Splitting Specimen Aggregate Placement Area. حسب Nan Ru (9594384)

"…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …"

Specimen for the splitting test. حسب Nan Ru (9594384)

"…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …"

Example Diagram. حسب Nan Ru (9594384)

"…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …"

Aggregate Measurement Image in IPP. حسب Nan Ru (9594384)

"…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …"

Internal changes of the specimen of 0.82 to 0.84. حسب Nan Ru (9594384)

"…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …"

Internal changes of the specimen of 0.86 to 0.88. حسب Nan Ru (9594384)

"…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …"

Internal changes of the specimen of 0.7 to 0.75. حسب Nan Ru (9594384)

"…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …"

Internal changes of the specimen of 0.87 to 0.9. حسب Nan Ru (9594384)

"…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …"

Internal changes of the specimen of 0.74 to 0.76. حسب Nan Ru (9594384)

"…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …"

Internal changes of the specimen 1.55 to 1.60. حسب Nan Ru (9594384)

"…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …"

Internal changes of the specimen of 1.70 to 1.75. حسب Nan Ru (9594384)

"…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …"

Internal changes of the specimen of 0.89 to 1. حسب Nan Ru (9594384)

"…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …"

Data features examined for potential biases. حسب Harry Hochheiser (3413396)

"…Representativeness of the population, differences in calibration and model performance among groups, and differences in performance across hospital settings were identified as possible sources of bias.…"

Analysis topics. حسب Harry Hochheiser (3413396)

"…Representativeness of the population, differences in calibration and model performance among groups, and differences in performance across hospital settings were identified as possible sources of bias.…"

Overview of deep learning terminology. حسب Aaron E. Maxwell (8840882)

"…This paper introduces the geodl R package, which supports pixel-level classification applied to a wide range of geospatial or Earth science data that can be represented as multidimensional arrays where each channel or band holds a predictor variable. geodl is built on the torch package, which supports the implementation of DL using the R and C++ languages without the need for installing a Python/PyTorch environment. …"

Reaction Alignment of the Tricarboxylic Acid (TCA) Cycle Network. حسب Adel Heydarabadipour (22290905)

Supplementary file 1_ParaDeep: sequence-based deep learning for residue-level paratope prediction using chain-aware BiLSTM-CNN models.docx حسب Piyachat Udomwong (22563212)

"…The implementation is freely available at https://github.com/PiyachatU/ParaDeep, with Python (PyTorch) code and a Google Colab interface for ease of use.…"

Datasets To EVAL. حسب Jin Lu (428513)

"…We evaluated our proposed system on five educational datasets—AI2_ARC, OpenBookQA, E-EVAL, TQA, and ScienceQA—which represent diverse question types and domains. Compared to vanilla Large Language Models (LLMs), our approach combining Retrieval-Augmented Generation (RAG) with Code Interpreters achieved an average accuracy improvement of 10−15 percentage points. …"

Statistical significance test results. حسب Jin Lu (428513)

"…We evaluated our proposed system on five educational datasets—AI2_ARC, OpenBookQA, E-EVAL, TQA, and ScienceQA—which represent diverse question types and domains. Compared to vanilla Large Language Models (LLMs), our approach combining Retrieval-Augmented Generation (RAG) with Code Interpreters achieved an average accuracy improvement of 10−15 percentage points. …"

How RAG work. حسب Jin Lu (428513)

"…We evaluated our proposed system on five educational datasets—AI2_ARC, OpenBookQA, E-EVAL, TQA, and ScienceQA—which represent diverse question types and domains. Compared to vanilla Large Language Models (LLMs), our approach combining Retrieval-Augmented Generation (RAG) with Code Interpreters achieved an average accuracy improvement of 10−15 percentage points. …"