A Machine Learning Approach to Predicting Diabetes Complications حسب Jian, Yazan Khaled

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CAD TOOL FOR THE AUTOMATIC-GENERATION OF MICROPROGRAMS حسب Sait, Sadiq M.

"…Since the UAHPL model is directly related to hardware, this approach is better than those based on ordinary high-level languages or special microprogram languages. …"
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Multimodal feature fusion and ensemble learning for non-intrusive occupancy monitoring using smart meters حسب Sakib Mahmud (15302404)

"…In this study, we introduce the multimodal feature fusion for non-intrusive occupancy monitoring (MMF-NIOM) framework, which leverages both classical and deep machine learning algorithms to achieve state-of-the-art occupancy detection performance using smart meter data. …"

From Collatz Conjecture to chaos and hash function حسب Masrat Rasool (17807813)

"…The effectiveness and dependability of the proposed hash function are evaluated by comparing it with two well-known hash algorithms, namely SHA-3 and SHA-2, as well as several other Chaos-based hash algorithms. …"

Fuzzy controllers design using space-filling curves حسب Elshafei-Ahmed, M.

"…We then propose a SFC fuzzy inference model based on clustering the object space. The SFC fuzzy model is then used to design a fuzzy controller. …"
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Fuzzy Controllers Design Using Space-Filling Curves حسب Elshafei-Ahmed, M

"…We then propose a SFC fuzzy inference model based on clustering the object space. The SFC fuzzy model is then used to design a fuzzy controller. …"
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A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks حسب Sakib Mahmud (15302404)

"…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. …"

Single-channel speech denoising by masking the colored spectrograms حسب Sania Gul (18272227)

"…With a slightly reduced PESQ score (by 0.58 points), the proposed model offers an improvement of 2 % in STOI, and 4375 and 1135 times reduction respectively in the required number of training epochs and network parameters when compared to a GAN-based model augmented by WavLM; a large-scale self-supervised learning model. …"

Nonlinear Friction Identification of A Linear Voice Coil DC Motor حسب Takrouri, Mohannad Hashem

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Teachers' Perceptions of the Role of Artificial Intelligence in Facilitating Inclusive Practices for Students with Special Educational Needs and Disabilities: A Case Study in a Pri... حسب BACHIR, HIBAH AHMAD

"…Findings referred these barriers to limited teacher training, technological accessibility, and data privacy concerns, as well as ethical biases in AI algorithms. …"
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Efficient XML Structural Similarity Detection using Sub-tree Commonalities حسب Tekli, Joe

"…Various algorithms for comparing hierarchically structured data, e.g. …"
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Optimising Nurse–Patient Assignments: The Impact of Machine Learning Model on Care Dynamics—Discursive Paper حسب Mutaz I. Othman (21186827)

"…Future research should focus on refining algorithms, ensuring real‐time adaptability, addressing ethical considerations, evaluating long‐term patient outcomes, fostering cooperative systems, and integrating relevant data and policies within the healthcare framework.…"

Diabetic Sensorimotor Polyneuropathy Severity Classification Using Adaptive Neuro Fuzzy Inference System حسب Fahmida Haque (16896489)

"…Patients have been classified into four classes: Absent, Mild, Moderate, and Severe. The model accuracy was validated with the results from different machine learning algorithms. …"

Copy number variations in the genome of the Qatari population حسب Khalid A. Fakhro (3158862)

"…Genotyping intensities and genome sequencing data from 97 Qataris were analyzed with four different algorithms and integrated to discover 16,660 high confidence CNV regions (CNVRs) in the total population, affecting ~28 Mb in the median Qatari genome. …"

Machine Learning Techniques for Pharmaceutical Bioinformatics حسب SULTAN, AHMED ATTA AHMED

"…The study integrates knowledge visualization, analysis, as well as development of a predictive model based on the Drug-Drug Interactions (DDIs) as a complex network. …"
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Dynamic Cyber Resilience of Interdependent Critical Information Infrastructures حسب JUMA, MAZEN GHAZI

"…The technology stack was also enhanced with three new algorithms and five protocols. The proposed solution was optimized using the iterative four-objective cycle based on previous primary phase results. …"
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Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE حسب Ben Romdhane, Haifa

"…The validation of these results was performed using previous archaeological works as well as geological and geomorphological field surveys. The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …"
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LDSVM: Leukemia Cancer Classification Using Machine Learning حسب Abdul Karim (417009)

"…The main aim was to predict the initial leukemia disease. Machine learning algorithms such as decision tree (DT), naive bayes (NB), random forest (RF), gradient boosting machine (GBM), linear regression (LinR), support vector machine (SVM), and novel approach based on the combination of Logistic Regression (LR), DT and SVM named as ensemble LDSVM model. …"

Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges حسب Muhammad Mohsin Khan (22303366)

"…Still, challenges in adversarial attacks, algorithmic bias, and variable regulatory frameworks remain strong. …"

Diagnostic test accuracy of AI-assisted mammography for breast imaging: a narrative review حسب Daksh Dave (17949239)

"…This review focuses on the diagnostic accuracy of AI-assisted mammography, synthesizing findings from studies across different clinical settings and algorithms. The motivation for this research lies in addressing the need for enhanced diagnostic tools in breast cancer screening, where early detection can significantly impact patient outcomes. …"