Test case generation for path coverage. (c2000) حسب Salame, Miran

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Intelligent Rapidly-Exploring Random Tree Star Algorithm حسب Ahmed, Khidir Galal Eldin Khidir

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Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem حسب Abu Zitar, Raed

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Data Generation for Path Testing حسب Mansour, Nashat

"…We present two stochastic search algorithms for generating test cases that execute specified paths in a program. …"
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Bird’s Eye View feature selection for high-dimensional data حسب Samir Brahim Belhaouari (16855434)

"…BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …"

Mobile Robot Navigation in Dynamic Environments Using an Improved RRT* Approach حسب Mohammed, Hussein Ali

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DRL-Based UAV Path Planning for Coverage Hole Avoidance: Energy Consumption and Outage Time Minimization Trade-Offs حسب Bahareh Jafari (22501715)

"…By deploying a deep reinforcement learning algorithm, we find optimal UAV paths based on the two families of trajectories: spiral and oval curves, to tackle different design considerations and constraints, in terms of QoS, energy consumption and coverage hole avoidance. …"

Particle swarm optimization algorithm: review and applications حسب Abualigah, Laith

"…Particle swarm optimization (PSO) is a heuristic global optimization technique and an optimization algorithm that is swarm intelligence-based. It is based on studies into the movement of bird flocks. …"
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A Novel Hybrid Genetic-Whale Optimization Model for Ontology Learning from Arabic Text حسب M. Ghoniem , Rania

"…The algorithm calculates the concept frequency weights using the term frequency weights. …"
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RHEEMix in the data jungle: a cost-based optimizer for cross-platform systems. حسب Sebastian Kruse (18595195)

"…Our main contributions are: (i) a mechanism based on graph transformations to explore alternative execution strategies; (ii) a novel graph-based approach to determine efficient data movement plans among subtasks and platforms; and (iii) an efficient plan enumeration algorithm, based on a novel enumeration algebra. …"

Forecasting the Direction of GCC Stock Indexes Using Support Vector Machine (SVM) Algorithm حسب Zeino, Yaser Abdullah

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Towards Scalable Process Mining Pipelines حسب Mohamed, Belal

"…Contributions have covered the spectrum of better algorithms, richer comparison metrics, and movement towards online analysis for process data. …"
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT حسب Dhananjay Bisen (19482454)

"…<p dir="ltr">In mobile edge computing (MEC), it is difficult to recognise an optimum solution that can perform in limited energy by selecting the best communication path and components. This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …"

Generation and Detection of Sign Language Deepfakes - A Linguistic and Visual Analysis حسب Naeem, Shahzeb

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QoS-driven multicast tree generation using tabu search حسب Youssef, H.

"…The problem to be solved is to find a minimum cost multicast treee where each source to destination path is contrained by a delay bound. …"
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Real-Time Path-Planning using Depth/INS Sensor Fusion for Localization حسب Alkhawja, Fares Amin E

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Optimal Routing Protocol in Multimedia Wireless Sensor Networks حسب Al-Zurba, Hiba

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Design of A Theoretical Framework For A Real-Time Fire Evacuation Guidance System حسب Abougharib, Arwa

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Evacuation of a highly congested urban city حسب El Khoury, John

"…The algorithm uses Dijkstras algorithm to find the shortest path(s) and a modified greedy algorithm to assign maximum flows to selected paths given a specific schedule per time interval. …"
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Solar power forecasting beneath diverse weather conditions using GD and LM-artificial neural networks حسب Sharma, Neetan

"…A case study has been done in the Peer Panjal region. The data collected for four months with various parameters have been applied randomly as input data using GD and LM type of artificial neural network compared to actual solar energy data. …"
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