Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level by Giovanni Nattino (561797)

“…We fill the gap by developing an iterative matching algorithm for the three-group setting. Our algorithm outperforms the nearest neighbor algorithm and is shown to produce matched samples with total distance no larger than twice the optimal distance. …”

Principle of the SVM algorithm. by Anfeng Zhu (17817144)

A construction method of a multidimensional and multilingual association network for earth surface system science data by Qinjun Qiu (13306416)

“…The method quantitatively computes one-dimensional and multidimensional similarities using five primary indicators of multilingual data, enabling semantic interconnection and facilitating knowledge discovery within open scientific data related to the Earth surface system. …”

Analysis and design of algorithms for the manufacturing process of integrated circuits by Sonia Fleytas (16856403)

“…The (approximate) solution proposals of state-of-the-art methods include rule-based approaches, genetic algorithms, and reinforcement learning. …”

Proposed model tuned hyperparameters. by Subathra Gunasekaran (19492680)

“…This involves extracting features based on tumor shape, position, shape, and surface characteristics. To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

The workflow of the proposed model. by Subathra Gunasekaran (19492680)

“…This involves extracting features based on tumor shape, position, shape, and surface characteristics. To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

ResNeXt101 training and results. by Subathra Gunasekaran (19492680)

“…This involves extracting features based on tumor shape, position, shape, and surface characteristics. To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Proposed model specificity and DSC outcomes. by Subathra Gunasekaran (19492680)

“…This involves extracting features based on tumor shape, position, shape, and surface characteristics. To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Accuracy comparison of proposed and other models. by Subathra Gunasekaran (19492680)

“…This involves extracting features based on tumor shape, position, shape, and surface characteristics. To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Architecture of ConvNet. by Subathra Gunasekaran (19492680)

“…This involves extracting features based on tumor shape, position, shape, and surface characteristics. To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Comparison of state-of-the-art method. by Subathra Gunasekaran (19492680)

“…This involves extracting features based on tumor shape, position, shape, and surface characteristics. To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Proposed model sensitivity outcome. by Subathra Gunasekaran (19492680)

“…This involves extracting features based on tumor shape, position, shape, and surface characteristics. To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Proposed ResNeXt101 operational flow. by Subathra Gunasekaran (19492680)

“…This involves extracting features based on tumor shape, position, shape, and surface characteristics. To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”

Data used to drive the Double Layer Carbon Model in the Qinling Mountains. by Huiwen Li (17705280)

“…</p><p dir="ltr">Here we provided the dataset used to drive the DLCM, including annual net primary production (NPP) from 1982 to 2018, SOC maps in the two soil layers during the 1980s, annual mean temperature maps from 1982 to 2018, and annual surface soil moisture and root-zone soil moisture maps from 1982 to 2018. …”

Data_Sheet_1_Hierarchical multi-class Alzheimer’s disease diagnostic framework using imaging and clinical features.docx by Yao Qin (385509)

Molecular modeling and SEC analysis of CAR and CD46 binding. by A. Manuel Liaci (20642831)

Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles by Soham Savarkar (21811825)

“…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…”