Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm by De Rochechouart, Maxence

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General Inspection Plan For Critical Multicharacteristic Components by Duffuaa, S. O.

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A COMPLETE INSPECTION PLAN FOR DEPENDENT MULTICHARACTERISTIC CRITICAL COMPONENTS by Duffuaa, S. O.

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A pragmatic approach for testing robustness on real-time component based systems by Tarhini, Abbas

“…In this paper, we suggest a realistic methodology for testing robustness of real-time component-based systems (RTCBS). A RTCBS system is described as a collection of components where each component is specified by a nominal and a degraded specification, modeled as a timed input-output automaton (TIOA). …”
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Agent-Based Reactive Geographic Routing Protocol for Internet of Vehicles by Mazouzi, Mohamed

“…In this paper, we first propose a novel lightweight location service that permits to discover all the geographical paths between two vehicles based on smart mobile agents. Second, we proposed ARGENT an Agent-Based Reactive Geographic Routing Protocol that couples the routing process with the novel lightweight location service. …”
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Multi-Robot Map Exploration Based on Multiple Rapidly-Exploring Randomized Trees by Umari, Hassan Abdul-Rahman

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ARDENT: A Proactive Agent-Based Routing Protocol for Internet of Vehicles by Mazouzi, Mohamed

“…Then, we present an Agent-Based Proactive Geographic Routing Protocol called ARDENT to route data packets with reduced delay and higher delivery ratio. …”
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Distributed optimal coverage control in multi-agent systems: Known and unknown environments by Mohammadhasan Faghihi (22303057)

“…<p>This paper introduces a novel approach to solve the coverage optimization problem in multi-agent systems. The proposed technique offers an optimal solution with a lower cost with respect to conventional Voronoi-based techniques by effectively handling the issue of agents remaining stationary in regions void of information using a ranking function. …”

Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization by De Rochechouart, Maxence

“…This paper presents a reinforcement learning agent-based model that works by incorporating the MESA environment with the Stone Soup radar systems simulator. …”
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Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction by Syed Mohammad (21075689)

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An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure by Fahmy, Ahmed

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Reliability of artificial intelligence in predicting total knee arthroplasty component sizes: a systematic review by Loay A. Salman (14150322)

Public health utility of cause of death data: applying empirical algorithms to improve data quality by Sarah Charlotte Johnson (9715415)

A decoding algorithm for I-Q space-time coded systems in fadingenvironments by Zummo, S.A.

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Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk by Mohamed Chaouch (17983846)

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Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval by Mohammed Tahar Habib Kaib (21633176)

“…The proposed algorithm has been tested on three tank system pilot plant and Ain El Kebira Cement rotary kiln process. …”

Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques by Hassan, Mahitab Alaaeldin

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A novel hybrid methodology for fault diagnosis of wind energy conversion systems by Khaled Dhibi (16891524)

“…Therefore, a hybrid feature selection based diagnosis technique, that can preserve the advantages of wrapper and filter algorithms as well as RF model, is proposed. In the first phase, the neighborhood component analysis (NCA) filter algorithm is used to reduce and select only the pertinent features from the original raw data. …”

Single channel speech denoising by DDPG reinforcement learning agent by Sania Gul (18272227)

“…In this paper, a novel SD algorithm is presented based on the deep deterministic policy gradient (DDPG) agent; an off-policy reinforcement learning (RL) agent with a continuous action space. …”

Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management by Alhusin, Mohammed Omer Alamin

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