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A multi agent-based approach for energy efficient water resource management (2020)
Journal Article
Aydin, M. E., & Keles, R. (in press). A multi agent-based approach for energy efficient water resource management. Computers and Industrial Engineering,

Water supply remains one of globally recognised challenging problems due to the scarcity in the water sources, the environmental concerns and hardness in access to clean and fresh water. Besides, energy consumption is also under focus as much as acce... Read More about A multi agent-based approach for energy efficient water resource management.

Feature selection with artificial bee colony algorithms for classifying Parkinson’s diseases (2020)
Conference Proceeding
Durgut, R., Baydilli, Y. Y., & Aydin, M. E. (2020). Feature selection with artificial bee colony algorithms for classifying Parkinson’s diseases. In Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference. , (338-351). https://doi.org/10.1007/978-3-030-48791-1_26

Parkinson’s is a brain disease that affects the quality of human life significantly with very slow progresses. It is known that early diagnosis is of great importance to arrange relevant and efficient treatments. Data analytics and particularly predi... Read More about Feature selection with artificial bee colony algorithms for classifying Parkinson’s diseases.

QoE-based Mobility-aware Collaborative Video Streaming on the Edge of 5G (2020)
Journal Article
Tuysuz, M. F., & Aydin, M. E. (in press). QoE-based Mobility-aware Collaborative Video Streaming on the Edge of 5G. IEEE Transactions on Industrial Informatics, 1-1. https://doi.org/10.1109/tii.2020.2972931

Today's Internet traffic is dominated by video streaming applications transmitted through wireless/cellular interfaces of mobile devices. Although ultra-high-definition videos are now easily transmitted through mobile devices, video quality level tha... Read More about QoE-based Mobility-aware Collaborative Video Streaming on the Edge of 5G.

An analytical framework for high-speed hardware particle swarm optimization (2019)
Journal Article
Damaj, I., Elshafei, M., El-Abd, M., & Aydin, M. E. (2020). An analytical framework for high-speed hardware particle swarm optimization. Microprocessors and Microsystems, 72, 102949. https://doi.org/10.1016/j.micpro.2019.102949

Engineering optimization techniques are computationally intensive and can challenge implementations on tightly-constrained embedded systems. Particle Swarm Optimization (PSO) is a well-known bio-inspired algorithm that is adopted in various applicati... Read More about An analytical framework for high-speed hardware particle swarm optimization.

Threats on the horizon: Understanding security threats in the era of cyber-physical systems (2019)
Journal Article
Walker-Roberts, S., Hammoudeh, M., Aldabbas, O., Aydin, M., & Dehghantanha, A. (in press). Threats on the horizon: Understanding security threats in the era of cyber-physical systems. Journal of Supercomputing, https://doi.org/10.1007/s11227-019-03028-9

Disruptive innovations of the last few decades, such as smart cities and Industry 4.0, were made possible by higher integration of physical and digital elements. In today's pervasive cyber-physical systems, connecting more devices introduces new vuln... Read More about Threats on the horizon: Understanding security threats in the era of cyber-physical systems.

A honeybees-inspired heuristic algorithm for numerical optimisation (2019)
Journal Article
Dugenci, M., & Aydin, M. E. (2019). A honeybees-inspired heuristic algorithm for numerical optimisation. Neural Computing and Applications, https://doi.org/10.1007/s00521-019-04533-x

© 2019, The Author(s). Swarm intelligence is all about developing collective behaviours to solve complex, ill-structured and large-scale problems. Efficiency in collective behaviours depends on how to harmonise the individual contributors so that a c... Read More about A honeybees-inspired heuristic algorithm for numerical optimisation.

A comparison of reinforcement learning algorithms in fairness-oriented OFDMA schedulers (2019)
Journal Article
Ghinea, G., Comşa, I. S., Comsa, I., Zhang, S., Aydin, M., Kuonen, P., …Ghinea, G. (2019). A comparison of reinforcement learning algorithms in fairness-oriented OFDMA schedulers. Information, 10(10), 315. https://doi.org/10.3390/info10100315

Due to large-scale control problems in 5G access networks, the complexity of radio resource management is expected to increase significantly. Reinforcement learning is seen as a promising solution that can enable intelligent decision-making and reduc... Read More about A comparison of reinforcement learning algorithms in fairness-oriented OFDMA schedulers.

Enhancing user fairness in OFDMA radio access networks through machine learning (2019)
Conference Proceeding
Comsa, I., Zhang, S., Aydin, M., Kuonen, P., Trestian, R., & Ghinea, G. (2019). Enhancing user fairness in OFDMA radio access networks through machine learning. In 2019 Wireless Days (WD), (1-8). https://doi.org/10.1109/WD.2019.8734262

The problem of radio resource scheduling subject to fairness satisfaction is very challenging even in future radio access networks. Standard fairness criteria aim to find the best trade-off between overall throughput maximization and user fairness sa... Read More about Enhancing user fairness in OFDMA radio access networks through machine learning.

Monitoring the performance of petrochemical organizations in Saudi Arabia using data envelopment analysis (2019)
Journal Article
Alidrisi, H., Aydin, M. E., Bafail, A. O., Abdulal, R., & Karuvatt, S. A. (2019). Monitoring the performance of petrochemical organizations in Saudi Arabia using data envelopment analysis. Mathematics, 7(6), 519. https://doi.org/10.3390/math7060519

The petrochemical industry plays a crucial role in the economy of the Kingdom of Saudi Arabia. Therefore, the effectiveness and efficiency of this industry is of high importance. Data envelopment analysis (DEA) is found to be more acceptable in measu... Read More about Monitoring the performance of petrochemical organizations in Saudi Arabia using data envelopment analysis.

An agent-based approach for strategic alignment in enterprise systems: A cancer care case (2019)
Conference Proceeding
Aydin, M. E., Oztemel, E., Nashawati, D., Odeh, M., & Mansour, A. (2019). An agent-based approach for strategic alignment in enterprise systems: A cancer care case. In M. Odeh, & F. Kharbat (Eds.),

Enterprise systems are viewed as large-scale software systems, which are usually assembled through a number of protocols inspired by political coalitions. This is due to the fact that incompatibilities emerge through the nature of subsystems can only... Read More about An agent-based approach for strategic alignment in enterprise systems: A cancer care case.

Towards 5G: A Reinforcement Learning-Based Scheduling Solution for Data Traffic Management (2018)
Journal Article
Comsa, I. S., Zhang, S., Aydin, M. E., Kuonen, P., Lu, Y., Trestian, R., & Ghinea, G. (2018). Towards 5G: A Reinforcement Learning-Based Scheduling Solution for Data Traffic Management. IEEE Transactions on Network and Service Management, 15(4), 1661-1675. https://doi.org/10.1109/TNSM.2018.2863563

© 2004-2012 IEEE. Dominated by delay-sensitive and massive data applications, radio resource management in 5G access networks is expected to satisfy very stringent delay and packet loss requirements. In this context, the packet scheduler plays a cent... Read More about Towards 5G: A Reinforcement Learning-Based Scheduling Solution for Data Traffic Management.

Managing Congestion in Vehicular Networks Using Tabu Search (2018)
Journal Article
Ishaq, M., Malik, M. H., & Aydin, M. E. (2018). Managing Congestion in Vehicular Networks Using Tabu Search. Communications in Computer and Information Science, 893, 118-129. https://doi.org/10.1007/978-3-319-98204-5_10

© 2018, Springer Nature Switzerland AG. In this era of communication, exponentially growing networks bring a lot of challenges to address for smoother network functionalities. Among them is efficiency in handling packet traffic to avoid and control c... Read More about Managing Congestion in Vehicular Networks Using Tabu Search.

An adaptive opportunistic routing scheme for reliable data delivery in WSNs (2018)
Conference Proceeding
Hasnain, M., Malik, M. H., & Aydin, M. E. (2018). An adaptive opportunistic routing scheme for reliable data delivery in WSNs. In A. Abuarqoub, M. Hammudah, & S. Murad (Eds.), Proceedings of the 2nd International Conference on Future Networks and Distributed Systems - ICFNDS '18, (1-7). https://doi.org/10.1145/3231053.3231085

© 2018 ACM. With the emergence of miniature technologies such as sensor nodes powered with limited batteries, many applications came into existence such as detection of mine reconnaissance, pollution monitoring, data gathering from remote locations,... Read More about An adaptive opportunistic routing scheme for reliable data delivery in WSNs.

Selecting Display Products for Furniture Stores Using Fuzzy Multi-criteria Decision Making Techniques (2018)
Journal Article
Uygun, Ö., Güven, İ., Şimşir, F., & Aydin, M. E. (2018). Selecting Display Products for Furniture Stores Using Fuzzy Multi-criteria Decision Making Techniques. Communications in Computer and Information Science, 893, 181-193. https://doi.org/10.1007/978-3-319-98204-5_15

© 2018, Springer Nature Switzerland AG. Efficient marketing in which the right products are supplied to the right consumer plays a crucial role for a profitable business in the age of highly accessible and competitive global market. This fact enforce... Read More about Selecting Display Products for Furniture Stores Using Fuzzy Multi-criteria Decision Making Techniques.

Diversifying search in bee algorithms for numerical optimisation (2018)
Journal Article
Düg̃enci, M., & Aydin, M. E. (2018). Diversifying search in bee algorithms for numerical optimisation. Lecture Notes in Artificial Intelligence, 11056 LNAI, 132-144. https://doi.org/10.1007/978-3-319-98446-9_13

© Springer Nature Switzerland AG 2018. Swarm intelligence offers useful instruments for developing collective behaviours to solve complex, ill-structured and large-scale problems. Efficiency in collective behaviours depends on how to harmonise the in... Read More about Diversifying search in bee algorithms for numerical optimisation.

Building collaboration in multi-agent systems using reinforcement learning (2018)
Journal Article
Aydin, M. E., & Fellows, R. (2018). Building collaboration in multi-agent systems using reinforcement learning. Lecture Notes in Artificial Intelligence, 11056 LNAI, 201-212. https://doi.org/10.1007/978-3-319-98446-9_19

© Springer Nature Switzerland AG 2018. This paper presents a proof-of concept study for demonstrating the viability of building collaboration among multiple agents through standard Q learning algorithm embedded in particle swarm optimisation. Collabo... Read More about Building collaboration in multi-agent systems using reinforcement learning.

A parametric study for congestion control in queuing networks (2017)
Presentation / Conference
Malik, M. H., Majeed, A., Aydin, M. E., & Malik, M. H. (2017, July). A parametric study for congestion control in queuing networks. Paper presented at ICFNDS '17 International Conference on Future Networks and Distributed Systems

Congestion avoidance mechanisms are used to prevent the saturation of the bottleneck under mean-field domain where large numbers of TCP connections interact with one another. It is clear that selections of parameters play an important role on the per... Read More about A parametric study for congestion control in queuing networks.

Creep modelling of polypropylenes using artificial neural networks trained with Bee algorithms (2015)
Journal Article
Düğenci, M., Aydemir, A., Esen, İ., & Aydin, M. E. (2015). Creep modelling of polypropylenes using artificial neural networks trained with Bee algorithms. Engineering Applications of Artificial Intelligence, 45, 71-79. https://doi.org/10.1016/j.engappai.2015.06.016

Polymeric materials, being capable of high mouldability, usability of long lifetime up to 50 years and availability at low cost properties compared to metallic materials, are in demand but finite element-based design engineers have limited means in t... Read More about Creep modelling of polypropylenes using artificial neural networks trained with Bee algorithms.

Cognitive access point to handle delay sensitive traffic in WLANs (2015)
Conference Proceeding
Aydin, M., Malik, M. H., Aydin, M. E., & Awais, Q. (2015). Cognitive access point to handle delay sensitive traffic in WLANs. In 2015 IEEE International Conference on Computational Intelligence & Communication Technology, (317-322). https://doi.org/10.1109/CICT.2015.137

© 2015 IEEE. Over the last few years, the widespread use of wireless local area networks (WLANs) continues to gain more and more impetus. Due to the increase in variety of multimedia applications such as voice, video and gaming traffic, it is paramou... Read More about Cognitive access point to handle delay sensitive traffic in WLANs.

Stochastic model of TCP and UDP traffic in IEEE 802.11b/g (2014)
Conference Proceeding
Malik, M. H., Aydin, M., Shah, Z., & Hussain, S. (2014). Stochastic model of TCP and UDP traffic in IEEE 802.11b/g. In 2014 9th IEEE Conference on Industrial Electronics and Applications, (2170-2175). https://doi.org/10.1109/ICIEA.2014.6931531

© 2014 IEEE. IEEE 802.11 networks have been widely explored since last decade and IEEE802.11g was proposed to increase the data rate of wireless networks up to 54Mbps which ensure backward capability with IEEE802.11b. The main goal of increasing the... Read More about Stochastic model of TCP and UDP traffic in IEEE 802.11b/g.


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