Estimation of Correlation Functions by Stochastic Approximation

Two techniques for estimating the correlation function of a stationary random process using the method of stochastic approximation are developed. Both provide updated estimates as successive T-second observations are processed. Both assume a functional form for the correlation function that depends on a number of parameters that are estimated. One technique is based on the mean-square error; the other maximizes a likelihood function. Examples are included.     

Biologically weighted measurement of UV radiation in space and on Earth with the biofilm technique.

Biological dosimetry has provided experimental proof of the high sensitivity of the biologically effective UVB doses to changes in atmospheric ozone and has thereby confirmed the predictions from model calculations. The biological UV dosimeter 'biofilm' whose sensitivity is based on dried spores of B. subtilis as UV target weights the incident UV radiation according to its DNA damaging potential. Biofilm dosimetry was applicated in space experiments as well as in use in remote areas on Earth. Examples are long-term UV measurements in Antarctica, measurements of diurnal UV profiles parallel in time at different locations in Europe, continuous UV measurements in the frame of the German UV measurement network and personal UV dosimetry. In space biofilms were used to determine the biological efficiency of the extraterrestrial solar UV, to simulate the effects of decreasing ozone concentrations and to determine the interaction of UVB and vitamin D production of cosmonauts in the MIR station.     

A Pulsewidth-Modulated Dc-to-Dc Converter That Utilizes a Small Number of Components

In general, circuit reliability can be enhanced by either incorporating redundancy or by minimizing a circuits component count. Conventional nonregulating converters generally require two active devices, whereas in regulating converters or switching regulators as many as 10 transistors, either integrated or discrete, is not uncommon. A regulating dc-to-dc converter which provides useful regulation and which can be constructed with either two or three transistors is described.     

Harnessing functional food strategies for the health challenges of space travel—Fermented soy for astronaut nutrition

Astronauts face numerous health challenges during long-duration space missions, including diminished immunity, bone loss and increased risk of radiation-induced carcinogenesis. Changes in the intestinal flora of astronauts may contribute to these problems. Soy-based fermented food products could provide a nutritional strategy to help alleviate these challenges by incorporating beneficial lactic acid bacteria, while reaping the benefits of soy isoflavones. We carried out strain selection for the development of soy ferments, selecting strains of lactic acid bacteria showing the most effective growth and fermentation ability in soy milk (Streptococcus thermophilus ST5, Bifidobacterium longum R0175 and Lactobacillus helveticus R0052). Immunomodulatory bioactivity of selected ferments was assessed using an in vitro challenge system with human intestinal epithelial and macrophage cell lines, and selected ferments show the ability to down-regulate production of the pro-inflammatory cytokine interleukin-8 following challenge with tumour necrosis factor-alpha. The impact of fermentation on vitamin B1 and B6 levels and on isoflavone biotransformation to agluconic forms was also assessed, with strain variation-dependent biotransformation ability detected. Overall this suggests that probiotic bacteria can be successfully utilized to develop soy-based fermented products targeted against health problems associated with long-term space travel.     

Identification of Aircraft Stability and Control Parameters Using Hierarchical State Estimation

Previous attempts to identify aircraft stability and control derivatives from flight test data, using three-degrees-of-freedom (3-DOF) longitudinal or lateral-directional perturbation equation-of-motion models, suffer from the disadvantage that the coupling between the longitudinal and lateral-directional dynamics has been ignored. In this paper, the identification of aircraft stability parameters is accomplished using a more accurate 6-DOF model which includes this coupling. Hierarchical system identification theory is used to reduce the computational effort involved. The 6-DOF system of equations is first decomposed into two 3-DOF subsystems, one for the longitudinal dynamics and the other for the lateral-directional dynamics. The two subsystem parameter identification processes are then coordinated in such a way that the overall system parameter identification problem is solved. Next, a six-subsystem decomposition is considered. Computational considerations and comparison with the unhierarchically structured problem are presented.     

A Nominator-Selector Two-Stage Signal Detection Scheme

A two-stage approach to computationally efficient signal detection is to nominate candidate signal vectors using a suboptimal, but computationally cheap, detection scheme, and subsequently perform optimal detection on the candidates. Bounds on the detection performance of this approach are presented along with sufficient conditions for optimality. Examples are presented of an optimal and nearly optimal two-stage detection scheme where computational costs are drastically reduced relative to the singli-stage optimal detector.     

Solar modulation model with reentrant particles

We developed a one dimensional model of particle transport in the heliosphere. As opposite to widely used models, we apply a method where a quasi-particle is traced back in time. The model gives us the possibility to work on the possible existence of reentrant particles in the heliosphere that can be hardly solved by the traditional forward tracking method. Particles escape from the heliosphere and may reenter back. We estimate how these particles affect the modulation process in the heliosphere. Presented here are the results for different values of particles mean free path in the interstellar space and for different interstellar magnetic field values.     

“Modular Biospheres” – New testbed platforms for public environmental education and research

This paper will review the potential of a relatively new type of testbed platform for environmental education and research because of the unique advantages resulting from their material closure and separation from the outside environment. These facilities which we term “modular biospheres”, have emerged from research centered on space life support research but offer a wider range of application. Examples of this type of facility include the Bios-3 facility in Russia, the Japanese CEEF (Closed Ecological Experiment Facility), the NASA Kennedy Space Center Breadboard facility, the Biosphere 2 Test Module and the Laboratory Biosphere. Modular biosphere facilities offer unique research and public real-time science education opportunities. Ecosystem behavior can be studied since initial state conditions can be precisely specified and tracked over different ranges of time. With material closure (apart from very small air exchange rate which can be determined), biogeochemical cycles between soil and soil microorganisms, water, plants, and atmosphere can be studied in detail. Such studies offer a major advance from studies conducted with phytotrons which because of their small size, limit the number of organisms to a very small number, and which crucially do not have a high degree of atmospheric, water and overall material closure. Modular biospheres take advantage of the unique properties of closure, as representing a distinct system “metabolism” and therefore are essentially a “mini-world”. Though relatively large in comparison with most phytotrons and ecological microcosms, which are now standard research and educational tools, modular biospheres are small enough that they can be economically reconfigured to reflect a changing research agenda. Some design elements include lighting via electric lights and/or sunlight, hydroponic or soil substrate for plants, opaque or glazed structures, and variable volume chambers or other methods to handle atmospheric pressure differences between the facility and the outside environment.     

Application of SVM on satellite images to detect hotspots in Jharia coal field region of India

The present paper deals with the application of Support Vector Machine (SVM) and image analysis techniques on NOAA/AVHRR satellite image to detect hotspots on the Jharia coal field region of India. One of the major advantages of using these satellite data is that the data are free with very good temporal resolution; while, one drawback is that these have low spatial resolution (i.e., approximately 1.1 km at nadir). Therefore, it is important to do research by applying some efficient optimization techniques along with the image analysis techniques to rectify these drawbacks and use satellite images for efficient hotspot detection and monitoring. For this purpose, SVM and multi-threshold techniques are explored for hotspot detection. The multi-threshold algorithm is developed to remove the cloud coverage from the land coverage. This algorithm also highlights the hotspots or fire spots in the suspected regions. SVM has the advantage over multi-thresholding technique that it can learn patterns from the examples and therefore is used to optimize the performance by removing the false points which are highlighted in the threshold technique. Both approaches can be used separately or in combination depending on the size of the image. The RBF (Radial Basis Function) kernel is used in training of three sets of inputs: brightness temperature of channel 3, Normalized Difference Vegetation Index (NDVI) and Global Environment Monitoring Index (GEMI), respectively. This makes a classified image in the output that highlights the hotspot and non-hotspot pixels. The performance of the SVM is also compared with the performance obtained from the neural networks and SVM appears to detect hotspots more accurately (greater than 91% classification accuracy) with lesser false alarm rate. The results obtained are found to be in good agreement with the ground based observations of the hotspots. This type of work will be quite helpful in the near future to develop a hotspots monitoring system using these operational satellites data.