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    Data Structures

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    EE2410: Data Structures Cheng-Wen Wu Spring 2000 cww@ee.nthu.edu.tw http://larc.ee.nthu.edu.tw/˜cww/n/241 Class Hours: W5W6R6 (Rm 208‚ EECS Bldg) Requirements The prerequites for the course are EE 2310 & EE 2320‚ i.e.‚ Computer Programming (I) & (II). I assume that you have been familiar with the C programming language. Knowing at least one of C++ and Java is recommended. Course Contents 1. Introduction to algorithms [W.5‚S.2] 2. Recursion [W.7‚S.14] 3. Elementary data structures: stacks‚ queues

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    big data

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    Big Data In It terminology‚ Big Data is looked as a group of data sets‚ which are so sophisticated and large that the data can not be easily taken‚ stored‚ searched‚ shared‚ analyzed or visualized making use of offered tools. In global market segments‚ such “Big Data” generally looks throughout attempts to identify business tendencies from accessible files sets. Other areas‚ exactly where Big Data continually appears include various job areas of research for example the human being genome and also

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    Data Encryption

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    its simplest terms‚ the translation of data into a secret code. In order to read an encrypted file‚ the receiver of the file must obtain a secret key that will enable him to decrypt the file. A deeper look into cryptography‚ cryptanalysis‚ and the Data Encryption Standard (DES) will provide a better understanding of data encryption. Cryptographic Methods There are two standard methods of cryptography‚ asymmetric encryption and symmetric encryption. Data that is in its original form (unscrambled)

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    Wastewater Data

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    Treatment Process in Houston CIVT 301 Outline Wastewater collection data in Houston What is sewage treatment? Where does wastewater come from? Factors that affect the flow of pipelines Industrial wastewater? Storm water/ Data The treatment plant operator Sources of wastewater Why treat wastes Waste water treatment facilities Treatment processes Drinking water What can be done to help? Wastewater collection data in Houston 640 square miles area 3 million citizens served 6

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    Data Warehousing

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    Data warehousing is the process of collecting data in raw form for analyzing trends. The benefits to data warehousing are improved end-user access‚ increased data consistency‚ various kinds of reports can be made from the data collected‚ gather the data in a common place from separate sources and additional documentation of data. Potential lower computing costs‚ increased productivity‚ end-users can query the database without using overhead of the operational systems and creates an infrastructure

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    Data Representation

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    ITE 221 – Project#1 – Data Representation http://msdn.microsoft.com/en-us/library/d11h6832%28v=VS.71%29.aspx Class library of the .NET Framework for Microsoft. 1. What is a data structure? A data structure is a related group of primitive data elements organized for some type of common processing and is defined and manipulated in software. 2. What is a library? A library contains resources for developing software. These resources could be pre-written code‚ subroutines‚ classes‚ values

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    Data Representation

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    Data Representation Data and instructions that are presented in a written or typed format can only be understood by the user. If the data is not in the user’s language‚ s/he will not be able to understand it. It is the same way with the computer; the computer’s language is binary 0s and 1s. The computer cannot understand typed or written instructions or data. Whenever data or instructions or input to the computer it is first converted to 0s and 1s‚ these are called binary digits (bits). There

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    Distinguish between primary data and secondary data? Primary data is the data that is collected first hand from the original source for the purpose of making statistical inference while secondary data is the data that is collected by the method of abstraction and is used to make statistical inference by using primary data already collected by an investigator. Primary data is collected by  Identifying population of interest  choosing sample  analyse sample information  draw inference from

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    s= = x-x2n-1 | Q1n+14‚ Q7+14=84=2postion Q3=3(n+1)4=3(7+1)4=244=6‚ IQR Q3-Q1‚ | CV=sx×1003.297×100%=47%/ n = 5 has a mean of 10.2.four data: 9‚ 10‚ 8 17‚ find the missing data value.x=i=1nxin=8+9+10+17+?5=*5=10.2‚ 5×10.2=51 Therefore: 8+9+10+17+?=51Therefore: 8+9+10+17+?=51Simplifying: 44+?=51And so ?=51-44=7Thus the missing data value is 7. | Variance/s2= x-x2n-1‚ [3-72+4-72+7-72+7-72+9-72+12-72]6-1 =545 =10.8 | egA manufacturer of insulation randomly selects 20 winter days

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    of the research project specifies both the data that are needed and how they are to be obtained. The first step in the data-collection process is to look for secondary data. These are data that were developed for some purpose other than for helping to solve the problem at hand. The data that are still needed after that search is completed will have to be developed specifically for the research project and are known as primary data. The secondary data that are available are relatively quick and

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