Design of Soft Viterbi Algorithm Decoder Enhanced With Non-Transmittable Codewords for Storage Media

Viterbi Algorithm Decoder Enhanced with Non-transmittable Codewords is one of the best decoding algorithm which effectively improves forward error correction performance. HoweverViterbi decoder enhanced with NTCs is not yet designed to work in storage media devices. Currently Reed Solomon (RS) Algorithm is almost the dominant algorithm used in correcting error in storage media. Conversely, recent studies show that there still exist low reliability of data in storage media while the demand for storage media increases drastically. This study proposes a design of the Soft Viterbi Algorithm decoder enhanced with Non-transmittable Codewords (SVAD-NTCs) to be used in storage media for error correction. Matlab simulation was used in this design in order to investigate behavior and effectiveness of SVAD-NTCs in correcting errors in data retrieving from storage media.Sample data of one million bits are randomly generated, Additive White Gaussian Noise (AWGN) was used as data distortion model and Binary Phase- Shift Keying (BPSK) was applied for simulation modulation. Results show that,behaviors of SVAD-NTC performance increase as you increase the NTCs, but beyond 6NTCs there is no significant change and SVAD-NTCs design drastically reduce the total residual error from 216,878 of Reed Solomon to 23,900

A Comparative Study on Performance of SVM and CNN in Tanzania Sign Language Translation Using Image Recognition

Sign language is an effective form of communication for speech impaired people. However, there is a challenge for people without impairment to communicate with speech impaired people because most are unaware of the language. There are several Machine Learning techniques that have been used in sign language translation. However, no study has been found in Tanzania Sign Language which is the sign language used by speech impaired people in Tanzania. This study seeks to compare the performance of SVM and CNN on translating sign language through the image recognition. The study employs Tanzanian Sign Language images as datasets. Principal Component Analysis was employed for feature extraction. Furthermore, the study used Combined 5x2cv F test to compare the two techniques. The findings indicate that CNN scored 96% in all of the parameters which are accuracy, recall, and precision while SVM scored similar rate in precision but lag behind on recall and accuracy. Additionally, the results show that there is significant difference in performance between the techniques. Therefore, the study recommends the use of CNN since it has high accuracy

Fuel Adulteration in Tanzania and its Consequencies: An Overview

A research article was published by Research Journal in Engineering and Applied Sciences 2(4)Adulteration of petrol and diesel fuel with kerosene is very common in Tanzania. It increases the tailpipe emissions of harmful pollutants from vehicles. These leads to this study, which tends to show the rate of emission of CO (carbon II oxide) and PM (Particulate matters) from engines when they are run on adulterated fuel. Petroleum products are essential inputs needed in economic activities, hence a necessity for the economy of any Country. Adulteration of petroleum products especially petrol (motor gasoline) and diesel (high speed diesel (HSD)), has become a serious problem. Expensive consumer products are often adulterated by integrating with cheaper low quality materials having similar physical and chemical properties. Kerosene is the most important domestic fuel for economically weaker sections of society and hence is heavily subsidized. The large differences in the prices of petrol, diesel and kerosene, the easy availability of kerosene and the fact that it is miscible in petrol and diesel, make the unhealthy and unethical practice of adulteration of petrol and diesel a very plausible proposition. Effects of adulteration on the environment and on human health were discussed and possible solutions to combat adulteration of fuel were highlighted

Performance of Soft Viterbi Decoder enhanced with Non-Transmittable Codewords for storage media

The introduction of Non-Transmittable Codewords (NTCs) into Viterbi Algorithm Decoder has emerged as one of the best ways of improving performance of the Viterbi Algorithm Decoder. However, the performance has been tested only in hard decision Viterbi Decoder in telecommunication systems, but not in soft decision Viterbi Decoder and storage media. Most storage media use Reed Solomon (RS) Algorithm Decoder. Yet, the field experience still shows failure of the algorithm in correcting burst errors in reading data from the storage media; leading into data loss. This paper introduces the Soft Viterbi Algorithm Decoding enhanced with Non-Transmittable Codewords for storage media. Matlab software was used to simulate the algorithm and the performance was measured by comparing residual errors in a data length of one million bits. Additive White Gaussian Noise model was applied to distort the stored data. The performance comparison was made against the Reed Solomon code, Normal Soft Viterbi and Hard decision Viterbi enhanced with NTCs. The results showed that the Soft Viterbi Algorithm enhanced with NTCs performed remarkably better by 88.98% against RS, 84.31% against Normal Soft Viterbi and 67.26% against Hard Viterbi enhanced with NTCs

Forward Error Correction for Storage Media: An Overview

Research Article published byInternational Journal of Computer Science and Information Security (IJCSIS), Vol. 13, No. 12, December 2015As the adoption of Information and Communication Technology (ICT) tools in production and service rendering sectors increases, the demand for digital data storage with large storage capacity also increases. Higher storage media systems reliability and fault tolerance are among the key factors that the existing systems sometimes fail to meet and therefore, resulting into data loss. Forward error correction is one of the techniques applied to reduce the impact of data loss problem in digital data storage. This paper presents a survey conducted in different digital data storage companies in Dar es Salam, Tanzania. Data were collected and analyzed using Statistical Package for Social Sciences (SPSS). Secondary data were captured from user and manufacturer technical reports. It was revealed that data loss is still a predominant challenge in the digital data storage industry. Therefore, the study proposes the new storage media FEC model using locked convolutional encoder with the enhanced NTCViterbi decoder

First results of phase 3 trial of RTS,S/AS01 malaria vaccine in african children

Background An ongoing phase 3 study of the efficacy, safety, and immunogenicity of candidate malaria vaccine RTS,S/AS01 is being conducted in seven African countries. Methods From March 2009 through January 2011, we enrolled 15,460 children in two age categories - 6 to 12 weeks of age and 5 to 17 months of age - for vaccination with either RTS,S/AS01 or a non-malaria comparator vaccine. The primary end point of the analysis was vaccine efficacy against clinical malaria during the 12 months after vaccination in the first 6000 children 5 to 17 months of age at enrollment who received all three doses of vaccine according to protocol. After 250 children had an episode of severe malaria, we evaluated vaccine efficacy against severe malaria in both age categories. Results In the 14 months after the first dose of vaccine, the incidence of first episodes of clinical malaria in the first 6000 children in the older age category was 0.32 episodes per person-year in the RTS,S/AS01 group and 0.55 episodes per person-year in the control group, for an efficacy of 50.4% (95% confidence interval [CI], 45.8 to 54.6) in the intention-to-treat population and 55.8% (97.5% CI, 50.6 to 60.4) in the per-protocol population. Vaccine efficacy against severe malaria was 45.1% (95% CI, 23.8 to 60.5) in the intention-to-treat population and 47.3% (95% CI, 22.4 to 64.2) in the per-protocol population. Vaccine efficacy against severe malaria in the combined age categories was 34.8% (95% CI, 16.2 to 49.2) in the per-protocol population during an average follow-up of 11 months. Serious adverse events occurred with a similar frequency in the two study groups. Among children in the older age category, the rate of generalized convulsive seizures after RTS,S/AS01 vaccination was 1.04 per 1000 doses (95% CI, 0.62 to 1.64). Conclusions The RTS,S/AS01 vaccine provided protection against both clinical and severe malaria in African children. (Funded by GlaxoSmithKline Biologicals and the PATH Malaria Vaccine Initiative; RTS,S ClinicalTrials.gov number, NCT00866619 .