scholarly journals NOVEL APPROACH FOR BEST SIGNAL PROCESSING AND NETWORK STRUCTURE TO IMPROVE CLOUD ERP RELIABILITY AND HIGH SPEED

2021 ◽  
Vol 9 (09) ◽  
pp. 93-105
Author(s):  
R. Gaverineni Siva Ratna Kiran ◽  
◽  
Jammal Madaka Kodanda Rama Sastry ◽  
Keyword(s):  
Pattern Recognition ◽  
Signal Processing ◽  
Network Structure ◽  
High Speed ◽  
Fitness Function ◽  
Base Station ◽  
Optimization Approach ◽  
Erp Systems ◽  
Cluster Heads ◽  
Fitness Value

If the companies face difficulties in using ERP systems because of its complicated integrating and customising functions, the company can consider some other software for processing their data. On the other hand, those who are using ERP system should make precise settings for providing accurate data and timely service. An error-free network structure must be maintained by cloud ERP systems for providing enhanced service. Based on the network structure and best optimization methods, it must focus on nodes, clusters, LANs, and WANs. The novel data pre-processing consists of three core areas, and they are Pattern Recognition, Data Clustering, and Signal Processing. In this paper, Dynamic cluster formation and pattern recognition are given special weightage. For offering high-speed data transactions with data shrinking, Hybrid dynamic clustering algorithm is explained. As there is a shortage of electricity, the priority is given to energy savings by WSN (Wireless Sensor Network). The consumption of energy has decreased by permitting few cluster heads in the network, also known as nodes for communicating with the base station. A simple, effective, and computationally efficient optimization approach known as Particle swarm optimization (PSO) is utilized. With the usage of fitness function every particle poss the fitness value and even their speed it controlled using velocity. These values have been utilized by WSN for rectifying the issues like optimal deployment, clustering, node selection, and data aggregation. Efforts have been made to reduce the energy consumption occurs by the nodes and for extending the life of the network by proposing a PSO-based technique which selects the best nodes as cluster heads and a reselect mechanism for extending the network lifetime.

scholarly journals Using Fitness Value for Monitoring Kiwifruit’s Variant Seedling in Tissue Culture

2016 ◽  
Vol 16 (5) ◽  
pp. 59-68
Author(s):  
Shouguo Tang ◽  
Yong Li ◽  
Zhikun Zhang
Keyword(s):  
Genetic Algorithm ◽  
Genetic Diversity ◽  
Pattern Recognition ◽  
Tissue Culture ◽  
Genetic Stability ◽  
Genomic Dna ◽  
Dna Polymorphism ◽  
Fitness Function ◽  
Fitness Value ◽  
Pattern Recognition Approach

Abstract Based on Genetic Algorithm, a pattern recognition approach using fitness to dynamically monitor the sub cultured seeding of kiwifruit is proposed in order to decrease the loss of variant seedlings in tissue culture. By coding, selection, mutation and cross-overing the selected primer pairs of the sub cultured seeding, we simulate the process of optimizing the kiwifruit’s genomic DNA polymorphism. The corresponding fitness values of the primer pairs are evaluated with fitness function for monitor the variation of kiwi’s DNA. The result shows that kiwi’s plantlets can better maintain their genes’ genetic stability for the first to the ninth generation. But from the tenth generation, the fitness values become variation. The results are based on experimentation, which uses optimized AFLP system for analyzing genetic diversity of 75 samples of seventh to eleventh 5 generations of kiwi.

scholarly journals EODC: An Energy Optimized Dynamic Clustering Protocol for Wireless Sensor Network using PSO approach

2019 ◽  
Vol 14 (2) ◽  
pp. 183-198 ◽  
Author(s):  
Jothi Kumar C ◽  
Revathi Venkataraman
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Fitness Function ◽  
Cluster Head ◽  
Base Station ◽  
Link Quality ◽  
Wireless Sensor ◽  
Manhattan Distance ◽  
Dynamic Clustering ◽  
Cluster Heads

Wireless Sensor Network comprises of a number of small wireless nodes whose role is to sense, gather, process and communicate. One of the primary concerns of the network is to optimize the energy consumption and extend the network lifespan. Sensor nodes can be clustered to increase the network lifespan. This is done by selecting the cluster head for every cluster and by performing data fusion on the cluster head. The proposed system is using an energy efficient hierarchical routing protocol named Energy Optimized Dynamic Clustering (EODC) for clustering large ad-hoc WSN and route the data towards the sink. The sink receives the data collected from the set of cluster heads after every round. The cluster head was selected using Particle Swarm Optimization (PSO) approach and the cluster members are allocated based on Manhattan distance. The metrics used to find the fitness function are location, link quality, energy of active node and energy of inactive node. The system employs shortest path approach to communicate between the cluster heads till it reaches the base station. By this, we have increased the energy efficiency and lifetime of the network. The analysis and outcomes show that the EODC was found to outperform the existing protocol which compares with this algorithm.

Parallel Genetic Algorithm for Design of Morphing Cellular Truss Structures

Aerospace ◽  
2005 ◽  
Author(s):  
Deepak S. Ramrakhyani ◽  
George A. Lesieutre ◽  
Mary Frecker ◽  
Smita Bharti
Keyword(s):  
Genetic Algorithm ◽  
Fitness Function ◽  
Unit Cell ◽  
Truss Structures ◽  
Optimization Approach ◽  
Parallel Genetic Algorithm ◽  
Ground Structure ◽  
Structural Layout ◽  
Fitness Value ◽  
Wing Structure

A parallel genetic algorithm is developed for the design of morphing aircraft structures using tendon actuated compliant truss. The wing structure in this concept is made of solid members and cables. The solid members are connected through compliant joints so that they can be deformed relatively easily without storing much strain energy in the structure. The structure is actuated using cables to deform into a required shape. Once the structure is deformed, the cables are locked and hence carry loads. Previously an octahedral unit cell made of cables and truss members was developed to achieve the required shape change of a morphing wing developed at NASA. It was observed that a continuously deformable truss structure with required morphing capability can be achieved by a cellular geometry tailored to local strain deformation. A wing structure made of these unit cells was sized for a representative aircraft and was found to be suitable. This paper describes the development of new unit cell designs that fit the morphing requirements using topology optimization. A ground structure approach is used to set up the problem. A predetermined set of points is selected and the members are connected in between the neighboring nodes. Each member in this ground structure has four possibilities, 1) a truss member, 2) a cable that morphs the structure into a required shape, 3) a cable that is antagonistic and brings it back to the original shape 4) a void, i.e., the member doesn’t exist in the structure. This choice is represented with a discrete variable. A parallel genetic algorithm is used as an optimization approach to optimize the variables in the ground structure to get the best structural layout. The parallelization is done using a master slave process. A fitness function is used to calculate how well a structural layout fits the design requirements. In general, a unit cell that has lesser deflection under external loads and higher deflection under actuation has a higher fitness value. Other requirements such as having fewer cables and achieving a required morphing shape are also included in the fitness function. The finite element calculations in the fitness function can be done using either linear or nonlinear analysis. The paper discusses the different ways of formulating the fitness function and the results thereof.

scholarly journals Genetic-fuzzy based load balanced protocol for WSNs

2019 ◽  
Vol 9 (2) ◽  
pp. 1168
Author(s):  
Pankaj Kumar Kashyap ◽  
Sushil Kumar
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Cluster Head ◽  
Base Station ◽  
Optimal Number ◽  
Hybrid Technique ◽  
Total Energy Consumption ◽  
Cluster Heads ◽  
Fitness Value ◽  
Selection Of

<p><span>Recent advancement in wireless sensor networks primarily depends upon energy constraint. Clustering is the most effective energy-efficient technique to provide robust, fault-tolerant and also enhance network lifetime and coverage. Selection of optimal number of cluster heads and balancing the load of cluster heads are most challenging issues. Evolutionary based approach and soft computing approach are best suitable for counter the above problems rather than mathematical approach. In this paper we propose hybrid technique where Genetic algorithm is used for the selection of optimal number of cluster heads and their fitness value of chromosome to give optimal number of cluster head and minimizing the energy consumption is provided with the help of fuzzy logic approach. Finally cluster heads uses multi-hop routing based on A*(A-star) algorithm to send aggregated data to base station which additionally balance the load. Comparative study among LEACH, CHEF, LEACH-ERE, GAEEP shows that our proposed algorithm outperform in the area of total energy consumption with various rounds and network lifetime, number of node alive versus rounds and packet delivery or packet drop ratio over the rounds, also able to balances the load at cluster head.</span></p>

Shape optimization of a metallic flywheel using an evolutive system method: Design of an asymmetrical shape for mechanical interface

2016 ◽  
Vol 232 (2) ◽  
pp. 217-230
Author(s):  
L Pedrolli ◽  
A Zanfei ◽  
S Ancellotti ◽  
V Fontanari ◽  
M Benedetti
Keyword(s):  
Energy Storage ◽  
Fitness Function ◽  
Optimization Approach ◽  
System Method ◽  
Accurate Definition ◽  
Fitness Value ◽  
Ansys Apdl ◽  
Mechanical Interface ◽  
Asymmetrical Shape ◽  
Definition Of

In this work, a novel optimization approach is used to define the shape of a flywheel for energy storage. The procedure acts on a two-dimensional axisymmetric finite element method model, in which many parameters are used to describe the geometry. The optimization is performed by an evolutive system method, whereby the population’s genome is described with statistical quantities. An accurate definition of the fitness function allows for a broad spectrum of objectives. The evolution of the fitness value during population generation is discussed. The procedure does not benefit from parallelization: an alternative way of parallelizing the optimization process is presented, where the population is equally divided among the cores and calculated independently, allowing for an approximately linear performance scaling with the number of cores. The method is applied to the minimization of the mass in a flywheel for energy storage application, displaying great flexibility to the variation of the parameters describing the rotational speed, geometry constraints, and material properties. The true potential of the evolutive method is then demonstrated by optimizing an asymmetrical flywheel, where a mechanical interface lies on one side only. Usually additional parts are added manually on the optimized shape, increasing the thickness where necessary; this method permits to directly optimize to the final shape. The script used in this work is available upon request. Matlab and Ansys APDL software are needed.

scholarly journals Modeling the Excess Velocity of Low-Viscous Taylor Droplets in Square Microchannels

Fluids ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 162 ◽  
Author(s):  
Thorben Helmers ◽  
Philip Kemper ◽  
Jorg Thöming ◽  
Ulrich Mießner
Keyword(s):  
High Speed ◽  
Process Intensification ◽  
Continuous Phase ◽  
Channel Cross Section ◽  
Optimization Approach ◽  
Mean Flow ◽  
Bypass Flow ◽  
Wall Film ◽  
Proposed Model ◽  
The Mean

Microscopic multiphase flows have gained broad interest due to their capability to transfer processes into new operational windows and achieving significant process intensification. However, the hydrodynamic behavior of Taylor droplets is not yet entirely understood. In this work, we introduce a model to determine the excess velocity of Taylor droplets in square microchannels. This velocity difference between the droplet and the total superficial velocity of the flow has a direct influence on the droplet residence time and is linked to the pressure drop. Since the droplet does not occupy the entire channel cross-section, it enables the continuous phase to bypass the droplet through the corners. A consideration of the continuity equation generally relates the excess velocity to the mean flow velocity. We base the quantification of the bypass flow on a correlation for the droplet cap deformation from its static shape. The cap deformation reveals the forces of the flowing liquids exerted onto the interface and allows estimating the local driving pressure gradient for the bypass flow. The characterizing parameters are identified as the bypass length, the wall film thickness, the viscosity ratio between both phases and the C a number. The proposed model is adapted with a stochastic, metaheuristic optimization approach based on genetic algorithms. In addition, our model was successfully verified with high-speed camera measurements and published empirical data.

scholarly journals Three-Axis Inductive Displacement Sensor Using Phase-Sensitive Digital Signal Processing for Industrial Magnetic Bearing Applications

Actuators ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 115
Author(s):  
Teemu Sillanpää ◽  
Alexander Smirnov ◽  
Pekko Jaatinen ◽  
Jouni Vuojolainen ◽  
Niko Nevaranta ◽  
...  
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Eddy Current ◽  
High Speed ◽  
Digital Signal ◽  
Magnetic Bearing ◽  
Air Gap ◽  
Sensor Design ◽  
Quadrature Demodulation ◽  
Displacement Sensors

Non-contact rotor position sensors are an essential part of control systems in magnetically suspended high-speed drives. In typical active magnetic bearing (AMB) levitated high-speed machine applications, the displacement of the rotor in the mechanical air gap is measured with commercially available eddy current-based displacement sensors. The aim of this paper is to propose a robust and compact three-dimensional position sensor that can measure the rotor displacement of an AMB system in both the radial and axial directions. The paper presents a sensor design utilizing only a single unified sensor stator and a single shared rotor mounted target piece surface to achieve the measurement of all three measurement axes. The sensor uses an inductive measuring principle to sense the air gap between the sensor stator and rotor piece, which makes it robust to surface variations of the sensing target. Combined with the sensor design, a state of the art fully digital signal processing chain utilizing synchronous in-phase and quadrature demodulation is presented. The feasibility of the proposed sensor design is verified in a closed-loop control application utilizing a 350-kW, 15,000-r/min high-speed industrial induction machine with magnetic bearing suspension. The inductive sensor provides an alternative solution to commercial eddy current displacement sensors. It meets the application requirements and has a robust construction utilizing conventional electrical steel lamination stacks and copper winding.

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