Diamond sensor arrays for neutron detection: Preamplifier signal dependence on sensor array configuration

2015 ◽  
Vol 73 ◽  
pp. 18-25 ◽  
Author(s):  
Eric Lukosi ◽  
Mark Prelas
Keyword(s):  
Sensor Array ◽  
Sensor Arrays ◽  
Neutron Detection ◽  
Array Configuration ◽  
Signal Dependence

scholarly journals Tensor-Based Methods for Blind Spatial Signature Estimation in Multidimensional Sensor Arrays

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Paulo R. B. Gomes ◽  
André L. F. de Almeida ◽  
João Paulo C. L. da Costa ◽  
João C. M. Mota ◽  
Daniel Valle de Lima ◽  
...  
Keyword(s):  
Sensor Array ◽  
State Of The Art ◽  
Sensor Arrays ◽  
Iterative Estimation ◽  
Practical Applications ◽  
Estimation Algorithms ◽  
Array Configuration ◽  
Spatial Frequencies ◽  
Simulation Results ◽  
Configuration Simulation

The estimation of spatial signatures and spatial frequencies is crucial for several practical applications such as radar, sonar, and wireless communications. In this paper, we propose two generalized iterative estimation algorithms to the case in which a multidimensional (R-D) sensor array is used at the receiver. The first tensor-based algorithm is anR-D blind spatial signature estimator that operates in scenarios where the source’s covariance matrix is nondiagonal and unknown. The second tensor-based algorithm is formulated for the case in which the sources are uncorrelated and exploits the dual-symmetry of the covariance tensor. Additionally, a new tensor-based formulation is proposed for anL-shaped array configuration. Simulation results show that our proposed schemes outperform the state-of-the-art matrix-based and tensor-based techniques.

Fundamental Sensor Development in Electrical Resistance Tomography

2015 ◽  
Vol 73 (6) ◽  
Author(s):  
Ling En Hong ◽  
Ruzairi Hj. Abdul Rahim ◽  
Anita Ahmad ◽  
Mohd Amri Md. Yunus ◽  
Khairul Hamimah Aba ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Data Acquisition ◽  
Electrical Resistance ◽  
Sensor Array ◽  
Sensor Arrays ◽  
Region Of Interest ◽  
Display System ◽  
Electrical Resistance Tomography ◽  
Fundamental Understanding ◽  
Collection Strategies

This paper will provide a fundamental understanding of one of the most commonly used tomography, Electrical Resistance Tomography (ERT). Unlike the other tomography systems, ERT displayed conductivity distribution in the Region of Interest (ROI) and commonly associated to Sensitivity Theorem in their image reconstruction. The fundamental construction of ERT includes a sensor array spaced equally around the imaged object periphery, a Data Acquisition (DAQ), image reconstruction and display system. Four ERT data collection strategies that will be discussed are Adjacent Strategy, Opposite Strategy, Diagonal Strategy and Conducting Boundary Strategy. We will also explain briefly on some of the possible Data Acquisition System (DAQ), forward and inverse problems, different arrangements for conducting and non-conducting pipes and factors that influence sensor arrays selections. 

scholarly journals Curating Metal-Organic Frameworks to Compose Robust Gas Sensor Arrays in Dilute Conditions

2019 ◽  
Author(s):  
Arni Sturluson ◽  
Rachel Sousa ◽  
Yujing Zhang ◽  
Melanie T. Huynh ◽  
Caleb Laird ◽  
...  
Keyword(s):  
Sensor Array ◽  
Gas Sensing ◽  
Metal Organic Frameworks ◽  
Sensor Arrays ◽  
Gas Composition ◽  
Composition Space ◽  
The Matrix ◽  
Metal Organic ◽  
Analyte Detection ◽  
Value Decomposition

Metal-organic frameworks (MOFs)-- tunable, nano-porous materials-- are alluring recognition elements for gas sensing. Mimicking human olfaction, an array of cross-sensitive, MOF-based sensors could enable analyte detection in complex, variable gas mixtures containing confounding gas species. Herein, we address the question: given a set of MOF candidates and their adsorption properties, how do we select the optimal subset to compose a sensor array that accurately and robustly predicts the gas composition via monitoring the adsorbed mass in each MOF? We first mathematically formulate the MOF-based sensor array problem under dilute conditions. Instructively, the sensor array can be viewed as a linear map from <i>gas composition space</i> to <i>sensor array response space</i> defined by the matrix <b>H</b> of Henry coefficients of the gases in the MOFs. Characterizing this mapping, the singular value decomposition of <b>H </b>is a useful tool for evaluating MOF subsets for sensor arrays, as it determines the sensitivity of the predicted gas composition to measurement error, quantifies the magnitude of the response to changes in composition, and recovers which direction in gas composition space elicits the largest/smallest response. To illustrate, on the basis of experimental adsorption data, we curate MOFs for a sensor array with the objective of determining the concentration of CO<sub>2</sub> and SO<sub>2</sub> in the gas phase.

scholarly journals Development of a Pattern Recognition Tool for the Classification of Electronic Tongue Signals Using Machine Learning

2021 ◽  
Vol 5 (1) ◽  
pp. 21
Author(s):  
Edgar G. Mendez-Lopez ◽  
Jersson X. Leon-Medina ◽  
Diego A. Tibaduiza
Keyword(s):  
Machine Learning ◽  
Dimensionality Reduction ◽  
Performance Measures ◽  
Sensor Array ◽  
Three Dimensional ◽  
Electronic Tongue ◽  
Sensor Arrays ◽  
Classification Performance ◽  
Supervised Machine Learning ◽  
Electrochemical Tests

Electronic tongue type sensor arrays are made of different materials with the property of capturing signals independently by each sensor. The signals captured when conducting electrochemical tests often have high dimensionality, which increases when performing the data unfolding process. This unfolding process consists of arranging the data coming from different experiments, sensors, and sample times, thus the obtained information is arranged in a two-dimensional matrix. In this work, a description of a tool for the analysis of electronic tongue signals is developed. This tool is developed in Matlab® App Designer, to process and classify the data from different substances analyzed by an electronic tongue type sensor array. The data processing is carried out through the execution of the following stages: (1) data unfolding, (2) normalization, (3) dimensionality reduction, (4) classification through a supervised machine learning model, and finally (5) a cross-validation procedure to calculate a set of classification performance measures. Some important characteristics of this tool are the possibility to tune the parameters of the dimensionality reduction and classifier algorithms, and also plot the two and three-dimensional scatter plot of the features after reduced the dimensionality. This to see the data separability between classes and compatibility in each class. This interface is successfully tested with two electronic tongue sensor array datasets with multi-frequency large amplitude pulse voltammetry (MLAPV) signals. The developed graphical user interface allows comparing different methods in each of the mentioned stages to find the best combination of methods and thus obtain the highest values of classification performance measures.

scholarly journals Sensor arrays: an inspired idea or an objective measurement of environmental odours?

2001 ◽  
Vol 44 (9) ◽  
pp. 53-58 ◽  
Author(s):  
R.M. Stuetz ◽  
J. Nicolas
Keyword(s):  
Sensor Array ◽  
Sensory System ◽  
Sensor Arrays ◽  
Objective Measurement ◽  
Chemical Compositions ◽  
Response Patterns ◽  
Human Response ◽  
Control And Prevention ◽  
On Line ◽  
The Right

The measure of annoyance odours from sewage tratment, landfill and agricultural practise has become highly significant in the control and prevention of dorous emissions from existing facilities and its crucial for new planning applications. Current methods (such as GC-MS analysis, H2S and NH3 measurements) provide an accurate description of chemical compositions or act as surrogates for odour strength, but tell us very little about the perceived effect, whereas olfactometry gives the right human response but is very subjective and expensive. The use of non-specific sensor arrays may offer an objective and on-line instrument for assessing olfactive annoyance. Results have shown that sensor array systems can discriminate between different odour sources (wastewater, livestock and landfill). The response patterns from these sources can be significantly different and that the intensity of sensor responses is proportional to the concentration of the volatiles. The correlation of the sensors responses against odour strengths have also shown that reasonable fits can be obtained for a range of odour concentrations (100-800,000 ou/m3). However, the influence of environmental fluctuations (humidity and temperature) on sensor baselines still remains an obstacle, as well as the need for periodic calibration of the sensory system and the choice of a suitable gas for different environmental odours.

scholarly journals Spline approximation-based data compression for sensor arrays in the wireless hydrologic monitoring system

2017 ◽  
Vol 13 (2) ◽  
pp. 155014771769258
Author(s):  
Danyang Li ◽  
Wei Huangfu ◽  
Keping Long
Keyword(s):  
Data Compression ◽  
Monitoring System ◽  
Sensor Array ◽  
Spline Approximation ◽  
Sensor Arrays ◽  
Huffman Coding ◽  
Long Distance ◽  
Data Set ◽  
Array Data ◽  
Hydrologic Monitoring

A sensor array produces lots of bits of data every sample period, which may cause a heavy burden on the long-distance wireless data transmission, especially in the scenarios of wireless sensor networks. A lossy but error-bounded sensor array data compression algorithm is proposed, in which the major part of the sensor array data are approximated by the Catmull-Rom spline curve and the residual errors are quantized and encoded with Huffman coding. The performance of this algorithm has been evaluated with a real data set from the wireless hydrologic monitoring system deployed in Qinhuangdao Port of China. The results show that the algorithm performs well for the hydrologic sensor array data.

Disease-specific protein corona sensor arrays may have disease detection capacity

2019 ◽  
Vol 4 (5) ◽  
pp. 1063-1076 ◽  
Author(s):  
Giulio Caracciolo ◽  
Reihaneh Safavi-Sohi ◽  
Reza Malekzadeh ◽  
Hossein Poustchi ◽  
Mahdi Vasighi ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Sensor Array ◽  
Sensor Arrays ◽  
Protein Corona ◽  
Specific Protein ◽  
Disease Detection ◽  
P Protein ◽  
Array Technology ◽  
Disease Specific

Protein corona sensor array technology identifies diseases through specific proteomics pattern recognition.

Water Content Estimation in Soils Using Novel Planar Electromagnetic Sensor Arrays

2013 ◽  
Vol 64 (5) ◽  
Author(s):  
Mohd Amri Md Yunus ◽  
Syahrul Hisyam Mohamad ◽  
Alif Syarafi M. Nor ◽  
Muhammad Hafis Izran ◽  
Sallehuddin Ibrahim
Keyword(s):  
Water Content ◽  
Sensor Array ◽  
Printed Circuit Board ◽  
Agricultural Soils ◽  
Sensor Arrays ◽  
Circuit Board ◽  
Waveform Generator ◽  
Electromagnetic Sensors ◽  
Electromagnetic Sensor ◽  
The Relationship

Agriculture is one of the important sectors for food supplies. Therefore, a tool for monitoring the agro-environment is important in order to maintain the permanence of agricultural soils. This paper suggests an alternative method for the detection of water content in soils by developing a sensor array with a combination of planar meander and interdigital electromagnetic sensors. The study involved sensor array fabrication using the printed circuit board (PCB) method. The experimental setup consisted of a frequency waveform generator and a signal oscilloscope to collect and analyse the sensors’ output, with VEE Agilent software used to establish the interface. A set of experiments was conducted to determine the relationship between the sensors’ output and the soils’ parameters. The performance of the system was observed where the sensors were tested with the addition of various kinds of soil samples with different concentrations of water content. The sensitivity of the developed sensors was evaluated where the best sensor was selected. Based on the outcomes of the experiments, the Y sensor array placement has the highest sensitivity and can be used to measure the water content in the soils where the data accuracy is compared

scholarly journals Frequency Invariant Beamforming for a Small-Sized Bi-Cone Acoustic Vector–Sensor Array

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 661
Author(s):  
Erzheng Fang ◽  
Chenyang Gui ◽  
Desen Yang ◽  
Zhongrui Zhu
Keyword(s):  
Sensor Array ◽  
Three Dimensional ◽  
Sensor Arrays ◽  
Signal Frequency ◽  
Acoustic Vector Sensor ◽  
Mechanical Coupling ◽  
Vector Sensor ◽  
Coupling System ◽  
Simulation Results ◽  
Vector Sensor Array

In this work, we design a small-sized bi-cone acoustic vector-sensor array (BCAVSA) and propose a frequency invariant beamforming method for the BCAVSA, inspired by the Ormia ochracea’s coupling ears and harmonic nesting. First, we design a BCAVSA using several sets of cylindrical acoustic vector-sensor arrays (AVSAs), which are used as a guide to construct the constant beamwidth beamformer. Due to the mechanical coupling system of the Ormia ochracea’s two ears, the phase and amplitude differences of acoustic signals at the bilateral tympanal membranes are magnified. To obtain a virtual BCAVSA with larger interelement distances, we then extend the coupling magnified system into the BCAVSA by deriving the expression of the coupling magnified matrix for the BCAVSA and providing the selecting method of coupled parameters for fitting the underwater signal frequency. Finally, the frequency invariant beamforming method is developed to acquire the constant beamwidth pattern in the three-dimensional plane by deriving several sets of the frequency weighted coefficients for the different cylindrical AVSAs. Simulation results show that this method achieves a narrower mainlobe width compared to the original BCAVSA. This method has lower sidelobes and a narrower mainlobe width compared to the coupling magnified bi-cone pressure sensor array.

Sign in / Sign up

Export Citation Format

Share Document