1141 75 16048 4 53307 document 16048 ACute3D_data.zip application/zip 7179c95ad17b711b44ac2db046492d61 MD5 40531515 2022-05-29 09:42:46 https://researchdata.bath.ac.uk/1141/1/ACute3D_data.zip 1141 1 1 application/zip other Data and analysis Jupyter notebooks for all experiments performed to characterise the performance of the Acute3D. This zip file also contains a folder of frames captured by the autocollimator during operation, and a Python script that reads the EXIF saved in these images. en public cc_by

ACute3D_data.zip

data 16049 3 53309 document 16049 ACute3D_software.zip application/zip 0c8a2c0cbfb4efa4f83f4706fbe2609f MD5 106254 2022-05-29 09:42:58 https://researchdata.bath.ac.uk/1141/2/ACute3D_software.zip 1141 2 2 application/zip other The software that drives the autocollimator, it contains the data collection code for all experiments performed in this project. This zip file also includes a Jupyter notebook that explains the adaptive thresholding algorithm we developed for accurate spot tracking. en public cc_gnu_gpl

ACute3D_software.zip

code 16051 2 53313 document 16051 ACute3D_hardware.zip application/zip 7bb79599e2361be90c677c5a6b8d4bf0 MD5 35782952 2022-05-29 09:43:16 https://researchdata.bath.ac.uk/1141/4/ACute3D_hardware.zip 1141 4 4 application/zip other The hardware design of the Acute3D provided in the form of parametric CAD files and exported STLs. This zip file also contains the assembly instruction for building an autocollimator. en public cern_ohl

ACute3D_hardware.zip

code archive 10144 disk0/00/00/11/41 2022-06-01 09:43:50 2024-07-15 10:59:58 2022-06-01 09:43:50 data_collection show Meng Qingxin qm237@bath.ac.uk 0000-0003-0680-7000 University of Bath TRUE Stirling Julian js3214@bath.ac.uk 0000-0002-8270-9237 University of Bath FALSE Wadsworth William pyswjw@bath.ac.uk 0000-0003-4733-7594 University of Bath FALSE Bowman Richard rwb34@bath.ac.uk 0000-0002-1531-8199 University of Bath FALSE FE0040 dept_physics Autocollimator, Open source hardware, Optical metrology, Three-dimensional printing This data archive is for the Acute3D, a 3D printed, open source, laser autocollimator. The hardware design is provided in the form of parametric CAD files to make the autocollimator convenient to customise and integrate into larger instruments. Assembly instructions on building the Acute3D can be found alongside the hardware design. The software that drives the autocollimator is provided in the form of Python scripts to allow immediate use of the device and data replication. The performance of the autocollimator was characterised through a series of experiments. This archive contains the data and analysis Jupyter notebook for all experiments performed in this project. The code for data collection is embedded in the software. A folder of example frames captured by the autocollimator during operation is also provided. 2022-05-13 University of Bath public https://gitlab.com/bath_open_instrumentation_group/autocollimator GitLab repository RightsHolder University of Bath Engineering and Physical Sciences Research Council https://doi.org/10.13039/501100000266 EP/R013969/1 Detailed Malaria Diagnostics with Intelligent Microscopy Royal Society https://doi.org/10.13039/501100000288 URF\R1\180153 UR Fellowship - Robotic microscopy for globally accessible science & healthcare Royal Society https://doi.org/10.13039/501100000288 RGF\EA\181034 Robotic microscopy for globally accessible science and healthcare University of Bath https://doi.org/10.13039/501100000835 Global Challenges Research Fund https://doi.org/10.13039/100016270 The performance of the autocollimator was characterised through a series of experiments. We organised the data and analysis code by experiment and added a README file in each folder. The README file explains the aim of the experiment, equipment used in the setup, method, and the structure of the data. Unless specified, the experiments were carried out in ambient conditions without thermal stabilisation. Software environment: Raspberry Pi 3 Python 3 See requirements.txt in ACute3D_software.zip for more details The data files can be viewed using text editors such as Notepad or Python packages such as Pandas en 1 10.15125/BATH-01141 https://doi.org/10.1109/TIM.2022.3174267 pub open