Dynamic single node failure recovery in distributed storage systems by Itani, M.

“…The contributions of the paper are four fold: (i) generating an optimized block distribution scheme among the nodes of a given data center for fixed and variable size blocks; (ii) optimization of storage allocation under dynamic environments with data block arrivals; (iii) optimization of storage allocation with newly added storage nodes; and (iv) generating an effective block distribution scheme among the nodes by accounting for varying priorities among data blocks. …”
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An Infrastructure-Assisted Workload Scheduling for Computational Resources Exploitation in the Fog-Enabled Vehicular Network by Sorkhoh, Ibrahim

“…A Dantzig–Wolfe decomposition algorithm is proposed which yields to a master program solvable by the Barrier algorithm and subproblems solve...…”
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Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark by Ameema Zainab (16864263)

“…However, with the huge increase in data size, sophisticated models have to be created which require big data platforms. Optimal and effective use of the available computational resources can be attained by maximizing the effective utilization of the cluster nodes. …”

Dynamic multiple node failure recovery in distributed storage systems by Itani, May

“…We present a range of results for our proposed algorithms in several scenarios to assess the effectiveness of the solution approaches that are shown to generate results close to optimal.…”
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Parameterization and compensation of friction forces using geneticalgorithms by Al-Duwaish, H.N.

“…A PI controller with parameters optimized using genetic algorithms is used to control the position of a DC motor with friction. …”
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From Collatz Conjecture to chaos and hash function by Masrat Rasool (17807813)

“…By incorporating the Collatz process and carefully considering key-controlled variables, the proposed model aims to offer enhanced security properties while meeting the necessary criteria for a reliable and effective hashing mechanism. The effectiveness and dependability of the proposed hash function are evaluated by comparing it with two well-known hash algorithms, namely SHA-3 and SHA-2, as well as several other Chaos-based hash algorithms. …”

On-demand deployment of multiple aerial base stations for traffic offloading and network recovery by Sharafeddine, Sanaa

“…We present performance results for the proposed algorithm as a function of various system parameters and demonstrate its effectiveness compared to the close-to-optimal greedy approach and its superiority compared to recent related work from the literature.…”
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Iterative heuristics for multiobjective VLSI standard cellplacement by Sait, Sadiq M.

“…We employ two iterative heuristics for the optimization of VLSI standard cell placement. These heuristics are based on genetic algorithms (GA) and tabu search (TS) respectively. …”
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Framework for rapid design and optimisation of immersive battery cooling system by Ali Almshahy (23544823)

“…Two key parameters are optimised, namely: battery gap spacing (3–10 mm) and inlet/outlet width (5–15 mm), via Optimal Latin Hypercube Sampling, Support Vector Regression, and GDE3 algorithm. …”

AI-based remaining useful life prediction and modelling of seawater desalination membranes by Al Ali, Fajer

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A METHODOLOGY FOR NETWORK TOPOLOGY DESIGN USING FUZZY EVALUATIONS by Khan, Salman A.

“…This methodology is based on two algorithms, namely, fuzzy simulated evolution algorithm and the augmenting path algorithm. …”
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Autonomous 3D Deployment of Aerial Base Stations in Wireless Networks with User Mobility by Islambouli, Rania

“…The simulation results demonstrate the effectiveness of the proposed algorithm compared to the optimal solution and related work in the literature for various network scenarios with user mobility.…”
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Impacts of On-Grid Solar PV on Distribution Networks and Potential Solutions: A Case Study in the Region of Zahle by Korkmaz, Jessica

“…The siting and sizing methodology is conducted by considering five different optimization algorithms, namely the single-objective genetic algorithm (SOGA), the combined SOGA and loss sensitivity factor algorithm (SOGA-LSF), the multi-objective genetic algorithm (MOGA), the combined MOGA-LSF and the CAPADD algorithm of OpenDSS. …”
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Enhancement of Frequency Control for Stand-Alone Multi-Microgrids by Kavita Singh (182141)

“…For getting superior outcomes and enhanced steadiness of the microgrid, the controller gains are streamlined utilizing an imperialist competitive algorithm (ICA). To demonstrate the efficiency of ICA, The obtained results are compared with the genetic algorithm and particle swarm optimization algorithm. …”

A learning approach for prioritized handoff channel allocation in mobile multimedia networks by El-Alfy, E.-S.M.

“…Simulations are provided to compare the effectiveness of the proposed algorithm with other known resource-sharing policies such as complete sharing and reservation policies.…”
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Power system output feedback stabilizer design via geneticalgorithms by Abdel-Magid, Y.L.

“…A digital simulation of the power system is then used in conjunction with the genetic algorithm to determine the output feedback gains. In the second method, the problem of selecting the output feedback gains is converted to a simple optimization problem with an eigenvalue based objective function, which is solved by a genetic algorithm. …”
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Peak Loads Shaving in a Team of Cooperating Smart Buildings Powered Solar PV-Based Microgrids by Ahmed Ouammi (14151039)

“…The developed predictive model is implemented as a smart energy management based high-level control of the TCM to reduce/shave the peak loads and satisfy the EVs power demands through a coordination of the power exchanges between the microgrids. The algorithm has been tested through a case study to demonstrate its performance and effectiveness.…”

Multidimensional Gains for Stochastic Approximation by Saab, Samer S.

“…The two algorithms assume full knowledge of the Jacobian. The recursive algorithms are proposed for generating the optimal iterative-dependent matrix gain. …”
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The bus sightseeing problem by Qian Hu (205735)

“…A mixed-integer programming formulation for the BSP is provided and solved by a Benders decomposition algorithm. For large-scale instances, an iterated local search based metaheuristic algorithm is developed with some tailored neighborhood operators. …”

The Use of Microwave Tomography in Bone Healing Monitoring by Alkhodari, Mohanad Ahmed

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