The article discusses a new QAM signal demodulation algorithm operating at a clock speed of 1.5 sample per symbol. The demodulation algorithm implements a modified adaptive equalizer scheme that allows clock synchroni...
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At present, the communications industry is one of the fastest-growing sectors, as well as an important component of modern society, which has led to rapid growth in demand for the radio frequency spectrum (RF). Since ...
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This article clarifies the parameters of a quantum-resistant algorithm based on AG codes. This algorithm was proposed in previous works by the authors to counter the quantum threat when designing various on-board syst...
This article clarifies the parameters of a quantum-resistant algorithm based on AG codes. This algorithm was proposed in previous works by the authors to counter the quantum threat when designing various on-boardsystems. The article describes the procedure for quickly decoding the corresponding codes, estimates the key length and the probability of applying one of the existing attacks to such algorithms. This work can be useful for increasing the security of arbitrary Internet of Things systems. .
In modern telecommunications, radio engineering and measuring technologies, an important place is occupied by systems of synchronization, formation and processing of signals. The development and effective use of such ...
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The main trends in the development of intelligent transport systems are considered. It is shown that the relevance of the problem of interoperability is increasing in the context of digital transformation of the trans...
The main trends in the development of intelligent transport systems are considered. It is shown that the relevance of the problem of interoperability is increasing in the context of digital transformation of the transport industry. One approach to ensuring interoperability is open systems technology and functional standardization. Methodological approaches to localizing interoperability barriers for further optimization are considered and problems are formulated that can be solved using fuzzy logic calculation algorithms.
The paper considers the use of deep learning methods in the task of determining a personality type based on photography. The neural network architecture was developed and trained on the data collected specifically for...
The paper considers the use of deep learning methods in the task of determining a personality type based on photography. The neural network architecture was developed and trained on the data collected specifically for this task. The Myers-Briggs Types Indicator model was used for the typology. This model distinguishes 4 binary scales in personality types. Good model accuracy in each class and high performance of all the metrics used were the results. The resulting model can be used in processingsignals from video surveillance cameras and in other areas related to image analysis.
Within the framework of Industry 4.0, one of the innovative solutions in the field of production of autonomous mobile robotic devices is the development and application of digital twins. This technology significantly ...
Within the framework of Industry 4.0, one of the innovative solutions in the field of production of autonomous mobile robotic devices is the development and application of digital twins. This technology significantly accelerates the design and optimization of production processes of autonomous moving systems. The article presents the process of developing a digital twin demonstrator for scientific research in the field of autonomous robotics using the program for creating digital twins “Rational production” R-Pro Digital.
In this paper, an approach to determining pavement defects using an acoustic sensor is considered. The aim of the study is to propose the idea of developing an inexpensive method for detecting various types of damage ...
In this paper, an approach to determining pavement defects using an acoustic sensor is considered. The aim of the study is to propose the idea of developing an inexpensive method for detecting various types of damage to the roadway, such as cracks, potholes and irregularities, using acoustic analysis. In the course of the work, the characteristics of sound waves that occur when exposed to defective sections of the road surface were studied. The acoustic sensor allows you to analyze these sound signals and determine the presence and nature of defects based on their changes. The technique includes data collection using an acoustic sensor, signal processing using machine learning algorithms to classify defects and visualization of the results.
Going on a trip, however, this does not guarantee the normal condition of the driver while driving. This paper proposes a method of monitoring the driver based on video images that are processed by a neural network an...
Going on a trip, however, this does not guarantee the normal condition of the driver while driving. This paper proposes a method of monitoring the driver based on video images that are processed by a neural network and determines such indicators as head movement, arm movement, and upper shoulder joints. The paper compares the main architectures of neural network frameworks: AlphaPose, OpenPose, PoseNet and Mask R-CNN. Mathematical description of kinematics of human hands and head movement is given A program continuous monitoring of driver's condition by means of video image processing in real conditions is proposed.
This paper investigates the application of machine learning techniques to analyze and classify the state of a vehicle driver while driving to improve road safety. Driver states were analyzed for loss of attention whil...
This paper investigates the application of machine learning techniques to analyze and classify the state of a vehicle driver while driving to improve road safety. Driver states were analyzed for loss of attention while driving. The object of the study was video images from cameras located in vehicles and directed at drivers. Four models were analyzed in Jupyter notebook environment using NumPy, scikit-learn, Matplotlib. The results of the analysis show that EfficientNet-B0 is the best algorithm and that it can be effectively applied in future studies and predictions.
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