οΊPlease Subscribe to this Channel for more solutions and lectures
http://www.youtube.com/onlineteaching
Chapter 10: Correlation and Regression
10.2: Regression
Spline interpolation is a problem of "Numerical Methods".
This slide covers the basics of spline interpolation mostly the linear spline and cubic spline interpolation.
Design of Second Order Digital Differentiator and Integrator Using Forward Di...inventionjournals
Β
In this paper, the second order differentiator and integrator, design is investigated. Firstly, the forward difference formula is applied in numerical differentiation for deriving the transfer function of second order differentiator and integrator. Thereafter, the Richardson extrapolation is used for generating the high accuracy results, while using low order formulas. Further, the conventional Lagrange FIR fractional delay filter is applied directly for implementation of the second order differentiator, design. Finally, the effectiveness of this new design approach is illustrated by using several numerical examples.
Collinearity Equations
Kinds of product that can be derived by the collinearity equation
- Space Resection By Collinearity
- Space Intersection By Collinearity
- Interior Orientation
- Relative Orientation
- Absolute Orientation
- Self-Calibration
The International Journal of Engineering and Science (The IJES)theijes
Β
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
οΊPlease Subscribe to this Channel for more solutions and lectures
http://www.youtube.com/onlineteaching
Chapter 10: Correlation and Regression
10.2: Regression
Spline interpolation is a problem of "Numerical Methods".
This slide covers the basics of spline interpolation mostly the linear spline and cubic spline interpolation.
Design of Second Order Digital Differentiator and Integrator Using Forward Di...inventionjournals
Β
In this paper, the second order differentiator and integrator, design is investigated. Firstly, the forward difference formula is applied in numerical differentiation for deriving the transfer function of second order differentiator and integrator. Thereafter, the Richardson extrapolation is used for generating the high accuracy results, while using low order formulas. Further, the conventional Lagrange FIR fractional delay filter is applied directly for implementation of the second order differentiator, design. Finally, the effectiveness of this new design approach is illustrated by using several numerical examples.
Collinearity Equations
Kinds of product that can be derived by the collinearity equation
- Space Resection By Collinearity
- Space Intersection By Collinearity
- Interior Orientation
- Relative Orientation
- Absolute Orientation
- Self-Calibration
The International Journal of Engineering and Science (The IJES)theijes
Β
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
MIXTURES OF TRAINED REGRESSION CURVESMODELS FOR HANDRITTEN ARABIC CHARACTER R...ijaia
Β
In this paper, we demonstrate how regression curves can be used to recognize 2D non-rigid handwritten shapes. Each shape is represented by a set of non-overlapping uniformly distributed landmarks. The underlying models utilize 2nd order of polynomials to model shapes within a training set. To estimate the regression models, we need to extract the required coefficients which describe the variations for a set of shape class. Hence, a least square method is used to estimate such modes. We proceed then, by training these coefficients using the apparatus Expectation Maximization algorithm. Recognition is carried out by finding the least error landmarks displacement with respect to the model curves. Handwritten isolated Arabic characters are used to evaluate our approach.
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 New Approach to Design a Reduced Order ObserverIJERD Editor
Β
In this paper, a new method for designing a reduced order observer for linear time-invariant system is
proposed. The approach is based on matrix inversion with proper dimension. The arbitrariness associated with
the method proposed by OβReilly is presented here and has been reduced with the help of pole-placement
technique. It also helps reducing the computations regarding the observer design parameters. Illustrative
numerical examples with simulation results are also included.
Derivation and Application of Six-Point Linear Multistep Numerical Method for...IOSR Journals
Β
A six-step Continuous Block method of order (5, 5, 5, 5, 5, 5) T is proposed for direct solution of the second (2nd) order initial value problems. The main method and additional ones are obtained from the same continuous interpolant derived through interpolation and collocation procedures. The methods are derived by interpolating the continuous interpolant at π₯ = π₯π+π , π = 6 and collocating the first and second derivative of the
continuous interpolant at π₯π+π , π = 0 and π = 2, 3, β¦ 5 respectively. The stability properties of the methods are discussed and the stability region shown. The methods are then applied in block form as simultaneous numerical integrators. Two numerical experiments are given to illustrate the efficiency of the new methods.
Machine learning in science and industry β day 1arogozhnikov
Β
A course of machine learning in science and industry.
- notions and applications
- nearest neighbours: search and machine learning algorithms
- roc curve
- optimal classification and regression
- density estimation
- Gaussian mixtures and EM algorithm
- clustering, an example of clustering in the opera
MIXTURES OF TRAINED REGRESSION CURVESMODELS FOR HANDRITTEN ARABIC CHARACTER R...ijaia
Β
In this paper, we demonstrate how regression curves can be used to recognize 2D non-rigid handwritten shapes. Each shape is represented by a set of non-overlapping uniformly distributed landmarks. The underlying models utilize 2nd order of polynomials to model shapes within a training set. To estimate the regression models, we need to extract the required coefficients which describe the variations for a set of shape class. Hence, a least square method is used to estimate such modes. We proceed then, by training these coefficients using the apparatus Expectation Maximization algorithm. Recognition is carried out by finding the least error landmarks displacement with respect to the model curves. Handwritten isolated Arabic characters are used to evaluate our approach.
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 New Approach to Design a Reduced Order ObserverIJERD Editor
Β
In this paper, a new method for designing a reduced order observer for linear time-invariant system is
proposed. The approach is based on matrix inversion with proper dimension. The arbitrariness associated with
the method proposed by OβReilly is presented here and has been reduced with the help of pole-placement
technique. It also helps reducing the computations regarding the observer design parameters. Illustrative
numerical examples with simulation results are also included.
Derivation and Application of Six-Point Linear Multistep Numerical Method for...IOSR Journals
Β
A six-step Continuous Block method of order (5, 5, 5, 5, 5, 5) T is proposed for direct solution of the second (2nd) order initial value problems. The main method and additional ones are obtained from the same continuous interpolant derived through interpolation and collocation procedures. The methods are derived by interpolating the continuous interpolant at π₯ = π₯π+π , π = 6 and collocating the first and second derivative of the
continuous interpolant at π₯π+π , π = 0 and π = 2, 3, β¦ 5 respectively. The stability properties of the methods are discussed and the stability region shown. The methods are then applied in block form as simultaneous numerical integrators. Two numerical experiments are given to illustrate the efficiency of the new methods.
Machine learning in science and industry β day 1arogozhnikov
Β
A course of machine learning in science and industry.
- notions and applications
- nearest neighbours: search and machine learning algorithms
- roc curve
- optimal classification and regression
- density estimation
- Gaussian mixtures and EM algorithm
- clustering, an example of clustering in the opera
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana LuΓsa Pinho
Β
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Ioβs surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Ioβs trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Ioβs surface using adaptive
optics at visible wavelengths.
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4β0.9Β΅m) and novel JWST images with 14 filters spanning 0.8β5Β΅m, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3Β΅m to construct an ultradeep image, reaching as deep as β 31.4 AB mag in the stack and
30.3-31.0 AB mag (5Ο, r = 0.1β circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 β 15. These objects show compact half-light radii of R1/2 βΌ 50 β 200pc, stellar masses of
Mβ βΌ 107β108Mβ, and star-formation rates of SFR βΌ 0.1β1 Mβ yrβ1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of βΌ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
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As consumer awareness of health and wellness rises, the nutraceutical marketβwhich includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutritionβis growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
Β
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Β
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), NiΕ‘, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
1. CHAPTER 2. DERIVATIVE
Materials :
οΆ Initial Concept of Derivative
οΆ Gradient of Function at a Point
οΆ Operation on Derivative
οΆ Derivative Mind Map
Indicators of Achievement :
1. Students are able to explain the concept of derivative correctly.
2. Students are able to determine the average velocity, instantaneous
velocity, and gradient of a function at a point using the concept of
derivative.
3. Students are able to calculate the derivative and explain the operations
that apply to the derivative of a function.
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SUB-CPMK020301 | Pertemuan 4
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Tangent Line
Tangent line of the curve π¦ = π(π₯) at point π(π₯, π π ) is a line that goes through π
with slope
π = lim
ββ0
π π₯ + Ξπ₯ β π(π₯)
Ξπ₯
= 2.5
2.1 Two Problems One Solution
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Average speed vs instantaneous speed
Suppose π(π‘) is the position of an object at time π‘, hence average velocity at time
t1 to t2 be :
π£ππ£π π‘1, π‘2 =
π π‘2 β π(π‘1)
π‘2 β π‘1
The smaller the difference between π‘1 and π‘2, we can get the "instantaneous
speed":
π£ π‘ = lim
Ξπ‘β0
π£ππ£π π‘, π‘ + Ξπ‘ = lim
Ξπ‘β0
π π‘ + Ξπ‘ β π(π‘)
Ξπ‘
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Definition of Derivatives
A function π is said to have a derivative at point π₯ if,
lim
Ξπ₯β0
π π₯ + Ξπ₯ β π(π₯)
Ξπ₯
There is and is up.
If the above limit exists, then the derivative of f at point x i.e. fβ²(x) is equal
to the limit value above. The form of the limit above is equivalent to,
πβ² π = lim
xβπ
π π₯ β π(π)
x β c
Here are some notations for derivatives of f at point x,
πβ²
π₯ π·π₯π(π₯)
π
ππ₯
π(π₯)
π(π π₯ )
ππ₯
2.2 Derivative
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If f has a derivative at point x=c, then f is continuous at point x=c.
If f is not continuous at point x=c, then f has no derivative at point x=c.
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Constant Function Rules
If π π₯ = π, where k is a constant, then for any x,πβ²
π₯ = 0.
Identity function rules
If f x = π₯, maka πβ²
π₯ = 1
Rank Rules
If π π₯ = π₯π
, with n rational numbers, thenπβ²
π₯ = ππ₯πβ1
Constant Multiplier Rules
ππ β² π₯ = π β πβ² π₯ , with k a constant
Addition and subtraction rules
π β π β² π₯ = π π₯ πβ² π₯ + πβ² π₯ π π₯
Division Rules
π
π
β²
π₯ =
π π₯ πβ²
π₯ β π π₯ πβ²(π₯)
π2(π₯)
, πβ²
π₯ β 0
2.3 Rules for searching derivative
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Trigonometric Derivatives
The sin x and cos x functions are differentiated across real numbers with
π·π₯ sin π₯ = cos π₯
π·π₯ cos π₯ = β sin π₯
Advanced Trigonometric Derivatives
The derivative of the trigonometric function below can be obtained from the derivative
rules in the previous chapter and utilizes the basic derivative of trigonometry
π·π₯ tan π₯ = sec2
π₯
π·π₯ cot π₯ = β csc2
π₯
π·π₯(sec π₯) = sec π₯ tan π₯
π·π₯ csc π₯ = β csc π₯ cot π₯
2.4 Derivatives of Trigonometric Functions
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Example, π¦ = π π’ and π’ = π π₯ .
π β π β² π = πβ² π π β πβ² π
Or
ππ¦
ππ₯
=
ππ¦
ππ’
β
ππ’
ππ₯
Example:
Asked to look for derivatives of π₯2 + 3π₯ 3
π¦ = π’3, π’ = π₯2 + 3π₯
So
ππ¦
ππ₯
= 3 π₯2
+ 3π₯ 2
β 2π₯
2.5 Chain Rules
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Derivatives of Order 2 and 3
The second and third derivatives of the function f at point x are respectively
written πβ²β²
π₯ and πβ²β²β²
(π₯) where πβ²β²
(π₯) is obtained by deriving πβ²
(π₯) once and
πβ²β²β²
(π₯) is obtained by decreasing πβ²β²
(π₯) once again.
Derivatives of Order More than 3
The nth derivative of the function f at point x is written in the form π π
(π₯).
2.6 Higher Order derivatives
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Implicit derivative y with respect to x.
For example, given the function of two variables f, g, and a curve equation
π π₯, π¦ = π π₯, π¦
Can we determine the derivative of y to x?
We can proceed by considering y as a function of x (in other words, π¦(π₯)), and
deriving both segments of this equation to x. These are referred to as implicit
derivatives.
2.7 Implicit Derivatives
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Example, Suppose we are asked to specify
ππ¦
ππ₯
from the following equation:
π₯π¦ = π₯2
+ π¦2
π
ππ₯
π₯π¦ =
π
ππ₯
π₯2
+ π¦2
We apply the multiplication rule to the left field, and the addition rule to the right field
π
ππ₯
π₯ β π¦ + π₯ β
π
ππ₯
π¦ =
π
ππ₯
π₯2 +
π
ππ₯
π¦2
Since we think of y as a function of x, we need to apply the chain rule to
π
ππ₯
π¦2 .
1 β π¦ + π₯ β
ππ¦
ππ₯
= 2π₯ + 2π¦ β
ππ¦
ππ₯
π₯ β
ππ¦
ππ₯
β 2π¦ β
ππ¦
ππ₯
= 2π₯ β π¦
ππ¦
ππ₯
=
2π₯ β π¦
π₯ β 2π¦
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Rate-related problem-solving strategies,
In general, the steps that can be done:
1. Create simple modeling
2. Determine variables and the relationship between variables
3. Calculate the implicit derivative
4. Search according to what is asked
2.8 Related Rate
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Approximation
Approximation with differentials is carried out by approaching Ξπ¦ with
ππ¦ = πβ² π₯ ππ₯
Ξy β ππ¦
π π₯ + Ξπ₯ β π(π₯) β πβ² π₯ ππ₯
π π₯ + Ξπ₯ β π π₯ + πβ²
π₯ Ξx
2.9 Approximation
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Example: Use differential to approximate 4.5 !
Suppose π π₯ = π₯ . We are asked to
approach 4.5 = π 4 + 0.5
π 4 + 0.5 β π 4 + πβ²(4) β 0.5
Then we need to find out first.πβ²
4 .
π π₯ = π₯ = π₯
1
2 βΉ πβ²
π₯ =
1
2 π₯
πβ²
4 =
1
2.2
=
1
4
So 4.5 β 2 +
1
4
β 0.5 = 2.215
We can use this technique to approach the
roots of other things. For example 5 with
ππ₯ = 1 . But of course, the approximate
results will be less accurate as the ππ₯ gets
bigger.
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Specify the turnan of the following functions:
1. 2π₯3 + 3π₯
2. 4π₯3
+ π₯ β 5 π₯2
+ 2π₯
3.
π₯2+1
2π₯β1