Blood-Based Proteomic Profiling Identifies Potential Biomarker Candidates and Pathogenic Pathways in Dementia by Hanan Ehtewish (17149825)

“…We used a high-throughput proximity extension immunoassay to quantify 1090 proteins in 122 participants (22 with dementia, 64 with mild cognitive impairment (MCI), and 36 controls with normal cognitive function). Limma-based differential expression analysis reported the dysregulation of 61 proteins in the plasma of those with dementia compared with controls, and machine learning algorithms identified 17 stable diagnostic biomarkers that differentiated individuals with AUC = 0.98 ± 0.02. …”

Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018) by Tay, Bilal M.

“…Moreover, we propose in this thesis a Deep Learning Based Approach to Predict Non-Performing Loans. Compared to the literature, the proposed model embeds a new feature selection method and offers higher detection accuracy, which helps lenders and financial institutions to better manage their lending activities and loan monitoring processes.…”
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On the protection of power system: Transmission line fault analysis based on an optimal machine learning approach by Md. Sihab Uddin (17542488)

“…The design is carried out based on the selection of the optimal model parameters using a search optimization algorithm called GridSearchCV. …”

A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks by Umesh Kumar Lilhore (17727684)

“…The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. …”

On the Optimization of Band Gaps in Periodic Waveguides by Jamil Renno (14070771)

“…For the first optimization scenario, distribution-free analysis showed that at intermediate function evaluation budgets, detectable differences emerge among algorithms, whereas in the second scenario, these differences diminish at higher evaluation budgets (with no significant pairwise contrasts), indicating convergence. …”

Reliability and fault tolerance based topological optimization of computer networks - part II: iterative techniques by Abd-El-Barr, Mostafa

“…Topological optimization of computer networks is concerned with the selection of a subset of the available links such that the reliability and fault-tolerance aspects are maximized while meeting a cost constraint. …”
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Reliability and fault tolerance based topological optimization of computer networks - part I: enumerative techniques by Abd-El-Barr, Mostafa

“…A number of enumeration-based techniques were proposed to solve this problem. …”
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Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects by Majdi Mansouri (16869885)

“…Future research directions towards the improvement of the performance of the DL-based FDD techniques are also discussed. This review paper aims to systematically present the development of DL-based FDD for PV systems and provide guidelines for future research in the field.…”

Development of a deep learning-based group contribution framework for targeted design of ionic liquids by Sadah Mohammed (18192859)

“…Correlation results align with the experimental data, affirming the applicability of our framework. Finally, the algorithm is employed in a CO₂ capture case study to generate and select the best-performing novel ILs, which exhibit behavior consistent with established ILs in the literature.…”

Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study by Alaa Abd-alrazaq (17058018)

“…</p><h3>Results</h3><p dir="ltr">After applying the study selection criteria, we included 33,206 abstracts in the analysis of this study. …”

A data envelopment analysis model for opinion leaders’ identification in social networks by Hamed Baziyad (19273738)

“…Another contribution of this paper is introducing a new framework (OL-Finder Evaluator or OLFE) for validating the OLs’ detection algorithms under imbalanced datasets. DEA methods, when compared with SNA methods, have the advantage of being able to apply over non-graph-based datasets and to work with substantially smaller datasets. …”

Robust Kalman filter and smoother for errors-in-variables model with observation outliers based on Least-Trimmed-Squares by ALMutawa, Jaafar

“…We introduce the EIV problem with outliers and then we present the Least-Trimmed-Squares (LTS) estimator which is highly robust estimator to detect outliers. As a result, a new statistical test to check the existence of outliers which is based on the Kalman filter and smoother has been formulated. …”
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A degree-based heuristic for strongly connected dominating-absorbent sets in wireless ad-hoc networks by Abu-Khzam, Faisal N.

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Video Streaming over D2D Networks by Ahmed, Ibtihal Mohamed Taha

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Edge Caching in Fog-Based Sensor Networks through Deep Learning-Associated Quantum Computing Framework by Tayyabah Hasan (18427887)

“…<div><p>Fog computing (FC) based sensor networks have emerged as a propitious archetype for next-generation wireless communication technology with caching, communication, and storage capacity services in the edge. …”

A systematic review of recent advances in the application of machine learning in membrane-based gas separation technologies by Farideh Abdollahi (22303153)

“…This study aims to bridge this gap by comprehensively reviewing ML concepts, approach, and algorithms in the <u>membrane separation</u> sector. …”

Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV by Zulkifli, Muhammad

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A novel XML document structure comparison framework based-on sub-tree commonalities and label semantics by Tekli, Joe

“…XML similarity evaluation has become a central issue in the database and information communities, its applications ranging over document clustering, version control, data integration and ranked retrieval. Various algorithms for comparing hierarchically structured data, XML documents in particular, have been proposed in the literature. …”
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Thermal Change Index-Based Diabetic Foot Thermogram Image Classification Using Machine Learning Techniques by Amith Khandakar (14151981)

“…Plantar foot thermogram images acquired using an infrared camera have been shown to detect changes in temperature distribution associated with a higher risk of foot ulceration. …”

Predicting Plasma Vitamin C Using Machine Learning by Daniel Kirk (17302798)

“…Variables were selected based on a known or hypothesized relationship with plasma vitamin C, and variables that are expensive or difficult to obtain were excluded in order to more closely replicate the situation of a real health application. …”