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381
Artificial Intelligence in Predicting Cardiac Arrest: Scoping Review
Published 2021“…Machine learning models were the most prominent branch of AI used in the prediction of cardiac arrest in the studies (38/47, 81%), and the most used algorithm was the neural network (23/47, 49%). …”
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382
Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle Networks
Published 2024“…Based on our thorough analysis, we identify key limitations in current methodologies and propose potential paths for future research, focusing on integrating real-time data analysis, cross-layer security measures, and collaborative IDS frameworks.…”
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383
Agent-Based Reactive Geographic Routing Protocol for Internet of Vehicles
Published 2023“…Geographic routing protocols are a promising solution for the IoV, since they are based mainly on the location information which can be easily obtained through a location-based service. …”
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384
Edge intelligence for network intrusion prevention in IoT ecosystem
Published 2023“…This paper proposes a deep learning-based algorithm to protect the network against Distributed Denial-of-Service (DDoS) attacks, insecure data flow, and similar network intrusions. …”
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385
RRT and Octomap based 3D environment exploration and mapping
Published 2020Get full text
doctoralThesis -
386
Acoustic Based Localization of Partial Discharge Inside Oil-Filled Transformers
Published 2022“…<p dir="ltr">This paper addresses the localization of Partial Discharge through a 3D Finite Element Method analysis of acoustic wave propagation inside a 3-phase 35kV transformer with the help of COMSOL Multiphysics software. …”
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387
Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images
Published 2023“…Considering these shortcomings, computational methods especially machine learning and deep learning algorithms are leveraged as an alternative to accelerate the accurate detection of CT scans as cancerous, and non-cancerous. …”
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388
CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…Three machine learning algorithms support vector machine (SVM), AdaBoost, and Random forest are employed to assess the performance of the CNN features and fused CNN features. …”
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389
A novel few shot learning derived architecture for long-term HbA1c prediction
Published 2024“…For the first time in the literature, this work proposes a novel FSL-derived algorithm for the long-term prediction of clinical HbA1c measures. …”
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390
CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…Three machine learning algorithms support vector machine (SVM), AdaBoost, and Random forest are employed to assess the performance of the CNN features and fused CNN features. …”
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391
From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors
Published 2021“…The methods for correcting and calibrating these biases and dependencies that have been used in the literature likewise range from simple linear and quadratic models to complex machine learning algorithms. Here we review the needs and challenges when trying to get high-quality data from low-cost sensors. …”
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392
Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review
Published 2025“…In current literature, there are a number of papers that address all these faults using different methods, and this paper compiles the information from the written works for ease of access. Machine learning algorithms are a set of data-driven rules that are able to classify specific faults in induction motors, which will be explained further in this review paper. …”
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393
A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method
Published 2022“…The LSB substitution method can minimize the error rate in embedding process and can achieve greater reliability in criteria, using novel algorithm based on value difference. In this paper, we proposed a novel technique in steganography within the digital images such is RGB, Gray Scale, Texture, Aerial images to achieve higher security, imperceptibility, capacity, and robustness as compared with existing methods. …”
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394
A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks
Published 2025“…This review synthesizes evidence from more than 500 peer-reviewed studies published between 2020 and 2026, mapping DRL applications across distributed generation, transmission, distribution, energy storage systems, energy markets, local energy management, grid security, and data privacy. We present a structured taxonomy covering value-based, policy-based, actor-critic, model-based, and advanced multi-agent and multi-objective approaches, and link algorithms to tasks such as dispatch, microgrid coordination, real-time pricing, load balancing, and demand–response. …”
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395
A geometric-primitives-based compression scheme for testingsystems-on-a-chip
Published 2001“…In this paper, it is assumed that an embedded core will be used to execute the decompression algorithm and decompress the test data…”
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396
Energy-aware adaptive compression for mobile devices. (c2009)
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masterThesis -
397
ARDENT: A Proactive Agent-Based Routing Protocol for Internet of Vehicles
Published 2023“…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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398
An Ontology-based Semantic Web for Arabic Question Answering: The Case of E-Government Services
Published 2018“…Further, 414 automatic questions are tested on the QA algorithm using two methods, semantics-based and keyword-based. …”
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399
Novel RFID-Based Pose Estimation Using Single Stationary Antenna
Published 2016“…Our scheme is based on power map matching algorithm that is capable in estimating the location and orientation of objects. …”
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400
Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information
Published 2019“…In all likelihood, while features from several modalities may enhance the classification performance, they might exhibit high dimensionality and make the learning process complex for the most used machine learning algorithms. …”
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