Sirajudeen Gulam Razul

Validation of the IRI-2012 model with GPS-based ground observation over a low-latitude Singapore station

The ionospheric total electron content (TEC) in the low-latitude Singapore region (geographic latitude 01.37° N, longitude, 103.67° E, geomagnetic latitude 8.5° S) for 2010 to 2011 was retrieved using the data from global positioning system (GPS)-based measurements. The observed TEC from GPS is compared with those derived from the latest International Reference Ionosphere (IRI)-2012 model with three options, IRI-Nequick (IRI-Neq), IRI-2001, and IRI-01-Corr, for topside electron density. The results showed that the IRI-Neq and IRI-01-Corr models are in good agreement with GPS-TEC values at all times, in all seasons, for the year 2010. For the year 2011, these two models showed agreement at all times with GPS-TEC only for the summer season, and for the period 11:00 to 24:00 UT hours (19:00 to 24:00 LT and 00:00 to 08:00 LT) during the winter and equinox seasons. The IRI-2012 model electron density profile showed agreement with constellation observing system for meteorology, ionosphere, and climate (COSMIC) radio occultation (RO)-based measurements around 250 to 300 km and was found to be independent of the options for topside density profiles. However, above 300 km, the IRI-2012 model electron density profile does not show agreement with COSMIC measurements. The observations (COSMIC and GPS) and IRI-2012-based data of TEC and electron density profiles were also analyzed during quiet and storm periods. The analysis showed that the IRI model does not represent the impact of storms, while observations show the impact of storms on the low-latitude ionosphere. This suggests that significant improvements in the IRI model are required for estimating behavior during storms, particularly in low-latitude regions.

An efficient sub-Nyquist receiver architecture for spectrum blind reconstruction and direction of arrival estimation

Spectrum blind reconstruction and direction-of-arrival (DOA) estimation of multiple narrow-band signals spread over wide spectrum sampled at sub-Nyquist sampling rates are considered in this paper. A new sub-Nyquist sampling receiver architecture which requires minimal hardware along with an efficient algorithm for estimation of the parameters and spectrum reconstruction is presented. We further show with the proposed approach, that a minimum average sampling rate of 2(N + 1)B would be sufficient in order to reconstruct the spectrum as well as estimate their corresponding DOA of N narrow-band signals of maximum bandwidth B. Simulation results are also provided which shows the performance very close to the Cramer Rao bound.

Modified CRLB for Cooperative Geolocation of Two Devices Using Signals of Opportunity

We consider the problem of localizing two devices using signals of opportunity from beacons with known positions. Beacons and devices have asynchronous local clocks or oscillators with unknown clock skews and offsets. We model clock skews as random, and analyze the biases introduced by clock asynchronism in the received signals. By deriving the equivalent Fisher information matrix for the modified Bayesian Cramér-Rao lower bound (CRLB) of device position and velocity estimation, we quantify the errors caused by clock asynchronism. We propose an algorithm based on differential time-difference-of-arrival (DTDOA) and frequency-difference-of-arrival (FDOA) that mitigates the effects of clock asynchronism to estimate the device positions and velocities. Simulation results suggest that our proposed algorithm is robust and approaches the CRLB when clock skews have small standard deviations.

Distributed Localization of a RF Target in NLOS Environments

We propose a novel distributed expectation maximization (EM) method for non-cooperative RF target localization using a wireless sensor network. We consider the scenario where few or no sensors receive line-of-sight signals from the target. In the case of non-line-of-sight signals, the signal path consists of a single reflection between the transmitter and receiver. Each sensor is able to measure the time difference of arrival of the targets signal with respect to a reference sensor, as well as the angle of arrival of the targets signal. We derive a distributed EM algorithm where each node makes use of its local information to compute summary statistics, and then shares these statistics with its neighbors to improve its estimate of the target localization. We show that our distributed algorithm converges, and simulation results suggest that our method achieves an accuracy close to the centralized EM algorithm. We apply the distributed EM algorithm to a set of experimental measurements with a network of four nodes, which confirm that the algorithm is able to localize a RF target in a realistic non-line-of-sight scenario.

Diagnosis of virus infection in orchid plants with high-resolution optical coherence tomography.

This work investigates the use of optical coherence tomography (OCT) to identify virus infection in orchid plants. Besides revealing the cross-sectional structure of orchid leaves, highly scattering upper leaf epidermides are detected with OCT for virus-infected plants. This distinct feature is not observable under histological examination of the leaf samples. Furthermore, the leaf epidermides of stressed but healthy plants, which exhibit similar visual symptoms as virus-infected plants, are not highly scattering and are similar to those of healthy plants. The results suggest that virus-infected orchid plants can be accurately identified by imaging the epidermal layers of their leaves with OCT. The OCT modality is suitable for fast, nondestructive diagnosis of orchid virus infection, which may potentially lead to significant cost savings and better control of the spread of viruses in the orchid industry.

Target Tracking in Mixed LOS/NLOS Environments Based on Individual Measurement Estimation and LOS Detection

In this paper, a new method based on estimation and line-of-sight (LOS) detection of individual time-of-arrival (TOA) measurement and Kalman filter (KF) is proposed to track a moving target in mixed line-of-sight and non-line-of-sight (LOS/NLOS) environments. In the proposed tracking algorithm, TOA measurements collected by multiple stationary sensors in a wireless sensor network are used. First, a pseudo-measured position is calculated by choosing the point along the circle defined by a given TOA measurement which has the shortest distance to the predicted position of a moving target. The pseudo-measured position is shown to be an approximately unbiased estimate of the true position of the target. Second, each pseudo-measured position calculated is passed to a detector to be identified as either LOS or NLOS. The average of all the selected LOS pseudo-measured positions is then used as a new pseudo-measurement for the KF to track the moving target. Unlike all the existing target tracking algorithms in mixed LOS/NLOS environments, the proposed tracking algorithm is able to perform target tracking even with just one LOS TOA measurement at a given time instance without prior information of the NLOS noise which may be difficult to obtain in practice. Another advantage of the proposed tracking algorithm is its computational efficiency. Simulation results show that the proposed tracking algorithm performs better than some recent tracking algorithms, particularly in severe mixed LOS/NLOS environments.

Quantitative diagnosis of cervical neoplasia using fluorescence lifetime imaging on haematoxylin and eosin stained tissue sections.

The use of conventional fluorescence microscopy for characterizing tissue pathological states is limited by overlapping spectra and the dependence on excitation power and fluorophore concentration. Fluorescence lifetime imaging microscopy (FLIM) can overcome these limitations due to its insensitivity to fluorophore concentration, excitation power and spectral similarity. This study investigates the diagnosis of early cervical cancer using FLIM and a neural network extreme learning machine classifier. A concurrently high sensitivity and specificity of 92.8% and 80.2%, respectively, were achieved. The results suggest that the proposed technique can be used to supplement the traditional histopathological examination of early cervical cancer.

Spectrum blind reconstruction and direction of arrival estimation at sub-Nyquist sampling rates with uniform linear array

This paper considers the problem of sparse spectrum blind reconstruction and its constituent narrow band (bandwidth not exceeding B Hz) source direction of arrival (DOA) estimation, at sub-Nyquist sampling rates and with an M element uniform linear array. We propose a modification to the receiver architecture by adding an M channel delay network to only the first sensor element. This delay network in practice can simply be realized by cascading M identical delays. Further, a novel ESPRIT based algorithm, by making use of new transformation matrices, which automatically pairs the carrier frequencies along with their corresponding DOAs is presented. We show that with the proposed approach, an ADC sampling frequency of fs ≥ B Hz is sufficient and upto M - 2 source DOAs and their corresponding spectrum can be reconstructed even if all the frequencies exactly alias to the same frequency.

Fluorescence lifetime discrimination using expectation-maximization algorithm with joint deconvolution

The fluorescence lifetime technique offers an effective way to resolve fluorescent components with overlapping emission spectra. The presence of multiple fluorescent components in biological compounds can hamper their discrimination. The conventional method based on the nonlinear least-squares technique is unable to consistently determine the correct number of fluorescent components in a fluorescence decay profile. This can limit the applications of the fluorescence lifetime technique in biological assays and diagnoses where more than one fluorescent component is typically encountered. We describe the use of an expectation-maximization (EM) method with joint deconvolution to estimate the fluorescence decay parameters, and the Bayesian information criterion (BIC) to accurately determine the number of fluorescent components. A comprehensive simulation and experimental study is carried out to compare the performance and accuracy of the proposed method. The results show that the EM-BIC method is able to accurately identify the correct number of fluorescent components in samples with weakly fluorescing components.

Heart Sound localization from Respiratory Sound using a robust wavelet based approach

This paper addresses the problem of heart sounds (HS) localization from single channel respiratory sounds (RS) recordings by applying wavelet-based localization scheme. After a wavelet-based multiscale decomposition of the noisy signal, HS contaminated segments are localized in the noisy RS signal based on the cumulative sums of likelihood ratios capturing the dynamic behaviour of the signal. Quantitative evaluation of the localized HS segments for various types of simulated data has been performed. The comparisons between the estimated boundaries of the localized HS segments and the actual segment boundaries of the synchronized pure HS signals show the proposed method is able to localize the HS segments accurately in an automatic way. Also, the test results on real RS recordings in terms of the detection accuracy show the promising performance by the proposed method.