This dataset has been taken using the Photonic Mixer Device (PMD) Selene Module. To capture the image, we have constructed a demonstrator setup consisting of five materials (i.e., foam board (location: center), crepe paper (location: top), polystyrene (location: right), bubble wrap (location: left), wax (location: bottom)). Each image has been taken at 5 different distances (uniformly distributed between 82 cm to 47 cm) and at 3 different orientations (uniformly distributed between -10 degree to 10 degree) for each material. To avoid noise, each image has been taken in dark environment.


During Printed Circuit Board (PCB) manufacturing, it is critical to dispense the correct amount of conductive glue on the substrate LCP surface before die attachment, as the dispensing of excessive or insufficient glue may cause defects through short circuits or weak die bonding. Therefore it is critical to monitor the amount of the dispensed glue during production.


This work investigates an innovative magnetic field probe especially suitable but not limited to the characterization of insertion devices for light sources such as undulators and wigglers. Examples of such systems include the undulators planned for the Advanced Light Source Upgrade (ALS-U), where a complete magnetic characterization of the device is an integral part of their construction and certification. Current magnetic field measurement technologies for such hardware include Hall effect probes, wire-based systems, and sensing coils.


Dataset contains all raw data measured with our developed sensor and two other for evaluation.


This data set contains data collected from an overhead crane ( OPC UA server when driving an L-shaped path with different loads (0kg, 120kg, 500kg, and 1000kg). Each driving cycle was driven with an anti-sway system activated and deactivated. Each driving cycle consisted of repeating five times the process of lifting the weight, driving from point A to point B along with the path, lowering the weight, lifting the weight, driving back to point A, and lowering the weight.


This handbook and dataset provides a large set of ferromagnetic saturation curves with Hysteresis based on JA model and nonlinear reluctance of Matlab/Simulink/Simscape.
The saturation curves are available for different materials, but for simulations, the JA parameters are also needed which are not available to the public. Therefore, this handbook will help researchers to find the best fit between their specimen and curves provided in this handbook to find the approximate JA parametes to use, or start fiding accurate JA using them as the initial values.


The data we are providing this time is a part of the dataset which was used in our previous work, titled “Integrating Activity Recognition and Nursing Care Records: The System, Deployment, and a Verification Study”. The authors of this work proposed a theory that extending of start and end times of the activities can increase the prediction rate. The reason behind the theory is that many of the nurses provided the labels before or after completing an activity. In the paper, they verified and proved this theory.

Last Updated On: 
Thu, 06/30/2022 - 01:03

Three real geological sensor data with missing values (namely, 45710421 x, 45710421 y, and 45710422 x).


This dataset accurately models the internal behavior of an IoT spectrum sensor (belonging to the ElectroSense platform and consisting of a Raspberry Pi 3 with a software-defined radio kit) when it is functioning normally and under attack. To accomplish it, the system calls of the IoT sensor are monitored under normal behavior, gathered, cleaned, and stored in a centralized directory. Then, the device is infected with current malware affecting IoT devices, such as the Bashlite botnet, Thetick backdoor, Bdvl rootkit, and a Ransomware proof of concept.


This database includes subject-specific daily living activity data obtained from smartphones' inbuilt accelerometer, gyroscope, and linear acceleration sensors.