What does difference in math mean?

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In mathematics, the term “difference” typically refers to the result of subtracting one number from another. It is the answer to a subtraction problem. The process of finding the difference between two numbers involves determining how much one number needs to be increased or decreased to reach the other number. For example, in the subtraction … Read more

Single digit addition and subtraction

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Single-digit addition and subtraction are fundamental arithmetic operations. They are usually among the first math skills taught in elementary school. Let’s break down each one with explanations and examples. Single-Digit Addition Addition is the process of calculating the total of two or more numbers. With single-digit addition, you are adding numbers between 0 and 9. … Read more

Does dyslexia affect math?

Yes, dyslexia can affect math skills, although the primary difficulties associated with dyslexia are related to reading and language processing. The impact of dyslexia on math is often referred to as “dyscalculia,” which is specifically a difficulty in understanding numbers, learning how to manipulate numbers, performing mathematical calculations, and learning facts in mathematics. However, dyscalculia … Read more

Is discrete math hard?

Whether discrete mathematics is hard or not can depend on several factors, including your background, interests, and the way the material is taught. Discrete mathematics is a branch of mathematics dealing with discrete elements that uses algebra and arithmetic. It is typically contrasted with “continuous” mathematics, which deals with objects that can vary smoothly, like … Read more

You Can Run, You Can Hide: The Epidemiology and Statistical Mechanics of Zombies

We use a popular fictional disease, zombies, in order to introduce techniques used in modern epidemiology modelling, and ideas and techniques used in the numerical study of critical phenomenon. We consider variants of zombie models, from fully connected continuous time dynamics to a full scale exact stochastic dynamic simulation of a zombie outbreak on the … Read more

The Muisca Calendar: An approximation to the timekeeping system of the ancient native people of the northeastern Andes of Colombia

The aim of this project is to review and expand upon the model proposed by Father Jose Domingo Duquesne de la Madrid (1745-1821) regarding the calendar of the ancient Muisca culture of the central Colombia. This model was dismissed by scholars in the late 19th century, calling it just a simple invention of a clergyman; … Read more

Rowhammer.js: A Remote Software-Induced Fault Attack in JavaScript

As DRAM has been scaling to increase in density, the cells are less isolated from each other. Recent studies have found that repeated accesses to DRAM rows can cause random bit flips in an adjacent row, resulting in the so called Rowhammer bug. This bug has already been exploited to gain root privileges and to … Read more

The Human Body and Millimeter-Wave Wireless Communication Systems: Interactions and Implications

With increasing interest in millimeter wave wireless communications, investigations on interactions between the human body and millimeter wave devices are becoming important. This paper gives examples of current regulatory requirements, and provides an example for a 60 GHz transceiver. Also, the propagation characteristics of millimeter-waves in the presence of the human body are studied, and … Read more

Donor Retention in Online Crowdfunding Communities: A Case Study of DonorsChoose.org

Online crowdfunding platforms like DonorsChoose.org and Kickstarter allow specific projects to get funded by targeted contributions from a large number of people. Critical for the success of crowdfunding communities is recruitment and continued engagement of donors. With donor attrition rates above 70%, a significant challenge for online crowdfunding platforms as well as traditional offline non-profit … Read more

Generative Adversarial Networks as Variational Training of Energy Based Models

In this paper, we study deep generative models for effective unsupervised learning. We propose VGAN, which works by minimizing a variational lower bound of the negative log likelihood (NLL) of an energy based model (EBM), where the model density p(x) is approximated by a variational distribution q(x) that is easy to sample from. The training … Read more