Abstract: Advancements in the field of artificial intelligence
(AI) made during this decade have forever changed the way we look
at automating spacecraft subsystems including the electrical power
system. AI have been used to solve complicated practical problems
in various areas and are becoming more and more popular nowadays.
In this paper, a mathematical modeling and MATLAB–SIMULINK
model for the different components of the spacecraft power system is
presented. Also, a control system, which includes either the Neural
Network Controller (NNC) or the Fuzzy Logic Controller (FLC) is
developed for achieving the coordination between the components of
spacecraft power system as well as control the energy flows. The
performance of the spacecraft power system is evaluated by
comparing two control systems using the NNC and the FLC.
Abstract: Stevia rebaudiana Bertoni (natural sweetener) belongs
to Asteraceae family and can be used as substitute of artificial
sweeteners for diabetic patients. Conventionally, it is cultivated by
seeds or stem cutting, but seed viability rate is poor. A protocol for
callus induction and multiplication was developed to produce large
no. of calli in short period. Surface sterilized nodal, leaf and root
explants were cultured on Murashige and Skoog (MS) medium with
different concentrations of plant hormone like, IBA, kinetin, NAA,
2,4-D, and NAA in combination with 2,4-D. 100% callusing was
observed from leaf explants cultured on combination of NAA and
2,4-D after three weeks while with 2,4-D, only 10% callusing was
observed. Calli obtained from leaf and root explants were shiny green
while with nodal explants it was hard and brown. The present
findings deal with induction of callusing in Stevia to achieve the
rapid callus multiplication for study of steviol glycosides in callus
culture.
Abstract: Rapid urbanization, industrialization and population
growth have led to an increase in number of automobiles that cause
air pollution. It is estimated that road traffic contributes 60% of air
pollution in urban areas. A case by case assessment is required to
predict the air quality in urban situations, so as to evolve certain
traffic management measures to maintain the air quality levels with
in the tolerable limits. Calicut city in the state of Kerala, India has
been chosen as the study area. Carbon Monoxide (CO) concentration
was monitored at 15 links in Calicut city and air quality performance
was evaluated over each link. The CO pollutant concentration values
were compared with the National Ambient Air Quality Standards
(NAAQS), and the CO values were predicted by using CALINE4 and
IITLS and Linear regression models. The study has revealed that
linear regression model performs better than the CALINE4 and
IITLS models. The possible association between CO pollutant
concentration and traffic parameters like traffic flow, type of vehicle,
and traffic stream speed was also evaluated.