The multi-parameterized cluster editing problem by Abu-Khzam, Faisal N.

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Design and analysis of entropy-constrained reflected residual vector quantization by Mousa, W.A.H.

“…Residual vector quantization (RVQ) is a vector quantization (VQ) paradigm which imposes structural constraints on the encoder in order to reduce the encoding search burden and memory storage requirements of an unconstrained VQ. Jointly optimized RVQ (JORVQ) is an effective design algorithm for minimizing the overall quantization error. …”
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Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques by Fares, Samar

“…The first method uses an offline technique based on a global optimizer called the CMA-ES algorithm and the second one uses LSTM in its different forms to learn the online adjustment of the fusion weights between the two tracks. …”
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A novel approach for real time flows scheduling by Fawaz, W.

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Energy utilization assessment of a semi-closed greenhouse using data-driven model predictive control by Farhat Mahmood (15468854)

“…The proposed method consists of a multilayer perceptron model representing the greenhouse system integrated with an objective function and an optimization algorithm. The multilayer perceptron model is trained using historical data from the greenhouse with solar radiation, outside temperature, humidity difference, fan speed, HVAC control as the input parameters to predict the temperature. …”

Optimisation of PV Cleaning Practices: Comparison Between Performance Based and Periodic Based Approaches by ALHAJERI, RASHED ABDULLA

“…It is important to choose the correct cleaning method, frequency, and approach to ensure that the best practices are being used on the basis of both economic and technical criteria. To optimize the cleaning practices, an algorithm was developed by the author based on the literature review and economic analysis, and was run for multiple panels and tilts at the DEWA OTF solar lab in Dubai, UAE. …”
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Enhancing Healthcare Systems With Deep Reinforcement Learning: Insights Into D2D Communications and Remote Monitoring by Zina Chkirbene (16869987)

“…<p dir="ltr">The traditional healthcare system is increasingly challenged by its dependence on inperson consultations and manual monitoring, struggling with issues of scalability, the immediacy of care, and efficient resource allocation. As the global population ages and chronic conditions proliferate, the demand for healthcare systems capable of delivering efficient and remote care is becoming more pressing. …”

Modeling and thermoeconomic analysis of new polygeneration system based on geothermal energy with sea water desalination and hydrogen production by Wulaer Shaersaikai (21436652)

“…A USPC of 5.37 $/GJ and a NPV of 15.48 M$ support the system's economic performance and show that it is feasible in a market with favorable conditions. The Grey Wolf Optimization (GWO) algorithm, which directs the system's optimization process, demonstrates a competitive trade-off between exergy efficiency, freshwater production, costs, NPV, and environmental impact. …”

A Dual Vibration Absorber for Vibration Suppression of Harmonically Forced Systems by El Khoury, Elie

“…And, as in the case of the platform absorber, an optimal absorber mass exists for the lower absorber. …”
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Mobile robots obstacles avoidance using dynamic window approach by Abubakr, Omer Ali

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State-of-Charge Estimation Using Triple Forgetting Factor Adaptive Extended Kalman Filter for Battery Energy Storage Systems in Electric Bus Applications by Mena S. ElMenshawy (17983807)

“…It is concluded that the presented method offers faster convergence and lower error. Results have demonstrated that the proposed algorithm provides an RMSE of 0.3%, an MAE of 0.01%, and a MaxAE of 1.7% for SoC estimation.…”

Dynamic Layout Planning Using a Hybrid Incremental Solution Method by Zouein, Pierrette

“…The resulting sequence of layouts is suboptimal in terms of the stated global objective, but the algorithm helps the layout planner explore better alternative solutions.…”
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Reinforcement Learning-Based School Energy Management System by Yassine Chemingui (18891757)

“…However, lowering energy consumption cannot be done despite the occupants’ comfort. …”

UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks by Ebrahimi, Dariush

“…We formulate a joint optimization problem and divide it into four complementary subproblems to generate close-to-optimal results with lower complexity. …”
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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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MSD-NAS: multi-scale dense neural architecture search for real-time pedestrian lane detection by Sui Paul Ang (18460605)

“…The proposed method designs an optimized deep network with multi-scale input branches, allowing the derived network to utilize local and global contexts for predictions. …”

MoveSchedule by Zouein, Pierette

“…The layout construction algorithm that underlies MoveSchedule uses Constraint Satisfaction to find the set of all positions that meet the constraints on resources' positions and Linear Programming to find the optimal positions that minimize resource transportation and relocation costs. …”
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Enhancing building sustainability: A Digital Twin approach to energy efficiency and occupancy monitoring by Aya Nabil Sayed (17317006)

“…<p dir="ltr">The unprecedented rise in global temperatures, extreme weather events, and the depletion of <u>natural resources</u> underscore the urgent need for <u>sustainable practices</u>. …”

On the complexity of bilinear computations by Takche, Jean Halim

“…We will also consider special classes of three bilinear forms, and efficient algorithms will be developed, which are optimal in most cases.…”
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Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast d... by Tarik Elhadd (5480393)

“…<h3>Objective</h3><p dir="ltr">To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapies who fast during Ramadan.…”