Impact of Q on cost analysis diagram. by Guanghui Chen (316677)

“…However, these delivery vehicles generate carbon emissions during the process, which has an impact on environment. …”

Stations spatial distribution diagram. by Guanghui Chen (316677)

“…However, these delivery vehicles generate carbon emissions during the process, which has an impact on environment. …”

shared bikes distribution vehicle routes diagram. by Guanghui Chen (316677)

“…However, these delivery vehicles generate carbon emissions during the process, which has an impact on environment. …”

Stations location and demand. by Guanghui Chen (316677)

“…However, these delivery vehicles generate carbon emissions during the process, which has an impact on environment. …”

Data Sheet 1_Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease.docx by Hsin-Yueh Liang (20887901)

“…Our model generated results within one minute after completing ExECG.…”

pointpairs.json by Juan Wang (115708)

“…This data represents the pairwise correspondence of single reflections traced via OptiX, specifically recording the point-to-point mapping relationships generated by single reflection events in the optical simulation process, which can support the verification and optimization of specular surface reconstruction algorithms.…”

CAFD: China’s annual forest disturbance dates at 30-m spatial resolution from 1986 to 2021 by Rong Shang (17306089)

“…<p dir="ltr">This dataset comprises China's annual forest disturbance dates at a 30-meter resolution, captured within an analysis-ready data (ARD) tile system from 1986 to 2021. Generated using the modified COLD algorithm (mCOLD), it optimizes storage efficiency by converting forest disturbance dates into years and days of the year (DOY). …”

Numerical Simulation and Machine Learning-Driven Engineering of K₂GeI₆ Perovskite Solar Cells for High-Efficiency and Sustainable Photovoltaics by Md. Tarekuzzaman (21793271)

“…Key photovoltaic parameterssuch as <i>J</i>–<i>V</i> response, quantum efficiency, recombination and generation rates, capacitance, and Mott–Schottky behaviorwere thoroughly evaluated. …”

Landscape17 by Vlad Carare (22092515)

“…The NEB algorithm optimizes these interpolations of 20 images with a 50 eV/Å spring constant and convergence criterion of 10⁻² eV/Å for the maximum force component. …”

CIAHS-Data.xls by Yingchang Li (22195585)

“…This method identifies inherent natural grouping points within the data through the Jenks optimization algorithm, maximizing between-class differences while minimizing within-class differences37. …”

S1 Data - by Hongping Wei (196994)

“…Experimental results confirmed that the proposed estimation algorithm exhibits optimal performance compared to EDR estimations based on PCE and VWE, and the estimated values have smaller errors relative to the true EDR values. …”

<b>A Single-cell Transcriptomic Sequencing Dataset of Early Female and Male Chicken (</b><b><i>Gallus gallus</i></b><b>) Embryos</b> by Zhi Cao (20682218)

“…The UMAP algorithm was optimized with a neighborhood size of 20 to achieve optimal cell clustering and clear visual representation of the cell populations.…”

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. …”

Loss curves of the multi-head mechanism. by Hongping Wei (196994)

“…Experimental results confirmed that the proposed estimation algorithm exhibits optimal performance compared to EDR estimations based on PCE and VWE, and the estimated values have smaller errors relative to the true EDR values. …”

Training flow chart of the multi-head mechanism. by Hongping Wei (196994)

“…Experimental results confirmed that the proposed estimation algorithm exhibits optimal performance compared to EDR estimations based on PCE and VWE, and the estimated values have smaller errors relative to the true EDR values. …”

Introduction of turbulence field related content. by Hongping Wei (196994)

“…Experimental results confirmed that the proposed estimation algorithm exhibits optimal performance compared to EDR estimations based on PCE and VWE, and the estimated values have smaller errors relative to the true EDR values. …”

Power spectrum diagram. by Hongping Wei (196994)

“…Experimental results confirmed that the proposed estimation algorithm exhibits optimal performance compared to EDR estimations based on PCE and VWE, and the estimated values have smaller errors relative to the true EDR values. …”

Aluminum alloy industrial materials defect by Ying Han (20349093)

“…<p dir="ltr">The dataset used in this study experiment was from the preliminary competition dataset of the 2018 Guangdong Industrial Intelligent Manufacturing Big Data Intelligent Algorithm Competition organized by Tianchi Feiyue Cloud (https://tianchi.aliyun.com/competition/entrance/231682/introduction). …”

Table 2_Artificial intelligence in vaccine research and development: an umbrella review.docx by Rabie Adel El Arab (14113425)

“…</p>Results<p>Among the 27 reviews, traditional machine learning approaches—random forests, support vector machines, gradient boosting, and logistic regression—dominated tasks from antigen discovery and epitope prediction to supply‑chain optimization. Deep learning architectures, including convolutional and recurrent neural networks, generative adversarial networks, and variational autoencoders, proved instrumental in multiepitope vaccine design and adaptive clinical trial simulations. …”

Table 3_Artificial intelligence in vaccine research and development: an umbrella review.docx by Rabie Adel El Arab (14113425)

“…</p>Results<p>Among the 27 reviews, traditional machine learning approaches—random forests, support vector machines, gradient boosting, and logistic regression—dominated tasks from antigen discovery and epitope prediction to supply‑chain optimization. Deep learning architectures, including convolutional and recurrent neural networks, generative adversarial networks, and variational autoencoders, proved instrumental in multiepitope vaccine design and adaptive clinical trial simulations. …”