Error Simulation Enviroment For The Dicode Pulse Position Modulation Essay

Error Simulation Enviroment For The Dicode Pulse Position Modulation - Essay Example The number of erasure error symbols that is erased is within the capacity of the decoder in his recovery of the original data. In this test design, the number of erasure error symbols must be less or equal to 8 symbols per codeword. Figures (7.2) & (7.3) show the system input/output signals. Figure (7.2) shows the performance of the system when the number of erasure symbols equals 8 per codeword, while the figure (7.3) displays the system signals when the number of erasure symbols equals 5. In these figures, the fail output signal is logic 0. This means that the system has successfully decoded the original codeword. We can add or delete erasures by updating lines 294 and 295 inside the code. The number of erasure error symbols that is erased is greater than the capacity of the decoder to recover the original data. In this test design, the number of erasure symbols is greater than 8 symbols per codeword. Figure (7.4) shows the system input/output signals when the number of erasure sym bols equals 9 per codeword. In this figure, the fail output signal is logic 1, which means that the system has failed to decode the original codeword. We can add or delete erasures by updating lines 294 and 295. A VHDL test bench program Appendix ( ) has been built to provide an environment where errors can be injected into the system. According to equation (6.7), the designed system has the ability to correct up to 4 erasure errors only. Above this number, the system will fail to decode the original message.

Research Proposal Essay Example | Topics and Well Written Essays - 4000 words

Research Proposal - Essay Example Information on the prevalence of obesity within the military is limited and usually relies on reported data on height and weight or on unrepresented smaller samples. According to Rona et al (2010), BMI is the usual indicator to assess overweight and obesity among army personnel but its validity is questionable because some people may have huge bodies but not obese. As such, in this proposal the author will make reasoned judgements and draw conclusions from these findings along with evaluating the significance of the assessment criteria used in monitoring obesity. Furthermore, the proposal also seeks to highlight the reason why the prevalence rate of obesity at the time of recruitment is low and subsequently increases over the years. The problem of obesity affects the military personnel in many ways. According to the World Health Organisation (2000) ‘Obesity is diagnosed as having a body mass index of 25 and over’. Thus the Ministry of Defence has adopted the WHO BMI char t and all personnel have their measurements taken and calculated as above and classified according to this chart. This will be further reviewed within this proposal. CONCLUSION Prevalence rates of obesity from this study should be viewed with caution as the sample studied is not representative of the UK Armed Forces. The true percentage of obesity could be higher since the sample is drawn from a small number of people. This research proposal aims to use a quantitative research method to evaluate the use of BMI and waist circumference to monitor obesity levels within the RAF. In turn this research proposal will highlight how BMI and waist circumference monitoring negatively reflects the obesity statistics in RAF personnel. Consequently the results of this research proposal will be used to: Highlight the importance of accurate measurements to assess obesity. In turn it will provide evidence to HQ Air to rethink current policy and perhaps adopt a tri service approach to tackling this p roblem in the future. INTRODUCTION Preventing obesity is essential within the military, not only to decrease the risk of cardiovascular disease and other chronic conditions (Ogden, et al 2007) but also to increase fitness and operational preparedness. This is essential since it improves their performance and physical fitness. The prevalence of obesity in the United Kingdom Armed Forces has not previously been monitored. Military personnel undergo annual health examination dependent on trade/branch (Joint Service Publication, 346 Chapter 2, 2008 will be hereafter referred to as JSP). Despite these examinations, there appears to be a requirement for a more robust information system to estimate obesity within the military (Rona et al, 2011). According to the JSP 346 the assessment process appears to rely heavily on how healthcare staff interprets height and weight measurements in order to calculate Body Mass Index (BMI). BMI provides the most useful population-level measure of obesity as it is the same for both sexes and for all ages of adults (WHO, 2012). The notion that BMI should be used when assessing obesity is backed by US research (Rona, 2012). However, the drawback of this method is that an increase in BMI may not necessarily mean that a person is obese since military personnel have greater muscle mass than ordinary citizens. In 2006, the National Institute for Health and Clinical