On the complexity of multi-parameterized cluster editing by Abu-Khzam, Faisal

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Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

“…This paper presents a novel hybrid optimization method to solve the resource allocation problem for multi-target multi-sensor tracking of drones. …”
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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management by Alhusin, Mohammed Omer Alamin

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Dynamic task offloading and scheduling for low-latency IoT services in multi-access edge computing by Alameddine, Hyame Assem

“…Multi-access edge computing (MEC) has recently emerged as a novel paradigm to facilitate access to advanced computing capabilities at the edge of the network, in close proximity to end devices, thereby enabling a rich variety of latency sensitive services demanded by various emerging industry verticals. …”
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Van der Pol-informed Neural Networks for Multi-step-ahead Forecasting of Extreme Climatic Events by Dutta, Anurag

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Multi-UAV-Enabled Mobile Edge Computing IoT Systems: Joint Association and Resource Allocation Framework by Abu Farha, Yazan Mahmoud

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A Comprehensive Framework for Optimizing and Integrating Electric Bus Service with Smart Grids for Sustainable Public Transportation by AlAli, Aisha Abdalla

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A parallel optimization algorithm for the maximum clique problem. (c2008) by Rizk, Mohamad A.

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Knowledge integration in large-scale organizations and networks – Conceptual overview and operational definition by Haddad, Marc

“…Knowledge integration is an emerging discipline in organizational science where the central proposition is that the increasing complexity of products and services being developed and delivered, means that the knowledge required for production is increasingly specialized, varied (multi-disciplinary) and distributed across the organization’s internal boundaries, and as a result there is a need for organizations to continuously gather their knowledge resources in order to maintain their ability to innovate, and to sustain their competitive position in the market. …”
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Arabic Sentiment Analysis using Machine Learning by ATIYAH, SASI FUAD

“…The research showed that through parameter optimization, basic machine learning classifiers achieved higher results than other more complex hybrid approaches, in addition, the overall parameters settings were tested on two new datasets and provided very promising results indicating that performance weren’t as a cause of overfitting. …”
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Intelligent Control of Cable-Driven Parallel Robot for Rehabilitation by Khattab, Omar

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From Collatz Conjecture to chaos and hash function by Masrat Rasool (17807813)

“…Most Chaos-based hash functions are insecure or inefficient due to their dependence on complex, attacked multi-dimensional maps or uncertain, weak one-dimensional maps like logistic and tent. …”

Data collection in wireless sensor networks using UAV and compressive data gathering by Ebrahimi, Dariush

“…In order to overcome the complexity of the joint optimization problem, we decompose the problem into separate parts and propose a heuristic to solve each subproblem for large-scale network scenarios.…”
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Optimized provisioning of edge computing resources with heterogeneous workload in IoT networks by Kherraf, Nouha

“…Hence, in this paper, we study and formulate the problem of MEC Resource Provisioning and Workload Assignment for IoT services (RPWA) as a Mixed Integer Program (MIP) to jointly decide on the number and the location of edge servers and applications to deploy, in addition to the workload assignment. Given its complexity, we propose a decomposition approach to solve it which consists of decomposing RPWA into the Delay Aware Load Assignment (DALA) sub-problem and the Mobile Edge Servers Dimensioning (MESD) sub-problem. …”
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Traffic Offloading with Channel Allocation in Cache-Enabled Ultra-Dense Wireless Networks by Abbas, Nadine

“…We generate results as a function of a wide range of system parameters, and demonstrate that the proposed algorithms achieve near-optimal performance with notably low time complexity.…”
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Quarantine-aware home healthcare routing and scheduling: a bi-objective approach by Najmeh Nabavizadeh (22928821)

“…To illustrate the problem’s complexity and assess the effectiveness of the proposed MILP model across various scenarios, 15 additional sample instances have been solved and documented in the Appendix. …”

Uplink Noma in UAV-Assisted IoT Networks by Mrad, Ali

“…This problem is formulated to determine an optimized UAV trajectory, IoT devices scheduling, and power allocation in the NOMA clusters that maximize the number of served devices while considering various constraints including the energy and flight duration of the UAV and successive interference cancellation (SIC) in the NOMA cluster. Given the complexity of the problem and the incomplete knowledge about the environment, the problem is divided into two subproblems: the first models the UAV trajectory and the selection of the first device in the NOMA cluster at each time slot as a Markov Decision Process, and uses Proximal Policy Optimization to solve it. …”
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