Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain by Al Sadawi, Alia

“…An iterative dynamic scheduling algorithm (DCSDBP) was developed to address the data batching process. …”
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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data by Assaf, Ali

“…Distributed clustering algorithms, however, can fulfil this gap. They extract a classification model from the distributed objects even when they are in different sites and locations. …”
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Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction by Syed Mohammad (21075689)

“…The current study utilises state-of-the-art ML and DL models for predicting the hERG-blocking ability of chemical compounds using a dataset of 8337 molecules. …”

Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

“…The outcomes revealed that these ML algorithms can be useful in predicting ground losses during wild blueberry harvesting in the selected fields.…”

Approximation and heuristic algorithms for computing backbones in asymmetric ad-hoc networks by Abu-Khzam, Faisal N.

“…These networks have non-uniform transmission ranges and are modeled using directed disk graphs. The corresponding graph theoretic problem seeks a strongly connected dominating-absorbent set of minimum cardinality in a digraph. …”
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Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE by SHWEDEH, FATEN

“…We examined different feature selection methods and classification algorithms to find the best prediction model with the highest accuracy. …”
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A distributed genetic algorithm for deterministic and stochastic labor scheduling problems by Mansour, Nashat

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Correlation Clustering via s-Club Cluster Edge Deletion by Makarem, Norma

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Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data by Arfan Ahmed (17541309)

“…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …”

Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification by Rajendra Babu Chikkala (22330876)

“…The BRNN model, refined using the Adagrad optimization algorithm, efficiently integrates the learned features from both branches. …”

Forecasting the nearly unforecastable: why aren’t airline bookings adhering to the prediction algorithm? by Saravanan Thirumuruganathan (11038038)

“…The resulting model achieves an 89% predictive accuracy using historical data. …”

Comparative Analysis of Supervised Machine and Deep Learning Algorithms for Kyphosis Disease Detection by Alok Singh Chauhan (8264985)

Genetic Algorithm for Solving Site Layout Problem with Unequal-Size and Constrained Facilities by Zouein, P. P.

“…The layout problem considered in this paper is characterized by affinity weights used to model transportation costs between facilities and by geometric constraints that limit their relative positions on site. …”
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A quantum algorithm for evolving open quantum dynamics on quantum computing devices by Zixuan Hu (13719685)

“…<p dir="ltr">Designing quantum algorithms for simulating quantum systems has seen enormous progress, yet few studies have been done to develop quantum algorithms for open quantum dynamics despite its importance in modeling the system-environment interaction found in most realistic physical models. …”

A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models by Osama Bassam J. Rabie (21323741)

“…Moreover, the DBRF classification model is deployed to categorize the normal and attacking data flows using optimized features. …”

Optimizing Energy Consumption In Cloud Datacenters by Khan, Mueez Ahmad

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Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma by Rawan AlSaad (14159019)

“…</p><h3>Methods</h3><p dir="ltr">We use a real EHR dataset comprising 11071 patients, to evaluate and compare CD interpretations from LSTM and BiLSTM models. …”

Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition by Dabeeruddin Syed (16864260)

“…It investigates the gain in training time and the performance in terms of accuracy when clustering-based deep learning modeling is employed for STLF. A k-Medoid based algorithm is employed for clustering whereas the forecasting models are generated for different clusters of load profiles. …”

Minimizing Deadline Misses of Mobile IoT Requests in a Hybrid Fog- Cloud Computing Environment by Omer, Dalia Fatahelrahman

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Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model by Ramesh Sundar (19326046)

“…In this paper, a Dual-Deep-Network technique is described for the extraction of statistical structures from a hybrid beam forming model based on mmWave logics, as well as training logic for the network map functions. …”