Motor point identification is pivotal to elicit comfortable and sustained muscle contraction through functional electrical stimulation. To this purpose, anatomical charts and manual search techniques are used to extract subject-specific stimulation profile. Such information being heterogenous they lack standardization and reproducibility. To address these limitations; we aim to identify, localize, and characterize the motor points of forearm muscles across nine healthy subjects.
The paper deals with fractional-slot permanent magnet synchronous machines
(FSPMSMs) equipped with phases made up of one coil parallel branches, with emphasis on their
faculty to reject the harmonic currents circulating in the loops yielded by the phase parallel branches.
These exhibit attractive potentialities, especially their enhanced open-circuit fault tolerance capability.
Furthermore, these topologies are suitably-adapted for low-voltage power supply that makes them
This .zip file contains two files: Temperature_outdoor.xlsx and TestData.xlsx. This .zip file provides detailed configuration information of the case system mentioned in artical "Dynamic Optimal Energy Flow in the Heat and Electricity Integrated Energy System".
The videos demonstrate 2D thermal gradient mappings based on two pairs of 50 µm x- an y- thin film thermocouple (TFTC) sensors. We investigate thin film thermocouples (TFTC) as
These are OMNeT++ flooding simulation results of four-UAV FANET in three different topologies, as mentioned in "The Broadcast Storm Problem in FANETs and the Dynamic Neighborhood-Based Algorithm as a Countermeasure".
Please, check the paper for more information.
This is the dataset for the manuscript entitled "Physics-prior Bayesian neural networks in semiconductor processing", IEEE Access
Simulated Disaster Victim dataset consists of images and video frames containing simulated human victims in cluttered scenes along with pixel-level annotated skin maps. The simulation was carried out in a controlled environment with due consideration towards the health of all the volunteers. To generate a real effect of a disaster, Fuller’s earth is used which is skin-friendly and does not cause harm to humans. It created an effect of disaster dust over the victims in different situations. The victims included one female and four male volunteers.
Geomagnetic field variations produce geoelectric fields that can affect the operation of technological networks at the Earth’s surface, including power systems, pipelines, phone cables and railway circuits. To assess the geomagnetic hazard to this technology, it is necessary to model the geomagnetically induced currents (GIC) produced in these systems during geomagnetic disturbances. This requires use of geomagnetic data with appropriate Earth conductivity models to calculate the geoelectric fields that drive GIC.
This dataset is in support of my 3 research papers - 'Comparative SoC Analysis using Non-Linear Kalman Estimation in 8RC ECM of 72Ah LIB - Part I', ' Comparative SoC Analysis using Non-Linear Kalman Estimation in 8RC ECM of 72Ah LIB - Part II' , and 'Comparative SoC Analysis using Non-Linear Kalman Estimation in 8RC ECM of 72Ah LIB - Part III'.
MILP instances (in LP format) of the paper
Alberto Borghetti
A Mixed-Integer Linear Programming Approach for the Computation of the Minimum-Losses Radial Configuration of Electrical Distribution Networks
IEEE Transactions on Power Systems (Issue: 3, Aug. 2012, pp. 1264-1273)
https://doi.org/10.1109/TPWRS.2012.2184306
previously available at http://www.lisep.ing.unibo.it/optree.zip
Abstractــــ Wireless Sensor Networks (WSNs) typically have been consumed high energy in monitoring and radio communication trends. Furthermore, data diffusion modes in WSN typically generate errors such as noisy values, incorrect measurements or missing information, which minimize the standard of performance in such dynamic systems. In this article, we will present a Clustered Data Reduction Model (CDRM) at both sensor node level and cluster head level, which aims to reduce data transfer rates, and reach energy more effectively.
Dataset for Capturing Fine-grained Human Poses by Off-the-shelf Wi-Fi
The files in this dataset each contain vectors Time, PEDAL, SPEED, ACCEL, VOLTAGE and CURRENT related to an Electric Vehicle travelling on one of four different roads, mostly in urban areas. Data is obtained from the CAN bus of the vehicle (a Zhidou ZD model ZD2) resampled in order to obtain a single time coordinate and stored in the dataset.
This dataset is in support of my research paper 'Analysis of Power Generation And Turbine Characteristics of 2.2 kW Residential Wind Generators'.
Related Claim : Novel ß Wind Turbine Urban Residential Controller and Novel ß Wind Vibration Octa Axis Harvesting System in Patent 'Novel ß 10-Axis Grid Compatible Multi-Controller'
Preprint :
Hyperspectral (HS) imaging presents itself as a non-contact, non-ionizing and non-invasive technique, proven to be suitable for medical diagnosis. However, the volume of information contained in these images makes difficult providing the surgeon with information about the boundaries in real-time. To that end, High-Performance-Computing (HPC) platforms become necessary. This paper presents a comparison between the performances provided by five different HPC platforms while processing a spatial-spectral approach to classify HS images, assessing their main benefits and drawbacks.
Car-hailing order data are a rich source to study the human mobility patterns, which could contribute to transporation planning and policy-making. In general, a orginal car-hailing order record includes information such as origin, destination, pick-up time, drop-off time, and travel distance. Beijing car-hailing order dataset stored the discretized order data at a traffic analysis zone(TAZ) scale, including the dataset for training and test.
A comparison of designs obtained by statistical and deterministic methods is being carried out. Points that are difficult to address in the statistical approaches are considered. A formulation of a regularized solution to experimental design is described in detail. The peculiarities of the optimal design for three types of regressions are revealed. The main factors that govern the estimation errors are determined.
Present dataset intended to give human footprint a legal capacity. The human footprint can be a good candidate for biometric identification. The presented dataset has been created using EPSON 5500 Scanner, which is an ordinary PSC machine. This dataset consists of 6 right side multispectral footprints per person from 220 volunteers captured at different periods.
Abstract— In this research, a model for LTE network performance forecast during the rainy season was developed. During the rainy season, cellular network performance is greatly affected. optimization Engineers find it difficult to ascertain cellular (LTE) network parameters that negatively influences the network performance and make a performance prediction during the rainy season. In achieving this, an experimental approach was used to study network samples collected over the LTE network of MTTN in Lagos during the rainy season for a period of 48weeks.
This dataset is in support of my 2 research papers - 'Short Circuit Analysis of 72Ah Li-Ion BMC - Part I' and 'Short Circuit Analysis of 72Ah Li-Ion BMC - Part II'.
Faults and datasets can be copied to submit in fire cause investigation reports or thesis.
This dataset is a collection of data of battery and BMC faults.
PrePrint : (Make sure you have read Caution.)
This folder contains two csv files and one .py file. One csv file contains NIST canopy PV plant data imported from https://pvdata.nist.gov/. This csv file has 1041 days raw data consisting PV plant POA irradiance, ambient temperature, Inverter DC current, DC voltage, AC current and AC voltage. Second csv file contains user created data. The Python file imports two csv files. The Python program executes four proposed corrupt data detection methods to detect corrupt data in NIST canopy PV plant data.
Indoor positioning systems based on radio frequency systems such as UWB inherently present multipath related phenomena. This causes ranging systems such as UWB}to lose accuracy by detecting secondary propagation paths between two devices. If a positioning algorithm uses ranging measurements without considering these phenomena, it will make important errors in estimating the position. This work analyzes the performance obtained in a localization system when combining location algorithms with machine learning techniques for a previous classification and mitigation of the propagation effects.
This contains data for ISFET based pH sensor drift compensation using machine learning techniques
