Predicting fraud in mobile money transfer using case-based reasoning

This paper proposes an improved CBR approach for the identification of money transfer fraud in Mobile Money Transfer (MMT) environments. Standard CBR capability is augmented by machine learning techniques to assign parameter weights in the sample dataset and automate k-value random selection in k-NN classification to improve CBR performance. The CBR system observes users’ transaction behaviour within the MMT service and tries to detect abnormal patterns in the transaction flows. To capture user behaviour effectively, the CBR system classifies the log information into five contexts and then combines them into a single dimension, instead of using the conventional approach where the transaction amount, time dimensions or features dimension are used individually. The applicability of the proposed augmented CBR system is evaluated using simulation data. From the results, both dimensions show good performance with the context of information weighted CBR system outperforming the individual features approach

MODELLING HEALTH MAINTENANCE ORGANIZATIONS PAYMENTS UNDER THE NATIONAL HEALTH INSURANCE SCHEME IN NIGERIA

The Nigerian National Health Insurance Scheme (NHIS) is set up to ensure equitable payment of health care bills combining and prudently reducing cost-burden distribution for residents, versus high health care costs. Health maintenance organizations (HMO) are limited liability companies which could be established by private, public or individual entities with the main aim of being players in the scheme. This paper explored logistic regression (LR), linear discriminant analysis (LDA) and random forest (RF) in determining the factors that could determine if an HMO will cover full or part of an individual's healthcare bill. The results do not show a significant difference in the classification accuracies of the three methods. Inferring that the highest number of the Nigerian residents that make use of the NHIS lie between the 31-40yrs age bracket and that largely, ailment classification and the insured’s age are key determining factors of whether an HMO would cover all or part of the bill

TRCM: a methodology for temporal analysis of evolving concepts in Twitter

The Twitter network has been labelled the most commonly used microblogging application around today. With about 500 million estimated registered users as of June, 2012, Twitter has become a credible medium of sentiment/opinion expression. It is also a notable medium for information dissemination; including breaking news on diverse issues since it was launched in 2007. Many organisations, individuals and even government bodies follow activities on the network in order to obtain knowledge on how their audience reacts to tweets that affect them. We can use postings on Twitter (known as tweets) to analyse patterns associated with events by detecting the dynamics of the tweets. A common way of labelling a tweet is by including a number of hashtags that describe its contents. Association Rule Mining can find the likelihood of co-occurrence of hashtags. In this paper, we propose the use of temporal Association Rule Mining to detect rule dynamics, and consequently dynamics of tweets. We coined our methodology Transaction-based Rule Change Mining (TRCM). A number of patterns are identifiable in these rule dynamics including, new rules, emerging rules, unexpected rules and ?dead' rules. Also the linkage between the different types of rule dynamics is investigated experimentally in this paper

Pozzolanic properties of Waste Agricultural Biomass - African Locust Bean Pod Waste

The increase in agricultural waste such as African locust bean pod have resulted in endangering the life of plants and animals. Researchers have found out ways that this environmental pollution can be of positive relevance by recycling the waste to be re-used or reduce to ensure a cleaner and healthier environment. African locust bean pod was ashed and the pozzolanic properties were investigated. The pod was dried, blended and ashed in a furnace at 500°C for two (2) hours; different analysis was carried out on the ash obtained to prove the pozzolanic properties, such as sieve analysis to determine the particle size distribution; reaction of calcium hydroxide with the ash in relation to time which proved that pozzolanic reactivity increases with time, comparison of hydration of Portland cement with ashed locust bean pod mixture and compressive strength test

Matrix Diagonalization as a Board Game: Teaching an Eigensolver the Fastest Path to Solution

Matrix diagonalization is at the cornerstone of numerous fields of scientific computing. Diagonalizing a matrix to solve an eigenvalue problem requires a sequential path of iterations that eventually reaches a sufficiently converged and accurate solution for all the eigenvalues and eigenvectors. This typically translates into a high computational cost. Here we demonstrate how reinforcement learning, using the AlphaZero framework, can accelerate Jacobi matrix diagonalizations by viewing the selection of the fastest path to solution as a board game. To demonstrate the viability of our approach we apply the Jacobi diagonalization algorithm to symmetric Hamiltonian matrices that appear in quantum chemistry calculations. We find that a significant acceleration can often be achieved. Our findings highlight the opportunity to use machine learning as a promising tool to improve the performance of numerical linear algebra.Comment: 14 page

Particle morphology of CuCl2 droplets in evaporative spray drying of aqueous slurries by laser diffraction and microscopy

New empirical correlations that predict the evaporative spray drying behavior of slurries are developed in this paper. The analysis examines a single droplet of CuCl2 solution in a continuum drying media. The results indicate a combination of convection and spray drying modes could improve the drying process. Validation of the experimental results involves comparisons based on non-dimensional analysis. The Ohnesorge number has a greater effect on the particle diameter than the Nusselt numbers. Analytical models of heat and mass Spalding numbers are developed for the aqueous solution, subject to various drying conditions. Also, the effect of temperature on the atomization flow rate is reported. The Log-normal distribution provides the most accurate fit for the measured data. Particle size diameters are predicted and compared with experimental results using SEM and laser diffraction. The results indicate the average particle size is about 229.5 μm

Evidence for glutamate as a neuroglial transmitter within sensory ganglia

This study examines key elements of glutamatergic transmission within sensory ganglia of the rat. We show that the soma of primary sensory neurons release glutamate when depolarized. Using acute dissociated mixed neuronal/glia cultures of dorsal root ganglia (DRG) or trigeminal ganglia and a colorimetric assay, we show that when glutamate uptake by satellite glial cells (SGCs) is inhibited, KCl stimulation leads to simultaneous increase of glutamate in the culture medium. With calcium imaging we see that the soma of primary sensory neurons and SGCs respond to AMPA, NMDA, kainate and mGluR agonists, and selective antagonists block this response. Using whole cell patch-clamp technique, inward currents were recorded from small diameter (<30 µm) DRG neurons from intact DRGs (ex-vivo whole ganglion preparation) in response to local application of the above glutamate receptor agonists. Following a chronic constriction injury (CCI) of either the inferior orbital nerve or the sciatic nerve, glutamate expression increases in the trigeminal ganglia and DRG respectively. This increase occurs in neurons of all diameters and is present in the somata of neurons with injured axons as well as in somata of neighboring uninjured neurons. These data provides additional evidence that glutamate can be released within the sensory ganglion, and that the somata of primary sensory neurons as well as SGCs express functional glutamate receptors at their surface. These findings, together with our previous gene knockdown data, suggest that glutamatergic transmission within the ganglion could impact nociceptive thresholdpublished_or_final_versio

Evaluation of climate variability impact on sources of water supply

Climate is a key factor in water availability and accessibility on both the earth surface and below the earth surface. The study evaluated climate variability impact on sources of water supply in Offa, Kwara State, Nigeria. The study utilized both primary and secondary source of data. Household proximity to water sources was computed using the percentages of household that falls within the basic indicator for measuring water access by World Health Organization. Correlation and multiple regression analyses were used to determine the relationship between the climatic variables and water supply; and groundwater level in the study area. Pearson Product Moment Correlation was employed to establish the association between climate and water supply; and groundwater level. Multiple regression analysis was used to examine the relationship between water supply and the selected climatic variables. Trend analysis was used to determine the trend of the selected climatic variables in the study area. The result revealed that rainfall amount, minimum and maximum temperature, and evaporation exhibit an upward trend which are not statistically significant. The fluctuating trend in these climatic variables, though not statistically significant are probably related to the already established changes in climatic parameters in Nigeria. The result also showed that the spatial distributions of public boreholes in the study area are heterogeneous in nature. The study recommended that the clustering of water sources, especially the shallow wells should be discouraged to avoid over abstraction of groundwater in the study area

Monitoring and Evaluating Fiscal Solvency in times of Crisis: Framework for Enhancing Revenue Generating Capacity in Nigeria

This study contributes to the existing literature on the ​fundamentals of public finance management efforts by sub-national governments in developing economies. The paper's primary contribution is finding that choice of public policy intervention by a central government requires establishing frameworks that first monitors individual efforts of sub-national government before approval of such interventions are made. It also suggests the application of certain methodologies for performance measurement in public finance section of the government

Heat and mass transfer in a copper oxy-chloride spray reactor for thermochemical hydrogen production

A new predictive model is developed in this paper to analyze the height of the reactor for continuous production of copper oxy-chloride in the thermochemical Cu–Cl cycle for hydrogen production. The volumetric phase fraction is used to develop an energy balance and integrated spatially to determine the inlet temperature of nitrogen and steam mixtures for continuous production of copper oxy-chloride. The effects of the ratio of mixing power to mass of the suspended particle, the ratio of interfacial surface area of the gas film to the volume of liquid, and diameter of the steam/nitrogen bubble in the reactor, on the height of the reactor are reported for a production capacity of 3 kg of hydrogen per day. Results indicate that a smaller ratio of interfacial surface area to volume of liquid significantly reduces the height of the reactor