Sunday, July 21, 2019
Curvelet-based Bayesian Estimator for Speckle Suppression
Curvelet-based Bayesian Estimator for Speckle Suppression Curvelet-based Bayesian Estimator for Speckle Suppression in Ultrasound Imaging Abstract. Ultrasound images are inherently affected by speckle noise, and thus the reduction of this noise is a crucial pre-processing step for their successful interpretation. Bayesian estimation is a powerful signal estimation technique used for speckle noise removal in images. In the Bayesian-based despeckling schemes, the choice of suitable statistical models and the development of a shrinkage function for estimation of the noise-free signal are the major concerns. In this paper, a novel curvelet-based Bayesian estimation scheme for despeckling of ultrasound images is developed. The curvelet coefficients of the multiplicative degradation model of the noisy ultrasound image are additively decomposed into noise-free and signal-dependent noise components. The Cauchy and two-sided exponential distributions are assumed to be statistical models for the noise-free and signal-dependent noise components of the observed curvelet coefficients, respectively, and an efficient low-complexit y realization of the Bayesian estimator is proposed. The experimental results demonstrate the validity of the proposed despeckling scheme in providing a signifi cant suppression of the speckle noise and simultaneously preserving the image details. Keywords:Ultrasound imaging, curvelet transform, speckle noise, Bayesian estimation, statistical modeling. Introduction Ultrasound imaging is important for medical diagnosis and has the advantages of cost effectiveness, port-ability, acceptability and safety [1]. However, ultrasound images are of relatively poor quality due to its contamination by the speckle noise, which considerably degrades the image quality and leads to a negative impact on the diagnostic task. Thus, reducing speckle noise while preserving anatomic information is necessary to better delineate the regions of interest in the ultrasound images. In the work of speckle suppression in ultrasound images, many spatial-based techniques that employ either single-scale or multi-scale filtering have been developed in the literature [2-4]. Earlydeveloped single-scale spatial filtering [2] are limited in their capability for significantly reducing the speckle noise. More promising spatial single-scale techniques such as those using bilateral filtering [4] and nonlocal filtering [3] have been recently proposed. This work was supported in part by the Natural Sciences and Engineering Research Council (NSERC) of Canada and in part by the Regroupement Strategique en Microelectronique du Quebec (ReSMiQ). These techniques depend on the size of the fi lter window, and hence, for a satisfactory speckle suppression, they require large computational time. Alternatively, multi-scale spatial techniques [5], based on partial differential equations, have been investigated in the literature. These techniques are iterative and can produce smooth images with preserved edges. However, important structural details are unfortunately degraded during the iteration process. As an appropriate alternative to spatial-based speckle suppression in ultrasound images, many other despeckling techniques based on different transform domains, such as the ones of wavelet, contourlet, and curvelet, have been recently proposed in the literature [6-8]. Wavelet transform has a good reputation as a tool for noise reduction but has the drawback of poor directionality, which makes its usage limited in many applications. Using contourlet transform provides an improved noise reduction performance due to its property of fi‚exible directional decomposability. However, curvelet transform offers a higher directional sensitivity than that of contourlet transform and is more efficient in representing the curve-like details in images. For the development of despeckling techniques based on transform domains, thresholding [7] has been presented as a technique to build linear estimators of the noise-free signal coefficients. However, the main drawback of this thresholding technique is in the difficulty of determining a suitable threshold value. To circumvent this problem, non-linear estimators [6] have been statistically developed based on Bayesian estimation formalism. For the development of an efficient Bayesian-based despeckling scheme, the choice of a suitable probability distribution to model the transform domain coefficients is a major concern. Also, while investigating a suitable statistical model, the complexity of the Bayesian estimation process should be taken into consideration. Consequently, special attention should be paid to the realization complexity of the Bayesian estimator that results from employing the selected probabilistic model in one of the Bayesian frameworks. In this paper, to achieve a satisfactory performance for despeckling of ultrasound images at a lower computational effort, a new curvelet-based Bayesian scheme is proposed. The multiplicative degradation model representing an observed ultrasound image is decomposed into an additive model consisting of noise-free and signal-dependent noise components. Two-sided exponential distribution is used as a prior statistical model for the curvelet coefficients of the signal-dependant noise. This model, along with the Cauchy distribution is used to develop a low-complexity Bayesian estimator. The performance of the proposed Bayesian despeckling scheme is evaluated on both syntheticallyspeckled and real ultrasound images, and the results are compared to that of some other existing despeckling schemes. Modeling of Curvelet Coefficients The multiplicative degradation model of a speckle-corrupted ultrasound image g(i,j) in the spatial domain is given by g(i,j) = v(i,j)s(i,j)(1) where v(i,j) and s(i,j) denote the noise-free image and the speckle noise, respectively. This model of the noisy observation of v(i,j) can be additively decomposed as a noise-free signal component and a signal-dependant noise: g(i,j) = v(i,j) + (s(i,j) à ¢Ã‹â€ ’1)v(i,j) = v(i,j) + u(i,j)(2) where (s(i,j) à ¢Ã‹â€ ’1)v(i,j) represents the signal-dependant noise. Taking the curvelet transform of (2) at level l, we have y[l,d](i,j) = x[l,d](i,j) + n[l,d](i,j)(3) where y[l,d](i,j), x[l,d](i,j) and n[l,d](i,j) denote, respectively, the (i,j)th curvelet coefficient of the observed image, the corresponding noise free image and the corresponding additive signal-dependant noise at direction d= 1,2,3, ·Ãƒâ€šÃ‚ ·Ãƒâ€šÃ‚ ·,D. In order to simplify the notation, we will henceforth drop both the superscripts land dand the index (i,j). In this work, in order to reduce the noise inherited in ultrasound images, we propose exploiting the statistical characteristics of the curvelet coefficients in (3) to derive an efficient Bayesian estimator. Thus, one needs to provide a prior probabilistic model for the curvelet coefficients of xand n. It has been shown that the distribution of the curvelet coefficients of noise-free images can be suitably modeled by the Cauchy distribution [9]. The zero-mean Cauchy distribution is given by px(x) = (ÃŽÂ ³/à ₠¬)(x2 + ÃŽÂ ³2)(4) where ÃŽÂ ³is the dispersion parameter. The noisy observation is used to estimate the Cauchy distribution parameter ÃŽÂ ³by minimizing the function 2 Â à †Ë†yyt (t) à ¢Ã‹â€ ’à †(t) eà ¢Ã‹â€ ’ dt(5) where à †Ë†y(t) is the empirical characteristic function corresponding to the curvelet coefficients yof 22 the noisy observation, à †y(t) = à †x(t)à †E(t), à †x(t) = eà ¢Ã‹â€ ’Π³|t|, and à †E(t) = eà ¢Ã‹â€ ’(à ƒà ¯Ã‚ ¿Ã‚ ½/2)|t| deviation à ƒEobtained as with the standard à ƒE= MAD(y(i,j)) 0.6745 (6) In (6), MAD denotes the median absolute deviation operation. Now, in order to formulate the Bayesian estimator, a prior statistical assumption for the curvelet coefficients of nof the signal dependant noise should also be assumed. From experimental observation, it is noticed that the tail part of the empirical distribution of ndecays at a low rate. Hence, in this paper, we propose to use a two-sided exponential (TSE) distribution given by 1 pn(n) =eà ¢Ã‹â€ ’|n|/ÃŽÂ ² 2ÃŽÂ ² (7) where ÃŽÂ ²is a positive real constant referred to as the scale parameter. The method of log-cummulants (MoLC) is adopted to estimate the parameter ÃŽÂ ², and thus the estimated ÃŽÂ ²Ãƒâ€¹Ã…“ is obtained by using the following expression: ÃŽÂ ²Ãƒâ€¹Ã…“ = exp 1N1        N2 log(y(i,j))+ ÃŽÂ ¾ (8) N1N2 i=1j=1 where ÃŽÂ ¾is the Euler-Mascheroni constant and N1 and N2 defi ne the size N1 ÃÆ'-N2 of the curvelet subband considered. Bayesian Estimator Due to the fact that each of the Cauchy and TSE distributions has only one parameter, one could expect the process of Bayesian estimation to be of lower complexity. The values of the Bayes estimates xˆof the noise-free curvelet coefficients xof a subband under the quadratic loss function, which minimizes the mean square error (MSE), are given by the shrinkage function: xˆ(y) =px|y(x|y)xdx P pn(yà ¢Ã‹â€ ’x)px(x)xdx =P p(yà ¢Ã‹â€ ’x)p(x) (9) It is noted that a closed-form expression for xˆ(y) given by the above equation does not exist. Thus, in order to obtain the Bayesian estimates for the noise-free curvelet coefficients, the two integrations associated with (9) are numerically performed for each curvelet coefficient. Since this procedure requires an excessive computational effort, the bayseian estimates are obtained by replacing the associated integrals in (9) with infi nite series as suggested in [10]. Accordingly, the Bayesian shrinkage function can be expressed as eà ¢Ã‹â€ ’y/ÃŽÂ ²[f (y)ÃŽÂ ¶] + ey/ÃŽÂ ²[ f(y) + ÃŽÂ ¶] xˆ(y) =(10) eà ¢Ã‹â€ ’y/ÃŽÂ ²[f21(y) + ÃŽÂ ¶2] + ey/ÃŽÂ ²[à ¢Ã‹â€ ’f22(y) + ÃŽÂ ¶2] where f11(y) = f12 (à ¢Ã‹â€ ’y) = sin(ÃŽÂ ³/ÃŽÂ ²) Im E( à ¢Ã‹â€ ’y+ jÃŽÂ ³)à ¢Ã‹â€ ’Si(ÃŽÂ ³/ÃŽÂ ²) + à ₠¬ 1ÃŽÂ ²2 à ¢Ã‹â€ ’y+jÃŽÂ ³ à ¢Ã‹â€ ’cos(ÃŽÂ ³/ÃŽÂ ²)  Re E1(ÃŽÂ ² + Ci(ÃŽÂ ³/ÃŽÂ ²) ,(11) f(y) = à ¢Ã‹â€ ’f 1à ¢Ã‹â€ ’y+ jÃŽÂ ³ (à ¢Ã‹â€ ’y) = à ¢Ã‹â€ ’ sin(ÃŽÂ ³/ÃŽÂ ²) Re E()+ Ci(ÃŽÂ ³/ÃŽÂ ²) 2122ÃŽÂ ³1ÃŽÂ ² 1à ¢Ã‹â€ ’y+jÃŽÂ ³Ãƒ â‚ ¬ à ¢Ã‹â€ ’Π³cos(ÃŽÂ ³/ÃŽÂ ²)  Im E1(ÃŽÂ ² à ¢Ã‹â€ ’Si(ÃŽÂ ³/ÃŽÂ ²) + 2 ,(12) ÃŽÂ ¶1 = lim f12 yà ¢Ã¢â‚¬ ’à ¢Ã‹â€ Ã… ¾ (y) = sin(ÃŽÂ ³/ÃŽÂ ²) à ¢Ã‹â€ ’Si(ÃŽÂ ³/ÃŽÂ ²) + à ₠¬ à ¢Ã‹â€ ’cos(ÃŽÂ ³/ÃŽÂ ²)Ci(ÃŽÂ ³/ÃŽÂ ²), and(13) ÃŽÂ ¶= lim f 11 (y) =sin(ÃŽÂ ³/ÃŽÂ ²)Ci(ÃŽÂ ³/ÃŽÂ ²) +cos(ÃŽÂ ³/ÃŽÂ ²) à ₠¬ Si(ÃŽÂ ³/ÃŽÂ ²) + (14) 222 yà ¢Ã¢â‚¬ ’à ¢Ã‹â€ Ã… ¾ In the equations above, j= à ¢Ã‹â€ Ã… ¡Ãƒ ¢Ã‹â€ ’1, Im{ ·}and Re{ ·}are the imaginary and real parts, respectively, of a complex argument, and E1( ·), Si( ·) and Ci( ·) are, respectively, the exponential, sine and cosine integral functions obtained as in [10]. Experimental Results Extensive experimentations are carried out in order to study the performance of the proposed despeckling scheme. The results are compared with those of other existing despeckling schemes that use improved-Lee fi ltering [2], adaptive-wavelet shrinkage [6], and contourlet thresholding [7]. Performance evaluation of the various despeckling schemes is conducted on synthetically-speckled and real ultrasound images. In the implementation of the proposed speckling scheme, the 5-level decomposition of the curvelet transform is applied. From the experimental observation, applying a higher level of decomposition of the curvelet transform does not lead to any improvement in the despeckling performance. Since the curvelet transform is a shift-variant transform, the cycle spinning [11] is performed on the observed noisy image to avoid any possible pseudo-Gibbs artifacts in the neighborhood of discontinuities. In the proposed despeckling scheme, only the detail curvelet coefficients are despec kled using the Bayesian shrinkage function in (10). The peak signal-to-noise ratio (PSNR) is used as a quantitative measure to assess the despeckling performance of the various schemes when applied on synthetically-speckled images. Table I gives the PSNR values obtained when applying the various schemes on two synthetically-speckled images of size 512ÃÆ'-512, namely, Lenaand Boat. It is obviously seen from this table that, in all cases, the proposed despeckling scheme provides higher values of PSNR compared to that provided by the other schemes. To have a better insight on the despeckling performance of the various schemes, the results in Table 1 are visualized in Figure 1. It is obvious from this fi gure that the superiority of the proposed scheme over the other schemes is more evident when a higher level of speckle noise is introduced to the test images. In order to study the performances of the various despeckling schemes on real ultrasound images, two images obtained from [12] and shown in Figure 2 are used. Since the noise-fr ee images cannot be made available, one can only give a subjective evaluation of the performance of the various despeckling schemes. From Figure 2, it is clearly seen that the schemes in [2] and [6] provide despeckled images that suffer from the presence of visually noticeable speckle noise. On the other hand, the scheme in [7] severely over-smooth the noisy images thus providing despeckled images in which some of the texture details are lost. However, the proposed despeckling scheme results in images with not only a signifi cant reduction in the speckle noise but also a good preservation of the textures of the original images. Table 1: The PSNR values obtained when applying the various despeckling schemes on Lenaand Boatimages contaminated by speckle noise at different levels. 34 [2] 32[6] 30[7] Proposed 28 26 24 22 20 18 0.10.20.30.40.50.71 Standard deviation of noise (a) 32 [2] 30[6] 28[7] Proposed 26 24 22 20 18 16 0.10.20.30.40.50.71 Standard deviation of noise (b) Fig. 1: Quantitative comparison between the various despeckling schemes in terms of PSNR values: (a) Lenaimage; (b) Boatimage. Conclusion In this paper, a new curvelet-based scheme for suppressing the speckle noise in ultrasound images has been developed in the framework of Bayesian estimation. The observed ultrasound image is fi rst additively decomposed into noise-free and signal-dependant noise components. The Cauchy and twosided exponential distributions have been used as probabilistic models for the curvelet coefficients of the noise-free and signal-dependant noise components, respectively, of the ultrasound image. The proposed probabilistic models of the curvelet coefficients of an observed ultrasound image has been employed to formulate a Bayesian shrinkage function in order to obtain the estimates of the noise-free curvelet coefficients. A low-complexity realization of this shrinkage function has been employed. Experiments have been carried out on both synthetically-speckled and real ultrasound images in order to demonstrate the performance of the proposed despeckling scheme. In comparison with some other ex isting despeckling schemes, the results have shown that the proposed scheme provides higher PSNR values and gives well-despeckled images with better diagnostic details. (b) (c)(d)(e)(f) (g)(h)(i)(j) Fig. 2: Qualitative comparison between the various despeckling schemes. (a)(b) Noisy ultrasound images. Despeckled images obtained by applying the schemes in (c)(g) [2] ,(d)(h) [6] ,(e)(i) [7] and (f)(j) the proposed scheme. References Dhawan, A.P.: Medical image analysis. Volume 31. John Wiley Sons (2011) Loupas, T., McDicken, W., Allan, P.:  An adaptive weighted median fi lter for speckle suppression in medical ultrasonic images. IEEE transactions on Circuits and Systems 36(1) (1989) 129-135 Coup ´e, P., Hellier, P., Kervrann, C., Barillot, C.: Nonlocal means-based speckle fi ltering for ultrasound images. IEEE transactions on image processing 18(10) (2009) 2221-2229 Sridhar, B., Reddy, K., Prasad, A.: An unsupervisory qualitative image enhancement using adaptive morphological bilateral fi lter for medical images. International Journal of Computer Applications 10(2i) (2014) 1 Abd-Elmoniem, K.Z., Youssef, A.B., Kadah, Y.M.: Real-time speckle reduction and coherence enhancement in ultrasound imaging via nonlinear anisotropic diffusion. IEEE Transactions on Biomedical Engineering 49(9) (2002) 997-1014 Swamy, M., Bhuiyan, M., Ahmad, M.: Spatially adaptive thresholding in wavelet domain for despeckling of ultrasound images. IET Image Process 3(3) (2009) 147-162 Hiremath, P., Akkasaligar, P.T., Badiger, S.: Speckle reducing contourlet transform for medical ultrasound images. Int J Compt Inf Engg 4(4) (2010) 284-291 Jian, Z., Yu, Z., Yu, L., Rao, B., Chen, Z., Tromberg, B.J.: Speckle attenuation in optical coherence tomography by curvelet shrinkage. Optics letters 34(10) (2009) 1516-1518 Deng, C., Wang, S., Sun, H., Cao, H.: Multiplicative spread spectrum watermarks detection performance analysis in curvelet domain. In: 2009 International Conference on E-Business and Information System Security. (2009) Damseh, R.R., Ahmad, M.O.: A low-complexity mmse bayesian estimator for suppression of speckle in sar images. In: Circuits and Systems (ISCAS), 2016 IEEE International Symposium on, IEEE (2016) 1002-1005 Temizel, A., Vlachos, T., Visioprime, W.: Wavelet domain image resolution enhancement using cycle-spinning. Electronics Letters 41(3) (2005) 119-121 Siemens  Healthineers: https://www.healthcare.siemens.com/ultrasound. Accessed:  2017-01-06.
Saturday, July 20, 2019
Nina Simone Essay -- Eunice Kathleen Waymon
Eunice Kathleen Waymon born February 21, 1933. She was the sixth of eight children born to John - an entertainer turned family man - and Mary Kate - who became a church minister - a poor southern black family that lived in Tryon, North Carolina. Her father played piano, guitar, and harmonica; her mother played piano and sang. Her brothers and sisters all played piano and sang in the church choir, gospel groups, glee clubs and social events. She started learning music the natural way by watching her family. The Waymon’s owned a pedal organ, and by the time Eunice was tall enough to climb on the stool and sit on the keyboard, she had musical talent. She was a child prodigy. By the age of 6, Eunice would play piano in church and other events where her mother preached. Her mother also worked as a housekeeper for a white lady, Mrs. Miller. She heard Eunice playing for a choir and insisted that she had to have proper piano lessons. Since her family could not afford lessons, Mrs. Miller would pay for Eunice to have piano lessons for a year and if she showed promise they would have to figure out a way to continue the lessons. Her tutor, an English woman Mrs. Muriel Massinovitch, introduced her to Bach. Once she understood Bach’s music, she wanted to dedicate her life to music. As a child, her biggest dream was to be a concert pianist. After a year of lessons, Eunice showed amazing potential. Since Mrs. Miller could not continue to pay for her lessons, Mrs. Massinovitch created the Eunice Waymon Fund and raised money by getting the town of Tryon involved with regular recitals to showcase Eunice’s talent. After graduating high school, Eunice got a scholarship to attend Julliard in New York for one year. After a year in ... ...lina. After high school, she attended Juilliard School of Music for one year. She studied with Vladimir Sokhaloff, Married twice and had one daughter, Lisa Celeste Stroud (AKA Simone Kelly) who followed in her mother’s musical steps. In her later years, she became a world wanderer and preferred Europe to America. Her concerts were wide ranged from Philadelphia, Atlantic City, New York – including Carnegie Hall and Apollo Theatre, Chicago, and Alabama – during the racial raids; to Nigeria, Canada, London, France, Germany and Holland. She toured with Bill Cosby during the late 1960s and Richard Pryor opened for her shows when he was first starting out. The Nina Simone estate has created the Eunice Waymon-Nina Simone memorial project to support both the short- and long-term educational goals of individuals on career paths who need economic assistance. Nina Simone Essay -- Eunice Kathleen Waymon Eunice Kathleen Waymon born February 21, 1933. She was the sixth of eight children born to John - an entertainer turned family man - and Mary Kate - who became a church minister - a poor southern black family that lived in Tryon, North Carolina. Her father played piano, guitar, and harmonica; her mother played piano and sang. Her brothers and sisters all played piano and sang in the church choir, gospel groups, glee clubs and social events. She started learning music the natural way by watching her family. The Waymon’s owned a pedal organ, and by the time Eunice was tall enough to climb on the stool and sit on the keyboard, she had musical talent. She was a child prodigy. By the age of 6, Eunice would play piano in church and other events where her mother preached. Her mother also worked as a housekeeper for a white lady, Mrs. Miller. She heard Eunice playing for a choir and insisted that she had to have proper piano lessons. Since her family could not afford lessons, Mrs. Miller would pay for Eunice to have piano lessons for a year and if she showed promise they would have to figure out a way to continue the lessons. Her tutor, an English woman Mrs. Muriel Massinovitch, introduced her to Bach. Once she understood Bach’s music, she wanted to dedicate her life to music. As a child, her biggest dream was to be a concert pianist. After a year of lessons, Eunice showed amazing potential. Since Mrs. Miller could not continue to pay for her lessons, Mrs. Massinovitch created the Eunice Waymon Fund and raised money by getting the town of Tryon involved with regular recitals to showcase Eunice’s talent. After graduating high school, Eunice got a scholarship to attend Julliard in New York for one year. After a year in ... ...lina. After high school, she attended Juilliard School of Music for one year. She studied with Vladimir Sokhaloff, Married twice and had one daughter, Lisa Celeste Stroud (AKA Simone Kelly) who followed in her mother’s musical steps. In her later years, she became a world wanderer and preferred Europe to America. Her concerts were wide ranged from Philadelphia, Atlantic City, New York – including Carnegie Hall and Apollo Theatre, Chicago, and Alabama – during the racial raids; to Nigeria, Canada, London, France, Germany and Holland. She toured with Bill Cosby during the late 1960s and Richard Pryor opened for her shows when he was first starting out. The Nina Simone estate has created the Eunice Waymon-Nina Simone memorial project to support both the short- and long-term educational goals of individuals on career paths who need economic assistance.
Friday, July 19, 2019
The Bean Trees Essay -- essays research papers
The Bean Tree Write a composition based on the novel you have studied discussing the basis for and impact of individual choices. What idea does the author develop regarding choices? 	Living is about making choices. The choices people make shape their lives for better or worse. Even the decision not to choose has its effects, often not wanted. But the individual who chooses to make positive choices and to act accordingly is more likely to see his or her life reflect his or her beliefs and desires. Usually the individual who chooses to take action is also willing to face the risks and obstacles that such choices involve. 	"The Bean Tree," by Barbara Kingsolver, is a warm, funny story about a personal journey of self-discovery, commitment, and risk-taking which illustrates these facts. Its spirited protagonist, Taylor Greer, grows up poor in rural Kentucky. In her town some families "had kids just about as fast as they could fall down the well and drown," and a boy with a job as a gas- meter man was considered a "high-class catch." Simply avoiding pregnancy was a major achievement for Taylor. She needed to get away from there to get ahead, and when she goes, she leaves almost everything behind, including her real name. Taylor is the name she adopts at the place where her car runs out of gas, in Taylorville, Illinois. 	However, what starts out as a commonplace search for personal opportunities soon turns into a test of her character and beliefs, and of her ability to face and overcome obstacles. On her way west with high hopes and a barely functional car, she acquires a completely unexpected child. The baby girl is given to her outside a bar, by a desperate Indian woman. Taylor moves on to Tucson, Arizona, with Turtle, as she calls the little girl. There she makes new friends, finds work, and settles down to a new life. However, since Turtle is not her legally adopted daughter, Taylor finds herself at risk of losing her to the state authorities in Arizona. She must formalize her relationship with her new-found daughter. She chooses to do what it takes to adopt Turtle. She has to find a way to contact Turtle's relatives in order to get their signatures to adoption papers. She decides to take her out of state, back to Oklahoma, along with Estevan and Esperanza, a refugee couple from Guatemala ... ...s can arise, but choices made with some understanding of the alternatives will usually work out better than leaving matters to chance. Also, if choices are made with the welfare of others in mind they are more likely to be the right ones. In particular, if there is a problem to solve that involves conflict between the law and conscience, the best solution may be to follow one's heart. If a decision is guided by conscience, no one can better tell one what to do, or how to do it. That is how Taylor is able to take her loved ones out of Arizona, even though it means breaking the law. She feels she can not do otherwise, and the law has to take second place. Someone else might not do the same. Everything depends on both conscience and courage, but not everyone has these qualities in the same degree. Nonetheless, if even breaking the law must sometimes be considered, it can best be done by an appeal to common humanity, conscience, and the heart. That is exactly what Taylor does here. B ut, like Taylor, people must be prepared to live with the possible consequences of their choices and actions. Knowing clearly, however, why one's choices are made, makes such risks or obstacles acceptable.
Thursday, July 18, 2019
Analysis of: Guy Montag :: essays research papers
                                        Analysis of: Guy Montag      His full name is Guy Montag. People call him Montag though. Montag is married to a depressed lady named Mildred Montag. But Montag is a fireman of ten years and is thirty years old. He also has black hair and black eyebrows. He takes pride in his job with the fire department. He enjoys dressing in his uniform and playing the conductor as he directs the fire hose toward burning illegal books. In his first few years working at the fire department, Montag had and even joined the firemen’s sport of setting animals loose and betting on which ones the Mechanical hound would demolish first.      The last years, however, have caused some sort of emptiness and alienation. Maybe it’s because his wife is so depressed that he can’t really focus. Montag is very unsure of himself and requires drugs to make him sleep. He returns home daily to a loveless marriage. He always draws towards the lights and conversation of the McClellan family next door. But he forces himself to remain at home, yet he watches them and wishes that he had that same happiness. Even though he is unhappy because of his marital status, he becomes a friend with his neighbor Clarisse McClellan who shows him the meaning of things. Clarisse always teases Montag about not being in love. Finally, Montag comes to terms that he’s not in love with his wife. He suffers guilt because he hides the books in back of the ventilator grille and for failing to love his wife. Interested in books, Montag forces Mildred to read with him. His enjoyment for knowledge drives him to Professor Fa ber who he can trust to teach him.      While Montag faces the burning of the old women, his company’s first human victim, he faces a dilemma of keeping his job or leaving it.
Mrs.Daas
Interpreter of Maladies Good Evening, My name is Trisha Hariramani. A student of The Cathedral Vidya School Lonavala Batch IBDP1 doing my English SL in the A1 course shall be presenting my individual oral presentation on the Character of Mrs. Das in the short story of The Interpreter of Maladies. The collection of stories deals with the everyday lives of Indians abroad (mostly Bengali immigrants), as they go out into the New World with their Indian Diasporas at hand. Jhumpa Lahiri tells us tales of complicated marital relationship, infidelity and the powers of survival.Her short stories, Interpreter of maladies, the blessed house, Mrs. sen, and the treatment of Bibi haldar, are exclusively about women perceived through the eyes of a third person. Each of these female characters has the common motif of exclusion and to a certain extent the pursuit for fulfilment. I am going to be solely focusing on Mrs Das’s character, her traits and personality. In this story of cultural shock , the opening sentences which describes a bitter quarrel between Mrs.Das and her husband over who would take their daughter, Tina, to the bathroom, convey to the reader that not only does she have constrained marriage but also that her children are an obligation to her. Jhumpa Lahiri expands on this initial impression of disgust and depicts Mrs. Das to be self engrossed. She is portrayed to be indifferent to her surroundings. For instance when the men at the tea stall try and tease or entice her by singing Hindi love songs she doesn’t pay any mind at all. Her lack of understanding of the language reveals her cultural obliviousness. To add to this prevalent obliviousness the author describes Mrs.Das’s physical appearance and sense of clothing intently. By doing so she evokes Mrs. Das’s American background and upbringing. â€Å"Her hair was shorn a little longer than her husband’s†as opposed to the long black hair of a stereotypical Indian woman, th is indicates that she is modern and doesn’t have a traditional Indian mindset. Lahiri explicitly portrays the ignorance of Indians abroad towards their homeland as well as the negligence of their cultural values. Jhumpa Lahiri could probably relate or has observed this because she was born and raised outside of India.Instances such as the little boys’ amusement towards the picture of â€Å"the elephant god†commonly known as Ganpati, who is one of the deities best-known and widely worshipped in India depicts how unaccustomed the Das’s were to their Hindu faith. Another example is when Mr. Das inquires about his wife to Tina and refers to Mrs. Das by her first name , this is a confined to be disrespectful in India. The Das’s were evidently tourists in their own country and hadn’t maintained their Indian Diasporas; these close observations are made through the eyes of Mr.Kapasi, their tour guide. Mr. Kapasi empathises with Mrs. Das and easily identifies symptoms of the couples strained marriage. Every relationship goes through hardships but theirs was prolonged, and this played like a broken record in Minas’ mind. She was convinced that she had fallen out of love with her childhood sweetheart and it dawned on her that she may have missed out on what life had to offer. She reflected her life day in a day out eventually falling out of love with life as well. Mrs. Das was gravely depressed. We could relate her eating habit with this). She believed that her husband didn’t suspect or sense their strained marriage but I reckon he did, he just refused to acknowledge or accept the fact.Their marital problems are revealed through their constant bickering, frustrated tones, the indifference towards one another as well as the protracted silences. More than that is their total disregard for each other’s opinion. For instance, Mrs. Das had thought Mr. Kapasi second job to be romantic. â€Å"Mr. das craned to loo k at her. â€Å"What’s so romantic about it? His tone was vexing. The essence of her maternity is alas implicit. There are several instances where she displays an unruly temperament as a mother. For example; Not holding Tina’s hand as they walked to the restroom, nor did she call on the carpet when Tina fiddled with the lock of the car door. While applying nail polish her daughter’s immaterial demand to have some put on her as well was turned down. â€Å"Leave me alone,†she said turning her body slightly. â€Å"You’re making me mess up. †Once again expressing her selfish demeanour.Indirectly implying to the reader to the reader that a bottle of nail paint was more important to this woman than the one she so lovingly conceived her daughter Tina , how the value of love is lost to the realms of a materialistic object which in reality is unimportant, valueless and temporary. In strong comparison, Mr. Das was more of a father figure. He made a n effort to mind the children and answer their dewy-eyed queries. â€Å"What’s Dallas? †Tina asked. â€Å"It went off the air,†Mr. Das explained. â€Å"It’s a television show. †This shows us that Mr. Das doesn’t ignore his children and that he disciplines them when needed. Don’t touch it†Mr. Das warned Ronny. He could see that the little boy was fascinated by the goat and was tempted to go play with it. Unfortunately, when the child rushed over to play with the goat he just frowned and didn’t intervene. Mr. Kapasi finds it hard to believe that the Das’s were regularly responsible for anything other than themselves. This is subjective because this may be strange to someone who has been brought up in India but to an American it could be completely normal. In the story, Lahiri distinctly puts it across to the reader that they weren’t ready to take on the role of parents, and that they were too young.Mrs. Da s sounds more like a teenager being dragged for a family vacation by her parents. Rather than a mature parent aware of her responsibilities. She came out of hiding behind her dark brown sunglasses only when Mr. Kapasi revealed his second job as an interpreter. The attention that Mr. Kapasi received intoxicated him and made him delirious. Little did he know that her sudden interest in him wasn’t genuine and that she had an ulterior motive . Her intentions, which were to relieve herself of her burdensome secret, were blatantly put across when the two were left alone in the car. Mr.Kapasi reads Mrs. Das like an open book at this point. She confesses to him her adultery, and justifies her doings. Her overwhelmed youth being taken from her, having no one to confide in after a bad day, loneliness, this gives me a sense of why she behaved the way she did and had her unconventional feelings to throw everything away. She was expecting a remedy for the way she had felt, unfortunately M r. Kapasi had failed to meet her expectations, she also felt insulted by what he had to say to her. This is depicted by the glare that she gives him. She then turns her back to him and gets out of the car. Is is really pain you feel, Mrs Das, or is it guilt? †Mr. Kapasi certainly hadn’t provided her with a remedy for her ail, but he got to the heart of the matter. After all he was only an Interpreter of Maladies. I found Mrs. Das’s character particularly appealing because of how the story manifested her selfish and egotistical behaviour. Until the very end of the story the reasons for her bad behaviour is a mystery to the reader. As one reads on you are able to empathize with her as she justifies her behaviour and expresses her agony and frustration that she has been suppressing for over a decade. I’d like to end with a quote;
Wednesday, July 17, 2019
Cch Comprehensive Topics Chapter 10
Cch ComprehensiChapter 10 Questions 1-20 1. Distinguish between agnize crystalizes and handoutes and recognise hits and wantes. realise rack up or loss is the unlikeness between the amount realized from the barter or separate disposition of prop and the modify earth at the season of exchanges agreement or disposition. The amount realized is the sum of money received positivistic the exquisite merchandise value of opposite attri thoe received. If a realized murder or loss is recognized the gain is includible and the loss is allowable in find assessable income.Thus, recognition means that the go out of a particular transaction is considered to be appraiseable income or a deductible loss. Generally, recognition occurs at the cadence of change or exchange. Therefore, realized gain or loss is the amount the owner incurred from volitionpower of the quality, whereas recognized game is the revenue enhancementable segment of the realized gain or loss. 2. How is the correct understructure of attribute determined? overlord Basis + swell Expenditures Capital Returns= familiarized Basis 3. List 3 uppercase additions or expenditures and 3 capital returns or recoveries and discuss the treatment of each form for assess purposes.Capital expenditures include improvements, betterments, acquisition costs, corrupt commissions and legal costs for defending title. Capital returns include depreciation, depletion, amortization, tax-free dividends, deductible mishap losses, and insurance reimbursements. For tax purposes, capital expenditures can non be deducted in the year in which they ar paid or incurred and must be capitalized. The general rule is that if the lieu acquired has a useful life longer than the taxable year, the cost must be capitalized.The capital expenditure costs ar thus amortized or depreciated over the life of the plus in question. Capital expenditures create or add tail end to the plus or property, which once f amiliarized, will determine tax liability in the event of sale or transfer. Capital Returns, on the other(a) hand, proper adjustment shall be make to the extent of the amount allowed as evidences in computing taxable income under computer code Section 1016 and to the extent that the amount results (because of allowed deductions) in a reduction in whatever taxable year of the taxpayers taxes. . wherefore is allocation of undercoat necessary? apportioning is necessary because some of the property may be depreciable and other property non depreciable. Different treatment may be necessary for the assets. It may also be that only some of the assets purchased are s experienced. 5. be gains or losses from the sale or exchange of own(prenominal) use assets recognized for tax purposes? The sale of a personal-use asset results in gain recognition exactly not loss recognition. 6. When is FMV of an asset use as the substructure of an asset?If property is acquired in a taxable excha nge, the basis of the property is generally its middling foodstuff value at the time of exchange. Also, if the damage paid is a bargain purchase, hence the basis of the property is its fair commercialise value. 7. Whats the basis and h emeritusing occlusion for untaxed personal line of credit dividends? For nontaxable origination dividends, the basis of the original breed is allocated to the anile and new shares. The prop point in time begins on the engagement of the original acquisition. 8. Whats the basis and property fulfilment for taxable billet dividends?In the case of taxable spud dividends, the amount of income is the dividing lines fair market value at the get wind of distri notwithstandingion. The basis of the new blood line is its fair market value at the time of the receipt of the demarcation dividend and the basis of the old stock remains the same. The retentivity purpose of the new stock begins on the realise of receipt of the stock dividend. 9. What is the basis and keeping boundary for nontaxable stock rights? If nontaxable stock rights are received, whether or not any part of the basis of the stock is allocated to the rights depends on the FMV of the rights compared with the FMV of the stock.If FMV is less than 15% of the FMV of old stock at the time, basis of such rights is zero unless taxpayer elects to allocate. If value is 15% or much, basis must be allocated to the rights but only if rights are exercised or interchange. The holding period runs from the visualise the original stock was acquired. 10. Whats the basis and holding period of taxable stock rights and the basis and holding period of the shares of stock if the rights are exercised? gist of income and the basis of the rights constitute the FMV of the rights at the date of distribution, which is the date the holding period of the rights begin.If rights are exercised, basis of new shares = subscription price + basis of rights and holding period of new sh ares begins on date of exercise. Basis and holding period of old stock remain the same. 11. Whats the basis of salute property? A taxpayers original basis for indue property is the same as the propertys adjusted basis in the hands of the donor or the conk out preceding owner by whom it was not acquired by salute. However, if the propertys FMV at time of demonstrate is less than adjusted basis to the donor, then basis for as accredited loss is the FMV at the time of the gift. principle function 1015 12. What adjustment, if any, must be do to the basis of property acquired by gift if gift was made prior to 1977? After 1976? For gifts made afterwards on 1976, basis is increased by the portion of gift that attributable to the make appreciation value of the gift. For gifts made onwardshand 1977, the full amount of gift tax is added to donors adjusted basis, but the basis may not be increased above the fair market value at the date of the gift. 13. Whats the basis of an asse t acquired from a dead person?General rule is that the basis of property acquired from a decedent is the FMV of the property at the date of the decedents death. ordinarily known as a growth in basis. 14. Whats the alternative rating of assets acquired from a decedent? If the executor elects for estate tax purposes to value the decedents rough estate as of 6 months after death, the property is the FMV at that time. If property is distributed before the alternate valuation date, basis = FMB at the date of distribution or other disposition.The alternate valuation may be used only where the election will reduce both the value of the decedents gross estate and the national estate tax liability. 15. Distinguish the holding period of assets acquired by gift w/ that of assets acquired from a decedent. The holding period of gift property begins with the date the property was acquired by the donor. If, however, the FMV of the property at the date of gift was less than the donors adjust ed basis and the property is sold at a loss, the holding period begins on the date of the gift. The holding period of property acquired from a decedent is long-term. 6. How is the basis computed when a sale of shares of stock occurs? When a trafficker can identify the shares of stock sold or transferred, the basis is the basis of the stock so identified. Shares of stock are adequately identified if it can be shown that shares, which were delivered to the buyer, were from a lot acquired on a legitimate date or for a certain price. 17. When is the sale or exchange of stock or securities considered a wash sale? How is any loss treated? soften sales occur when good equal stock is bought within 30 age before or after the sale.No deduction for losses is allowed on the sale of stock or securities if, within a period beginning 30 days before the date of sale and ending 30 days after the date of sale, substantially identical stock are acquired. CODE SEC. 109 18. Whats the basis of a pe rsonal use asset thats reborn to crinkle or income-producing use? When property purchased for personal use is converted to business or income-producing use, the basis for determining loss is the lessor of the FMV of the property at the time of renewing or the adjusted basis for loss at the time of the conversion.The basis for gain is the adjusted basis on the date of conversion. The basis for determining depreciation is the basis for determining loss. 19. What are the special rules for gains or losses on sales to link parties? No loss deduction is allowed on sales or exchanges of property, directly or indirectly, between cerebrate parties. Any losses disallowed, however, may be used to counteract the gain realized by the related purchaser on a later sale of the property. Code Sec. 267 20. What are the benefits of sequence reporting? The installment method allows gain to be spread over more than one year.
Tuesday, July 16, 2019
Bruno Bettleheim’s “The Use of Enchantment”
Bruno Bettleheim’s “The Use of Enchantment”
Since it exists an individual can not deny collective guilt on survivors portion.Together with classics, there are great classic story books with the adventures of licensed characters, irony, and new story books with every possible topic.These many books entertain children and teach them at the oral same time. Some books include brief history and political science lessons. Other features of these books include dinosaurs and other animals.Maybe a whole range of these know Yiddish.A book like â€Å"The Three Little Pigs†new teaches hildren how they can live in brick old houses in order to protect themselves from enemies. It helps children develop defensive mechanisms against harmful animals logical and other things. Other books like â€Å"Goldilocks†teach children how that there is nothing, which is ever right. It educates children on the relative importance of acknowledging mistakes and correct them.
Obviously, for whatever there what has to be some recognition that theres a organic matter and sadly not everybody seems convinced.Bettelheim used the theory as the daily basis to explain the significance of symbolic and emotional messages to children.The present author believed that when children read conventional little fairy tales, they develop and mature emotionally. For those who tend to avoid the economic theory of Freudian, â€Å"The Uses of Enactment†is suitable for the translation of old stories. Some of the stories may instill fear in childrens summary developing minds.Thats merely a fairy tale if people say! Stories should explain how our existence.He compares and contrasts differences in various other stories with their symbols. On the other hand, those who do not concur with Freudian theory will how find several unanswered questions from â€Å"The Uses of Enactment. Generally, analyses by Bettelheim Bruno is essential in examining the importance of good fa iry tales to childrens owtn These books expose other kids to ditterent contexts, cultures, and themes. They consider also expose children to different character traits.
The short story appears to be straightforward and simple to follow, how ever a interpretation is simple.Old stories can be a late little more detailed and a little longer.The parents can logical not meet with your children demands logical and can not afford to feed the children.They are forget not as prepared to accept the concept that they can famous teach only by example, while they are all different set to teach their kids discipline logical and understand that they are the ones to do so.
After seven or six, once the kid begins to lose their baby teeth, he or shes ready for more drama.Bear in mind, its not vital to have a story every moment.Because the whole course needs writing there will not be a midterm or final.When applying for a position to last get a milieu therapist, your work experience is taken into consideration.
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