A Novel Methodology for Human Kinematics Motion Detection Based on Smartphones Sensor Data Using Artificial Intelligence by Raza, Ali

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Deep Learning for Arabic Error Detection and Correction by ALKHATIB, MANAR

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Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine by Debendra Muduli (20748758)

“…For mass fundus image-based glaucoma classification, an improved automated computer-aided diagnosis (CAD) model performing binary classification (glaucoma or healthy), allowing ophthalmologists to detect glaucoma disease correctly in less computational time. …”

Enhanced PSO-Based NN for Failures Detection in Uncertain Wind Energy Systems by Khaled Dhibi (16891524)

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

Generative AI in finance: Replicability, methodological contingencies, and future research directions by Hassnian Ali (22330396)

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

Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques by Ameema Zainab (16864263)

“…A dataset publicly available for a smart home, along with weather conditions, is used for the methodology validation. The proposed algorithm is used to detect the spamicity score of the connected IoT devices in the network. …”

Deep learning-based marine big data fusion for ocean environment monitoring: Towards shape optimization and salient objects detection by Sulaiman Khan (12585349)

“…This research study presents a data fusion-based method for underwater salient object detection and ocean environment monitoring by utilizing a deep model.…”

Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis by Hassan, Ali

“…This work introduces a novel, unsupervised detection methodology for detecting adversarial inputs to NLP classifiers. …”
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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis by Hassan Ali (3348749)

“…This work introduces a novel, unsupervised detection methodology for detecting adversarial inputs to NLP classifiers. …”

A Fully Optical Laser Based System for Damage Detection and Localization in Rail Tracks Using Ultrasonic Rayleigh Waves: A Numerical and Experimental Study by Masurkar, Faeez

“…Based on the obtained accuracy of the results, the proposed methodology has been found to be capable of inspecting rail track specimens in a completely non-contact manner with reasonably good accuracy…”
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Wavelet Analysis- Singular Value Decomposition Based Method for Precise Fault Localization in Power Distribution Networks Using k-NN Classifier by Abhishek Raj (7245425)

Artificial Intelligence for Skin Cancer Detection: Scoping Review by Abdulrahman Takiddin (14153181)

“…Hence, to aid in diagnosing skin cancer, artificial intelligence (AI) tools are being used, including shallow and deep machine learning–based methodologies that are trained to detect and classify skin cancer using computer algorithms and deep neural networks.…”

Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts by ALSHAMSI, SUROUR

“…As a function of the proposed objective, ensembling algorithms applicable to network security have been investigated and evaluated, and a methodology for detecting infected PAGE 2 hosts using ensembling has been developed, based on experiments designed and tested with real datasets. …”
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Fault Detection of Fuel Systems Using Polynomial Regression Profile Monitoring by Awad, Mahmoud

“…We present in this paper a new monitoring framework for smart fuel systems utilizing outlying observations detection and monitoring using ccharts. The traditional control charts based on the Hotelling's T2 statistic were deficient in detecting SFS anomalies and a new approach was necessary to isolate faulty profiles. …”
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A Two-Tier Post-Processing Framework for Lightweight Video Anomaly Detection by Akhtar, Muhammad Hannan

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Non-Linear Profile Monitoring Using Artificial Neural Network Fault Detection by Mohamed, Ahmed Fares

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AI-driven wearable sensors for postoperative monitoring in surgical patients: A systematic review by Muhammad Mohsin Khan (22150360)

“…Traditional monitoring systems, based on periodic measurement of vital signs, often cannot detect subtle physiological changes that herald early clinical deterioration. …”

Crowd behavior detection: leveraging video swin transformer for crowd size and violence level analysis by Marwa Qaraqe (10135172)

“…Moreover, the prevailing approach to crowd behavior recognition, which solely relies on the analysis of closed-circuit television (CCTV) footage and overlooks the integration of online social media video content, leads to a primarily reactive methodology. This paper proposes a crowd behavior detection framework based on the swin transformer architecture, which leverages crowd counting maps and optical flow maps to detect crowd behavior across various sizes and violence levels. …”