Sani Isah Abba

Prince Muhammad Bin Fahd University · Civil Engineering

Traditional methods for proportioning of high-performance concrete (HPC) have certain shortcomings, such as high costs, usage constraints, and nonlinear relationships. Implementing a strategy to optimize the mixtures of HPC can minimize design expenses, time spent, and material wastage in the construction sector. Due to HPC's exceptional qualities,...

Dynare is a popular software for solving dynamic stochastic general equilibrium (DSGE) and overlapping generations (OLG) models. It is used along with Octave or Matlab. However, writing documents using Dynare outputs can be error-prone and time-consuming, as it requires copying and pasting the outputs into the document. To address this problem and...

Geopolymer concrete, made from fly ash, offers a sustainable alternative to Portland cement-based concrete due to its mechanical strength, and resistance to adverse conditions. Its minimal carbon footprint and environmental benefits make it a promising alternative for infrastructure projects. Four models are evaluated in this study: Random Forest (...

The effective prediction of corrosion inhibition efficiency (%IE) of modified graphene oxides (GOs); diaminohexane-modified graphene oxide (DAH-GO) and diaminooctane-modified graphene oxide (DAO-GO) is vital for advanced material applications. This study employs a dual-modelling scheme to predict the %IE, for this purpose, four stand-alone machine...

This study presents an innovative approach for predicting water and groundwater quality indices (WQI and GWQI) in the Eastern Province of Saudi Arabia, addressing critical challenges of scarcity and pollution in arid regions. Recent literature highlights the increasing attention towards WQI based on water pollution index (WPI) and GWQI as essential...

This study explores two scenarios for optimizing the predictive control of flux in water desalination systems: experimental design of direct contact membrane distillation (DCMD) and artificial intelligence (AI) models. Deep learning networks, specifically Long Short-Term Memory (LSTM), and standalone AI models, including hybrid Adaptive Neuro-Fuzzy...

It is important to point out that the precise prediction of water binder ratio “w/b ratio” is indispensable for gaining the desirable characteristics of strength and duration of concrete constructions. This research offers a new method for w/b ratio prediction based on state-of-art machine learning algorithms accompanied with Explainable artificial...

Reliable energy demand estimation and optimal sizing of a stand-alone photovoltaic/wind/battery hybrid energy system are critical for achieving sustainable development goals. This study presents a hybridized design of an off-grid multi-region energy system to reduce the total annual cost of the system based on a genetic algorithm. A stand-alone ker...

Potentially toxic elements (PTEs) are well-known for exposing living organisms and humans to different levels of risk. The present study aimed to evaluate the extent of exposure to health risks sustained by the inhabitants of different suburbs across Southeastern Nigeria as a result of contaminated water sources. There are existing literatures on h...

Several obstacles impede renewable energy penetration into the global energy sector. Amongst the apparent challenges which require credible research attention, is the selection of appropriate energy storage technologies in the context of intermittent renewable resources and frequent grid outages. Given these, the present study investigated the tech...

Predicting the efficacy of micropollutant separation through functionalized membranes is an arduous endeavor. The challenge stems from the complex interactions between the physicochemical properties of the micropollutants and the basic principles underlying membrane filtration. This study aimed to compare the effectiveness of a modest dataset on va...

For herbal and modern drug research, secondary metabolites produced by plants are a valuable source of pharmaceutically active compounds. Northern Nigeria relies heavily on plants as a source of medication. Succulent perennial herb Bryophyllum pinnatum is endemic to Africa and Asia. The current study investigates the in vitro pharmacological potent...

The agricultural sector faces challenges in managing water resources efficiently, particularly in arid regions dealing with water scarcity. To overcome water stress, treated wastewater (TWW) is increasingly utilized for irrigation purpose to conserve available freshwater resources. There are several critical aspects affecting the suitability of TWW...

This study will comprehensively evaluate the Rispana River's aquatic environment from February to June 2021, integrating physicochemical, biological, and hydrological data. Key objectives include identifying pollution sources, assessing climate change impacts, and evaluating health effects on humans and aquatic life. Analysis of 50 water samples re...

This study establishes the real-time monitoring and prediction of treated wastewater quality in Al-Hassa, Saudi Arabia, utilizing an integrated system of sensors, the Internet of Things (IoT), and machine learning. Targeting resistivity as a key indicator of salinity and purity, the research aims to advance water resource management through technol...

This study delves into the exploration of Kernel Support Vector Regression (KSVR) models for predicting oil flux and separation efficiency in wastewater treatment. The research underscores the KSVR-S.E model is notably superior, exhibiting an R2 value of 0.989739, elucidating nearly 99% of the variance in training data. A rigorous evaluation reveal...

This study aimed to explore the level of heavy metal contamination in the soil of agricultural and industrial areas in the Eastern Province of Saudi Arabia. It adopted a novel approach integrating multiple disciplines including sampling, laboratory analysis, spatial analysis, and risk evaluation. The research focused on pinpointing levels of contam...

Efficient flood risk management hinges on the precise mapping and assessment of areas vulnerable to flooding. This research endeavors to advance the flood susceptibility mapping in Jeddah, Saudi Arabia by harnessing the long short-term memory (LSTM) algorithm enriched with two sophisticated metaheuristic optimizers: invasive weed optimization (IWO)...

The knitr package provides an avenue for incorporating programming languages and statistical applications into R Markdown and Quarto document for the sake of reproducibility. However, deep technical knowledge of R programming is required to achieve this task. In addition to this, the existing literature does not provide a guide on how to add econom...

Contamination in coastal regions attributed to fluoride and nitrate cannot be disregarded, given the substantial environmental and public health issues they present worldwide. For effective decontamination, it is pivotal to identify regional pollution hotspots. This comprehensive study was performed to assess the spatial as well as indexical water...

Artificial intelligence (AI) is being employed in brine mining to enhance the extraction of lithium, vital for the manufacturing of lithium-ion batteries, through improved recovery efficiencies and the reduction of energy consumption. An innovative approach was proposed combining Emotional Neural Networks (ENN) and Random Forest (RF) algorithms to...

Four easy steps to add new knit-engine to knitr R package

River water quality management and monitoring are essential responsibilities for communities near rivers. Government decision-makers should monitor important quality factors like temperature, dissolved oxygen (DO), pH, and biochemical oxygen demand (BOD). Among water quality parameters, the BOD throughout 5 days is an important index that must be d...

In a world where plastics have become an integral part of daily life, the ubiquitous presence of microplastics (MPs) is hardly surprising. However, the emergence of MPs in one of humanity’s most vital resources—groundwater—is concerning. This review explores the widespread reports of MPs in drinking water, examining their origins and the potential...

In recent decades, the discovery, extraction, and export of petroleum have significantly strengthened the economy. However, the processes of petroleum exploration, development and production have localized negative impacts on the atmosphere, soil, sediments, surface, groundwater, marine environment, and terrestrial ecosystems. The presence of petro...

MXene, a recently identified 2D nanosheet, has drawn interest due to its potential application in the modification of thin film nanocomposite (TFN) membranes for the production of clean water. This study presents the development of MXene-based sulfonated TFN (STFN) nanofiltration membrane for the desalination application and chlorine resistance. A...

Flooding is a major environmental problem facing urban cities, causing varying degrees of damage to properties and disruption to socio-economic activities. Nigeria is the most populous African country and Kano metropolis is the second largest urban center in Nigeria, and the most populated in Northern Nigeria. The aim of the paper was to conduct a...

Contamination in coastal regions attributed to fluoride and nitrate cannot be disregarded, given the substantial environmental and public health issues they present worldwide. Maintaining water quality is crucial for environmental well-being. This comprehensive study was performed to assess the spatial as well as indexical water quality, identify c...

Total dissolved gas (TDG) concentration plays an important role in the control of the aquatic life. Elevated TDG can cause gas-bubble trauma in fish (GBT). Therefore, controlling TDG fluctuation has become of great importance for different disciplines of surface water environmental engineering.. Nowadays, direct estimation of TDG is expensive and t...

River flow (Qflow) is a hydrological process that considerably impacts the management and sustainability of water resources. The literature has shown great potential for nature-inspired optimized algorithms (NIOAs), like hybrid artificial intelligence (HAI) models, for Qflow modeling. Qflow forecasting needs to be accurate, robust, reliable, and ca...

When selecting biomass feedstock for sustainable heat and electricity generation, higher heating value (HHV) is an important consideration. Meanwhile, the laboratory procedures of using an adiabatic oxygen bomb calorimeter to determine the HHV are strenuous, costly, and time-consuming. As a result, researchers have turned to artificial intelligence...

Predictions of thermal performance (η) of flat plate solar collectors (FPSCs) can provide essential information for diverse engineering applications such as thermal and energy areas. Several thermal and operating parameters influence η, and its prediction and quantification are highly complex and challenging. The current research was adopted to inv...

.(1) Background: Groundwater resources management in dry lands, characterized by climate var-iability and population growth, is difficult. Exploration and exploitation of groundwater, due to inadequate surface water is very costly. The present study employed Analytic Hierarchy Process (AHP) and GIS to identify Ground-Water Potential (GWP) areas in...

Accurate and reliable estimation of Reference Evapotranspiration (ETo) is crucial for water resources management , hydrological processes, and agricultural production. The FAO-56 Penman-Monteith (FAO-56PM) approach is recommended as the standard model for ETo estimation; nevertheless, the absence of comprehensive meteorological variables at many gl...

Flooding is one major environmental problem facing urban cities causing varying degree of damages to properties and disruptions to socio-economic activities. Nigeria is the most populated African country and Kano metropolis is the second largest urban center in Nigeria and the most populated in Northern Nigeria. The aim of the paper is to conduct f...

Computer aid models such as machine learning (ML) are massively observed to be successfully applied in different engineering-related domains. The current research was designed to predict the thermo-economic performances of hybrid organic Rankine plants. The XGBoost optimization algorithm was used to select the influencing parameters for the plant's...

This study proposes different standalone models viz: Elman neural network (ENN), Boosted Tree algorithm (BTA), and f relevance vector machine (RVM) for modeling arsenic (As (mg/kg)) and zinc (Zn (mg/kg)) in marine sediments owing to anthropogenic activities. A heuristic algorithm based on the potential of RVM and a flower pollination algorithm (RVM...

Water scarcity is a pressing global challenge, and arid regions like Saudi Arabia face the urgent need for effective water stress management. The current study proposes an innovative method to tackle this issue by utilizing a hybrid time series analysis model, comprising of Autoregressive Integrated Moving Average (ARIMA) and Generalized Least Squa...

The availability of water is crucial for the growth and sustainability of human development. The effective management of water resources is essential due to their renewable nature and their critical role in ensuring food security and water safety. In this study, the multi-step-ahead modeling approach of the Gravity Recovery and Climate Experiment (...

Background and Aims: : In this study, thymoquinone (TQ) from black cumin will be quantified from several geographical regions, including India, Syria, Saudi Arabia, Iraq, and Turkey. Additionally, to forecast the chromatographic behavior of the analyte in artificial intelligence (AI)-based models, the study used both ensemble machine learning metho...

Cancer is one of the major causes of death in the modern world, and the incidence varies considerably based on race, ethnicity, and region. Novel cancer treatments, such as surgery and immunotherapy, are ineffective and expensive. In this situation, ion channels responsible for cell migration have appeared to be the most promising targets for cance...

The rising global demand for brine resources necessitates the exploration of alternative sources to complement existing natural sources. It is imperative to explore innovative approaches, such as emerging machine learning-aided tools, to ensure sustainable and secure brine resources. We proposed a kernel support vector regression (k-SVR), and Gauss...

Global groundwater resources have been threatened by both climate change and anthropogenic activities. Both factors could lead to groundwater depletion that might seriously threaten the living environment and food security. As one of the world’s most water-stressed countries, Saudi Arabia has experienced long-term groundwater depletion due to exces...

Reinforced concrete footings (RCF) enhance stability and longevity by evenly dispersing a building's weight into the ground. However, concentrated loads, like columns, can cause punching shear stress. Proper reinforcement and design are crucial for footing structural integrity, with higher compressive strength (CS) concrete better able to control p...

The study presents a sophisticated hybrid machine learning methodology tailored for predicting energy loads in occupied buildings. Leveraging eight pivotal input features-building compactness, surface area, wall area, roof area, overall height, orientation, glazing area, and glazing area distribution-we elucidate the intricate relationships between...

The global significance of fluoride and nitrate contamination in coastal areas cannot be overstated, as these contaminants pose critical environmental and public health challenges across the world. Water quality is an essential component in sustaining environmental health. This integrated study aimed to assess indexical and spatial water quality, p...

EViews is a software designed for conducting econometric data analysis. There exists a one-way communication between EViews and R, as the former can run the code of the latter, but the reverse is not the case. We describe EviewsR, an R package which allows users of R, R Markdown and Quarto to execute EViews code. In essence, EviewsR does not only p...

This article aimed to present a new continuous probability density function for a non-negative random variable that serves as an alternative to some bounded domain distributions. The new distribution, termed the log-Kumaraswamy distribution, could faithfully be employed to compete with bounded and unbounded random processes. Some essential features...

The construction industry, being a significant contributor to greenhouse gas emissions, faces considerable attention and demand on account of the increasing global apprehension regarding climate change and its adverse impacts on the environment. Geopolymer shows itself as a viable and sustainable alternative to the Portland cement binder in civil i...

The prediction of the yields of light olefins in the direct conversion of crude oil to chemicals requires the development of a robust model that represents the crude-to-chemical conversion processes. This study utilizes artificial intelligence (AI) and machine learning algorithms to develop single and ensemble learning models that predict the yield...

Apart from the long-term changes in the climate patterns, the extreme weather conditions (heat waves, heavy precipitation, and droughts) have also emerged as a prominent consequence of the global climate change. Pakistan being listed among the most susceptible nations to the changing climate patterns has witnessed an increasing trend of extreme pre...

Natural hazard threats have grown as a result of climate change, fast demographic development, and major urbanization. Devastating floods have occurred in several areas of the world recently, including the Kingdom of Saudi Arabia, which is located in a region with a dry environment. In arid or semi-arid regions, rapidly forming flash floods associa...

Efficient oil–water separation using membranes directly aligns with removing oil pollutants from water sources, promoting water quality. Hence, mitigating environmental harm from oil spills and contamination and fostering ecosystem health for sustainable development. Computational learning, such as artificial intelligence (AI), enhances membrane oi...

The need for reliable, state-of-the-art environmental investigations and pioneering approaches to address pressing ecological dilemmas and to nurture the sustainable development goals (SDGs) cannot be overstated. With the power to revolutionize desalination processes, artificial intelligence (AI) models hold the potential to address global water sc...