Artificial Intelligence
In this paper, a sliding mode adaptive control strategy is proposed to improve driving comfort effectivelyunder the conditions of ensuring driving safety and limited suspension travel.Considering the non-linear characteristics of the asymmetric single-rod hydraulic actuator with a small occupied volume, the uncertainty of the parameters of the body mass, the friction of the suspension components and the unmodeled dynamics of the system, a half-vehicle active suspension model wasestablished. The adaptive law is designed to combine sliding mode and adaptive algorithms.
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The nucleus and micronucleus images in this dataset are collected manually from Google images. Many of these images are in RGB color while a few of them are in grayscale. The dataset includes 148 nucleus images and 158 micronucleus images. The images are manually curated, cropped, and labeled into these two classes by a domain of experts in biology. The images have different sizes and different resolutions. The sizes and shapes for nucleuses and micronucleuses images differ from one image to another. Each image may contain one or more nucleus or micronucleus.
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This data set includes Covid-19 related Tweet messages written in Turkish that contain at least one of four keywords (Covid, Kovid, Corona, Korona). These keywords are used to express Covid-19 virus in Turkey. Tweets collection was started from 11th March 2020, the first Covid-19 case seen in Turkey.
Currently dataset contain 4,8 million tweets with 6 different attribute of each tweets that were sent from 9 March 2020 until 6 May 2020.
The data file contains comma separated values (CSV). It contains the following information (6 Column) for each tweet in the data file:
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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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test
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Learning To Simulate Asymmetric Encryption With Adversarial Neural Networks
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Digital signature is an encryption mechanism used to verify the authenticity and integrity of message, which has higher complexity and security than traditional handwritten signature. However, the two main challenges of digital signature are security and computing speed. It then imposes a problem - how to quickly verify and sign digital signatures under the premise of ensuring security.
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Academic spaces are an environment that promotes student performance not only because of the quality of its equipment, but also because of its ambient comfort conditions, which can be controlled by means of actuators that receive data from sensors. Something similar can be said about other environments, such as home, business, or industry environment. However, sensor devices can cause faults or inaccurate readings in a timely manner, affecting control mechanisms. The mutual relationship between ambient variables can be a source of knowledge to predict a variable in case a sensor fails.
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PV data
Temperature (Celsius)33.00
Number of cells in series (ns)1
Number of cells in parallel (np)1
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