VHDRA: A Vertical and Horizontal Intelligent Dataset Reduction Approach for Cyber-Physical Power Aware Intrusion Detection Systems by Hisham A. Kholidy (18891802)

“…VHDRA provides the following functionalities: (1) it vertically reduces the dataset features by selecting the most significant features and by reducing the NNGE’s hyperrectangles. (2) It horizontally reduces the size of data while preserving original key events and patterns within the datasets using an approach called STEM, State Tracking and Extraction Method. …”

The distribution of toxic sources in Louisiana by Djoundourian, Salpie Sarkis

“…The results reveal that income levels in communities that host toxic sources are consistently and significantly lower than the state averages. …”
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Renewable Energy, Coal as a Baseload Power Source, and Greenhouse Gas Emissions: Evidence from U.S. State-Level Data by Squalli, Jay

“…After accounting for the role of coal as a baseload power source, an increase in the share of renewable energy is estimated to mitigate N2O emissions at the U.S. state level only if states individually decrease their share of coal use to levels below 41.47%. …”
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Ammonia Production Plants—A Review by Abdulkarem I. Amhamed (17017737)

“…However, regarding carbon reduction in the ammonia production process, it is clear that the effort is less significant when compared to the global scientific and industrial progress in other areas.…”

Zooming Into Clarity: Image Denoising Through Innovative Autoencoder Architectures by Khatereh Mohammadi (17309662)

“…Empirical evaluations on diverse datasets, including CelebA and Autism Face data, demonstrate significant improvements in the Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM). …”

Assessing the Electricity Production Capacities of Emerging Markets for the Sustainable Investments by Tamer Aksoy (17947802)

An End-to-End Deep Learning Framework for Real-Time Denoising of Heart Sounds for Cardiac Disease Detection in Unseen Noise by Shams Nafisa Ali (17949191)

An Optimized Feature Selection Technique in Diversified Natural Scene Text for Classification Using Genetic Algorithm by Ghulam Jillani Ansari (16896342)

Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk by Mohamed Chaouch (17983846)

“…<p dir="ltr">This paper introduces novel nonparametric supervised learning techniques for classifying massive datasets, addressing key limitations of existing methods in Big and Streaming Data framework. …”

The Effect of HuArgI (Co)-PEG5000 on The Migration of Ovarian Cancer by El Mais, Nour

“…In this study, we hypothesized that HuArgI (Co)- PEG5000 can decrease the migration of ovarian cancer cells. Our results show a decrease in the migratory rate of the cells and their rate in wound closure. …”
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Assessment of the use of dolomite for the recovery of ammonia from field landfill leachate. (c2019) by Rayshouni, Hussein

“…However, using dolomite calcined at 950 °C with the same phosphate source showed a significant decrease in removal efficiency to 44%, while using dolomite calcined at 750 °C (under continuous CO2 injection) resulted in a removal efficiency of 37%. …”
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Semi-supervised Clustering of Facial Expressions by Jalal, Ahsan

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An Effective Fault Diagnosis Technique for Wind Energy Conversion Systems Based on an Improved Particle Swarm Optimization by Majdi Mansouri (16869885)

“…In addition, the proposed reduced PSO-NN (RPSO-NN) technique not only enhances the results in terms of accuracy but also provides a significant reduction in computation time and storage cost by reducing the size of the training dataset and removing irrelevant and redundant samples. …”

A Novel Features-Based Multivariate Gaussian Distribution Method for the Fraudulent Consumers Detection in the Power Utilities of Developing Countries by Ammar Yousaf Kharal (16891470)

“…The adaptation of smart metering technology has enabled much of the developed world to significantly reduce their NTLs. Also, the recent advancements in machine learning and data analytics have enabled a further reduction in these losses. …”

Modified Aquila Optimizer Feature Selection Approach and Support Vector Machine Classifier for Intrusion Detection System by Abualigah, Laith

“…Our comparative analysis reveals the superiority of the proposed method, with standout results in terms of feature reduction, detection accuracy, and false alarm mitigation, yielding significant improvements of 11%, 98.76%, and 0.02%, respectively.…”
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Orthodontic camouflage versus orthodontic-orthognathic surgical treatment in borderline class III malocclusion: a systematic review by Maged S. Alhammadi (14150757)

“…Regarding the vertical jaw relation, one study reported a significant decrease in mandibular plane inclination in OC and a significant increase in OOS. …”

Particle size impact on pyrolysis of multi-biomass: a solid-state reaction modeling study by Sabah Mariyam (14150859)

“…<p dir="ltr">yrolysis has gained significant attention due to its generation of value-added products from waste feeds in an environmentally friendly manner. …”

Traffic Transformer: Transformer-based framework for temporal traffic accident prediction by Mansoor G. Al-Thani (19237204)

“…Extensive comparative experiments conducted on a real-world dataset from Qatar demonstrate that our proposed Traffic Transformer model significantly outperforms existing mainstream time series forecasting models across all evaluation metrics and forecast horizons. …”

Addressing Challenges of Distance Learning in the Pandemic with Edge Intelligence Enabled Multicast and Caching Solution by Kashif Bilal (16896357)

“…Multicasting a video session for distance learning significantly lowers the burden on core and Radio Access Networks (RAN) as demonstrated by evaluation over a real-world dataset. …”

Exploring Effects of Mental Stress with Data Augmentation and Classification Using fNIRS by Khan, Malik Nasir Afzal

“…These findings illustrate the ability to detect changes in brain states with high accuracy using fNIRS, underline the need for larger datasets, and demonstrate that data augmentation can significantly help when data are scarce in the case of brain signals.…”
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