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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 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.
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.
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.
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.
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.
ASSESSMENT OF FGFR2 AND FGFR4 POLYMORPHISMS IN NIGERIAN BREAST CANCER PATIENTS
(Covenant University Ota, 2025-09) OGBODO, Peace Nzubechukwu; Covenant University Dissertation
Breast cancer (BC) persists as the most frequently occurring cancer in females, with a growing incidence percentage in sub-Saharan Africa. BC has been correlated with FGFR2 and FGFR4 genetic variations in different populations. However, the data on Nigerian women are scarce. This study investigated the association of FGFR2 rs1219648 (A>G), FGFR2 rs2981582 (A>G), and FGFR4 rs351855 (G>A) with BC risk in a Nigerian cohort. A case-control design was employed involving 75 BC cases and 75 controls. Using blood samples, genomic DNA was extracted, and SNP genotyping was conducted with the use of TaqMan® allelic discrimination assay. Genotype and allele frequencies comparison was conducted using chi-square, odds ratios, and Fisher’s exact tests. The FGFR2 rs1219648 G allele was significantly more common (48.0%) in cases than controls (35.3%), with the GG genotype conferring a significant increase in risk (OR = 2.61, 95% CI: 1.07 - 6.64, p = 0.039). FGFR2 rs2981582 showed no significant genotype-level association, but the minor A allele was more common in cases (43.2%) than controls (31.3%) (p = 0.045). FGFR4 rs351855 was not significantly associated with BC. None of the SNPs showed association with tumour immunohistochemical subtypes. The findings identify FGFR2 rs1219648 as a significant risk factor for BC in Nigerian women and highlight the need for larger, multi-centre studies to validate these associations.
ASSESSMENT OF HEALING ARCHITECTURE STRATEGIES FOR THE DESIGN OF ORIKI GROUP WELLNESS CENTRE, JABI, ABUJA, NIGERIA
(Covenant University Ota, 2025-06) INI-UKIM, Didarabasi Esther; Covenant University Dissertation
This study investigates the implementation of healing architecture strategies in the design of a wellness centre located in Jabi, Abuja, with a focus on enhancing users’ physical, emotional, and mental well-being. The study grounded in Biophilic Design Theory and Therapeutic Landscape Theory explores how nature-integrated and sensory design elements promote health and wellbeing. The research reviewed literature and relevant theoretical frameworks to reveal elements such as natural and artificial lighting, ventilation, biophilic elements, acoustic comfort, colour psychology and spatial coherence play crucial roles in a therapeutic environment to support physical and mental balance. A comparative analysis of international and domestic case studies to evaluate how these strategies have been implemented in existing wellness centres around the world including SHA Wellness Clinic, Chiva-Som, Mii Amo and Abuja based centres such as Nisa Wellness Retreat, Beauty Secrets MedSpa, and JVee Wellness Spa. Findings from the analysis showed Nisa Wellness Retreat and Beauty Secrets MedSpa demonstrated stronger biophilic and therapeutic elements compared to JVee Wellness Spa. Structured questionnaires were administered to assess user perception of these healing architecture strategies, and the responses were analysed using descriptive statistics and reliability tests (Cronbach’s Alpha = 0.856). The results indicate users highly value natural lighting, quietness, ventilation and exposure to nature, as these strategies contribute significantly to relaxation, mental clarity and overall comfort. The research offers valuable design insights for architects and developers seeking to incorporate healing architecture strategies therapeutic environments.
ASSESSMENT OF INCLUSIVE ARCHITECTURAL STRATEGIES FOR THE DESIGN OF AN INNOVATION HUB FOR OYO STATE GOVERNMENT IN OGBOMOSO, NIGERIA
(Covenant University Ota, 2025-07) OYELUDE, Felicia Opeyemi; Covenant University Dissertation
Inclusive architectural strategies are crucial in ensuring that innovation hubs serve as equitable environments to promote creativity, social participation, and accessibility for all users. This study explores the assessment of inclusive architectural strategies and their impact on social inclusion within selected innovation hubs in Southwest Nigeria. The aim of the study was to enhance social inclusivity through the integration of inclusive design principles in the architectural development of innovation hubs. To achieve this, the study pursued four key objectives: to identify inclusive architectural strategies applicable to innovation hub design; to examine the social inclusion characteristics within innovation hubs; to assess the impact of inclusive architectural strategies on improving social inclusion; and to apply findings in the design of a proposed innovation hub in Ogbomoso. A pragmatic research philosophy guided the study, adopting a mixed-methods approach. The research design was based on case studies of five innovation hubs: Oluseun Onigbinde Resource Centre, Premier Hub Innovation Centre, Co-Creation Hub, PDX Innovation Hub, and Dare Adeboye Innovation Hub. Data were collected through structured questionnaires (n=170) and observation checklists, and analysed using SPSS for quantitative data and thematic analysis for qualitative insights. Key findings reveal that inclusive architectural features, such as barrier-free access, intuitive wayfinding, sensory design elements, and flexible workspaces, positively influence users’ sense of belonging, engagement, and social interaction. However, several barriers hinder full implementation, including weak policy enforcement, limited funding, inadequate stakeholder awareness, and partial adherence to national accessibility codes. This study contributes to the growing body of knowledge on inclusive architecture in developing contexts and highlights the need for architects, policymakers, and innovation hub managers to prioritize universal design principles from inception. It also provides a practical design framework for inclusive innovation hubs. Limitations of the study include its geographical focus on innovation hubs in Southwest Nigeria and the fact that only innovation hubs that granted access for case study visits were used, resulting in a purposive selection. Recommendations for future research include expanding the scope to other regions in Nigeria or other developing countries, incorporating longitudinal studies to assess long-term user experience, and exploring digital inclusivity in hybrid innovation environments.
Assessment of Lighting Strategies in Art Galleries: A Comparative Case Study of Selected Art Galleries in Lagos State
(3rd International Conference on Energy and Sustainable Environment (IOP Publishing), 2022) Ekhaese, Eghosa N.; Solaja, A. O.
Light is so important in our everyday lives that it effects user experiences of spaces as well as the user's overall well-being for a large portion of the day in the built environment. Lighting, among the other aspects that make up the design of spaces, is an important characteristic in a building because it is the primary means of appreciating art and culture. The study aimed to assess purposively selected art galleries as the basis for determining the best lighting strategies to be adopted in the design of an art gallery in Lagos, Nigeria. This study addressed two key objectives – identify the existing lighting strategies used in the assessed art galleries to recommend the best lighting strategies to be used and ascertain how the lighting strategies are implemented. A qualitative research method using case study approach was employed in the research. Content and narrative analyses were used to analyse data. Findings show a significant need for daylight to be implemented alongside artificial lighting in an art gallery. The results align with current global trends towards sustainability.
ASSESSMENT OF PASSIVE DESIGN STRATEGIES FOR ENHANCING USERS’ COMFORT IN DENNIS OSADEBEY UNIVERSITY LIBRARY, ASABA, NIGERIA
(Covenant University Ota, 2025-07) AMADHE, Florence Ewomazino; Covenant University Dissertation
Academic libraries in tropical regions like southern Nigeria often suffer from poor environmental control and user discomfort due to limited application of passive design strategies. This study aimed to assess the effectiveness of passive design elements in enhancing user comfort, with a focus on informing the design of a proposed academic library at Dennis Osadebay University, Asaba. The research was guided by Environmental Comfort Theory and the Bioclimatic Design Framework, which emphasize human-centred, climate-responsive architectural solutions. Four objectives directed the study: to examine effective implementations of passive strategies in hot-humid climates; to determine the extent of adoption in selected academic libraries; to evaluate how the presence or absence of these strategies impacts user comfort; and to apply the findings in the design of a new academic library. A mixed-methods approach was employed, combining literature review, structured observations, international case analyses, and a user survey involving 315 respondents. Data analysis included content analysis, descriptive statistics, Spearman’s rank correlation, and CATREG regression modeling. Findings from the literature review revealed that natural ventilation, daylighting, spatial zoning, thermal massing, and shading devices are among the most frequently recommended passive design strategies for hot-humid climates. Observations from three academic libraries in Delta State showed limited implementation of ventilation and shading strategies, though daylight access and spatial layout were moderately considered. Survey results indicated strong correlations between user comfort and proximity to windows, daylight quality, and spatial flexibility, with regression analysis identifying spatial layout (β = 0.402), artificial lighting, and sunlight control as the strongest predictors of comfort (Adjusted R² = 0.530). These findings informed the final architectural design proposal, incorporating passive techniques adapted to Asaba’s climatic context. The study concludes that passive design strategies significantly enhance comfort in academic libraries and recommends prioritizing adaptable layouts, hybrid ventilation systems, and daylight optimization in future institutional projects.