All Outputs (35)

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.

Editorial for the Special Issue on Blockchain: Applications, Challenges, and Solutions (2022)
Other
ZareRavasan, A., Mansouri, T., Krčál, M., & Rouhani, S. (2022). Editorial for the Special Issue on Blockchain: Applications, Challenges, and Solutions

Blockchain is believed to have the potential to digitally transform and disrupt industry sectors such as finance, supply chain, healthcare, marketing, and entertainment [...]

IoT data quality issues and potential solutions : a literature review (2021)
Journal Article
Mansouri, T., Sadeghi Moghadam, M., Monshizadeh, F., & Zareravasan, A. (2021). IoT data quality issues and potential solutions : a literature review. Computer Journal, https://doi.org/10.1093/comjnl/bxab183

In the Internet of Things (IoT), data gathered from dozens of devices are the base for creating business value and developing new products and services. If data are of poor quality, decisions are likely to be non-sense. Data quality is crucial to gai... Read More about IoT data quality issues and potential solutions : a literature review.

IoT data quality issues and potential solutions: a literature review (2021)
Journal Article
Mansouri, T., Moghadam, M., Monshizadeh, F., & Zareravasan, A. (2021). IoT data quality issues and potential solutions: a literature review. Computer Journal, https://doi.org/10.1093/comjnl/bxab183

In the Internet of Things (IoT), data gathered from dozens of devices are the base for creating business value and developing new products and services. If data are of poor quality, decisions are likely to be non-sense. Data quality is crucial to gai... Read More about IoT data quality issues and potential solutions: a literature review.

Credit card fraud detection using asexual reproduction optimization (2021)
Journal Article
Farhang, A., Mansouri, T., Sadeghi Moghaddam, M., Bahrambeik, N., Yavari, R., & Fani Sani, M. (2021). Credit card fraud detection using asexual reproduction optimization. Kybernetes, https://doi.org/10.1108/K-04-2021-0324

Purpose – The best algorithm that was implemented on this Brazilian dataset was artificial immune system (AIS)
algorithm. But the time and cost of this algorithm are high. Using asexual reproduction optimization (ARO) algorithm,
the authors achieve... Read More about Credit card fraud detection using asexual reproduction optimization.

An FCM-based dynamic modeling of operability and maintainability barriers in road projects (2021)
Journal Article
Ghaleenoei, N., Saghatforoush, E., Mansouri, T., & Zareravasan, A. (2021). An FCM-based dynamic modeling of operability and maintainability barriers in road projects. International Journal of Pavement Research and Technology, https://doi.org/10.1007/s42947-021-00027-z

Building a new road infrastructure in the country leads to economic and industrial growth. A massive amount of money is paid by governments to build them; however, they fail due to many reasons related to operability and maintainability (O&M) issues.... Read More about An FCM-based dynamic modeling of operability and maintainability barriers in road projects.