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    International Journal of Computer Science‚ Engineering and Applications (IJCSEA) Vol.3‚ No.1‚ February 2013 WATERMARKING RELATIONAL DATABASES Mayuree K.Rathva¹‚Prof.G.J.Sahani² Dept.of Computer Engineering‚ SVIT‚Vasad‚ Anand‚Gujarat‚ INDIA ¹mayurirathva@gmail.com and ²Gurcharan_sahani@yahoo.com ABSTRACT Uptil now most of the work is done on image‚ video‚ audio.but today the Database watermarking becomes the research topic because of the increasing the use of relational database systems

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    Signal Processing

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    IEEE TRANSACTIONS ON INFORMATION THEORY‚ VOL. 48‚ NO. 7‚ JULY 2002 1849 Performance of Blind and Group-Blind Multiuser Detectors Anders Høst-Madsen‚ Member‚ IEEE‚ and Xiaodong Wang‚ Member‚ IEEE Abstract—In blind (or group-blind) linear multiuser detection‚ the detector is estimated from the received signals‚ with the prior knowledge of only the signature waveform of the desired user (or the signature waveforms of some but not all users). The performance of a number of such estimated linear

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    Mathematical Modeling

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    Mathematical modeling is commonly used to predict the behavior of phenomena in the environment. Basically‚ it involves analyzing a set of points from given data by plotting them‚ finding a line of "best fit" through these points‚ and then using the resulting graph to evaluate any given point. Models are useful in hypothesizing the future behavior of populations‚ investments‚ businesses‚ and many other things that are characterized by fluctuations. A mathematical model usually describes a

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    Traffic light sytem

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    CONTENTS: 1. Introduction. 2. System design. A) Timing circuits. B) Sequential circuits. c) Combinational circuits. 3. Bill of materials. 4. Hardware design. 5. References. 6. Appendices. 1. Introduction: This report is about the traffic light system through use of the digital logic design. The objective of this assignment is as follows: • To design and construct a prototype for digital logic circuit applications. • To apply and integrate the digital

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    The Law of Conservation of Mass  Goals:  1. To identify the parts of a chemical equation. Students need to identify subscripts‚  coefficients‚ reactants‚ products‚ chemical formulas‚ and chemical symbols  2. To appreciate that scientific discoveries are often the result of inquiry.  3. to distinguish between an element‚ a compound‚ and a mixture (and between  heterogeneous and homogeneous mixtures)  4. To balance a chemical equation­ in order to prove that the Law of Conservation of Mass  works quantitatively as well as conceptually 

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    Block Diagonalization

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    126 (2001) MATHEMATICA BOHEMICA No. 1‚ 237–246 BLOCK DIAGONALIZATION J. J. Koliha‚ Melbourne (Received June 15‚ 1999) Abstract. We study block diagonalization of matrices induced by resolutions of the unit matrix into the sum of idempotent matrices. We show that the block diagonal matrices have disjoint spectra if and only if each idempotent matrix in the inducing resolution double commutes with the given matrix. Applications include a new characterization of an eigenprojection

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    Name: ________________________ Date:__________________ Year & Section: _________________ Teacher: _______________ Reviewer: Quadratic Equations I. Multiple Choice: Choose the letter of the correct answer. Show your solution. 1. What are the values of x that satisfy the equation 3 – 27x2 = 0? A. x = [pic]3 B. x = [pic] C. x = [pic] D. x = [pic] 2. What are the solutions of the equation 6x2 + 9x – 15 = 0? A. 1‚ - 15 B. 1‚ [pic] C. – 1‚ - 5 D. 3‚ [pic]

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    Image Processing

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    DIGITAL IMAGE PROCESSING (CREATIVE WORLD OF FACE MORPHING) BY ABSTRACT A study on face morphing is proposed.The algorithms explains the extra feature of points on face and based on these feature points‚ images are portioned and morphing is performed. The algorithms has been used to generate morphing between images of face of different people as well as between images of face of individuals. To do face morphing‚ feature points are usually specified manually

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    Sample

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    EEE 21 Lecture Variable Entered Mapping Anastacia P. Ballesil EEE Department‚ UP Diliman‚ QC Example Given: F(A‚B‚C) = ∑m(0‚1‚4‚7) G(A‚B‚C) =∑m(0‚4‚5) F(A‚B‚C) + G(A‚B‚C) = ∑m(0‚1‚4‚5‚7) F(A‚B‚C) ⋅ G(A‚B‚C) = ∑m(0‚4) Anastacia P. Ballesil EEE Department‚ UP Diliman‚ QC F(A‚B‚C) AB C 0 1 00 1 1 01 0 0 11 0 1 10 1 0 AB C 0 1 00 1 0 G(A‚B‚C) 01 0 0 11 0 0 10 1 1 AB C 0 1 F+G 00 1 1 01 0 0 11 0 1 10 1 1 C AB 0 1 F•G 00 1 0 01 0 0 11 0 0 10 1 0 Anastacia P.

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    Matrix and Vector

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    Markov Processes 1. Introduction Before we give the definition of a Markov process‚ we will look at an example: Example 1: Suppose that the bus ridership in a city is studied. After examining several years of data‚ it was found that 30% of the people who regularly ride on buses in a given year do not regularly ride the bus in the next year. Also it was found that 20% of the people who do not regularly ride the bus in that year‚ begin to ride the bus regularly the next year. If 5000 people ride the

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