Busines organization Essay Example | Topics and Well Written Essays - 2250 words

Busines organization - Essay Example ts have regarded the debts of the corporation to be that of its shareholders, thereby piercing the corporate veil.2 The separate legal existence of a company was established by the court in the Salomon case. 3 As such, in Salomon v Salomon, 4 their Lordships created the rule that a company constitutes a separate legal entity that is distinct from its members. 5 This provided the direction to contemporary company law and the character of private limited companies. 6 European statutory provisions have incorporated this significant maxim. The objective behind providing for a separate legal persona and limited liability is to promote investment, foster trade and to furnish entrepreneurs with an incentive to commence new business. 7 In addition, in Adams v Cape Industries plc,8 a complete review of the Salomon ruling was achieved by the Court of Appeal. This case considered liability inside a group of companies. The claimant, moved the court to render the parent company liable for the obligations of the subsidiary company. The Court of Appeal lifted the corporate veil on the basis of the following considerations; namely, faà §ade, agency and single economic unit. 9 In its judgment, the Court of Appeal declared that the corporate veil could be pierced if there was an express agency agreement between the subsidiary company and the parent company. The presumption of an agency relationship, strictly relied upon the presence of such an agreement. 10 The Court, also held that the veil could not be pierced, merely because the defendant company was a member of a group of companies and the corporate framework had been adopted to avert the liability of the defendant company. 11 GHI Ltd was working as a subsidiary of its parent company ABC Ltd. As such, GHI Ltd can be deemed an agent of its parent company ABC Ltd. Furthermore, in DHN Food Distributors Ltd v Tower Hamlets London Borough Council,12 Lord Denning of the Court of Appeal held that the group of companies, in question,

VLSI Architecture for QR Decomposition on MHHT Algoritm

VLSI Architecture for QR Decomposition on MHHT Algoritm A VLSI Architecture for the QR Decomposition based on the MHHT Algorithm s.n.v.sai.pratap1 k.kalyani2 s.rajaram3 Abstract: This paper presents Novel VLSI (Very Large Scale of Integration) architecture for the QR decomposition (QRD) based on the Modified Householder transformation (MHHT) algorithm. QRD of a matrix H is decomposition of matrixHinto a productof an orthogonal matrix Qand an upper triangularR. QRD is often used to solve several engineering problems in many areas. Pre-processing modules based on QRD makes the decoding in signal processing easier and implementing data detection with QRD helps to reduce the complexity of spatial multiplexing MIMO – OFDM detection. The techniques used for implementing QR decomposition are: Givens rotation, Modified GramSchmidt Orthogonalization (MGS), Householder Transformations (HHT), and indeed Modified Householder transformation (MHHT). The proposed MHHT algorithm shows best trade-off between complexity and numerical precision, and also suites for VLSI architectures. The proposed MHHT algorithm reduces computation time and hardware area of the QRD block compared to the existing Householder algorithm. Implementation of this algorithm is carried out in FPGA Virtex6 xc6vlx550tl-1Lff1759 device with the help of Xilinx ISE 14.1. Keywords: MIMO systems,VLSI architecture, QR Decomposition (QRD), Householder Transformation(HHT). 1. INTRODUCTION: The QR decomposition (QRD) is a basic matrix factorization method from matrix-computation theory used to compute two output matrices Q and R from an input matrix H, such that H = QR. QRD is often used to solve many engineering areas like least-square problems, linear system equations etc. For symbol-decoding solutions inside Spatial-Multiplexing Multiple-Input Multiple-Output (SM-MIMO) systems, QRD basically consists in simplifying demodulation tasks in suboptimal and near-optimal solutions by finding an orthogonal matrix Q and an upper-triangular matrix R from an input matrix H. Several techniques towards implementing the QRD are already reported in literature. For instance, and under the context of SM-MIMO systems, the most explored are the Modified Gram-Schmidt Orthogonalization (MGS, as a generalized improvement of the Gram-Schmidt algorithm), Givens rotation, the Modified Householder Transformations (MHHT as an enhancement of the Householder Transformation algorithm). Due to its simplicity and numerical stability, the QR factorization algorithm utilizing Householder transformations has been adopted. An overview of the main steps of the Existing Householder QR algorithm is presented. The purpose of this work is to show that when modifying existing Householder QR factorization to the matrix H, the computational complexity and hardware area gets reduced. Due to its trade-off in complexity, numerical precision, and VLSI implementation suitability, the MHHT is preferred. The contribution of this paper is to present a flexible and scalable FPGA-based VLSI architecture with competitive capabilities against other related approaches, motivated on the context of SM-MIMO demodulation solutions. The organization of this paper is as follows: Section II presents the QRD. In Section III, the exisiting HHT and MHHT algorithm is exposed. Implementation results are reported in Section IV, and conclusions are covered in Section V. 2. QR DECOMPOSITION The QRD constitutes a relevant pre-processing operation in SM-MIMO demodulation tasks [1-2]. The baseband equivalent model can be described in (1) At each symbol time, a vector S with each symbol belonging to the Quadrature Amplitude Modulation (q-QAM) constellation passes through the channel response matrix H. The received vector y at the receiving antenna for each symbol time is a noisy superimposition of the signals contaminated by Additive White Gaussian Noise (AWGN) given by n.The maximum likelihood (ML) detector is the optimum detection algorithm for the MIMO system. It requires finding the signal point from all transmit vector signal sets that minimize the Euclidean distance with respect to the received signal vector. The transmitted symbol s can be estimated by solving (2) This gives the optimal result. However, solving (2) with larger constellations and multiple antennas will result in complex calculations. Instead of solving (2) as such, the symbol estimation can be simplified by using QR decomposition of.That is where resides the usefulness of decomposing matrix H in a QR form, yielding a back-recursive dependency on elements in S without incurring into a BER (Bit Error Rate) loss [3-4]. With this practice, the computational complexity is reduced. The detected vector is computed based on the ML algorithm with QR decomposition as given in (3) (3) where is in upper triangular form, approximation of is computationally simpler with the aid of (3). Note that for MIMO-OFDM systems operated in stationary environments, the channel matrix remains almost the same. Thus, QR decomposition of the channel matrix can be done only once to get matrix. On the other hand, the calculation of must be updated for every incoming signal. 2.1 QRD IMPLEMENTATION The techniques used for QR decomposition are: Gram–Schmidt algorithm obtains the orthogonal basis spanning the column space of the matrix by the orthogonality principle. Using a series of projection, subtraction, norm and division, the column vector of the unitary matrix containing the orthogonal basis can be acquired one by one and upper triangular matrix is also obtained as a by-product. Householder Transformation (HHT) tries to zero out the most elements of each column vector at a stroke by reflection operations. The upper triangular matrix is derived after each transformation matrix being applied to every column vector sequentially. The unitary matrix involves the multiplications of these Householder transformation matrices and thus the complexity is much higher. On the other hand, Givens Rotation (GR) zeros one element of the matrix at a time by two-dimensional rotation. If an identity matrix is fed as an input, the unitary matrix will be calculated by using the same rotation sequence when the upper triangular matrix is obtained (Malstev 2006; Hwang 2008 and Patel 2009).The Gram–Schmidt algorithm has the disadvantage that small imprecisions in the calculation of inner products accumulate quickly and lead to effective loss of orthogonality.HHT method has greater numerical stabilitythan the Gram–Schmidt method. Givens method stores two numbers c and s, for each rotation and thus requires more storage and work than Householder method .Givens rotation requires more complicated implementation in order to overcome this disadvantages. Givens rotation can be beneficial for computing QR factorization only when many entries of matrix are already zero, since nullifying certain matrix elements can be skipped. Unlike Givens Transform, Householder Transform can act on all columns of a matrix, and require less computations for Tridiagonalization and QR decomposition, but cannot be deeply or efficiently parallelized. Householder is used for dense matrices on sequential machines, while Givens is u sed for sparse matrices or/on parallel machines. 3. QRD using Householder Transformation In this section, the existing Householder Transformation algorithm is described, followed by proposed HHT method architecture is demonstrated in detail. 3.1 Householder Transformation Householder QR algorithm gradually transforms H into an upper triangular form R by applying a sequence of Householder matrices (multiplies H from the left with Q). Householder transformation is performed by projecting a multi-dimensional input vector onto a plane zeroes multiple elements at the same time. An nÃâ€"n matrix H of the form , (4) is called a Householder matrix. The vector is called a Householder vector. Pre-multiplication of the coefficient matrix with is used to zero out appropriate elements of. It is easy to verify that Householder matrices are symmetric and orthogonal. The Householder matrix block involves the computation of an outer product which requires complexity operation. However, the practical time requirement of using to zero out elements in is lower than that of computing a full outer product. This is because of the tedious computation of the full matrix which is not necessary in practice. Householder reflections work well for introducing large number of zeros using just one matrix multiplication (computing). Normally, all the elements below the diagonal of an entire column of the matrix are eliminated by one Householder reflection. However, this leads to a difficulty when Householder transforms are implemented on parallelly. One reflection affects multiple rows, and therefore, it is difficult to achieve fine-grained parallelism in the operation. The algorithm for Householder transform is given in Table 1. and its block diagram is given in Figure 2. Fig. 2 Block diagram of HHT Table 1 HHT algorithm End Householder vector block: The conventional method of Householder algorithm for decomposing channel matrix is given in Table 1. Initially, the channel matrix is assigned to matrix. It can be periodically updated by following steps to obtain upper triangular matrix. The first column of is assigned to ‘a’ vector. After that the norm value of ‘a’ is calculated and assigned it to ‘g’. The Householder vector ‘v’ is the division ‘u’ and‘t’ which is the norm operation of vector selection . Householder matrix block: The output of Householder vector is given as input to Householder matrix block. Finally, H is computed by The above operation can be updated upto n times to obtain the upper triangular matrix and unitary matrix. It is given below, (5) Q = (HnHn-1†¦H1) T (6) Here the matrix is given to the input of channel matrix to update its vector value. The orthogonal matrix is computed by the multiplication of ‘n’ Householder matrix. Hence its complexity increases and also it occupy more hardware area. If the matrix size increases, the hardware area also increases tremendously. So there is need to reduce the hardware complexity of this block. 3.2 Proposed HHT method The existing method of Householder reflection requires large hardware area and computation time. Householder transformations also provide the capability of nullifying multiple elements simultaneously by reflecting a multi-dimensional input vector onto a plane. However, VLSI implementation of the Householder algorithm needs square-root, multiplication and division operations, which require high hardware complexity. To resolve this issue, a novel Householder algorithm is presented that use series of simple Householder projections, which can be easily implemented using simple arithmetic operations. The proposed algorithm as given in table2 has lesser number of computations compared to the existing algorithm. In Figure 3, the block diagram of modified method is given. It shows two major sub blocks (i.e.) householder vector block and householder matrix block. Householder vector block is same to the previous method of computing ‘v’ with extra weight vector computation. Here modification taken in the Householder matrix block to eliminate matrix multiplication. The vector ‘v’ subtracted from ‘f’ and column vector of channel matrix to give ‘H’ value. Fig. 3 Block diagram of MHHT. In the first step, matrix H is reduced to with all zeros below the diagonal element in the first column by computing the sign of the pivot element d and weight value w. Compared to the previous algorithm, number of steps required to obtain the first matrix can be reduced. For example, if the initial channel matrix of 4Ãâ€"4 undergone to Householder reflection, then it reduces the matrix with all zeros below the first element. The computation of Householder vector in the existing algorithm requires large memory and area. Because is a 4Ãâ€"4 matrix, multiplication of become complex process. To avoid such a task, column vector of matrix has been taken one by one and process it iteratively to obtain the upper triangular matrix. After computation of the first step the matrix size reduced to. After that, the sub matrix of size 3Ãâ€"3 is taken and the steps can be applied repeatedly. The algorithm to compute Householder Vector block is given below. Table 2 HHT algorithm End Repeat above steps for right bottom (n-1)*(n-1) matrix of R Householder vector block: In this Householder reflection algorithm, it transforms the column (7) into the vector of the form (8) where the diagonal element (9) The Householder vector can be computed by, (10) where and This block computation is same as that of previous Householder vector block with a little modification in the weight value. Householder matrix block: After obtaining the Householder vector, the output vector is given to the input of Householder matrix block. The computation of this block is very simple compared to previous method of Householder matrix block computing. The Householder matrix element algorithm is given below, (11) where It reduces the channel matrix to its upper triangular form in steps. To reduce the complexity of computing Q, here the output vector y’ has been taken directly and its algorithm is given below, (12) So the execution time for computing the upper triangular matrix and output vector is very less when compared to conventional Householder reflection algorithm. This reduces the hardware area for the Householder matrix block. The QR decomposition using modified Householder transformation algorithm is simulated by taking ‘a’ as input channel matrix, ‘zb’ as output vector and ‘upper’ as upper triangular matrix. The unitary or orthogonal matrix ‘Q’ need not to be calculated. The output vector in (3) can be computed from the updated Householder vector ‘v’. Also the extra time needed to calculate ‘Q’ can be reduced. So the speed of decomposing the channel matrix can be increased tremendously. 4. Results and Discussion QR decomposition algorithm is required as a pre-processing unit for many MIMO detectors. The accuracy of the channel matrix QR decomposition does not have an impact on the MIMO detection process and finally receiver’s bit-error-rate (BER) performance. The existing and proposed Householder algorithms are downloaded on to Xilinx device xc6vlx550tl-1Lff1759. The synthesis results are compared to show the area efficiency of the proposed one. The channel matrix H elements are represented in floating point representation of 16 bits comprising 1 for sign bit,3 bits for decimal part and 12 bits for fractional part. The 16 bit representation shows an numerical precision oscillates around the interval[10-6,10-5] for both existing and modified algorithms . The computation of column vectors of the R matrix can be parallelised in modified algorithm and thus improvement is obtained in computational time of 49.7% reduction.The computational time for proposed algorithm is about 194.84ns,whereas exisiting algorithm is about 394.56ns. Modified algorithm reduces the matrix computation into vector multilications for some extent and thus reduces the hardware area as obtained from the synthesis report. Table 3 Synthesis report for Conventional Householder algorithm Logic Utilization Used Available Slice LUTs 11142 343680 Bonded IOBs 768 840 BUFG/BUFGCTRL’S 0 32 DSP48E1s 261 864 Table 4 Synthesis report for Proposed Householder algorithm Logic Utilization Used Available Slice LUTs 7634 343680 Bonded IOBs 385 840 BUFG/BUFGCTRL’S 1 32 DSP48E1s 70 864 Table 5 Comparison result Logic Utilization Conventional HHT Proposed HHT % reduced Slice LUTs 11142 7634 31% LUT Flip flops 768 385 49.8% Bonded IOBs 0 1 DSP48E1s 261 70 73% 5. Conclusion To reduce the computational and hardware complexity, Householder transformation algorithm for QRD has been modified. The computation of Q is the tedious process in the existing algorithm. In this work, it can be overcome by directly computing output vector. It reduces the computation time by 52.38% and also reduce in hardware area compared to previous HHT algorithm (Slices – 31%, LUTs – 49.8%) presented in the QRD. Thus it is evident from the comparison result that the number of slices and 4 input LUTs required in FPGA implementation of QR Decomposition is reduced thereby making the low complex design which can meet the specifications of most OFDM communication systems, including VDSL, 802.16, DAB and DVB. In future, this work can be extended to implement K-best LSD and Turbo decoding of LTE receiver. References Lee, K.F. and Williams, D.B.: A space-frequency transmitter diversity technique for OFDM systems. In Proc. Global Telecommunications Conf., San Francisco, CA, pp. 1473-1477. (Nov. 2000) H. Kim, J. Kim, S. Yang, M. Hong, and Y. Shin, â€Å"An effective MIMO–OFDM system for IEEE 802.22 WRAN channels,† IEEE Trans. Circuits Syst. II, Exp. Briefs, vol. 55, no. 8, pp. 821–825, Aug. 2008. H.-L. Lin, R. C. Chang, and H.-L. Chen, â€Å"A high speed SDM-MIMO decoder using efficient candidate searching for wireless communication,† IEEE Trans. Circuits Syst. II, Exp. Briefs, vol. 55, no. 3, pp. 289–293, Mar. 2008. L. Boher, R. Rabineau, and M. Helard, â€Å"FPGA implementation of an iterative receiver for MIMO–OFDM systems,† IEEE J. Sel. Areas Commun., vol. 26, no. 6, pp. 857–866, Aug. 2008. M.-S. Baek, Y.-H. You, and H.-K. Song, â€Å"Combined QRD-M and DFE detection technique for simple and efficient signal detection in MIMO–OFDM systems,† IEEE Trans. Wireless Commun., vol. 8, no. 4, pp. 1632–1638, Apr. 2009. C. F. T. Tang, K. J. R. Liu, and S. A. Tretter, â€Å"On systolic arrays for recursive complex Householder transformations with applications to array processing,† in Proc. Int. Conf. Acoustics, Speech, and Signal Process., 1991, pp. 1033–1036. K.-L. Chung and W.-M. Yan, â€Å"The complex Householder transform,† IEEE Trans. Signal Process., vol. 45, no. 9, pp. 2374–2376, Sep. 1997. S. Y. Kung, VLSI Array Processors. Upper Saddle River, NJ, USA: Prentice-Hall, 1987.

The Aesthetic Pedagogy of Francis of Assisi Essay -- Francis Assisi Es

The Aesthetic Pedagogy of Francis of Assisi ABSTRACT: Despite his anti-intellectualism, Francis of Assisi was an effective teacher who intentionally illustrated the life of virtue in his own way of living. He was a teacher in the sense that the Hebrew prophets, Socrates or Gandhi were teachers. He was a performance artist for whom drama functioned pedagogically. His life was not always meant to be an example to his followers; sometimes it was a dramatic lesson, meant to be watched, not imitated. All drama is inherently a distortion of reality because it focuses the attention on one aspect of reality. Francis’ dramatized life distorts the importance of poverty, but this is a distortion from which we may be able to learn if we are able to imaginatively identify with Francis. For Francis, asceticism was a form of obedience, and obedience a mode of knowledge. Such ‘personalized,’ lived teaching is the only way in which virtue (as opposed to ethics) may be effectively taught. Francis followed the same model of p aideia as Gandhi, bringing together the physical discipline of radical asceticism with the aesthetic experience of a dramatic life in which he played the roles of troubadour and fool. Unlike most of the other Western European figures of the 12th-century who are frequent subjects of academic study, Francis of Assisi was not a scholar. He had the education appropriate to the middle-class son of a prosperous merchant, but he never taught in a university, never wrote a Summa or a Commentary on the Sentences, never spent time in libraries. For much of his lifetime, the Order of Friars Minor didn’t even own a Bible, let alone any other books. Brother Leo, one of Francis’ closest companions, wrote of him that he "did not want ... ...hton, 1923), p. 106. (6) Bonaventure, Major Life, VI. 2. (7) Erving Goffman, The Presentation of Self in Everyday Life (Garden City: Doubleday, 1959), pp. 17-18. (8) cited in Goffman, op. cit., pp. 19, 20. (9) Dorothy Heathcote, Collected Writings on Education and Drama (London: Hutchinson, 1984), p. 114. (10) cited in Howard Williams, Concepts of Ideology (New York; St. Martin's Press, 1988), p. 111. (11) Walter Brueggemann, The Creative Word: Canon as a Model for Biblical Education, (Philadelphia: Fortress Press, 1986), p. 91. (12) Brueggemann, op. cit., p. 104. (13) Leroy S. Rouner, "Can Virtue Be Taught in a School?," Can Virtue Be Taught?, vol. 14, Boston University Studies in Philosophy and Religion, ed. Barbara Darling-Smith, p. 142. (14) Rouner, op. cit., p.147. (15) Rouner, op. cit., p. 148. (16) Chesterton, op. cit., p. 86.

Social Media Use

Abstract The purpose of this study is to actually look at the use of the social media (i. e Facebook, Twitter, Whatsapp,) in RSUST and the academic performance of the students. In this research a qualitative research method is used. 3 researched questions were asked 1. How common is the use of social media (i. e Facebook, BBM[BlackBerry Messenger], Whatsapp, Twitter) among RSUST students. 2. How often do these students spend using the social media? 3. How has it affected the academic performance of those who use the social media and those who don't?Introduction There has been a debate about the use of social media (e. g. , Facebook,Twitter,) by high school and college students, and the possible effect of those tools on students’ academic performance (Connolly, 2011; Hargitai, & Hsieh, 2010; Karpinski, & Duberstein, 2009). The main issue of this debate is whether the growing use of social media by high school and/or university students actually improves or worsens a studentâ₠¬â„¢s academic performance.The continued growth in the usage of the social media by students as early as the elementary school level (Anderson, & Rainie, 2012; Lenhart, 2009), In fact, the average time spent with screen media among 8- to 18-year-olds is more than twice the average amount of time spent in school each year (Kaiser Family Foundation, 2010; National Center for Education Statistics, 2007–2008). This issue has brought about concerns particularly for the areas of education (e. g. the identification and use of compatible teaching methods and the design of non-classroom educational assignments); communications (e. g. , the identification of appropriate channels on how to exchange educational information among individuals) (Chen, & Bryer, 2012; Anderson, & Rainie, 2012). Over the past 10 years, the media environment that children grow up in has changed dramatically, and the amount of time they spend consuming media has exploded. Students have been engulfed with— and possibly transformed by— reality TV, smartphones, iPads, Facebook, Twitter, YouTube.

How does Dickens present the poor and poverty in A Christmas Carol?

In the novel A Christmas Carol Dickens shows that there is much poor and poverty going on in the world. In the novel a families are exposed of going through poverty and being poor, Bob Cratchit and his wife and Tiny Tim and his other children, Bob Cratchit is a man who works for Mr Scrooge. He has a small family who depend on the income he gets from Mr Scrooge. This is already showing the readers that if Mr Scrooge did not pay him his earnings then Bob would be in trouble with his family. How will he manage to feed them?. Even though this family is poor, they seem to be in high spirits at all times. Bob's family are all depending on Mr Scrooge to pay him if not then they will not continue to exist. Showing the readers this family is very unfortunate to not have as much money as Mr Scrooge has. This shows that the Cratchits may not be as happier as they are now if they had no money at all, Yet going through poverty does not stop tiny Tim from praying to god â€Å"to help them all†. Fred, Scrooges nephew seems to be happy enough with the money he has and comes to share his happiness with Mr Scrooge but he neglects Fred's offer to have dinner at his home. Fred who had married a lady who was not as rich as Mr Scrooge was happy despite the lack of money he is determined to celebrate Christmas. He is always glad and joyful regardless of how much money he has. Men and women â€Å"should open their shut up hearts freely†, Even if you opened your heart freely what if money was stopping you? You have all the money you could ever wish for, yet your still not as happy as other are? Fred does not worry about what you think money can bring. Open your heart freely. Mr Scrooge shows not feeling but seems to be in a bad temper at all times even though he has more money than he needs. Fred shows he is better off without all the money that Mr Scrooge has, he has his wife, his family his friends even though he is going through poverty and Dickens is showing this by making Fred go round to his uncles work and invite him to his Christmas dinner and is ignored by Mr Scrooge by calling Christmas a â€Å"Humbug†, He is showing that even though you may be poor and are going through poverty there should be nobody to stop you from being in a excellent mood. Fezziwig, another business man just like Mr Scrooge has many more people and families who depend on him and rely on him to keep them alive with his money. Fezziwig is seen giving all his workers a day off and smiling and laughing away with them, Scrooge seems to think why Fezziwig will do such a thing (Spend so much money for his workers). Although Fezziwig is rich and has his family and friends with him he spends some of his money on his workers this expands the happiness he already has, and also makes his workers cheerful in the season of Christmas. Mr Scrooge seems to think that what Fezziwig is doing is also a â€Å"humbug† he cannot come to terms with the fact that sharing is caring. Fezziwig is better off giving money to the poor and being happy unlike Scrooge who has so much money but does not share at all he dislikes wasting money he dislikes spending his money altogether. Dickens is trying to show the readers that even having to be poor and going through tough times with getting to have a shelter and leaving in a place your family can sleep well, being happy about Christmas and the more merrier you are the more merrier your Christmas will be. The readers can tell that Scrooge is very different from Fezziwig the two differences that they have is that Scrooge hates spending his money, even though he is rich he is miserable rotting away in his work place and in his house on his own. Whereas Fezziwig is as rich as Scrooge, he spends a modest amount of money to make the life of his workers a little more enjoyable. What Dickens is trying to show the reader is that Scrooge is the type of person who is greedy at first and will want to keep his money to himself and all his thoughts and feelings kept inside himself. His character has formed for his past. Scrooge was a lonely boy and then as a young man he was employed by a kind and giving man. All the same, Ebenezer had magnificent ambitions. He also wanted to earn as much as he could ever get and this is what had distorted Scrooges personality as well as himself. His fear of having to lose all his money and Business, has changed his social life, and his personal life, it's affected him mentally and physically. He has neglected his friends and his family, he also seems to disregard himself and forget how he is, forgetting his health and well being for his money. This fear of poverty has taken over his life and changed him. Dickens is trying to show us that poverty is something very powerful, having no home or money could change the way you think of money completely you may steal to get money or even beg, but before when you did have the money you had taken it for granted. So once you have lost all of the money you once had you may want it back again and will do anything to gain it back. Dickens as a child had also gone through poverty as he used to work in a workhouse in his early ages, poverty was a great inspiration for Dickens to create A Christmas Carol as it shows so much that people may not understand, Charles Dickens is trying to show us how a Christmas should be spent without al the grief but full of joy and happiness. Dickens experience of poverty had also changed his way of thinking and has made him realise that poverty possibly will affect some ones family and their own self in a bad way. Just before his father's arrest, the 12-year-old Dickens had begun working ten-hour days at Warren's Blacking Warehouse. He earned six shillings a week pasting labels on jars of thick shoe polish. This money paid for his lodgings with Mrs. Roylance and helped support his family, So Dickens knows how Bob Cratchit will feel about his family being dependent on him for the money he earns for Scrooge. At this time there was a lot of poverty in London and it was not unusual for such a story as A Christmas Carol to occur. Transformation The transformation that took place had changed the way that scrooge used to think about Christmas, He was at first a very lonely and miserable old man, who used to keep everything to him self, his feelings were never expressed and by no means ever smiled. Scrooge is very touched by the visions that the ghost of Christmas past shows him; his transformation begins. He remembers the feelings he had for the love of his life, but he had left her for his business and his wealth. The scenes he had seen were appalling and he had realised that he could steer clear of ending his life in misery. He had seen the consequences of his actions, and stirred away from them. In the novel A Christmas Carol Dickens links Scrooge to `bad weather` on page 12 Dickens metaphorically describes Scrooge, â€Å"No Warmth could warm, no wintry weather chill him. No wind that blew was bitterer than he.† â€Å"The heaviest rain, and snow, and hail, and sleet could boast of the advantage over him in only one respect. They often `came down` handsomely, and scrooge never did.† Dickens had described Scrooge as being so â€Å"cold† that the heaviest rain and coldest weather were better off than him. He is compared to his nephew Fred who with such a uncle, who comes from such bad weather; â€Å"he was all in a glow; his face was ruddy and handsome; his eyes sparkled, and his breath smoked again.† This is showing us that Fred is a much happier person than scrooge. And even though he is from the same background as Scrooge, he is a completely different person to scrooge. Dickens is trying to show us that Scrooge and Fred have a complete contrast between them. Fred is â€Å"Warm† and Scrooge is â€Å"Cold†, As soon as Fred has entered the room the atmosphere had changed; from cold to warm, showing us how cold Scrooge really is. Furthermore Dickens shows Scrooge how the industrial revolution had changed London and the affect it had on the poor people. On Page 77 the phantom later takes Scrooge to an â€Å"obscure part of town, where Scrooge had never penetrated before, Although he recognised its situation and its bad repute.† Being so rich Scrooge had never stepped into the bad parts of town, which because of them that part of town was in that bad state The onset of the Industrial Revolution marked a major turning point in human society; and these poor people who had no jobs and no money had to stay at the dark parts of town which was in a bad condition. The industrial revolution had introduced many new things which had rapidly changed the whole world.