"favourite university experience moment to date" Essay

"favourite university experience moment to date" - Essay Example one written by Socrates and the other one he had written in the late 1990s and the essence of liberties and inner human understanding (Alder et al 134). I produced my notebook and pen and started to write important points that came from him. One of the enduring lessons he told us during the lecture was that the inner self was an integral component of human existence that would lead us everywhere. Prof. Gregory advised the class to always strive for internal motivation when pursuing all human endeavours such as career and love. I always consider the most favourite because after that, I started working on a project of book writing that I had always postponed for a long time. Additionally, I started believing in myself because he told the class self-confidence and self-esteem were vital instruments of excellence in the world. Before he left, he posed to the class: who does not want to be

Fashion Photography and it's affects on young women Research Paper

Fashion Photography and it's affects on young women - Research Paper Example The essay "Fashion Photography and it's affects on young women" focuses on the influence of fashion photography on the women. The manner in which fashion photography has begun to distract the attention of the young women from different priorities in their lives leaves a very bad taste in the mouth, especially when it is being debated upon. They often emphasize more on what the celebrities are doing and what kind of new photographs are coming out in the open for them. They are reliant on fashion for looking after their own requirements, which are insignificant if seen properly. They perceive true beauty to be hidden within fashion photography which is simply untrue. They would rather emphasize on how they could derive value from fashion than looking at the reality aspects. The negative effects of fashion photography are important to understand here. This is because the young women start believing that fashion photography is for real and that they must follow the celebrities and stars into becoming somewhat similar. They are of the view that the world of media and fashion is filled with glamour which is not anywhere close to reality. This element essentially makes them feel that they must do something collectively to welcome what is being shown to them through the different media outlets and domains. As far as their self image and self esteem issues are concerned, these young women need to understand where they are going wrong. Since self image is something that shapes up one’s own thinking.

Game Development Essay Example for Free

Game Development Essay Once upon a time, the peaceful Kingdom of Greenland was invaded by the unexplained monster ruled by a tyrannous Garviod who was famous for his black magic. The beautiful Kingdom fell into ruin and despair. The inhabitants become an unexplainable creature. Some are became plants, trees, animals and those who are unkind to the nature became stones, garbage and monsters. Unfortunately, one of the inhabitants that have been transformed by a black magic was the old Prophet living in a cage and he became an old Tree. According to his prophecy, there will be a simple gardener who will have the power to fight the monsters in the Kingdom. The old prophet Tree traveled to find the man on his prophecy. As he traveled, he found Seedy. Humble and loving nature gardener who was transform to a seed. The old Tree gives him a map to find the treasure of X-lost. Then he said, â€Å"That the only way to break the evil spell and return the inhabitants of Greenland into normal was the magical light hidden in the treasure of X-lost.† But the ruling monsters Garviod heard about the magical treasure of X-lost and he keeps the treasure in one if his castle. Seedy humbly vowed to rescue the Kingdom and he started his journey to find the treasure of X-lost in the Castle of Garviod. Could Seedy overcome the many obstacles facing him and became a true hero? Let’s find it in the â€Å"Adventure of Seedy†. 1.2 Statement of the Problem The following problems were identified: 1. In many computer games, others kids are rewarded for being more violent. The child practicing violence in his own like killing, stabbing and shooting. 2. Some computer games are teaching kids a wrong values. 3. Some of games are simply for entertainment. 1.3Objectives The aims of the study are: 1. To development a game that would not portray violence. Rather than using a objects that represents violence, the proponent will design an object that are simple yet related to the environment. 2. To design a game that will teach the kids/user the value of environment. 3. To develop a game that makes learning fun not only to entertain. The items, weapons and object in the game are design next to the concept of environment.

Comparative Analysis of Rank Techniques

Comparative Analysis of Rank Techniques Abstract There is paramount web data available in the form of web pages on the World Wide Web (WWW). So whenever a user makes a query, a lot of search results having different web links corresponding to a user’s query are generated. Out of which only some are relevant while the rest are irrelevant. The relevancy of a web page is calculated by search engines using page ranking algorithms. Most of the page ranking algorithm use web structure mining and web content mining to calculate the relevancy of a web page. Most of the ranking algorithms which are given in the literature are either link or content oriented which do not consider user usage trends. The Algorithm called Page Rank Algorithm was introduced by Google in beginning. It was considered a standard page rank because as no other algorithm of page rank was in existence. Later extensions of page rank algorithm were incorporated along with different variations like considering weights as well as visits of links. This paper presents the comparison among original page rank algorithm as well as its various variations. Keywords: inlinks, outlinks, search engine, web mining, World Wide Web (WWW), PageRank, Weighted page rank, VOL I. Introduction World Wide Web is a vast resource of hyperlinked and a variety of information including text, image, audio, video and metadata. It is anticipated that WWW has expanded by about 2000% since its progression and is doubling in magnitude with a gap of six to ten months. With the swift expansion of information on the WWW and mounting requirements of users, it is becoming complicated to manage web information and comply with the user needs. So users have to employ some information retrieval techniques to find, extract, filter and order the desired information. The technique used filters the web page according to query generated by the user and create an index. This indexing is related to the rank of web page. Lower the index value, higher will be the rank of the web page. 1. Data Mining over Web 1.1 Web Mining Data mining, which facilitates the knowledge discovery from large data sets by extracting potentially new useful patterns in the form of human understandable knowledge and structuring the same, can also be applied over the web. The application being named Web Mining thus becomes a technique for extracting useful information from a large, unstructured, heterogeneous data store. Web mining is quite a immense area with dozens of developments and technological enhancements. 1.2. Web Mining Categories According to literature, there are three categories of web mining: Web Content Mining (WCM), Web Structure Mining (WSM) and Web Usage Mining (WUM) WCM includes the web page information. In it, the actual content pages whether semi structured hypertext or multimedia information are used for searching purposes. WSM uses the central part linkage that flows through the entire web. The linkage of web content is called hyperlink. This hyperlinked structure is used for ranking the retrieved web pages on the basis of query generated by the user. WUM returns the dynamic results with respect to users’ navigation. This methodology uses the server logs ( the logs that are created during user navigation via searching. WUM is also called as Web Log Mining because it extracts knowledge from usage logs. 1.2 Page Rank Algorithm (By Google) This is the original PageRank algorithm. It was postulated by Lawrence Page and Sergey Brin. The formula is: where is the PageRank of page A is the PageRank of pages Ti which link to page A is the number of outbound links on page Ti d is a damping factor having value between 0 and 1. The PageRank algorithm is used to determine the rank of a web page individually. This algorithm is not meant to rank a web site. Moreover, the PageRank of a page say A, is recursively defined by the PageRanks of those pages which link to page A. The PageRank of pages which link to page A does not influence the PageRank of page A consistently. In PageRank algorithm, the PageRank of a page T is always weighted by the number of outbound links C(T) on page T. It means, more outbound links a page T has, the less will page A benefit from a link to it on page T. The weighted PageRank of pages Ti is then added up. But an additional inbound link for page A will always increase page As PageRank. In the end, the sum of the weighted PageRanks of all pages is multiplied with a damping factor d which can be set between 0 and 1. Thus, the extend of PageRank benefit for a page by another page linking to it is reduced. They deem PageRank as a genre of user behaviour, where a surfer clicks on links at random irrespective of content. The random surfer visits a web page with a certain probability which is solely given by the number of links on that page. Thus, one pages PageRank is not completely passed on to a page it links to, but is divided by the number of links on the page. So, the probability for the random surfer reaching one page is the sum of probabilities for the random surfer following links to this page. Now, this probability is diminish by the damping factor d. Sometimes, user doesnot move straight to the links of a page, instead the user jumps to some other page randomly. This probability for the random surfer is calculated by the damping factor d (also called as degree of probability having value between 0 and 1). Regardless of inbound links, the probability for the random surfer jumping to a page is always (1-d), so a page has always a minimum PageRank. A revised version of the PageRank Algorithm is given by Lawrence Page and Sergey Brin. In this algorithm, the PageRank of page A is given as where N is the total number of all pages on the web. This revised version of the algorithm is basically equivalent the original one. Regarding the Random Surfer Model, this version is the actual probability for a surfer reaching that page after clicking on many links. The sum of all page ranks of all pages will be one by calculating the probability distribution of all web pages. But, these versions of the algorithm do not differ fundamentally from each other. A PageRank which has been calculated by using the second version of the algorithm has to be multiplied by the total number of web pages to get the according PageRank that would have been calculated by using the first version. 1.3 Dangling Nodes A node is called a dangling node if it does not contain any out-going link, i.e., if the out-degree is zero. The hypothetical web graph taken in this paper is having a dangling node i.e. Node D. II Research background Brin and Page (Algorithm: Google Page Rank) The authors came up with an idea to use link structure of the web to calculate rank of web pages. This algorithm is used by Google based on the results produced by keyword based search. It works on the principle that if a web page has significant links towards it, then the links of this page to other pages are also considered imperative. Thus, it depends on the backlinks to calculate the rank of web pages. The page rank is calculated by the formula given in equation 1. (1) Where u represents a web page and represents the page rank of web pages u and v respectively is the set of web pages pointing to u represents the total numbers of outlinks of web page v and c is a factor used for normalization Original PageRank algorithm was modified considering that all users donot follow direct links on web data. Thus, the modified formula for calculating page rank is given in equation 2. (2) Where d is a dampening factor which represent the probability of user using direct links and it can be set between 0 and 1. Wenpu Xing and Ali Ghorbani (Algorithm: Weighted Page Rank) The authors gave this method by extending standard PageRank. It works on the theory that if a page is vital, it has many inlinks and outlinks. Unlike standard PageRank, it does not equally distribute the page rank of a page among its outgoing linked pages. The page rank of a web page is divided among its outgoing linked pages in proportional to the importance or popularity (its number of inlinks and outlinks). , the popularity from the number of inlinks, is calculated based on the number of inlinks of page u and the number of inlinks of all reference pages of page v as given in equation 3. (3) Where and are the number of inlinks of page u and p respectively represents the set of web pages pointed by v. , the popularity from the number of outlinks, is calculated based on the number of outlinks of page u and the number of outlinks of all reference pages of page v as given in equation. 4. (4) Where and are the number of outlinks of page u and p respectively represents the set of web pages pointed by v. The page rank using Weighted PageRank algorithm is calculated by the formula as given in equation 5. (5) Gyanendra Kumar et. al. (Algorithm : Page Rank with Visits of Links (VOL)) This methodology includes the browsing behavior of the user. The prior algorithms were either based on WSM or WCM. But it incluses Page Ranking based on Visits of Links (VOL). It modifies the basic page ranking algorithm by considering the number of visits of inbound links of web pages. It assists to prioritize the web pages on the basis of user’s browsing behavior. Also, the rank values are assigned in proportional to the number of visits of links in this algorithm. The more rank value is assigned to the link which is most visited by user. The Page Ranking based on Visits of Links (VOL) can be calculated by the formula given in equation 6. (6) Where and represent page rank of web pages u and v respectively d is dampening factor B(u) is the set of web pages pointing to u Lu is number of visits of links pointing from v to u TL(v) is the total number of visits of all links from v. Neelam Tyagi and Simple Sharma (Algorithm: Weighted Page Rank Algorithm Based on Number of Visits of Links of Web Page) The authors incorporate Weighted PageRank algorithm and the number of visits of links (VOL). This algorithm consigns more rank to the outgoing links having high VOL. It is based on the inlink popularity ignoring the outlink popularity. In this algorithm, number of visits of inbound links of web pages are taken into consideration in addition the weights of page. The rank of web page using this algorithm can be calculated as given in equation 7. (7) Where represent page rank of web page u and v respectively d is the dampening factor B(u) is the set of web pages pointing to u Lu is number of visits of links pointing from v to u is the total number of visits of all links from v represents the popularity from the number of inlinks of u. Sonal Tuteja (Algorithm: Enhancement in Weighted Page Rank Using Visits of Link (VOL)) The author incorporated i.e. the weight of link(v,u) and calculated based on the number of visits of inlinks of page u. the popularity from the number of visits of outlinks are used to calculate the value of page rank. is the weight of link(v, u) which is calculated based on the number of visits of inlinks of page u and the number of visits of inlinks of all reference pages of page v as given in equation 8. (8) Where and represents the incoming visits of links of page u and p respectively R(v) represents the set of reference pages of page v. is the weight of link(v, u) which is calculated based on the number of visits of outlinks of page u and the number of visits of outlinks of all reference pages of page v as given in equation 9. (9) Where and represents the outgoing visits of links of page u and v respectively R(v) represents the set of reference pages of page v. Now these values are used to calculate page rank using equation (10) (10) Where d is a dampening factor B(u) is the set of pages that point to u WPRVOL (u) and WPRVOL(v) are the rank scores of page u and v respectively represents the popularity from the number of visits of inlinks represents the popularity from the number of visits of outlinks III Numerical analysis of various page rank algorithms To demonstrate the working of page rank, consider a hypothetical web structure as shown below: Figure showing a web graph having three web pages i.e. A, B, C, D Page Rank (By Brin Page) Using equation 2, the ranks for pages A, B, C are calculated as follows: (1) (2) (3) (4) Having value d=0.25, 0.5, 0.85, the page ranks of pages A, B and C become: Dampening Factor PR(A) PR(B) PR(C) PR(D) 0.25 0.9 0.975 1.22 0.99 0.5 0.8 0.9 1.35 0.95 0.85 0.85 0.829 1.53 0.357 From the results, it is concluded that PR(C)> PR(D)> PR(B)> PR(A) 2. Iterative Method of Page Rank It is easy to solve the equation system, to determine page rank values, for a small set of pages, but the web consists of billions of documents and it is not possible to find a solution by inspection method. In iterative calculation, each page is assigned a starting page rank value of 1 as shown in table 1 below. These rank values are iteratively substituted in page rank equations to find the final values. In general, many iterations could be followed to normalize the page ranks. d=0.25 d=0.5 d=0.85 Iteration PR(A) PR(B) PR(C) PR(D) PR(A) PR(B) PR(C) PR(D) PR(A) PR(B) PR(C) PR(D) 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1.25 1 1 1 1.5 1 1 0.5 1.425 0.575 2 0.875 0.97 1.21 0.99 0.875 0.94 1.44 0.97 0.75 0.788 1.46 0.82 3 0.90 0.975 1.22 0.99 0.86 0.93 1.4 0.965 0.77 0.80 1.48 0.83 †¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦. From the results, it is concluded that PR(C)> PR(D)> PR(B)> PR(A) 3. Page Rank with Visits of Links (VOL) (Gyanendra Kumar) Using equation 6, the ranks for pages A, B, C are calculated as follows: (A)=(1-d)+d((1) (B)=(1-d)+d((2) (C)=(1-d)+d(+(3) (D)=(1-d)+d((4) The intermediate values can be calculated as: Similarly other values after calculation are: 2/3 Having value d=0.25,0.5, 0.85 the page ranks of pages A, B and C become: Dampening Factor PR(A) PR(B) PR(C) PR(D) 0.25 0.83 0.82 1.23 0.818 0.5 0.635 0.606 0.808 0.6 0.85 0.2478 0.22 0.3449 0.1123 From the results, it is concluded that PR(C)> PR(A)> PR(B)> PR(D) 4. Weighted Page Rank (Wenpu Xing and Ali Ghorbani) Using equation 3, the ranks for pages A, B, C are calculated as follows: (C,A).(1) (2) (3) (4) The weights of incoming as well as well as outgoing links can be calculated as: (C,A)= IA/IA+IC = 1/ 1+2 = 1/3 =OA/OA=1 Having value d=0.5, the page ranks of pages A, B and C become: Dampening Factor PR(A) PR(B) PR(C) PR(D) 0.25 0.8526 0.8210 1.2315 0.75 0.5 0.7059 0.6176 1.235 0.5 0.85 0.3380 0.2458 0.6636 0.15 From the results, it is concluded that PR(C)> PR(A)> PR(B)> PR(D) 5. Weighted Page Rank Based on Visits of Link (VOL) (Neelam Tyagi and Simple Sharma) Using equation 7, the ranks for pages A, B, C are calculated as follows: )(1) )(2) (3) (4) The weights of incoming, number of visits of link as well as total number of visits of all links can be calculated as Having value d=0.25, 0.5 0.85, the page ranks of pages A, B and C become: Dampening Factor PR(A) PR(B) PR(C) PR(D) 0.25 0.8061 0.7836 1.015 0.8153 0.5 05981 0.5498 0.8825 0.5916 0.85 0.1734 0.1735 0.3469 0.1994 From the results, it is concluded that PR(C)> PR(D)> PR(A)> PR(B) 5. Enhancement in Weighted Page Rank Using Visits of Link (VOL) (Sonal Tuteja) Using equation 10, the ranks for pages A, B, C are calculated as follows: (1) (2) (3) Intermediate values can be calculated as follows: =IA/IA=1 =OA/OA=1 Having value d=0.25, 0.5, 0.85 the page ranks of pages A, B and C become: Dampening Factor PR(A) PR(B) PR(C) PR(D) 0.25 0.7226 0.7951 1.029 0.75 0.5 0.9557 0.6195 0.9115 0.5 0.85 1.911 0.5561 1.116 0.15 From the results, it is concluded that PR(C)> PR(B)> PR(D)> PR(A) Comparison chart of various Ranking Algorithms Algorithm Page Rank Page Rank with VOL Weighted Page rank WPRV EWPRV

Lost Lenore Essay -- essays research papers

  Ã‚  Ã‚  Ã‚  Ã‚  A raven is a dark and mysterious bird, and in this poem a raven visits a man with a message. Edgar Allan Poe’s â€Å"The Raven† is about a man who is having a mental breakdown because of the death of a dear friend. The narrator presents a frightening and sad setting, while throughout the poem, talking about his dear friend Lenore, who has passed away. Later, the mysterious figure of the Raven is introduced as he appears in the narrator’s chamber. Puzzled and terrified by the appearance of this dark vision, the narrator questions his guest in various ways to find out the meaning of his visit. No matter what the narrator asks, the Raven has only one eerie reply.   Ã‚  Ã‚  Ã‚  Ã‚  The narrator describes his frightening and sad surroundings, which reflect his state of mind caused by the death of his dear friend. The narrator opens his sad tale with â€Å"Once upon a midnight dreary† and later offers, â€Å"it was in the bleak December.† He describes his chamber as containing â€Å"many quaint and curious volume of forgotten lore† and his fireplace as â€Å"each separate dying ember wrought its ghost upon the floor.† With such images as the old musty books and the dying fire, a mood is set that represents the lonely and frightened state of mind of the narrator. Later, he sees curtains moving without a window open, and hears someone tapping on his chamber door. We begin to see that the narrator is losing touch with reality because he is deeply depressed by of the ...

Cause and Effect of Sleep deprivation Essay

I am a firm believer that many factors such as our culture, our upbringing, and beliefs that we were introduced to all affects what we do, how we live and even what we eat! People in China, Vietnam and Switzerland have been known to eat dogs for thousands of year, some as a source of survival during war and famine while others eat it as a cuisine meaning it is a part of their regular diet! I’ve even read somewhere that people in China have been known to say that a huge reason they consume dog meat is to keep them warm in the harsh winters! Have they heard of a jacket and hot coco? They don’t see it any different from eating cows and pigs, but someone like me thinks that is disgusting! I see people all the time whose treat their dog as their best friend, I’ve heard that when you begin to grow attached to your dog you soon see them as people. I could never imagine it being okay to eat a dog! Functionalism has a lot to do with this also when you come to think of it. This tradition has been the norm in these places for years! It wasn’t until recently that proposed laws have been presented to implement a law that bans the eating of cats and dogs. Americans are truly the people of the land of the free and are strong believers that a dog is a mans best friend, in my opinion. Beating, not feeding, and mistreating dogs are all violations of the law, neglect, and animal abuse! I could not even imagine hearing a story of someone eating one! It is common knowledge here that dogs are like people and should be treated as such and so they are not put on a dinner plate, at least the way I view things. I strongly feel that our individual believes and knowledge is the reason we eat what we eat, they are culturally relative in more ways that one. This definitely is a beautiful thing as everyone can be their own person and act how they feel but this causes cultural diversity conflict all the time! Take this scenario for instance; two people are meeting for a blind date and obviously know nothing about one another. It becomes time to order and the woman is disgusted by the menu because everything is meat and fat of the meat from some type of animal, see, she’s vegetarian. The woman loves animals and does not believe in eating them and this sparks a conversation. Do you think it’s a good one as her date has already ordered the number four, which is the half slab of baby back ribs with chicken shish kabobs, and a side of pork rings? I can imagine that she stormed out of there after giving him a good lecture. Though her actions are understandable they aren’t quite right. Ethnocentrism would be the perfect would to explain that situation! The woman thinks that he beliefs are the right ones and that the man is wrong for eating what he loves to eat! Ethnocentrism is when you believe that your culture, your beliefs are better than everyone else’s and only yours make sense! This is a big reason there is conflict within cultures. Instead of using cultural relativism and trying to understand others point of view or even just accepting it as their choice we fight for what we think is the right way, the only way. Interactionism helps us understand that our mind plays a role in our how what our body does including why we eat or don’t eat what we eat. I love dogs, so I would vomit at the thought of eating one. However, once again this doesn’t mean I should hate someone that eats it as a dish at home. Being open and understanding can truly help because just as the conflict theory states that there is a power struggle between cultures, these cultures have the power to become knowledgeable of one another and ultimately obtain culture relativism.

Taylor Swift and Feminism

Correct me if I'm wrong but isn't the goal of feminism to be empowered to do whatever you want? To establish equal opportunities for women in education and employment? To control your own life and make it into a success in a male dominated society? Taylor Swift Isn't hurting feminism, the only thing being detrimental to fearfulness Is your own backwards ass Interpretation of feminism. I'd you hadn't notice I have miserable luck with relationships. Actually luck isn't Even a factor, thieve all been miserable failures.So what's got me in a huff now? See I met this girl at a friends birthday party and we hit it off beautifully. Others thought we were really cut together and we Just clicked. For probably the first time I actually experienced someone who was legitimately interested in me even if It was Just a tiny sliver of interest. So she asked my friend about me and suddenly she has no interest In me. Why? Because I'm only 22. What the tuck. That has to be the stupidest reason I've enc ountered.What the bloody hell does my age have to do with anything? There is absolutely no reason age should make any difference unless its something dramatic like I was still in high school. Age is of no importance or an indication of anything, anyone can grow old all you have to do is live long enough. I was born at a very early age are you going to hold that against me? Jokes aside, its backward ass thinking like this that makes me shake my head in confusion at people. This excuse has been used twice before and I had to laugh at one use of It.One girl put forward that I was to old for her, which is funny because he still lives at home with her mom, her room basically resembles a 10 year olds with a bunch of Sailor Moon crap and she has no education or ambitions. I on the other hand have an education, am self-supportive (mostly) and have a job that gives Age isn't a factor anyone can control if you like a person you like a person end of story. It'd be like me refusing to date any girls who's name is Amy. My reasoning is backwards and stupid and its a factor that the other party can't control. It's not like one of us is underage or there's like a fifty year age difference.Yet when I told some of my friends they defended this girl saying she was right. â€Å"Sorry but she's right, it's weird for a girl to be the older person in a relationship. † Oh that's logical, way to stand up for your gender. I have no use for pathetic outdated thinking, and anyone that subscribes to this limited world view needs to rethink what it means to have freedom of choice. Makes me cringe that I have a better grasp of this than most, or that I'm the one who doesn't get things because I don't see rules in he same narrow world view that is considered the norm.You can't date someone younger than you? Or some stupid preconceived notion prevents your brain from choosing on your own. Hopefully someday more people will be able to unlock their mind forgo manacles and think for thems elves but until then I have to wonder why anyone thinks this is something. Maybe I am being ostracize and demanding a bit but I stand by this. If you meet someone and hit it off shouldn't that be what you look for in a relationship? Or some sort of statistic.