International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
Comparative Study of Speed Characteristics of DC Motor with and without Contr...IJMTST Journal
In this paper a dc motor is modeled using transfer function analysis and the speed characteristics are
plotted for dc motor with and without controllers. The difference between load torque and electromagnetic
torque is improved using discrete p, I, d controllers for improving the speed characterics.the best speed
characteristics is obtained using proportional plus derivative controller. These characteristics are obtained by
formulating a relation between speed and torque. The entire simulation is conducted on mat
lab/simulink2013 environment.
Design of predictive controller for smooth set point tracking for fast dynami...eSAT Journals
Abstract Model Predictive Control is generally used for slow dynamic system. Here efforts are made to implement MPC controller for Fast dynamic System. Speed control of DC motor is taken as fast dynamic system for which the MPC controller would be implemented. To control the speed of the DC motor Generalized Predictive Control (GPC) algorithm is used. In this paper, ARIX model based GPC control is implemented in 2-DOF structure. Transfer function of the DC motor is derived using LABVIEW and system identification tool of MATLAB. From the response of the system, it can be seen that the GPC has improved the performance of the system rather than PID control algorithm from disturbance rejection point of view. Keywords: MPC (Model Predictive Controller), GPC (Generalized Predictive Controller), ARIX Model (Auto Regressive Integrated Exogenous Model).
OPTIMAL PID CONTROLLER DESIGN FOR SPEED CONTROL OF A SEPARATELY EXCITED DC MO...ijscmcjournal
This paper presents a new approach to determine the optimal proportional-integral-derivative controller
parameters for the speed control of a separately excited DC motor using firefly optimization technique.
Firefly algorithm is one of the recent evolutionary methods which are inspired by the Firefly’s behavior in
nature. The firefly optimization technique is successfully implemented using MATLAB software. A
comparison is drawn from the results obtained between the linear quadratic regulator and firefly
optimization techniques. Simulation results are presented to illustrate the performance and validity of the
design method.
Aplanning algorithm offive-axis feedrate interpolation based on drive and jer...IJRES Journal
CNC technology marks the core of modern manufacturing, and CNC interpolation module is one of the most important numerical control technology modules. Avery important feature of the CNC is to implement the feed rate that consists in producing the set points based on a NC program. In the high speed machining, the feed rate is restricted by the velocity, acceleration, and jerk. And the NURBS curve is a free curve, due to the many advantages of NURBS curves, it can be well applied to the CNC feed rate interpolation. The algorithm can get more smooth feed rate curves, which makes better use of kinematical characteristics of the machine. Finally, according to each machine axis capability, one can use the feed rate control method which is verified by simulation analysis and processing to test this method. The results show that the algorithm can effectively control the speed, acceleration and jerk.
Comparative Study of Speed Characteristics of DC Motor with and without Contr...IJMTST Journal
In this paper a dc motor is modeled using transfer function analysis and the speed characteristics are
plotted for dc motor with and without controllers. The difference between load torque and electromagnetic
torque is improved using discrete p, I, d controllers for improving the speed characterics.the best speed
characteristics is obtained using proportional plus derivative controller. These characteristics are obtained by
formulating a relation between speed and torque. The entire simulation is conducted on mat
lab/simulink2013 environment.
Design of predictive controller for smooth set point tracking for fast dynami...eSAT Journals
Abstract Model Predictive Control is generally used for slow dynamic system. Here efforts are made to implement MPC controller for Fast dynamic System. Speed control of DC motor is taken as fast dynamic system for which the MPC controller would be implemented. To control the speed of the DC motor Generalized Predictive Control (GPC) algorithm is used. In this paper, ARIX model based GPC control is implemented in 2-DOF structure. Transfer function of the DC motor is derived using LABVIEW and system identification tool of MATLAB. From the response of the system, it can be seen that the GPC has improved the performance of the system rather than PID control algorithm from disturbance rejection point of view. Keywords: MPC (Model Predictive Controller), GPC (Generalized Predictive Controller), ARIX Model (Auto Regressive Integrated Exogenous Model).
OPTIMAL PID CONTROLLER DESIGN FOR SPEED CONTROL OF A SEPARATELY EXCITED DC MO...ijscmcjournal
This paper presents a new approach to determine the optimal proportional-integral-derivative controller
parameters for the speed control of a separately excited DC motor using firefly optimization technique.
Firefly algorithm is one of the recent evolutionary methods which are inspired by the Firefly’s behavior in
nature. The firefly optimization technique is successfully implemented using MATLAB software. A
comparison is drawn from the results obtained between the linear quadratic regulator and firefly
optimization techniques. Simulation results are presented to illustrate the performance and validity of the
design method.
Aplanning algorithm offive-axis feedrate interpolation based on drive and jer...IJRES Journal
CNC technology marks the core of modern manufacturing, and CNC interpolation module is one of the most important numerical control technology modules. Avery important feature of the CNC is to implement the feed rate that consists in producing the set points based on a NC program. In the high speed machining, the feed rate is restricted by the velocity, acceleration, and jerk. And the NURBS curve is a free curve, due to the many advantages of NURBS curves, it can be well applied to the CNC feed rate interpolation. The algorithm can get more smooth feed rate curves, which makes better use of kinematical characteristics of the machine. Finally, according to each machine axis capability, one can use the feed rate control method which is verified by simulation analysis and processing to test this method. The results show that the algorithm can effectively control the speed, acceleration and jerk.
Analysis and Design of Conventional Controller for Speed Control of DC Motor ...IJERA Editor
The objective of this paper is to control the speed of the motor using conventional controller; compensator is used to improve the steady state error. To evaluate the performance of the controller, time response analysis is carried out. The time response analysis consists of two type of analysis. One is unit step response analysis and other is performance indices analysis. The paper describes the designing of a closed loop model of the dc motor drive for controlling speed. Accuracy and the dynamic responses are better in a closed loop system. The compensator is used to compensate the parameter of the system in such a way to meet the specification, so that it improves the steady state response of the system and get desired response.
Optimal PID Controller Design for Speed Control of a Separately Excited DC Mo...ijscmcj
This paper presents a new approach to determine the optimal proportional-integral-derivative controller parameters for the speed control of a separately excited DC motor using firefly optimization technique. Firefly algorithm is one of the recent evolutionary methods which are inspired by the Firefly’s behavior in nature. The firefly optimization technique is successfully implemented using MATLAB software. A comparison is drawn from the results obtained between the linear quadratic regulator and firefly optimization techniques. Simulation results are presented to illustrate the performance and validity of the design method.
Optimization of Economic Load Dispatch with Unit Commitment on Multi MachineIJAPEJOURNAL
Economic load dispatch (ELD) and Unit Commitment (UC) are significant research applications in power systems that optimize the total production cost of the predicted load demand. The UC problem determines a turn-on and turn-off schedule for a given combination of generating units, thus satisfying a set of dynamic operational constraints. ELD optimizes the operation cost for all scheduled generating units with respect to the load demands of customers. The first phase in this project is to economically schedule the distribution of generating units using Gauss seidal and the second phase is to determine optimal load distribution for the scheduled units using dynamic programming method is applied to select and choose the combination of generating units that commit and de-commit during each hour. These precommitted schedules are optimized by dynamic programming method thus producing a global optimum solution with feasible and effective solution quality, minimal cost and time and higher precision. The effectiveness of the proposed techniques is investigated on two test systems consisting of five generating units and the experiments are carried out using MATLAB R2010b software. Experimental results prove that the proposed method is capable of yielding higher quality solution including mathematical simplicity, fast convergence, diversity maintenance, robustness and scalability for the complex ELD-UC problem.
OPTIMAL TRAJECTORY OF ROBOT MANIPULATOR FOR ENERGY MINIMIZATION WITH QUARTIC ...cscpconf
In this paper, a different way to find the trajectory of the robot manipulators for energyoptimization is presented. In our method, the joint angles of the manipulator are set as quadratic polynomial functions. Then, with them taken into the variational function of energy consumption, Finite Element Modelling is employed to optimize the unknown parameters of the fourth order joint angles
Debabrata Pal, Aksum University, College of Engineering and Technology Department of Electrical and Computer Engineering Ethiopia, NE Africa, Email:debuoisi@gmail.com,website:www.ijrd.in
Analysis & Control of Inverted Pendulum System Using PID ControllerIJERA Editor
This Analysis designs a two-loop proportional–integral–derivative (PID) controller for an inverted cart– pendulum system via pole placement technique, where the (dominant) closed-loop poles to be placed at the desired locations are obtained from an Linear quadratic regulator (LQR) design. It is seen that in addition to yielding better responses (because of additional integral action) than this LQR (equivalent to two-loop PD controller) design, the proposed PID controller is robust enough. The performance and of the PID compensation are verified through simulations as well as experiments.
In this paper, the optimal control problem of a nonlinear robot manipulator in absence of holonomic constraint force based on the point of view of adaptive dynamic programming (ADP) is presented. To begin with, the manipulator was intervened by exact linearization. Then the framework of ADP and Robust Integral of the Sign of the Error (RISE) was developed. The ADP algorithm employs Neural Network technique to tune simultaneously the actor-critic network to approximate the control policy and the cost function, respectively. The convergence of weight as well as position tracking control problem was considered by theoretical analysis. Finally, the numerical example is considered to illustrate the effectiveness of proposed control design.
Locational marginal pricing framework in secured dispatch scheduling under co...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Genetic Algorithm for Solving the Economic Load DispatchSatyendra Singh
In this paper, comparative study of two approaches, Genetic Algorithm
(GA) and Lambda Iteration method (LIM) have been used to provide
the solution of the economic load dispatch (ELD) problem. The ELD
problem is defined as to minimize the total operating cost of a power
system while meeting the total load plus transmission losses within
generation limits. GA and LIM have been used individually for solving
two cases, first is three generator test system and second is ten
generator test system. The results are compared which reveals that GA
can provide more accurate results with fast convergence characteristics
and is superior to LIM.
Security constrained optimal load dispatch using hpso technique for thermal s...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Zarządzanie dokumentami w Enterprise 2.0- doświadczenia z wdrożeńEnterprise Content Management
Obecnie usługi Contium w zakresie Enterprise 2.0 świadczone są pod markę Intratic.
www.intratic.eu
Analysis and Design of Conventional Controller for Speed Control of DC Motor ...IJERA Editor
The objective of this paper is to control the speed of the motor using conventional controller; compensator is used to improve the steady state error. To evaluate the performance of the controller, time response analysis is carried out. The time response analysis consists of two type of analysis. One is unit step response analysis and other is performance indices analysis. The paper describes the designing of a closed loop model of the dc motor drive for controlling speed. Accuracy and the dynamic responses are better in a closed loop system. The compensator is used to compensate the parameter of the system in such a way to meet the specification, so that it improves the steady state response of the system and get desired response.
Optimal PID Controller Design for Speed Control of a Separately Excited DC Mo...ijscmcj
This paper presents a new approach to determine the optimal proportional-integral-derivative controller parameters for the speed control of a separately excited DC motor using firefly optimization technique. Firefly algorithm is one of the recent evolutionary methods which are inspired by the Firefly’s behavior in nature. The firefly optimization technique is successfully implemented using MATLAB software. A comparison is drawn from the results obtained between the linear quadratic regulator and firefly optimization techniques. Simulation results are presented to illustrate the performance and validity of the design method.
Optimization of Economic Load Dispatch with Unit Commitment on Multi MachineIJAPEJOURNAL
Economic load dispatch (ELD) and Unit Commitment (UC) are significant research applications in power systems that optimize the total production cost of the predicted load demand. The UC problem determines a turn-on and turn-off schedule for a given combination of generating units, thus satisfying a set of dynamic operational constraints. ELD optimizes the operation cost for all scheduled generating units with respect to the load demands of customers. The first phase in this project is to economically schedule the distribution of generating units using Gauss seidal and the second phase is to determine optimal load distribution for the scheduled units using dynamic programming method is applied to select and choose the combination of generating units that commit and de-commit during each hour. These precommitted schedules are optimized by dynamic programming method thus producing a global optimum solution with feasible and effective solution quality, minimal cost and time and higher precision. The effectiveness of the proposed techniques is investigated on two test systems consisting of five generating units and the experiments are carried out using MATLAB R2010b software. Experimental results prove that the proposed method is capable of yielding higher quality solution including mathematical simplicity, fast convergence, diversity maintenance, robustness and scalability for the complex ELD-UC problem.
OPTIMAL TRAJECTORY OF ROBOT MANIPULATOR FOR ENERGY MINIMIZATION WITH QUARTIC ...cscpconf
In this paper, a different way to find the trajectory of the robot manipulators for energyoptimization is presented. In our method, the joint angles of the manipulator are set as quadratic polynomial functions. Then, with them taken into the variational function of energy consumption, Finite Element Modelling is employed to optimize the unknown parameters of the fourth order joint angles
Debabrata Pal, Aksum University, College of Engineering and Technology Department of Electrical and Computer Engineering Ethiopia, NE Africa, Email:debuoisi@gmail.com,website:www.ijrd.in
Analysis & Control of Inverted Pendulum System Using PID ControllerIJERA Editor
This Analysis designs a two-loop proportional–integral–derivative (PID) controller for an inverted cart– pendulum system via pole placement technique, where the (dominant) closed-loop poles to be placed at the desired locations are obtained from an Linear quadratic regulator (LQR) design. It is seen that in addition to yielding better responses (because of additional integral action) than this LQR (equivalent to two-loop PD controller) design, the proposed PID controller is robust enough. The performance and of the PID compensation are verified through simulations as well as experiments.
In this paper, the optimal control problem of a nonlinear robot manipulator in absence of holonomic constraint force based on the point of view of adaptive dynamic programming (ADP) is presented. To begin with, the manipulator was intervened by exact linearization. Then the framework of ADP and Robust Integral of the Sign of the Error (RISE) was developed. The ADP algorithm employs Neural Network technique to tune simultaneously the actor-critic network to approximate the control policy and the cost function, respectively. The convergence of weight as well as position tracking control problem was considered by theoretical analysis. Finally, the numerical example is considered to illustrate the effectiveness of proposed control design.
Locational marginal pricing framework in secured dispatch scheduling under co...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Genetic Algorithm for Solving the Economic Load DispatchSatyendra Singh
In this paper, comparative study of two approaches, Genetic Algorithm
(GA) and Lambda Iteration method (LIM) have been used to provide
the solution of the economic load dispatch (ELD) problem. The ELD
problem is defined as to minimize the total operating cost of a power
system while meeting the total load plus transmission losses within
generation limits. GA and LIM have been used individually for solving
two cases, first is three generator test system and second is ten
generator test system. The results are compared which reveals that GA
can provide more accurate results with fast convergence characteristics
and is superior to LIM.
Security constrained optimal load dispatch using hpso technique for thermal s...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Zarządzanie dokumentami w Enterprise 2.0- doświadczenia z wdrożeńEnterprise Content Management
Obecnie usługi Contium w zakresie Enterprise 2.0 świadczone są pod markę Intratic.
www.intratic.eu
Lyon Diet Heart Study is still considered as the ultimate evidence for the health benefits of Mediterranean diet. Unfortunately its' results have never been re-produced since then. However, PREDIMED trial may change this situation.
J D Fuentes - Gut Impact pobierz darmowy ebook pdfTomasz Żmijewski
Jak bezpośrednio wpływać na ludzkie instynkty, emocje i wyobraźnię, sprawiając, że wszelkie Twoje sugestie staną się nieodparcie fascynujące, zniewalające i hipnotyczne?
http://www.responsabilitatesociala.ro/companii.html
Afla detalii despre performantele de CSR ale Cosmote Romania in 2010, din domeniile: management, mediu, societate, angajati si piata.
Permanent magnet direct current motors (PMDCM) are widely used in various applications such as space technologies, personal computers, medical, military, robotics, electrical vehicles, etc. In this paper, the mathematical model of PMDCM is designed and simulated using MATLAB software. The PMDCM speed is controlled using rate feedback controller due to its ability of improving system damping. To improve the controller performance, it’s parameters are tuned using genetic algorithm (GA) and direct search (DS) techniques. The tuning process based on different performance criteria. The most four common performance criteria used in this paper are JIAE (Integral of Absolute Error), JISE (Integral of Square Error), JITAE (Integral of Time-Weighted Absolute Error), and JITSE (Integral of Time-Weighted Square Error). The results obtained from these evolutionary techniques are compared. The results show an obvious improvement in system performance including enhancing the transient and steady state of PMDCM speed responses for all performance criteria.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
RGT is a planned test-analyze-and-fix (TAAF) process in which End Unit is tested under actual, simulated, or accelerated environments to disclose design deficiencies and defects. It is intended to provide a basis for early incorporation of corrective actions and for verification of their effectiveness, thus promoting reliability growth. RGT is intended to correct failures that reduce operational effectiveness and failures that increase maintenance and logistics support costs.
Design evaluation and optimization of steering yoke of an automobileeSAT Journals
Abstract The purpose of a steering system is to control the direction of the vehicle by operating the steering wheel of the steering system. The steering columns in a steering system are one of the main devices of an automobile. It is a very important part to attain stability and steady movement of the vehicle. The steering yoke consists of two forged-steel yokes or forks joined to the two shafts being coupled and situated at right angles to each other. A spider hinges these two yokes together. Since the arms of the spider are at right angles the spider arm rocks backwards and forward between four extreme positions. Motion transmission system of vehicles consist several components which sometimes encounter unfortunate failures. Some common reasons for the failures may be manufacturing, design faults, maintenance faults, raw material faults, material processing faults as well as the user originated faults. In this paper structural optimization of the steering yoke is carried out. For modeling of the component, CATIA V5 R17 software is used. It has been found that there are essentially in two stages of the design process that structural optimization can be applied. In the early stage of concept generation, topology optimization should be used to develop an efficient structure from the beginning. At this level an automatized variation of optimization parameters was proven useful to and the best feasible design possible. In the later stage, shape and size optimization should be used to fine-tune the structure realized from the topology optimization and carried out physical experimentation to validate the model. Keywords: Steering Yoke, Structural optimization, CATIA V5, Hyperworks
Optimization of vehicle suspension system using genetic algorithmIAEME Publication
Modeling the suspension of an automobile is of interest for many automotive and vibration engineers. Of importance for these engineers is the ride quality of the vehicle traversing over broken roads and control of body motion. When traveling over rough terrain, the vehicle exhibits bounce (up and down), pitch (rotation about the center of gravity along the vehicle's length) and roll (rotation about the center of gravity along the vehicle's width) motions.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
20 Comprehensive Checklist of Designing and Developing a WebsitePixlogix Infotech
Dive into the world of Website Designing and Developing with Pixlogix! Looking to create a stunning online presence? Look no further! Our comprehensive checklist covers everything you need to know to craft a website that stands out. From user-friendly design to seamless functionality, we've got you covered. Don't miss out on this invaluable resource! Check out our checklist now at Pixlogix and start your journey towards a captivating online presence today.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
International Journal of Computational Engineering Research (IJCER)
1. International Journal of Computational Engineering Research||Vol, 03||Issue, 7||
||Issn 2250-3005 || ||July||2013|| Page 1
Analysis&Optimization of Design Parameters of Mechanisms
Using Ga
B.Venu1
, Dr.M.nagaphani sastry2
1
Student, M.Tech (CAD/CAM), G.pullareddyengineering college(Autonomous), A.P, India, 2
Associate professor,
mechanical engineering, G.pullareddyengineering college(Autonomous), A.P, India,
I. INTRODUCTION
Here mechanism is a slider-crank mechanism. The slider-crank mechanism is one of the most useful
mechanisms in modern technology since it appears in most of the internal combustion engines including
automobiles, trucks and small engines. The slider-crank kinematic chain consists of four bodies linked with
three cylindrical joints and one sliding or prismatic joint. It is used to change circular into reciprocating motion,
or reciprocating into circular motion.
Figure 1: Slider Crank
The arm may be a bent portion of the shaft, or a separate arm attached to it. Attached to the end of
Velocity analysis of slider crank mechanism the crank by a pivot is a rod, usually called a connecting rod. The
end of the rod attached to the crank moves in a circular motion, while the other end is usually constrained to
move in a linear sliding motion, in and out.
A mechanism is used to produce mechanical transformations in a machine. This transformation could be any of
the following.
● It may convert one speed to another speed.
● It may convert one force to another force.
ABSTRACT
The main objective of this study is to investigate of dynamic reaction forces of a crank
mechanism. Therefore, this study consists of three major sections: (1) dynamic reactions investigation,
(2) analysis of the mechanisms (3) optimization for static analysis. Analysis on slider crank mechanism is
performed to calculate the reaction forces. This data is implemented for regression analysis for
regression equation. These parameters are aimed to be optimized using GA. Because genetic algorithm is
give good optimal values comparing to traditional optimization. This traditional optimization was done
by using MATLAB.
KEYWORDS: dynamic reactions, regression analysis, genetic algorithm (GA), MATLAB.
2. Analysis&Optimization Of Design…
||Issn 2250-3005 || ||July||2013|| Page 2
● It may convert one torque to another torque.
● It may convert force into torque.
● It may convert one angular motion to another angular motion.
● It may convert angular motion into linear motion.
● It may convert linear motion into angular motion.
1.1 STUDY OBJECTIVES :-
● Determine all loads acting on the links in a mechanism to allow stress and deflection analysis.
● Determine input torque(s) required to produce desired motion in a mechanism(input torque = torque
supplied by input device)
● This present study in the design of machine elements includes the minimization of weight of the individual
components in order to reduce the over all weight of the machine elements.
● It saves both cost and energy involved.
● The most important problem that confronts practical engineers is the mechanical design, a field of
creativity.
● Mechanical design can be defined as the selection of materials and geometry, which satisfies the specified
and implied functional requirements while remaining within the confines of inherently unavoidable
limitations.
1.2MAT LAB :-
Here we can calculate the dynamic reactions of a slider crank mechanism by using MATLAB.
MATLAB is an abbreviation for MATrix LABoratory. It is a matrix-based system for scientific calculations. we
can solve numerical problems without necessarily having to write a long pro-gram. This course provides an
introduction to MATLAB. It will provide the basics of MATLAB programming and applications (primarily) for
macroeconomics and international finance. MATLAB is a high-level language and interactive environment for
numerical computation, visualization, and programming. Using MATLAB, we can analyze data, develop
algorithms, and create models and applications. The language, tools, and built-in math functions are enable to
explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming
languages, such as C/C++ or Java. we can use MATLAB for a range of applications, including signal processing
and communications, image and video processing, control systems, test and measurement, computational
finance, and computational biology. More than a million engineers and scientists in industry and academia use
MATLAB, the language of technical computing.
1..2.1Genetic algorithm :
The Genetic Algorithm and Direct Search Toolbox is a collection of functions that extend the
capabilities of the Optimization Toolbox and the MATLAB® numeric computing environment. The Genetic
Algorithm and Direct Search Toolbox includes routines for solving optimization problems using
•Genetic algorithm
•Direct search
These algorithms are enabling to solve a variety of optimization problems that lie outside the scope of the
standard Optimization Toolbox. All the toolbox functions are MATLAB M-files, made up of MATLAB
statements that implement specialized optimization algorithms. we can view the MATLAB code for these
functions using the statement
type function _ name
we can extend the capabilities of the Genetic Algorithm and Direct Search Toolbox by writing our own M-files,
or by using the toolbox in combination with other toolboxes, or with MATLAB or Simulink®.
Dynamic reaction forces on MATLAB :
%1lb=453.592grams
g=386.4;
wbd=5.5*453.592; %weight of the connecting rod
wp=6.3*453.592; %weight of the piston
mp=wp/g; %mass of the piston
mbd=wbd/g;
l=10; %length of the connecting rod
b=3.5; %crank radius
i_bar=(1/12)*mbd*l^2; %mass moment of inertia
6. Analysis&Optimization Of Design…
||Issn 2250-3005 || ||July||2013|| Page 6
14 14 130 -141470 -362729 -46554 197065
15 15 140 -118990 -377260 -39346 196549
16 16 150 -91942 -384522 -29989 192980
17 17 160 -62319 -387635 -19942 188794
18 18 170 -31414 -388714 -9899 185653
19 19 180 0 -388947 0 184505
2.1 ANOVA table:
Response 1:
Source Sum of
Squares
df Mean
square
F
value
p-value
prob>F
Model 9.037E+010 6 1.506E+010 7759.79 <0.0001 significant
A-A 1.888E+010 1 1.888E+010 9725.85 <0.0001
A^2 4.921E+009 1 4.921E+009 2535.55 <0.0001
A^3 3.638E+009 1 3.638E+009 1874.39 <0.0001
A^4 1.022E+009 1 1.022E+009 526.47 <0.0001
A^5 7.862E+008 1 7.862E+008 405.04 <0.0001
A^6
RESIDUAL
4.082E+008
2.329E+007
1
12
4.082E+008
1.941E+006
210.32 <0.0001
COR TOTAL 9.039E+010 18
Obser vations:
I. The model F-value of 7759.79 implies the model is significant. There is only a 0.01% chance that a “model
F-value” this large could due to noise.
II. Values of “ prob>F ” less than 0.0500 indicate model terms are significant.
III.In this case A,A^2,A^3,A^4,A^5,A^6 are significant model terms.
IV.Values greater than 0.1000 indicate the model terms are not significant.
V. If there are many insignificant model terms(not counting those required to support hierarchy), model
reduction may improve the model.
R-Squared Results:
Std.Dev 1393.17 R-squared 0.9997
Mean -59774.89 Adj R-squared 0.9996
C.V.% 2.33 Pred R-squared 0.9968
7. Analysis&Optimization Of Design…
||Issn 2250-3005 || ||July||2013|| Page 7
PRESS 2.903E+008 Adeq precision 232.752
The “ pred R-squared”of 0.9968 is in reasonable agreement with the “ adj R-squared” of 0.9996.
“adeq precision” measures the signal to noise ratio. A ratio greater than 4 is desirable. The ratio of 232.752
indicates an adequate signal. This model can be used to navigate the design space.
Model equation of response1:-
R1= +121.51151+748.60025*A+103.03328*A^2-4.26162*A^3+0.048831*A^4-2.25466E-
004*A^5+3.74055E-007*A^6.
Proceed to diagnostics plots(the next icon in progression). Be sure to look at the:
1. Normal probability plot to the studentized residuals to check for normality of residuals.
2. Studentized residuals versus predicted values to check for constant error.
3. Externally studentized residuals to look for outliers, i.e., influential values.
4. Box-Cox plot for power transmissions
If all the model statistics and diagnostic plots are OK, finish up with the model graphs icon.
R1 vs A:A
-200000
-100000
0
100000
0 30 60 90 120150180
Response 2:
Source Sum of
Squares
df Mean
square
F
value
p-value
prob>F
Model 3.042E+012 6 5.069E+011 5.474E+005 <0.0001 significant
A-A 2.433E+011 1 2.433E+011 2.628E+011 <0.0001
A^2 1.870E+010 1 1.870E+010 20199.67 <0.0001
A^3 3.088E+009 1 3.088E+009 3334.99 <0.0001
A^4 2.414E+009 1 2.414E+009 2606.43 <0.0001
A^5 5.986E+007 1 5.986E+007 64.64 <0.0001
A^6 5.380E+008 1 5.380E+008 581.06 <0.0001
RESIDUAL 1.111E+007 12 9.260E+005
COR TOTAL 3.042E+012 18
8. Analysis&Optimization Of Design…
||Issn 2250-3005 || ||July||2013|| Page 8
Obser vations:
1. The model F-value of 547448.75 implies the model is significant. There is only a 0.01% chance that a
model F-value” this large could due to noise.
2. values of “ prob>F ” less than 0.0500 indicate model terms are significant.
3 In this case A,A^2,A^3,A^4,A^5,A^6 are significant model terms.
4. Values greater than 0.1000 indicate the model terms are not significant.
5 If there are many insignificant model terms(not counting those required to support hierarchy), model
reduction may improve the model.
R-Squared Results:
Std.Dev 962.28 R-squared 1.0000
Mean 7511.42 Adj R-squared 1.0000
C.V.% 12.81 Pred R-squared 1.000
PRESS 1.037E+008 Adeq precision 1822.836
The “ pred R-squared”of 1.0000 is in reasonable agreement with the “ adj R-squared” of 1.0000
“adeq precision” measures the signal to noise ratio. A ratio greater than 4 is desirable. The ratio of1822.836
indicates an adequate signal. This model can be used to navigate the design space.
Model equation of respone2:-
R2= +6.74815E+005-613.87632*A-95.42986*A^2-2.34427*A^3+0.044055*A^4-2.38374E-
004*A^5+4.29437E-007*A^6.
Proceed to diagnostics plots(the next icon in progression). Be sure to look at the:
1. Normal probability plot to the studentized residuals to check for normality of residuals.
2. Studentized residuals versus predicted values to check for constant error.
3. Externally studentized residuals to look for outliers, i.e., influential values.
4. Box-Cox plot for power transmissions
If all the model statistics and diagnostic plots are OK, finish up with the model graphs icon.
R2 vs A:A
Response 3:
Source Sum of
Squares
df Mean
Square
F
value
p-value
prob>F
Model 5.287E+010 6 8.812E+009 4544.83 <0.0001 significant
A-A 1.888E+010 1 1.888E+010 9736.05 <0.0001
0 30 60 90 120150180
9. Analysis&Optimization Of Design…
||Issn 2250-3005 || ||July||2013|| Page 9
A^2 1.910E+009 1 1.910E+009 985.14 <0.0001
A^3 3.638E+009 1 3.638E+009 1876.36 <0.0001
A^4 8.906E+008 1 8.906E+008 459.35 <0.0001
A^5 7.862E+008 1 7.862E+008 405.47 <0.0001
A^6 3.986E+008 1 3.986E+008 205.57 <0.0001
RESIDUAL 2.327E+007 12 1.939E+006
COR TOTAL 5.289E+010 18
Obser vations:
1. The model F-value of 4544.83 implies the model is significant. There is only a 0.01% chance that a “model
F-value” this large could due to noise.
2. Values of “ prob>F ” less than 0.0500 indicate model terms are significant.
3. In this case A,A^2,A^3,A^4,A^5,A^6 are significant model terms.
4. Values greater than 0.1000 indicate the model terms are not significant.
5. If there are many insignificant model terms(not counting those required to support hierarchy), model
reduction may improve the model.
R-Squared Results:
Std.Dev 1392.44 R-squared 0.9996
Mean 14763.58 Adj R-squared 0.9993
C.V.% 9.43 Pred R-squared 0.9945
PRESS 2.901E+008 Adeq precision 184.886
The “ pred R-squared”of 0.9945 is in reasonable agreement with the “ adj R-squared” of 0.9993.
“adeq precision” measures the signal to noise ratio. A ratio greater than 4 is desirable. The ratio of 184.886
indicates an adequate signal. This model can be used to navigate the design space.
Model equation of respone3:-
R3= 1021.12280+2911.61629*A+102.96956*A^2-4.36850*A^3+0.048767*A^4-2.23065E-
004*A^5+3.69608E-007*A^6.
Proceed to diagnostics plots(the next icon in progression). Be sure to look at the:
1.Normal probability plot to the studentized residuals to check for normality of residuals.
2. studentized residuals versus predicted values to check for constant error.
3.Externally studentized residuals to look for outliers, i.e., influential values.
4.Box-Cox plot for power transmissions
If all the model statistics and diagnostic plots are OK, finish up with the model graphs icon.
R3 vs A:A
10. Analysis&Optimization Of Design…
||Issn 2250-3005 || ||July||2013|| Page 10
Response 4:
Source Sum of
Squares
df Mean
Square
F
value
p-value
prob>F
Model 9.099E+011 6 1.516E+011 3.382E+005 <0.0001 significant
A-A 6.936E+010 1 6.936E+010 1.547E+005 <0.0001
A^2 9.064E+009 1 9.064E+009 20212.43 <0.0001
A^3 8.803E+008 1 8.803E+008 1962.89 <0.0001
A^4 1.170E+009 1 1.170E+009 2608.12 <0.0001
A^5 1.706E+007 1 1.706E+007 38.04 <0.0001
A^6 2.608E+008 1 2.608E+008 581.45 <0.0001
RESIDUAL 5.381E+006 12 4.485E+005
Obser vations:
1. The model F-value of338154.65 implies the model is significant. There is only a 0.01% chance that a “model
F-value” this large could due to noise.
2.Values of “ prob>F ” less than 0.0500 indicate model terms are significant.
3.In this case A,A^2,A^3,A^4,A^5,A^6 are significant model terms.
4.Values greater than 0.1000 indicate the model terms are not significant.
5.If there are many insignificant model terms(not counting those required to support hierarchy), model reduction
may improve the model.
R-Squared Results:
Std.Dev 669.67 R-squared 1.0000
Mean -5228.79 Adj R-squared 1.0000
C.V.% 12.81 Pred R-squared 0.9999
PRESS 5.020E+007 Adeq precision 1429.511
-100000
-50000
0
50000
100000
150000
0 30 60 90 120 150 180
11. Analysis&Optimization Of Design…
||Issn 2250-3005 || ||July||2013|| Page 11
The “ pred R-squared”of 0.9999 is in reasonable agreement with the “ adj R-squared” of 1.0000.
“adeq precision” measures the signal to noise ratio. A ratio greater than 4 is desirable. The ratio of 1429.511
indicates an adequate signal. This model can be used to navigate the design space.
Model equation of respone1:-
R4=-3.83503E+005+424.21111*A+53.57290*A^2+1.62285*A^3-0.030196*A^4+1.64893E-
004*A^5-2.98952E-007*A^6
Proceed to diagnostics plots(the next icon in progression). Be sure to look at the:
1.Normal probability plot to the studentized residuals to check for normality of residuals.
2.Studentized residuals versus predicted values to check for constant error.
3.Externally studentized residuals to look for outliers, i.e., influential values.
4.Box-Cox plot for power transmissions
If all the model statistics and diagnostic plots are OK, finish up with the model graphs icon.
R4 vs A:A
optimization of ga:
The above equations we can substitute MATLAB GA TOOL BOX .from these equations we can get function
values.
function y = multi(x)
y(1)=1021.51151+748.60025*x+103.03328*x^2-4.26162*x^3+0.048831*x^4-2.25466e-004*x^5+3.74055e-
007*x^6;
y(2)=6.74815e+005-613.87632*x-95.42986*x^2-2.34427*x^3+0.044055*x^4-2.38374e-004*x^5+4.29437e-
007*x^6;
y(3)=1021.12280+2911.61629*x+102.96956*x^2-4.36850*x^3+0.048767*x^4-2.23065e-004*x^5+3.69608e-
007*x^6;
y(4)=45120.14114-29.45313*x-6.47866*x^2-0.11183*x^3+2.14752e-003*x^4-1.1357e-005*x^5+2.02182e-
008*x^6;
ind
ex
F1 F2 F3 F4 X1
1.0
1030.010049855
302
674808.029509
5751
1054.138900225
9089
45119.8064592
0059
0.01133489916838526
2.0
3902.141474081
4184
672233.329683
2528
10073.31612038
6307
44980.8095858
9086
2.854612491185239
3.0
6666.648025134
849
669291.118940
7776
17217.29226297
474
44809.8760186
4121
4.884400935267964
-600000
-400000
-200000
0
200000
400000
0 30 60 90 120 150 180
12. Analysis&Optimization Of Design…
||Issn 2250-3005 || ||July||2013|| Page 12
4.0
13753.51897853
0545
659385.803384
3625
33698.28682758
919
44217.6049770
8893
9.262936403717731
5.0
7712.876010706
652
668051.906960
2515
19762.04229237
1087
44736.6350171
2435
5.580245386297689
6.0
15657.66439670
671
656040.114357
3725
37970.61293282
041
44015.9662240
23956
10.374399955568672
7.0
5387.727552646
778
670711.013621
3038
14006.13027983
8622
44893.0639376
19634
3.9882269438848876
8.0
17554.69403625
1265
652354.528369
2771
42220.02484493
131
43793.5813420
0431
11.48237864815935
9.0
2487.866063309
993
673559.506461
6316
5993.013496893
71
45054.9145250
8123
1.6209584805875714
10.
0
1030.010049855
302
674808.029509
5751
1054.138900225
9089
45119.8064592
0059
0.01133489916838526
11.
0
9375.899399967
24
665932.289871
1474
23699.13940182
108
44610.4958430
53366
6.6378561512343115
12.
0
1359.174821763
1664
674535.665531
3867
2281.220821239
2356
45106.3934545
1995
0.4264668284769069
13.
0
11868.02584851
2572
662388.188453
5601
29435.52447059
132
44398.1892400
7252
8.150745196936356
14.
0
19231.63099161
8444
648763.459435
4536
45989.58815874
372
43576.7721308
8078
12.471674419307638
15.
0
19231.63099161
8444
648763.459435
4536
45989.58815874
372
43576.7721308
8078
12.471674419307638
CONCLUSION
● In this study dynamic reactions investigation was successfully done by using MATLAB software.
● The obtained data have been statistically processed using Response Surface Method.
● The empirical models of output parameters are established and tested through the analysis of variance
to validate the adequacy of the models.
● A response surface optimization is attempted using DESIGN EXPERT software for output responses in
slider crank mechanism.
● The optimization of slider crank mechanism is done by using GA.
REFERENCES
a. MAT LAB R2009 SOFTWARE HELP .
b. SWILLSON.
c. GA TOOL BOX .
d. DESIGN EXPERT 8.0 HELP.
e. MAT LAB FOR MECHANICAL ENGINEERING TEXTBOOK.
f. WWW.MATLABTUTORIALS.COM.