All Outputs (40)

An image dataset for use in detecting unwanted bolt rotation (2025)
Journal Article

In any industrial system, ensuring that the engineered components therein are in working order is essential for the safety of workers and for efficient and cost-effective running. However, due to factors such as stress, deformation, and corrosion, in... Read More about An image dataset for use in detecting unwanted bolt rotation.

A novel triplet loss architecture with visual explanation for detecting the unwanted rotation of bolts in safety-critical environments (2025)
Journal Article

In the commonly used method of bolting to secure parts of equipment and structure, the bolts must be tightened to an adequate preload force. Failure to do so could affect the integrity of the structure, as well as the efficient runn... Read More about A novel triplet loss architecture with visual explanation for detecting the unwanted rotation of bolts in safety-critical environments.

Machine vs Machine: Using AI to Tackle Generative AI Threats in Assessment (2025)
Presentation / Conference Contribution

This paper presents a theoretical framework for addressing the challenges posed by generative artificial intelligence (AI) in higher education assessment through a machine-versus-machine approach. Large language models like GPT-4, Claude, and Llama i... Read More about Machine vs Machine: Using AI to Tackle Generative AI Threats in Assessment.

Bridging AI Skills Gaps in Marketing Education: Prompt Engineering as a Key Competency (2025)
Journal Article

The advancement of artificial intelligence is reshaping the marketing landscape, underscoring the need to integrate prompt engineering into marketing education. This study presents a conceptual framework for embedding prompt engineering within market... Read More about Bridging AI Skills Gaps in Marketing Education: Prompt Engineering as a Key Competency.

Saudi Arabia's Vision 2030: Leveraging Generative Artificial Intelligence to Enhance Software Engineering (2025)
Presentation / Conference Contribution

This research explores the transformative role of Generative Artificial Intelligence (GenAl) for the Kingdom of Saudi Arabia (KSA) software developers. KSA is transforming from an oil-dependent economy to a diversified one to achieve Vision 2030. Tec... Read More about Saudi Arabia's Vision 2030: Leveraging Generative Artificial Intelligence to Enhance Software Engineering.

A Novel Topic Modelling Framework for Automated Surveying of Computer Vision Research in Prostate Cancer Detection (2025)
Journal Article

Retrieving the relevant information or material makes a big difference in the medical field because it is necessary to acquire updates on recent findings and inferences so that the practitioners can understand the state-of-the-art topics. Thus, extra... Read More about A Novel Topic Modelling Framework for Automated Surveying of Computer Vision Research in Prostate Cancer Detection.

A Newly Adopted YOLOv9 Model for Detecting Mould Regions Inside of Buildings (2024)
Journal Article

Molds on wall and ceiling surfaces in damp indoor environments especially in houses with poor insulation and ventilation are common in the UK. Since it releases toxic chemicals as it grows, it is a serious health hazard for occupants who live in such... Read More about A Newly Adopted YOLOv9 Model for Detecting Mould Regions Inside of Buildings.

Review of farmer-centered AI systems technologies in livestock operations (2024)
Journal Article

The assessment of livestock welfare aids in keeping an eye on the health, physiology, and environment of the animals in order to prevent deterioration, detect injuries, stress, and sustain productivity. Because it puts more consumer pressure on farmi... Read More about Review of farmer-centered AI systems technologies in livestock operations.

Looking at AI Fairness from a Marketing Lenz: The Influence of Ethnicity on Facial Expression Recognition based on expert judgement and AI models (2024)
Presentation / Conference Contribution

This research investigates the influence of ethnicity on facial expression perception using insights from marketing experts and Computer Vision techniques. Marketing professionals were highly adept at recognizing expressions across varying ethnicitie... Read More about Looking at AI Fairness from a Marketing Lenz: The Influence of Ethnicity on Facial Expression Recognition based on expert judgement and AI models.

Identifying the threshold concepts in teaching marketing: A pedagogic research (2024)
Presentation / Conference
Mansouri, T., & Torkestani, M. (2024, May). Identifying the threshold concepts in teaching marketing: A pedagogic research. Presented at Learning, Teaching & Student Experience 2024, Birmingham

This research examines key threshold concepts in marketing pedagogy. It explores the fundamental principles that are essential for marketing education. The study provides insights for educators and enhance the learning experience for students.

The Intersection of Generative AI and Healthcare: Addressing Challenges to Enhance Patient Care (2024)
Presentation / Conference Contribution

This research analyses the evolving intersection of generative AI and healthcare. It explores the transformative potential of integrating generative AI in healthcare, particularly in process automation, patient care, patient monitoring, and diagnosis... Read More about The Intersection of Generative AI and Healthcare: Addressing Challenges to Enhance Patient Care.

A Comprehensive Review of AI Techniques for Addressing Algorithmic Bias in Job Hiring (2024)
Journal Article
Albaroudi, E., Mansouri, T., & Alameer, A. (2024). A Comprehensive Review of AI Techniques for Addressing Algorithmic Bias in Job Hiring. AI and Ethics, 5(1), 383-404. https://doi.org/10.3390/ai5010019

The study comprehensively reviews artificial intelligence (AI) techniques for addressing algorithmic bias in job hiring. More businesses are using AI in curriculum vitae (CV) screening. While the move improves efficiency in the recruitment process, i... Read More about A Comprehensive Review of AI Techniques for Addressing Algorithmic Bias in Job Hiring.

Towards Explainable Deep Learning Models for Fault Prediction based on IoT Sensor Data (2024)
Thesis

This thesis addresses a pressing issue in the realm of IoT-based fault prediction using sensor data, focusing on the crucial yet challenging aspect of explainability within deep learning models. While deep learning has showcased remarkable advancemen... Read More about Towards Explainable Deep Learning Models for Fault Prediction based on IoT Sensor Data.

SkinLesNet: Classification of Skin Lesions and Detection of Melanoma Cancer Using a Novel Multi-Layer Deep Convolutional Neural Network (2023)
Journal Article
Azeem, M., Kiani, K., Mansouri, T., & Topping, N. (2023). SkinLesNet: Classification of Skin Lesions and Detection of Melanoma Cancer Using a Novel Multi-Layer Deep Convolutional Neural Network. Cancers, 16(1), 108. https://doi.org/10.3390/cancers16010108

Skin cancer is a widespread disease that typically develops on the skin due to frequent exposure to sunlight. Although cancer can appear on any part of the human body, skin cancer accounts for a significant proportion of all new cancer diagnoses worl... Read More about SkinLesNet: Classification of Skin Lesions and Detection of Melanoma Cancer Using a Novel Multi-Layer Deep Convolutional Neural Network.

Startup’s critical failure factors dynamic modeling using FCM (2023)
Journal Article
Salmeron, J. L., Mansouri, T., Sadeghi Moghaddam, R., Yousefi, N., & Tayebi, A. (2023). Startup’s critical failure factors dynamic modeling using FCM. Journal of Global Entrepreneurship Research, 13(1), https://doi.org/10.1007/s40497-023-00352-6

The emergence of startups and their influence on a country's economic growth has become a significant concern for governments. The failure of these ventures leads to substantial depletion of financial resources and workforce, resulting in detrimental... Read More about Startup’s critical failure factors dynamic modeling using FCM.

A Data Brokering Architecture to Guarantee Nonfunctional Requirements in IoT Applications (2023)
Presentation / Conference Contribution

IoT sensors capture different aspects of the environmental data and generate high throughput data streams. To harvest potential values from these sensors, a system fulfilling the big data requirements should be designed. In this work, we reviewed the... Read More about A Data Brokering Architecture to Guarantee Nonfunctional Requirements in IoT Applications.

Explainable fault prediction using learning fuzzy cognitive maps (2023)
Journal Article
Mansouri, T., & Vadera, S. (2023). Explainable fault prediction using learning fuzzy cognitive maps. Expert Systems, 40(8), https://doi.org/10.1111/exsy.13316

IoT sensors capture different aspects of the environment and generate high throughput data streams. Besides capturing these data streams and reporting the monitoring information, there is significant potential for adopting deep learning to identify v... Read More about Explainable fault prediction using learning fuzzy cognitive maps.

Developing an industry 4.0 readiness model using fuzzy cognitive maps approach (2022)
Journal Article
Monshizadeh, F., Moghadam, M., Mansouri, T., & Kumar, M. (2022). Developing an industry 4.0 readiness model using fuzzy cognitive maps approach. International Journal of Production Economics, 255, https://doi.org/10.1016/j.ijpe.2022.108658

Industry 4.0, or the fourth industrial revolution, is a new paradigm in manufacturing digitalization, which provides various opportunities for enterprises. Industry 4.0 readiness models are worthy methods to aid manufacturing organizations in trackin... Read More about Developing an industry 4.0 readiness model using fuzzy cognitive maps approach.

Markowitz-based cardinality constrained portfolio selection using Asexual Reproduction Optimization (ARO) (2022)
Journal Article
Mansouri, T., Sadeghi Moghadam, M. R., & Sheykhizadeh, M. (2022). Markowitz-based cardinality constrained portfolio selection using Asexual Reproduction Optimization (ARO). https://doi.org/10.22059/IJMS.2021.313393.674293

The Markowitz-based portfolio selection turns to an NP-hard problem when considering cardinality constraints. In this case, existing exact solutions like quadratic programming may not be efficient to solve the problem. Many researchers, therefore, us... Read More about Markowitz-based cardinality constrained portfolio selection using Asexual Reproduction Optimization (ARO).

A deep explainable model for fault prediction using IoT sensors (2022)
Journal Article

IoT sensors and deep learning models can widely be applied for fault prediction. Although
deep learning models are considerably more potent than many conventional machine learning models, they
are not transparent. This paper first examines differen... Read More about A deep explainable model for fault prediction using IoT sensors.