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27,661 results on '"Abiodun, A. A."'

2. Revolutionizing Teacher Productivity: Unravelling the Secret of High-Performance Work System in Strategic Human Resource Management

Author

Rihanat Abiodun Ashade and Shareef Akanbi Ashade

Abstract

High-performance work systems (HPWS) have been a topic of interest in various industries, but their impact on teachers' productivity in Nigeria is a crucial area of study. The education sector in Nigeria faces numerous challenges, including inadequate resources, large class sizes, and limited professional development opportunities. In addressing the challenges, this research was conducted to seek their perception of the role of HPWS on teacher's productivity. Data were collected from the six educational districts of public schools, among 492 teachers in Lagos, Nigeria. The data was analyzed using Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). The findings provide new insights into the value of HPWS in SHRM in the education sector. The result showed that implementing high-performance work systems in this context could potentially lead to improved teacher productivity, benefiting both educators and students alike.

Published
2024

3. Determinants Influencing the Adoption of Metaverse-Based Learning Platforms among University Students

Author

Emmanuel John Anagu, Oladunjoye John Abiodun, Felicia Cletus, and Brown Ephraim

Abstract

Metaverse, an amalgamation of diverse information technologies, is seen as the future of the internet and holds promise for transforming education. Leveraging metaverse media for immersive learning has the potential to reshape education practices. Despite being a novel concept, metaverse-based education has the capacity to enrich online learning experiences. The study utilized the Unified Theory of Acceptance and Use of Technology (UTAUT) model alongside the factor of personal innovativeness in IT, conducting a comprehensive survey involving 244 students from Federal University Wukari, Nigeria. Employing STATA 14, a popular variance-based structural equation modeling technique in social sciences and management, the study analyzed the structural model and conceptual measures, confirming the discriminant validity, dependability, and content of the data. The research findings highlight the importance of personal innovativeness in IT as a direct and indirect predictor of adoption intention among Generation Z students in making decisions about integrating metaverse technologies into higher education. Students demonstrating a high level of innovativeness in IT exhibit a greater willingness to engage with metaverse-based learning incorporating artificial intelligence. The results demonstrate a strong association between the identified characteristics and students' intentions to utilize educational platforms utilizing metaverse technology, contributing valuable insights to the use of technology in educational settings.

Published
2024

4. Laboratory validation of a clinical metagenomic next-generation sequencing assay for respiratory virus detection and discovery.

Author

Tan, Jessica, Servellita, Venice, Stryke, Doug, Kelly, Emily, Streithorst, Jessica, Sumimoto, Nanami, Foresythe, Abiodun, Huh, Hee, Nguyen, Jenny, Oseguera, Miriam, Brazer, Noah, Tang, Jack, Ingebrigtsen, Danielle, Fung, Becky, Reyes, Helen, Hillberg, Melissa, Chen, Alice, Guevara, Hugo, Yagi, Shigeo, Morales, Christina, Wadford, Debra, Mourani, Peter, Langelier, Charles, de Lorenzi-Tognon, Mikael, Benoit, Patrick, and Chiu, Charles

Subjects
Humans, High-Throughput Nucleotide Sequencing, Metagenomics, Respiratory Tract Infections, Viruses, Female, Adult, Middle Aged, Male, Sensitivity and Specificity, Bronchoalveolar Lavage Fluid, Aged, Child, Adolescent, Young Adult, Viral Load, Child, Preschool
Abstract

Tools for rapid identification of novel and/or emerging viruses are urgently needed for clinical diagnosis of unexplained infections and pandemic preparedness. Here we developed and clinically validated a largely automated metagenomic next-generation sequencing (mNGS) assay for agnostic detection of respiratory viral pathogens from upper respiratory swab and bronchoalveolar lavage samples in

Published
2024

5. Predicting 3D Rigid Body Dynamics with Deep Residual Network

Author

Oketunji, Abiodun Finbarrs

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Graphics, Computer Science - Machine Learning, I.2.7
Abstract

This study investigates the application of deep residual networks for predicting the dynamics of interacting three-dimensional rigid bodies. We present a framework combining a 3D physics simulator implemented in C++ with a deep learning model constructed using PyTorch. The simulator generates training data encompassing linear and angular motion, elastic collisions, fluid friction, gravitational effects, and damping. Our deep residual network, consisting of an input layer, multiple residual blocks, and an output layer, is designed to handle the complexities of 3D dynamics. We evaluate the network's performance using a datasetof 10,000 simulated scenarios, each involving 3-5 interacting rigid bodies. The model achieves a mean squared error of 0.015 for position predictions and 0.022 for orientation predictions, representing a 25% improvement over baseline methods. Our results demonstrate the network's ability to capture intricate physical interactions, with particular success in predicting elastic collisions and rotational dynamics. This work significantly contributes to physics-informed machine learning by showcasing the immense potential of deep residual networks in modeling complex 3D physical systems. We discuss our approach's limitations and propose future directions for improving generalization to more diverse object shapes and materials.

Published
2024
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7. Risk Factors for Viral Non-suppression Among Youth Living with HIV in Nigeria: Findings from the iCARE Nigeria Study

Author

Balogun, Mobolanle, Kuhns, Lisa M., Akanmu, Alani S., Garofalo, Robert, Badru, Titilope, Adekanmbi, Abiodun F., Akinbami, Akinsegun, Agbaji, Oche, David, Agatha N., Omigbodun, Olayinka, Cevantes, Marbella, Janulis, Patrick, Akintan, Patricia, Awolude, Olutosin, Kuti, Kehinde M., Sodipo, Oluwajimi, Yiltok, Esther, Mautin, Gbenayon J., Ezemelue, Priscilla, Berzins, Baiba, and Taiwo, Babafemi

Published
2025
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11. African Control of Hypertension through Innovative Epidemiology and a Vibrant Ecosystem (ACHIEVE): novel strategies for accelerating hypertension control in Africa

Author

Owolabi, Mayowa, Olowoyo, Paul, Mocumbi, Ana, Ogah, Okechukwu S., Odili, Augustine, Wahab, Kolawole, Ojji, Dike, Adeoye, Abiodun M., Akinyemi, Rufus, Akpalu, Albert, Obiako, Reginald, Sarfo, Fred S., Bavuma, Charlotte, Beheiry, Hind Mamoun, Ibrahim, Moshen, El Aroussy, Wafaa, Parati, Gianfranco, Dzudie, Anastase, Singh, Sandhya, Akpa, Onoja, Kengne, Andre Pascal, Okekunle, Akinkunmi Paul, de Graft Aikins, Ama, Agyemang, Charles, Ogedegbe, Gbenga, Ovbiagele, Bruce, Garg, Renu, Campbell, Norman R. C., Lackland, Daniel T., Barango, Prebo, Slama, Slim, Varghese, Cherian V., Whelton, Paul K., and Zhang, Xin-Hua

Published
2025
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20. Design of a Process Route to Recover Antimony Ore Concentrate from the Sand Residue of Nigeria Ondo Tar Sand

Author

Adegbola, Abiodun S., Daniyan, Ayodele A., Adeleke, Abraham A., Akande, Rukayat T., Ibitoye, Simeon A., Oluwasegun, Kunle M., Forsberg, Kerstin, editor, Karamalidis, Athanasios, editor, Ouchi, Takanari, editor, Azimi, Gisele, editor, Alam, Shafiq, editor, Neelameggham, Neale R., editor, Baba, Alafara Abdullahi, editor, Peng, Hong, editor, and Kim, Hojong, editor

Published
2025
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21. PPP Potential of a Compact, Low-Cost GNSS Receiver’s Module in a Low Latitude Region: A Case Study at the Lautech GNSS Laboratory, Nigeria

Author

Segun, Adewumi Adebayo, Atilade, Àlàgbé George, Abiodun, Azeez Ibraheem, Benjamin, Ayantunji Gbenro, Anthony, Ogobor Efua, Oluwadara, Oyelowo, Iyinoluwa, Fajobi, Emmanuel, Eleyele Dolapo, Lee, Chuan-Pei, Series Editor, Weimin, Huang, Series Editor, Adimula, Isaac, editor, OJo, Joseph, editor, and Ogunjo, Samuel, editor

Published
2025
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23. Designing a Communication App for Privacy: A Scenario-Based and Participatory Approach

Author

Parrilli, Davide Maria, Ogunyemi, Abiodun Afolayan, Bauters, Merja Lina M., Hernández-Ramírez, Rodrigo, Tosi, Francesca, Editor-in-Chief, Germak, Claudio, Series Editor, Zurlo, Francesco, Series Editor, Jinyi, Zhi, Series Editor, Pozzatti Amadori, Marilaine, Series Editor, Caon, Maurizio, Series Editor, Martins, Nuno, editor, and Brandão, Daniel, editor

Published
2025
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24. An Authentication Model Using Brainwave Panic Region Classifications from Electroencephalography

Author

Abiodun, Opeyemi Anuoluwa, Oyinloye, Oghenerukevwe E., Thompson, Aderonke F., Olowoyo, Paul, Imoize, Agbotiname Lucky, Sur, Samarendra Nath, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Dhar, Sourav, editor, Do, Dinh-Thuan, editor, Sur, Samarendra Nath, editor, and Imoize, Agbotiname Lucky, editor

Published
2025
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25. Fault Detection in District Heating Substations: Overview of Real-Life Faults in Residential Heating Installations

Author

Marszal-Pomianowska, Anna, Leiria, Daniel, Johra, Hicham, Pomianowski, Michal, Praulins, Imants, Anoruo, Justus Chigozie Abiodun, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Jørgensen, Bo Nørregaard, editor, Ma, Zheng Grace, editor, Wijaya, Fransisco Danang, editor, Irnawan, Roni, editor, and Sarjiya, Sarjiya, editor

Published
2025
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26. Environmental Vibrio choierae Strains Harboring Cholera Toxin and Vibrio Pathogenicity Island 1, Nigeria, 2008-2015

Author

Morgado, Sergio, Adewale, Akinsinde, Abiodun, Iwalokun, Lawal, Salako, Freitas, Fernanda, Fonseca, Erica, and Vicente, Ana Carolina

Subjects
Control, Physiological aspects, Research, Environmental aspects, Vibrio cholerae -- Environmental aspects -- Physiological aspects -- Control, Public health -- Research
Abstract

Nigeria is one of the current cholera hotspots in Africa (1). The World Health Organization report On cholera cases in countries in Africa for January 2022-December 2023 showed that most [...]

Published
2024
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48. Generative AI in the Construction Industry: A State-of-the-art Analysis

Author

Taiwo, Ridwan, Bello, Idris Temitope, Abdulai, Sulemana Fatoama, Yussif, Abdul-Mugis, Salami, Babatunde Abiodun, Saka, Abdullahi, and Zayed, Tarek

Subjects
Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Human-Computer Interaction, Computer Science - Information Retrieval, Computer Science - Machine Learning
Abstract

The construction industry is a vital sector of the global economy, but it faces many productivity challenges in various processes, such as design, planning, procurement, inspection, and maintenance. Generative artificial intelligence (AI), which can create novel and realistic data or content, such as text, image, video, or code, based on some input or prior knowledge, offers innovative and disruptive solutions to address these challenges. However, there is a gap in the literature on the current state, opportunities, and challenges of generative AI in the construction industry. This study aims to fill this gap by providing a state-of-the-art analysis of generative AI in construction, with three objectives: (1) to review and categorize the existing and emerging generative AI opportunities and challenges in the construction industry; (2) to propose a framework for construction firms to build customized generative AI solutions using their own data, comprising steps such as data collection, dataset curation, training custom large language model (LLM), model evaluation, and deployment; and (3) to demonstrate the framework via a case study of developing a generative model for querying contract documents. The results show that retrieval augmented generation (RAG) improves the baseline LLM by 5.2, 9.4, and 4.8% in terms of quality, relevance, and reproducibility. This study provides academics and construction professionals with a comprehensive analysis and practical framework to guide the adoption of generative AI techniques to enhance productivity, quality, safety, and sustainability across the construction industry., Comment: 74 pages, 11 figures, 20 tables

Published
2024

49. Engineering A Large Language Model From Scratch

Author

Oketunji, Abiodun Finbarrs

Subjects
Computer Science - Computation and Language, Computer Science - Computers and Society, Computer Science - Machine Learning, Computer Science - Software Engineering, I.2.7
Abstract

The proliferation of deep learning in natural language processing (NLP) has led to the development and release of innovative technologies capable of understanding and generating human language with remarkable proficiency. Atinuke, a Transformer-based neural network, optimises performance across various language tasks by utilising a unique configuration. The architecture interweaves layers for processing sequential data with attention mechanisms to draw meaningful affinities between inputs and outputs. Due to the configuration of its topology and hyperparameter tuning, it can emulate human-like language by extracting features and learning complex mappings. Atinuke is modular, extensible, and integrates seamlessly with existing machine learning pipelines. Advanced matrix operations like softmax, embeddings, and multi-head attention enable nuanced handling of textual, acoustic, and visual signals. By unifying modern deep learning techniques with software design principles and mathematical theory, the system achieves state-of-the-art results on natural language tasks whilst remaining interpretable and robust.

Published
2024
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