Modelling and prediction of malaria vector distribution in Bangladesh from remote-sensing data

Epidemic malaria cases and satellite-based vegetation health (VH) indices were investigated to be used as predictors of malaria vector activities in Bangladesh. The VH indices were derived from radiances, measured by the Advanced Very High Resolution Radiometer (AVHRR) on National Oceanic and Atmospheric Administration (NOAA) afternoon polar orbiting satellites. Two indices characterizing moisture and thermal conditions were investigated using correlation and regression analysis applied to the number of malaria cases recorded in the entire Bangladesh region and three administrative divisions (Chittagong, Sylhet and Dhaka) during 1992–2001. It is shown that during the cooler months (November to March), when mosquitoes are less active, the correlation between number of malaria cases and two investigated indices was near zero. From April, when the mosquito activity season starts, the correlation increased, reaching a maximum value of 0.5–0.8 by the middle of the high season (June to July), reducing thereafter to zero by the beginning of the cool season in November. Following these results, regressional equations for the number of malaria cases as a function of VH indices were built and tested independently. They showed that, in the main malaria administrative division (Chittagong) and the entire Bangladesh region, the regressional equations can be used for early prediction of malaria development.     

Use of remote sensing data for estimation of winter wheat yield in the United States

This paper shows the application of remote sensing data for estimating winter wheat yield in Kansas. An algorithm uses the Vegetation Health (VH) Indices (Vegetation Condition Index (VCI) and Temperature Condition Index (TCI)) computed for each week over a period of 23 years (1982–2004) from Advance Very High Resolution Radiometer (AVHRR) data. The weekly indices were correlated with the end of the season winter wheat (WW) yield. A strong correlation was found between winter wheat yield and VCI (characterizing moisture conditions) during the critical period of winter wheat development and productivity that occurs during April to May (weeks 16 to 23). Following the results of correlation analysis, the principal components regression (PCR) method was used to construct a model to predict yield as a function of the VCI computed for this period. The simulated results were compared with official agricultural statistics showing that the errors of the estimates of winter wheat yield are less than 8%. Remote sensing, therefore, is a valuable tool for estimating crop yields well in advance of harvest, and at a low cost.     

Dynamic color quantization of video sequences

We present an efficient algorithm for dynamic adaptive color quantization of 24 bit image (video) sequences, important in multimedia applications. Besides producing hi fidelity 8 bit imagery, our algorithm runs with minimal computational cost and the generated colormaps are robust to small differences in consecutive images. Apart from the two standard color quantization tasks, colormap design and quantizer mapping, our algorithm includes colormap filling-an operation unique to dynamic color quantization. This task solves the problem of screen flicker, a serious problem in dynamic quantization of image sequences, resulting from rapid changes in display of colormaps. Our solution is based on two ideas: including in the current colormap a small set of color representatives from the previous image; assigning representatives to the colormap entries in an order that reduces the difference between contents of equal entries in consecutive colormaps. Our algorithm runs in near real time on medium range workstations     

Reconstruction of nonuniformly sampled band-limited signals and jitter error reduction

The restoration of a band-limited signal from its unequally spaced samples is considered. The proposed method is based on the correction of a response of an ideal LPF to the sampling data. The ideal LPF response to the unequally spaced samples is simply divided by a distribution function specified by the sampling times of the input data. The jitter error resulting from the application of the proposed method is evaluated. It is shown that the increase in sampling time deviations from their synchronous positions increases the efficiency. The proposed method is shown to give a more accurate signal restoration than the traditional one.     

Fault diagnosis in non-reciprocal networks

Based on the theorem concerning the maximum number of independent simulations in an m-port together with Tellegen's theorem, some methods are proposed for the determination of the values of the faulty elements. These methods require a minimum number of measurements at the external nodes of the circuit. A numerical example of the application of such a method is given.     

Forecasting crop production using satellite-based vegetation health indices in Kansas,USA

This article shows the results of early crop yield prediction from remote-sensing data. The study was carried out in Kansas, USA. The methodology proposed allows the estimation of winter wheat (WW), sorghum and corn yields 3–4 months before harvest. The procedure uses the vegetation health (VH) indices (vegetation condition index (VCI) and temperature condition index (TCI)) computed for each pixel and week over a 21-year period (1985–2005) from the Advanced Very High Resolution Radiometer (AVHRR) data. Over this period, a strong correlation was found between crop yield and VH indices during the weather-related critical period of crop development, which controls much final crop productivity. The 3-month advanced yield forecasts were independently compared with official agricultural statistics, showing that the estimation errors for WW, sorghum and corn were 8%, 6% and 3%, respectively. Implementing the 3–4 months lead forecast in operational practice will aid farmers to mitigate weather vagaries using irrigation, diseases/insects control, application of fertilizers and so on during a growing season and will help decision-makers to regulate marketing strategies, import/export and price policies and address food security issues.     

Nonuniform sampling of bandlimited modulated signals

In this paper it is shown that an unequally spaced sampling can be implemented on the base of sinc-composition function usually used in the uniform sampling expansion. The nonuniform sampler is based on a level crossing detector (LCD) which produces a sample of carrier whenever the integral of modulating function crosses a threshold level. The information about the modulated signal is contained in the carrier samples taken at the instants which are defined by modulating function. The Riemann-Stieltjes uniform integral sum representation of the Fourier transform of signal is used as a mathematical base for the derivation of the principal results. In the particular case of the representation of single-valued real positive function, the suggested method leads to the signal representation by the equally weighted sampling at the nonuniformly distributed instants. The error estimation and numerical example illustrating the methods are given.     

Unbiased estimation of an initial phase

This paper explores the problem of the unbiased estimation of the initial phase of a tone burst. Two types of initial phase estimators are investigated. The first one is based on the modification of a well-known statistically-optimal approach of estimation the phase of a continuous sinusoidal signal in the presence of a noise. The modified version permits nonlinear compensation of a priori unknown bias which is a function of a tone frequency, length of the observation interval, and of an unknown initial phase itself. The second approach employs a notch filter at the burst's ‘steady-state’ frequency. The transient of such a filter resulting from the onset of a burst can be used to deduce the signal's initial phase while the steady-state response is eliminated. Analysis shows that an estimation is unbiased and, therefore, it might be reasonably applied in high SNR environments where an estimate must be made within an extremely short length of an observation interval (less than one period).     

Multifrequency approach to fault diagnosis

This paper deals with multiple-fault diagnosis for linear analogue circuits. the proposed approach is based on multifrequency measurements of some voltage (transfer function) at the accessible output port and can be used for multiple-fault location. It uses certain algebraic invariant properties of the transfer function with respect to the set of faulty elements. Computationally this approach reduces checking the problem of multiple-fault diagnosis to one of the existence or non-existence of a common solution of two systems of linear equations; this amounts to the finding of the rank of a matrix. These linear equations are derived via symbolic representation of the measured voltage (transfer function) accessible for measurements. A numerical example of the application of such an approach is given.