Suleman Mazhar

A review of techniques for detection of movement intention using movement-related cortical potentials

The movement-related cortical potential (MRCP) is a low-frequency negative shift in the electroencephalography (EEG) recording that takes place about 2 seconds prior to voluntary movement production. MRCP replicates the cortical processes employed in planning and preparation of movement. In this study, we recapitulate the features such as signals acquisition, processing, and enhancement and different electrode montages used for EEG data recoding from different studies that used MRCPs to predict the upcoming real or imaginary movement. An authentic identification of human movement intention, accompanying the knowledge of the limb engaged in the performance and its direction of movement, has a potential implication in the control of external devices. This information could be helpful in development of a proficient patient-driven rehabilitation tool based on brain-computer interfaces (BCIs). Such a BCI paradigm with shorter response time appears more natural to the amputees and can also induce plasticity in brain. Along with different training schedules, this can lead to restoration of motor control in stroke patients.

Vocalization based Individual Classification of Humpback Whales using Support Vector Machine

Visual surveys and DNA analysis hold primary importance in marine mammal observation. Especially, recognition of whales and their population density estimation rely heavily on these costly and tedious methods. Acoustic survey of vocalizing cetaceans, in contrast, is emerging as a promising technique for efficient, automatic, non-invasive and convenient observation and analysis of such vocally active organisms. However, it is, yet, too premature to replace the conventional methods altogether. In this paper, we have presented our results on recognition of individual humpback whales based on their vocalization data. Cepstral coefficients from song units extracted from audio records of seven humpback whales, re-sampled at 8KHz, were subjected to cepstral analysis. The extracted coefficients were used to develop multi-class support vector machine (SVM) classifier model. The test phase results indicated classification accuracy as high as 99% as compared to earlier best results of 88%, achieved by Gaussian mixture model (GMM) trained on cepstral coefficients. Furthermore, this improvement was attained with a highly reduced training dataset size. It was also verified that the song duration of approximately 128 seconds was sufficient for reliable identification in test phase for given dataset.

Parallel stabilized mixed Galerkin method for three-dimensional Darcy flow using OpenMP

This paper presents a parallel stabilized mixed Galerkin method for three-dimensional steady-state Darcy flow using OpenMP for shared memory architecture. In finite element problems, the computational complexity increases with increasing number of elements needed for large and complex geometry. Shared memory architecture offers a platform for solving such large and complex problems for practical applications. In parallel solvers, the mesh reordering has proved to be an important preprocessing operation to enhance performance. The objective of this study is to compare the performance of octree-based mesh reordering with multilevel-based reordering in the parallel solution. The reported results include execution time, speedup and efficiency of the solution using hexahedral and tetrahedral meshes of various sizes. The numerical results suggest that the octree-based mesh reordering outperforms multilevel-based method with tetrahedral meshes.

Analysing the performance of EIT images using the point spread function

Electrical impedance tomography (EIT) is a noninvasive medical imaging technique in which a small current is applied to the electrodes attached to the surface of a subject body and a cross-sectional image of the resistivity (or conductivity) distribution inside the body is reconstructed using an inverse algorithm. Due to the ill-posed nature of EIT inverse problem, EIT bears poor spatial resolution and behaves non-linearly in nature. Point spread function (PSF), which is calculated over the whole domain as responses to a small circular anomaly moving around the entire domain, is a characteristic parameter to estimate the performance of imaging systems. In order to analyze the quality of EIT reconstructed image, PSF is employed in this work. PSF incorporates the key imaging attributes, comprising amplitude response, resolution, position error, shape deformation and ringing effect. This paper presents a numerical study on the use of PSF for static and dynamic EIT image reconstruction. The static image reconstruction is done using the modified Newton Raphson (mNR) algorithm whereas the dynamic image reconstruction is done with extended Kalman filter (EKF). A detailed analysis of the performance of mNR and EKF has been carried out based upon on the imaging attributes gathered using the said algorithms. The results are convincing and provide a fresh perspective to use the PSF in order to analyze the performance of EIT image reconstruction.

An analysis of Humpback whale songs for individual classification

Acoustics based tracking systems are in use for studying cetacean behaviour. Such noninvasive techniques can also prove efficient for population assessment of vocally active species. One problem in this regard is to distinguish already counted reappearing cetaceans, even if reappearance occurs after a brief interval. In this connection we propose development of individual identification system for humpback whales (Megaptera novaeangliae) based on unique acoustic features underlying a song. Earlier we analyzed recognition performance of cepstrum based voice signature in seven humpback whales. The results were based on training and test data sampled from the same song. In this work, we test our hypothesis using data from different songs (i.e., recording timings of training and test data sets do not overlap) for two different individuals. Recognition rates for two individuals are above 80% and 95%, respectively. However an eight years old song gives degraded recognition rate of around 58%. The results give a...

Design of a memory-card based low-cost GPS data-logger for livestock monitoring

This work presents details of a memory card based open-source, low-cost and low power solution for long-term monitoring of grazing livestock. The described global positioning system (GPS) based data logger node weighs 150g (including D-size battery of 3.6V and 13AH and a casing with dimensions of 10 × 7.5 × 3.5 cm). With a memory card of 4GB, it can record geo-coordinates for 248 days (4 readings per day), with bill of materials less than 150 USD. Earlier open-source works based on VHF radio tracking and other commercial devices cost above 1000 USD and are not customizable. This work presents the hardware design and trial data obtained from a grazing sheep in the northern Himalaya, Pakistan. The solution is relevant for applications where data-loggers are easy to retrieve.

Road quality classification for road repair authorities and regular drivers, using an on-board data logger: poster abstract

This paper attempts to improve road condition monitoring by providing a framework for real-time detection of road anomalies for city municipalities and regular drivers. We have developed and publicly shared a vast quantity of heterogeneous data set collected over a continuous drive for four different kinds of road anomalies - Cat eyes, Potholes, Manholes and Speed Bumps, using a custom-made, dedicated device for data logging, recording vehicles acceleration and GPS location. Sequential forward selection was performed on three groups of features i.e. FFT, DWT and peak accelerations for feature extraction and Classification and Regression Tree (CART) was used as the classifier. Performance metrics including FPR, FNR and TPR were calculated and compared and the best results have been reported. In addition to this, we also present annotated maps for repair authorities and regular drivers for visual inspection and intelligent navigation.

Numerical Solution and Analysis of Three-Dimensional Transient Darcy Flow

AbstractThis paper presents a detailed analysis of a numerical solution of three-dimensional transient Darcy flow. The numerical solution of the governing parabolic partial differential equations is obtained by using stabilized mixed Galerkin method and backward Euler method for the discretization of space and time, respectively. The resulting well-posed system of algebraic equations is subsequently solved using conjugate gradient method. The proposed model is validated against Mongan’s analytical model for underground water flow using a set of hexahedral and tetrahedral meshes. The model is used to analyze the transient behavior by simulating the Darcy flow through homogeneous and heterogeneous as well as isotropic and anisotropic media. For large meshes, a parallel algorithm of the transient Darcy flow is also developed for shared memory architecture using OpenMP library. For structured meshes, a speedup of over 22 is obtained on dual AMD Opteron processors. The proposed numerical method for transient Darcy flow offers stability, ease of implementation in higher dimensions and parallel solution for large and complex geometry using standard finite element spaces.

Validating numerical solution of transient Darcy flow using the stabilized mixed finite element method

The natural flows through porous media often exhibit transient behavior. Some of the examples include water movement in aquifers, oil flow in reservoirs and blood passing through arteries walls. For accurate modeling of such flows, the Darcy model is used with an additional time-dependent pressure term. In this paper, validation of the three-dimensional numerical solution of transient Darcy flow using the stabilized mixed finite element method is presented. The proposed numerical solution employs the implicit backward difference method for the discretization of time, whereas, for space discretization, the Galerkin technique is used. The model is validated against analytical models including the Theis equation for pressure drawdown near a pumping well. The proposed solution is tested for different values of the viscosity of the fluid, and the permeability and specific storage of the medium. The error analysis shows that the stabilized mixed Galerkin methods give stable solutions with no oscillations and spurious results. It is also found that the viscosity of the fluid and the permeability of the medium have prominent effects on the transient behavior of Darcy flow.

Three-Dimensional Stabilized Mixed Galerkin Method for Darcy Flow

Two-dimensional stabilized mixed Galerkin method using self-adjoint residual of the momentum equation (Darcys law) has been previously implemented. In the present work, we are extending the two-dimensional stabilized model by incorporating the third dimension into the mathematical formulation. This extended stabilized mixed model would be able to accurately simulate more realistic flow of incompressible fluid through porous media. In the experimentation, the media is assumed homogeneous and the flow is considered laminar. The study shows that the numerically computed Darcy pressure and the velocity using hexahedral elements are comparable to the analytical solutions. In addition, the approximations converge to the exact solutions as the size of the elements decreases.