AI and IoT-based concrete column base cover localization and degradation detection algorithm using deep learning techniques by Khalid, Naji

“…This paper proposes a novel automated algorithm for the health monitoring of concrete column base cover degradation based on IoT and the state-of-the-art deep learning framework, Convolutional Neural Network (CNN). …”
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Logarithmic spiral search based arithmetic optimization algorithm with selective mechanism and its application to functional electrical stimulation system control by Abu Zitar, Raed

An improved quorum selection algorithm (IQSA). (c2007) by Younes, Samer

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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

“…To overcome these challenges, a new FS algorithm named Uniform-solution-driven Binary Feature Selection (UniBFS) has been developed in this study. …”

The Detection of Dysarthria Severity Levels Using AI Models: A Review by Afnan Al-Ali (16888695)

Enhancing fairness and scalability in IOTA tangle networks: a POMDP-based tip selection algorithm for decentralized systems by Mays Alshaikhli (22564811)

“…This study presents a novel Partially Observable Markov Decision Process (POMDP)-based Tip Selection Algorithm (TSA) to optimize fairness in the IOTA Tangle. …”

Multiclass feature selection with metaheuristic optimization algorithms: a review by Abu Zitar, Raed

“…Metaheuristic algorithms have also been presented in four primary behavior-based categories, i.e., evolutionary-based, swarm-intelligence-based, physics-based, and human-based, even though some literature works presented more categorization. …”
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Optimal selection of the forgetting matrix into an iterative learning control algorithm by Saab, Samer S.

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A novel linear time corner detection algorithm by Sarfraz, M.

“…We have presented a novel scheme for detecting corners of a planner object SRM05. The core of the algorithm is based upon slope analysis. …”
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Variable Selection in Data Analysis: A Synthetic Data Toolkit by Mitra, Rohan

“…The contributions of this paper aim to foster the development of novel feature selection algorithms and advance their study.…”
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Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

“…The outcomes revealed that these ML algorithms can be useful in predicting ground losses during wild blueberry harvesting in the selected fields.…”

Application of particle swarm optimization algorithm to multiuser detection in CDMA by El-Mora, H.H.

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Bootstrap-based Aggregations and their Stability in Feature Selection by Salman, Reem Elfatih

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Interval-Valued Reduced Ensemble Learning Based Fault Detection and Diagnosis Techniques for Uncertain Grid-Connected PV Systems by Khaled Dhibi (16891524)

Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy by Raad, M.W.

“…A number of parameter estimation and digital online peak localisation algorithms are being developed, including a pulse classification technique which uses a simple peak search routine based on the smoothed first derivative method, which gave a percentage error of peak amplitude of less than 1%. …”
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Bird’s Eye View feature selection for high-dimensional data by 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. …”

Comparative Analysis of Supervised Machine and Deep Learning Algorithms for Kyphosis Disease Detection by Alok Singh Chauhan (8264985)

Anomaly Detection Based Framework for Profile Monitoring by Al-Rahim, Nour Al-Huda Z. Al-Abed

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Detection of Depression in Arabic Social Media: A Comparison of Traditional and Modern Machine Learning Algorithms by ALSHEHHI, OMAR KHALID HAMAD

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A machine learning model for early detection of diabetic foot using thermogram images by Amith Khandakar (14151981)

“…We have compared a machine learning-based scoring technique with feature selection and optimization techniques and learning classifiers to several state-of-the-art Convolutional Neural Networks (CNNs) on foot thermogram images and propose a robust solution to identify the diabetic foot. …”