bluuebunny/crossref_metadata_2025_split huggingface dataset:
Green Economy: The Role of Estate Surveyors and Valuer
Authors: Ajibola M. O. , Oluwunmi A. O. , Kabiamaowei A. I. , Owolabi D. R. , Akinwale O. M. 
Published: October 2019

Abstract
The continuous existence of man is dependent on the free goods and services (e.g. water, air purification, fisheries, timber production and nutrient cycling) provided by his natural environment. Due to the public nature of these goods and services, they are not traded in the open markets hence, they are regarded as not having market prices. As a result, the current economic system fails to capture their losses and this may continue for long if care is not taken. Unless economic decisions (and the associated implications of development options) are made based on valuing the invisible aspects of ecosystems, unfriendly environmental decisions may continue to be taken that will culminate into economic, social and environmental cost which may be unmanageable. It is therefore expedient that a Green Economy with consideration for the immense value of biodiversity and ecosystems be incorporated by both corporate and governmental agencies so as to ensure a sustainable development progression in an economy. In achieving sustainable green economy, the appropriate stakeholders should pay particular attention to the value of natural capital in any policy decision. Hence, this study examined the roles of Estate Surveyors and Valuers (ESVs) in a green economy. Exploratory approach was employed in carrying out the study. Literature review technique was adopted to examine the various aspects of the economy and the roles of ESVs that help in greening the economy. The study identify the roles of ESVs in greening an economy to include: ensuring the use of renewable energy instead of fossil fuel in their management properties, adoption of efficient technology that consumes less energy, advising on waste minimization and appropriate waste management approaches, giving consideration to ecosystem services while carrying out development valuation and finally promoting decent jobs that takes cognisance of employee’s welfare, job security and career prospects. The study therefore recommends that the time has come for Estate Surveyors and Valuers to be actively involved in greening Nigerian economy.
Analytical Form of Sputtering in Relation to Surface Binding Energy for Different Types of Perovskites
Authors: Akinpelu Akinwumi , Oyewande Oluwole E. , Adaeze  , Emuobor Arijaje T. , Olawole C , Ogunrionola I , Paul Ogundile O. 
Published: October 2019

Abstract
In recent years, perovskite materials have been the focus in solar cell fabrication industry. Herein, an investigation was conducted on the effect of ion-solid interactions on factors are responsible for differences in the properties of these perovskite materials by using a Monte Carlo simulations of ion beam surface sputtering. A connection was established between the experimental efficiencies of solar cells of these materials and both projected yield and sputter yield of these structurally alike perovskite materials.
Performance Evaluation of Inverter-equipped Drive to Regulate the Speed of Motor and Cooling Output of Air Conditioner
Authors: Sheu Akeem Lawal , Adagunodo Theophilus Aanuoluwa 
Published: October 2019

Abstract
The Inverter-equipped Drive designed and constructed in this paper adopts a solid state electronic conversion system using Variable Voltage Variable Frequency (VVVF) control method coupled with AC – DC Converter and DC – AC Converter technology. The method involves the assemblage of DC Power Supply Unit, Monitoring and Control Units and Power Unit. The DC Power Supply Unit in the design supplies power to the entire system by converting the incoming 230VAC of fixed 50Hz into 150VAC through a step – down transformer. A bridge rectifier converts the transformer output voltage to a varying DC voltage, which in turn is passed through an electronic filter to convert it to an unregulated DC voltage. This DC voltage is then converted back into AC voltage through the use of IGBT electronic power transistors using Pulse Width Modulation (PWM) technique. The entire process is controlled by a microcontroller (PIC18F4431) which monitors the incoming voltage supply, speed set-point, DC link voltage, output voltage and current by sampling the current ambient air temperature and adjust the speed of the compressor appropriately. The results showed the corresponding actual speeds, frequencies, the current drawn by the motor, stator voltage, consumption power, and torque – characteristics are observed for both conventional and inverter-equipped drive air conditioner.
Effect of Feature Selection on Performance of Internet Traffic Classification on NIMS Multi-Class dataset
Authors: Oluranti Jonathan , Omoregbe Nicholas , Misra Sanjay 
Published: October 2019

Abstract
The challenges faced by networks nowadays can be solved to a great extent by the application of accurate network traffic classification. Internet network traffic classification is responsible for associating network traffic with the application generating them and helps in the area of network monitoring, Quality of Service management, among other. Traditional methods of traffic classification including port-based, payload-load based, host-based, behavior-based exhibit a number of limitations that range from high computational cost to inability to access encrypted packets for the purpose of classification. Machine learning techniques based on statistical properties are now being employed to overcome the limitations of existing techniques. However, the high number of features of flows that serve as input to the learning machine poses a great challenge that requires the application of a pre-processing stage known as feature selection. Too many irrelevant and redundant features affect predictive accuracy and performance of the learning machine. This work analyses experimentally, the effect of a collection of ranking-basedfilter feature selection methods on a multi-class dataset for traffic classification. In the first stage, the proposed Top-N criterionis applied to the feature sets obtained, while in the second stage we generate for each Top-N set of features a new dataset which is applied as input to a set of four machine learning algorithms (classifiers).Experimental results show the viability of our model as a tool for selecting the optimal subset of features which when applied, lead to improvement of accuracy and performance of the traffic classification process.
Fraud prediction in bank loan administration using decision tree
Authors: Eweoya I O , Adebiyi A A , Azeta A A , Azeta Angela E 
Published: October 2019

Abstract
The rate at which banks looses funds to loan beneficiaries due to loan default is alarming. This trend has led to the closure of many banks, potential beneficiaries deprived of access to loan; and many workers losing their jobs in the banks and other sectors. This work uses past loan records based on the employment of machine learning to predict fraud in bank loan administration and subsequently avoid loan default that manual scrutiny by a credit officer would not have discovered. However, such hidden patterns are revealed by machine learning. Statistical and conventional approaches in this direction are restricted in their accuracy capabilities. With a large volume and variety of data, credit history judgement by man is inefficient; case-based, analogy-based reasoning and statistical approaches have been employed but the 21st century fraudulent attempts cannot be discovered by these approaches, hence; the machine learning approach using the decision tree method to predict fraud and it delivers an accuracy of 75.9 percent.
Twitter Sentiment Based Mining for Decision Making using Text Classifiers with Learning by Induction
Authors: Babafemi Odusote , Itakpe Jonathan D. , Afolabi Ibukun T. 
Published: October 2019

Abstract
The amount of data residing in social media currently untapped is certainly limitless as millions of people are constantly posting a message or the other to public forums on the internet. Twitter being one of the largest social media networks with over 336 million monthly active users has proven to be a fertile ground for harvesting opinion from multiple people. This work explores how opinion can be extracted from tweets to discover people’s view concerning a certain subject matter. It focuses mainly on overcoming the limitation of the current approach to social media sentiment based mining for decision making which is that opinions derived from multiple sources are limited to available connections on the social media platforms and lack of improved accuracy of mined opinions. In order to achieve this, the proposed framework provides a platform to mine opinions from more than the available friends and connections on the social media platform and in addition, improve the quality of the opinion mined by implementing supervised learning algorithms with learning by induction in Twitter data analysis.
In this research, three different supervised machine learning algorithms were applied to a dataset curated by graduate students at Stanford in order to accurately classify tweets into either positive or negative sentiment based on its content. It was discovered that Maximum Entropy had the highest accuracy of 83.5% among the three algorithms. The research has provided a web application which would enable users such as CEOs, Market Analysts, and random users make quality decision based on others’ opinions.
Maximum and Minimum Temperatures in South-Western Nigeria: Time trends, Seasonality and Persistence
Authors: Ogunsola O.E. , Yaya O.S. 
Published: October 2019

Abstract
Global temperature which is obtained as the average of both the zonal and national temperatures is a very fundamental quantity in determining global warming. The difference between the monthly diurnal temperature range (DTR) changes at different locations of the world is also responsible for the current warming being experienced worldwide. Monthly maximum and minimum temperature data for the South-western region of Nigeria (January, 1979 – December, 2014) obtained from the Nigerian Meteorological Agency (NIMET), Lagos were analyzed for their time trends, seasonality and persistence using standard statistical procedures including the fractional integration approach. The results of analyses obtained showed that significant positive time trend coefficients were obtained for the minimum temperature, while negative coefficients were obtained for the DTR at the stations considered which implied that global warming is also being experienced in this region of the country.
Geophysical Investigation of Building Foundation in Part of Ilorin, North Central Nigeria Using Electrical Resistivity Method
Authors: Egbeyale G. B. , Ogunseye T. T. , Ozegin K.O. 
Published: October 2019

Abstract
Electrical resistivity method has been performed using Vertical Electrical Sounding (VES) technique at a Bishop Smith Memorial College, Ilorin, Kwara State to examine the geophysical parameters that can be used to evaluate the subsurface competency. Eight VES stations were sounded, using Schlumberger configuration for data acquisition with current electrode spacing varying from 1.0 to 140.0 m. The VES data obtained were interpreted using ipi2win+ip Software. The field data acquired was presented as geoelectric sounding curves and geoelectric section. The interpretation of the field results revealed heterogeneous subsurface geologic sequence probed to 34.6 m and beyond. It also showed presence of near surface linear geologic structures of varying lengths, depths and attitude which suggest the competent zones for foundation laying. The major subsurface layers are the top soil which consists of interlocking and concretional lateritic stones and clayey sand, weathered basement, fractured basement and fresh basement. For building development in the study area, the topsoil must be excavated to at least the Fresh basement (competent layer) to avoid building deformation.
Evaluation of Structural Stability by Characterization of Lateritic Soils with Rock Flour along Ibadan-Iwo-Osogbo Highway, Southwestern Nigeria
Authors: Omowumi Ademila 
Published: October 2019

Abstract
Failures of different categories of roads shortly after being opened to traffic have necessitated the need for sustainable alternative road building materials. This study determines the potential of rock flour on the geotechnical properties of lateritic soils with a view to establish the optimum content of the rock flour required for effective stabilization and proffer lasting remediation measures to the incessant road failures. Ten bulk lateritic soil samples were collected from ten trial pits at depths of 1.5 m in different locations of the study area. Index and engineering property tests were performed on the soils, both in their natural and stabilized states by adding 2, 4, 6, 8 and 10% rock flour contents. In addition, CBR – UCS model was used to establish a third order polynomial to correlate the soil-rock flour mix. The results show that the plasticity and linear shrinkage of the soils decreased with increase in rock flour contents. The MDD of rock flour stabilized soils increase with the maximum improvement observed at 10% by weight of rock flour with the corresponding decrease in OMC. The load bearing capacities (LBC) of the soils increase with the stabilization mix. It was observed that the values meet the requirements for good quality subgrade, subbase materials and some of the soils for base materials in road construction. The results also reveal the improvement of the soil properties. This is further confirmed by the increase in UCS and shear strength of the soils which optimally improved on addition of 8% rock flour. Moreover, the addition of more than 8% by weight of rock flour caused reduction in UCS and shear strength. These results show the stabilizing potentials of rock flour on lateritic soils especially when added at the optimum level. The CBR - UCS models established are in form of third order polynomial (ax3- bx2 + cx +d) with the R2 values, 0.672 and 0.528 which indicate positive correlation of the soil-rock flour mix. Therefore, rock flour can potentially stabilize lateritic soils solely with addition of 8% recommended as an optimum content for stabilizing lateritic soils for road constructions.
The encumbrance of constructing on a swampy terrain
Authors: Nkem Ede Anthony , Emmanuel Salami Omobolaji , Michael Olofinnade Oluwarotimi , David Oyeyemi Kehinde 
Published: October 2019

Abstract
All through the ages, the provision of shelter has remained an ever-present challenge of mankind. Perennial difficulties of shelter provision are posed by varying strains dependent of numerous conflicting factors. Civil engineering and other specialty of science and humanity join hands in providing solutions to man’s basic housing and infrastructural needs, thereby adding values to what nature has provided. Constructing on different terrains cost different amount of resources and energy. This research evaluates the burden of constructing on swampy terrain. Mende-Maryland in Lagos is adopted as the area of study. This research analyzed the methods of constructing a duplex on a swampy terrain and modelled the behaviour of the same structure on a normal terrain. Successively, the economic burden of constructing on a swampy terrain is compared to that of constructing on a normal terrain. The result showed that constructing on a swampy terrain is a cost intensive process with the cost of pile foundation alone taking about 38 percent of the whole cost of construction when compared to the 17 percent cost of raft foundation for a normal terrain. This cost will go higher when the cost of engaging experts and equipment for soil consolidation, construction of superstructures on weak terrain and extra safety measures are computed.
Compressional-Shear Velocity Model of “Toki” Field using Support Vector Regression, Offshore Niger Delta
Authors: Adeniran A.E , Aizebeokhai A.P 
Published: October 2019

Abstract
Shear sonic log is invaluable for fluid and lithological classification. For most fields in the Niger Delta, shear sonic log are rarely acquired along with the compressional sonic log. Where acquired, they are usually very few relative to the number of wells. Hence, there is a need to derive shear velocity from the compressional sonic log. Most of the available models such as Castagna’s mud-rock model are not calibrated to suit the Niger Delta basin. Existing localized models are based on non-robust linear models such as the Ogagarue's localized compressional and shear velocity models for Niger Delta sedimentary region. These models are not reliable in the presence of hydrocarbon and anisotropy. A robust support vector regression (SVR) machine learning algorithm has been used to predict the relationship between compressional velocity and shear velocity. This study shows that in the Niger Delta, shear velocity can be predicted from compressional velocity with relatively high accuracy by using machine learning algorithms such as support vector regression. The mean-square error (MSE) obtained using Castagna’s and Ogagarue's models compared with acquired data are 1.8 and 2.3 times that of the value obtained using support vector regression respectively.
Assessment of Environmental Impact in Soil Samples from Selected Market Dumpsites in Ikorodu Metropolis, Lagos State, South Western Nigeria
Authors: Oyebanjo O.A. , Sowole O. , Oyebanjo O.O. , Ayedun F. , Adagunodo T.A. , Falayi E.O. 
Published: October 2019

Abstract
The study assessed the environmental impact of selected market waste dumpsites in soil samples in Ikorodu metropolis in order to determine the effect of the level of health hazard on the residents of Ikorodu community. The measurement was carried out using a Gamma ray Spectrometer NaI (TI)detector coupled to a Multichannel analyser for spectral analysis. Results revealed that the activity concentration of 40K in soil samples ranged from 14.84±1.07 BqKg−1 to 82.01±5.54 BqKg−1 with the highest found in Adamo Market and the lowest was found in Benson market. The activity concentration of 238U ranged from 0.029±0.05 BqKg−1 to 7.65±0.9 BqKg−1 with the highest found in Agunfoye Market and the lowest found in Benson Market. The activity concentrations of 232Th ranged from 1.68±0.14 BqKg−1 to 3.93±0.28 BqKg−1, the highest concentration was found in Agunfoye Market and the lowest was found in Ayangburen Market. The values were within the safety limit recommended by the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) with mean value of 13.5 - 69.8 BqKg−1. The Absorbed Dose Rate, Outdoor, Annual Effective Dose Rate, and the Internal and External Hazard Index was also calculated from the activity concentrations which shows that the absorbed dose rates due to gamma rays at 1m above the ground in the study area were within the range of 1.99 nGyh−1 to 7.06 nGyh−1 with an average of 4.08 nGyh−1 which is lower than the UNSCEAR average value of 59 nGyh−1. The annual effective doses are within the range of 0.00 to 0.01 mSvy−1 with an average value of 0.01 mSvy−1 which were lower when compared with the UNSCEAR value of 0.5 mSvy−1 and 0.07 mSvy−1 respectively. The External Hazard Index in the soil samples ranges from 0.01 to 0.04 with an average value of 0.02 and the Internal Hazard Index ranges from 0.01 to 0.06 with an average value of 0.03 both of which were below the permissible limit respectively, and less than 1. However, the values of the radiological parameters were below the UNSCEAR recommended international limits of 370Bq/kg and within the tolerance level indicating minimal radiological health burden on the people living in the study areas.
In-vitro Anti-Microbial Studies and GC/MS Analysis of the Leaf Extract and Fractions of Polyalthia longifolia (Engl. & Diels) Verde
Authors: Olanrewaju Ifedolapo O. , Mordi Raphael C. , Echeme Johnbull O. , Bolade Oladotun P. , Bashir Musa , Ekwuribe Silas , Ayo-Ajayi Joan I. 
Published: October 2019

Abstract
Extensive studies show that secondary metabolites in plants, used for centuries in traditional medicine, offer new sources of drugs. In the traditional setting, extracts from various parts of the plant Polyalthia longifolia (mast tree) are used in treating several ailments but the components of these extracts, which would allow for meaningful dosage, are not known. We therefore decided to examine the antimicrobial activity by testing on selected microorganisms and identify the volatile components by gas chromatography-mass spectrometry of the leaf extracts of Polyalthia longifolia (mast tree). The crude leaf extract and fractions derived from the crude exhibited anti-microbial activity against two (2) bacteria and two (2) fungi. The chloroform fraction was very active against Salmonella typhi (13.00±0.82) when compared to fractions in other solvents. The GC-MS analysis showed that the extracts were composed fatty acids and their ester along with some long chain aldehydes, like hexadecenal and tetradecenal, and Caryophyllene and Aromandendrene. These chemical constituents may be responsible for the pharmacological and therapeutic activities of this plant.
Development of national health-based target for regulating airborne polycyclic aromatic hydrocarbons exposure in Nigeria
Authors: Etchie T O , Etchie A T , Oluwasanya P , Shen H 
Published: October 2019

Abstract
Recent studies in different localities in Nigeria report high concentrations of airborne polycyclic aromatic hydrocarbons (PAHs) –a group of ubiquitous hazardous chemicals produced by incomplete combustion or pyrolysis processes. Inhalation exposure to PAHs has been shown to elicit both cancer and non-cancer adverse effects. Yet, there is currently no national guideline for regulating exposure to airborne PAHs in Nigeria. In this study, we developed national health-based target for 16 priority PAHs using literature information on the toxicity of the PAHs, the baseline severities of the diseases in Nigeria and the population demography. We developed ourhealth-based target (ng/m3) from 10cancers and 34 non-cancer adverse health outcomes linked to PAH exposure. Our proposed limits for the PAHs ranged from 0.02 ng/m3 for dibenzo[a,h]anthracene to 1.0 ng/m3 for benzo[g,h,i]perylene – the most or least toxic PAH, respectively. On the basis ofbenzo[a]pyrene equivalent concentration, ournational PAH limit of 0.15 ng/m3is however less stringent than the global PAH limit of 0.12 ng/m3.
Ground radiometric survey for assessment of environmental radioactivity in a fertilized farmland: a case history in southwestern Nigeria
Authors: Ekhaguere O. A. , Alatise O. O. , Oyeyemi K. D. 
Published: October 2019

Abstract
Soils in their natural state contain radionuclides and heavy metals at different concentrations which may be increased by the use of fertilizers. When the concentrations of radionuclides and in soils are higher in value than the recommended limits, this may pose health concern. In this study, absorbed dose rate was measured in-situ at thirty-five station points in the farmland using a caesium Iodide-based GammaRAE II R full range dosimeter held at gonald height above the surface. Results of the in-situ absorbed dose rate in air are presented and the potential risks to the farmers and near-by residents are equally assessed. The results revealed that the measured absorbed dose rate (ADRA) in the farm is high which is likely to be connected to the use of fertilizer in the farmland. It is highly recommended that the management of the farm should reduce the use of fertilizer but rather use natural organic manure that is less toxic. Also, a routine check on environmental radioactivity of the farmland should be done regularly for adequate monitoring.