The document provides an introduction and overview of a course on finite element procedures for linear analysis of solids and structures. The course covers modern and effective finite element formulations, implementation in computer programs, and recommendations for use in engineering practice. It is intended for practicing engineers and scientists who want to solve problems using efficient finite element methods. The course focuses on physical explanations rather than mathematical derivations and discusses techniques used in the SAP and ADINA computer programs.
This project aims to implement a recurrent neural network module for the ACL Neural Toolkit to expand its capabilities. A team will design the neuron and network models, develop a training algorithm, and integrate it into the Toolkit over 5 months. Milestones include preliminary models and algorithms, and incorporating it into the Toolkit to offer a necessary addition that can solve more complex problems than other methods.
Framework for Inter-Model Analysis of Cyber-Physical SystemsIvan Ruchkin
The document presents a framework for analyzing inconsistencies between models of cyber-physical systems. The framework uses views to represent each model's information relevant to other models in a common format. It assigns analysis contracts that specify inputs, outputs, assumptions and guarantees to verify correct composition of analyses from different models. The framework executes analyses in an order determined by their contracts and uses verification models to check that assumptions and guarantees are satisfied to identify inconsistencies.
This talk presents the results from one of our papers on the use of an evolutionary algorithm for an "inverse problem" on self-organised nano particles.
Surrogate modeling for industrial designShinwoo Jang
We describe GTApprox | a new tool for medium-scale surrogate modeling in industrial design. Compared to existing software, GTApprox brings several innovations: a few novel approximation algorithms, several advanced methods of automated model selection, novel options in the form of hints. We demonstrate the efficiency of GTApprox on a large collection of test problems. In addition, we describe several applications of GTApprox to real engineering problems.
Performance prediction for software architecturesMr. Chanuwan
The document proposes an approach called APPEAR for predicting software performance in component-based systems. APPEAR uses both structural and statistical modeling techniques. It consists of two main parts: (1) calibrating a statistical regression model by measuring performance of existing applications, and (2) using the calibrated model to predict performance of new applications. Both parts are based on a model that describes relevant execution properties in terms of a "signature". The method supports flexible choice of parts modeled structurally versus statistically. It is being validated on two industrial case studies.
This thesis examines methods for structural damage localization and quantification using modern optimization techniques. Finite element analysis software is developed to perform dynamic analysis of structures and extract modal properties. Two optimization algorithms - Particle Swarm Optimization and Sequential Quadratic Programming - are used to minimize objective functions based on modal flexibility, natural frequencies, and mode shapes. The efficiency of the objective functions and algorithms is demonstrated on a simply supported beam with 10 elements and a fixed frame with 20 elements, with different damage cases. Test results are presented to evaluate the proposed damage identification method and draw conclusions.
This document provides a summary of parallel evolutionary algorithms (PEAs). It discusses how PEAs can be implemented by either structuring populations into subpopulations (distributed EAs/island models) or neighborhoods (cellular EAs), or by parallelizing panmictic EAs without population structure. The document reviews the history of PEAs and discusses theoretical issues. It also outlines different types of structured PEAs and how they can be parallelized on different hardware. The summary provides an overview of PEAs and discusses open problems in the field.
This project aims to implement a recurrent neural network module for the ACL Neural Toolkit to expand its capabilities. A team will design the neuron and network models, develop a training algorithm, and integrate it into the Toolkit over 5 months. Milestones include preliminary models and algorithms, and incorporating it into the Toolkit to offer a necessary addition that can solve more complex problems than other methods.
Framework for Inter-Model Analysis of Cyber-Physical SystemsIvan Ruchkin
The document presents a framework for analyzing inconsistencies between models of cyber-physical systems. The framework uses views to represent each model's information relevant to other models in a common format. It assigns analysis contracts that specify inputs, outputs, assumptions and guarantees to verify correct composition of analyses from different models. The framework executes analyses in an order determined by their contracts and uses verification models to check that assumptions and guarantees are satisfied to identify inconsistencies.
This talk presents the results from one of our papers on the use of an evolutionary algorithm for an "inverse problem" on self-organised nano particles.
Surrogate modeling for industrial designShinwoo Jang
We describe GTApprox | a new tool for medium-scale surrogate modeling in industrial design. Compared to existing software, GTApprox brings several innovations: a few novel approximation algorithms, several advanced methods of automated model selection, novel options in the form of hints. We demonstrate the efficiency of GTApprox on a large collection of test problems. In addition, we describe several applications of GTApprox to real engineering problems.
Performance prediction for software architecturesMr. Chanuwan
The document proposes an approach called APPEAR for predicting software performance in component-based systems. APPEAR uses both structural and statistical modeling techniques. It consists of two main parts: (1) calibrating a statistical regression model by measuring performance of existing applications, and (2) using the calibrated model to predict performance of new applications. Both parts are based on a model that describes relevant execution properties in terms of a "signature". The method supports flexible choice of parts modeled structurally versus statistically. It is being validated on two industrial case studies.
This thesis examines methods for structural damage localization and quantification using modern optimization techniques. Finite element analysis software is developed to perform dynamic analysis of structures and extract modal properties. Two optimization algorithms - Particle Swarm Optimization and Sequential Quadratic Programming - are used to minimize objective functions based on modal flexibility, natural frequencies, and mode shapes. The efficiency of the objective functions and algorithms is demonstrated on a simply supported beam with 10 elements and a fixed frame with 20 elements, with different damage cases. Test results are presented to evaluate the proposed damage identification method and draw conclusions.
This document provides a summary of parallel evolutionary algorithms (PEAs). It discusses how PEAs can be implemented by either structuring populations into subpopulations (distributed EAs/island models) or neighborhoods (cellular EAs), or by parallelizing panmictic EAs without population structure. The document reviews the history of PEAs and discusses theoretical issues. It also outlines different types of structured PEAs and how they can be parallelized on different hardware. The summary provides an overview of PEAs and discusses open problems in the field.
Russell John Childs has over 20 years of experience in technical software engineering, modeling complex systems, and safety-critical C++ development. He has a PhD in Particle Physics from Birmingham University and skills in C++, algorithms, parallel programming, hardware modeling, testing, and more. His resume details roles at Microsoft, Sun Microsystems, Advantest, and more where he developed load balancing algorithms, hardware behavior models, testing frameworks, and more. He is currently seeking a role utilizing his experience in analysis, architecture, design, C++, and physics/mathematics background.
The Engineering process is the conversion of material into useful product. The need for both simulation and experiments for reliable and rapid development of new products is outlined. This report provides a brief overview of the simulation based engineered product development and testing for the first time right product development. The interplay between simulation and testing are highlighted.
On average case analysis through statistical bounds linking theory to practicecsandit
This summary provides the key points from the document in 3 sentences:
The document discusses the limitations of theoretical analysis of algorithms and argues that empirical analysis through statistical bounds can provide a more robust approach for average case analysis. It explains that statistical bounds allow for mixing of different operations rather than analyzing each separately, and do not require pre-assuming a specific input distribution like uniform. The use of statistical bounds for empirical analysis is proposed as a way to supplement theoretical analysis and provide more insight into how algorithms may perform in practice.
ON AVERAGE CASE ANALYSIS THROUGH STATISTICAL BOUNDS : LINKING THEORY TO PRACTICEcscpconf
Theoretical analysis of algorithms involves counting of operations and a separate bound is provided for a specific operation type . Such a methodology is plagued with its inherent
limitations. In this paper we argue as to why we should prefer weight based statistical bounds,which permit mixing of operations, instead as a robust approach. Empirical analysis is an important idea and should be used to supplement and compliment its existing theoretical counterpart as empirically we can work on weights (e.g. time of an operation can be taken as its weight). Not surprisingly, it should not only be taken as an opportunity so as to amend the mistakes already committed knowingly or unknowingly but also to tell a new story.
This document provides course information for several undergraduate electrical engineering and computer science courses offered at MIT in the 2014-2015 school year. It lists the course numbers, titles, prerequisites, instructors, credit units, and brief descriptions. The courses cover topics such as introductory programming, computational thinking, circuits, signals and systems, software construction, algorithms, electromagnetics, microelectronic devices, and cellular biophysics.
COVERAGE DRIVEN FUNCTIONAL TESTING ARCHITECTURE FOR PROTOTYPING SYSTEM USING ...VLSICS Design
Time and efforts for functional testing of digital logic is big chunk of overall project cycle in VLSI industry. Progress of functional testing is measured by functional coverage where test-plan defines what needs to be covered, and test-results indicates quality of stimulus. Claiming closer of functional testing requires that functional coverage hits 100% of original test-plan. Depending on the complexity of the design, availability of resources and budget, various methods are used for functional testing. Software simulations using various logic simulators, available from Electronic Design Automation (EDA) companies, is primary method for functional testing. The next level in functional testing is pre-silicon verification using Field Programmable Gate Array (FPGA) prototype and/or emulation platforms for stress testing the Design Under Test (DUT). With all the efforts, the purpose is to gain confidence on maturity of DUT to ensuresfirst time silicon success that meets time to market needs of the industry. For any test-environment the bottleneck, in achieving verification closer, is controllability and observability that is quality of stimulus to unearth issues at early stage and coverage calculation. Software simulation, FPGA prototype, or emulation, each method has its own limitations, be it test-time, ease of use, or cost of software, tools and
hardware-platform. Compared to software simulation, FPGA prototyping and emulation methods pose greater challenges in quality stimulus generation and coverage calculation. Many researchers have identified the problems of bug-detection / localization, but very few have touched the concept of quality stimulus generation that leads to better functional coverage and thereby uncover hidden bugs in FPGA prototype verification setup. This paper presents a novel approach to address above-mentioned issues by embedding synthesizable active-agent and coverage collector into FPGA prototype. The proposed architecture has been experimented for functional and stress testing of Universal Serial Bus (USB) Link Training and Status State Machine (LTSSM) logic module as DUT in FPGA prototype. The proposed solution is fully synthesizable and hence can be used in both software simulation as well as in prototype system. The biggest advantage is plug and play nature of this active-agent component, that allows its reusability in any USB3.0 LTSSM digital core.
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.
A brief introduction to network simulation and the difference between simulator and emulator along with the most important types of simulations techniques.
1. The document provides details of 19 new books added to the ENLIB collection in December 2013, including title, author(s), publication year, and call number. The books cover a wide range of topics including control systems, hybrid electric vehicles, linear algebra, 3D computer vision, nonlinear analysis, thermal stresses, intelligent automation, structural dynamics, maintenance and reliability, stochastic processes, reliability engineering, protection relays, mathematical modeling, optimal and robust control, solving nonlinear PDEs, image processing, and experimental design.
The final cost of public school building projects, like other construction projects, is unknown
to the owner till the account closure. Artificial Neural Networks (ANN) is used in an attempt to
predict the final cost of two story (12 classes) school projects under lowest bid system of award
before work starts. A database of (65) school projects records completed in (2007-2012) are used to
develop and verify the ANN model. Based on expert opinions, nine out of eleven parameters are
considered to have the most significant impact on the magnitude of final cost. Hence they are used as
model inputs while the output of the model is going to be the final cost (FC). These parameters are;
accepted bid price, average bid price, estimated cost, contractor rank, supervising engineer
experience, project location, number of bidders, year of contracting, and contractual duration. It was
found that ANN has the ability to predict the final cost for school projects with very good degree of
accuracy having a coefficient of correlation (R) of (91%), and an average accuracy percentage of
(99.98%).
Analysis of intelligent system design by neuro adaptive control no restrictioniaemedu
This document discusses using neuro-adaptive control to analyze the design of intelligent systems. It begins by introducing the topic and noting that conventional adaptive control techniques assume explicit system models or dynamic structures based on linear models, which may not be valid for complex nonlinear systems. Neural networks and other intelligent control approaches that do not require explicit mathematical modeling are presented as alternatives. The paper then focuses on using time-delay neural networks for system identification and control of nonlinear dynamic systems. Various neural network architectures and learning algorithms for system modeling and control are described.
Analysis of intelligent system design by neuro adaptive controliaemedu
This document summarizes the analysis of intelligent system design using neuro-adaptive control methods. It discusses using neural networks for system identification through series-parallel and parallel models. It also discusses supervised control using a neural network trained by an expert operator, inverse control using a neural network trained on the inverse system model, and neuro-adaptive control using two neural networks - one for system identification and one for control. Neuro-adaptive control allows handling nonlinear system behavior without linear approximations.
Control chart pattern recognition using k mica clustering and neural networksISA Interchange
Automatic recognition of abnormal patterns in control charts has seen increasing demands nowadays in manufacturing processes. This paper presents a novel hybrid intelligent method (HIM) for recognition of the common types of control chart pattern (CCP). The proposed method includes two main modules: a clustering module and a classifier module. In the clustering module, the input data is first clustered by a new technique. This technique is a suitable combination of the modified imperialist competitive algorithm (MICA) and the K-means algorithm. Then the Euclidean distance of each pattern is computed from the determined clusters. The classifier module determines the membership of the patterns using the computed distance. In this module, several neural networks, such as the multilayer perceptron, probabilistic neural networks, and the radial basis function neural networks, are investigated. Using the experimental study, we choose the best classifier in order to recognize the CCPs. Simulation results show that a high recognition accuracy, about 99.65%, is achieved.
This presentation discusses about the following topics:
Hybrid Systems
Hybridization
Combinations
Comparison of Expert Systems, Fuzzy Systems, Neural Networks and Genetic Algorithms
Current Progress
Primary Components
MultiComponents
Degree of Integration
Transformational, hierarchial and integrated
Stand Alone Models
Integrated – Fused Architectures
Generalized Fused Framework
System Types for Hybridization
Review on Algorithmic and Non Algorithmic Software Cost Estimation Techniquesijtsrd
Effective software cost estimation is the most challenging and important activities in software development. Developers want a simple and accurate method of efforts estimation. Estimation of the cost before starting of work is a prediction and prediction always not accurate. Software effort estimation is a very critical task in the software engineering and to control quality and efficiency a suitable estimation technique is crucial. This paper gives a review of various available software effort estimation methods, mainly focus on the algorithmic model and non algorithmic model. These existing methods for software cost estimation are illustrated and their aspect will be discussed. No single technique is best for all situations, and thus a careful comparison of the results of several approaches is most likely to produce realistic estimation. This paper provides a detailed overview of existing software cost estimation models and techniques. This paper presents the strength and weakness of various cost estimation methods. This paper focuses on some of the relevant reasons that cause inaccurate estimation. Pa Pa Win | War War Myint | Hlaing Phyu Phyu Mon | Seint Wint Thu "Review on Algorithmic and Non-Algorithmic Software Cost Estimation Techniques" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26511.pdfPaper URL: https://www.ijtsrd.com/engineering/-/26511/review-on-algorithmic-and-non-algorithmic-software-cost-estimation-techniques/pa-pa-win
This document discusses and references several books and publications related to automata theory, formal languages, and computation. It mentions the book "Introduction to Automata Theory, Languages and Computation" by Hopcroft, Motwani, and Ullman published by Pearson Education. Several other related books and publications are also referenced such as books on programming languages, artificial intelligence, and computer networks. The document provides information on syllabus and curriculum for computer science courses that include topics like automata theory, formal languages, and theory of computation.
A textbook of orthodontics by t. d. foster 1991doctor_fadi
This document discusses postnatal growth of the skull and jaws from birth to maturity. It covers:
1. The cranium grows rapidly in the first year to accommodate brain development, reaching 90% of its size by age 7, while facial growth lags behind.
2. Facial growth rates follow general body growth patterns, peaking at puberty before slowing to maturity. Tooth eruption drives expansion of the dental arches.
3. Skull growth occurs through cartilage growth at sutures, periosteal bone growth on outer surfaces, and endosteal bone growth on inner surfaces. These mechanisms drive the cranium and face to their adult proportions over time.
This document contains the instructor's manual for the book "C How to Program" by Deitel & Deitel. It provides solutions to exercises in each chapter of the book, which covers topics ranging from introduction to computers and the C programming language to more advanced topics like pointers, structures, file processing, and object-oriented programming in C++ and Java. The solutions demonstrate how to correctly write C code to solve programming problems, handle errors, and explain the logic and output of programs.
The photoshop element book revised 2013 ukNasr Zaara
Here are the key Create options available in Elements 11:
- Photo Books - Create professional-looking hardcover or softcover photo books with your images. Customise page layouts, add captions and choose from a variety of themes.
- Calendars - Design and order wall, desktop or page-a-day calendars featuring your photos. Add holidays and events.
- Cards - Send your images to friends and family as custom greeting cards for birthdays, holidays or any occasion. Choose from many templates.
- Photo Prints - Print individual photos or create photo collages and gallery wraps to display your images.
- Photo Gifts - Turn your photos into mousepads, mugs, t-shirts and other
Manual of local anesthesia in dentistry, 2 e (2010) [pdf][unitedvrg]Simona Belu
- Early humans experienced pain from injuries and diseases for hundreds of thousands of years, and sought ways to relieve suffering.
- Primitive methods included applying cold water to bruises and exposing wounds to heat from the sun, fire or warm stones.
- Around 25,000-40,000 years ago, early medicine men used smoke from fires and incantations to semi-asphyxiate injured individuals, providing a form of early anesthesia through inhalation.
The document is the fourth edition of the textbook "Engineering Optimization: Theory and Practice" by Singiresu S. Rao. It covers optimization theory and techniques applied to engineering problems. The book contains chapters on classical optimization methods, linear programming, nonlinear programming, and geometric programming. It provides theoretical background and numerical examples to illustrate optimization concepts and their application to engineering design problems.
Russell John Childs has over 20 years of experience in technical software engineering, modeling complex systems, and safety-critical C++ development. He has a PhD in Particle Physics from Birmingham University and skills in C++, algorithms, parallel programming, hardware modeling, testing, and more. His resume details roles at Microsoft, Sun Microsystems, Advantest, and more where he developed load balancing algorithms, hardware behavior models, testing frameworks, and more. He is currently seeking a role utilizing his experience in analysis, architecture, design, C++, and physics/mathematics background.
The Engineering process is the conversion of material into useful product. The need for both simulation and experiments for reliable and rapid development of new products is outlined. This report provides a brief overview of the simulation based engineered product development and testing for the first time right product development. The interplay between simulation and testing are highlighted.
On average case analysis through statistical bounds linking theory to practicecsandit
This summary provides the key points from the document in 3 sentences:
The document discusses the limitations of theoretical analysis of algorithms and argues that empirical analysis through statistical bounds can provide a more robust approach for average case analysis. It explains that statistical bounds allow for mixing of different operations rather than analyzing each separately, and do not require pre-assuming a specific input distribution like uniform. The use of statistical bounds for empirical analysis is proposed as a way to supplement theoretical analysis and provide more insight into how algorithms may perform in practice.
ON AVERAGE CASE ANALYSIS THROUGH STATISTICAL BOUNDS : LINKING THEORY TO PRACTICEcscpconf
Theoretical analysis of algorithms involves counting of operations and a separate bound is provided for a specific operation type . Such a methodology is plagued with its inherent
limitations. In this paper we argue as to why we should prefer weight based statistical bounds,which permit mixing of operations, instead as a robust approach. Empirical analysis is an important idea and should be used to supplement and compliment its existing theoretical counterpart as empirically we can work on weights (e.g. time of an operation can be taken as its weight). Not surprisingly, it should not only be taken as an opportunity so as to amend the mistakes already committed knowingly or unknowingly but also to tell a new story.
This document provides course information for several undergraduate electrical engineering and computer science courses offered at MIT in the 2014-2015 school year. It lists the course numbers, titles, prerequisites, instructors, credit units, and brief descriptions. The courses cover topics such as introductory programming, computational thinking, circuits, signals and systems, software construction, algorithms, electromagnetics, microelectronic devices, and cellular biophysics.
COVERAGE DRIVEN FUNCTIONAL TESTING ARCHITECTURE FOR PROTOTYPING SYSTEM USING ...VLSICS Design
Time and efforts for functional testing of digital logic is big chunk of overall project cycle in VLSI industry. Progress of functional testing is measured by functional coverage where test-plan defines what needs to be covered, and test-results indicates quality of stimulus. Claiming closer of functional testing requires that functional coverage hits 100% of original test-plan. Depending on the complexity of the design, availability of resources and budget, various methods are used for functional testing. Software simulations using various logic simulators, available from Electronic Design Automation (EDA) companies, is primary method for functional testing. The next level in functional testing is pre-silicon verification using Field Programmable Gate Array (FPGA) prototype and/or emulation platforms for stress testing the Design Under Test (DUT). With all the efforts, the purpose is to gain confidence on maturity of DUT to ensuresfirst time silicon success that meets time to market needs of the industry. For any test-environment the bottleneck, in achieving verification closer, is controllability and observability that is quality of stimulus to unearth issues at early stage and coverage calculation. Software simulation, FPGA prototype, or emulation, each method has its own limitations, be it test-time, ease of use, or cost of software, tools and
hardware-platform. Compared to software simulation, FPGA prototyping and emulation methods pose greater challenges in quality stimulus generation and coverage calculation. Many researchers have identified the problems of bug-detection / localization, but very few have touched the concept of quality stimulus generation that leads to better functional coverage and thereby uncover hidden bugs in FPGA prototype verification setup. This paper presents a novel approach to address above-mentioned issues by embedding synthesizable active-agent and coverage collector into FPGA prototype. The proposed architecture has been experimented for functional and stress testing of Universal Serial Bus (USB) Link Training and Status State Machine (LTSSM) logic module as DUT in FPGA prototype. The proposed solution is fully synthesizable and hence can be used in both software simulation as well as in prototype system. The biggest advantage is plug and play nature of this active-agent component, that allows its reusability in any USB3.0 LTSSM digital core.
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.
A brief introduction to network simulation and the difference between simulator and emulator along with the most important types of simulations techniques.
1. The document provides details of 19 new books added to the ENLIB collection in December 2013, including title, author(s), publication year, and call number. The books cover a wide range of topics including control systems, hybrid electric vehicles, linear algebra, 3D computer vision, nonlinear analysis, thermal stresses, intelligent automation, structural dynamics, maintenance and reliability, stochastic processes, reliability engineering, protection relays, mathematical modeling, optimal and robust control, solving nonlinear PDEs, image processing, and experimental design.
The final cost of public school building projects, like other construction projects, is unknown
to the owner till the account closure. Artificial Neural Networks (ANN) is used in an attempt to
predict the final cost of two story (12 classes) school projects under lowest bid system of award
before work starts. A database of (65) school projects records completed in (2007-2012) are used to
develop and verify the ANN model. Based on expert opinions, nine out of eleven parameters are
considered to have the most significant impact on the magnitude of final cost. Hence they are used as
model inputs while the output of the model is going to be the final cost (FC). These parameters are;
accepted bid price, average bid price, estimated cost, contractor rank, supervising engineer
experience, project location, number of bidders, year of contracting, and contractual duration. It was
found that ANN has the ability to predict the final cost for school projects with very good degree of
accuracy having a coefficient of correlation (R) of (91%), and an average accuracy percentage of
(99.98%).
Analysis of intelligent system design by neuro adaptive control no restrictioniaemedu
This document discusses using neuro-adaptive control to analyze the design of intelligent systems. It begins by introducing the topic and noting that conventional adaptive control techniques assume explicit system models or dynamic structures based on linear models, which may not be valid for complex nonlinear systems. Neural networks and other intelligent control approaches that do not require explicit mathematical modeling are presented as alternatives. The paper then focuses on using time-delay neural networks for system identification and control of nonlinear dynamic systems. Various neural network architectures and learning algorithms for system modeling and control are described.
Analysis of intelligent system design by neuro adaptive controliaemedu
This document summarizes the analysis of intelligent system design using neuro-adaptive control methods. It discusses using neural networks for system identification through series-parallel and parallel models. It also discusses supervised control using a neural network trained by an expert operator, inverse control using a neural network trained on the inverse system model, and neuro-adaptive control using two neural networks - one for system identification and one for control. Neuro-adaptive control allows handling nonlinear system behavior without linear approximations.
Control chart pattern recognition using k mica clustering and neural networksISA Interchange
Automatic recognition of abnormal patterns in control charts has seen increasing demands nowadays in manufacturing processes. This paper presents a novel hybrid intelligent method (HIM) for recognition of the common types of control chart pattern (CCP). The proposed method includes two main modules: a clustering module and a classifier module. In the clustering module, the input data is first clustered by a new technique. This technique is a suitable combination of the modified imperialist competitive algorithm (MICA) and the K-means algorithm. Then the Euclidean distance of each pattern is computed from the determined clusters. The classifier module determines the membership of the patterns using the computed distance. In this module, several neural networks, such as the multilayer perceptron, probabilistic neural networks, and the radial basis function neural networks, are investigated. Using the experimental study, we choose the best classifier in order to recognize the CCPs. Simulation results show that a high recognition accuracy, about 99.65%, is achieved.
This presentation discusses about the following topics:
Hybrid Systems
Hybridization
Combinations
Comparison of Expert Systems, Fuzzy Systems, Neural Networks and Genetic Algorithms
Current Progress
Primary Components
MultiComponents
Degree of Integration
Transformational, hierarchial and integrated
Stand Alone Models
Integrated – Fused Architectures
Generalized Fused Framework
System Types for Hybridization
Review on Algorithmic and Non Algorithmic Software Cost Estimation Techniquesijtsrd
Effective software cost estimation is the most challenging and important activities in software development. Developers want a simple and accurate method of efforts estimation. Estimation of the cost before starting of work is a prediction and prediction always not accurate. Software effort estimation is a very critical task in the software engineering and to control quality and efficiency a suitable estimation technique is crucial. This paper gives a review of various available software effort estimation methods, mainly focus on the algorithmic model and non algorithmic model. These existing methods for software cost estimation are illustrated and their aspect will be discussed. No single technique is best for all situations, and thus a careful comparison of the results of several approaches is most likely to produce realistic estimation. This paper provides a detailed overview of existing software cost estimation models and techniques. This paper presents the strength and weakness of various cost estimation methods. This paper focuses on some of the relevant reasons that cause inaccurate estimation. Pa Pa Win | War War Myint | Hlaing Phyu Phyu Mon | Seint Wint Thu "Review on Algorithmic and Non-Algorithmic Software Cost Estimation Techniques" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26511.pdfPaper URL: https://www.ijtsrd.com/engineering/-/26511/review-on-algorithmic-and-non-algorithmic-software-cost-estimation-techniques/pa-pa-win
This document discusses and references several books and publications related to automata theory, formal languages, and computation. It mentions the book "Introduction to Automata Theory, Languages and Computation" by Hopcroft, Motwani, and Ullman published by Pearson Education. Several other related books and publications are also referenced such as books on programming languages, artificial intelligence, and computer networks. The document provides information on syllabus and curriculum for computer science courses that include topics like automata theory, formal languages, and theory of computation.
A textbook of orthodontics by t. d. foster 1991doctor_fadi
This document discusses postnatal growth of the skull and jaws from birth to maturity. It covers:
1. The cranium grows rapidly in the first year to accommodate brain development, reaching 90% of its size by age 7, while facial growth lags behind.
2. Facial growth rates follow general body growth patterns, peaking at puberty before slowing to maturity. Tooth eruption drives expansion of the dental arches.
3. Skull growth occurs through cartilage growth at sutures, periosteal bone growth on outer surfaces, and endosteal bone growth on inner surfaces. These mechanisms drive the cranium and face to their adult proportions over time.
This document contains the instructor's manual for the book "C How to Program" by Deitel & Deitel. It provides solutions to exercises in each chapter of the book, which covers topics ranging from introduction to computers and the C programming language to more advanced topics like pointers, structures, file processing, and object-oriented programming in C++ and Java. The solutions demonstrate how to correctly write C code to solve programming problems, handle errors, and explain the logic and output of programs.
The photoshop element book revised 2013 ukNasr Zaara
Here are the key Create options available in Elements 11:
- Photo Books - Create professional-looking hardcover or softcover photo books with your images. Customise page layouts, add captions and choose from a variety of themes.
- Calendars - Design and order wall, desktop or page-a-day calendars featuring your photos. Add holidays and events.
- Cards - Send your images to friends and family as custom greeting cards for birthdays, holidays or any occasion. Choose from many templates.
- Photo Prints - Print individual photos or create photo collages and gallery wraps to display your images.
- Photo Gifts - Turn your photos into mousepads, mugs, t-shirts and other
Manual of local anesthesia in dentistry, 2 e (2010) [pdf][unitedvrg]Simona Belu
- Early humans experienced pain from injuries and diseases for hundreds of thousands of years, and sought ways to relieve suffering.
- Primitive methods included applying cold water to bruises and exposing wounds to heat from the sun, fire or warm stones.
- Around 25,000-40,000 years ago, early medicine men used smoke from fires and incantations to semi-asphyxiate injured individuals, providing a form of early anesthesia through inhalation.
The document is the fourth edition of the textbook "Engineering Optimization: Theory and Practice" by Singiresu S. Rao. It covers optimization theory and techniques applied to engineering problems. The book contains chapters on classical optimization methods, linear programming, nonlinear programming, and geometric programming. It provides theoretical background and numerical examples to illustrate optimization concepts and their application to engineering design problems.
This document discusses various computer-aided design (CAD) tools used for microelectromechanical systems (MEMS) simulation and design. It describes SUGAR, a MEMS simulation software that uses a nodal analysis approach. Examples of simulating a cantilever and micro mirror are provided. IntelliSuite is introduced as an integrated MEMS design tool with modules for mask design, fabrication simulation, and electro-mechanical analysis. COMSOL Multiphysics is summarized as a multiphysics simulation software with dedicated MEMS and microfluidic modules for modeling common devices.
This document discusses modeling DC servo motors using artificial neural networks (ANNs). It contains the following key points:
1. ANNs are a computational intelligence technique that can be used to model nonlinear systems like DC servo motors by learning from input-output data. ANNs have an interconnected structure that allows them to learn complex relationships.
2. A DC servo motor has electrical and mechanical components that can be modeled, including resistance, inductance, inertia, damping, input voltage, back EMF, and angular position/speed. Nonlinear effects like saturation and dead zones also need to be accounted for in the model.
3. The paper presents a motor model developed using ANN techniques to mimic the behavior of
This document proposes an approach called APPEAR (Analysis and Prediction of Performance for Evolving Architectures) for predicting software performance in component-based systems. APPEAR uses both structural and statistical modeling techniques. Structural modeling reasons about component properties, while statistical modeling abstracts irrelevant execution details. APPEAR consists of two parts: 1) calibrating a statistical regression model by measuring existing applications, and 2) using the calibrated model to predict new application performance. Both parts are based on a signature model describing relevant execution properties. APPEAR supports choosing parts for structural vs. statistical modeling to balance accuracy and effort. It is being validated on two industrial case studies.
This document discusses numerical methods and their applications. It begins by defining numerical methods as approaches for solving complex mathematical problems using simple arithmetic operations. Numerical methods are needed because many models cannot be solved analytically or the analytic solution is too costly. The key steps in solving a problem numerically are formulating the mathematical model, constructing an appropriate numerical method, implementing the method, obtaining a solution, and validating the solution. Engineering applications of numerical methods include modeling mechanical systems, analyzing structural loads and vibrations, and simulating processes like combustion and spacecraft re-entry. Everyday applications include modeling airflow over airplanes, estimating ocean currents, analyzing shock waves, and fitting curves to tabular data like in electromagnetics simulations.
A M ULTI -O BJECTIVE B ASED E VOLUTIONARY A LGORITHM AND S OCIAL N ETWOR...IJCI JOURNAL
In this paper, a multi-objective based NSGA-II algo
rithm is proposed for dynamic job-shop scheduling
problem (DJSP) with random job arrivals and machine
breakdowns. In DJSP schedules are usually
inevitable due to various unexpected disruptions. T
o handle this problem, it is necessary to select
appropriate key machines at the beginning of the si
mulation instead of random selection. Thus, this pa
per
seeks to address on approach called social network
analysis method to identify the key machines of the
addressed DJSP. With identified key machines, the e
ffectiveness and stability of scheduling i.e., make
span
and starting time deviations of the computational c
omplex NP-hard problem has been solved with propose
d
multi-objective based hybrid NSGA-ll algorithm. Sev
eral experiments studies have been conducted and
comparisons have been made to demonstrate the effic
iency of the proposed approach with classical multi
-
objective based NSGA-II algorithm. The experimental
results illustrate that the proposed method is ver
y
effective in various shop floor conditions
This document discusses hierarchical design models for use in the mechatronic product development process, specifically for synchronous machines. It proposes a hierarchical design process where domain-specific design tasks are not fully integrated at the mechatronic level, but instead models cover different views and levels of detail of a system. Models represent structural, behavioral, and functional knowledge and views of a system. The approach is demonstrated through the design process of synchronous machines.
The document discusses the need for an integrated mechatronic data model to facilitate collaboration between mechanical, electrical, and software engineering teams in product development. A key challenge is that mechanical and electrical engineering data models represent different levels of detail and have traditionally been managed separately. The document proposes representing both the mechanical and electrical product structures within a single Engineering Data Management system using an object-oriented data model. This would provide the deep integration and bidirectional associations between mechanical and electrical components needed for an effective mechatronic data model.
Unknown input observer for Takagi-Sugeno implicit models with unmeasurable pr...IJECEIAES
Recent years have seen a great deal of interest in implicit nonlinear systems, which are used in many different engineering applications.This study is dedicated to presenting a new method of fuzzy unknown inputs observer design to estimate simultaneously both non-measurable states and unknown inputs of continuous-time nonlinear implicit systems defined by Takagi-Sugeno (T-S) models with unmeasurable premise variables. The suggested observer is based on the singular value decomposition approach and rewritten the continuous-time T-S implicit models into an augmented fuzzy system, which gathers the unknown inputs and the state vector. The exponential convergence condition of the observer is established by using the Lyapunov theory and linear matrix inequalities are solved to determine the gains of the observer. Finally,the effectiveness of the suggested method is then assessed using a numerical application. It demonstrates that the estimated variables and the unknown input converge to the real variables accurately and quickly (less than 0.5 s).
International journal of engineering issues vol 2015 - no 2 - paper4sophiabelthome
This document discusses modeling cyber-physical systems for engineering complex software. It proposes using geometric algebra and grammar of graphics to provide better visualization of cyber-physical systems. The key points are:
1) Cyber-physical systems integrate computation, networking, and physical processes. They are complex software systems that connect various sub-systems.
2) Geometric algebra and grammar of graphics can provide a mathematical approach to model the dynamics of cyber-physical systems. This allows better visualization of interconnected elements, feedback processes, and emergent behaviors.
3) Geometric algebra represents geometric objects algebraically rather than through equations. This provides a unified language for engineering disciplines and aspects of computer science like graphics.
A Review on Prediction of Compressive Strength and Slump by Using Different M...IRJET Journal
The document reviews different machine learning techniques for predicting the compressive strength and slump of concrete, including artificial neural networks, genetic algorithms, and hybrid algorithms. It finds that artificial neural networks trained with the Levenberg-Marquardt algorithm can predict compressive strength with over 95% accuracy. For slump prediction, federated learning achieves the best results in terms of correlation coefficient, root mean square error, and mean absolute error. A hybrid approach combining biogeography-based optimization and multilayer perceptron neural networks most accurately predicts slope stability. In general, machine learning methods show potential for effectively predicting concrete properties.
This document outlines the curriculum and syllabus for the M.E. CAD/CAM program at Anna University in Chennai, India. It includes the course requirements and electives for each of the four semesters. The first semester covers topics like advanced numerical methods, computer applications in design, integrated mechanical design, and finite element analysis. The second semester focuses on design for manufacturing, additive manufacturing, and integrated product development. The third semester is dedicated to elective courses and a project phase. The final semester involves completing the project work. The document also provides the course codes, titles, credit hours and syllabus for each course.
Analytical transformations software for stationary modes of induction motors...IJECEIAES
A program was developed in the package of symbolic transformations Maple. It provides automatic analytical transformation and derivation of formulas and plotting of the main characteristics of induction motors (IM) in a convenient form for an electrical engineer and student: torque=f(slip) T=f(s), angular speed=f(Torque) ω=f(T), angular speed=f(Current) ω=f(I), current=f(slip) I=f(s); cos(φ) and phase angle (phi) φ for stator currents and rotor currents, and magnetizing circuit, machine efficiency η=f(s) and a number of other characteristics. The calculation is based on the equivalent circuit of IM motors in its different variants: with one cage in the rotor, with two or more cages in the rotor, taking into account the skin effect in the rotor rods and without it. The user can build up the equivalent circuit to the desired configuration. The algorithm of further transformations is based on analytical obtaining of amplitude/frequency and phase/frequency characteristics in the nodes of the equivalent circuits with further calculation by power and slip. Online animation of the graphs with alternate variations of all resistances R and inductances L values of the model is provided. The article contains screenshots of important parts of the programs and illustrates the complete set of graphs.
Mathematical models and algorithms challengesijctcm
This paper succinctly illustrates challenges encountered when modelling systems mathematically.
Mathematical modelling entirely entails math symbols, numbers and relations forming a functional
equation. These mathematical equations can represent any system of interests, also provides ease computer
simulations. Mathematical models are extensively utilized in different fields i.e. engineering, by scientists,
and analysts to give a clear understanding of the problem. Modelling contributed a lot since inversion of
the concept. Simple and complex structures erected as a result of modelling. In that sense modelling is an
important part of engineering. It can be referred to as the primary building block of every system. A
complex model however is not an ideal solution. Engineers have to be cautious not to discard all
information as this might render the designed model useless – as detailed in this paper the model should be
simple with all necessary and relevant data. Basically the purpose of this paper is to show the importance
and clearly explain in detail challenges encountered when modelling
Matrix and Tensor Tools for Computer VisionActiveEon
The document discusses various matrix and tensor tools for computer vision, including principal component analysis (PCA), singular value decomposition (SVD), robust PCA, low-rank representation, non-negative matrix factorization, tensor decompositions, and incremental methods for SVD and tensor learning. It provides definitions and explanations of the techniques along with references for further information.
Glenn Vanderburg — Real software engineeringatr2006
The document discusses software engineering and argues that an implementation plan focused only on analysis and coding steps is "doomed to failure" for developing large software systems. It presents a model with additional steps like requirements analysis, program design, testing, and operations. However, it notes that separating these steps risks major redesigns if issues are found between steps.
The document proposes an iterative model where each step involves feedback and iteration with preceding and succeeding steps. This allows issues to be addressed within manageable scope rather than requiring large redesigns. It argues five additional features must be added to fully eliminate development risks, and notes the importance of establishing requirements and having a "firm and close-coupled moving baseline" to fall back
1) A large-scale stochastic automotive crash simulation was performed using 128 parallel simulations on a Cray T3E supercomputer. This allowed analysis of the statistical effects of uncertainties in vehicle properties and crash conditions.
2) Results showed the deterministic single-point analyses produced conservative designs and did not capture the most likely responses. Intrusion values from stochastic analysis had higher means and different most probable values than the deterministic analyses.
3) The impact angle had a large influence on responses like intrusion based on scatter plots, showing a chaotic relationship and inability to control intrusions through angle variation. The stochastic analysis provided more insight than deterministic analysis alone.
This document discusses the digital circuit layout problem and approaches to solving it using graph partitioning techniques. It begins by introducing the digital circuit layout problem and how it has become more complex with increasing circuit sizes. It then discusses how the problem can be decomposed into subproblems using graph partitioning to assign geometric coordinates to circuit components. The document reviews several traditional approaches to solve the problem, such as the Kernighan-Lin algorithm, and discusses their limitations for larger circuit sizes. It also discusses more recent approaches using evolutionary algorithms and concludes by analyzing the contributions of various approaches.
This document summarizes research on using graph partitioning techniques to solve digital circuit layout problems. It discusses how the digital circuit layout problem is a constrained optimization problem that is NP-hard. It then reviews previous work on using techniques like min-cut bipartitioning, multi-way partitioning algorithms, and spectral graph partitioning to solve the problem. The document concludes by analyzing evolutionary approaches that have been used, including genetic algorithms, memetic algorithms, ant colony optimization, and particle swarm intelligence. It finds that these approaches are dependent on representation and initialization but can produce quality solutions for small circuits.
Using queuing theory to describe adaptive mathematical models of computing sy...journalBEEI
The article describes the issues of preparation and verification of mathematical models of computing systems with resource virtualization. The object of this study is to verify of mathematical models of computer systems with virtualization experimentally by creating a virtual server on the host platform and monitoring its characteristics under load. Known models cannot be applied to the aircraft with virtualization, because they do not allow a comprehensive analysis to determine the most effective option for the implementation of the initial allocation of resources and its optimization for a specific sphere and task of use. The article for the study used a closed queueing network. Simple models for the analysis of various structures of computer systems are experimentally obtained. To implement the properties of adaptability in the models, triggers are used that monitor and adjust the power of the processing channel in individual Queuing systems, depending on the specified conditions. Experiments prove the obtained results reliable and usable as a flexible tool for studying the virtualization properties when structuring computing systems. This knowledge could be of use for businesses interested in optimizing the server configuration for their IT infrastructure.
IRJET- Use of Artificial Neural Network in Construction ManagementIRJET Journal
This document discusses the use of artificial neural networks (ANNs) in construction management. It provides an overview of ANNs and their advantages over traditional methods for dealing with uncertainties in construction processes. The document then reviews several applications of ANNs in construction management, including predicting construction costs, safe work behavior, safety risks, building valuations, construction productivity, and labor productivity. It finds that ANNs have been effectively used for prediction and decision-making in the construction field. The review concludes that ANNs provide best results compared to conventional methods for solving complex civil engineering problems.
This document provides information about dimensional analysis and model studies in fluid mechanics. It defines dimensional analysis as a technique that uses the study of dimensions to help solve engineering problems. Buckingham π theorem is discussed, which states that physical phenomena with n variables can be expressed in terms of n-m dimensionless terms, where m is the number of fundamental dimensions. Several model laws are defined, including Reynolds, Froude, Euler, and Weber laws. Hydraulic models are classified as undistorted or distorted, and scale effects are discussed.
This document provides information about fluid flow through pipes, including definitions and equations. It defines types of fluid flow such as steady/unsteady, uniform/non-uniform, laminar/turbulent. It also defines compressible/incompressible flow and rotational/irrotational flow. Bernoulli's equation and its assumptions are described. Darcy-Weisbach and Hagen-Poiseuille equations for head loss due to friction are given. Reynolds number range for laminar and turbulent flow is provided. Shear stress, velocity distribution, and average velocity equations are listed. Factors affecting frictional head loss are also mentioned.
The document provides information about the unit II of the course CE6303 - Mechanics of Fluids. It includes topics like fluid statics and kinematics, Pascal's law, hydrostatic equation, buoyancy, meta centre, pressure measurement, fluid mass under relative equilibrium, fluid kinematics, stream, streak and path lines, classification of flows, continuity equation, stream and potential functions, flow nets, and velocity measurement techniques. It also lists 2 marks and 16 marks questions with answers related to these topics at the end.
This document provides two-mark and 16-mark questions and answers related to the topic of mechanics of fluids. Some key concepts defined and explained include fluid mechanics, mass density, specific weight, viscosity, specific volume, specific gravity, compressibility, surface tension, and capillarity. Formulas are given for calculations related to specific weight, density, specific gravity, viscosity, kinematic viscosity, capillary rise/fall, bulk modulus, and shear stress. Sample problems and their solutions are provided applying these formulas and concepts to calculate values for various fluids under given conditions.
This document contains 31 questions regarding boundary layer concepts and fluid mechanics. It covers topics such as the range of Reynolds numbers for laminar and turbulent flow, Hagen-Poiseuille formula, velocity distribution formulas, boundary layer thickness definitions, and equations for major and minor head losses in pipes. The document also provides definitions for terms like boundary layer, laminar sublayer, displacement thickness, and momentum thickness.
This document contains a series of logic and reasoning puzzles with the answers provided. Some examples include:
1) The name of the fifth son would be Fifty.
2) After taking away 2 apples from the original 3 apples, you would have 1 apple remaining.
3) Dividing 30 by 1/2 and then adding 10 would give the answer of 60.
4) The number that does not belong in the series 1,1,2,3,4,5,8,13,21 is 5 because it is not the result of adding the previous two numbers.
Fracture mechanics is concerned with studying crack propagation in materials. There are three modes of applying force to a crack: Mode I is opening, Mode II is sliding parallel to the crack plane and crack front, and Mode III is tearing parallel to the crack plane and front. Ductile fractures are characterized by plastic deformation, dull and fibrous fracture surfaces not related to principal stress direction, and cup-and-cone shapes from microvoid formation and 45 degree shear lips. Brittle fractures occur suddenly with little plasticity and no necking, often due to low temperatures making steel more brittle.
This document provides information on the B.E. Mechanical Engineering program at MEPCO Schlenk Engineering College in Sivakasi, India. It outlines the department vision and mission, which are to educate students to become professional mechanical engineers and serve society. The program educational objectives are for students to develop self-learning abilities, a breadth of engineering knowledge, analytical reasoning skills, and strong communication skills. The program outcomes cover imparting technical knowledge and developing skills in areas such as problem solving, design, tools/software usage, and professional/social responsibilities. The document also provides course details across 8 semesters, including required courses, electives, labs, and a project work component in the final year.
The document provides an overview of the history and evolution of lean manufacturing. It discusses key figures and developments that influenced lean thinking from the 1850s through the 1990s. These include Eli Whitney and interchangeable parts, Frederick Taylor's time and motion studies, Henry Ford's assembly line, and Eiji Toyoda and Taiichi Ohno's Toyota Production System. The core principles of lean focus on removing waste and only producing what is needed when it is needed to maximize value for the customer.
This document is the preface to a textbook on reactor shielding. It discusses how shielding technology has advanced in recent decades with new computational tools and measurement techniques. It aims to cover the fundamentals of neutron and gamma-ray transport in the first semester and special topics like Monte Carlo techniques and shield design in the second semester. It is intended for advanced undergraduate or graduate students in nuclear engineering and assumes familiarity with calculus, differential equations, and nuclear physics. The author acknowledges contributions from many reviewers and thanks the late E. P. Blizard for his influence on the field of shielding technology.
This document discusses different types of geometric modeling methods including wireframe, surface, and solid modeling. Wireframe modeling uses points and lines to define objects but does not represent actual surfaces or volumes. Surface modeling defines the outer surfaces of an object. Solid modeling precisely defines the enclosed volume of an object using its faces, edges, and vertices. Constructive solid geometry and boundary representation are two common solid modeling techniques. CSG uses Boolean operations to combine primitive shapes, while boundary representation stores topological information about faces, edges, and vertices. Feature-based modeling allows shapes to be created through operations like extruding, revolving, sweeping, and filling.
The document discusses geometric modeling techniques used in manufacturing. It describes wireframe, surface, and solid modeling and their advantages and limitations. Wireframe models represent objects with edges only, while surface and solid models contain additional geometric and topological information. Parametric and non-parametric representations are used to mathematically define curves and surfaces. Geometric modeling is important for design analysis, manufacturing, inspection, and other applications.
The document discusses geometric modeling techniques used in manufacturing. It describes wireframe, surface, and solid modeling and their advantages and limitations. Wireframe models represent objects with edges only, while surface and solid models contain additional geometric and topological information. Parametric and non-parametric representations are used to mathematically define curves and surfaces. Geometric modeling is important for design analysis, manufacturing, inspection, and other applications.
Geometric modeling is a fundamental CAD technique that allows for the complete representation of parts, including their geometry and topology. There are several techniques for geometric modeling, including wireframe modeling, surface modeling, and solid modeling. Solid modeling uses half-spaces and Boolean operations to represent parts as volumes. Common solid modeling techniques are Constructive Solid Geometry (CSG) and Boundary Representation (B-rep). CSG uses primitives and Boolean operations to combine them into a modeling tree, while B-rep represents parts using their boundary surfaces and connectivity. Feature-based, parametric modeling further advanced modeling by using modeling features instead of basic primitives. Geometric modeling continues to evolve with new challenges like modeling porous media and biomedical
The document discusses geometric modeling techniques used in manufacturing. It describes wireframe, surface, and solid modeling and their advantages and limitations. Wireframe models represent objects with edges only, while surface and solid models contain additional geometric and topological information. Parametric and non-parametric representations are used to mathematically define curves and surfaces. Geometric modeling is important for design analysis, manufacturing, inspection, and other applications.
Geometric modeling is an important part of CAD systems. There are several techniques for geometric modeling including wireframe modeling, surface modeling, and solid modeling. Solid modeling uses half-spaces and boolean operations to define objects by their volume and boundaries. Constructive solid geometry (CSG) and boundary representation (B-rep) are two common solid modeling techniques. CSG uses predefined geometric primitives and boolean operations to combine them. B-rep represents solids as collections of boundary surfaces and records the geometry and topology of the surfaces.
This document discusses 3D modeling systems and solid modeling concepts. It covers terminology used in examining 3D modeling systems and applying geometric modeling to engineering design. A 3D model creates an analogous representation of an object that approximates the real world object but is not identical. The model is stored in a database that contains geometric and topological information about the model. Secondary models may be derived from the primary model for specific applications like display or analysis. Associativity links primary and secondary models so changes can propagate between them. Solid modeling systems aim to represent real world objects by ensuring models are bounded, finite, and homogeneously 3-dimensional without dangling faces or edges.
This document discusses geometric modeling techniques, specifically focusing on solid modeling and drafting packages. It outlines the salient features of solid modeling, including feature-based design, modeling tools, and characteristics of solid modeling packages. It also describes the features of drafting packages, such as drawing utilities, dimensioning, entities, and drawing interchange files. Finally, it briefly discusses surface modeling and curve and surface representations.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
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Resource: Finite Element Procedures for Solids and Structures
Klaus-Jürgen Bathe
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