CAN-Marg is multifaceted, allowing researchers and policy and program analysts to explore multiple dimensions of marginalization in urban and rural Canada. The index was developed using a theoreticalframework based on previous work on deprivation and marginalization. It was then empirically derived using principal components factor analysis. It has been demonstrated to be stable across time periods and across different geographic areas (e.g. cities and rural areas). It has also been demonstrated to be associated with health outcomes including hypertension, depression, youth smoking, alcohol consumption, injuries, body mass index and infant birthweight.Canadian Marginalization Index (CAN-Marg) data for 1991, 1996, 2001 and 2006 for dissemination areas are freely available in Excel format (CAN-Marg_EA_1991.xls; CAN-Marg_EA_1996.xls; CAN-Marg_DA_2001.xls; and CAN-MargDA_2006.xls). CANUE staff downloaded Excel files for 2001 and 2006 on March 15, 2018; data for 1991 and 1996 were downloaded on August 21, 2018 . ArcGIS was used by CANUE staff to associate the single link DMTI Spatial postal codes to the Statistics Canada dissemination or enumeration areas boundry files, and then join the CAN-Marg data to the postal codes, using dissemination or enumeration area unique identifiers. There may be many postal codes within a single dissemination area - these will have the same index values and may not be suitable for summation, etc. Please refer to the CAN-Marg documentation, listed below under Supporting Documentation.

Contains the Complete Inertial Pose (CIP) Dataset:

1) Ergowear: acquisition using custom Ergowear wearable system (9 low-cost MARG sensors - MPU9250) and custom software. Contains ~4.17M@100Hz samples of data.

2) MTwAwinda: acquisition using XsensAwinda Mocap system (17 high-end MARG sensors - MTw) and the XsensMtManager software. Contains ~1.0M@60Hz samples of data.

Both systems contain synchronized GT data from a commercial MoCap system (XsensAwinda Hardware + XsensAnalyse Software), sampled at 60Hz.

Updated code, with extended functionality can be accessed on github.com/ManuelPalermo/HumanInertialPose.

The CIP dataset is composed of 2 subsets, containing low-cost (MPU9250) and high-end (MTwAwinda) Magnetic, Angular Rate, and Gravity (MARG) sensor data respectively. It provides data for the analysis of the complete inertial pose pipeline, from raw measurements, to sensor-to-segment calibration, multi-sensor fusion, skeleton kinematics, to the complete human pose. Multiple trials were collected with 21 and 10 subjects respectively, performing 6 types of movements (ranging from calibration, to daily-activities, range-of-motion and random). It presents a high degree of variability and complex dynamics while containing common sources of error found on real conditions. This amounts to 3.5M samples, synchronized with a ground-truth inertial motion capture system (Xsens) at 60hz. This dataset may contribute to assess, benchmark and develop novel algorithms for each of the pipelines' processing steps, with applications in classic or data-driven inertial pose estimation algorithms, human movement understanding and forecasting and ergonomic assessment in industrial or rehabilitation settings.

Marge

## Overview

Marge is a dataset for object detection tasks - it contains Flag Of Saudi annotations for 216 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Marge V1

## Overview

Marge V1 is a dataset for instance segmentation tasks - it contains Road Objects annotations for 1,137 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This dataset is about books. It has 1 row and is filtered where the book is Marge and the secret tunnel. It features 6 columns including author, publication date, book publisher, and ISBN.

This dataset is about books. It has 2 rows and is filtered where the author is Marge Conger. It features 7 columns including author, publication date, language, and book publisher.

This dataset is about books. It has 1 row and is filtered where the author is Marge Aylward. It features 7 columns including author, publication date, language, and book publisher.

The data set contains recording from 5 9-axis IMU (MARG) sensors. Attached to ankles, hips and chest. The sensors were sampled at 100Hz. The experiment involved 22 subjects walking around natural environments wearing the five sensors. Though a BLE connections the sensors streamed data to an app on an android phone. The subjects labeled data in real time using buttons in the app. The data was collected in an unsupervised manner and shared with the researchers anonymously.

The following activities were recorded; Walking, Ramp Ascent, Ramp Descent, Stair Ascent, Stair Descent, Stopped

Please Cite

Sherratt, F.; Plummer, A.; Iravani, P. Understanding LSTM Network Behaviour of IMU-Based Locomotion Mode Recognition for Applications in Prostheses and Wearables. Sensors 2021, 21, 1264. https://doi.org/10.3390/s21041264

URL: https://geoscience.data.qld.gov.au/dataset/cr118209

EPM 19834, MT MARGE, ANNUAL REPORT FOR PERIOD ENDING 3/3/2020

URL: https://geoscience.data.qld.gov.au/dataset/cr100068

EPM 19834, MOUNT MARGE, ANNUAL REPORT FOR PERIOD ENDING 3/3/2017

ObjectiveThis work aims to study the disproportionate impact of the COVID-19 pandemic on the Jane and Finch community, one of the socially vulnerable neighborhoods in the Greater Toronto Area (GTA), Ontario, Canada, in terms of morbidity, mortality, and healthcare services.MethodologyA dataset provided by the Black Creek Community Health Centre (BCCHC), gathered from different health-related portals, covering various health statistics during COVID-19, namely, COVID-19 number of cases, hospitalizations, deaths, percentage of vaccination with one-, two-, and three-dose(s), Primary and Preventive Care (PPC) visits which include fecal and pap-smear cancer tests, and percentage of completed Imaging, Procedures, and Surgeries (IPS) which include the number of patients waiting for surgery were studied using statistical analysis. Underserved communities in the Peel, York, and City of Toronto regions were recognized using the Ontario Marginalized Index (ON-Marg). The Jane and Finch community was selected from the fifth quintile of the ON-Marg index and compared with the remaining locations (first to fourth ON-Marg quantiles) using Kruskal-Wallis, Mann–Whitney u, and t-tests. The Gini index was used to understand the inequality of the health parameters among the selected neighborhoods. Local Indicator of Spatial Association (LISA) was used to detect the neighborhoods with significantly higher numbers of COVID-19 cases, hospitalizations, and mortalities.ResultsThe Jane and Finch community had a significantly (p

Cet ensemble de donnees fournit le cout mensuel, trimestriel et annuel moyen du petrole brut, la taxe sur l'essence de l'Ontario, la taxe d'accise federale, la TVH, la marge de gros et la marge de detail en fonction du prix a la pompe de l'essence ordinaire sans plomb a Toronto. Vous pouvez aussi voir le prix actuel des carburants et des diagrammes s'y rapportant a la page prix des carburants. *[TVH]: taxe de vente harmonisée