Library research Essay Example | Topics and Well Written Essays - 1250 words

Library research - Essay Example Jimenez, E., Tejeda, A., Blanco, J. and Martinez, E. â€Å"Application of lean production with VSM to the Rioja wine sector.† International Journal of Production Research 50.7 (2012): 1890-1904. Print. The article reports on a study on the use of lean production in wine sector in La Rioja. Its subject, lean production is a theory that aims at achieving economic utilization of resources towards optimum production levels, is a topic in operations management. The authors focus on lean production in a different sector from the theory’s traditional industry of application and investigate potential use of the lean production theory for economic utility of resources in the La Rioja’s wine sector towards optimum benefits. Operations management however defines management of processes in production and transportation of goods and services to users and this incorporates lean production concepts at the management’s production stage. The authors identify significance o f lean production in attaining competitiveness and efficiency and the fact that lean production has not been popular in many sectors. The theory establishes and eliminates all activities and processes in a production that do not benefit the process. Using Main Stream Mapping, the authors demonstrates applicability of lean production in La Rioja’s wine sector with the objective of making inference from the results. Lean production was developed in Japan’s motor vehicle industry but its advantages such as lower change periods, better working environments, quality workforce and accurate improvement initiatives has extended its popularity and application in other industries. Results show â€Å"reduction in raw materials† that â€Å"clarifying and quality test process† aids as well as lower inventory level for the organizations in the region’s wine sector. A number of benefits to the sector are attributed to the lean production strategy and examples inc lude lower overall production lead-time that can reduce by up to 60 percent, lower cost of raw materials from reduced volume, and this decrease can be as much as 13 percent of an organization’s expenditure on raw materials. The production approach also reduces losses and depreciation in materials’ value over the production process and facilitates communication between involved parties and departments in a production process. Improved efficiency in space and equipment utilization and better allocation of human resources across the production process are other identified benefits from the study. The results are valid because of their simulation in the target population with positive outcomes (Jimenez, Perez, Blanco and Martinez 1890- 1902). The article demonstrates the role of operations management, through lean production, in organization’s production efficiency and profitability. It identifies efficiency through improvements in production activities and processe s such as economical utility of time, space and human resource and improved quality that is also a result of the efficiency. This corresponds to the overall management objective, considering operations management as a branch of management, of reducing overall costs and improving overall revenues. The article therefore explains the role of oper

Special Education Classroom Essay Example for Free

Special Education Classroom Essay The purpose of this study is to know whether or not the Discrete Trials Training, one of the main strategies under the Applied Behavior Analysis of Lovaas, is an effective and applicable strategy for special children students especially those who are severely mentally handicapped. Knowing whether or not this strategy is effective for special children, this could be considered as the immediate instruction that will be used by teachers for special children who are mentally handicapped. This study will look into whether there would be progress on the development of a mentally handicapped child when applying the Discrete Trials Training; if results will show that there are improvements on the performance of the student, then this study could be considered as a reference to support the strategy’s effectiveness. Information in this literature review was gathered through the accessibility of various online resources. The online libraries for different researches such as Questia and ERIC libraries were used as search engines to provide various abstracts and overviews of researches about discrete trial training. This literature review also made use of online libraries that specifically contain researches in line with special education. These online sources are Research Autism, Holding Thresholds, Down Syndrome Online, Central Valley Autism Project and Comprehensive information on Autism, Autism Spectrum, and Consulting Services. Different researches that are found to be helpful for this literature review were accessed through these websites. Aside from online research libraries, there are also information used in these literature reviews that were accessed through the website of a university, the University of Wisconsin-Stout. The main motive in conducting such a review is to prove whether the discrete trial training strategy of teaching is an effective way for special children particularly those who have difficulty in generalization of ideas and concepts. Historical Overview It has always been a challenge for special education teachers or instructors to develop new and innovative ways to help special children learn considering their mental capabilities. Special children are called special because they have special and different needs. The demand of educators of special children to posses the most effective strategy in promoting development in the mental thinking of a child is the primary reason why this literature review is done. At this point, there are many strategies that have been discovered by different people, but the question remains: Which one would be the most effective strategy to use? One of the many strategies that could be used in special education classes is Discrete Training Trials which is the main strategy of the Applied Behavior Analysis approach created by Lovaas (Discrete trial training, 2010). If a number of researches have already been done to prove that this strategy would be most effective for the mental development of a special child then more and more schools could adopt this strategy into their own so that the development of a special child can be assured. Relevant Theoretical Literature Since there are a number of strategies that have been developed, the search for the best and most effective strategy to implement inside the classroom is what this review is all about. The strategies that have been formulated have their basis on different learning theories. The Discrete Trial Training strategy is one of the many Applied Behavior Analysis (ABA) approaches. In one literature review, the different behavioral approaches were examined to have their basis on the behavioral theory of Skinner (Benedict, 2007). Considering the behavioral theory of Skinner, Lovaas developed the Discrete Trial Training as a strategy that upholds the view of behaviorists that learning could be acquired through the use of positive and negative reinforcement (Benedict, 2007). This literature reviewed that the learning theory basis of the Discrete Trial Training under the Applied Behavior Analysis is grounded on the behaviorist learning principle which make use of imitation and reinforcement. This literature also reviewed that the children with special needs who experienced such mode of learning had noticeable development (Benedict, 2007). Applied Behavior Analysis in one study is mentioned to be the study of behavior and the manipulation to achieve a desired behavior and reduce and eventually remove an undesired behavior (Choutka et al. , 2004). With the Discrete Trial Training as one of its subsets, this particular strategy is said to monitor skill acquisition by undergoing a one-on-one instruction (Choutka et al. , 2004). The study also talked about how this particular strategy lacks research to support the reliability and effectiveness of such strategy. Relevant Research There has been an occurring question as to whether which strategy to implement is most effective for special children. In one study of the proponent of the discrete trial training strategy, Dr. O. Ivar Lovaas conducted behavior modification treatments for children with autism and after post treatment, results showed progress in the children’s comprehension and mental development were undoubtedly apparent (Lovaas, 1987). Results also manifested that this type of procedure could be used for other disorders that children may have, one of which could be schizophrenia (Lovaas, 1987). It is also found in one literature that studied the effectiveness of the discrete trial training for the treatment of children with autism. It is said in this study that the discrete trial training method could be used to advance children’s skills and at the same time manage their corresponding negative behavior (Smith, 2001). This research gathered all the necessary information regarding the basic steps of the discrete trial training, the time frame that each child must undergo the said strategy and what other strategies that could be combined with the use of the discrete trial training to further strengthen the development of the child (Smith, 2001). It is also discussed in this study that to effectively implement the discrete trial training strategy inside the classroom, teachers should undergo intensive and specialized training (Smith, 2001). Results showed that though the discrete trial training is a necessary strategy to help children with autism in their mental development, this strategy alone would not be sufficient (Smith, 2001). Though this may be the result of such studies, the researcher believed that there should be more studies and evaluation of the said strategy to further enhance and improve this particular strategy. This study of Smith showed the demand for a thorough evaluation and study of the effectiveness of the discrete trial training as a strategy in the mental development of a child. Another study examined and reviewed other studies, researches on the effectiveness of the discrete trial training as one of the treatment programs for the development of children with autism. This study reviewed how the applied behavior analysis method, most specifically the discrete trial training, is used to treat children with autism (Tews, 2007). After reviewing various studies and results, the review concluded that the method under the applied behavior analysis which is the discrete trial training is one possible strategy to help children with autism (Tews, 2007). Another study discussed the use of the discrete trial training to activate the spontaneity of special children’s response (Feeley and Jones, 2008). The study discussed how the discrete trial training provides much possibility to teach children in such a short span of time by using reinforcements to strengthen positive responses (Feeley and Jones, 2008). Results showed that the effectiveness of a strategy should not solely rely on which skill to attend to, rather consider which skill a child must acquire immediately (Feeley and Jones, 2008). Implications for Practice These researches showed that there is a need to continuously study and evaluate strategies and programs that would be implemented inside the special education classrooms. The researches showed inconsistent results, which give it more reason to further give emphasis on the study whether the discrete trial training is indeed an effective strategy to improve the mental development of a special child. Though there have been numerous studies and researches about the effectiveness of such strategy, these studies also pose questions that seem to be unanswered until now. This only implies that though this strategy has already been implemented to other special education classrooms, the inconsistency of the results should be considered as a sign that this strategy is not applicable for every child. Implications for Inquiry Though there are a number of studies about the effectiveness of the discrete trial training strategy to improve the mental development of a child with special needs, there is a noticeable inconsistency with the results of these studies conducted. This means that there is still a great deal of further research to be done and consistent results should be seen to prove that discrete trial training is indeed an effective strategy to use for the mental development of a special child. Summary The studies that are cited in this review of literature examined whether the discrete trial training is an effective strategy to use for the mental development of a child with special needs. In this study, there will also be adaptations as to how this strategy is implemented to special children in other researches. There will be interventions using the discrete trial training for the development of special children. Before and after the discrete trial training is implemented, the performances of each child will be compared and the result of this comparison will serve as the findings and conclusion of this study. This study would most likely be the same as that of previous studies as regards to the effectiveness of the discrete trial training; however most of these studies require further studies as well. References Benedict, C. S. (2007) Communication intervention for children with autism: a literature review, Retrieved from http://www. uwstout. edu/static/lib/thesis/2007/2007benedictc. pdf Choutka, C. , Doloughty, P. T. and Zirkel, P. A. (2004) The discrete trials of applied behavior analysis for children with autism: outcome-related factors in the case law. Questia, 38. Retrieved from http://www. questia. com/googleScholar. qst;jsessionid=MDDf7QMp2FwKnvN1r83h HlgdnDzL36BblJL6C3hLKd1TLTLcFgs! 1115883797! 2083947951? docId=5006551916 Discrete Trial Training (2010, May 20). Retrieved from http://www. researchautism. net/interventionitem. ikmlprintra=92infolevel=4 Feeley, K. and Jones, E. (2008) Teaching Spontaneous Responses to a Young Child with Down Syndrome, 12. Retrieved from http://www. downsyndrome. org/case- studies/2007/case-studies-2007. pdf Lovaas, O. I. (1987) Behavioral Treatment and Normal Educational and Intellectual Functioning in Young Autistic Children, 55 (1), pp. 3-9. Retrieved from http://www. cvapinc. org/files/1987_Lovaas_Study. pdf Smith, T. (2001) Discrete trial training in the treatment of autism, Retrieved from http://petemolino. com/uploads/Smith_-_DTT_in_Tx_of_Autism. pdf Tews, L. (2007) Early intervention for children with autism: methodologies critique. Education Resources Information Center (ERIC), Retrieved from http://www. eric. ed. gov/ERICWebPortal/custom/portlets/recordDetails/detailmini. jsp _nfpb=true_ERICExtSearch_SearchValue_0=EJ812650ERICExtSearch_Searc Type_0=noaccno=EJ812650 Tews, L. (2007) Research: early intervention for children with autism: methodologies critique. Healing Thresholds, 35 (1), Retrieved from http://autism. healingthresholds. com/research/early-intervention-children-autism methodologies-critique

Quantization process

Quantization process Quantization is a process of mapping an infinite set of scalar or vector quantities by a finite set of scalar or vector quantities. Quantization has applications in the areas of signal processing, speech processing and Image processing. In speech coding, quantization is required to reduce the number of bits used for representing a sample of speech signal there by the bit-rate, complexity and memory requirement can be reduced. Quantization results in the loss in the quality of a speech signal, which is undesirable. So a compromise must be made between the reduction in bit-rate and the quality of speech signal. Two types of quantization techniques exist they are: scalar quantization and vector quantization. Scalar quantization deals with the quantization of samples on a sample by sample basis, while vector quantization deals with quantizing the samples in groups called vectors. Vector quantization increases the optimality of a quantizer at the cost of increased computational complexity and memory requirements. Shannon theory states that quantizing a vector will be more effective than quantizing individual scalar values in terms of spectral distortion. According to Shannon the dimension of a vector chosen greatly affects the performance of quantization. Vectors of larger dimension produce better quality when compared to vectors of smaller dimension and in vectors of smaller dimension the transparency in the quantization is not good at a particular bit-rate chosen [8]. This is because in vectors of smaller dimension the correlation that exists between the samples will be lost and the scalar quantization itself destroys the correlation that exists between successive samples so the quality of the quantized speech signal will be lost. Therefore, quantizing correlated data requires techniques that preserve the correlation between the samples, such a technique is the vector quantization technique (VQ). Vector quantization is the simplification of scalar quantization. Vectors of larger dimension produce transparency in quantization at a particular bit-rate chosen. In Vector quantization the data is quantized in the form of contiguous blocks called vectors rather than individual samples. But later with the development of better coding techniques, it is made possible that transparency in quantization can also be achieved even for vectors of smaller dimension. In this thesis quantization is performed on vectors of full length and on vectors of smaller dimensions for a given bit-rate [4, 50]. An example of 2-dimensional vector quantizer is shown in Fig 4.1. The 2-dimensional region shown in Fig 4.1 is called as the voronoi region, which in turn contains several numbers of small hexagonal regions. The hexagonal regions defined by the blue borders are called as the encoding regions. The green dots represent the vectors to be quantized which fall in different hexagonal regions and the red dots represent the codewords (centroids). The vectors (green dots) falling in a particular hexagonal region can be best represented by the codeword (red dot) falling in that hexagonal region [51-54]. Vector quantization technique has become a great tool with the development of non variational design algorithms like the Linde, Buzo, Gray (LBG) algorithm. On the other hand besides spectral distortion the vector quantizer is having its own limitations like the computational complexity and memory requirements required for the searching and storing of the codebooks. For applications requiring higher bit-rates the computational complexity and memory requirements increases exponentially. The block diagram of a vector quantizer is shown in Fig 4.2. Let be an N dimensional vector with real valued samples in the range. The superscript T in the vector denotes the transpose of the vector. In vector quantization, a real valued N dimensional input vector is matched with the real valued N dimensional codewords of the codebook Ci , the codeword that best matches the input vector with lowest distortion is taken and the input vector is replaced by it. The codebook consists of a finite set of codewords C=Ci,, where , where C is the codebook, L is the length of the codebook and Ci denote the ith codeword in a codebook. In LPC coding the high bit-rate input vectors are replaced by the low bit-rate codewords of the codebook. The parameters used for quantization are the line spectral frequencies (LSF). The parameters used in the analysis and synthesis of the speech signals are the LPC coefficients. In speech coding the quantization is not performed directly on the LPC coefficients, the quantization is performed by transforming the LPC coefficients to other forms which ensure filter stability after quantization. Another reason for not using LPC coefficients is that, LPC coefficients have a wide dynamic range and so the LPC filter easily becomes unstable after quantization. So LPC coefficients are not used for quantization. The alternative to LPC coefficients is the use of line spectral frequency (LSF) parameters which ensure filter stability after quantization. The filter stability can be checked easily just by observing the order of the LSF samples in an LSF vector after quantization. If the LSF samples in a vector are in the ascending or descending order the filter stability can be ensured otherwise the filter stability cannot be ensured [54-58]. The angular positions of the roots of and gives us the line spectral frequencies and occurs in complex conjugate pairs. The line spectral frequencies range from. The line spectral frequencies have the following properties: Ø All the roots of and must lie on the unit circle which is the required condition for stability. Ø The roots of and are arranged in an alternate manner on the unit circle i.e., The roots of equation (4.6) can be obtained using the real root method [31] and is The coefficients of equations (4.6) and (4.7) are symmetrical and so the order p of equations (4.6) and (4.7) get reduces to p/2. Vector quantization of speech signals requires the generation of codebooks. The codebooks are designed using an iterative algorithm called Linde, Buzo and Gray (LBG) algorithm. The input to the LBG algorithm is a training sequence. The training sequence is the concatenation of a set LSF vectors obtained from people of different groups and of different ages. The speech signals used to obtain training sequence must be free of background noise. The speech signals used for this purpose can be recorded in sound proof booths, computer rooms and open environments. In this work the speech signals are recorded in computer rooms. In practice speech data bases like TIMIT database, YAHOO data base are available for use in speech coding and speech recognition. The codebook generation using LBG algorithm requires the generation of an initial codebook, which is the centroid or mean obtained from the training sequence. The centroid, so obtained is then splitted into two centroids or codewords using the splitting method. The iterative LBG algorithm splits these two codewords into four, four into eight and the process will be continued till the required numbers of codewords in the codebook are obtained [59-61]. The flow chart of LBG algorithm is shown in Fig 4.3. The LBG algorithm is properly implemented by a recursive procedure given below: 1. Initially the codebook generation requires a training sequence of LSF parameters which will be the input to LBG algorithm. The training sequence is obtained from a set of speech samples recorded from different groups of people in a computer room. 2. Let R be the region of the training sequence. 3. Obtain an initial codebook from the training sequence, which is the centroid or mean of the training sequence and let the initial codebook be C. 4. Split the initial codebook C into a set of codewords and where is the minimum error to be obtained between old and new codewords. 5. Compute the difference between the training sequence and each of the codewords and and let the difference be D. 6. Split the training sequence into two regions R1 and R2 depending on the difference D between the training sequence and the codewords and. The training vectors closer to falls in the region R1 and the training vectors closer to falls in the region R2. 7. Let the training vectors falling in the region R1 be TV1 and the training sequence vectors falling in the region R2 be TV2. 8. Obtain the new centroid or mean for TV1 and TV2. Let the new centroids be CR1 and CR2. 9. Replace the old centroids and by the new centroids CR1 and CR2. 10. Compute the difference between the training sequence and the new centroids CR1 and CR2 and Let the difference be . 11. Repeat steps 5 to 10 until . 12. Repeat steps 4 to 11 till the required number of codewords in the codebook are obtained. Where N=2b represents the number of codewords in the codebook and b represents the number of bits used for codebook generation. represents the difference between the training sequence and the old codewords, represents the difference between the training sequence and the new codewords. The quality of the speech signal is an important parameter in speech coders and is measured in terms of spectral distortion measured in decibels (dB). The spectral distortion is measured between the LPC power spectra of the quantized and unquantized speech signals. The spectral distortion is measured frame wise and the average or mean of the spectral distortion calculated over all frames will be taken as the final value of the spectral distortion. For a quantizer to be transparent the mean of the spectral distortion must be less than 1 dB without any audible distortion in the reconstructed speech. But the mean of the spectral distortion is not a sufficient measure to find the performance of a quantizer, this is because the human ear is sensitive to large quantization errors that occur occasionally. So in addition to measuring the mean of the spectral distortion it is also necessary to have another measure of quality which is the percentage number of frames having a spectral distorti on greater than 2dB and less than 4dB and the percentage number of frames having a spectral distortion greater than 4dB. The frames having spectral distortion between 2 to 4dB and greater than 4dB are called as outlier frames [54]. In order to measure objectively the distortion between the quantized and unquantized outputs, a method called the spectral distortion is often used in narrowband speech coding. For an ith frame the spectral distortion (in dB), is given by equation (4.19). (4.19) Where and are the LPC power spectra of the unquantized and quantized ith frame respectively. The frequency f is in Hz and the frequency range is given by f1 and f2. The frequency range used in practice for narrowband speech coding is 0-4000 Hz [12, 33]. The conditions for transparent speech coding are: Ø The average or mean of the spectral distortion (SD) must be less than or equal to 1dB. Ø There must be no outlier frames having a spectral distortion greater than 4dB. Ø The number of outlier frames between 2 to 4dB must be less than 2%. These three conditions are required to evaluate the performance of a quantizer. At a given bit-rate, an optimization process has to be carried out so as to obtain better performance i.e., accepting a large average spectral distortion for a few outliers. In the design of a vector quantizer instead of using the mean squared error (MSE) distance measure the weighted LSF distance measurement is used. This is done to place emphasis on the low frequency LSFs and on the LSFs with higher power spectrum. The weights used can be of two types they are: static or dynamic [54]. Ø Fixed or Static weights : These are used to place emphasis on the low frequency LSFs in order to account for the sensitivity of human ear for low and high frequency LSFs. Ø Varying or Dynamic weights : These are used to place emphasis on the LSFs with high power spectrum. There exist a number of vector quantization techniques each one is having its own advantages and disadvantages. Each technique is developed to decrease the parameters like spectral distortion, computational complexity and memory requirements. The vector quantization techniques that exist are the Split Vector Quantization (SVQ) technique, Multistage Vector Quantization (MSVQ) technique, Split-Multistage Vector Quantization (S-MSVQ) technique and Switched Split Vector Quantization (SSVQ) technique. As marketability and cost of a product depends on the complexity and memory requirements, the performance of the vector quantization techniques is measured in terms of spectral distortion in decibels, computational complexity in kilo flops per frame and memory requirements in floats. The performance of a vector quantization technique mainly depends on how efficiently the codebook is generated. The codebook can be generated efficiently using a large training set and using more number of bits for codebook generation. The goal involved in the design of each vector quantization technique is to make the technique to use more number of training vectors and less number of bits for codebook generation there by the spectral distortion, computational complexity and memory requirements can be reduced. It has been observed that as the number of bits used for codebook generation decreases the computational complexity and memory requirements decreases but the spectral distortion increases, this increase in spectral distortion can be reduced by increasing the number of training vectors used for codebook generation [62-71]. The block diagram of an Unconstrained Vector Quantizer (UVQ) is shown in Fig 4.4. Unconstrained Vector Quantization technique is the most awful vector quantization technique used for achieving lowest distortion at a given bit-rate and dimension. In LPC-10 the order of the filter chosen is 10 and so the length of each LSF vector will be 10. In Unconstrained Vector Quantization technique the quantization is done on vectors of full length i.e., using 10 samples of an LSF vector. From Fig 4.4 S1, S2, S3Sn are the input LSF vectors to be quantized using the Unconstrained Vector Quantizer. The main advantage of this vector quantization technique is that it is expected to give lowest quantization distortion at a given bit-rate as the correlation that exists between the samples of a vector is preserved. But the disadvantage with this quantization technique is that as vectors of full length are used, at higher bit-rates the computational complexity and memory requirements increases in an exponential manner making it impractical for applications requiring higher bit-rates. Another problem with this quantization technique is that at higher bit-rates the size of the codebook will be large and the generation of the codebook for this type of quantization technique will be difficult on general purpose computers as the memory available with them is limited. So the number of training vectors used for codebook generation must be limited in number or the length of each vector must be reduced. In practice on general purpose computers the codebook cannot be generated even with train ing vectors less than the number of codewords in a codebook at higher bit-rates. But the number of training vectors required to generate the codebook must be large than the number of codewords in a codebook otherwise there will be too much over fitting of the training set [54]. The computational complexity and memory requirements of a b bit, n dimensional vector quantizer are calculated as follows [54]: Ø To calculate the mean square error (MSE) between two vectors of n dimension, n subtractions, n multiplications and n-1 additions are required. So a total of 3n-1 flops are required. Ø To search a codebook of 2b code vectors, (3n-1)2b flops are required in addition to the minimum distortion search requiring 2b-1 flops. Ø So the number of computations made by a b bit, n dimensional vector quantizer is Total complexity = (3n-1)2b + 2b-1 = 3n2b-1 flops per vector. (4.24) In the computing the complexity each addition, multiplication and comparison is considered as one floating point operation. So a b bit n dimensional vector quantizer requires a codebook of 2b code vectors, it needs to store n2b floating point values, it computes 3n2b 1 flops per vector. Instead of the mean square error distance measure if weighted distance measure is used in the design of a vector quantizer the complexity increases from 3n2b 1 to 4n2b 1 flops per vector. The computational complexity of an Unconstrained Vector Quantizer is given by equation (4.25) Where n is the dimension of the vector b is the number of bits allocated to the vector quantizer. The Memory requirements of an Unconstrained Vector Quantizer is given by equation (4.26) Exhaustive search vector quantizers achieve lowest distortion at the expense of complexity and memory requirements at higher bit- rates. So to make the vector quantizers more practical for vectors of larger dimension and higher bit-rates structural constraints are imposed on the design of a vector quantizer or codebook. One way of achieving this is to decompose the codebook into a Cartesian product of smaller codebooks i.e., C = C1 * C2 * C3 . ..*Cm. The advantage with smaller codebooks is that the computational complexity and memory requirements can be reduced to a very great extent. This is because the number of bits used for codebook generation will be divided among the sets of the decomposed codebook [12, 18]. Examples of product code vector quantization techniques are Split Vector Quantization (SVQ), Multistage Vector Quantization (MSVQ), Split-Multistage Vector Quantization (S-MSVQ), Switched Split Vector Quantization (SSVQ). In this thesis two product code vector quantization techniques are proposed they are: Switched Multistage Vector Quantization (SWMSVQ) and Multi Switched Split Vector Quantization (MSSVQ) techniques [54, 72]. The main disadvantage of Unconstrained Vector Quantizer is that the complexity, memory requirements are very high and the generation of codebook is a very difficult task as vectors of full length are used for quantization without any structural constraint. As a result more number of training vectors and bits cannot be used for codebook generation. With these constraints the quantizer cannot produce better quality quantized outputs. So to improve the performance of Unconstrained Vector Quantization technique a well known technique called Split Vector Quantization has been developed. The concept behind Split Vector Quantization is that, in it vectors of larger dimensions are splitted into vectors of smaller dimensions and the bits allocated to the quantizer are divided among the splits (parts). Due to splitting the dimension of a vector gets decreased hence more number of training vectors and bits are used for codebook generation. As a result the performance of quantization is increas ed, the complexity and memory requirements are reduced. But the main disadvantage with this technique is that, due to splitting the linear and non linear dependencies that exist between the samples of a vector will be lost and the shape of the quantizer cells will be affected. As a result the spectral distortion increases slightly. This increase in spectral distortion can be compensated by increasing the number of training vectors and using more number of bits for codebook generation. The number of splits in this type of quantizer must be limited in number otherwise the vector quantizer will act as a scalar quantizer. In Split Vector Quantization the training sequence used for codebook generation will also be splitted into vectors of smaller dimension and each split of the training sequence is used to generate separate sub codebooks, there by independent vector quantizers exist and the bits must be allocated to each of them. As a result less number of bits will be available at each quantizer, the computational complexity and memory requirements gets reduced as they depend on the number of bits allocated to the quantizer and on the dimension of the vector to be quantized. The block diagram of a three part Split vector quantizer is shown in Fig 4.5. From Fig 4.5 it can be observed that a vector S1 of dimension n is quantized by splitting it into sub-vectors S11, S12, S13 of smaller dimensions. Each of these sub-vectors are quantized using their respective codebooks. In this work the order of the filter is taken as 10 and so the LSF vector contain 10 samples and these 10 samples are splitted into three parts of 3, 3, 4 samples [54, 73-75]. From results of Split Vector Quantization technique it is proved that the computational complexity and memory requirements gets decreased when compared to Unconstrained Vector Quantization technique. So Split Vector Quantization technique is superior to Unconstrained Vector Quantization technique in terms of the computational complexity and memory requirements. In a Split Vector Quantizer of n dimension, SP splits, operating at b bits per vector. The vector space Rn will be splitted into SP subspaces or splits or parts of lower dimension then the dimension of each subspace will be and . The number of independent quantizers will be equal to the number of splits and the bits used for quantization are divided among the splits and is . Where is the number of bits allocated to each vector quantizer. The computational complexity of a Split Vector Quantizer is given by equation (4.27) Where ni is the dimension of a sub-vector in ith split bi is the number of bits allocated to the ith split of a quantizer sp is the number of splits. The Memory requirements of a Split Vector Quantizer is given by equation (4.28) Multistage Vector Quantization is a modification of Unconstrained Vector Quantization technique. It is also called as Multistep, Residual or Cascaded Vector Quantization. Multistage Vector Quantization (MSVQ) technique preserves all the features of Unconstrained Vector Quantization technique and decreases the computational complexity, memory requirements and spectral distortion when compared to it. When compared to Split Vector Quantization technique, Multistage Vector Quantization technique shows significant improvement in the quality of the speech signal, by decreasing the spectral distortion, but at the expense of increased computational complexity and memory requirements. This is because Split Vector Quantization technique deals with vectors of lower dimensions while Unconstrained and Multistage Vector Quantization techniques deal with vectors of larger dimensions. So the complexity and memory requirements are less for Split Vector Quantization technique. Multistage Vector Quantizer is a cascaded connection of several vector quantizers, where the output of one stage is given as an input to the next stage and the bits used for quantization are divided among the stages connected in cascade [12, 14]. As a result the computational complexity and memory requirements get reduced when compared to Unconstrained Vector Quantizer. The generation of codebooks at different stages of a three stage MSVQ is shown in Fig 4.6. From Fig 4.6 it can be observed that the codebook at the first stage is generated by taking the training sequence as an input. At the second stage the codebook is generated using the quantization errors of the first stage, likewise the codebook at the third stage is generated using the quantization errors of the second stage. This process is continued for the required number of stages [76-80]. The block diagram of a three stage Multistage Vector Quantizer is shown in Fig 4.7. Its implementation requires the design of vector quantizers at each stage. In Multistage Vector Quantization the input vector s to be quantized is passed through the first stage of the vector quantizer so as to obtain the quantized version of the input vector i.e., . The quantization error or residual error at the first stage will be computed which is the difference of the input vector and the quantized version of the input vector. The quantization error at the first stage is given as an input to the vector quantizer of the second stage so as to obtain the quantized version of the error vector at the first stage i.e., . Likewise the quantization error at the second stage will be given as an input to the vector quantizer of the third stage so as to obtain the quantized version of the error vector at the second stage i.e., and this process can be continued for the required number of stages. Finally the decoder takes the indices Ii from each quantizer stage and adds the corresponding c odewords to obtain the quantized version of the input vector i.e., [54]. In a Multistage Vector Quantizer each stage acts as an independent vector quantizer and the total bits available for vector quantization will be divided among the stages. Then the complexity of a particular stage becomes, where bj is the number of bits allocated to the jth stage. This is less than the complexity of Unconstrained Vector Quantizer. Likewise the memory requirements at each stage are , which is less than the memory requirements of Unconstrained Vector Quantizer. The computational complexity of a Multistage Vector Quantizer is given by equation (4.29) Where n is the dimension of the vector bj is the number of bits allocated to the jth stage P is the number of stages The Memory requirements of a Multistage Vector Quantizer is given by equation (4.30) In order to improve the performance of Multistage Vector Quantization and Split Vector Quantization techniques a hybrid product code vector quantization technique called Split-Multistage Vector Quantization technique has been developed. Split-Multistage Vector Quantization technique is a hybrid of Multistage Vector Quantization and Split Vector Quantization techniques. At reasonable improvement in the quality of the output speech signal, Split-Multistage Vector Quantization technique provides the lowest spectral distortion, computational complexity and memory requirements when compared to Unconstrained Vector Quantization, Multistage Vector Quantization and Split Vector Quantization techniques [73-80]. The decrease in spectral distortion is due to summing of the quantized errors at each stage. In Split-Multistage Vector Quantization the dimension of the vectors to be quantized has been reduced by means of splitting. Likewise the bits used for quantization are also divided among the stages and among the splits of each stage. As a result the computational complexity and memory requirements get decreased when compared to Unconstrained Vector Quantization, Multistage Vector Quantization and Split Vector Quantization techniques. This is due to the decrease in the dimension of vectors, number of bits used for quantization at each stage and at each split of the vector quantizer. The generation of the codebooks at each stage of the Split-Multistage Vector Quantizer is similar to the codebooks generation at each stage of the Multistage Vector Quantizer. But the difference is that each stage of the Split-Multistage Vector Quantizer involves the generation of several sub codebooks. The number of sub codebooks generated at each stage is equal to the number of splits at that stage. In this work, Split-Multistage Vector Quantizer with three parts (splits) and three stages have been developed. The performance of quantization depends on the number of stages and on the number of splits at each stage. As the number of stages increases the quality of the quantized output can be increased, but there must be a limit on the number of stages and on the number of splits at each stage as the number of bits at each stage is limited. The allocation of the bits at each stage is shown in Table 4.1 and the allocation of bits to each split of a stage is shown in Table 4.2. From Ta bles 4.1 and 4.2 it can be observed that the minimum number of bits at each stage with three parts must be at least three. So with three parts (splits) and three stages, in Split-Multistage Vector Quantizer the number of bits at a frame cannot be reduced below 9 bits. The block diagram of a Split-Multistage Vector Quantizer with three parts and three stages is shown in Fig 4.8. The block diagram is similar to three stage Multistage Vector Quantizer except for the splits at each stage. In Split-Multistage Vector Quantizer each split is treated as a separate vector quantizer and the vectors at each split are quantized independently. The quantization mechanism involved in Split-Multistage Vector Quantizer is similar to the quantization mechanism involved in Multistage Vector Quantizer, except that in Split-Multistage Vector Quantizer at each stage the sub-vectors are quantized independently. Split-Multistage Vector Quantizer is a hybrid of Split Vector Quantizer and Multistage Vector Quantizer. The equations for computational complexity and memory requirements are derived from the complexity and memory requirement equations of a Split Vector Quantizer and Multistage Vector Quantizer. Equations (4.31) and (4.32) below are obtained from the equations (4.29) and (4.30) by including the splits (SP) at each stage with a summation term having limits from 1 to SP. The computational complexity of a Split-Multistage Vector Quantizer is given by equation (4.31) Where nji is the dimension of a sub-vector in jth stage ith split bji is the number of bits allocated to the jth stage and ith split of a quantizer P is the number of stages sp is the number of splits. The Memory requirements of a Split-Multistage Vector Quantizer is given by equation (4.32) Switched Split Vector Quantization (SSVQ) is one of the latest vector quantization techniques and is developed to improve the performance of Split Vector Quantization technique. Switched Split Vector Quantization technique is a hybrid of Switch Vector Quantization and Split Vector Quantization techniques and is used to exploit the linear and non linear dependencies that exist between the splits of a Split Vector Quantizer. In Switched Split Vector Quantizer initially the Switch Vector Quantizer partitions the entire vector space into voronoi regions and exploits the dependencies that exist across all dimensions of the vector space. Then a Split Vector Quantizer is designed for each of the voronoi regions. As a Split Vector Quantizer is adapted to the local statistics of the Voronoi region the sub optimalitys of the Split Vector Quantizer will be localized. In a Switched Split Vector Quantizer a number of vector quantizers are connected in parallel and it can be implemented in two wa ys: hard decision scheme and soft decision scheme. In hard decision scheme each vector to be quantized is quantized in only one of the codebooks connected in parallel, the selection of a codebook for quantization depends on the nearest codeword selected in the initial codebook. An initial codebook is one which is designed for the selection of a switch. The initial codebook is generated by the training vectors used for the generation of the codebooks at the vector quantizers connected in parallel. The number of codewords or centroids in the initial codebook is equal to the number of switches chosen or number of codebooks connected in parallel and these centroids are used to form the Switch Vector Quantizer. In soft decision sc

Social and Individual Responsibility in Frankenstein :: Social Responsibility in Frankenstein

Social and Individual Responsibility in Frankenstein    Mary Shelly wrote Frankenstein in a time of wonder. A main wonder was whether you could put life back into the dead. Close to the topic of bringing life back into the dead was whether you could create your own being, like selective breeding but a bit more powerful. Close to where Mary lived there was a man named Vultair was experimenting putting electricity through Frogs to see if they could come back to life. With that going on close to her as well as the fear of a revolution and the pressure on her to think of a ghost story it is not surprising she thought of a horror story that would still be popular in the 21st Century. Now I have explained where the story came from and why it is as it is I will explain the social responsibility it brings up and how it is still important today. Looking after something you create is one point it brings up. Frankenstein created his creature so he should have looked after it but instead just because he didn't like the way it looked he ran away. He never taught his creature anything so for all the creature knew it could have been okay to kill people and suchlike. That relates to today as some children who were not taught right from wrong by their parents watch films like Scream and I know what you did last summer where murdering seems cool as it involves Jennifer Love Hewit, Sarah Michelle Geller and Neve Cambell getting killed. The children watch these and think "I want to be like that scary guy with the mask" and they go and try to kill someone. If they do they get charged for the offence but many people think that the children's parents should be blamed as they never taught the child right from wrong and they didn't stop the child (sometimes as young as eight or nine) from watching the video which is rated eighteen or fiftee n. When the filmmakers hear about how their film was responsible for a death they never (except for once) take the film away from the public and what they usually do is make a less violent sequel, which isn't really helping anyone and less violence still is some violence. Teaching a child right from wrong is another point it brings up but I feel I have covered this point in the section above.

Essay --

Rachel Reed PHIL 389 Saint-Croix 10 February 2014 Question #7: Descartes’ Foundationalism In this paper I will describe the foundationalist structure of Descartes’ arguments in his work Meditations on First Philosophy. Foundationalism is the view that there are some beliefs are epistemologically basic and can be known without knowing anything else is true (Loeb, Lecture 1-14). For example, philosophers such as Descartes would acknowledge that geometric truths, such as 2 + 2 = 4, are so fundamental that they don’t need to be proven through argumentation. Thus, these truths can provide the basic foundation for further arguments. In my paper, I will show that two foundational claims of Descartes are first, the existence of the mind, and second, the existence of God. From these claims Descartes derives many others, including the argument for material objects and souls. As I lay out Descartes’ case, I will examine the philosophical soundness and validity of his foundationalist account, as well as its merits and potential weaknesses. In the end, I will conc lude that Descartes’ foundationalism, while alluring in its simplicity, does not survive deeper investigation. Descartes’ first foundational argument asserts that one can have knowledge of one’s own existence. The claim is essential to many arguments that follow because it survives his â€Å"Deceiver Hypothesis.† This hypothesis states that â€Å"there may be a powerful deceiver of supreme power who is deliberately and constantly deceiving me† (Med III, p. 17). This demonstrates that we cannot know, or be sure of, anything based on sensory experience alone. However, Descartes supports the idea that some things can be known entirely outside of sensory experience; through the use of logic and re... ...undational premises, such as the existence of God and the mind, do not provide indisputable groundwork for Descartes’ argument. First begging the question to prove the existence of the mind via dualism, and then conflating logic with cultural and personal ideals, these two tenets cannot stand on their own. In the case of Descartes’ Meditations on First Philosophy, foundationalism does not endure close scrutiny. Grade: B- General comments: Your paper doesn't really address the prompt. It does not discuss arguments that might be offered in favor of Foundationalism or discuss how effective such arguments might be, nor does it address the question of what arguments Descartes does offer. There's also little in the way of focused discussion of what you take to be the problem with the position. It seems like you started on a different prompt and switched part-way through.

Public Administrations Essay

The external environment is the highly complex macro-environment that influences the purposes and modes of operation of public organizations. The importance of the ability of public organizations in properly responding to the pressures by these external influences is crucial in maintaining the organization’s optimum functions (Mc Kinney & Howard, 1998). The external environment plays important role in the functioning of the organization. First, it provides demands and resources that trigger and sustain the organization. Second, it sets parameters for organizational activities and third, it belongs to one of the major places where organizational activities are judged. The three major components of the external environment are ecology, cultural setting and the political economy. There is interrelation between the components and change in the external environment cause change in the structure and internal processes of public administration. The changes influence the outputs of the organization. Public administration takes the central role in a political system. By studying each component and understanding why and how organizations behave and perform the way they do, public administrators are able to manage the external environment in order to make the organization function more accountably. The ecology of the government determines greatly what is to be done while the cultural setting helps identify the proper response to these particular demands. Political economy specifies how government officials exercise the power that is granted to them. At the executive level of an organization, leaders are asked to deal with the external environment that include the market organization works within, the competitors and the workforce fluctuations that may be present. At this level, individuals lead the organization in terms of the mission and the vision of the organization and they are in charge as well to strategically plan for the future (Rabin, 2003).

Organization And Management Essay

INTRODUCTION Control is the process of assuring the efficient accomplishment of enterprise objectives. In the turbulent environment faced by management, power and control is necessary to anticipate problems, measure performance against standards, take corrective actions for deviations from plans and if necessary, modify plans. The term control may have some negative connotations for some. In the management process, it is a facilitating function aiding the organization to accomplish the set objectives. The primary responsibility for exercising control rests with management at HQ division with the execution of plans. In an organization, control consists in verifying whether everything occurs in conformity with the plans adopted, the instructions issued and principles established. Its object is to point out weaknesses and errors in order to rectify them and prevent recurrence. It operates on everything, things, people, and actions. It is wrong to assume that only top management has the responsibility for power and control and that there is little need for control at lower levels of management. While the scope for control may vary to some extent depending upon the position of an employee in the hierarchy, all those who have responsibility for the execution of plans need to exercise control too. M/s Engineering Products is an engineering company, based in UK, manufacturing mechanical tools for various industrial manufactures .Due to the marketing trend and policy change, the company sometime in 1980 did some major deviations by closing and selling some units and presently in the trade of defense, industrial services and auto parts. The company is in the line of exporting components to different countries. It has processed for expansion, 50% of the employees are stationed in Western Europe and North America. Bulk of the sales is taken care by Western Europe and America and a very small portion by UK. AIMS AND OBJECTIVES The major prerequisites of control are two: a plan and a structure. a) Plan: controls must be based on plan. The more clear and complete the plans are the more effective controls can be; plans become the standards by which the actions are measured. b) Structure: There is need for a structure to know where the responsibility rests for deviations and corrective action, if any needed. As in the case of plans, the more clear and complete the organization structure is, the more effective control can be. Controls, to be effective, should share the following basic characteristics: Appropriate: Controls should correspond to an organization’s plans. Controls designed for a Management Executive are inappropriate for a supervisor Strategic: Control should serve a strategic purpose and provide spotlight on positive and negative exceptions at critical points. Acceptable: Controls will not work unless people want them to. They should be acceptable to those to whom they apply. Reliable and objective: Controls should be accurate and unbiased. If they are unreliable and subjective, people will resent them. THE POWER AND CONTROL PROCESS In the Engineering Products the control process used  Ã‚     involves three steps: (a) establishing standards. (b) measuring performance against these standards, and (c) reinforcing success/correcting deviations. a) Establishing Standards: Standards mean criteria of performance. Standards may be of many kinds and include verifiable goals set in qualitative or quantitative terms. Engineering Products has established standards in areas such as: (a) Profitability (b) Productivity (c) Market Share (d) Worker Performance (e) Innovation (f) Social Responsibility Standards are based on past performance, managerial judgment or scientific analysis. Standards are used to measure performance and judge success or failure. b) Measuring of Performance: Essentially, it is a comparison between â€Å"what is† and â€Å"what should be† the performance. Ideally, measurement should be done on a forward-looking basis to predict probable deviations from standards rather than merely be used as a post mortem exercise. c) Reinforcing Success/Correcting Deviations: When plans and organization structures are clear, it is easy to reinforce success and avoid failures. When deviations are noticed or apprehended based on warning signs, the reasons can be analyzed and appropriate corrective actions taken promptly. LITERATURE REVIEW POLICIES AND DESIGN CHOICES IN CONTROL Engineering Products are following three options in exercising control: centralization or delegation formal or informal direct or indirect preferences for one or a mix of all options are matters of judgment. Each option has relevance in a particular situation Centralization or Delegation Centralization is an approach where control is exercised by the HQ or the top management group.   Thus, functional autonomy will be lacking at operating levels. Delegation, on the contrary, manifests transfer of decision-making authority downward and outward within the formal structure. Sometimes, decision-making power is transferred downwards in a hierarchy prescribing limits on the scope and type of decisions. Centralized Control: makes it easier to coordinate the activities of various subunits/departments in an organization. seeks to achieve balance among various functions because the top management can be expected to have a broad organization-wide perspective. proves more useful because control will be in the hands of senior, experienced top executives. is necessary to meet extraordinary situations. is economical since duplication in activities and resource use can be avoided. Delegation and decentralization too have positive features: they relieve the top management from overload. motivate individuals to give better performance due to opportunities for individual freedom, discretion and control. contribute to the personal and professional development of managers.†¢ people at operating Direct or Indirect There are two ways of controlling. One way is to supervise subordinates’ activities closely, trace deviations to the persons responsible and get them to correct their practices. This is called indirect control The other way is to develop high quality managers who will properly understand and apply managerial principles, functions, techniques and philosophy, make few mistakes and initiate corrective actions, wherever necessary, themselves. This is called direct control. The higher the quality of managers and their subordinates, the less will be the need for indirect controls. Conflict and Negotiation Life is a never ending process of one conflict after another. Conflict has always been widespread in society but it is only recently that it has generated a lot of interest and has been the focus of research and study. Employees have become more vociferous in their demands for a better deal. Various departments in an organization face a situation full of conflicts due to a number of reasons like goal diversity, scarcity of resources or task interdependence etc. Negotiation is an attempt to find a solution that reconciles or integrates the needs of both parties who work together to define the problem and to identify mutually satisfactory solutions. In negotiation, there is open expression of feelings as well as exchange of task-related information. The most critical ingredients in successful negotiation are: 1 Definition of the problem should be a joint effort based on shared fact finding. 2 Problems should be stated in terms of specifics. 3 Discussions between the groups should consist of specific, non-evaluative comments and questions should be asked to elicit information. 4The groups should work together in developing alternative solutions. 5All agreements about separate issues should he considered tentative.   Without trust, each group will fear manipulation and may not reveal its true preferences. Secondly, integrative problem solving takes a lot of time and can succeed only in the absence of pressure for a quick settlement. Direct control hastens corrective actions, lightens the burden caused by indirect control and subordinates feel less concerned about superior’s subjectivity in rating their performance because in indirect control one would feel a close relationship between performance and measurement. METHODOLOGY The central HR function at Engineering Products had been placed on a different platform after the other units placed at different places are moving towards international integration. integration. A system is being formed for interaction of different managers of different units and how international postings to be managed HR department at HQ office desires to play a more forceful role rather than doing only doing routine administrative work. The Dynamics of Personnel/Human Resource Management (P/HRM) is a dynamic discipline as it mostly deals with ever-changing work settings, characterized by people having varied cultural, social and religious backgrounds, diverse goals, multifarious expectations and attitudes. The personnel scene itself has been changing quite dramatically over the years. State regulations, competitive pressures, unionization of employees, do exert a strong influence on the way the personnel function is carried out in various organizations. Over the years, employees have become more sophisticated in their demands for high quality work environments, adequate benefits, proper training and career growth opportunities. All these factors compel human resource professionals to look for ways to improve their interactions with employees, other managers and outside groups in order to maximize worker productivity and satisfaction. Changing Role of Human Resource in View of Social Factors: A number of environmental factors influence the work of HR office.They cannot perform  Ã‚   in a vacuum. These factors influence the organization through human resources. External factors separately or in combination can influence the HR function of any organization. The job of a HR manager is to balance the demands and expectations of the external groups with the internal requirements and achieve the assigned goals in an efficient and effective manner. The HR manager has to work closely with these constituent parts, understand the internal dynamics properly and devise ways and means to survive and progress. Local and State Factors State is the custodian of industrial and economic activities. The emergence of problems on the industrial front in the form of trade union movement, failure of many employers to deal fairly with workers, non-fulfillment of plan targets forced the states to intervene in human resource management and to enact various pieces of labor legislation.    Unions Unions have also gained strength. At present, these organizations constitute one of the power blocks in many countries. With the formation and recognition of these organizations, the issues relating to employee interests are no longer determined by the unilateral actions of management. These have to be discussed with union representatives invariably.   In consequence, the scope of managerial discretion in personnel activities has been narrowed down. Changing Work Values   Organizations must now advance from general affirmation and enthusiasm for the career development of their personnel to greater precision. The concepts and goals development programmes must be more precise, more widely understood, reflected in formal policy statements and translated into institutional and personnel practice. Alienation from the job, increasing counter-productive behavior, rising expectations and changing ideas of employees are some of the other factors responsible for the changing values and roles of human force. Consequently it has become imperative for the management to include  Ã‚   benefits to improve morale, introduce a machinery to redress grievances, encourage employee participation in decision-making and the like to pave the way for industrial betterment and to meet the ever increasing demands of workforce. Culture In Organization Every organization has some characteristics which are common with any other organization. At the same time, each organization has its unique set of characteristics and properties. This psychological structure of organization and their sub-units is usually referred to as Organizational Culture. Organizational culture is a relatively enduring quality of the internal environment that is experienced by the members, influences their behavior, and can be described in terms of values of a particular set of characteristics of the organization. Organizational culture is the set of characteristics that describe an organization and that (a) distinguish one organization from other organizations; (b) are relatively enduring over time and (c) influence the behavior of the people in the organization. Organizational Culture is a relatively uniform perception held of the organization, it has common characteristics, it is descriptive, it can distinguish one organization from another and it integrates individual, group and organization system variables. ORGANISATIONAL STRUCTURE. Organization structure refers to the formal, established pattern of relationships amongst the various parts of a firm or any organization. The fact that these relationships are formal implies that they are deliberately specified and adopted and do not evolve on their own. Of course, it may sometimes happen that given an unusual situation, new working relationships may evolve and which may later be adopted as representing the formal structure.   Only when relationships are clearly spelled out and accepted by everyone, can they be considered as constituting a structure. This does not mean that once established, there can be no change in these relationships. Changes may be necessary with passage of time and change of circumstances, but frequent and erratic changes are to be avoided. References Peters, Thomas, J. and Waterman, Robert H., 1999. Management of Development Programmes, Harper and Row: New York. Elbing, A.1998. Behavioral Decisions in Organizations, Scott Foresman: Glenview. 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Wendell L French et al) Business Publications Inc., Dallas (1998). Chris Argyris, Management and Organization Development: The Path form X4 to YB, McGraw Hill, New York (1991). Beckhard, R. Harris, R. T Organization transitions: Managing Complex Changes, Addison Wesley (1997). Cascio, W.F., Fundamentals of Modern Organisations, McGraw-Hill Book Company, New York,1992 Purecell J.,Boxall P., Organisational Management, Plagrave, Macmillan, New York,2003