; Taule, Petter; Thomassen, Jan Brede; Madsen, Eirik Blix

2018-04-01

We present Minimum-Resolvable Temperature Difference (MRTD) curves obtained by letting an ensemble of observers judge how many of the six four-bar patterns they can "see" in a set of images taken with different bar-to-background contrasts. The same images are analyzed using elemental signal analysis algorithms and machine-analysis based MRTD curves are obtained. We show that by adjusting the minimum required signal-to-noise ratio the machine-based MRTDs are very similar to the ones obtained with the help of the human observers.

Analysis of monochromatic signals by using data from the detector of Allegro gravitational waves

International Nuclear Information System (INIS)

Oliveira, Fernanda Gomes de

2010-01-01

The present work is developed in the searching for monochromatic gravitational waves signals in ALLEGRO's data. We have two procedures for data analysis based on the periodogram of Welch, which a method for the detection of monochromatic signals in the middle of noise which basically makes power spectrum estimates using averaged modified periodograms. By using this method it was possible to obtain a power spectrum for the data which reinforce peaks due to monochromatic signals. The two procedures of analysis for the years 1997 and 1999, were focused on monitoring a peak that appears in the spectral density of ALLEGRO's detector, so called 'mystery mode' (near 887 Hz). We look for variations in the frequency of the mystery mode that agree with the variation of the Doppler effect. In the rst analysis we have used by the variation of daily and annual Doppler shift. For the second one, we have only searched annual Doppler shift. We have applied the periodogram of Welch in both tests in the raw data of the detector in the search for a real signal and we found some peaks that can be candidates of gravitational radiation only the second analysis. In order to test the method we used in both analysis a simulated gravitational wave signal modulated by the Doppler effect injected in the data. We detected in both methods the artificial signal of GW simulated. Therefore we have reason to conclude that both methods are efficient in the search for monochromatic signals. (author)

Advanced Electrical Machines and Machine-Based Systems for Electric and Hybrid Vehicles

Directory of Open Access Journals (Sweden)

Ming Cheng

2015-09-01

Full Text Available The paper presents a number of advanced solutions on electric machines and machine-based systems for the powertrain of electric vehicles (EVs. Two types of systems are considered, namely the drive systems designated to the EV propulsion and the power split devices utilized in the popular series-parallel hybrid electric vehicle architecture. After reviewing the main requirements for the electric drive systems, the paper illustrates advanced electric machine topologies, including a stator permanent magnet (stator-PM motor, a hybrid-excitation motor, a flux memory motor and a redundant motor structure. Then, it illustrates advanced electric drive systems, such as the magnetic-geared in-wheel drive and the integrated starter generator (ISG. Finally, three machine-based implementations of the power split devices are expounded, built up around the dual-rotor PM machine, the dual-stator PM brushless machine and the magnetic-geared dual-rotor machine. As a conclusion, the development trends in the field of electric machines and machine-based systems for EVs are summarized.

Microwave life detector for buried victims using neutrodyning loop based system

Science.gov (United States)

Tahar J., Bel Hadj

2009-07-01

This paper describes a new design of an electromagnetic life detector for the detection of buried victims. The principle of the microwave life sensor is based on the detection of the modulated part of a scattered wave which is generated by the breathing activity of the victim. Those movements generate a spectral component located in the low frequency range, which for most of the cases, is located in a spectrum extending from 0.18 Hz to 0.34 Hz. The detection process requires high sensitivity with respect to breathing movements and, simultaneously, a relative insensitivity for other non-modulated or modulated parasitic signals. Developed microwave system, generating a frequency adjustable between 500 MHz and 1 GHz, is based on a neutrodyning loop required to cancel any non-modulated background and reflected signals in order to get better receiver sensitivity without introducing supplementary distortions on the received signal. Life signal is considered practically periodic that facilitates the extraction of this spectral component using several processing techniques, such as adaptive filtering and correlation permitting to ameliorate the detection range to be more than 15 m in low-loss medium. Detection range is a fundamental parameter for a microwave life detector. A range around 1 m doesn't have a large interest for this application. To attain a range more than 15 m, while guaranteeing professional performances, the technology has to optimize the system parameters as well as the involved signal processing for the purpose of overcoming the presence of obstacles, attenuation, and noise perturbation. This constitutes the main contribution of the present work. Experimental measurements have confirmed the potentiality of this microwave technique for life detector with best space covering detection.

Identification of Auditory Object-Specific Attention from Single-Trial Electroencephalogram Signals via Entropy Measures and Machine Learning

Directory of Open Access Journals (Sweden)

Yun Lu

2018-05-01

Full Text Available Existing research has revealed that auditory attention can be tracked from ongoing electroencephalography (EEG signals. The aim of this novel study was to investigate the identification of peoples’ attention to a specific auditory object from single-trial EEG signals via entropy measures and machine learning. Approximate entropy (ApEn, sample entropy (SampEn, composite multiscale entropy (CmpMSE and fuzzy entropy (FuzzyEn were used to extract the informative features of EEG signals under three kinds of auditory object-specific attention (Rest, Auditory Object1 Attention (AOA1 and Auditory Object2 Attention (AOA2. The linear discriminant analysis and support vector machine (SVM, were used to construct two auditory attention classifiers. The statistical results of entropy measures indicated that there were significant differences in the values of ApEn, SampEn, CmpMSE and FuzzyEn between Rest, AOA1 and AOA2. For the SVM-based auditory attention classifier, the auditory object-specific attention of Rest, AOA1 and AOA2 could be identified from EEG signals using ApEn, SampEn, CmpMSE and FuzzyEn as features and the identification rates were significantly different from chance level. The optimal identification was achieved by the SVM-based auditory attention classifier using CmpMSE with the scale factor τ = 10. This study demonstrated a novel solution to identify the auditory object-specific attention from single-trial EEG signals without the need to access the auditory stimulus.

BPM Electronics based on Compensated Diode Detectors – Results from development Systems

CERN Document Server

Gasior, M; Steinhagen, RJ

2012-01-01

High resolution beam position monitor (BPM) electronics based on diode peak detectors is being developed for processing signals from button BPMs embedded into future LHC collimators. Its prototypes were measured in a laboratory as well as with beam signals from the collimator BPM installed on the SPS and with LHC BPMs. Results from these measurements are presented and discussed.

Model-based machine learning.

Science.gov (United States)

Bishop, Christopher M

2013-02-13

Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.

A Novel Immune-Inspired Shellcode Detection Algorithm Based on Hyperellipsoid Detectors

Directory of Open Access Journals (Sweden)

Tianliang Lu

2018-01-01

Full Text Available Shellcodes are machine language codes injected into target programs in the form of network packets or malformed files. Shellcodes can trigger buffer overflow vulnerability and execute malicious instructions. Signature matching technology used by antivirus software or intrusion detection system has low detection rate for unknown or polymorphic shellcodes; to solve such problem, an immune-inspired shellcode detection algorithm was proposed, named ISDA. Static analysis and dynamic analysis were both applied. The shellcodes were disassembled to assembly instructions during static analysis and, for dynamic analysis, the API function sequences of shellcodes were obtained by simulation execution to get the behavioral features of polymorphic shellcodes. The extracted features of shellcodes were encoded to antigens based on n-gram model. Immature detectors become mature after immune tolerance based on negative selection algorithm. To improve nonself space coverage rate, the immune detectors were encoded to hyperellipsoids. To generate better antibody offspring, the detectors were optimized through clonal selection algorithm with genetic mutation. Finally, shellcode samples were collected and tested, and result shows that the proposed method has higher detection accuracy for both nonencoded and polymorphic shellcodes.

Pulse-height loss in the signal readout circuit of compound semiconductor detectors

Science.gov (United States)

Nakhostin, M.; Hitomi, K.

2018-06-01

Compound semiconductor detectors such as CdTe, CdZnTe, HgI2 and TlBr are known to exhibit large variations in their charge collection times. This paper considers the effect of such variations on the measurement of induced charge pulses by using resistive feedback charge-sensitive preamplifiers. It is shown that, due to the finite decay-time constant of the preamplifiers, the capacitive decay during the signal readout leads to a variable deficit in the measurement of ballistic signals and a digital pulse processing method is employed to correct for it. The method is experimentally examined by using sampled pulses from a TlBr detector coupled to a charge-sensitive preamplifier with 150 μs of decay-time constant and 20 % improvement in the energy resolution of the detector at 662 keV is achieved. The implications of the capacitive decay on the correction of charge-trapping effect by using depth-sensing technique are also considered.

The CMS Beam Halo Monitor Detector System

CERN Document Server

CMS Collaboration

2015-01-01

A new Beam Halo Monitor (BHM) detector system has been installed in the CMS cavern to measure the machine-induced background (MIB) from the LHC. This background originates from interactions of the LHC beam halo with the final set of collimators before the CMS experiment and from beam gas interactions. The BHM detector uses the directional nature of Cherenkov radiation and event timing to select particles coming from the direction of the beam and to suppress those originating from the interaction point. It consists of 40 quartz rods, placed on each side of the CMS detector, coupled to UV sensitive PMTs. For each bunch crossing the PMT signal is digitized by a charge integrating ASIC and the arrival time of the signal is recorded. The data are processed in real time to yield a precise measurement of per-bunch-crossing background rate. This measurement is made available to CMS and the LHC, to provide real-time feedback on the beam quality and to improve the efficiency of data taking. In this talk we will describ...

Ionization signals from diamond detectors in fast-neutron fields

Energy Technology Data Exchange (ETDEWEB)

Weiss, C. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); CIVIDEC Instrumentation, Wien (Austria); Frais-Koelbl, H. [University of Applied Sciences, Wiener Neustadt (Austria); Griesmayer, E.; Kavrigin, P. [CIVIDEC Instrumentation, Wien (Austria); Vienna University of Technology, Wien (Austria)

2016-09-15

In this paper we introduce a novel analysis technique for measurements with single-crystal chemical vapor deposition (sCVD) diamond detectors in fast-neutron fields. This method exploits the unique electronic property of sCVD diamond sensors that the signal shape of the detector current is directly proportional to the initial ionization profile. In fast-neutron fields the diamond sensor acts simultaneously as target and sensor. The interaction of neutrons with the stable isotopes {sup 12}C and {sup 13}C is of interest for fast-neutron diagnostics. The measured signal shapes of detector current pulses are used to identify individual types of interactions in the diamond with the goal to select neutron-induced reactions in the diamond and to suppress neutron-induced background reactions as well as γ-background. The method is verified with experimental data from a measurement in a 14.3 MeV neutron beam at JRC-IRMM, Geel/Belgium, where the {sup 13}C(n, α){sup 10}Be reaction was successfully extracted from the dominating background of recoil protons and γ-rays and the energy resolution of the {sup 12}C(n, α){sup 9}Be reaction was substantially improved. The presented analysis technique is especially relevant for diagnostics in harsh radiation environments, like fission and fusion reactors. It allows to extract the neutron spectrum from the background, and is particularly applicable to neutron flux monitoring and neutron spectroscopy. (orig.)

The effects of LIGO detector noise on a 15-dimensional Markov-chain Monte Carlo analysis of gravitational-wave signals

International Nuclear Information System (INIS)

Raymond, V; Mandel, I; Kalogera, V; Van der Sluys, M V; Roever, C; Christensen, N

2010-01-01

Gravitational-wave signals from inspirals of binary compact objects (black holes and neutron stars) are primary targets of the ongoing searches by ground-based gravitational-wave (GW) interferometers (LIGO, Virgo and GEO-600). We present parameter estimation results from our Markov-chain Monte Carlo code SPINspiral on signals from binaries with precessing spins. Two data sets are created by injecting simulated GW signals either into synthetic Gaussian noise or into LIGO detector data. We compute the 15-dimensional probability-density functions (PDFs) for both data sets, as well as for a data set containing LIGO data with a known, loud artefact ('glitch'). We show that the analysis of the signal in detector noise yields accuracies similar to those obtained using simulated Gaussian noise. We also find that while the Markov chains from the glitch do not converge, the PDFs would look consistent with a GW signal present in the data. While our parameter estimation results are encouraging, further investigations into how to differentiate an actual GW signal from noise are necessary.

Machine Learning for Optical Performance Monitoring from Directly Detected PDM-QAM Signals

DEFF Research Database (Denmark)

Wass, J.; Thrane, Jakob; Piels, Molly

2016-01-01

Supervised machine learning methods are applied and demonstrated experimentally for inband OSNR estimation and modulation format classification in optical communication systems. The proposed methods accurately evaluate coherent signals up to 64QAM using only intensity information....

EMD-Based Symbolic Dynamic Analysis for the Recognition of Human and Nonhuman Pyroelectric Infrared Signals

Directory of Open Access Journals (Sweden)

Jiaduo Zhao

2016-01-01

Full Text Available In this paper, we propose an effective human and nonhuman pyroelectric infrared (PIR signal recognition method to reduce PIR detector false alarms. First, using the mathematical model of the PIR detector, we analyze the physical characteristics of the human and nonhuman PIR signals; second, based on the analysis results, we propose an empirical mode decomposition (EMD-based symbolic dynamic analysis method for the recognition of human and nonhuman PIR signals. In the proposed method, first, we extract the detailed features of a PIR signal into five symbol sequences using an EMD-based symbolization method, then, we generate five feature descriptors for each PIR signal through constructing five probabilistic finite state automata with the symbol sequences. Finally, we use a weighted voting classification strategy to classify the PIR signals with their feature descriptors. Comparative experiments show that the proposed method can effectively classify the human and nonhuman PIR signals and reduce PIR detector’s false alarms.

Development and tests of MCP based timing and multiplicity detector for MIPs

Science.gov (United States)

Feofilov, G.; Kondratev, V.; Stolyarov, O.; Tulina, T.; Valiev, F.; Vinogradov, L.

2017-01-01

We present summary of technological developments and tests of the MCP based large area detector aimed at precise timing and charged particles multiplicity measurements. Results obtained in course of these developments of isochronous (simultaneity) precise signal readout, passive summation of 1 ns signals, fast (1 GHz) front-end electronics, miniature vacuum systems, etc. could be potentially interesting for a number of future applications in different fields.

Signal and noise analysis in TRION-Time-Resolved Integrative Optical Fast Neutron detector

International Nuclear Information System (INIS)

Vartsky, D; Feldman, G; Mor, I; Goldberg, M B; Bar, D; Dangendorf, V

2009-01-01

TRION is a sub-mm spatial resolution fast neutron imaging detector, which employs an integrative optical time-of-flight technique. The detector was developed for fast neutron resonance radiography, a method capable of detecting a broad range of conventional and improvised explosives. In this study we have analyzed in detail, using Monte-Carlo calculations and experimentally determined parameters, all the processes that influence the signal and noise in the TRION detector. In contrast to event-counting detectors where the signal-to-noise ratio is dependent only on the number of detected events (quantum noise), in an energy-integrating detector additional factors, such as the fluctuations in imparted energy, number of photoelectrons, system gain and other factors will contribute to the noise. The excess noise factor (over the quantum noise) due to these processes was 4.3, 2.7, 2.1, 1.9 and 1.9 for incident neutron energies of 2, 4, 7.5, 10 and 14 MeV, respectively. It is shown that, even under ideal light collection conditions, a fast neutron detection system operating in an integrative mode cannot be quantum-noise-limited due to the relatively large variance in the imparted proton energy and the resulting scintillation light distributions.

Classification of Motor Imagery EEG Signals with Support Vector Machines and Particle Swarm Optimization

Science.gov (United States)

Ma, Yuliang; Ding, Xiaohui; She, Qingshan; Luo, Zhizeng; Potter, Thomas; Zhang, Yingchun

2016-01-01

Support vector machines are powerful tools used to solve the small sample and nonlinear classification problems, but their ultimate classification performance depends heavily upon the selection of appropriate kernel and penalty parameters. In this study, we propose using a particle swarm optimization algorithm to optimize the selection of both the kernel and penalty parameters in order to improve the classification performance of support vector machines. The performance of the optimized classifier was evaluated with motor imagery EEG signals in terms of both classification and prediction. Results show that the optimized classifier can significantly improve the classification accuracy of motor imagery EEG signals. PMID:27313656

Features of measurement and processing of vibration signals registered on the moving parts of electrical machines

OpenAIRE

Gyzhko, Yuri

2011-01-01

Measurement and processing of vibration signals registered on the moving parts of the electrical machines using the diagnostic information-measuring system that uses Bluetooth wireless standard for the transmission of the measured data from moving parts of electrical machine is discussed.

Pulse shape analysis and position determination in segmented HPGe detectors: The AGATA detector library

Energy Technology Data Exchange (ETDEWEB)

Bruyneel, B. [Universitaet zu Koeln, Institut fuer Kernphysik, Koeln (Germany); Service de Physique Nucleaire, CEA Saclay, Gif-sur-Yvette (France); Birkenbach, B.; Reiter, P. [Universitaet zu Koeln, Institut fuer Kernphysik, Koeln (Germany)

2016-03-15

The AGATA Detector Library (ADL) was developed for the calculation of signals from highly segmented large volume high-purity germanium (HPGe) detectors. ADL basis sets comprise a huge amount of calculated position-dependent detector pulse shapes. A basis set is needed for Pulse Shape Analysis (PSA). By means of PSA the interaction position of a γ -ray inside the active detector volume is determined. Theoretical concepts of the calculations are introduced and cover the relevant aspects of signal formation in HPGe. The approximations and the realization of the computer code with its input parameters are explained in detail. ADL is a versatile and modular computer code; new detectors can be implemented in this library. Measured position resolutions of the AGATA detectors based on ADL are discussed. (orig.)

A novel signal compression method based on optimal ensemble empirical mode decomposition for bearing vibration signals

Science.gov (United States)

Guo, Wei; Tse, Peter W.

2013-01-01

Today, remote machine condition monitoring is popular due to the continuous advancement in wireless communication. Bearing is the most frequently and easily failed component in many rotating machines. To accurately identify the type of bearing fault, large amounts of vibration data need to be collected. However, the volume of transmitted data cannot be too high because the bandwidth of wireless communication is limited. To solve this problem, the data are usually compressed before transmitting to a remote maintenance center. This paper proposes a novel signal compression method that can substantially reduce the amount of data that need to be transmitted without sacrificing the accuracy of fault identification. The proposed signal compression method is based on ensemble empirical mode decomposition (EEMD), which is an effective method for adaptively decomposing the vibration signal into different bands of signal components, termed intrinsic mode functions (IMFs). An optimization method was designed to automatically select appropriate EEMD parameters for the analyzed signal, and in particular to select the appropriate level of the added white noise in the EEMD method. An index termed the relative root-mean-square error was used to evaluate the decomposition performances under different noise levels to find the optimal level. After applying the optimal EEMD method to a vibration signal, the IMF relating to the bearing fault can be extracted from the original vibration signal. Compressing this signal component obtains a much smaller proportion of data samples to be retained for transmission and further reconstruction. The proposed compression method were also compared with the popular wavelet compression method. Experimental results demonstrate that the optimization of EEMD parameters can automatically find appropriate EEMD parameters for the analyzed signals, and the IMF-based compression method provides a higher compression ratio, while retaining the bearing defect

Low complexity detectors for cooperative wireless sensor networks

KAUST Repository

Ahmed, Qasim Zeeshan

2012-09-01

This paper investigates and compares the performance of wireless sensor networks (WSN) when sensors operate on the principles of cooperative communications. We consider a scenario where the source transmits signals to the destination with the help of L sensors. As the destination has the capacity of processing only U out of these L signals, U strongest signals are selected while the remaining (L - U) signals are suppressed. A preprocessing block similar to channel-shortening (CS) is proposed in this contribution. However, this preprocessing block employs rank-reduction technique instead of CS. This detector operates on the principles of principal components (PC). From our simulations it can be observed that this detector is capable of achieving a similar bit error rate (BER) performance as the full-rank MMSE detector with significantly lower complexity. It outperforms the CS-based detector in terms of BER performance when using fixed amplification factor. However, for variable gain amplification factor a tradeoff between the diversity gain and the receiver complexity can be observed. From the simulations it can be concluded that the BER performance of the PC-based detector when using variable gain amplification factor are better than that of the CS-based detector for lower signal to noise ratio. © 2012 IEEE.

Observation of meander pattern in signals from superconducting MgB{sub 2} detector by scanning pulsed laser imaging

Energy Technology Data Exchange (ETDEWEB)

Ishida, Takekazu, E-mail: ishida@center.osakafu-u.ac.jp [Department of Physics and Electronics, Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531 (Japan); Institute for Nanofabrication Research, Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531 (Japan); Yagi, Ikutaro; Yoshioka, Naohito; Huy, Ho Thanh [Department of Physics and Electronics, Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531 (Japan); Yotsuya, Tsutomu [Institute for Nanofabrication Research, Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531 (Japan); Nanoscience and Nanotechnology Research Center, Osaka Prefecture University, 2-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8570 (Japan); Shimakage, Hisashi [Department of Electrical and Electronic Engineering, College of Engineering, 4-12-1, Nakanarusawa, Hitachi, Ibaraki 316-8511 (Japan); Miki, Shigehito [Kansai Advanced Research Center, National Institute of Information and Communications Technology, 588-2 Iwaoka-cho, Nishi-ku, Kobe, Hyogo 651-2429 (Japan); Wang, Zhen [Institute for Nanofabrication Research, Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531 (Japan); Kansai Advanced Research Center, National Institute of Information and Communications Technology, 588-2 Iwaoka-cho, Nishi-ku, Kobe, Hyogo 651-2429 (Japan)

2013-01-15

Highlights: ► We fabricate a superconducting MgB{sub 2} meander detector as a solid-state neutron detector. ► MgB{sub 2} detector uses XYZ stage, optical fiber and focused lens to scan as a microscope. ► The 6 μm line-and-space in meandering pattern can be resolved in signals against pulsed laser. -- Abstract: Superconducting MgB{sub 2} meander detector has been imaged by scanning a spot of 1.5-μm focused pulsed laser. The superconducting detector using high-quality {sup 10}B-enriched MgB{sub 2} thin films at higher operating temperatures has been fabricated to utilize a resistance change induced by the nuclear energy of {sup 10}B and neutron. The MgB{sub 2} detector consists of a 200-nm-thick MgB{sub 2} thin-film meander line, a 300-nm-thick SiO protective layer, and 150-nm-thick Nb electrodes with 1-μm MgB{sub 2} wires. The devices were placed in a 4 K refrigerator to control at a certain temperature below T{sub c}. A scanning laser spot can be used by the combination of the XYZ piezo-drive stage and an optical fibre with an aspheric focused lens. The measurement system is fully controlled by LabVIEW based software. We succeeded in observing a line-and-space image of a meandering pattern by analysing response signals.

Inverter ratio failure detector

Science.gov (United States)

Wagner, A. P.; Ebersole, T. J.; Andrews, R. E. (Inventor)

1974-01-01

A failure detector which detects the failure of a dc to ac inverter is disclosed. The inverter under failureless conditions is characterized by a known linear relationship of its input and output voltages and by a known linear relationship of its input and output currents. The detector includes circuitry which is responsive to the detector's input and output voltages and which provides a failure-indicating signal only when the monitored output voltage is less by a selected factor, than the expected output voltage for the monitored input voltage, based on the known voltages' relationship. Similarly, the detector includes circuitry which is responsive to the input and output currents and provides a failure-indicating signal only when the input current exceeds by a selected factor the expected input current for the monitored output current based on the known currents' relationship.

Measurements of fast-neutron-induced signals in silicon pad detectors

Czech Academy of Sciences Publication Activity Database

Linhart, V.; Bedajanek, I.; Bém, Pavel; Götz, Miloslav; Honusek, Milan; Pospíšil, S.; Šimečková, Eva

2006-01-01

Roč. 563, č. 1 (2006), s. 263-267 ISSN 0168-9002 R&D Projects: GA MPO(CZ) 1H-PK/07 Institutional research plan: CEZ:AV0Z10480505 Keywords : background signals * neutron reactions * solid-state detectors Subject RIV: BG - Nuclear, Atomic and Molecular Physics, Colliders Impact factor: 1.185, year: 2006

Robust Bio-Signal Based Control of an Intelligent Wheelchair

Directory of Open Access Journals (Sweden)

Dongyi Chen

2013-09-01

Full Text Available In this paper, an adaptive human-machine interaction (HMI method that is based on surface electromyography (sEMG signals is proposed for the hands-free control of an intelligent wheelchair. sEMG signals generated by the facial movements are obtained by a convenient dry electrodes sensing device. After the signals features are extracted from the autoregressive model, control data samples are updated and trained by an incremental online learning algorithm in real-time. Experimental results show that the proposed method can significantly improve the classification accuracy and training speed. Moreover, this method can effectively reduce the influence of muscle fatigue during a long time operation of sEMG-based HMI.

A New Waveform Signal Processing Method Based on Adaptive Clustering-Genetic Algorithms

International Nuclear Information System (INIS)

Noha Shaaban; Fukuzo Masuda; Hidetsugu Morota

2006-01-01

We present a fast digital signal processing method for numerical analysis of individual pulses from CdZnTe compound semiconductor detectors. Using Maxi-Mini Distance Algorithm and Genetic Algorithms based discrimination technique. A parametric approach has been used for classifying the discriminated waveforms into a set of clusters each has a similar signal shape with a corresponding pulse height spectrum. A corrected total pulse height spectrum was obtained by applying a normalization factor for the full energy peak for each cluster with a highly improvements in the energy spectrum characteristics. This method applied successfully for both simulated and real measured data, it can be applied to any detector suffers from signal shape variation. (authors)

3D CT cerebral angiography technique using a 320-detector machine with a time–density curve and low contrast medium volume: Comparison with fixed time delay technique

International Nuclear Information System (INIS)

Das, K.; Biswas, S.; Roughley, S.; Bhojak, M.; Niven, S.

2014-01-01

Aim: To describe a cerebral computed tomography angiography (CTA) technique using a 320-detector CT machine and a small contrast medium volume (35 ml, 15 ml for test bolus). Also, to compare the quality of these images with that of the images acquired using a larger contrast medium volume (90 or 120 ml) and a fixed time delay (FTD) of 18 s using a 16-detector CT machine. Materials and methods: Cerebral CTA images were acquired using a 320-detector machine by synchronizing the scanning time with the time of peak enhancement as determined from the time–density curve (TDC) using a test bolus dose. The quality of CTA images acquired using this technique was compared with that obtained using a FTD of 18 s (by 16-detector CT), retrospectively. Average densities in four different intracranial arteries, overall opacification of arteries, and the degree of venous contamination were graded and compared. Results: Thirty-eight patients were scanned using the TDC technique and 40 patients using the FTD technique. The arterial densities achieved by the TDC technique were higher (significant for supraclinoid and basilar arteries, p < 0.05). The proportion of images deemed as having “good” arterial opacification was 95% for TDC and 90% for FTD. The degree of venous contamination was significantly higher in images produced by the FTD technique (p < 0.001%). Conclusion: Good diagnostic quality CTA images with significant reduction of venous contamination can be achieved with a low contrast medium dose using a 320-detector machine by coupling the time of data acquisition with the time of peak enhancement

Systematic survey for monitor signals to reduce fake burst events in a gravitational-wave detector

International Nuclear Information System (INIS)

Ishidoshiro, Koji; Ando, Masaki; Tsubono, Kimio

2006-01-01

We present methods and results to reduce fake burst events induced by nonstationary noises. To reduce these fake events, we systematically surveyed monitor signals recorded with a main (or gravitational-wave) signal of a gravitational-wave detector so as to watch the detector. Our survey was to check whether or not there was a coincidence between the main and monitor signals when we found a burst event from the main signal. If there was a coincidence, we rejected this event as a fake event induced by nonstationary noises, regarding the main signal as being dominated by nonstationary noises. As a result, we succeeded to reject about 90% of the burst events of which the SNR values were larger than 10 as fake events, with an accidental probability of about 5% to reject burst-gravitational-wave candidates

Surface electromyography based muscle fatigue detection using high-resolution time-frequency methods and machine learning algorithms.

Science.gov (United States)

Karthick, P A; Ghosh, Diptasree Maitra; Ramakrishnan, S

2018-02-01

Surface electromyography (sEMG) based muscle fatigue research is widely preferred in sports science and occupational/rehabilitation studies due to its noninvasiveness. However, these signals are complex, multicomponent and highly nonstationary with large inter-subject variations, particularly during dynamic contractions. Hence, time-frequency based machine learning methodologies can improve the design of automated system for these signals. In this work, the analysis based on high-resolution time-frequency methods, namely, Stockwell transform (S-transform), B-distribution (BD) and extended modified B-distribution (EMBD) are proposed to differentiate the dynamic muscle nonfatigue and fatigue conditions. The nonfatigue and fatigue segments of sEMG signals recorded from the biceps brachii of 52 healthy volunteers are preprocessed and subjected to S-transform, BD and EMBD. Twelve features are extracted from each method and prominent features are selected using genetic algorithm (GA) and binary particle swarm optimization (BPSO). Five machine learning algorithms, namely, naïve Bayes, support vector machine (SVM) of polynomial and radial basis kernel, random forest and rotation forests are used for the classification. The results show that all the proposed time-frequency distributions (TFDs) are able to show the nonstationary variations of sEMG signals. Most of the features exhibit statistically significant difference in the muscle fatigue and nonfatigue conditions. The maximum number of features (66%) is reduced by GA and BPSO for EMBD and BD-TFD respectively. The combination of EMBD- polynomial kernel based SVM is found to be most accurate (91% accuracy) in classifying the conditions with the features selected using GA. The proposed methods are found to be capable of handling the nonstationary and multicomponent variations of sEMG signals recorded in dynamic fatiguing contractions. Particularly, the combination of EMBD- polynomial kernel based SVM could be used to

Fault Diagnosis for Engine Based on Single-Stage Extreme Learning Machine

Directory of Open Access Journals (Sweden)

Fei Gao

2016-01-01

Full Text Available Single-Stage Extreme Learning Machine (SS-ELM is presented to dispose of the mechanical fault diagnosis in this paper. Based on it, the traditional mapping type of extreme learning machine (ELM has been changed and the eigenvectors extracted from signal processing methods are directly regarded as outputs of the network’s hidden layer. Then the uncertainty that training data transformed from the input space to the ELM feature space with the ELM mapping and problem of the selection of the hidden nodes are avoided effectively. The experiment results of diesel engine fault diagnosis show good performance of the SS-ELM algorithm.

Note: The design of thin gap chamber simulation signal source based on field programmable gate array

International Nuclear Information System (INIS)

Hu, Kun; Wang, Xu; Li, Feng; Jin, Ge; Lu, Houbing; Liang, Futian

2015-01-01

The Thin Gap Chamber (TGC) is an important part of ATLAS detector and LHC accelerator. Targeting the feature of the output signal of TGC detector, we have designed a simulation signal source. The core of the design is based on field programmable gate array, randomly outputting 256-channel simulation signals. The signal is generated by true random number generator. The source of randomness originates from the timing jitter in ring oscillators. The experimental results show that the random number is uniform in histogram, and the whole system has high reliability

The novel photon detectors based on MPGD technologies for the upgrade of COMPASS RICH-1

CERN Document Server

Tessarotto, F.; Alexeev, M.; Azevedo, C.D.R.; Birsa, R.; Bradamante, F.; Bressan, A.; Chatterjee, C.; Chiosso, M.; Cicuttin, A.; Ciliberti, P.; Crespo, M.L.; Dalla Torre, S.; Dasgupta, S.S.; Denisov, O.; Finger, M.; Finger Jr., M.; Gobbo, B.; Gregori, M.; Hamar, G.; Levorato, S.; Maggiora, A.; Martin, A.; Menon, G.; Novy, J.; Panzieri, D.; Pereira, F.A.B.; Santos, C.A.; Sbrizzai, G.; Slunecka, M.; Steiger, K.; Steiger, L.; Sulc, M.; Veloso, J.F.C.A.; Zhao,Y.

2018-01-01

The RICH-1 Detector of the COMPASS experiment at CERN SPS has undergone an important upgrade in 2016. Four new photon detectors, based on MPGD technology and covering a total active area larger than 1.2~m2 have replaced the previously used MWPC-based photon detectors. The new detector architecture, resulting from a dedicated, eight years long, R\\&D program, consists in a hybrid MPGD combination of two THGEMs and a Micromegas stage; the first THGEM, coated with a CsI layer, acts as a reflective photocathode. The signals are extracted from the anode pads by capacitive coupling and read-out by analog front-end electronics based on the APV25 chip. The new COMPASS RICH-1 photon detectors are described in detail: the detector design, the engineering aspects, the mass production, and the quality assessment are discussed. The assembly of the MPGD components and the installation of the new detectors are illustrated together with the main aspects of the commissioning. Preliminary indication of performance results a...

Machine assisted histogram classification

Science.gov (United States)

Benyó, B.; Gaspar, C.; Somogyi, P.

2010-04-01

LHCb is one of the four major experiments under completion at the Large Hadron Collider (LHC). Monitoring the quality of the acquired data is important, because it allows the verification of the detector performance. Anomalies, such as missing values or unexpected distributions can be indicators of a malfunctioning detector, resulting in poor data quality. Spotting faulty or ageing components can be either done visually using instruments, such as the LHCb Histogram Presenter, or with the help of automated tools. In order to assist detector experts in handling the vast monitoring information resulting from the sheer size of the detector, we propose a graph based clustering tool combined with machine learning algorithm and demonstrate its use by processing histograms representing 2D hitmaps events. We prove the concept by detecting ion feedback events in the LHCb experiment's RICH subdetector.

Machine assisted histogram classification

Energy Technology Data Exchange (ETDEWEB)

Benyo, B; Somogyi, P [BME-IIT, H-1117 Budapest, Magyar tudosok koerutja 2. (Hungary); Gaspar, C, E-mail: Peter.Somogyi@cern.c [CERN-PH, CH-1211 Geneve 23 (Switzerland)

2010-04-01

LHCb is one of the four major experiments under completion at the Large Hadron Collider (LHC). Monitoring the quality of the acquired data is important, because it allows the verification of the detector performance. Anomalies, such as missing values or unexpected distributions can be indicators of a malfunctioning detector, resulting in poor data quality. Spotting faulty or ageing components can be either done visually using instruments, such as the LHCb Histogram Presenter, or with the help of automated tools. In order to assist detector experts in handling the vast monitoring information resulting from the sheer size of the detector, we propose a graph based clustering tool combined with machine learning algorithm and demonstrate its use by processing histograms representing 2D hitmaps events. We prove the concept by detecting ion feedback events in the LHCb experiment's RICH subdetector.

Machine Fault Detection Based on Filter Bank Similarity Features Using Acoustic and Vibration Analysis

Directory of Open Access Journals (Sweden)

Mauricio Holguín-Londoño

2016-01-01

Full Text Available Vibration and acoustic analysis actively support the nondestructive and noninvasive fault diagnostics of rotating machines at early stages. Nonetheless, the acoustic signal is less used because of its vulnerability to external interferences, hindering an efficient and robust analysis for condition monitoring (CM. This paper presents a novel methodology to characterize different failure signatures from rotating machines using either acoustic or vibration signals. Firstly, the signal is decomposed into several narrow-band spectral components applying different filter bank methods such as empirical mode decomposition, wavelet packet transform, and Fourier-based filtering. Secondly, a feature set is built using a proposed similarity measure termed cumulative spectral density index and used to estimate the mutual statistical dependence between each bandwidth-limited component and the raw signal. Finally, a classification scheme is carried out to distinguish the different types of faults. The methodology is tested in two laboratory experiments, including turbine blade degradation and rolling element bearing faults. The robustness of our approach is validated contaminating the signal with several levels of additive white Gaussian noise, obtaining high-performance outcomes that make the usage of vibration, acoustic, and vibroacoustic measurements in different applications comparable. As a result, the proposed fault detection based on filter bank similarity features is a promising methodology to implement in CM of rotating machinery, even using measurements with low signal-to-noise ratio.

Feature recognition and detection for ancient architecture based on machine vision

Science.gov (United States)

Zou, Zheng; Wang, Niannian; Zhao, Peng; Zhao, Xuefeng

2018-03-01

Ancient architecture has a very high historical and artistic value. The ancient buildings have a wide variety of textures and decorative paintings, which contain a lot of historical meaning. Therefore, the research and statistics work of these different compositional and decorative features play an important role in the subsequent research. However, until recently, the statistics of those components are mainly by artificial method, which consumes a lot of labor and time, inefficiently. At present, as the strong support of big data and GPU accelerated training, machine vision with deep learning as the core has been rapidly developed and widely used in many fields. This paper proposes an idea to recognize and detect the textures, decorations and other features of ancient building based on machine vision. First, classify a large number of surface textures images of ancient building components manually as a set of samples. Then, using the convolution neural network to train the samples in order to get a classification detector. Finally verify its precision.

LHC luminosity upgrade detector challenges

CERN Multimedia

CERN. Geneva; de Roeck, Albert; Bortoletto, Daniela; Wigmans, Richard; Riegler, Werner; Smith, Wesley H

2006-01-01

LHC luminosity upgrade: detector challenges The upgrade of the LHC machine towards higher luminosity (1035 cm -2s-1) has been studied over the last few years. These studies have investigated scenarios to achieve the increase in peak luminosity by an order of magnitude, as well as the physics potential of such an upgrade and the impact of a machine upgrade on the LHC DETECTORS. This series of lectures will cover the following topics: • Physics motivation and machine scenarios for an order of magnitude increase in the LHC peak luminosity (lecture 1) • Detector challenges including overview of ideas for R&D programs by the LHC experiments: tracking and calorimetry, other new detector developments (lectures 2-4) • Electronics, trigger and data acquisition challenges (lecture 5) Note: the much more ambitious LHC energy upgrade will not be covered

Inter-crystal scatter identification for a depth-sensitive detector using support vector machine for small animal positron emission tomography

Energy Technology Data Exchange (ETDEWEB)

Yoshida, Eiji [National Institute of Radiological Sciences, Anagawa 4-9-1 Inage-ku, Chiba-shi, Chiba 263-8555 (Japan)]. E-mail: rush@nirs.go.jp; Kitamura, Keishi [National Institute of Radiological Sciences, Anagawa 4-9-1 Inage-ku, Chiba-shi, Chiba 263-8555 (Japan); Shimadzu Corporation, Nishinokyo Kuwabaracho 1 Nakagyo-ku, Kyoto-shi, Kyoto 604-8511 (Japan); Kimura, Yuichi [Tokyo Metropolitan Institute of Gerontology, Nakamachi 1-1 Itabashi-ku, Tokyo 173-0022 (Japan); Nishikido, Fumihiko [National Institute of Radiological Sciences, Anagawa 4-9-1 Inage-ku, Chiba-shi, Chiba 263-8555 (Japan); Shibuya, Kengo [National Institute of Radiological Sciences, Anagawa 4-9-1 Inage-ku, Chiba-shi, Chiba 263-8555 (Japan); Yamaya, Taiga [National Institute of Radiological Sciences, Anagawa 4-9-1 Inage-ku, Chiba-shi, Chiba 263-8555 (Japan); Murayama, Hideo [National Institute of Radiological Sciences, Anagawa 4-9-1 Inage-ku, Chiba-shi, Chiba 263-8555 (Japan)

2007-02-01

In a conventional positron emission tomography (PET) detector, detected events are projected onto a 2D position histogram by an Anger calculation for crystal identification. However, the measured histogram is affected by inter-crystal scatterings (ICS) which occur in the entire detector. Peaks which are projected for each crystal in the histogram are blurred, and this causes ICS mispositioning. A depth-of-interaction (DOI) detector has been developed for the small animal PET scanner jPET-RD. This DOI detector uses 32x32 crystals with four layers and a 256-channel multi-anode flat panel photomultiplier tube (FP-PMT) which was developed by Hamamatsu Photonics K.K. Each crystal element is 1.45x1.45x4.5 mm{sup 3}. The FP-PMT has a large detective area (49x49 mm{sup 2}) and a small anode pitch (3.04 mm). Therefore, the FP-PMT can extensively trace the behavior of incident {gamma} rays in the crystals including ICS event. We, therefore, propose a novel method for ICS estimation using a statistical pattern recognition algorithm based on a support vector machine (SVM). In this study, we applied the SVM for discriminating photoelectric events from ICS events generated from multiple-anode outputs. The SVM was trained by uniform irradiation events generated from a detector simulator using a Monte Carlo calculation. The success rate for ICS event identification is about 78% for non-training data. The SVM can achieve a true subtraction of ICS events from measured events, and it is also useful for random correction in PET.

Inter-crystal scatter identification for a depth-sensitive detector using support vector machine for small animal positron emission tomography

International Nuclear Information System (INIS)

Yoshida, Eiji; Kitamura, Keishi; Kimura, Yuichi; Nishikido, Fumihiko; Shibuya, Kengo; Yamaya, Taiga; Murayama, Hideo

2007-01-01

In a conventional positron emission tomography (PET) detector, detected events are projected onto a 2D position histogram by an Anger calculation for crystal identification. However, the measured histogram is affected by inter-crystal scatterings (ICS) which occur in the entire detector. Peaks which are projected for each crystal in the histogram are blurred, and this causes ICS mispositioning. A depth-of-interaction (DOI) detector has been developed for the small animal PET scanner jPET-RD. This DOI detector uses 32x32 crystals with four layers and a 256-channel multi-anode flat panel photomultiplier tube (FP-PMT) which was developed by Hamamatsu Photonics K.K. Each crystal element is 1.45x1.45x4.5 mm 3 . The FP-PMT has a large detective area (49x49 mm 2 ) and a small anode pitch (3.04 mm). Therefore, the FP-PMT can extensively trace the behavior of incident γ rays in the crystals including ICS event. We, therefore, propose a novel method for ICS estimation using a statistical pattern recognition algorithm based on a support vector machine (SVM). In this study, we applied the SVM for discriminating photoelectric events from ICS events generated from multiple-anode outputs. The SVM was trained by uniform irradiation events generated from a detector simulator using a Monte Carlo calculation. The success rate for ICS event identification is about 78% for non-training data. The SVM can achieve a true subtraction of ICS events from measured events, and it is also useful for random correction in PET

Classification of EEG signals using a genetic-based machine learning classifier.

Science.gov (United States)

Skinner, B T; Nguyen, H T; Liu, D K

2007-01-01

This paper investigates the efficacy of the genetic-based learning classifier system XCS, for the classification of noisy, artefact-inclusive human electroencephalogram (EEG) signals represented using large condition strings (108bits). EEG signals from three participants were recorded while they performed four mental tasks designed to elicit hemispheric responses. Autoregressive (AR) models and Fast Fourier Transform (FFT) methods were used to form feature vectors with which mental tasks can be discriminated. XCS achieved a maximum classification accuracy of 99.3% and a best average of 88.9%. The relative classification performance of XCS was then compared against four non-evolutionary classifier systems originating from different learning techniques. The experimental results will be used as part of our larger research effort investigating the feasibility of using EEG signals as an interface to allow paralysed persons to control a powered wheelchair or other devices.

Electronic noise of superconducting tunnel junction detectors

International Nuclear Information System (INIS)

Jochum, J.; Kraus, H.; Gutsche, M.; Kemmather, B.; Feilitzsch, F. v.; Moessbauer, R.L.

1994-01-01

The optimal signal to noise ratio for detectors based on superconducting tunnel junctions is calculated and compared for the cases of a detector consisting of one single tunnel junction, as well as of series and of parallel connections of such tunnel junctions. The influence of 1 / f noise and its dependence on the dynamical resistance of tunnel junctions is discussed quantitatively. A single tunnel junction yields the minimum equivalent noise charge. Such a tunnel junction exhibits the best signal to noise ratio if the signal charge is independent of detector size. In case, signal charge increases with detector size, a parallel or a series connection of tunnel junctions would provide the optimum signal to noise ratio. The equivalent noise charge and the respective signal to noise ratio are deduced as functions of tunnel junction parameters such as tunneling time, quasiparticle lifetime, etc. (orig.)

Automated valve fault detection based on acoustic emission parameters and support vector machine

Directory of Open Access Journals (Sweden)

Salah M. Ali

2018-03-01

Full Text Available Reciprocating compressors are one of the most used types of compressors with wide applications in industry. The most common failure in reciprocating compressors is always related to the valves. Therefore, a reliable condition monitoring method is required to avoid the unplanned shutdown in this category of machines. Acoustic emission (AE technique is one of the effective recent methods in the field of valve condition monitoring. However, a major challenge is related to the analysis of AE signal which perhaps only depends on the experience and knowledge of technicians. This paper proposes automated fault detection method using support vector machine (SVM and AE parameters in an attempt to reduce human intervention in the process. Experiments were conducted on a single stage reciprocating air compressor by combining healthy and faulty valve conditions to acquire the AE signals. Valve functioning was identified through AE waveform analysis. SVM faults detection model was subsequently devised and validated based on training and testing samples respectively. The results demonstrated automatic valve fault detection model with accuracy exceeding 98%. It is believed that valve faults can be detected efficiently without human intervention by employing the proposed model for a single stage reciprocating compressor. Keywords: Condition monitoring, Faults detection, Signal analysis, Acoustic emission, Support vector machine

Man machine interface based on speech recognition

International Nuclear Information System (INIS)

Jorge, Carlos A.F.; Aghina, Mauricio A.C.; Mol, Antonio C.A.; Pereira, Claudio M.N.A.

2007-01-01

This work reports the development of a Man Machine Interface based on speech recognition. The system must recognize spoken commands, and execute the desired tasks, without manual interventions of operators. The range of applications goes from the execution of commands in an industrial plant's control room, to navigation and interaction in virtual environments. Results are reported for isolated word recognition, the isolated words corresponding to the spoken commands. For the pre-processing stage, relevant parameters are extracted from the speech signals, using the cepstral analysis technique, that are used for isolated word recognition, and corresponds to the inputs of an artificial neural network, that performs recognition tasks. (author)

Microcomputer-based instrument for the detection and analysis of precession motion in a gas centrifuge machine

International Nuclear Information System (INIS)

Paulus, S.S.

1986-03-01

The Centrifuge Precession Analyzer (CPA) is a microcomputer-based instrument which detects precession motion in a gas centrifuge machine and calculates the amplitude and frequency of precession. The CPA consists of a printed circuit board which contains signal-conditioning circuitry and a 24-bit counter and an INTEL iSBC 80-/24 single-board computer. Precession motion is detected by monitoring a signal generated by a variable reluctance pick-up coil in the top of the centrifuge machine. This signal is called a Fidler signal. The initial Fidler signal triggers a counter which is clocked by a high-precision, 20.000000-MHz, temperature-controlled, crystal oscillator. The contents of the counter are read by the computer, and the counter reset after every ten Fidler signals. The speed of the centrifuge machine and the amplitude and frequency of precession are calculated, and the results are displayed on a liquid crystal display on the front panel of the CPA. The thesis contains results from data generated by a Fidler signal simulator and data taken when the centrifuge was operated under three test conditions: (1) nitrogen gas during drive-up, steady state, and drive-down, (2) xenon gas during slip test, steady state, and the addition of gas, and (3) no gas during steady state. The qualitative results were consistent with experience with centrifuge machines UF 6 in that the amplitude of precession increased and the frequency of precession decreased during drive-up, drive-down and the slip check. The magnitude of the amplitude and frequency of precession were proportional to the molecular weight of the gases in steady state

A Novel Bearing Fault Diagnosis Method Based on Gaussian Restricted Boltzmann Machine

Directory of Open Access Journals (Sweden)

Xiao-hui He

2016-01-01

Full Text Available To realize the fault diagnosis of bearing effectively, this paper presents a novel bearing fault diagnosis method based on Gaussian restricted Boltzmann machine (Gaussian RBM. Vibration signals are firstly resampled to the same equivalent speed. Subsequently, the envelope spectrums of the resampled data are used directly as the feature vectors to represent the fault types of bearing. Finally, in order to deal with the high-dimensional feature vectors based on envelope spectrum, a classifier model based on Gaussian RBM is applied. Gaussian RBM has the ability to provide a closed-form representation of the distribution underlying the training data, and it is very convenient for modeling high-dimensional real-valued data. Experiments on 10 different data sets verify the performance of the proposed method. The superiority of Gaussian RBM classifier is also confirmed by comparing with other classifiers, such as extreme learning machine, support vector machine, and deep belief network. The robustness of the proposed method is also studied in this paper. It can be concluded that the proposed method can realize the bearing fault diagnosis accurately and effectively.

A Performance Survey on Stack-based and Register-based Virtual Machines

OpenAIRE

Fang, Ruijie; Liu, Siqi

2016-01-01

Virtual machines have been widely adapted for high-level programming language implementations and for providing a degree of platform neutrality. As the overall use and adaptation of virtual machines grow, the overall performance of virtual machines has become a widely-discussed topic. In this paper, we present a survey on the performance differences of the two most widely adapted types of virtual machines - the stack-based virtual machine and the register-based virtual machine - using various...

LHCb: Machine assisted histogram classification

CERN Multimedia

Somogyi, P; Gaspar, C

2009-01-01

LHCb is one of the four major experiments under completion at the Large Hadron Collider (LHC). Monitoring the quality of the acquired data is important, because it allows the verification of the detector performance. Anomalies, such as missing values or unexpected distributions can be indicators of a malfunctioning detector, resulting in poor data quality. Spotting faulty components can be either done visually using instruments such as the LHCb Histogram Presenter, or by automated tools. In order to assist detector experts in handling the vast monitoring information resulting from the sheer size of the detector, a graph-theoretic based clustering tool, combined with machine learning algorithms is proposed and demonstrated by processing histograms representing 2D event hitmaps. The concept is proven by detecting ion feedback events in the LHCb RICH subdetector.

Acquisition System and Detector Interface for Power Pulsed Detectors

CERN Document Server

Cornat, R

2012-01-01

A common DAQ system is being developed within the CALICE collaboration. It provides a flexible and scalable architecture based on giga-ethernet and 8b/10b serial links in order to transmit either slow control data, fast signals or read out data. A detector interface (DIF) is used to connect detectors to the DAQ system based on a single firmware shared among the collaboration but targeted on various physical implementations. The DIF allows to build, store and queue packets of data as well as to control the detectors providing USB and serial link connectivity. The overall architecture is foreseen to manage several hundreds of thousands channels.

Improving the spatial resolution in CZT detectors using charge sharing effect and transient signal analysis: Simulation study

Energy Technology Data Exchange (ETDEWEB)

Zheng, Xiaoqing; Cheng, Zeng [Department of Electrical and Computer Engineering, McMaster University (Canada); Deen, M. Jamal, E-mail: jamal@mcmaster.ca [Department of Electrical and Computer Engineering, McMaster University (Canada); School of Biomedical Engineering, McMaster University (Canada); Peng, Hao, E-mail: penghao@mcmaster.ca [Department of Electrical and Computer Engineering, McMaster University (Canada); School of Biomedical Engineering, McMaster University (Canada); Department of Medical Physics, McMaster University, Ontario L8S 4K1, Hamilton (Canada)

2016-02-01

Cadmium Zinc Telluride (CZT) semiconductor detectors are capable of providing superior energy resolution and three-dimensional position information of gamma ray interactions in a large variety of fields, including nuclear physics, gamma-ray imaging and nuclear medicine. Some dedicated Positron Emission Tomography (PET) systems, for example, for breast cancer detection, require higher contrast recovery and more accurate event location compared with a whole-body PET system. The spatial resolution is currently limited by electrode pitch in CZT detectors. A straightforward approach to increase the spatial resolution is by decreasing the detector electrode pitch, but this leads to higher fabrication cost and a larger number of readout channels. In addition, inter-electrode charge spreading can negate any improvement in spatial resolution. In this work, we studied the feasibility of achieving sub-pitch spatial resolution in CZT detectors using two methods: charge sharing effect and transient signal analysis. We noted that their valid ranges of usage were complementary. The dependences of their corresponding valid ranges on electrode design, depth-of-interaction (DOI), voltage bias and signal triggering threshold were investigated. The implementation of these two methods in both pixelated and cross-strip configuration of CZT detectors were discussed. Our results show that the valid range of charge sharing effect increases as a function of DOI, but decreases with increasing gap width and bias voltage. For a CZT detector of 5 mm thickness, 100 µm gap and biased at 400 V, the valid range of charge sharing effect was found to be about 112.3 µm around the gap center. This result complements the valid range of the transient signal analysis within one electrode pitch. For a signal-to-noise ratio (SNR) of ~17 and preliminary measurements, the sub-pitch spatial resolution is expected to be ~30 µm and ~250 µm for the charge sharing and transient signal analysis methods

On a Three-Channel Cosmic Ray Detector based on Aluminum Blocks

Science.gov (United States)

Arceo, L.; Félix, J.

2017-10-01

There are many general purpose cosmic ray detectors based on plastic scintillators and electronic boards from the market. This is a new cosmic ray detector designed on three 2.54 cm × 5.08 cm × 20.32 cm Aluminum blocks in stack arrangement, and three Hamamatsu S12572-100P photodiodes. The photodiode board, the passive electronic board, and the discriminator board are own designed. The electronic signals are stored with a CompactRIO -cRIO- by National Instruments. It is presented the design, the construction, the data acquisition system algorithm, and the preliminary physical results.

Thermoluminescent signal fading of encapsulated lif: Mg,Ti detectors in PTFE-Teflon registered trademark

International Nuclear Information System (INIS)

Sasho Nikolovski, Sasho; Nikolovska, Lidija; Velevska, Marija; Velev, Velko

2010-01-01

Fading is a process when the latent information of a detector is unintentionally lost mainly due to the thermal influence. Thermoluminescent (TL) detectors have different sensitivities as far as the fading effect. Encapsulated TL detectors mounted within shielded filter holders are used during the personal monitoring of occupationally exposed persons in R. Macedonia. PTFE-Teflon registered trademark polymer is an example of encapsulation material that has a temperature resistance and it allows the luminescence signal to pass through. Since the encapsulated TL detectors cannot be submitted to annealing treatment in an oven, another fading reduction method is needed. The TL evaluation method suggested in this work is based on a specific glow-curve region. Irradiations were conducted using 90Sr/90Y source. Post-irradiation fade investigations were conducted for evaluation periods that varied up to 4 months. Two areas of the TL glow-curve were selected with the WimRems software. They correspond to the high and the low fading emission peaks (the lower temperature peaks display a greater degree of thermal fading than the higher temperature peaks). Post-irradiation fade is a contributing factor that affects the response of a thermoluminescent (TL) phosphor as a function of time. PTFE - Polytetrafluoroethylene most well known by the DuPont brand name Teflon registered trademark. (Author)

How the machine learning conquers reconstruction in neutrino experiments

CERN Multimedia

CERN. Geneva

2017-01-01

An evolution from the purely algorithmic approaches towards the machine learning solutions started a few years ago in the neutrino experiments. Now, this process turns into a true boom, especially in the experiments based on the imaging technologies, such as LArTPC’s used in MicroBooNE and DUNE experiments or liquid scintillator detector implemented by the NOvA Collaboration. High resolution, image-like projections of events obtained with these detectors proved to be hard pattern recognition problems for the conventional reconstruction techniques. In the seminar, I will present why the neutrino events are so challenging and how the essential difficulties are now being attacked with the machine learning.

A Multilayer Perceptron-Based Impulsive Noise Detector with Application to Power-Line-Based Sensor Networks

KAUST Repository

Chien, Ying-Ren

2018-04-10

For power-line-based sensor networks, impulsive noise (IN) will dramatically degrade the data transmission rate in the power line. In this paper, we present a multilayer perceptron (MLP)-based approach to detect IN in orthogonal frequency-division multiplexing (OFDM)-based baseband power line communications (PLCs). Combining the MLP-based IN detection method with the outlier detection theory allows more accurate identification of the harmful residual IN. For OFDM-based PLC systems, the high peak-to-average power ratio (PAPR) of the received signal makes detection of harmful residual IN more challenging. The detection mechanism works in an iterative receiver that contains a pre-IN mitigation and a post-IN mitigation. The pre-IN mitigation is meant to null the stronger portion of IN, while the post-IN mitigation suppresses the residual portion of IN using an iterative process. Compared with previously reported IN detectors, the simulation results show that our MLP-based IN detector improves the resulting bit error rate (BER) performance.

X-ray light valve (XLV): a novel detectors' technology for digital mammography

Science.gov (United States)

Marcovici, Sorin; Sukhovatkin, Vlad; Oakham, Peter

2014-03-01

A novel method, based on X-ray Light Valve (XLV) technology, is proposed for making good image quality yet inexpensive flat panel detectors for digital mammography. The digital mammography markets, particularly in the developing countries, demand quality machines at substantially lower prices than the ones available today. Continuous pressure is applied on x-ray detectors' manufacturers to reduce the flat panel detectors' prices. XLV presents a unique opportunity to achieve the needed price - performance characteristics for direct conversion, x-ray detectors. The XLV based detectors combine the proven, superior, spatial resolution of a-Se with the simplicity and low cost of liquid crystals and optical scanning. The x-ray quanta absorbed by a 200 μm a-Se produce electron - hole pairs that move under an electric field to the top and bottom of a-Se layer. This 2D charge distribution creates at the interface with the liquid crystals a continuous (analog) charge image corresponding to the impinging radiation's information. Under the influence of local electrical charges next to them, the liquid crystals twist proportionally to the charges and vary their light reflectivity. A scanning light source illuminates the liquid crystals while an associated, pixilated photo-detector, having a 42 μm pixel size, captures the light reflected by the liquid crystals and converts it in16 bit words that are transmitted to the machine for image processing and display. The paper will describe a novel XLV, 25 cm x 30 cm, flat panel detector structure and its underlying physics as well as its preliminary performance measured on several engineering prototypes. In particular, the paper will present the results of measuring XLV detectors' DQE, MTF, dynamic range, low contrast resolution and dynamic behavior. Finally, the paper will introduce the new, low cost, XLV detector based, digital mammography machine under development at XLV Diagnostics Inc.

Signal-Conditioning Block of a 1 × 200 CMOS Detector Array for a Terahertz Real-Time Imaging System

Directory of Open Access Journals (Sweden)

Jong-Ryul Yang

2016-03-01

Full Text Available A signal conditioning block of a 1 × 200 Complementary Metal-Oxide-Semiconductor (CMOS detector array is proposed to be employed with a real-time 0.2 THz imaging system for inspecting large areas. The plasmonic CMOS detector array whose pixel size including an integrated antenna is comparable to the wavelength of the THz wave for the imaging system, inevitably carries wide pixel-to-pixel variation. To make the variant outputs from the array uniform, the proposed signal conditioning block calibrates the responsivity of each pixel by controlling the gate bias of each detector and the voltage gain of the lock-in amplifiers in the block. The gate bias of each detector is modulated to 1 MHz to improve the signal-to-noise ratio of the imaging system via the electrical modulation by the conditioning block. In addition, direct current (DC offsets of the detectors in the array are cancelled by initializing the output voltage level from the block. Real-time imaging using the proposed signal conditioning block is demonstrated by obtaining images at the rate of 19.2 frame-per-sec of an object moving on the conveyor belt with a scan width of 20 cm and a scan speed of 25 cm/s.

Calculated WIMP signals at the ANDES laboratory: comparison with northern and southern located dark matter detectors

Science.gov (United States)

Civitarese, O.; Fushimi, K. J.; Mosquera, M. E.

2016-12-01

Weakly interacting massive particles (WIMPs) are possible components of the Universe’s dark matter (DM). The detection of WIMPs is signaled by the recoil of the atomic nuclei which form a detector. CoGeNT at the Soudan Underground Laboratory (SUL) and DAMA at the Laboratori Nazionali del Gran Sasso (LNGS) have reported data on annual modulation of signals attributed to WIMPs. Both experiments are located in laboratories in the Northern Hemisphere. DM detectors are planned to operate (or already operate) in laboratories in the Southern Hemisphere, including SABRE at Stawell Underground Physics Laboratory (SUPL) in Australia, and DM-ICE in Antarctica. In this work we have analyzed the dependence of diurnal and annual modulation of signals, pertaining to the detection of WIMP, on the coordinates of the laboratory, for experiments which may be performed in the planned new Agua Negra Deep Experimental Site (ANDES) underground facility, to be built in San Juan, Argentina. We made predictions for NaI and Ge-type detectors placed in ANDES, to compare with DAMA, CoGeNT, SABRE and DM-ICE arrays, and found that the diurnal modulation of the signals, at the ANDES site, is amplified at its maximum value, both for NaI (Ge)-type detectors, while the annual modulation remains unaffected by the change in coordinates from north to south.

Calculated WIMP signals at the ANDES laboratory: comparison with northern and southern located dark matter detectors

International Nuclear Information System (INIS)

Civitarese, O; Mosquera, M E; Fushimi, K J

2016-01-01

Weakly interacting massive particles (WIMPs) are possible components of the Universe’s dark matter (DM). The detection of WIMPs is signaled by the recoil of the atomic nuclei which form a detector. CoGeNT at the Soudan Underground Laboratory (SUL) and DAMA at the Laboratori Nazionali del Gran Sasso (LNGS) have reported data on annual modulation of signals attributed to WIMPs. Both experiments are located in laboratories in the Northern Hemisphere. DM detectors are planned to operate (or already operate) in laboratories in the Southern Hemisphere, including SABRE at Stawell Underground Physics Laboratory (SUPL) in Australia, and DM-ICE in Antarctica. In this work we have analyzed the dependence of diurnal and annual modulation of signals, pertaining to the detection of WIMP, on the coordinates of the laboratory, for experiments which may be performed in the planned new Agua Negra Deep Experimental Site (ANDES) underground facility, to be built in San Juan, Argentina. We made predictions for NaI and Ge-type detectors placed in ANDES, to compare with DAMA, CoGeNT, SABRE and DM-ICE arrays, and found that the diurnal modulation of the signals, at the ANDES site, is amplified at its maximum value, both for NaI (Ge)-type detectors, while the annual modulation remains unaffected by the change in coordinates from north to south. (paper)

Intelligent Automatic Right-Left Sign Lamp Based on Brain Signal Recognition System

Science.gov (United States)

Winda, A.; Sofyan; Sthevany; Vincent, R. S.

2017-12-01

Comfort as a part of the human factor, plays important roles in nowadays advanced automotive technology. Many of the current technologies go in the direction of automotive driver assistance features. However, many of the driver assistance features still require physical movement by human to enable the features. In this work, the proposed method is used in order to make certain feature to be functioning without any physical movement, instead human just need to think about it in their mind. In this work, brain signal is recorded and processed in order to be used as input to the recognition system. Right-Left sign lamp based on the brain signal recognition system can potentially replace the button or switch of the specific device in order to make the lamp work. The system then will decide whether the signal is ‘Right’ or ‘Left’. The decision of the Right-Left side of brain signal recognition will be sent to a processing board in order to activate the automotive relay, which will be used to activate the sign lamp. Furthermore, the intelligent system approach is used to develop authorized model based on the brain signal. Particularly Support Vector Machines (SVMs)-based classification system is used in the proposed system to recognize the Left-Right of the brain signal. Experimental results confirm the effectiveness of the proposed intelligent Automatic brain signal-based Right-Left sign lamp access control system. The signal is processed by Linear Prediction Coefficient (LPC) and Support Vector Machines (SVMs), and the resulting experiment shows the training and testing accuracy of 100% and 80%, respectively.

Current signal of silicon detectors facing charged particles and heavy ions; Reponse en courant des detecteurs silicium aux particules chargees et aux ions lourds

Energy Technology Data Exchange (ETDEWEB)

Hamrita, H

2005-07-01

This work consisted in collecting and studying for the first time the shapes of current signals obtained from charged particles or heavy ions produced by silicon detectors. The document is divided into two main parts. The first consisted in reducing the experimental data obtained with charged particles as well as with heavy ions. These experiments were performed at the Orsay Tandem and at GANIL using LISE. These two experiments enabled us to create a data base formed of current signals with various shapes and various times of collection. The second part consisted in carrying out a simulation of the current signals obtained from the various ions. To obtain this simulation we propose a new model describing the formation of the signal. We used the data base of the signals obtained in experiments in order to constrain the three parameters of our model. In this model, the charge carriers created are regarded as dipoles and their density is related to the dielectric polarization in the silicon detector. This phenomenon induces an increase in permittivity throughout the range of the incident ion and consequently the electric field between the electrodes of the detector is decreased inside the trace. We coupled with this phenomenon a dissociation and extraction mode of the charge carriers so that they can be moved in the electric field. (author)

Functional Requirements on the Design of the Detectors and the Interaction Region of an e+e- Linear Collider with a Push-Pull Arrangement of Detectors

International Nuclear Information System (INIS)

Markiewicz, T.

2009-01-01

The Interaction Region of the International Linear Collider is based on two experimental detectors working in a push-pull mode. A time efficient implementation of this model sets specific requirements and challenges for many detector and machine systems, in particular the IR magnets, the cryogenics and the alignment system, the beamline shielding, the detector design and the overall integration. This paper attempts to separate the functional requirements of a push pull interaction region and machine detector interface from any particular conceptual or technical solution that might have been proposed to date by either the ILC Beam Delivery Group or any of the three detector concepts. As such, we hope that it provides a set of ground rules for interpreting and evaluating the MDI parts of the proposed detector concept's Letters of Intent, due March 2009. The authors of the present paper are the leaders of the IR Integration Working Group within Global Design Effort Beam Delivery System and the representatives from each detector concept submitting the Letters Of Intent.

Signal encoding method for a time-of-flight PET detector using a silicon photomultiplier array

Science.gov (United States)

Kwon, Sun Il; Lee, Jae Sung

2014-10-01

The silicon photomultiplier (SiPM) is a promising photosensor for magnetic resonance (MR) compatible time-of-flight (TOF) positron emission tomography (PET) scanners. The compact size of the SiPM allows direct one-to-one coupling between the scintillation crystal and the photosensor, yielding better timing and energy resolutions than the light sharing methods that have to be used in photomultiplier tube (PMT) PET systems. However, the one-to-one coupling scheme requires a huge volume of readout and processing electronics if no electric signal multiplexing or encoding scheme is properly applied. In this paper, we develop an electric signal encoding scheme for SiPM array based TOF PET detector blocks with the aim of reducing the complexity and volume of the signal readout and processing electronics. In an M×N SiPM array, the output signal of each channel in the SiPM array is divided into two signal lines. These output lines are then tied together in row and column lines. The row and column signals are used to measure the energy and timing information (or vice versa) of each incident gamma-ray event, respectively. Each SiPM channel was directly coupled to a 3×3×20 mm3 LGSO crystal. The reference detector, which was used to measure timing, consisted of an R9800 PMT and a 4×4×10 mm3 LYSO crystal and had a single time resolution of ~200 ps (FWHM). Leading edge discriminators were used to determine coincident events. Dedicated front-end electronics were developed, and the timing and energy resolutions of SiPM arrays with different array sizes (4×4, 8×8, and 12×12) were compared. Breakdown voltage of each SiPM channel was measured using energy spectra within various bias voltages. Coincidence events were measured using a 22Na point source. The average coincidence time resolution of 4×4, 8×8, and 12×12 SiPM arrays were 316 ps, 320 ps, and 335 ps (FWHM), respectively. The energy resolution of 4×4, 8×8, and 12×12 SiPM arrays were 11.8%, 12.5%, and 12.8% (FWHM

Machine function based control code algebras

NARCIS (Netherlands)

Bergstra, J.A.

Machine functions have been introduced by Earley and Sturgis in [6] in order to provide a mathematical foundation of the use of the T-diagrams proposed by Bratman in [5]. Machine functions describe the operation of a machine at a very abstract level. A theory of hardware and software based on

Numerical Investigation on Electron and Ion Transmission of GEM-based Detectors

Directory of Open Access Journals (Sweden)

Bhattacharya Purba

2018-01-01

Full Text Available ALICE at the LHC is planning a major upgrade of its detector systems, including the TPC, to cope with an increase of the LHC luminosity after 2018. Different R&D activities are currently concentrated on the adoption of the Gas Electron Multiplier (GEM as the gas amplification stage of the ALICE-TPC upgrade version. The major challenge is to have low ion feedback in the drift volume as well as to ensure a collection of good percentage of primary electrons in the signal generation process. In the present work, Garfield simulation framework has been adopted to numerically estimate the electron transparency and ion backflow fraction of GEM-based detectors. In this process, extensive simulations have been carried out to enrich our understanding of the complex physical processes occurring within single, triple and quadruple GEM detectors. A detailed study has been performed to observe the effect of detector geometry, field configuration and magnetic field on the above mentioned characteristics.

Numerical Investigation on Electron and Ion Transmission of GEM-based Detectors

Science.gov (United States)

Bhattacharya, Purba; Sahoo, Sumanya Sekhar; Biswas, Saikat; Mohanty, Bedangadas; Majumdar, Nayana; Mukhopadhyay, Supratik

2018-02-01

ALICE at the LHC is planning a major upgrade of its detector systems, including the TPC, to cope with an increase of the LHC luminosity after 2018. Different R&D activities are currently concentrated on the adoption of the Gas Electron Multiplier (GEM) as the gas amplification stage of the ALICE-TPC upgrade version. The major challenge is to have low ion feedback in the drift volume as well as to ensure a collection of good percentage of primary electrons in the signal generation process. In the present work, Garfield simulation framework has been adopted to numerically estimate the electron transparency and ion backflow fraction of GEM-based detectors. In this process, extensive simulations have been carried out to enrich our understanding of the complex physical processes occurring within single, triple and quadruple GEM detectors. A detailed study has been performed to observe the effect of detector geometry, field configuration and magnetic field on the above mentioned characteristics.

Inspection of four-sensor falls detector

Directory of Open Access Journals (Sweden)

Bartłomiej Wójtowicz

2015-06-01

Full Text Available The studies presented in this article are the continuation of previous work to develop a mobile fall detector. The algorithm is based on a discrete wavelet transform of the signals from the sensors available at the detector and a linear support vector machine as a classifier. Fisher score method is used for feature selection in the proposed algorithm. As a result of reducing the number of features, the number of support vectors has been also reduced — it has a direct impact on the upper estimate of the classification error. On the basis of the obtained results, the classifier parameters have been calculated. This allows presenting the developed concept in the field of ROCROCROC curves (Receiver Operating Characteristics and their comparison with the results obtained for individual sensors. The developed concept gives much better results than each of the sensors acting independently. The findings of this study have given very good results in comparison with the previous findings, with a significant reduction in the number of required features. Due to the close relationship between the number of training data and the number of support vectors which directly affect the upper estimate of the classification error, the number of features has been reduced. Finally, satisfactory results have been obtained with the reduction of the number of features from 38 to just six, ensuring that the upper estimation of the classification error in the set of the new test data does not exceed 5.3%.[b]Keywords[/b]: falls detection, data fusion, discrete wavelet transform, support vector machine

Biologically based machine vision: signal analysis of monopolar cells in the visual system of Musca domestica.

Science.gov (United States)

Newton, Jenny; Barrett, Steven F; Wilcox, Michael J; Popp, Stephanie

2002-01-01

Machine vision for navigational purposes is a rapidly growing field. Many abilities such as object recognition and target tracking rely on vision. Autonomous vehicles must be able to navigate in dynamic enviroments and simultaneously locate a target position. Traditional machine vision often fails to react in real time because of large computational requirements whereas the fly achieves complex orientation and navigation with a relatively small and simple brain. Understanding how the fly extracts visual information and how neurons encode and process information could lead us to a new approach for machine vision applications. Photoreceptors in the Musca domestica eye that share the same spatial information converge into a structure called the cartridge. The cartridge consists of the photoreceptor axon terminals and monopolar cells L1, L2, and L4. It is thought that L1 and L2 cells encode edge related information relative to a single cartridge. These cells are thought to be equivalent to vertebrate bipolar cells, producing contrast enhancement and reduction of information sent to L4. Monopolar cell L4 is thought to perform image segmentation on the information input from L1 and L2 and also enhance edge detection. A mesh of interconnected L4's would correlate the output from L1 and L2 cells of adjacent cartridges and provide a parallel network for segmenting an object's edges. The focus of this research is to excite photoreceptors of the common housefly, Musca domestica, with different visual patterns. The electrical response of monopolar cells L1, L2, and L4 will be recorded using intracellular recording techniques. Signal analysis will determine the neurocircuitry to detect and segment images.

Characterization of LiF-based soft X-ray imaging detectors by confocal fluorescence microscopy

International Nuclear Information System (INIS)

Bonfigli, F; Gaudio, P; Lupelli, I; Nichelatti, E; Richetta, M; Vincenti, M A; Montereali, R M

2010-01-01

X-ray microscopy represents a powerful tool to obtain images of samples with very high spatial resolution. The main limitation of this technique is represented by the poor spatial resolution of standard imaging detectors. We proposed an innovative high-performance X-ray imaging detector based on the visible photoluminescence of colour centres in lithium fluoride. In this work, a confocal microscope in fluorescence mode was used to characterize LiF-based imaging detectors measuring CC integrated visible fluorescence signals of LiF crystals and films (grown on several kinds of substrates) irradiated by soft X-rays produced by a laser plasma source in different exposure conditions. The results are compared with the CC photoluminescence spectra measured on the same samples and discussed.

Cherenkov Detector for Beam Quality Measurement

CERN Document Server

AUTHOR|(CDS)2078842

2016-01-01

A new detector to measure the machine induced background at larger radiihas been developed and installed in the CMS experiment at LHC. Itconsists of 40 modules, each comprising a quartz bar read out by aphotomultiplier. Since Cerenkov radiation is emitted in a forward conearound the charged particle trajectory, these detectors can distinguishthe directions of the machine induced background.The back-end consists of a microTCA readout with excellent time resolution.The performance of the detector modules measured in several test-beamcampaigns will be reported. The installation in CMS will be described, andfirst results about operating the detector during data taking will begiven.

Boiling detection using signals of self-powered neutron detectors and thermocouples

International Nuclear Information System (INIS)

Kozma, R.

1989-01-01

A specially-equipped simulated fuel assembly has been placed into the core of the 2 MW research reactor of the IRI, Delft. In this paper the recent results concerning the detection of coolant boiling in the simulated fuel assembly are introduced. Applying the theory of boiling temperature noise, different stages of boiling, i.e. one-phase flow, subcooled boiling, volume boiling, were identified in the measurements using the low-frequency noise components of the thermocouple signals. It has been ascertained that neutron noise spectra remained unchanged when subcooled boiling appeared, and that they changed reasonably only when developed volume boiling took place in the channels. At certain neutron detector positions neutron spectra did not vary at all, although developed volume boiling occurred at a distance of 3-4 cm from these neutron detectors. This phenomenon was applied in studying the field-of-view of neutron detectors

Research on bearing life prediction based on support vector machine and its application

International Nuclear Information System (INIS)

Sun Chuang; Zhang Zhousuo; He Zhengjia

2011-01-01

Life prediction of rolling element bearing is the urgent demand in engineering practice, and the effective life prediction technique is beneficial to predictive maintenance. Support vector machine (SVM) is a novel machine learning method based on statistical learning theory, and is of advantage in prediction. This paper develops SVM-based model for bearing life prediction. The inputs of the model are features of bearing vibration signal and the output is the bearing running time-bearing failure time ratio. The model is built base on a few failed bearing data, and it can fuse information of the predicted bearing. So it is of advantage to bearing life prediction in practice. The model is applied to life prediction of a bearing, and the result shows the proposed model is of high precision.

Quantative Evaluation of the Efficiency of Facial Bio-potential Signals Based on Forehead Three-Channel Electrode Placement For Facial Gesture Recognition Applicable in a Human-Machine Interface

Directory of Open Access Journals (Sweden)

Iman Mohammad Rezazadeh

2010-06-01

Full Text Available Introduction: Today, facial bio-potential signals are employed in many human-machine interface applications for enhancing and empowering the rehabilitation process. The main point to achieve that goal is to record appropriate bioelectric signals from the human face by placing and configuring electrodes over it in the right way. In this paper, heuristic geometrical position and configuration of the electrodes has been proposed for improving the quality of the acquired signals and consequently enhancing the performance of the facial gesture classifier. Materials and Methods: Investigation and evaluation of the electrodes' proper geometrical position and configuration can be performed using two methods: clinical and modeling. In the clinical method, the electrodes are placed in predefined positions and the elicited signals from them are then processed. The performance of the method is evaluated based on the results obtained. On the other hand, in the modeling approach, the quality of the recorded signals and their information content are evaluated only by modeling and simulation. In this paper, both methods have been utilized together. First, suitable electrode positions and configuration were proposed and evaluated by modeling and simulation. Then, the experiment was performed with a predefined protocol on 7 healthy subjects to validate the simulation results. Here, the recorded signals were passed through parallel butterworth filter banks to obtain facial EMG, EOG and EEG signals and the RMS features of each 256 msec time slot were extracted.  By using the power of Subtractive Fuzzy C-Mean (SFCM, 8 different facial gestures (including smiling, frowning, pulling up left and right lip corners, left/right/up and down movements of the eyes were discriminated. Results: According to the three-channel electrode configuration derived from modeling of the dipoles effects on the surface electrodes and by employing the SFCM classifier, an average 94

A High Density Low Cost Digital Signal Processing Module for Large Scale Radiation Detectors

International Nuclear Information System (INIS)

Tan, Hui; Hennig, Wolfgang; Walby, Mark D.; Breus, Dimitry; Harris, Jackson T.; Grudberg, Peter M.; Warburton, William K.

2013-06-01

A 32-channel digital spectrometer PIXIE-32 is being developed for nuclear physics or other radiation detection applications requiring digital signal processing with large number of channels at relatively low cost. A single PIXIE-32 provides spectrometry and waveform acquisition for 32 input signals per module whereas multiple modules can be combined into larger systems. It is based on the PCI Express standard which allows data transfer rates to the host computer of up to 800 MB/s. Each of the 32 channels in a PIXIE-32 module accepts signals directly from a detector preamplifier or photomultiplier. Digitally controlled offsets can be individually adjusted for each channel. Signals are digitized in 12-bit, 50 MHz multi-channel ADCs. Triggering, pile-up inspection and filtering of the data stream are performed in real time, and pulse heights and other event data are calculated on an event-by event basis. The hardware architecture, internal and external triggering features, and the spectrometry and waveform acquisition capability of the PIXIE- 32 as well as its capability to distribute clock and triggers among multiple modules, are presented. (authors)

Recent Developments in GEM-Based Neutron Detectors

International Nuclear Information System (INIS)

Saenboonruang, K.

2014-01-01

The gas electron multiplier (GEM) detector is a relatively new gaseous detector that has been used for less than 20 years. Since the discovery in 1997 by F. Sauli, the GEM detector has shown excellent properties including high rate capability, excellent resolutions, low discharge probability, and excellent radiation hardness. These promising properties have led the GEM detector to gain popularity and attention amongst physicists and researchers. In particular, the GEM detector can also be modified to be used as a neutron detector by adding appropriate neutron converters. With properties stated above and the need to replace the expensive 3 He-based neutron detectors, the GEM-based neutron detector will be one of the most powerful and affordable neutron detectors. Applications of the GEM-based neutron detectors vary from researches in nuclear and particle physics, neutron imaging, and national security. Although several promising progresses and results have been shown and published in the past few years, further improvement is still needed in order to improve the low neutron detection efficiency (only a few percent) and to widen the possibilities for other uses.

Signal collection and position reconstruction of silicon strip detectors with 200 μm readout pitch

International Nuclear Information System (INIS)

Krammer, M.; Pernegger, H.

1997-01-01

Silicon strip detectors with large readout pitch and intermediate strips offer an interesting approach to reduce the number of readout channels in the tracking systems of future collider experiments without compromising too much on the spatial resolution. Various detector geometries with a readout pitch of 200 μm have been studied for their signal response and spatial resolution. (orig.)

Simulation of optical configurations and signal processing methods in Anger-type neutron-position scintillation detector

International Nuclear Information System (INIS)

Roche, C.T.; Strauss, M.G.; Brenner, R.

1984-01-01

The spatial linearity and resolution of Anger-type neutron-position scintillation detectors are studied using a semi-empirical model. Detector optics with either an air gap or optical grease between the scintillator and the dispersive light guide are considered. Three signal processing methods which truncate signals from PMT's distant from the scintillation are compared with the linear resistive weighting method. Air gap optics yields a 15% improvement in spatial resolution and 50% reduction in differential and integral nonlinearity relative to grease coupled optics, using linear processing. Using signal truncation instead of linear processing improves the resolution 15-20% for the air gap and 20-30% for the grease coupling case. Thus, the initial discrepancy in the resolution between the two optics nearly vanished, however the linearity of the grease coupled system is still significantly poorer

Polymer fiber detectors for photoacoustic imaging

Science.gov (United States)

Grün, Hubert; Berer, Thomas; Pühringer, Karoline; Nuster, Robert; Paltauf, Günther; Burgholzer, Peter

2010-02-01

Photoacoustic imaging is a novel imaging method for medical and biological applications, combining the advantages of Diffuse Optical Imaging (high contrast) and Ultrasonic Imaging (high spatial resolution). A short laser pulse hits the sample. The absorbed energy causes a thermoelastic expansion and thereby launches a broadband ultrasonic wave (photoacoustic signal). The distribution of absorbed energy density is reconstructed from measurements of the photoacoustic signals around the sample. For collecting photoacoustic signals either point like or extended, integrating detectors can be used. The latter integrate the pressure at least in one dimension, e.g. along a line. Thereby, the three dimensional imaging problem is reduced to a two dimensional problem. For a tomography device consisting of a scanning line detector and a rotating sample, fiber-based detectors made of polymer have been recently introduced. Fiber-based detectors are easy to use and possess a constant, high spatial resolution over their entire active length. Polymer fibers provide a better impedance matching and a better handling compared with glass fibers which were our first approach. First measurement results using polymer fiber detectors and some approaches for improving the performance are presented.

Performance Analysis of Millimeter-Wave Multi-hop Machine-to-Machine Networks Based on Hop Distance Statistics

Directory of Open Access Journals (Sweden)

Haejoon Jung

2018-01-01

Full Text Available As an intrinsic part of the Internet of Things (IoT ecosystem, machine-to-machine (M2M communications are expected to provide ubiquitous connectivity between machines. Millimeter-wave (mmWave communication is another promising technology for the future communication systems to alleviate the pressure of scarce spectrum resources. For this reason, in this paper, we consider multi-hop M2M communications, where a machine-type communication (MTC device with the limited transmit power relays to help other devices using mmWave. To be specific, we focus on hop distance statistics and their impacts on system performances in multi-hop wireless networks (MWNs with directional antenna arrays in mmWave for M2M communications. Different from microwave systems, in mmWave communications, wireless channel suffers from blockage by obstacles that heavily attenuate line-of-sight signals, which may result in limited per-hop progress in MWNs. We consider two routing strategies aiming at different types of applications and derive the probability distributions of their hop distances. Moreover, we provide their baseline statistics assuming the blockage-free scenario to quantify the impact of blockages. Based on the hop distance analysis, we propose a method to estimate the end-to-end performances (e.g., outage probability, hop count, and transmit energy of the mmWave MWNs, which provides important insights into mmWave MWN design without time-consuming and repetitive end-to-end simulation.

Performance Analysis of Millimeter-Wave Multi-hop Machine-to-Machine Networks Based on Hop Distance Statistics.

Science.gov (United States)

Jung, Haejoon; Lee, In-Ho

2018-01-12

As an intrinsic part of the Internet of Things (IoT) ecosystem, machine-to-machine (M2M) communications are expected to provide ubiquitous connectivity between machines. Millimeter-wave (mmWave) communication is another promising technology for the future communication systems to alleviate the pressure of scarce spectrum resources. For this reason, in this paper, we consider multi-hop M2M communications, where a machine-type communication (MTC) device with the limited transmit power relays to help other devices using mmWave. To be specific, we focus on hop distance statistics and their impacts on system performances in multi-hop wireless networks (MWNs) with directional antenna arrays in mmWave for M2M communications. Different from microwave systems, in mmWave communications, wireless channel suffers from blockage by obstacles that heavily attenuate line-of-sight signals, which may result in limited per-hop progress in MWNs. We consider two routing strategies aiming at different types of applications and derive the probability distributions of their hop distances. Moreover, we provide their baseline statistics assuming the blockage-free scenario to quantify the impact of blockages. Based on the hop distance analysis, we propose a method to estimate the end-to-end performances (e.g., outage probability, hop count, and transmit energy) of the mmWave MWNs, which provides important insights into mmWave MWN design without time-consuming and repetitive end-to-end simulation.

Multichannel Signals Reconstruction Based on Tunable Q-Factor Wavelet Transform-Morphological Component Analysis and Sparse Bayesian Iteration for Rotating Machines

Directory of Open Access Journals (Sweden)

Qing Li

2018-04-01

Full Text Available High-speed remote transmission and large-capacity data storage are difficult issues in signals acquisition of rotating machines condition monitoring. To address these concerns, a novel multichannel signals reconstruction approach based on tunable Q-factor wavelet transform-morphological component analysis (TQWT-MCA and sparse Bayesian iteration algorithm combined with step-impulse dictionary is proposed under the frame of compressed sensing (CS. To begin with, to prevent the periodical impulses loss and effectively separate periodical impulses from the external noise and additive interference components, the TQWT-MCA method is introduced to divide the raw vibration signal into low-resonance component (LRC, i.e., periodical impulses and high-resonance component (HRC, thus, the periodical impulses are preserved effectively. Then, according to the amplitude range of generated LRC, the step-impulse dictionary atom is designed to match the physical structure of periodical impulses. Furthermore, the periodical impulses and HRC are reconstructed by the sparse Bayesian iteration combined with step-impulse dictionary, respectively, finally, the final reconstructed raw signals are obtained by adding the LRC and HRC, meanwhile, the fidelity of the final reconstructed signals is tested by the envelop spectrum and error analysis, respectively. In this work, the proposed algorithm is applied to simulated signal and engineering multichannel signals of a gearbox with multiple faults. Experimental results demonstrate that the proposed approach significantly improves the reconstructive accuracy compared with the state-of-the-art methods such as non-convex Lq (q = 0.5 regularization, spatiotemporal sparse Bayesian learning (SSBL and L1-norm, etc. Additionally, the processing time, i.e., speed of storage and transmission has increased dramatically, more importantly, the fault characteristics of the gearbox with multiple faults are detected and saved, i.e., the

Plastic Scintillator Based Detector for Observations of Terrestrial Gamma-ray Flashes.

Science.gov (United States)

Barghi, M. R., Sr.; Delaney, N.; Forouzani, A.; Wells, E.; Parab, A.; Smith, D.; Martinez, F.; Bowers, G. S.; Sample, J.

2017-12-01

We present an overview of the concept and design of the Light and Fast TGF Recorder (LAFTR), a balloon borne gamma-ray detector designed to observe Terrestrial Gamma-Ray Flashes (TGFs). Terrestrial Gamma-Ray Flashes (TGFs) are extremely bright, sub-millisecond bursts of gamma-rays observed to originate inside thunderclouds coincident with lightning. LAFTR is joint institutional project built by undergraduates at the University of California Santa Cruz and Montana State University. It consists of a detector system fed into analog front-end electronics and digital processing. The presentation focuses specifically on the UCSC components, which consists of the detector system and analog front-end electronics. Because of the extremely high count rates observed during TGFs, speed is essential for both the detector and electronics of the instrument. The detector employs a fast plastic scintillator (BC-408) read out by a SensL Silicon Photomultiplier (SiPM). BC-408 is chosen for its speed ( 4 ns decay time) and low cost and availability. Furthermore, GEANT3 simulations confirm the scintillator is sensitive to 500 counts at 7 km horizontal distance from the TGF source (for a 13 km source altitude and 26 km balloon altitude) and to 5 counts out to 20 km. The signal from the SiPM has a long exponential decay tail and is sent to a custom shaping circuit board that amplifies and shapes the signal into a semi-Gaussian pulse with a 40 ns FWHM. The signal is then input to a 6-channel discriminator board that clamps the signal and outputs a Low Voltage Differential Signal (LVDS) for processing by the digital electronics.

Automatic vetting of planet candidates from ground based surveys: Machine learning with NGTS

Science.gov (United States)

Armstrong, David J.; Günther, Maximilian N.; McCormac, James; Smith, Alexis M. S.; Bayliss, Daniel; Bouchy, François; Burleigh, Matthew R.; Casewell, Sarah; Eigmüller, Philipp; Gillen, Edward; Goad, Michael R.; Hodgkin, Simon T.; Jenkins, James S.; Louden, Tom; Metrailler, Lionel; Pollacco, Don; Poppenhaeger, Katja; Queloz, Didier; Raynard, Liam; Rauer, Heike; Udry, Stéphane; Walker, Simon R.; Watson, Christopher A.; West, Richard G.; Wheatley, Peter J.

2018-05-01

State of the art exoplanet transit surveys are producing ever increasing quantities of data. To make the best use of this resource, in detecting interesting planetary systems or in determining accurate planetary population statistics, requires new automated methods. Here we describe a machine learning algorithm that forms an integral part of the pipeline for the NGTS transit survey, demonstrating the efficacy of machine learning in selecting planetary candidates from multi-night ground based survey data. Our method uses a combination of random forests and self-organising-maps to rank planetary candidates, achieving an AUC score of 97.6% in ranking 12368 injected planets against 27496 false positives in the NGTS data. We build on past examples by using injected transit signals to form a training set, a necessary development for applying similar methods to upcoming surveys. We also make the autovet code used to implement the algorithm publicly accessible. autovet is designed to perform machine learned vetting of planetary candidates, and can utilise a variety of methods. The apparent robustness of machine learning techniques, whether on space-based or the qualitatively different ground-based data, highlights their importance to future surveys such as TESS and PLATO and the need to better understand their advantages and pitfalls in an exoplanetary context.

ANN Based Tool Condition Monitoring System for CNC Milling Machines

Directory of Open Access Journals (Sweden)

Mota-Valtierra G.C.

2011-10-01

Full Text Available Most of the companies have as objective to manufacture high-quality products, then by optimizing costs, reducing and controlling the variations in its production processes it is possible. Within manufacturing industries a very important issue is the tool condition monitoring, since the tool state will determine the quality of products. Besides, a good monitoring system will protect the machinery from severe damages. For determining the state of the cutting tools in a milling machine, there is a great variety of models in the industrial market, however these systems are not available to all companies because of their high costs and the requirements of modifying the machining tool in order to attach the system sensors. This paper presents an intelligent classification system which determines the status of cutt ers in a Computer Numerical Control (CNC milling machine. This tool state is mainly detected through the analysis of the cutting forces drawn from the spindle motors currents. This monitoring system does not need sensors so it is no necessary to modify the machine. The correct classification is made by advanced digital signal processing techniques. Just after acquiring a signal, a FIR digital filter is applied to the data to eliminate the undesired noisy components and to extract the embedded force components. A Wavelet Transformation is applied to the filtered signal in order to compress the data amount and to optimize the classifier structure. Then a multilayer perceptron- type neural network is responsible for carrying out the classification of the signal. Achieving a reliability of 95%, the system is capable of detecting breakage and a worn cutter.

Reactor refueling machine simulator

International Nuclear Information System (INIS)

Rohosky, T.L.; Swidwa, K.J.

1987-01-01

This patent describes in combination: a nuclear reactor; a refueling machine having a bridge, trolley and hoist each driven by a separate motor having feedback means for generating a feedback signal indicative of movement thereof. The motors are operable to position the refueling machine over the nuclear reactor for refueling the same. The refueling machine also has a removable control console including means for selectively generating separate motor signals for operating the bridge, trolley and hoist motors and for processing the feedback signals to generate an indication of the positions thereof, separate output leads connecting each of the motor signals to the respective refueling machine motor, and separate input leads for connecting each of the feedback means to the console; and a portable simulator unit comprising: a single simulator motor; a single simulator feedback signal generator connected to the simulator motor for generating a simulator feedback signal in response to operation of the simulator motor; means for selectively connecting the output leads of the console to the simulator unit in place of the refueling machine motors, and for connecting the console input leads to the simulator unit in place of the refueling machine motor feedback means; and means for driving the single simulator motor in response to any of the bridge, trolley or hoist motor signals generated by the console and means for applying the simulator feedback signal to the console input lead associated with the motor signal being generated by the control console

Robust power detector for wideband signals among many single tone signals

Science.gov (United States)

Musgrove, Cameron H.; Thompson, Douglas

2018-03-06

Various technologies for isolating a signal of interest from signals received contemporaneously by an antenna are described herein. A time period for which a signal of interest is present in a second signal can be identified based upon ratios of values of the second signal to the mean value of the second signal. When the ratio of the value of the second signal at a particular time to the mean of the second signal exceeds a threshold value, the signal of interest is considered to be present in the second signal.

Eddy-current guidance of the automatic inspection machine for the main vessel of the superphenix reactor

International Nuclear Information System (INIS)

David, B.; Pigeon, M.

1985-01-01

The weld detector device is an eddy-current measurement system consisting of four dual sensors (absolute + differential types), and a control cabinet with eight analog channels. The system delivers all the signals required for computing the correct track of the MIR machine along the welds, irrespective of bend, temperature, width and type of the seam, junctions of seams

Separation of pulsar signals from noise using supervised machine learning algorithms

Science.gov (United States)

Bethapudi, S.; Desai, S.

2018-04-01

We evaluate the performance of four different machine learning (ML) algorithms: an Artificial Neural Network Multi-Layer Perceptron (ANN MLP), Adaboost, Gradient Boosting Classifier (GBC), and XGBoost, for the separation of pulsars from radio frequency interference (RFI) and other sources of noise, using a dataset obtained from the post-processing of a pulsar search pipeline. This dataset was previously used for the cross-validation of the SPINN-based machine learning engine, obtained from the reprocessing of the HTRU-S survey data (Morello et al., 2014). We have used the Synthetic Minority Over-sampling Technique (SMOTE) to deal with high-class imbalance in the dataset. We report a variety of quality scores from all four of these algorithms on both the non-SMOTE and SMOTE datasets. For all the above ML methods, we report high accuracy and G-mean for both the non-SMOTE and SMOTE cases. We study the feature importances using Adaboost, GBC, and XGBoost and also from the minimum Redundancy Maximum Relevance approach to report algorithm-agnostic feature ranking. From these methods, we find that the signal to noise of the folded profile to be the best feature. We find that all the ML algorithms report FPRs about an order of magnitude lower than the corresponding FPRs obtained in Morello et al. (2014), for the same recall value.

Self-powered detectors for power reactors: an overview

International Nuclear Information System (INIS)

Ma, J.

2006-01-01

In this paper, Self-Powered Detectors (SPDs) for applications in nuclear power reactors have been reviewed. Based on their responses to radiation, these detectors can be divided into delayed response Self-Powered Neutron Detector (SPND), prompt response SPND and Self-Powered Gamma Detector (SPGD). The operational principles of these detectors are presented and their distinctive characteristics are examined accordingly. The analytical models and Monte Carlo method to calculate the responses of these detectors to neutron flux and external gamma rays are reviewed. The paper has also considered some related signal processing techniques, such as detector calibrations and detector signal compensations. Furthermore, a couple of failure modes have also been analyzed. Finally, applications of SPD in nuclear power reactors are summarized. (author)

Self-powered detectors for power reactors: an overview

Energy Technology Data Exchange (ETDEWEB)

Ma, J. [Univ. of Western Ontario, Dept. of Mechanical and Materials Engineering, London, Ontario (Canada)]. E-mail: jma64@uwo.ca

2006-07-01

In this paper, Self-Powered Detectors (SPDs) for applications in nuclear power reactors have been reviewed. Based on their responses to radiation, these detectors can be divided into delayed response Self-Powered Neutron Detector (SPND), prompt response SPND and Self-Powered Gamma Detector (SPGD). The operational principles of these detectors are presented and their distinctive characteristics are examined accordingly. The analytical models and Monte Carlo method to calculate the responses of these detectors to neutron flux and external gamma rays are reviewed. The paper has also considered some related signal processing techniques, such as detector calibrations and detector signal compensations. Furthermore, a couple of failure modes have also been analyzed. Finally, applications of SPD in nuclear power reactors are summarized. (author)

Neutron detection at jet using artificial diamond detectors

International Nuclear Information System (INIS)

Pillon, M.; Angelone, M.; Lattanzi, D.; Marinelli, M.; Milani, E.; Tucciarone, A.; Verona-Rinati, G.; Popovichev, S.; Montereali, R.M.; Vincenti, M.A.; Murari, A.

2007-01-01

Artificial diamond neutron detectors recently proved to be promising devices to measure the neutron production on large experimental fusion machines. Diamond detectors are very promising detectors to be used in fusion environment due to their radiation hardness, low sensitivity to gamma rays, fast response and high energy resolution. High quality 'electronic grade' diamond films are produced through microwave chemical vapour deposition (CVD) technique. Two CVD diamond detectors have been installed and operated at joint European torus (JET), Culham Science Centre, UK. One of these detectors was a polycrystalline CVD diamond film; about 12 mm 2 area and 30 μm thickness while the second was a monocrystalline film of about 5 mm 2 area and 20 μm thick. Both diamonds were covered with 2 μm of lithium fluoride (LiF) 95% enriched in 6 Li. The LiF layer works as a neutron-to-charged particle converter so these detectors can measure thermalized neutrons. Their output signals were compared to JET total neutron yield monitors (KN1 diagnostic) realized with a set of uranium fission chambers. Despite their small active volumes the diamond detectors were able to measure total neutron yields with good reliability and stability during the recent JET experimental campaign of 2006

Qualification measurements of the voltage supply system as well as conceptionation of a state machine for the detector control of the ATLAS pixel detector; Qualifizierungsmessungen des Spannungsversorgungssystems sowie Konzeptionierung einer Zustandsmaschine fuer die Detektorkontrolle des ATLAS-Pixeldetektors

Energy Technology Data Exchange (ETDEWEB)

Schultes, Joachim

2007-02-15

The supply system and the control system of the ATLAS pixel detector represent important building blocks of the pixel detector. Corresponding studies of the supply system, which were performed within a comprehensive test system, the so-called system test, with nearly all final components and the effects on the pixel detector are object of this thesis. A further point of this thesis is the coordination and further development of the detector-control-system software under regardment of the different partial systems. A main topic represents thereby the conceptionation of the required state machine as interface for the users and the connection to the data acquisition system.

Fast digitization and discrimination of prompt neutron and photon signals using a novel silicon carbide detector

International Nuclear Information System (INIS)

Brandon W. Blackburn; James T. Johnson; Scott M. Watson; David L. Chichester; James L. Jones; Frank H. Ruddy; John G. Seidel; Robert W. Flammang

2007-01-01

Current requirements of some Homeland Security active interrogation projects for the detection of Special Nuclear Material (SNM) necessitate the development of faster inspection and acquisition capabilities. In order to do so, fast detectors which can operate during and shortly after intense interrogation radiation flashes are being developed. Novel silicon carbide (SiC) semiconductor Schottky diodes have been utilized as robust neutron and photon detectors in both pulsed photon and pulsed neutron fields and are being integrated into active inspection environments to allow exploitation of both prompt and delayed emissions. These detectors have demonstrated the capability of detecting both photon and neutron events during intense photon flashes typical of an active inspection environment. Beyond the inherent insensitivity of SiC to gamma radiation, fast digitization and processing has demonstrated that pulse shape discrimination (PSD) in combination with amplitude discrimination can further suppress unwanted gamma signals and extract fast neutron signatures. Usable neutron signals have been extracted from mixed radiation fields where the background has exceeded the signals of interest by >1000:1

Microcomputer-based instrument for the detection and analysis of precession motion in a gas centrifuge machine. Revision 1

International Nuclear Information System (INIS)

Paulus, S.S.

1986-03-01

The Centrifuge Procession Analyzer (CPA) is a microcomputer-based instrument which detects precession motion in a gas centrifuge machine and calculates the amplitude and frequency of precession. The CPA consists of a printed circuit board which contains signal-conditioning circuitry and a 24-bit counter and an INTEL iSBC 80/24 single/board computer. Pression motion is detected by monitoring a signal generated by a variable reluctance pick-up coil in the top of the centrifuge machine. This signal is called a Fidler signal. The initial Fidler signal triggers a counter which is clocked by a high-precision, 20.000000-MHz, temperature-controlled, crystal oscillator. The contents of the counter are read by the computer and the counter reset after every ten Fidler signals. The speed of the centrifuge machine and the amplitude and frequency of precession are calculated and the results are displayed on a liquid crystal display on the front panel of the CPA. The report contains results from data generated by a Fidler signal simulator and data taken when the centrifuge was operated under three test conditions: (1) nitrogen gas during drive-up, steady state, and drive-down; (2) xenon gas during slip test, steady state, and the addition of gas; and (3) no gas during steady state. The qualitative results were consistent with experience with centrifuge machines using UF 6 in that the amplitude of precession increased and the frequency of precession decreased during drive-up, drive-down and the slip check. The magnitude of the amplitude and frequency of precession were proportional to the molecular weight of the gases in steady state

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.

Machinability of nickel based alloys using electrical discharge machining process

Science.gov (United States)

Khan, M. Adam; Gokul, A. K.; Bharani Dharan, M. P.; Jeevakarthikeyan, R. V. S.; Uthayakumar, M.; Thirumalai Kumaran, S.; Duraiselvam, M.

2018-04-01

The high temperature materials such as nickel based alloys and austenitic steel are frequently used for manufacturing critical aero engine turbine components. Literature on conventional and unconventional machining of steel materials is abundant over the past three decades. However the machining studies on superalloy is still a challenging task due to its inherent property and quality. Thus this material is difficult to be cut in conventional processes. Study on unconventional machining process for nickel alloys is focused in this proposed research. Inconel718 and Monel 400 are the two different candidate materials used for electrical discharge machining (EDM) process. Investigation is to prepare a blind hole using copper electrode of 6mm diameter. Electrical parameters are varied to produce plasma spark for diffusion process and machining time is made constant to calculate the experimental results of both the material. Influence of process parameters on tool wear mechanism and material removal are considered from the proposed experimental design. While machining the tool has prone to discharge more materials due to production of high energy plasma spark and eddy current effect. The surface morphology of the machined surface were observed with high resolution FE SEM. Fused electrode found to be a spherical structure over the machined surface as clumps. Surface roughness were also measured with surface profile using profilometer. It is confirmed that there is no deviation and precise roundness of drilling is maintained.

Research on intelligent machine self-perception method based on LSTM

Science.gov (United States)

Wang, Qiang; Cheng, Tao

2018-05-01

In this paper, we use the advantages of LSTM in feature extraction and processing high-dimensional and complex nonlinear data, and apply it to the autonomous perception of intelligent machines. Compared with the traditional multi-layer neural network, this model has memory, can handle time series information of any length. Since the multi-physical domain signals of processing machines have a certain timing relationship, and there is a contextual relationship between states and states, using this deep learning method to realize the self-perception of intelligent processing machines has strong versatility and adaptability. The experiment results show that the method proposed in this paper can obviously improve the sensing accuracy under various working conditions of the intelligent machine, and also shows that the algorithm can well support the intelligent processing machine to realize self-perception.

Two-phase xenon detector with gas amplification and electroluminescent signal detection

International Nuclear Information System (INIS)

Akimov, D.Yu.; Burenkov, A.A.; Grishkin, Yu.L.; Kovalenko, A.G.; Lebedenko, V.N.; Stekhanov, V.N.

2008-01-01

An optical technique for detecting ionization electrons produced during ionization of the liquid phase has been experimentally tested in two-phase (liquid-gas) xenon. The effects of gas and electroluminescent amplifications at the wire anode are simultaneously used for detection. This method allows construction of a supersensitive detector of small ionization signals-down to those corresponding to the detection of single electrons [ru

Preliminary Test of Upgraded Conventional Milling Machine into PC Based CNC Milling Machine

International Nuclear Information System (INIS)

Abdul Hafid

2008-01-01

CNC (Computerized Numerical Control) milling machine yields a challenge to make an innovation in the field of machining. With an action job is machining quality equivalent to CNC milling machine, the conventional milling machine ability was improved to be based on PC CNC milling machine. Mechanically and instrumentally change. As a control replacing was conducted by servo drive and proximity were used. Computer programme was constructed to give instruction into milling machine. The program structure of consists GUI model and ladder diagram. Program was put on programming systems called RTX software. The result of up-grade is computer programming and CNC instruction job. The result was beginning step and it will be continued in next time. With upgrading ability milling machine becomes user can be done safe and optimal from accident risk. By improving performance of milling machine, the user will be more working optimal and safely against accident risk. (author)

Operation of an InGrid based X-ray detector at the CAST experiment

Science.gov (United States)

Krieger, Christoph; Desch, Klaus; Kaminski, Jochen; Lupberger, Michael

2018-02-01

The CERN Axion Solar Telescope (CAST) is searching for axions and other particles which could be candidates for DarkMatter and even Dark Energy. These particles could be produced in the Sun and detected by a conversion into soft X-ray photons inside a strong magnetic field. In order to increase the sensitivity for physics beyond the Standard Model, detectors with a threshold below 1 keV as well as efficient background rejection methods are required to compensate for low energies and weak couplings resulting in very low detection rates. Those criteria are fulfilled by a detector utilizing the combination of a pixelized readout chip with an integrated Micromegas stage. These InGrid (Integrated Grid) devices can be build by photolithographic postprocessing techniques, resulting in a close to perfect match of grid and pixels facilitating the detection of single electrons on the chip surface. The high spatial resolution allows for energy determination by simple electron counting as well as for an event-shape based analysis as background rejection method. Tests at an X-ray generator revealed the energy threshold of an InGrid based X-ray detector to be well below the carbon Kα line at 277 eV. After the successful demonstration of the detectors key features, the detector was mounted at one of CAST's four detector stations behind an X-ray telescope in 2014. After several months of successful operation without any detector related interruptions, the InGrid based X-ray detector continues data taking at CAST in 2015. During operation at the experiment, background rates in the order of 10-5 keV-1 cm-2 s-1 have been achieved by application of a likelihood based method discriminating the non-photon background originating mostly from cosmic rays. For continued operation in 2016, an upgraded InGrid based detector is to be installed among other improvements including decoupling and sampling of the signal induced on the grid as well as a veto scintillator to further lower the

Enhanced operator interface for hand-held landmine detector

Science.gov (United States)

Herman, Herman; McMahill, Jeffrey D.; Kantor, George

2001-10-01

As landmines get harder to detect, the complexity of landmine detectors has also been increasing. To increase the probability of detection and decrease the false alarm rate of low metallic landmines, many detectors employ multiple sensing modalities, which include radar and metal detector. Unfortunately, the operator interface for these new detectors stays pretty much the same as for the older detectors. Although the amount of information that the new detectors acquire has increased significantly, the interface has been limited to a simple audio interface. We are currently developing a hybrid audiovisual interface for enhancing the overall performance of the detector. The hybrid audiovisual interface combines the simplicity of the audio output with the rich spatial content of the video display. It is designed to optimally present the output of the detector and also to give the proper feedback to the operator. Instead of presenting all the data to the operator simultaneously, the interface allows the operator to access the information as needed. This capability is critical to avoid information overload, which can significantly reduce the performance of the operator. The audio is used as the primary notification signal, while the video is used for further feedback, discrimination, localization and sensor fusion. The idea is to let the operator gets the feedback that he needs and enable him to look at the data in the most efficient way. We are also looking at a hybrid man-machine detection system which utilizes precise sweeping by the machine and powerful human cognitive ability. In such a hybrid system, the operator is free to concentrate on discriminant task, such as manually fusing the output of the different sensing modalities, instead of worrying about the proper sweep technique. In developing this concept, we have been using the virtual mien lane to validate some of these concepts. We obtained some very encouraging results form our preliminary test. It clearly

Quantum cloning and signaling

International Nuclear Information System (INIS)

Simon, C.; Weihs, G.; Zeilinger, A.

1999-01-01

We discuss the close connections between cloning of quantum states and superluminal signaling. We present an optimal universal cloning machine based on stimulated emission recently proposed by the authors. As an instructive example, we show how a scheme for superluminal communication based on this cloning machine fails. (Authors)

Porting Gravitational Wave Signal Extraction to Parallel Virtual Machine (PVM)

Science.gov (United States)

Thirumalainambi, Rajkumar; Thompson, David E.; Redmon, Jeffery

2009-01-01

Laser Interferometer Space Antenna (LISA) is a planned NASA-ESA mission to be launched around 2012. The Gravitational Wave detection is fundamentally the determination of frequency, source parameters, and waveform amplitude derived in a specific order from the interferometric time-series of the rotating LISA spacecrafts. The LISA Science Team has developed a Mock LISA Data Challenge intended to promote the testing of complicated nested search algorithms to detect the 100-1 millihertz frequency signals at amplitudes of 10E-21. However, it has become clear that, sequential search of the parameters is very time consuming and ultra-sensitive; hence, a new strategy has been developed. Parallelization of existing sequential search algorithms of Gravitational Wave signal identification consists of decomposing sequential search loops, beginning with outermost loops and working inward. In this process, the main challenge is to detect interdependencies among loops and partitioning the loops so as to preserve concurrency. Existing parallel programs are based upon either shared memory or distributed memory paradigms. In PVM, master and node programs are used to execute parallelization and process spawning. The PVM can handle process management and process addressing schemes using a virtual machine configuration. The task scheduling and the messaging and signaling can be implemented efficiently for the LISA Gravitational Wave search process using a master and 6 nodes. This approach is accomplished using a server that is available at NASA Ames Research Center, and has been dedicated to the LISA Data Challenge Competition. Historically, gravitational wave and source identification parameters have taken around 7 days in this dedicated single thread Linux based server. Using PVM approach, the parameter extraction problem can be reduced to within a day. The low frequency computation and a proxy signal-to-noise ratio are calculated in separate nodes that are controlled by the master

Development of the microstrip silicon detector for imaging of fast processes at a synchrotron radiation beam

Energy Technology Data Exchange (ETDEWEB)

Aulchenko, V. [Budker Institute of Nuclear Physics, 630090 Novosibirsk (Russian Federation); Novosibirsk State University, 630090 Novosibirsk, Russian Federtion (Russian Federation); Pruuel, E. [Lavrentiev Institute of Hydrodynamics, 630090 Novosibirsk, Russian Federtion (Russian Federation); Novosibirsk State University, 630090 Novosibirsk, Russian Federtion (Russian Federation); Shekhtman, L. [Budker Institute of Nuclear Physics, 630090 Novosibirsk (Russian Federation); Novosibirsk State University, 630090 Novosibirsk, Russian Federtion (Russian Federation); Ten, K. [Lavrentiev Institute of Hydrodynamics, 630090 Novosibirsk, Russian Federtion (Russian Federation); Tolochko, B. [Institute of Solid State chemistry and Mechanochemistry, 630090 Novosibirsk, Russian Federtion (Russian Federation); Novosibirsk State University, 630090 Novosibirsk, Russian Federtion (Russian Federation); Zhulanov, V. [Budker Institute of Nuclear Physics, 630090 Novosibirsk (Russian Federation); Novosibirsk State University, 630090 Novosibirsk, Russian Federtion (Russian Federation)

2017-02-11

In situ imaging of explosions allows to study material properties under very high pressures and temperatures. Synchrotron radiation (SR) is a powerful tool for such studies because of its unique time structure. Flashes of X-rays from individual bunches in a storage ring are so short that an object under study does not move more than 1–10 μm during exposure. If a detector is able to store images synchronously with bunches of an SR source the time resolution of such method will be determined by the duration of SR flash from individual bunch. New beam line at the VEPP-4M storage ring will allow to get X-Ray flux from each bunch close to 10{sup 6} photons/channel where channel area is 0.05×0.5 mm{sup 2} and average beam energy is about 30 keV. Bunches in the machine can be grouped into trains with 20 ns time gap. In order to meet these requirements a new detector development was started based on Si microstrip technology. The detector with a new dedicated front-end chip will be able to record images with maximum signal equivalent to 10{sup 6} photons/channel, with signal to noise ratio of ∼10{sup 3}, spatial resolution of 50 μm and maximum frame rate of 50 MHz. The detector has to drive very high peak and average currents without affecting the front-end chip, therefore a specific design of Si sensor should be developed. The front-end chip has to provide signal measurements with the dynamic range of about 10{sup 4} or more and recording of the signal to an analogue memory with the rate of 50 MHz. The concept of such detector is discussed in the paper. The results of the simulations of the main detector parameters and the results of the first measurements with the prototype sensors are presented.

Partial discharge signal denoising with spatially adaptive wavelet thresholding and support vector machines

Energy Technology Data Exchange (ETDEWEB)

Mota, Hilton de Oliveira; Rocha, Leonardo Chaves Dutra da [Department of Computer Science, Federal University of Sao Joao del-Rei, Visconde do Rio Branco Ave., Colonia do Bengo, Sao Joao del-Rei, MG, 36301-360 (Brazil); Salles, Thiago Cunha de Moura [Department of Computer Science, Federal University of Minas Gerais, 6627 Antonio Carlos Ave., Pampulha, Belo Horizonte, MG, 31270-901 (Brazil); Vasconcelos, Flavio Henrique [Department of Electrical Engineering, Federal University of Minas Gerais, 6627 Antonio Carlos Ave., Pampulha, Belo Horizonte, MG, 31270-901 (Brazil)

2011-02-15

In this paper an improved method to denoise partial discharge (PD) signals is presented. The method is based on the wavelet transform (WT) and support vector machines (SVM) and is distinct from other WT-based denoising strategies in the sense that it exploits the high spatial correlations presented by PD wavelet decompositions as a way to identify and select the relevant coefficients. PD spatial correlations are characterized by WT modulus maxima propagation along decomposition levels (scales), which are a strong indicative of the their time-of-occurrence. Denoising is performed by identification and separation of PD-related maxima lines by an SVM pattern classifier. The results obtained confirm that this method has superior denoising capabilities when compared to other WT-based methods found in the literature for the processing of Gaussian and discrete spectral interferences. Moreover, its greatest advantages become clear when the interference has a pulsating or localized shape, situation in which traditional methods usually fail. (author)

Simulation based investigation of source-detector configurations for non-invasive fetal pulse oximetry

Directory of Open Access Journals (Sweden)

Böttrich Marcel

2015-09-01

Full Text Available Transabdominal fetal pulse oximetry is a method to monitor the oxygen supply of the unborn child non-invasively. Due to the measurement setup, the received signal of the detector is composed of photons coding purely maternal and photons coding mixed fetal-maternal information. To analyze the wellbeing of the fetus, the fetal signal is extracted from the mixed component. In this paper we assess source-detector configurations, such that the mixed fetal-maternal components of the acquired signals are maximized. Monte-Carlo method is used to simulate light propagation and photon distribution in tissue. We use a plane layer and a spherical layer geometry to model the abdomen of a pregnant woman. From the simulations we extracted the fluence at the detector side for several source-detector distances and analyzed the ratio of the mixed fluence component to total fluence. Our simulations showed that the power of the mixed component depends on the source-detector distance as expected. Further we were able to visualize hot spot areas in the spherical layer model where the mixed fluence ratio reaches the highest level. The results are of high importance for sensor design considering signal composition and quality for non-invasive fetal pulse oximetry.

Design and implementation of the NaI(Tl)/CsI(Na) detectors output signal generator

Science.gov (United States)

Zhou, Xu; Liu, Cong-Zhan; Zhao, Jian-Ling; Zhang, Fei; Zhang, Yi-Fei; Li, Zheng-Wei; Zhang, Shuo; Li, Xu-Fang; Lu, Xue-Feng; Xu, Zhen-Ling; Lu, Fang-Jun

2014-02-01

We designed and implemented a signal generator that can simulate the output of the NaI(Tl)/CsI(Na) detectors' pre-amplifier onboard the Hard X-ray Modulation Telescope (HXMT). Using the development of the FPGA (Field Programmable Gate Array) with VHDL language and adding a random constituent, we have finally produced the double exponential random pulse signal generator. The statistical distribution of the signal amplitude is programmable. The occurrence time intervals of the adjacent signals contain negative exponential distribution statistically.

Advanced Electrical Machines and Machine-Based Systems for Electric and Hybrid Vehicles

OpenAIRE

Ming Cheng; Le Sun; Giuseppe Buja; Lihua Song

2015-01-01

The paper presents a number of advanced solutions on electric machines and machine-based systems for the powertrain of electric vehicles (EVs). Two types of systems are considered, namely the drive systems designated to the EV propulsion and the power split devices utilized in the popular series-parallel hybrid electric vehicle architecture. After reviewing the main requirements for the electric drive systems, the paper illustrates advanced electric machine topologies, including a stator perm...

Floating-point-based hardware accelerator of a beam phase-magnitude detector and filter for a beam phase control system in a heavy-ion synchrotron application

International Nuclear Information System (INIS)

Samman, F.A.; Pongyupinpanich Surapong; Spies, C.; Glesner, M.

2012-01-01

A hardware implementation of an adaptive phase and magnitude detector and filter of a beam-phase control system in a heavy ion synchrotron application is presented in this paper. The main components of the hardware are adaptive LMS (Least-Mean-Square) filters and phase and magnitude detectors. The phase detectors are implemented by using a CORDIC (Coordinate Rotation Digital Computer) algorithm based on 32-bit binary floating-point arithmetic data formats. The floating-point-based hardware is designed to improve the precision of the past hardware implementation that were based on fixed-point arithmetics. The hardware of the detector and the adaptive LMS filter have been implemented on a programmable logic device (FPGA) for hardware acceleration purpose. The ideal Matlab/Simulink model of the hardware and the VHDL model of the adaptive LMS filter and the phase and magnitude detector are compared. The comparison result shows that the output signal of the floating-point based adaptive FIR filter as well as the phase and magnitude detector agree with the expected output signal of the ideal Matlab/Simulink model. (authors)

Boron-coated straws as a replacement for 3He-based neutron detectors

International Nuclear Information System (INIS)

Lacy, Jeffrey L.; Athanasiades, Athanasios; Sun, Liang; Martin, Christopher S.; Lyons, Tom D.; Foss, Michael A.; Haygood, Hal B.

2011-01-01

US and international government efforts to equip major seaports with large area neutron detectors, aimed to intercept the smuggling of nuclear materials, have precipitated a critical shortage of 3 He gas. It is estimated that the annual demand of 3 He for US security applications alone is more than the worldwide supply. This is strongly limiting the prospects of neutron science, safeguards, and other applications that rely heavily on 3 He-based detectors. Clearly, alternate neutron detection technologies that can support large sensitive areas, and have low gamma sensitivity and low cost must be developed. We propose a low-cost technology based on long copper tubes (straws), coated on the inside with a thin layer of 10 B-enriched boron carbide ( 10 B 4 C). In addition to the high abundance of boron on Earth and low cost of 10 B enrichment, the boron-coated straw (BCS) detector offers distinct advantages over conventional 3 He-based detectors, and alternate technologies such as 10 BF 3 tubes and 10 B-coated rigid tubes. These include better distribution inside moderator assemblies, many-times faster electronic signals, no pressurization, improved gamma-ray rejection, no toxic or flammable gases, and ease of serviceability. We present the performance of BCS detectors dispersed in a solid plastic moderator to address the need for portal monitoring. The design adopts the outer dimensions of currently deployed 3 He-based monitors, but takes advantage of the small BCS diameter to achieve a more uniform distribution of neutron converter throughout the moderating material. We show that approximately 63 BCS detectors, each 205 cm long, distributed inside the moderator, can match or exceed the detection efficiency of typical monitors fitted with a 5 cm diameter 3 He tube, 187 cm long, pressurized to 3 atm.

Boron-coated straws as a replacement for 3He-based neutron detectors

Science.gov (United States)

Lacy, Jeffrey L.; Athanasiades, Athanasios; Sun, Liang; Martin, Christopher S.; Lyons, Tom D.; Foss, Michael A.; Haygood, Hal B.

2011-10-01

US and international government efforts to equip major seaports with large area neutron detectors, aimed to intercept the smuggling of nuclear materials, have precipitated a critical shortage of 3He gas. It is estimated that the annual demand of 3He for US security applications alone is more than the worldwide supply. This is strongly limiting the prospects of neutron science, safeguards, and other applications that rely heavily on 3He-based detectors. Clearly, alternate neutron detection technologies that can support large sensitive areas, and have low gamma sensitivity and low cost must be developed. We propose a low-cost technology based on long copper tubes (straws), coated on the inside with a thin layer of 10B-enriched boron carbide ( 10B 4C). In addition to the high abundance of boron on Earth and low cost of 10B enrichment, the boron-coated straw (BCS) detector offers distinct advantages over conventional 3He-based detectors, and alternate technologies such as 10BF 3 tubes and 10B-coated rigid tubes. These include better distribution inside moderator assemblies, many-times faster electronic signals, no pressurization, improved gamma-ray rejection, no toxic or flammable gases, and ease of serviceability. We present the performance of BCS detectors dispersed in a solid plastic moderator to address the need for portal monitoring. The design adopts the outer dimensions of currently deployed 3He-based monitors, but takes advantage of the small BCS diameter to achieve a more uniform distribution of neutron converter throughout the moderating material. We show that approximately 63 BCS detectors, each 205 cm long, distributed inside the moderator, can match or exceed the detection efficiency of typical monitors fitted with a 5 cm diameter 3He tube, 187 cm long, pressurized to 3 atm.

Enhancement of Twins Fetal ECG Signal Extraction Based on Hybrid Blind Extraction Techniques

Directory of Open Access Journals (Sweden)

Ahmed Kareem Abdullah

2017-07-01

Full Text Available ECG machines are noninvasive system used to measure the heartbeat signal. It’s very important to monitor the fetus ECG signals during pregnancy to check the heat activity and to detect any problem early before born, therefore the monitoring of ECG signals have clinical significance and importance. For multi-fetal pregnancy case the classical filtering algorithms are not sufficient to separate the ECG signals between mother and fetal. In this paper the mixture consists of mixing from three ECG signals, the first signal is the mother ECG (M-ECG signal, second signal the Fetal-1 ECG (F1-ECG, and third signal is the Fetal-2 ECG (F2-ECG, these signals are extracted based on modified blind source extraction (BSE techniques. The proposed work based on hybridization between two BSE techniques to ensure that the extracted signals separated well. The results demonstrate that the proposed work very efficiently to extract the useful ECG signals

A free-running, time-based readout method for particle detectors

International Nuclear Information System (INIS)

Goerres, A; Ritman, J; Stockmanns, T; Bugalho, R; Francesco, A Di; Gastón, C; Gonçalves, F; Rolo, M D; Silva, J C da; Silva, R; Varela, J; Veckalns, V; Mazza, G; Mignone, M; Pietro, V Di; Riccardi, A; Rivetti, A; Wheadon, R

2014-01-01

For the EndoTOFPET-US experiment, the TOFPET ASIC has been developed as a front-end chip to read out data from silicon photomultipliers (SiPM) [1]. It introduces a time of flight information into the measurement of a PET scanner and hence reduces radiation exposure of the patient [2]. The chip is designed to work with a high event rate up to 100 kHz and a time resolution of 50 ps LSB. Using two threshold levels, it can measure the leading edge of the event pulse precisely while successfully suppressing dark counts from the SiPM. This also enables a time over threshold determination, leading to a charge measurement of the signal's pulse. The same, time-based concept is chosen for the PASTA chip used in the PANDA experiment. This high-energy particle detector contains sub-systems for specific measurement goals. The innermost of these is the Micro Vertex Detector, a silicon-based tracking system. The PASTA chip's approach is much like the TOFPET ASIC with some differences. The most significant ones are a changed amplifying part for different input signals as well as protection for radiation effects of the high-radiation environment. Apart from that, the simple and general concept combined with a small area and low power consumption support the choice for using this approach

A free-running, time-based readout method for particle detectors

Science.gov (United States)

Goerres, A.; Bugalho, R.; Di Francesco, A.; Gastón, C.; Gonçalves, F.; Mazza, G.; Mignone, M.; Di Pietro, V.; Riccardi, A.; Ritman, J.; Rivetti, A.; Rolo, M. D.; da Silva, J. C.; Silva, R.; Stockmanns, T.; Varela, J.; Veckalns, V.; Wheadon, R.

2014-03-01

For the EndoTOFPET-US experiment, the TOFPET ASIC has been developed as a front-end chip to read out data from silicon photomultipliers (SiPM) [1]. It introduces a time of flight information into the measurement of a PET scanner and hence reduces radiation exposure of the patient [2]. The chip is designed to work with a high event rate up to 100 kHz and a time resolution of 50 ps LSB. Using two threshold levels, it can measure the leading edge of the event pulse precisely while successfully suppressing dark counts from the SiPM. This also enables a time over threshold determination, leading to a charge measurement of the signal's pulse. The same, time-based concept is chosen for the PASTA chip used in the PANDA experiment. This high-energy particle detector contains sub-systems for specific measurement goals. The innermost of these is the Micro Vertex Detector, a silicon-based tracking system. The PASTA chip's approach is much like the TOFPET ASIC with some differences. The most significant ones are a changed amplifying part for different input signals as well as protection for radiation effects of the high-radiation environment. Apart from that, the simple and general concept combined with a small area and low power consumption support the choice for using this approach.

Analysis of the imaging performance in indirect digital mammography detectors by linear systems and signal detection models

International Nuclear Information System (INIS)

Liaparinos, P.; Kalyvas, N.; Kandarakis, I.; Cavouras, D.

2013-01-01

Purpose: The purpose of this study was to provide an analysis of imaging performance in digital mammography, using indirect detector instrumentation, by combining the Linear Cascaded Systems (LCS) theory and the Signal Detection Theory (SDT). Observer performance was assessed, by examining frequently employed detectors, consisting of phosphor-based X-ray converters (granular Gd 2 O 2 S:Tb and structural CsI:Tl), coupled with the recently introduced complementary metal-oxide-semiconductor (CMOS) sensor. By applying combinations of various irradiation conditions (filter-target and exposure levels at 28 kV) on imaging detectors, our study aimed to find the optimum system set-up for digital mammography. For this purpose, the signal to noise transfer properties of the medical imaging detectors were examined for breast carcinoma detectability. Methods: An analytical model was applied to calculate X-ray interactions within software breast phantoms and detective media. Modeling involved: (a) three X-ray spectra used in digital mammography: 28 kV Mo/Mo (Mo: 0.030 mm), 28 kV Rh/Rh (Rh: 0.025 mm) and 28 kV W/Rh (Rh: 0.060 mm) at different entrance surface air kerma (ESAK) of 3 mGy and 5 mGy, (b) a 5 cm thick Perspex software phantom incorporating a small Ca lesion of varying size (0.1–1 cm), and (c) two 200 μm thick phosphor-based X-ray converters (Gd2O2S:Tb, CsI:Tl), coupled to a CMOS based detector of 22.5 μm pixel size. Results: Best (lowest) contrast threshold (CT) values were obtained with the combination: (i) W/Rh target-filter, (ii) 5 mGy (ESAK), and (iii) CsI:Tl-CMOS detector. For lesion diameter 0.5 cm the CT was found improved, in comparison to other anode/filter combinations, approximately 42% than Rh/Rh and 55% than Mo/Mo, for small sized carcinoma (0.1 cm) and approximately 50% than Rh/Rh and 125% than Mo/Mo, for big sized carcinoma (1 cm), considering 5 mGy X-ray beam. By decreasing lesion diameter and thickness, a limiting CT (100%) was occurred for size

Design and Test of a Signal Packet Router Prototype for the ATLAS NSW sTGC Detector

CERN Document Server

Hu, Xueye; The ATLAS collaboration

2016-01-01

Abstract– The New Small Wheel (NSW) small-strip thin-gap chambers (sTGC) detector will be installed in Large Hadron Collider (LHC) during ATLAS Phase-I upgrade. For sTGC detector, it requires very high-speed electronic triggering of signal events. On detecting a signal peak, sTGC front-end trigger logic will send out serialized track information on twinax fast serial copper wires to the signal packet Router on the periphery of the new small wheel. The signal packet Router boards handle all incoming traffic from the TDS chips (4.8 Gbps), serving as a very fast switching-yard between incoming active TDS signals and a limited number of optoelectronic outputs. There are several design requirements on router: radiation-hard (9kRad), high-speed serial link and low fixed latency in FPGA (field-programmable gate array) data processing. To meet those requirements, a router prototype has been developed for demonstration purpose. The components used in router prototype have been tested in radiation environment to m...

Design and implementation of the NaI(Tl)/CsI(Na) detectors output signal generator

International Nuclear Information System (INIS)

Zhou Xu; Liu Congzhan; Zhao Jianling

2014-01-01

We designed and implemented a signal generator that can simulate the output of the NaI(Tl)/CsI(Na) detectors' pre-amplifier onboard the Hard X-ray Modulation Telescope (HXMT). Using the development of the FPGA (Field Programmable Gate Array) with VHDL language and adding a random constituent, we have finally produced the double exponential random pulse signal generator. The statistical distribution of the signal amplitude is programmable. The occurrence time intervals of the adjacent signals contain negative exponential distribution statistically. (authors)

UBO Detector - A cluster-based, fully automated pipeline for extracting white matter hyperintensities.

Science.gov (United States)

Jiang, Jiyang; Liu, Tao; Zhu, Wanlin; Koncz, Rebecca; Liu, Hao; Lee, Teresa; Sachdev, Perminder S; Wen, Wei

2018-07-01

We present 'UBO Detector', a cluster-based, fully automated pipeline for extracting and calculating variables for regions of white matter hyperintensities (WMH) (available for download at https://cheba.unsw.edu.au/group/neuroimaging-pipeline). It takes T1-weighted and fluid attenuated inversion recovery (FLAIR) scans as input, and SPM12 and FSL functions are utilised for pre-processing. The candidate clusters are then generated by FMRIB's Automated Segmentation Tool (FAST). A supervised machine learning algorithm, k-nearest neighbor (k-NN), is applied to determine whether the candidate clusters are WMH or non-WMH. UBO Detector generates both image and text (volumes and the number of WMH clusters) outputs for whole brain, periventricular, deep, and lobar WMH, as well as WMH in arterial territories. The computation time for each brain is approximately 15 min. We validated the performance of UBO Detector by showing a) high segmentation (similarity index (SI) = 0.848) and volumetric (intraclass correlation coefficient (ICC) = 0.985) agreement between the UBO Detector-derived and manually traced WMH; b) highly correlated (r 2  > 0.9) and a steady increase of WMH volumes over time; and c) significant associations of periventricular (t = 22.591, p deep (t = 14.523, p < 0.001) WMH volumes generated by UBO Detector with Fazekas rating scores. With parallel computing enabled in UBO Detector, the processing can take advantage of multi-core CPU's that are commonly available on workstations. In conclusion, UBO Detector is a reliable, efficient and fully automated WMH segmentation pipeline. Copyright © 2018 Elsevier Inc. All rights reserved.

Comparison of machine learning algorithms for detecting coral reef

Directory of Open Access Journals (Sweden)

Eduardo Tusa

2014-09-01

Full Text Available (Received: 2014/07/31 - Accepted: 2014/09/23This work focuses on developing a fast coral reef detector, which is used for an autonomous underwater vehicle, AUV. A fast detection secures the AUV stabilization respect to an area of reef as fast as possible, and prevents devastating collisions. We use the algorithm of Purser et al. (2009 because of its precision. This detector has two parts: feature extraction that uses Gabor Wavelet filters, and feature classification that uses machine learning based on Neural Networks. Due to the extensive time of the Neural Networks, we exchange for a classification algorithm based on Decision Trees. We use a database of 621 images of coral reef in Belize (110 images for training and 511 images for testing. We implement the bank of Gabor Wavelets filters using C++ and the OpenCV library. We compare the accuracy and running time of 9 machine learning algorithms, whose result was the selection of the Decision Trees algorithm. Our coral detector performs 70ms of running time in comparison to 22s executed by the algorithm of Purser et al. (2009.

Studies on the transmission and processing of pulse-shaped signals from nuclear radiation detectors using methods of systems theory

International Nuclear Information System (INIS)

Spillekothen, H.G.

2007-01-01

Using methods of the systems theory of electronic communications and theoretical electrical science, this study describes the transmission of pulse-shaped signals from nuclear radiation detectors from the detector over ''electrically long lines'' (cables) to the output of the first pulse amplifier. The example of pulses from BF 3 -proportional counters shows, using the Fourier transformation, that pulses from radiation detectors contain a frequency spectrum ranging well above 10 8 Hz. If these pulses are transmitted to the first amplifier over a line length of several meters, the laws of the theory of transmission lines must be taken into account to avoid false signals caused by reflections. In the example, line equations are applied and the influence of the line and the terminating impedance is demonstrated. The influence of the frequency response ν(ω) and the phase response δ(ω) of the amplifier is also considered in the sample calculation. The methods presented make it possible to analyze and optimize the transmission and amplification of signals from radiation detectors. Close agreement emerges between empirically observed and calculated pulse shapes. (orig.)

Physics of scintillation detectors

International Nuclear Information System (INIS)

Novotny, R.

1991-01-01

The general concept of a radiation detector is based on three fundamental principles: sensitivity of the device to the radiation of interest which requires a large cross-section in the detector material, detector response function to the physical properties of the radiation. As an example, a scintillation detector for charged particles should allow to identify the charge of the particle, its kinetic energy and the time of impact combined with optimum resolutions. Optimum conversion of the detector response (like luminescence of a scintillator) into electronical signals for further processing. The following article will concentrate on the various aspects of the first two listed principles as far as they appear to be relevant for photon and charged particle detection using organic and inorganic scintillation detectors. (orig.)

Four wind speed multi-step forecasting models using extreme learning machines and signal decomposing algorithms

International Nuclear Information System (INIS)

Liu, Hui; Tian, Hong-qi; Li, Yan-fei

2015-01-01

Highlights: • A hybrid architecture is proposed for the wind speed forecasting. • Four algorithms are used for the wind speed multi-scale decomposition. • The extreme learning machines are employed for the wind speed forecasting. • All the proposed hybrid models can generate the accurate results. - Abstract: Realization of accurate wind speed forecasting is important to guarantee the safety of wind power utilization. In this paper, a new hybrid forecasting architecture is proposed to realize the wind speed accurate forecasting. In this architecture, four different hybrid models are presented by combining four signal decomposing algorithms (e.g., Wavelet Decomposition/Wavelet Packet Decomposition/Empirical Mode Decomposition/Fast Ensemble Empirical Mode Decomposition) and Extreme Learning Machines. The originality of the study is to investigate the promoted percentages of the Extreme Learning Machines by those mainstream signal decomposing algorithms in the multiple step wind speed forecasting. The results of two forecasting experiments indicate that: (1) the method of Extreme Learning Machines is suitable for the wind speed forecasting; (2) by utilizing the decomposing algorithms, all the proposed hybrid algorithms have better performance than the single Extreme Learning Machines; (3) in the comparisons of the decomposing algorithms in the proposed hybrid architecture, the Fast Ensemble Empirical Mode Decomposition has the best performance in the three-step forecasting results while the Wavelet Packet Decomposition has the best performance in the one and two step forecasting results. At the same time, the Wavelet Packet Decomposition and the Fast Ensemble Empirical Mode Decomposition are better than the Wavelet Decomposition and the Empirical Mode Decomposition in all the step predictions, respectively; and (4) the proposed algorithms are effective in the wind speed accurate predictions

Improvement of an X-ray imaging detector based on a scintillating guides screen

CERN Document Server

Badel, X; Linnros, J; Kleimann, P; Froejdh, C; Petersson, C S

2002-01-01

An X-ray imaging detector has been developed for dental applications. The principle of this detector is based on application of a silicon charge coupled device covered by a scintillating wave-guide screen. Previous studies of such a detector showed promising results concerning the spatial resolution but low performance in terms of signal to noise ratio (SNR) and sensitivity. Recent results confirm the wave-guiding properties of the matrix and show improvement of the detector in terms of response uniformity, sensitivity and SNR. The present study is focussed on the fabrication of the scintillating screen where the principal idea is to fill a matrix of Si pores with a CsI scintillator. The photoluminescence technique was used to prove the wave-guiding property of the matrix and to inspect the filling uniformity of the pores. The final detector was characterized by X-ray evaluation in terms of spatial resolution, light output and SNR. A sensor with a spatial resolution of 9 LP/mm and a SNR over 50 has been achie...

Control of deviations and prediction of surface roughness from micro machining of THz waveguides using acoustic emission signals

Science.gov (United States)

Griffin, James M.; Diaz, Fernanda; Geerling, Edgar; Clasing, Matias; Ponce, Vicente; Taylor, Chris; Turner, Sam; Michael, Ernest A.; Patricio Mena, F.; Bronfman, Leonardo

2017-02-01

By using acoustic emission (AE) it is possible to control deviations and surface quality during micro milling operations. The method of micro milling is used to manufacture a submillimetre waveguide where micro machining is employed to achieve the required superior finish and geometrical tolerances. Submillimetre waveguide technology is used in deep space signal retrieval where highest detection efficiencies are needed and therefore every possible signal loss in the receiver has to be avoided and stringent tolerances achieved. With a sub-standard surface finish the signals travelling along the waveguides dissipate away faster than with perfect surfaces where the residual roughness becomes comparable with the electromagnetic skin depth. Therefore, the higher the radio frequency the more critical this becomes. The method of time-frequency analysis (STFT) is used to transfer raw AE into more meaningful salient signal features (SF). This information was then correlated against the measured geometrical deviations and, the onset of catastrophic tool wear. Such deviations can be offset from different AE signals (different deviations from subsequent tests) and feedback for a final spring cut ensuring the geometrical accuracies are met. Geometrical differences can impact on the required transfer of AE signals (change in cut off frequencies and diminished SNR at the interface) and therefore errors have to be minimised to within 1 μm. Rules based on both Classification and Regression Trees (CART) and Neural Networks (NN) were used to implement a simulation displaying how such a control regime could be used as a real time controller, be it corrective measures (via spring cuts) over several initial machining passes or, with a micron cut introducing a level plain measure for allowing setup corrective measures (similar to a spirit level).

Characterization of Harmonic Signal Acquisition with Parallel Dipole and Multipole Detectors

Science.gov (United States)

Park, Sung-Gun; Anderson, Gordon A.; Bruce, James E.

2018-04-01

Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) is a powerful instrument for the study of complex biological samples due to its high resolution and mass measurement accuracy. However, the relatively long signal acquisition periods needed to achieve high resolution can serve to limit applications of FTICR-MS. The use of multiple pairs of detector electrodes enables detection of harmonic frequencies present at integer multiples of the fundamental cyclotron frequency, and the obtained resolving power for a given acquisition period increases linearly with the order of harmonic signal. However, harmonic signal detection also increases spectral complexity and presents challenges for interpretation. In the present work, ICR cells with independent dipole and harmonic detection electrodes and preamplifiers are demonstrated. A benefit of this approach is the ability to independently acquire fundamental and multiple harmonic signals in parallel using the same ions under identical conditions, enabling direct comparison of achieved performance as parameters are varied. Spectra from harmonic signals showed generally higher resolving power than spectra acquired with fundamental signals and equal signal duration. In addition, the maximum observed signal to noise (S/N) ratio from harmonic signals exceeded that of fundamental signals by 50 to 100%. Finally, parallel detection of fundamental and harmonic signals enables deconvolution of overlapping harmonic signals since observed fundamental frequencies can be used to unambiguously calculate all possible harmonic frequencies. Thus, the present application of parallel fundamental and harmonic signal acquisition offers a general approach to improve utilization of harmonic signals to yield high-resolution spectra with decreased acquisition time. [Figure not available: see fulltext.

Very forward calorimeters readout and machine interface

Indian Academy of Sciences (India)

for the instrumentation of the forward region of the future detector at the international linear collider. ... The LumiCal can be used for the measurement of integrated luminosity based on Bhabha scattering process with a relative precision of 10−4. The BeamCal can be used to ... the machine control system. The purpose of ...

A correlation-based pulse detection technique for gamma-ray/neutron detectors

International Nuclear Information System (INIS)

Faisal, Muhammad; Schiffer, Randolph T.; Flaska, Marek; Pozzi, Sara A.; Wentzloff, David D.

2011-01-01

We present a correlation-based detection technique that significantly improves the probability of detection for low energy pulses. We propose performing a normalized cross-correlation of the incoming pulse data to a predefined pulse template, and using a threshold correlation value to trigger the detection of a pulse. This technique improves the detector sensitivity by amplifying the signal component of incoming pulse data and rejecting noise. Simulation results for various different templates are presented. Finally, the performance of the correlation-based detection technique is compared to the current state-of-the-art techniques.

2-Dimension pulse shape discriminator for phoswich detector based on FPGA

International Nuclear Information System (INIS)

Ji Jianfeng; Liu Congzhan; Zhang Zhi

2011-01-01

It improves the data acquire system for the pulse signal based on digital front-rear pulse shape discrimination system. It adds pulse width information into the pulse's data package. Base on this, we divide the pulse event process into two process, on line coast process and offline accurate process: the online process sets a big threshold, just save the data of the event below this threshold; the offline process uses the acquired data, get the pulse amplitude and pulse width, and then according the spectrum's real shape, set the accurate threshold. this design resolves the problem that the detector's decay time change with the temperature; at the same time, it can correct the system's distortion when the input signal at small amplitude, improves the discrimination system's accuracy. (authors)

X-ray detectors based on image sensors

International Nuclear Information System (INIS)

Costa, A.P.R.

1983-01-01

X-ray detectors based on image sensors are described and a comparison is made between the advantages and the disadvantages of such a kind of detectors with the position sensitive detectors. (L.C.) [pt

Audio-based, unsupervised machine learning reveals cyclic changes in earthquake mechanisms in the Geysers geothermal field, California

Science.gov (United States)

Holtzman, B. K.; Paté, A.; Paisley, J.; Waldhauser, F.; Repetto, D.; Boschi, L.

2017-12-01

The earthquake process reflects complex interactions of stress, fracture and frictional properties. New machine learning methods reveal patterns in time-dependent spectral properties of seismic signals and enable identification of changes in faulting processes. Our methods are based closely on those developed for music information retrieval and voice recognition, using the spectrogram instead of the waveform directly. Unsupervised learning involves identification of patterns based on differences among signals without any additional information provided to the algorithm. Clustering of 46,000 earthquakes of $0.3

Progress in the optoelectronic analog signal transfer for high energy particle detectors

International Nuclear Information System (INIS)

Tsang, T.; Radeka, V.

1992-05-01

We report the progress in the development of a radiation hard Optoelectronic analog system to transfer particle detector signals with high accuracy. We will present the motivation of this study, the operating principle of the optoelectronic system, the system noise study, the recent R ampersand D efforts on radiation effect, temperature stability, and the realization of an integrated l x l6 optical modulator. The issue of photon source for driving such a large-scale optoelectronic modulators is a major concern. We will address this problem by examining different possible photon sources and comment on other possible alternative for signal transfer

Signal height in silicon pixel detectors irradiated with pions and protons

International Nuclear Information System (INIS)

Rohe, T.; Acosta, J.; Bean, A.; Dambach, S.; Erdmann, W.; Langenegger, U.; Martin, C.; Meier, B.; Radicci, V.; Sibille, J.; Trueb, P.

2010-01-01

Pixel detectors are used in the innermost part of multi-purpose experiments at the Large Hadron Collider (LHC) and are therefore exposed to the highest fluences of ionising radiation, which in this part of the detectors consists mainly of charged pions. The radiation hardness of the detectors has been tested thoroughly up to the fluences expected at the LHC. In case of an LHC upgrade the fluence will be much higher and it is not yet clear up to which radii the present pixel technology can be used. To establish such a limit, pixel sensors of the size of one CMS pixel readout chip (PSI46V2.1) have been bump bonded and irradiated with positive pions up to 6x10 14 n eq /cm 2 at PSI and with protons up to 5x10 15 n eq /cm 2 . The sensors were taken from production wafers of the CMS barrel pixel detector. They use n-type DOFZ material with a resistance of about 3.7kΩcm and an n-side read out. As the performance of silicon sensors is limited by trapping, the response to a Sr-90 source was investigated. The highly energetic beta-particles represent a good approximation to minimum ionising particles. The bias dependence of the signal for a wide range of fluences will be presented.

Development of FPGA-based digital signal processing system for radiation spectroscopy

International Nuclear Information System (INIS)

Lee, Pil Soo; Lee, Chun Sik; Lee, Ju Hahn

2013-01-01

We have developed an FPGA-based digital signal processing system that performs both online digital signal filtering and pulse-shape analysis for both particle and gamma-ray spectroscopy. Such functionalities were made possible by a state-of-the-art programmable logic device and system architectures employed. The system performance as measured, for example, in the system dead time and accuracy for pulse-height and rise-time determination, was evaluated with standard alpha- and gamma-ray sources using a CsI(Tl) scintillation detector. It is resulted that the present system has shown its potential application to various radiation-related fields such as particle identification, radiography, and radiation imaging. - Highlights: ► An FPGA-based digital processing system was developed for radiation spectroscopy. ► Our digital system has a 14-bit resolution and a 100-MHz sampling rate. ► The FPGA implements the online digital filtering and pulse-shape analysis. ► The pileup rejection is implemented in trigger logic before digital filtering process. ► Our digital system was verified in alpha-gamma measurements using a CsI detector

An example of e-p colliding machine experiments at TRISTAN

International Nuclear Information System (INIS)

1980-01-01

This is a design report of a possible detector system of the e-p colliding machine experiment at TRISTAN. The aim of this note is to know what kind of detectors should be developed and what kind of requirements the TRISTAN machines and the environmental supporting facilities should fulfill. (author)

Denoising of gravitational wave signals via dictionary learning algorithms

Science.gov (United States)

Torres-Forné, Alejandro; Marquina, Antonio; Font, José A.; Ibáñez, José M.

2016-12-01

Gravitational wave astronomy has become a reality after the historical detections accomplished during the first observing run of the two advanced LIGO detectors. In the following years, the number of detections is expected to increase significantly with the full commissioning of the advanced LIGO, advanced Virgo and KAGRA detectors. The development of sophisticated data analysis techniques to improve the opportunities of detection for low signal-to-noise-ratio events is, hence, a most crucial effort. In this paper, we present one such technique, dictionary-learning algorithms, which have been extensively developed in the last few years and successfully applied mostly in the context of image processing. However, to the best of our knowledge, such algorithms have not yet been employed to denoise gravitational wave signals. By building dictionaries from numerical relativity templates of both binary black holes mergers and bursts of rotational core collapse, we show how machine-learning algorithms based on dictionaries can also be successfully applied for gravitational wave denoising. We use a subset of signals from both catalogs, embedded in nonwhite Gaussian noise, to assess our techniques with a large sample of tests and to find the best model parameters. The application of our method to the actual signal GW150914 shows promising results. Dictionary-learning algorithms could be a complementary addition to the gravitational wave data analysis toolkit. They may be used to extract signals from noise and to infer physical parameters if the data are in good enough agreement with the morphology of the dictionary atoms.

Discriminating cosmic muons and X-rays based on rise time using a GEM detector

Science.gov (United States)

Wu, Hui-Yin; Zhao, Sheng-Ying; Wang, Xiao-Dong; Zhang, Xian-Ming; Qi, Hui-Rong; Zhang, Wei; Wu, Ke-Yan; Hu, Bi-Tao; Zhang, Yi

2016-08-01

Gas electron multiplier (GEM) detectors have been used in cosmic muon scattering tomography and neutron imaging over the last decade. In this work, a triple GEM device with an effective readout area of 10 cm × 10 cm is developed, and a method of discriminating between cosmic muons and X-rays based on rise time is tested. The energy resolution of the GEM detector is tested by 55Fe ray source to prove the GEM detector has a good performance. Analysis of the complete signal-cycles allows us to get the rise time and pulse heights. The experiment result indicates that cosmic muons and X-rays can be discriminated with an appropriate rise time threshold. Supported by National Natural Science Foundation of China (11135002, 11275235, 11405077, 11575073)

Fetal QRS extraction from abdominal recordings via model-based signal processing and intelligent signal merging

International Nuclear Information System (INIS)

Haghpanahi, Masoumeh; Borkholder, David A

2014-01-01

Noninvasive fetal ECG (fECG) monitoring has potential applications in diagnosing congenital heart diseases in a timely manner and assisting clinicians to make more appropriate decisions during labor. However, despite advances in signal processing and machine learning techniques, the analysis of fECG signals has still remained in its preliminary stages. In this work, we describe an algorithm to automatically locate QRS complexes in noninvasive fECG signals obtained from a set of four electrodes placed on the mother’s abdomen. The algorithm is based on an iterative decomposition of the maternal and fetal subspaces and filtering of the maternal ECG (mECG) components from the fECG recordings. Once the maternal components are removed, a novel merging technique is applied to merge the signals and detect the fetal QRS (fQRS) complexes. The algorithm was trained and tested on the fECG datasets provided by the PhysioNet/CinC challenge 2013. The final results indicate that the algorithm is able to detect fetal peaks for a variety of signals with different morphologies and strength levels encountered in clinical practice. (paper)

A Bayesian least squares support vector machines based framework for fault diagnosis and failure prognosis

Science.gov (United States)

Khawaja, Taimoor Saleem

A high-belief low-overhead Prognostics and Health Management (PHM) system is desired for online real-time monitoring of complex non-linear systems operating in a complex (possibly non-Gaussian) noise environment. This thesis presents a Bayesian Least Squares Support Vector Machine (LS-SVM) based framework for fault diagnosis and failure prognosis in nonlinear non-Gaussian systems. The methodology assumes the availability of real-time process measurements, definition of a set of fault indicators and the existence of empirical knowledge (or historical data) to characterize both nominal and abnormal operating conditions. An efficient yet powerful Least Squares Support Vector Machine (LS-SVM) algorithm, set within a Bayesian Inference framework, not only allows for the development of real-time algorithms for diagnosis and prognosis but also provides a solid theoretical framework to address key concepts related to classification for diagnosis and regression modeling for prognosis. SVM machines are founded on the principle of Structural Risk Minimization (SRM) which tends to find a good trade-off between low empirical risk and small capacity. The key features in SVM are the use of non-linear kernels, the absence of local minima, the sparseness of the solution and the capacity control obtained by optimizing the margin. The Bayesian Inference framework linked with LS-SVMs allows a probabilistic interpretation of the results for diagnosis and prognosis. Additional levels of inference provide the much coveted features of adaptability and tunability of the modeling parameters. The two main modules considered in this research are fault diagnosis and failure prognosis. With the goal of designing an efficient and reliable fault diagnosis scheme, a novel Anomaly Detector is suggested based on the LS-SVM machines. The proposed scheme uses only baseline data to construct a 1-class LS-SVM machine which, when presented with online data is able to distinguish between normal behavior

Machine interlock and protection system based on PLC for the SSRF linac

International Nuclear Information System (INIS)

Chou Wenjun; Zhou Dayong; Chen Jianfeng; Shen Liren; Liu Yajuan

2008-01-01

This paper describes a machine interlock and protection system used for accelerators based on EPICS (Experimental physics and industrial control system). The system is composed of a front-end computer and an FM-3R logic controller PLC. The alarm signal is passed by the hardware directly, and would be deal with PLC. The reporting, recording and analyst of the event are accomplished by EPICS control software. And PLC is linked to the EPICS by Internet. (authors)

Aging Detection of Electrical Point Machines Based on Support Vector Data Description

Directory of Open Access Journals (Sweden)

Jaewon Sa

2017-11-01

Full Text Available Electrical point machines (EPM must be replaced at an appropriate time to prevent the occurrence of operational safety or stability problems in trains resulting from aging or budget constraints. However, it is difficult to replace EPMs effectively because the aging conditions of EPMs depend on the operating environments, and thus, a guideline is typically not be suitable for replacing EPMs at the most timely moment. In this study, we propose a method of classification for the detection of an aging effect to facilitate the timely replacement of EPMs. We employ support vector data description to segregate data of “aged” and “not-yet-aged” equipment by analyzing the subtle differences in normalized electrical signals resulting from aging. Based on the before and after-replacement data that was obtained from experimental studies that were conducted on EPMs, we confirmed that the proposed method was capable of classifying machines based on exhibited aging effects with adequate accuracy.

A fax-machine amorphous silicon sensor for X-ray detection

Energy Technology Data Exchange (ETDEWEB)

Alberdi, J. [Association EURATOM/CIEMAT, Madrid (Spain); Barcala, J.M. [Association EURATOM/CIEMAT, Madrid (Spain); Chvatchkine, V. [Association EURATOM/CIEMAT, Madrid (Spain); Ioudine, I. [Association EURATOM/CIEMAT, Madrid (Spain); Molinero, A. [Association EURATOM/CIEMAT, Madrid (Spain); Navarrete, J.J. [Association EURATOM/CIEMAT, Madrid (Spain); Yuste, C. [Association EURATOM/CIEMAT, Madrid (Spain)

1996-10-01

Amorphous silicon detectors have been used, basically, as solar cells for energetics applications. As light detectors, linear sensors are used in fax and photocopier machines because they can be built with a large size, low price and have a high radiation hardness. Due to these performances, amorphous silicon detectors have been used as radiation detectors, and, presently, some groups are developing matrix amorphous silicon detectors with built-in electronics for medical X-ray applications. Our group has been working on the design and development of an X-ray image system based on a commercial fax linear amorphous silicon detector. The sensor scans the selected area and detects light produced by the X-ray in a scintillator placed on the sensor. Image-processing software produces a final image with better resolution and definition. (orig.).

Timing, Trigger and Control Systems for LHC Detectors

CERN Multimedia

2002-01-01

\\\\ \\\\At the LHC, precise bunch-crossing clock and machine orbit signals must be broadcast over distances of several km from the Prevessin Control Room to the four experiment areas and other destinations. At the LHC experiments themselves, quite extensive distribution systems are also required for the transmission of timing, trigger and control (TTC) signals to large numbers of front-end electronics controllers from a single location in the vicinity of the central trigger processor. The systems must control the detector synchronization and deliver the necessary fast signals and messages that are phased with the LHC clock, orbit or bunch structure. These include the bunch-crossing clock, level-1 trigger decisions, bunch and event numbers, as well as test signals and broadcast commands. A common solution to this TTC system requirement is expected to result in important economies of scale and permit a rationalization of the development, operational and support efforts required. LHC Common Project RD12 is developi...

Mining Data of Noisy Signal Patterns in Recognition of Gasoline Bio-Based Additives using Electronic Nose

Directory of Open Access Journals (Sweden)

Osowski Stanisław

2017-03-01

Full Text Available The paper analyses the distorted data of an electronic nose in recognizing the gasoline bio-based additives. Different tools of data mining, such as the methods of data clustering, principal component analysis, wavelet transformation, support vector machine and random forest of decision trees are applied. A special stress is put on the robustness of signal processing systems to the noise distorting the registered sensor signals. A special denoising procedure based on application of discrete wavelet transformation has been proposed. This procedure enables to reduce the error rate of recognition in a significant way. The numerical results of experiments devoted to the recognition of different blends of gasoline have shown the superiority of support vector machine in a noisy environment of measurement.

Diamond Detector Technology: Status and Perspectives

CERN Document Server

Reichmann, M; Artuso, M; Bachmair, F; Bäni, L; Bartosik, M; Beacham, J; Beck, H; Bellini, V; Belyaev, V; Bentele, B; Berdermann, E; Bergonzo, P; Bes, A; Brom, J-M; Bruzzi, M; Cerv, M; Chiodini, G; Chren, D; Cindro, V; Claus, G; Collot, J; Cumalat, J; Dabrowski, A; D'Alessandro, R; Dauvergne, D; de Boer, W; Dorfer, C; Dünser, M; Eremin, V; Eusebi, R; Forcolin, G; Forneris, J; Frais-Kölbl, H; Gallin-Martel, L; Gallin-Martel, M L; Gan, K K; Gastal, M; Giroletti, C; Goffe, M; Goldstein, J; Golubev, A; Gorišek, A; Grigoriev, E; Grosse-Knetter, J; Grummer, A; Gui, B; Guthoff, M; Haughton, I; Hiti, B; Hits, D; Hoeferkamp, M; Hofmann, T; Hosslet, J; Hostachy, J-Y; Hügging, F; Hutton, C; Jansen, H; Janssen, J; Kagan, H; Kanxheri, K; Kasieczka, G; Kass, R; Kassel, F; Kis, M; Konovalov, V; Kramberger, G; Kuleshov, S; Lacoste, A; Lagomarsino, S; Lo Giudice, A; Lukosi, E; Maazouzi, C; Mandic, I; Mathieu, C; Menichelli, M; Mikuž, M; Morozzi, A; Moss, J; Mountain, R; Murphy, S; Muškinja, M; Oh, A; Oliviero, P; Passeri, D; Pernegger, H; Perrino, R; Picollo, F; Pomorski, M; Potenza, R; Quadt, A; Re, A; Riley, G; Roe, S; Sanz-Becerra, D A; Scaringella, M; Schaefer, D; Schmidt, C J; Schnetzer, S; Sciortino, S; Scorzoni, A; Seidel, S; Servoli, L; Smith, S; Sopko, B; Sopko, V; Spagnolo, S; Spanier, S; Stenson, K; Stone, R; Sutera, C; Tannenwald, B; Taylor, A; Traeger, M; Tromson, D; Trischuk, W; Tuve, C; Uplegger, L; Velthuis, J; Venturi, N; Vittone, E; Wagner, S; Wallny, R; Wang, J C; Weingarten, J; Weiss, C; Wengler, T; Wermes, N; Yamouni, M; Zavrtanik, M

2018-01-01

The planned upgrade of the LHC to the High-Luminosity-LHC will push the luminosity limits above the original design values. Since the current detectors will not be able to cope with this environment ATLAS and CMS are doing research to find more radiation tolerant technologies for their innermost tracking layers. Chemical Vapour Deposition (CVD) diamond is an excellent candidate for this purpose. Detectors out of this material are already established in the highest irradiation regimes for the beam condition monitors at LHC. The RD42 collaboration is leading an effort to use CVD diamonds also as sensor material for the future tracking detectors. The signal behaviour of highly irradiated diamonds is presented as well as the recent study of the signal dependence on incident particle flux. There is also a recent development towards 3D detectors and especially 3D detectors with a pixel readout based on diamond sensors.

Onboard autonomous mineral detectors for Mars rovers

Science.gov (United States)

Gilmore, M. S.; Bornstein, B.; Castano, R.; Merrill, M.; Greenwood, J.

2005-12-01

Mars rovers and orbiters currently collect far more data than can be downlinked to Earth, which reduces mission science return; this problem will be exacerbated by future rovers of enhanced capabilities and lifetimes. We are developing onboard intelligence sufficient to extract geologically meaningful data from spectrometer measurements of soil and rock samples, and thus to guide the selection, measurement and return of these data from significant targets at Mars. Here we report on techniques to construct mineral detectors capable of running on current and future rover and orbital hardware. We focus on carbonate and sulfate minerals which are of particular geologic importance because they can signal the presence of water and possibly life. Sulfates have also been discovered at the Eagle and Endurance craters in Meridiani Planum by the Mars Exploration Rover (MER) Opportunity and at other regions on Mars by the OMEGA instrument aboard Mars Express. We have developed highly accurate artificial neural network (ANN) and Support Vector Machine (SVM) based detectors capable of identifying calcite (CaCO3) and jarosite (KFe3(SO4)2(OH)6) in the visible/NIR (350-2500 nm) spectra of both laboratory specimens and rocks in Mars analogue field environments. To train the detectors, we used a generative model to create 1000s of linear mixtures of library end-member spectra in geologically realistic percentages. We have also augmented the model to include nonlinear mixing based on Hapke's models of bidirectional reflectance spectroscopy. Both detectors perform well on the spectra of real rocks that contain intimate mixtures of minerals, rocks in natural field environments, calcite covered by Mars analogue dust, and AVIRIS hyperspectral cubes. We will discuss the comparison of ANN and SVM classifiers for this task, technical challenges (weathering rinds, atmospheric compositions, and computational complexity), and plans for integration of these detectors into both the Coupled Layer

Digital signal processing for He3 proportional counter

International Nuclear Information System (INIS)

Zeynalov, Sh.S.; Ahmadov, Q.S.

2010-01-01

Full text : Data acquisition systems for nuclear spectroscopy have traditionally been based on systems with analog shaping amplifiers followed by analog-to-digital converters. Recently, however, new systems based on digital signal processing make possible to replace the analog shaping and timing circuitry the numerical algorithms to derive properties of the pulse such as its amplitude. DSP is a fully numerical analysis of the detector pulse signals and this technique demonstrates significant advantages over analog systems in some circumstances. From a mathematical point of view, one can consider the signal evolution from the detector to the ADC as a sequence of transformations that can be described by precisely defined mathematical expressions. Digital signal processing with ADCs has the possibility to utilize further information on the signal pulses from radiation detectors. In the experiment each step of the signal generation in the 3He filled proportional counter was described using digital signal processing techniques (DSP). The electronic system has consisted of a detector, a preamplifier and a digital oscilloscope. The pulses from the detector were digitized using a digital storage oscilloscope. This oscilloscope allowed signal digitization with accuracy of 8 bit (256 levels) and with frequency of up to 5 * 10 8 samples/s. As a neutron source was used Cf-252. To obtain detector output current pulse I(t) created by the motions of the ions/electrons pairs was written an algorithm which can easily be programmed using modern computer programming languages.

Parsimonious Wavelet Kernel Extreme Learning Machine

Directory of Open Access Journals (Sweden)

Wang Qin

2015-11-01

Full Text Available In this study, a parsimonious scheme for wavelet kernel extreme learning machine (named PWKELM was introduced by combining wavelet theory and a parsimonious algorithm into kernel extreme learning machine (KELM. In the wavelet analysis, bases that were localized in time and frequency to represent various signals effectively were used. Wavelet kernel extreme learning machine (WELM maximized its capability to capture the essential features in “frequency-rich” signals. The proposed parsimonious algorithm also incorporated significant wavelet kernel functions via iteration in virtue of Householder matrix, thus producing a sparse solution that eased the computational burden and improved numerical stability. The experimental results achieved from the synthetic dataset and a gas furnace instance demonstrated that the proposed PWKELM is efficient and feasible in terms of improving generalization accuracy and real time performance.

Objective Auscultation of TCM Based on Wavelet Packet Fractal Dimension and Support Vector Machine

Science.gov (United States)

Yan, Jian-Jun; Wang, Yi-Qin; Liu, Guo-Ping; Yan, Hai-Xia; Xia, Chun-Ming; Shen, Xiaojing

2014-01-01

This study was conducted to illustrate that auscultation features based on the fractal dimension combined with wavelet packet transform (WPT) were conducive to the identification the pattern of syndromes of Traditional Chinese Medicine (TCM). The WPT and the fractal dimension were employed to extract features of auscultation signals of 137 patients with lung Qi-deficient pattern, 49 patients with lung Yin-deficient pattern, and 43 healthy subjects. With these features, the classification model was constructed based on multiclass support vector machine (SVM). When all auscultation signals were trained by SVM to decide the patterns of TCM syndromes, the overall recognition rate of model was 79.49%; when male and female auscultation signals were trained, respectively, to decide the patterns, the overall recognition rate of model reached 86.05%. The results showed that the methods proposed in this paper were effective to analyze auscultation signals, and the performance of model can be greatly improved when the distinction of gender was considered. PMID:24883068

Validation of Energy Expenditure Prediction Models Using Real-Time Shoe-Based Motion Detectors.

Science.gov (United States)

Lin, Shih-Yun; Lai, Ying-Chih; Hsia, Chi-Chun; Su, Pei-Fang; Chang, Chih-Han

2017-09-01

This study aimed to verify and compare the accuracy of energy expenditure (EE) prediction models using shoe-based motion detectors with embedded accelerometers. Three physical activity (PA) datasets (unclassified, recognition, and intensity segmentation) were used to develop three prediction models. A multiple classification flow and these models were used to estimate EE. The "unclassified" dataset was defined as the data without PA recognition, the "recognition" as the data classified with PA recognition, and the "intensity segmentation" as the data with intensity segmentation. The three datasets contained accelerometer signals (quantified as signal magnitude area (SMA)) and net heart rate (HR net ). The accuracy of these models was assessed according to the deviation between physically measured EE and model-estimated EE. The variance between physically measured EE and model-estimated EE expressed by simple linear regressions was increased by 63% and 13% using SMA and HR net , respectively. The accuracy of the EE predicted from accelerometer signals is influenced by the different activities that exhibit different count-EE relationships within the same prediction model. The recognition model provides a better estimation and lower variability of EE compared with the unclassified and intensity segmentation models. The proposed shoe-based motion detectors can improve the accuracy of EE estimation and has great potential to be used to manage everyday exercise in real time.

Machine Learning

CERN Multimedia

CERN. Geneva

2017-01-01

Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses on developing algorithms to identify patterns and regularities in data, and using these learned patterns to make predictions on new observations. Boosted by its industrial and commercial applications, the field of machine learning is quickly evolving and expanding. Recent advances have seen great success in the realms of computer vision, natural language processing, and broadly in data science. Many of these techniques have already been applied in particle physics, for instance for particle identification, detector monitoring, and the optimization of computer resources. Modern machine learning approaches, such as deep learning, are only just beginning to be applied to the analysis of High Energy Physics data to approach more and more complex problems. These classes will review the framework behind machine learning and discuss recent developments in the field.

PMT Dark Noise Monitoring System for Neutrino Detector Borexino Based on the Devicenet Protocol and WEB-Access

International Nuclear Information System (INIS)

Chepurnov, A.S.; Orekhov, D.I.; Maimistov, D.A.; Sabelnikov, A.A.; Etenko, A.V.

2006-01-01

Monitoring of PMT dark noise in a neutrino detector BOREXINO is a procedure that indicates condition of the detector. Based on CAN industrial network, top level DeviceNet protocol and WEB visualization, the dark noise monitoring system having 256 channels for the internal detector and for the external muon veto was created. The system is composed as a set of controllers, converting the PMT signals to frequency and transmitting them over Can network. The software is the stack of the DeviceNet protocols, providing the data collecting and transporting. Server-side scripts build web pages of user interface and graphical visualization of data

Automatic readout system for superheated emulsion based neutron detector

International Nuclear Information System (INIS)

Meena, J.P.; Parihar, A.; Vaijapurkar, S.G.; Mohan, Anand

2011-01-01

The paper presents a microcontroller based automatic reader system for neutron measurement using indigenously developed superheated emulsion detector. The system is designed for real time counting of bubbles formed in superheated emulsion detector. A piezoelectric transducer is used for sensing bubble acoustic during the nucleation. The front end of system is mainly consisting of specially designed signal conditioning unit, piezoelectric transducer, an amplifier, a high-pass filter, a differentiator, a comparator and monostable multivibrator. The system is based on PlC 18F6520 microcontroller having large internal SRAM, 10-bit internal ADC, I 2 C interface, UART/USART modules. The paper also describes the design of following microcontroller peripheral units viz temperature monitoring, battery monitoring, LCD display, keypad and a serial communication. The reader system measures and displays neutron dose and dose rate, number of bubble and elapsed time. The developed system can be used for detecting very low neutron leakage in the accelerators, nuclear reactors and nuclear submarines. The important features of system are compact, light weight, cost effective and high neutron sensitivity. The prototype was tested and evaluated by exposing to 241 Am-Be neutron source and results have been reported. (author)

Bridging the Gap between Social Animal and Unsocial Machine: A Survey of Social Signal Processing

NARCIS (Netherlands)

Vinciarelli, Alessandro; Pantic, Maja; Heylen, Dirk K.J.; Pelachaud, Catherine; Poggi, Isabella; D’Ericco, Francesca; Schröder, Marc

Social Signal Processing is the research domain aimed at bridging the social intelligence gap between humans and machines. This paper is the first survey of the domain that jointly considers its three major aspects, namely, modeling, analysis, and synthesis of social behavior. Modeling investigates

Boron-coated straws as a replacement for {sup 3}He-based neutron detectors

Energy Technology Data Exchange (ETDEWEB)

Lacy, Jeffrey L., E-mail: jlacy@proportionaltech.com [Proportional Technologies, Inc., 8022 El Rio Street, Houston, TX 77054 (United States); Athanasiades, Athanasios; Sun, Liang; Martin, Christopher S.; Lyons, Tom D.; Foss, Michael A.; Haygood, Hal B. [Proportional Technologies, Inc., 8022 El Rio Street, Houston, TX 77054 (United States)

2011-10-01

US and international government efforts to equip major seaports with large area neutron detectors, aimed to intercept the smuggling of nuclear materials, have precipitated a critical shortage of {sup 3}He gas. It is estimated that the annual demand of {sup 3}He for US security applications alone is more than the worldwide supply. This is strongly limiting the prospects of neutron science, safeguards, and other applications that rely heavily on {sup 3}He-based detectors. Clearly, alternate neutron detection technologies that can support large sensitive areas, and have low gamma sensitivity and low cost must be developed. We propose a low-cost technology based on long copper tubes (straws), coated on the inside with a thin layer of {sup 10}B-enriched boron carbide ({sup 10}B{sub 4}C). In addition to the high abundance of boron on Earth and low cost of {sup 10}B enrichment, the boron-coated straw (BCS) detector offers distinct advantages over conventional {sup 3}He-based detectors, and alternate technologies such as {sup 10}BF{sub 3} tubes and {sup 10}B-coated rigid tubes. These include better distribution inside moderator assemblies, many-times faster electronic signals, no pressurization, improved gamma-ray rejection, no toxic or flammable gases, and ease of serviceability. We present the performance of BCS detectors dispersed in a solid plastic moderator to address the need for portal monitoring. The design adopts the outer dimensions of currently deployed {sup 3}He-based monitors, but takes advantage of the small BCS diameter to achieve a more uniform distribution of neutron converter throughout the moderating material. We show that approximately 63 BCS detectors, each 205 cm long, distributed inside the moderator, can match or exceed the detection efficiency of typical monitors fitted with a 5 cm diameter {sup 3}He tube, 187 cm long, pressurized to 3 atm.

Kalman filtering of self-powered neutron detectors

International Nuclear Information System (INIS)

Kantrowitz, M.L.

1992-01-01

Pressurized water reactors employ a wide variety of in-core detectors to determine the neutronic behavior within the core. Among the detectors used are rhodium and vanadium self-powered detectors (SPDs), which are very accurate, but respond slowly to changes in neutron flux. This paper describes a new dynamic compensation algorithm, based on Kalman filtering, which converts delayed-responding rhodium and vanadium SPDs into prompt-responding detectors by reconstructing the dynamic flux signal sensed by the detectors from the prompt and delayed components. This conversion offers the possibility of utilizing current fixed in-core detector systems based on these delayed-responding detectors for core control and/or core protection functions without the need for fixed in-core detectors which are prompt-responding. As a result, the capabilities of current fixed in-core detector systems could be expanded significantly without a major hardware investment

Diamond Particle Detector Properties during High Fluence Material Damage Tests and their Future Applications for Machine Protection in the LHC

CERN Document Server

Burkart, F; Borburgh, J; Dehning, B; Di Castro, M; Griesmayer, E; Lechner, A; Lendaro, J; Loprete, F; Losito, R; Montesano, S; Schmidt, R; Wollmann, D; Zerlauth, M

2013-01-01

Experience with LHC machine protection (MP) during the last three years of operation shows that the MP systems sufficiently protect the LHC against damage in case of failures leading to beam losses with a time constant exceeding 1ms. An unexpected fast beam loss mechanism, called UFOs [1], was observed, which could potentially quench superconducting magnets. For such fast losses, but also for better understanding of slower losses, an improved understanding of the loss distribution within a bunch train is required [2]. Diamond particle detectors with bunch-by-bunch resolution and high dynamic range have been developed and successfully tested in the LHC and in experiments to quantify the damage limits of LHC components. This paper will focus on experience gained in use of diamond detectors. The properties of these detectors were measured during high-fluence material damage tests in CERN’s Hi-RadMat facility. The results will be discussed and compared to the cross-calibration with FLUKA simulations. Future app...

Diamond pad detector telescope for beam conditions and luminosity monitoring in ATLAS

Energy Technology Data Exchange (ETDEWEB)

Mikuz, M. [Jozef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana (Slovenia)], E-mail: Marko.Mikuz@ijs.si; Cindro, V.; Dolenc, I. [Jozef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana (Slovenia); Frais-Koelbl, H. [University of Applied Sciences Wiener Neustadt and Fotec, Wiener Neustadt (Austria); Gorisek, A. [CERN, Geneva (Switzerland); Griesmayer, E. [University of Applied Sciences Wiener Neustadt and Fotec, Wiener Neustadt (Austria); Kagan, H. [Ohio State University, Columbus (United States); Kramberger, G.; Mandic, I. [Jozef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana (Slovenia); Niegl, M. [University of Applied Sciences Wiener Neustadt and Fotec, Wiener Neustadt (Austria); Pernegger, H. [CERN, Geneva (Switzerland); Trischuk, W. [University of Toronto, Toronto (Canada); Weilhammer, P. [CERN, Geneva (Switzerland); Zavrtanik, M. [Jozef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana (Slovenia)

2007-09-01

Beam conditions and the potential detector damage resulting from their anomalies have pushed the LHC experiments to plan their own monitoring devices in addition to those provided by the machine. ATLAS decided to build a telescope composed of two stations with four diamond pad detector modules each, placed symmetrically around the interaction point at z={+-}183.8cm and r{approx}55mm ({eta}{approx}4.2). Equipped with fast electronics it allows time-of-flight separation of events resulting from beam anomalies from normally occurring p-p interactions. In addition it will provide a coarse measurement of the LHC luminosity in ATLAS. Ten detector modules have been assembled and subjected to tests, from characterization of bare diamonds to source and beam tests. Preliminary results of beam test in the CERN PS indicate a signal-to-noise ratio of 14{+-}2.

Diamond pad detector telescope for beam conditions and luminosity monitoring in ATLAS

International Nuclear Information System (INIS)

Mikuz, M.; Cindro, V.; Dolenc, I.; Frais-Koelbl, H.; Gorisek, A.; Griesmayer, E.; Kagan, H.; Kramberger, G.; Mandic, I.; Niegl, M.; Pernegger, H.; Trischuk, W.; Weilhammer, P.; Zavrtanik, M.

2007-01-01

Beam conditions and the potential detector damage resulting from their anomalies have pushed the LHC experiments to plan their own monitoring devices in addition to those provided by the machine. ATLAS decided to build a telescope composed of two stations with four diamond pad detector modules each, placed symmetrically around the interaction point at z=±183.8cm and r∼55mm (η∼4.2). Equipped with fast electronics it allows time-of-flight separation of events resulting from beam anomalies from normally occurring p-p interactions. In addition it will provide a coarse measurement of the LHC luminosity in ATLAS. Ten detector modules have been assembled and subjected to tests, from characterization of bare diamonds to source and beam tests. Preliminary results of beam test in the CERN PS indicate a signal-to-noise ratio of 14±2

Upgrade of the InGrid based X-ray detector for the CAST experiment

Energy Technology Data Exchange (ETDEWEB)

Desch, Klaus; Kaminski, Jochen; Krieger, Christoph; Schmidt, Sebastian [Physikalisches Institut, Universitaet Bonn, Nussallee 12, 53115 Bonn (Germany)

2016-07-01

The CERN Axion Solar Telescope (CAST) is a magnetic helioscope searching for solar axions and chameleons using the inverse Primakoff effect. The produced photons are in the low X-ray regime. Chameleon search demands high sensitivity to photons with less than 1 keV and a very low background rate. Several improvements to the detector design used in 2014/15 are envisaged for 2016. The readout system is to be improved by including a flash ADC to read out the analog signal induced on the grid. The pulse shape contains information about the longitudinal shape of the event in addition to the transverse shape given by the pixel read out. Tracks passing through the chip orthogonally resemble photons in transverse shape. A scintillator behind the detector will also allow cross referencing chip and and scintillator signals to further reduce background rates. Finally, a new X-ray window separating detector and X-ray telescope volume from one another will be installed. Due to the low expected signal rate, a window with very low X-ray opacity is needed. Due to a pressure difference of ∝1 bar between detector and the vacuum of CAST this is demanding. The usage of silicon nitride windows is being explored. The current progress of the detector upgrade will be presented.

Neural processing of auditory signals and modular neural control for sound tropism of walking machines

DEFF Research Database (Denmark)

Manoonpong, Poramate; Pasemann, Frank; Fischer, Joern

2005-01-01

and a neural preprocessing system together with a modular neural controller are used to generate a sound tropism of a four-legged walking machine. The neural preprocessing network is acting as a low-pass filter and it is followed by a network which discerns between signals coming from the left or the right....... The parameters of these networks are optimized by an evolutionary algorithm. In addition, a simple modular neural controller then generates the desired different walking patterns such that the machine walks straight, then turns towards a switched-on sound source, and then stops near to it....

Evaluating lane-by-lane gap-out based signal control for isolated intersection under stop-line, single and multiple advance detection systems

Directory of Open Access Journals (Sweden)

Chandan Keerthi Kancharla

2016-12-01

Full Text Available In isolated intersection’s actuated signal control, inductive loop detector layout plays a crucial role in providingthe vehicle information to the signal controller. Based on vehicle actuations at the detector, the green time is extended till a pre-defined threshold gap-out occurs. The Federal Highway Administration (FHWA proposed various guidelines for detec-tor layouts on low-speed and high-speed approaches. This paper proposes single and multiple advance detection schemes for low-speed traffic movements, that utilizes vehicle actuations from advance detectors located upstream of the stop-line, which are able to detect spill-back queues. The proposed detection schemes operate with actuated signal control based on lane-by-lane gap-out criteria. The performance of the proposed schemes is compared with FHWA’s stop-line and single advance detection schemes in the VISSIM simulation tool. Results have shown that the proposed single advance detection schemes showed improved performance in reducing travel time delay and average number of stops per vehicle under low volumes while the multiple advance detection scheme performed well under high volumes.

Academic Training - LHC luminosity upgrade: detector challenges

CERN Multimedia

Françoise Benz

2006-01-01

ACADEMIC TRAINING LECTURE SERIES 13, 14, 15, March, from 11:00 to 12:00 - 16 March from 10:00 to 12:00 Main Auditorium, bldg. 500 on 14, 15 March, Council Room on 13, 16 March LHC luminosity upgrade: detector challenges A. De Roeck / CERN-PH, D. Bortoletto / Purdue Univ. USA, R. Wigmans / Texas, Tech Univ. USA, W. Riegler / CERN-PH, W. Smith / Wisconsin Univ. USA The upgrade of the LHC machine towards higher luminosity (1035 cm-2s-1) has been studied over the last few years. These studies have investigated scenarios to achieve the increase in peak luminosity by an order of magnitude, as well as the physics potential of such an upgrade and the impact of a machine upgrade on the LHC DETECTORS. This series of lectures will cover the following topics: Physics motivation and machine scenarios for an order of magnitude increase in the LHC peak luminosity (lecture 1) Detector challenges including overview of ideas for R&D programs by the LHC experiments: tracking and calorimetry, other new detector ...

Support vector machine for automatic pain recognition

Science.gov (United States)

Monwar, Md Maruf; Rezaei, Siamak

2009-02-01

Facial expressions are a key index of emotion and the interpretation of such expressions of emotion is critical to everyday social functioning. In this paper, we present an efficient video analysis technique for recognition of a specific expression, pain, from human faces. We employ an automatic face detector which detects face from the stored video frame using skin color modeling technique. For pain recognition, location and shape features of the detected faces are computed. These features are then used as inputs to a support vector machine (SVM) for classification. We compare the results with neural network based and eigenimage based automatic pain recognition systems. The experiment results indicate that using support vector machine as classifier can certainly improve the performance of automatic pain recognition system.

Research on output signal of piezoelectric lead zirconate titanate detector using Monte Carlo method

Energy Technology Data Exchange (ETDEWEB)

Takechi, Seiji, E-mail: takechi@elec.eng.osaka-cu.ac.jp [Graduate School of Engineering, Osaka City University, Osaka 558-8585 (Japan); Mitsuhashi, Tomoaki; Miura, Yoshinori [Graduate School of Engineering, Osaka City University, Osaka 558-8585 (Japan); Miyachi, Takashi; Kobayashi, Masanori; Okudaira, Osamu [Planetary Exploration Research Center, Chiba Institute of Technology, Narashino, Chiba 275-0016 (Japan); Shibata, Hiromi [The Institute of Scientific and Industrial Research, Osaka University, Ibaraki, Osaka 567-0047 (Japan); Fujii, Masayuki [Famscience Co., Ltd., Tsukubamirai, Ibaraki 300-2435 (Japan); Okada, Nagaya [Honda Electronics Co., Ltd., Toyohashi, Aichi 441-3193 (Japan); Murakami, Takeshi; Uchihori, Yukio [National Institute of Radiological Sciences, Chiba 263-8555 (Japan)

2017-06-21

The response of a radiation detector fabricated from piezoelectric lead zirconate titanate (PZT) was studied. The response signal due to a single 400 MeV/n xenon (Xe) ion was assumed to have a simple form that was composed of two variables, the amplitude and time constant. These variables were estimated by comparing two output waveforms obtained from a computer simulation and an experiment on Xe beam irradiation. Their values appeared to be dependent on the beam intensity. - Highlights: • The performance of PZT detector was studied by irradiation of a 400 MeV/n Xe beam. • Monte Carlo simulation was used to examine the formation process of the output. • The response signal due to a single Xe ion was assumed to have a simple form. • The form was composed of two variables, the amplitude and time constant. • These variables appeared to be dependent on the beam intensity.

Variable reflectivity signal mirrors and signal response measurements

International Nuclear Information System (INIS)

Vine, Glenn de; Shaddock, Daniel A; McClelland, David E

2002-01-01

Future gravitational wave detectors will include some form of signal mirror in order to alter the signal response of the device. We introduce interferometer configurations which utilize a variable reflectivity signal mirror allowing a tunable peak frequency and variable signal bandwidth. A detector configured with a Fabry-Perot cavity as the signal mirror is compared theoretically with one using a Michelson interferometer for a signal mirror. A system for the measurement of the interferometer signal responses is introduced. This technique is applied to a power-recycled Michelson interferometer with resonant sideband extraction. We present broadband measurements of the benchtop prototype's signal response for a range of signal cavity detunings. This technique is also applicable to most other gravitational wave detector configurations

Variable reflectivity signal mirrors and signal response measurements

CERN Document Server

Vine, G D; McClelland, D E

2002-01-01

Future gravitational wave detectors will include some form of signal mirror in order to alter the signal response of the device. We introduce interferometer configurations which utilize a variable reflectivity signal mirror allowing a tunable peak frequency and variable signal bandwidth. A detector configured with a Fabry-Perot cavity as the signal mirror is compared theoretically with one using a Michelson interferometer for a signal mirror. A system for the measurement of the interferometer signal responses is introduced. This technique is applied to a power-recycled Michelson interferometer with resonant sideband extraction. We present broadband measurements of the benchtop prototype's signal response for a range of signal cavity detunings. This technique is also applicable to most other gravitational wave detector configurations.

A framework for detection of malicious software in Android handheld systems using machine learning techniques

OpenAIRE

Torregrosa García, Blas

2015-01-01

The present study aims at designing and developing new approaches to detect malicious applications in Android-based devices. More precisely, MaLDroide (Machine Learning-based Detector for Android malware), a framework for detection of Android malware based on machine learning techniques, is introduced here. It is devised to identify malicious applications. Este trabajo tiene como objetivo el diseño y el desarrollo de nuevas formas de detección de aplicaciones maliciosas en los dispositivos...

Multiplicity counting from fission detector signals with time delay effects

Science.gov (United States)

Nagy, L.; Pázsit, I.; Pál, L.

2018-03-01

In recent work, we have developed the theory of using the first three auto- and joint central moments of the currents of up to three fission chambers to extract the singles, doubles and triples count rates of traditional multiplicity counting (Pázsit and Pál, 2016; Pázsit et al., 2016). The objective is to elaborate a method for determining the fissile mass, neutron multiplication, and (α, n) neutron emission rate of an unknown assembly of fissile material from the statistics of the fission chamber signals, analogous to the traditional multiplicity counting methods with detectors in the pulse mode. Such a method would be an alternative to He-3 detector systems, which would be free from the dead time problems that would be encountered in high counting rate applications, for example the assay of spent nuclear fuel. A significant restriction of our previous work was that all neutrons born in a source event (spontaneous fission) were assumed to be detected simultaneously, which is not fulfilled in reality. In the present work, this restriction is eliminated, by assuming an independent, identically distributed random time delay for all neutrons arising from one source event. Expressions are derived for the same auto- and joint central moments of the detector current(s) as in the previous case, expressed with the singles, doubles, and triples (S, D and T) count rates. It is shown that if the time-dispersion of neutron detections is of the same order of magnitude as the detector pulse width, as they typically are in measurements of fast neutrons, the multiplicity rates can still be extracted from the moments of the detector current, although with more involved calibration factors. The presented formulae, and hence also the performance of the proposed method, are tested by both analytical models of the time delay as well as with numerical simulations. Methods are suggested also for the modification of the method for large time delay effects (for thermalised neutrons).

Radiation detectors based by polymer materials

International Nuclear Information System (INIS)

Cherestes, Margareta; Cherestes, Codrut; Constantinescu, Livia

2004-01-01

Scintillation counters make use of the property of certain chemical compounds to emit short light pulses after excitation produced by the passage of charged particles or photons of high energy. These flashes of light are detected by a photomultiplier tube that converts the photons into a voltage pulse. The light emitted from the detector also can be collected, focussed and dispersed by a CCD detector. The study of the evolution of the light emission and of the radiation damage under irradiation is a primary topic in the development of radiation hard polymer based scintillator. Polymer scintillator thin films are used in monitoring radiation beam intensities and simultaneous counting of different radiations. Radiation detectors have characteristics which depend on: the type of radiation, the energy of radiation, and the material of the detector. Three types of polymer thin films were studied: a polyvinyltoluene based scintillator, fluorinated polyimide and PMMA. (authors)

Digital signal processing for He3 proportional counter

International Nuclear Information System (INIS)

Ahmadov, Q.S.; Institute of Radiation Problems, ANAS, Baku

2011-01-01

Full text: Data acquisition systems for nuclear spectroscopy have traditionally been based on systems with analog shaping amplifiers followed by analog-to-digital converters. Recently, however, new systems based on digital signal processing allow us to replace the analog shaping and timing circuitry the numerical algorithms to derive properties of the pulse such as its amplitude. DSP is a fully numerical analysis of the detector pulse signals and this technique demonstrates significant advantages over analog systems in some circumstances. From a mathematical point of view, one can consider the signal evolution from the detector to the ADC as a sequence of transformations that can be described by precisely defined mathematical expressions.Digital signal processing with ADCs has the possibility to utilize further information on the signal pulses from radiation detectors [1] [2]. In the experiment each step of the signal generation in the 3He filled proportional counter was described using digital signal processing techniques (DSP). The electronic system has consisted of a detector, a preamplifier and a digital oscilloscope. The pulses from the detector were digitized using a OTSZS-02 (250USB)-4 digital storage oscilloscope from ZAO R UDNEV-SHILYAYEV . This oscilloscope allowed signal digitization with accuracy of 8 bit(256 levels) and with frequency of up to 5.10''8 samples/s. As a neutron source was used Cf-252.To obtain detector output current pulse I(t) created by the motions of the ions/electrons pairs was written an algorithm which can easily be programmed using modern computer programming languages

Machinery vibration signal denoising based on learned dictionary and sparse representation

International Nuclear Information System (INIS)

Guo, Liang; Gao, Hongli; Li, Jun; Huang, Haifeng; Zhang, Xiaochen

2015-01-01

Mechanical vibration signal denoising has been an import problem for machine damage assessment and health monitoring. Wavelet transfer and sparse reconstruction are the powerful and practical methods. However, those methods are based on the fixed basis functions or atoms. In this paper, a novel method is presented. The atoms used to represent signals are learned from the raw signal. And in order to satisfy the requirements of real-time signal processing, an online dictionary learning algorithm is adopted. Orthogonal matching pursuit is applied to extract the most pursuit column in the dictionary. At last, denoised signal is calculated with the sparse vector and learned dictionary. A simulation signal and real bearing fault signal are utilized to evaluate the improved performance of the proposed method through the comparison with kinds of denoising algorithms. Then Its computing efficiency is demonstrated by an illustrative runtime example. The results show that the proposed method outperforms current algorithms with efficiency calculation. (paper)

Development of signal processing electronics for self powered neutron detector signal with built-in on-line insulation monitoring [Paper No.:E3

International Nuclear Information System (INIS)

Das, Amitabha; Chaganty, S.P.

1993-01-01

Self powered neutron detectors (SPNDs) are employed to monitor in-core neutron flux in nuclear reactors for control, safety and mapping of in-core neutron flux. The d.c. current produced by SPND is converted into a proportional d.c. voltage, which in turn is used for various purposes stated above. This paper describes various features of the SPND amplifier developed in the Electronics Division of Bhabha Atomic Research Centre (BARC). It also outlines the principle of working of on-line monitoring of insulation resistance (IR) of the detector and associated mineral insulated (MI) and soft cables. The amplifier generates an alarm in case of the IR of the detector and the cable assembly falls below an accepted value or the cable is not connected to the amplifier and relieves the operator from periodic and manual checking of each of the individual detectors and ensures the validity of the signal for further processing. (author). 3 figs

Introduction to detectors

CERN Document Server

Walenta, Albert H

1995-01-01

Concepts for momentum measurements,particle identification and energy measurements (calorimeters) as well for imaging applications in medecine, biology and industry (non destructive testing) will be put into relation to the specific detection princip In particular the resolution for position, time, energy and intensity measurement and the efficiency will be discussed. Signal extraction,electronic signal processing and principles of information capture will close the logic circle to the input : the radiation properties.The lecture will provide some sources for data tables and small demonstration computer programs f The basic detector physics as interaction of radiation with matter, information transport via free charges,photons and phonons and the signal formation will be presented in some depth with emphasis on the influence on specific parameters for detector The lecture will cover the most popular detector principles, gas detectors (ion chambers,MPWC's and MSGC's), semiconductor detectors scintillators and ...

The quench detector on magnetic modulator for the UNK quench protection system

International Nuclear Information System (INIS)

Bolotin, I.M.; Enbaev, A.V.; Erokhin, A.N.; Gridasov, V.I.; Priyma, M.V.; Sychev, V.A.; Vasiliev, L.M.

1992-01-01

When designing and constructing superconducting high energy accelerators, the development of the Quench Detection System (QDS) for superconducting (SC) magnets becomes an important and critical problem. At present there is experience in developing such systems for the Tevatron (FNAL, USA) and HERA (Hamburg, Germany). The machines for more than 3 TeV-the UNK (Russia) and SSC (USA), which are presently under construction, have very large circumferences, 21 and 87 km, respectively. The QDS's, similar to those of the Tevatron, require a larger part of the active components of the electronic equipment be placed in the machine tunnel close to the magnets, and protected from irradiation or additional surface buildings will have to be constructed. In either case the cost of such a QDS increases. In addition the former ones reliability decreases and maintenance becomes more difficult. For such machines, a QDS in which the quench signal, in each superconducting magnet (SCM) or groups of SCM'S, is extracted with the help of a bridge circuit (BC) appears to be more suitable. The half coils of SCM's are connected as two arms of the bridge and the resistors placed in the vacuum vessels of the magnet cryostats are connected to the other two. The off-balance signal of each BC is enhanced with the help of magnetic amplifiers. This note describes the experimental prototype of a bridge-type Quench Detector (QD) based on a magnetic amplifier Magnetic Modulator (MM) type, allowing one not only to detect a quench in a SCM, but also making feasible a wider system capability, namely: to record the signals from all SC elements during a quench for further analysis of its causes; to check the presence of short circuits of the ring electromagnet bus relative to the cryostats and to localize their position

Machine Protection for the Experiments of the LHC

CERN Document Server

Appleby, R B

2010-01-01

The LHC stored beam contains 362 MJ of energy at the top beam energy of 7 TeV/c, presenting a significant risk to the components of the machine and the detectors. In response to this threat, a sophisticated system of machine protection has been developed to minimize the danger, and detect potentially dangerous situations. In this paper, the protection of the experiments in the LHC from the machine is considered, focusing on pilot beam strikes on the experiments during injection and on the dynamics of hardware failure with a circulating beam, with detailed time-domain calculations performed for LHC ring power converter failures and magnet quenches. The prospects for further integration of the machine protection and experimental protection systems are considered, along with the risk to nearbeam detectors from closed local bumps.

Steering a Tractor by Means of an EMG-Based Human-Machine Interface

Directory of Open Access Journals (Sweden)

Sergio Alonso-Garcia

2011-07-01

Full Text Available An electromiographic (EMG-based human-machine interface (HMI is a communication pathway between a human and a machine that operates by means of the acquisition and processing of EMG signals. This article explores the use of EMG-based HMIs in the steering of farm tractors. An EPOC, a low-cost human-computer interface (HCI from the Emotiv Company, was employed. This device, by means of 14 saline sensors, measures and processes EMG and electroencephalographic (EEG signals from the scalp of the driver. In our tests, the HMI took into account only the detection of four trained muscular events on the driver’s scalp: eyes looking to the right and jaw opened, eyes looking to the right and jaw closed, eyes looking to the left and jaw opened, and eyes looking to the left and jaw closed. The EMG-based HMI guidance was compared with manual guidance and with autonomous GPS guidance. A driver tested these three guidance systems along three different trajectories: a straight line, a step, and a circumference. The accuracy of the EMG-based HMI guidance was lower than the accuracy obtained by manual guidance, which was lower in turn than the accuracy obtained by the autonomous GPS guidance; the computed standard deviations of error to the desired trajectory in the straight line were 16 cm, 9 cm, and 4 cm, respectively. Since the standard deviation between the manual guidance and the EMG-based HMI guidance differed only 7 cm, and this difference is not relevant in agricultural steering, it can be concluded that it is possible to steer a tractor by an EMG-based HMI with almost the same accuracy as with manual steering.

A Review of Virtual Machine Attack Based on Xen

Directory of Open Access Journals (Sweden)

Ren xun-yi

2016-01-01

Full Text Available Virtualization technology as the foundation of cloud computing gets more and more attention because the cloud computing has been widely used. Analyzing the threat with the security of virtual machine and summarizing attack about virtual machine based on XEN to predict visible security hidden recently. Base on this paper can provide a reference for the further research on the security of virtual machine.

Three Alternative Symbol-Lock Detectors

Science.gov (United States)

Shihabi, Mazen M.; Hinedi, Sami M.; Shah, Biren N.

1993-01-01

Three symbol-lock detectors proposed as alternatives in advanced receivers processing non-return-to-zero binary data signals. Two perform operations similar to those of older square-law and absolute-value types. However, integrals computed during nonoverlapping symbol periods and, therefore, only one integrator needed in each such detector. Proposed detectors simpler, but performances worse because noises in overlapping samples correlated, whereas noises in nonoverlapping samples not correlated. Third detector is signal-power-estimator type. Signal integrated during successive half symbol cycles, and therefore only one integrator needed. Half-cycle integrals multiplied to eliminate effect of symbol polarity, and products accumulated during M-cycle observation period to smooth out estimate of signal power. If estimated signal power exceeds threshold, delta, then lock declared.

A new configuration of the Moxon-Rae detector based on Si detector

International Nuclear Information System (INIS)

Niu, H.; Hsu, J.Y.; Liang, J.H.; Yuan, L.G.

2002-01-01

A new Moxon-Rae detector configuration based on Si semiconductor detector was proposed in this paper. Three γ-ray sources, 137 Cs, 60 Co, and 24 Na, were employed to make actual measurements using the new Moxon-Rae detector. The measured pulse height spectra and detection efficiencies were compared with the EGS4 simulated values. The results revealed that the proposed new configuration is indeed a successful method and specially a useful technique for higher energy γ-ray measurement

A Field Programmable Gate Array-Based Reconfigurable Smart-Sensor Network for Wireless Monitoring of New Generation Computer Numerically Controlled Machines

Directory of Open Access Journals (Sweden)

Ion Stiharu

2010-08-01

Full Text Available Computer numerically controlled (CNC machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA-based sensor node.

A Field Programmable Gate Array-Based Reconfigurable Smart-Sensor Network for Wireless Monitoring of New Generation Computer Numerically Controlled Machines

Science.gov (United States)

Moreno-Tapia, Sandra Veronica; Vera-Salas, Luis Alberto; Osornio-Rios, Roque Alfredo; Dominguez-Gonzalez, Aurelio; Stiharu, Ion; de Jesus Romero-Troncoso, Rene

2010-01-01

Computer numerically controlled (CNC) machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA)-based sensor node. PMID:22163602

Real-time power angle determination of salient-pole synchronous machine based on air gap measurements

Energy Technology Data Exchange (ETDEWEB)

Despalatovic, Marin; Jadric, Martin; Terzic, Bozo [FESB University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, R. Boskovica bb, 21000 Split (Croatia)

2008-11-15

This paper presents a new method for the real-time power angle determination of the salient-pole synchronous machines. This method is based on the terminal voltage and air gap measurements, which are the common features of the hydroturbine generator monitoring system. The raw signal of the air gap sensor is used to detect the rotor displacement with reference to the fundamental component of the terminal voltage. First, the algorithm developed for the real-time power angle determination is tested using the synthetic data obtained by the standard machine model simulation. Thereafter, the experimental investigation is carried out on the 26 MVA utility generator. The validity of the method is verified by comparing with another method, which is based on a tooth gear mounted on the rotor shaft. The proposed real-time algorithm has an adequate accuracy and needs a very short processing time. For applications that do not require real-time processing, such as the estimation of the synchronous machine parameters, the accuracy is additionally increased by applying an off-line data-processing algorithm. (author)

Simulation study of signal formation in position sensitive planar p-on-n silicon detectors after short range charge injection

International Nuclear Information System (INIS)

Peltola, T.; Eremin, V.; Verbitskaya, E.; Härkönen, J.

2017-01-01

Segmented silicon detectors (micropixel and microstrip) are the main type of detectors used in the inner trackers of Large Hadron Collider (LHC) experiments at CERN. Due to the high luminosity and eventual high fluence of energetic particles, detectors with fast response to fit the short shaping time of 20–25 ns and sufficient radiation hardness are required. Charge collection measurements carried out at the Ioffe Institute have shown a reversal of the pulse polarity in the detector response to short-range charge injection. Since the measured negative signal is about 30–60% of the peak positive signal, the effect strongly reduces the CCE even in non-irradiated detectors. For further investigation of the phenomenon the measurements have been reproduced by TCAD simulations. As for the measurements, the simulation study was applied for the p-on-n strip detectors similar in geometry to those developed for the ATLAS experiment and for the Ioffe Institute designed p-on-n strip detectors with each strip having a window in the metallization covering the p + implant, allowing the generation of electron-hole pairs under the strip implant. Red laser scans across the strips and the interstrip gap with varying laser diameters and Si-SiO 2 interface charge densities ( Q f ) were carried out. The results verify the experimentally observed negative response along the scan in the interstrip gap. When the laser spot is positioned on the strip p + implant the negative response vanishes and the collected charge at the active strip increases respectively. The simulation results offer a further insight and understanding of the influence of the oxide charge density in the signal formation. The main result of the study is that a threshold value of Q f , that enables negligible losses of collected charges, is defined. The observed effects and details of the detector response for different charge injection positions are discussed in the context of Ramo's theorem.

Simulation study of signal formation in position sensitive planar p-on-n silicon detectors after short range charge injection

Science.gov (United States)

Peltola, T.; Eremin, V.; Verbitskaya, E.; Härkönen, J.

2017-09-01

Segmented silicon detectors (micropixel and microstrip) are the main type of detectors used in the inner trackers of Large Hadron Collider (LHC) experiments at CERN. Due to the high luminosity and eventual high fluence of energetic particles, detectors with fast response to fit the short shaping time of 20-25 ns and sufficient radiation hardness are required. Charge collection measurements carried out at the Ioffe Institute have shown a reversal of the pulse polarity in the detector response to short-range charge injection. Since the measured negative signal is about 30-60% of the peak positive signal, the effect strongly reduces the CCE even in non-irradiated detectors. For further investigation of the phenomenon the measurements have been reproduced by TCAD simulations. As for the measurements, the simulation study was applied for the p-on-n strip detectors similar in geometry to those developed for the ATLAS experiment and for the Ioffe Institute designed p-on-n strip detectors with each strip having a window in the metallization covering the p+ implant, allowing the generation of electron-hole pairs under the strip implant. Red laser scans across the strips and the interstrip gap with varying laser diameters and Si-SiO2 interface charge densities (Qf) were carried out. The results verify the experimentally observed negative response along the scan in the interstrip gap. When the laser spot is positioned on the strip p+ implant the negative response vanishes and the collected charge at the active strip increases respectively. The simulation results offer a further insight and understanding of the influence of the oxide charge density in the signal formation. The main result of the study is that a threshold value of Qf, that enables negligible losses of collected charges, is defined. The observed effects and details of the detector response for different charge injection positions are discussed in the context of Ramo's theorem.

A Machine Learning Approach to the Detection of Pilot’s Reaction to Unexpected Events Based on EEG Signals

Directory of Open Access Journals (Sweden)

Bartosz Binias

2018-01-01

Full Text Available This work considers the problem of utilizing electroencephalographic signals for use in systems designed for monitoring and enhancing the performance of aircraft pilots. Systems with such capabilities are generally referred to as cognitive cockpits. This article provides a description of the potential that is carried by such systems, especially in terms of increasing flight safety. Additionally, a neuropsychological background of the problem is presented. Conducted research was focused mainly on the problem of discrimination between states of brain activity related to idle but focused anticipation of visual cue and reaction to it. Especially, a problem of selecting a proper classification algorithm for such problems is being examined. For that purpose an experiment involving 10 subjects was planned and conducted. Experimental electroencephalographic data was acquired using an Emotiv EPOC+ headset. Proposed methodology involved use of a popular method in biomedical signal processing, the Common Spatial Pattern, extraction of bandpower features, and an extensive test of different classification algorithms, such as Linear Discriminant Analysis, k-nearest neighbors, and Support Vector Machines with linear and radial basis function kernels, Random Forests, and Artificial Neural Networks.

The influence of anisotropic electron drift velocity on the signal shapes of closed-end HPGe detectors

CERN Document Server

Mihailescu, L; Lieder, R M; Brands, H; Jaeger, H

2000-01-01

This study is concerned with the anisotropy of the electron drift velocity in germanium crystals at high electric fields and low temperature, and its influence on the charge collection process in n-type, high-purity germanium (HPGe) detectors of closed-end, coaxial geometry. The electron trajectories inside HPGe detectors are simulated using a phenomenological model to calculate the dependence of the drift velocity on the angle between the electric field and the crystal orientation. The resulting induced currents and pulse shapes for a given detector geometry and preamplifier bandwidth are compared to experiment. Experimentally, the dependence of the pulse shapes on the conductivity anisotropy in closed-end HPGe detectors was observed. The experimental data on pulse shapes were obtained by sampling preamplifier signals of an encapsulated, hexaconical EUROBALL detector, which was irradiated by collimated sup 2 sup 2 Na and sup 2 sup 4 sup 1 Am sources. The crystal orientation was measured by neutron reflection...

Operation of an InGrid based X-ray detector at the CAST experiment

Directory of Open Access Journals (Sweden)

Krieger Christoph

2018-01-01

During operation at the experiment, background rates in the order of 10−5 keV−1 cm−2 s−1 have been achieved by application of a likelihood based method discriminating the non-photon background originating mostly from cosmic rays. For continued operation in 2016, an upgraded InGrid based detector is to be installed among other improvements including decoupling and sampling of the signal induced on the grid as well as a veto scintillator to further lower the observed background rates and improving sensitivity.

Machine intelligence and knowledge bases

Energy Technology Data Exchange (ETDEWEB)

Furukawa, K

1981-09-01

The basic functions necessary in machine intelligence are a knowledge base and a logic programming language such as PROLOG using deductive reasoning. Recently inductive reasoning based on meta knowledge and default reasoning have been developed. The creative thought model of Lenit is reviewed and the concept of knowledge engineering is introduced. 17 references.

Direct Dark Matter Detection through the use of a Xenon Based TPC Detector

Science.gov (United States)

Daniel, Jonathan; Akerib, Daniel; LZ group at SLAC

2018-01-01

The vast majority of matter in the universe is unaccounted for. Only 15% of the universe's mass density is visible matter, while the other 85% is Dark Matter (DM). The Weakly Interacting Massive Particle (WIMP) is currently the frontrunner of the DM candidates. The Large Underground Xenon (LUX) and next generation LUX-ZEPLIN (LZ) experiments are designed to directly detect WIMPs. Both experiments are xenon-based Time Projection Chambers (TPC) used to observe possible WIMP interactions. These interactions produce photons and electrons with the photons being collected in a set of two photomultiplier tube (PMT) arrays and the electrons drifted upwards in the detector by a strong electric field to create a secondary production of photons in gaseous xenon. These two populations of photons are classified as S1 and S2 signals, respectively. Using these signals we reconstruct the energy and position of the interaction and in doing so we can eliminate background events that would otherwise “light up” the detector. My participation in the experiment, while at SLAC, was the creation of the grids that produce the large electric field, along with additional lab activities aimed at testing the grids. While at Stan State, I work on background modeling in order to distinguish a possible WIMP signal from ambient backgrounds.

Statistical Signal Processing by Using the Higher-Order Correlation between Sound and Vibration and Its Application to Fault Detection of Rotational Machine

Directory of Open Access Journals (Sweden)

Hisako Masuike

2008-01-01

Full Text Available In this study, a stochastic diagnosis method based on the changing information of not only a linear correlation but also a higher-order nonlinear correlation is proposed in a form suitable for online signal processing in time domain by using a personal computer, especially in order to find minutely the mutual relationship between sound and vibration emitted from rotational machines. More specifically, a conditional probability hierarchically reflecting various types of correlation information is theoretically derived by introducing an expression on the multidimensional probability distribution in orthogonal expansion series form. The effectiveness of the proposed theory is experimentally confirmed by applying it to the observed data emitted from a rotational machine driven by an electric motor.

Temperature estimation of induction machines based on wireless sensor networks

Directory of Open Access Journals (Sweden)

Y. Huang

2018-04-01

Full Text Available In this paper, a fourth-order Kalman filter (KF algorithm is implemented in the wireless sensor node to estimate the temperatures of the stator winding, the rotor cage and the stator core in the induction machine. Three separate wireless sensor nodes are used as the data acquisition systems for different input signals. Six Hall sensors are used to acquire the three-phase stator currents and voltages of the induction machine. All of them are processed to root mean square (rms in ampere and volt. A rotary encoder is mounted for the rotor speed and Pt-1000 is used for the temperature of the coolant air. The processed signals in the physical unit are transmitted wirelessly to the host wireless sensor node, where the KF is implemented with fixed-point arithmetic in Contiki OS. Time-division multiple access (TDMA is used to make the wireless transmission more stable. Compared to the floating-point implementation, the fixed-point implementation has the same estimation accuracy at only about one-fifth of the computation time. The temperature estimation system can work under any work condition as long as there are currents through the machine. It can also be rebooted for estimation even when wireless transmission has collapsed or packages are missing.

Accurate and independent spectral response scale based on silicon trap detectors and spectrally invariant detectors

International Nuclear Information System (INIS)

Gran, Jarle

2005-01-01

The study aims to establish an independent high accuracy spectral response scale over a broad spectral range based on standard laboratory equipment at a moderate cost. This had to be done by a primary method, where the responsivity of the detector is linked to fundamental constants. Summary, conclusion and future directions: In this thesis it has been demonstrated that an independent spectral response scale from the visual to the IR based on simple relative measurements can be established. The accuracy obtained by the hybrid self-calibration method demonstrates that state of the art accuracy is obtained with self-calibration principles. A calculable silicon trap detector with low internal losses over a wide spectral range is needed to establish the scale, in addition to a linear, spectrally independent detector with a good signal to noise ratio. By fitting the parameters in the responsivity model to a purely relative measurement we express the spectral response in terms of fundamental constants with a known uncertainty This is therefore a primary method. By applying a digital filter on the relative measurements of the InGaAs detectors in the infrared reduces the standard deviation by 30 %. In addition, by optimising the necessary scaling constant converting the relative calibration to absolute values, we have managed to establish an accurate and cost efficient spectral response scale in the IR. The full covariance analysis, which takes into account the correlation in the absolute values of the silicon detector, the correlation caused by the filter and the scaling constant, shows that the spectral response scale established in the infrared with InGaAs detectors is done with high accuracy. A similar procedure can be used in the UV, though it has not been demonstrated here. In fig. 10 the responsitivities of the detectors (a) and their associated uncertainties (b) at the 1 sigma level of confidence is compared for the three publications. We see that the responsivity

Signal-to-noise ratio and detective quantum efficiency determination by and alternative use of photographic detectors

International Nuclear Information System (INIS)

Burgudzhiev, Z.; Koleva, D.

1986-01-01

A known theoretical model of an alternative use of silver-halogenid pnotographic emulsions in which the number of the granulas forming the photographic image is used as a detector output instead of the microdensiometric blackening density is applied to some real photographic emulsions. It is found that by this use the Signal-to-Noise ratio of the photographic detector can be increased to about 5 times while its detective quantum efficiency can reach about 20%, being close to that of some photomultipliers

Research of optical coherence tomography microscope based on CCD detector

Science.gov (United States)

Zhang, Hua; Xu, Zhongbao; Zhang, Shuomo

2008-12-01

The reference wave phase was modulated with a sinusoidal vibrating mirror attached to a Piezoelectric Transducer (PZT), the integration was performed by a CCD, and the charge storage period of the CCD image sensor was one-quarter period of the sinusoidal phase modulation. With the frequency- synchronous detection technique, four images (four frames of interference pattern) were recorded during one period of the phase modulation. In order to obtain the optimum modulation parameter, the values of amplitude and phase of the sinusoidal phase modulation were determined by considering the measurement error caused by the additive noise contained in the detected values. The PZT oscillation was controlled by a closed loop control system based on PID controller. An ideal discrete digital sine function at 50Hz with adjustable amplitude was used to adjust the vibrating of PZT, and a digital phase shift techniques was used to adjust vibrating phase of PZT so that the phase of the modulation could reach their optimum values. The CCD detector was triggered with software at 200Hz. Based on work above a small coherent signal masked by the preponderant incoherent background with a CCD detector was obtained.

High Frequency Amplitude Detector for GMI Magnetic Sensors

Directory of Open Access Journals (Sweden)

Aktham Asfour

2014-12-01

Full Text Available A new concept of a high-frequency amplitude detector and demodulator for Giant-Magneto-Impedance (GMI sensors is presented. This concept combines a half wave rectifier, with outstanding capabilities and high speed, and a feedback approach that ensures the amplitude detection with easily adjustable gain. The developed detector is capable of measuring high-frequency and very low amplitude signals without the use of diode-based active rectifiers or analog multipliers. The performances of this detector are addressed throughout the paper. The full circuitry of the design is given, together with a comprehensive theoretical study of the concept and experimental validation. The detector has been used for the amplitude measurement of both single frequency and pulsed signals and for the demodulation of amplitude-modulated signals. It has also been successfully integrated in a GMI sensor prototype. Magnetic field and electrical current measurements in open- and closed-loop of this sensor have also been conducted.

Intravascular imaging with a storage phosphor detector

Energy Technology Data Exchange (ETDEWEB)

Shikhaliev, Polad M; Petrek, Peter; Matthews, Kenneth L II; Fritz, Shannon G [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, LA (United States); Bujenovic, L Steven [PET Imaging Center, Our Lady of the Lake Medical Center, Baton Rouge, LA (United States); Xu Tong, E-mail: pshikhal@lsu.ed [Department of Physics, Carleton University, Ottawa (Canada)

2010-05-21

The aim of this study is to develop and test an intravascular positron imaging system based on a storage phosphor detector for imaging and detecting vulnerable plaques of human coronary arteries. The radiotracer F18-FDG accumulates in vulnerable plaques with inflammation of the overlying cap. The vulnerable plaques can, therefore, be imaged by recording positrons emitted from F18-FDG with a detector inserted into the artery. A prototype intravascular detector was constructed based on storage phosphor. The detector uses a flexible storage phosphor tube with 55 mm length, 2 mm diameter and 0.28 mm wall thickness. The intravascular detector is guided into the vessel using x-ray fluoroscopy and the accumulated x-ray signal must be erased prior to positron imaging. For this purpose, a light diffuser, 0.9 mm in diameter and 55 mm in length, was inserted into the detector tube. The light diffuser was connected to a laser source through a 2 m long optical fiber. The diffuser redirected the 0.38 W laser light to the inner surface of the phosphor detector to erase it. A heart phantom with 300 cm{sup 3} volume and three coronary arteries with 3.2 mm diameter and with several plaques was constructed. FDG solution with 0.5 {mu}Ci cm{sup -3} activity concentration was filled in the heart and coronary arteries. The detector was inserted in a coronary artery and the signal from the plaques and surrounding background activity was recorded for 2 min. Then the phosphor detector was extracted and read out using a storage phosphor reader. The light diffuser erased the signal resulting from fluoroscopic exposure to level below that encountered during positron imaging. Vulnerable plaques with area activities higher than 1.2 nCi mm{sup -2} were visualized by the detector. This activity is a factor of 10-20 lower than that expected in human vulnerable plaques. The detector was able to image the internal surface of the coronary vessels with 50 mm length and 360{sup 0} circumference. Spatial

Epileptic seizure detection from EEG signals with phase-amplitude cross-frequency coupling and support vector machine

Science.gov (United States)

Liu, Yang; Wang, Jiang; Cai, Lihui; Chen, Yingyuan; Qin, Yingmei

2018-03-01

As a pattern of cross-frequency coupling (CFC), phase-amplitude coupling (PAC) depicts the interaction between the phase and amplitude of distinct frequency bands from the same signal, and has been proved to be closely related to the brain’s cognitive and memory activities. This work utilized PAC and support vector machine (SVM) classifier to identify the epileptic seizures from electroencephalogram (EEG) data. The entropy-based modulation index (MI) matrixes are used to express the strength of PAC, from which we extracted features as the input for classifier. Based on the Bonn database, which contains five datasets of EEG segments obtained from healthy volunteers and epileptic subjects, a 100% classification accuracy is achieved for identifying seizure ictal from healthy data, and an accuracy of 97.67% is reached in the classification of ictal EEG signals from inter-ictal EEGs. Based on the CHB-MIT database which is a group of continuously recorded epileptic EEGs by scalp electrodes, a 97.50% classification accuracy is obtained and a raising sign of MI value is found at 6s before seizure onset. The classification performance in this work is effective, and PAC can be considered as a useful tool for detecting and predicting the epileptic seizures and providing reference for clinical diagnosis.

Microscopic Simulation of Particle Detectors

CERN Document Server

Schindler, Heinrich

Detailed computer simulations are indispensable tools for the development and optimization of modern particle detectors. The interaction of particles with the sensitive medium, giving rise to ionization or excitation of atoms, is stochastic by its nature. The transport of the resulting photons and charge carriers, which eventually generate the observed signal, is also subject to statistical fluctuations. Together with the readout electronics, these processes - which are ultimately governed by the atomic cross-sections for the respective interactions - pose a fundamental limit to the achievable detector performance. Conventional methods for calculating electron drift lines based on macroscopic transport coefficients used to provide an adequate description for traditional gas-based particle detectors such as wire chambers. However, they are not suitable for small-scale devices such as micropattern gas detectors, which have significantly gained importance in recent years. In this thesis, a novel approach, bas...

Kalman filtering for rhodium self-powered neutron detectors

International Nuclear Information System (INIS)

Kantrowitz, M.L.

1988-01-01

Rhodium self-powered neutron detectors are utilized in many pressurized water reactors to determine the neutronic behavior within the core. In order to compensate for the inherent time delay associated with the response of these detectors, a dynamic compensation algorithm is currently used in Combustion Engineering plants to reconstruct the dynamic flux signal which is being sensed by the rhodium detectors. This paper describes a new dynamic compensation algorithm, based on Kalman filtering, which improves on the noise gain and response time characteristics of the algorithm currently used, and offers the possibility of utilizing the proven rhodium detector based fixed in-core detector system as an integral part of advanced core control and/or protection systems

First evaluation of low frequency noise measurements of in core detector signals in the measuring assembly Rheinsberg

International Nuclear Information System (INIS)

Collatz, S.

1982-01-01

Reactor noise spectra of in core neutron detectors are measured in the low frequency range (0.03 Hz to 1 Hz) and evaluated. The increase of the effective noise signal value is due to pressure oscillations or oscillations of special steam volume portions. Thus boiling monitoring of reactor cores in PWR type reactors may be possible, if the low frequency noise of the whole set of in core detectors is taken into account

Prospects for SUSY discovery based on inclusive searches with the ATLAS detector

International Nuclear Information System (INIS)

Ventura, Andrea

2009-01-01

The search for Supersymmetry (SUSY) among the possible scenarios of new physics is one of the most relevant goals of the ATLAS experiment running at CERN's Large Hadron Collider. In the present work the expected prospects for discovering SUSY with the ATLAS detector are reviewed, in particular for the first fb -1 of collected integrated luminosity. All studies and results reported here are based on inclusive search analyses realized with Monte Carlo signal and background data simulated through the ATLAS apparatus.

Enhancing spatial resolution of 18F positron imaging with the Timepix detector by classification of primary fired pixels using support vector machine

International Nuclear Information System (INIS)

Wang, Qian; Liu, Zhen; Ziegler, Sibylle I; Shi, Kuangyu

2015-01-01

Position-sensitive positron cameras using silicon pixel detectors have been applied for some preclinical and intraoperative clinical applications. However, the spatial resolution of a positron camera is limited by positron multiple scattering in the detector. An incident positron may fire a number of successive pixels on the imaging plane. It is still impossible to capture the primary fired pixel along a particle trajectory by hardware or to perceive the pixel firing sequence by direct observation. Here, we propose a novel data-driven method to improve the spatial resolution by classifying the primary pixels within the detector using support vector machine. A classification model is constructed by learning the features of positron trajectories based on Monte-Carlo simulations using Geant4. Topological and energy features of pixels fired by 18 F positrons were considered for the training and classification. After applying the classification model on measurements, the primary fired pixels of the positron tracks in the silicon detector were estimated. The method was tested and assessed for [ 18 F]FDG imaging of an absorbing edge protocol and a leaf sample. The proposed method improved the spatial resolution from 154.6   ±   4.2 µm (energy weighted centroid approximation) to 132.3   ±   3.5 µm in the absorbing edge measurements. For the positron imaging of a leaf sample, the proposed method achieved lower root mean square error relative to phosphor plate imaging, and higher similarity with the reference optical image. The improvements of the preliminary results support further investigation of the proposed algorithm for the enhancement of positron imaging in clinical and preclinical applications. (paper)

Parametric roll resonance monitoring using signal-based detection

DEFF Research Database (Denmark)

Galeazzi, Roberto; Blanke, Mogens; Falkenberg, Thomas

2015-01-01

Extreme roll motion of ships can be caused by several phenomena, one of which is parametric roll resonance. Several incidents occurred unexpectedly around the millennium and caused vast fiscal losses on large container vessels. The phenomenon is now well understood and some consider parametric roll...... algorithms in real conditions, and to evaluate the frequency of parametric roll events on the selected vessels. Detection performance is scrutinised through the validation of the detected events using owners’ standard methods, and supported by available wave radar data. Further, a bivariate statistical...... analysis of the outcome of the signal-based detectors is performed to assess the real life false alarm probability. It is shown that detection robustness and very low false warning rates are obtained. The study concludes that small parametric roll events are occurring, and that the proposed signal...

Emotion Recognition of Speech Signals Based on Filter Methods

Directory of Open Access Journals (Sweden)

Narjes Yazdanian

2016-10-01

Full Text Available Speech is the basic mean of communication among human beings.With the increase of transaction between human and machine, necessity of automatic dialogue and removing human factor has been considered. The aim of this study was to determine a set of affective features the speech signal is based on emotions. In this study system was designs that include three mains sections, features extraction, features selection and classification. After extraction of useful features such as, mel frequency cepstral coefficient (MFCC, linear prediction cepstral coefficients (LPC, perceptive linear prediction coefficients (PLP, ferment frequency, zero crossing rate, cepstral coefficients and pitch frequency, Mean, Jitter, Shimmer, Energy, Minimum, Maximum, Amplitude, Standard Deviation, at a later stage with filter methods such as Pearson Correlation Coefficient, t-test, relief and information gain, we came up with a method to rank and select effective features in emotion recognition. Then Result, are given to the classification system as a subset of input. In this classification stage, multi support vector machine are used to classify seven type of emotion. According to the results, that method of relief, together with multi support vector machine, has the most classification accuracy with emotion recognition rate of 93.94%.

Note: Measurements of fast electrons in the TORE-SUPRA tokamak by means of modified Cherenkov-type diamond detector

Energy Technology Data Exchange (ETDEWEB)

Jakubowski, L.; Sadowski, M. J.; Zebrowski, J.; Rabinski, M.; Jakubowski, M. J.; Malinowski, K.; Mirowski, R. [National Centre for Nuclear Research (NCBJ), 7 Andrzeja Soltana Str., 05-400 Otwock (Poland); Lotte, Ph.; Goniche, M.; Gunn, J.; Colledani, G.; Pascal, J.-Y.; Basiuk, V. [CEA, IRFM, F-13108 Saint Paul-lez-Durance (France)

2013-01-15

The Note reports on experimental studies of ripple born fast electrons within the TORE-SUPRA facility, which were performed by means of a modified measuring head equipped with diamond detectors designed especially for recording the electron-induced Cherenkov radiation. There are presented signals produced by fast electrons in the TORE-SUPRA machine, which were recorded during two experimental campaigns performed in 2010. Shapes of these electron-induced signals are considerably different from those observed during the first measurements carried out by the prototype Cherenkov probe in 2008. An explanation of the observed differences is given.

Note: Measurements of fast electrons in the TORE-SUPRA tokamak by means of modified Cherenkov-type diamond detector

International Nuclear Information System (INIS)

Jakubowski, L.; Sadowski, M. J.; Zebrowski, J.; Rabinski, M.; Jakubowski, M. J.; Malinowski, K.; Mirowski, R.; Lotte, Ph.; Goniche, M.; Gunn, J.; Colledani, G.; Pascal, J.-Y.; Basiuk, V.

2013-01-01

The Note reports on experimental studies of ripple born fast electrons within the TORE-SUPRA facility, which were performed by means of a modified measuring head equipped with diamond detectors designed especially for recording the electron-induced Cherenkov radiation. There are presented signals produced by fast electrons in the TORE-SUPRA machine, which were recorded during two experimental campaigns performed in 2010. Shapes of these electron-induced signals are considerably different from those observed during the first measurements carried out by the prototype Cherenkov probe in 2008. An explanation of the observed differences is given.

A REVIEW OF VIBRATION MACHINE DIAGNOSTICS BY USING ARTIFICIAL INTELLIGENCE METHODS

Directory of Open Access Journals (Sweden)

Grover Zurita

2016-09-01

Full Text Available In the industry, gears and rolling bearings failures are one of the foremost causes of breakdown in rotating machines, reducing availability time of the production and resulting in costly systems downtime. Therefore, there are growing demands for vibration condition based monitoring of gears and bearings, and any method in order to improve the effectiveness, reliability, and accuracy of the bearing faults diagnosis ought to be evaluated. In order to perform machine diagnosis efficiently, researchers have extensively investigated different advanced digital signal processing techniques and artificial intelligence methods to accurately extract fault characteristics from vibration signals. The main goal of this article is to present the state-of-the-art development in vibration analysis for machine diagnosis based on artificial intelligence methods.

Blind Reduced-Rank MMSE Detector for DS-CDMA Systems

Directory of Open Access Journals (Sweden)

Xiaodong Cai

2003-01-01

Full Text Available We first develop a reduced-rank minimum mean squared error (MMSE detector for direct-sequence (DS code division multiple access (CDMA by forcing the linear MMSE detector to lie in a signal subspace of a reduced dimension. While a reduced-rank MMSE detector has lower complexity, it cannot outperform the full-rank MMSE detector. We then concentrate on the blind reduced-rank MMSE detector which is obtained from an estimated covariance matrix. Our analysis and simulation results show that when the desired user′s signal is in a low-dimensional subspace, there exists an optimal subspace so that the blind reduced-rank MMSE detector lying in this subspace has the best performance. By properly choosing a subsspace, we guarantee that the optimal blind reduced-rank MMSE detector is obtained. An adaptive blind reduced-rank MMSE detector, based on a subspace tracking algorithm, is developed. The adaptive blind reduced-rank MMSE detector exhibits superior steady-state performance and fast convergence speed.

Getting the traces (FADCs) of a water Cherenkov detector signal

International Nuclear Information System (INIS)

Ponce, E.; Salazar, H.; Martinez, O.; Moreno, E.

2003-01-01

In this work we present the electronics developed into a complete data acquisition system (DAS) for a water Cherenkov detector (WCD) in order to detect cosmic rays with energies from 1 x 1014 to 1 x 1016 eV. The components are: a high voltage source, a bleeder circuit for each photomultiplier, an electronic unit to amplify, compare, determine coincidence and sum the signals produced by the PMTs, a control circuit to digitalize and store the information corresponding to a valid event and finally an interface to a PC to record data for further analysis. The sampling rate of the system is 40 MHz

Piezoelectric self-sensing actuator for active vibration control of motorized spindle based on adaptive signal separation

Science.gov (United States)

He, Ye; Chen, Xiaoan; Liu, Zhi; Qin, Yi

2018-06-01

The motorized spindle is the core component of CNC machine tools, and the vibration of it reduces the machining precision and service life of the machine tools. Owing to the fast response, large output force, and displacement of the piezoelectric stack, it is often used as the actuator in the active vibration control of the spindle. A piezoelectric self-sensing actuator (SSA) can reduce the cost of the active vibration control system and simplify the structure by eliminating the use of a sensor, because a SSA can have both actuating and sensing functions at the same time. The signal separation method of a SSA based on a bridge circuit is widely applied because of its simple principle and easy implementation. However, it is difficult to maintain dynamic balance of the circuit. Prior research has used adaptive algorithm to balance of the bridge circuit on the flexible beam dynamically, but those algorithms need no correlation between sensing and control voltage, which limit the applications of SSA in the vibration control of the rotor-bearing system. Here, the electromechanical coupling model of the piezoelectric stack is established, followed by establishment of the dynamic model of the spindle system. Next, a new adaptive signal separation method based on the bridge circuit is proposed, which can separate relative small sensing voltage from related mixed voltage adaptively. The experimental results show that when the self-sensing signal obtained from the proposed method is used as a displacement signal, the vibration of the motorized spindle can be suppressed effectively through a linear quadratic Gaussian (LQG) algorithm.

Scalar top study: Detector optimization

Indian Academy of Sciences (India)

This scenario could for example occur if the vertex detector is exposed to a large dose of machine background from the accelerator. The optimization of the radius of the innermost layer is an important aspect in the design of a vertex detector for a linear collider. VX32: Five layers and double material thickness (0.128% X0 ...

Vibration Sensor Monitoring of Nickel-Titanium Alloy Turning for Machinability Evaluation

Directory of Open Access Journals (Sweden)

Tiziana Segreto

2017-12-01

Full Text Available Nickel-Titanium (Ni-Ti alloys are very difficult-to-machine materials causing notable manufacturing problems due to their unique mechanical properties, including superelasticity, high ductility, and severe strain-hardening. In this framework, the aim of this paper is to assess the machinability of Ni-Ti alloys with reference to turning processes in order to realize a reliable and robust in-process identification of machinability conditions. An on-line sensor monitoring procedure based on the acquisition of vibration signals was implemented during the experimental turning tests. The detected vibration sensorial data were processed through an advanced signal processing method in time-frequency domain based on wavelet packet transform (WPT. The extracted sensorial features were used to construct WPT pattern feature vectors to send as input to suitably configured neural networks (NNs for cognitive pattern recognition in order to evaluate the correlation between input sensorial information and output machinability conditions.

Vibration Sensor Monitoring of Nickel-Titanium Alloy Turning for Machinability Evaluation.

Science.gov (United States)

Segreto, Tiziana; Caggiano, Alessandra; Karam, Sara; Teti, Roberto

2017-12-12

Nickel-Titanium (Ni-Ti) alloys are very difficult-to-machine materials causing notable manufacturing problems due to their unique mechanical properties, including superelasticity, high ductility, and severe strain-hardening. In this framework, the aim of this paper is to assess the machinability of Ni-Ti alloys with reference to turning processes in order to realize a reliable and robust in-process identification of machinability conditions. An on-line sensor monitoring procedure based on the acquisition of vibration signals was implemented during the experimental turning tests. The detected vibration sensorial data were processed through an advanced signal processing method in time-frequency domain based on wavelet packet transform (WPT). The extracted sensorial features were used to construct WPT pattern feature vectors to send as input to suitably configured neural networks (NNs) for cognitive pattern recognition in order to evaluate the correlation between input sensorial information and output machinability conditions.

A DBN based anomaly targets detector for HSI

Science.gov (United States)

Ma, Ning; Wang, Shaojun; Yu, Jinxiang; Peng, Yu

2017-10-01

Due to the assumption that Hyperspectral image (HSI) should conform to Gaussian distribution, traditional Mahalanobis distance-based anomaly targets detectors perform poor because the assumption may not always hold. In order to solve those problems, a deep learning based detector, Deep Belief Network(DBN) anomaly detector(DBN-AD), was proposed to fit the unknown distribution of HSI by energy modeling, the reconstruction errors of this encode-decode processing are used for discriminating the anomaly targets. Experiments are implemented on real and synthesized HSI dataset which collection by Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS). Comparing to classic anomaly detector, the proposed method shows better performance, it performs about 0.17 higher in Area Under ROC Curve (AUC) than that of Reed-Xiaoli detector(RXD) and Kernel-RXD (K-RXD).

Signal Region Optimisation Studies Based on BDT and Multi-Bin Approaches in the Context of Supersymmetry Searches in Hadronic Final States with the ATLAS Detector

CERN Document Server

AUTHOR|(CDS)2097636; Makovec, Nikola; Rúriková, Zuzana

The searches for supersymmetric phenomena are mostly based on simple Cut & Count methods. One example is the search for squarks and gluinos in final states with multiple jets, missing transverse momentum and without leptons. This analysis, based on $36.1\\,\\text{fb}^{−1}$ of $pp$ collision data at $\\sqrt{s}$ = 13 TeV recorded with the ATLAS detector, uses Cut & Count based methods in the signal regions. In order to improve the analysis sensitivity, the use of sophisticated techniques, such as boosted decision trees (BDT) and Multi-Bin, is being investigated in this thesis. The focus of the study lies on squarks and gluino searches. These techniques are evaluated using Monte Carlo simulation. The goal is to find a new approach which is on the one hand simple but allows for a significant improvement. A gain up to approximately 200 GeV in the neutralino mass and an enhancement of about 200 GeV in the squark and gluino mass is achieved with these new techniques.

Application of Machine Learning Algorithms to the Study of Noise Artifacts in Gravitational-Wave Data

Science.gov (United States)

Biswas, Rahul; Blackburn, Lindy L.; Cao, Junwei; Essick, Reed; Hodge, Kari Alison; Katsavounidis, Erotokritos; Kim, Kyungmin; Young-Min, Kim; Le Bigot, Eric-Olivier; Lee, Chang-Hwan;

High-quality 3D correction of ring and radiant artifacts in flat panel detector-based cone beam volume CT imaging

Science.gov (United States)

Abu Anas, Emran Mohammad; Kim, Jae Gon; Lee, Soo Yeol; Kamrul Hasan, Md

2011-10-01

The use of an x-ray flat panel detector is increasingly becoming popular in 3D cone beam volume CT machines. Due to the deficient semiconductor array manufacturing process, the cone beam projection data are often corrupted by different types of abnormalities, which cause severe ring and radiant artifacts in a cone beam reconstruction image, and as a result, the diagnostic image quality is degraded. In this paper, a novel technique is presented for the correction of error in the 2D cone beam projections due to abnormalities often observed in 2D x-ray flat panel detectors. Template images are derived from the responses of the detector pixels using their statistical properties and then an effective non-causal derivative-based detection algorithm in 2D space is presented for the detection of defective and mis-calibrated detector elements separately. An image inpainting-based 3D correction scheme is proposed for the estimation of responses of defective detector elements, and the responses of the mis-calibrated detector elements are corrected using the normalization technique. For real-time implementation, a simplification of the proposed off-line method is also suggested. Finally, the proposed algorithms are tested using different real cone beam volume CT images and the experimental results demonstrate that the proposed methods can effectively remove ring and radiant artifacts from cone beam volume CT images compared to other reported techniques in the literature.

High-quality 3D correction of ring and radiant artifacts in flat panel detector-based cone beam volume CT imaging

International Nuclear Information System (INIS)

Anas, Emran Mohammad Abu; Hasan, Md Kamrul; Kim, Jae Gon; Lee, Soo Yeol

2011-01-01

The use of an x-ray flat panel detector is increasingly becoming popular in 3D cone beam volume CT machines. Due to the deficient semiconductor array manufacturing process, the cone beam projection data are often corrupted by different types of abnormalities, which cause severe ring and radiant artifacts in a cone beam reconstruction image, and as a result, the diagnostic image quality is degraded. In this paper, a novel technique is presented for the correction of error in the 2D cone beam projections due to abnormalities often observed in 2D x-ray flat panel detectors. Template images are derived from the responses of the detector pixels using their statistical properties and then an effective non-causal derivative-based detection algorithm in 2D space is presented for the detection of defective and mis-calibrated detector elements separately. An image inpainting-based 3D correction scheme is proposed for the estimation of responses of defective detector elements, and the responses of the mis-calibrated detector elements are corrected using the normalization technique. For real-time implementation, a simplification of the proposed off-line method is also suggested. Finally, the proposed algorithms are tested using different real cone beam volume CT images and the experimental results demonstrate that the proposed methods can effectively remove ring and radiant artifacts from cone beam volume CT images compared to other reported techniques in the literature.

An Interactive Web-based Learning System for Assisting Machining Technology Education

Directory of Open Access Journals (Sweden)

Min Jou

2008-05-01

Full Text Available The key technique of manufacturing methods is machining. The degree of technique of machining directly affects the quality of the product. Therefore, the machining technique is of primary importance in promoting student practice ability during the training process. Currently, practical training is applied in shop floor to discipline student’s practice ability. Much time and cost are used to teach these techniques. Particularly, computerized machines are continuously increasing in use. The development of educating engineers on computerized machines becomes much more difficult than with traditional machines. This is because of the limitation of the extremely expensive cost of teaching. The quality and quantity of teaching cannot always be promoted in this respect. The traditional teaching methods can not respond well to the needs of the future. Therefore, this research aims to the following topics; (1.Propose the teaching strategies for the students to learning machining processing planning through web-based learning system. (2.Establish on-line teaching material for the computer-aided manufacturing courses including CNC coding method, CNC simulation. (3.Develop the virtual machining laboratory to bring the machining practical training to web-based learning system. (4.Integrate multi-media and virtual laboratory in the developed e-learning web-based system to enhance the effectiveness of machining education through web-based system.

Limits of a spatial resolution of the cascaded GEM based detectors

International Nuclear Information System (INIS)

Kudryavtsev, V.N.; Maltsev, T.V.; Shekhtman, L.I.

2017-01-01

Spatial resolution of tracking detectors based on GEM cascades is determined in the simulation and measured. The simulation includes GEANT4 implemented transport of high energy electrons with careful accounting for atomic relaxation processes including emission of fluorescent photons and Auger electrons and custom post-processing taking into account diffusion, gas amplification fluctuations, the distribution of signals over readout electrodes, electronics noise and particular algorithm of final coordinate calculation (centre-of-gravity algorithm). The simulation demonstrates that the minimum of the spatial resolution of about 10–20 μm can be achieved with a gas mixture of Ar-CO 2 (75%–25%) at a strip pitch in the range from 250 μm to 300 μm. At a larger pitch the resolution quickly degrades reaching 70–100 μm at a pitch of 450–500 μm. The reasons of such behavior are discussed and corresponding hypothesis is tested. Particularly, the effect of electron cloud modification due to a GEM operation is considered using the ANSYS and Garfield++ simulation programs. The detection efficiency and spatial resolution of low-material triple-GEM detectors for the DEUTERON facility at BINP are measured at the extracted beam facility of the VEPP-4M collider. One-coordinate resolution of two detectors for the DEUTERON facility is measured with a 2 GeV electron beam. The determined values of the detectors' spatial resolution is equal to 46.6 ± 0.1 μm and 38.5 ± 0.2 μm for orthogonal tracks in two detectors, respectively.

Limits of a spatial resolution of the cascaded GEM based detectors

Science.gov (United States)

Kudryavtsev, V. N.; Maltsev, T. V.; Shekhtman, L. I.

2017-06-01

Spatial resolution of tracking detectors based on GEM cascades is determined in the simulation and measured. The simulation includes GEANT4 implemented transport of high energy electrons with careful accounting for atomic relaxation processes including emission of fluorescent photons and Auger electrons and custom post-processing taking into account diffusion, gas amplification fluctuations, the distribution of signals over readout electrodes, electronics noise and particular algorithm of final coordinate calculation (centre-of-gravity algorithm). The simulation demonstrates that the minimum of the spatial resolution of about 10-20 μm can be achieved with a gas mixture of Ar-CO2 (75%-25%) at a strip pitch in the range from 250 μm to 300 μm. At a larger pitch the resolution quickly degrades reaching 70-100 μm at a pitch of 450-500 μm. The reasons of such behavior are discussed and corresponding hypothesis is tested. Particularly, the effect of electron cloud modification due to a GEM operation is considered using the ANSYS and Garfield++ simulation programs. The detection efficiency and spatial resolution of low-material triple-GEM detectors for the DEUTERON facility at BINP are measured at the extracted beam facility of the VEPP-4M collider. One-coordinate resolution of two detectors for the DEUTERON facility is measured with a 2 GeV electron beam. The determined values of the detectors' spatial resolution is equal to 46.6 ± 0.1 μm and 38.5 ± 0.2 μm for orthogonal tracks in two detectors, respectively.

Study on single-channel signals of water Cherenkov detector array for the LHAASO project

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