A Brief Introduction Network Programming and Encryption Rich Lundeen Introduction This paper is the report of an exercise in socket programming and encryption. The objectives of this project were as follows: ● ● ● ● To create two programs‚ a client and a server The server broadcasts its public key to all who connect A client attaches to the server and exchanges a session key using public key encryption A message is passed between the client and the server encrypted with a symmetric key
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This assignment gave me the opportunity to computerize a manual membership system of Richard’s Tennis Club using various methods and techniques. The computerization of this system introduced several advantages but also created some limitations. The first report in task 1 had to contain a list of all the paid up members. To compile this list‚ the expiry date of each member was calculated depending upon the type of membership. Once the expiry date was set‚ this date was compared to the variable ‘today’
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1 ) The sum of the digits of a two-digit number is 7. When the digits are reversed‚ the number is increased by 27. Find the number. 2 ) A passenger jet took three hours to fly 1800 miles in the direction of the jetstream. The return trip against the jetstream took four hours. What was the jet’s speed in still air and the jetstream’s speed? 3 ) These circles are identical. What is the value of x ? 4 ) Solve for x using these two equations: 2x + 6 = y; y - x = 2 5 ) The perimeter and the
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Euros. A linear equation of a function‚ E‚ which converts US dollars (D) to Euros (E) would be E = 0.7749D You would just put the number of dollars in for "D" and multiply by 0.7749 and this will give you the number of Euros you would get for your US dollars. This is a "real world application" of a linear function. Cell Phones Just about everyone has a cell phone‚ and most rate plans are a linear function of some kind. Let’s take a look at a basic example that is a real-life application of a linear
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understanding of system software tools. UNIT I INTRODUCTION System software and machine architecture – The Simplified Instructional Computer (SIC) - Machine architecture - Data and instruction formats - addressing modes instruction sets - I/O and programming. 8 UNIT II ASSEMBLERS 10 Basic assembler functions - A simple SIC assembler – Assembler algorithm and data structures - Machine dependent assembler features - Instruction formats and addressing modes – Program relocation - Machine independent
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study retailers behavior towards Aircel in selected region. The data is collected directly by visiting outlets through structured interview scheduled. The statistical tools used to analyze the data are: Co-relation analysis‚ Simple Linear Regression and Multiple Linear Regression. The software used to analyze the data is Windostat version 8.6‚ developed by Indostat services‚ is an advanced level statistical software for research and experimental data analysis. The study is carried mainly in the
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• It is easy to use the Excel Solver to solve NLPs. • The process is similar to a linear model. • For NLPs having multiple local optimal solutions‚ the Solver may fail to find the optimal solution because it may pick a local extremum that is not a global extremum. 22 Example 2 • Trucko is trying to determine where they should locate a single warehouse. The positions in the x‐y plane of their four customers and the number of shipments made annually to each customer are given. Trucko
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Summary of PL/1 (Programming Languages 1) History (Programming Language 1) A high-level IBM programming language introduced in 1964 with the System/360 series‚ developed by George Radin of IBM in 1964. Originally named (NPL) and Fortran VI. It was designed to combine features of and eventually supplant COBOL and FORTRAN‚ which never happened. A PL/I program is made up of procedures (modules) that can be compiled independently. There is always a main procedure and zero or more additional ones.
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The linear probability model‚ ctd. When Y is binary‚ the linear regression model Yi = β0 + β1Xi + ui is called the linear probability model. • The predicted value is a probability: • E(Y|X=x) = Pr(Y=1|X=x) = prob. that Y = 1 given x • Yˆ = the predicted probability that Yi = 1‚ given X • β1 = change in probability that Y = 1 for a given ∆x: Pr(Y = 1 | X = x + ∆x ) − Pr(Y = 1 | X = x ) β1 = ∆x 5 Example: linear probability model‚ HMDA data Mortgage denial v. ratio of debt payments to income (P/I
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College of Business Hospitality & Tourism Studies Department of Computer Science & Information System CIN623 Database Design & Programming Final Examination Trimester 1 – 2011 Date: Duration:3 hours plus 10 minutes INSTRUCTION TO STUDENTS 1. You are allowed ten minutes extra reading time during which you are not to write 2. Write all answers to each question in the Answer Booklet. 3. Write your Student ID number at the top of each attached sheet. 4. Insert all written foolscaps in their correct sequence
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