Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk حسب Mohamed Chaouch (17983846)

"…Additionally, an online classifier is developed for streaming data, combining online PCA with a kernel-based recursive classifier using a stochastic approximation algorithm. …"

DRL-Based UAV Path Planning for Coverage Hole Avoidance: Energy Consumption and Outage Time Minimization Trade-Offs حسب Bahareh Jafari (22501715)

"…As such, in addition to avoiding coverage holes, we should also make the outage time as small as possible. By deploying a deep reinforcement learning algorithm, we find optimal UAV paths based on the two families of trajectories: spiral and oval curves, to tackle different design considerations and constraints, in terms of QoS, energy consumption and coverage hole avoidance. …"

Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification حسب Rajendra Babu Chikkala (22330876)

"…The BRNN model, refined using the Adagrad optimization algorithm, efficiently integrates the learned features from both branches. …"

Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review حسب Avneet Kaur (712349)

"…It has been learned that image-processing techniques overwhelm the existing research and have the potential to integrate meteorological data. …"

Wavelet Analysis- Singular Value Decomposition Based Method for Precise Fault Localization in Power Distribution Networks Using k-NN Classifier حسب Abhishek Raj (7245425)

"…Additionally, the computational efficiency of the algorithm is evidenced by an average processing time of 0.0764 seconds per fault event, making it well-suited for real-time applications.…"

A machine learning model for early detection of diabetic foot using thermogram images حسب Amith Khandakar (14151981)

"…However, the distribution of plantar temperature may be heterogeneous, making it difficult to quantify and utilize to predict outcomes. …"

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

"…Finally, a 3D Finite Element simulation was conducted to validate the findings and each observation resulting from the experiments. …"
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A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition حسب Hanif Heidari (22467148)

"…The proposed method divides multiple regions (different data lengths) into the feature space, allowing the algorithm to learn more complex decision boundaries. …"

Enhancing e-learning through AI: advanced techniques for optimizing student performance حسب Rund Mahafdah (21399854)

"…AI algorithms, known for their cognitive ability and capacity to learn, adapt, and make decisions, are employed to analyze and forecast student performance, thereby improving educational quality and outcomes. …"

DoFP-ML: A Machine Learning Approach to Food Quality Monitoring Using a DoFP Polarization Image Sensor حسب Maen Takruri (10873368)

Ensemble Deep Random Vector Functional Link Neural Network for Regression حسب Minghui Hu (2457952)

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. …"

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

Deep and transfer learning for building occupancy detection: A review and comparative analysis حسب Aya Nabil Sayed (17317006)

"…Besides, integrating artificial intelligence (AI) into the BIoT is essential for data analysis and intelligent decision-making. Thus, data-driven approaches to infer occupancy patterns usage are gaining growing interest in BIoT applications. …"

The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review حسب Zainab Jan (17306614)

"…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …"

Artificial Intelligence for Cochlear Implants: Review of Strategies, Challenges, and Perspectives حسب Billel Essaid (22047578)

"…The process involves receiving the speech signal in analog form, followed by various signal processing algorithms to make it compatible with devices of limited capacities, such as cochlear implants (CIs). …"

An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study حسب Ayman Hassan (14426412)

"…For cases in which Ornge air services and land ambulance medical transport were both involved in a patient transport process, data were merged and time intervals of the transport journey were determined. …"

Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks حسب Mohamed Massaoudi (16888710)

"…The proposed algorithm unlocks scalability and system adaptability to operational variability by adopting numeric imputation and missing-data-tolerant techniques. …"

Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms حسب Marwan Dhuheir (19170898)

"…A key requirement in these applications is minimizing the latency of data processing, particularly for time-sensitive tasks like image classification of IIoT device data. …"