A hybrid model to predict the pressure gradient for the liquid-liquid flow in both horizontal and inclined pipes for unknown flow patterns حسب Md Ferdous Wahid (13485799)

"…The first model (M1) determines the oil-water FP, whereas the second model (M2) predicts the oil-water PG. 1637 experimental data points for the oil-water flow in both horizontal and inclined pipes are used to develop the models. …"

Fine-grain watermarking for intellectual property protection حسب Stefano Giovanni Rizzo (18615112)

"…The core method is based on homoglyph characters substitution for latin symbols and whitespaces. …"

Optimal Trajectory and Positioning of UAVs for Small Cell HetNets: Geometrical Analysis and Reinforcement Learning Approach حسب Mohammad Taghi Dabiri (16904658)

"…Then, using geometrical analysis and deep reinforcement learning (RL) method, we propose several algorithms to find the optimal trajectory and select an optimal pattern during the trajectory. …"

CEAP حسب Abdel Wahab, Omar

"…The first challenge is related to the highly mobile nature of vehicles that complicates the processes of monitoring, buffering, and analyzing observations on these vehicles as they are continuously moving and changing their locations. …"
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Deep Neural Networks for Electromagnetic Inverse Scattering Problems in Microwave Imaging حسب Maricar, Mohammed Farook

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Multimodal feature fusion and ensemble learning for non-intrusive occupancy monitoring using smart meters حسب Sakib Mahmud (15302404)

"…We combine features from all three modes of MMF-NIOM to achieve a state-of-the-art non-intrusive occupancy classification performance of 91.5 % accuracy and 91.5 % f1-score, approximately, by an ensemble of fine-tuned classifiers on the electricity consumption & occupancy (ECO) dataset. The proposed method is sustainable, robust, adaptable to various households, and can be mass-implemented within smart meters at a much lower cost and effort compared to the traditional internet of things (IoT)-based intrusive systems.…"

Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis حسب Hassan, Ali

"…We thus propose Con-Detect—a Contribution based Detection method—for detecting adversarial attacks against NLP classifiers. …"
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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis حسب Hassan Ali (3348749)

"…We thus propose Con-Detect—a Contribution based Detection method—for detecting adversarial attacks against NLP classifiers. …"