Towards a self-powering greenhouse using semi-transparent PV: Utilizing hybrid BESS-hydrogen energy storage system by Gholami, Mohammadreza

“…By leveraging the long-term storage capabilities of hydrogen—particularly during periods of surplus energy in summer—we aim to significantly reduce energy dependency in winter when STPV alone is insufficient. The findings reveal that the hybrid system significantly reduces ED, with reductions ranging from 61.82 % to as low as 1.56 % in winter. …”
Get full text
Get full text
Get full text

Towards a self-powering greenhouse using semi-transparent PV: Utilizing hybrid BESS-hydrogen energy storage system by Mohammadreza Gholami (17032317)

“…By leveraging the long-term storage capabilities of hydrogen—particularly during periods of surplus energy in summer—we aim to significantly reduce energy dependency in winter when STPV alone is insufficient. The findings reveal that the hybrid system significantly reduces ED, with reductions ranging from 61.82 % to as low as 1.56 % in winter. …”

Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts by ALSHAMSI, SUROUR

“…So far none addresses the use of Threat Intelligence (IT) data in Ensemble Learning algorithms to improve the detection process, nor does it work as a function of time, that is, taking into account what happens on the network in a limited time interval. …”
Get full text

Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management by Alhusin, Mohammed Omer Alamin

Get full text

Metaheuristic Optimization‐Based Sliding Mode Control With Modified Perturb and Observe for Controlling MPPT of a PV Interfaced Grid Connected System by Anupama Ganguly (22502969)

“…The suggested approach looks for every maximum point across a lengthy number of cycles to find the global maximum point after introducing (MGO‐MPb&O), and the results of the MATLAB/Simulink show that the algorithm performs well under the arbitrary changes of the physical parameters of the proposed system and ambient scenario. …”

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

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

Performance Modeling of Rooftop PV Systems in Arid Climate, a Case Study for Qatar: Impact of Soiling Losses and Albedo Using PVsyst and SAM by Sachin Jain (19161721)

“…<p dir="ltr">This study presents a comparative performance modeling and optimization framework for a 5 kWp rooftop photovoltaic (PV) system in Qatar, using two widely adopted simulation tools, PVsyst and the System Advisor Model (SAM). …”

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

“…Finally, a 3D Finite Element simulation was conducted to validate the findings and each observation resulting from the experiments. …”
Get full text

Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods by Sivakavi Naga Venkata Bramareswara Rao (15944992)

“…In addition, three distinct optimization techniques are used to find the optimum ANN training algorithm: Levenberg–Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient. …”

A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition by 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. …”

Dynamic performance evaluation and machine learning-assisted optimization of a solar-driven system integrated with PCM-based thermal energy storage: A case study approach by Haitham Osman (11737057)

“…A comprehensive techno-economic analysis is conducted, supported by a machine learning-assisted optimization framework that combines artificial neural networks with genetic algorithms. Considering optimum conditions, the system attains an exergetic efficiency of 30.13 % and a power generation of 7.24 MW, with a cost rate of 232.06 $/h and a payback period of 4.09 years. …”

A smart decentralized identifiable distributed ledger technology‐based blockchain (DIDLT‐BC) model for cloud‐IoT security by Shitharth Selvarajan (14157976)

“…The primary purpose of the Blockchain Consent Algorithm (BCA) is to find solutions for numerous unreliable nodes with varying hash values. …”

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

“…The main goals consist of creating an AI-based framework to monitor and analyze student interactions, evaluating the influence of online learning platforms on student understanding using advanced algorithms, and determining the most efficient methods for blended learning systems. …”

A Cyber-Physical System and Graph-Based Approach for Transportation Management in Smart Cities by Muhammad Mazhar Rathore (17051745)

“…To efficiently process the incoming big data streams, the proposed architecture uses the Apache GraphX tool with several parallel processing nodes, along with Spark and Hadoop that ultimately provide better performance against various state-of-the-art solutions. …”

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

A hybrid Harris Hawks optimizer for economic load dispatch problems by Al-Betar, Mohammed Azmi

“…ELD is an important problem in power systems that is tackled by finding the optimal schedule of the generation units that minimize fuel conceptions under a set of constraints. …”
Get full text

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

Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective by 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 by 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 by Alaa Abd-alrazaq (17058018)