Discuss the extent to which authors are successful in representing the Essay

Discuss the extent to which authors are successful in representing the child's point of view in scenes about education in 20th century literature - Essay Example Her depiction of the education system is reflective of this simplistic and disconnected with reality. Roald Dahl’s depiction is similar, his reflection helps us also identify a need for escapism and appreciation of the absurd. Phil Grange, Sue Townsend and J.D Salinger all are very realistic in their depictions of the educational systems of the time which reflects the trouble that adolescents face dealing with the social realities around them. Harry Potter deals with a world of fantasy embedded in a boarding-school life. This depiction of school life is reminiscent of books like ‘Tom Brown’s school days’. Jill Murphy’s series is along the same line but less intense and targeted towards a younger audience. Each author uses his skill to depict the educational systems as children see them and each is a fusion of the author’s own style and experience and the broader social realities in which they were writing. This paper reviews children’s literature in the 20th century by focusing on specific pieces of writing, with special references to their depiction of the educational system. It will first review the relevant piece of literature and then discuss the social and historical context in which it was written. Although the paper describes the depictions of the educational system that the works cover it also studies the broader context in which these systems exist and also the elements in the work and the authors style which influence the way the educational system is depicted. Amongst the tools used the paper looks at the narrative styles used and the depiction of adults in the work to get insight into the impact that the social and historical elements have on children’s lives. The key focus of this paper is to explain that the depiction of childhood in children’s literature is influenced by the social and historical

Intensive Design Project of Fast Computer File System Essay

Intensive Design Project of Fast Computer File System - Essay Example The proposed file system has to cater to the needs of both these types that would allow for the storage and retrieval of any type of file. Secondly, the proposed file system will be incorporated with or will function under the simple commands of read (), write (), open (), store () that is similar to the calls under UNIX. The proposed file system will implement the concept of directories with a unique feature. As the total disk size given for the assignment is 120GB, storage and retrieval will take a lot of time is the entire disk space were to be considered as a single entity. Also the amount of information that would have to be maintained by the table in the main memory for the purpose of caching would be enormous and would occupy a lot of space. Therefore, in order to reduce the sizes of the tables and in order to improve the speed of accessing, the entire disk space will be partitioned into a series of virtual drives that will be considered as independent entities on logical terms. Thus, any file system will revolve around these virtual drives. Each virtual drive will have a size of 8GB each. Each of 8GB virtual drives will be made up of blocks of size 8kB each. Thus, in order to access any particular file, the file system can initially switch over to the particular drive by looking up at just 4 bits (24 =16), as the number of such virtual drives is 15. Thus, such an indexing will enable the search for a particular location simple and fast. VIRTUAL DRIVES As has been previously mentioned, the file system will support directories, but the unique features of the directories is that they can span over different virtual drives in case there is not enough space for an existing directory to accommodate more files. There will be two primary types of files that will be maintained by the file system, which will be known as the GB_dir table and the KB_fil table. As the names suggest, the former will be used to index the directories while the latter one will be used for files. The KB_fil table will have the following fields: Blocknum: This will be the number of the block that is already held by some file information. Filname: as the name suggests, this denotes the name of the file that occupies the block. Seq-nr: this field holds significance if the size of the file is more than that of a block (>8KB). Size: This filed is used to specify the actual size of the file. Endaddress: this will be localized to the block and will hold the last address of the memory location within the block, which is actually

Narrative Writting Essay Example | Topics and Well Written Essays - 1000 words

Narrative Writting - Essay Example I’ve lived here for about a year, but I still don’t know all that many people and an invitation to a costume party is unlikely at this point. The only people I know are the policeman and his wife next door and they’re not really the partying type. Then the doorbell rings. Not just the one she’s standing next to in the movie, but the one right behind my head. I almost hit my head on the ceiling I jump so high. The ring is followed immediately by frantic knocking. The knowledge that it’s the killer on the other side of the door in Scream doesn’t help much in getting me to answer the door. My feet are lead anvils and my legs are Jell-O, but some kind of curious invisible hook has snagged inside my belly compelling me to move to the door even while the two hemispheres of my brain argue back and forth about the wisdom of this movement. My right arm reaches to bang on the neighbor’s wall. He is a cop, after all. But the wall we share is on my left side, so it’s a fruitless but valiant effort by the creative side of me to preserve me from my logical curiosity. The ten steps it would take for me to reach the door of my tiny apartment have stretched to a marathon mile and the standard beige carpet has become molasses warmed. I have to walk past a darkened hallway on my right before I even come close to the door. The air kicks on at just this moment and I receive a quick burst of warm air puffing out of the open spaces. It feels like the breath of some giant creature leaning against my neck. The air is stale, I haven’t cleaned yet this week, and it’s full of dust since this is the first week the heater’s been on this year. This hallway reaches back into the bedrooms and bathroom areas. It’s an open hole, a gaping darkness, threatening to swallow me up or concealing malevolent beings, I don’t know which. I’m actually afraid to move across this open space. It just now occurs to me that the cat had

Strathfield Health Centre Case Study Example | Topics and Well Written Essays - 750 words

Strathfield Health Centre - Case Study Example It will also demonstrate an ability to relate key roles of information systems in improving supply and inventory activities. The point of supply chain managing is to do away with inefficiencies, mainly surplus inventory. Inventory is a barrier to uncertainty. Uncertainty is hard to predict. Partnership between supply chain allies assists to lessen uncertainty since they have a faster ability to react and adjust, but they do not eradicate it. Supply chain visibility is extremely valuable, in that, it eases uncertainty and manages inventories (Silver 7). This would make it easier for SHC to know what inventory is where in the supply chain. This should be from purchase demands to suppliers to where customer demands are collected at supply centers, the better SHC can run their inventory. People, process and skill used to manage all inventory should be examined by the SHC. The following method should be applied by the SHC management team in order to improve its supply of medical products. Plan for an improved supply system In order to manage an office supplies inventory, SHC needs recognize everything that is happening around them. The SHC team needs to look over their office supplies and determine which items are mostly used in the health centre. Secondly, the team needs to create a list of items that if they lacked at any moment it would lead to a halt of the business. SHC should store a reasonable amount of these medical supplies in case a shortage arises. They will bring efficiency around the health care centre. The SHC team should also maintain a list of the required supplies to save them the energy and time of preparing a new list every time they want to order medical supplies. They should look over the list of supplies on a weekly basis to update it and make sure that all medical supplies that the health centre requires are within their reach. Key roles of Information Systems in improving supply and inventory processes An information system (IS) refers to any blend of information technology and an individual’s actions that sustain management, operations and making of decisions. It is also referred to as an application landscape (Rainer 3). In an exceptionally wide logic, the phrase information system is normally used to refer to the communication between processes, people, technology and data. In this view, the expression is used not only to refer to the ICT that an organization employs, but also to the means in which individuals in the organization can work together with this technology in support of business activities (Rainer 45). An organization’s information systems refer to a set of interconnected modules that gather, develop, store up, and distribute information. This is for the reason of supporting an organization’s administrative team in making decisions, controlling, coordinating and analyzing. Improving the computer information system is not a choice in this technology-motivated age. It is an obligation. Organizations that use the latest information system to collect, incorporate, and calculate internal plus external information are achieving competitive benefit over other organizations (Rainer 50). With the development of communication networks and systems, there are almost no obstacles between the organization’s administration, customers, employees and suppliers. Management now caters much faster to a customer’s requirements and moans. Networked computing systems have

Texas Science Scholars program Essay Example for Free

Texas Science Scholars program Essay Mrs. Page, I would like you to know that I do not consider English as one of my strongest subjects; however, I still am excited to be in this class. From what I can tell, your particular style of instruction will definitely be helpful towards my education in literature. I feel you are someone who can help me to better myself in writing. My name is Michael Cortinas. I will be majoring in Computer Science and I am currently part of the Texas Science Scholars program. I enjoy reading, but struggle when it comes to writing on a designated prompt. In high school, I was part of both the varsity track, and cross-country team. Before college, I would run two or three miles every morning, but, because all my classes take place in the morning, I haven’t had time. I have been working part-time at H-E-B for nearly a year now, where I do anything from cashier to push carts. I currently live with my mother, step-father, and three younger siblings, meaning most of my homework will be done on campus. When it comes to college, I hope to obtain the skills necessary to become an impact in my community and in the lives of those close to me. I feel if I can get enough from college, I can be the type of person that people feel confident in putting their trust and coming to for advice. I guess this desire was inspired my great-grandfather, who passed away last year. He was someone that everyone felt comfortable confiding in and always seemed to know just what to say. Your class, being one that works with word choice, is a great start towards this goal. I feel that I am going to enjoy your class and all it has to offer.

Determining Attributes to Maximize Visibility of Objects

Determining Attributes to Maximize Visibility of Objects A Critique on  Determining Attributes to  Maximize Visibility of Objects Muhammed Miah Gautam Das Vagelis Hristidis Heikki Mannila Vidisha H. Shah 1. Summary of the published work Das, Hristidis, and Mannila (2009, p. 959) discussed about the ranking function and top k retrieval algorithms that helps user (potential buyers to search for the required product from the available catalog. The problem is how a user (potential seller) should select attributes of new tuple that the product stands out from the other available products. So there are several formulation that were developed by the author and few that are already in practice. According to authors, to run a query(search) keywords are entered on basis of which search is conducted (p. 959). The query anserwing system may return all the values that fulfill the condition it is also called as unranked retrieval or Boolean retrieval, or can rank the answers and return top k values known as ranked retrieval or Top-k retrieval. The example given by the author is objects can be ranked on the attribute based on price or based on relevance. The example and a problem related to it is described by the author. A user wants to classify an ad to rent an apartment in an online newspaper (p. 959). The given ad (tuple) has various attributes like number of bedrooms, location and so on. The cost factor is also involved in any ad so accordingly attribute that will provide better visibility should be selected. To understand which attributes provide better visibility we can built it on basis of previous sellers recommendation (tradition technique) or an argument by which we can view the ranking function buy which we can understand which attribute will lead to high ranking score. Example adding an attribute swimming pool can increase the visibility, or a catchy title or indexing keywords (for an article). Let D be the database of some product that has been advertised already (competitor). Author is considering that the database can be a relational table or a text document (p. 960). If database is a relational table then each tuple i n the table is a product and every column is an attribute related to the product. If database is a collection of text document then each document contains data regarding a specific product (ad). The set of queries or search conditions that have been executed in past by the user is stated as Q. therefore Q is the â€Å"query log† or â€Å"workload†. The query log is the record of the queries that have been used buy the potential buyers in the past. So the query could be like SQL query or query based on key word that will return a tuple from D(database). The problem given by the author is when a D(database), Q(query log), new tuple t and integer m are given determine best m attributes for tuple t such that when the shortened version of the tuple t with m attributes is inserted in d then the number of queries from Q retrieving tuple t is maximized (p. 960). In this paper variant of m is also considered that is when m is given by the user or when m is not mentioned. In this paper author has consider several variants like Boolean (unranked retrieval) (P 960), categorical variant, text and numeric data variant and conjunctive and disjunctive query semantics. Budget variant is also considered where in if m is not given the objective of maximizing the visibility is achieved keeping m minimum. No- budget variant is also considered where value of m is not given and the only aim is to gain maximum visibility of the object and for that all possible attributes can be added. In the preliminaries section author describes that for the given database D it contains tuples {t1, t2,†¦.tm}. Each tuple t has various attributes { a1, a2,†¦. an}. Tuple t will have either value 1 or 0. 0 implies that the attribute is absent and 1 implies that the feature is available. Tuple Domination means that if a tuple has all attributes value 1 that that tuple dominates. Tuple compression of t which has m attributes. It retains all 1’s in m and converts rest all attributes to 0 (p. 961). In Conjunctive Boolean with query log(CB-QL) variant the problem definition stated by the author is when a Q with Conjunctive Boolean retrieval semantics, tuple t, and integer m are given then have to compute compressed tuple with m attribute with maximum visibility(p. 961). For this problem author uses NP-Completeness Results and derives the Theorem that the decision version of CB-QL problem is NP-hard. Author explains various algorithms for Conjunctive Boolean with query log (p. 961). First is Optimal Brute Force Algorithm. As stated earlier that CB-QL is NP-hard so during worst case optional algorithm will run in polynomial time. The problem can be solved by a simple. This problem can be solved by simple brute force algorithm. So can be called as Brute Force-CB-QL which will consider all the combination of all m attributes of the tuple t such that the combination will satisfy to achieve maximum visibility among Q. In Optimal Algorithm Based on Integer Linear programming an ILP framework CB-QL can be described as follows, new tuple t be a Boolean vector has various attributes {a1,a2,†¦an}. Q be the query log and S be the total number of queries in query log. So the task is to This integer linear formulation is attractive unlike other general IP solvers, ILP solvers and are also usually more efficient(p. 962). According to author in Optimal Algorithm that is Based on Maximal Frequent Item Sets according to the author this algorithm is based on Integer Linear Programming, but this has certain limitation so author says it is impractical if there are more than few hundred of queries in the Q query log. The author has develop an alternate approach for the same which scales large query logs very well (p. 963). This algorithm is called MaxFreqItemSets-CB-QL, for this author has defined the frequent item set problem, Complementing the Query Log, Setting of the Threshold Parameter, Random Walk to Compute Maximal Frequent Item Sets, Complexity Analysis of a Random Walk Sequence, Number of Iterations, Frequent Item Sets at Level M _ m, Preprocessing Opportunities, The Per-Attribute Variant. Author says in Greedy Heuristics algorithm becomes slow for large query logs when maximal frequent item set based algorithm has better scalability then the IPL based algorithm (p. 964). So author has developed suboptimal greedy heuristic for solving CB-QL. The algorithm consist of ConsumeAttr-CB-QL computes the number of times each attribute appears in Q. Using this top m attributes that have highest frequency is computed. The algorithm ConsumeAttrCumul-CB-QL first selects the attributes from the query log Q that has occurred maximum times and then finds the attribute that occurs second highest in the Q, and so on. The algorithm ConsumeQueries-CB-QL picks the query with minimum number of attributes first, and then selects all attributes specified in the query. In next section author explains problem variant for text data. In the text database there is a collection of documents, and each document consist a data of a particular ad (p. 965). The problem definition for text data is that query is a set of keywords and have to retrieve top-k documents via query specific scoring functions and make the document maximum visible. According to author text database can be directly mapped into Boolean database (p. 965). So the algorithm and the working can be made similar to that of Boolean Data but author says that there is a problem with attribute selection for text data is NP-complete. It can convert it into Boolean considering each key word as a Boolean attribute. So according to author since text database can be converted to Boolean database in the algorithm for text data the are two issues firstly to view each text keyword as a Boolean attribute in query log Q, and none of the optimal algorithms are feasible for text data (p. 965) . Second issue is that in text data the scoring functions that are used takes account of the document length and leads to decrease the score if keyword has low frequency. In the next section author has described about the experiments that were conducted and there results. For this experiments system that was used had following configuration P4, 1 GB RAM, 3.2- GHZ processor, 100 GB HDD, Microsoft SQL Server 2,000 RDBMS. Algorithms were implemented in C# Language, for backend RDBMS and connectivity was done using ADO. 2 data sets were used for Boolean data and publication titles were used for text data experiments. 185 queries in query log were created for the experiments, 205 distinct keywords were created by other students. The experiment worked well for Boolean data CB-QL where top m attributes were given and had maximum visibility for 185 queries. Individual experiments were done to calculate the execution time of each algorithms of CB-QL. Various statistical data is given by the author that gives how individual algorithm runs under various workload. Various similar experiments were done for text data also and its algorithm and similar statistical d ata is given by the author (p. 965). In the next section various other problem variants for Boolean data, categorical and numeric data are considered. In that author has first explain Conjunctive Boolean-Data (CB-D) in which author describes its problem definition for maximum visibility given D(database), Q(query log), t (new tuple) and m(integer). For the given problem definition complexity results for CB-D and its algorithm are given by the author (p. 967). Then next variant considered is Top-k – Global Ranking (Tk-GR) and Top-k – Query-Specific Ranking (Tk-QR) and in that author considers Top-k retrieval using Global and Query-Specific Scoring Function. Then problem definition for Tk-GR and Tk-QR is stated by the author and then its complexity and algorithm for the same are given(P.968). Next variant considered by the author is Skyline Boolean (SB) where skyline retrieval semantics are considered then problem definition for SB then its complexity and algorithms are discussed. In the similar way remainin g variants Conjunctive Boolean—Query Log—Negation (CB-QL-Negation), Maximize Query Coverage (MQC), Categorical and Numeric Data are discussed by the author(P. 969). In conclusion author describes that how the best attributes for the problem can be selected from the data set given query log. Author has presented variants for many cases like Boolean data or categorical or text data and numeric data (p. 972). And has showed that even though the problem is NP complete the optimal algorithms are feasible for small inputs. Author has also presented greedy algorithms that can produce good approximation ratio. 2. My Opinion on published work The use of internet and network has increased tremendously and with that the data available on network has increased but the main problem is information to knowledge conversion that is finding data that is useful to the user, over spam. The algorithm discussed by the author can be used to improve the visibility of the document. In the paper author has not just given algorithm for Boolean type data but also text data and other variant that is the algorithm can be used for real time data that is in various forms. The main focus of the author is on potential seller and what all attributes should be added to maximize the visibility of the advisement or the document on the web so that the potential buyers can view that document in first few options, but this can be used other way round to and using this spam can be created, a document that is a fake document that has various attributes which are not true but are added added to gain maximum visibility, which should not be even displayed in the given category. The author makes assumption about the competitors or say other advertise, and assumptions about the users preferences are made as well. The queries in the query log where written by random students and not according to what actual users want, so there is no guarantee that this will work equally well in real time environment and will actually maximize the visibility with real time users and on real network. As given by the author in every problem definition of every variant that given D database and given Q query log but in real time for many application neither D(database) nor Q(query log) is available for analysis so user have to make assumptions about the competitors and users (potential buyers) need and there after have to decide the Top-k attributes from the subset of all the attributes that will help the user to achieve maximum visibility with minimum number of attributes. In the paper the author has given various variant by which the visibility of the object can be maximized in various cases and has various optimal algorithms and greedy algorithm. Optimal algorithm gives optimal outputs but works well for small inputs only as and when the size of input increases the algorithm does not work well. Greedy algorithm produces approximate results that can be seen from the experiments done by the author with various variants. According to Ao-Jan Su, Y. Charlie Hu, Aleksandar Kuzmanovic, and Cheng-Kok Koh Page rank of any document or advertisement is not only depended on the attributes but also on key words in host name, the key words in the URL, HTML header so with the selection of proper attributes in the document user also needs to keep a check on above mentioned factors also to maximize the visibility of the object.(2010, P. 55) Angelica Caro has given a table of Data quality and visibility rankings for Spanish university portals. In which author has given DQ* ranking, Visibility ranking, Partial visibility rankings in terms of Site, Links and Popularity, Distance* where *DQ means data quality and *Distance between the data quality and visibility rankings. Teal numbers indicate the portals that are relatively close in both rankings. So from the result given by the author it is seen that there is not a precise order that is the data quality of a site can be ranked 1 but visibility is 19 because it is based on other factors also like its popularity, links, sites and distance. So even if the DQ is not very good but it is popular or it has many incoming links can lead to improve the overall ranking of the page and thereby maximizes the visibility of the page. The statistic of the site that has ranks first in visibility is data quality is 5 visibility is 1 site 1 links 1 popularity 3 distance 4 so it can be seen that to gain maximum visibility we cannot just depend on attributes of the data that is not just data quality but there are various other factors that is required to be considered to improve visibility of the object, that is not considered in the paper by the author.(2011, p. 46). References Ao-Jan Su, Hu, Y.C., Kuzmanovic, A., Cheng-Kok Koh (2010). How to Improve Your Google Ranking: Myths and Reality.2010 IEEE/WIC/ACM International Conference onWeb Intelligence and Intelligent Agent Technology (WI-IAT),1, 50-57.doi: 10.1109/WI-IAT.2010.195 Caro, A., Calero, C., Moraga, M.A.(2011). Are Web Visibility and Data Quality Related Concepts?.Internet Computing, IEEE, 15(2), 43-49.doi: 10.1109/MIC.2010.126 Miah, M., Das, G., Hristidis, V., Mannila, H. (2009). Determining Attributes to Maximize Visibility of Objects.Knowledge and Data Engineering, IEEE Transactions on,21(7), 959-973.doi: 10.1109/TKDE.2009.72

Fight Club :: Fight Club Tyler Durdens

Fight Club Before the Narrator actually "meets" Tyler, he sees him in brief, one-frame flashes, representing Tyler's development in his mind. Below is a list of these appearances. - Tyler is standing in front of the copier at the Narrator's company, as the Narrator says, "Everything is a copy of a copy of a copy." - When the Narrator goes to the doctor for his insomnia, Tyler appears as the doctor tells him to go to the testicular cancer support group. As the doctor says, "That's pain," Tyler is standing just over his shoulder, laughing. - At the support group, when the leader says "really open ourselves up," Tyler is smirking and leaning against him with his arm around him. - After the Narrator confronts Marla and is watching her walk away, Tyler appears in his line of vision, smoking. - In the Pressman Hotel welcome video, Tyler is the waiter on the far right. (Thanks to Caite!) This appearance isn't actually subliminal. The Narrator, as Tyler, really did work at the Pressman Hotel, so he would have appeared in the video. - Tyler is riding down an escalator as the Narrator is riding up in an airport. Nick writes, "In the beginning there are quick flashes of Tyler in the back ground. I counted 3 of them in different times. Later in the movie they explained the projectionist job that Tyler had and how he put pornographic clips in family movies. Do you think those two things have anything in common?" I hadn't really thought about this before, but it's a good point. The characters are aware that they are in the movie (Tyler's references to "flashback humor," etc.), and Tyler DID splice a porn clip in at the end, so it's very likely that he put himself in as well. Kevin asks, "...what are your thoughts on why the bullet killed Tyler but not the Narrator? My own theory is that Tyler was destroyed because the Narrator hit bottom when he was so unafraid of death that he was able to put a gun in his mouth and pull the trigger. The Narrator no longer needed Tyler because he had hit bottom, and he had become Tyler." Cramer replies, "I disagree on this point. Tyler's presence isn't completely gone. While the main internal conflict of the Narrator may have been how to mesh Tyler's and his own personalities together into a single individual, I believe that the reoccuring thesis of "It's only after you've lost everything that you're free to do anything," can explain that Tyler (the rebel, the nonconformist) is not "dead.