Syntax and Semantic

WRF ,as mentioned in part 1 and part2 , is a system designed for both operational and research purposes, and to run on systems from conventional laptops to super computers. The design of such a versatile system is a real challenge. In this post we will explore some of the WRF's Software Framework design and explain the functionality of the different layers of the system. Also we'll discuss how the system handles parallelism in different hardware environments. Software Framework Architecture [1][2] : (The following functionalities doesn't include parallelism handling)  Figure1: Hierarchical WRF Software Design As it appears in Figure 1, the system design has 3 layers: The Driver Layer: It defines and allocates domains and associates them in a nest hierarchy. It also manages the flow of a system run as it's responsible for stepping the time for the loop mentioned in part1. And it's responsible for I/O operations.  The Mediation Layer: It interfaces between...

In the part 1 we introduced WRF and discussed the meteorological basics of Advanced Research WRF. In this part we discuss the concept of nesting and explain different system parts of WRF. But first we'll define two basic terms. Grid: Raw atmospheric data layed out as a discrete grid for an area of the map. Figure 1 [1] Grid examples Domian: A model created by processing grid information and making it ready for processing by WRF Model. Nesting: Nesting is a way of getting high resolution data from low resolution data.That's achieved by introducing more grid or grids to the initial state. Those finer grain grids force the need for more high resolution data. That data is obtained by interpolating data from coarse grain grids or could be user input. Figure 2 [1] Nested grid WRF System Components: Figure3 [1] WRF system components As it appears in figure 1, the system has 3 main components: Preprocessor (WPS), the WRF Model and Post Processor. The WPS is responsible for pre...

My goal here is to give a simple overview of the WRF for computer science students. The Weather Resarch and Forecasting (WRF, pronounced "worf") model is an open-source numerical weather prediction (NWP) and atmospheric simulation system designed for both research and operational applications [1]. This system was developed as joint effort between National Center of Atmospheric Research, National Oceanic and Atmospheric Administration (NOAA), Air Force Weather Agency and others. In this post ,and the posts to follow, I'll try to explain the WRF from two different perspectives, the first being Meteorology and the second being Computer Science. I am here concerned with the Advanced Research WRF (ARW) subset of WRF. Weather Prediction Basics: Weather Prediction means to predict the state of the atmosphere in terms of (pressure, temperature, speed of wind, etc). Our atmosphere is controlled by flow and the conditions of the air across the planet and by predicting that fl...

(This is an enhanced version of the my earlier post with the results of your comments and my discussions with friends). With the relatively rise of online social networks and it's uncontrolable availability to vulnerable users (children, teenager and even people with low or no technical background) exposed a huge privacy concerns for everyone. Your data that your putting on the internet are available one way or another to almost everyone. Along with web giants such as Google and Facebook keeping track of every click you make for either targeted services or anonymized purposes. And that made me ask one basic question: Do they have the right to know all my internet behaviour ? Lets first state some important definitions that we'll need. My behaviour is what I the links I click on the internet to browse the web to check, read and edit free online content. My service request is the link I click to ask some service provider to make something for me. My main goal is to make m...

If you look at the current internet, giving its age and the type of problems it's facing, you can see clearly that we're still in the middle of, what I'd like to call it, the stone age of the internet. We're talking about a technology that's only 30 years old, it has yet a lot of potentials to be discovered and drawbacks and problems to be solved. The problem I want to expose here is privacy. I'd like to compare the real stone age (5000 years B.C.) to the internet stone age (1985 to 2009). The stone age: During the stone age humans lived in the forests and took cover in caves from the rain, they lived in tribes that shared the same interest and cared for each other's interests. Communication between those tribes was almost impossible and they probably fought over everything (territory, food, women, etc). They slept right there in the open thinking that they are well protected that way. Invented some traps and protection systems to protect them and maybe c...

Demand for Ubuntu CDs is very high, and we're trying to ensure that we have enough CDs for those who really need one. We've noticed that you've already received CDs of several previous Ubuntu releases. You can help us ensure the continued availability of Ubuntu CDs by * upgrading to the new release without a CD * downloading your own CD for free * becoming an Ubuntu member by contributing to Ubuntu, and thereby becoming eligible for more CDs Thanks for your support of Ubuntu! I am sure they are trying to do there best but my point of view that people with longest history with Ubuntu are the best candidates to share the CDs with others. Maybe I am wrong but I just want a CD :(

First I'd like to define roughly what video segmentation is then talk about it in more technical details. The term video segmentation is used with two applications in mind, the first making a long video short by extracting the key shots and images and puting them in a sequence summarizing the long video. So you can think of it as making movies trailers automatically. The other is extracting the objects that were shot in a video and tracking them through a series of shots; in short making videos of the objects in one big video. So you can think of it as Arnold Schwarzenegger moving as the terminator identifying objects with his "eyes" and getting data about objects he's seeing. Both problems are challenging and interesting but I'll focus more on the challenges faced when developing algorithms for the second definition. If you used Photoshop ever then you must have done some image segmentation before. If you still don't know what I am talking about, remembe...