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Outline of the research.
Published 2025“…This system allows medical experts to manually refine the automatically extracted data, making it more accurate and closer to the ideal dataset. First, Python programming is used to automatically generate and save JPEG-format image data from DICOM data for display in Blender. …”
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List of Abbreviations
Published 2025“…However, existing BCI frameworks face several limitations, including a lack of stage-wise flexibility essential for experimental research, steep learning curves for researchers without programming expertise, elevated costs due to reliance on proprietary software, and a lack of all-inclusive features leading to the use of multiple external tools affecting research outcomes. …”
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Raw datasets acquired to investigate the possible roles of CAHS proteins from tardigrade in osmotic stress tolerance in mammalian cells and their analysis program
Published 2024“…</p> <p><br></p> <p>In order to utilize the Python program code, it is necessary to refer to the file whose name corresponds to the respective filename.…”
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Instance segmentation benchmarking results.
Published 2025“…<div><p>Time-lapse microscopy has long been used to record cell lineage trees. Successful construction of a lineage tree requires tracking and preserving the identity of multiple cells across many images. …”
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Training details of the trackers.
Published 2025“…<div><p>Time-lapse microscopy has long been used to record cell lineage trees. Successful construction of a lineage tree requires tracking and preserving the identity of multiple cells across many images. …”
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Not All local LLMs Are Equal: A Benchmark of Energy and Performance
Published 2025“…However, installing these specific versions is not mandatory:<br><br>```bash<br>bash scripts/install_prerequisites.sh<br>```<br><br>#### Dependencies<br><br>1. Install all Python libraries listed in `requirements.txt` using a virtual environment (e.g., named `env`):<br><br>```bash<br># Create a virtual environment named 'env'<br>python3 -m venv env<br><br># Activate the virtual environment<br>source env/bin/activate<br><br># Install the required Python libraries<br>pip3 install -r requirements.txt<br>```<br><br>For `llama-cpp-python` installation with CPU support (used in this paper), execute:<br><br>```bash<br>CMAKE_ARGS="-DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS" pip3 install llama-cpp-python<br>```<br><br>For other hardware acceleration backends, refer to the [llama-cpp-python documentation](<u>https://github.com/abetlen/llama-cpp-python?…”
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The artifacts and data for the paper "DD4AV: Detecting Atomicity Violations in Interrupt-Driven Programs with Guided Concolic Execution and Filtering" (OOPSLA 2025)
Published 2025“…</p><h3><b>Steps:</b></h3><h4><b>1) Navigate to the working directory:</b><br><code>cd $ROOT_DIR/test/simple_test</code></h4><p><br></p><p dir="ltr"><b>2) Build the program using the provided scripts:</b><br><code>.…”
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Replication package for Automated Extract Method Refactoring with Open-Source LLMs
Published 2025“…The framework allows you to test and evaluate multiple models on real-world Python code samples.</p><p dir="ltr"><br></p><p>---</p>Features<p dir="ltr">- Supports 5 popular LLMs for code refactoring</p><p dir="ltr">- Works on sample Python files in batch</p><p dir="ltr">- Flexible model configuration via `model.yaml`</p><p dir="ltr">- Designed for experimentation and evaluation in research or production</p><p dir="ltr">- Uses CodeNet dataset</p><p><br></p><p><br></p><p dir="ltr">Specify one of the following in `CodeBase/model.yaml`:</p><p><br></p><p dir="ltr">- `Qwen/CodeQwen1.5-7B-Chat`</p><p dir="ltr">- `deepseek-ai/deepseek-coder-6.7b-instruct`</p><p dir="ltr">- `meta-llama/Llama-3.2-3B-Instruct`</p><p dir="ltr">- `Qwen/Qwen2.5-Coder-7B-Instruct`</p><p dir="ltr">- `microsoft/Phi-4-mini-instruct`</p><p><br></p><p dir="ltr">Specify one of the following in `CodeBase/prompts.yaml`:</p><p><br></p><p dir="ltr">- `few_shot`</p><p dir="ltr">- `zero_shot`</p><p dir="ltr">- `rci`</p><p><br></p><p dir="ltr">Dependencies:</p><p><br></p><p dir="ltr">- pip install -r requirements.txt</p><p><br></p><p dir="ltr">Data:</p><p><br></p><p dir="ltr">- data/Python_wrapped </p><p dir="ltr">- data/Problem_descriptions </p><p dir="ltr">- selected_files.txt</p><p><br></p><p dir="ltr">Run :</p><p><br></p><p dir="ltr">- inference.main</p>…”
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