Comparison And Contrast Between Nuclear And Solar Energy Engineering Essay

Comparison And Contrast Between Nuclear And Solar Energy Engineering Essay Human beings have been using fossil fuels for hundreds of years, satisfying the demand of industrialization. The behavior of using fossil fuels, on the other hand, causes huge pollution, such as soil, water and atmosphere contamination. In addition, fossil fuels, such as solid, liquid and gas, are all facing on the exhaustion. It is evidential that the situations need to be checked or repressed. However, the solutions should satisfy the urgent requirement of energy as well. Nuclear and solar energy are two clean, practicable solutions for human beings. Because they have been tested and been put to use since the mid twentieth century. On the surface, nuclear and solar energy seem absolutely different in other aspects except for low direct pollution and practicability. In fact, they share some significant similarities while they are totally different in other aspects. This essay will concentrate on comparing and contrasting nuclear and solar energy by discussing the similarities in gas emissions, high expend in increasing efficiency and electricity price, and the differences in safety and equipments. There are numerous similarities between nuclear and solar energy. The most significant one is that they are pollution-free and have no direct emission of carbon dioxide or other greenhouse gases. Both nuclear and solar energy will give a carbon dioxide saving of 1330kg for 1kw electric power per year (Bosshard, 2006). Even though they lead to indirect emission of gases, the quantity of pollutant is small and unavoidable. However, at the price of low emission, the improvement of efficiency is expensive and difficult for both. In other words, they require high expenses in material and maintenance, especially when increasing the electricity production. Furthermore, according to Bosshard (2006) and Murray (2000), low efficiency is a traditional challenge for nuclear energy to conquer as it is in the solar energy field. Nuclear plant has efficiency about 7% in collecting radioactive energy to drive dynamotors. Merely 30-40% energy can be converted into electricity power by dynamotors. Likewise, neither silicon solar cell nor compound solar cell has an average efficiency which is over 16% (Edmonds, 2007). Even thought both nuclear and solar energy have plans for increase of efficiencyà ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬fusion for nuclear energy and Thin Film Poly for solar energyà ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬that will make a great improvement in efficiency, these techniques will not be conquer and put into application within a decade . Another common point that these two kinds of energy share together is the price of electricity. According to Thamm (2007), the price for solar energy is $0.35-$0.6 per kWh for solar cell and $0.085-$0.135 per kWh for solar thermal, while Fell (2006) claimed that the nuclear electricity price was from $0.3/kWh to $0.6/kWh; whereas, comparing to fossil fuels energy, which is merely 0.04 dollar per kilowatt-hour; hence, the expensive costs these two energies need will influence the competitive ability of worldwide market obviously. In spite of the similarities, safety is the main problem. It caused the differences of worldwide application in fund input and popularity between nuclear and solar energy. According to Duncan (2002), radioactive materials are regarded as the most basic sources for nuclear plant, which is extremely deadly pollutant. Therefore, as a solution, it will be stored in deeply in the earth with high-end and mature technology. Nuclear energy becomes one of the luxury goods for some wealthy countries. In contrast, solar energy application is much safer, such as solar cell, it can not only be built in solar station but also be applied in every aspect of daily life in both developed and developing countries. For instance, it supplies energy to homes or even playthings. Furthermore, the two famous nuclear accidents, The Three Mile Island in 1979 and The Chernobyl in 1986, are regarded as the another main evident reason for environmentalists to refuse nuclear power and for many counties to prefer p utting more fund into other clean energy like solar energy. There are three differences of the equipment applied to generate electricity for these two kinds of energy. The main difference involves the principle of operation of energy transformation. In this area, solar energy is more direct. Gonyeau (2003) stated that nuclear plant applied some special substance to absorb the radioactive energy from radioactive material in order to convert the energy into the heat of vapor, which would drive the thermoelectric generator to produce electricity. Moreover, heavy water, which is so difficult to produce that its value is higher than gold, is requite as Refrigerant. In contrast, Solar equipments prefer to generate electricity more directly by collecting photon energy and transforming it into potential energy in the cell or just gather the heat of light with water or parabolic dish collector (Corporation, 2008). As result, solar energy is more convenient than nuclear energy. Not only the ways of energy transformation are distinct, protection problem is also regarded as the area where difference exists. Nuclear plant needs frequent examination and to be well protected, because every little mistake will deal to the over heated of the reactor which is likely to cause the disaster that beyond retrieve. However, solar equipments are more easy to be controlled and do not requite as much care as nuclear plant does. The last point of difference is in energy gathering. It is obviously that nuclear plant can generate hundreds of times electricity than solar equipments (Edmonds, 2007). In addiction, difficulty in gathering energy is regarded as the disadvantage of solar energy, while the nuclear plant is good at this work. From what has been discussed above, it is easy to identify that solar energy is more promising than nuclear energy for its pollution-free production, safety, and convenience. Also, while nuclear energy, especially the fusion reaction that will be applied in future, is much danger and shouldering the pressure of nuclear proliferation, solar energy has wider and wider application in all aspects in society. Moreover, solar energy is one of the energies which are almost infinity for humankinds, because it can be found even outside the solar system; while nuclear energy is suffering the shortage of source. In brief, solar energy will develop well and become far more popular than now. In conclusion, by comparing and contrasting these two kinds of energy, it is clear that nuclear and solar energy share the common point of low greenhouse gas emissions and high cost of electricity. However, they still differ in many areas such as safety and principle of operation of devices. It is evidently that the application of nuclear and solar energy will grow in the future; while solar energy is more promising. Although there are several difficulties for both nuclear and solar energy to conquer, great progresses will be made. Consequently, they will serve Human beings and satisfy the increasing demand of consuming energy. ReferenceÃÆ' ¯Ã‚ ¼Ãƒâ€¦Ã‚ ¡ Corporation, P .W (2008). Solar Energy. available at: http://www.window.state.tx.us/specialrpt/energy/pdf/10-SolarEnergy.pdf (Accessed date 09/03/2010) Duncan, T (2000). Advanced Physics. 4th Edition, London: Murray Publishers Ltd. Edmonds, JA (2007). Nuclear Energy. available at: http://www.nuclear.gov/pdfFiles/History.pdf (Accessed date 08/03/2010) Bosshard, P (2006). An Assessment of Solar Energy Conversion Technologies and Research Opportunities. Available at: http://gcep.stanford.edu/pdfs/assessments/solar_assessment.pdf (Accessed date 07/03/2010) Gonyeau, J (2003). Nuclear Energy. available at: http://www.pnl.gov/gtsp/docs/getspnuclear.pdf (Accessed date 08/03/2010) Fell, H. J. (2006). Uranium Resources and Nuclear Energy. available at: http://www.lbst.de/publications/studies__e/2006/EWG-paper_1-06_Uranium-Resources-Nuclear-Energy_03DEC2006.pdf (Accessed date 09/03/2010) Murray, R. L (2000). Nuclear Energy available at: http://www.thevespiary.org/LYC/Chemistry/Nuclear%20chemistry/Nuclear%20Energy,%20An%20Introduction%20to%20the%20concept.pdf (Accessed date 11/03/2010 Thamm, A. L (2007). A Strategic Research Agenda for Photovoltaic Solar Energy Technology. available at: http://www.eupvplatform.org/fileadmin/Documents/PVPT_SRA_Complete_070604.pdf (Accessed date 07/03/2010)

Pros And Cons Of Delegating Human Resources Management Essay

Pros And Cons Of Delegating Human Resources Management Essay A line manager is responsible for an employee or a work group who do not have any managerial responsibility. Some of the daily duties that a line manager undertakes are people management, dealing with customers/clients, monitoring work process, measuring operational performance, organising allocation and rotas and monitoring absenteeism. Although line managers play a vital role in bridging the top level management and the lower hierarchical staff on a daily basis, it is seen that most of the line managers, however, may not have formal management education because he/she is generally promoted from within. Due to the daily and frequent contacts between the line managers and the staff to whom he/she is responsible, it has been a more common practice to see the line managers undertaking several human resources responsibilities including recruiting and selection of employee the function otherwise used to be exclusively of the human resource department in the past. This is widely practiced lately mainly because of the fact that the line managers have a better understanding of the job that needs to be carried out in order to match the corporate strategy and operations strategy of the organisation. With the prevailing frequent communication between the line managers and the employees, it also contributes towards increased morale in the employees ensuring a higher productivity and competency of the employees and enhanced focus on customers. Since most of the line managers do not have formal management education, they might not be fully reliant on the managerial tasks that they perform and hence they have drawback in their undertaking of human resources tasks although they have added value to the human resources professionals by allowing them to invest their time on more strategic issues. Pros and Cons of Delegating Human Resources roles to Line Managers Cons Increased speed of decision making Line management responsibility for people issues Local management accountability Potential cost savings Strategic role for central HR/IR Short lines of communication Lack of time to perform HR duties Increase in line managers workload Additional costs of training managers Increase in grievances/tribunal cases Potential for HR/IR to be marginalized People management not considered to be part of the line managers job Pros: Increased speed of decision making: Line management responsibility for people issues Local management accountability Potential cost savings Strategic role for central HR Short lines of communication B. Cons: Lack of time to perform Human Resources duties Increase in line managers workload Additional cost of training line managers Increase in grievance/tribunal case Potential for HR to be marginalised People management not considered to be line managers job The people and performance research carried out for the Chartered Institute of Personnel Development (CIPD) by a team at Bath University (Hutchinson, 2003) found that the line managers played a vital role in terms of implementing and enacting HR policies and practices. They found that where employees feel positive about their relationship with their line managers they are more likely to have higher levels of job satisfaction, commitment and loyalty which are associated with higher levels of performance or discretionary behaviour. Discretionary behaviour is defined as that which goes beyond the requirement of the job to give extra performance which can boost the bottom line. Line managers also play the strongest part in structuring peoples actual experience of doing a job. According to an online survey of 121 organisations, collectively employing almost a quarter of a million people, shows that four in five (80.2%) organisations have devolved responsibilities such as managing flexible working requests and handling grievance and disciplinary procedures to line managers over the past few years. And two in three predict the role of line managers will take on even more HR functions over the next few years. (Williams, 2008) Also, another interesting finding was that the line managers claimed to be satisfied with the HR responsibilities that have been devolved to them and are keen to take on activities that relate explicitly to the development of their team. Most line managers report working closely with their HR counterparts and see the configuration moving towards a partnership. The line managers main concern is that a lack of support from HR during the delivery of the service can detract from the overall effectiveness. They also note that junior level line managers are likely to feel less supported by HR and comment that it is merely their high level position that drives the HR-line partnership in their situations. (Susan Whittaker, 2003). The role of line managers in both public and private organisations has changed quite significantly in recent years. The line managers have been allocated more responsibilities and are accountable not only for budgeting and allocating of resources, but most importantly for people management issues as per Hoogenboorn Brewster (1992.). According to some sources such as Storey (1992: 190), he argues that line managers may well be playing a far more central role in labour management than HR personnel. Whereas another source, Hales (2005) traces the greater involvement of line managers in HR issues to two developments. He argues that the line managers have been taking on the role of a coach , conductor or a leader of a highly motivated team as a result of the spread of Human Resource Management and the adoption of more participative forms of management concerned with securing high performance through commitment rather than control. Human Resource Devolvement has led to line managers acquiring middle management functions and becoming mini-general managers accompanied by the loss of supervisory functions downwards to work teams. It is hence more appropriate for line managers to take responsibility for people development since they operate alongside the people they manage and therefore it is argued that that their reactions are more immediate and appropriate (Whittaker and Marchington, 2003). Initial research indicates some positive support for line manager HR involvement. Hutchinson and Purcell (2003) found that line manager involvement in coaching, guidance and communication positively influences organisational performance. Likewise, a case study of line manager involvement in HR in the NHS by Currie and Proctor (2001) found that line managers are important contributors to strategic change when provided with discretion in implementing HR strategies within their own work groups. Whittaker and Marchington (2003) maintain that line managers increasingly welcome HR responsibilities and are prepared to take them on as they add variation and challenge to their work. Gibb (2003) argues that requiring line managers to be more involved in the HR issues may also lead to a transformation of managers own attitudes towards HR, organisational change and thus a transformation of human relations at work (Gibb, 2003). By increasing line manager involvement in HR, it is argued that better workplace conditions will result as line managers have better understanding than specialists of the type and range of interventions needed. In this pursuit, line managers are assisted by more effective and user-friendly human resource information systems, new technologies and Human Resource call centres, making it possible for line managers to handle some HR work without the assistance of Human Resource Department. It is seen that a speedy resolution of conflicts and lower rate of employee turnover is possible by moving Human Resources responsibilities closer to employees through line managers. Indeed, providing greater authority to line managers and encouraging greater initiative taking may address a long-standing criticism levelled at HR departments; namely a lack of appreciation of the immediacy of the line managers problems (Harris, L, Doughty, D. Kirk, S. (2002). According to Maxwell and Watson (2006), business partnerships between HR specialists and line managers have emerged as the dominant model for Human Resources operations within organisations. Similarly, Ulrich (2005) outlines the role of HR Strategic Partners as working alongside line managers to help them reach their goals by crafting strategies to maximise productivity through alignment of corporate resources to these goals. We can hence understand that devolving HR responsibilities to line managers offers a number of benefits to organisations. A greater freedom to HR specialists to engage with strategic issues is provided enabling them to forge closer relationships with line managers and a partnership model towards managing employees is developed. Similarly, line managers understand and appreciate the complex nature of dealing with the employee issues and become more encouraged and involved in everyday workplace management tasks. However, line managers have pointed various issues concerning HR involvement despite the above mentioned benefits of participating in HR activities. It will obviously increase their workload by getting involved in HR tasks. Increased workload leads to feelings of incompetence among line managers and reluctance to take responsibility for devolved HR activities. Indeed, this has led to feelings amongst some line managers of being dumped upon (Renwick 2003: 265) or pushed upon to take new HR responsibilities (Harris, L, Doughty, D. Kirk, S. (2002):) due to a climate of fear and mistrust driven by HR. The experience and ability of line managers to take responsibility for HR issues may present a major barrier to devolvement. Both Whittaker and Marchington (2003) and Hailey, V.H., Farndale, E. Truss, C. (2005) suggest that line managers skills and competence in HR practices may be limited and a lack of training in this area will undoubtedly affect a line managers overall effectiveness. I ncapability and misunderstanding of HR practices on the part of line managers will prevent the organisation from developing a strong learning culture (McCracken and Wallace, 2000) with McGovern et al. (1997) arguing that a lack of training may lead to inconsistencies in implementing organisational HR policies potentially exposing the organisation to lawsuits and employment tribunals. Their research though, indicates that management development is not a priority for the top management and reliance on the notion of trial-and-error is prevalent in organisations. Furthermore, the failure of organisations to take a long-term developmental view is exposed by a reluctance to set aside a specific budget for training and the belief that management development is the individuals responsibility. Many line managers get under pressure to meet operational targets, and often struggle to fulfil their people management duties. This is partly because they are not equipped with the tools, skills and knowledge they need to be effective. As a result, managers sometimes effectively abdicate responsibility for aspects of people management. A commonly used phrase is thats HRs job often tends to be heard a lot in many companies whether relating to employee development, managing an individuals performance or dealing with absenteeism issues. Recent research involving nearly 3,000 employers by the Work Foundation and the Institute for Employment Studies found that organisations with a comprehensive, structured approach to people management, covering areas such as recruitment, development plans and employee appraisals, perform better than those without, as indicated by higher profits per employee, higher profit margins and ultimately higher productivity. Sometimes its easy to be critical of managers, but often theyre not properly equipped to be effective. Investment in management training requires clearly set-down policies and procedures. There appears to be lack of clear guidance and easily accessible information, its not surprising that many line managers response when an issue arises is either to pick up the phone to HR or to ignore the problem and hope it would goes away or transfer responsibility to someone else. It is interesting but to be fair to line managers, sometimes part of the problem may also lie with the HR department itself. For all the talk about wanting to devolve more responsibility to the line, in practice HR professionals are sometimes reluctant to trust line managers to manage. They are unwilling to give managers the tools and information they need to do the job effectively: after all, knowledge is power, and by being the gatekeepers of all information relating to employees, policies and processes, HR may feel that it has power. This is clearly not in the long-term interests of the HR function. HR teams must realise that if they are to fulfil their potential and be true partners to the business, then they need to trust their managers with the day-today stuff. This doesnt mean being unsupportive but continued support to line managers to assist them with responsibility for the way that people are managed. It does mean defining strategies and policies and then putting in place the frameworks and the systems that enable managers to take accountability for the day-to-day execution but in a controlled, informed and effective way. Line managers must aim to be more accountable whereas HR professionals being more strategic could assist when working together. Better solutions are needed to support key people management processes and its likely that intelligent use of technology is likely to represent at least part of the answer. Technology-based services offer organisations the potential to give much greater support to their line managers, but in a highly cost-effective way. Line managers can be given tools to walk them through common processes, access to comprehensive information about their employees, guidance on how to manage effectively, and prompts when tasks or actions are due all accessed via a single web-based service. In view of the above, making line managers responsible for the delivery of HR can be complex. Line managers may not possess the required skills needed to implement HR initiatives and may feel ill-equipped or insufficiently trained to accept responsibility for day-to-day HR tasks. Devolving HR responsibilities may also represent a lack of appreciation of the workloads, time pressures and overall priorities of line managers threatening the overall standards of HR delivery across the organisation and diminishing the value of HR. It is found that getting line managers involved in HR tasks is a step towards achieving a more strategic, value-added approach to managing employees. Line managers play an important position in the organisational hierarchy and can directly affect the quality of front-line services. It will greatly increase the existing pressures of excess workload and the need to deliver on short-term priorities by devolving line managers with HR responsibilities. It will also mean the requirement of display of a higher level of HR competency by the line managers which calls for the need for high-quality training programmes for line managers to ensure that they feel confident in discharging their new HR responsibilities. Such training may help organisations avoid costly litigation and damage to their public reputation. Therefore, HR professionals must engage with line managers and develop a partnership to bring about a speedier resolution to workplace conflicts by allowing line managers to seek guidance and advice whenever required thereby making line managers more responsible for HR.

Encoder Viterbi Matlab

Encoder Viterbi Matlab Implementation of Convolutional Encoder and Viterbi Decoder Using Matlab and FPGA Abstract Channel coding is widely used in digital communication. By using channel encoding methods we can minimize signal noise and signal interference in our system. These techniques also utilize less bandwidth for error free transmission. In our project we have implemented convolutional encoder and viterbi decoder for channel coding. Convolutional encoding is vastly used for error correction in digital communication. We have implemented these techniques on matlab and performed a lot of simulation to check their performance. Chapter 1 DIGITAL COMMUNICATION SYSTEM INTRODUCTION Early communication was based on implicit assumption that messages signal is continuous varying time signal waveform. Such continuous time signals are referred as analog signals and there corresponding information sources are called analog sources. Analog signals are transmitted using carrier modulation over communication channel and accordingly demodulated at receiver. Such communication system is called analog communication systems. In digital transmission analog source output is converted to digital form. Message can be transmitted using digital modulation and at receiver demodulated as digital signal. The basic feature of digital communication system is that during finite interval of time it sends a waveform from possible number of waveforms. Important measure of system performance in digital communication systems is probability of error. 1.2 WHY DIGITAL COMMUNICATION Digital communication is preferred over analog communication because digital circuits have a less probability of distortion and interference than analog. Digital circuits are reliable than analog and have low cost. Digital hardware is more flexible to implement than analog. In digital signals time division multiplexing is simpler then FDM in analog signals. DIGITAL COMMUNICATION In digital communication system functional operations performed at both transmitter and receiver should be expanded to add messages signal bias at transmitter and message signal synthesis or interpolating at receiver. Additional functions include redundancy removal and channel encoding and decoding. 1.3.1 Source Nature Information is knowledge. Information can be of two types either analog or digital. We can collect information through listening or watching. Receiver newer know what it will receive in advance but only when some source generates an output towards it. The main responsibility on any communication channel is to send error less information towards receiver. 1.3.3 Source Encoder/Decoder What is source encoder? It is a technique which changes an analog signal into sequence of bits. This sequence of bits that is produced can also be used for the reconstruction of the signal. These bits contain information about the original signal. If we use this encoding technique it can also be helpful in appropriate bandwidth utilization. The sequence of bits is such that it can be used for data compression. 1.3.4 Quantization It is a process in which we sample the amplitude of a analog signal. Irreversible mechanism in which we erradicate redundant bits is called QUANTIZERS. The disadvantage of quantization is that it introduces noise in the sampled signal. Whereas while sampling distortion donot occur. But inspite of all that, quantizers and quantization is still widely used in determining the bit rate. And in any coding procedure of speech, amplitude quantization is the most important step. X8 X7 X6 X5 X4 X3 X2 X1 Figure 1.2: 8-level quantization 1.3.5 Modulation and Demodulation What is modulation and demodulation? Modulation is a process in which a baseband signal is mixed with a carier and converted into bandpass signal. And demodulation is a process in which original signal is recovered from modulated signal. And modulator and demodulators perform the above information. The modulator changes the signal into the form representing the required information. And reverse operation is performed by demodulator. The purpose of these devices is to produce and convey messages with minimum bit error rate. NOISE IN COMMUNICATION SYSTEMS Noise refers to something which is always present in the entire communication world. Noise is something that can be created or produced from variety of possessions. If noise is present in any system it makes the system ambiguous and less efficient. It also makes our receiver capability less efficient. And therefore also confines the transmission rate. Noise can be minimized by efficient designing technique which is not desired through different methods such as filtering. Noise which is caused by the thermal motion of electrons in all dissipative resistors is called thermal noise. These electrons are also responsible for thermal noise as a zero mean Gaussian random process. CHAPTER 2 CHANNEL CODING 2.1 INTRODUCTION Channel coding is used in communication system to improve the signal reliability in communication systems. By performing channel coding we can protect our signal from different types of noises and distortion. These methods of signal processing are tools for accomplishing desirable system tradeoffs. By using large scale integrated circuit and high speed digital processing methods it had made possible to provide as much as 10db performance improvement at much less cost. Shannon showed that by the addition of redundant bits to source information we introduce a method to minimize error in channel without disturbing information transmission rate provided that the information rate is less than channel capacity. Average number of information bits per unit time can be reduced by using function of the speech code. Minimum number of information bits should be transmitted. The input to encoder is the output of speech code. Radio link performance is improved by using Channel coding in mobile communication by the addition of redundant bits to source information. At the transmitter channel code maps the digital information which is produced by a data source into a form that can be decoded by the receiver with minimum errors. Channel coding mechanism insert noise to the codes in a controlled manner by adding extra bits so that the receiver can do detection and correction in a noisy channel. Channel codes which are produced are classified as block codes and convolution codes The hamming distance (minimum), dmin of a code is used as criteria for determining error correction ability. The minimum hamming distance is defined as smallest value of d. if minimum hamming distance is dmin ,(dmin -1)bit errors can be detected and we correct the integer [(dmin-1)/2] bit errors .raw data transmission rate can be reduced additional coded bits. Using Error-Correction Codes These codes are very useful to use.Without implementing these codes in our communication system our data delievered will be very noisy and corrupted.Below is the graph which showz comparison between uncoded and coded data error performance. Chapter 3 CONVLUTIONAL CODING INTRODUCTION TO CONVOLUTIONAL ENCODING The idea is to make all code word symbols to be the weighted sum of the input message symbols. And that is similar to the convolution used in linear time invariant systems where the output of system is found, if you know about the input and impulse response. So in convolutional encoder we usually get the output of the system, by convolving the input bits. Basically, convolutional codes do not reduce much noise as compared to an equivalent block code. In most of the cases, they generally offer more simple implementation upon block code of same power. The encoder is a simple circuit which contains the memory states and feedback logic, normally supported by XOR gates. The decoder is usually implemented in software. The Viterbi algorithm is the most favourable algorithm which is used to decode convolutional codes. It is found that they generally give good results in environment of lower noise. OVERVIEW OF CONVOLUTIONAL CODES Convolution codes represent one method within the general class of codes. Channel codes which are also called error-correction codes allow reliable communication of an information sequence over that channel which adds noise, bring in bit errors, or otherwise deform the transmitted signal. These codes have many applications which include deep-space communication and voice band modems. Convolutional codes are commonly prà ©cised by the following three parameters; (n, k, m). n = output bits k = input bits m= memory registers L=constraint length The quantity k/n which is called code rate is a measure of the capability of the codes. Usually range of n and k is from 1 to 8 and range of m is from 2 to 10 and the code rate from 1/8 to 7/8 except for deep space application where the code rates as low as 1/100 or even longer has been engaged. Often the manufactures of the Convolutional code chips specify the codes by the following parameters n, k, L. The quantity L is the constraint length of the code and is defined by Constraint length, L = k*(m-1). The constraint length L stand for the bits in the encoder memory that effects the production of n output bits. The constraint length L is also indicated by the letter K. 3.2.1 CONVOLUTIONAL ENCODING ENCODER STRUCTURE Convolutional codes protect by adding unwanted bits as any binary code. A rate k/n Convolutional encoder develops the input series of k-bit information symbols through one or more binary shift registers. The convolutional encoder calculates every n-bits representation (n > k) of the output series from linear process on the present input symbol and the contents of the shift register(s). Therefore, a k-bit input symbol is processed by a rate k/n convolutional encoder and computes an n-bit out put symbol with every shift update. Figure shows a non recursive convolutional encoder having rate of 1/2. For the encoder above, shows state variations and resulting output code words. Sequence U for the message sequence m=1 1 0 1 1 Solution Table 3.1 Branch word at time ti u1 u2 State at Time ti+1 State at Time ti Register Contents Input Bit mi 0 0 0 0 0 0 0 1 1 1 0 0 0 1 0 0 1 1 0 1 1 1 0 1 1 0 1 1 0 0 1 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 1 1 0 1 1 1 0 1 1 0 1 1 0 0 1 1 1 0 1 1 0 1 1 0 0 0 1 0 0 1 0 U = 1 1 0 1 0 1 0 0 0 1 0 1 1 1 POLYNOMIAL REPRESENTATION Sometimes, the encoder characters are characterized by initiator polynomial. Representation of an encoder can be done with a set of n initiator polynomial, one for each of the n modulo-2 adders. Each polynomial is of degree K-1 or less and tell about the connection of encoding shift register to that modulo-2 adder as the connection vector normally do. The coefficient of all the terms is either 1 or 0 of the degree polynomial depending upon whether connection exists or doesnt. For example in figure 4.1, we can write the generator polynomial g1(X) for the upper connections and g2(X) for the lower connections as follow. g1(X) = 1+X+X2 g2(X) = 1+ X2 The output sequence is found as follow U(X) = m(X) g1(X) interlaced with m(X) g2(X) Let the message vector m = 101 as a polynomial is represented as m(X) = 1+ X2 Then output polynomial U(X), of the figure 4.1 encoder can be calculated for the input message m is given as under. m(X) g1(X) = (1+ X2 )( 1+X+X2) = 1+X+X3+X4 m(X) g2(X) = (1+ X2 ) (1+ X2 ) = 1+ X4 m(X) g1(X) = 1+X+0X2+X3+X4 m(X) g2(X) = 1+0X+0X2+0X3+ X4 U(X) = (1, 1) + (1, 0) X + (0, 0) X2 + (1, 0) X3 + (1, 1) X4 U = 11 10 00 10 11 We demonstrated the encoder with polynomial initiators as also described for cyclic codes. Graphically there are three ways in which we can look at the encoder to gain better understanding of its operations. These are (a) State diagram (b) Tree diagram (c) Trellis diagram 3.2.2 STATE DIAGRAM Convolution encoders are finite-state technology. Hence state diagram offers significant insight into their performance. The states showed in the diagram symbolize the probable contents of right most K-1 stages of register, and paths represent the output symbols coming from such state changes. The states of registers are nominated as a=00, b=10, c=01 and d=11. There are only two conversions originating from every state, corresponding to two probable input bits. Output branch word is written next to every path state that is linked with the state transition. In below figure, we have used the complete line which denotes a path linked with input bit, 0 and a doted line is to a path with an input bit, 1. Observe that it is impossible in a single transition state to move forward from a given state to any random state. 3.2.3 THE TREE DIAGRAM One cannot easily use the state diagram for tracing back the encoder transitions as a function of time because it has only one disadvantage i.e. it cannot maintain the history record while the state diagram fully characterize encoder. State diagram is the advance form of tree diagram; it adds the dimensions of time than tree diagram. As the custom these trees also traverse from left to right at each bit inputs and each branch of the tree is describing the output branch. Following rule can be used to find the sequence of codeword; for an input bit of zero, its related branch word can be obtained by advancing to subsequent rightmost branch in the up direction. For an input bit of 1, its branch word can be obtained in the down direction. If we assume that the major contents of encoder are zeros, the diagram shows if initial input bit to the encoder is set to zero, the output will be 00 and if the initial input bit is a one, the output will be 11. Also if the initial bit input is one and next input is zero, the next output bit is one; the next output branch word is 01.By following these steps we observe that input bit stream 11011 traces bold line on the tree. This path matches to the output codeword sequence 1101010001. CHAPTER 4 VITERBI DECODER 4.1 VITERBI DECODING ALGORITHM This algorithm was revealed by Viterbi in 1967. The Viterbi algorithm performs maximum likelihood decoding. By taking benefit of the structure in the code trellis it also reduces the computational load. The benefit of Viterbi decoding is that its difficulty is not a function of the information of symbols in the code word sequence. The algorithm includes calculating a distance, or measure of resemblance b/w the received signal, and every the trellis paths entering each state at the same time. Those trellis paths that could not possibly by candidates for the maximum likelihood choice, viterbi algorithm removes them from consideration when two paths are entering the same state then the one having the best metric is selected and that path is called the surviving path. This choice of surviving path is carry out for every state. The complexity of the decoder is reduced by the remove paths with maximum unlikeliness. The decoder continues in this way to go forward into the trellis and making decision by eradicating the slightest likely paths. In fact in 1969, Omura also demonstrated that the Viterbi algorithm is maximum likelihood. The objective of selecting the optimum path can be articulated by selecting codeword which as minimum distance metric. 4.2 EXAMPLE OF VITERBI CONVOLUTIONAL DECODING Binary Symmetric Channel is assumed for simplicity thus hamming distance is a suitable measured distance .A similar trellis which we are using in encoder can also be used in decoder, as shown in figure 4.5. We set up at time t1 in 00 state referring to trellis diagram. Flushing in encoder is very important because it tells the decoder about the starting state because in this example there are only two likely transitions departing any state and not all the branches need to shown firstly. The full trellis structure starts after time t3. Central idea following the decoding procedure can be demonstrated by seeing the figure 4.1 encoder trellis in contrast with the figure 4.2 decoder trellis. It is suitable at each time interval, for the decoder to label every branch with hamming distance b/w the received input code symbols and the current transition word matching to the same transition at encoder end. The example in figure 4.2 shows the equivalent codeword sequence U, a message sequence m, and a noise distorted received sequence Z = 11 01 01 10 01 †¦Ã¢â‚¬ ¦. . Code symbols that will come from the encoder output which are results of state transitions are the encoder branch words As the code symbols are received they are accumulated by the decoder and are labeled on trellis branch. That is for each and every branch of the decoder trellis it will be marked with a matrix of likeliness i.e. Hamming distance. From the received sequence Z, we observe that code symbols received as the convolutional output at time t1 are 11, shown in figure 4.2. With the aim of labeling the decoder branches at time t1 with the least Hamming distance metric, we glance at the encoder state diagram figure encoder trellis. At this point we observe that a state 00-00 transition gives an output branch word of 00, but we are receiving 11. Consequently, on the decoder trellis we label 00—00 transition with hamming distance of 0. Observing encoder trellis, a state 00—10 transition yields an hamming distance of 1 with the output of 11. Hence, on the decoder trellis, we also label the state 00—01 transition with a Hamming distance of 0. So, the metric entered on the decoder trellis branch tells compares the corrupted and correct distances received associated with the branch transmitted with the branch word. To all intents and purposes, these metrics describes a correlation. The decoding algorithm finds the minimum distance path in order to correctly decode the data. The foundation of Viterbi decoding is that between any two paths which are ending up to the same state, path with minimum hamming distance will always be selected and other one will be discarded. Its example can be seen in figure 4.3 below. 4.3 Decoder Implementation In the decoding context the transitions during any of the time interval can be combined into 2^v-1 disjoint cells, where each cell is dissipating four of the possible transitions, where v is called the encoder memory. 4.3.1 Add-Compare-Select Computation Starting with the K=3, 2—cell example, figure 4.4 below shows the logic unit that corresponds to cell 1. The logic executes the special purpose calculation called add-compare-select (ACS). The state metric is calculated by adding the previous-time state metric of state a, to the branch metric and the previous-time state metric of state c, to the branch metric, this fallout in two possible path metrics as candidates for the new state metric. These two results are compared in the logic units of figure 4.4. The biggest likelihood (smallest distance) of the two path metrics is saved as the new state metric for the state a. Also shown in the figure 4.4 is the cell-1 add compare select logic that tells the new state metric and the new path history. This ACS process is also performed for the paths in other cells. The oldest bit on the path with the smallest state metric forms the decoder output. 4.3.2 Add-compare-select as seen Trellis Consider the same example for describing viterbi decoding. The codeword sequence was U = 1101010001, the message sequence was m = 11011 and received was Z = 1101011001. Figure 4.5 give a picture of a decoding trellis diagram. Most important point in the decoding through trellis tree is its hamming distance. This is the distance between received code symbols and their equivalent branch words. Trellis tells the value at every state x and for each time to time t1 to t6. We do ACS operation when we have two transitions ending up to the same state. And we get these types of situations after t4 transition and after that. For instance at time t4 the value for the state metric is obtained by incrementing sate t3. Similar operation is done for the state t2. The ACS process chose the minimum hamming distance path which also has maximum likelihood. The paths with minimum hamming distances are shown with bold lines and the paths with minimum likelihood are shown with faded lines. Trellis trees a re always observed from left to right. At any time when we want to check our decoder output we initiate with those states which has smallest paths. If we look at the figure below we can see that at time t6 path with minimum hamming distance has survived with distance =1. CHAPTER 5 SIMULATION METHODOLOGY 5.1 MATLAB SIMULATION 5.1.1 CONVOLUTONAL ENCODER VERTERBI DECODER We have implemented Convolutional encoder and viterbi decoder as source code. Matlab code also compares our viterbi decoder output with the built in decoder output by comparing bit error rates in our project. Making Matlab code and generating different code words for different symbols using convolutional codes and then decoding them with errors using viterbi decoder was the first step in our project. We have taken input from the user which will be coded by the convolutional encoder. Here we have generated random bits. Then the coded data will be decoded at the viterbi decoder. At the decoder side we have corrupted different bits by simply inverting them manually. Just to check what will be the bit error rate if different bits will be corrupted. Then we have compared our built in decoder function with our decoder code efficiency. In the receiver side we have used viterbi decoding algorithm to decode the transmitted signal. After these two steps (encoding and decoding) original data is obtained, which have errors if low SNR is used. 5.2 VHDL SIMULATION Our second step regarding to this project was to make synthesizable code of encoder and decoder in vhdl. For this we have used modelsim. Here we have implemented same logic as we used in matlab. 5.3 FPGA In the end we have burned our code in field programmable gate array. We made a synthesizable code in vhdl of our matlab logic and implemented on fpga. MATLAB RESULTS Here is the result of our matlab codes. If one bit is corrupted data_str = 111011010101000001111101101010101000101100111011010001000100011001111111110101100010101111100101010011101011101001000110 conv_code_str = 100110010001000010001000111100000011001010100100000100100010011000101100101000010111100110010001000010110011111100111011011101011111001010101010111001001000000111001110011000011010110111111000110010111101110100100001110100101111111100110101 msg_rec = 11101101010100000111110110 101010100010110011101 10100010 0010001 10 011 1111111010110001010111110 0101010 01110101110 1001000110 Message/ber retrieved with Verterbi_link_cont1 ber = 0 Message/ber retrieved with Vitdec ber =0 If two bits are corrupted data_str = 100010111000000011101000101100010010100110101101110110110010001100010010010011111001100001101000001001111000101011011101 conv_code_str = 100011001110011110011100011000001101111100101100100000010111010110111110010011110101010000010100000001000101011101111110101011010111010110111110100110111101110010011111001111000011001100101100011011101111000010011100100000100001001001100100 msg_rec = 10001011100000001110100010110001001010011010110 1110110110 0 10 001100010 010010011111001100001101000 001 0011110001 010110 11 1 0 1 Message/ber retrieved with Verterbi_link_cont1 ber = 0 Message/ber retrieved with Vitdec ber = 0.2667 if 3 bits are corrupted data_str = 101100011101110010110100100110010010001010111010011011111000000000110110000110101111100000100010100011001001111110001100 conv_code_str = 100110010111010011100100000111111110011011001011100101110101100000111110101101100010011000010010100011010001110100011100011110000000101011000101101110110101010110011010111001000000100101001110010101001101000001101111000100101001101101010111 msg_rec = 1110011111 01110 0 1 0 11010010011011 0 01010101011101 000 111 011 10 00100000110110100110111010100000100010 11011001110 0111110101100 Message/ber retrieved with Verterbi_link_cont1 ber = 0.1750 Message/ber retrieved with Vitdec ber = 0.2000 As the errors in bits increases bit error rate also increases. Appendix A Matlab Code %*********************************************************************************** %** CONVOLUTIONAL ENCODING TRELLIS DIAGRAM IMPLEMENTATION %************************************************************************************ function [code]= Conv_Enc(message1) % K=3 Length of Shift Register % # of states = 2^(K-1) = 4 % State can be considered as first two or last two bits of the shift register % 1/n Convolutional Encoder, Rate = 1/2 % n= length of generated codeword for i=1:length(message1) message(i)= num2str(message1(i)); end state=00; next_state=00; code1=[]; message=[message 00]; message=[message]; for t=1:length(message) inp= message(t); state=next_state; if(state==00) if(inp==0) next_state=00; outp=00; else next_state=10; outp= 11; end elseif(state==10) if(inp==0) next_state=01; outp=10; else next_state=11; outp= 01; end elseif(state==01) if(inp==0) next_state=00; outp=11; else next_state=10; outp= 00; end elseif(state==11) if(inp==0) next_state=01; outp=01; else next_state=11; outp= 10; end end code1= [code1 outp]; end for i=1:length(code1) code(i)= str2num(code1(i)); end % code=code1; %*********************************************************************************** %***************** DECODER IMPLEMENTATION*********************** %************************************************************************************ function [messa

Thomas Edison Essay -- essays research papers

Thomas Alva Edison is considered one of the greatest inventors in history. He was born in Milan, Ohio on February 11, 1847 and died in 1931. During his life he patented 1,093 inventions. Many of these inventions are in use today and changed the world forever. Some of his inventions include telegraphy, phonography, electric lighting and photography. His most famous inventions were the phonograph and the incandescent light bulb. Edison did some of his greatest work at Menlo Park. While experimenting on an underwater cable for the automatic telegraph, he found that the electrical resistance and conductivity of carbon varied accordingly to the pressure it was under. This was a major theoretical discovery, which enabled Edison to invent a "pressure relay" using carbon rather than magnets, which was the usual way to vary and balance electrical currents. In February of 1877 Edison began experiments designed to produce a pressure relay that would amplify and improve the audibility of the telephone, a device that Edison and others had studied but which Alexander Graham Bell was the first to patent, in 1876. By the end of 1877 Edison had developed the carbon-button transmitter that is still used today in telephone speakers and microphones. Many of Thomas Edison’s inventions including the carbon transmitter were in response to demands for new products and improvements. In 1877, he achieved his most unique discovery, the phonograph. During the summer of 1877 Edison was attempting to devise for the automatic telegraph a machine that would transcribe a signals as they were received into a form of the human voice so that they could then be delivered as telegraph messages. Some researchers had theorized that each sound, if it could be graphically recorded, would produce a distinct shape resembling short hand, or phonography, as it was known then. Edison hoped to make this concept real by employing a stylus-tipped carbon transmitter to make impressions on a strip of paraffined paper. To his amazement, the barley visible indentations generated a vague sound when the paper was pulled back beneath the stylus. In December 1877 Edison unveiled the tinfoil phonograph, which replaced the strip of paper wrapped in tinfoil. Many people would not believe what they were hearing including a leading French scientist who declared it to be a trick device of a ventri... ...ed whether something might be done, only how. Edison’s career, the fulfillment of the American dream of rags-to-riches through hard work and intelligence, made him a folk hero to his countrymen. In temperament he was an uninhibited egotist, at once a tyrant to his employees and their most entertaining companion, so that there was never a dull moment with him. He was charismatic and courted publicity, but he had difficulty socializing and neglected his family. His shafts at the expense of the "long-haired" fraternity of theorists sometimes led formally trained scientists to depreciate him as anti-intellectual; yet he employed as his aides, at various times a number of eminent mathematical physicists, such as Nicole Tesla and A.E. Kennelly. The contradictory nature of his forceful personality, as well as such eccentricities as his ability to catnap anywhere, contributed to his legendary status. By the time he was in his middle 30s Edison was said to be the best-known American in the world. When he died he was the venerated and mourned as the man who, more than any other, had laid the basis for the technological and social revolution of the modern electrical world.

Comparing Kafkas Metamorphosis and The Stranger (The Outsider) :: comparison compare contrast essays

The Metamorphosis and The Stranger (The Outsider)  Ã‚   Existentialism is defined as a philosophical movement that human beings are completely free and responsible for their own actions.   Existentialists will try not to cause waves and remain completely uninvolved with anyone because they do not want to hurt anybody.  Ã‚   There is absolutely no such thing as an existentialist because he would have to be so uninvolved to the point where he would not be able to live at all.   Although the two stories: The Metamorphosis by Franz Kafka and The Stranger by Albert Camus are very different in approach, their endings are similar in that they both support the basics of existentialism.     Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚   The biggest difference between the two characters: Gregor and Mersault is their physical form.   One has changed physically into a giant insect while the other remains a normal human being.   Another difference is the situation between the characters and their mothers.   Gregor wants to have a relationship with his mother but cannot because of his physical form.   Mersault’s mother is alive and well for part of the novel, but he does not want to take care of her or have anything to do with her.   The two characters are similar in the way that they do not believe in God and will both die lonely and abandoned.  Ã‚     Kafka creates a very lonely and abandoned world for Gregor Samsa in his short novel Metamorphosis.   Gregor is an existentialist character who mutates into a giant bug without reason and no longer has any control over his life.   He becomes completely uninvolved in the way that he does not talk or have any interaction with anyone inside or outside of the family.   He is dehumanized.   Gregor’s mother is disgusted by the looks of him and refuses to see or talk to him.   Gregor is now lonely and abandoned by his family, does not eat and eventually dies.  Ã‚     Ã‚     Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚   In the short novel The Stranger, Mersault is also an existentialistic character.   He does not wish to become involved with anyone, including God and his own mother and does not have any emotion what so-ever when she dies.   Although Mersault does not want to become involved with anyone, he also does not want to create waves, thus he cannot help but to say yes to a friend when he asks him for help.

Nature vs. Nurture Essay -- Heredity and Environment

Abstract Nature vs. nurture has been discussed by philosophers in the past and by scientists more recently. Philosophers such as Plato argued that all knowledge was inherited from your parents and when you were told something you didn’t learn it you were just reminded of it. Aristotle however argued that all humans were born with a blank slate and built on it with influence from there environment. In the 1700’s the empiricists and the internalists took over the argument. They fought through letters explaining there point of views and denouncing the others. This leads to Pavlov coming up with the idea of behaviorism in the early 1900‘s. Behaviorism became the new wave of Psychology and influenced a lean towards the nurture side. It was not effectively argued against until 1928 when Watson published his book. This opened up the floodgates for environmental influences studies. Soon the idea of nurture was the popular excuse for behavior. Studies using animals were the most po pular was in which scientists used to prove a theory, or disprove a theory. The newest studies use human twins to prove nature vs. nurture. An age-old question has been asked for generations before us. What is the reasons behind the development of human behavior? There have been many theories formulated to explain why humans behave the way they do. Explanations vary from demonology to magnetic fluids controlling people’s behaviors. Over time, two theories have remained popular in academic fields such as philosophy and psychology. The surviving theories for behavior stem from physiological and sociological explanations. However, the two explanations have not always been compatible with each other. The famous nature vs. nurture debate over human behavior resulted from conflicting views between proponents of the physiological (nature) and sociological (nurture) explanations. Throughout history, research has swayed popularity back and forth between the theories. Yet, theorists have broken down the line separating nature and nurture. Today, people us both explanations in research to advance the knowledge of human behavior. Thousands of years before the field of psychology, philosophers pondered on human behavior. As early as 350 BC, such philosophers as Plato and Aristotle tried to understand behavior. The question of nature or nurture as the primary drive can be traced to these... ...y the effects of each in development. In these future studies, more groundbreaking advances will be made to aid humans in better understanding human behavior. In the end, that is what both sides of the nature vs. nurture debate intended to accomplish. Bibliography Amsel, A. (1989). Behaviorism, Neobehaviorism, and Cognitivism in Learning   Ã‚  Ã‚  Ã‚  Ã‚  Theory. Hillsdale, NJ: Erlbaum,. Ashcraft, M. (1998). Fundamentals of Cognition. New York, NY: Longman. Barnet, A. (1998). The Youngest Minds. New York, NY: Simon & Schuster. Cowie, F. (1999). What’s Within?. Oxford: Oxford University Press. Devlin, B. (1997). Intelligence, Genes, and Success. New York, NY: Copernicus. Deutschmann, Linda B. (2002). Deviance and Social Control Third Edition. Scarborough,   Ã‚  Ã‚  Ã‚  Ã‚  ON: Nelson Thomson Learning. Fujita, Frank. (2000). Nature vs. Nurture. 3/15/2002 from http://folk.uio.no/roffe/faq/node   Ã‚  Ã‚  Ã‚  Ã‚  11.html McGraw, M. (1995). Beyond Heredity and Environment. San Francisco, CA: Westview   Ã‚  Ã‚  Ã‚  Ã‚  Press. Modgil, S. (1987). B.F. Skinner: Consensus and Controversy. New York, NY: Falmer   Ã‚  Ã‚  Ã‚  Ã‚  Press. Myers, David G. (2001). Psychology Sixth Edition. New York, NY: Worth Publishers.

Intuitions :: Philosophy Judgement Papers

Intuitions This paper examines two attempts to justify the way in which intuitions about specific cases are used as evidence for and against philosophical theories. According to the concept model, intuitions about cases are trustworthy applications of one’s typically tacit grasp of certain concepts. We argue that regardless of whether externalist or internalist accounts of conceptual content are correct, the concept model flounders. The second justification rests on the less familiar belief model, which has it that intuitions in philosophy derive from one’s (often tacit) beliefs. Although more promising than the concept model, the belief model fails to justify traditional philosophical use of intuitions because it is not clear a priori that the beliefs at issue are true. The latter model may, however, legitimize a less a prioristic approach to intuitions. If anything unifies different philosophical methodologies it's some sort of reliance on intuitions. It's remarkable, therefore, how rarely we attempt to justify their employment in philosophy. The intuitions philosophers care about are typically judgements about whether specific (hypothetical or actual) cases are cases of a certain kind. Some philosophical topic such as reference, knowledge or personal identity is under investigation. A theory is proposed and is then tested against our intuitions about specific cases that bear on the topic. In general, if our intuitions contradict what a theory implies about whether, say, S refers to x, or knows that p, or is identical to T, this counts against the theory. If on the other hand, our intuitions match what a theory tells us about particular cases, this usually counts in favor of the theory. All procedures of this sort rest on a principle like I: I Intuitions about specific cases can be used as evidence for and against philosophical theories. This paper is about whether I can be justified. We examine two models, the Concepts Model (CM) and the Belief Model (BM). In our view, neither of them provides a solid foundation for I as it is traditionally applied in philosophy. CM CM has four components: 1. A concept, C, determines what it takes for something to fall under that concept (what it takes for something to be a C). 2. Someone who possesses or grasps a concept, C, doesn't always know explicitly what it takes to be a C because some (maybe most) concepts are understood by us in part tacitly. 3. Intuitions about whether specific cases fall under C are reliably guided by, or generally "match" one's understanding, tacit or otherwise, of C.