Themes in Hamlet Essay Example for Free

Themes in Hamlet Essay To what extent does Shakespeare deal with these themes in Hamlet? As consistent with all Shakespearean tragedies, Shakespeare uses the fatal flaws of the central characters to bring about their downfall which ultimately leads to their death. In Hamlet, deceit and betrayal initiates the failures of the main characters, particularly Prince Hamlet, King Claudius and Ophelia. These themes are pivotal to their actions and are used to expose the flaws of the characters that lead to their downfall and eventually, death. Shakespeare begins the play with the depressed, yet innocent Hamlet, who is in mourning for the recently dead king, his father. He is angry at his mother, for quickly marrying the new King, also his uncle. He feels betrayed by his mother because she was able to forget her previous husband so quickly and easily. He is melancholic because of his father’s death but more because of his mother’s â€Å"speedy marriage†. In his fury, he stereotypes all women as weak, â€Å"Frailty, thy name is woman. † He is uncomfortable with what he feels is an unacceptable situation and he senses, â€Å"It is not, nor can it come to, good. † Despite his negative feelings, his emotions are controlled and he does not even consider the possibility that his father was murdered and he is portrayed as blameless and wide open to deceit. Shakespeare creates the first twist of the play when Hamlet meets the ghost, his â€Å"father’s spirit†. The ghost divulges to a shocked Hamlet that his father was victim of â€Å"murder most foul† and urges the prince to â€Å"revenge his foul and most unnatural murder. The serpent that did sting thy father’s life now wears his crown,† thus revealing to Hamlet the betrayal and deceit of Claudius. Hamlet is outraged and disgusted by what he learns and promises the ghost, â€Å"Thy commandment all alone shall live within the book and volume of my brain. † He will seek nothing but revenge and he entrusts only the loyal Horatio and Marcellus with his sinister findings. Claudius murders his own brother and king to introduce the complex web of deceit and betrayal that make up the play. After Hamlet’s meeting with the ghost, Hamlet is convinced that he has been victim of betrayal and deceit as he refers to the spirit as â€Å"an honest ghost†. His previously controlled emotions reach boiling point and he is furious enough to call his mother a â€Å"most pernicious woman†. He is traumatised by the news and his emotions start to become uncontrolled causing Horatio to say, â€Å"These are but wild and whirling words, my lord. † Slowly, the idea of revenge overcomes all his thoughts and Shakespeare feeds idea of deceit and betrayal into his mind. Hamlet decides that the only way he can see through the deceit and confirm the murder claim is by deception himself. He decides to â€Å"put on an antic disposition† to enable him to spy on his uncle without arousing any suspicion. Ophelia, although innocent, is a character who is in the way of Hamlet without meaning to do any harm. Her father is the Lord Chamberlain who is capable of extracting all scraps of information from her, against her will. He is very loyal to the king and will pass on anything he knows to him. As a consequence, Ophelia cannot be trusted with the truth and is subjected to deceit and betrayal. Hamlet deceives her by deliberately acting mad to confuse her and telling her that he â€Å"loved her not†. This is a downright lie as is obvious towards the end of the play when he is distraught to discover her death and tells an equally distressed Laertes that â€Å"forty thousand brothers with all their quantity of love could not love her more than [he] did†. Hamlet betrays her by being cruel and sarcastic to her and making comments such as, â€Å"Get thee to a nunnery† to keep her away from him. Hamlet is forced to take this path because he knows she must not find out what he knows regarding his father’s death; otherwise he risks endangering his life from Claudius. Shakespeare uses all the deceit and betrayal to create a conflict of loyalty inside Ophelia and she is unsure whether she should stay true to her love Hamlet or obey her father. She betrays Hamlet by choosing to obey her father rather that staying loyal to Hamlet. Despite her feeble attempts to try to defend Hamlet by saying, â€Å"He hath importuned me with love in honourable fashion,† she cannot disobey her father. She is torn between a strong father and a strong lover but being the dutiful daughter she promises her father, â€Å"I shall obey, my lord,† when ordered to stay away from Hamlet and not to â€Å"give words or talk† to him. She deceives Hamlet when she allows Claudius and her father to spy on him by trying to engage him in conversation in the presence of the two men. Her decision to obey her father means she is completely reliant on him. Being a lady of her time, she does not have any independence and needs the support of a man which makes her vulnerable and ultimately a failure. Hamlet’s rudeness towards her and her betrayal of Hamlet makes her believe that he will not care for her again. When her father dies she feels as if she has lost everything and this drives her towards insanity and eventually, death. As is obvious from the beginning of the play, Hamlet’s main failure is that he is very indecisive and thinks about issues too much which lead to his downfall and ultimately, death. He is also quite lonely and throughout the course of the play, only Horatio remains loyal to the prince and Hamlet can talk to and trust only him. All others, including his girlfriend, Ophelia, betray him and he cannot speak freely with them. The lack of people to talk to means that thoughts build up in his mind and he is constantly thinking about issues, such as revenge and suicide, too much without being able to reach an appropriate decision. His main failure and fatal flaw is this inability to make quick decisions and take action before it is too late. Typically, Shakespeare shows Claudius’ main flaw and failure to be his ambition which is what possesses him to perform the evil deed of murdering the king. He confesses, â€Å"I am still possess’d of those effects for which I did the murder, my crown, mine own ambition and my queen. † He tries to convince himself that he cannot turn around and make up for what he has done because he has waded too far into the pool of evil. He offers what is really an empty prayer because his â€Å"words fly up† but â€Å"thoughts remain below† and he says, â€Å"Words without thoughts never to heaven go. † His failure is that he is too ambitious and greedy and he cannot bear to think about life without his throne and queen. He does not make any attempt to make up for what he has done because he does not want to which creates problems because eventually the truth is discovered and this brings about his downfall and death. All the actions of the main characters are shaped by Shakespeare through the themes of deceit, betrayal and failure. He uses the deceit and betrayal of Claudius and Ophelia to cause Hamlet himself to deceive and betray which enables him to discover the truth. Shakespeare uses the deceit and betrayal to bring out the failures of the characters that lead to their downfall and death.

Compression Techniques used for Medical Image

Compression Techniques used for Medical Image 1.1 Introduction Image compression is an important research issue over the last years. A several techniques and methods have been presented to achieve common goals to alter the representation of information of the image sufficiently well with less data size and high compression rates. These techniques can be classified into two categories, lossless and lossy compression techniques. Lossless techniques are applied when data are critical and loss of information is not acceptable such as Huffman encoding, Run Length Encoding (RLE), Lempel-Ziv-Welch coding (LZW) and Area coding. Hence, many medical images should be compressed by lossless techniques. On the other hand, Lossy compression techniques such as Predictive Coding (PC), Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Vector Quantization (VQ) more efficient in terms of storage and transmission needs but there is no warranty that they can preserve the characteristics needed in medical image processing and diagnosis [1-2]. Data compression is the process that transform data files into smaller ones this process is effective for storage and transmission. It presents the information in a digital form as binary sequences which hold spatial and statistical redundancy. The relatively high cost of storage and transmission makes data compression worthy. Compression is considered necessary and essential key for creating image files with manageable and transmittable sizes [3]. The basic goal of image compression is to reduce the bit rate of an image to decrease the capacity of the channel or digital storage memory requirements; while maintaining the important information in the image [4]. The bit rate is measured in bits per pixel (bpp). Almost all methods of image compression are based on two fundamental principles: The first principle is to remove the redundancy or the duplication from the image. This approach is called redundancy reduction. The second principle is to remove parts or details of the image that will not be noticed by the user. This approach is called irrelevancy reduction. Image compression methods are based on either redundancy reduction or irrelevancy reduction separately while most compression methods exploit both. While in other methods they cannot be easily separated [2]. Several image compression techniques encode transformed image data instead of the original images [5]-[6]. In this thesis, an approach is developed to enhance the performance of Huffman compression coding a new hybrid lossless image compression technique that combines between lossless and lossy compression which named LPC-DWT-Huffman (LPCDH) technique is proposed to maximize compression so that threefold compression can be obtained. The image firstly passed through the LPC transformation. The waveform transformation is then applied to the LPC output. Finally, the wavelet coefficients are encoded by the Huffman coding. Compared with both Huffman, LPC- Huffman and DWT-Huffman (DH) techniques; our new model is as maximum compression ratio as that before. However, this is still needed for more work especially with the advancement of medical imaging systems offering high resolution and video recording. Medical images come in the front of diagnostic, treatment and fellow up of different diseases. Therefore, nowadays, many hospitals around the world are routinely using medical image processing a nd compression tools. 1.1.1 Motivations Most hospitals store medical image data in digital form using picture archiving and communication systems due to extensive digitization of data and increasing telemedicine use. However, the need for data storage capacity and transmission bandwidth continues to exceed the capability of available technologies. Medical image processing and compression have become an important tool for diagnosis and treatment of many diseases so we need a hybrid technique to compress medical image without any loss in image information which important for medical diagnosis. 1.1.2 Contributions Image compression plays a critical role in telemedicine. It is desired that either single images or sequences of images be transmitted over computer networks at large distances that they could be used in a multitude of purposes. The main contribution of the research is aim to compress medical image to be small size, reliable, improved and fast to facilitate medical diagnosis performed by many medical centers. 1.2 Thesis Organization The thesis is organized into six chapters, as following: Chapter 2 Describes the basic background on the image compression technique including lossless and lossy methods and describes the types of medical images Chapter 3 Provides a literature survey for medical image compression. Chapter 4 Describes LPC-DWT-Huffman (proposed methods) algorithm implementation. The objective is to achieve a reasonable compression ratio as well as better quality of reproduction of image with a low power consumption. Chapter 5 Provides simulation results of compression of several medical images and compare it with other methods using several metrics. Chapter 6 Provides some drawn conclusions about this work and some suggestions for the future work. Appendix A Provides Huffman example and comparison between the methods for the last years. Appendix B Provides the Matlab Codes Appendix C Provides various medical image compression using LPCDH. 1.3 Introduction Image compression is the process of obtaining a compact representation of an image while maintaining all the necessary information important for medical diagnosis. The target of the Image compression is to reduce the image size in bytes without effects on the quality of the image. The decrease in image size permits images to save memory space. The image compression methods are generally categorized into two central types: Lossless and Lossy methods. The major objective of each type is to rebuild the original image from the compressed one without affecting any of its numerical or physical values [7]. Lossless compression also called noiseless coding that the original image can perfectly recover each individual pixel value from the compressed (encoded) image but have low compression rate. Lossless compression methods are often based on redundancy reduction which uses statistical decomposition techniques to eliminate or remove the redundancy (duplication) in the original image. Lossless Image coding is also important in applications where no information loss is allowed during compression. Due to the cost, it is used only for a few applications with stringent requirements such as medical imaging [8-9]. In lossy compression techniques there are a slight loss of data but high compression ratio. The original and reconstructed images are not perfectly matched. However, practically near to each other, this difference is represented as a noise. Data loss may be unacceptable in many applications so that it must be lossless. In medical images compression that use lossless techniques do not give enough advantages in transmission and storage and the compression that use lossy techniques may lose critical data required for diagnosis [10]. This thesis presents a combination of lossy and lossless compression to get high compressed image without data loss. 1.4 Lossless Compression If the data have been lossless compressed, the original data can be exactly reconstructed from the compressed data. This is generally used for many applications that cannot allow any variations between the original and reconstructed data. The types of lossless compression can be analyzed in Figure 2.1. Figure 2.1: lossless compression Run Length Encoding Run length encoding, also called recurrence coding, is one of the simplest lossless data compression algorithms. It is based on the idea of encoding a consecutive occurrence of the same symbol. It is effective for data sets that are consist of long sequences of a single repeated character [50]. This is performed by replacing a series of repeated symbols with a count and the symbol. That is, RLE finds the number of repeated symbols in the input image and replaces them with two-byte code. The first byte for the number and the second one is for the symbol. For a simple illustrative example, the string AAAAAABBBBCCCCC is encoded as A6B4C5; that saves nine bytes (i.e. compression ratio =15/6=5/2). However in some cases there is no much consecutive repeation which reduces the compression ratio. An illustrative example, the original data 12000131415000000900, the RLE encodes it to 120313141506902 (i.e. compression ratio =20/15=4/3). Moreover if the data is random the RLE may fail to achieve any compression ratio [30]-[49]. Huffman encoding It is the most popular lossless compression technique for removing coding redundancy. The Huffman encoding starts with computing the probability of each symbol in the image. These symbols probabilities are sorted in a descending order creating leaf nodes of a tree. The Huffman code is designed by merging the lowest probable symbols producing a new probable, this process is continued until only two probabilities of two last symbols are left. The code tree is obtained and Huffman codes are formed from labelling the tree branch with 0 and 1 [9]. The Huffman codes for each symbol is obtained by reading the branch digits sequentially from the root node to the leaf. Huffman code procedure is based on the following three observations: 1) More frequently(higher probability) occurred symbols will have shorter code words than symbol that occur less frequently. 2) The two symbols that occur least frequently will have the same length code. 3) The Huffman codes are variable length code and prefix code. For more indication Huffman example is presented in details in Appendix (A-I). The entropy (H) describes the possible compression for the image in bit per pixel. It must be noted that, there arent any possible compression ratio smaller than entropy. The entropy of any image is calculated as the average information probability [12]. (2.1) Where Pk is the probability of symbols, k is the intensity value, and L is the number of intensity values used to present image. The average code length is given by the sum of product of probability of the symbol and number of bits used to encode it. More information can be founded in [13-14] and the Huffman code efficiency is calculated as (2.2) LZW coding LZW (Lempel- Ziv Welch) is given by J. Ziv and A. Lempel in 1977 [51].T. Welchs refinements to the algorithm were published in 1984 [52]. LZW compression replaces strings of characters with single codes. It does not do any analysis of the input text. But, it adds every new string of characters to a table of strings. Compression occurs when the output is a single code instead of a string of characters. LZW is a dictionary based coding which can be static or dynamic. In static coding, dictionary is fixed during the encoding and decoding processes. In dynamic coding, the dictionary is updated. LZW is widely used in computer industry and it is implemented as compress command on UNIX [30]. The output code of that the LZW algorithm can be any arbitrary length, but it must have more bits than a single character. The first 256 codes are by default assigned to the standard character set. The remaining codes are assigned to strings as the algorithm proceeds. There are three best-known applications of LZW: UNIX compress (file compression), GIF image compression, and V.42 bits (compression over Modems) [50]. Area coding Area coding is an enhanced form of RLE. This is more advance than the other lossless methods. The algorithms of area coding find rectangular regions with the same properties. These regions are coded into a specific form as an element with two points and a certain structure. This coding can be highly effective but it has the problem of a nonlinear method, which cannot be designed in hardware [9]. 1.5 Lossy Compression Lossy Compression techniques deliver greater compression percentages than lossless ones. But there are some loss of information, and the data cannot be reconstructed exactly. In some applications, exact reconstruction is not necessary. The lossy compression methods are given in Figure 2.2. In the following subsections, several Lossy compression techniques are reviewed: Figure 2.2: lossy compression Discrete Wavelet Transform (DWT) Wavelet analysis have been known as an efficient approach to representing data (signal or image). The Discrete Wavelet Transform (DWT) depends on filtering the image with high-pass filter and low-pass filter.in the first stage The image is filtered row by row (horizontal direction) with two filters and and down sampling (keep the even indexed column) every samples at the filter outputs. This produces two DWT coefficients each of size N ÃÆ'-N/2. In the second stage, the DWT coefficients of the filter are filtered column by column (vertical direction) with the same two filters and keep the even indexed row and subsampled to give two other sets of DWT coefficients of each size N/2ÃÆ'-N/2. The output is defined by approximation and detailed coefficients as shown in Figure 2.3. Figure 2.3: filter stage in 2D DWT [15]. LL coefficients: low-pass in the horizontal direction and lowpass in the vertical direction. HL coefficients: high-pass in the horizontal direction and lowpass in the vertical direction, thus follow horizontal edges more than vertical edges. LH coefficients: high-pass in the vertical direction and low-pass in the horizontal direction, thus follow vertical edges than horizontal edges. HH coefficients: high-pass in the horizontal direction and high-pass in the vertical direction, thus preserve diagonal edges. Figure 2.4 show the LL, HL, LH, and HH when one level wavelet is applied to brain image. It is noticed that The LL contains, furthermore all information about the image while the size is quarter of original image size if we disregard the HL, LH, and HH three detailed coefficients shows horizontal, vertical and diagonal details. The Compression ratio increases when the number of wavelet coefficients that are equal zeroes increase. This implies that one level wavelet can provide compression ratio of four [16]. Figure 2.4: Wavelet Decomposition applied on a brain image. The Discrete Wavelet Transform (DWT) of a sequence consists of two series expansions, one is to the approximation and the other to the details of the sequence. The formal definition of DWT of an N-point sequence x [n], 0 à ¢Ã¢â‚¬ °Ã‚ ¤ n à ¢Ã¢â‚¬ °Ã‚ ¤ N à ¢Ã‹â€ Ã¢â‚¬â„¢ 1 is given by [17]: (2.3) (2.4) (2.5) Where Q (n1 ,n2) is approximated signal, E(n1 ,n2) is an image, WQ (j,k1,k2) is the approximation DWT and W µ (j,k1,k2) is the detailed DWT where i represent the direction index (vertical V, horizontal H, diagonal D) [18]. To reconstruct back the original image from the LL (cA), HL (cD(h)), LH (cD(v)), and HH (cD(d)) coefficients, the inverse 2D DWT (IDWT) is applied as shown in Figure 2.5. Figure 2.5: one level inverse 2D-DWT [19]. The equation of IDWT that reconstruct the image E () is given by [18]: (2.6) DWT has different families such as Haar and Daupachies (db) the compression ratio can vary from wavelet type to another depending which one can represented the signal in fewer number coefficients. Predictive Coding (PC) The main component of the predictive coding method is the Predictor which exists in both encoder and decoder. The encoder computes the predicted value for a pixel, denote xˆ (n), based on the known pixel values of its neighboring pixels. The residual error, which is the difference value between the actual value of the current pixel x (n) and x ˆ (n) the predicted one. This is computed for all pixels. The residual errors are then encoded by any encoding scheme to generate a compressed data stream [21]. The residual errors must be small to achieve high compression ratio. e (n) = x (n) xˆ (n)(2.7) e (n) =x(n) (2.8) Where k is the pixel order and ÃŽÂ ± is a value between 0 and 1 [20]. The decoder also computes the predicted value of the current pixel xˆ  (n) based on the previously decoded color values of neighboring pixels using the same method as the encoder. The decoder decodes the residual error for the current pixel and performs the inverse operation to restore the value of the current pixel [21]. x (n) = e (n) + xˆ  (n)(2.9) Linear predictive coding (LPC) The techniques of linear prediction have been applied with great success in many problems of speech processing. The success in processing speech signals suggests that similar techniques might be useful in modelling and coding of 2-D image signals. Due to the extensive computation required for its implementation in two dimensions, only the simplest forms of linear prediction have received much attention in image coding [22]. The schemes of one dimensional predictors make predictions based only on the value of the previous pixel on the current line as shown in equation. Z = X D(2.10) Where Z denotes as output of predictor and X is the current pixel and D is the adjacent pixel. The two dimensional prediction scheme based on the values of previous pixels in a left-to-right, top-to-bottom scan of an image. In Figure 2.6 X denotes the current pixel and A, B, C and D are the adjacent pixels. If the current pixel is the top leftmost one, then there is no prediction since there are no adjacent pixels and no prior information for prediction [21]. Figure 2.6: Neighbor pixels for predicting Z = x (B + D)(2.11) Then, the residual error (E), which is the difference between the actual value of the current pixel (X) and the predicted one (Z) is given by the following equation. E = X Z(2.12) Discrete Cosine Transform (DCT) The Discrete Cosine Transform (DCT) was first proposed by N. Ahmed [57]. It has been more and more important in recent years [55]. The DCT is similar to the discrete Fourier transform that transforms a signal or image from the spatial domain to the frequency domain as shown in Figure 2.7. Figure 2.7: Image transformation from the spatial domain to the frequency domain [55]. DCT represents a finite series of data points as a sum of harmonics cosine functions. DCTs representation have been used for numerous data processing applications, such as lossy coding of audio signal and images. It has been found that small number of DCT coefficients are capable of representing large sequence of raw data. This transform has been widely used in signal processing of image data, especially in coding for compression for its near-optimal performance. The discrete cosine transform helps to separate the image into spectral sub-bands of differing importance with respect to the images visual quality [55]. The use of cosine is much more efficient than sine functions in image compression since this cosine function is capable of representing edges and boundary. As described below, fewer coefficients are needed to approximate and represent a typical signal. The Two-dimensional DCT is useful in the analysis of two-dimensional (2D) signals such as images. We say that the 2D DCT is separable in the two dimensions. It is computed in a simple way: The 1D DCT is applied to each row of an image, s, and then to each column of the result. Thus, the transform of the image s(x, y) is given by [55], (2.13) where. (n x m) is the size of the block that the DCT is applied on. Equation (2.3) calculates one entry (u, v) of the transformed image from the pixel values of the original image matrix [55]. Where u and v are the sample in the frequency domain. DCT is widely used especially for image compression for encoding and decoding, at encoding process image divided into N x N blocks after that DCT performed to each block. In practice JPEG compression uses DCT with a block of 88. Quantization applied to DCT coefficient to compress the blocks so selecting any quantization method effect on compression value. Compressed blocks are saved in a storage memory with significantly space reduction. In decoding process, compressed blocks are loaded which de-quantized with reverse the quantization process. Inverse DCT was applied on each block and merging blocks into an image which is similar to original one [56]. Vector Quantization Vector Quantization (VQ) is a lossy compression method. It uses a codebook containing pixel patterns with corresponding indexes on each of them. The main idea of VQ is to represent arrays of pixels by an index in the codebook. In this way, compression is achieved because the size of the index is usually a small fraction of that of the block of pixels. The image is subdivided into blocks, typically of a fixed size of nÃÆ'-n pixels. For each block, the nearest codebook entry under the distance metric is found and the ordinal number of the entry is transmitted. On reconstruction, the same codebook is used and a simple look-up operation is performed to produce the reconstructed image [53]. The main advantages of VQ are the simplicity of its idea and the possible efficient implementation of the decoder. Moreover, VQ is theoretically an efficient method for image compression, and superior performance will be gained for large vectors. However, in order to use large vectors, VQ becomes complex and requires many computational resources (e.g. memory, computations per pixel) in order to efficiently construct and search a codebook. More research on reducing this complexity has to be done in order to make VQ a practical image compression method with superior quality [50]. Learning Vector Quantization is a supervised learning algorithm which can be used to modify the codebook if a set of labeled training data is available [13]. For an input vector x, let the nearest code-word index be i and let j be the class label for the input vector. The learning-rate parameter is initialized to 0.1 and then decreases monotonically with each iteration. After a suitable number of iterations, the codebook typically converges and the training is terminated. The main drawback of the conventional VQ coding is the computational load needed during the encoding stage as an exhaustive search is required through the entire codebook for each input vector. An alternative approach is to cascade a number of encoders in a hierarchical manner that trades off accuracy and speed of encoding [14], [54]. 1.6 Medical Image Types Medical imaging techniques allow doctors and researchers to view activities or problems within the human body, without invasive neurosurgery. There are a number of accepted and safe imaging techniques such as X-rays, Magnetic resonance imaging (MRI), Computed tomography (CT), Positron Emission Tomography (PET) and Electroencephalography (EEG) [23-24]. 1.7 Conclusion In this chapter many compression techniques used for medical image have discussed. There are several types of medical images such as X-rays, Magnetic resonance imaging (MRI), Computed tomography (CT), Positron Emission Tomography (PET) and Electroencephalography (EEG). Image compression has two categories lossy and lossless compression. Lossless compression such as Run Length Encoding, Huffman Encoding Lempel-Ziv-Welch, and Area Coding. Lossy compression such as Predictive Coding (PC), Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), and Vector Quantization (VQ).Several compression techniques already present a better techniques which are faster, more accurate, more memory efficient and simpler to use. These methods will be discussed in the next chapter.

Intelligent Extraterrestrial Life Essay -- Science

Intelligent Extraterrestrial Life When I look up at the stars at night, I just have to wonder who or what is looking back at me from some distant planet in some distant galaxy. We’ve all probably wondered what lies beyond our small, self-contained little world. The question many have pondered is whether or not there is intelligent life beyond earth. In the words of Metrodorus, a Greek philosopher of the fourth century, "To consider the Earth as the only populated world in infinite space is as absurd as to assert that in an entire field of millet, only one grain will grow." I believe that intelligent extraterrestrial life does exist. Critics of the theory of intelligent life beyond earth will argue that there is no such thing because they’ve never seen a "little green man." There are those who want proof of extraterrestrial life before they can accept the fact that there is any life besides what is on our Earth. They have a point. I’ve never seen an alien. I’ve never talked to anyone whose had a "close encounter." Sure, we’ve all seen the shows on TV with convincing footage of flying saucers, but we have no actual proof of intelligent life dependent from earth. It is true that we have no evidence of intelligent life beyond earth, but to claim that none exists because we’ve never seen aliens is like saying that the atom doesn’t exist because you can’t see one. We who have a grasp of our physical surroundings, and a basic knowledge of chemistry realize that the atom is the basic building block of matter. Those who say that there is no intelligent life other than our own need to realize several things. First, our universe is infinite. This leaves literally infinit... ...ence, why is our government so concerned about it? Although we can’t prove the existence of intelligent life beyond earth, it is very likely that it does exist. When one considers the vast infinite universe we live in, it would be completely foolish to believe that life on earth is unique. It is not just me who says that other intelligent life exists, though. Many scientists and philosophers have speculated about life on other planets for centuries, and today the search for life is a major driving factor in space exploration. Extraterrestrial life is not just an idea reserved for those who watch The X-files every night with all the lights out, it is an important concept in our current space-age, and to ignore the fact that extraterrestrial life would be like those of our ancestors who refused to believe that the world was round.

Pushed, Chosen, And Choosing :: essays research papers

Their Eyes Were Watching God, by Zora Neale Hurston, was a novel about one woman’s self-revelation. It began when she was a very young girl, first being pushed, then chosen, and finally choosing. Born a victim of circumstance, Janie was subject to her position in life. She was raised to uphold the standards of the early African American generation. From the beginning, she was taught to be passive and subject to whatever life gave her. As she grew older she began to realize she must give in to her desires and not suppress them. Janie, the main character of the story, was set up for her journey of self-discovery by her grandmother. Nanny set a goal for Janie’s life by saying, â€Å"Ah wanted you to look upon yo’ self. Ah don’t want yo’ feathers always crumpled by folks throwin’ up things in yo’ face.† Janie’s grandmother pushed Janie into a marriage, which she considered a ‘safe’ place for Janie. Though hesitant, Janie agreed to marry Logan Killicks. He was a farmer who married Janie shortly after she completed school. Killicks was the first antagonist that Janie encountered in the story. He was there for one purpose, to destroy Janie’s new sense of self-awarenes. Logan demanded things of Janie that she did not wish to do and tried to push her into his mold of a perfect wife. Janie did not love Logan nor did he love her. She didn’t know what she wanted, but she knew that she didn’t want Logan Killicks. Joe Starks appeared in Janie’s yard one afternoon. He said the sweet things that Janie wanted to hear. Though Janie hardly knew the man, she was chosen by his words—being young and gullible. She took another step in her journey, leaving Logan the next day and traveling to Eatonville with Joe Starks. Aspiring to be the mayor of Eatonville, Joe Starks was a man concerned with little except power. He wanted it, and he was going to use Janie to get it. She wore nice dresses during this marriage because Joe wanted her to stand out from the rest of the town; he used her as an icon of his prosperity and power. He was cruel to Janie and stomped out all of her free will. He built his town of Eatonville, became the mayor crushing all in his path, and made many enemies along the way, including Janie. During the period that she was married to Joe Starks, Janie was not allowed to talk and act as herself, but she began to think for herself—never revealing to Joe how she felt until just before he died. Pushed, Chosen, And Choosing :: essays research papers Their Eyes Were Watching God, by Zora Neale Hurston, was a novel about one woman’s self-revelation. It began when she was a very young girl, first being pushed, then chosen, and finally choosing. Born a victim of circumstance, Janie was subject to her position in life. She was raised to uphold the standards of the early African American generation. From the beginning, she was taught to be passive and subject to whatever life gave her. As she grew older she began to realize she must give in to her desires and not suppress them. Janie, the main character of the story, was set up for her journey of self-discovery by her grandmother. Nanny set a goal for Janie’s life by saying, â€Å"Ah wanted you to look upon yo’ self. Ah don’t want yo’ feathers always crumpled by folks throwin’ up things in yo’ face.† Janie’s grandmother pushed Janie into a marriage, which she considered a ‘safe’ place for Janie. Though hesitant, Janie agreed to marry Logan Killicks. He was a farmer who married Janie shortly after she completed school. Killicks was the first antagonist that Janie encountered in the story. He was there for one purpose, to destroy Janie’s new sense of self-awarenes. Logan demanded things of Janie that she did not wish to do and tried to push her into his mold of a perfect wife. Janie did not love Logan nor did he love her. She didn’t know what she wanted, but she knew that she didn’t want Logan Killicks. Joe Starks appeared in Janie’s yard one afternoon. He said the sweet things that Janie wanted to hear. Though Janie hardly knew the man, she was chosen by his words—being young and gullible. She took another step in her journey, leaving Logan the next day and traveling to Eatonville with Joe Starks. Aspiring to be the mayor of Eatonville, Joe Starks was a man concerned with little except power. He wanted it, and he was going to use Janie to get it. She wore nice dresses during this marriage because Joe wanted her to stand out from the rest of the town; he used her as an icon of his prosperity and power. He was cruel to Janie and stomped out all of her free will. He built his town of Eatonville, became the mayor crushing all in his path, and made many enemies along the way, including Janie. During the period that she was married to Joe Starks, Janie was not allowed to talk and act as herself, but she began to think for herself—never revealing to Joe how she felt until just before he died.

Essay --

Theodore Roosevelt National Park INTRODUCTION Do you want to hear about the first national park that is the first and only dedicated to a president? Theodore Roosevelt National Park was established in 1947. The Mountains are over 55 million years old. The badlands of Theodore Roosevelt national park is dry with occasional monsoon showers. The park is located in Medora, North Dakota, and is home to some amazing animals including wild horses, reptiles and mammals. GEOLOGY The Little Missouri River eroding the mountain range is the reason that the park is as it looks today. The park is believed to be

Alfie Kohn

In the modern age of No Child Left Behind and similar mandates, there has been an increased focus placed on what schools must do in order to improve the educational outcomes of each and every student. It has finally become apparent that the traditional method of schooling is not as effective as once believed.Evidence of this fact can be found within the test scores of individual schools as well as entire school districts. Alfie Kohn is a leader in school reform and he focuses on non traditional ways to educate students so they are excited and eager to learn.Despite the idea held my many Americans that current methods do not work, the vast majority of schools continue to rely on â€Å"back to basics† strategies for instruction (Kohn, 1999, 2). While â€Å"back to basics† may have worked for previous generations it is not working for the current generation.Kohn emphasizes the need to shift focus away from traditional methods of school in favor of non traditional methods i n order to motivate students to want to learn. A biography of Kohn is offered as well as a discussion based on his personal contributions to the field of education and classroom management.BiographyAlfie Kohn is one of the most vocal critics of the intense focus placed on standardized tests and test scores (Kohn, 1998, 1). His theories and ideas have motivated many educators and administrators to reexamine the way that students learn and the way that teachers teach.Kohn began his career as a high school teacher and enjoyed making improvements to his curriculum and lesson plans in order to provide the best educational experiences for his students.After Kohn left the classroom he realized that using the same curriculum in the same way for each group of students is not the most effective way to motivate students to learn. Instead, he realized that adapting the course material to each group of students was a more effective way to provide authentic learning experiences that left students wanting to know more (Kohn, 1998, 1).Kohn also spent a great deal of time observing other teachers and engaging in dialogue with education experts in order to present a cohesive view of the education system in America. Kohn is most well known for his stand against teaching to the test and relying on test scores as adequate measures of educational progress.Kohn also is known for his idea that the ultimate outcome of education is not that each child receive all A’s because this is not the point of school. Finally, Kohn is known for his idea that current assessment measures are not adequate and do not give a clear representation of what really happens in classrooms (Kohn, 1998, 1).Contributions to EducationThe most important contribution that Alfie Kohn has made in the field of education is the shift in focus that has occurred from assessment measures such as standardized tests to a more comprehensive view of education that is primarily concerned with students’ ability t o learn and keep on learning (Kohn, 2004, 27).Kohn emphasizes that the intense focus placed on grading and assessment has taken away the potential for authentic learning experiences that truly benefit students rather than simply teach them how to take a test.Further, teachers spend so much time worrying about what amount or level of work constitutes what grade when their focus should be on enabling students to make significant progress in their understanding of certain subjects regardless of what grade they end up with (Kohn, 2004, 28).This contribution is essential within the education field because it has allowed teachers to question the traditional methods of instruction and begin to consider non traditional methods that may motivate students to learn more than what is possible through traditional education.It has also motivated many educators to begin to work with experts and policy makers in the field in order to discover alternate ways to assess student progress that does not rely solely on the outcome of standardized testing (Kohn, 2004, 28).A similar idea that has stemmed from the idea that alternate testing measures must be discovered is the idea that grades cause students to do as little as possible and still get a good grade. In this way, grades actually disable the desire to learn more because students quickly find out how little they can get away with and still receive an acceptable grade (Kohn, 2004, 28).At the same time, the motivation to learn more decreases as student desire to receive a good grade increases. Students who receive grades based on performance are reluctant to try challenging things because of their fear of failing and/or receiving a poor grade.On the other hand, students who are encouraged to think for themselves and explore topics that interest them without the fear of being graded are more likely to recall the information that they learn as well as continue to seek opportunities to learn new things (Kohn, 2004, 28).While this certainly does not mean that schools are going to stop handing down grades to students this idea has allowed many educators to reexamine the way they assess their students in order to provide ample opportunity for students to learn without the fear of failure.Another important realization that has come from Kohn’s view of traditional assessment models is that there must be an educational goal behind assessing students.In other words, assessment must be used to enhance the educational opportunities for students. Instead, assessment is most often used to categorize students and determine who is smarter than whom or as a technique to motivate students to work harder in order to get the â€Å"A† (Kohn, 2004, 28).Therein lies the problem with standardized tests. Kohn emphasizes that standardized tests do not truly show how much teaching or learning has taken place. Instead, they simply show how well a child can do on a test on any given day and/or how well a student is able to guess on questions they do not know (Kohn, 2004, 28).Kohn has opened the eyes of educators and allowed many of them to see the error of their ways in relying solely on the outcome of standardized tests in measuring student progress. Kohn has also forced many experts and policy makers within the field of education to realize that perhaps there is a better way to determine how well America’s students are doing in school.Contributions to Classroom ManagementKohn has questioned the use of traditional discipline strategies that focus on getting students to do what the teacher wants them to do. Traditionally, the teacher creates a set of classroom rules and expects students to obey them.These rules often include detailed consequences that accompany them in order to show students what will happen to them if they break one of the rules (Kohn, 2006, 1). Similar to his work with standardized tests and assessment measures, Kohn’s work with classroom management has forced many teachers to reexamine how they approach classroom management.Obviously, it is necessary that students be taught to how to behave appropriately in the classroom in order to create an environment conducive to learning. However, Kohn feels that classroom management is significantly more effective if students take part in creating caring environments rather than being expected to follow the rules decided upon by the teacher (Kohn, 2006, 1).In other words, Kohn has shown teachers that not all discipline problems are because students are naughty but rather because a caring community has not been created that encourages students to work together to learn and grow.

Audiences and Spectatorship

Are audiences' vulnerable pawns ensnared under the manipulative and calculating control of the media or, do audiences' actively engage in the media by constructing their own interpretations and meanings of the world? This is an extremely controversial issue that is extensively debated all around the world. Some view audiences as being easily influenced masses of people who can be persuaded to purchase products and conform to societies ideals or even follow corrupt leaders through advertising. There have also been fears that the media may alter the way people behave for example, being more violent and aggressive. On the other side of the coin, there are theorists who believe that the media has a great deal less influence over audiences then is hypothesized. This is the central argument that this essay will be debating, to conclude whether audiences are passive individuals who are targeted victims of the media, or whether they are active and are thus not fictitious cohorts who believe everything they are told or watch in the media. To avoid misrepresentation the definition and differentiation of audiences is crucial. An Audience is†¦Ã¢â‚¬ ¦ dictionary definition. There are two types of audiences that are marketed in the media-mass and niche. The mass audience includes people of different social cultures, different degrees of class and wealth and people with varying grades of education. The mass is composed of individuals who are oblivious to each other and who, in an ocean of people, don't individually stand out. Due to this oblivion, members of the mass audience rarely interact and this lack of interaction means little exchange of experiences. A niche is that part of the audience, being relatively small in size, that marketers produce and can thus be easily targeted, producing only a small but secure profit. Audiences are not blank sheets of paper on which media messages can be written; members of an audience will have prior attitudes and beliefs which will determine how effective media messages are. † (Abercrombie, 1996:140) Mass media assumes that its audiences are credulous, susceptible and incompetent. This is however challenged by the idea of an ‘active audience' in which individuals are not mere sheep that follow the flock but individuals who possess agency over their lives and the messages they receive. As Philip Hanes (2000) states, meanings are encoded by the producer into the media text and the audiences decodes the meaning from the text. â€Å"†¦ this intended message is not simply dumped into the minds of passive audiences†¦ â€Å"(Croteau and Hoynes, 2000:263), the producer inscribes a specific meaning in the text that he/she hopes to be decoded, but encodes it by the conventions of the particular medium so as to hide the texts own ideological construction. This concealed message is then decoded by the audience according to external influences such as class, ethnicity, gender, age etc. Thus a text could mean completely different things to different audiences meaning that no text has only one meaning and is thus polysemic. ‘Reception Analysis' suggests the audience themselves help to create the meaning of the text by individually decoding the intended message in different ways according to the mood one may be in or as a result of ones own beliefs and morals. So we can conclude that audiences create their own meanings from the text and are thus not mere passive adherents. However, Its is also shown that media texts contain an excess of meanings within them and thus, â€Å"media contains the raw materials for multiple interpretations; the texts are structured in ways that facilitate peoples reading against the grain†¦ the most successful texts will have components that appeal to different audiences† (Croteau and Hoynes, 2000:266-267) As with all debates it is imperative to discuss and analyze certain theories pertaining to that debate. Firstly, it is important to note that the media only has a limited influence and effect on audiences. As Klapper(1960) demonstrates, â€Å"persuasive mass communication is in general more likely to reinforce the existing opinions of its audience than it is to change its opinion. † The idea of ‘Selectivity† deals with the idea of the resistant audience-it is up to the audience to resist the manipulative powers of the media and be not only cognizant of its manipulative capacity but bend these manipulations in favour of themselves. The Gratifications theory is in support of the premise that audiences are active. This theory testifies that we do not engage in media texts as â€Å"some kind of mindless entertainment. â€Å"(Baker) but make choices over what we consume and thus presume to get something out of it, some form of satisfaction. The types of gratification that we incur comprise of: satisfying our curiosity regarding the world-information; finding ones personal identity by looking to others i. e. celebrities for assistance and corroboration; to find out more about others circumstances and for social interaction(Media allows for communication amongst friends. ); and lastly for pure entertainment. Agenda setting' deals with the notion that although there is an abundance of media messages being thrown at the audience, the audience intercepts this bombardment with their prior beliefs and attitudes. Thus media effects are limited because the audience practices a degree of autonomy. The Marketplace Model positions the audience in the rank of the consumer. This model states that audiences are not inert victims of the media but enthusiastically elect to choose commodities that satisfy their desires and preferences. This model suggests that audiences are realistic and clued-up and know exactly what it is they want. Their preferences allow them to pick and choose the viewing they wish to indulge in and if â€Å"the audience demands diverse content, then the marketplace will provide it. â€Å"(Webster and Phalen, 1994:29) This model insinuates that in view of the fact that audiences actively engage in their choice of viewing they, to a certain degree, have power over the media. One must, however, not be too hasty in succumbing to the notion of the active audience because there is a proliferation of theories regarding audiences as being passive entities. The debate concerning audiences being passive victims of the media and media being capable of radically effecting people's behavior and beliefs, dates far back into history. An extremely appropriate illustration of this is when Hitler and Stalin attempted to use the media as propaganda by persuading the mass audiences to follow their policies and beliefs. Thus we can see how what an extremely precarious weapon media can be in the wrong hands, capable even of convincing millions to follow iniquitous beliefs. We see this persuasion still today in elections which is the same sort of propaganda. The Effects model of media audiences assumes that being exposed to adverse content can result in harm, that the audience is equally harmed by the media withholding high-quality content and the fact that although beneficial content is made accessible, it is being underused by the audience. â€Å"The Commodity Model is less wedded to any notion of audiences as individual decision makers and is more a reflection of the fact that, under advertiser support, they are a common coin of exchange. (Webster, 1994:30) Audiences are thus seen as commodities; the media will construct a text, in such a way that it will produce an audience. An example of this is the show Friends and how it is theorized that this show is actually a method of selling beauty products. Friends features stunning people, in amusing situations who are all blissful. Thus young audiences wanting to follow the latest trends of the main characters and experience their happiness would buy the beauty products sponsoring the show. In the argument pro passivity, â€Å"The Frankfurt School, who were concerned about the possible effects of mass media†¦ considered society to be composed of isolated individuals who were susceptible to media messages. â€Å"(Hanes, 2000) Thus the theory of the Hypodermic Syringe was proposed. This theory states that the media takes on the life of a syringe by injecting principles, and beliefs into the audience, who as passive mass viewers have no option but to be influenced and accept or imitate these messages. An example of this is if you see a woman sweeping the floor, being a woman you would go and do the same or being a man, you would expect the woman to go and sweep the floor. † Certain films such as the Exorcist were banned for this very reason; it was felt that it might encourage people to imitate the acts of violence in the film, in other words, if you watch something violent you will accordingly perform a violent act yourself. Yet another theory supporting the passivity debate is the Cultivation theory. This theory surmises that although an individual media text might not impact or affect an individual, years and years of being exposed to violence may consequently make you less sensitive and responsive to violence. If an audience, for instance, is constantly exposed to domestic violence, it may not bother them too much because they have been desensitized and domestic violence may have become just another societal norm which is exceptionally problematic. Yet another theory hypothesizes that we are likely to communicate our media encounters with others, and if we value their judgment, the likelihood is that we will be influenced by it and thus come to a deduction concerning our experience established on the foundation of the ‘opinion leaders'. These theories give us a great deal of insight into the reality of the audience as a passive victim. It is imperative that mention is given of how violence in the media can influence audiences as this is an integral part favouring the audience as victims' debate. It seems evident that by observing violent or aggressive acts on television and film, audiences are learn behaviors which are appropriate, in other words, which behaviors will be punished and which are rewarded. Audiences imitate those behaviors which are positively rewarded. For instance, if the protagonist is in a fight scene with the ‘enemy,' although the enemy may get punished by being defeated by the protagonist and thus the protagonist be rewarded for defeating evil, the protagonist himself was still involved in the violence and aggression. What is problematic is the fact that the protagonist is seen as the hero and is in turn imitated by audiences as it is seen as a good thing. So we can assume that violence in television and film is encoded and continuous viewing of this violence can help to maintain aggressive thoughts and violent ideas. It is also evident how the media may allow for the release of tension and desires through identification with fictional characters. Violent acts in the media may also erode inbuilt inhibitions against acting violently. Through the attraction of television and films, audiences acquire an imprecise comprehension of society, realism and moral values. Although the many theories surrounding the debate of whether audiences are passive or active are extremely influential, they have also been criticized. Firstly, the Gratifications theory can be criticized as it disregards the actuality that we do not always have absolute selection as to what we receive from the media. We typically have to choose the media that we consume from what is available. This emasculates the Gratification theory since we may not all have the equal prospects to utilize and benefit from the media merchandise we want. The Hypodermic Model can also be criticized on account of it being too simplistic and disregarding audiences' individuality. There is a definite association between the mass media and social change but many of the consequences attributed to the mass media can also be attributed to many other influences within society, thus the extensive debate. In weighing up the evidence of whether mass media is influential or not, it is clearly identifiable that the media does play a major role in the construction of representations in society. Therefore we see how the media is used as a powerful instrument in influencing audiences into certain modes and beliefs within society. So we can deduce from the arguments presented in this essay that while audiences are passive victims of an all-encompassing world of messages, they too are active in that they can rebel against the medias domination by ardently participating in it or by resisting it.