Maritime security requirements Essay Example for Free

Maritime security requirements Essay Maritime security refers to the security offered to the shipping industry in a country. It refers to the measures taken by the government to ensure that the port, the employers, the employees as well as the equipments in the ports are well guarded from threats which face them. The ports face risks which may arise due to unlawful acts done on them or even on the persons stationed in them. Strategic planning to cub any uncertainty is thus essential for the well being of a nation and its citizens. The security of a country like the United States is dependent on the security of the world’s oceans. There are different forms of threats which face the maritime security. To attain maritime security, it is thus vital to combine the efforts of both the public and private sectors globally. Maritime security may also be used to refer to the comprehensive security for the international shipping which started functioning on July 2004. It forms part of the IMO’s activities. This is a security practice code which is exercised in ports which is meant to compliment the international ships and the port equipments security. The IMO/ILO code was implemented to offer security for the whole port area and was approved in March 2004. IMO is an acronym for international maritime organization while ILO refers to the international labor organization. IMO code of practice is not binding and should not replace the laws and regulations of a country. It does not affect the fundamental rights and principles of the workers as provided by the ILO document or the workers access to the ports or terminals and even the vessels. The IMO is thus used to provide guidance to member countries on how to deal with matters relating to security in the ports. It also helps in identifying a government’s roles and responsibilities as well as for those of the employers and their employees (Pugh, 1994). The main objective of the formation of the code of practice relating to security on the ports was to enable all the stakeholders including the government minimize the risks which may be incurred by the port due to unlawful acts in the port. It was also intended to provide a common basis of approach to security on ports amongst affiliated states. This code also sought to extend the area covered by port security to include the whole port. Threats and measures used to combat maritime security Maritime insecurity has been on the rise for the past few years with terrorists using this domain to attack most countries. This has called for strict measures to ensure such attacks are reduced or eliminated. For maritime security to be attained, a number of plans have to be put in place to address the different forms of maritime security. These plans form the basic requirements for successful attaining of maritime security. One of the plans which are vital is a national plan to create and achieve Maritime’s domain awareness. After creating a national awareness, a global integration of intelligence is important and hence its plan. A single country may not be in a position to fight and lead to maritime security thus the need to cooperate with other countries. Other plans are the maritime infrastructure plan and the maritime security plans. The security plans includes the transportation plan, the commerce plan and the facilities plan. Before the formulation of these plans, the country needs to understand the threats which maritime environment faces (Hawkes, 1989). For a country to formulate the measures it has to take to attain maritime security, it needs to evaluate the threats the oceans are exposed to which in turn affect the countries stability. Different countries have adopted different measures to ensure that their ports are safe. The most common threats that face the oceans include the threat to the maritime security itself. Today’s maritime environment is marked by complexity and ambiguity thus making it difficult to maintain and protect it. This is more pronounced in the maritime environment. This is enhanced by the operations carried out at the sea which exposes the countries to acts of terrorism. These kinds of attack are more dangerous and pure military actions may not be effective in fighting them. They thus require other measures and the countries exposed to such threats must device ways to combat them. Advancement in telecommunications and the expansion of the international and commercial logistics have led to an increase in the range and also the effects which arise due to the terrorist attacks. They have made it possible to enter even the borders considered to be most secure with great speed and for greater distances. Terrorists take advantage of such capabilities and cause great damage globally and also in the political and economic environment (Higgie, 2005). Maritime domain could also be used to export illegal goods to other countries thus posing a threat to the other country. Strict measures are thus required to cub this and to ensure that all transported goods are of high standards and are not harmful to the citizens in a country. Terrorism acts are rampant in the maritime domain. Fighting these threats is becoming more difficult since different terrorist groups from different countries have joined together due to the improved telecommunications. They also operate under the shadows thus making it hard to fight them. Cooperation amongst the member states is required to maintain maritime security. The increasing international trade through the maritime domain has also led to increased maritime related criminal activities. Such activities include smuggling of drugs and weapons to or out of a country. People smuggling has also been on the rise in the maritime domain especially in areas characterized by heavy commercial seas activities. In countries with unstable political environment, this is more rampant. Illegal immigration through the sea has been rampant in the recent past thus posing a major threat to maritime security and also to the economic and political stability of a country (Pugh, 1994). The main objective for the countries faced by these maritime threats is to eliminate or reduce the activities which pose these threats. One of the major steps towards preventing the terrorist attacks and other criminal and unlawful acts is through monitoring and controlling or patrolling the maritime borders. High seas areas which are of national interest should be safeguarded. Detecting and stopping criminal activities before they are committed is the main aim of the countries exposed to maritime threats. To be effective in detecting the threats to maritime security, the country has to be aware of the threat and have detective capabilities. Such knowledge helps in deterring and also defeating adversaries early enough before much damage have been caused (Higgie, 2005). Another objective of a country in cubing maritime insecurity is by protecting the critical maritime infrastructure and also the related population centers. All the main and important infrastructures both physical and network operations should be guarded by military facilities for security purposes. Population should also be controlled so as to make it difficult for people to collect information which could be used in committing criminal maritime acts. Overcrowding in the ports makes it easier for illegal immigration and smuggling of goods and people. The responsibility of protecting these infrastructures should be taken up by both the private and public sectors. A country should also work towards minimizing the damages which may arise in the maritime domain. Safeguarding the maritime domain and their resources from exploitation is another aim of a country (Pugh, 1994). For a country to attain maritime security, there are a number of things or requirement that it has to meet. There are no international standards which have been set to control, regulate or maintain maritime security and thus a country has to set its own standards and work towards maintaining maritime securities. However, as mentioned earlier the international maritime organization has set guidelines which a country may apply in dealing with maritime related issues. Attaining maritime security is a continuous activity especially with the emergence of different activities which are posing threats to maritime security. International cooperation and coordination is vital in achieving maritime security. Information sharing and also intelligence assistance are also vital in effective elimination of maritime insecurity. Public and private sectors should also work in cooperation to attain and secure maritime security (Hawkes, 1989). The minimum requirement is the acquiring of an identification card of maritime security. This card shows that the holder has been checked from his background and thus can work in the port unescorted. This card covers the seafarers and the persons working or who supply oil and gas facilities offshore. This card mainly operates in the Australian waters. For one to qualify to be given unmonitored access to the maritime security zone, one should not have an adverse criminal record and should be a citizen. If he is not a citizen, he must have a right to work in the country. Automatic identification systems are also a requirement in maritime security. These systems are supposed to be installed on commercial vessels which are on international voyage. This may include vessels used in fishing and even passenger vessels which are over 65’ in length (Office of the Press Secretary, 2003). Prescreening cargo before lading is also another requirement for attaining maritime security. All international cargos should be examined before they are allowed into a country to ascertain their safety and to eliminate possibilities of threats. Procedures to enforce action against a cargo suspected to be carrying illegal commodities or terrorists into or out of a country should be formulated. These procedures should be implemented and enforced to reduce the possibility of a repeat of the same action. Seizing cargo procedures should also be implemented and streamlined for easier confiscation of the goods or persons (Bahar, 2007). One of the vital requirements in achieving maritime security is by enhancing international cooperation amongst the member states. The oceans cover more than two thirds of the earth’s surface. As such, no single country can achieve maritime security on its own. Cooperation with other countries is thus a vital tool in achieving maritime security. Countries which are interested in attaining maritime security and are willing to fight terrorism and other maritime crime come together to device ways to combat these crimes. These countries should seek to understand the threats and prioritize them according to there urgency. Unified actions and plans are then implemented to reduce maritime insecurity (Hawkes, 1989). To enhance this cooperation, the nations should endeavor to standardize international security to ensure that all the goods and people going to a country through the maritime domain are not a threat to the citizens that country. The use of automated systems should be implemented to register maritime vessels, their ownership and also their operations. The crew operating them should also be registered as well as the cargo being transported to enhance transparency. The member states should also develop a mutual fund ensure effective and efficient implementation of measures to interdict criminals before the damages are done. The means of rapid exchanges amongst the government and intelligence agencies should also be enforced by the law and suspected criminals should be persecuted. Streamlined procedures should also be adopted to verify vessels nationality so as to take appropriate enforcement measures on time (Bahar, 2007). Another requirement for maritime security is the foreign vessel security plans. This requirement has a provision that members of SOLAS are not required to produce their security plans to coast guards for their vessels to be approved. However, those who are not affiliated to this group of SOLAS have to produce their security plans before being allowed to enter into a country. Their security plan should also comply with the measures which are stipulated in the trade agreement. SOLAS is an acronym for safety of life at seas. A vessel not complying with these requirements is denied entrance to a country. This is in operation in the united stated (Office of the Press Secretary, 2003). Vessel security plans is also another requirement for ensuring maritime security. All vessels are required to have security plans before being allowed to move in the American waters. This requirement however exempts vessels which carry less than one hundred and fifty passengers without considering the number of overnight passengers in the vessel. Other vessels exempted in this provision are the drilling units which are non self propelling and are operated offshore. Industrial vessels like the dredges are also exempted from the security plans provision for vessels. Facilities are supposed to come up with their individual plans for security. Exempted in this requirement are facilities which only service the passenger vessels but whose vessels do not carry passengers. Others are the public access facilities which are purely used for recreation and retail purposes by the public. Vessels which the public uses for entertainment and tourist purposes are also exempted. The owners and the operators of these exempted facilities are held responsible and are supposed to implement necessary security measures. These measures are supposed to comply with the area security plan (Office of the Press Secretary, 2003). These requirements are made possible and viable by offering assistance and training to the maritime security operators. Economic assistance is also vital in ensuring that maritime security among the nations is attained. Another way that the governments have done to ensure maritime security is maintained is by expanding the international port and maritime security officer programs. This ensures that the diverse threats posed by unlawful acts are minimized and awareness is created. The number of agency attaches has also been increased (Pugh, 1994). Deploying layered security is also another requirement for ensuring that maritime security is achieved and maintained. A system of layered security ensures that the capabilities of the member governments and those of commercial interests are integrated globally. Both the public and the private sectors can help in controlling terrorism activities if they could act in concert. These two sectors may use diverse though complementary measures to eliminate the criminal acts instead of relying on the government alone. A layered approach is not a static approach but keeps on being improved. These changes serve to create uncertainty thus reducing the possibility of terrorist attacks. This approach is mainly used in the most vulnerable areas like the marine transportation sector, passenger and cargo ferrying, staff and also in conveyances. It is also effective in ports and also the route of transportation (Bahar, 2007). Maximizing domain awareness is a vital tool in eliminating threats and maintaining peace and security in the maritime environment. Understanding the trends and all the events in a domain helps to predict likely events and also the possible threats facing a certain domain. Prior knowledge of the threats is important for securing the security of a maritime domain and also helps in reducing detrimental events. In trying to gain knowledge of the possible threats, the government and all the stakeholders should aim at trying to understand who their enemies are and their capabilities and also their goals. Factors influencing their behavior and also their organizational structure should be analyzed. A vital area is learning the adversary’s weak points and also the centers of their gravity. This knowledge is used in planning the course of action and also in deciding and prioritizing the allocation of resources. Awareness of maritime domain thus helps in earlier identification of threats and thus prompts appropriate actions to be taken to prevent such attacks (Higgie, 2005). Conclusion Maritime security as discussed above is not only vital to the seas environment but also affects the whole country and the world in general. No single country is immune to maritime threats and as such, all the countries should work together to attain maritime security. Creating awareness may be costly but should be advocated for to ensure that terrorist attacks and other criminal and hostile acts are recognized and deterred. Stern measures should be undertaken by the international body concerned with maritime security on countries that collude or allow terrorist to operate from their waters. Those convicted of violating maritime security should be persecuted and heavy punishment imposed so as to deter others from engaging in similar acts. However, while dealing with matters relating to maritime security, extra care should be taken. Damages caused by criminal acts via maritime domain may be devastating thus caution should be exercised. The countries should also strive at protecting the maritime domain from exploitation so as to preserve the ecosystem of the country as well as that of the aquatic life. Reference: Bahar M. (2007): Attaining Optimal Deterrence at Sea: A Legal and Strategic Theory for Naval Anti-Piracy Operations Journal article of Vanderbilt Journal of Transnational Law, Vol. 40 Hawkes K. G. (1989): Maritime Security. ISBN 087033395X. Published by Cornell Maritime Press Higgie D. (2005): Combating Terrorism: Dell Higgie Surveys the International Counter-Terrorism Scene. Journal article of New Zealand International Review, Vol. 30 Office of the Press Secretary. (2003): Fact Sheet: Maritime Security Requirements. Retrieved on 10th December 2008 from, http://www. dhs. gov/xnews/releases/press_release_0282. shtm. Pugh M. C. (1994): Maritime Security and Peacekeeping: A Framework for United Nations Operations. ISBN 0719045630. Published by Manchester University Press

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

Symbolism In Macbeth Essay -- William Shakespeare

In William Shakespeare's Macbeth, symbolism plays a prominent role to emphasize the theme of corruption of power. Throughout the play there are several main symbols repeatedly used to emphasize this theme. The contrast of light and dark representing good and evil, blood representing guilt, murder, and pain, and the archetypal pattern of purification by using water represents removal of guilt, cleansing and peace. Symbolism is used repeatedly to emphasize the theme of corruption of power. The image of blood plays an important role throughout Macbeth. Blood represents the murders that Macbeth had committed, the guilt that went along with the murders and the pain that it brought on him during his downfall. The soldier describes the violence and bloodshed, in the war between Scotland and Norway, "Except they meant to bathe in reeking wounds." (I. ii. 43) foreshadows the violent nature of the play filled with murder, guilt and pain. Blood in the murder of King Duncan also plays a major role because it represents Macbeth's guilt as well as his shame for slaying King Duncan. Macbeth observes his blood stained hands and remarks "As they had seen me with these hangman's hands." (II. ii. 28) This reveals his guilt and shame because he is comparing his hands to those of an executioner's. After the murder, Macbeth refuses to return back to the bed chamber of Kind Duncan to smear the blood on the sleeping guards, because he is afraid that the blood will incriminate him further. Lady Macbeth smearing the blood onto the guards represents them trying to rub their guilt off onto the guard. "I'll gild the faces of the grooms withal, for it must seem their guilt" (II. ii. 73) but this proves to be ineffective because Macbeth ends up murdering t... ... a dark setting used which involved supernatural events, while the light setting was used for last battle, when Macbeth was slain at the end to show the restoration of peace and honesty. Thus the symbolism of light and darkness representing good and evil in the play emphasizes the theme of corruption of power. In conclusion, symbolism is used to emphasize a theme through repetition and imagery. It is used to emphasize the theme of the corruption of power due to Macbeth's actions. Blood representing guilt, blood murder, and pain, the contrast of light and dark representing good and evil and the archetypal pattern of purification by using water representing removal of guilt, cleansing and peace are the main symbols used repeatedly to emphasize this theme. These symbols portray the theme effectively to allow the audience to grasp and involve themselves into the play.

Hercules and Syprus :: essays research papers

Now Heracles had just finished his tweleveth labour when the king said that he has another labour.Hercales is now devistated and angry at the king but he does not show it.He looks up to the king and says "O your highness, haven't you put me into enough danger of your liking?""No!"The king shouted.Heracles was now ready to run away because the king was putting to much pressure on him but he decided to do this one last labour."You will have to go into the village of Athens and there you will ask many people about Syprus,the deadliest dragon ever" Said the king Zeus.Now the king was very satisfied that Heracles fullfilled all his demands but he was'nt satisfied with the quantity of labours."This dragon is so fierce that he can eat the lions of the forests and jungles without even trying.He once had eaten the godess Aphrodite but she had escaped with great courage and strength" said the king."And what are the weaknesses of this fierce and dangerous creature you are talking about oh great one"said Heracles."There are none, I'm afraid"said the king slyly."You will have to kill this dragon and flay it.Then you will put your hands amongst it's long and leathery tail and you will feel for a large rectangular box.You will bring this box to me but you shall not open it.This is your final labour and I wish you to fullfill it or else...."the king said nodding."Well I must be heading my way to the village Athen to do my last labour,do you wish me good luck and safety,o great one?"asked Heracles.The king did not say anything for a moment and then shouted out "Go on before I change my mind to something more worse."But there was'nt anything more worse than the Syprus, so if Heracles stayed the king would just have to make up something.Heracles left and made his way to Athen's.When he got there he asked almost all of the working villagers and all of them pointed him to go into the large cave in the North of Athen's.Heracles went North and found a large cave that can fit the whol e world."By the looks of this cave I can see that the one that I've been looking for has been looking for me"siad Heracles.Heracles went into the cave and took out his large club that he had carved and went to explore.

Religious Ceremonies In Theatre :: essays research papers fc

Theatre as a Religious Ceremony   Ã‚  Ã‚  Ã‚  Ã‚  Ã¢â‚¬Å"The drama in Greece was inextricably bound up with religious feeling and religious observance.† (Cheney 33) The citizens of the Greek states were the first European communities to raise dramatic performances to the level of an art. Furthermore, the Greek playwrights still exercise a potent creative force, and many modern dramatists find strong relationships between these legendary themes and modern conditions. The Greek’s religion is wholly responsible for the creation of all facets of early Greek theatre; whether it is the content of the plays, or the immense size of the theaters required to accommodate the attendance of the city’s men.   Ã‚  Ã‚  Ã‚  Ã‚  Although much is speculated about the origins of early Greek theater, it may be stated that the â€Å"source of tragedy is to be found in choric dithyrambs sung in honor of the god Dionysus† (Nicoll 9). The performance took place in an open-air theater. The word tragedy is derived from the term â€Å"tragedia† or â€Å"goat-song†, named for the goat skins the chorus wore in the performance. Originally these songs were improvised and rhapsodical as time passed by they were â€Å"poetized or rendered literary† (Nicoll 9). The word â€Å"chorus† meant â€Å"dance or â€Å"dancing ground†, which was how dance evolved into the drama. Members of the chorus were characters in the play that commented on the action. They drew the audience into the play and reflected the audience’s reactions. The change from freelance song to theatre was obtained at the hands of a Greek named Thespis. He turned what was originally a song lea der, or priest, into an actor whose words were answered by a chanting chorus. Thespis also â€Å"changed the subject matter of theatre events, expanding them to deal not solely on stories of Dionysus† (Nicoll 9). In the sixth century B.C., drama had been born in Greece and with the introduction of a second actor and later a third, this art form was ready to mature at the hands of Aeschylus, Sophocles, and Euripides.   Ã‚  Ã‚  Ã‚  Ã‚  These festivals grew in size and complexity, especially in Athens, where the largest of these festivals were held and only the premier playwrights released their plays. These prestigious and elaborate plays were performed at dramatic festivals. The two main festivals were the Feast of the Winepress in January and the City Dionysia at the end of March. The Proceeding began with the procession of choruses and actors of the three competing poets.

Puck’s Mischief Essay

Puck may be mischievous, but he is not cruel or evil. Do you agree? I agree to a large extent that; although Puck may be mischievous and playful, it does not mean that he is inherently cruel and evil. Mischievousness, implies a sort of roguish fondness for trickery and pranks, this however does not necessarily dictate that Puck is evil at heart. At the outset, the first impression the audience receives of Puck is that of a merry prankster and not a hard-hearted plotter who wishes ill. The first fairy the audience meets describes Puck as a ‘shrewd and knavish sprite’ referring directly to his mischievous spirit. The fairy describes Puck’s pranks of making ‘the drink to bear no barm’ and Puck himself talks about how he ‘jest[s] to Oberon, and make[s] him smile’ and even pretends to be a stool only to disappear when one wants to sit; all of which though they may sometimes be unkind, do not mean any serious harm. Thus from the beginning, Shakespeare creates the impression of a character that delights in mischief, but does not go out of his way to harm people. Though Puck catalyses the conflict between the lovers, it is not because of evil intent that he does this. In fact if anyone should be deemed cruel or evil in A Midsummer Night’s Dream, it should be Oberon. As it was due to carrying out Oberon’s orders, Puck caused the confusion amongst the lovers seen in Act 3 Scene 2. It is doubtless that Puck was indeed the one who ‘anoint[s]’ Lysander’s eyes instead of Demetrius, causing Lysander to pursue Helena to ‘honour†¦ [her] and be†¦ [her] knight’, creating a tangle of lovers when all four finally meet in Act 3 Scene 2. However, he does this obliviously, as seen in how he later admits that he had ‘mistook’ Lysander for Demetrius because Oberon identified Demetrius by ‘the Athenian garments he hath on’. Thus going to show that he had no intention of causing the trouble he did. Additionally, he is willing to make amends for the trouble he has caused, showing that he meant no permanent harm. After finding out that he had ‘laid the love juice on some true-love’s sight’ causing a ‘true love [to] turn’d false’, by causing Lysander to fall for Helena, he immediately commits himself to being ‘swifter than an arrow from tartar’s bow’ in searching for Helena to make things right. Later he honestly admits his mistake to Oberon, pleading Oberon ‘King of shadows’ to ‘believe [him that he]†¦ mistook’. Thus by willingly admitting his mistake and swiftly making amends, Puck shows that he had no intent to harm the lovers at all, shedding light on his character that he is not intrinsically evil. Furthermore, Puck shows compassion for the lovers in his actions, revealing a somewhat unexpected benevolent nature. This is seen when he mistakes Lysander’s reason for sleeping so far from Hermia as ‘lack[ing]-love and†¦ courtesy’. He echoes similar sentiments when he comments that ‘Cupid is a knavish lad, Thus to make poor females mad’ at the end of all the chaos of Act 3 Scene 2. Similarly, although Puck leads Demetrius and Lysander ‘Up and down, up and down’, seeming to goad them, he does so for good reason- in order to lead them away from each other to prevent a fight. Hence through these instances, Puck shows himself to be even less of the hot-headed mischief maker. However, Puck does show a streak of cruelty in his dealings with the craftsmen. His attitude to the craftsmen and Bottom in particular is scornful, calling them the ‘shallowest thicksin of that barren sort’. This conflicts with the audience’s previous encounters with the craftsmen, which though show them to be ‘shallow’ they are certainly not ‘barren’, and ‘The Most Lamentable Comedy and Most Cruel Death of Pyramus and Thisbe’ they persevered in practicing is proof of this. Thus Puck comes across here as very caustic and snide, which may lead the audience to think of him as a wicked character. He even gloats to Oberon about how he had ‘An ass’s noll fixed on’ Bottom’s head, which reveals a certain malicious streak in him. Nonetheless, Puck’s conclusion of the play emphasizes that he means no ill will. In his closing statement, he says to the audience that ‘If you pardon, we shall amend’, for he is ‘an honest Puck’. Highlighting yet again that although he may delight in and make a ‘sport’ out of mischief, he means no real injury, for he is no cruel fairy.

Labor, Stocks and Bonds

According to the basic law of demand and supply, increases in the real wage rate or the price of labor must decrease the quantity of labor demanded, as employers find it increasingly expensive to hire more people.   Would increases in the real wage rate, therefore, decrease the productivity of the firm, that is, the number of the outputs that it produces? – Not necessarily. This is where the assumption of diminishing marginal product of labor steps in to save the firm from significantly reducing its supply of outputs.   Marginal product of labor refers to the â€Å"increase in output produced from a given capital stock when an additional worker is employed (â€Å"Marginal Product of Labor†).†Ã‚   On the other hand, diminishing marginal product of labor means that â€Å"each additional labor hour results in less and less extra output (â€Å"Costs of Production†).   This assumption is explained by the popular saying, ‘Too many cooks spoil the broth.’   Thus, the firm does not need to increase its demand for labor beyond a certain number in any case. Stocks and Bonds The dissimilarity between stocks and bonds is explained by the difference between â€Å"owning and lending (â€Å"The Difference Between a Stock and a Bond†).†Ã‚   The purchaser of a stock is a part owner of the company whose stock he has bought.   He gets to vote on the way the company should be run, and enjoy dividends in addition to â€Å"capital appreciation† as a participator in its success (â€Å"The Difference Between a Stock and a Bond†). Of course, he gets to participate in the failures of the company to boot, through lower dividends and stock prices.   The purchaser of a bond, on the contrary, will be paid before the stockholders in the case of company failure.   He has lent money to the company after all.   The company, in turn, promises to repay its loan at a fixed time, with interest.   Even so, the purchaser of the bond does not enjoy extra interest when the company performs exceptionally well (â€Å"The Difference Between a Stock and a Bond†). Works Cited â€Å"Costs of Production.† Ohio State University. 8 Oct. 2007. . â€Å"Marginal Product of Labor.† London South East. 8 Oct. 2007. . â€Å"The Difference Between a Stock and a Bond.† Cash +, Issue 1 (Fall 2006). 8 Oct. 2007. .