winforms ean 13 reader

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00:1 391:1 271:1 325:1 273:1 x6 4 1 2 1 4 2 2 2 4 2 2 1 2 4 4 4 2 2 4 2 4 2 2 2 4 x7 3 3 3 3 3 3 4 5 3 4 4 3 3 3 3 3 3 3 3 5 3 5 3 3 3 x8 2003 1967 1999 1941 1845 1793 1557 1652 1954 1606 1704 1715 1999 2241 2310 1967 1793 2142 196 1652 228 1715 2153 2155 1852 x9 699 722 740 718 69 654 64 65 744 622 669 77 74 798 797 722 654 763 73 618 798 634 76.

and the initial fills of ( X ,A, B ) .

3 785 69 x10 3910 3510 3890 3365 4215 3020 1905 2320 3885 2009 2655 3375 3890 5290 5185 3910 3050 4250 3850 2275 5430 2535 4370 4540 3660 x11 A A A M A A M M A M M A A A A A A A A M A M A A A.

y: Miles/gallon x1: Displacement (cubic inches) x2: Horsepower (foot-pounds) x3: Torque (foot-pounds) x4: Compression ratio x5: Rear axle ratio x6: Carburetor (barrels) x7: No. of transmission speeds x8: Overall length (inches) x9: Width (inches) x10: Weight (pounds) x11: Type of transmission (A automatic, M manual)

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13. This problem deals with the branching that occurs in the ORYX attack. a. How much branching is expected at the K1 step of the ORYX attack Hint: After the KOstep, there are 65,536 putative fills. At the next iteration, we test 12 extensions of each of these putative fills. How many of these 65,536 produce more than one result that is consistent with an extension of X b. What is the expected branching at each of steps K1 through K N c. Suppose that we implement the ORYX attack without branching. That is, no more than one valid extension of any given fill is retained. If this is the case, what is the probability that the solution is found 14. When analyzing the ORYX attack, we assumed that the permutation L acts as a random permutation of the values {0,1,2,. . . ,255). Suppose that instead, L is the identity, that is, L[i]= i, for i = 0 , 1 , 2 , .. . ,255. In this case, explain why the ORYX attack given in this chapter will fail and describe an alternative attack that will succeed. 15. Discuss possible ways that the ORYX keystream generator can be modified to prevent the attack given in this chapter. Consider methods that result in a more efficient cipher than the modifications mentioned in Section 3.3.3. 16. Analyze the modified version of ORYX discussed in Section 3.3.3 for potential weaknesses. You may assume that unlimited known plaintext is available.

(c) Compute the standard errors of the regression coefficients. (d) Predict power consumption for a month in which x1 75 F, x2 24 days, x3 90%, and x4 98 tons. 12-7. A study was performed on wear of a bearing y and its relationship to x1 oil viscosity and x2 load. The following data were obtained. y 293 230 172 91 113 125 x1 1.6 15.5 22.0 43.0 33.0 40.0 x2 851 816 1058 1201 1357 1115

(a) Fit a multiple linear regression model using x2, x3, x4, and x5 as the regressors. (b) Estimate 2. (c) Find the se( j). How precisely are the regression coefficients estimated, in your opinion (d) Use the model from part (a) to predict pull strength when x2 = 20, x3 = 30, x4 = 90, and x5 = 2.0. 12-9. An engineer at a semiconductor company wants to model the relationship between the device HFE ( y) and three parameters: Emitter-RS (x1), Base-RS (x2), and Emitter-to-Base RS (x3). The data are shown in the following table. x1 Emitter-RS 14.620 15.630 14.620 15.000 14.500 15.250 16.120 15.130 15.500 15.130 15.500 16.120 15.130 15.630 15.380 14.380 15.500 14.250 14.500 14.620 x2 Base-RS 226.00 220.00 217.40 220.00 226.50 224.10 220.50 223.50 217.60 228.50 230.20 226.50 226.60 225.60 229.70 234.00 230.00 224.30 240.50 223.70 x3 E-B-RS 7.000 3.375 6.375 6.000 7.625 6.000 3.375 6.125 5.000 6.625 5.750 3.750 6.125 5.375 5.875 8.875 4.000 8.000 10.870 7.375 y HFE-1M-5V 128.40 52.62 113.90 98.01 139.90 102.60 48.14 109.60 82.68 112.60 97.52 59.06 111.80 89.09 101.00 171.90 66.80 157.10 208.40 133.40

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