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

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

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

Assessment of Tree Species Diversity, Family Composition and Diameter Size Class of Tree Species in Igbo-Olua Sacred Groove, Ondo State, Nigeria

This study was carried out to assess the tree species diversity, family composition and diameter size distribution of the tree species in Igbo-Olua sacred groove, Ondo state, Nigeria using appropriate standard techniques. A total of 34 tree species distributed in 23 families were recorded.  Sterculiaceae family (66) had the highest number of individual stem per ha while Moraceae family had the highest number in terms of tree species per hectare (7). The distribution of the diameter structure is typical of the natural forest type with high number of tree species in the smaller size classes or interval (12.5) and the number of tree species decreases with increasing size class or interval. Diversity measures obtained included Shannon-Weiner index (3.09), Evenness (0.64) and Margalef index (6.36). Awakening the consciousness of people towards the protection of sacred groves has practical implications on their survival. Hence government and other allied institutions should gear efforts towards grove conservation

Acute Kidney Injuries in Children with Severe Malaria: A comparative study of diagnostic criteria based on serum cystatin C and creatinine levels

Objectives: Serum creatinine levels are often used to diagnose acute kidney injury (AKI), but may not necessarily accurately reflect changes in glomerular filtration rate (GFR). This study aimed to compare the prevalence of AKI in children with severe malaria using diagnostic criteria based on creatinine values in contrast to cystatin C. Methods: This prospective cross-sectional study was performed between June 2016 and May 2017 at the University of Ilorin Teaching Hospital, Ilorin, Nigeria. A total of 170 children aged 0.5–14 years old with severe malaria were included. Serum cystatin C levels were determined using a particle-enhanced immunoturbidmetric assay method, while creatinine levels were measured using the Jaffe reaction. Renal function assessed using cystatin C-derived estimated GFR (eGFR) was compared to that measured using three sets of criteria based on creatinine values including the Kidney Disease: Improved Global Outcomes (KDIGO) and World Health Organization (WHO) criteria as well as an absolute creatinine cut-off value of >1.5 mg/dL. Results: Mean serum cystatin C and creatinine levels were 1.77 ± 1.37 mg/L and 1.23 ± 1.80 mg/dL, respectively (P = 0.002). According to the KDIGO, WHO and absolute creatinine criteria, the frequency of AKI was 32.4%, 7.6% and 16.5%, respectively. In contrast, the incidence of AKI based on cystatin C-derived eGFR was 51.8%. Overall, the rate of detection of AKI was significantly higher using cystatin C compared to the KDIGO, WHO and absolute creatinine criteria (P = 0.003, <0.001 and <0.001, respectively). Conclusion: Diagnostic criteria for AKI based on creatinine values may not indicate the actual burden of disease in children with severe malaria. Keywords: Biomarkers; Acute Kidney Injury; Renal Failure; Glomerular Filtration Rate; Cystatin C; Creatinine; Malaria; Nigeria

Machine Learning Applications in Renewable Energy (MLARE) Research: A Publication Trend and Bibliometric Analysis Study (2012-2021)

This study examines the research climate on machine learning applications in renewable energy (MLARE). Therefore, the publication trends (PT) and bibliometric analysis (BA) on MLARE research published and indexed in the Elsevier Scopus database between 2012 and 2021 were examined. The PT was adopted to deduce the major stakeholders, top-cited publications, and funding organizations on MLARE, whereas BA elucidated critical insights into the research landscape, scientific developments, and technological growth. The PT revealed 1218 published documents comprising 46.9% articles, 39.7% conference papers, and 6.0% reviews on the topic. Subject area analysis revealed MLARE research spans the areas of science, technology, engineering, and mathematics among others, which indicates it is a broad, multidisciplinary, and impactful research topic. The most prolific researcher, affiliations, country, and funder are Ravinesh C. Deo, National Renewable Energy Laboratory, United States, and the National Natural Science Foundation of China, respectively. The most prominent journals on the top are Applied Energy and Energies, which indicates that journal reputation and open access are critical considerations for the author’s choice of publication outlet. The high productivity of the major stakeholders in MLARE is due to collaborations and research funding support. The keyword co-occurrence analysis identified four (4) clusters or thematic areas on MLARE, which broadly describe the systems, technologies, tools/technologies, and socio-technical dynamics of MLARE research. Overall, the study showed that ML is critical to the prediction, operation, and optimization of renewable energy technologies (RET) along with the design and development of RE-related materials

An evaluation of the tourism-induced environmental Kuznets curve (T-EKC) hypothesis: Evidence from G7 countries

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This paper analyzes the legitimacy of the Environmental Kuznets Curve (EKC) hypothesis for a group of seven (G7) countries over the period 1995–2015. In addition to testing the EKC speculation, the authors also would like to understand the ways in which increases in renewable energy consumption and the international tourism receipt affect the CO2 emissions in G7 countries, because the energy and tourism sectors may have considerable direct impacts on CO2 emissions. In this investigation, a panel bootstrap cointegration test and an augmented mean group (AMG) estimator were applied. The empirical findings indicate that the tourism-induced EKC hypothesis is valid only for France. Additionally, it was detected that a rise in renewable energy consumption has a negative (reduction) impact on CO2 emissions in France, Italy, the UK, and the US. However, an increase in the receipt of international touristm has a positive (additional) impact on Italy’s CO2 emissions. Hence, this country’s decision-makers should re-review their tourism policy to adopt a renewable-inclusive one for sustainable tourism and the environment

Chapter 11 - Near-term climate change: Projections and predictability

This chapter assesses the scientific literature describing expectations for near-term climate (present through mid-century). Unless otherwise stated, "near-term" change and the projected changes below are for the period 2016-2035 relative to the reference period 1986-2005. Atmospheric composition (apart from CO2; see Chapter 12) and air quality projections through to 2100 are also assessed

An Assessment of the UK’s Trade with Developing Countries under the Generalised System of Preferences

The European Union (EU) Generalised System of Preferences (GSP Scheme) grants preferential treatment to 88 eligible countries. There are, however, concerns that the restrictive features (such as Rules of Origin, Low Preference Margin and Low Coverage) of the existing scheme indicate gravitation towards commercial trade agenda to which efficiency imperatives appear subordinated. Whether these concerns are genuine is an empirical question whose answer largely determines whether, after Brexit, the UK continues with the existing specifics of the EU scheme or develops a more inclusive UK-specific GSP framework. This study quantitatively examines the efficiency of the EU GSP as it relates to UK beneficiaries from 2014 to 2017. We draw on the descriptive efficiency estimation (The utilisation Rate, Potential Coverage Rate, and the Utility Rate) using import data across 88 beneficiary countries and agricultural products of the Harmonised System Code Chapter 1 to 24. Asides the Rules of Origin that, generally, harm the uptake of GSP, low preference margin is found to cause low utilisation rates in a non-linear manner. Essentially, a more robust option (such that allows “global Cumulation” or broader product coverage) could, substantially, lower the existing barriers to trade and upsurge the efficiency of the GSP scheme