Model-Based Clustering of Categorical Data Based on the Hamming Distance by Raffaele Argiento (647076)

Computational Micromechanics and Machine Learning-Informed Design of Composite Carbon Fiber-Based Structural Battery for Multifunctional Performance Prediction by Mohamad A. Raja (19640297)

“…To preform accurate forecasts on energy storage, a data-driven machine learning approach based on artificial neural networks (ANN) was optimized via a Bayesian optimization algorithm to predict the structural battery’s future capacity. …”

Pareto optimal front result of MOCOA. by Hang Zhao (143592)

“…A deep VMD-attention network based on MOCOA was developed for ECG signal classification. …”

Confusion matrix. by Hang Zhao (143592)

“…A deep VMD-attention network based on MOCOA was developed for ECG signal classification. …”

Action potential of sample points in model 1. by Hang Zhao (143592)

“…A deep VMD-attention network based on MOCOA was developed for ECG signal classification. …”

Performance validation on the MIT-BIH database. by Hang Zhao (143592)

“…A deep VMD-attention network based on MOCOA was developed for ECG signal classification. …”

Exponentially attenuated sinusoidal function. by Hang Zhao (143592)

“…A deep VMD-attention network based on MOCOA was developed for ECG signal classification. …”

Performance comparison with other papers. by Hang Zhao (143592)

“…A deep VMD-attention network based on MOCOA was developed for ECG signal classification. …”

Action potential of sample points in model 2. by Hang Zhao (143592)

“…A deep VMD-attention network based on MOCOA was developed for ECG signal classification. …”

Action potential of sample points in model 0. by Hang Zhao (143592)

“…A deep VMD-attention network based on MOCOA was developed for ECG signal classification. …”

Yellow River Basin Industrial Base Spatio-temporal Monitoring and Impact Assessment Dataset by Libing Wang (21723566)

“…The dataset aggregates data elements and core algorithm codes that underpin the key research stages of the paper, with a focus on demonstrating and reproducing the innovative methodologies employed, rather than directly sharing sensitive raw data or precise measurement values.…”

data and code by PENGCHENG LIU (20680641)

“…</p><p dir="ltr"> <b>Description of development environment: </b>this algorithm model is mainly based on ArcGIS Engine provided by ESRI company in the United States Net framework.…”

Machine Learning-Assisted Accelerated Research of Energy Storage Properties of BaTiO₃–BiMeO₃ Ceramics by Jian Liu (33711)

“…Three distinct feature vector spaces were constructed based on the physicochemical characteristics of constituent elements, related property information, and sintering process parameters. …”

Collaborative Research: SCIPE: Interdisciplinary Research Support Community for Artificial Intelligence and Data Sciences by Sanmukh Kuppannagari (21798863)

“…<br><br>To achieve 10x-100x reduction in DNN energy consumption, a holistic approach is pursued, which encompasses: (1) new circuit designs that leverage emerging CMOS+X technologies; (2) a novel near-memory architecture in which processing elements are seamlessly integrated with traditional Dynamic RAM (DRAM); (3) novel 3D-matrix-based per-layer DNN computations and data-layout optimizations for kernel weights; and (4) algorithms and hardware/software co-design tailored for near-real-time DNN-based signal classification in next-generation wireless systems. …”

Supporting data for Histone crotonylation is a novel epigenetic regulation and a therapeutic vulnerability for liver cancer treatment by Qidong Li (9069932)

Data Sheet 1_Image-assisted textural analysis of plagioclase crystals in volcanic rocks: an application to lavas erupted on 2021 at Pacaya volcano, Guatemala.docx by Roberto Visalli (8152251)

“…The processing strategy is based on the sequential application of the Principal Components Analysis and the supervised Maximum Likelihood Classification algorithms that allow us distinguishing among rock constituents (mineral phases, vesicles and glasses), quantifying their modal abundances, and identifying textural and chemical variations in a simplified and quick process. …”

Supporting files for thesis "Deep-learning-based Morphological Modelling: Case Study in Soft Robot Control, Shape Sensing and Deformation" by Yingqi Li (9151304)

“…<p dir="ltr">The main focus of this thesis is to develop appropriate morphology modelling strategies for typical deformable structures by integrating physics-aligned prior knowledge and deep learning algorithms. …”

<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) by Erola Fenollosa (20977421)

“…</li><li>The dataframe of extracted colour features from all leaf images and lab variables (ecophysiological predictors and variables to be predicted)</li><li>Set of scripts used for image pre-processing, features extraction, data analytsis, visualization and Machine learning algorithms training, using ImageJ, R and Python.…”

Additional file 1 of The origin and evolution of cultivated rice and genomic signatures of heterosis for yield traits in super-hybrid rice by Yiyong Zhao (21466062)

“…This analysis is based on hybrid data derived from 90,113 SNP loci, where P1 and P2 denote the maternal and paternal parents, respectively, and Gamma represents the fraction of genetic contribution from P1 to the hybrid. …”

Table 1_Image-assisted textural analysis of plagioclase crystals in volcanic rocks: an application to lavas erupted on 2021 at Pacaya volcano, Guatemala.xlsx by Roberto Visalli (8152251)

“…The processing strategy is based on the sequential application of the Principal Components Analysis and the supervised Maximum Likelihood Classification algorithms that allow us distinguishing among rock constituents (mineral phases, vesicles and glasses), quantifying their modal abundances, and identifying textural and chemical variations in a simplified and quick process. …”