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Wyniki wyszukiwania dla: VEHICLE DETECTION, TRAFFIC MONITORING SYSTEM, BACKGROUND SUBTRACTION, CONVOLUTIONAL NEURAL NETWORK
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Analiza ruchu drogowego z wykorzystaniem analizy akustycznej
PublikacjaTematyka pracy porusza zagadnienia dotyczące pozyskiwania informacji o ruchu drogowym z wykorzystaniem monitoringu akustycznego. Przybliżono podstawowe techniki nadzoru nad ruchem drogowym. Przedstawiono założenia akustycznego detektora ruchu i zbadano jego skuteczność na trzech płaszczyznach działania – zliczania pojazdów, klasyfikacji rodzajowej i klasyfikacji warunków pogodowych panujących na nawierzchni
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Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images
PublikacjaIn remote sensing images, change detection (CD) is required in many applications, such as: resource management, urban expansion research, land management, and disaster assessment. Various deep learning-based methods were applied to satellite image analysis for change detection, yet many of them have limitations, including the overfitting problem. This research proposes the Feature Weighted Attention (FWA) in Bidirectional Long...
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Predicting the impact of traffic–induced vibrations on buildings using artificial neural networks
PublikacjaTraffic–induced vibrations may constitute a considerable load to a building, cause cracking of plaster, cracks in load–bearing elements or even a global structural collapse of the whole structure [1-4]. Vibrations measurements of real structures are costly and laborious, not justified in all cases. The aim of the paper is to create an original algorithm, to predict the negative dynamic impact on the examined residential building...
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Detection of the Incoming Sound Direction Employing MEMS Microphones and the DSP
PublikacjaA 3D acoustic vector sensor based on MEMS microphones and its application to road traffic monitoring is presented in the paper. The sensor is constructed from three pairs of digital MEMS microphones, mounted on the orthogonal axes. Signals obtained from the microphones are used to compute sound intensity vectors in each direction. With this data, it is possible to compute the horizontal and vertical angle of an incoming sound....
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Deep neural networks for human pose estimation from a very low resolution depth image
PublikacjaThe work presented in the paper is dedicated to determining and evaluating the most efficient neural network architecture applied as a multiple regression network localizing human body joints in 3D space based on a single low resolution depth image. The main challenge was to deal with a noisy and coarse representation of the human body, as observed by a depth sensor from a large distance, and to achieve high localization precision....
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Dynamically positioned ship steering making use of backstepping method and artificial neural networks
PublikacjaThe article discusses the issue of designing a dynamic ship positioning system making use of the adaptive vectorial backstepping method and RBF type arti cial neural networks. In the article, the backstepping controller is used to determine control laws and neural network weight adaptation laws. e arti cial neural network is applied at each time instant to approximate nonlinear functions containing parametric uncertainties....
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Diagnosing wind turbine condition employing a neural network to the analysis of vibroacoustic signals
PublikacjaIt is important from the economic point of view to detect damage early in the wind turbines before failures occur. For this purpose, a monitoring device was built that analyzes both acoustic signals acquired from the built-in non-contact acoustic intensity probe, as well as from the accelerometers, mounted on the internal devices in the nacelle. The signals collected in this way are used for long-term training of the autoencoder...
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublikacjaAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublikacjaAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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System of wireless magnetic sensors for detection and identification of ferromagnetic vehicles
PublikacjaThe paper presents the results of deformation of the Earth's magnetic field by land vehicles. Basing on the analysis of the shape of the magnetic field deformation, it is possible to detect and identify a vehicle. In order to eliminate the interference of the Earth's magnetic field by the environment, the measurements were performed in a differential configuration. Under a development project a wireless system of magnetic sensors...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublikacjaThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Video content analysis in the urban area telemonitoring system
PublikacjaThe task of constant monitoring of video streams from a large number of cameras and reviewing the recordings in order to find a specified event requires a considerable amount of time and effort from the system operators and it is prone to errors. A solution to this problem is an automatic system for constant analysis of camera images being able to raise an alarm if a predefined event is detected. The chapter presents various aspects...
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Wireless Systems of Threats Monitoring
PublikacjaThe concept of wireless system of threats monitoring with self-organizing network of multipurpose data transfer nodes are presented. Two practical applications of this system are also presented. The first of these is the Global Wireless Monitoring System for Containers, and the second is the Mobile Monitoring System for Gas Air Pollution Measurements. Presented practical applications of the wireless threats monitoring system is...
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Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning
PublikacjaThe Lombard effect is a phenomenon that results in speech intelligibility improvement when applied to noise. There are many distinctive features of Lombard speech that were recalled in this dissertation. This work proposes the creation of a system capable of improving speech quality and intelligibility in real-time measured by objective metrics and subjective tests. This system consists of three main components: speech type detection,...
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Detection and segmentation of moving vehicles and trains using Gaussian mixtures, shadow detection and morphological processing
PublikacjaSolution presented in this paper combines background modelling, shadow detection and morphological and temporal processing into one system responsible for detection and segmentation of moving objects recorded with a static camera. Vehicles and trains are detected based on their pixellevel difference from the continually updated background model utilizing a Gaussian mixture calculated separately for every pixel. The shadow detection...
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Training of Deep Learning Models Using Synthetic Datasets
PublikacjaIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Urban scene semantic segmentation using the U-Net model
PublikacjaVision-based semantic segmentation of complex urban street scenes is a very important function during autonomous driving (AD), which will become an important technology in industrialized countries in the near future. Today, advanced driver assistance systems (ADAS) improve traffic safety thanks to the application of solutions that enable detecting objects, recognising road signs, segmenting the road, etc. The basis for these functionalities...
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Capacity analysis of the selected track system in partially ordered space
PublikacjaA proper location of the interval sections has significant impact on the traffic flow in the railway track network. This issue is critical during line modernization as well as when a new solution accounting for the traffic forecast at particular element of the railway track network is developed . However, the situation is more complex and more expensive for railway stations since improvement of the capacity requires critical organizational...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublikacjaThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
PublikacjaA problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is based on a well-known NeuroEvolution of Augmenting Topologies (NEAT) algorithm. The NEAT algorithm has been adjusted by allowing additional connections within an artificial neural network and...
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Akustyczna analiza natężenia ruchu drogowego dla systemów zarządzania ruchem
PublikacjaW pracy przybliżono wybrane zagadnienia z dziedziny zarządzania transportem drogowym w Polsce i na świecie. W tym kontekście pzredstawiono potrzeby rynkowe, wymagania jak i możliwości w zakresie pozyskiwania informacji o aktualnym stanie sieci drogowych. Zaproponowano akustyczną metodę nadzorowania ruchu drogowego i jej możliwości w kontekście systemów zarządzania ruchem. Przedstawiono schemat akwizycji sygnału wraz z danymi odniesienia....
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Innowacyjny moduł ultradźwiękowy systemu monitoringu technicznego mostu podwieszonego w Rzeszowie
PublikacjaW artykule przedstawiono system monitoringu technicznego konstrukcji mostu podwieszonego nad rzeką Wisłok. System będzie wyposażony w dodatkowy moduł ultradźwiękowy umożliwiający śledzenie degradacji mechanicznej betonu w pylonie mostu. Wczesne wykrywanie stref mikropęknięć, przed pojawieniem się widocznych rys, umożliwia monitorowanie amplitud propagującej fali ultradźwiękowej oraz analizę sygnałów w dziedzinie częstotliwości.
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Management Information Base module for electrical power system configuration and use
PublikacjaInternet standards describe a virtual information store, termed the Management Information Base (MIB), which is made available through Simple Network Management Protocol (SNMP). No standard MIB exists to date for monitoring power lines in facilities over IP network. This paper defines a subset of the MIB for power system monitoring.
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Hybrid System for Ship-Aided Design Automation
PublikacjaA hybrid support system for ship design based on the methodology of CBR with some artificial intelligence tools such as expert system Exsys Developer along with fuzzy logic, relational Access database and artificial neural network with backward propagation of errors.
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TOWARDS EXPLAINABLE CLASSIFIERS USING THE COUNTERFACTUAL APPROACH - GLOBAL EXPLANATIONS FOR DISCOVERING BIAS IN DATA
PublikacjaThe paper proposes summarized attribution-based post-hoc explanations for the detection and identification of bias in data. A global explanation is proposed, and a step-by-step framework on how to detect and test bias is introduced. Since removing unwanted bias is often a complicated and tremendous task, it is automatically inserted, instead. Then, the bias is evaluated with the proposed counterfactual approach. The obtained results...
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Performance evaluation of GPS anti-spoofing system based on antenna array processing
PublikacjaThis article concerns the problem of detection and mitigation of spoofing attacks in Global Navigation Satellite Systems. First, background information about spoofing and its possible countermeasures is provided. Next, concept of a novel GPS anti-spoofing system based on antenna array processing is presented and implementation of prototype of this system is described. The third section outlines the performance evaluation of proposed...
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Playback detection using machine learning with spectrogram features approach
PublikacjaThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Semantic segmentation training using imperfect annotations and loss masking
PublikacjaOne of the most significant factors affecting supervised neural network training is the precision of the annotations. Also, in a case of expert group, the problem of inconsistent data annotations is an integral part of real-world supervised learning processes, well-known to researchers. One practical example is a weak ground truth delineation for medical image segmentation. In this paper, we have developed a new method of accurate...
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CNN Architectures for Human Pose Estimation from a Very Low Resolution Depth Image
PublikacjaThe paper is dedicated to proposing and evaluating a number of convolutional neural network architectures for calculating a multiple regression on 3D coordinates of human body joints tracked in a single low resolution depth image. The main challenge was to obtain a high precision in case of a noisy and coarse scan of the body, as observed by a depth sensor from a large distance. The regression network was expected to reason about...
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Deep learning approach on surface EEG based Brain Computer Interface
PublikacjaIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Identification of safety hazards and their sources in tram transport
PublikacjaBoth in Poland and in most countries of the European Union, the tram infrastructure is extensively expanding. Contemporary low-floor trams are constructed according to different technical assumptions than typical railway vehicles or high floor trams. In Poland such vehicles rides often on lines designed according to standards developed to the classical vehicles. At the same time, the intensity of road traffic and the number of...
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Automatic Watercraft Recognition and Identification on Water Areas Covered by Video Monitoring as Extension for Sea and River Traffic Supervision Systems
PublikacjaThe article presents the watercraft recognition and identification system as an extension for the presently used visual water area monitoring systems, such as VTS (Vessel Traffic Service) or RIS (River Information Service). The watercraft identification systems (AIS - Automatic Identification Systems) which are presently used in both sea and inland navigation require purchase and installation of relatively expensive transceivers...
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Neural Architecture Search for Skin Lesion Classification
PublikacjaDeep neural networks have achieved great success in many domains. However, successful deployment of such systems is determined by proper manual selection of the neural architecture. This is a tedious and time-consuming process that requires expert knowledge. Different tasks need very different architectures to obtain satisfactory results. The group of methods called the neural architecture search (NAS) helps to find effective architecture...
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User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning
PublikacjaIn this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...
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Research on Quality Requirements of Data Transmission Services in RSMAD
PublikacjaThe paper presents a results and analysis of research of the quality of service requirements (defined by the QoS attributes) for imaging data transmission services using Radio System for Monitoring and Acquisition of Data from Traffic Enforcement Cameras (in short RSMAD). The paper also presents and discusses results of test on the impact of the size of photos from traffic enforcement cameras on the average transmission time. These...
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OOA-modified Bi-LSTM network: An effective intrusion detection framework for IoT systems
PublikacjaCurrently, the Internet of Things (IoT) generates a huge amount of traffic data in communication and information technology. The diversification and integration of IoT applications and terminals make IoT vulnerable to intrusion attacks. Therefore, it is necessary to develop an efficient Intrusion Detection System (IDS) that guarantees the reliability, integrity, and security of IoT systems. The detection of intrusion is considered...
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Zastosowanie sieci neuronowych do detekcji impulsów o znanym kształcie w obecności silnego szumu i trendu
PublikacjaDetekcja impulsów w odebranym sygnale radiowym, zwłaszcza w obecności silnego szumu oraz trendu, jest trudnym zadaniem. Artykuł przedstawia propozycje rozwiązań wykorzystujących sieci neuronowe do detekcji impulsów o znanym kształcie w obecności silnego szumu i trendu. Na potrzeby realizacji tego zadania zaproponowano dwie architektury. W pracy przedstawiono wyniki badań wpływu kształtu impulsu, mocy zakłóceń szumowych oraz trendu...
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An application of acoustic sensors for the monitoring of road traffic
PublikacjaAssessment of road traffic parameters for the developed intelligent speed limit setting decision system constitutes the subject addressed in the paper. Current traffic conditions providing vital data source for the calculation of the locally fitted speed limits are assessed employing an economical embedded platform placed at the roadside. The use of the developed platform employing a low-powered processing unit with a set of microphones,...
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Quality Parameters in IMS/NGN Networks
PublikacjaThe Next Generation Network (NGN) architecture, including elements of the IP Multimedia Subsystem (IMS) concept, is a proposition of a telecommunication network dedicated to the needs of current and future information society. The main goal of NGN is to provide Quality of Service (QoS), for which proper network design is necessary with respect to among others standardized call processing performance parameters, including expected...
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Selective monitoring of noise emitted by vehicles involved in road traffic
PublikacjaAn acoustic intensity probe was developed measures the sound intensity in three orthogonal directions, making possible to calculate the azimuth and elevation angles, describing the sound source position. The acoustic sensor is made in the form of a cube with a side of 10 mm, on the inner surfaces of which the digital MEMS microphones are mounted. The algorithm works in two stages. The first stage is based on the analysis of sound...
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Impact of Visual Image Quality on Lymphocyte Detection Using YOLOv5 and RetinaNet Algorithms
PublikacjaLymphocytes, a type of leukocytes, play a vital role in the immune system. The precise quantification, spatial arrangement and phenotypic characterization of lymphocytes within haematological or histopathological images can serve as a diagnostic indicator of a particular lesion. Artificial neural networks, employed for the detection of lymphocytes, not only can provide support to the work of histopathologists but also enable better...
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Architektury klasyfikatorów obrazów
PublikacjaKlasyfikacja obrazów jest zagadnieniem z dziedziny widzenia komputerowego. Polega na całościowej analizie obrazu i przypisaniu go do jednej lub wielu kategorii (klas). Współczesne rozwiązania tego problemu są w znacznej części realizowane z wykorzystaniem konwolucyjnych głębokich sieci neuronowych (convolutional neural network, CNN). W tym rozdziale opisano przełomowe architektury CNN oraz ewolucję state-of-the-art w klasyfikacji...
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Performance Evaluation of Selected Parallel Object Detection and Tracking Algorithms on an Embedded GPU Platform
PublikacjaPerformance evaluation of selected complex video processing algorithms, implemented on a parallel, embedded GPU platform Tegra X1, is presented. Three algorithms were chosen for evaluation: a GMM-based object detection algorithm, a particle filter tracking algorithm and an optical flow based algorithm devoted to people counting in a crowd flow. The choice of these algorithms was based on their computational complexity and parallel...
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Performance Analysis of Convolutional Neural Networks on Embedded Systems
PublikacjaMachine learning is no longer confined to cloud and high-end server systems and has been successfully deployed on devices that are part of Internet of Things. This paper presents the analysis of performance of convolutional neural networks deployed on an ARM microcontroller. Inference time is measured for different core frequencies, with and without DSP instructions and disabled access to cache. Networks use both real-valued and...
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Self-Organizing Wireless Monitoring System for Containers
PublikacjaThis paper presents a description of new global monitoring system for containers, with its layer-modular structure, as a solution for enhance security and efficiency of container transport with particular emphasis on the practical implementation of that system for maritime container terminals. Especially the Smart Container Module (SCM) architecture and its operation as a part of the Self-Organizing Container Monitoring Network...
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Viewpoint independent shape-based object classification for video surveillance
PublikacjaA method for shape based object classification is presented.Unlike object dimension based methods it does not require any system calibration techniques. A number of 3D object models are utilized as a source of training dataset for a specified camera orientation. Usage of the 3D models allows to perform the dataset creation process semiautomatically. The background subtraction method is used for the purpose of detecting moving objects...
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Parallel Background Subtraction in Video Streams Using OpenCL on GPU Platforms
PublikacjaImplementation of the background subtraction algorithm using OpenCL platform is presented. The algorithm processes live stream of video frames from the surveillance camera in on-line mode. Processing is performed using a host machine and a parallel computing device. The work focuses on optimizing an OpenCL algorithm implementation for GPU devices by taking into account specific features of the GPU architecture, such as memory access,...
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Novel proposal for V2X systems and WBAN cooperation to improve road safety
PublikacjaIn this paper, a novel proposal of the automotive Vehicle-to-Everything system solution is presented. In this proposal, there are included the Machine to Machine type communication system and the sensor system based on a short-range the Wireless Body Area Network communication. The aim of this paper is the analysis of the model for communication, especially its architecture and signals structure for the proposed solution. The use...
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The application of neural networks in forecasting the influence of traffic-induced vibrations on residential buildings
PublikacjaTraffic-induced vibrations may cause the cracking of plaster, damage to structural elements and, in extreme cases, may even lead to the structural collapse of residential buildings. The aim of this article is to analyse the effectiveness of a method of forecasting the impact of vibrations on residential buildings using the concept of artificial intelligence. The article presents several alternative forecasting systems for which...
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Development of Intelligent Road Signs with V2X Interface for Adaptive Traffic Controlling
PublikacjaThe objective of this paper is to present a practical project of intelligent road signs, under which a series of new products for the regulation of traffic is being created. The engineering part of the project, described in this paper, was preceded by a series of experimental studies, the results of which were described in another paper accepted for publication at the MTS-ITS conference 2019, entitled "Comparative study on the effectiveness...