Regression estimation for continuous-time functional data processes with missing at random response حسب Mohamed Chaouch (17983846)

Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data حسب Rajesh Kumar Dhanaraj (19646269)

"…During this process, the input patterns are categorized into different clusters. …"

A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT حسب Dhananjay Bisen (19482454)

Modelling fatigue uncertainty by means of nonconstant variance neural networks حسب Mohamad Shadi Nashed (21363557)

"…First, we model the fatigue life of cover‐plated beams under constant amplitude loading, and then we model the relationship between random vibration velocity and equivalent stress in process pipework. The two case studies demonstrate that PNNs with nonconstant variance can model the distribution of the data while also considering the variability of both distribution parameters (mean and standard deviation). …"

Assessing the risk of vibration-induced fatigue in process pipework using convolutional neural networks حسب Ahmed Mohamed (628889)

"…In contrast, vibration data can be efficiently collected using accelerometers and single-channel data loggers, providing a more feasible solution for initial screening. …"

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

"…<h3>Objective</h3><p dir="ltr">During the last few years, underwater object detection and marine resource utilization have gained significant attention from researchers and become active research hotspots in underwater image processing and analysis domains. This research study presents a data fusion-based method for underwater salient object detection and ocean environment monitoring by utilizing a deep model.…"

Experimental Verification of Low-Pressure Kinetics Model for Direct Synthesis of Dimethyl Carbonate Over CeO₂ Catalyst حسب G. Ibrahim (7601063)

"…The kinetic model predictions closely aligned with experimental data, demonstrating a 17% mean absolute percentage error and indicating a high level of predictability. …"

‘Leanomics’ in healthcare: a three-year quality improvement study on the financial impact of a modified Kanban system in hospital storerooms حسب Kenneth Jun Logrono (23124322)

"…Impact was assessed using statistical process control charts generated with QI Macros software. …"

Enhancing waste sorting and recycling efficiency: robust deep learning-based approach for classification and detection حسب Faizul Rakib Sayem (21399890)

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. …"

A Novel Non-Invasive Estimation of Respiration Rate From Motion Corrupted Photoplethysmograph Signal Using Machine Learning Model حسب Md. Nazmul Islam Shuzan (16888827)

Traffic fatality trends in four continents based micro level data for three decades حسب Hashim M. N. Al-Madani (19807239)

"…It took over three years to gather such data. Such large gathered data for such long period of time are yet not observed in the literature using the common means. …"

MCDFN: supply chain demand forecasting via an explainable multi-channel data fusion network model حسب Md Abrar Jahin (20108252)

"…MCDFN utilizes Convolutional Neural Networks (CNNs), Long Short-Term Memory networks (LSTMs), and Gated Recurrent Units (GRUs) to extract spatial and temporal features from time series data. Comparative benchmarking against seven other deep-learning models validates MCDFN’s efficacy, showing it outperforms its counterparts across key metrics with a mean squared error (MSE) of 23.5738, root mean squared error (RMSE) of 4.8553, mean absolute error (MAE) of 3.9991, and mean absolute percentage error (MAPE) of 20.1575%. …"

SAppKG: Mobile App Recommendation Using Knowledge Graph and Side Information-A Secure Framework حسب Daksh Dave (17949239)

"…These systems need access to user data, which is a serious security violation. While users seek accurate opinions, they do not want to compromise their privacy in the process. …"

Effect of cold and hot compactions on corrosion behavior of p- and n-type bismuth telluride-based alloys developed through microwave sintering process حسب Aicha S. Lemine (17148352)

Household-Level Energy Forecasting in Smart Buildings Using a Novel Hybrid Deep Learning Model حسب Dabeeruddin Syed (16864260)

"…The proposed framework consists of two stages, namely, data cleaning, and model building. The data cleaning phase applies pre-processing techniques to the raw data and adds additional features of lag values. …"

Improving MRI Resolution: A Cycle Consistent Generative Adversarial Network-Based Approach for 3T to 7T Translation حسب Zakaria Shams Siam (22048001)

Traffic Transformer: Transformer-based framework for temporal traffic accident prediction حسب Mansoor G. Al-Thani (19237204)

"…</p><h2>Other Information</h2><p dir="ltr">Published in: AIMS Mathematics<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3934/math.2024617" target="_blank">https://dx.doi.org/10.3934/math.2024617</a></p>…"

Explainable deep learning for rainfall prediction: A CNN-XGBoost hybrid approach in the northern region of Bangladesh حسب Md Safayet Islam (23073187)

"…These findings demonstrate the model’s efficacy across several data sources. To enhance the interpretability of the proposed CNN-XGB model, we deployed the SHAP (Shapley Additive exPlanations) explainer, providing insights into the model’s decision-making process. …"

Lifestyle Disease Surveillance Using Population Search Behavior: Feasibility Study حسب Shahan Ali Memon (18812038)

"…<h3>Background</h3><p dir="ltr">As the process of producing official health statistics for lifestyle diseases is slow, researchers have explored using Web search data as a proxy for lifestyle disease surveillance. …"