Simulations of systematic direction-dependent instrumental effects in intensity mapping experiments

Intensity mapping experiment treats the 21 cm radio emission as a diffuse source and allows smaller and relatively cheaper radio antennas with short baselines to be used in such experiments. However, the technique is restricted by the precise subtraction of the foreground continuum signal from Galactic and extragalactic radio sources. Furthermore, the signal is subjected to direction-dependent effects, particularly the primary beam, as it modulates the intensity as a function of the sky position. In addition, due to the imperfections in the antenna feeds, a portion of the polarized foreground tends to find its way into the total intensity, making it a major obstacle to detect the H I signal. In the case of dish arrays, this will be dominated by the instrument mispointings and polarization leakage. To estimate this contamination, we use OSKAR to simulate ‘dish-like’ primary beams and then perturb these primary beams by introducing gain, phase, and surface distribution errors. We then simulate the foregrounds with these modelled beams to determine the errors in Stokes I and also observe the amount of |Q + iU| that corrupts I. Our simulation shows that the H I signal power can be measured at a multipole moment of l = 100 if we do not correct for any polarization leakage of the beam and at a multiple moment of l = 25 if we correct for the beam from I, assuming the beam is not known to the extent to which we have considered in this paper

Primary beam effects of radio astronomy antennas -- II. Modelling the MeerKAT L-band beam

After a decade of design and construction, South Africa's SKA-MID precursor MeerKAT has begun its science operations. To make full use of the widefield capability of the array, it is imperative that we have an accurate model of the primary beam of its antennas. We have taken available L-band full-polarization 'astro-holographic' observations of three antennas and a generic electromagnetic simulation and created sparse representations of the beams using principal components and Zernike polynomials. The spectral behaviour of the spatial coefficients has been modelled using discrete cosine transform. We have provided the Zernike-based model over a diameter of 10 deg averaged over the beams of three antennas in an associated software tool (EIDOS) that can be useful in direction-dependent calibration and imaging. The model is more accurate for the diagonal elements of the beam Jones matrix and at lower frequencies. As we get more accurate beam measurements and simulations in the future, especially for the cross-polarization patterns, our pipeline can be used to create more accurate sparse representations of MeerKAT beams.Comment: 16 pages, 18 figures. This is a pre-copyedited, author-produced PDF of an article accepted for publication in MNRAS following peer review. The version of record [K. M. B. Asad et al., 2021] is available online at: https://doi.org/10.1093/mnras/stab10

Anomaly Detection in Power Generation Plants Using Machine Learning and Neural Networks

The availability of constant electricity supply is a crucial factor to the performance of any industry. Nevertheless, the unstable supply of electricity in Cameroon has led to countless periods of electricity load shedding, hence, making the management of the telecom industry to fall on backup power supply such as diesel generators. The fuel consumption of these generators remain a challenge due to some perturbations in the mechanical fuel level gauges and lack of maintenance at the base stations resulting to fuel pilferage. In order to overcome these effects, we detect anomalies in the recorded data by learning the patterns of the fuel consumption using four classification techniques namely; support vector machines (SVM), K-Nearest Neighbors (KNN), Logistic Regression (LR), and MultiLayer Perceptron (MLP) and then compare the performance of these classification techniques on a test data. In this paper, we show the use of supervised machine learning classification based techniques in detecting anomalies associated with the fuel consumed dataset from TeleInfra base stations using the generator as a source of power. Here, we perform the normal feature engineering, selection, and then fit the model classifiers to obtain results and finally, test the performance of these classifiers on a test data. The results of this study show that MLP has the best performance in the evaluation measurement recording a score of 96% in the K-fold cross validation test. In addition, because of class imbalance in the observation, we use the precision-recall curve instead of the ROC curve and registered the probability of the Area Under Curve (AUC) as 0:98

Cause-specific childhood mortality in Africa and Asia : evidence from INDEPTH health and demographic surveillance system sites

Childhood mortality, particularly in the first 5 years of life, is a major global concern and the target of Millennium Development Goal 4. Although the majority of childhood deaths occur in Africa and Asia, these are also the regions where such deaths are least likely to be registered. The INDEPTH Network works to alleviate this problem by collating detailed individual data from defined Health and Demographic Surveillance sites. By registering deaths and carrying out verbal autopsies to determine cause of death across many such sites, using standardised methods, the Network seeks to generate population-based mortality statistics that are not otherwise available.; To present a description of cause-specific mortality rates and fractions over the first 15 years of life as documented by INDEPTH Network sites in sub-Saharan Africa and south-east Asia.; All childhood deaths at INDEPTH sites are routinely registered and followed up with verbal autopsy (VA) interviews. For this study, VA archives were transformed into the WHO 2012 VA standard format and processed using the InterVA-4 model to assign cause of death. Routine surveillance data also provided person-time denominators for mortality rates. Cause-specific mortality rates and cause-specific mortality fractions are presented according to WHO 2012 VA cause groups for neonatal, infant, 1-4 year and 5-14 year age groups.; A total of 28,751 childhood deaths were documented during 4,387,824 person-years over 18 sites. Infant mortality ranged from 11 to 78 per 1,000 live births, with under-5 mortality from 15 to 152 per 1,000 live births. Sites in Vietnam and Kenya accounted for the lowest and highest mortality rates reported.; Many children continue to die from relatively preventable causes, particularly in areas with high rates of malaria and HIV/AIDS. Neonatal mortality persists at relatively high, and perhaps sometimes under-documented, rates. External causes of death are a significant childhood problem in some settings