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Nano-biosorbents for Decontamination of Water, Air, and Soil
Pollution explores the properties of nanobiosorbents and their
applications in the removal of contaminants from the natural
environment. The use of nanobiosorbents for environmental
protection is a combinational approach that incorporates
nanotechnology with naturally occurring biopolymers that form an
amalgamation of nano-biopolymers used as sorbent materials in the
removal of a variety of contaminants from wastewaters. This is an
important reference source for materials scientists, bioscientists
and environmental scientists who are looking to understand how
nanobiosorbents are being used for a range of environmental
applications.
Smart Polymer Nanocomposites: Design, Synthesis, Functionalization,
Properties, and Applications brings together the latest research on
synthetic methods and surface functionalization of polymers and
polymer composites for advanced applications. Sections cover the
basic principles of advanced polymer nanocomposites, including
morphology, materials, characterization, and copolymerization,
provide in-depth coverage of synthetic methods, facilitating the
preparation of polymeric nanoparticles with the required
properties, examine the morphologies of polymer nanocomposites and
stimuli-responsive surfaces, and focus on cutting-edge approaches
to tailoring polymeric nanocomposites according to the
requirements. The book's final chapters focus on smart polymer
nanocomposites for specific advanced applications, including
high-temperature environments, bone tissue regeneration,
biomedicine, wastewater treatment, dielectric and energy storage,
chiral separation, food packaging, sensing, and drug delivery. This
is a valuable resource for researchers and advanced students in
polymer science, composite science, nanotechnology, and materials
science, as well as those approaching the area from a range of
other disciplines, including industry R&D.
Significant performance gains are achievable in wireless systems
using a Multi-Input Multi-Output (MIMO) communication system
employing multiple antennas.This architecture is suitable for
higher data rate multimedia communications.One of the challenges in
building a MIMO system is the tremendous processing power required
at the receiver. MIMO Symbol detection involves detecting symbol
from a complex signal at the receiver. Nature Inspired techniques
for non-linear approximate MIMO detectors with a low complexity
near-optimal performance is presented. The approach is particularly
attractive as Swarm Intelligence (SI) is well suited for physically
realizable, real- time applications, where low complexity and fast
convergence is of absolute importance. Application of Particle
Swarm Optimization (PSO) and Ant Colony Optimization (ACO)
algorithms is studied. While an optimal Maximum Likelihood (ML)
detection using an exhaustive search method is prohibitively
complex, it is established that Swarm Intelligence optimized MIMO
detection algorithms gives near-optimal Bit Error Rate (BER)
performance, thereby reducing the ML computational complexity
significantly
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