ODS Page Breaking
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A novel way to figure out the length in inches of each character to enable correct page breaking for use with SAS ODS RTF.
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5 6
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% echo $?
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2) Their most recent role was as a senior PHP developer and team leader at MUSK HOST TECHNOLOGIES LLP, where they worked on projects using Symfony and other frameworks.
3) Education includes a bachelor's degree in computer science and engineering from M.G.M. Jawaharlal Nehru College of Engineering.
INTRODUCTION TO SAS
This document provides an introduction and outline for using SAS software. It covers basic SAS windows and rules, loading and viewing data, manipulating data by selecting subsets, adding or deleting variables, sorting, summarizing data with procedures, and creating plots and outputting results to Word. Examples are provided for common procedures like SORT, MEANS, UNIVARIATE, FREQ, CORR and PLOT. Practice exercises are included to try these skills on a sample dataset.
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Hello, I need help with the following assignmentThis assignment w.pdf
Hello, I need help with the following assignment:
This assignment will give you practice in manipulating lists of data stored in arrays.
1 General Instructions
Read the general instructions on preparing and submitting assignments.
Read the Counting Words problem description below. Implement the histogram function to
complete the desired program.
You must use dynamically allocated arrays for this purpose.
For your initial implementation, use ordered insertion to keep the words in order and ordered
sequential search when looking for words. Note that the array utility functions from the lecture
notes are available to you as art of the provided code.
Although we are counting words in this program, the general pattern of counting occurrences of
things is a common analysis step in laboratory work, statistical studies, and business tasks. The
results of such a program are often fed into other programs for further processing and/or display.
Such results are often displayed as histograms. The CSV output format is a common “data
exchange” format recognized by many programs. Almost all spreadsheets, for example, will read
CSV files.
When you have the program running, execute it using a short paragraph of text as an input,
saving the output in a file ending with a “.csv” extension. Run a spreadsheet program (e.g.,
Microsoft Excel). You should be able to load your .csv file directly into the spreadsheet.
Try displaying your results as a histogram. In Excel (2007), for example, select the two columns
of data, choose “Sort” from the Data tab and sort your data on the numeric column. Then, with
the two sorted columns of data still selected, go to the Insert tab and select a 2D Bar chart. Save
your spreadsheet in Excel (.xsl) format. You will turn this in later.
As documents get larger, the total number of words increases far, far faster than does the number
of distinct words. Our personal vocabularies are only so large, after all. In fact, most writers
unconsciously limit themselves to writing with a small fraction of their personal “reading”
vocabularies. So most words in a large document are bound to be repeats. That means that, for
this application, the speed of the functions for searching for words is probably more important
than the speed of the functions for inserting new words into the array. We do many more
searches than insertions.
Try running your program on one of the large text files provided in the assignment directory.
Time it to see how long it takes. Now replace all uses of ordered sequential search by calls to the
binary search function. Run it on the same output, timing it again. You should see a substantial
improvement.
Use the button below to submit your completed program and your saved spreadsheet.
2 Problem Description
2.1 Counting Words
Develop a program to prepare a list of all words occurring in a plain-text document, counting
how many times each word occurs. In determining whether two words are different, punctuation
(non-alphabetic.
Program 1 – CS 344This assignment asks you to write a bash.docx
Program 1 – CS 344
This assignment asks you to write a bash shell script to compute statistics. The purpose
is to get you familiar with the Unix shell, shell programming, Unix utilities, standard
input, output, and error, pipelines, process ids, exit values, and signals.
What you’re going to submit is your script, called stats.
Overview
NOTE: For this assignment, make sure that you are using Bash as your shell (on Linux,
/bin/sh is Bash, but on other Unix O/S, it is not). This is because the Solaris version of
Bourne shell has some annoying bugs that are really brought out by this script. Bash can
execute any /bin/sh script.
In this assignment you will write a Bourne shell script to calculate averages and medians
from an input file of numbers. This is the sort of calculation I might do when figuring
out the grades for this course. The input file will have whole number values separated by
tabs, and each line of this file will have the same number of values. (For example, each
row might be the scores of a student on assignments.) Your script should be able to
calculate the average and median across the rows (like I might do to calculate an
individual student's course grade) or down the columns (like I might do to find the
average score on an assignment).
You will probably need commands like these, so please read up on them: sh, read, expr,
cut, head, tail, wc, and sort.
Your script will be called stats. The general format of the stats command is
stats {-rows|-cols} [input_file]
Note that when things are in curly braces separated by a vertical bar, it means you should
choose one of the things; here for example, you must choose either -rows or -cols. The
option -rows calculates the average and median across the rows; the option -cols
calculates the average and median down the columns. When things are in square braces
it means they are optional; you can include them or not, as you choose. If you specify an
input_file the data is read from that file; otherwise, it is read from standard input.
Here is a sample run of what your script might return, using an input file called test_file
(this particular one can be downloaded here , note that in Windows, the newline
characters may not display as newlines. Move this to your UNIX account, without
opening and saving it in Windows, and then cat it out: you'll see the newlines there):
% cat test_file
1 1 1 1 1
9 3 4 5 5
6 7 8 9 7
3 6 8 9 1
3 4 2 1 4
6 4 4 7 7
% stats -rows test_file
Average Median
1 1
5 5
7 7
5 6
3 3
6 6
% cat test_file | stats –c
Averages:
5 4 5 5 4
Medians:
6 4 4 7 5
% echo $?
0
% stats
Usage: stats {-rows|-cols} [file]
% stats -r test_file nya-nya-nya
Usage: stats {-rows|-cols} [file]
% stats -both test_file
Usage: stats {-rows|-cols} [file]
% chmod -r test_file
% stats -columns test_file
stats: cannot read test_file
% stats -columns no_such_file
stats: cannot read no_such_file
% echo $?
1
Specifications
You must ch ...
Strings-Computer programming
The document discusses various concepts related to strings in C programming language. It defines fixed length and variable length strings. For variable length strings, it explains length controlled and delimited strings. It describes how strings are stored and manipulated in C using character arrays terminated by a null character. The document also summarizes various string manipulation functions like string length, copy, compare, concatenate etc available in C standard library.
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50120130405006
This document summarizes research on optimizing the LZ77 data compression algorithm. The researchers present a method to improve LZ77 compression by using variable triplet sizes instead of fixed sizes. Specifically, when the offset is equal to the match length, they represent it with a "doublet" of just length and next symbol, saving bits compared to the standard triplet representation. They show this optimization achieves higher compression ratios than the conventional LZ77 algorithm in experiments. The decoding process is made slightly more complex to identify doublets versus triplets but still allows decompressing the encoded data back to the original.
OPTIMIZATION OF LZ77 DATA COMPRESSION ALGORITHM
Data compression refers to reducing the amount of space needed to store data or reducing the
amount of time needed to transmit data. Many data compression techniques allow encoding the
compressed form of data with different compression ratio. In particular, in the case of LZ77
technique, it reduces the data concurrency of an input file. In the output of this technique it conveys
more information that is actually not needed in practical. Removing the extra information from the
encoded file that makes this algorithm more optimal. Our task is to identify how much extra
information it conveys and how can we minimize it so that there is no trouble at the time of
decoding. Basically the encoded output of LZ77 is the sequence of triplets (a structure of encoded
output) that is in binary and having fix size. For making the triplets of fix size, sometimes we are
creating unnecessary information. We present the method of variable triplet size as a way to improve
LZ77 compression and demonstrate it through many experiments. In our optimization algorithm we
are getting more compression ratio compare to the conventional LZ77 data compression algorithm.
Data structure and algorithm
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This document discusses generating strings from regular expressions and constructing deterministic finite automata (DFAs) from regular expressions. It provides background on regular expressions and finite automata. It then describes algorithms like the Thompson construction and Glushkov construction for generating DFAs from regular expressions. It proposes a system that would take a regular expression as input, generate the strings that are part of the language for that expression, and output the probable number of states for the DFA. It discusses limitations and future work, and provides references for further research on regular expressions, finite automata, and related topics.
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Souvenir's Booth - Algorithm Design and Analysis Project Project Report
Project Title: Souvenir's Booth using Auto-Complete
Subject: Analysis and Design of Algorithms (UCS501)
Made by:
Abhinav Garg (101303004) abhinavgarg017@gmail.com,
Akshit Arora (101303012) akshit.arora1995@gmail.com and
Chahak Gupta (101303041) chahakgupta4@gmail.com
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This document provides an overview of regular expressions (regex). It defines regex as patterns that define classes of strings. Regex are used by utilities like grep, sed, awk, vi and emacs to search for patterns in text. The document discusses the syntax of regex like alternation, grouping and quantification. It provides examples of regex patterns and explains how commands like grep can be used with regex to search files.
Console I/o & basics of array and strings.pptx
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MULTIDIMENSIONAL ARRAYS
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The document discusses using Python, ROS, and mixed integer linear programming (MILP) for coordinating unmanned aerial vehicles (UAVs). Python is used for its simplicity and features like lists and functions. ROS provides a framework for coordinating UAV nodes. MILP is used to model the UAV coordination problem and find optimal trajectories that minimize time while avoiding collisions. Several scenarios are modeled using MILP, demonstrating how it can find paths for UAVs to visit waypoints in order while avoiding each other.
Apache Arrow: Leveling Up the Data Science Stack
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- 11. Code
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- 20. Thank You!!