A GRASP Approach for Solving Large-Scale Electric Bus Scheduling Problems by Raka Jovanovic (17947838)

“…To be more precise, a greedy randomized adaptive search procedure (GRASP) algorithm is developed and its performance is evaluated against optimal solutions acquired using the MIP. …”

Role and Applications of Artificial Intelligence and Machine Learning in Manufacturing Engineering by Al-Ebrahim, Meshari A.

“…Because of the rise in cloud computing and a significant decrease in data storage costs, a massive amount of information and data can now be stored and transmitted to ML and AI algorithms to streamline and automate different processes of an organization. …”
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Hardware Model of an Expandable RSA Cryptographic System by Gutub, Adnan

“…Data security is an important aspect of information transmission and storage in an electronic form. Cryptographic systems are used to encrypt such information to guarantee its security. …”
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Fleet sizing of trucks for an inter-facility material handling system using closed queueing networks by Mohamed Amjath (17542512)

“…Within this context, the problem is modelled as a closed queueing network (CQN) combined with mixed-integer nonlinear programming (MINLP) to determine the optimal fleet size. This study proposes an analytical method based on sequential quadratic programming (SQP) methodology coupled with a mean value analysis (MVA) algorithm to solve this NP-Hard problem. …”

Scatter search technique for exam timetabling by Mansour, Nashat

“…We evaluate our suggested technique on real-world university data and compare our results with the registrar’s manual timetable in addition to the timetables of other heuristic optimization algorithms. The experimental results show that our adapted scatter search technique generates better timetables than those produced by the registrar, manually, and by other meta-heuristics.…”
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FoGMatch by Arisdakessian, Sarhad

“…Our solution consists of (1) two optimization problems, one for the IoT devices and one for the fog nodes, (2) preference functions for both the IoT and fog layers to help them rank each other on the basis of several criteria such latency and resource utilization, and (3) centralized and distributed intelligent scheduling algorithms that consider the preferences of both the fog and IoT layers to improve the performance of the overall IoT ecosystem. …”
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Electric Vehicles Charging Station Load Forecasting Integration With Renewable Energy Using Novel Deep EfficientBiLSTMNet by Vineet Dhanawat (22361395)

“…The model’s hyperparameters are optimized using an Enhanced Firefly Algorithm (EFA). …”

Development of a deep learning-based group contribution framework for targeted design of ionic liquids by Sadah Mohammed (18192859)

“…Our proposed framework consists of two essential steps: establishing a correlation between IL viscosity and CO₂ solubility by merging two deep learning models (DNN-GC and ANN-GC) and utilizing this correlation to identify the optimal IL structure with maximal CO₂ absorption capacity. …”

3D deployment of UAVs in wireless networks for traffic offloading and edge computing. (c2019) by Islambouli, Rania

“…This being said, computation tasks generated by IoT devices can be pro- cessed in less latency and with much lower energy consumption at the devices. To optimally deploy UAVs as mounted cloudlets, we formulate our problem as mixed integer program and then use an e cient meta-heuristic algorithm to generate optimized results for large scale IoT networks. …”
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Seasonal variations in feed-water chemistry and fouling dynamics of reverse-osmosis systems: A global climate lens by Nasser Zareei (22921226)

“…Future installations should align membrane materials, pretreatment systems, and control algorithms with site-specific hydrological calendars.…”

Work in Progress: Enhancing Sewage Systems Monitoring Through the Integration of Optical Fibre Sensors in IoT by Bustamante, Heriberto

“…The proposed platform leveragescompression algorithms and edge devices to optimize data communication. …”
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A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai by ALGHANEM, HANI SUBHI MOHD

“…The framework is validated through three domain expert interviews; the insights gleaned from the experts have instilled a sense of optimism regarding its theoretical efficacy and its capacity to adeptly tackle the distinct challenges encountered within the realm of government fleet management in Dubai. …”
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Hybrid deep learning based threat intelligence framework for Industrial IoT systems by Jahanzaib Malik (23718816)

“…The proposed approach was also compared against several contemporary deep learning-based architectures and existing benchmark algorithms. The results indicate that the proposed method achieves superior detection accuracy, with only a minimal compromise in speed efficiency. …”