Why Technical English

Who else will discuss PageRank calculations?

April 3, 2012
16 Comments

Composed by Galina Vitkova

Procedure of calculations

In the field of information retrieval on the web, PageRank has emerged as the primary (and most widely discussed) hyperlink analysis algorithm. But how it works still remains an obscurity to many in the SEO online community.

PageRanks-Example

Nevertheless, regarding to the importance of PageRank it worth trying to examine or analyse how it is calculated. The study is meaningful even if Google keeps the real algorithm of PageRank calculations secret.

In any case PageRank calculations are performed in compliance with The PageRank Algorithm

Let us consider the example consisting of  4 pages: Page A, Page B, Page C and Page D (or simply A, B, C, D having their PageRanks with the same notation). The pages link to each other as shown in the following picture. In the beginning the PageRanks for the pages are unknown, so we’ll just assign „1“ to each page.

 Linking of four pages

It means that the first calculation begins with PageRanks as follows:

  A = 1    B = 1    C = 1    D = 1

According to the rules about passing rank, which come out from the mentioned formula, each page passes a part of its PageRank to other pages. So, first we apply the dampening factor “d”, which ensures that a page cannot pass to another page its entire PageRank. Then the remaining value is divided by the number of links outcoming from this page. Finally the entire ranking is summed up and added to each page. In the first table below you see the value of PageRanks passing from one page to another:

A (2 links)  = 1*0.85 / 2 = 0.425
passes  0.425 to B
          0.425 to C
B (1 link)    = 1*0.85  = 0.85
passes  0.85  to  C
C (1 link)    = 1*0.85  = 0.85
passes  0.85  to  A
D (1 link)    = 1*0.85  = 0.85
passes  0.85  to  C

The resulting PageRanks are depicted in the following table below:

A = 1 + 0.85 = 1.85
B = 1 + 0.425 = 1.425
C = 1 + 0.425+0.85+0.85 = 3.125
D = 1

So, the next run of calculations begins with:

A = 1.85    B = 1.425    C = 3.125    D = 1

And after performing the same operations it comes to the result as follows:

A = 4.50625     B = 2.9975    C = 5.18625    D = 1

In practice it is necessary to do identical operations 50 to 100 times to guarantee the sufficient accuracy of the iterations.

Here needful to notice that in the first run of the calculations, Page C increases PageRank of Page A. In the next run Page C gets itself an increase in PageRank that is proportional to the new improved PageRank of Page A. It means Page C gets a proportion of its PageRank back to itself. It is PageRank feedback, an essential part of the way how PageRank works.

Links to and from your site

PageRank is the hardest factor to manipulate when optimising your pages. It is both difficult to achieve and more difficult to catch up with.

GoogleBot-byFML

When trying to optimise your PageRank the following factors should be taken into consideration:

  • Choice of the links you want to link to your site;
  • Selection of a site you want to link out to from your site;
  • Production of maximum PageRank feedback by changes of the internal structure and linkage of your pages.

When looking for links to your site, from a purely PageRank point of view, the pages with the highest Toolbar PageRank seem to be the best solution. Nonetheless, it is not truthful.

As more and more people try and get links from only high PageRank sites, it becomes less and less profitable. Thus sites that need to improve their PageRanks should be more receptive and exchange links with sites that have similar interests. Moreover, the number of links on the page linking to you will alter the amount of feedback, etc.

Therefore, maybe the best solution is getting links from sites that seem appropriate and have good quality, regardless of their current PageRank. The quality sites will either help your PageRank now, or will do so in the future.

To consider the best strategy concerning links out from your site, the general rule is: keep PageRank within your own site. Control of feedback by using the internal pages of your site, is much easier than control with the help of links to external pages. It means to make links out from a page on your site that has a low PageRank itself, and which also contains many internal links. Then, when linking out choose those external sites, which do not point to your page with a significant number of links.  It will get a better increase in PageRank, in particular due to the power of feedback. 

Placing some your links back into your site system rather than letting it go to external links improves PageRanks of your pages. That is why larger sites generally have a better PageRank than smaller ones.

References:

 

Dear friend of technical English,  
Do you want to improve your professional English?
Do you want at the same time to gain comprehensive information about the Internet and Web?

Subscribe to “Why Technical English“ clicking SIGN ME UP at the top of the sidebar 

 

 

Advertisements

One way to understand PageRank

February 15, 2012
5 Comments
Dear friend of Technical English,
In the following text I am trying to explain how I understand the topic. After having studied different sources I have drawn up this post.
The post topic is important for every blogger who wants to have a quality blog with quality content which attracts search engines and visitors. On the other hand, it is a great opportunity for writing a lively technical text for studying Tech English online. So, study the topic, study Tech English and write comments, which is the best way for practising the language.
Find necessary terminology in the Internet English Vocabulary.
Galina Vitkova

 

PageRank

Is a link analysis algorithm used by the Google Internet search engine. The algorithm assigns a numerical weighting to each element of hyperlinked documents on the World Wide Web with the purpose of “measuring” its relative importance within it. According to the Google theory if Page A links to Page B, then Page A is saying that Page B is an important page. If a page has more important links to it, then its links to other pages also become more important.

Principles of PageRank

History

PageRank was developed at the Stanford University by Larry Page (thus the term PageRank is after him) and Sergey Brin as part of a research project about a new kind of a search engine. Now the “PageRank” is a trademark of Google. The PageRank process has been patented and assigned to the Stanford University, not to Google. Google has exclusive license rights on this patent from the university. The university received 1.8 million shares of Google in exchange for use of the patent; the shares were sold in 2005 for $336 million.
The first paper about the project, describing PageRank and the initial prototype of the Google search engine, was published in 1998: shortly after, Page and Brin founded the company Google Inc. Even if PageRank now is one of about 200 factors that determine the ranking of Google search results, it continues to provide the basis for all of Google web search tools.
Since 1996 a small search engine called “RankDex” designed by Robin Li has already been exploring a similar strategy for site-scoring and page ranking. This technology was patented by 1999 and was used later by Li when he founded Baidu in China.

Some basic information about PageRank

There is some basic information, which is needed to know for understanding PageRank.
First, PageRank is a number that only evaluates the voting ability of all incoming (inbound) links to a page.
Second, every unique page of a site that is indexed in Google has its own PageRank.
Third, internal site links interact in passing PageRank to other pages of the site.
Forth, the PageRank stands on its own. It is not tied in with the anchor text of links.
Fifth, there are two values of the PageRank that should be distinguished:
a. PageRank which you can get from the Internet Explorer toolbar (http://toolbar.google.com);
b. Actual or real PageRank that is used by Google for calculation of ranking web pages.
PageRank from the toolbar (sometimes called the Nominal Pagerank) has value from zero to ten. It is not very accurate information about site pages, but it is the only thing that gives you any idea about the value. It is updated approximately once every three months, more or less, while the real PageRank is calculated permanently as the Google bots crawl the web finding new web pages and new backlinks.
Thus, in the following text the term actual PageRank is employed to deal with the actual PageRank value stored by Google, and the term Toolbar PageRank concerns the evaluation of the value that you see on the Google Toolbar.

This is how the PageRank works.

The Toolbar value is just a representation of the actual PageRank. While real PageRank is linear, Google uses a non-linear graph to show its representation. So on the toolbar, moving from a PageRank of 2 to a PageRank of 3 takes less of an increase than moving from a PageRank of 3 to a PageRank of 4.
This is illustrated by a comparison table (from PageRank Explained by Chris Ridings). The actual figures are kept secret, so for demonstration purposes some guessed figures were used:

If the actual PageRank is between

The Toolbar Shows

0.00000001 and 5
6 and 25
25 and 125
126 and 625
626 and 3125
3126 and 15625
15626 and 78125
78126 and 390625
390626 and 1953125
1953126 and infinity
1
2
3
4
5
6
7
8
9
10

 

The PageRank Algorithm

Lawrence Page and Sergey Brin have published two different versions of their PageRank algorithm in different papers.

First version (so called the Random Surfer Model) was published on the Stanford research paper titled The Anatomy of a Large-Scale Hypertextual Web Search Engine in 1998:

PR(A) = (1-d) + d(PR(T1)/C(T1) + … + PR(Tn)/C(Tn))

Where PR(A) is the PageRank of page A.
d is a damping factor, which is set between 0 and 1, nominally it is set to 0.85.
PR(T1) is the PageRank of a site page pointing to page A.
C(T1) is the number of outgoing links on page T1.

In the second version of the algorithm, the PageRank of page A is given as:

PR(A) = (1-d) / N + d (PR(T1)/C(T1) + … + PR(Tn)/C(Tn))

Where N is the total number of all pages on the Web.

The first model is based on a very simple intuitive concept. The PageRank is put down as a model of user behaviour, where a surfer clicks on links at random. The probability that the surfer visits a page is the page PageRank. The probability that the surfer clicks on one link at the page is given by the number of links at the page. The probability at each page that the surfer will get bored and will jump to another random page is the damping factor d.

The second notation considers PageRank of a page the actual probability for a surfer reaching that page after clicking on many links. The PageRanks then form a probability distribution over web pages, so the sum of all pages PageRanks will be one.

As for calculating PageRank the calculations by means of its first model are easier to compute because the total number of web pages is disregarded.

References:

 

Dear friend of technical English,  

Do you want to improve your professional English?

Do you want at the same time to gain comprehensive information about the Internet and Web?

Subscribe to “Why Technical English”  clicking   RSS – Posts

 


Education: Why blogs need SEO

January 28, 2012
2 Comments

Composed by Galina Vitkova

SEO (Search engine optimisation)

Is the process of improving the visibility of a website or a web page or a blog in search engines. SEO aims to maximise profitable traffic from search engines to websites. In general, the more frequently a site appears in the search results list, the more visitors it will receive from the search engine users. Thus, technical communication among the search engine users, including bloggers will improve. Experience has shown that search engine traffic can make a firm success. Targeted visitors to a website or a blog may provide publicity, revenue, and exposure like no other. Investing in SEO, whether through time or finances, can have an exceptional rate of return.

What really is Search Engine Optimization?

SEO evaluates how search engines work, what people search for, the actual search terms typed into search engines. Moreover, SEO considers which search engines are preferred by their targeted audience. Optimising a website for searching may involve editing its content to increase its relevance to specific keywords and to remove barriers to the indexing activities of search engines (see Search engine essential information).  Promoting a site to increase the number of backlinks, or inbound links, is another SEO task.

The success and popularity of a search engine is determined by its ability to produce the most relevant results to any given search. Otherwise, false search results could turn users to find other search sources. Therefore search engines with more complex ranking algorithms (which strongly affects SEO), taking into account additional factors have been evolved.

Google and its PageRank   

The breakthrough idea behind Google was to analyse the relationships between the websites and pages to determine the relevancy of those pages to specific search queries. The Google founders, graduate students at Stanford University Larry Page and Sergey Brin, used this principle and developed a mathematical algorithm for a search engine to rate the prominence of web pages. The number calculated by the algorithm, has been named PageRank after Larry Page. PageRank estimates the likelihood that a given page will be reached by a user who randomly surfs the web and follows links from one page to another. In effect, this means that some links are stronger than others because a higher PageRank page is more likely to be reached by the random surfer.

Page and Brin founded Google using the developed algorithm for searching in 1998. Google attracted immediately the growing number of Internet users due to its simple design. In Google off-page factors (such as the PageRank and hyperlink analysis) as well as on-page factors (such as keyword frequency, meta tags, headings, links and site structure) were considered. It enables Google to avoid the kind of manipulation seen in search engines that only deliberated on-page factors for their rankings

Against improper SEO

Since the time of appearing ranking tools webmasters developed a great amount of link building instruments to influence search engine results within SEO. Many sites focused on exchanging, buying, and selling links, often on a massive scale which is not connected much with the spirit of SEO.

By 2004, search engines incorporated a wide range of undisclosed factors in their ranking algorithms to reduce the impact of link manipulation. The leading search engines, Google, Bing, and Yahoo, do not disclose their ranking algorithms, too.  

Image of Google & Yahoo offices in Haifa. Both...

Image via Wikipedia

In 2007, Google announced a campaign against paid links that transfer PageRank. On June 15, 2009, it took special measures to mitigate the effects of PageRank sculpting. In December 2009, Google announced it would be using the web search history of all its users in order to populate search results.

Google Instant, real-time-search, was introduced in late 2009 in an attempt to make search results more timely and relevant. Site administrators have spent months or even years optimising a website to increase search rankings. With the growth in popularity of social media sites and blogs the leading engines made changes to their algorithms to allow fresh content to rank quickly within the search results.

Increasing prominence

A variety of methods can increase the prominence of a webpage within the search results. Cross linking between pages of the same website or blog to provide more links to most important pages may improve its visibility. Writing content that includes frequently searched keyword phrases, so as to be relevant to a wide variety of search queries will tend to increase traffic. Updating content so as to keep search engines crawling back frequently can give additional weight to a site. Adding relevant keywords to web page meta data, including the title tag and meta description, will tend to improve the relevancy of a site search listings, thus increasing traffic. Several other techniques can help towards the page link popularity score. In any case, creating a useful, information-rich site, with pages that clearly and accurately describe your content should be one of the main goals of SEO.

References

 

Dear friend of technical English,  

If you want to improve your professional English and at the same time to gain basic comprehensive targetted information about the Internet and Web, then

subscribe to “Why Technical English”.

Find on the right sidebar subsription options and:

  • Subscribe by Email Sign me up        OR
  • Subsribe with Bloglines              OR
  • Subsribe.ru

Subscribe and and choose free e-books from http://bookgrill.com/?lb.

 

 

Translatorsbase


Search engine – essential information

December 29, 2011
12 Comments
Composed by Galina Vitkova using Wikipedia

A search engine usually refers to searching for information on the Web. Other kinds of the search engine are enterprise search engines, which search on intranets, personal search engines, and mobile search engines. Different selection and relevance criteria may apply in different environments, or for different uses.

Diagram of the search engine concept (en)

Web search engines operate in the following order: 1) Web crawling, 2) Indexing, 3) Searching. Search engines store information about a large number of web pages, which they look up in the Web itself. These pages are retrieved by a Web crawler (sometimes also known as a spider). It is

Architecture of a Web crawler.

 an automated Web browser which follows every link it sees. The contents of each page are then analyzed to determine how it should be indexed. Data about web pages are stored in an index database. Some search engines, such as Google, store all or part of the source page (referred to as a cache) as well as information about the web pages. Other engines, such as AltaVista, store every word of every page they find. This cached page always holds the actual search text since it is the one that was actually indexed. Search engines use regularly updated indexes to operate quickly and efficiently.

When a user makes a query, commonly by giving key words, the search engine looks up the index and provides a listing of best-matching web pages according to its criteria. Usually the listing comprises a short summary containing the document title and sometimes parts of the text. Most search engines support the use of the Boolean terms AND, OR and NOT to further specify the search query. The listing is often sorted with respect to some measure of relevance of the results. An advanced feature is proximity search, which allows users to define the distance between key words.

Most Web search engines are commercial ventures supported by advertising revenue. As a result, some of the engines employ the controversial practice of allowing advertisers to pay money to have their listings ranked higher in search outcomes. The vast majority of search engines running by private companies use proprietary algorithms and closed databases, though a few of them are open sources.

Nowadays the most popular search engines are as follows:

Google. Around 2001, the Google search engine rose to prominence. Its success was based in part on the concept of link popularity and PageRank. Further it utilizes more than 150 criteria to determine relevancy. Google is currently the most of all used search engine.

Baidu. Due to the difference between Ideographic and Alphabet writing system, the Chinese search market didn’t boom until the introduction of Baidu in 2000. Since then, neither Google, Yahoo nor Microsoft could come to the top like in other part of the world. The reason may be the media control policy of the Chinese government, which requires any network media to filter any possible sensitive information out from their web pages.

Yahoo! Search. Only since 2004, Yahoo! Search has become an original web crawler-based search engine, with a reinvented crawler called Yahoo! Slurp. Its new search engine results were included in all of Yahoo! sites that had a web search function. It also started to sell its search engine results to other companies, to show on their web sites.

After the boom success of key word search engines, such as Google and Yahoo! search, a new type of a search engine, a meta search engine, appears. In general, the meta search engine is not a search engine. Technically, it is a search engine based on search engines. A typical meta search engine accepts user queries the same as that of traditional search engines. But instead of searching key words in its own database, it sends those queries to other non-meta search engines. Then based on the search results returned by several non-meta search engines, it selects the best ones (according on different algorithms), showing back to users. Examples of those meta search engines are Dog Pile (http://www.dogpile.com/) and All in One News (http://www.allinonenews.com/About Allinonenews).

English: Meta search engine Français : metamoteur

PS: The text is drawn up within an upcoming e-book titled Internet English (see Number 33 – WWW, Part 1 / August 2011 – Editorial). G. Vitkova

 

Dear visitor,  If you want to improve your professional English and at the same time to gain basic comprehensive targetted information about the Internet and Web, then

subscribe to “Why Technical English”.

Find on the right sidebar subsription options and:

  • Subscribe by Email Sign me up        OR
  • Subsribe with Bloglines                   OR
  • Subsribe.ru

 


The Semantic Web – great expectations

October 31, 2011
3 Comments

By Galina Vitkova

The Semantic Web brings the further development of the World Wide Web aimed at interpreting the content of the web pages as machine-readable information.

In the classical Web based on HTML web pages the information is comprised in the text or documents which are read and composed into visible or audible for humans web pages by a browser. The Semantic Web is supposed to store information as a semantic network through the use of ontologies. The semantic network is usually a directed or undirected graph consisting of vertices, which represent concepts, and edges, which represent relations among the concepts.  An ontology is simply a vocabulary that describes objects and how they relate to one another. So a program-agent is able to mine facts immediately from the Semantic Web and draw logical conclusions based on them. The Semantic Web functions together with the existing Web and uses the protocol HTTP and resource identificators URIs.

The term  Semantic Web was coined by sir Tim Berners-Lee, the inventor of the World Wide Web and director of the World Wide Web Consortium (W3C) in May 2001 in the journal «Scientific American». Tim Berners-Lee considers the Semantic Web the next step in the developing of the World Wide Web. W3C has adopted and promoted this concept.

Main idea

The Semantic Web is simply a hyper-structure above the existing Web. It extends the network of hyperlinked human-readable web pages by inserting machine-readable metadata about pages and how they are related to each other. It is proposed to help computers “read” and use the Web in a more sophisticated way. Metadata can allow more complex, focused Web searches with more accurate results. To paraphrase Tim Berners-Lee the extension will let the Web – currently similar to a giant book – become a giant database. Machine processing of the information in the Semantic Web is enabled by two the most important features of it.

  • First – The all-around application of uniform resource identifiers (URIs), which are known as addresses. Traditionally in the Internet these identifiers are used for pointing hyperlinks to an addressed object (web pages, or e-mail addresses, etc.). In the Semantic Web the URIs are used also for specifying resources, i.e. URI identifies exactly an object. Moreover, in the Semantic Web not only web pages or their parts have URI, but objects of the real world may have URI too (e.g. humans, towns, novel titles, etc.). Furthermore, the abstract resource attribute (e.g. name, position, colour) have their own URI. As the URIs are globally unique they enable to identify the same objects in different places in the Web. Concurrently, URIs of the HTTP protocol (i.e. addresses beginning with http://) can be used as addresses of documents that contain a machine-readable description of these objects.

  • Second – Application of semantic networks and ontologies. Present-day methods of automatic processing information in the Internet are as a rule based on the frequency and lexical analysis or parsing of the text, so it is designated for human perception. In the Semantic Web instead of that the RDF (Resource Description Framework) standard is applied, which uses semantic networks (i.e. graphs, whose vertices and edges have URIs) for representing the information. Statements coded by means of RDF can be further interpreted by ontologies created in compliance with the standards of RDF Schema and OWL (Web Ontology Language) in order to draw logical conclusions. Ontologies are built using so called description logics. Ontologies and schemata help a computer to understand human vocabulary.

 

Semantic Web Technologies

The architecture of the Semantic Web can be represented by the Semantic Web Stack also known as Semantic Web Cake or Semantic Web Layer Cake. The Semantic Web Stack is an illustration of the hierarchy of languages, where each layer exploits and uses capabilities of the layers below. It shows how technologies, which are standardized for the Semantic Web, are organized to make the Semantic Web possible. It also shows how Semantic Web is an extension (not replacement) of the classical hypertext Web. The illustration was created by Tim Berners-Lee. The stack is still evolving as the layers are concretized.

Semantic Web Stack

As shown in the Semantic Web Stack, the following languages or technologies are used to create the Semantic Web. The technologies from the bottom of the stack up to OWL (Web Ontology Langure) are currently standardized and accepted to build Semantic Web applications. It is still not clear how the top of the stack is going to be implemented. All layers of the stack need to be implemented to achieve full visions of the Semantic Web.

  • XML (eXtensible Markup Language) is a set of rules for encoding documents in machine-readable form. It is a markup language like HTML. XML complements (but does not replace) HTML by adding tags that describe data.
  • XML Schema published as a W3C recommendation in May 2001 is one of several XML schema languages. It can be used to express a set of rules to which an XML document must conform in order to be considered ‘valid’.
  • RDF (Resource Description Framework) is a family of W3C specifications originally designed as a metadata data model. It has come to be used as a general method for conceptual description of information that is implemented in web resources. RDF does exactly what its name indicates: using XML tags, it provides a framework to describe resources. In RDF terms, everything in the world is a resource. This framework pairs the resource with a specific location in the Web, so the computer knows exactly what the resource is. To do this, RDF uses triples written as XML tags to express this information as a graph. These triples consist of a subject, property and object, which are like the subject, verb and direct object of an English sentence.
  • RDFS (Vocabulary Description Language Schema) provides basic vocabulary for RDF, adds classes, subclasses and properties to resources, creating a basic language framework
  • OWL (Web Ontology Language) is a family of knowledge representation languages for creating ontologies. It extends RDFS being the most complex layer, formalizes ontologies, describes relationships between classes and uses logic to make deductions.
  • SPARQL (Simple Protocol and RDF Query Language) is a RDF query language, which can be used to query any RDF-based data. It enables to retrieve information for semantic web applications.
  • Microdata (HTML)  is an international standard that is applied to nest semantics within existing content on web pages. Search engines, web crawlers, and browsers can extract and process Microdata from a web page providing better search results

As mentioned, top layers contain technologies that are not yet standardized or comprise just ideas. May be, the layers Cryptography and Trust are the most uncommon of them. Thus Cryptography ensures and verifies the origin of web statements from a trusted source by a digital signature of RDF statements. Trust to derived statements means that the premises come from the trusted source and that formal logic during deriving new information is reliable.


World Wide Web

September 3, 2011
Leave a Comment

Dear friends of Technical English,

I have just started publishing materials for my projected e-book devoted to the Internet English, i.e. English around the Internet. It means that during a certain period of time I will publish posts which will make basic technical texts in units of the mentioned e-book with a working name Internet English. The draft content of the e-book has already been published on my blog http://traintechenglish.wordpress.com in the newsletter Number 33 – WWW, Part 1 / August 2011. One topic in the list means one unit in the e-book.

Thus you find below the first post of a post series dealing with Internet English. I hope these texts will contribute to develop your professional English and at the same time will bring you topical information about the Internet.    Galina Vitkova

 

World Wide Web

 Composed by Galina Vitkova

The World Wide Web (WWW or simply the Web) is a system of interlinked, hypertext documents that runs over the Internet. A Web browser enables a user to view Web pages that may contain text, images, and other multimedia. Moreover, the browser ensures navigation between the pages using hyperlinks. The Web was created around 1990 by the English Tim Berners-Lee and the Belgian Robert Cailliau working at CERN in Geneva, Switzerland.

Today, the Web and the Internet allow connecti...

Today, the Web and the Internet allow connecti...

The term Web is often mistakenly used as a synonym for the Internet itself, but the Web is a service that operates over the Internet, as e-mail, for example, does. The history of the Internet dates back significantly further than that of the Web.

Basic terms

The World Wide Web is the combination of four basic ideas:

  • The hypertext: a format of information which in a computer environment allows one to move from one part of a document to another or from one document to another through internal connections (called hyperlinks) among these documents;
  • Resource Identifiers: unique identifiers used to locate a particular resource (computer file, document or other resource) on the network – this is commonly known as a URL (Uniform Resource Locator) or URI (Uniform Resource Identifier), although the two have subtle technical differences;
  • The Client-server model of computing: a system in which client software or a client computer makes requests of server software or a server computer that provides the client with resources or services, such as data or files;
  • Markup language: characters or codes embedded in a text, which indicate structure, semantic meaning, or advice on presentation.

 

How the Web works

Viewing a Web page or other resource on the World Wide Web normally begins either by typing the URL of the page into a Web browser, or by following a hypertext link to that page or resource. The act of following hyperlinks from one Web site to another is referred to as browsing or sometimes as surfing the Web. The first step is to resolve the server-name part of the URL into an Internet Protocol address (IP address) by the global, distributed Internet database known as the Domain name system (DNS). The browser then establishes a Transmission Control Protocol (TCP) connection with the server at that IP address.

TCP state diagram

TCP state diagram

The next step is dispatching a HyperText Transfer Protocol (HTTP) request to the Web server in order to require the resource. In the case of a typical Web page, the HyperText Markup Language (HTML) text is first requested and parsed (parsing means a syntactic analysis) by the browser, which then makes additional requests for graphics and any other files that form a part of the page in quick succession. After that the Web browser renders (see a note at the end of this paragraph) the page as described by the HyperText Markup Language (HTML), Cascading Style Sheets (CSS) and other files received, incorporating the images and other resources as necessary. This produces the on-screen page that the viewer sees.

Notes:

  • Rendering is the process of generating an image from a model by means of computer programs.
  • Cascading Style Sheets (CSS) is a style sheet language used to describe the look and formatting of a document written in a markup language.

 

Web standards

At its core, the Web is made up of three standards:

  • the Uniform Resource Identifier (URI), which is a string of characters used to identify a name or a resource on the Internet;
  • the HyperText Transfer Protocol (HTTP), which presents a networking protocol for distributed, collaborative, hypermedia information systems, HTTP is the foundation of data communication on the Web;
  • the HyperText Markup Language (HTML), which is the predominant markup language for web pages. A markup language presents a modern system for annotating a text in a way that is syntactically distinguishable from that text.

 


100% integration of renewable energies?

August 13, 2011
1 Comment

Composed by Galina Vitkova

The Renewables-Grid-Initiative (RGI) promotes effective integration of 100% electricity produced from renewable energy sources.

EnergyGreenSupply

Energy Green Supply

I do not believe in this statement RGI. I am sure that it is impossible from technical and technological points of view. Simply remind the very low share of renewables in entire production of world electricity (3% without hydroelectricity), very high investment costs and very high prices of electricity produced from renewables nowadays.

Concerns about climate and energy security (especially, in the case of nuclear power plants) are reasons supporting the efforts for a quick transformation towards a largely renewable power sector. The European emissions reduction targets to keep temperature increase below 2°C require the power sector to be fully decarbonised by 2050. Large parts of society demand that the decarbonisation is achieved predominantly with renewable energy sources.

Illustration: Different types of renewable energy.

Different types of renewable energy

Renewables advocates do not speak much about real solutions of real greatly complex problems of renewable sources. Very often they are not aware of them. Even if renewable energy technologies are now established and appreciated by officials and green activists as a key means of producing electricity in a climate and environment friendly way, many crucial problems remain unsolved. Additional power lines, which are needed for transporting electricity from new renewable generation sites to users, raise negative impact on the environment, including biodiversity, ecosystems and the landscape. Furthermore, electricity surpluses, produced by renewables when electricity consumption is very low, causes enormous problems with storage of these surpluses. Besides, there are serious problems with dispatch controlling of a power system with the great penetration (see Variability and intermittency of wind energy in Number 31 – Giving a definition / July 2011) of renewables. On the whole, three the most important problems are waiting to be solved and each of them demands massive investments:

  • building the additional electricity transmission lines in a great amount due to numerous and dispersed renewable sites;
  • accommodation of electricity storage needs in the case of electricity surpluses from renewables;
  • integration of intermittent sources of electricity production in scheduled control of power grids.

Thus, concerns about the impacts of renewables integration in European power systems need to be carefully studied, fully understood and addressed.

Let us closely consider the issues of building new transmission lines. In the coming decade thousands of kilometers of new lines should be built acrossEurope. Renewable energy sources are abundant and vary, but they are mostly available in remote areas where demand is low and economic activities infrequent. Therefore, thorough strategic planning is required to realise a new grid infrastructure that meets the electricity needs of the next 50-70 years. The new grid architecture is supposed to enable the integration of all renewable energy sources – independently from where and when they are generated – to expand the possibility for distributed generation and demand-side management.

Grid expansion is inevitable but often controversial. The transmission system operators (TSOs) need to accommodate not only the 2020 targets but also to prepare for the more challenging full decarbonisation of the power sector by 2050. The non-governmental organisations (NGO Global Network) community is still not united with respect to supporting or opposing the grid expansion. A number of technical, environmental and health questions need to be addressed and clarified to improve a shared understanding among and across TSOs and NGOs. RGI is trying to bring together cooperating TSOs and NGOs.

The grid expansion could be accomplished by means of overhead lines and underground cables. Both of them may transmit alternative current (AC) and direct current (DC). In the past it was relatively easy to select between lines and cables:

Cables mainly used in the grid for shorter distances mostly due to being more expensive and shorter technical lifetime (50% of overhead lines) whereas overhead lines were used in another cases. Nowadays the situation is more complex since more options and more parameters should be considered. In the future cables will prospectively be even more utilised as development is going towards higher power levels.

Cables have higher public acceptance because of their lower disturbance of natural scenery, lower electromagnetic radiation, avoidance of wildlife, higher weather tolerance. The overhead lines unfortunately disturb the scenery and seriously influence wildlife and protected areas.

The grid development for expanding the renewables by means of overhead lines endangers bird populations inEurope. High and large-scale bird mortality from aboveground power lines progresses due to:

  • Risk of electrocution,
  • Risk of collision,
  • Negative impacts on habitats.

And that all makes up a significant threat to birds and other wildlife. For these reasons Standards to protect birds (Habitats and Birds Directives) are being worked out. 

Moreover, the European Commission is currently working on a new legislation to ensure that the energy infrastructure needed for implementing the EU climate and energy targets will be built in time.

References


Fuel cycle in fusion reactors

May 25, 2011
Leave a Comment

Composed by Galina Vitkova

Common notes

The basic concept behind any fusion reaction is to bring two or more nuclei close enough together, so that the nuclear force in nuclei will pull them together into one larger nucleus. If two light nuclei fuse, they will generally form a single nucleus with a slightly smaller mass than the sum of their original masses (though this is not always the case). The difference in mass is released as energy according to Albert Einstein’s mass-energy equivalence formula E = mc2. If the input nuclei are sufficiently massive, the resulting fusion product will be heavier than the sum of the reactants’ original masses. Due to it the reaction requires an external source of energy. The dividing line between “light” and “heavy” nuclei is iron-56. Above this atomic mass, energy will generally be released by nuclear fission reactions; below it, by fusion.

Fusion between the nuclei is opposed by their shared electrical charge, specifically the net positive charge of the protons in the nucleus. In response to it some external sources of energy must be supplied to overcome this electrostatic force. The easiest way to achieve this is to heat the atoms, which has the side effect of stripping the electrons from the atoms and leaving them as nuclei. In most experiments the nuclei and electrons are left in a fluid known as a plasma. The temperatures required to provide the nuclei with enough energy to overcome their repulsion is a function of the total charge. Thus hydrogen, which has the smallest nuclear charge, reacts at the lowest temperature. Helium has an extremely low mass per nucleon and therefore is energetically favoured as a fusion product. As a consequence, most fusion reactions combine isotopes of hydrogen (“protium“, deuterium, or tritium) to form isotopes of helium.

In both magnetic confinement and inertial confinement fusion reactor designs tritium is used as a fuel. The experimental fusion reactor ITER (see also The Project ITER – past and present) and the National Ignition Facility (NIF) will use deuterium-tritium fuel. The deuterium-tritium reaction is favorable since it has the largest fusion cross-section, which leads to the greater probability of a fusion reaction occurrence.

Deuterium-tritium (D-T) fuel cycle

D-T fusion

Deuterium-tritium (D-T) fusion

 

The easiest and most immediately promising nuclear reaction to be used for fusion power is deuterium-tritium Fuel cycle. Hydrogen-2 (Deuterium) is a naturally occurring isotope of hydrogen and as such is universally available. Hydrogen-3 (Tritium) is also an isotope of hydrogen, but it occurs naturally in only negligible amounts as a result of its radioactive half-life of 12.32 years. Consequently, the deuterium-tritium fuel cycle requires the breeding of tritium from lithium. Most reactor designs use the naturally occurring mix of lithium isotopes.

Several drawbacks are commonly attributed to the D-T fuel cycle of the fusion power:

  1. It produces substantial amounts of neutrons that result in induced radioactivity within the reactor structure.
  2. The use of D-T fusion power depends on lithium resources, which are less abundant than deuterium resources.
  3. It requires the handling of the radioisotope tritium. Similar to hydrogen, tritium is difficult to contain and may leak from reactors in certain quantity. Hence, some estimates suggest that this would represent a fairly large environmental release of radioactivity.

Problems with material design

The huge neutron flux expected in a commercial D-T fusion reactor poses problems for material design. Design of suitable materials is under way but their actual use in a reactor is not proposed until the generation later ITER (see also The Project ITER – past and present). After a single series of D-T tests at JET (Joint European Torus, the largest magnetic confinement experiment currently in operation), the vacuum vessel of the fusion reactor, which used this fuel, became sufficiently radioactive. So, remote handling needed to be used for the year following the tests.

In a production setting, the neutrons react with lithium in order to create more tritium. This deposits the energy of the neutrons in the lithium, for this reason it should be cooled to remove this energy. This reaction protects the outer portions of the reactor from the neutron flux. Newer designs, the advanced tokamak in particular, also use lithium inside the reactor core as a key element of the design.

PS: I strongly recommend to read the article FUSION(A Limitless Source Of Energy). It is a competent technical text for studying Technical English. Consequently it offers absorbing information about the topic.

 


Game Theory in Computer Science

January 25, 2011
Leave a Comment


        By Galina Vitkova  

Computer science or computing science (sometimes abbreviated CS) is the study of the theoretical foundations of information and computation and of practical techniques for their implementation and application in computer systems. It concerns the systematic study of algorithmic processes that describe and transform information. Computer science has many sub-fields. For example, computer graphics, computational complexity theory (studies the properties of computational problems), programming language theory (studies approaches to describing computations), computer programming (applies specific programming languages to solve specific problems), and human-computer interaction (focuses on making computers universally accessible to people) belong to such very important sub-fields of computer science. 

Game theory has come to play an increasingly important role in computer science. Computer scientists have used games to model interactive computations and for developing communication skills. Moreover, they apply game theory as a theoretical basis to the field of multi-agent systems (MAS), which are systems composed of multiple interacting intelligent agents (or players). Separately, game theory has played a role in online algorithms, particularly in the k-server problem.

Interactive computation is a kind of computation that involves communication with the external world during the computation. This is in contrast to the traditional understanding of computation which assumes a simple interface between a computing agent and its environment. Unfortunately, a definition of adequate mathematical models of interactive computation remains a challenge for computer scientists. 

 
An online algorithm is the one that can process its input piece-by-piece in a serial mode, i.e. in the order that the input is fed to the algorithm, without having the entire input available from the start of the computation. On the contrary, an offline algorithm is given the whole problem data from the beginning and it is required to output an answer which solves the problem at hand.    

An animation of the quicksort algorithm sortin...

Image via Wikipedia

 (For example, selection sort requires that the entire list be given before it can sort it, while insertion sort doesn’t.) As the whole input is not known, an online algorithm is forced to make decisions that may later turn out not to be optimal. Thus the study of online algorithms has focused on the quality of decision-making that is possible in this setting.

The Canadian Traveller Problem exemplifies the concepts of online algorithms. The goal of this problem is to minimize the cost of reaching a target in a weighted graph where some of the edges are unreliable and may have been removed from the graph. However, the fact that an edge was removed (failed) is only revealed to the traveller when she/he reaches one of the edge’s endpoints. The worst case in study of this problem is simply a situation when all of the unreliable edges fail and the problem reduces to the usual Shortest Path Problem. This 

Johnson's algorithm for transforming a shortes...

Image via Wikipedia

 

 problem concerns detecting a path between two vertices (or nodes) of the graph such that the sum of the weights of its edges is minimized. An example is finding the quickest way to get from one location to another on a road map. In this case, the nodes represent locations, the edges represent segments of road and are weighted by the time needed to travel that segment.

The k-server problem is a problem of theoretical computer science in the category of online algorithms. In this problem, an online algorithm must control the movement of a set of k servers, represented as points in a metric space, and handle requests that are also given in the form of points in the space. As soon as a request arrives, the algorithm must determine which server to be moved to the requested point. The goal of the algorithm is to keep the total distance all servers move small, relative to the total distance the servers could have moved by an optimal adversary who knows in advance the entire sequence of requests.

The problem was first posed in 1990. The most prominent open question concerning the k-server problem is the so-called k-server conjecture. This conjecture states that there is an algorithm for solving the k-server problem in an arbitrary metric space and for any number k of servers. The special case of metrics in which all distances are equal is called the paging problem because it models the problem of page replacement algorithms in memory caches. In a computer operating system that uses paging for virtual memory management, page replacement algorithms decide which memory pages to page out (swap out, write to disk) when a page of memory needs to be allocated. Paging happens when a page fault occurs and a free page cannot be used to satisfy the allocation, either because there are none, or because the number of free pages is lower than a set threshold. 

 


Accumulate Your Vocabulary

September 25, 2010
2 Comments
                                          BGalina Vitkova   
 
  
          

Tips and steps

One of the most difficult work in studying a language is building and learning the language vocabulary. You should build your vocabulary all your life. But how? On the Internet and numerous English course books you can find ample tips and strategies that may help you in this sense.

In my opinion, based on my own experience and testing advices and recommendations of specialists in this area, the main, principal steps in building your own vocabulary are as follows: 

  • First of all, it is necessary to focus on several common ways to your vocabulary skills. Generally, building vocabulary goes from passive knowledge to active knowledge – by repeating a word so long until it becomes active vocabulary. This process requires time. So, be prepared for that and arm yourself with patience.
  • Learning vocabulary in groups of words appears to be much more effective than memorizing random lists. In this case words that are related to each other are more likely to be remembered over the long-term period.
  • The best way of learning words is to study and read systematically related texts and make a list of words of frequent occurrence.
  • Focusing on certain topics, which you are most interested in, brings good results, too;
  • For technical students and professionals such topics are comprised in technical texts typical and ultimate in their branch. Related activities include:
 
  • building a specialized list of common words appeared with high frequency in technical texts, which attract your attention,
  • building a list of professional words, expressions, collocations used in your branch,
  • building a list of words used in common communication (radio, TV, magazines, journals) to be able to understand discussions on topics that concern you;

After building such lists you can memorize them successfully.

Vocabulary Trees                                 

Vocabulary trees provide a solid ground for building your vocabulary and enhancing its level. People, especially students very often learn a new vocabulary by simply writing lists of new vocabulary words and then memorize these words by heart. Unfortunately, this technique generally brings only few positive consequences. Such learning helps you to pass exams, different tests, interviews etc. It leads to open up a kind of “short term” remembering. Vocabulary trees, on the other hand, provide a clue to “long term” memorization by placing vocabulary in connected categories. The example of a vocabulary tree on the right is taken up from http://esl.about.com/ .

A concept of vocabulary trees is applied in Improve Vocabulary with Vocabulary.Net Builder, which is strongly recommended to try. Enjoy the citrates from this publication:

“English vocabulary level has been shown to be strongly related to educational success. In addition, it is related to the level of occupation attained“. Bowker, R. (1981).

“A rich vocabulary is a valuable asset and an important attribute of success in any walk of life …”. Elley, W.B. (1988).

Vocabulary Tables

Vocabulary tables can help you in enriching your vocabulary based on different forms of a particular word that is known to you. If you build regularly vocabulary tables based on specific topics, namely in our case on technical topics, which you study or work in, you will certainly improve your knowledge of English.

Building tables on specific topics also helps to improve “long term” memory of related words. See below an example of such a vocabulary table based on words related to the post Speech and Handwriting Recognition in Windows 7 , which is the most popular last weeks:

NOUNS VERBS ADJECTIVES ADVERBS
availability, availableness   available availably
computer, computation, computerisation, computability compute, computerise computable,  computerisable,    
change change changeable changeably
implementation implement implementable  
improvement improve improvable  
recognition, recognisability recognise recognitive, recognisable recognisably
use, usage, usability use usable  

 

850 Words for Basic Conversational Fluency

Even if learning words from casual lists is certainly not the most effective method for long-term word remembering, it is very helpful to know what words are the most usable in English. It provides you with a good roadmap in studying the language. A list of such 850 words was published in 1930 in the book by Charles K. Ogden named Basic English: A General Introduction with Rules and Grammar.

The book contains basic verbs, articles, pronouns, prepositions, etc. split into categories. These 850 words should give you a solid basis for conversation. For more information about this list you can find in Ogden’s Basic English page. In any case, this list is an excellent starting point for building up a vocabulary that allows you to converse fluently in English.

Below the hyperlinks to these 850 Words are given:

Basics (verbs, articles, pronouns, prepositions, etc.)
General Nouns 1 – 200
General Nouns 201 – 400
Specific Nouns 1 – 200
Adjectives 1 – 150

For more advanced vocabulary building that helps you quickly improve your English study Kenneth Beare (http://esl.about.com/) recommends these vocabulary books. They will help you enhance your vocabulary, which is especially important for professional English knowledge.

 Use more your Dictionary

Since you can use it not only for finding words, but also in order to explain meanings of words, to improve your pronunciation by hearing words, in order to check spellings of less-known words and spelling variations, to find synonyms and more. Drop a look again at Dictionary – your best helper in mastering English words . There you will find the detailed information of possible usage of dictionaries for building your specialized vocabulary.

Read more about the topic at http://socyberty.com/languages/who-wants-to-improve-the-vocabulary/#ixzz0zzVciIw1 .

References

PS:

  • It is very helpful to be aware of what kind of the English reader you are. Complete Personality Quiz – What Kind of English Learner Are You?
  • Build your vocabulary and study English in compliance with your type of the English Learner!
  • In Free Rice you can find a very nice game that helps you in learning English words. English grammar and other topics. At the same time the game will entertain you.

 

 


Next Page »

    September 2017
    M T W T F S S
    « Jul    
     123
    45678910
    11121314151617
    18192021222324
    252627282930  

    Blog Stats

    • 203,228 hits

    Subscribe with BlogLines

    Translatorsbase

    Dynamic blog-up

    technorati

    Join the discussion about

    Seomoz

    I <3 SEO moz