Indian Power Sector Evening Hour Peak Demand data has been shown in this sheet from January 2014 to the beginning of July 2021. The n_mw, w_mw, s_mw, e_mw, ne_mw and ind_mw indicate Northern Region peak MW, Western Region peak MW, Southern Region peak MW, Eastern Region peak MW, North Eastern Region peak MW and overall India peak MW respectively
The dataset of labeled tracking evolution of static warnings between the SOA approach and our approach.
The dataset of labeled tracking evolution of static warnings between the SOA approach and our approach.
The data are made of nine sets of measurements of four chipless RFID tags. The first two are made of 2600 measurements made at 160 centimeters (distance between the tag and the antenna) without (first) and with (second) initial background subtraction. The third set is made of 5600 measurements made in the range of 50 – 140 centimeters. The next six sets are measurements made to test models trained with the third set. All the measurements are made in the monostatic configuration.
This dataset is related to dog activity and is sensor data.
Search-based software testing (SBST) is now a mature area, with numerous techniques developed to tackle the increasingly challenging task of software testing. SBST techniques have shown promising results and have been successfully applied in industry to automatically generate test cases for large and complex software systems. Their effectiveness, however, has been shown to be problem dependent.
With the rapid deployment of indoor Wi-Fi networks, Channel State Information (CSI) has been used for device-free occupant activity recognition. However, various environmental factors interfere with the stable propagation of Wi-Fi signals indoors, which causes temporal variation of CSI data. In this study, we investigated temporal CSI variation in a real-world housing environment and its impact on learning-based occupant activity recognition.
Screening tools play a vital role in sensory processing disorder detection. The automatic collection of features related to behavioral parameters and the response to given stimuli is possible with the recent technology. Real time stress related health parameters are collected as response to visual stimuli created with experts’ suggestions based on visual sensory processing related questionnaire. Body temperature and heart rate are obtained by smart watch.
The design and implementation of an anthropomorphic robotic hand control system for the Bioengineering and Neuroimaging Laboratory LNB of the ESPOL were elaborated. The myoelectric signals were obtained using a bioelectric data acquisition board (CYTON BOARD) using six channels out of 8 available, which had an amplitude of 200 [uV] at a sampling frequency of 250 [Hz].
Eight participants, sat on a stable chair with no arm rests and a high backrest, with his/her right arm strapped to the passive manipulator. The participant’s motion was simultaneously recorded using a Kinect sensor, an electronic goniometer (Biopac Systems, USA), and a passive marker motion capture system, V120:Trio (OptiTrack, USA). The Kinect sensor was placed 2 m in front and slightly above the participant. The goniometer was attached, using double-sided tape, to the participant’s arm above the elbow. Three reflective markers were used for the V120:Trio recording.
