A comparative analysis to forecast carbon dioxide emissions حسب Md. Omer Faruque (17545671)

"…Based on multivariate time series prediction, four deep learning algorithms are analyzed in this work, those are convolution neural network (CNN), CNN long short-term memory (CNN–LSTM), long short-term memory (LSTM), and dense neural network (DNN). …"

Decomposition-based wind power forecasting models and their boundary issue: An in-depth review and comprehensive discussion on potential solutions حسب Yinsong Chen (16685508)

"…These methods generally disaggregate the original time series data into sub-time-series with better stationarity, and then the target data is predicted based on the sub-series. …"

Generative AI revolution in cybersecurity: a comprehensive review of threat intelligence and operations حسب Mueen Uddin (4903510)

"…<p dir="ltr">Cyber threats are increasingly frequent in today’s world, posing challenges for organizations and individuals to protect their data from cybercriminals. On the other hand, Generative Artificial Intelligence (GAI) technology offers an efficient way to automatically address these issues with the help of AI models and algorithms. …"

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

"…The novel contribution of this work is to incorporate the operations of Rabin digital data signature generation, DIDLT‐based blockchain construction, and BCA algorithms for ensuring overall data security in IoT networks. …"

Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort حسب Sergio Márquez-Sánchez (19437985)

"…Moreover, the prevalent cloud-based nature of these systems introduces elevated cybersecurity risks and substantial data transmission overheads. In response to these challenges, this article introduces a cutting-edge edge computing architecture grounded in virtual organizations, federated learning, and deep reinforcement learning algorithms, tailored to optimize energy consumption within buildings/homes and facilitate demand response. …"

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

Fuzzy Logic Based Patients' Monitoring System حسب Al-Dmour, Jumana

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Predicting Plasma Vitamin C Using Machine Learning حسب Daniel Kirk (17302798)

"…The low R-squared scores obtained by the models are likely to be due to the low resolution of the NHANES data, particularly the dietary 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 حسب Sachin Jain (19161721)

"…To overcome these limitations, the Humboldt State University (HSU) soiling model was calibrated using field measurements from a DustIQ sensor, and its parameters, rainfall cleaning threshold and particulate deposition velocity were optimized through a Differential Evolution algorithm. …"

LungVision: X-ray Imagery Classification for On-Edge Diagnosis Applications حسب Aldamani, Raghad

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Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts حسب 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. …"
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Improving MRI Resolution: A Cycle Consistent Generative Adversarial Network-Based Approach for 3T to 7T Translation حسب Zakaria Shams Siam (22048001)

Identification of the Uncertainty Structure to Estimate the Acoustic Release of Chemotherapeutics From Polymeric Micelles حسب Wadi, Ali

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Load Partitioning for Matrix-Matrix Multiplication on a Cluster of CPUGPU Nodes Using the Divisible Load Paradigm حسب Elhiny, Lamees

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HVAC system attack detection dataset حسب Mariam Elnour (14147790)

"…It aims to promote and support the research in the field of cybersecurity of HVAC systems in smart buildings by facilitating the validation of attack detection and mitigation strategies, benchmarking the performance of different data-driven algorithms, and studying the impact of attacks on the HVAC system.…"

Impacts of climate change on the global spread and habitat suitability of <i>Coxiella burnetii</i>: Future projections and public health implications حسب Abdallah Falah Mohammad Aldwekat (22457821)

"…In interpreting these results, it is important to consider modelling uncertainties, including assumptions and data limitations.…"

Toward automatic motivator selection for autism behavior intervention therapy حسب Siyam, Nur

"…The states, actions and rewards design consider the factors that impact the efectiveness of a motivator based on applied behavior analysis as well as learners’ individual preferences. We use a Q-learning algorithm to solve the modeled problem. Our proposed solution is then implemented as a mobile application developed for special education plans coordination. …"
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Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model حسب Ramesh Sundar (19326046)

"…The proposed approach of DDN is trained with proper data sequences used for communication and the training phase is conducted with the norms of numerous channel variants. …"

Study of the Impact of Land Use and Land Cover (LULC) Changes on local climate in Six Mega Global Cities in the 21st Century حسب Sabobeh, Lara Ali

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Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information حسب M. Ghoniem, Rania

"…For classifying unimodal data of either speech or EEG, a hybrid fuzzy c-means-genetic algorithm-neural network model is proposed, where its fitness function finds the optimal fuzzy cluster number reducing the classification error. …"
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