Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective حسب Zhitao Xu (2426023)

"…It contributes to the literature by identifying the four OR innovations to typify the recent advances in SC optimization: new modeling conditions, new inputs, new decisions, and new algorithms. Furthermore, we recommend four promising research avenues in this interplay: (1) incorporating new decisions relevant to data-enabled SC decisions, (2) developing data-enabled modeling approaches, (3) preprocessing parameters, and (4) developing data-enabled algorithms. …"

Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review حسب Rehaan Hussain (22302742)

"…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. …"

Adaptive PPO With Multi-Armed Bandit Clipping and Meta-Control for Robust Power Grid Operation Under Adversarial Attacks حسب Mohamed Massaoudi (16888710)

"…Specifically, our approach introduces three key innovations: 1) multi-armed bandit (MAB) mechanism for dynamic epsilon-clipping that adaptively adjusts exploration-exploitation trade-offs; 2) meta-controller framework that automatically tunes hyperparameters including the activation learning rate (ALR) penalties and exploration factors; and 3) integrated gradient-based optimization approach that combines policy gradients with environmental feedback. …"

Deep Neural Networks for Electromagnetic Inverse Scattering Problems in Microwave Imaging حسب Maricar, Mohammed Farook

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Decision-level fusion for single-view gait recognition with various carrying and clothing conditions حسب Al-Tayyan, Amer

"…Such a system is needed in access control applications whereby a single view is imposed by the system setup. The gait data is firstly processed using three gait representation methods as the features sources; Accumulated Prediction Image (API) and two new gait representations namely; Accumulated Flow Image (AFI) and Edge-Masked Active Energy Image (EMAEI). …"
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Enhancing building sustainability: A Digital Twin approach to energy efficiency and occupancy monitoring حسب Aya Nabil Sayed (17317006)

"…Our data-driven occupancy detection approach utilized Machine Learning (ML) algorithms to intelligently determine room occupancy, allowing for precise energy management based on real-time usage patterns. …"

Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier حسب Syed Ali Jafar Zaidi (19563178)

"…<div><p>Machine learning (ML)-based prediction is considered an important technique for improving decision making during the planning process. …"

The Assessment and Allocation of Public Private Partnership Risks in the UAE حسب Shaban, Mazhd

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Evolutionary support vector regression for monitoring Poisson profiles حسب Ali Yeganeh (16624998)

"…The proposed monitoring scheme is revealed to be superior to its counterparts, including the likelihood ratio test (LRT), multivariate exponentially weighted moving average (MEWMA), LRT-EWMA and other machine learning-based schemes. The simulation results show superiority of the proposed method in profiles with fixed explanatory variables and non-parametric models in nearly all situations while it is not able to be the best in all the simulations when there are with random explanatory variables. …"

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

"…Feature selection pre-processing is an important step to increase the accuracy of the classification algorithm and decrease the dimensionality of a dataset. …"

Comparative Study on Arabic Text Classification: Challenges and Opportunities حسب Abualigah, Laith

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LNCRI: Long Non-Coding RNA Identifier in Multiple Species حسب Saleh Musleh (15279190)

"…To overcome these challenges we developed LNCRI (Long Non-Coding RNA Identifier), a novel machine learning (ML)-based tool for the identification of lncRNA transcripts. …"

Automated systems for diagnosis of dysgraphia in children: a survey and novel framework حسب Jayakanth Kunhoth (14158908)

"…This work discusses the data collection method, important handwriting features, and machine learning algorithms employed in the literature for the diagnosis of dysgraphia. …"

Prediction of Multiple Clinical Complications in Cancer Patients to Ensure Hospital Preparedness and Improved Cancer Care حسب Regina Padmanabhan (14231606)

Real-Time Smart-Digital Stethoscope System for Heart Diseases Monitoring حسب Muhammad E.H. Chowdhury (17151154)

Short-Term Load Forecasting in Active Distribution Networks Using Forgetting Factor Adaptive Extended Kalman Filter حسب Mena S. ElMenshawy (17983807)

"…A few research studies focused on developing data filtering algorithm for the load forecasting process using approaches such as Kalman filter, which has good tracking capability in the presence of noise in the data collection process. …"

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

"…The model accuracy was validated with the results from different machine learning algorithms. The Accuracy, sensitivity, and specificity of the ANFIS model are 91.17±1.18%, 92±2.26%, 96.72±0.93%, respectively. …"

MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network حسب Sakib Mahmud (15302404)

"…Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. Although a few deep learning-based models have been proposed for the removal of ocular, muscle, and cardiac artifacts from EEG data to the best of our knowledge, there is no attempt has been made in removing motion artifacts from motion-corrupted EEG signals: In this paper, a novel 1D convolutional neural network (CNN) called multi-layer multi-resolution spatially pooled (MLMRS) network for signal reconstruction is proposed for EEG motion artifact removal. …"

A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation حسب Khaled Dhibi (16891524)

A survey and comparison of wormhole routing techniques in a meshnetworks حسب Al-Tawil, K.M.

"…These multiprocessing systems consist of processing elements or nodes which are connected together by interconnection networks in various topologies. …"
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