This document provides an overview of fundamental arithmetic concepts including:
1) The real number system and identifying types of real numbers.
2) The order of operations for performing calculations with real numbers, which specifies evaluating expressions in brackets first, then multiplication/division from left to right, followed by addition/subtraction from left to right.
3) Examples demonstrating the application of the order of operations without and with a calculator.
This document provides a progression grid for teaching number concepts in stages 7-9 of the Cambridge Lower Secondary Mathematics curriculum. It outlines learning objectives and examples for teaching integers, place value, fractions, decimals, percentages, ratios, proportions, and standard form. Key concepts covered include addition and subtraction of integers, order of operations, factors and multiples, square and cube roots, rounding, and multiplying/dividing by powers of ten. The document is intended to guide teachers in building students' number sense and mathematical skills over several years.
Unit-1 Basic Concept of Algorithm.pptxssuser01e301
The document discusses various topics related to algorithms including algorithm design, real-life applications, analysis, and implementation. It specifically covers four algorithms - the taxi algorithm, rent-a-car algorithm, call-me algorithm, and bus algorithm - for getting from an airport to a house. It also provides examples of simple multiplication methods like the American, English, and Russian approaches as well as the divide and conquer method.
This document discusses arithmetic sequences. It begins by defining an arithmetic sequence as a sequence of numbers where the difference between consecutive terms is constant. It provides the formula an = a1 + (n-1)d to calculate the nth term, where an is the nth term, a1 is the first term, d is the common difference. Several examples are worked out applying this formula. Real-life examples of arithmetic sequences are discussed, like rows of seats in a stadium increasing by a constant amount. Students are assigned problems evaluating arithmetic sequences and finding specific terms, as well as researching other real-world applications of arithmetic sequences.
The absolute value of a number represents the distance of that number from zero on the number line. It is always positive or zero. Addition of integers can be done using number lines, signed tiles, or rules. When integers have like signs, add the numbers and keep the common sign. When they have unlike signs, subtract the numbers and use the sign of the number with the greater absolute value.
The document discusses several algorithms:
1. Program verification - A technique to mathematically prove that a program's output matches its specifications for any input.
2. Algorithm efficiency - Designing algorithms that are economical with resources like time and memory.
3. Analysis of algorithms - Qualities like correctness, understandability and efficiency.
It then provides examples of algorithms for:
1. Swapping variable values
2. Counting elements that meet a condition in a set
3. Summing a set of numbers
4. Computing factorials
5. Evaluating trigonometric functions like sine
The document provides study material for mathematics for class 10 students of Kendriya Vidyalaya Sangathan. It was prepared by the Patna regional office in accordance with instructions from KVS headquarters. The study material aims to help students understand concepts well and meet quality expectations. It was prepared under the guidance of the Deputy Commissioner with contributions from teachers of KV No. 2 Gaya.
This document provides a progression grid for teaching number concepts in stages 7-9 of the Cambridge Lower Secondary Mathematics curriculum. It outlines learning objectives and examples for teaching integers, place value, fractions, decimals, percentages, ratios, proportions, and standard form. Key concepts covered include addition and subtraction of integers, order of operations, factors and multiples, square and cube roots, rounding, and multiplying/dividing by powers of ten. The document is intended to guide teachers in building students' number sense and mathematical skills over several years.
Unit-1 Basic Concept of Algorithm.pptxssuser01e301
The document discusses various topics related to algorithms including algorithm design, real-life applications, analysis, and implementation. It specifically covers four algorithms - the taxi algorithm, rent-a-car algorithm, call-me algorithm, and bus algorithm - for getting from an airport to a house. It also provides examples of simple multiplication methods like the American, English, and Russian approaches as well as the divide and conquer method.
This document discusses arithmetic sequences. It begins by defining an arithmetic sequence as a sequence of numbers where the difference between consecutive terms is constant. It provides the formula an = a1 + (n-1)d to calculate the nth term, where an is the nth term, a1 is the first term, d is the common difference. Several examples are worked out applying this formula. Real-life examples of arithmetic sequences are discussed, like rows of seats in a stadium increasing by a constant amount. Students are assigned problems evaluating arithmetic sequences and finding specific terms, as well as researching other real-world applications of arithmetic sequences.
The absolute value of a number represents the distance of that number from zero on the number line. It is always positive or zero. Addition of integers can be done using number lines, signed tiles, or rules. When integers have like signs, add the numbers and keep the common sign. When they have unlike signs, subtract the numbers and use the sign of the number with the greater absolute value.
The document discusses several algorithms:
1. Program verification - A technique to mathematically prove that a program's output matches its specifications for any input.
2. Algorithm efficiency - Designing algorithms that are economical with resources like time and memory.
3. Analysis of algorithms - Qualities like correctness, understandability and efficiency.
It then provides examples of algorithms for:
1. Swapping variable values
2. Counting elements that meet a condition in a set
3. Summing a set of numbers
4. Computing factorials
5. Evaluating trigonometric functions like sine
The document provides study material for mathematics for class 10 students of Kendriya Vidyalaya Sangathan. It was prepared by the Patna regional office in accordance with instructions from KVS headquarters. The study material aims to help students understand concepts well and meet quality expectations. It was prepared under the guidance of the Deputy Commissioner with contributions from teachers of KV No. 2 Gaya.
The document defines algorithms and their components. An algorithm is a series of unambiguous instructions to solve a problem. It has inputs, outputs, and each step can be carried out in a finite time. An algorithm description includes the name, inputs, outputs, definition, and method. The method is a step-by-step process. Algorithms use variables that represent memory locations storing values. Tracing confirms an algorithm works correctly with sample inputs. Data types specify the kind, range, size, and operations for variables.
The document discusses scientific notation, dimensional analysis, uncertainty in data, and representing data graphically. It defines scientific notation and explains how to perform operations like addition, subtraction, multiplication, and division when numbers are in scientific notation. Dimensional analysis is introduced as a systematic approach to problem solving using conversion factors. The concepts of accuracy, precision, error, and percent error are defined in relation to experimental uncertainty. Rules for significant figures are provided to quantify uncertainty in measurements and calculations. Finally, different types of graphs like line graphs, bar graphs, and circle graphs are described along with interpreting graphs through interpolation and extrapolation.
This document introduces coordinate systems on a line. It defines how to assign coordinates to points on a line by choosing an origin point and direction, and measuring distances from the origin. Points to the right of the origin have positive coordinates equal to their distance from the origin, while points to the left have negative coordinates equal to the negative of their distance. The absolute value of a real number is defined as its magnitude, regardless of sign.
The document discusses various methods for developing empirical dynamic models from process input-output data, including linear regression and least squares estimation. Simple linear regression can be used to develop steady-state models relating an output variable y to an input variable u. The least squares approach is introduced to calculate the parameter estimates that minimize the error between measured and predicted output values. Graphical methods are also presented for estimating parameters of first-order and second-order dynamic models by fitting step response data. Finally, the development of discrete-time models from continuous-time models using finite difference approximations is covered.
Special webinar on tips for perfect score in sat mathCareerGOD
Math is the language of logic and is therefore tested in all the major examinations where SAT is no exception.
Scoring well in Math can do wonders to your career and college candidature. Conversely, any complacency in Math affect your score and thus prove dangerous.
In this webinar, “Tips for perfect Math score in SAT and SAT- Math subject test” from the 5-day webinar series ‘Experts’ Speak: Demystifying US Admissions’, seasoned math trainers and subject experts with decades of experience in the industry share important insights on maximising your Math scores and minimising mistakes to lose out on Math scores.
Visit www.careergod.com for more info.
Chapter 1 Errors and Approximations.pptEyob Adugnaw
This document provides an introduction to numerical methods. It discusses how numerical methods are used to find approximate solutions to problems where an exact analytical solution does not exist, such as higher order polynomial equations. Numerical methods are iterative and provide approximations that improve in accuracy with each iteration. Examples of numerical methods covered include finding the square root of a number and solving a second order polynomial equation. The document also discusses concepts such as error analysis, significant figures, rounding, and sources of numerical errors.
This document contains tutorial questions covering topics related to number systems, real numbers, indices, surds, logarithms and equations. It includes 27 multiple part questions testing concepts such as classifying numbers, evaluating expressions, solving equations, graphing intervals and more. An example study tip is provided at the end recommending desire, discipline and time management as keys to academic success.
Economics
Curve Fitting
macroeconomics
Curve fitting helps in capturing the trend in the data by assigning a single function
across the entire range.
If the functional relationship between the two quantities being graphed is known to be
within additive or multiplicative constants, it is common practice to transform the data in
such a way that the resulting line is a straight line.(by plotting) A process of quantitatively
estimating the trend of the outcomes, also known as regression or curve fitting, therefore
becomes necessary.
For a series of data, curve fitting is used to find the best fit curve. The produced equation is
used to find points anywhere along the curve. It also uses interpolation (exact fit to the data)
and smoothing.
Some people also refer it as regression analysis instead of curve fitting. The curve fitting
process fits equations of approximating curves to the raw field data. Nevertheless, for a
given set of data, the fitting curves of a given type are generally NOT unique.
Smoothing of the curve eliminates components like seasonal, cyclical and random
variations. Thus, a curve with a minimal deviation from all data points is desired. This
best-fitting curve can be obtained by the method of least squares.
What is curve fitting Curve fitting?
Curve fitting is the process of constructing a curve, or mathematical functions, which possess closest
proximity to the series of data. By the curve fitting we can mathematically construct the functional
relationship between the observed fact and parameter values, etc. It is highly effective in mathematical
modelling some natural processes.
What is a fitting model?
A fit model (sometimes fitting model) is a person who is used by a fashion designer or
clothing manufacturer to check the fit, drape and visual appearance of a design on a
'real' human being, effectively acting as a live mannequin.
What is a model fit statistics?
The goodness of fit of a statistical model describes how well it fits a set of
observations. Measures of goodness of fit typically summarize the discrepancy
between observed values and the values expected under the model in question.
What is a commercial model?
Commercial modeling is a more generalized type of modeling. There are high
fashion models, and then there are commercial models. ... They can model for
television, commercials, websites, magazines, newspapers, billboards and any other
type of advertisement. Most people who tell you they are models are “commercial”
models.
What is the exponential growth curve?
Growth of a system in which the amount being added to the system is proportional to the
amount already present: the bigger the system is, the greater the increase. ( See geometric
progression.) Note : In everyday speech, exponential growth means runaway expansion, such
as in population growth.
Why is population exponential?
Exponential population growth: When resources are unlimited, populations
exhibit exponential growth, resulting in a J-shaped curve.
This document provides an overview and contents for a course on mathematical methods and models. It covers topics including numbers, standard functions, trigonometric functions, complex numbers, differentiation, integration, vector algebra, and differential equations. The first unit reviews foundational concepts like numbers, measurement, functions, calculus, and introduces the computer algebra package used in the course. Subsequent units cover first and second order differential equations, initial and boundary value problems, and vector algebra. The goal is to equip students with mathematical techniques for modeling real-world problems and to provide exercises for developing skills in applying these techniques.
The document outlines the revised first and second semester engineering course for the University of Mumbai from the 2012-2013 academic year onwards. It provides the course structure, syllabus, credit details, examination scheme, and term work details for various subjects in the first year of engineering, including Applied Mathematics, Physics, Chemistry, Engineering Mechanics, Electrical Engineering, Environmental Studies, and Workshop Practice. The subjects are common for all branches of engineering in the first year. The document specifies the number of lecture, practical, and tutorial hours for each subject, as well as the internal and external assessment details and distribution of marks. Recommended books and instructions for term work are also provided.
This document introduces numerical analysis and discusses floating point numbers. It covers topics such as absolute and relative errors, roundoff and truncation errors, Taylor series approximations, interpolation methods, solving nonlinear equations, numerical differentiation and integration, numerical solutions to differential equations, and linear algebra techniques. Example C programs are provided to illustrate various numerical methods.
The document discusses key concepts related to derivatives including:
1) Derivatives of trigonometric functions, implicit derivatives, and derivative applications are the main materials covered.
2) The achievement indicators are to calculate derivatives of trig functions correctly, determine implicit derivatives correctly, and explain applications of derivatives correctly.
3) Examples are provided for derivatives of trig functions, implicit derivatives, and composition functions to illustrate these concepts.
- The document is a mark scheme that provides guidance for examiners marking the Pearson Edexcel International GCSE Mathematics exam.
- It outlines general marking principles such as marking candidates positively and awarding all marks that are deserved.
- The mark scheme then provides specific guidance on marking parts of questions, including how to award method marks and accuracy marks.
1. The document provides information about an orientation session for a business statistics course, including the contact information for the instructor, Ahmad Jalil Ansari.
2. It outlines the course objectives to introduce basic statistical techniques applicable to business studies and research. Upon completing the course, students will be able to use statistical tools in various fields.
3. The document details the topics to be covered in the course before and after midterms, drawing mainly from the textbook "Statistics for Management, 7th Edition".
K to 12 - Grade 8 Math Learners Module Quarter 2Nico Granada
Here are the completed statements based on the conclusions:
1. n(A × B) = n(B × A).
2. A × B ≠ B × A.
The key conclusions are:
1. The cardinalities of the Cartesian products A × B and B × A are equal, since n(A × B) = n(B × A).
2. However, the sets A × B and B × A are not equal, since the ordered pairs will be arranged differently, so A × B ≠ B × A.
The document introduces the topic of relations and functions and outlines 3 lessons that will be covered - rectangular coordinate system, representations of relations and functions, and linear functions and applications. It provides learning objectives for each lesson and examples of how concepts like slope, intercepts, and graphs will be explored. A pre-assessment with 20 multiple choice questions is also included to gauge students' prior knowledge.
The document introduces the key concepts that will be covered in a module on relations and functions, including the rectangular coordinate system, representations of relations and functions, and linear functions and their applications. It outlines 3 lessons that will examine how to predict the value of a quantity given the rate of change, and provides sample problems to assess students' prior knowledge on these topics before beginning the lessons.
This document provides an introduction to MATLAB and Simulink. It explains that MATLAB is a software package used for numerical computation, while Simulink is used for modeling and simulating dynamic systems. The document outlines some key things readers can learn, including basics of MATLAB/Simulink functions, getting started, vectors and matrices, M-files, and modeling examples. It also provides examples of basic MATLAB operations on vectors and matrices.
This document discusses different types of sequences in mathematics, including linear, quadratic, and geometric sequences. It provides examples and explanations of how to determine the rule that generates each sequence, either from term-to-term or from the position of a term in the sequence. Key points covered include finding the common difference or second difference to classify a sequence as linear or quadratic, and determining the formula for the nth term of a sequence from its pattern of terms. Examples are given of predicting future terms and finding specific terms of various sequences.
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
The document defines algorithms and their components. An algorithm is a series of unambiguous instructions to solve a problem. It has inputs, outputs, and each step can be carried out in a finite time. An algorithm description includes the name, inputs, outputs, definition, and method. The method is a step-by-step process. Algorithms use variables that represent memory locations storing values. Tracing confirms an algorithm works correctly with sample inputs. Data types specify the kind, range, size, and operations for variables.
The document discusses scientific notation, dimensional analysis, uncertainty in data, and representing data graphically. It defines scientific notation and explains how to perform operations like addition, subtraction, multiplication, and division when numbers are in scientific notation. Dimensional analysis is introduced as a systematic approach to problem solving using conversion factors. The concepts of accuracy, precision, error, and percent error are defined in relation to experimental uncertainty. Rules for significant figures are provided to quantify uncertainty in measurements and calculations. Finally, different types of graphs like line graphs, bar graphs, and circle graphs are described along with interpreting graphs through interpolation and extrapolation.
This document introduces coordinate systems on a line. It defines how to assign coordinates to points on a line by choosing an origin point and direction, and measuring distances from the origin. Points to the right of the origin have positive coordinates equal to their distance from the origin, while points to the left have negative coordinates equal to the negative of their distance. The absolute value of a real number is defined as its magnitude, regardless of sign.
The document discusses various methods for developing empirical dynamic models from process input-output data, including linear regression and least squares estimation. Simple linear regression can be used to develop steady-state models relating an output variable y to an input variable u. The least squares approach is introduced to calculate the parameter estimates that minimize the error between measured and predicted output values. Graphical methods are also presented for estimating parameters of first-order and second-order dynamic models by fitting step response data. Finally, the development of discrete-time models from continuous-time models using finite difference approximations is covered.
Special webinar on tips for perfect score in sat mathCareerGOD
Math is the language of logic and is therefore tested in all the major examinations where SAT is no exception.
Scoring well in Math can do wonders to your career and college candidature. Conversely, any complacency in Math affect your score and thus prove dangerous.
In this webinar, “Tips for perfect Math score in SAT and SAT- Math subject test” from the 5-day webinar series ‘Experts’ Speak: Demystifying US Admissions’, seasoned math trainers and subject experts with decades of experience in the industry share important insights on maximising your Math scores and minimising mistakes to lose out on Math scores.
Visit www.careergod.com for more info.
Chapter 1 Errors and Approximations.pptEyob Adugnaw
This document provides an introduction to numerical methods. It discusses how numerical methods are used to find approximate solutions to problems where an exact analytical solution does not exist, such as higher order polynomial equations. Numerical methods are iterative and provide approximations that improve in accuracy with each iteration. Examples of numerical methods covered include finding the square root of a number and solving a second order polynomial equation. The document also discusses concepts such as error analysis, significant figures, rounding, and sources of numerical errors.
This document contains tutorial questions covering topics related to number systems, real numbers, indices, surds, logarithms and equations. It includes 27 multiple part questions testing concepts such as classifying numbers, evaluating expressions, solving equations, graphing intervals and more. An example study tip is provided at the end recommending desire, discipline and time management as keys to academic success.
Economics
Curve Fitting
macroeconomics
Curve fitting helps in capturing the trend in the data by assigning a single function
across the entire range.
If the functional relationship between the two quantities being graphed is known to be
within additive or multiplicative constants, it is common practice to transform the data in
such a way that the resulting line is a straight line.(by plotting) A process of quantitatively
estimating the trend of the outcomes, also known as regression or curve fitting, therefore
becomes necessary.
For a series of data, curve fitting is used to find the best fit curve. The produced equation is
used to find points anywhere along the curve. It also uses interpolation (exact fit to the data)
and smoothing.
Some people also refer it as regression analysis instead of curve fitting. The curve fitting
process fits equations of approximating curves to the raw field data. Nevertheless, for a
given set of data, the fitting curves of a given type are generally NOT unique.
Smoothing of the curve eliminates components like seasonal, cyclical and random
variations. Thus, a curve with a minimal deviation from all data points is desired. This
best-fitting curve can be obtained by the method of least squares.
What is curve fitting Curve fitting?
Curve fitting is the process of constructing a curve, or mathematical functions, which possess closest
proximity to the series of data. By the curve fitting we can mathematically construct the functional
relationship between the observed fact and parameter values, etc. It is highly effective in mathematical
modelling some natural processes.
What is a fitting model?
A fit model (sometimes fitting model) is a person who is used by a fashion designer or
clothing manufacturer to check the fit, drape and visual appearance of a design on a
'real' human being, effectively acting as a live mannequin.
What is a model fit statistics?
The goodness of fit of a statistical model describes how well it fits a set of
observations. Measures of goodness of fit typically summarize the discrepancy
between observed values and the values expected under the model in question.
What is a commercial model?
Commercial modeling is a more generalized type of modeling. There are high
fashion models, and then there are commercial models. ... They can model for
television, commercials, websites, magazines, newspapers, billboards and any other
type of advertisement. Most people who tell you they are models are “commercial”
models.
What is the exponential growth curve?
Growth of a system in which the amount being added to the system is proportional to the
amount already present: the bigger the system is, the greater the increase. ( See geometric
progression.) Note : In everyday speech, exponential growth means runaway expansion, such
as in population growth.
Why is population exponential?
Exponential population growth: When resources are unlimited, populations
exhibit exponential growth, resulting in a J-shaped curve.
This document provides an overview and contents for a course on mathematical methods and models. It covers topics including numbers, standard functions, trigonometric functions, complex numbers, differentiation, integration, vector algebra, and differential equations. The first unit reviews foundational concepts like numbers, measurement, functions, calculus, and introduces the computer algebra package used in the course. Subsequent units cover first and second order differential equations, initial and boundary value problems, and vector algebra. The goal is to equip students with mathematical techniques for modeling real-world problems and to provide exercises for developing skills in applying these techniques.
The document outlines the revised first and second semester engineering course for the University of Mumbai from the 2012-2013 academic year onwards. It provides the course structure, syllabus, credit details, examination scheme, and term work details for various subjects in the first year of engineering, including Applied Mathematics, Physics, Chemistry, Engineering Mechanics, Electrical Engineering, Environmental Studies, and Workshop Practice. The subjects are common for all branches of engineering in the first year. The document specifies the number of lecture, practical, and tutorial hours for each subject, as well as the internal and external assessment details and distribution of marks. Recommended books and instructions for term work are also provided.
This document introduces numerical analysis and discusses floating point numbers. It covers topics such as absolute and relative errors, roundoff and truncation errors, Taylor series approximations, interpolation methods, solving nonlinear equations, numerical differentiation and integration, numerical solutions to differential equations, and linear algebra techniques. Example C programs are provided to illustrate various numerical methods.
The document discusses key concepts related to derivatives including:
1) Derivatives of trigonometric functions, implicit derivatives, and derivative applications are the main materials covered.
2) The achievement indicators are to calculate derivatives of trig functions correctly, determine implicit derivatives correctly, and explain applications of derivatives correctly.
3) Examples are provided for derivatives of trig functions, implicit derivatives, and composition functions to illustrate these concepts.
- The document is a mark scheme that provides guidance for examiners marking the Pearson Edexcel International GCSE Mathematics exam.
- It outlines general marking principles such as marking candidates positively and awarding all marks that are deserved.
- The mark scheme then provides specific guidance on marking parts of questions, including how to award method marks and accuracy marks.
1. The document provides information about an orientation session for a business statistics course, including the contact information for the instructor, Ahmad Jalil Ansari.
2. It outlines the course objectives to introduce basic statistical techniques applicable to business studies and research. Upon completing the course, students will be able to use statistical tools in various fields.
3. The document details the topics to be covered in the course before and after midterms, drawing mainly from the textbook "Statistics for Management, 7th Edition".
K to 12 - Grade 8 Math Learners Module Quarter 2Nico Granada
Here are the completed statements based on the conclusions:
1. n(A × B) = n(B × A).
2. A × B ≠ B × A.
The key conclusions are:
1. The cardinalities of the Cartesian products A × B and B × A are equal, since n(A × B) = n(B × A).
2. However, the sets A × B and B × A are not equal, since the ordered pairs will be arranged differently, so A × B ≠ B × A.
The document introduces the topic of relations and functions and outlines 3 lessons that will be covered - rectangular coordinate system, representations of relations and functions, and linear functions and applications. It provides learning objectives for each lesson and examples of how concepts like slope, intercepts, and graphs will be explored. A pre-assessment with 20 multiple choice questions is also included to gauge students' prior knowledge.
The document introduces the key concepts that will be covered in a module on relations and functions, including the rectangular coordinate system, representations of relations and functions, and linear functions and their applications. It outlines 3 lessons that will examine how to predict the value of a quantity given the rate of change, and provides sample problems to assess students' prior knowledge on these topics before beginning the lessons.
This document provides an introduction to MATLAB and Simulink. It explains that MATLAB is a software package used for numerical computation, while Simulink is used for modeling and simulating dynamic systems. The document outlines some key things readers can learn, including basics of MATLAB/Simulink functions, getting started, vectors and matrices, M-files, and modeling examples. It also provides examples of basic MATLAB operations on vectors and matrices.
This document discusses different types of sequences in mathematics, including linear, quadratic, and geometric sequences. It provides examples and explanations of how to determine the rule that generates each sequence, either from term-to-term or from the position of a term in the sequence. Key points covered include finding the common difference or second difference to classify a sequence as linear or quadratic, and determining the formula for the nth term of a sequence from its pattern of terms. Examples are given of predicting future terms and finding specific terms of various sequences.
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
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
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.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
3. Table of contents
Page
Pre-test 1
Introduction 1
How to do the written pre-test 1
Questions 3
Module 1 – Fundamentals of arithmetic 9
Objectives 9
1.1 Review of the real number system 9
1.2 Order of operations 10
1.3 Numerical fractions 16
1.3.1 Addition and subtraction of fractions 16
1.3.2 Multiplication of fractions 23
1.3.3 Division of fractions 27
1.4 Indices 31
Powers using calculator 31
Multiplication 32
Division 32
Power of a power 32
Power of a product 32
Fractional index 33
Zero index 34
Negative index 34
1.5 Scientific notation 38
1.6 Metric units 42
Module 1: Self assessment 45
Questions 1.1 45
Questions 1.2 46
Module 2 – Basic algebra 47
Objectives 47
2.1 Variables and expressions 47
2.2 Algebraic expressions 52
2.2.1 Addition and subtraction of like terms 52
2.2.2 Expansion and the Distributive Law 56
2.2.3 Factorisation 62
2.3 Algebraic fractions 66
2.3.1 Cancellation in fractions 66
2.3.2 Addition and subtraction of fractions 68
2.4 Solving equations and inequations 70
2.4.1 Linear equations 70
2.4.2 Rearranging formulae 79
2.4.3 Quadratic equations 88
2.4.4 Polynomial equations 97
2.4.5 Inequalities 102
4. Module 2: Self assessment 107
Questions 2.1 107
Questions 2.2 108
Module 3 – Functions and relations 109
Objectives 109
3.1 What is a function? 109
3.1.1 Algebra of functions 111
3.2 Graphs of functions and relations 116
3.2.1 Cartesian coordinate system 116
3.2.2 The linear function 117
3.2.3 The quadratic function 128
3.2.4 Cubic functions 138
3.2.5 The circle 142
3.2.6 Rational functions 149
3.2.7 Other functions 157
3.3 Intersections of functions 164
3.3.1 Intersection of linear functions 164
3.3.2 Intersection of functions other than straight lines or planes 171
Module 3: Self assessment 177
Questions 3.1 177
Questions 3.2 178
Module 4 – Logarithms and related functions 179
Objectives 179
4.1 Logarithms 179
4.2 Equations involving logarithms 187
4.3 Exponential functions 192
4.4 Logarithmic functions 199
4.5 Further applications of logarithms and exponentials 206
Module 4: Self assessment 215
Questions 4.1 215
Questions 4.2 216
Module 5 – Trigonometry 217
Objectives 217
5.1 Trigonometric relationships 218
5.2 Trigonometric identities 228
5.3 Triangle solution 231
5.4 Compound angles 239
5.5 Radian measure 244
Length of arc of a circle 245
Area of a sector of a circle 246
5.6 Graphs involving trigonometric functions 248
Module 5: Self assessment 255
Questions 5.1 255
Questions 5.2 256
75. ENM1500 – Introductory engineering mathematics 71
Number Type Example Steps involved
1 x + a = b
9 12
9 9 12 9
3
x
x
x
+ =
+ − = −
=
By subtracting 9 from the LHS we cancel the given 9.
To keep the balance do the same to the RHS.
Check: LHS = 3 + 9 = 12 = RHS
2 x – a = b
2 7
2 2 7 2
5
x
x
x
− = −
− + = − +
= −
Add 2 to the LHS to cancel the given 2.
Add 2 to the RHS to keep the balance.
Check: LHS = –5 – 2 = – 7 = RHS
3 ax = b
3 29
3 29
3 3
2
9
3
9.67
x
x
x
x
=
=
=
≈
Cancel the 3 on the LHS by dividing by 3.
Do the same to the RHS.
Coefficient of x is now 1.
Express answer as either a mixed number or a decimal.
Check: LHS =
2 29
3 9 3 29 RHS
3 3
× = × = =
4
x
b
a
=
4
5
5 4 5
5
20
x
x
x
= −
× = − ×
= −
Multiply the LHS by 5 to cancel the given 5.
Maintain the balance by multiplying the RHS by 5.
Check: LHS =
20
4 RHS
5
−
= − =
5 a + x = b
3 8.5
3 3 8.5 3
5.5
x
x
x
+ =
+ − = −
=
Subtract 3 from both sides.
Check: LHS = 3 + 5.5 = 8.5 = RHS
6 a – x = b
7 2
7 7 2 7
5
1 5 1
5
x
x
x
x
x
− =
− − = −
− = −
− × − = − × −
=
Coefficient of x is –1.
Multiply LHS by –1 to give a coefficient of 1.
Do the same for the RHS.
Check: LHS = 7 – 5 = 2 = RHS
7 ax + b = c
3 8 14
3 8 8 14 8
3 6
3 6
3 3
2
x
x
x
x
x
+ =
+ − = −
=
=
=
Cancel out addition first.
Then cancel multiplication.
Check: LHS = 3 × 2 + 8 = 6 + 8 = 14 = RHS
8 b + ax = c
3 7 17
3 7 3 17 3
7 14
7 14
7 7
2
x
x
x
x
x
+ =
+ − = −
=
=
=
Cancel addition.
Cancel multiplication.
Check: LHS = 3 + 7 × 2 = 3 + 14 = 17 = RHS
76. 72 ENM1500 – Introductory engineering mathematics
Number Type Example Steps involved
9 b – ax = c
18 5 17
18 5 18 17 18
5 1
5 1
5 5
1
5
x
x
x
x
x
− =
− − = −
− = −
− −
=
− −
=
Cancel 18 on LHS.
Cancel –5 on LHS.
Check: LHS =
1
18 5 18 1 17 RHS
5
− × = − = =
10 ax + b + cx = d
( )
2 8 3 3
2 3 8 3
2 3 8 3
5 8 3
5 8 8 3 8
5 5
5 5
5 5
1
x x
x x
x
x
x
x
x
x
+ + =
+ + =
+ + =
+ =
+ − = −
= −
−
=
= −
Group like terms.
Cancel 8 on LHS
Cancel 5 on LHS
Check: LHS = 2 × –1 + 8 + 3 × –1 = –2 + 8 – 3 = 3 = RHS
11 a(x + b) = c
( )
( )
3 1 12
3 1 12
3 3
1 4
1 1 4 1
3
x
x
x
x
x
+ =
+
=
+ =
+ − = −
=
Leave brackets.
Cancel 3 on LHS
Now cancel 1 on LHS
Check: LHS = 3(3 + 1) = 3 × 4 = 12 = RHS
12 ax + b = cx + d
( )
3 2 5 4
3 2 5 5 4 5
3 5 2 4
3 5 2 4
2 2 4
2 2 2 4 2
2 2
2 2
2
1
x x
x x x x
x x
x
x
x
x
x
x
x
+ = +
+ − = + −
− + =
− + =
− + =
− + − = −
− =
−
=
−
= −
Group like terms on LHS
Cancel 2 on LHS
Cancel –2 on LHS
Check: LHS = 3(–1) + 2 = –1
RHS = 5(–1) + 4 = –1
LHS = RHS