Physicochemical evaluation of industrial potentialities of Getso Kaolin

Fossil fuel depletion has prompted the need for alternative sources of energy and income generation. Kaolin is an abundant solid mineral found in many parts of Nigeria, whose economy is over dependent on oil. However, lack of detailed study, characterization and analysis made it difficult for investors to show interest in this manufacturing sector. In this study kaolin from Getso, Kano state, northern part of Nigeria was characterized using pH measurement, X-Ray Fluorescence Analysis (XRF), Thermogravimetric-Derivative Thermal Analysis (TG-DTA), X-Ray Diffraction (XRD) and Fourier Transform Infra-Red Analysis (FTIR) to establish its potentialities for industrial applications. The XRF analysis indicated that Getso kaolin consists mainly of silica, 47.07% and alumina, 39.20% with other metal oxides like iron (III) oxide as minor component, while the XRD and FTIR results indicated that the main mineral present in the sample is kaolinite with small amounts of mica and quartz. The pH was found to be 7.2, which qualified it for very good industrial applications. The chemical composition of Getso kaolin was found to be comparable to the theoretical composition and that of commercial kaolin making it suitable for some industrial applications like paper, adhesives, plastics, fiberglass, rubber and paints.Keywords: Getso Kaolin, Characterization, Theoretical kaolinit

Comparative evaluation of genetic algorithm-based test case optimization

Software testing is a crucial phase in software development process although it consumes more time and cost of software development. Researchers have proposed several approaches focusing on helping software testers to reduce the execution time and cost of the testing process. Test case optimization is a multi-objective approach that has become one of the best solutions to overcome these problems. Test case optimization focusing on reducing the number of test cases in the test suite that may reduce the overall testing time, cost and effort of software testers especially in regression testing. This paper presents the comparative evaluation between test case optimization techniques that are based on Genetic Algorithm (GA). The evaluation is based on five criteria i.e. technique objectives, applied fitness function, contributions, the percentage of the reduced test cases, fault detection capability, and technique limitations. The evaluation results able identify the gaps in the existing GAbased test case optimization approaches and provide insight in determining the potential research directions in this area.Keywords: Test case optimization, regression testing, multi-objectives, genetic algorithm, software testin

On Solution of Fractional Differential Equations Using Osler Definition in Hilbert Space

In this paper we consider the fractional differential equations with constant coefficients, using Osler definition.......

Detection of asphyxia in infants using deep learning Convolutional Neural Network (CNN) trained on Mel Frequency Cepstrum Coefficient (MFCC) features extracted from cry sounds

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Agarwood oil quality classifier using machine learning

Agarwood oil is known as one of the most expensive and precious oils being traded. It is widely used in traditional ceremonies and religious prayers. Its quality plays an important role on the market price that it can be traded. This paper proposes on a proper classification method of the agarwood oil quality using machine learning model k-nearest neighbour (k-NN). The chemical compounds of the agarwood oil from high and low quality are used to train and build the k-NN classifier model. Correlation reduce the dimension of the data before it is being fed into the model. The results show a very high accuracy (100%) model trained and can be used to classify the agarwood oil quality accurately. Keywords: agarwood oil; k-nearest neighbours; quality; machine learning

Application of direct bioautography and SPME-GC-MS for the study of antibacterial chamomile ingredients

The isolation and characterization of antibacterial chamomile components were performed by the use of direct bioautography and solid phase microextraction (SPME)-GC-MS. Four ingredients, active against Vibrio fischeri, were identified as the polyacetylene geometric isomers cis- and trans-spiroethers, the coumarin related herniarin, and the sesquiterpene alcohol (-)-alpha-bisabolol

Reply to commentary on "History of spinal neurosurgery and spine societies"

Scientific Assessment and Innovation in Neurosurgical Treatment Strategie

PERFORMANCE OF YIELD AND YIELD CONTRIBUTING CHARACTERISTICS OF BC2F3 POPULATION WITH ADDITION OF BLAST RESISTANT GENE

ABSTRACTThe study was carried out in the University Putra Malaysia (UPM) Rice Research Centre to evaluate the yield performance of newly developed selected blast resistant plants of BC2F3 generations derived from a cross between MR263, a high yielding rice variety but blast susceptible and Pongsu Seribu 1, donor with blast resistant (Pi-7(t)and Pi-d (t)1, Pir2-3(t)genes and qLN2 QTL), Malaysian local variety. On the basis of assessed traits, the plants 12, 6, 7, 5, 21, 22, 5, 26, 11, 8, 10, 13 and 15 had the higher yield, blast resistant and good morphological traits. More than 70% heritability was found in days to maturity, plant height, tiller numbers per hill, and panicle per hill, 80% heritability was found in filled grain and yield per hill and more than 90% heritability was found in grain length, grain width and seed weight. Cluster analysis based on the traits grouped 30 plants along with MR263 into seven clusters. According to PCA, the first four principal components account for about 69.3% total variation for all measured traits and exhibited high correlation among the characteristics analyzed