Solar power forecasting beneath diverse weather conditions using GD and LM-artificial neural networks by Sharma, Neetan

“…A case study has been done in the Peer Panjal region. The data collected for four months with various parameters have been applied randomly as input data using GD and LM type of artificial neural network compared to actual solar energy data. …”
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Digital Image Watermarking Using Balanced Multiwavelets by Ghouti, L.

“…This increase could also be exploited as a side channel for embedding watermark synchronization recovery data. …”
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Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices by Neder Karmous (19743430)

“…It had an impressive accuracy of 99.99%, and it could mitigate DDoS attacks in less than 3 s. We conducted a comparative analysis of various models and algorithms used in the related works. …”

A Full-System Approach of the Elastohydrodynamic Line/Point Contact Problem by Habchi, Wassim

“…The use of the finite element method allows the use of variable unstructured meshing and different types of elements within the same model which leads to a reduced size of the problem. …”
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Positive Unlabelled Learning to Recognize Dishes as Named Entity by TAREK, AIMAN

“…The results show how we can automate entity recognition process, using dictionaries and machine learning techniques and achieve an acceptable accuracy of 67% and boost the newly discovered entities by around 15% using Positive Unlabelled learning over automatically build lookup table. This research has the potential to be extended to other topics other than food and dish names, also it acts as a framework and algorithm independent.…”
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Downlink channel estimation for IMT-DS by Faisal, S.

“…The proposed schemes are assessed over the IMT-DS system by performing simulations…”
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Query acceleration in distributed database systems by Haraty, Ramzi A.

“…Query optimization strategies aim to minimize the cost of transferring data across networks. Many techniques and algorithms have been proposed to optimize queries. …”
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An Infrastructure-Assisted Workload Scheduling for Computational Resources Exploitation in the Fog-Enabled Vehicular Network by Sorkhoh, Ibrahim

“…Among these parameters are the variability of vehicles availability and their computational power, the individual tasks’ weighted priorities and their deadlines, the tasks required computational power as well as the required data to upload/download. This article proposes an infrastructure-assisted task scheduling scheme where the roadside unit receives computational tasks from different sources and schedules these tasks over a computationally capable vehicle residing within the roadside unit’s range. …”
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Lagrangian tracking in stochastic fields with application to an ensemble of velocity fields in the Red Sea by Issa, Leila

“…Lagrangian tracking of passive tracers in a stochastic velocity field within a sequential ensemble data assimilation framework is challenging due to the exponential growth in the number of particles. …”
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MoveSchedule by Zouein, Pierette

“…Four different space profiles describe variations in resource space needs over time. The timing of these needs is inferred from the activity schedule. …”
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A novel few shot learning derived architecture for long-term HbA1c prediction by Marwa Qaraqe (10135172)

“…For the first time in the literature, this work proposes a novel FSL-derived algorithm for the long-term prediction of clinical HbA1c measures. …”

Isolating Physical Replacement of Identical IoT Devices Using Machine and Deep Learning Approaches by Mohammad, Areej Osama

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An Infrastructure-Assisted Crowdsensing Approach for On-Demand Traffic Condition Estimation by Abdul Rahman, Sawsan

“…However, the current solutions proposed for the use of crowdsensing for the collection of traffic related data adopt an opportunistic continuous sensing approach, which entails high resource consumption on the server and mobile device side, a high communication overhead, while offering little control of the users over the sensing activity. …”
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A survey and comparison of wormhole routing techniques in a meshnetworks by Al-Tawil, K.M.

“…They consist of many processing nodes that interact by sending messages (containing both data and synchronization information) over a communication link, between nodes. …”
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Investigation of Forming a Framework to shortlist contractors in the tendering phase by DABASH, MOHANNAD SALAH

“…The limitation of this research is that to use the framework to its full extent, it needs a huge database that includes data from numerous previous projects to be able to accurately predict the success rate of the upcoming project; however, if it could be regulated through governmental institutes then the database can be quickly collected within a relatively short period of time.…”
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Decomposition-based wind power forecasting models and their boundary issue: An in-depth review and comprehensive discussion on potential solutions by 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. …”

Communications in electronic textile systems by Nakad, Z.

“…Abstract- Electronic textiles (e-textiles) are emerging as a novel method for constructing electronic systems in wearable and large area applications. …”
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Design of A Theoretical Framework For A Real-Time Fire Evacuation Guidance System by Abougharib, Arwa

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The Effectiveness of Supervised Machine Learning in Screening and Diagnosing Voice Disorders: Systematic Review and Meta-analysis by Ghada Al-Hussain (18295426)

“…Machine learning (ML) algorithms have been used as an objective tool in screening or diagnosing voice disorders. …”

Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends by Abdellatif M. Sadeq (16931841)

“…In addition, the possible minimum and maximum values of responses at the corresponding operating parameters are found using a genetic algorithm (GA) approach. Model 1 could capture the computational fluid dynamics (CFD) outputs with high precision at different flame radiuses and time instants with a maximum absolute error percentage of 5.46%. …”