Life Experiences That Influenced My Academic Career

Running Header: LIFE EXPERIENCES 2 Life Experiences that Influenced My Academic Career My collegiate career began in August 1999, only a few months following my high school graduation. Most of my classmates had gone through the process of submitting college applications and applying for scholarships and financial aide, signing military contracts and receiving funds for school via those means, in fact, many had post graduation plans before we reached ninth grade. That was not my reality however. I had plans, but they had nothing to do with attending college, pursuing scholarships or financial aide, or even joining the military. My plans were on the total opposite end of the spectrum. My intentions were to relax for the next year and enjoy some perks of being â€Å"out of school.† The justification for this extreme slacker mentality was solidified by possessing my diploma. No one had graduated high school in my immediate family except my mother. Honestly speaking, no one besides my mom had attained success beyond 11th grade. There was no one who could contest my decision to suspend my educational endeavors until I decided to reengage. Prior to this place in life I had been provided a false sense of reality, in that, there was a notion that I could get by on talent alone. As a result of this ideology, instead of pursuing greatness, whether it was by way of great opportunity, or exercising the habits and practices of the great people around me, I would prefer to do what felt good,Show MoreRelatedWhy Is It Queer With Its Twists And Turns As Every One Of Us Sometimes Learn865 Words   |  4 PagesConsidering the Present â€Å"Life is queer with its twists and turns as every one of us sometimes learn† (Don’t Quit, 1881-1959). As I begin to reflect on events in my life that made me who I am today in my development, I would have to highlight receiving my high school diploma and passing the Praxis Para-Pro assessment. These two events have shaped my development in terms of gaining opportunities, increased confidence, and self-respect. These two events have also taught me the importance of remainingRead MoreReporting Studying senior social science subjects was the most influential factor which provided a1600 Words   |  7 Pagesa wonderful opportunity to discover my abilities and develop skills and confidence in critical thinking and systematic research processes. Especially, getting an A+ for a psychology report assignment and genuinely enjoying the process have given me a sense of competence in performing similar tasks such as planning and conducting experiments, analysing results, and evaluating research processes. 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Resource Allocation Paper - 2424 Words

Resource Allocation Paper Jody Bryant, Vann Haigler, Rose Matos, and James Sampson University of Phoenix Mark Fechtel May 25, 2006 Resource Allocation Paper Project management is the discipline of defining and achieving targets while optimizing the use of resources: time, money, people, materials, energy, space, etc., over the course of a project. The most important resources that project managers have to plan and manage on day-to-day basis are people, materials, equipment and working capital. Obviously, if these resources are available in abundance then the project could be accelerated to achieve shorter project duration. On the other hand, [Avoid using colloquial language, slang or jargon in formal†¦show more content†¦She will be responsible for overseeing Big Time Builders, Keep-em Happy Architectural, Martin Grading, and other of contractors such as electrical, plumbing, mechanical, and industrial engineers. James Vann Haigler is functional manager over quality assurance. 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Data Compression Essay Example For Students

Data Compression Essay subject = Information Theorytitle = Data CompressionData Compression-inbeginners terms?Data Compression just sounds complicated. Dont beafraid, compression is our good friend for many reasons. It saves hard drivespace. It makes data files to handle. It also cuts those immense file downloadtimes from the Internet. Wouldnt it be nice if we could compress all filesdown to just a few bytes?There is a limit to how much you can compressa file. How random the file is, is the determining factor to how far it canbe compressed. If the file is completely random and no pattern can be found,then the shortest representation of the file is the file it self. The actualproof that proves this is at the end of my paper. The key to compressing afile is to find some sort of exploitable pattern. Most of this paper willbe explaining those patterns that are commonly used. Null suppression isthe most primitive form of data compression that I could find. Basically,it says that if you have different fields that data is in (possibly a spreadsheet), and any of them have only zeros in them, then the program just eliminatesthe data and goes straight from the empty data set to the next. Only onestep up from null suppression is Run Length Encoding. Run length encodingsimply tells you how many of what you have in a row. It would change a setof binary data like {0011100001} into what the computer reads as (2)zeros,(3)ones, (4)zeros, 1. As you can see, it works on the same basic idea of findinga series of 0s (null suppression) and 1s in this case too and abbreviatingthem. Once the whole idea of data compression caught on, more people startedworking on programs for it. From these people we got some new premises towork with. Substitutional encoding is a big one. It was invented jointlyby two people: Abraham Lempel and Jakob Ziv. Most compression algorithms (bigword meaning roughly ?program) using substitutional encoding start with ?LZfor Lempel-Ziv. LZ-77 is a really neat compression in which the programstarts off just copying the source file over to the new target file, but whenit recognizes a phrase of data that it has previously written, it replacesthe second set of data in the target file with directions on how to get tothe first occurrence of it and copy it in the directions place. This is morecommonly called a sliding-window compression because the focus of the programis always sliding all around the file. LZ-78 is the compression that mostpeople have in their homes. Some of the more common ones are ZIP, LHA, ARJ,ZOO, and GZIP. The main idea behind LZ-78 is a ?dictionary. Yet it worksquite a bit like the LZ-77. For every phrase it comes across, it indexes thestring by a number and writes it in a ?dictionary. When the program comesacross the same string, it uses the associated number in the ?dictionary insteadof the string. The ?dictionary is then written along side the compressedfile to be used in decoding. There is a combined version of LZ-77 anLZ-78. It is called LZFG. It only writes to the dictionary when it findsthe repeated phrase, not on every phrase. Then instead of LZFG replacing thesecond set of data with directions on how to get to the first occurrence ofit, the program puts in the number reference for the dictionarys translation. Not only is it faster, but it compresses better because of the fact that itdoesnt have as big of a dictionary attached. .u653a13bfb98b37c7dc1e9eb906c53603 , .u653a13bfb98b37c7dc1e9eb906c53603 .postImageUrl , .u653a13bfb98b37c7dc1e9eb906c53603 .centered-text-area { min-height: 80px; position: relative; } .u653a13bfb98b37c7dc1e9eb906c53603 , .u653a13bfb98b37c7dc1e9eb906c53603:hover , .u653a13bfb98b37c7dc1e9eb906c53603:visited , .u653a13bfb98b37c7dc1e9eb906c53603:active { border:0!important; } .u653a13bfb98b37c7dc1e9eb906c53603 .clearfix:after { content: ""; display: table; clear: both; } .u653a13bfb98b37c7dc1e9eb906c53603 { display: block; transition: background-color 250ms; webkit-transition: background-color 250ms; width: 100%; opacity: 1; transition: opacity 250ms; webkit-transition: opacity 250ms; background-color: #95A5A6; } .u653a13bfb98b37c7dc1e9eb906c53603:active , .u653a13bfb98b37c7dc1e9eb906c53603:hover { opacity: 1; transition: opacity 250ms; webkit-transition: opacity 250ms; background-color: #2C3E50; } .u653a13bfb98b37c7dc1e9eb906c53603 .centered-text-area { width: 100%; position: relative ; } .u653a13bfb98b37c7dc1e9eb906c53603 .ctaText { border-bottom: 0 solid #fff; color: #2980B9; font-size: 16px; font-weight: bold; margin: 0; padding: 0; text-decoration: underline; } .u653a13bfb98b37c7dc1e9eb906c53603 .postTitle { color: #FFFFFF; font-size: 16px; font-weight: 600; margin: 0; padding: 0; width: 100%; } .u653a13bfb98b37c7dc1e9eb906c53603 .ctaButton { background-color: #7F8C8D!important; color: #2980B9; border: none; border-radius: 3px; box-shadow: none; font-size: 14px; font-weight: bold; line-height: 26px; moz-border-radius: 3px; text-align: center; text-decoration: none; text-shadow: none; width: 80px; min-height: 80px; background: url(https://artscolumbia.org/wp-content/plugins/intelly-related-posts/assets/images/simple-arrow.png)no-repeat; position: absolute; right: 0; top: 0; } .u653a13bfb98b37c7dc1e9eb906c53603:hover .ctaButton { background-color: #34495E!important; } .u653a13bfb98b37c7dc1e9eb906c53603 .centered-text { display: table; height: 80px; padding-left : 18px; top: 0; } .u653a13bfb98b37c7dc1e9eb906c53603 .u653a13bfb98b37c7dc1e9eb906c53603-content { display: table-cell; margin: 0; padding: 0; padding-right: 108px; position: relative; vertical-align: middle; width: 100%; } .u653a13bfb98b37c7dc1e9eb906c53603:after { content: ""; display: block; clear: both; } READ: Genetic Diversity In Agriculture EssayStatistical encoding is anotherone of the new compression concepts. It is an offshoot of the LZ family ofcompressors; It uses basically the same style as LZFG, but instead of assigningthe numbers in order that the strings come out of the source file, statisticalcompressors do some research. It calculates the number of times each stringis used and then ranks the string with the most number of uses at the top ofthe hash table. The string with the least is ranked at the bottom. (A hashtable is where the rank is figured) The higher up a string is on this list,the smaller of a reference number it gets to minimize the total bit usage. This gives this compression just a slight edge on the others, but every littlebit helps. (ha ha -bit- )Beware! There are a few compression programsout there that claim wonderful compression ratios; ratios that beat the compressionlimit for that files randomness. These programs arent really compressionprograms. They are OWS and WIC. Never compress anything with these. Whatthey do is split up the file that you desired to compress and hide most ofit on another part of your hard drive. OWS puts it in a specific spot on thephysical hard drive disk. WIC puts the extra information in a hidden filecalled winfile.dll. The real problems with these programs are that if youdont have the winfile.dll or the information on the certain spot on your drive,then the program wont put your file back together. My original intentwith this project was to invent a new compression algorithm. I started withthe idea that if you took the file in its pure binary form and laid it outin a matrix, there were certain rows and columns that you could add up to getan output that would be able to recreate the original matrix. I was closetoo. I had four different outputs that actually would be what would make upthe compressed file that combined together to create one output for each bit. From this single output I could determine if the bit was 1 or 0. It workedperfectly for matrixes of 11, 22, and 33. Except that with this small ofa matrix, I wasnt compressing it at all. It was more of a coding system thattook up more space than did the original file. I even found a way to shrinkthe size of the four outputs but it was not enough to even break even on bitcount. When I got to the 44s I found an overlap. An overlap is a term Imade up for this algorithm. It means that I got the same single output fora 1 as I did a 0. When that happens, I cant figure out which it is: a 1or 0. When you cant recreate the original file, data compression has failed. It becomes lossy. I needed a fifth original output. If you want more informationon how I thought the algorithm would have worked, please refer to my InventorsLog that I included. Its way too much to re-type here and it would serveno real purpose in this paper. If you were paying attention earlier, youwould be saying, ?Why dont you find a pattern? Otherwise you cant compressit. You are treating it like a random file.? I didnt find out that it wasimpossible to compress random data until about the time my algorithm was failing. Becauseof my setbacks I started looking for an entirely new way to compress data,using a pattern of some sort. I got to thinking about all of the existingalgorithms. I wanted to combine a hash table, statistical coder, and a runlength coder. The only hard part that I would see in that would be tryingto get the patent holders of each of those algorithms to allow me to combinethem and actually modify them slightly. .u8e84900216c659a8b350f624c6667fc7 , .u8e84900216c659a8b350f624c6667fc7 .postImageUrl , .u8e84900216c659a8b350f624c6667fc7 .centered-text-area { min-height: 80px; position: relative; } .u8e84900216c659a8b350f624c6667fc7 , .u8e84900216c659a8b350f624c6667fc7:hover , .u8e84900216c659a8b350f624c6667fc7:visited , .u8e84900216c659a8b350f624c6667fc7:active { border:0!important; } .u8e84900216c659a8b350f624c6667fc7 .clearfix:after { content: ""; display: table; clear: both; } .u8e84900216c659a8b350f624c6667fc7 { display: block; transition: background-color 250ms; webkit-transition: background-color 250ms; width: 100%; opacity: 1; transition: opacity 250ms; webkit-transition: opacity 250ms; background-color: #95A5A6; } .u8e84900216c659a8b350f624c6667fc7:active , .u8e84900216c659a8b350f624c6667fc7:hover { opacity: 1; transition: opacity 250ms; webkit-transition: opacity 250ms; background-color: #2C3E50; } .u8e84900216c659a8b350f624c6667fc7 .centered-text-area { width: 100%; position: relative ; } .u8e84900216c659a8b350f624c6667fc7 .ctaText { border-bottom: 0 solid #fff; color: #2980B9; font-size: 16px; font-weight: bold; margin: 0; padding: 0; text-decoration: underline; } .u8e84900216c659a8b350f624c6667fc7 .postTitle { color: #FFFFFF; font-size: 16px; font-weight: 600; margin: 0; padding: 0; width: 100%; } .u8e84900216c659a8b350f624c6667fc7 .ctaButton { background-color: #7F8C8D!important; color: #2980B9; border: none; border-radius: 3px; box-shadow: none; font-size: 14px; font-weight: bold; line-height: 26px; moz-border-radius: 3px; text-align: center; text-decoration: none; text-shadow: none; width: 80px; min-height: 80px; background: url(https://artscolumbia.org/wp-content/plugins/intelly-related-posts/assets/images/simple-arrow.png)no-repeat; position: absolute; right: 0; top: 0; } .u8e84900216c659a8b350f624c6667fc7:hover .ctaButton { background-color: #34495E!important; } .u8e84900216c659a8b350f624c6667fc7 .centered-text { display: table; height: 80px; padding-left : 18px; top: 0; } .u8e84900216c659a8b350f624c6667fc7 .u8e84900216c659a8b350f624c6667fc7-content { display: table-cell; margin: 0; padding: 0; padding-right: 108px; position: relative; vertical-align: middle; width: 100%; } .u8e84900216c659a8b350f624c6667fc7:after { content: ""; display: block; clear: both; } READ: Global Climate Change EssayIn its current algorithm, the statisticalcoder only accepts alpha-numeric phrases. I would like to modify it to notread the characters that the binary code spells out, but the binary code itself. I dont know what form the output is aside from compressed, but formy purposes it wouldnt matter what the form the output is. I would programinto the program all of the 32 combinations of 5 bits (2^5). Each of the combinationswould be labeled in the program 1 through 32. I would then make a hash tableof all of the 5 bit combinations. This would give me an output which I wouldrun through a run length coder. Since the entire algorithm is reliant on binaryco de and not on characters, it can be recursable, or it can compress furtheran already compressed file. LZs cant do that because once they convert astring into its dictionary/sliding window form, it ceases to be one of thecharacters that it compresses. Now that you are aquatinted with our friend,Data Compression, I hope he will be able to serve you better. Now you candownload programs faster, save space, and who knows? Maybe you will inventthe next new compression algorithm. Until then, keep your mice happy and yourmonitors warm. Proof that random data is not compressible:Lets supposethe file to be compressed is 8 bits long (x works, but this is easier) andis randomThere are exactly 2^8 different possible 8 bit data strings. (2^x)Tocompress the file it must shrink it by at least one bit (2^x)-1So there areat most 2^7 different compressed files 2^(x-1)Thus at least two source filescompress down to the same file. Therefore The compression cannot be lossless. BibliographyAronson, Jules Data Compression- a comparison of MethodsWashington D.C.: Institute for Computer Science and Technologyhttp://simr02.si.ehu.es/DOCS/mice/compression-faq/part1/faq-doc-x.htmlx=Intro,8,9, and 10http://www.epl.co.uk/genit18.htmhttp://www.sees.bangor.ac.uk/~gerry/sp_summary.htmlhttp://Literacy.com//mkp/pages/3468/index.html