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

“…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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Automated skills assessment in open surgery: A scoping review by Hawa Hamza (17707224)

“…In this scoping review, we present the open surgeries and clinical settings where AI-based skill assessment has been applied, the kind of surgical data acquired for the AI-based algorithms, and the types of AI-based models used for automated skills assessment. …”

Predicting COVID-19 cases using bidirectional LSTM on multivariate time series by Ahmed Ben Said (14158926)

“…Unlike other forecasting techniques, our proposed approach first groups the countries having similar demographic and socioeconomic aspects and health sector indicators using K-means clustering algorithm. The cumulative case data of the clustered countries enriched with data related to the lockdown measures are fed to the bidirectional LSTM to train the forecasting model. …”

Using Data Mining in CRM to Understand the Insurance Market by Qadadeh, Wafa

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Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks by Daou, Leonardo

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MDPF: Minimum Distance Packet Forwarding for Search Applications in Mobile Ad Hoc Networks by Artail, Hassan

“…This paper introduces a message forwarding algorithm for search applications within mobile ad hoc networks that is based on the concept of selecting the nearest node from a set of designated nodes. …”
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Optimizing ADWIN for Steady Streams by Moharram, Hassan

“…We evaluate our technique on the same data sets above and new datasets with fewer drifts. …”
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Scan Test Cost and Power Reduction Through Systematic Scan Reconfiguration by Al-Yamani, A.

“…The architecture and the algorithm were applied to both single stuck as well as transition fault test sets…”
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Benchmarking Concept Drift Detectors for Online Machine Learning by Mahgoub, Mahmoud

“…The main task is to detect changes in data distribution that might cause changes in the decision bound aries for a classification algorithm. …”
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High-order parametrization of the hypergeometric-Meijer approximants by Abouzeid M. Shalaby (16329062)

“…We also show that such extension of the hypergeometric resummation algorithm is able to employ non-perturbative information like strong-coupling and large-order asymptotic data which are always used to accelerate the convergence. …”

A Comprehensive Overview of the COVID-19 Literature: Machine Learning–Based Bibliometric Analysis by Alaa Abd-Alrazaq (17430900)

“…Specifically, we used a clustering algorithm to group published articles based on the similarity of their abstracts to identify research hotspots and current research directions. …”

Improving INS/GPS Integration for Mobile Robotics Applications by AbuHashim, Tariq Salman

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Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”

Phased Array Technique for Brain Source Localization by Zarghami, Tahereh

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Deep Reinforcement Learning for Resource Constrained HLS Scheduling by Makhoul, Rim

“…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …”
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Use of Data Mining Techniques to Detect Fraud in Procurement Sector by AL HAMMADI, SUMAYYA ABDULLA

“…The method used in this research is a classification of models and algorithms used in data mining. All techniques also will be studied; they include clustering, tracking patterns, classifications and outlier detection. …”
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Teachers' Perceptions of the Role of Artificial Intelligence in Facilitating Inclusive Practices for Students with Special Educational Needs and Disabilities: A Case Study in a Pri... by BACHIR, HIBAH AHMAD

“…Findings referred these barriers to limited teacher training, technological accessibility, and data privacy concerns, as well as ethical biases in AI algorithms. …”
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Analysis of Using Machine Learning to Enhance the Efficiency of Facilities Management in the UAE by ULLAH, SAAD

“…This study addresses these issues by Implementing Machine Learning (ML) algorithms using data from Building Management Systems (BMS) and FM maintenance reports, focussing on predictive maintenance for Fresh Air Handling Units. …”
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A modified coronavirus herd immunity optimizer for capacitated vehicle routing problem by Abu Zitar, Raed

“…Moreover, the results achieved by modified CHIOare compared against the results of other 13 well-regarded algorithms. For the first data set, the modifiedCHIO is able to gain the same results as the other comparative methods in two out of ten instances andacceptable results in the rest. …”
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Regression Testing of Database Applications by Haraty, Ramzi A.

“…In phase 2, further reduction in the regression test cases is performed by using reduction algorithms. We present two such algorithms. The Graph Walk algorithm walks through the control flow graph of database modules and selects a safe set of test cases to retest. …”
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