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method algorithm » mould algorithm (Expand Search)
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method algorithm » mould algorithm (Expand Search)
path processing » image processing (Expand Search)
code algorithm » cosine algorithm (Expand Search), rd algorithm (Expand Search), colony algorithm (Expand Search)
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT
Published 2023“…<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. …”
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Impact Of Multidisciplinary Maternal Resuscitation Training Program on Improving the Front-Line Care Provider’s Readiness to Manage Maternal Cardiac Arrest: A Pre-test/Post-test St...
Published 2024“…The multidisciplinary resuscitation teams were observed during the cardiac arrest mock drills both before and after conducting the multidisciplinary resuscitation simulation-based training program and the introduction of the maternal resuscitation algorithm pathway against seven KPIs. Those KPIs were Time to Confirm Cardiac Arrest; Code Blue and /or Code White Activation Time; Time to attempt first chest compression; Defibrillator Arrival Time; Time to First Defibrillation shock; Code blue/code white arrival time and Time to perform Perimortem Caesarean Delivery.…”
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Computation of conformal invariants
Published 2020“…In particular, we provide an algorithm for computing the conformal capacity of a condenser. …”
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Design of A Theoretical Framework For A Real-Time Fire Evacuation Guidance System
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Developing a Cooperative Behavior for Multi Agents System Application to Robot Soccer
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doctoralThesis -
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Communications in electronic textile systems
Published 2017“…Abstract- Electronic textiles (e-textiles) are emerging as a novel method for constructing electronic systems in wearable and large area applications. …”
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Computation of conformal invariants
Published 2021“…In particular, we provide an algorithm for computing the conformal capacity of a condenser. …”
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Analysis of Using Machine Learning to Enhance the Efficiency of Facilities Management in the UAE
Published 2022“…This study addresses these issues by Implementing Machine Learning (ML) algorithms using data from Building Management Systems (BMS) and FM maintenance reports, focussing on predictive maintenance for Fresh Air Handling Units. …”
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Loop based scheduling for high level synthesis
Published 1995“…This paper describes a new loop based scheduling algorithm. The algorithm aims at reducing the runtime processing complexity of path based scheduling techniques. …”
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A smart decentralized identifiable distributed ledger technology‐based blockchain (DIDLT‐BC) model for cloud‐IoT security
Published 2024“…The novel contribution of this work is to incorporate the operations of Rabin digital data signature generation, DIDLT‐based blockchain construction, and BCA algorithms for ensuring overall data security in IoT networks. …”
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Downlink channel estimation for IMT-DS
Published 2001“…IMT-DS system is an approved terrestrial radio interface standard for 3G mobile communication based on direct sequence code division multiple access (DS-CDMA). It employs a RAKE receiver to exploit multipath diversity. …”
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Dynamic multiple node failure recovery in distributed storage systems
Published 2018“…In this work, we address the problem of multiple failure recovery with dynamic scenarios using the fractional repetition code as a redundancy scheme. The fractional repetition (FR) code is a class of regenerating codes that concatenates a maximum distance separable code (MDS) with an inner fractional repetition code where data is split into several blocks then replicated and multiple replicas of each block are stored on various system nodes. …”
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Deep Reinforcement Learning for Resource Constrained HLS Scheduling
Published 2022“…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …”
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An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System
Published 2019“…Historical data of Dubai Toll Collection System is utilized to investigate multiple machine learning algorithms. Experiment is performed using Azure Machine Learning (ML) platform to test and assess the most efficient model that would predict the failure of system elements and predict the abnormality of the operation. …”
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On the Provisioning of Ultra-Reliable Low-Latency Services in IoT Networks with Multipath Diversity
Published 2020“…Simulation results are presented for both parts of the thesis to illustrate the effectiveness of the proposed solutions and algorithms in comparison with optimal solutions and baseline algorithms.…”
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Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model
Published 2024“…The proposed approach of DDN is trained with proper data sequences used for communication and the training phase is conducted with the norms of numerous channel variants. …”
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An Evolutionary Meta-Heuristic for State Justification in Sequential Automatic Test Pattern Generation
Published 2001“…In this work, we propose a hybrid approach which uses a combination of evolutionary and deterministic algorithms for state justification. A new method based on Genetic algorithms is proposed, in which we engineer state justification sequences vector by vector. …”
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