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7,378 results for “case”
Data related to Mapping user-related comfort conditions to identify urban planning issues for improved quality of places in cities: The case of Ljubljana, Slovenia
<p>The data consists of parameters including air temperature, noise levels, humidity, and air quality (PM 2.5), measured using a portable ICT device while cycling through the city of Ljubljana between August 1 and August 30, 2022. The data is available as raw CSV files, with each measurement session stored in a separate file. An additional QGIS Project file (qgz) is included, along with maps (in jpg format in ppt) that visually represent the results presented in the article.</p>
Datasets used for case studies in M-VIDIA paper
We provide the extracted view data from the datasets we used for our case studies. There are three datasets, including the Thyroid Nodule Classification (TNC) dataset, the Single Mouse Oocytes (SMO) dataset, and the Pick-up Single-cell Proteomic Analysis (PiSPA) dataset. The TNC dataset is used to test the performance of applying M-VIDIA for patient diagnosis. The SMO and PiSPA are used to test the performance of M-VIDIA in cell clustering.
A Modeling Framework for Near-Road Population Exposure to Traffic-Related PM2.5 and Environmental Equity Analysis: A Case Study in Atlanta, Georgia
<p>This is the dataset for the NCST project <em>"A Modeling Framework for Near-Road Population Exposure to Traffic-Related PM2.5 and Environmental Equity Analysis: A Case Study in Atlanta, Georgia"</em> by the Georgia Tech research team.</p> <p> </p> <p>Here is the abstract of the research: </p> <p>In this study, a modeling framework for population exposure to traffic-related PM2.5 with high spatiotemporal resolution is proposed and applied to the I-575/I-75 Northwest Corridor (NWC) in Atlanta, GA, for environmental equity analysis. The analyses retrieved trip data from the Atlanta Regional Commission’s (ARC) Activity-Based Model 2020 (ABM2020), after implementing path retention algorithms (Zhao, et al., 2019) to generate individual travel paths for more than 20 million predicted vehicle trips. Emission rates for each link were retrieved from MOVES-Matrix given the ABM link speed and facility type, the ARC’s county-level fleet composition data, and regional fuel properties and I&M program parameters. High-resolution downwind concentration profiles were predicted using EPA’s AERMOD microscale dispersion model with AERMET meteorology profiles for a huge array of receptors. Trip-end locations were derived from the ABM trip data, and the on-road trajectories for each person-trip (vehicle trace data) were derived from the travel paths through network. ABM synthetic household and person data were used in demographic assessment, and linked to representative household latitude and longitude locations in the Epsilon 2019 household demographic dataset. Individual exposure to traffic-related PM2.5 in time and space (average hourly concentration) was assessed by overlaying the second-by-second person location profiles (for 24 hours) against the hourly predicted PM2.5 concentration profiles. The analyses summarize the results across 16 demographic groups and the aggregate population exposure are compared to assess potential impact differences across demographics. High-income households in the corridor were exposed to less traffic-related air pollution as they tended to live further from the freeways. The analyses did not reveal large disproportionate negative impacts on low income groups along this specific corridor, but lager disproportionate negative impacts are expected elsewhere in the metro area due to the spatial clustering of income groups along other corridors. Overall, the research demonstrates the applicability of the modeling framework and describes how the various elements (e.g., link screening, dispersion modeling, path tracing, etc.) are optimized on the supercomputing cluster.</p>
Analysis of Determining the Location of Public Electric Battery Exchange Stations (SPBKLU) using The Buffer Method in The Geographical Information System (GIS) in The Central Jakarta Region (Case Study of PT. XYZ)
<p>Figure 1. The Existing Station Map in the Central Jakarta Area</p> <p><strong><span>Figure 2.</span></strong><span> The Suitability of Battery Replacement Station Location and Closeness to Alfamart Supermarket </span></p> <p><strong><span>Figure 3.</span></strong><span> The Suitability of Battery Replacement Station Location and Closeness to District Office </span></p> <p><strong><span>Figure 4.</span></strong><span> The Suitability of Battery Replacement Station Location in the Central Jakarta Area</span></p> <p><span>Data (The Variable Weight & The Variable Criteria)</span></p>
Reproducibility Case Study and Survey: Machine Learning-based Additive Manufacturing Process Monitoring and Quality Prediction
<p><span>Machine learning (ML)-based monitoring systems have been extensively developed to enhance the print quality of additive manufacturing (AM). However, the reproducibility of the proposed ML-based AM monitoring systems in published works has not been investigated due to a lack of evaluation methods. In the paper 'Towards reproducible machine learning-based process monitoring and quality prediction research for additive manufacturing,' we propose a reproducibility investigation pipeline and conduct two case studies to validate the pipeline. This dataset records the data generated by one of the case studies. This dataset also contains the reproducibility survey results.</span></p>
Automatic Complaints Classification in E-Commerce: A Case Study Using CRISP-DM
<p>The growth of e-commerce has been remarkable in recent years, driven by increasing consumer demand for attention and quick responses. Given the large volume of transactions and complaints accompanying this increase, automating the classification of these complaints can help quickly route them to the appropriate departments. This paper presents a computational approach using the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology to automate the complaints screening process. We categorized 600 real complaints from three e-commerce platforms in Brazil. The learning model was trained progressively, using an initial set of 25 complaints in each category. The classification model obtained an accuracy of 85\% and an average of over 80\% across all relevant metrics, including precision, recall, and F1-Score. The results confirmed the effectiveness of the developed model for automated complaint classification in e-commerce, providing a computational strategy that improves the customer service process and allows for quicker problem resolution.</p>
FIG. 44 in Horses in the suburbs of a medieval city - a case study from Brno (Czech Republic)
FIG. 44. — Proliferative periosteal lesions on the rib of the horse T_3258. Scale bar: 5 cm.
FIG. 34 in Horses in the suburbs of a medieval city - a case study from Brno (Czech Republic)
FIG. 34. — Distal phalanges (from the top) of the horses T_3164, T_3256, and M_802. Scale bar 5 cm.
FIG. 29. — Horse K in Horses in the suburbs of a medieval city - a case study from Brno (Czech Republic)
FIG. 29. — Horse K_802: bone proliferation and cavity on the third tarsal bone. Scale bar: 5 cm.
FIG. 45 in Horses in the suburbs of a medieval city - a case study from Brno (Czech Republic)
FIG. 45. — Proliferative periosteal lesions on the rib of the horse T_3258. Scale bar: 5 cm.
FIG. 18 in Horses in the suburbs of a medieval city - a case study from Brno (Czech Republic)
FIG. 18. — Occlusal bevel on second premolars of the horse T_1490. Scale bar: 5 cm.
FIG. 17 in Horses in the suburbs of a medieval city - a case study from Brno (Czech Republic)
FIG. 17. — Enamel/dentine exposure on the second premolar of the horse T_3257. Scale bar: 1 cm.
FIG. 19 in Horses in the suburbs of a medieval city - a case study from Brno (Czech Republic)
FIG. 19. — Pitting on the maxillary bone of the horse T_3256. Scale bar: 5 cm.
FIG. 36. — Horse M in Horses in the suburbs of a medieval city - a case study from Brno (Czech Republic)
FIG. 36. — Horse M_802: degraded posterior distal phalanx. Scale bar: 5 cm.
FIG. 9 in Horses in the suburbs of a medieval city - a case study from Brno (Czech Republic)
FIG. 9. — Křídlovická Street, Brno: horse K_801. Courtesy of Archaia Brno.
FIG. 1 in Horses in the suburbs of a medieval city - a case study from Brno (Czech Republic)
FIG. 1. — Localization of the investigated sites south of the city of Brno (Czech Republic).
FIG. 5 in Horses in the suburbs of a medieval city - a case study from Brno (Czech Republic)
FIG. 5. — Trnitá Street, Brno: horse T_3164. Courtesy of Archaia Brno.
FIG. 2 in Horses in the suburbs of a medieval city - a case study from Brno (Czech Republic)
FIG. 2. — Suburban villages south of Brno (Joris Hoefnagel, 1617).
FIG. 8 in Horses in the suburbs of a medieval city - a case study from Brno (Czech Republic)
FIG. 8. — Křídlovická Street, Brno: horse K_800. Courtesy of Archaia Brno.
FIG. 7 in Horses in the suburbs of a medieval city - a case study from Brno (Czech Republic)
FIG. 7. — Křídlovická Street, Brno: excavated plot with horse burials. Courtesy of Archaia Brno.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.