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All Outputs (28)

Towards Explainable Deep Learning Models for Fault Prediction based on IoT Sensor Data (2024)
Thesis
Mansouri, T. (2024). Towards Explainable Deep Learning Models for Fault Prediction based on IoT Sensor Data. (Thesis). University of Salford

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)
Conference Proceeding
Mansouri, T., Bass, J., Gaber, T., Wright, S., & Scorey, B. (2023). A Data Brokering Architecture to Guarantee Nonfunctional Requirements in IoT Applications. In Big Data Technologies and Applications (75-84). https://doi.org/10.1007/978-3-031-33614-0_6

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
Mansouri, T., & Vadera, S. (2022). A deep explainable model for fault prediction using IoT sensors. IEEE Access, https://doi.org/10.1109/ACCESS.2022.3184693

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.

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.

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.

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.

A Learning Fuzzy Cognitive Map (LFCM) approach to predict student performance (2021)
Journal Article
Mansouri, T., ZareRavasan, A., & Ashrafi, A. (2021). A Learning Fuzzy Cognitive Map (LFCM) approach to predict student performance. Journal of Information Technology Education: Research, 20, 221-243. https://doi.org/10.28945/4760

Aim/Purpose: This research aims to present a brand-new approach for student performance prediction using the Learning Fuzzy Cognitive Map (LFCM) approach. Background: Predicting student academic performance has long been an important research topic i... Read More about A Learning Fuzzy Cognitive Map (LFCM) approach to predict student performance.

An FCM-based dynamic modelling of integrated project delivery implementation challenges in construction projects (2018)
Journal Article
Kahvandi, Z., Saghatforoush, E., Ravasan, A., & Mansouri, T. (2018). An FCM-based dynamic modelling of integrated project delivery implementation challenges in construction projects. Lean construction journal, 2018, 63-87

Question: What are the Integrated Project Delivery Implementation challenges in construction projects, their interrelationships and their effects on the project time, cost and quality? Purpose: The Purpose of this study is applying an efficient me... Read More about An FCM-based dynamic modelling of integrated project delivery implementation challenges in construction projects.

Learning Fuzzy Cognitive Maps with modified asexual reproduction optimisation algorithm (2018)
Journal Article
Salmeron, J., Mansouri, T., Moghadam, M., & Mardani, A. (2019). Learning Fuzzy Cognitive Maps with modified asexual reproduction optimisation algorithm. Knowledge-Based Systems, 163, 723-735. https://doi.org/10.1016/j.knosys.2018.09.034

This paper present a comparison between Fuzzy Cognitive Map (FCM) learning approaches and algorithms. FCMs are fuzzy digraphs with weights and feedback loops, consisting of nodes interconnected through directed arcs mostly used for knowledge represen... Read More about Learning Fuzzy Cognitive Maps with modified asexual reproduction optimisation algorithm.

A fuzzy ANP based weighted RFM model for customer segmentation in auto insurance sector (2018)
Book Chapter
Ravasan, A., & Mansouri, T. (2018). A fuzzy ANP based weighted RFM model for customer segmentation in auto insurance sector. In Intelligent systems : concepts, methodologies, tools, and applications (1050-1067). IGI Global. https://doi.org/10.4018/978-1-5225-5643-5.ch044

Data mining has a tremendous contribution for researchers to extract the hidden knowledge and information which have been inherited in the raw data. This study has proposed a brand new and practical fuzzy analytic network process (FANP) based weighte... Read More about A fuzzy ANP based weighted RFM model for customer segmentation in auto insurance sector.

A dynamic ERP critical failure factors modelling with FCM throughout project lifecycle phases (2015)
Journal Article
Ravansan, A., & Mansouri, T. (2016). A dynamic ERP critical failure factors modelling with FCM throughout project lifecycle phases. Production Planning and Control, 27(2), 65-82. https://doi.org/10.1080/09537287.2015.1064551

Implementation of enterprise resource planning systems (ERPs) is a complex and costly task which usually results in serious failures. Numerous factors affect these projects implementation due to their size, complexity and high chance of failure. Ther... Read More about A dynamic ERP critical failure factors modelling with FCM throughout project lifecycle phases.

A practical model for ensemble estimation of QoS and QoE in VoIP services via fuzzy inference systems and fuzzy evidence theory (2015)
Journal Article
Mansouri, T., Nabavi, A., Ravasan, A., & Ahangarbahan, H. (2016). A practical model for ensemble estimation of QoS and QoE in VoIP services via fuzzy inference systems and fuzzy evidence theory. Telecommunication Systems, 61(4), 861-873. https://doi.org/10.1007/s11235-015-0041-6

Nowadays, there is an increasing number of Voices over IP (VoIP) services offered in telecommunication networks with specific quality requirements. Such requirements impact upon both the objective quality of service (QoS) of the end-to end connection... Read More about A practical model for ensemble estimation of QoS and QoE in VoIP services via fuzzy inference systems and fuzzy evidence theory.

A fuzzy ANP based weighted RFM model for customer segmentation in auto insurance sector (2015)
Journal Article
Ravasan, A., & Mansouri, T. (2015). A fuzzy ANP based weighted RFM model for customer segmentation in auto insurance sector. International Journal of Information Systems in the Service Sector, 7(2), 5. https://doi.org/10.4018/ijisss.2015040105

Data mining has a tremendous contribution for researchers to extract the hidden knowledge and information which have been inherited in the raw data. This study has proposed a brand new and practical fuzzy analytic network process (FANP) based weighte... Read More about A fuzzy ANP based weighted RFM model for customer segmentation in auto insurance sector.