Essay --

Kassidy Hause CWL 320-06, Fall 2013 Dr. Talar Chahinian Final Paper 12-10-13 Ways of Dying, Violence, Fantasy & Comedy Zakes Mda was born in 1948 in Herschel, South Africa and is known for being a novelist, poet, activist, playwright and cultural theorist. Ways of Dying by Zakes Mda is a novel from western form. Literature that was written by Black South African writers between the 1948 and 1994 really captures the oppression and tragic violence that characterized the lives of Blacks under the apartheid. The apartheid or â€Å"apartness† as some Afrikaans call it, describes a system of laws and policies of complete and total racial segregation in South Africa that began in 1948 when the national party came to power. The apartheid did not end until 1994 when Nelson Mandela was elected president in the first democratic elections. The horrific deaths that are portrayed throughout Zake Mda’s novel Ways of Dying, were all true ways of dying that Zakes Mda, saw himself, read about in the newspaper or read when he was doing research. The very true deaths that he portrays in the novel really p aint a picture of the structural and political violence that was going on in South Africa during the apartheid. This violence and oppression really creates a tragic background for the novel however, Zakes Mda challenges the norm of violence and finds a way to portray it as something somewhat idiotic, which in turn makes Ways of Dying quite comical. He also combines fantasy and magic to the novel, which emulates all the spectacular and wonderful parts of South African beliefs and traditions. Zakes unique way of combining the depiction of how ridiculous it is that death has become so normalized in South Africa and magic and fantasy makes Ways of Dying an ... ... Magic and fantasy is also a central theme for this book because magic gives a sense of hope and belief in people and a strength that people never knew they had. The biggest example is the garden, a magic garden of beauty that still stands among all the horrible things that Toloki and Noria are living in. The garden gives them hope that magic and beauty still exist in the world. In this part of the novel the readers are laughing and smiling because they feel hope and happiness and sense of magic that they are going to get through their issues and be okay. Ways of Dying is a spectacular novel by Zakes Mda, written during the apartheid era, which was a horrific time for South Africans who were abused and murdered by their corrupt government. Zakes Mda was able to provide a sense of history, comedy and hope all into one novel and that any reader would enjoy to read.

Juvenile Court System Essay -- essays research papers

Waiving juvenile cases to a criminal court is a complicated process, and may take some time in order to make the proper decision. There are a few different ways in which this decision is made. In some jurisdictions, the cases may be decided upon an intake unit within the court which then decides to process it formally or informally. Other jurisdictions may use another agency such as the prosecutor’s office, or a social service agency to decide whether the case should go to juvenile or criminal court. When a decision is made to transfer a juvenile case to criminal court, a judicial waiver is petitioned for, and the juvenile judge then has to make the decision whether the case should be criminally prosecuted. In some places though, the prosecutor has the legal right to make that judgment without involving the juvenile court, and send the case directly to criminal court.   Ã‚  Ã‚  Ã‚  Ã‚  When a juvenile commits the crime of homicide, I personally think that any offender 13 years or older should be tried in adult criminal court. I do understand that the juvenile may lack some mental reasoning or may even have some mental disorder, just as I think that anyone who commits violent crimes have this also regardless of age, but that doesn’t mean they shouldn’t be still be tried in criminal court for the horrible crimes they committed. The only part of the sentencing I don’t agree with in convicting a juvenile is to where he is sent to prison. I do not believe th...

Separation of Eddy Current and Hysteresis Losses

Laboratory Report Assignment N. 2 Separation of Eddy Current and Hysteresis Losses Instructor Name:  Ã‚  Ã‚   Dr. Walid Hubbi By: Dante Castillo Mordechi Dahan Haley Kim November 21, 2010 ECE 494 A -102 Electrical Engineering Lab Ill Table of Contents Objectives3 Equipment and Parts4 Equipment and parts ratings5 Procedure6 Final Connection Diagram7 Data Sheets8 Computations and Results10 Curves14 Analysis20 Discussion27 Conclusion28 Appendix29 Bibliography34 ObjectivesInitially, the purpose of this laboratory experiment was to separate the eddy-current and hysteresis losses at various frequencies and flux densities utilizing the Epstein Core Loss Testing equipment. However, due to technical difficulties encountered when using the watt-meters, and time constraints, we were unable to finish the experiment. Our professor acknowledging the fact that it was not our fault changed the objective of the experiment to the following: * To experimentally determine the inductance value of an in ductor with and without a magnetic core. * To experimentally determine the total loss in the core of the transformer.Equipment and Parts * 1 low-power-factor (LPF) watt-meter * 2 digital multi-meters * 1 Epstein piece of test equipment * Single-phase variac Equipment and parts ratings Multimeters: Alpa 90 Series Multimeter APPA-95 Serial No. 81601112 Wattmetters:Hampden Model: ACWM-100-2 Single-phase variac:Part Number: B2E 0-100 Model: N/A (LPF) Watt-meter: Part Number: 43284 Model: PY5 Epstein test equipment: Part Number: N/A Model: N/A Procedure The procedure for this laboratory experiment consists of two phases: A. Watt-meters accuracy determination -Recording applied voltage -Measuring current flowing into test circuit Plotting relative error vs. voltage applied B. Determination of Inductance value for inductor w/ and w/o a magnetic core -Measuring the resistance value of the inductor -Recording applied voltages and measuring current flowing into the circuit If part A of the ab ove described procedure had been successful, we would have followed the following set of instructions: 1. Complete table 2. 1 using (2. 10) 2. Connect the circuit as shown in figure 2. 1 3. Connect the power supply from the bench panel to the INPUT of the single phase variac and connect the OUTPUT of the variac to the circuit. 4.Wait for the instructor to adjust the frequency and maximum output voltage available for your panel. 5. Adjust the variac to obtain voltages Es as calculated in table 2. 1. For each applied voltage, measure and record Es and W in table 2. 2. The above sets of instructions make references to the manual of our course. Final Connection Diagram Figure 1: Circuit for Epstein core loss test set-up The above diagrams were obtained from the section that describes the experiment in the student manual. Data Sheets Part 1: Experimentally Determining the Inductance Value of Inductor Table 1: Measurements obtained without magnetic coreInductor Without Magnetic Core| V [V ]| I [A]| Z [ohm]| P [W]| 20| 1. 397| 14. 31639| 27. 94| 10| 0. 78| 12. 82051| 7. 8| 15| 1. 067| 14. 05811| 16. 005| Table 2: Measurements obtained with magnetic core Inductor With Magnetic Core| V [V]| I [A]| Z [ohm]| P [W]| 10. 2| 0. 188| 54. 25532| 1. 9176| 15. 1| 0. 269| 56. 13383| 4. 0619| 20| 0. 35| 57. 14286| 7| Part 2: Experimentally Determining Losses in the Core of the Epstein Testing Equipment Table 3: Core loss data provided by instructor | f=30 Hz| f=40 Hz| f=50 Hz| f=60 Hz| Bm| Es [Volts]| W [Watts]| Es [Volts]| W [Watts]| Es [Volts]| W [Watts]| Es [Volts]| W [Watts]| 0. | 20. 8| 1. 0| 27. 7| 1. 5| 34. 6| 3. 0| 41. 5| 3. 8| 0. 6| 31. 1| 2. 5| 41. 5| 4. 5| 51. 9| 6. 0| 62. 3| 7. 5| 0. 8| 41. 5| 4. 5| 55. 4| 7. 4| 69. 2| 11. 3| 83. 0| 15. 0| 1. 0| 51. 9| 7. 0| 69. 2| 11. 5| 86. 5| 16. 8| 103. 6| 21. 3| 1. 2| 62. 3| 10. 4| 83. 0| 16. 2| 103. 8| 22. 5| 124. 5| 33. 8| Table 4: Calculated values of Es for different values of Bm Es=1. 73*f*Bm| Bm| f=30 Hz| f=40 Hz| f=50 Hz| f =60 Hz| 0. 4| 20. 76| 27. 68| 34. 6| 41. 52| 0. 6| 31. 14| 41. 52| 51. 9| 62. 28| 0. 8| 41. 52| 55. 36| 69. 2| 83. 04| 1| 51. 9| 69. 2| 86. 5| 103. 8| 1. 2| 62. 28| 83. 04| 103. 8| 124. 56| Computations and ResultsPart 1: Experimentally Determining the Inductance Value of Inductor Table 5: Calculating values of inductances with and without magnetic core Calculating Inductances| Resistance [ohm]| 2. 50| Impedence w/o Magnetic Core (mean) [ohm]| 13. 73| Impedence w/ Magnetic Core (mean) [ohm]| 55. 84| Reactance w/o Magnetic Core [ohm]| 13. 50| Reactance w/ Magnetic Core [ohm]| 55. 79| Inductance w/o Magnetic Core [henry]| 0. 04| Inductance w/ Magnetic Core [henry]| 0. 15| The values in Table 4 were calculated using the following formulas: Z=VI Z=R+jX X=Z2-R2 L=X2 60 Part 2: Experimentally Determining Losses in the Core of the Epstein TestingEquipment Table 5: Calculation of hysteresis and Eddy-current losses Table 2. 3: Data Sheet for Eddy-Current and Hysteresis Losses|   | f=30 Hz| f=40 Hz| f=50 Hz| f=60 Hz| Bm| slope| y-intercept| Pe [W]| Ph [W]| Pe [W]| Ph [W]| Pe [W]| Ph [W]| Pe [W]| Ph [W]| 0. 4| 0. 0011| -0. 0021| 1. 01| 0. 06| 1. 80| 0. 08| 2. 81| 0. 10| 4. 05| 0. 12| 0. 6| 0. 0013| 0. 0506| 1. 19| 1. 52| 2. 12| 2. 02| 3. 31| 2. 53| 4. 77| 3. 03| 0. 8| 0. 0034| 0. 0493| 3. 07| 1. 48| 5. 46| 1. 97| 8. 53| 2. 47| 12. 28| 2. 96| 1. 0| 0. 0041| 0. 1169| 3. 72| 3. 51| 6. 62| 4. 68| 10. 34| 5. 85| 14. 89| 7. 01| 1. 2| 0. 0070| 0. 1285| 6. 6| 3. 86| 11. 12| 5. 14| 17. 38| 6. 43| 25. 02| 7. 71| Table 6: Calculation of relative error between measure core loss and the sum of the calculated hysteresis and Eddy-current losses at f=30 Hz W=Pe+Ph @ f=30 Hz| W [Watts]| Pe [Watts]| Ph [Watts]| Pe+Ph| Rel. Error| 1. 0| 1. 0125| 0. 0625| 1. 075| 7. 50%| 2. 5| 1. 1925| 1. 5174| 2. 7099| 8. 40%| 4. 5| 3. 069| 1. 479| 4. 548| 1. 07%| 7. 0| 3. 7215| 3. 507| 7. 2285| 3. 26%| 10. 4| 6. 255| 3. 855| 10. 11| 2. 79%| Table 7: Calculation of relative error between measure core los s and the sum of the calculated hysteresis and Eddy-current losses at f=40 HzW=Pe+Ph @ f=40 Hz| W [Watts]| Pe [Watts]| Ph [Watts]| Pe+Ph| Rel. Error| 1. 5| 1. 8| 0. 0833| 1. 8833| 25. 55%| 4. 5| 2. 12| 2. 0232| 4. 1432| 7. 93%| 7. 4| 5. 456| 1. 972| 7. 428| 0. 38%| 11. 5| 6. 616| 4. 676| 11. 292| 1. 81%| 16. 2| 11. 12| 5. 14| 16. 26| 0. 37%| Table 8: Calculation of relative error between measure core loss and the sum of the calculated hysteresis and Eddy-current losses at f=50 Hz W=Pe+Ph @ f=50 Hz| W [Watts]| Pe [Watts]| Ph [Watts]| Pe+Ph| Rel. Error| 3. 0| 2. 8125| 0. 1042| 2. 9167| 2. 78%| 6. 0| 3. 3125| 2. 529| 5. 8415| 2. 64%| 11. 3| 8. 525| 2. 465| 10. 99| 2. 1%| 16. 8| 10. 3375| 5. 845| 16. 1825| 3. 39%| 22. 5| 17. 375| 6. 425| 23. 8| 5. 78%| Table 9: Calculation of relative error between measure core loss and the sum of the calculated hysteresis and Eddy-current losses at f=60 Hz W=Pe+Ph @ f=60 Hz| W [Watts]| Pe [Watts]| Ph [Watts]| Pe+Ph| Rel. Error| 3. 8| 4. 05| 0. 125| 4. 175| 11. 33%| 7. 5| 4. 77| 3. 0348| 7. 8048| 4. 06%| 15. 0| 12. 276| 2. 958| 15. 234| 1. 56%| 21. 3| 14. 886| 7. 014| 21. 9| 3. 06%| 33. 8| 25. 02| 7. 71| 32. 73| 3. 02%| Curves Figure 1: Power ratio vs. frequency for Bm=0. 4 Figure 2: Power ratio vs. frequency for Bm=0. 6Figure 3: Power ratio vs. frequency for Bm=0. 8 Figure 4: Power ratio vs. frequency for Bm=1. 0 Figure 5: Power ratio vs. frequency for Bm=1. 2 Figure 6: Plot of the log of normalized hysteresis loss vs. log of magnetic flux density Figure 7: Plot of the log of normalized Eddy-current loss vs. log of magnetic flux density Figure 8: Plot of Kg core loss vs. frequency Figure 9: Plot of hysteresis power loss vs. frequency for different values of Bm Figure 10: Plot of Eddy-current power loss vs. frequency for different values of Bm Analysis Figure 11: Linear fit through power frequency ratio vs. requency for Bm=0. 4 The plot in Figure 6 was generated using Matlab’s curve fitting tool. In addition, in order to ob tain the straight line displayed in figure 6, an exclusion rule was created in which the data points in the middle were ignored. The slope and the y-intercept of the line are p1 and p2 respectively. y=mx+b fx=p1x+p2 m=p1=0. 001125 b=p2=-0. 002083 Figure 12: Linear fit through power frequency ratio vs. frequency for Bm=0. 6 The plot in figure 7 was generated in the same manner as the plot in figure 6. The slope and y-intercept obtained for this case are: m=p1=0. 001325 b=p2=0. 5058 Figure 13: Linear fit through power frequency ratio vs. frequency for Bm=0. 8 For the linear fit displayed in figure 8, no exclusion was used. The data points were well behaved; therefore the exclusion was not necessary. The slope and y-intercept are the following: m=p1=0. 00341 b=p2=0. 0493 Figure 14: Linear fit through power frequency ratio vs. frequency for Bm=1. 0 The use of exclusions was not necessary for this particular fit. The slope and y-intercept are listed below: m=p1=0. 004135 b=p2=0. 1169 Fig ure 15: Linear fit through power frequency ratio vs. frequency for Bm=1. 2The use of exclusions was not necessary for this particular fit. The slope and y-intercept are listed below: m=p1=0. 00695 b=p2=0. 1285 Figure 16: Linear fit through log (Kh*Bm^n) vs. log Bm For the plot in figure 11, exclusion was created to ignore the value in the bottom left corner. This was done because this value was negative which implies that the hysteresis loss had to be negative, and this result did not make sense. The slope of this straight line represents the exponent n and the y intercept represents log(Kh). b=logKh>Kh=10b=10-1. 014=0. 097 n=m=1. 554 Figure 17: Linear fit through log (Ke*Bm^2) vs. og Bm No exclusion rule was necessary to perform the linear fit through the data points. b=logKe>Ke=10b=0. 004487 Discussion 1. Discuss how eddy-current losses and hysteresis losses can be reduced in a transformer core. To reduce eddy-currents, the armature and field cores are constructed from laminated s teel sheets. The laminated sheets are insulated from one another so that current cannot flow from one sheet to the other. To   reduce   hysteresis   losses,   most   DC   armatures   are   constructed   of   heat-treated   silicon   steel, which has an inherently low hysteresis loss. . Using the hysteresis loss data, compute the value for the constant n. n=1. 554 The details of how this parameter was computed are under the analysis section. 3. Explain why the wattmeter voltage coil must be connected across the secondary winding terminals. The watt-meter voltage coil must be connected across the secondary winding terminals because the whole purpose of this experiment is to measure and separate the losses that occur in the core of a transformer, and connecting the potential coil to the secondary is the only way of measuring the loss.Recall that in an ideal transformer P into the primary is equal to P out of the secondary, but in reality, P into the primary is n ot equal to P out of the secondary. This is due to the core losses that we want to measure in this experiment. Conclusion I believe that this laboratory experiment was successful because the objectives of both part 1 and 2 were fulfilled, namely, to experimentally determine the inductance value of an inductor with and without a magnetic core and to separate the core losses into Hysteresis and Eddy-current losses.The inductance values were determined and the values obtained made sense. As expected the inductance of an inductor without the addition of a magnetic core was less than that of an inductor with a magnetic core. Furthermore, part 2 of this experiment was successful in the sense that after our professor provided us with the necessary measurement values, meaningful data analysis and calculations were made possible. The data obtained using matlab’s curve fitting toolbox made physical sense and allowed us to plot several required graphs.Even though analyzing the first set of values our professor provided us with was very difficult and time consuming, after receiving an email with more detailed information on how to analyze the data provided to us, we were able to get the job done. In addition to fulfilling the goals of this experiment, I consider this laboratory was even more of a success because it provided us with the opportunity of using matlab for data analysis and visualization. I know this is a valuable skill to mastery over. Appendix Matlab Code used to generate plots and the linear fits %% Defining range of variables Bm=[0. 4:. 2:1. ]; % Maximum magnetic flux density f=[30:10:60]; % range of frequencies in Hz Es1=[20. 8 31. 1 41. 5 51. 9 62. 3]; % Induced voltage on the secundary @ 30 Hz Es2=[27. 7 41. 5 55. 4 69. 2 83. 0]; % Induced voltage on the secundary @ 40 Hz Es3=[34. 6 51. 9 69. 2 86. 5 103. 8]; % Induced voltage on the secundary @ 50 Hz Es4=[41. 5 62. 3 83. 0 103. 6 124. 5]; % Induced voltage on the secundary @ 60 Hz W1=[1 2. 5 4. 5 7 10. 4]; % Power loss in the core @ 30 Hz W2=[1. 5 4. 5 7. 4 11. 5 16. 2]; % Power loss in the core @ 40 Hz W3=[3 6 11. 3 16. 8 22. ]; % Power loss in the core @ 50 Hz W4=[3. 8 7. 5 15. 0 21. 3 33. 8]; % Power loss in the core @ 60 Hz W=[W1†² W2†² W3†² W4†²]; % Power loss for all frequencies W_f1=W(1,:). /f; % Power to frequency ratio for Bm=0. 4 W_f2=W(2,:). /f; % Power to frequency ratio for Bm=0. 6 W_f3=W(3,:). /f; % Power to frequency ratio for Bm=0. 8 W_f4=W(4,:). /f; % Power to frequency ratio for Bm=1 W_f5=W(5,:). /f; % Power to frequency ratio for Bm=1. 2 %% Generating plots of W/f vs frequency for diffrent values of Bm Plotting W/f vs. frequency for Bm=0. 4 plot(f,W_f1,'rX','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Power Ratio [W/Hz]'); grid on; title(‘Power Ratio vs. Frequency For Bm=0. 4†²); % Plotting W/f vs. frequency for Bm=0. 6 figure(2); plot(f,W_f2,'rX','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(â €˜Power Ratio [W/Hz]'); grid on; title(‘Power Ratio vs. Frequency For Bm=0. 6†²); % Plotting W/f vs. frequency for Bm=0. 8 figure(3); plot(f,W_f3,'rX','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Power Ratio [W/Hz]'); grid on; title(‘Power Ratio vs. Frequency For Bm=0. 8†²); % Plotting W/f vs. frequency for Bm=1. figure(4); plot(f,W_f4,'rX','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Power Ratio [W/Hz]'); grid on; title(‘Power Ratio vs. Frequency For Bm=1. 0†²); % Plotting W/f vs. frequency for Bm=1. 2 figure(5); plot(f,W_f5,'rX','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Power Ratio [W/Hz]'); grid on; title(‘Power Ratio vs. Frequency For Bm=1. 2†²); %% Obtaining Kh and n b=[-0. 002083 0. 05058 0. 0493 0. 1169 0. 1285]; % b=Kh*Bm^n log_b=log10(abs(b)); % Computing the log of magnitude of b( y-intercept) log_Bm=log10(Bm); % Computing the log of Bm Plotting log(Kh*Bm^n) vs. log(B m) figure(6); plot(log_Bm,log_b,'rX','MarkerSize',12); xlabel(‘log(Bm)'); ylabel(‘log(Kh*Bm^n)'); grid on; title(‘Log of Normalized Hysteresis Loss vs. Log of Magnetic Flux Density'); %% Obtaining Ke m=[0. 001125 0. 001325 0. 00341 0. 004135 0. 00695]; % m=Ke*Bm^2 log_m=log10(m); % Computing the log of m% Plotting log(Ke*Bm^2) vs. log(Bm) figure(7); plot(log_Bm,log_m,'rX','MarkerSize',12); xlabel(‘log(Bm)'); ylabel(‘log(Ke*Bm^2)'); grid on; title(‘Log of Normalized Eddy-Current Loss vs. Log of Magnetic Flux Density'); % Plotting W/10 vs. frequency at different values of Bm PLD1=W(1,:). /10; % Power Loss Density for Bm=0. 4 PLD2=W(2,:). /10; % Power Loss Density for Bm=0. 6 PLD3=W(3,:). /10; % Power Loss Density for Bm=0. 8 PLD4=W(4,:). /10; % Power Loss Density for Bm=1. 0 PLD5=W(5,:). /10; % Power Loss Density for Bm=1. 2 figure(8); plot(f,PLD1,'rX','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Power Loss Density [W/Kg]'); grid on; title(‘Power Loss Density vs. Frequency'); old; plot(f,PLD2,'bX','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Power Loss Density [W/Kg]'); grid on; title(‘Power Loss Density vs. Frequency'); plot(f,PLD3,'kX','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Power Loss Density [W/Kg]'); grid on; title(‘Power Loss Density vs. Frequency'); plot(f,PLD4,'mX','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Power Loss Density [W/Kg]'); grid on; title(‘Power Loss Density vs. Frequency'); plot(f,PLD5,'gX','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Power Loss Density [W/Kg]'); grid on; title(‘Power Loss Density vs.Frequency');legend(‘Bm=0. 4†²,'Bm=0. 6', ‘Bm=0. 8', ‘Bm=1. 0', ‘Bm=1. 2†²); %% Defining Ph and Pe Ph=abs(f'*b); Pe=abs(((f'). ^2)*m); %% Plotting Ph for different values of frequency % For Bm=0. 4 figure(9); plot(f,Ph(:,1),'r','MarkerSize',12); xl abel(‘Frequency [Hz]'); ylabel(‘Hysteresis Power Loss [W]'); grid on; title(‘Hysteresis Power Loss vs. Frequency'); % For Bm=0. 6 hold; plot(f,Ph(:,2),'k','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Hysteresis Power Loss [W]'); grid on; title(‘Hysteresis Power Loss vs. Frequency'); % For Bm=0. 8 lot(f,Ph(:,3),'g','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Hysteresis Power Loss [W]'); grid on; title(‘Hysteresis Power Loss vs. Frequency'); % For Bm=1. 0 plot(f,Ph(:,4),'b','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Hysteresis Power Loss [W]'); grid on; title(‘Hysteresis Power Loss vs. Frequency'); % For Bm=1. 0 plot(f,Ph(:,5),'c','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Hysteresis Power Loss [W]'); grid on; title(‘Hysteresis Power Loss vs. Frequency'); legend(‘Bm=0. 4†²,'Bm=0. 6', ‘Bm=0. 8', ‘Bm=1. 0', ‘Bm=1. 2†²); % Plotting P e vs frequency for different values of Bm % For Bm=0. 4 figure(9); plot(f,Pe(:,1),'r','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Hysteresis Power Loss [W]'); grid on; title(‘Hysteresis Power Loss vs. Frequency'); % For Bm=0. 6 hold; plot(f,Pe(:,2),'k','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Hysteresis Power Loss [W]'); grid on; title(‘Hysteresis Power Loss vs. Frequency'); % For Bm=0. 8 plot(f,Pe(:,3),'g','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Hysteresis Power Loss [W]'); grid on; title(‘Hysteresis Power Loss vs. Frequency'); For Bm=1. 0 plot(f,Pe(:,4),'b','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Hysteresis Power Loss [W]'); grid on; title(‘Hysteresis Power Loss vs. Frequency'); % For Bm=1. 0 plot(f,Pe(:,5),'c','MarkerSize',12); xlabel(‘Frequency [Hz]'); ylabel(‘Eddy-Current Power Loss [W]'); grid on; title(‘Eddy-Current Power Loss vs. Frequency'); l egend(‘Bm=0. 4†²,'Bm=0. 6', ‘Bm=0. 8', ‘Bm=1. 0', ‘Bm=1. 2'); Bibliography Chapman, Stephen J. Electric Machinery Fundamentals. Maidenhead: McGraw-Hill Education, 2005. Print. http://www. tpub. com/content/doe/h1011v2/css/h1011v2_89. htm

Health Policies in Relation to Nurse to Patient Ratio Essay

One suggested approach to ensure safe and effective patient care has been to mandate nurse staffing ratios. In 1999 California became the first state to mandate minimum nurse-to-patient ratios in hospitals. California is not the only state to enact minimum nurse staffing ratios for hospitals, over the past four years at least eighteen other states have considered legislation regarding nurse staffing in hospitals. Policymakers are forced to consider alternatives to nurses ratios due to nurse shortages. Whether minimum staffing ratios will improve working conditions enough to increase nurse supply is unknown. The United States healthcare system has changed significantly over the past two decades. Advances in technology and an aging population (baby boomers) have led to changes in the structure, organization, and delivery of health care services (Spetz, 2001). Low nurse staffing levels in acute care hospitals are jeopardizing the quality of patient care and is the leading cause for Registered Nurses (RNs) to leave the profession (Spetz, Seago, et al., 2000). Apprehension for the nursing workforce and the safety of patients in the U.S. healthcare system now has the unprecedented attention of healthcare policy leaders at every level (Spetz, 2001). One suggested approach to ensure safe and effective patient care has been to mandate nurse staffing ratios (Donaldson, FAAN, Bolton, Janet, Meenu Sandhu, 2005). In 1999 California did just that, it became the first state to enact legislation mandating minimum nurse-to-patient ratios in acute care hospitals (Donaldson, FAAN, Bolton, Janet, Meenu Sandhu, 2005). Assembly Bill 394 (1999), directed the California Department of Health Services (DHS) to establish specific nurse-to-patient ratios for inpatient units in acute care hospitals. This was done by creating a hospital Licensed nurses classification to include both RNs and licensed vocational nurses (LVNs) also referred to as licensed practical nurses (LPNs) (California, 2002 July). This was not the first time a legislation had contemplated a nurse-to-patient ratio. In 1996, proposition 216 would have established staffing standards for all licensed health care facilities in addition to creating a statewide health insurance system (California, 2002 Janurary). The ballot proposition  that was rejected by the voters in 1996. Again in 1998, Assembly Bill 695 was introduced and approved by the state legislature but vetoed by then Gov. Pete Wilson (California, 2002 Janurary). Intense lobbying by unions representing California nurses would change everything with the passage of Assembly Bill 394 (California, 2002 July). The intense lobbing paid off with the election of a new governor, Gray Davis, in November 1998, who was endorsed by unions representing nurses and other workers (Spetz, Seago, et al., 2000). California DHS proposed the minimum nurse-to-patient ratios (California Hospital, 2004). Thus ranged from one nurse per patient in operating rooms to one nurse per eight infants in newborn nurseries. The DHS proposed that the minimum ratios for medical-surgical and rehabilitation units be phased in (California Hospital, 2004). They initially set minimum ratios for these units at one RN or LVN per six patients and within twelve to eighteen months the goal was to shift to one nurse per five patients (California, 2002 July). Prior California law regarding nurse staffing in acute care hospitals were extended under Assembly Bill 394 (1999). State and federal regulations affect the demand for licensed nurses. Under the 1976-77 state legislative session, California hospitals must have a minimum ratio of one licensed nurse per two patients in intensive care and coronary care units (California Hospital, 2003). Federally certified nursing homes are required to have a RN director of nursing and a RN on duty 8 hours a day, seven days a week (California state). If the facility has under 60 beds, the director of nursing can serve as the RN on duty (Harrington, 2001). This legislation also requires that at least half of licensed nurses working in intensive care and coronary care units be RNs (California state ,Title 22, Division 5, Chapter 1, Article 6, Section 70495(e).) Legislation enacted in the early 1990s requires hospitals to use patient classification systems to determine nurse staffing needs for inpatient units on a shift-by-shift basis and to staff accordingly (California state ,Title 22, Division 5, Chapter 1, Article 6, Section 70495(e)). In January 2004, hospitals also will face minimum licensed nurse-to-patient  ratio requirements in other hospital units, as established by Assembly Bill 394 (California state, Chapter 945, Statutes of 1999). Numerous estimates of the effect of these ratios on demand for licensed nurses have been published. The DHS analysis, conducted by researchers at the University of California, Davis, predicts that 5,820 new nurses will be needed in California hospitals to meet the staffing requirements (Kravitz, Sauve, Hodge, et al., 2002). Other analyses conducted by independent researchers have reported that the increased demand for nurses due to the ratios could be as low as 1,600 (Spetz, 2002). Growing numbers of research associates important benefits for patients and nurses will arise with the Assembly Bill 394 (Aiken, Clarke, Sloane, 2002). It has been argued that nurse staffing levels are now so low as to jeopardize the well-being of hospital patients (California. Office of the Governor, 2002). Supporting Assembly Bill 394, minimum nurse-to-patient ratios assure quality by establishing a minimum standard below which no hospital can fall (Assembly Bill 394, 1999). Researchers disagree with California’s statute requiring use of acuity-based patient classification systems because it is inadequate and difficult to determine whether hospitals are complying with this mandate (California Hospital, 2004). Instead they support a, simple minimum ratios to enable nurses, patients, and family members to easily identify and report inpatient units with dangerously low staffing levels (Donaldson, FAAN, Bolton, Janet, Meenu Sandhu, 2005). It is believed that working conditions have a large influence on the number of persons willing to practice nursing in hospitals (Kravitz, Sauve, Hodge, 2002). To most, minimum staffing ratios would improve working conditions, which would in turn reduce the numbers of nurses leaving hospital positions and the nursing profession (Donaldson, FAAN, Bolton, Janet, Meenu Sandhu, 2005). Creating a better work environment and conditions also may attract more young persons to nursing (Kravitz, Sauve, Hodge, 2002). Increased attention to nursing and rising salaries are already raising interest levels; the American Association of Colleges of Nursing reports that enrollments in baccalaureate nursing programs increased in 2001, for the first time in six years (American Association of Colleges of Nursing, 2001). The Assembly Bill 394 (1999), is great and will create a safer environment for patients, and staffing ratios would help to alleviate the nursing shortage but without nurses to meet the ratios one cannot uphold and follow the nurse-patient-ratios. This is why California Governor Gray Davis announced the Nurse Workforce Initiative in his January 2002 State-of-the-State speech (California. Office of the Governor, 2002). The purpose of the Nurse Workforce Initiative (NWI) is to develop and implement proposals to recruit, train, and retain nurses both to address the current shortage of nurses in California and to support implementation of new hospital nurse-to-patient staffing ratios also announced in late January 2002 (Seago, Spetz, Coffman, Rosenoff, O’Neil, 2003). The Governor made available $60 million over three years for the NWI (California, 2002 July). His goal is to use components designed to address the nurse shortage using both short and longer term strategies. This can range from working in partnership with local hospitals, scholarships for nursing students, career ladder projects, workplace reform efforts, and other strategies to increase the number of nurses (California, 2002 July). An evaluation will be done to determine which strategies to increase the supply of nurses are most effective and improve the understanding of the labor market dynamics for nurses (Seago, et al, 2003). Whether minimum staffing ratios will improve working conditions enough to increase nurse supply is unknown. The experience of hospitals in Victoria, Australia, one of the few jurisdictions to implement minimum nurse-to-patient ratios in hospitals, is instructive (Needleman, Buerhaus, Mattke, Stewart, Zelevinsky, 2001). Large numbers of nurses returned to the nursing profession after the minimum ratios were established. However, hospitals continued to face a shortage of nurses, because there were not enough returning nurses to meet demand, forcing hospital to close hospital beds (Needleman, Buerhaus, Mattke, Stewart, Zelevinsky, 2001). Besides, minimum staffing ratios address only one piece of the ‘  dissatisfaction with hospital nursing. Staffing is a major concern of many nurses, but RN job satisfaction indicates that they are also dissatisfied with other aspects of their work, including low salaries, lack of control over work schedules, lack of opportunities for advancement, lack of support from nursing administrators, lack of input into policy and management decisions, and inadequate support staff to perform non nursing tasks (Spetz, 2002). Maine and Massachusetts state affiliates cut their ties with the American Nurses Association (ANA) in 2001, in large part because they did not fully agree with the ANA’s opposition to minimum nurse-to-patient ratios (American Nurses Association, 2003). This led to the establishment of the American Association of Registered Nurses in February 2002, leaders of unions representing nurses in California, Maine, Massachusetts, Missouri, and Pennsylvania joined to establish a new national association (New England, 2005). The unions will join forces on national projects and support one another’s state legislative, collective bargaining, and organizing campaigns. Further research is needed to establish the number of states in which nurses’ unions have sufficient political power to enact minimum nurse-to-patient ratios. In the short term, the number of states is likely to be small. California’s rate of unionization among nurses, approximately 25 percent, is much higher than that of most states (Aiken, Clarke, Sloane, 2002). In addition, ANA affiliates are more powerful in other states than in California. Proactive ANA affiliates may be able to persuade policymakers to implement other reforms that address nurses’ concerns about hospital staffing (American Nurses Association, 2003). Other important variables include the political influence of state AHA affiliates and elected officials’ ties to organized labor (American Nurses Association, 2003). California is not the only state to enact minimum nurse staffing ratios for hospitals, over the past four years at least eighteen other states have considered legislation regarding nurse staffing in hospitals (New England, 2005). Twelve states have considered bills that would mandate minimum nurse-to-patient ratios in hospitals. Fourteen states have considered  legislation that attempts to address nurses’ concerns about staffing through other means, such as requiring hospitals to develop staffing plans based on patient acuity, mandating disclosure of nurse staffing ratios, and establishing a task force to study and monitor nurse staffing. Oregon, has enacted legislation that requires acuity-based staffing plans (New England, 2005). Policymakers in other states may wish to consider a well-designed acuity-based ratio system as an alternative to minimum nurse-to-patient ratios (New England, 2005). Many states have regulations that require hospitals to use patient classification systems to determine nurse staffing, but these regulations face much criticism, as discussed above. Although many of these regulatory systems do not function well today, they could form the basis for strong but flexible staffing regulations in the future (New England, 2005). States could mandate particular patient classification systems, develop methods of ensuring that staff and patients are aware of the required staffing during every shift, and establish effective enforcement mechanisms (New England, 2005). Alternatively, states could require that hospitals submit information relevant to their staffing needs every quarter and could mandate a ratio for that quarter based on an analysis of patients’ needs, availability of support staff, and other factors (New England, 2005). Texas is pursuing a totally different approach to the nursing situation that is tailored to the unique circumstances of individual hospitals. Under regulations issued 24 March 2002, hospitals are required to establish committees to develop nurse staffing plans and to use data on nurse-sensitive patient outcomes to assess and adjust staffing plans (Texas Nurses Association, 2002). At least one-third of the members of these committees must be RNs engaged primarily in direct patient care (Institute, 1999). The minimal nurse staffing on patient acuity or nurse-sensitive outcomes respond to nurses’ justifiable concerns about hospital staffing without imposing rigid mandates (Harrington, 2001). The flexible staffing approaches seem more appropriate than ratios, given the complexity and rapid pace of  technology changing the delivery of hospital care. (Harrington, 2001). Nurses’ job satisfaction and retention may enhance the opportunities for hospital nurses to play a more direct role in staffing decisions (Kravitz, Sauve, Hodge, 2002). The key is without more nurses no ratio can be met. So the focus needs shift on reaching as many young people as possible by showing them that they to could be a good fit in the nursing community. They need to know that nurses are people too, and the traits of a nurse, such as not being squeamish over the sight of blood comes with time. Stepping out into the high schools and broadcasting information about nurses can translate into only one thing, more students who pursue a nursing career. There is no better way to start, than by planting a seed in the mind of a young person who is about to step out into the world and choose a career. The more educating and qualified young people health care workers can get to chose a nursing career, the better off the nurse-to-patient ratio becomes, allowing for a safer environment for future patients, by permitting more effective health care. References Aiken, L., & Clarke, S., & Sloane, D. (2002). Hospital Restructuring: Does It AdverselyAffect Care and Outcomes? Journal of Nursing Administration, 30(10), 457-465. American Nurses Association. (2003). Nurse Staffing Plans and Ratios. Retrieved June, 10, 2007, from http://nursingworld.org/GOVA/STATE/2003/ratio1203.pdfAmerican Association of Colleges of Nursing. (2001, December 20). Enrollments Rise at U.S. Nursing Colleges and Universities Ending a Six-Year Period of Decline, Press Release, Retrieved 10 June, 2007, from www.aacn.nche.edu/Media/NewsReleases/enrl01.htmAssembly Bill 394. (1999). Retrieved 10 June, 2007, from http://info.sen.ca.gov/pub/99-00/bill/asm/ab_0351-0400/ab_394_cfa_19990628_171358_sen_comm.htmlCalifornia Hospital Association. (2004). California’s nurse-to-patient staffing ratios: Proposedmodifications. Retrieved March 14, 2005 from http://www.calhealth.org/public/press/Article/124/Ratio%20Modifications%20Fac t%20Sheet%20finaCalifornia Hospital Association. (2003, September). Hospital minimum nurse-to-patient ratios asrequired by AB 394. Retrieved April 13, 2005 fromhttp://www.calhealth.org/public/press/Article/113/Nurse%20Ratio%20chart.pdfCalifornia. Office of the Governor. (2002, January 22). Governor Gray Davis Announces Proposed Nurse-to-Patient Ratios. Press Release, Sacramento: Office of the Governor. California. Office of the Governor. (2002, July 15). Sets Nation’s First Safe Nursing Standards: Governor Davis Announces Nurse-to-Patient Ratios, Press Release, Retrieved 10 June, 2007, fromhttp://www.calnurses.org/nursing-practice/ratios/ratios_index.htmlCalifornia state legislature Retrieved 10 June, 2007, from http://www.legislature.ca.gov/Donaldson, N., & FAAN, B., & Bolton, L., & Janet E., & Meenu Sandhu, M. (2005, August 08). New study examines impact of nurse-patient ratios law, California. Retrieved 10 June, 2007, from Policy, Politics & Nursing Practice’s website: http://ppn.sagepub.comHarrington, Charlene. 2001. â€Å"Nursing Facility Staffing Policy: A Case Study for Political Change.† Policy, Politics, and Nursing Practice, 2(2), 117-127. Institute for Health and Socio-Economic Policy. (1999 September). California Health Care: Sicker Patients, Fewer RNs, Fewer Staffed Beds. Retrieved 10 June, 2007 from www.calnurse.org/cna/pdf/StaffingRatios6.pdfKravitz, R., & Sauve, M., & Hodge, M. (2002). Hospital NursingStaff Ratios and Quality of Care. University of California – Davis, report submitted to State of California, Department of Health Services, Licensing andCertification. Needleman, J., & Buerhaus, P., & Mattke, S., & Stewart, M., & Zelevinsky, K. (2001). Nurse Staffing and Patient Outcomes in Hospitals. Washington DC: Bureau of Health Professions, U.S. Department of Health and Human Services. Retrieved June, 10, 2007, from http://bhpr.hrsa.gov/nursing/staffstudy.htmNew England public policy center and the Massachusetts health policy forum. (2005, July). Nurse-to-patient ratios: Research and reality. Retrieved 10 June, 2007, from http://www.bos.frb.org/economic/neppc/conreports/2005/conreport051.pdfSpetz,

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