Refereed Journals

The significance of adjustment and computation studies has grown in recent years, influencing allied fields like arithmetic and satellite geodesy. This empirical study explores the effectiveness of various soft and traditional regression methods in correcting survey field data. Specifically, it investigates soft computing techniques such as back-propagation artificial neural network (BPANN), radial basis function artificial neural network (RBFANN), generalized regression artificial neural network (GRANN), and traditional regression methods like polynomial regression model (PRM) and least square regression (LSR) techniques. The study aims to fill the knowledge gap regarding soft computing strategies for modifying real-time kinematics (RTK) GPS field data and the ongoing debate between artificial intelligence techniques (ANN) and traditional methods on which technique offers the best results in modifying survey field data. Performance criteria, including horizontal displacement (HE), arithmetic mean error (AME), arithmetic mean square error (AMSE), minimum and maximum error values, and arithmetic standard deviation (ASD), were used to assess each model technique. Statistical analysis revealed that RBFANN, BPANN, and GRANN achieved superior accuracy compared to conventional techniques (PRM and LSR) in adjusting real time kinematics GPS data. RBFANN outperformed BPANN and GRANN in terms of AME, AMSE, and ASD of their horizontal displacement. These findings suggest that soft computing techniques enhance real-time kinematics GPS field data adjustment, addressing critical issues in accurate positioning, particularly in Ghana. This study contributes to the knowledge base for developing an accurate geodetic datum in Ghana for national and local objectives. This will lay a foundation for the global determination of exact positions in Ghana. RBFANN emerges as a promising option for real-time kinematics GPS field data adjustment in topographic surveys. However, care should be taken to check issues of data overfitting

Across West African built environments, patterns of high greenhouse gas emissions are driven by the widespread importation of high embodied carbon building materials by a largely self-built industry and recurring operational carbon costs driven by increased access to fossil-fuel based energy services. Using a whole life cycle assessment (LCA) of major residential typologies in two case-study West African countries, Ghana and Senegal, this paper compares the greenhouse gas emissions of imported building materials with local alternative biogenic and geogenic materials within conventional housing typologies. Results indicated that locally sourced biogenic and geogenic materials may be rendered ineffective in buildings if future typologies do not address the effective space density, passive design strategies and increased renewable energy-use. For the building typology with the highest carbon footprint, the Ghanaian detached house, the substitution of conventional building materials with non-fired earth masonry did not have any significant impact. As shown in the housing typology with the lowest operational to embodied carbon ratio, the Senegalese vertical housing case study, optimizing the thermal mass design of earthen building envelopes can significantly drive down lifetime operational carbon emissions. For tropical low-rise building typologies dominated by high roof area to building volume ratios, roof insulation could drive down operational carbon of the building by a factor of 4 to 5. Although each additional storey results in approximately 10–12 % increase in greenhouse gas emissions, the vertical expansion of housing represents an important driver in reducing greenhouse gas emissions per capita.

The use of superplasticizers is very uncommon in many developing countries. However, its inclusion in concrete enhances concrete's mechanical and durability properties. There is a yawning gap in the literature on the performance of Sulphonated Naphthalene Formaldehyde (SNF) superplasticizers in concrete, especially in the sub-Saharan construction industry where the quality of aggregates used in production is questionable. This study produced two batches of concrete produced with locally sourced pit sand, with characteristic strength of 30 MPa. One batch was without the SNF superplasticizer to serve as a control, whereas the other batch was made with the incorporation of the superplasticizer. The fresh properties of slump and air content and the hardened properties of compressive and flexural strength, elastic, and dynamic moduli were investigated. Further, durability indicators comprising sorption, water absorption, sorptivity, chloride penetration, electrical surface resistivity, and acid attack were investigated. The results of the study demonstrated that the incorporation of SNF superplasticizers in concrete resulted in improved workability and a reduction in ion mobility within the concrete. This was attributed to a decrease in the presence of interconnected pores, leading to notable enhancements in mechanical properties such as increased strength, as well as improvements in both elastic and dynamic moduli. Moreover, concrete containing SNF superplasticizer protects the concrete much better from acid attack than those without SNF superplasticizer. The study recommends the use of SNF superplasticizers in concrete for improved workability, reduced ion movement via fewer interconnected pores, and enhanced mechanical properties, potentially boosting overall durability.

The detrimental impact of anthropogenic gases such as carbon dioxide, methane, and nitrous oxide has become a pressing concern across various industries. In this study, thermally activated clay (TAC) was investigated as a substitute for Portland cement in proportions ranging from 10 to 40 wt%. Compressive strength and efficiency factors were employed to ascertain the optimal mortar mixture. Both the control mortar and the optimal blend underwent capillary water sorptivity tests. Fourier Transformed Infrared spectroscopy (FT-IR) was utilized to gain insight into the hydration process and pozzolanic reaction within the mortar mixtures. Furthermore, the study assessed the impact of the optimized blended mortar on greenhouse gas emissions through estimated carbon dioxide equivalent values. Results revealed that incorporating 30% TAC attained the maximum strength of approximately 33, 36, and 48 MPa at 3, 7, and 28 days respectively compared with the other mortars. The mortar containing 30% TAC enhances both compressive strength and efficiency factors, demonstrating effective pozzolanic activity and minimal compromise on performance. Notably, the inclusion of 30% TAC also led to reduced water absorption rates, indicating improved durability-related performance. Additionally, the study uncovered the superior performance of the 30% TAC mix in terms of efficiency factors and carbon savings. FTIR analysis provided novel insights into the hydration and pozzolanic reactions induced by TAC, resulting in the formation of compounds contributing to enhanced compressive strength over time. This research advocates for the substitution of Portland cement with TAC as a low-carbon binder alternative to traditional Portland cement binders

This study simultaneously modelled the injury severity of motorcycle riders and their pillion passengers and determine the associated risk factors. The analysis is based on motorcycle crashes data in Ashanti region of Ghana spanning from 2017 to 2019. The study implemented bivariate ordered probit model to identify the possible risk factors under the premise that the injury severity of pillion passenger is endogenously related to that of the rider in the event of crash. The model provides more efficient estimates by considered the common unobserved factors shared between rider and pillion passenger. The result shows a significant positive relationship between the two injury severities with a correlation coefficient of 0.63. Thus, the unobservable factors that increase the probability of the rider to sustain more severe injury in the event of crash also increase that of their corresponding pillion passenger. The rider and their pillion passenger injury severities have different propensity to some of the risk factors including passengers’ gender, day of week, road width and light condition. In addition, the study found that time of day, weather condition, collision type, and number of vehicles involved in the crash jointly influence the injury severity of both rider and pillion passenger significantly.