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International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)

作者： Attaqa Bashir Faria Malik Farwa Haider Muhammad Ehatisham-ul-Haq Aasim Raheel Aamir Arsalan Signal Image Multimedia Signal Processing and LEarning (SIMPLE) Research Group University of Engineering and Technology Taxila Pakistan

ISBN: (数字)9781728149707

ISBN: (纸本)9781728149714

With the rapid advancement of technology in the current era, mobile and wearable devices have attracted the attention of end users. Smartwatches available in the market have embedded movement sensors whose potential applications have not been explored to a great extent. This study proposes a gesture recognition module using a smart sensor Metawear which can potentially be used to control various functions of a media player. Inertial sensors data from 9 subjects for 12 different gestures (3 trials for each gesture) are acquired. Fifteen different features are extracted from the acquired data. Wrapper method for feature selection is applied on the extracted features which select features from six features groups among the fifteen extracted feature groups. Classification of gestures is performed using three different classifiers i.e., random forest (RF), Naive Bayes (NB) and k-nearest neighbors (kNN) algorithm. The best classification accuracy of 85.80% is achieved by using a fusion of features extracted from accelerometer and gyroscope data by kNN classifier. Experimental results show that the proposed scheme outperforms the existing schemes in literature in terms of classification accuracy for the larger number of gestures.

关键词： Feature extraction Gesture recognition Media Intelligent sensors Sensor fusion Forestry

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3D spatial soundfield recording over large regions

3D spatial soundfield recording over large regions

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International Workshop on Acoustic signal Enhancement, IWAENC 2012

作者： Samarasinghe, Prasanga N. Abhayapala, Thushara D. Poletti, M.A. Applied Signal Processing Group Research School of Engineering CECS Australian National University CanberraACT0200 Australia Industrial Research Limited PO Box 31-310 Lower Hutt New Zealand

ISBN: (纸本)9783800734511

Capturing large three dimensional sound fields is a prevailing challenge due to the requirement of extracting a huge number of harmonic components describing the spatial soundfield. In this paper, we develop a theoretical solution to the problem by employing an array of higher order microphones distributed on a surface enclosing the region of concern. Spatial sound fields recorded by the higher order microphones are combined based on the three dimensional addition theorem to form the global soundfield of interest. Design examples are given for both interior and exterior field recordings. © 2012, Institute of Electrical and Electronics Engineers Inc. All rights reserved.

关键词： Acoustic fields

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A Novel Residual Attitude Estimation Approach Using Georeferenced Satellite imagery

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Photogrammetric Engineering and Remote Sensing 2022年第10期88卷 631-641页

作者： Dubey, Bhaskar Kartikeyan, B. Image Analysis and Quality Evaluation Division of the Signal and Image Processing Group Space Applications Centre Indian Space Research Organisation Ahmedabad India

This article presents an efficient novel approach estimating residual attitude based on geometrically corrected (GEO) satellite images. A technique is presented that uses orbital plane geometry to compute the rotation angle as a function of geographic latitude between GEO image space and radiometrically corrected (RAD) image space. First, a nonlinear forward model is established that translates the residual errors in roll, pitch, and yaw to scan errors and pixel errors in GEO image space. Subsequently, the inverse problem is solved using Newton’s method of nonlinear optimization for estimating residual roll, pitch, and yaw. We demonstrate our results on data products of the high-resolution Indian satellites Cartosat-2E and Cartosat-2F. Further, the superiority of the proposed method is established by comparing it with multiple existing methods in the literature. The R2 measures of good-ness of fit for roll, pitch, and yaw estimation based on RAD and GEO products using the proposed method are 0.65, 0.99, and 0.65, respec-tively;using the existing method, they are 0.074, 0.005, and 0.50. © 2022 American Society for Photogrammetry and Remote Sensing.

关键词： Inverse problems

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Deformable image registration

Deformable image registration

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IEEE International Conference on image processing

作者： Jian-Kun Shen B.J. Matuszewski Lik-Kwan Shark Research Center for Applied Digital Signal and Image Processing University of Central Lancashire Preston UK

The paper describes a novel deformable data registration algorithm. The proposed method can be seen as a tradeoff between the landmark and intensity driven data registration techniques. The algorithm is fast, robust and offers high registration accuracy. The algorithm enables to include complex constraints on the allowable data deformations. It is shown that some of these constraints permit to treat part of the data as rigid objects or restrict its deformation to a predefined shape. The main focus of the paper is put on the description of the elastic deformation model used in the method. The performance of this new technique is illustrated using simulated as well as real computed tomography (CT) images.

关键词： image registration Deformable models Mesh generation Interpolation Computed tomography Motion estimation signal processing image processing Robustness Shape

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Contrasting spatial, temporal and Spatio-Temporal ICA applied to ictal EEG recordings

Contrasting spatial, temporal and Spatio-Temporal ICA applie...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Christopher J. James Mike E. Davies Signal Processing and Control Group ISVR University of Southampton UK IDCOM and the Joint Research Institute for Signal and Image Processing University of Edinburgh UK

In this paper we contrast three implementations of Independent Component Analysis (ICA) as applied to epileptic scalp electroencephalographic (EEG) recordings, these are; Spatial (Ensemble) ICA, Temporal (single-channel) ICA and Spatio-Temporal ICA. These techniques are based on information derived from both multi-channel as well as single channel biomedical signal recordings. We assess the suitability of the three techniques in isolating and extracting out epileptic seizure sources. Although our results are preliminary in nature, we show that standard implementations of ICA (ensemble ICA) are lacking when attempting to extract complex underlying activity such as ictal activity in the EEG. Temporal ICA performs well in separating underlying sources, although it is clearly lacking in spatial information. Spatio-Temporal ICA has the advantage of using temporal information to inform the ICA process, aided by the spatial information inherent in multi-channel recordings. This work is being expanded for seizure onset analysis through scalp EEG.

关键词： Integrated circuits Information filters Electroencephalography Delays Independent component analysis

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A fast algorithm for automated independent process separation from single channel biomedical signal recordings: FastIPA

A fast algorithm for automated independent process separatio...

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4th IET International Conference on Advances in Medical, signal and Information processing - MEDSIP 2008

作者： C.J. James M.E. Davies Signal Processing and Control Group ISVR University of Southampton UK IDCOM and the Joint Research Institute for Signal and Image Processing University of Edinburgh UK

Independent component analysis (ICA) has found many uses in source separation in biomedical signals. We highlight a methodology and put forward an algorithm which allows single channel ICA to be performed on single channel biomedical signal recordings. The algorithm uses a fast, deflationary approach to efficiently extract independent processes underlying the single channel recordings. We show that for processes which are reasonably spectrally disjoint the algorithm can separate out individual sources. We show examples of this using brain signal recordings and abdominal foetal recordings.

关键词： Independent component analysis (ICA) Single channel ICA Blind source separation Automated source extraction Independent process analysis Blind source separation Recordings single-channel algorithms signals Independent component analysis A* Algorithm Source separation Automation islet cell antibody

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NON-RIGID STRUCTURE FROM MOTION WITH INCREMENTAL SHAPE PRIOR

NON-RIGID STRUCTURE FROM MOTION WITH INCREMENTAL SHAPE PRIOR

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IEEE International Conference on image processing

作者： Lili Tao Bogdan J. Matuszewski Stephen J. Mein Applied Digital Signal and Image Processing Research Centre University of Central Lancashire Preston UK

Most existing approaches to the non-rigid structure from motion problem use batch type algorithms with all the data collected before 3D shape reconstruction takes place. Such a methodology is not suitable for real-time applications. Concurrent on-line estimation of the camera position and 3D structure, based only on the measurements up to that moment is much more a challenging problem. In this paper, a novel approach is proposed for recursive recovery of non-rigid structures from image sequences captured by an orthographic camera. The main novelty in the proposed method is an adaptive algorithm for construction of shape constraints imposing stability on the on-line reconstructed shapes. The proposed, adaptively learned constraints have two aspects, consisting of constraints imposed on the basic shapes, the basic "building blocks" from which shapes are reconstructed, as well as constraints imposed on the mixing coefficients in a form of their probability distribution. The constraints are updated when the current model inadequately represents new shapes. This is achieved by means of Incremental Principal Component Analysis (IPCA). Results of the proposed method are shown on synthetic and real data of articulated face.

关键词： Shape image reconstruction Principal component analysis Cameras Face Vectors Optimization

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Supervised machine learning-based salp swarm algorithm for fault diagnosis of photovoltaic systems

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Journal of Engineering and applied Science 2024年第1期71卷 12页

作者： Hichri, Amal Hajji, Mansour Mansouri, Majdi Nounou, Hazem Bouzrara, Kais Research Unit Advanced Materials and Nanotechnologies Higher Institute of Applied Sciences and Technology of Kasserine Kairouan University Kairouan Tunisia Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar Laboratory of Automatic Signal and Image Processing National School of Engineers of Monastir University of Monastir Monastir5019 Tunisia

The diagnosis of faults in grid-connected photovoltaic (GCPV) systems is a challenging task due to their complex nature and the high similarity between faults. To address this issue, we propose a wrapper approach called the salp swarm algorithm (SSA) for feature selection. The main objective of SSA is to extract only the most important features from the raw data and eliminate unnecessary ones to improve the classification accuracy of supervised machine learning (SML) classifiers. Subsequently, the selected features are used to train supervised machine learning (SML) techniques in distinguishing between various operating modes. To evaluate the efficiency of the technique, we used healthy and faulty data from GCPV systems that have been injected with frequent faults, 20 different types of faults were introduced, including line-to-line, line-to-ground, connectivity faults, and those affecting the operation of bay-pass diodes. These faults present diverse conditions, such as simple and multiple faults in the PV arrays and mixed faults in both arrays. The performances of the developed SSA-SML are compared with those using principal component analysis (PCA) and kernel PCA (KPCA) based SML techniques through different criteria (i.e., accuracy, recall, precision, F1 score, and computation time). The experimental findings demonstrated that the proposed diagnosis paradigm outperformed the other techniques and achieved a high diagnostic accuracy (an average accuracy greater than 99%) while significantly reducing computation time. © 2023, The Author(s).

关键词： Failure analysis

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Three-dimensional-two-dimensional coupled model for eddy currents in laminated iron cores

Three-dimensional-two-dimensional coupled model for eddy cur...

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作者： De Gersem, Herbert Vanaverbeke, Siegfried Samaey, Giovanni Wave Propagation and Signal Processing Research Group Katholieke Universiteit Leuven Kortrijk Belgium Department of Computer Science and Applied Mathematics Katholieke Universiteit Leuven Leuven Belgium

Eddy currents due to magnetic flux perpendicular to the sheets of a lamination iron core are represented on a number of 2D slice models, which are embedded in a 3D model of the entire device using a multi-scale technique. The choice of a different spatial resolution enables to attain an advantageous convergence of the discretization error for the eddy-current power losses, compared to a standard modelling technique using an anisotropic surrogate material. © 2012 IEEE.

关键词： Eddy currents

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An agent-based approach to health monitoring systems applied to the ISS power system

An agent-based approach to health monitoring systems applied...

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45th AIAA Aerospace Sciences Meeting 2007

作者： Lyell, M.J. Krueger, W. Zhang, G. Xu, R. Haynes, L. Alena, Richard Intelligent Automation Inc. Rockville MD 20855 United States NASA Ames Research Center Moffett Field CA 94035 United States Distributed Systems Group 15400 Calhoun Drive AIAA Signal/Image Processing Group 15400 Calhoun Drive Signal Processing Group 15400 Calhoun Drive Intelligent Automation Inc. 15400 Calhoun Drive Computational Sciences Division MS 269-4

ISBN: (纸本)1563478900

We report on the design and development of an agent-based approach for health monitoring systems. A health monitoring system typically involves multiple sensors whose readings provide information as to the status of equipment components. Abnormal sensor readings can indicate malfunctions, either in a particular piece of equipment or in another component on which it depends or with which it interacts. Health monitoring systems operate in near real time. Large or complex systems that involve numerous sensors are data intensive. Various algorithms or data mining approaches support the identification of anomalous system operation, as well as classification of probable cause;i.e., what has failed. As physical systems become more complex and/ or more autonomous, health monitoring systems become more critical. Our work has focused on the design and development of an agent-based health monitoring system that serves as a conceptual prototype for autonomous health monitoring systems for support of space exploration applications. We utilized the electrical power system (EPS) of the International Space Station (ISS) as the physical system of interest. Pertinent data used in our health monitoring system is provided by results from a high fidelity simulation of the ISS Power System. Our agent-based health monitoring (ABHM) system design provides for flexibility;multiple families of assessment algorithms can be applied to the sensor data in parallel.

关键词： Health care

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