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computerized student academic transcript management system pdf with source code

Abstract:

A number of problems associated with student academic record management include improper course registration, late release of students results, inaccuracy due to manual and tedious calculation and retrieval difficulties/inefficiency. In most cases the data generated by academic institutions are usually created in non-delineated files for use by different departments/units within the institutions with the same data
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lecturer interview questions and answers pdf

The job interview questions sample below are used to ask Lecturer and other Lecturer positions related. You can use them to ask yourself or candidate as follows:

1. Tell me about yourself?
2. Why did you leave your last job?
3. What are your career goals for Lecturer?
4. Why do you want to work here?
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automatic power factor controller - Presentation Transcript



1. Power Factor & APFC By: Ravi Shankar Singh
2. What is power factor ? Power Factor = Active Power (kW)/Apparent Power (kVA) PF 1.0 Usually P.F is always Lag (Inductive) Some time P.F can be Lead (Capacitive).
3. Origin of Low Power Factor
Electrical Equipment need Reactive Power
Inductive loads draw Reactive Power
Phase difference between current & Voltage reduces Displacement PF .
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Two aspects of attacks on steganography are detection and destruction of embedded message. Any object can be manipulated with the intent of destroying some hidden information whether an embedded message exist or not. .

Attacking steganographic algorithm is very similar to attacking cryptographic algorithms and similar techniques apply. If the original unmodified file used as a cover by the stegosystem is available to an attacker or investigator all he has to do is a bit-by-bit comparison with the suspect version in order to establish steganogr ....etc

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A genetic algorithm (GA) is a method for solving both constrained and unconstrained optimization problems based on a natural selection process that mimics biological evolution. The algorithm repeatedly modifies a population of individual solutions. At each step, the genetic algorithm randomly selects individuals from the current population and uses them as parents to produce the children for the next generation. Over successive generations, the population evolves toward an optimal solution.

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