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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Application of Red Deer Algorithm in Optimizing Complex functions حسب Zitar, Raed

"…The Red Deer algorithm (RDA), a recently developed population-based meta-heuristic algorithm, is examined in this paper with the optimization task of complex functions. …"
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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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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. …"

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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Efficient Approximate Conformance Checking Using Trie Data Structures حسب Awad, Ahmed

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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. …"

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

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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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SDODV. (c2018) حسب Assi, Maram

"…Experimental results prove that SDODV out-performs shortest path and reduces the energy consumption.…"
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Computer-aided detection of Melanoma using geometric features حسب Azar, Danielle

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Video features with impact on user quality of experience حسب Abbas, Nadine

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On the disk dimension of planar graphs حسب Abu-khzam, Faisal

"…More significantly, we devise a direct and highly practical linear-time algorithm to decide whether an arbitrary graph has fixed disk dimension k or less. …"
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Dynamic Cyber Resilience of Interdependent Critical Information Infrastructures حسب JUMA, MAZEN GHAZI

"…The technology stack was also enhanced with three new algorithms and five protocols. The proposed solution was optimized using the iterative four-objective cycle based on previous primary phase results. …"
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Nouveaux points de coupure et primitives pour les préoccupations de renforcement de sécurité حسب Mourad, Azzam

"…The first one is the GAFlow, the Closest Guaranteed Ancestor, which returns the closest ancestor join point to the pointcuts of interest that is on all their runtime paths. The second one is the GDFlow, the Closest Guaranteed Descendant, which returns the closest child join point that can be reached by all paths starting from the pointcuts of interest. …"
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New aspect-oriented constructs for security hardening concerns حسب Mourad, Azzam

"…The first one is the GAFlow, Closest Guaranteed Ancestor, which returns the closest ancestor join point to the pointcuts of interest that is on all their runtime paths. The second one is the GDFlow, Closest Guaranteed Descendant, which returns the closest child join point that can be reached by all paths starting from the pointcut of interest. …"
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