A hybrid model to predict the pressure gradient for the liquid-liquid flow in both horizontal and inclined pipes for unknown flow patterns by 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. …”

Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms by Md Ferdous Wahid (13485799)

“…This study aims to develop five robust machine learning (ML) algorithms and their fusions for a wide range of flow patterns (FP) regimes. …”

Public health utility of cause of death data: applying empirical algorithms to improve data quality by Sarah Charlotte Johnson (9715415)

Face Flow: Constrained Optical Flow Framework for Faces by Alkaddour, Muhannad

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Assessment of calcified aortic valve leaflet deformations and blood flow dynamics using fluid-structure interaction modeling by Armin, Amindari

“…However, implementation of this approach is difficult using custom built codes and algorithms. In this paper, we present an FSI modeling methodology for aortic valve hemodynamics using a commercial modeling software, ANSYS. …”
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Assessment of calcified aortic valve leaflet deformations and blood flow dynamics using fluid-structure interaction modeling by Amindari, Armin

“…However, implementation of this approach is difficult using custom built codes and algorithms. In this paper, we present an FSI modeling methodology for aortic valve hemodynamics using a commercial modeling software, ANSYS. …”
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Forward simulation of three-dimensional advection-diffusion using a fundamental solution for a linear flow by Wehbe, Rawan

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Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques by Hassan, Mahitab Alaaeldin

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Large language models for code completion: A systematic literature review by Rasha Ahmad Husein (19744756)

“…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”

Enhanced Inverse Model Predictive Control for EV Chargers: Solution for Rectifier-Side by Ali Sharida (17947847)

Energy-Aware QoS Uplink Scheduling for UGS Traffic Flows in WiMAX Networks by Noorani, Sanabel

“…We used Voice-over-IP (VoIP) traffic connection models for UGS traffic flows to simulate and validate algorithm. …”
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Adaptive temperature control of a reverse flow process by using reinforcement learning approach by A. Binid (22046054)

“…Additionally, a second algorithm is presented to enhance the implementability of the reinforcement learning algorithm from a practical perspective. …”

Auto Takeoff and Precision Landing using Integrated GPS/INS/Optical Flow Solution by Al-Sharman, Mohammad Khaled Salameh

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Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach by Sarif, Bambang

“…Multiple-Valued Logic (MVL) has been used in the design of a number of logic systems, including memory, multi-level data communication coding, and a number of special purpose digital processors. …”
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ON-LINE IDENTIFICATION AND CONTROL THROUGH SERIES CONVERTER VOLTAGE OF A UNIFIED POWER FLOW CONTROLLER by Rahim, A.H.M.A

“…The plant parameters are identified through a regressive least square algorithm and the stabilizing control is derived through a pole-shifting technique using the adaptive plant model. …”
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Block constrained pressure residual preconditioning for two-phase flow in porous media by mixed hybrid finite elements by Stefano Nardean (14151900)

“…<p dir="ltr">This work proposes an original preconditioner that couples the Constrained Pressure Residual (CPR) method with block preconditioning for the efficient solution of the linearized systems of equations arising from fully implicit multiphase flow models. This preconditioner, denoted as Block CPR (BCPR), is specifically designed for Lagrange multipliers-based flow models, such as those generated by Mixed Hybrid Finite Element (MHFE) approximations. …”

Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition by Dabeeruddin Syed (16864260)

“…It investigates the gain in training time and the performance in terms of accuracy when clustering-based deep learning modeling is employed for STLF. A k-Medoid based algorithm is employed for clustering whereas the forecasting models are generated for different clusters of load profiles. …”

Optimal Planning of Distributed Generators and Shunt Capacitors in Isolated Microgrids With Nonlinear Loads by Yazdavar, Ameen H.

“…The intermittent natures of loads and renewable DGs are modelled probabilistically. The effectiveness of the proposed planning approach has been validated using the PG&E 69-bus system, and the followings are observed: 1) the significance of applying suitable fundamental-power-flow and harmonic-power-flow algorithms for isolated microgrids, and 2) the possibility of avoiding a severe voltage distortion by utilizing an appropriate planning method and only small increase in the cost.…”
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Optimized FPGA Implementation of PWAM-Based Control of Three—Phase Nine—Level Quasi Impedance Source Inverter by Syed Rahman (569240)

“…Since, PWAM control algorithm is more complex than PSCPWM, FPGA based implementation for PWAM control is discussed. …”

Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands by Peng, Wang

“…In order to mitigate the charging effects of electric vehicles on the hybrid AC–DC microgrid operation, some remotely switches are considered in the system which make it possible for changing the topology and power flow way. In order to model the uncertainty effects, a data-driven framework based on point estimate method and support vector machine is developed. …”
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