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The glycemia response for this experiment was obtained in-silico, using the complex physiology-based nonlinear simulation model with the basal glycemia 6 mmol/l and the corresponding basal insulin administration rate 0.01 U/min.
The data acquisition experiment was designed to mimic the regular insulin treatment of a type 1 diabetic subject during the 6-day period with an overall number of 25 meals and a total carbohydrate amount of 433 g.
The virtual continuous glucose monitoring readings were sampled with the sample time 20 min.
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Data and Reuslts from this work:
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The leakage data of the natural gas pipeline comes from the simulated leakage device of the pressure pipeline. The pipeline material is seamless steel pipe, the outer diameter of the pipeline is 108mm, the wall thickness of the pipeline is 4.5mm, and the length of the pipeline is about 100m. According to the specifications of the air compressor and air storage tank (the maximum allowable pressure is 2Mpa) and the standard of high-pressure and sub-high-pressure pipeline gas transmission pressure, the selected experimental pressure range is 0.5Mpa to 2Mpa.
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This dataset consists of measurements from a foot-mounted inertial measurement unit (IMU). In total, we provide data from five different test subjects travelling over more than 7.6 km. The data are combined with various forms of ground truth positioning information that can be used to evaluate the accuracy of a zero-velocity-aided, foot-mounted inertial navigation system (INS).
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1585 Views
High-voltage batteries in battery electric vehicles face significant load fluctuations due to driving behavior. This dynamic performance of the powertrain is contrasted by the almost constant load of the auxiliary consumers. The highest auxiliary consumption is generated by the heating and air conditioning system, which decreases the vehicles range significantly. 72 real driving trips with a BMW i3 (60 Ah) were recorded, serving for model validation of a full vehicle model consisting of the powertrain and the heating circuit.
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Ten volunteers were trained through a series of twelve daily lessons to type in a computer using the Colemak keyboard layout. During the fourth-, eight-, and eleventh-session, electroencephalography (EEG) measurements were acquired for the five trials each subject performed in the corresponding lesson. Electrocardiography (ECG) data at each of those trials were acquired as well. The purpose of this experiment is to aim in the development of different methods to assess the process of learning a new task.
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Participants were 61 children with ADHD and 60 healthy controls (boys and girls, ages 7-12). The ADHD children were diagnosed by an experienced psychiatrist to DSM-IV criteria, and have taken Ritalin for up to 6 months. None of the children in the control group had a history of psychiatric disorders, epilepsy, or any report of high-risk behaviors.
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This dataset provides the magneto-inertial signals from six MIMU (2 Xsens, 2 APDM, 2 Shimmer) and orientation from 8 reflective markers (VICON) at 3 different speeds (slow, medium, fast). Marker trajectories are provided. Proprietary orientations from MIMU vendors are also included. All data are synchronized at 100 Hz.
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The dataset comprises up to two weeks of activity data taken from the ankle and foot of 14 people without amputation and 17 people with lower limb amputation. Walking speed, cadence, and lengths of strides taken at and away from the home were considered in this study. Data collection came from two wearable sensors, one inertial measurement unit (IMU) placed on the top of the prosthetic or non-dominant foot, and one accelerometer placed on the same ankle. Location information was derived from GPS and labeled as ‘home’, ‘away’, or ‘unknown’. The dataset contains raw acce
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This dataset includes high-resolution (1 s) power and reactive power profiles of household appliances. The dataset consists of ground truth data from a European household, laboratory measurements and few artificial created data. Specifically, the dataset includes data for TV, washing machine, toaster, iron, hairdryer, dish washer, PC, refrigerator, air-conditioner unit, range, dryer, heat pump (different modes of operation), BEV, water heater, light bulb and always-on load profiles.
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