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A Bibliometric Analysis of AI Trends in the AEC Industry
(Preprints, 2025-09) Adewale, B. A.; Ene, Vincent Onyedikachi; Aigbavboa, Clinton Ohis
This study employs a comprehensive bibliometric analysis to examine the evolving landscape of Artificial Intelligence (AI) research within the Architecture, Engineering, and Construction (AEC) industry over the past decade. Through systematic analysis of 68 publications from the Scopus database, utilizing co-authorship networks, citation analysis, and keyword co-occurrence mapping, the research reveals significant patterns and trends in AI adoption and research focus. The findings indicate a rapid growth in research output, with China, the United States, and the United Kingdom emerging as leading contributors. The analysis identifies four primary research clusters: AI integration across AEC processes, building lifecycle applications, digital technologies convergence, and automation techniques. A temporal evolution is observed, transitioning from basic automation to sophisticated applications involving machine learning, digital twins, and deep learning. The study highlights geographical disparities in research contributions and emphasizes the need for standardization in AI implementation. By providing insights into research trends, collaborative networks, and evolving focus areas, this analysis contributes to a deeper understanding of AI's role in transforming the AEC industry. The findings can guide future research directions, inform industry practitioners about emerging technologies, and support policymakers in developing frameworks for AI adoption in construction, ultimately facilitating more effective and responsible integration of AI technologies in AEC practices.
A COMPUTATIONAL FRAMEWORK FOR PREDICTING COMPOUNDPROTEIN INTERACTION FOR PROSTATE CANCER THERAPEUTIC DISCOVERY
(Covenant University Ota, 2025-08) AGBI, Mayowa; Covenant University Dissertation
Prostate cancer (PCa) is a major public health issue globally. In sub-Saharan Africa, with its limited number of diagnostic and treatment resources, it accounts for high mortality. The conventional approach to drug discovery is lengthy, expensive, and often insufficient to address the complex treatment-resistant prostate cancers present. In this study, a deep learning computational framework to predict Compound-Protein Interactions (CPI) for prostate cancer drug discovery was developed. An end-to-end machine learning pipeline was implemented using curated datasets from Zenodo, ChEMBL, BindingDB, and UniProt. Molecular representations for compounds were constructed using 2048-bit Morgan fingerprints, dimensionally reduced to 200 via Principal Component Analysis (PCA), and for the proteins, 100-dimensional 3-mer Word2Vec embeddings were used. These features were fed into a double-input deep neural network that was optimized with binary-cross-entropy loss, the Adam optimizer, and dropout regularization. The model identified five novel bioactive compounds for targeting proteins of prostate cancer biomarkers. Model confidence was used to prioritize predicted interactions for AR, SRC, and EGFR. Molecular docking in PyRx and AutoDock Vina, followed by visualization in Discovery Studio supporting strong binding affinity (-7.2 to -10) and complementarity from the structural point of view, constituting therapeutic potential. An integration of molecular docking enriched translational value to the prediction. The results presented here point to a disease-specific platform for in silico drug discovery in prostate cancer. This study opens a very promising path toward giving priority to candidate compounds by coupling the deep learning with structure-based affirmation. It provides a very viable ground to be merged with experimental validation and combinatorial therapy design, thereby taking one step further into machine learning-assisted precision oncology.
A MULTI-DOCUMENT SUMMARIZATION APPROACH FOR QUERY-DRIVEN NON-FACTOID QUESTION-ANSWERING SYSTEM
(Covenant University Ota, 2025-07) EFOSA-ZUWA, Emmanuel Temidire; Covenant University Dissertation
In Natural Language Processing (NLP), Question Answering Systems (QAS) are essential for facilitating efficient access to relevant information. Traditional QAS approaches typically involve decomposing user queries, retrieving relevant documents, and ranking potential answers, often struggle with non-factoid questions that require detailed, context-rich responses synthesized from multiple sources. While existing research has focused heavily on passage selection and ranking, many methods fail to produce a coherent answer, leaving the challenge of multi-source summarization largely unresolved. This study presents a transfer learning-based QAS framework that addresses non-factoid queries through multi-source summarization. The framework follows a multi-stage methodology incorporating question paraphrasing, contradiction detection, sentence embedding and pruning, and a hybrid approach combining extractive and abstractive summarization techniques. Quantitative and qualitative analyses were conducted using benchmark datasets, including WikiHow QA and PubMedQA to evaluate its effectiveness. The proposed system achieved strong quantitative results, with scores on WikiHow QA (ROUGE-1: 34.10, ROUGE-2: 12.30, ROUGE-L: 32.10, BLEU: 25.14, BERTScore: 95.17) and PubMedQA (ROUGE-1: 42.30, ROUGE-2: 16.10, ROUGE-L: 33.40, BLEU: 31.66, BERTScore: 95.72), demonstrating its ability to generate accurate and contextually relevant answers. Qualitative evaluations also yielded promising outcomes, with average ratings of 4.37 for information, 4.16 for conciseness, 4.20 for readability, and 4.01 for correctness on a 5-point scale, confirming the model’s effectiveness in delivering accurate and comprehensible responses. This transfer learning-based QAS framework contributes meaningfully to advancements in NLP and offers valuable support for researchers and developers working on intelligent, explainable, and practical question answering systems.
A review of sustainable housing preferences and affordability
(7th International Conference on Science and Sustainable Development and Workshop, 2024) Mushanga, S.; OLOKE, Olayinka C.; Olukanni, D. O.
The review examined the potential connections between sustainable housing, and sustainable affordability of such housing while meeting the housing preferences of various households. It is widely known that many lower-income countries are facing a housing crisis, and it is crucial to address this issue by providing affordable housing that meets individual needs while also promoting environmentally friendly living. This review paper Is centered on the research question: How can sustainable housing be made more affordable and accessible to all households while meeting their housing preferences? A qualitative study of 66 publications from 2019 to September 2023 found that sustainable housing offers ecological and energy-efficient benefits, but there are barriers to scaling up these models, including economic, cultural, and legal challenges. Housing preferences are influenced by factors such as cost, location, and amenities, with affordability being a significant concern. While environmental and economic sustainability can positively impact housing prices in turn affect the affordability of such housing, the initial investment costs can be challenging for lower-middle-income households. The review further established that Sustainable housing, housing preference, and affordability are broad topics that have been explored by many researchers. However, there are still some research gaps that need to be addressed. There is a significant gap in how sustainable housing can be made affordable to all households while meeting their housing preference hence the need to explore the intersection between sustainable housing, housing preference, and affordability by carrying out empirical research to identify ways in which sustainable housing can be designed and built to meet the needs and preferences of low-income households while remaining affordable.
A Snapshot of Nigeria’s Biodiversity Loss: Architectural Implications
(Preprints, 2024-08) Babalola, Daniel Olatunde; Ndimako, Onyedikachukwu; Nduka-Kalu, Chidinma
Biodiversity loss poses a significant threat to ecosystems and human well-being globally, with Nigeria no exception. This article delves into the architectural implications of biodiversity loss in Nigeria, exploring the multifaceted factors contributing to this phenomenon and its ramifications for architectural practice. The discussion encompasses the adverse impacts of deforestation, pollution, and climate change on Nigeria's rich biodiversity and the challenges and opportunities they present for architects. Through examining case studies and examples, the article highlights innovative architectural projects that address biodiversity loss while promoting sustainable design principles. Moreover, it elucidates the importance of interdisciplinary collaboration between architects, biologists, and policymakers in developing effective mitigation and adaptation strategies. Ultimately, this article underscores the urgent need for architects to integrate biodiversity conservation into their practices and advocates for policy interventions that prioritise the preservation of Nigeria's natural heritage.
A STUDY OF BIOPHILIC DESIGN STRATEGIES FOR THE DESIGN OF A CONDOMINIUM IN PORT HARCOURT, NIGERIA
(Covenant University Ota, 2025-05) LEBELE-ALAWA, Gold Tonubari; Covenant University Dissertation
Urbanization in Port Harcourt, Nigeria, has significantly increased the demand for high-density residential solutions, particularly condominiums. However, many of these developments tend to neglect the significance of nature-centric design strategies, which are crucial for occupant well-being. Biophilic design—an approach that incorporates natural elements into architectural spaces—presents an effective solution for enhancing the quality of life in urban settings. This study explored the relevance and impacts of biophilic design strategies within high-rise condominiums in Port Harcourt. Its objectives include identifying effective biophilic elements, evaluating their application, and assessing their effect on resident satisfaction and well-being. Utilizing a mixed-methods approach, the research integrated a literature review, case studies, observational analysis, and structured surveys across selected condominium developments. The findings highlighted a prevalent underutilization of biophilic features such as natural lighting, ventilation, green spaces, and water elements. Nevertheless, in instances where these features were implemented, they positively influenced thermal comfort, psychological wellness, and overall user satisfaction. The study concluded with a proposal for a context-sensitive biophilic condominium design that aligns with the climatic and urban realities of Port Harcourt. Recommendations were made to promote policy-driven biophilic adoption and culturally adaptive sustainable architecture, aiming to improve urban residential quality while aligning with global sustainability objectives.
ADAPTING MOBILESAM FOR FEW-SHOT SEGMENTATION OF PROSTATE CANCER IN HISTOPATHOLOGY IMAGES
(Covenant University Ota, 2025-08) ANTHONY, Micheal IdediA; Covenant University Dissertation
Segmenting prostate cancer in tissue images is difficult because of irregular gland shapes, broken tissue structures, and very few labelled images available for training. This study introduces FrozenSE-SAM, a segmentation method that works well even with small datasets. It combines a frozen MobileSAM encoder with a lightweight decoder enhanced by Squeeze-and-Excitation (SE) blocks and is trained using Focal Tversky Loss, which helps focus on difficult regions. Unlike older methods that need extra shape information or lots of labels, FrozenSE-SAM can directly segment tumour regions without prompts. It was trained on only 35 tissue microarray (TMA) cores from the Gleason 2019 dataset and tested on 100 new samples. The model achieved a Dice score of 68.45%, which is better than U-Net (60.72%), Swin-UNETR (58.12%), and a Signed Distance Function (SDF) based model (62.77%). For measuring boundary accuracy, FrozenSE-SAM showed better performance with HD95 = 0.0228 mm and ASD = 0.0056 mm, compared to the SDF model (HD95 = 0.0328 mm, ASD = 0.0072 mm), and worse scores from U-Net and Swin-UNETR. Visual/Qualitative result also confirmed that FrozenSE-SAM was better at outlining complex tumour regions. It could accurately segment cribriform and fused glands without including nearby healthy tissue. In contrast, the SDF model produced blurry edges and missed finer structures, leading to under-segmentation. These results show that FrozenSE-SAM is a strong, reliable method for prostate cancer segmentation, especially in real-world situations with limited data.
Adoption of Inclusive Architecture Design Strategies in Selected Community Centres, Lagos Mainland, Nigeria
(Civil Engineering and Architecture 12(6), 2024) Adewale, B. A.; Odewumi, Anuoluwa Nissi
Community centres play a variety of important responsibilities in communities. They function as cohesive environments, fostering the convergence of individuals from diverse backgrounds to engage in collaborative endeavours and promote inclusion, which is essential for sustainable urban development. This study examined the adoption of inclusive architecture strategies in three selected community centres in Lagos Mainland, Nigeria – Araromi Youth Development Centre, Magodo Residents Association Community Centre, and Ikeja Youth Centre, in order to improve inclusion in public spaces and foster sustainable urban development. Employing a qualitative approach, the research aimed to evaluate the adoption level of inclusive architecture strategies in the study area. Utilising an observation guide as a research instrument supported by a thorough literature review, the study conducted in-depth case studies within the study area, revealing commendable levels of adoption. However, a deeper examination reveals opportunities for greater adoption of inclusive architecture strategies in order to achieve a more holistic and inclusive design aligned with global standards. This study also offers significant implications in the field of architecture as it provides a comprehensive framework that future research can use to assess and compare the inclusiveness of different public spaces. This research underscores the pressing need for enhanced inclusivity in urban spaces and public areas, contributing valuable insights to academic discussions and offering practical implications for educators, architects, urban planners, and policymakers, thus fostering inclusivity and sustainable urban development.
ALABI, Kehinde Elizabeth
(Covenant University Ota, 2025)
Prostate cancer (PCa) remains a major health concern, particularly in Nigeria, where incidence and mortality are high. Globally, PCa is a leading malignancy among men. Genetic variations, such as single-nucleotide polymorphisms (SNPs), may influence PCa susceptibility and progression. This study investigates the association of three SNPs, rs11549465 (Hypoxia Inducible Factor 1A), rs3211938 (Cluster of Differentiation 36), and rs6152 (Androgen Receptor), with PCa risk and severity in Nigerian men. A case-control study was conducted involving 73 PCa patients and 80 healthy controls. Genotyping was performed using the TaqMan assay, and allele and genotype frequencies were calculated. The rs6152 SNP showed a higher frequency of the A/G genotype in cases (24%) than controls (9.7%), with an odds ratio of 4.95 (95% CI: 1.54–17.35; p = 0.0091), suggesting a significant association with increased PCa risk. For rs11549465, the C/T genotype was more prevalent in cases (10.1%) than controls (2.6%), with an OR of 0.24 (95% CI: 0.02–1.33; p = 0.061), indicating a possible protective effect, though not statistically significant. The rs3211938 SNP showed no significant association with PCa risk. No investigated SNP showed a statistically significant association with the Gleason score. For rs11549465, the mean score for C/C was 7.34 compared with 7.75 for C/T (Mann–Whitney U = 66.0, p = 0.673). For rs3211938, T/T had a mean of 7.29 versus 7.64 for G/T (Mann–Whitney U = 199.0, p = 0.407). For rs6152, A/A, A/G, and G/G showed mean scores of 7.36, 6.00, and 7.80, respectively (Kruskal–Wallis H = 1.62, p = 0.445). These findings suggest a significant association between rs6152 and PCa risk in Nigerian men, highlighting the role of genetic factors in susceptibility. Further studies with larger cohorts are warranted to validate these associations and explore their potential in personalised medicine for PCa management in African populations.
An Assessment of the Implementation of Green Design Strategies in Selected Museums in Abuja, Nigeria
(Civil Engineering and Architecture e 12(3A), 2024) Adewale, B. A.; Ene, Vincent Onyedikachi
This study evaluates the implementation of green design strategies in selected museums in Abuja, Nigeria to inform sustainable approaches tailored to the local context. The qualitative study utilizes observational assessments of 3 major museums – Discovery Museum, Nike Art Gallery, and Retro Africa Gallery. A comparative analysis investigates the adoption of passive design, alternative energy, and water efficiency strategies based on a structured criterion aligned with global sustainability standards. The findings reveal a moderate integration of fundamental techniques like proper orientation, thermal mass walls, solar PV panels, and native drought-resistant plants across the museums. However, substantial gaps exist in implementing more comprehensive solutions like building insulation, greywater recycling, rain gardens, eco fixtures, and real-time metering. While initial steps have been taken, holistic opportunities remain to transform the museums into genuinely sustainable, net-zero facilities through extensive daylighting, diverse renewable systems, and total water recycling. The Retro Africa Gallery emerges as a leader, exemplifying an integrated green design approach. Recommendations are provided focused on state-of-the-art passive design, diversified alternative energy generation, and closed-loop water conservation strategies tailored to the contextual needs of Nigerian museums. The study concludes these institutions can become inspiring models of ecological design, leading broad climate action through pioneering sustainable architecture.
An Assessment of the Influence of Passive Cooling Strategies on Level of Thermal Comfort in Selected Office Buildings in Abuja, Nigeria
(Journal of Environment Sciences (JOES) ISSN 1118-8936 (Print); 3043-6176 (Online), Vol. 23, No. 2,, 2024-12) Oluwatayo, Adedapo Adewunmi; NDUKA, Miracle D.
Buildings contribute significantly to global energy consumption, with cooling needs forming a substantial part of this demand. Passive cooling techniques present an energy-efficient alternative, promoting occupant comfort while reducing energy costs. This study analyzed the influence of passive cooling strategies on thermal comfort within office buildings in Abuja, Nigeria. Specifically, it evaluated current practices, analyzed implementation patterns, and provided recommendations for improved adoption. A quantitative research approach was employed, involving data collection through questionnaires distributed to 73 participants across three office buildings, with a response rate of 90%. The data, analyzed using both descriptive and inferential statistical techniques, revealed that most respondents (69.7%) reported discomfort. Regression analysis identified 15 significant factors affecting thermal comfort, including operable windows, courtyards, and window-to-wall area ratios, which had positive effects, while factors such as external insulation and vertical air shafts negatively impacted comfort. These findings offer insights into designing more sustainable and energy-efficient office environments, ultimately enhancing occupant well-being and productivity.
An Assessment of User Satisfaction with Security Strategies in Selected Bus Terminals in Lagos, Nigeria
(Covenant Journal of Research in the Built Environment (CJRBE) Vol.12, No.1, 2024-10) Ekhaese, Eghosa N.; Okonkwo, E. Emmanuel
Public transportation systems, especially bus terminals, are critical for urban mobility but face significant security challenges due to high foot traffic and open access. This research aims to assess user satisfaction with security measures at four major bus terminals in Lagos, Nigeria. The study adopts a quantitative design, employing a purposive sampling method to select 400 users from a population of approximately 1,200 daily commuters. Out of these, 320 valid responses were obtained and analyzed using SPSS software. Analytical tools such as descriptive statistics and chi-square tests were utilized to explore the data. Key findings reveal that while there is a general awareness of security strategies, their perceived adequacy and availability vary. CCTV surveillance and physical security are widely recognized, yet measures like threat assessment are less familiar. Respondents rated CCTV surveillance as the most adequate, though all strategies positively impacted users' safety perceptions. Despite this, satisfaction levels indicate room for improvement. Recommendations include enhancing public awareness, continuous monitoring, and incorporating user feedback into security protocols. This multi-layered approach aims to foster a secure environment, boosting public confidence and efficient mobility. The study's insights are valuable for policymakers and security professionals in refining and implementing robust, user-centric security measures in public transportation systems.
AN OPTIMIZED DEEP-FOREST MODEL USING A MODIFIED DIFFERENTIAL EVOLUTION OPTIMIZATION ALGORITHM: A CASE OF HOST-PATHOGEN PROTEIN-PROTEIN INTERACTION PREDICTION
(Covenant University Ota, 2025-04) EMMANUEL JERRY DAUDA; Covenant University Thesis
Deep forest is an advanced ensemble learning technique that employs forest structures within a cascade framework, leveraging deep architectures to enhance predictive performance by adaptively capturing high-level feature representations. Despite its promise, deep forest models often face critical challenges, including manual hyperparameter optimization and inefficiencies in computational time and memory usage. To address these limitations, Bayesian optimization, a prominent model-based hyperparameter optimization method, is frequently utilized, with Differential Evolution (DE) serving as the acquisition function in recent implementations. However, DE's reliance on random index selection for constructing donor vectors introduces inefficiencies, as suboptimal or redundant indices may hinder the search for optimal solutions. This study introduces an optimized deep forest algorithm that integrates a modified DE acquisition function into Bayesian optimization to improve host-pathogen protein-protein interaction (HPPPI) prediction. The modified DE approach incorporates a weighted and adaptive donor vector selection mechanism, enhancing the exploration and exploitation of hyperparameter configurations. Performance evaluations using 10-fold cross-validation on human–Plasmodium falciparum (PF) protein sequence datasets sourced from reputable databases demonstrated the model's superiority over traditional Bayesian optimization, genetic algorithms, evolutionary strategies, and conventional machine learning models. The optimized framework achieved an accuracy of 89.3%, sensitivity of 85.4%, precision of 91.6%, and Area Under the Receiver Operating Characteristic Curve (AUROC) of 89.1%, surpassing existing methods. Additionally, the model exhibited reduced computational time and memory usage. The optimized DF was deployed as a web-based pipeline, DFH3PI (Deep Forest Host-Pathogen Protein-Protein Interaction Prediction), which successfully identified three potential human–PF PPIs previously classified as non-interacting: P50250–P08319, Q8ILI6–O94813, and Q7KQL3–Q96GQ7. These findings not only present the potential of DFH3PI for advancing HPPPI prediction but also establish the optimized deep forest framework as a transformative tool in computational biology. Its ability to combine accuracy and efficiency marks a significant step forward in predictive modeling.
ANALYSIS OF PHYTATE CONTENT VARIABILITY AND MOLECULAR CHARACTERISATION OF GENES IN COWPEA LANDRACES
(Covenant University Ota, 2025-08) OMODIAGBE, David Eromosele; Covenant University Dissertation
Phytate is a naturally occurring phosphorus-storage compound in seeds, but it reduces the bioavailability of iron, zinc, and calcium in human diets. Cowpea (Vigna unguiculata (L.) Walp), an essential dietary protein source widely consumed in Nigeria, contains notable phytate levels, which may hinder micronutrient absorption with regular consumption. This study investigated phytate content in Nigerian cowpea accessions and explored candidate genes involved in its biosynthesis to guide future efforts for nutritional improvement. Thirty (30) cowpea landraces were obtained from the National Centre for Genetic Resources and Biotechnology (NACGRAB). Phytate concentration was quantified using acid digestion followed by filtration and titration. To explore the genetic basis of phytate accumulation, protein sequences of known phytate biosynthetic genes from Arabidopsis thaliana, Glycine max, and Phaseolus vulgaris were retrieved from Phytozome 14.0. These sequences were used for BLASTp searches to identify putative homologues in cowpea. Homologous cowpea sequences were aligned and subjected to phylogenetic analysis using the Neighbour-Joining method in MEGA v12.0.11 with 10,000 bootstrap replicates to assess evolutionary relationships. The results showed significant variation in phytate content, 3.96‒30.94mg/g (p < 0.001) across cowpea accessions. The cowpea sequences displayed strong homology to known phytate biosynthetic enzymes in seed, MIPS (Myo-inositol-3-phosphate synthase), ITPK (Inositol 1,3,4-triphosphate 5/6-kinase), IPK2 (Inositol 1,4,5-tris-phosphate kinase), MRP (Multidrug-resistance-associated protein ATP-binding cassette), IMP (Inositol monophosphate phosphatase), MIK (Myo-inositol kinase), and IPK1 (Inositol 1,3,4,5,6 pentakisphosphate 2-kinase), with low E-values and high identity percentages. Phylogenetic clustering of cowpea sequences alongside those from related legumes suggests potential functional conservation, although expression-level validation is necessary. Quantitative gene expression profiling to further clarify the roles of these genes in phytate biosynthesis and accumulation is needed. These identified genes could be prioritised for reverse genetics or transcriptomic studies, provided that tissue-specific expression and off-target impacts are carefully evaluated
Application of Artificial Intelligence (AI) in Sustainable Building Lifecycle; A Systematic Literature Review
(Preprints, 2024) Adewale, B. A.; Ene, Vincent Onyedikachi; Ogunbayo, Babatunde Fatai; Aigbavboa, Clinton Ohis
With buildings accounting for a significant portion of global energy consumption and greenhouse gas emissions, the application of artificial intelligence (AI) holds promise for enhancing sustainability in the building lifecycle. This systematic literature review addresses the current understanding of AI’s potential to optimize energy efficiency and minimize environmental impact in building design, construction, and operation. A comprehensive literature review and synthesis were conducted to identify AI technologies applicable to sustainable building practices, examine their influence, and analyze the challenges of implementation. The review was guided by a meticulous search strategy utilizing keywords related to AI application in sustainable building design, construction, and operation. The findings reveal AI’s capabilities in optimizing energy efficiency through intelligent control systems, enabling predictive maintenance, and aiding design simulation. Advanced machine learning algorithms facilitate data‐driven analysis and prediction, while digital twins provide real‐time insights for informed decision‐making. Furthermore, the review identifies barriers to AI adoption, including cost concerns, data security risks, and challenges in implementation. AI presents a transformative opportunity to enhance sustainability in the built environment, offering innovative solutions for energy optimization and environmentally conscious practices. However, addressing technical and practical challenges will be crucial for the successful integration of AI in sustainable building practices.
Application of VLF-EM response and geoelectrical sounding in groundwater investigation around an active dumpsite
(Application of VLF-EM response and geoelectrical sounding in groundwater investigation around an active dumpsite, 2024) Adeniji, A. A.; Ajani, O. O.; Adagunodo, T. A.
An integrated geophysical method combining very low frequency electromagnetic (VLF-EM) and vertical electrical sounding (VES) methods were carried out around Adaland, Southwestern Nigeria, located within latitude 70 54' 0" and longitude 40 43' 0", with a view to investigate the possible impact of dumpsite on groundwater.This is the major study in the environment to offer extensive evidence regarding the suitability of obtaining quality groundwater. In this research, eight VLF-EM and twelve VES data sets were generated, which were then used to estimate the linear structure, bedrock formation, subsurface geological characteristics, and identification of leachate pathways. The VLF-EM data were analyzed by employing Karous_Hjelt and Microsoft Excel, while the VES data were investigated using the WinRESIST software. TheVLF-EM results confirmed the presence of conductive zones, which might be due to fracture, fault and contact zones or weathered basements. The lithological units acquired from the electrical resistivity results revealed four geoelectrical layers such as topsoil, weathered-based, fractured basement and fresh basement. However, the identified weathered layers and fractured basements from the geoelectrical sections and the corresponding Karous and Hjelt (K-H) pseudo sectionresults around the dumpsite, constitute the main passages for the possible impact of the open dumpsite on groundwater quality, since leachates from the dumpsite could slowly percolate downwards from the topsoil to the water table. Therefore, the impact of the dumpsite on the groundwater is caused by the inadequate clay materials, near-surface features such as fractures/faults, and lateral in-homogeneity. Thus, integrating both methods has been recommended in site characterization for accessing quality groundwater around a dumpsite environment.
Assessing Building Information Modelling Usage Level in Construction Projects: Construction Professionals Perspectives
(The Fourteenth International Conference on Construction in the 21st Century, 2024-09) Ogunbayo, B. F.; Aigbavboa, Clinton; Liphadzi, Murendeni; Adewale, B. A.
Building Information Modelling (BIM) usage in the construction industry has rapidly become a game-changer in construction activities, which has revolutionised project planning, designing, construction and management, leading to significant improvements in project coordination, collaboration, efficiency, and overall project outcomes. Hence, this study aims to assess BIM usage in construction projects based on construction professionals' perspectives toward establishing its usage level for different construction activities. Structured questionnaires were distributed to construction professionals in Gauteng province, South Africa, using systematic random sampling techniques to collect data on the level of BIM usage for construction activities for projects within the construction industry. Data was collected through the quantitative approach using a questionnaire survey. A valid mean item score was determined in the study using a statistical data equation; each item was ranked with standard deviations, and Cronbach’s alpha was established. The study findings indicated that project design and planning were the highest-ranked levels of BIM usage in projects in the construction industry. The study recommends that evolving BIM with other innovative technologies, such as cloud-based collaboration, digital twins, and artificial intelligence, will drive the digital transformation of construction projects, improve project delivery processes, and create value for construction stakeholders. The study concluded that the continuous usage of BIM for construction activities will play a key role in reshaping the future of activities in projects and driving digital transformation within the construction industry.
Assessing Building Information Modelling Usage Level in Construction Projects: Construction Professionals Perspectives
(The Fourteenth International Conference on Construction in the 21st Century, 2024-09) Ogunbayo, B. F.; Aigbavboa, Clinton; Liphadzi, Murenden; Adewale, B. A.
Assessing subsurface heterogenenity and infiltration capacity at a restored wetland using geophysical imaging and infiltration tests
(2025) Otchere, Nana-Aboagye; Aizebeokhai, Ahzegbobor P.; Martin-Hayden, James; Doro, Kennedy O.
Wetland soil properties and stratigraphic heterogeneity influence their water-holding capacity, 15 infiltration, and subsurface flow. Infiltration, however, depends on the soil’s saturated hydraulic 16 conductivity (Ksat) whose spatial variability at field scale is difficult to quantify. In this study, we 17 combined electromagnetic imaging (EMI) and electrical resistivity (ER) with infiltration tests to 18 assess the spatial variation in the shallow subsurface stratigraphy and Ksat at a restored wetland in 19 northwest Ohio. We used a Geonics EM38-MK2, with a transmitter and two receivers spaced 0.5 20 and 1.0 m to map the spatial distribution of the soil’s apparent electrical conductivity (ECa). The 21 ER measurements were acquired along nine transects using a SuperSting R8 resistivity meter 22 with 84-electrode and a dipole-dipole electrode array. The ER results, constrained with 23 lithostratigraphic logs, showed 0.7 m thick topsoil (silty loam) underlain by 0.5 m thick clayey 24 loam interspersed with coarser materials and alternating units of diamictons. The observed ECa 25 were relatively higher (10 – 40 mS/m) for the 0.5 m T-R spacing compared to the 1.0 m spacing 26 (8 – 36 mS/m). The spatial distribution of Ksat ranged from 0.01 – 0.9 mm/min with higher 27 values at areas with high silt and sand content. A least-squared linear regression between Ksat 28 and ECa yielded coefficient of determination (R2) values >0.62 indicating the effectiveness of 29 EMI for predicting the spatial variation of Ksat. Thus, combining geophysical imaging with field 30 infiltration tests provided valuable insights into infiltration through the soil and potential 31 subsurface flow at the restored wetland with limited details on subsurface flow.
ASSESSMENT OF AIRBORNE AND TERRESTRIAL RADIOMETRIC CONCENTRATIONS AND ASSOCIATED HEALTH RISKS IN SELECTED LOCATIONS IN SOUTHWEST NIGERIA
(Covenant University Ota, 2025-08) MORAKINYO, Ruth Omoseeke; Covenant University Thesis
Radiation is an inevitable part of the human environment, both from terrestrial and anthropogenic sources. Elevation of radiation levels in an environment above the threshold limit is detrimental to man and the ecosystem. Therefore, monitoring the radiation level of every human environment is expedient because of the harmful effect of exposure to ionizing radiation. The radiometric data of selected locations in southwest Nigeria was collected from the database of the Nigeria Geological Survey Agency (NGSA) and analysed using the Oasis Montaj software. The result of the NGSA data served as a guide in the selection of locations for in-situ assessment using an RS-125 handheld gamma spectrometer. Soil and water samples were collected in those locations and some quarry sites and analysed in the laboratory using NaI (TI) detector. The obtained activity concentrations were used to determine the radiological parameter. The absorbed dose rate for analysed aero radiometry data ranges between 31.92-214.04, 36.31-192.77, 13.82-162.02, 6.57-119.62, 10.83-116.93 and 16.4-63.70 nGy/h for Ado-Ekiti, Akure, Ondo, Apomu, Ibadan, and Ijebu-ode sheets respectively. The mean absorbed dose rate for in-situ assessment for the exact locations ranges between 38.00-149.43, 86.00-179.27, 51.21-116.53, 72.76-109.09, 84.32-194.41, 56.27-64.55nGy/h respectively. The results of soil and water samples of selected locations and quarry sites revealed that the absorbed dose rate in soil samples in 80% of the locations and 100% of the quarry sites was higher than the world average value. The estimated total annual committed dose for various categories of ages in all the water samples were higher than the world average value. The estimated annual effective dose and excess lifetime cancer risk in most locations in in-situ assessment and analysis of soil samples was higher than the global limit. Statistical analysis revealed that the concentration of 232Th contributes significantly to the absorbed dose rate in air and the total annual committed dose due to ingestion of water. In contrast, the activity concentration of 40K contributes significantly to the absorbed dose rate in soil samples in the study area. The need for potable water for the various communities in the region cannot be over-emphasized as the total annual effective dose for all categories of ages was higher than the reference limit. The study concludes that analysis of aero-radiometry data can be an effective guide in monitoring the radioactivity level of an environment.