Effect of Public Educational Spending and Macroeconomic Uncertainty on Schooling Outcomes: Evidence from Nigeria

This study examines the effect of government educational spending and macroeconomic uncertainty on schooling outcomes in Nigeria using the econometric methods of cointegration and error correction mechanism together with the vector autoregression methodology. The results indicate that schooling outcome cointegrated with all the identified explanatory variables. The study found that public educational spending impacts positively on schooling outcome while macroeconomic instability impacts negatively. The variance decomposition analysis shows that “own shocks” constitute the predominant source of variation in schooling outcome. The impulse response analysis shows that any unanticipated increase in the macroeconomic uncertainty rate will have a contractionary impact on literacy rate. The policy implication of this study is that government should pay attention to policies that enhance educational attainment through adequate public social investment under stable macroeconomic environment.Public spending; education expenditures; education/schooling outcomes; macroeconomic uncertainty.

Adamawa primary education research: final report

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Adamawa primary education research: executive summary

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Classification of infectious diseases via hybrid k-means clustering technique

Identifying groups of objects that are similar to each other but different from individuals in other groups can be intellectually satisfying, profitable, or sometimes both. Kmeans clustering is one of the well known partitioning algorithms. But basic K-means method is insufficient to extract meaningful information and its output is very conscious to initial positions of cluster centers. In this paper, data of infectious diseases were analyzed with the hybrid K-means clustering technique. This method is developed to preprocess the dataset that will be used in the K-means clustering problems. Specifically, it performs K-means clustering on preprocessed dataset instead of raw dataset to remove the impact of irrelevant features and selection of good initial centers. The experimental results revealed that all the three water related diseases are grouped together in one cluster for both KGHK and FMCK data sets. They also show the high prevalence compared to airborne particle related diseases in the other group. The study concludes that K-means clustering method provides a suitable tool for assessing the level of infectious diseases

A comparative study and performance evaluation of similarity measures for data clustering

Clustering is a useful technique that organizes a large quantity of unordered datasets into a small number of meaningful and coherent clusters. A wide variety of distance functions and similarity measures have been used for clustering, such as squared Euclidean distance, Manhattan distance and relative entropy. In this paper, we compare and analyze the effectiveness of these measures in clustering for high dimensional datasets. Our experiments utilize the basic K-means algorithm with application of PCA and we report results on simulated high dimensional datasets and two distance/similarity measures that have been most commonly used in clustering. The analyzed results indicate that Squared Euclidean distance is much better than the Manhattan distance method

Occupational mobility in engineering profession (craftman and artisan) in Oyo State, Nigeria.

This paper evaluate occupational mobility in engineering professional in Oyo State of Nigeria with the goal assessing causes and readiness of the professionals to return to the profession when the hindering factors are removed as well as sufficiency of the survey instrument in addressing the research problems. The study was conducted using a well structured questionnaire administered in 20 local government of Oyo State, Nigeria representing the sample space of 0.424. The Cronbach’s alpha of the reliability test of 0.453 was returned for the scale mean statistics of 11516.83 and variance of 0.0000007 showing that the survey instrument was sufficient and could be relied upon. The result of the socio economic analysis showed that 80% of the respondents were married while (15%) were single and the rest (5%) were divorced. The age distribution of the respondents ranged between greater than 50 years groups (12%) and 30 -39 years group (39%).The result of the analysis of job characteristics of the respondents showed that the longer the year of graduation, the lesser the number of graduates still in the business. The cross table analysis of the socio-economic indices with the job status of the respondents showed that marital status and level of education does not have significant effects on the job status of the respondents (whether still practicing or not) because 1.454 and 5.223 returned for both marital status and level of education are not significant (P<0.05). Also, the contingency table analysis of the effects of the skill acquisition methods showed that more of the respondents who acquired their skill via Technical School (70%) are willing to go back to the professions. However, for those who acquired their skill through Learning/artisanship, less than average (32%) of the respondents are ready to return to the profession. Lastly, the establishment of the regression model for the relationship between the proportion of the people wishing to go back to the profession and year of practicing the profession provide a necessary impetus for addressing the Job mobility problem faced by the profession

The female teacher trainee scholarship scheme: operational research study for UNICEF Girls Education Project Phase 3 (GEP3)

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Effect of cutting speed on cutting torque and cutting power of varying kenaf-stem diameters at different moisture contents

This study focused on the development of an efficient cutting system for kenaf harvesters. Laboratory experiments were conducted on cutting kenaf stems of variety V36 using a rotary serrated cutting system. The Torque Trak 10k data acquisition system was used for the experiment. The effect of cutting speed on cutting torque and cutting power of varying kenaf-stem diameters and at different moisture contents was investigated. Four different cutting speeds of 400 rpm, 500 rpm, 600 rpm and 700 rpm were used. The experiments showed that cutting speed had significant effect on cutting torque and cutting power requirements. The cutting speed was directly proportional to the specific cutting power, while the cutting torque was inversely proportional to the moisture content. Increasing the rotational speed from 400 rpm to 700 rpm reduced the cutting torque from 1.91 Nm to 1.49 Nm. The cutting torque was observed to be higher at lower moisture levels of less than 35%. As the moisture content was increased to values greater than 35%, the torque decreased considerably. This invariably indicated that an increase in moisture content reduced cutting torque as shown by the model coefficient of moisture content. Thus, more energy saving and hence, high efficiency, were achieved at high cutting speeds as compared to impact cutting system at similar speeds. Regression equations capable of predicting cutting torque and cutting power at varying stem diameters and cutting speeds, in relation to kenaf stem moisture contents, are presented