Satellite Communications Systems Systems Techniques And Technology By Gerard Maral

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Written for research students studying or researching in the areas related to satellite communications systems and networks, the updated sixth edition of Satellite Communications Systems offers an essential guide to the most recent developments in the field of satellite communications engineering and references to international standards.

MICHEL BOUSQUET, ISAE-SUPAERO (Retired) has lectured on satellite communications in numerous universities and continuing education courses world-wide. He was involved in several EU and ESA research programmes. Standing on the committees of AIAA and IEEE conferences, he is the recipient of the AIAA Communications Award for 2019.

Building on the success of previous editions, Satellite Communications Systems, Fifth Edition covers the entire field of satellite communications engineering from orbital mechanics to satellite design and launch, configuration and installation of earth stations, including the implementation of communications links and the set-up of the satellite network. This book provides a comprehensive treatment of satellite communications systems engineering and discusses the technological applications. It demonstrates how system components interact and details the relationship between the system and its environment. The authors discuss the systems aspects such as techniques enabling equipment and system dimensioning and state of the art technology for satellite platforms, payloads and earth stations.

By offering a detailed and practical overview, Satellite Communications Systems continues to be an authoritative text for advanced students, engineers and designers throughout the field of satellite communications and engineering.

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HgI2 is an excellent semiconductor material for a low energy, room temperature x-ray spectrometer. The high values of the atomic numbers for its constituent elements gives high x-ray and gamma ray stopping power. The band gap of HgI2 is significantly higher than other commonly used semiconductors. Owing to the large value band gap, the leakage current for HgI2 devices is smaller, thus allowing low noise performance. Devices fabricated from HgI2 crystals have demonstrated energy resolution sufficient to distinguish the x-ray emission from the neighboring elements on the periodic table. Also the power requirements of HgI2 are very low. These characteristics make a HgI2 spectrometer an ideal component in a satellite based detection system. Unfortunately, HgI2 crystals tend to deteriorate with time, even if protected by standard semiconductor encapsulants. This degradation ruins the performance of the device in terms of its energy resolution and pulse amplitude. The degrading mechanism is believed to be material loss occurring from below the electrodes, due to high vapor pressure of HgI2 at room temperature. To address this major obstacle to rapid expansion of HgI2 technology, a research program aimed at improving device stability by encapsulation with inert polymeric materials was carried out. The program focused specifically on optimizing the encapsulant materials and their deposition techniques. The principal objectives for this program were device encapsulation, device testing, and accelerated testing to ensure very long term stability of these high resolution sensors. A variety of encapsulants were investigated with the selection criteria based on their chemical diffusion barrier properties, mechanical stability, reactivity, and morphology of encapsulant films. The investigation covered different classes of encapsulants including solvent based encapsulants, vapor deposited encapsulants, and plasma polymerized encapsulants. A variety of characterization techniques

Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC. The software DIY ABC is freely available at

Summary: Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC. Availability: The software DIY ABC is freely available at Contact: j.cornuet@imperial.ac.uk Supplementary information: Supplementary data are also available at PMID:18842597 153554b96e

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