Understanding the movement of fluids through diffusion

Passive transport means there is no expenditure of energy ATP. Passive transport requires the substance to move from an area of high concentration to low concentration. Simple diffusion across membranes occurs when substances other than water move across the phospholipid bilayer between the phospholipids or through protein channels. Substances that move across the membrane are usually small non-charged particles i.

Understanding the movement of fluids through diffusion

Understanding Convolution in Deep Learning by Tim Dettmers Comments Convolution is probably the most important concept in deep learning right now. But what makes convolution so powerful?

How does it work?

Understanding the movement of fluids through diffusion

In this blog post I will explain convolution and relate it to other concepts that will help you to understand convolution thoroughly. There are already some blog post regarding convolution in deep learning, but I found all of them highly confusing with unnecessary mathematical details that do not further the understanding in any meaningful way.

This blog post will also have many mathematical details, but I will approach them from a conceptual point of view where I represent the underlying mathematics with images everybody should be able to understand. The second part of this blog post includes advanced concepts and is aimed to further and enhance the understanding of convolution for deep learning researchers and specialists.

This whole blog post will build up to answer exactly this question, but it may be very helpful to first understand in which direction this is going, so what is convolution in rough terms?

You can imagine convolution as the mixing of information. Imagine two buckets full of information which are poured into one single bucket and then mixed according to a specific rule.

Each bucket of information has its own recipe, which describes how the information in one bucket mixes with the other. So convolution is an orderly procedure where two sources of information are intertwined.

But for now we will look at convolution from a practical perspective. When we apply convolution to images, we apply it in two dimensions — that is the width and height of the image.

We mix two buckets of information: The output of the kernel is the altered image which is often called a feature map in deep learning. There will be one feature map for every color channel. Convolution of an image with an edge detector convolution kernel. The computation ends when all pixels of the feature map have been computed this way.

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This procedure is illustrated for one image patch in the following gif. Convolution operation for one pixel of the resulting feature map: Gif by Glen Williamson who runs a website that features many technical gifs.

As you can see there is also a normalization procedure where the output value is normalized by the size of the kernel 9 ; this is to ensure that the total intensity of the picture and the feature map stays the same.

Why is convolution of images useful in machine learning? There can be a lot of distracting information in images that is not relevant to what we are trying to achieve. The Burda Bootcamp is a rapid prototyping lab where students work in a hackathon-style environment to create technologically risky products in very short intervals.

Together with my 9 colleagueswe created 11 products in 2 months. In one project I wanted to build a fashion image search with deep autoencoders: You upload an image of a fashion item and the autoencoder should find images that contain clothes with similar style.

Now if you want to differentiate between styles of clothes, the colors of the clothes will not be that useful for doing that; also minute details like emblems of the brand will be rather unimportant. What is most important is probably the shape of the clothes.Sign up to receive ATOTW weekly - email [email protected] BODY FLUIDS - PART 1 ANAESTHESIA TUTORIAL OF THE WEEK 21st JUNE Dr Matthew Gwinnutt.

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Osmosis is the facilitated diffusion of water through a selectively permeable BUILD Understanding Passive Transport Diffusion is the movement of particles from an area of high concentration to an area of low concentration.

Osmosis is the diffusion of water through a selectively permeable membrane.

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Online homework and grading tools for instructors and students that reinforce student learning through practice and instant feedback. Sign up to receive ATOTW weekly - email [email protected] BODY FLUIDS - PART 1 ANAESTHESIA TUTORIAL OF THE WEEK .

Describe the movement of fluids, electrolytes and other substances throughout the body by the following: diffusion, osmosis, pressure differential, and other essential mechanisms.

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