In text mining and Natural Language Processing (NLP), extracting emotions from textual data is gaining rapid attraction. The proliferation of online content and the freedom of expression on social media platforms has ...
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In this paper, we consider the learning of a Reduced-Order Linear Parameter-Varying Model (ROLPVM) of a nonlinear dynamical system based on data. This is achieved by a two-step procedure. In the first step, we learn a...
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In this paper, we consider the learning of a Reduced-Order Linear Parameter-Varying Model (ROLPVM) of a nonlinear dynamical system based on data. This is achieved by a two-step procedure. In the first step, we learn a projection to a lower dimensional state-space. In step two, an LPV model is learned on the reduced-order state-space using a novel, efficient parameterization in terms of neural networks. The improved modeling accuracy of the method compared to an existing method is demonstrated by simulation examples.
This paper provides a comprehensive tutorial on a family of Model Predictive control (MPC) formulations, known as MPC for tracking, which are characterized by including an artificial reference as part of the decision ...
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This article describes a solution for automating measurements on CNC machines equipped with automatic measurement tools using a vision system that simulates stereoscopic vision. The proposed method of measurement allo...
This article describes a solution for automating measurements on CNC machines equipped with automatic measurement tools using a vision system that simulates stereoscopic vision. The proposed method of measurement allows non-contact determination of the approximate position of the workpiece on the machine to fill in the parameters of measuring cycles. A three-stage algorithm for image processing by a software module of such a system is described, including recognition of the area with the workpiece, automatic correction of input images for successful contour recognition, determining of the contours of the workpieces and their geometric parameters, as well as calculation of the approximate dimensions of the workpieces relatively to the marks applied to the machine worktable beforehand. The calculated dimensions must be transmitted to the CNC system of the machine to run a parameterized program that calls a measuring cycle that clarifies the position of the workpiece on the machine. A model of the vision system has been implemented and tested.
The rapid development of digital technology has brought about the challenge of ensuring information security. Cryptography and steganography are among the various techniques available to address this challenge. These ...
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In the paper, the authors check the behaviour of Bluetooth Low Energy protocol in a popular smart wristband and a microcontroller in the heart rate monitoring application. The measurements were collected using a devel...
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In the paper, the authors check the behaviour of Bluetooth Low Energy protocol in a popular smart wristband and a microcontroller in the heart rate monitoring application. The measurements were collected using a development board with the ESP32 System on Chip. The authors tested measurement period stability and measurement reliability in various conditions.
This article describes a possible method for automating measurements on CNC machines that support measurements in semi-automatic mode by calling parameterized measurement cycles. The proposed method is based on the us...
This article describes a possible method for automating measurements on CNC machines that support measurements in semi-automatic mode by calling parameterized measurement cycles. The proposed method is based on the use of a vision system integrated with a CNC system and approximately determining the geometric parameters and coordinates of the workpiece to fill in the parameters of the measuring cycle. The requirements for the installation of the system hardware on the equipment are formulated. The methodology of measurement using the system is described. Algorithms for obtaining and software processing of images are described, including recognition of the area with the workpiece, automatic correction of brightness and contrast of input images and determination of the contours of the workpieces and their parameters. An algorithm for processing data on the obtained contours for calculating the approximate dimensions of the workpiece relative to the marks previously applied to the machine desktop is also described. The interaction of the vision system with the CNC system is described to run a template control program that causes a filled measuring cycle to determine the position and dimensions of the workpiece accurately. The prototype of the vision system is installed on real equipment.
Longer training times pose a significant challenge in Artificial neural networks (ANNs) as it may leads to increasing the computational costs and decreasing the effectiveness of the model. Therefore, it is imperative ...
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Longer training times pose a significant challenge in Artificial neural networks (ANNs) as it may leads to increasing the computational costs and decreasing the effectiveness of the model. Therefore, it is imperative to reduce training times in ANNs to enhance the computational efficiency. The initialization of the weights between the layers in ANN plays a vital role in reducing training times. Appropriate weight initialization can help the network converge faster during the training by providing an optimum starting point for the network. Therefore, weight initialization techniques are essential for efficient training of ANNs. This paper revisits and implements different popular weight initialization techniques in ANNs and analyzes their impact on training time. Specifically, this paper implements Gaussian-based, Kaming-based, and Xavier-based weight initiation atop a popular DNN-based network. The experiments are conducted by employing a well-known dataset. The results show that the scenario when no weight initiation is applied consumed the highest training time, whereas different weight initiation techniques contribute in reducing the training times for the network.
The issues of developing control programs for machine tools with dynamically changing kinematics are considered. The features and additional control commands related to changing the kinematic scheme, controlling the c...
The issues of developing control programs for machine tools with dynamically changing kinematics are considered. The features and additional control commands related to changing the kinematic scheme, controlling the channels of the control system, switching the operating modes of the axes, saving the state of the M and G-vectors are generalized. The features of the execution of the control program in one or several channels are considered. In the case of a program running in several channels and using processors with low performance, it is possible to use a memory-oriented architecture of the control system. A technique for developing control programs has been developed, individual steps of the technique have been identified, features and ways of their implementation have been given. An example of the development of a control program according to the obtained methodology is given.
3D object detection from LiDAR sensor data is an important topic in the context of autonomous cars and drones. In this paper, we present the results of experiments on the impact of backbone selection of a deep convolu...
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