Over the decades, electricity demand has
increased considerably. Electric energy is produced in power
plants that are located far away from consumers. It is given for
consumption through a vast network of transmission and
distribution lines. In many places on the power grid, it may be
desirable and necessary to modify some features of the power
supply. This is accomplished by a suitable device assembly
called a substation. Some characteristics of the power supply
include voltage level, power factor, frequency, AC to DC, etc.
are included. It is a major challenge to design such a modern
complex structure keeping in mind all the design parameters.
This paper targets the design and implementation of a 16-bit RISC Processor using VHDL (Very High Speed Integrated Circuit Hardware Description Language). As IC chip design involves complex computations and intense usage of resources, by using an HDL we can save resources and time by implementing it using the software approach. The implementation strategies have been borrowed from the popular MIPS architecture to a certain extent. The processor has 16-bit arithmetic and logical instruction set which has been designed
and simulated. The instruction set is extremely simple and it gives
an insight into the kind of hardware that would be required to
execute the instructions accordingly. The ALU, instruction
register, program counter, register file, control unit and memory
have been integrated in the proposed processor. All the modules
in the design are coded in VHDL to ease the description,
verification, simulation and hardware implementation. The
blocks are designed using the behavioral approach.
This paper deals with the Taguchi technique and
Genetic algorithm (GA) for predicting the responses of turning
operation on CNC lathemachine for EN19steel. The number of
experiments has been carried out using Taguchi’s orthogonal
array in the design ofexperiments (DOE). The cutting
parameters are spindle speed, feed rate and depth of cut. The
Analysis of Variance (ANOVA) and Signal-to-Noise ratio were
used to study the performance characteristics in turning
operation. The accurate mathematical model has been
developed using genetic algorithm.The genetic algorithm is used
to get the optimum cutting parameters by using the regression
equations of different parameters. The research showed
acceptable prediction results for the developed model.
Abstract- The case study depicts the outcome of implementing a Realtime Continuous Water Monitoring System designed specially for surface water bodies called FOREMS. The device helped in analysing various pollution index while it was installed in Najafgarh drain in Haryana. An IOT device is used to remotely log the pollution indices online for applied data analytics. The conclusion depicts a theoretical analysis against pollution source identification.
(PDF) Realtime Monitoring Source Tracking Water Pollution in Najafgarh Drain Before During COVID-19 Outbreak with FOREMS. Available from: https://www.researchgate.net/publication/342331206_Realtime_Monitoring_Source_Tracking_Water_Pollution_in_Najafgarh_Drain_Before_During_COVID-19_Outbreak_with_FOREMS [accessed Jun 26 2020].
COVID-19, outbreak since December 2019, has impacted more than 150 countries as of May 2020. The uncertainty prevails with no cure and vaccine for this pandemic, and the economic situation worsens globally. Indian economy contracts as this uncertainty prolongs. Companies and business need a proper data driven guidance system to suggest their recovery trajectory and also give them optimal prioritization of their resources and operations to reduce unnecessary cash burn and sustain themselves in these unforeseen times. This should be addressed by looking into all local and global economic parameters, current market dynamics, consumer purchase intent and shift in behavior. Ensemble framework to integrate various econometric models, and mathematical constructs are used to further simulate various shock/stress scenarios to identify the pace and path to recovery for different businesses in the short-term and long-term perspectives. Hence this paper attempts at quantifying the impact of COVID19 on different business sectors and their comeback strategy by analyzing all different self/competitive/market indicators.