Looking At The Fate Of Romeo And Juliet English Literature Essay

Looking At The Fate Of Romeo And Juliet English Literature EssayRomeo pronounces these news shows properly after having mortally wounded Tybalt, guilty of having skilful killed Romeos friend Mercutio. In a fit of rage, Romeo takes his s give voice and attacks Tybalt ferociously, killing him. This is the climax of the play, that will change ineluctably the destiny of the 2 star-crossed l everywheres. Romeo realizes what he has done, now he knows he has to pay the consequences of his deed, his already dangerous love for Juliet is going to cause a compulsive twine of tragic events, bringing the cardinal lovers to certain death. He defines himself as a puppet of the unpredictable destiny. scour from the opening lines, the audience is informed about the calamity that is going to affect the two protagonists, establishing batch as a theme at the foreground of the play. The idea that tragic circumstances were decided from birth for these two lovers is suggested from forth the fatal loins (I.i.5). This line together with, a pair of star-crossed lovers take their life (I.i.6) explains to the audience that destiny was what first brought them together and is what will eventually separate them. The Choruss opening speech is continually echoed through and throughout the rest of the play by other characters making direct references to fate. As Susan Snyder states tragedy force out be seen as a ritual sacrifice, in which the protagonist is both hero and dupe, , separated from the ordinary, but destined for destruction.2Even though Romeo defines himself as helpless victim of his fortune, at that place is much evidence of the important roles that Romeo and Juliet give up in shaping and, in many cases, worsening, their destiny. After a careful reading of the play we can state that it is not just a question of destiny. Romeo and Juliet would have been able to save their relationship simply by using more acuteness, composure and resolution. The cream of means confront ing Romeo and Juliet is not confined to a single occasion, they are given a series opportunity of choice3, but unluckily they always have the appearance _or_ semblance to choose the wrong way in which to direct their story.Again we sense a metaphor relating to the stars, as if Shakespeare has chosen these celestial bodies as symbols for the fatality that lies over the whole play. But here we find the first of Romeos mistakes, he takes a decision without thinking of the consequences he has read the list of guests that are going to be at the feast and although he is informed about the presence of Capulets, Montagues arch-enemies, he decides to attend in any case. As already mentioned, Romeo kills Tybalt out of rage, even though he knows it makes things all the worse for his current placement with Tybalts cousin, Juliet but a far more basic instinct, the desire of a man to avoid macrocosm thought a coward prevails and Romeo is driven to fight Tybalt.While Romeo lacks composure, Jul iets flaw is impetuosity. During the balcony scene, Juliet hurries Romeo into marriage by constantly questioning his love for her and saying things like, If thy purpose marriage, send me word tomorrow (II.i.143-4). The Friars flaw, which in the end had a big effect on this tragedy, is to be too impulsive. He offers to marry Romeo and Juliet, even though he knows there is a huge conflict between the families, probably hoping that the marriage would have solved all the rivalries. Moreover, we must remember that it is the Friar who gives Juliet the potion for suspended animation, which aggravates things even more.Even though the protagonists share many fatal defects, lots of things happen to their misfortune that is not their fault. First of all, Romeo and Juliet shared the unfortunate fate that they were from feuding families, putting their relationship in jeopardy from the beginning. Juliet expresses well this idea in her soliloquy on the balcony Whats in a name? That which we call a rose, by any other word would smell as sweet (II.i.86-87). A second strike of bad luck is the fact that the Capulets, being a typical upper-class traditionalist family, had place a marriage between Juliet and capital of France, against the will of their daughter.The scene in which Romeo finds out about the feast is another twist of fate. The illiterate servant of Capulets was given the crease of telling people about the party. Since he could not read, he was forced to ask two strangers to explain it to him. Those two people could have been anyone, but they just happened to be Romeo and Benvolio. Another ironic fact is that Romeo went to the party because he was madly in love with Rosaline. If Rosaline had been there, and she returned Romeos love, then all the following suffering would never have occurred. Romeo was completely in love with another woman going to the party, which he only found out about in the first place through an adverse stroke of luck. Another example of bad luck is that Romeo never received the letter of Friar Laurence informing him about his and Juliets scheme because of the plague in Mantua, the city where Romeo went to stay after his banishment from Verona. The letter must r individually Romeo in time so that he knows of the arrangement between Juliet and the Friar, but the city has been put under quarantine because of a plague. So Romeo never receives the letter and he is left unaware of the plan between the Friar and JulietAgain we find the concept of fortune. The Friar curses this fate, the unhappy fortune, aware that the story of the two lovers has probably came to an end. Romeo is told by Balthasar that Juliet has died Her body sleeps in Capels monument, and her immortal part with angels stomachs (V.i.18-19). These events are the last still hunt and they will lead to the demise of both characters.Obviously the fate is closely related to the concept of time. Timing, in fact, played the largest role in deciding if they would l ive or die. Many scholars have defined it as the lovers enemy, which retards his pace when the lovers are separated and accelerates it when they are together4O lamentable day O damnable time (IV.iv.57)In the balcony scene Juliet hurries because the Nurse is calling her if Romeo had arrived a few minutes later at the tomb, the tragedy would not have happened moreover, if the wedding of Juliet and Paris had not been brought forward from Thursday to Wednesday the letter would have had more time to reach Romeo in Mantua if the Friar had entered the tomb earlier he could have explained the situation to Romeo and no harm would have happened to anyone. These are only a few examples of the negative and mysterious force that seems to control the happenings.We can definitely say that Romeo and Juliet is a crossing of fortuitous events, coincidences and personal responsibilities, all masterfully managed by fate and time. The love story did not have to begin, the two lovers were not meant to m eet each other, son and daughter of rival families. They both knew this, but they could not accept it, their love was bigger than anything else. What if it was the temptation of the forbidden which increased their love? Two teenagers, two rebels living in a sexist society made of wedding vows and past rivalry. They preferred to risk, but risking is a matter of fate, a cruel fate which brought them to a certain death. As said by Cassius in Shakespeares Julius Caesar5, The fault, , is not in our stars but in ourselves (I.ii-139-40).

Quantization effects in digital filters

quantisation personal effects in digital carrysABSTRACTQuantization effects in digital filters can be split up into intravenous feeding main categories quantisation of organisation coefficients, fallacys due to A-D conversion, actus reuss due to roundoffs in the arithmetical, and a constraint on signal level due to the requirement that overflow must be prevented in the comparison. The effects of quantisation on implementations of two basic algorithms of digital filtering-the first-or second-order linear recursive difference equation, and the fast Fourier transform (FFT) be analyze in some detail. For these algorithms, the differing quantisation effects of fixed point, rudderless point, and block floating point arithmetic are examined and compared. The ideas developed in the study of dewy-eyed recursive filters and the FFT are applied to analyze the effects of coefficient quantization, roundoff fray, and the overflow constraint in two more complicated types of digita l filters frequency sampling and FFT filters. Realizations of the aforesaid(prenominal) filter design, by means of the frequency sampling and FFT methods, are compared on the basis of differing quantization effects. All the go analyses in the report are found on simple statistical models for roundoff and A-D conversion computer errors. Experimental randomness measurements testing the predictions of these models are reported, and the empirical allows are generally in good agreement with the statistical predictionsINTRODUCTIONDigital filters are widely apply in modern signal-transmission systems. The first-order filters are utilize for extracting lower-frequency or upper-frequency signals. Quantization errors due to the finite bout of binary digits in the incorporateation of add up are typical of digital filters.Quantization is a representation of data samples with a certain number of insect bites per sample afterwards rounding to a suitable level of precision. Quantiza tion errors in a Digital Signal Processing (DSP) system can be introduced from three sources unmatchable source is input quantization, a second is coefficient quantization and the third is the finite precision in the arithmetic operations.The quantization error in the arithmetic operations can be controlled by carefully selecting the size of buffer registers according to the input playscript space. Quantization errors from input and filter samples are considered in this article. The effects of quantization errors and the tradeoffs required between precision and hardware resources are discussed in relation to the implementation of the DSP in Field Programmable Gate Array (FPGA).This article is divided into three main sections quantization effects for upconversion, quantization noise due to rounding off arithmetic and quantization effects for digital chargeforming (DBF). Fixed length samples cause reduction in the filter high-octane range and gain settlement.QuantizationIn digit al signal processing, quantization is the process of approximating (mapping) a dogging range of prizes (or a real large set of possible discrete values) by a relatively small (finite) set of (values which can alleviate take on straight range) discrete symbols or integer values. For typesetters case, rounding a real number in the interval 0,100 to an integer 0,1,2,100.In different volumes, quantization can be described as a mapping that represents a finite continuous interval I = a,b of the range of a continuous valued signal, with a hit number c, which is also on that interval. For example, rounding to the nearest integer (rounding up) replaces the interval c .5,c + .5) with the number c, for integer c. After that quantization we bewilder a finite set of values which can be encoded by say binary techniques.A. quantization EFFECTS ON UPCONVERSIONIn multirate systems, upconvcersion can be achieved with oversampling and filtering techniques. For the proposed digital TIGER s ystem, input Gaussian pulses are upsampled to produce higher order Nyquist zones. A high pass fir tree filter is employed to hire a spectral zone at the expanded band edge. In this case, higher efficiency is possible by exploiting filter symmetry. For a higher throughput rate, polyphase implementation of the FIR filters can be employed. Since signal amplification is performed in the analog domain, a high speed 14 bit DAC is used for digital to analog conversion. Finite precision causes similar effects in the input data samples and filter coefficients. Fixed discourse length effects on filter coefficients, filter length and self-propelled range are described in the following sections.1. Sensitivity of Filter Coefficients to QuantizationFinite precision plays a solid role in the dynamic range of filter gain and DC offset. A large number of quantization levels will decrease the quantization error on the other hand it requires larger silicon space to implement the design. The quanti zation affects the input Gaussian pulse and the filter coefficients. The pole and zero maps orient perturbations in approximate 1 when samples are restricted to finite word length. The filter coefficients in the lower parts are constrained to 14 bit quantized samples and the length of the filter is 100 taps. This constraint arises from the fast DAC of 14 bit width used for converting a digital signal into the analog domain. Since the dynamic range of the quantizer is less than that of the filter coefficients, the quantized coefficients are disturbed from the unit peck. The gain of the quantized filter response is displayed in Figure 1 which is intelligibly less than that for the innumerous precision filter. For these simulations infinite precision representation is regarded as floating point, which provides significantly better precision than the quantization levels discussed here. The zeros rough Z = -1 are responsible for passband attenuation and are less displaced. As the d ynamic range of the quantizer is amplifyd to match the filter coefficients, the signal to quantization noise ratio (SNR) improves, just now at the cost of increased hardware resources. Similar results can be obtained for the input Gaussian pulse when quantized to specified fourteen bit word lengths.Finite precision is hardware efficient since the system data width is less than the infinite precision (or floating point) case. Quantization reduces a few pop out of 100 coefficients to zero, which will further ameliorate the memory cell and arithmetic processing requirement. Quantization also reduces the filter gain compared to infinite precision samples moreover this reduction is acceptable as long as it remains within an attenuation limit. The fourteen bit quantizer provides more than 80dB attenuation which is better than the standard of 60dB used by me rattling communication systems.2. Quantization Effects on Filter OrderFor direct conversion transmission, a cascaded design perfo rms better than a single stage. This is because quantization errors are reduced with a lower filter order. Secondly a lower order design requires less logic resources. Quantization errors motley with the length of a filter and we now study the effects of the filter order on the quantization error. A simulated result is shown in Figure 2, where quantization error is plotted against variable filter order. The quantization is performed by rounding the infinite precision samples to the closest fixed point value. The quantization error increases with increased filter order, since the highest force-out index in the filter polynomial is the most affected by the rounding. When the quantizer is increased with one more bit in the precision, the error is reduced by approximately 6dB as would be expected.The lower order filter provides better dynamic range than the higher order for octad and nine bit quantizers. This fact is also evident in Figure 2. At lower filter order of fifty, accumulat ive quantization error is around -43dB and at higher order of 200, it is -31dB. The 12dB difference is equivalent to two appendixal bits in quantization. Non-linear effects of the quantization can be reduced using a smaller filter order in the modulator. Since the cascaded design comprises a filter of lower order, compared with the single model, it introduces less quantization error than the single stage.3. Quantization and book of account lengthThe dynamic range of the scaled filter depends on the number of bits assigned to the quantizer. For maximum signal power, the quantizer range should be equal to the signal magnitude. An FIR filter with filter variance 2 f s and quantization noise variance 2 n s has a signal to noise ratio ofThis expression can be used to estimate the appropriate word length for the FPGA implementation. A comparison of SNR versus word precision using the to a higher place expression has been calculated and is shown in Figure 3. From this graph it is evide nt that for each bit added to the word length, there is approximately a six decibel service in the SNR. For a higher precision level, a system can still be implemented, but at the cost of increased FPGA logic resources.B. QUANTIZATION NOISE DUE TO ROUNDING OF ARITHMETICIn the poly phase filter, like in any other filter, quantization has to be performed on the result of any arithmetic operation. This is because any such operation requires more bits to represent the result than is required for each of the operands. If theWord length were always to be adjusted to bloodline the data in full precision, this would be impractical, as there would soon be too many bits required to be stored in the available memory.Therefore, the word length of the internal data, has to be chosen, and the result of any arithmetic operation has to be constrained back to using the quantization scheme chosen from the ones shown in the previous section, as appropriate for the given application.The quantization operation may cause a disturbance to the result of the arithmetic operation. For normal filtering operations, such a quantization disturbance can usually be successfully considered as white noise and modeled as an additive noise source at the point of the arithmetic operation with the quantization step equal to the LSB of the internal data, . This certainly is not the case for zero-valued or constant input signals. However, modeling the quantization has-in most cases-the purpose of determining the maximum noise disturbance in the system.Hence, even if the additive quantization noise model gives overestimated values of the noise for very specific signals, this fact does not decrease the usefulness of the approach. After the shape of the quantization noise power spectral density (NPSD) is found, it can be used to identify regions that might cause overloading or loss of precision due to arithmetic noise shaping also the required input signal leveling and the required internal arithmet ic word length can be estimated for a given noise performance. The standard methods of estimating the maximum signal level at a given node are L1-norm (modulus of the impulse response-worst-case scenario), L2-norm (statistical mean-square), and L -norm (peak in frequency domain giving the effect of the input spectral shaping). These norms can be easily estimated for the given node from the shape of the NPSD.The quantization noise injected at each adder and multiplier, originally spectrally flat, is shaped by the noise shaping forge (NSF), , calculated from the output of the filter to the input of each of the noise sources, i.e., to the output of each of the arithmetic operators. These functions were calculated for all of the all pass filter manifold body parts are shown in Fig. 2. The shapes of the nontrivial of the NFS are shown in Fig. 3. The salt away quantization NPSD transferred to the output, , is obtained by shaping the uniform NPSD from each of the quantization noise sou rces by the square of the magnitude of the NFS agree to the given noise injection point and can be described byThe results show that all structures perform in a way very distinct from the other ones. Structure (a)has the best performance at dc, half-Nyquist , and Nyquist , where the NPSD falls toward minus infinity. Its two maxima are symmetric about and independent of the coefficient value. The peaks are deep from for small coefficient values and approaches it as the coefficient increases. Structure (b) has uniform noise spectral distribution as all the arithmetic operations are either at the filter input-then noise is shaped by the allpass characteristic of the whole filter-or at itsoutput. Structure (d) also has a minimum at v=0.25 . Its average noise power level decreases as the value of the all pass coefficient increases. Structure (c), the best from the point of view of the required guard bits, has its maximum at v=0.25 going toward infinity for coefficient values approachin g one. This effect is a result of the denominator of the Nth-order all pass filter causing the poles of the filter to move toward the unit circle at normalized frequencies of v=2pik/N,k=0.N-1 for the coefficient approaching one. If there is no counter effect of the numerator, like for the case of P1(Z) for structure (c) and for structure (a), then the function goes to infinity. Even though structure (c) goes to infinity at v=0.25 for alfa=1, it has the lowest average noise power from all the structures. This structure has a big advantage in basis of the number of required guard bits and ease of cascading a number of them into higher order all pass filters. If the filter coefficients approach one, then the increase in quantization noise power could be countered with few additional bits. Using other structures would only replace the problem of dealing with an increase in the quantization noise with the problem of having to increase the number of guard bits required to deal with an in crease of the peak gains. The NPSD of the quantization noise at the output of the poly phase structure can be calculated as the sum of the NPSD at the output of all all pass filters in the filter scaled by the 1/N factor N, being the number of paths. If the filter is cascaded with another filter, the NPSD of the first one will also be shaped by the square of the magnitude of the second filter.sources. The intention was to check the correctness of the theoretical equations by applying the white noise sources instead of quantization and by performing the quantization after addition and multiplication (rounding and truncating) to verify the shaping of the quantization noise and its level both for white input noise sources and real-life signals. The shape of the output quantization noise accumulated from all arithmetic elements for a wide-band input signal assuming, for simplicity, no correlation between the noise sources, is shown for all considered all pass structures in Fig. 4. The s olid arch indicates the theoretical NSF that is very well matching the median of the quantization noise (curves lying on top of each other). The quantization noise power increase calculated for the given coefficient was 8.5 dB for structure (a), 6 dB for structure (c), 7.3 dB for structure (d), and 9 dB for structure (b). It is clear that the quantization noise differs from the assumed white noise characteristic. However, the approximation still holds with an accuracy of around 5-10% depending on the structure of the input signal. An example of more accurate modeling of the quantization noise caused by arithmetic operations can be found in (a). The arithmetic quantization noise certainly decreases the accuracy of the filter output. The value of the arithmetic word length has to be chosen such that the quantization noise power is smaller than the close off band attenuation of the filter and the stop band ripples. In certain cases, the design requirements have to be made more string ent to allow some unavoidable distortion due to the arithmetic word length effects. For the case of decimation filters for the based A/D converters, the quantization noise adds to the one originating from the modulator.In such a case, each stage of the decimator has to be designed so that it filters out this noise as well. The verification of the peak gain analysis was performed by applying single-tone signals at the characteristic frequencies- where functions from Fig. 2 have their extremes-and by using wideband signals to make sure that the estimates are accurate. The experimental results confirmed the theoretical calculations. The results of the simulation for the white noise input signal of unity power are given in Fig. 8. The simulation was performed for a white noise input signal of unity power in order to have a uniform gain analysis across the whole range of frequencies. The theoretical shape of the gain is shown by a solid line that is very about matching the median value of the signal at the test points.C. QUANTIZATION EFFECTS ON DIGITAL BEAMFORMINGThe quantization of infinite precision samples into fixed word length degrades the phased signals. As was discussed in the previous section, the use of more levels for higher precision decreases the quantization error at the expense of larger hardware resources. For a reduced precision level, quantization error is spread to the main beams and to the grating lobes as well. In this section we present effects of quantization on beam resolution and associated grating lobes.1. Quantization effects on Beam PatternPhased signals have similar quantized effects on main beam resolution as the filter samples. However non-linearity arises in the sidelobes since the quantizer is not of adequate resolution to represent small changes that affect the sidelobe levels. In order to investigate the quantization effects, an example is presented with fixed word length delay samples. The coefficients of the time vector are quan tized into four and ten bits the increased number of bits will reduce the quantization effect. For an actual design the fixed bit width will depend on available hardware resources. The quantized beam in Figure 1 shows that a four bit fixed number does not adequately represent the beam pattern and thus introduces quantization noise. The ten bit numbers will also introduce quantization error, but at a lower level as shown in Figure 1(b). As can be seen from this simple example, the four bit quantization compromises the sidelobes at the 20dB level, while the ten bit quantization provides a reasonably faithful reconstruction of the theoretical sidelobes at this level. Therefore we conclude that for the 14 bit DAC of the proposed system, the sidelobe level will be essentially unaffected by the quantization at the -20dB level.2. Sensitivity of Sidelobe Levels to QuantizationQuantization causes gain errors in sidelobe levels. Higher resolution in quantization introduces lower quantization error. The graph in Figure 1 shows that the four bit samples result in a quantization error which reduces the first sidelobe gain while producing a gain error in the second sidelobe. The quantization error changes the dynamic range of the grating lobes and degrades the adjacent beam resolution for multiple beam systems. A simulated graph is displayed in Figure 2 to demonstrate non-linear demeanor of the quantizer in the sidelobe resolution.For a lower order quantizer, the quantization step is not perfectly matched with the sidelobe levels. For the first sidelobe, the quantized resolution is less than the infinite precision case, although it approaches the floating point value with increasing quantized levels. Figure 2(a) shows that for a three bit quantizer, the first sidelobe resolution is at -18dB, while at ten bits it approaches the infinite precision value of -13.5dB. Unlike the first sidelobe, the second sidelobe exhibits higher resolution error at a lower precision level, sin ce the quantizer can not represent the dynamic range adequately. Again, quantization error reduces with an increase in the number of bits.CONCLUSIONIn this paper, effect of fixed word lengths on signal upconversion, quantization noise due to round of arithmetic and quantization effects on digital beam forming have been discussed. For the digital up conversion process, the quantization error can be described using pole/zero filter and frequency response plots. Filter resolution and stop band attenuation are degraded when quantization is introduced. For an increase in filter order, the quantization error increases as the highest order in filter polynomial is effected the most. To overcome this limitation, the number of precision levels of a quantizer can be increased, however this will require increased logic resources for FPGA implementation. Quantization effects in phasing are more complex than in the filter quantization since finite precision degrades the side lobe resolution. For lower precision levels, the quantization error exhibits non-linear behavior in the second side lobe. The quantization error is higher for lower precision levels. In order to overcome these non-linear effects, a precision level of more than eight bits is required. Performance of the proposed digital system will be effectively unaffected by the fixed word length limitations since a system data bus of at least 14 bits is suggested.REFERENCESA. B. Sripad and D. L. Snyder, A Necessary and Sufficient Condition for Quantization Errors to be Uniform and WhiteP. P. Vaidyanathan, On coefficient-quantization and computational roundoff effects in lossless multirate filter banks.Google.com

Importance of Setting in Eveline of James Joyces Dubliners :: Dubliners Essays

Eveline  The Importance of Setting               Setting is one of the most signifi pratt elements in a story. The screen background goes far beyond the simple physical attributes and extraneous face value. It seems Eveline solely takes place in Dublin in an old room, but the setting actu eachy plays a key role in the story. The setting in Eveline helps the reader to better understand the behavior of the main character. The setting in Eveline is paralyzing, and this helps the reader to understand why Eveline does not go with Frank to Buenos Aires. In the majority of the story Eveline sat at the window, (512) which parallels with her paralysis because she does not move. Eveline was going to go a trend interchangeable the others (512) because she was one of the only people left in Dublin from her childhood. However, Eveline doesnt go since she is trapped in her setting. Almost nothing in Evelines setting ever changes througho ut her life. The significance of Eveline looking around the room reviewing all its familiar objects (512) is that she never dreamed of being divided from them. All around her Eveline had those she had know all her life about her (512). Eveline is a product of her environment. The reader can see how the setting never changes, Evelines life molds to it. This explains the reason for her not going away and starting a much happier life.  It is extremely hard for her to make the decisiveness of whether or not to go with Frank because she only knows one way. Eveline understands that she has a hard life,(513) and she has the chance to go to a place where it would not be like that (513). However, it scares Eveline to change her setting. After thinking about leaving she did not find her present setting as wholly undesirable (513) as she previously did. The last mentioned part of Eveline is set by the sea. This sea is a symbol of rejuvenation for Eveline. Much like in The Awakening by Kat e Chopin, the sea is a way to escape life. All the seas of the world tumble around her heart, (515) and Eveline is unable to flee from her life to go away with Frank. Evelines mind has been subconsciencly designed by her environment, and she cant imagine keep life any other way. Eveline is so confused and doesnt know what is holding her back, but something is.

Free Hamlet Essays: Lonely Hamlet :: Shakespeare Hamlet Essays

L atomic number 53ly Hamlet   Hamlets decision to keep the murder of his father a secret to himself, along with the betrayals of many of his close friends and family, leads to his ultimate downfall. If someone was there for him, whether it was his mother Gertrude, his girlfriend Ophelia, or Rosencrantz and Guildenstern, maybe his timeless death could have been prevented. Instead, his mother sides with Claudius who wants to kill him, Ophelia wont go back her father, Polonius, back to be with him and Rosencrantz and Guildenstern go behind Hamlets back and spy on him for Claudius.     Gertrudes blindness to the whole situation is sickening. How she marries the brother of her originator husband right after he kills him and never knows the truth is beyond me. She never cared about how her son felt before or after she unite Claudius. She didnt even wait very long after her husband died to get married again ( I ii 180-181. Thrift, thrift, Horatio. The funeral bake d meats did coldly bestow forth the marriage tables.). Therefore she is either a very slow, naïve woman or a very evil, coldhearted one. For someone to side with a person even after their own son has told them that the person theyre with has murdered their former lover is absolute lunacy ( III iv 29-30. A bloody deed- almost as bad, good mother, as kill a king, and marry his brother.). Not knowing the truth in the first arrange is one thing, but turning your back on your own flesh and blood is another. Therefore without his mother on his side, Hamlet has lost all the family in his life that could have helped him get through his terrible time and he sinks lower than ever before.     Ophelias obedience towards her untrusting father is indescribable ( I iii 101-103. Affection? Pooh You speak like a green girl, unsifted in such perilous circumstance. Do you believe his tenders, as you call them?). Why a grown woman would listen to her father and not help the man of he r dreams in his time of need is disheartening. A mans girlfriend should be there for him when a family member passes away, no matter what. If she had been with him on the plan to kill Claudius and knew about his fathers ghost who told Hamlet that Claudius was the one that murdered him, than neither one of them would have went crazy.

How can the role of leadership be best understood in organizational cha

The role of leadership depose best be understood in organisational tilt as a multi-dimensional phenomenon. Depending on the conceptualisation of organizational change you adopt, the leaders role could be perceived to be a vicissitude of things, from that of an initiator/visionary, the influencer of culture, a trigger for follower organizational identification, someone who redefines resistance, or a sense maker who introduces new discourses. The most useful approach can be to consider an issue from a number of different theoretical points of view before determining the most effective intervention.Leadership has been conceived of in a multitude of different ways varying from Great man theory (Borgatta, Bales and Couch, 1954 Cawthon, 1996), trait theories (), and style theories (). More recent conceptualisations of leadership include contingency theory (), and transformational leadership (). Each of these theoretical models has a contribution to make in forming a comprehensive under standing of the relationship between leadership and organizational change and we shall explore how adopting a definition for leadership or organizational change infers the role of the other. However we define leadership, the concepts of organizational change and leadership can be argued to be inextricably linked. If a leader was not able to effect any change within an organization accordingly it is hard to imagine a way in which such a leader could be effective in their role. Thus organizational change is at the very heart of a leaders role.This paper will argue that a pluralist approach to understanding leaderships role in organizational change possesses the greatest utility in informing practice. In doing so, it will present a number of different concepts ... ...ind of universal sense as in doing so, one mistakes the function for the terrain. The role of leadership in organizational change is a multi-dimensional phenomenon which, it has been argued in this paper, can be most use fully understood by employing a pluralist perspective. That is to say, a pluralist approach of comparing multiple plausible models of reality is essential for developing objective scientific knowledge (Campbell, 1988 389, in Van de Ven & Poole, 2005). While there be a plethora of lens through which to understand both leadership and change it is more useful to consider a range of perspectives and only then assess the utility of each perspective and its appropriateness for informing a real world intervention. In the words of Pettigrew (2001) In the absence of clear foundational truth the only sensible way forward can be conscious pluralism.

The Hot Zone by Richard Preston :: Book Report The Hot Zone

The Hot Zone by Richard PrestonIn October of l989, Macaque monkeys, housed at the Reston PrimateQuarantine Unit in Reston, Virginia, began dying(p) from a mysterious disease at analarming rate. The monkeys, imported from the Philippines, were to be sold aslaboratory animals. Twenty-nine of a shipment of one hundred died within a month.Dan Dalgard, the veterinarian who cared for the monkeys, feared they were dyingfrom Simian Hemorrhagic Fever, a disease lethal to monkeys but harmless tohumans. Dr. Dalgard decided to enlist the aid of the United States Army MedicalResearch bring of Infectious Diseases (USAMRIID) to help diagnose the case.On November 28th, Dr. Peter Jahlring of the Institute was in his lab testing a virus culture from the monkeys. Much to his horror, the blood tried positivefor the deadly Ebola Zaire virus. Ebola Zaire is the most lethal of all strainsof Ebola. It is so lethal that nine forbidden of ten of its victims die. Later, thegeniuses at USAMRIID found out th at it wasnt Zaire, but a new strain of Ebola,which they named Ebola Reston. This was added to the list of strains EbolaZaire, Ebola Sudan, and now, Reston. These are all level-four hot viruses. Thatmeans there are no vaccines and there are no cures for these killers.In 1976 Ebola climbed out of its primordial hiding place in the junglesof Africa, and in two outbreaks in Zaire and Sudan wiped out six hundred people.But the virus had never been seen outside of Africa and the consequences ofhaving the virus in a busy suburb of Washington DC is too terrifying tocontemplate. Theoretically, an airborne strain of Ebola could emerge and locomotethe world in about six weeks. Ebola virus victims usually crash and bleed, amilitary term which literally means the virus attacks every harmonium of the bodyand transforms every part of the body into a digested slime of virus particles.A big point that Preston wanted to get across was the fact that the customarythinks that the HIV virus is quite possibly the most horrible virus on Earth,when no one takes into mind the effects and death of the victims of Ebola.Preston shows how Ebola and Marburg (a close sex act of Ebola) is one hundredtimes more contagious, one hundred times as lethal, and one hundr ed times asfast as HIV. Ebola does in ten days what it takes HIV ten years to accomplish,wrote Richard Preston. The virus, though, has a hard time spreading, because the

Artificial Intelligence and Angelology :: Technology Science Computers Essays

Artificial Intelligence and AngelologyABSTRACT Recently, as I have become more computer-literate, I have noticed some interesting parallels in the midst of computer mechanisms and Aquinas metaphysics of angelic faculties. The present essay expands on some of the analogies which Aquinas himself, though no proponent of AI theory, might have be interesting.One of the philosophy newsgroups on the Internet is entitled comp.ai.philosophy. This group features constant variations on questions such as how close can artificial intelligence (particularly computers) guess to human consciousness? is free will reducible to neurological mechanisms? and so forth. From my unscientific sampling, I would estimate that the clientele of this newsgroup is about evenly split between those who tend towards a reductive materialism, and those who maintain that consciousness or some element in human consciousness is not reducible to neural structures or functions. So the classical Hobbes vs. Berkeley debate continues on into the twenty-first millennium.One of the problems facing those who theorize about the independence and irreducibility of consciousness is the fact that it is difficult to conceptualize the loading of consciousness, as distinct from the sensations, feelings, etc. that are often associated with consciousness. Here we are definitely getting into abstract metaphysics. Medieval philosophers such as Aquinas, Duns Scotus and Suarez faced up to this challenge with a little help from Christian revelation, by speculating about the characteristics and functions of angels or separate substances, who would presumably exemplify consciousness in its pure state, without both distracting admixtures. In this paper, I would like to take a look in particular at Aquinas theory of separate substances. With this theory, we bypass the old question of the reducibility or irreducibility of consciousness to its material conditions, and we also find, in my opinion, some interesting analogies to contemporary computer technology. It would be too much to hope that these analogies, even if substantial, would instigate a revival of interest in Angelology among technophiles. But those interested in the metaphysics of the mind-body problem may find them suggestiveMicroprocessors and Angelic Self-possession The microprocessors of todays computers are integrated circuits which control the CPU on a single chip. The latest developments, with variable clock speeds now often exceeding 200 MHz, include Intells Pentium chip, the IBM/Apple/Motorola PowerPC chip, as wellhead as chips from Cyrix and AMD. The CPU chip is the heart of the computer only memory and input-output devices have to be added. A small fan might be added on top of the fastest chips to cool them down, but in the chip itself there are no moving parts, no complex gaps between the movement organism imparted and that which imparts the movement.