Active distribution network type identification method of high proportion new energy power system based on source-load matching by Qinlin, Shi

“…Here, we report an active distribution network type identification method based on source-load matching. Firstly, the typical daily output scenarios of DG are extracted by clustering method, and the generalized load curve model is solved by the optimization algorithm to obtain the source load operation data; Secondly, calculate the source-load matching indicators (including matching performance, matching degree, and matching rate) according to the source load data of each region, and identify the distribution network type according to the range of the index values; Finally, several indicators are introduced to quantify the characteristics of different types of distribution networks. …”
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Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods by Sivakavi Naga Venkata Bramareswara Rao (15944992)

“…From the results, it is found that the Levenberg–Marquardt optimization algorithm-based ANN model gives the best electrical load forecasting results.…”

An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting by Mohamed Massaoudi (16888710)

“…The performance of the proposed PVPF technique was investigated using two real datasets with different scales and locations. The comparative analysis of the NARX-LSTM with twelve existing benchmarks confirms its superiority in terms of accuracy measures. …”

Blue collar laborers’ travel pattern recognition: Machine learning classifier approach by Aya Hasan Alkhereibi (17151070)

“…Raw data preprocessing and outliers detection and filtering algorithms were applied at the first stage of the analysis, and consequently, an activity-based travel matrix was developed for each household. …”

A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security by S. Shitharth (12017480)

“…Moreover, the Reconciliate Multi-Agent Markov Learning (RMML) based classification algorithm is used to predict the intrusion with its appropriate classes. …”

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

“…Further, As the quality of received signals differs at different sensing points as a result of the surface conditions of the specimen, the Self Adaptive Smart Algorithm (SASA) method was adopted to filter out the noise and accurately pinpoint the defect reflected wave packet which ultimately aids in better detection and localization. …”
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Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review by Mohamed Sadok Massaoudi (17984071)

“…This review aims to support research in this area of DRL algorithms to embrace PSS against unseen faults and different PS topologies.…”

Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”

A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti (21593819)

“…The paper uses naive Bayes, Support Vector Machine (SVM), and Random Forest (RF) as classifiers after careful investigation. Three different publicly available datasets have been used based on the age group to create the best predicting model for each case. …”

Detection of statistically significant network changes in complex biological networks by Raghvendra Mall (581171)

“…Several procedures have been recently proposed to detect sub-network differences in pairwise labeled weighted networks.</p><h3>Methods</h3><p dir="ltr">In this paper, we propose an improvement over the state-of-the-art based on the Generalized Hamming Distance adopted for evaluating the topological difference between two networks and estimating its statistical significance. …”

Thermal convection of fluid in fractured media by Sfeir, Abdallah

“…Including this phenomenon in a modelling process led us to propose a development of the UDEC code. The computational algorithm is based on the differences between the rates of convective and conductive heat transfers. …”
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Accurate multiple network alignment through context-sensitive random walk by Hyundoo Jeong (3840013)

“…Until now, a number of network alignment algorithms have been proposed based on different formulations and approaches, many of them focusing on pairwise alignment. …”

Localization of Damages in Plain And Riveted Aluminium Specimens using Lamb Waves by S. Andhale, Yogesh

“…The TOA data of the wave reflected from the damage is used in the two arrival time difference and astroid algorithms to locate the damage in an enclosed area. …”
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Optimizing clopidogrel dose response by Saab, Yolande B.

“…Clopidogrel adjusted dose was computed based on area under the curve ratios for different CYP2C19 genotypes when a drug interacting with CYP2C19 is added to clopidogrel treatment. …”
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A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method by Shahid Rahman (16904613)

“…The LSB substitution method can minimize the error rate in embedding process and can achieve greater reliability in criteria, using novel algorithm based on value difference. In this paper, we proposed a novel technique in steganography within the digital images such is RGB, Gray Scale, Texture, Aerial images to achieve higher security, imperceptibility, capacity, and robustness as compared with existing methods. …”

Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP by Abdelhafez, Nada

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Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series by Lasfer, Assia

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Heat rate curve approximation for power plants without data measuring devices by Poullikkas, Andreas

“…In this work, a numerical method, based on the one-dimensional finite difference technique, is proposed for the approximation of the heat rate curve, which can be applied for power plants in which no data acquisition is available. …”
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Mobile Robot Trajectory Tracking Using Neural Networks by Mohareri, Omid

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Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques by Fares, Samar

“…The first method uses an offline technique based on a global optimizer called the CMA-ES algorithm and the second one uses LSTM in its different forms to learn the online adjustment of the fusion weights between the two tracks. …”
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