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

“…The actions and rewards for the proposed algorithm are selected carefully to guide the agent to its objective. …”
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Local convexity preserving rational cubic spline curves by Sarfraz, M.

“…An algorithm is presented which constructs a curve by interpolating the given data points. …”
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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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A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass by Uzma Nawaz (21980708)

“…By synthesizing findings across various data sources and model architectures, we offer critical insights into the selection of context-aware algorithms and identify key research gaps, an essential step for advancing the reliability and applicability of AI-driven seagrass conservation efforts.…”

Improving Rule Set Based Software Quality Prediction by Azar, Danielle

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Estimating Bridge Deterioration Age Using Artificial Neural Networks by AL HUSSEIN, ASEEL

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A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks by Sakib Mahmud (15302404)

“…Reported benefits include energy savings, emissions reduction, and improved operational efficiency, although gains are often contingent on data quality, reward design, and benchmark selection. …”

A Machine Learning Approach to Predicting Diabetes Complications by Jian, Yazan Khaled

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Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features by Mariam Bahameish (19255789)

“…To account for limitations associated with small datasets, robust strategies were implemented based on methodological recommendations for ML with a limited dataset, including data segmentation, feature selection, and model evaluation. …”

A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security by S. Shitharth (12017480)

“…Then, the Conjugate Self-Organizing Migration (CSOM) optimization algorithm is deployed to select the most relevant features to train the classifier, which also supports increased detection accuracy. …”

Systematic review and meta-analysis of performance of wearable artificial intelligence in detecting and predicting depression by Alaa Abd-Alrazaq (17430900)

“…The search sources in this systematic review were 8 electronic databases. Study selection, data extraction, and risk of bias assessment were carried out by two reviewers independently. …”

Design and development of an embedded controller for roboticmanipulator by Bakhashwain, J.M.

“…Mohseni's Proposed Algorithm, MPA, has been incorporated into the embedded controller to reduce the computational efforts and to obtain a close-to-optimal control law. …”
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Edge Caching in Fog-Based Sensor Networks through Deep Learning-Associated Quantum Computing Framework by Tayyabah Hasan (18427887)

“…After selecting the most appropriate lattice map (32 × 32) in 750,000 iterations using SOMs, the data points below the dark blue region are mapped onto the data frame to get the videos. …”

Estimation of power grid topology parameters through pilot signals by Hargossian, H.

“…The measured data is evaluated through correlation, and a weighed least-square algorithm, applied to the network’s dynamic model, estimates those unknown parameters and provides an accurate snapshot of the power network topology. …”
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Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying by Tekli, Joe

“…We use a semantic-aware inverted index to allow semantic-aware search, result selection, and result ranking functionality. The semantically augmented XML data tree is processed for structural node clustering, based on semantic query concepts (i.e., key-concepts), in order to identify and rank candidate answer sub-trees containing related occurrences of query key-concepts. …”
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FPGA-Based Network Traffic Classification Using Machine Learning by Elnawawy, Mohammed

“…The results of the conducted experiments indicate that random forest outperforms other algorithms achieving a maximum accuracy of 98.5% and an F-score of 0.932. …”
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Structural similarity evaluation between XML documents and DTDs by Tekli, J.

“…Nonetheless, several operations based on the structure of XML data have not yet received strong attention. Among these is the process of matching XML documents with XML grammars, useful in various applications such as documents classification, retrieval and selective dissemination of information. …”
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Plant disease detection using drones in precision agriculture by Ruben Chin (17725986)

“…Color-infrared (CIR) images are the most preferred data used and field images are the main focus. The machine learning algorithm applied most is convolutional neural network (CNN). …”

Development of a deep learning-based group contribution framework for targeted design of ionic liquids by Sadah Mohammed (18192859)

“…Finally, the algorithm is employed in a CO₂ capture case study to generate and select the best-performing novel ILs, which exhibit behavior consistent with established ILs in the literature.…”

A hybrid model to predict the pressure gradient for the liquid-liquid flow in both horizontal and inclined pipes for unknown flow patterns by Md Ferdous Wahid (13485799)

“…Statistical analysis showed that the selected features for liquids' and pipe's properties using the BGWOPSO algorithm were adequate to attain superior performance for both models. …”