Unit 18 Lab 18 Report

4.1.6 Flip ops as Counters As can be seen from Figure 4.7 and Figure 4.8, a T-FF can be implemented using a D- FF feeding back the negate output /Q to the input D. The input clock to be divided is then provided at the CLK input. Cascading n T-FF stages as shown in Figure 4.8, it is 26 possible to divide the input frequency by a factor of 2^n . Based on current requirement Figure 4.7: FlipFlop of IC, size and availability and operating temperature, the rst combination which is the cascade of divide-by-4, divide-by-10 and divide-by-10 is chosen. The ip op as divide by 4, 10, 40 etc have been simulated with ADS.

Anderson and Wood (1925) determined a magnification value equal to 2800 but they neglected the deformation of the tungsten wire under different equilibrium situations. Conversely, the deformation of the wire could be sufficient to reduce the magnification factor of 30%, increasing the moment of inertia. For this reason Uhrhammer and Collins (1990) and Uhrhammer et al. (1996) recomputed the instrument static magnification (GS) that was estimated equal to 2080 ± 60. Using 2800 instead of 2080 in the BB WA simulations leads to a magnitude error of +0.129 (e.g. Uhrhammer et al., 2011).

Experiment 7 In this experiment we configured several DC circuits consisting of an emf and a network of resistors. The circuits were composed of a power supply, two DMMs, a circuit board, an SPST switch, and an assortment of known resistors along with one unknown resistor. We measured the current and voltage of the entire circuit as well as the potential drops across each resistor to determine the parameters of the circuit including the resistance, voltage, and current for each component.

(a) 3Mbps / 150Kbpa =3 X 1024 / 150 = 3072 / 150 =20.48 20 Users can be supported 150Kbps dedicated. (b)

Figure shows the intersection of line joining the camera center and image points ${\bf x}$ and ${\bf x'}$ which will be the 3D point ${\bf X}$.\\ \end{figure} The ‘gold standard’ reconstruction algorithm minimizes the sum of squared errors between the measured and predicted image positions of the 3D point in all views in which it is visible, i.e.\\ \begin{equation} {\bf X=\textrm{arg min} \sum_{i} ||x_i-\hat{x_i}(P_i,X)||^2} \end{equation} Where ${\bf x_i}$ and ${\bf \hat{x_i}(P_i,X)}$ are the measured and predicted image positions in view $i$ under the assumption that image coordinate measurement noise is Gaussian-distributed, this approach gives the maximum likelihood solution for ${\bf X}$. Hartley and Sturm [3] describe a non-iterative

Using the data provided in each one of these tests it can be assumed that one has done the steps to be able to determine the magnitude and orientation of the charges of the tape in each test, thus, allowing them to apply the same principle to any object they so desired. Their results would line up with the following; that if the two pieces of tape are torn from the same 40 centimeter strip then the tops of both pieces of tape would be positive and the bottoms of both pieces of tape would be negative and that if they would double the tape the attraction or repulsion in general would lower due to the increased density. Their data would also show that two pieces of tape ripped from each other would result in one piece being entirely positive and the other being entirely negative, they would also be able to state that the orientation of how the tape is paired up doesn’t matter.

determine each pixel belongs to background or foreground. Wis the weights between the pattern and summationneurons, which are used to point out with which a pattern belongs to the background or foreground. They areupdated when each new value of a pixel at a certain position received by implementing the following function:Wt+1ib =fc(1−βNpn)Wib+MAtβ!(37)Wt+1i f=(1−Wt+1ib)(38)whereWtibis the weight between theith pattern neuron and the background summation neuron at timet,βisthe learning rate,Npnis the number of the pattern neurons of BNN,fcis the following function:fc(x)1,x>1x,x≤1(39)MAtindicates the neuron with the maximum response (activation potential) at frame t, according to:MAt1,f or neuron with maximum response0,otherwise(40)Function

1. A) Show that the relation R over bit strings where (x, y) is in R if and only bit strings x and y length 16 that agree on their last 4 bits is an equivalence relation. Define the equivalence classes and the partition induced by R. Answer: A relation R is said to be an equivalence relation if and only if it has all the following three properties: • Reflexive • Symmetric and • Transitive

The topic the scientists will be conducting is called Alka-Seltzer Tablets, Rate of Reaction. Here the scientists will be testing the reaction time of Alka-Seltzer tablets. The scientists will be testing that by taking various substances and dropping in one Alka-Seltzer tablet per each cup of liquid. The scientists will be testing the variables include the temperature such as cold water, salt water at room temperature, room temperature water, vinegar water at room temperature that’s the independent variables. The dependent variable is the rate of dissolving in seconds.

19.386526 -67.45 -44.1 20.53525 -68.39 -44.1 21.75204 -68.56 -44.1 23.04093 -67.97 -44.1 24.406191 -67.25 -44.1 25.852348 -66.75 -44.1 27.384196 -66.66 -44.1 29.006812 -66.79 -44.1 11.54782 -67.25 -44.1 12.232071 -66.3 -44.1 12.956867 -65.38 -44.1 13.72461 -64.56 -44.1 14.537844 -64.01 Adrian Bersiks_bersik_Acoustic Analysis_Excel.xlsx-44.1 15.399265 -63.86 -44.1 From the figure above there are no interpolation points above the reference line, which means the frequencies were bounded nicely under the maximum amplitude, and the greatest amplitude was captured on the sampling interval exactly, with a closer distribution in amplitudes. Again the 130Hz drop is consistent. Looking at the Excel spreadsheet, the resposnse almost mimics the

Chapter 7 is to discuss the actual implementation and issues found during the experiment. The number of issues that were found during the project will be discussed in this chapter. Types of issues that will be discussed, are component issues, integration issues and construction issues. A cost summary of the components that were bought, will be shown in this chapter. 7.2 COMPONENT AND INTEGRATION

Typical sample dimensions 9.51 × 4.83 mm2in surface area and1.58 mm in thickness were coated with conductive silver paint formetallic contacts. The dielectric constant of the sample was mea-sured for the applied frequency that varies from 100 Hz to 1 MHz atdifferent temperatures (40◦C, 60◦C, 80◦C). The observations weremade while cooling the sample. The dielectric constant εrwas cal-culated using the relation, εr =

Temperature: In this experiment, we will examine how the temperature affects the decomposition rate of a cough drop in water. There will be 3 different temperatures (cold, warm and hot) and all of the three experiment will be performed at the same time. Equipment: 3x Hot plates 3x Magnetic stirrers 3x 150 mL beakers 3x Cough drops 3x

Forces and Newton II Elias Ghantous PHYS 151 – Section NQ Thursday 10:10am Hasbrouck Lab Room 214 October 13, 2017 Abstract In this experiment, I studied how forces cause an object to accelerate. I also studied the relationship between force vectors, mass and acceleration. Gathering of data took place through the use of a force table and a PAScar track system.

The effect of temperatures on rate of reaction Temperature (degrees Celsius) Room temperature 35 50 Rate of reaction (seconds) 69 56.03 53.63 Table 2: The effect of temperatures when the temperatures were above room temperature. Graph 1: The graph of the results from table 1 Graph 2: The graph of the results from table 2 The results displayed in all the graphs and tables had shown a decrease in time for the rate of reaction, as the temperature increases. The results support the idea that as the temperature of the solution increases, the time, the rate of reaction, decreases.