- TEACH NUMBERS AND COUNTING: The Montessori approach recognizes that a child’s potential for learning is greatest when provided with tactile, multisensory tools. Counting Peg Boards capitalize on this concept by helping children grasp the concept of numbers at an early age through sight recognition and the use of wooden counting pegs.
- QUALITY & LONGEVITY: You can count on these Counting Peg Boards lasting through the preschool years and beyond! They are crafted of durable hardwood, and coated with a child-safe lacquer for a smooth, beautiful, lasting finish. Made from high-quality, sustainably harvested rubberwood.
- MONTESSORI TEACHER APPROVED: Children can practice counting and developing early math skills with these hands-on, natural wooden counting peg boards. This educational material introduces children to the concept of one-to-one correspondence between name, quantity and numeral, and can be adapted in many ways as your child progresses through his or her math curriculum.
- STORAGE BAG AND BOX INCLUDED: The storage box neatly holds all 10 wooden counting boards and the canvas drawstring bag holds the pegs, making it easy to present this activity on a shelf or take it on the go.
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Montessori & Me Counting Peg Boards are a fun and intuitive way to help toddlers grasp the concept of one-to-one correspondence, or the idea that numbers correspond to specific quantities. This beautiful set includes 57 colorful counting pegs and 10 number boards that help children develop mathematical concepts, fine motor skills, and concentration from a very early age.
Carefully crafted from natural materials with a safe, non-toxic finish, Montessori & Me Counting Peg Boards are made to last a lifetime, while providing endless value.
This set includes:
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Explore, play and learn at KidsMuseum Children’s Museum, a hands-on, interactive museum for children and families designed to engage kids from birth to age eight. KidsMuseum exhibits and programs integrate science, technology, engineering, art and math for whole-body, whole-brain learning.
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In Python, “//” is an operator which stands for floor division in Python, also known as integer division. It divides one integer by another and then rounds off the quotient to the nearest whole number.
It lies under the arithmetic operators in Python. Similarly, many other operators are used in Python programming.
These operators help to build the code and provide the functionality to it. These operators are divided into categories like arithmetic operators, comparison operators, logical operators, identity operators, and many more.
So let’s discuss all the types of operators in Python with their signs and uses.
The Role of Operators in Python
In Python, operators play a fundamental role in performing various operations on data, variables, and values. These operators are symbols or special keywords that allow you to manipulate and interact with different types of data in a concise and efficient manner.
Python supports a wide range of operators, including arithmetic operators (such as +, -, *, /), comparison operators (like ==, !=, <, >), logical operators (such as and, or, not), assignment operators (like =, +=, -=), and more.
These operators enable you to perform tasks like mathematical calculations, making decisions based on conditions, combining and manipulating strings, and much more.
Understanding and effectively using operators is essential for writing efficient and expressive Python code, as they form the building blocks for performing diverse operations within programs.
Types of Operators in Python
Arithmetic operators in Python perform arithmetic functions in a program like Addition, subtraction, division, etc. Here are the arithmetic operators present in Python.
- Unary Addition: “+” is called the unary positive operator. The use of the unary operator looks like “+a.” However, it doesn’t add any meaning to the code. It is similar to writing 1 as +1 in everyday mathematics.
- Unary Negation: “-” is called the unary Negation. It is used to write a negative term in Python. For example, “-a” is the negative of a, as the only change here is the sign.
- Addition: “+” is the addition operator in Python. It is used for Addition in Python, such as “a+b.”
- Subtraction: “-” is the subtraction operator in Python used for subtraction. For example, “a-b,” here b will get subtracted from a.
- Multiplication: “*” is the multiplication operator in Python. It is used for multiplication, such as “a*b.”
- Division: “/” is known as the division operator. It divides one integer by another. For example, “a/b.”
- Floor Division in python: “//” is also a division operator. However, when a//b, the quotient will get rounded off to the nearest whole number.
- Modulus: “%” also acts as a division operator, but as a result, it declares the remainder and not the quotient.
- Exponentiation: “**” is used to raise a number to a power. For example, a**b is equal to ab.
- Equal to: “==” compares two numbers and states them as equal. For example, a==b.
- Not equal to: “!=” Is the operator which compares two numbers and states them as unequal. For example, a!=b.
- Greater than: “>” is used to compare a bigger number on the left to a smaller number on the right. For example, a>b.
- Less than: “< “is used to compare a smaller number on the left to a bigger number on the right. For example, a<b.
- Greater than or equal to: “>=” is used for a greater or equal number on the left. For example, a >= b.
- Less than or equal to: “<=” is used for a lesser or equal number on the left. For example, a <=b.
Logical operators in Python are used for performing logical operations on boolean values or expressions. Boolean values are the values that can either be true or false.
Moreover, based on the combination of logical operators with boolean values, the flow of the program is controlled.
- Logical AND: “and” logical operator returns true only if both the operands are true. Otherwise, it returns false if any of the two operands is false or both are false.
- Logical OR: “or” operator returns true if any of the two operands is true. Moreover, it only returns false if both operands are false.
- Logical NOT: “not” operator is used to negate the boolean value. If the operand is true, the result will be false. Similarly, if the operand is false, the result will be true. Exactly the opposite of the initial state of the boolean value.
As the name suggests, bitwise operators operate on operands bitwise. Here are the bitwise operators in Python.
- Bitwise AND (&): Performs a bitwise AND operation on individual bits of two integers. It sets each bit to 1 only if both corresponding bits in the operands are 1.
- Bitwise OR (|): Performs a bitwise OR operation on individual bits of two integers. It sets each bit to 1 if at least one of the corresponding bits in the operands is 1.
- Bitwise XOR (^): Performs a bitwise exclusive OR (XOR) operation on individual bits of two integers. It sets each bit to 1 if only one of the corresponding bits in the operands is 1.
- Bitwise NOT (~): Performs a bitwise NOT operation (complement) on individual bits of an integer. It inverts all the bits, turning 0s into 1s and 1s into 0s. The result is the two’s complement representation of the negative of the number minus one.
- Left Shift (<<): Shifts the bits of an integer to the left by a specified number of positions. It effectively multiplies the integer by 2, raised to the power of the shift amount.
- Right Shift (>>): Shifts the bits of an integer to the right by a specified number of positions. It effectively divides the integer by 2, raised to the power of the shift amount, discarding the remainder.
What is Binary Search Python?
Binary search Python algorithm is used to search for an element’s position in a sorted array. Binary search Python algorithms can be of two types: iterative and recursive.
Here is an example of the binary search Python algorithm.
- Binary Search Python (Iterative)
Sorted Array: [2, 5, 8, 12, 16, 23, 38, 45, 56, 72, 91]
Target Element: 23
Operators in Python are important components to write code. Learning about all the operators in Python is necessary to write correct and concise codes.
Moreover, you should also know these operators’ meanings and proper use. Otherwise, it may lead to errors while running the program. So, keep learning and keep coding.


Specification ... Mark schemes (6) Question papers Component "component" Paper 1 (2) Paper 2 (2) Paper 3 (2) Exam Series (1) ... June 2017. June 2017 Question papers, mark schemes and reports on the exam. ... AQA GCSE Mathematics (8300) June 2017: Paper 3: Calculator 8300/3H – Higher: Q A: AQA: AQA GCSE Mathematics A (4360) June 2016: Edexcel GCSE Maths June 2017. 8300. 2H Paper Mark Scheme Solutions Video Solutions. 1H Paper Mark Scheme Solutions. This material is for teachers only. Find recent GCSE past papers from AQA. Download our collection of AQA GCSE 9-1 Maths Past Papers & Mark Schemes. GCSE Mathematics. Download the question papers, mark schemes and reports on the exam for the June 2017 exams below. Practice Papers GCSE Statistics Foundation Tier (43101F) Mark Scheme June 2017 ♥ (1) Download file (547.2k) Pure Core 3 Mark Scheme June 2006. AQA GCSE Higher Paper 1 June 2017 (8660) mark scheme. aqa-exam-board-gcse-past-papers 1/1 Downloaded from registroperspectivas.clave.com.ec on December 27, 2020 by guest AQA GCSE Maths: Higher-Stephen Fearnley 2015-11-05 Please note this title is suitable for any student studying: Exam Board: AQA Level: GCSE Subject: Mathematics First teaching: September 2015 First exams: June 2017 AQA GCSE Maths, Higher Student Book has been approved by AQA … MARK SCHEME – GCSE MATHEMATICS – 8300/1H – JUNE 2017 3 Glossary for Mark Schemes GCSE examinations are marked in such a way as to award positive achievement wherever possible. In this area you will find PDF copies of the GCSE 8300 question papers, mark schemes and reports on the exam from June 2017. These are available to you completely free of charge. Download file (206.7k) Related resources: June 2017 Level 3 Mathematical Studies question papers, mark schemes and reports on the exam. Thus, for GCSE Mathematics papers, marks are awarded under various categories. You can download each of the AQA GCSE past papers and Mark Schemes and Specifications. AQA GCSE Higher Paper 1 June 2017 (8660) worked solution. Thus, for GCSE Mathematics papers, marks are awarded under various categories. Mock exam analysers for these papers are also available. Download & use today. MARK SCHEME – GCSE MATHEMATICS – 8300/2F – JUNE 2017 3 Glossary for Mark Schemes GCSE examinations are marked in such a way as to award positive achievement wherever possible. Mock Exam Analysers for these papers are available here.
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Good Morning folks, I got a big doubt in my mind and need your help in clarifying it…
I was getting ready for the school today morning and while getting dressed up, its my favorite game to play with the fan regulator..while playing today, I got a doubt that why cant we have a 10 speed fan. Don’t you all agree that it would be fun to have a 10 speed fan? So I started asking all the questions about the fan to my mom, as to who gave the fan to us and why did he use only 5 speed motor? If that person or the inventor as my mom calls him, gives us a 10 speed motor, then it would become easier for my teacher aunty to teach numbers to kids like us na..she can make each one of us sit next to the regulator and then ask us to change the regulator to various numbers, that way we can learn all the numbers in one single day. Then we can watch the number videos or color the numbers later, but we would know how to recognize all the numbers in one single day isn’t it?
It was such a simple task to teach numbers to the kids with the regulator, if I become big like Swati aunty (my teacher in the school), then I would definitely put 5-6 regulators in the class room and teach the kids using the regulators, which would make my life happier and I don’t have to shout asking kids to watch videos so my throat would be happy and I don’t have to drink water 3-4 times in the class.
Don’t you all agree with me, that its such a simple task, in my mommy’s words, its very simple my dear Watson….(please don’t ask me who that Watson is?, my mommy never explained me so far about Watson, I need to ask her one day about it. The moment she tells this statement to me, I love the expression on her face so would always end up hugging her and kissing her…so in that whole process I would forget to question her who is this Watson…so in case you guys know this Watson story, please do tell me OK? when you would tell me is your choice, by buzzing me or mailing me)
Chalo then, so far so good, will talk to you later..and meet you real soon, please wait for me next story OK????


The Mathematical Challenge for Filipino Kids Training Program (MCFKTP)
The MCFKTP is the first stage of the MTG intensive and comprehensive training program for mathematically gifted elementary and high school students. The program supplements and enriches the existing mathematics curriculum and programs in the country.
The MCFKTP has a total of 12 Saturday sessions that are usually conducted for 3 hours within the academic year. It challenges students with a variety of activities, including specialized topics in mathematics like Number Theory, Combinatorics, Non-Euclidean Geometry and Higher Algebra, Integration of Complex Numbers in other fields of Mathematics and the latest problem solving strategies. This program aims to initially prepare and expose them to international math competitions through correspondences. Furthermore, this stage develops their higher order thinking skills to be globally competitive as they foster national/international brotherhood
Young Mathematicians’ In-House Intensive Training Program (YMIITP)
All the successful trainees of the MCFKTP are invited to attend the four to five days in-house intensive training program. After lectures have been provided, trainees are evaluated through assignments and a battery of quizzes and examinations. The top scorers are selected on the basis of their over-all remarkable performance which includes attitudes/behavior, while the alternates will be decided upon by the screening committee based on the results of the written outputs, presentation of solution and character traits. Both the top scorers and the alternates are potential representatives of the Philippine teams provided they will attend the next and last phase of the training program.
Mathematical Olympiad Summer Training Program (MOSTP)
The summer enhancement program is compulsory to all successful MTG YMIITP trainees who eventually will represent the Philippines in different international mathematics competitions. The training is usually scheduled for three to four weeks.
Within the weeks’ schedule, the contest committee will conduct about 10 to 12 sets of test to enable them to identify the performance of each participant and use her/his overall performance as a reference for the selection of team members who will be sent to the international competitions.


How do you calculate the hydraulic horsepower of a pump? To find the input horsepower requirement for a hydraulic pump, use this hydraulic pump horsepower formula:
Pump Calculations, Pump Equations. Liquid Gallon = 3.26417 US Liquid Gallons 1 Cubic Foot = 7.31 How do I calculate Brake Horsepower Required for a
Water Horsepower is the energy or power added to water by the pump. Calculate the HP, Flow Rate or Discharge, and Total Head using this simple online calculator.
Horsepower for driving a pump: For every 1 hp of drive, the equivalent of 1 gpm @ 1500 psi can be produced. Horsepower for idling a pump:
PUMP SYSTEM FORMULAS (METRIC UNITS) (change to Imperial units) This page contains many applets to help you do calculations and to SAVE YOU TIME.
Vacuum Pump Power Calculation. different pumps can be obtained by calculating the cfm of free air removed per horsepower. Or input horsepower can be compared
Calculate Brake Horsepower Explains basic formula format, discusses elements; Pump Water Horsepower, How to calculate hydraulic horse power
This formula may also be used to calculate the horsepower The French Navy used the same definition of nominal horse power as the water pump, and
Complete playlist of Wastewater Dan’s Math Solutions. This is the Pump Performance And Efficiency Calculations presentation in my series of “Math Solutions.”
VALUABLE PUMP FORMULAS Pressure Pipe Velocity Centrifugal Pumps Rotary Positive Displacement Pumps Approximate RPM @ Full Load - for medium sized motors
An example to demonstrate required pump power calculations based on - required pressure drop, given flow rate and estimated pump efficiency.
Advanced Fluid Systems Leave only one field open in each formula and click the “Calculate” button for the result of that field. Hydraulic Pump and Motor Formulas
This is a theoretical calculation based on the pump working at rate and pressure of the mud pump. Total hydraulic horsepower is Wellsite math:
The “head” form of the Engineering Bernoulli Equation is obtained Assuming the pump is 85% efficient, calculate the BHP (Brake Horse Power) of the pump
Defintion of Brake Horsepower in a Centrifugal Pump application
Submersible Pump Sizing & Selection First, let’s calculate friction loss! You’ll need 1.5kW per motor HP So…a 5HP pump needs a minimum of 7.5kW
Fuel pump FLOW - Forced Induction (E85) 0. Lph. 0. Bar. Calculators Injector Flow Calculator Injector HP/KW Rating Calculator Injector Flow VS Fuel Pressure Calculator
Calculate the Brake Horsepower by putting the values for Flow rate or discharge (Q), total head (H) and pump efficiency (n) and applying the formula through advanced
What is the formula of brake horsepower (BHP) and indicated horsepower (IHP)? water pump, or other accessories How do you calculate horsepower if only BHP is
Horsepower on the pump curve Brake horsepower is the actual horsepower delivered to the pump shaft. The formula for figuring brake horsepower is:
? n by the pump manufacturer calculate required BHP, knowing E pump Water horsepower is defined as: the head loss equation


In probability and statistics, the expectation or expected value, is the weighted average value of a random variable. Example Involving Probability Distributions & Expected Value. Example. If the table below represents the PDF of the random variable X, find E(X) (the expected. Definition of expected value & calculating by hand and in Excel. again, your expected payoff (gain) is $1 each time you play, as shown by the following table. B6 into the cell where Nursing degree university Lisa, If you follow the steps in this how-to, you can skip using the formula. Generally, real world situations are not as easily definable as something like rolling dice or drawing cards. Turning Https://www.allmystery.de/themen/mg30125-8 Into Information Expected value table casino bremen poker von 11 12 2017 To find the partial value due to each outcome, multiply the value of the outcome times its bus simu. A discrete random variable is odd deutsch random neon games online that can only take on rtl de gewinnspiel certain number of values. It was first devised in the 17th century to analyze gambling games and answer questions such as: Definition Let be a sample space , a probability measure defined on the events of and a random variable defined on. These topics will be presented here: A fair six-sided die is tossed. Over many many draws, the theoretical value to expect is 6. For instance, if you play the game times, win 50 times and lose the remaining 50, then your average winning is equal to the expected value: This section introduces a general formula for computing the expected value of a random variable. Knowing how to calculate expected expected value table can be useful in numerical statistics, in gambling or other south lake tahoe casino of probability, in stock market investing, or in many other situations that have a magic theme of outcomes. A stronger linearity property holds, which involves two or more random variables. Other times, wm quali 2018 the case of a model, you may need to assign a value or score that represents monetary amounts. Generally, real world situations are not as easily definable as something like rolling dice or drawing cards.


Everything about Money To Bitcoin
Let's say you had one legit $20 and one quite good photocopy of that same $20. If someone were to try to spend both the true bill and the imitation one, someone who took the problem of looking at either of those bills' serial numbers would observe that they were exactly the exact same number, and consequently one of them needed to be false.
That isn't a great analogy--we will explain in more detail below. .
Once a miner has verified 1 MB (megabyte) worth of Bitcoin transactions, they are entitled to win the 12.5 BTC. The 1 MB limit was established by Satoshi Nakamoto, and can be a matter of controversy, as some miners believe the block size ought to be increased to accommodate more data.
Note that I said that verifying 1 MB worth of transactions makes a miner qualified to earn Bitcoin--not everyone who supports transactions will receive paid off.
1MB of transactions can technically be little as 1 transaction (though this is not at all common) or several thousand. It depends on how much data the transactions take up.
In order to earn Bitcoin, you need to meet two conditions. One is a matter of work, one is a matter of luck.
2) You must be the first miner to reach the right answer to some numeric problem. This process is also known as a proof of work.
The fantastic news: No advanced math or computation is involved. You may have discovered that miners are solving challenging mathematical problems--that is not true at all. What they are actually doing is trying to be the first miner to come up with a 64-digit hexadecimal number (a"hash") that is less than or equal to the target hash.
Indicators on Bitcoin Mining Code You Need To
The bad news: Because it is guesswork, you need a good deal of computing power in order to get there first. To mine , you need to have a higher"hash speed," that is measured in terms of megahashes per second (MH/s), gigahashes per second (GH/s), and terahashes per second (TH/s).
If you want to estimate how much Bitcoin you could mine with your mining rig's hash pace, the website Cryptocompare offers a very helpful calculator.
Either way a GPU (graphics processing unit) miner or an application-specific integrated circuit (ASIC) miner. These can run from $500 to the tens of thousands. Some miners--especially Ethereum miners--purchase individual graphics cards (GPUs) as a low-cost method to cobble together mining operations. The photo below is a makeshift, home-made mining machine. The cards are those rectangular cubes with whirring circles. Note the sandwich twist-ties holding the graphics cards into the metal pole.
Case in point : I tell three friends I'm thinking about a number between 1 and 100, and that I write that number on a sheet of paper and seal it in an envelope. My friends don't need to guess the exact number, they simply have to be the very first person to guess any number that's less than or equal to the number I'm thinking Visit This Link of.
Rumored Buzz on Bitcoin Mining Code
Let us say I am thinking of the number 19. If Friend A guesses 21, they shed because 21>19. If Friend B guesses 16 and Friend C supposes 12, then they've both theoretically arrived at workable answers, since 16<19 and 12<19. There is no"extra credit" for Friend B, even though B's answer was closer to the goal answer of 19. .
In Bitcoin conditions, simultaneous answers occur frequently, but in the end of the day there can only be one winning answer. When multiple simultaneous answers are presented that are equal to or less than the target number, the Bitcoin network will decide by a simple majority--51 percent --which miner to honour. Typically, it's the miner that has done the most work, i.e.
The losing click site block then becomes an"orphan block" .
Now imagine that I pose the"guess what number I am thinking of" question, but I'm not asking just 3 friends, and I'm not thinking of a number between 1 and 100. Instead, I'm asking millions of prospective miners and I'm thinking about a 64-digit hexadecimal number. Now you see that it's going to be extremely hard to guess the ideal answer.
Getting My Bitcoin Mining Code To Work
The number above has 64 digits. Easy enough to understand up to now. As you probably noticed, that number consists not only of numbers, but also letters of the alphabet. Why is that
In order to understand these letters are doing in the center of numbers, let's unpack the term"hexadecimal."
As you know, we utilize the"decimal" system, which means it is base 10. This in turn means that each and every digit has 10 possibilities, 0-9.


Title：Ellipticity of the Bartnik Boundary Conditions
Speaker：Zhongshan An（University of Connecticut）
Place：Room 5406, The 5th Teaching Building, East Campus
Abstract：The Bartnik quasi-local mass is defined to measure the mass of a bounded manifold with boundary, where a collection of geometric boundary data — the so-called Bartnik boundary data— plays a key role. Bartnik proposed the open problem whether, on a given manifold with boundary, there exists a stationary vacuum metric so that the Bartnik boundary conditions are realized. In the effort to answer this question, it is important to prove the ellipticity of Bartnik boundary conditions for stationary vacuum metrics. In this talk, I will start with an introduction to the Bartnik quasi-local mass and the moduli space of stationary vacuum metrics. Then I will explain the ellipticity result for the Bartnik boundary conditions and, as an application, derive a local result to the existence question.


Trigonometry helps to calculate values of the sides of right triangles once another angle (other than the right angle) is known.
Among the scientific fields that make use of trigonometry are these:
acoustics, architecture, astronomy (and hence navigation, on the oceans, in aircraft, and in space; in this connection, see great circle distance), biology, cartography, chemistry, civil engineering, computer graphics, geophysics, crystallography, economics (in particular in analysis of financial markets), electrical engineering, electronics, land surveying and geodesy, many physical sciences, mechanical engineering, machining, medical imaging (CAT scans and ultrasound), meteorology, music theory, number theory (and hence cryptography), oceanography, optics, pharmacology, phonetics, probability theory, psychology, seismology, statistics, and visual perception, education. From here.
The names of the three primary trigonometry functions are:
- sine: The value for the sine of angle A is defined as the value that you get when you divide the opposite side by the hypotenuse.
- cosine: The value for…
View original post 336 more words


A sixteen year old student, Shouryya Ray, is the first person to solve a mathematical problem posed by Sir Isaac Newton more than 300 years ago. The clever teen has also solved a second problem dealing with the collision of a body with a wall, posed in the 19th Century.
Due to his efforts, scientists can now calculate the flight path of a thrown ball and then predict how it will hit and bounce off a wall. He has solved two theories physicists have previously been unable to calculate without the use of powerful computers.
Shouryya said his natural curiosity and schoolboy naivety helped him solve the problems. When professors said the problems had no solutions, he thought he'd have a go.
Born in India, his father instilled in him a "hunger for mathematics" and taught him calculus at the age of six. His family moved to Germany when he was 12, after his father, an engineer, was offered employment at a technical college. His father Subhashis said his son's mathematical prowess quickly outstripped his own considerable knowledge and the maths involved in solving both problems were far beyond his capabilities.
Shouryya says he's no genius and wishes he were better at sports, particularly football. But teachers were quick to recognize his superior intelligence and he was moved up two years in school and this week, he will sit Germany's high school leaving exams, two years ahead of his peers.
Countries around the world will be head-hunting this brilliant young man, who says he has always enjoyed the "intrinsic beauty" of maths.


To safeguard users from unnecessary liquidation triggered by abnormal market price, Mark Price is introduced to calculate the UPL.
The Mark Price is the price at which the contract is marked for unrealized PNL and liquidation purposes.
As for perpetual contract, the Mark Price is equal to the Index Price plus the Moving Average of Basis.
Please note that the mark price will not influence the realized PNL.
Funding Basis Rate = Funding Rate *( time of the next funding payment/ time interval of funding payment)
Mark Price = Index Price * (1+Funding Basis Rate)


Virtus et Integritas
T: Telephone02 9825 9815
The study of mathematics develops the students’ ability to meet the demands of life at home and work and for participation in community and civil life. Students study number and patterns and algebra, algebraic, techniques and equations, angles and parallel lines, fractions, decimals, time, and length. In conjunction with these topics, we incorporate working mathematically where students engage in mathematical activity and develop skills to become flexible and creative users of mathematics.
Following are the links for maths related resources:
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Copyright for this website is owned by the State of New South Wales through the Department of Education. For more information go to http://www.dec.nsw.gov.au/footer/copyright.


While it’s possible to look up probabilities for a normal distribution using thez-table, it’s actually much easier to calculate probabilities in Excel for a couple of reasons. First, there’s no looking at a table; the NORMDIST function does the hard work for you. Second, Excel does the intermediate calculations for you. Most calculation errors happen in an intermediate step (such as calculating the z-score to look up) rather than the actual z-score itself. Excel can handle three types of probability calculations: more than, less than, and in between. These instructions work for Excel 2007 and Excel 2010.
Sample Question: Suppose that a contaminant in samples from a city’s water supply has a meanof 500 ppm and a standard deviation of 100 ppm. What is the probability that bacteria in a randomly selected water sample will be: 1/ less than600 ppm 2/More than 600 ppm 3/between 400 and 600 ppm?
Calculate Normal Distribution Probability in Excel: Less than
Click an empty cell.
Click “Insert Formula”.
Type “Normdist” into the search box and then click “Go.”
Select “NORMDIST” from the list and then click “OK” to open the Function Arguments window.
Enter your data into the box. For this example, type “600” in the X box, “500” in the Meanbox, “100” in the Standard Deviation box and “true” in the cumulative box..
Click “OK.”. This returns 0.84134474 in the cell you clicked in Step 1, which is the probability of getting under 600 ppm.
Calculate Normal Distribution Probability in Excel: More than
Subtract your answer from Step 7 (above) from 1:
Calculate Normal Distribution Probability in Excel: Between
Repeat Steps 1 through 8 for the second value, which for this example is 400. The probability is 0.15865526.
Subtract the larger probability from the smaller probability. In this example:
0.84134474 – 0.15865526 = 0.68269


Body Mass Index can be calculated using pounds and inches with this equation
(Height in inches) x (Height in inches)
For example, a person who weighs 220 pounds and is 6 feet 3 inches tall has a BMI of 27.5.
( 220 lbs.
(75 inches) x (75 inches)
) x 703 = 27.5
Body Mass Index can also be calculated using kilograms and meters (or centimeters).
(Height in Meters) x (Height in Meters)
|BMI = (||
(Height in centimeters) x (Height in centimeters)
|) x 10,000|
For example, a person who weighs 99.79 Kilograms and is 1.905 Meters (190.50 centimeters) tall has a BMI of 27.5.
(1.905 m) x (1.905 m)


Published 1987 .
Written in EnglishRead online
|The Physical Object|
|Number of Pages||167|
Download Bayesian analysis of directional data.
Although this makes Bayesian analysis seem subjective, there are a number of advantages to Bayesianism. It tends to permit more direct conclusions about parameters than the frequentist approach and, once a prior is established, estimation. (). A Bayesian Analysis of Directional Data Using the von Mises–Fisher Distribution.
Communications in Statistics - Simulation and Computation: Vol. 34, No. 4, pp. Cited by: Winner of the De Groot Prize from the International Society for Bayesian analysis of directional data.
book Analysis. Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research by: (). A Bayesian analysis of the change-point problem for directional data. Journal of Applied Statistics: Vol.
35, No. 6, pp. Cited by: 9. In this paper, we discuss a simple fully Bayesian analysis of the change-point problem for the directional data in the parametric framework with von Mises or circular normal distribution as the underlying distribution. We first discuss the problem of.
A little more than 15 years ago, I picked up the first edition of this book and learned Bayesian data analysis from it.
The topic is introduced from a practical perspective designed for someone who wants to use these methods for data analysis applied to real problems. This relatively small book clearly, cogently, and pleasantly covers the Reviews: Bayes and Empirical Bayes Methods for Data Analysis, Second Edition Bradley and Thomas Bayesian Data Analysis, Second Edition Andrew Gelman, JohnHaland Donald Beyond ANOVA—Basics of Applied StatisticsJr.
‘Bayesian Methods for Statistical Analysis’ is a book onstatistical methods for analysing a wide variety of data.
The consists of book 12 chapters, starting with basic concepts and numerous topics, covering including Bayesian estimation, decision theory, prediction, hypothesis. Introduction to Bayesian Analysis Lecture Notes for EEB z, °c B.
Walsh As opposed to the point estimators (means, variances) used by classical statis- tics, Bayesian statistics is concerned with generating the posterior distribution of the unknown parameters given both the data.
The second edition of Bayesian Analysis with Python is an introduction to the main concepts of applied Bayesian inference and its practical implementation in Python using PyMC3, a state-of-the-art probabilistic programming library, and ArviZ, a new library for exploratory analysis of Bayesian models.
Chapter 3 Computational Bayesian data analysis. In the previous chapter, we learned how to analytically derive the posterior distribution of the parameters in our model. In practice, however, this is possible for only a very limited number of cases.
Bayesian Analysis Of Linear Models Bayesian Analysis Of Linear Models by Broemeling. Download it Bayesian Analysis Of Linear Models books also available in PDF, EPUB, and Mobi Format for read it on your Kindle device, PC, phones or tablets.
In addition, this text isideal Bayesian analysis of directional data. book students in graduate-level courses such as linear models, econometrics, andBayesian inference.
This book collects important advances in methodology and data analysis for directional statistics. It is the companion book of the more theoretical treatment presented in Modern Directional Statistics (CRC Press, ).
The field of directional statistics has received a lot of attention due to demands from disciplines such as life sciences or machine learning, the availability of massive data. Preface. This book is intended to be a relatively gentle introduction to carrying out Bayesian data analysis and cognitive modeling using the probabilistic programming language Stan (Carpenter et al.
), and the front-end to Stan called brms (Bürkner ).Our target audience is cognitive scientists (e.g., linguists and psychologists) who carry out behavioral experiments, and who are.
Data analysis. We focus on iEEG data 10 s before seizure onset times at the region G Following Burns et al. (), we divided iEEG time series into segments of 1-second length and applied the MODDM to each segment independently.
We selected the directional network edges using the FDR of 5% so that the ensuring networks have sparse. If you’re interested in learning more about the Bayesian approach, there are many good books you could look into.
John Kruschke’s book Doing Bayesian Data Analysis is a pretty good place to start (Kruschke ), and is a nice mix of theory and practice.
His approach is a little different to the “Bayes factor” approach that I’ve. Bayesian methods play a role central to the future of data and knowledge integration in the field of Bioinformatics. This book is devoted exclusively to Bayesian methods of analysis for applications to high-throughput gene expression data, exploring the relevant methods that are changing Bioinformatics.
Book Description. Winner of the De Groot Prize from the International Society for Bayesian Analysis. Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data.
Bayesian Data Analysis Second Edition Bayesian Data Analysis Second Edition by Andrew Gelman. Download it Bayesian Data Analysis Second Edition books also available in PDF, EPUB, and Mobi Format for read it on your Kindle device, PC, phones or tablets.
Incorporating new and updated information, this second edition of THE bestselling text in Bayesian data analysis continues to. The likelihood is how we will introduce data in our analysis. It is an expression of the plausibility of the data given the parameters. The posterior distribution is the result of the Bayesian analysis and reflects all that we know about a problem (given our data and model).
The posterior is a probability distribution for the parameters in our. Data from examples in Bayesian Data Analysis. References to tables, figures, and pages are to the second edition of the book except where noted.
We thank Kjetil Halvorsen for pointing out a typo. The book includes the following data sets that are too large to effortlessly enter on the computer. New techniques are introduced into the Bayesian modeling procedure to estimate directional wave spectra based on ship motion data.
In the proposed method, the triple-valued function problem in following seas is strictly taken into account and the optimum solution is obtained from the stochastic viewpoint.
Bayesian Data Analysis Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Donald B. Rubin Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data.
The electronic version of the course book Bayesian Data Analysis, 3rd ed, by by Andrew Gelman, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Donald Rubin is available for non-commercial purposes. Hard copies are available from the publisher and many book stores. See also home page for the book, errata for the book, and chapter notes.
Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS provides an accessible approach to Bayesian data analysis, as material is explained clearly with concrete examples. The book begins with the basics, including essential concepts of probability and random sampling, and gradually progresses to advanced hierarchical modeling.
Incorporating new and updated information, this second edition of THE bestselling text in Bayesian data analysis continues to emphasize practice over theory, describing how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective.
Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses 4/5(3).
An Introduction to Bayesian Analysis: Theory and Methods - Ebook written by Jayanta K. Ghosh, Mohan Delampady, Tapas Samanta. Read this book using Google Play Books app on your PC, android, iOS devices. Download for offline reading, highlight, bookmark or take notes while you read An Introduction to Bayesian Analysis: Theory and Methods.
Andrew Gelman and his coauthors, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Don Rubin, have now published the latest edition of their book Bayesian Data and Aki are newcomers to the authors’ list, with an extended section on non-linear and non-parametric models.
I have been asked by Sam Behseta to write a review of this new edition for JASA (since Sam. Doing Bayesian Data Analysis - A Tutorial with R and BUGS.
Genuinely accessible to beginners, with broad coverage of data-analysis applications, including power and sample size planning. Complete analysis programs. Bayesian Data Analysis describes how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective.
Using examples largely from the authors' own experiences, the book focuses on modern computational tools and obtains inferences using computer simulations. Its unique features include thorough discussions of the methods for. Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Edition 2 - Ebook written by John Kruschke.
Read this book using Google Play Books app on your PC, android, iOS devices. Download for offline reading, highlight, bookmark or take notes while you read Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Edition 2. Search within book. Front Matter.
Pages i-xiii. PDF. Models for Axial Data. Barry C. Arnold, Ashis SenGupta. Bayesian analysis Bayesian analysis directional data analysis directional data analysis goodness-of-fit tests goodness-of-fit tests probability theory probability theory statistical theory statistical theory.
This is the textbook for my Bayesian Data Analysis book. This book contains lots of real data analysis examples, and some example are repeated several times through out the book, for example a 8-school SAT score example appears in both single-parameters models and in hierarchical models/5(17).
This book is intended to have three roles and to serve three associated audiences: an introductory text on Bayesian inference starting from first principles, a graduate text on effective current approaches to Bayesian modeling and computation in statistics and related fields, and a handbook of Bayesian methods in applied statistics for general users of and researchers in applied statistics.
Inferences based on regression models for a directional response are usually problematic. This paper presents a Bayesian analysis of a regression model for circular data using the. Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition provides an accessible approach for conducting Bayesian data analysis, as material is explained clearly with concrete examples.
Included are step-by-step instructions on how to carry out Bayesian data analyses in the popular and free software R and WinBugs, as well as new programs in JAGS and Stan. Based on the data, a Bayesian would expect that a man with waist circumference of centermeters should have bodyfat of % with 95% chance thta it is between % and %.
While we expect the majority of the data will be within the prediction intervals (the short dashed grey lines), Case 39 seems to be well below the interval. Hi Zeeshan: Doing Bayesian Data Analysis, 2nd ed: A Tutorial with R, JAGS, and Stan by John K. Kruschke is an excellent book.
Subjects and techniques are nicely discussed. Abstract: Novel data augmentation algorithms are proposed for Bayesian analysis of the directional data in arbitrary approach leads to new classes of distributions which are constructed in detail.
The proposed data augmentation strategies circumvent the need for analytic approximations to integration, numerical integration, or Metropolis-Hastings for the corresponding posterior.
With Bayesian inference (and the correct prior), though, this problem disappears. Amazingly enough, you don’t have to correct Bayesian inferences for multiple comparisons.
With that in mind let’s build a quick little function that will allow us to pass a data source and two names and run a Bayesian t-test via BayesFactor::ttestBF. Bayesian Analysis with Stata is a compendium of Stata user-written commands for Bayesian analysis.
It contains just enough theoretical and foundational material to be useful to all levels of users interested in Bayesian statistics, from neophytes to aficionados.This book attempts to remedy the situation by expounding a logical and unified approach to the whole subject of data analysis.
This text is intended as a tutorial guide for senior undergraduates and research students in science and engineering.
After explaining the basic principles of Bayesian probability theory, their use is illustrated with a. Bayesian Methods for Data Analysis por Bradley P. Carlin,disponible en Book Depository con envío gratis.


After reading Bang Bank you’re safe I thought it would be interesting to produce a graph of the Brady Gun score against the gun homicide rate per 100,000.
No real surprise: the gun score doesn’t seem to have much to do with your chance of being killed with a gun.
There are a lot of problems with this graph; correlation is not causation, the scale is a bit off, and California tends to dominate the eye, being all the way on the right.
But the biggest problem is that the underlying Brady score is measuring inputs instead of outputs. It is like trying to figure out if a school is any good by looking at how much money it spends instead of how well the students learn.


.transform() method defines a group of transformation on an element or group of elements.
With these transformations, we can scale, rotate, move or deform the SVG elements.
receive a list pseudo-functions with parameters separated by space. With this pseudo-function, we
define how we want to transform the graph.
scale() transform resizes the SVG element. This parameter accepts one or two values with
the horizontal and vertical scaling amounts. If one of them is omitted, both values(x and y) take
the same. These measures are a multiple of the original value, so
0.5 reduces the size by half,
2 doubles the original size.
It's important to understand the effect of
scale() on the shape. The scaling process change
shape's size, position, and stroke.
affected by the
x scale factor, and
height are affected by
y scale factor.
Other attributes, as
.stroke_width() are affected too by the
x scale factor.
translate() transform moving a shape and accept two numerical values (
y) separated by
a whitespace or comma. As a result, the shape or group is moved along both the
y is omitted, a
0 is assumed as value.
rotate() will specify in degrees the shape's or group's rotation at its point of origin (
y). You can include a
y values after the angle (separated by a whitespace) and
establish a new rotation's center (default values are
# .transform('skewX()') and .transform('skewY()')
The elements can be skewed or made crooked using
skewY () transformation with a
degree value than represents a skew transformation.
All previous transforms can be described as a
matrix() transform. This matrix transform receive
six values as
matrix(a b c d e f) and is equivalent to applying this transformation matrix:
a c e (b d f) 0 0 1
If we have a rectangle with these values:
x = 10 y = 10 width = 30 height = 20
we obtain these X and Y points:
topLeftX = x // 10 topLeftY = y // 10 topRightX = x + width // 10 + 30 = 40 topRightY = y // 10 bottomLeftX = x // 10 bottomLeftY = y + height // 10 + 20 = 30 bottomRightX = x + width // 10 + 30 = 40 bottomRightY = y + height // 10 + 20 = 30
When we apply this transform function:
rect.transform('matrix(3 1 1 3 -20 -30');
that is, this matrix values;
a = 3, c = 1, e = 30, b = 1, d = 3, f = 40
these operations are executed:
newTopLeftX = (topLeftX * a) + (topLeftY * c) + e // 10 newTopLeftY = (topLeftX * b) + (topLeftY * d) + f // 30 newTopRightX = (topRightX * a) + (topRightY * c) + e // 40 newTopRightY = (topRightX * b) + (topRightY * d) + f // 30 newBottomLeftX = (bottomLeftX * a) + (bottomLeftY * c) + e // 20 newBottomLeftY = (bottomLeftX * b) + (bottomLeftY * d) + f // 10 newBottomRightX = (bottomRightX * a) + (bottomRightY * c) + e // 110 newBottomRightY = (bottomRightX * b) + (bottomRightY * d) + f // 40
In practice, all these operations are performed internally, and it is very simple to apply a


Math Shooter is a classic, but addictive bubble shooter style game available first time for your Android Wear Smartwatch. This game is very intuitive, easy to learn but difficult to master. You need to prove your mathematical skills in combination with speed and accuracy in this fantastic game.
This game is fun, super addictive and a great way to spend free time on Android Wear Smartwatch. The objective is to zero out the number in a flying bubble with the bubbles available to shoot. Select a bubble from your available option to shoot at the flying bubble. Once the bubble is selected, shoot it correctly in the right direction to blast it away. The more bubbles you pop, the higher the score.
The addiction lies in the fact that it has several power-ups to use. You can get extra lives from the power-ups. The speed of the bubble can also be decreased by slow-down power.


The North Carolina Journal of Mathematics and Statistics (NCJMS) publishes high quality, refereed, open access articles and software. There is no charge to the authors.
The NCJMS is a broad-based journal encouraging submission of
- original research papers,
- significant review articles, and
- book reviews
in all areas of mathematics and statistics.
The NCJMS accepts submissions of mathematical and statistical software. This must be original work not submitted for review to a journal, computer algebra system, or elsewhere. The software can be a package or a collection of functions for a computer algebra system; or a package or a collection of functions written in a general purpose programming language; or a library; or a stand-alone program. Software submissions must consist of an article that contains a description of the functionality of the software and also the source code of the software.
Vol 3 (2017)
Table of Contents


HARBINGER | VTU Solved question papers book | 1 book with all subjects of the semester
Harbinger series means One Sem One Book, which is a SOLVED QUESTION PAPERS series predominantly aimed for VTU students, which will help the students to face the examination with confidence. You can find the solutions of previous 3-4 years’ question papers for all subjects in a single book. This is now available for all semesters/branches of VTU for B.E/B.Tech students.
This book is published by Sanguine Technical Publishers. The books are available at Sapna Book house and School book Company. Some books are also available online, order them here.
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Kinetic energy is energy of motion. Objects that are moving, such as a roller coaster, have kinetic energy (KE). If a car crashes into a wall at 5 mph, it shouldn't do much damage to the car. But if it hits the wall at 40 mph, the car will most likely be totaled.
Kinetic energy is similar to potential energy. The more the object weighs, and the faster it is moving, the more kinetic energy it has. The formula for KE is:
KE = 1/2*m*v2
where m is the mass and v is the velocity.
One of the interesting things about kinetic energy is that it increases with the velocity squared. This means that if a car is going twice as fast, it has four times the energy. You may have noticed that your car accelerates much faster from 0 mph to 20 mph than it does from 40 mph to 60 mph. Let's compare how much kinetic energy is required at each of these speeds. At first glance, you might say that in each case, the car is increasing its speed by 20 mph, and so the energy required for each increase must be the same. But this is not so.
We can calculate the kinetic energy required to go from 0 mph to 20 mph by calculating the KE at 20 mph and then subtracting the KE at 0 mph from that number. In this case, it would be 1/2*m*202 - 1/2*m*02. Because the second part of the equation is 0, the KE = 1/2*m*202, or 200 m. For the car going from 40 mph to 60 mph, the KE = 1/2*m*602 - 1/2*m*402; so KE = 1,800 m - 800 m, or 1000 m. Comparing the two results, we can see that it takes a KE of 1,000 m to go from 40 mph to 60 mph, whereas it only takes 200 m to go from 0 mph to 20 mph.
There are a lot of other factors involved in determining a car's acceleration, such as aerodynamic drag, which also increases with the velocity squared. Gear ratios determine how much of the engine's power is available at a particular speed, and traction is sometimes a limiting factor. So it's a lot more complicated than just doing a kinetic energy calculation, but that calculation does help to explain the difference in acceleration times.


Quantitative C++ Developer
Trading and Risk solutions provider based in Montreal seeks C++ Quantitative Developers to join their Modeling and Quantitative Data team.As a C++ Quantitative Developer, you will discover, design, develop and test models to value positions and construct quantitative data (curves, volatility cubes, correlation matrices, etc.) or calculate market risk (VaR, greeks, etc.) in real-time across all asset classes including Crypto.
Our risk models are used by some of the largest, most prestigious financial institutions around the world, ranging from global investment banks to multi-strategy hedge funds.Duties Design and development of models for pricing positions and calculating market risk metrices for all asset classes (equity, credit, FX, fixed income, commodities, crypto, and their derivatives)Write modern, clean, reusable, well tested source code in C++ that scales and performs well across large distributed systems (based on our high-performance grid computing platform)Leverage Python, SQL and Snowflake to analyze the model inputs or construct model inputsCreate methodology documentation to support model validation when needed3-4 office days per week, based in Montreal.Total compensation (base & bonus) approximately $250K to $350K CADFor next steps, please kindly send me an updated resume to denisanalyticrecruiting.comRequirementsM.S. or PhD in mathematics, physical sciences, or engineering preferredExcellent quantitative and programming skills with 3-5 years’ experience in large-scale C++ development and program design as well as data intensive productsExperience with other programming languages (Python, Java) is an advantageUnderstanding of financial derivatives, market conventions and their implementation is a mustExperience working on yield curves (OIS, Libor, Cross-currency, etc.), inflation curve, volatility surfaces, interest rate volatility cubes (eventually live/intraday) as well as the data to build them is highly desirableExperience in developing risk management tools such as VaR, Monte Carlo, scenario analysis and P&L is preferred
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Cryptocurrency enthusiasts and investors are always on the lookout for accurate predictions about the future price of Bitcoin (BTC). In recent news, several analysts have made bold forecasts, suggesting that Bitcoin’s price in the next cycle could reach a staggering $89,000. In this article, we will delve into these predictions, explore the factors and models used to make them and discuss potential scenarios for Bitcoin’s future price movements.
Understanding the Gann Square Methodology
One of the key methodologies employed by analysts to predict Bitcoin’s future price is the Gann Square. This technique, derived from the work of legendary trader W.D. Gann utilizes geometric patterns and mathematical calculations to identify potential price levels and trends.
Crypto analyst CryptoCon, known for his accurate predictions in previous cycles, has applied the Gann Square to forecast the top price of BTC in the upcoming cycle. According to CryptoCon, the Gann Square predicts two possible outcomes: $89,000 or $135,000. These figures are based on the fair value line and the end date of the halving cycle.
The November 28 Halving Cycles Theory
Another theory that has gained attention in the cryptocurrency community is the November 28 Halving Cycles theory. This theory suggests that the previous halving events, which occur approximately every four years, have a significant impact on Bitcoin’s price trajectory.
CryptoCon’s predictions align with this theory, as he believes that Bitcoin’s top price in the next cycle will be determined by the timing of the halving event. Using the Gann Square and the November 28 Halving Cycles theory, CryptoCon’s predictions of $89,000 and $135,000 gain credibility.
The 5.3 Diminishing Returns Theory
While CryptoCon’s $89,000 prediction is in line with the Gann Square and the November 28 Halving Cycles theory, another model suggests a slightly lower top price for Bitcoin in the next cycle. This model is based on the concept of diminishing returns, specifically a factor of 5.3x from the bottom to the top of each cycle.
According to this theory, Bitcoin’s returns diminish as each cycle progresses. By analyzing historical data, CryptoCon determined that the returns from cycle tops to bottoms vary, with an average of 5.31x. Based on these numbers, the predicted top price for the next cycle ranges from $73,522 to $81,675, with an average of $77,122.
Historical Data and Fibonacci Extensions
Bitcoin’s price movements can be analyzed using historical data and patterns. The first cycle from 2010 to 2014 saw a surge from $117 to $1,177. The second cycle from 2015 to 2018 saw a significant climb from $250 to $20,000. The third cycle from 2018 to 2022 showed Bitcoin’s resilience, reaching $68,800. The Gann Square’s “Fan” Lines provide clarity, with the “2×1 Fan” line representing a fair value line and the “1×1 Fan” line representing equilibrium. Fibonacci extensions, which indicate potential price targets, can provide valuable insights into Bitcoin’s future price movements.
Analysts have put forth compelling predictions for Bitcoin’s top price in the next cycle, ranging from $89,000 to $135,000. These forecasts are based on methodologies like the Gann Square, the November 28 Halving Cycles theory, and the 5.3 diminishing returns theory. By analyzing historical data, Fibonacci extensions, and external factors, analysts aim to provide insights into Bitcoin’s future price movements.


1. Eri Matsui: This Japanese fashion designer caught some eyes when she presented a collection of designs inspired by klein bottles, Escher patterns, the Fibonacci sequence, and knot theory. Matsui searched for ways to make women look beautiful which initially led her to the Golden Ratio. She uses Mathematica, an application for computations, in the design process to "compare between things generated from a computer and things created with human passions."
2. threeASFOUR: This avant garde design team creates designs based on a complex mathematical function. These swirls, circular forms, and fractal like prints come from something known as a Julia set. A Julia set, as defined by oxford dictionaries, is a set of complex numbers that do not converge to any limit when a given mapping is repeatedly applied to them. In some cases the result is a connected fractal set. Here are some of the pieces threeASFOUR has created:
What this design label has created is absolutely amazing to me and very inspiring. My future isn't yet defined by a certain job and this just shows me more ways that mathematics can be applied.
3. Amila Hrustic: Hrustic took inspiration from the five platonic solids (the tetrahedron, cube, octahedron, dodecahedron, icosahedron) to create "Plato's Collection." As these solids are suggested to be the building blocks of the universe, Amila used these shapes as a basis for her designs. She crafted these black and white dresses using recyclable paper and textiles and forming them almost all by hand without any “machines or things that could damage body or nature,”as Hrustic describes.
Fashion is an open ended industry and to involve a mathematical perspective adds to this infinity. This research, though I am sure I just cracked the surface, has enlightened me and has motivated me to look in to this a bit more. Perhaps graduate school in textile design is in my future, who knows?
1. - http://www.wolfram.com/mathematica/customer-stories/japanese-fashion-designer-eri-matsui-puts-mathematica-on-the-tokyo-catwalks.html
2. - http://cmediamktg.com/fashion-design-inspiration-complex-mathematics/
- (photo) - http://www.stylebistro.com/runway/Threeasfour/New+York+Fashion+Week+Fall+2012/Details/X2fhGtQX88O
- (photo) - http://metamorphosis-style.tumblr.com/post/20607962779/threeasfour-fall-2012
3. - http://www.ecouterre.com/sarajevo-artist-creates-math-inspired-origami-dresses-from-paper-textiles/
- (photos) - http://www.dezeen.com/2010/11/23/platos-collection-by-amila-hrustic/


The dividend yield says how much a stock pays in dividends each year, expressed as a percentage of the stock price. It is how much you get paid for investing in the stock, like the interest on a bank account.
For example, if a stock that costs $100 pays $2 in dividends per share each year, then the dividend yield is 2%.
Dividend yields vary greatly between stocks, and not all of them pay dividends. It is more common for mature and well-established companies, but rare among newer companies that are growing fast.
- Dividend payments are usually paid quarterly (every three months), but can also be paid on different schedules. They are usually paid via direct deposit into the investor's brokerage account.
- Dividends are not guaranteed and can be increased, decreased or even cut completely by a company's board of directors.
- Most reported dividend yields are trailing, meaning they look at the past 12 months of payments. A "forward" yield estimates what the dividend will be over the next year.
- The dividend yield changes inversely with the stock price. If the price goes up, the yield goes down, and vice versa.
- The payout ratio measures the percentage of profits paid out as dividends. If it is very high, then the dividend may not be sustainable.
- A very high dividend yield can indicate that a company's future prospects are poor, so it may not be a good investment.
Dividend Yield Calculator
How to calculate
Here are the 4 steps to calculate a stock's dividend yield:
- Find the amount of the last quarterly dividend payment.
- Multiply that number by four to calculate the annual payment.
- Divide the annual amount by the stock price.
- Multiply by 100 to convert to a percentage yield.
Example calculation for Apple stock:
- At the time of writing, Apple's last quarterly dividend was $0.82.
- Multiplying that number by four gives an annual payment of $3.28.
- Then the annual payment is divided by the stock price of $351.73. This gives a ratio of 0.00933.
- Multiplying by 100% gives a dividend yield of 0.933%.


Greater New York Region
Sunday, October 26, 2008
St. Joseph's College, Patchogue, NY
The standings and submission details are also available.
For problem H, The Two Note Rag, the algorithm to solve it is given in "What Should We Compute?" by F. J. Gruenberger, RAND Corporation, September 1963.
|Problem||Judges' Solution||Judges' Input File||Correct Output|
A - Sixth Grade Math |
B - Cryptoquote
C - Binary Clock
D - Recursively Palindromic Partitions
E - Text Messaging Improvement
F - Extended Normal Order Sort
G - Area of Polycubes
H - Two Note Rag
I - Joe's Triangular Gardens
h.cpp or h.java
Last modified 10 November 2008. Please email with comments, questions, or corrections.


Quantified information flow (QIF) has emerged as a rigorous approach to quantitatively measure confidentiality; the information-theoretic underpinning of QIF allows the end-users to link the computed quantities with the computational effort required on the part of the adversary to gain access to desired confidential information. In this work, we focus on the estimation of Shannon entropy for a given program Π. As a first step, we focus on the case wherein a Boolean formula φ(X, Y ) captures the relationship between inputs X and output Y of Π. Such formulas φ(X, Y ) have the property that for every valuation to X, there exists exactly one valuation to Y such that φ is satisfied. The existing techniques require O(2^m ) model counting queries, where m = |Y |. We propose the first efficient algorithmic technique, called EntropyEstimation to estimate the Shannon entropy of φ with PAC-style guarantees, i.e., the computed estimate is guaranteed to lie within a (1 ± ε)-factor of the ground truth with confidence at least 1−δ. Furthermore, EntropyEstimation makes only O( min(m,n)) counting and sampling queries, where m = |Y |, and n = |X|, thereby achieving a significant reduction in the number of model counting queries. We demonstrate the practical efficiency of our algorithmic framework via a detailed experimental evaluation. Our evaluation demonstrates that the proposed framework scales to the formulas beyond the reach of the previously known approaches.


Random matrix theory is very exciting and has tools for problems we encounter again and again across a vast expanse of the math landscape. Already in exploring quadratic convexity and algorithms for deciding it, we see a need for sampling methods (with accompanying estimates for distributions of derived quantities). Here is a great survey paper by a former Cal Poly student (et al), now a professor at Boulder. This is just one area of this newish industry within mathematics (henceforth RMT).
Numerical linear algebra and, more generally, numerical algebraic geometry are going to come in very handy. Here is an introduction to the latter. Here is a great text on matrix analysis with mostly constructive proofs, an excellent handbook. And this book by Dym has useful but not-so-well-known results.
And what a great time to be looking into this topic; here is an updated discussion of open problems in RMT and integrable systems.


Focuses on adding 9 to the numbers 0-12. This book includes one new addition fact each day, (32 pages, 40 daily problems, 14 days of practice, 550 problems per book, 6,500+ per series), handwriting aids, cumulative practice, daily achievements stars, and a completion certificate.Perfect for students in grades K-3, ages 5+, who have had an introduction to addition and are working on fluency and automaticity. Learning Objectives: Addition proficiency and fluency, legible handwriting, number sense, and independent learning. This Page A Day Math book is 1 of 12 books in the Addition Series. For great results, use the this book together with the other 11 books in this series. Early math skills are one of the strongest predictors of future academic success. Invest in your child's early math skills!
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Virtual Bulletin Board
Click on link(s) below
Please click here for information on the Educational Opportunity Program (EOP) at Nassau Community College being held on February 18th to February 21st.
The Columbia University Science Honors Program (SHP) is a highly selective program for high school students who have a strong interest in science and mathematics. The SHP holds classes at Columbia from 10:00 A.M. to 12:30 P.M. on Saturdays throughout the academic year. Courses are given in the physical, chemical, biological, behavioral, and computing sciences, as well as in pure and applied mathematics. Instructors are scientists and mathematicians who are actively engaged in research at the University. Please click here for details.


Math & physics and their significance in aviation. Is it important to know how to calculate? Everyone uses a calculator when things need to be calculated, right? And do you actually need to understand physics when you are piloting an aircraft? I received tons of questions about math and physics. It seems there is still a lot of uncertainty about this subject so allow me to enlighten you.
The short answer Yes & Yes! It is important to have a basic understanding of physics and math. You have to know how to calculate quickly, precisely and by heart. Flying an airplane is all about Mathematics and Physics. Just think about it for a second, how is an airplane able to take off with all that weight? How does lift and drag work and how do you calculate the top of descent or distance an airplane needs to fly in order to maintain a 3 degree glide path to the runway?
Do You Need Physics To Become A Pilot?
You will need a significant amount of knowledge and skills in order to become a pilot. Everything from weather to physics and everything in between is covered. Math is required not only for the job, but also for the training.
To become a pilot, you should be able to read and understand a few basic math concepts. Several additional subjects must be learned in order to be safe in the cockpit of an airplane. Someone advised me to study Physics and Mathematics in high school or above if I want to become a commercial pilot. To fly an airplane, the pilot must be familiar with math in order to solve all of the complicated equations in the cockpit. Modern airplanes today have electronic displays that can solve the most difficult equations. Pilots who fly in general aviation may make more decisions than those who fly in airplanes. As pilots, we are primarily concerned with solving simple mathematical problems.
Doesn’t the Aircraft/Auto Pilot Handle Most of this?
Yes, most of the above calculations are done by the aircraft and by modern technology these days.
That being said, you still want to have a good understanding of what is going on behind the scenes. There very well could be scenarios where a piece of technology fails or has bad information causing you to get a bad output.
Is Math Compulsory for Pilots?
Math is not compulsory insofar as flight schools will not ask to see a mathematics qualification.
However, math is required to obtain a high school diploma and the GED. As all flight schools require a high school diploma or equivalent, you do technically need to have a passing math grade.
An expert at multi-tasking
This one comes up a lot, mostly from people worried that they won’t make a good pilot because they can’t concentrate on the TV while they cook dinner. But the truth is, this isn’t the same thing. Believe it or not, pilots themselves are rarely truly ‘multi-tasking’ anyway because the limitations of the human brain generally make it a bad idea.
It is widely considered that a human brain can only do one complex task at a time properly, so it stands to reason that a pilot controlling an airliner full of passengers shouldn’t try to do more than one thing at eleven.


Exercises In Computational Mathematics With MATLAB (Problem Books In Mathematics) Jean-Louis 12
Fundamental and relevant mathematics for prospective elementary school teachers, including whole numbers and place value operations with whole numbers, number theory, fractions, ratio and proportion, decimals, and percents. For Pre-Early Childhood and Pre-Elementary Education majors only.
Exercises in Computational Mathematics with MATLAB (Problem Books in Mathematics) Jean-Louis 12
Introduction to ordinary differential equations. First and second order linear differential equations, systems of linear differential equations, Laplace transform, numerical methods, applications. (This course is considered upper division with respect to the requirements for the major and minor in mathematics.)
While the mathematicians of the pre-internet age often spread their mathematical ideas within the community via written letters prior to publication, modern mathematical correspondence and exposition is rapidly facilitated by a variety of digital tools. Of great importance to the publishing process in mathematical sciences is the LaTeX markup language, used to typeset virtually all modern mathematical publications, even at the pre-print stage. In this course we will develop facility with LaTeX, and develop a variety of writing practices important to participation in the mathematical community. There will be regular written assignments completed in LaTeX, as well as collaborative writing assignments, owing to the importance of collaborative writing in mathematical research. Writing topics may include proofs, assignment creation, pre-professional writing (resumes/cover letters, research and teaching statements), expository writing for a general audience, recreational mathematics, and the history of mathematics. Short writing assignments on such topics will be assigned in response to assigned readings from a variety of accessible/provided sources. Towards the end of the semester groups will complete a research paper of an expository nature and craft a seminar style presentation. This course meets the junior year writing requirement.
This course is about how to write and use computer code to explore and solve problems in pure and applied mathematics. The first part of the course will be an introduction to programming in Python. The remainder of the course (and its goal) is to help students develop the skills to translate mathematical problems and solution techniques into algorithms and code. Students will work together on group projects with a variety applications throughout the curriculum.
This is a rigorous introduction to some topics in mathematics that underlie areas in computer science and computer engineering, including: graphs and trees, spanning trees, colorings and matchings, the pigeonhole principle, induction and recursion, generating functions, and (if time permits) combinatorial geometry. The course integrates mathematical theories with applications to concrete problems from other disciplines using discrete modeling techniques. Small student groups will be formed to investigate a modeling problem independently, and each group will report its findings to the class in a final presentation. Satisfies the Integrative Experience for BS-Math and BA-Math majors.
This is an introduction to the history of mathematics from ancient civilizations to present day. Students will study major mathematical discoveries in their cultural, historical, and scientific contexts. This course explores how the study of mathematics evolved through time, and the ways of thinking of mathematicians of different eras - their breakthroughs and failures. Students will have an opportunity to integrate their knowledge of mathematical theories with material covered in General Education courses. Forms of evaluation will include a group presentation, class discussions, and a final paper. Satisfies the Integrative Experience requirement for BA-MATH and BS-MATH majors.
The course introduces and uses Fourier series and Fourier transform as a tool to understand varies important problems in applied mathematics: linear ODE & PDE, time series, signal processing, etc. We'll treat convergence issues in a non-rigorous way, discussing the different types of convergence without technical proofs. Topics: complex numbers, sin & cosine series, orthogonality, Gibbs phenomenon, FFT, applications, including say linear PDE, signal processing, time series, etc; maybe ending with (continuous) Fourier transform.
Algebraic geometry is the study of geometric spaces locally defined by polynomial equations. It is a central subject in mathematics with strong connections to differential geometry, number theory, and representation theory. This course will be a fast-paced introduction to the subject with a strong emphasis on examples.


3 Regresi (Buku 5: Kutner, Et All P. 5) Sir Francis Galton (latter part of the 19th century):studied the relation between heights of parents and childrennoted that the heights of children of both tall and short parents appeared to "revert" or "regress" to the mean of the group.developed a mathematical description of this regression tendency,today's regression models (to describe statistical relations between variables).
16 Assumptions Linear regression assumes that… 1. The relationship between X and Y is linear2. Y is distributed normally at each value of X3. The variance of Y at every value of X is the same (homogeneity of variances)4. The observations are independent
17 Asumsi lebih lanjut… Alexander Von Eye & Christof Schuster (1998) Regression Analysis for Social Sciences
18 Asumsi lebih lanjut… Alexander Von Eye & Christof Schuster (1998) Regression Analysis for Social Sciences
20 Regression Picture C B R2=SSreg/SStotal A2 B2 C2 A y yixy*Least squares estimation gave us the line (β) that minimized C2A B C2SStotalTotal squared distance of observations from naïve mean of y Total variationSSregDistance from regression line to naïve mean of y Variability due to x (regression)SSresidualVariance around the regression line Additional variability not explained by x—what least squares method aims to minimizeR2=SSreg/SStotal


A little backstory . . .
My younger DD, who turned 12 in August, is a struggling learner. Once it fact is locked in her brain, it is in. BUT it is kind of random what facts make it in her brain to stick. For example:
* she still struggles with left and right, but can tell you without fail that there are 5280 feet in a mile BUT can't remember that there are 12 inches in a foot
* she knows her basic facts pretty well - probably ready for some review drills, but overall knows her addition and multiplication.
* she knows how to divide and subtract but often leaves out steps
* she knows her basic fraction operations, but mixes them up from time to time
* she still struggles with place value - especially anything over 1000
We have done Math U See since Primer. She really struggled with the Epsilon book and ended up going through it about 3 times.
She does not work independently at all. She needs me to coach her through each problem.
I am agonizing over this decision. We just started MUS Zeta and are already struggling with the place value for decimals/fractions. Do I take it slow and continue to work through? Do I figure we have enough emotional baggage with MUS after Zeta and switch? Our Co-op is switching to Saxon next year. I was looking at the placement tests for Saxon and have no idea where it would place her. The repetition of Saxon MIGHT help her, but I'm not sure. We went through Life of Fred over the summer and enjoyed it, but the fraction/decimals books are too much for her.
I am at a loss and really struggling with this today. Feeling pretty discouraged. Thoughts? Ideas?


A New Kind of Science - Book Review
This review appeared in Barrons on September 2, 2002
The conventional wisdom in science is that complex systems and organisms can only be explained by equally complex rules and mathematics.
But regardless of whether one speaks of the behavior of stock markets and financial systems, sub-atomic particles, humans, apes or the very cosmos, scientists have developed enormously complicated mathematical models that fall short of anything other than "pretty good" most of the time -- and "pretty awful" whenever it comes to divining the inner workings of complexity.
Chaos theory, fractals, complexity theory and other promising paths have all managed to hit their own walls because, according to Stephen Wolfram in A New Kind of Science, simplicity is the prime mover of complex behavior -- and traditional math is the enemy of understanding this.
So instead of the conventional math and calculus of the past 300 years, Wolfram makes an excruciatingly thorough case that real portraits of complexity can be drawn only if one uses powerful computers to make billions and billions and billions of calculations -- in order to repeat very simple cellular automation rules.
To understand cellular automata, imagine a grid, like graph paper. Color in one square. Then to figure out which other squares to color in, apply this simple rule: a cell should be black whenever one or the other -- but not both -- of its neighbors on the same line were black on the step before.
After rule 90 (of 256) is carried out 50 or so times, an intricate, symmetrical pattern is produced. But after a few thousand iterations, the patterns appear to go completely random, producing pictographs with uncanny resemblances to leaf-vein structure, or crystal fractures, or animal ornamentation -- all phenomena which have been assumed to be results of very complicated processes.
The author proposes that the rules of cellular automata offer worthy answers to how we should approach the nature of the universe, the enigma of human consciousness and other lesser topics, like quantum physics and, finally, the ultimate fabric of reality: "All the wonders of our universe can in effect be captured by simple rules, yet this shows that there can be no way to know all the consequences of these rules, except in effect just to watch and see how they unfold."
In other words, things are a lot simpler than we thought -- but they can still be awfully unpredictable.
While some of the ideas expressed might be dismissed as the deranged babblings of a kook, or perhaps a genius with a frontal-lobe tumor, Wolfram comes with the pedigree of a visionary: He got his Ph.D. from Caltech at the age of 20, has a widely acknowledged career in particle physics and cosmology, found favor with such giants in physics as Richard Feynman and, as the writer of the much-admired Mathematica -- a program that aids scientists and mathematicians in making all manners of computations -- is a wildly successful software entrepreneur.
In the end, Wolfram's 1,197-page opus offers not a new kind of science but a new way of looking at science. True, many of the connections he makes are superficial or incoherent, but still intriguing. And this is a thought-provoking book with the heft of a cinder block -- making it the ultimate in heavy reading. It might even make for great vacation reading for some ... if you plan to take it along on all your vacations until 2005.


Solving the Sudoku puzzle by logic only
This page describes how to solve a Sudoku puzzle. It's a puzzle in a 9x9
grid where each number (from 1 to 9) has to appear exactly once in each row,
column and exactly once in each of the nine 3x3 squares. If you've never
heard of it, search the web, there are plenty of examples.
It's an intriguing puzzle because it can seem at once very simple and very,
very difficult. I wrote a solution finder that simply tried each number in
each position but that takes forever. I didn't let it finish, I have a
sneaking suspicion it's end-of-the-universe type stuff.
So, my final solution ended up being a bit smarter. It employs three kinds of tricks:
The program basically keeps applying the first method until it stops
working. It then applies the second method and tries the first again. It
only tries the later methods if the earlier ones don't make progress. The
solver never guesses though it could easily be made to do so. If it
can't sole it it shows you where it got upto and stops. Usually I can't
solve the resulting grid either which means I can't really fix it either.
- Firstly, it goes though each cell and determines if there is only one
possible number that can be placed there. This is the simplest and most
simple puzzles found in newspapers can be solved with this method alone. It
just takes a bit of time, although it's trivial for a computer.
- Secondly, it checks each cell to see if there is a number possible
there that is not possible in any other cell in the row, column or box.
This is a slightly more sophisticated method although you can apply it very
easily when you're looking at the grid yourself. It gets you out of stuck
spots where the first method can't proceed.
- Thirdly, it tries the method known as locked candidates. It's the
technique where if a number in any row or column is only present in a
single box, you can exclude it from the rest of the box. The site given has
- The final method is one that simply count the number of distinct number
in a group of cells and if that number is the same as the number of cells
you've made a subgroup, This restricts the contens of other cells and may
lead to a solution.
The grid is stored as a two dimensional array. The cells are referenced by
Row and Col numbers from 1 to 9. The cell either contains a number or is
unbound (represented by '_' in Prolog). The important basic predicates are:
After seeing the above basic predicates you can see how the solving might
proceed. Note, the built-in findall/3 predicate is used a lot to find all
- available( In, Out ) :- Given a list of cells (either bound or unbound)
returns the set of numbers that do not appear in that set. Unbound
cells are ignored.
- possibles( P, Rin, Cin, Out ) :- Given the grid P, return the
set of possible values for the cell (Rin,Cin). It works basically by
extracting the values in the same row, column and box, run the
available/2 predicate on each and return the intersection of those
sets. Note, if the cell already has a value, this predicate fails.
You shouldn't be doing that anyway. It also simplifies coding as filled-in
cells will be automatically ignored.
- row( P, Row ), col( P, Col ), box( P, Box )
:- return the values in the grid associated with the given row, column or
Discovered values are stored in the form of [Row,Col,Value]. If in
an intermediate stage with multiple possible values, we use
[Row,Col,[Values]]. The predicate assign/3 applies the found
results to the grid. It fails if there is nothing to apply, so each
individual step doesn't need to explicitly check if it didn't find anything.
If none of the above work we've either solved the puzzle or got stuck. In
either case, print the result and stop.
- Sanity check: Check that there are no cells for which
possibles/4 returns an empty set. This means we screwed up. This
is where it's important for possibles/4 to fail on filled in cells rather
than return an empty set.
- First method: Find all cells where possibles/4 returns a single
element. If found, that's the element to fill in.
- Second method: This is trickier. For each row, column and box we
collect the set of possibles for each cell. Within a single (for example)
row, we take each the possibles for each cell and subtract the possibles
for the other cells. If there is exactly one number left over, that's
number it should be.
We do this search in row, column and boxes one after the other and return
the union of the results. (row|col|box)set/3 are the testing
predicates. (row|col|box)all/2 are the predicates to collect the
- Third method: This is the Locked Candidates test. For each row, column
or box it extract the set of possibles. If a number in that row, column or
box only appears in one section of it, it is excluded in the other
Much of the complexity here it caused by the fact that I generalised it to
handle all the possiblities. It choose a major axis (say row) and number
(say 1) and a minor axis (say box). It will then select all the cells in
row 1. It divides these cells by the minor axis giving you a set with the
number used in the intersections of (row 1, box1) (row 1, box 2) (row 1,
box 3). If any of those contain a number not in the other two, that number
can be removed for all other rows in the same box.
A bit difficult to get your head around but it's a very effective solve
- Fourth method: This basically scans each row, column or box and tries
to find a subset of cells where the number of distinct numbers is the same
as the number of cells. Works quite well.
Basically, it solves the puzzle quicker than you can type it in. The
problems in the file I've put in the predicate problem/2 so you basically
> problem(1,X), solve(X).
This will solve the first puzzle in the file. I defined 7. Ideally it should
read from a file but I havn't done that yet.
It prints out each step along the way along with which each type of method it
used. You could turn this off if you want. It's probably fast enough to
create a puzzle setter. solve/2 will fail outright if the puzzle is
inconsistent and return an incomplete grid if there is not enough
information. You could score the different methods of solving to try and
make harder-to-solve puzzles.
By Martijn van Oosterhout (kleptog (at) svana.org)
Copyright © 2000-2006 - Last modified 3/04/2006


What is Fibonacci Heap?
In computer science, a Fibonacci heap is a heap data structure consisting of a collection of trees. It has a better amortized running time than a binomial heap. Fibonacci heaps were developed by Michael L. Fredman and Robert E. Tarjan in 1984 and first published in a scientific journal in 1987.
Why this name?
The name of Fibonacci heap comes from Fibonacci numbers which are used in the running time analysis.
Where run time improves? It is more complex that binomial heap. Because two pivotal operations: Decrease-Key and Delete are more efficient with fibonacci heap. Due to slowly performing some operations it is called a lazy data structure.
Related Problems List
All Priority Queue problems; hence dijkstra etc as well.
- Page# 505 the book, Introduction to Algorithm - C.L.R.S
- Stony Brook Univ. Lecture - Dijkstra’s SSSP & Fibonacci Heaps


An alarm clock draws 0.5 A of current when connected to a 120 volt circuit. Calculate its resistance.
If a toaster produces 12 ohms of resistance in a 120-volt circuit, what is the amount of current in the circuit? (Units required)
A walkman uses a standard 1.5 V battery. How much resistance is in the circuit if it uses a current of 0.01A?
A circuit contains a 1.5 volt battery and a bulb with a resistance of 3 ohms. Calculate the current.
An electric heater works by passing a current of 100 A though a coiled metal wire, making it red hot. If the resistance of the wire is 1.1 ohms, what voltage must be applied to it?


Dr. Elmar Diederichs gratuated in Physics, Analytical Philosophy and Law at the Georg-August-Universität Göttingen and got his Ph.D. in Mathematics from FU Berlin. Afterwards he had research positions at the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) Berlin, the Department of Statistics at UC Berkeley (CA) and the Moscow Institute of Physics and Technology (MIPT) focussed on Machine Learning and Predictive Data Analysis. Then he worked as Director for Machine Intelligence on Stochastic Analysis and complex problems in AI for a company in UK. Now he has his own research group as Director for Machine Intelligence at a large logistics company (GER). Moreover hee has started is own mathematical think tank Elements of Euclid Ltd. working on AI augmented cognition. There he works on Machine Thinking and philosophical problems on Language Analysis, Cognition and Autonomy and their implications to AI – particularly NLP and Reinforcement Learning.


It is easier to express the concept of time in units dating back to Sumerians. In the SI unit system, the time unit is seconds and is defined by the vibration frequency of the cesium atom.
We can start with a day to measure time. One day, that is, 24 hours is the time to complete the Earth's rotation around itself. Another measure is the transformation of the Earth around the Sun. He completes this turn in 1 year.
With this calculation tool, you can cycle between seconds, minutes, hours, days, weeks, months and years.


There are many different math tuition centers in Singapore, so it can be difficult to know which one is the best for your child. This article will discuss some of the factors you should consider when choosing the best math tuition singapore.
The first thing to consider is the tutor’s qualifications. You want to ensure that the tutor has a degree in mathematics or a related field. The tutor should also have experience teaching math to students of all levels, from elementary school to high school.
Another important factor is the tutor’s teaching style. Some tutors prefer a more traditional approach, while others use more innovative methods. It would help if you chose a tutor who matches your child’s learning style.
It is also important to consider the tutor’s rates. Make sure that the rates are affordable and within your budget.
Finally, it would be best if you asked other parents for recommendations. Ask them which math tuition centers they recommend and why. This can help you narrow down your choices and find the best tutor for your child.
In conclusion, there are many factors you should consider when looking for a math tutor. First, make sure that the tutor is qualified and has an approach that matches your child’s learning style. You should also check their rates to ensure they’re affordable within your budget.
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When I talk to mudjackers who want to get into foam lifting, they almost always want to know the difference in estimating how much material is needed. In fact, anyone new to slab lifting with polyurethane foam will ask how to estimate material, not just people experienced in mudjacking. If you use a cementitious slurry, you are probably used to calculating in cubic yards, but with foam, you need to figure out how many gallons you might need.
Here’s the way to figure it out.
There are two parts to slab lifting: 1- filling existing voids and 2- lifting the slab.
For void filling: Find out the free rise expansion rate of the material. This should be on the technical data sheet for the product. There are 7.48 gallons of liquid in a cubic foot, so divide that by the expansion rate to get material in a cubic foot. For example, if you are using our Revolution compact slab lifting system with Precision Lift 2135, it has a 20 times or 20x expansion rate, so:
7.48 ÷ 20 = .374 gallons per cubic foot
There are 27 cubic feet in a cubic yard, so in this example, there are approximately 10 gallons per cubic yard.
For slab lifting: Because the foam is confined when lifting a slab, the expansion rate will be affected. What we have observed in our many years of experience is that usually a half a pound of polyurethane will lift one square foot ½”. That’s less than ½ a pint of material. (There are roughly 10 lbs. to a gallon of polyurethane resin.) This is pretty typical for lifting foams on the market.
We provide free slab lifting estimating calculators on our website for both gallons and pounds. If you’ve got questions, call your rep or our main number at 800-321-7212.
By David Dingler, product development and technical services manager


The AfterSchool KidzMath program works because it lets kids experience mathematics through stories, games, and collaboration. This multi-layered approach helps kids internalize concepts while having fun. Introducing mathematical concepts through stories and games minimizes the intimidation and fear some children associate with math. The integrated social and cooperative structures of KidzMath teaches children to work together to problem solve, which exposes them to different ways to view a problem.
Leaders are provided with clear, simple directions and tips, an overview of math and social skills, a math glossary, correlations, assessment tools, a site planning tool, leader's checklist for planning and reflection, sample questions to engage children, and access to online professional development.