Holistic Transitional Approach of Humanitarian Shelters Through The Implementation of Adaptable Design Strategies. by ALSHALABI, WASEEM

“…This causes multiple and repeatable humanitarian efforts and results in increased waste, costs and time. This escalates the unwelcomed results and environmental impacts and fails in achieving population recovery, community resilience and self-reliance. …”
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VisioDECT: a novel approach to drone detection using CBAM-integrated YOLO and GELAN-E models by Md. Sakib Bin Islam (22828181)

“…Our article proposes a vision-based system for real-time drone identification and classification utilizing YOLOv5, YOLOv8, and GELAN-E deep learning models, enhanced with novel attention mechanisms and interpretability techniques. …”

From classrooms to controllers: how school closures shaped children's video gaming habits by Muna Abed Alah (14779534)

“…Average weekly screen time increased significantly from 19.7 ± 10.1 h to 31.9 ± 12.6 h during closure (<i>p</i> < 0.001). …”

Impact of Exclusive Bus Lanes on Traffic Performance in Urban Areas by Abdulwahid, Amro Riyadh

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Behavioral Modeling of RF Power Amplifiers Using Reduced Sampling Rate by Abdelnaby, Moustafa Farag

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GIS-based spatiotemporal analysis for road traffic crashes; in support of sustainable transportation Planning by Semira Mohammed (15294167)

“…<p>Road traffic crashes pose a significant challenge worldwide, necessitating increased efforts to reduce them and promote sustainable transport systems. …”

Monitoring the Athlete Match Response: Can External Load Variables Predict Post-match Acute and Residual Fatigue in Soccer? A Systematic Review with Meta-analysis by Karim Hader (2548618)

“…For every 100-m run above 5.5 m·s⁻¹, CK activity measured 24 h post-match increased by 30% and CMJPPO decreased by 0.5%. Conversely, the total distance covered did not present any evidence of a clear relationship with any fatigue-related marker at any time-point.…”

Effective non-intrusive load monitoring of buildings based on a novel multi-descriptor fusion with dimensionality reduction by Yassine Himeur (14158821)

“…This paper presents an efficient non-intrusive load monitoring framework that consists of the following main components: (i) a novel fusion of multiple time-domain features is proposed to extract appliance fingerprints; (ii) a dimensionality reduction scheme is introduced to be applied to the fused time-domain features, which relies on fuzzy-neighbors preserving analysis based QR-decomposition. …”

A heuristics for HTTP traffic identification in measuring user dissimilarity by Adeyemi R. Ikuesan (14157123)

A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition by Hanif Heidari (22467148)

“…Most improved RF versions modify attribute selection processes or combine them with other machine learning algorithms, increasing their complexity. Identifying an appropriate training dataset and determining its size remain open questions. …”

Temporal self-attention for risk prediction from electronic health records using non-stationary kernel approximation by Rawan AlSaad (14159019)

“…However, in practice, a patient’s visits are irregularly spaced over a relatively long period of time, and disease progression patterns exhibit non-stationarity. …”

Effect of sulfonated poly (ether ether ketone) on the sensitivity of polyvinylidene fluoride-based resistive humidity sensors by Shoaib Mallick (14578565)

“…As the concentration of SPEEK increases in the blend film, the hydrophilicity of the composite film also increases, which enhances the sensitivity of the sensing film. …”

Towards electric digital twin grid: Technology and framework review by Md. Mhamud Hussen Sifat (17337913)

“…Electric Digital Twin grid can perform online analysis of the grid in real-time and integrates all the past and present data and express the current grid status to the producers and consumers and also predicts the future grid status. …”

Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting by Abdelkader Baggag (16864140)

“…., its generation, propagation and mitigation, in order to increase operational efficiency and improve livability within smart cities. …”

Enhancing Healthcare Systems With Deep Reinforcement Learning: Insights Into D2D Communications and Remote Monitoring by Zina Chkirbene (16869987)

“…<p dir="ltr">The traditional healthcare system is increasingly challenged by its dependence on inperson consultations and manual monitoring, struggling with issues of scalability, the immediacy of care, and efficient resource allocation. …”

Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by 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. …”

Blockchain-Based Local Energy Market Enabling P2P Trading: An Australian Collated Case Study on Energy Users, Retailers and Utilities by Liaqat Ali (641438)

“…Moreover, the margins of both energy retailers and distribution utilities are kept unchanged or increased to some extent by the proposed trading model to incorporate them in the LEM framework effectively. …”

Cognitive Load Estimation Using a Hybrid Cluster-Based Unsupervised Machine Learning Technique by Iqbal Hassan (22155274)

“…<p dir="ltr">The increasing prevalence of non-invasive, portable Electroencephalography (EEG) sensors for neuro-physiological measurements has propelled EEG-based assessments of cognitive load (CL) into the spotlight. …”

SPARQ: A Cyber-Resilient Voltage Regulation Using Soft Q-Learning Approach for Autonomous Grid Operations by Mohamed Massaoudi (16888710)

“…<p dir="ltr">The growing integration of distributed energy resources and increased interconnectivity in cyber-physical power systems (CPPSs) have heightened their complexity. …”

Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval by Mohammed Tahar Habib Kaib (21633176)

“…For a large-sized data set, KPCA’s execution time and occupied storage space will increase drastically and the monitoring performance can also be affected in this case. …”