All Outputs (41)

The effect of parameters on the success of heuristic algorithms in personalized personnel scheduling (2023)
Conference Proceeding
Gülmez, E., Urgancı, K. B., Koruca, H. İ., & Aydin, M. E. (2023). The effect of parameters on the success of heuristic algorithms in personalized personnel scheduling. In Advances in Intelligent Manufacturing and Service System Informatics (600-611). https://doi.org/10.1007/978-981-99-6062-0_55

Work-life balance is an approach that aims to enable employees to balance their work, family, and private lives. It is seen that the factors in the work-life balance are not relevant to work and family, considering the activities that one wishes for... Read More about The effect of parameters on the success of heuristic algorithms in personalized personnel scheduling.

Enhancing software fault prediction with deep neural networks: An empirical analysis of error-type metrics (2023)
Conference Proceeding
Phung, K., Ogunshile, E., & Aydin, M. E. (in press). Enhancing software fault prediction with deep neural networks: An empirical analysis of error-type metrics.

In the context of software quality assurance, Software Fault Prediction (SFP) serves as a critical technique to optimise costs and efforts by classifying software modules as faulty or not, using pertinent project characteristics. Despite considerable... Read More about Enhancing software fault prediction with deep neural networks: An empirical analysis of error-type metrics.

Problem classification for tailored help desk auto replies (2022)
Conference Proceeding
Nicholls, R., Fellows, R., Battle, S., & Ihshaish, H. (2022). Problem classification for tailored help desk auto replies. In E. Pimenidis, P. Angelov, C. Jayne, A. Papaleonidas, & M. Aydin (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2022 (445-454). https://doi.org/10.1007/978-3-031-15937-4_37

IT helpdesks are charged with the task of responding quickly to user queries. To give the user confidence that their query matters, the helpdesk will auto-reply to the user with confirmation that their query has been received and logged. This auto-re... Read More about Problem classification for tailored help desk auto replies.

Analysing the predictivity of features to characterise the search space (2022)
Conference Proceeding
Durgut, R., Aydin, M. E., Ihshaish, H., & Rakib, A. (2022). Analysing the predictivity of features to characterise the search space. In E. Pimenidis, P. Angelov, C. Jayne, A. Papaleonidas, & M. Aydin (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2022 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6–9, 2022, Proceedings; Part IV (1-13). https://doi.org/10.1007/978-3-031-15937-4_1

Exploring search spaces is one of the most unpredictable challenges that has attracted the interest of researchers for decades. One way to handle unpredictability is to characterise the search spaces and take actions accordingly. A well-characterised... Read More about Analysing the predictivity of features to characterise the search space.

A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning (2021)
Conference Proceeding
Phung, K., Ogunshile, E., & Aydin, M. (2021). A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning. In 2021 9th International Conference in Software Engineering Research and Innovation (CONISOFT) (168-179). https://doi.org/10.1109/CONISOFT52520.2021.00032

Software fault prediction makes software quality assurance process more efficient and economic. Most of the works related to software fault prediction have mainly focused on classifying software modules as faulty or not, which does not produce suffic... Read More about A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning.

Modeling diseases with Stream X Machine (2021)
Conference Proceeding
Jayatilake, S., Ogunshile, E., Aydin, M., & Phung, K. (2021). Modeling diseases with Stream X Machine. In 2021 9th International Conference in Software Engineering Research and Innovation (CONISOFT) (61-68). https://doi.org/10.1109/CONISOFT52520.2021.00020

At present the world is moving towards alternative medicine and behavioural alteration for treating, managing, and preventing chronical diseases. With the individuality of the human beings has added more complexity in a domain where very high accurac... Read More about Modeling diseases with Stream X Machine.

Reinforcement learning-based adaptive operator selection (2021)
Conference Proceeding
Durgut, R., & Aydin, M. E. (2021). Reinforcement learning-based adaptive operator selection. In B. Dorronsoro, L. Amodeo, M. Pavone, & P. Ruiz (Eds.), . https://doi.org/10.1007/978-3-030-85672-4_3

Metaheuristic and swarm intelligence approaches require devising optimisation algorithms with operators to let produce neighbouring solutions to conduct a move. The efficiency of algorithms using single operator remains recessive in comparison with t... Read More about Reinforcement learning-based adaptive operator selection.

A strategic search algorithm in multi-agent and multiple target environment (2021)
Conference Proceeding
Afzalov, A., Lotfi, A., & Aydin, M. E. (2021). A strategic search algorithm in multi-agent and multiple target environment. In E. Chew, A. P. Abdul Majeed, P. Liu, J. Platts, H. Myung, J. Kim, & J. Kim (Eds.), RiTA 2020 (195-204). https://doi.org/10.1007/978-981-16-4803-8_21

The aim of this study is to investigate how to solve the path-planning problem of multiple competing players towards moving targets within a dynamically changing environment. A novel approach is needed to exceed the classical solutions for single or... Read More about A strategic search algorithm in multi-agent and multiple target environment.

A comparative analysis for binary search operators used in artificial bee colony (2021)
Conference Proceeding
Atli, I., Durgut, R., & Aydin, M. E. (2021). A comparative analysis for binary search operators used in artificial bee colony. In 2021 29th Signal Processing and Communications Applications Conference (SIU). https://doi.org/10.1109/SIU53274.2021.9477907

Metaheuristic optimization algorithms are developed to find the best or near-best solutions within a reasonable time frame utilizing various neighbourhood functions (i.e., operators). Variety of studies have been proposed for structural modifications... Read More about A comparative analysis for binary search operators used in artificial bee colony.

Multi-agent path planning approach using assignment strategy variations in pursuit of moving targets (2021)
Conference Proceeding
Afzalov, A., He, J., Lotfi, A., & Aydin, M. E. (2021). Multi-agent path planning approach using assignment strategy variations in pursuit of moving targets. In G. Jezic, J. Chen-Burger, M. Kusek, R. Sperka, R. Howlett, & L. Jain (Eds.), Agents and Multi-Agent Systems: Technologies and Applications 2021 (451-463). https://doi.org/10.1007/978-981-16-2994-5_38

This study aims to investigate the problem of assignment strategies for multiple agents. In multi-agent scenarios, agents compute a path towards the goal, while these goal destinations in some cases are predefined in advance. The topic of assignment... Read More about Multi-agent path planning approach using assignment strategy variations in pursuit of moving targets.

Multiple pursuers TrailMax algorithm for dynamic environments (2021)
Conference Proceeding
Afzalov, A., Lotfi, A., Inden, B., & Aydin, M. (2021). Multiple pursuers TrailMax algorithm for dynamic environments. In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART (437-443). https://doi.org/10.5220/0010392404370443

Multi-agent multi-target search problems, where the targets are capable of movement, require sophisticated algorithms for near-optimal performance. While there are several algorithms for agent control, comparatively less attention has been paid to ne... Read More about Multiple pursuers TrailMax algorithm for dynamic environments.

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.

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.

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.), 2018 1st International Conference on Cancer Care Informatics (CCI) (25-31). https://doi.org/10.1109/CANCERCARE.2018.8618176

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.

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.

A parametric study for congestion control in queuing networks (2017)
Conference Proceeding
Malik, M. H., Majeed, A., Aydin, M. E., & Malik, M. H. (2017). A parametric study for congestion control in queuing networks. In ICFNDS '17: Proceedings of the International Conference on Future Networks and Distributed Systems. https://doi.org/10.1145/3102304.3105574

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.

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.

Adaptive proportional fair parameterization based LTE scheduling using continuous actor-critic reinforcement learning (2014)
Conference Proceeding
Comsa, I. S., Zhang, S., Aydin, M., Chen, J., Kuonen, P., & Wagen, J. F. (2014). Adaptive proportional fair parameterization based LTE scheduling using continuous actor-critic reinforcement learning. In 2014 IEEE Global Communications Conference (4387-4393). https://doi.org/10.1109/GLOCOM.2014.7037498

© 2014 IEEE. Maintaining a desired trade-off performance between system throughput maximization and user fairness satisfaction constitutes a problem that is still far from being solved. In LTE systems, different tradeoff levels can be obtained by usi... Read More about Adaptive proportional fair parameterization based LTE scheduling using continuous actor-critic reinforcement learning.

Scheduling policies based on dynamic throughput and fairness tradeoff control in LTE-A networks (2014)
Conference Proceeding
Comşa, I. S., Aydin, M., Zhang, S., Kuonen, P., Wagen, J. F., & Lu, Y. (2014). Scheduling policies based on dynamic throughput and fairness tradeoff control in LTE-A networks. In 39th Annual IEEE Conference on Local Computer Networks (418-421). https://doi.org/10.1109/LCN.2014.6925806

© 2014 IEEE. In LTE-A cellular networks there is a fundamental trade-off between the cell throughput and fairness levels for preselected users which are sharing the same amount of resources at one transmission time interval (TTI). The static paramete... Read More about Scheduling policies based on dynamic throughput and fairness tradeoff control in LTE-A networks.