Cointegration growth, poverty and inequality in Sudan

This analytical review explores the links between growth, poverty and inequality in Sudan for the period 1956-2003. This paper build upon different models to investigate empirically the relationship between economic growth – as measured by GDP per capita growth- and inequality as measured by Gini coefficient (the growth, inequality and poverty triangle hypotheses), using data from the national and international sources. The paper tries to answer the following questions: i) whether growth, inequality and poverty are cointegrated, ii( whether growth Granger causes inequality, iii) and whether inequality Granger causes poverty. Finally, a VAR is constructed and impulse response functions (IRFs) are employed to investigate the effects of macroeconomic shocks. The results suggest that growth; poverty and inequality are cointegrated when poverty and inequality are the dependent variable, but are not cointegrated when growth is the dependent variable. In the long- run the causality runs from inequality, poverty to growth, to poverty. In the short-run causal effects, runs from poverty to growth. Thus, there is unidirectional relationship, running from growth to poverty, both in the long- run and short rungrowth; poverty; inequality; Sudan

Social protection and economic growth in the Sudan: Trends, perspectives, cointegration and causality

This paper takes into account the recent role of social protection on economic growth as a socio-economic-political stabilizer. Social protection outcome in Sudan is influenced by limited targeting actions with very low interventions between results in economic growth and accesses to basic social services. These may affects the social protection contributes to the process of development in the Sudan during the period under consideration. The results show that more social spending increase output which enhances GDP per capita growth by 0.5% with 3.1% towards convergence equilibrium in the long run. Moreover, universal approach and expanded cover to social protection services which aim at building a social protection as a productive factor may have contributed to enhancing income security, education and health outcomes, reducing the poverty, income inequality, socio-political stability, encouraged poor productive activities and enhancing economic growth lead to sustainable development.Social Protection, Growth, Cointegration, causality, Sudan

Arabic Spelling Correction using Supervised Learning

In this work, we address the problem of spelling correction in the Arabic language utilizing the new corpus provided by QALB (Qatar Arabic Language Bank) project which is an annotated corpus of sentences with errors and their corrections. The corpus contains edit, add before, split, merge, add after, move and other error types. We are concerned with the first four error types as they contribute more than 90% of the spelling errors in the corpus. The proposed system has many models to address each error type on its own and then integrating all the models to provide an efficient and robust system that achieves an overall recall of 0.59, precision of 0.58 and F1 score of 0.58 including all the error types on the development set. Our system participated in the QALB 2014 shared task "Automatic Arabic Error Correction" and achieved an F1 score of 0.6, earning the sixth place out of nine participants.Comment: System description paper that is submitted in the EMNLP 2014 conference shared task "Automatic Arabic Error Correction" (Mohit et al., 2014) in the Arabic NLP workshop. 6 page

Register Transfer Level Implementation Of Pooling - Based Feature Extraction For Finger Vein Identification

Recently, finger vein biometric identification methods have had more attention among the researchers due to its various advantages such as: uniqueness to individuals, immunity to ages and invisibility to human eye (hard to duplicate). Many improvements methods were utilized to increase the speed and accuracy of the identification. Feature extraction techniques based on global feature extraction such as Principle Component Analysis (PCA) were implemented. However, the results did not show robustness to occlusions and misalignments on the finger vein images. Therefore, local feature extraction techniques were used to overcome these issues. A pooling based feature extraction technique for finger vein identification was implemented in this research. The proposed algorithm extracted the local feature information of the finger vein pattern (patches), and used these patches to improve the robustness of the identification. The algorithm was mainly inspired by spatial pyramid pooling in generic image classification combined with PCA. With patch size = 4, four pyramid levels = [1x1, 2x2, 3x3, 4x4] and ~38 % dimension reduction on the extracted features vector (10 PCA coefficient), the accuracy of the identification was 88.69 % which was higher than PCA by 10.10%. The proposed algorithm was implemented on hardware using Verilog-HDL, and targeting Field Programmable Gate Array (FPGA) applications. The result showed an outstanding speed improvement compared to software implementation. The time consumed by the hardware for extracting the features of one image was 310X time faster than the consumed time for software implementation. With those improvements in accuracy and the speed, the proposed algorithm contributes to the advancement of finger vein biometric system