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Wyniki wyszukiwania dla: BLOOD PRESSURE, ESTIMATION, NEURAL NETWORK
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Noise Analysis of Continuous GPS Time Series of Selected EPN Stations to Investigate Variations in Stability of Monument Types
PublikacjaThe type of monument that a GPS antenna is placed on plays a significant role in noise estimation for each permanent GPS station. In this research 18 Polish permanent GPS stations that belong to the EPN (EUREF Permanent Network) were analyzed using Maximum Likelihood Estimation (MLE). The antennae of Polish EPN stations are placed on roofs of buildings or on concrete pillars. The analyzed data covers a period of 5 years from 2008...
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Innovative Implantable Left Ventricular Assist Device—Performance under Various Resistances and Operating Frequency Conditions
PublikacjaThis paper presents the operation of an innovative left ventricular assist device under various resistances and operating frequencies. The operating principle of the device is based on pulsatile blood flow, which is forced by a suction–discharge device pumping helium into a set of intra-cardiac balloons. In this way, the ejection fraction of the left ventricle is increased, and the mitral valve is additionally occluded. What is...
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CZYNNIKI DECYDUJĄCE O PRZYDATNOŚCI KOMPUTEROWEGO MODELU PRZEPŁYWÓW W SIECI WODOCIĄGOWEJ
PublikacjaW pracy poddano analizie wielozadaniowy proces tworzenia komputerowego modelu przepływów. W efekcie zidentyfikowano szereg czynników ograniczających obszar stosowania modelu w praktyce inżynierskiej. W zakresie pozyskiwania danych strukturalnych i operacyjnych wskazano potencjalne źródła błędów, które przyczyniają się do zmniejszenia dokładności odwzorowania stanu rzeczywistego. Specjalną rangę nadano specyfikacji czynników związanych...
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Applying artificial neural networks for modelling ship speed and fuel consumption
PublikacjaThis paper deals with modelling ship speed and fuel consumption using artificial neural network (ANN) techniques. These tools allowed us to develop ANN models that can be used for predicting both the fuel consumption and the travel time to the destination for commanded outputs (the ship driveline shaft speed and the propeller pitch) selected by the ship operator. In these cases, due to variable environmental conditions, making...
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Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks
PublikacjaObject detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...
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Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing
PublikacjaDeveloping signal processing methods to extract information automatically has potential in several applications, for example searching for multimedia based on its audio content, making context-aware mobile applications (e.g., tuning apps), or pre-processing for an automatic mixing system. However, the last-mentioned application needs a significant amount of research to reliably recognize real musical instruments in recordings....
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LONG-TERM RISK CLASS MIGRATIONS OF NON-BANKRUPT AND BANKRUPT ENTERPRISES
PublikacjaThis paper investigates how the process of going bankrupt can be recognized much earlier by enterprises than by traditional forecasting models. The presented studies focus on the assessment of credit risk classes and on determination of the differences in risk class migrations between non-bankrupt enterprises and future insolvent firms. For this purpose, the author has developed a model of a Kohonen artificial neural network to...
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Real-Time Sensor-Based Human Activity Recognition for eFitness and eHealth Platforms
PublikacjaHuman Activity Recognition (HAR) plays an important role in the automation of various tasks related to activity tracking in such areas as healthcare and eldercare (telerehabilitation, telemonitoring), security, ergonomics, entertainment (fitness, sports promotion, human–computer interaction, video games), and intelligent environments. This paper tackles the problem of real-time recognition and repetition counting of 12 types of...
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublikacjaWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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Hydration of N-Hydroxyurea from Ab Initio Molecular Dynamics Simulations
PublikacjaN-Hydroxyurea (HU) is an important chemotherapeutic agent used as a first-line treatment in conditions such as sickle cell disease and β-thalassemia, among others. To date, its properties as a hydrated molecule in the blood plasma or cytoplasm are dramatically understudied, although they may be crucial to the binding of HU to the radical catalytic site of ribonucleotide reductase, its molecular target. The purpose of this work...
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Badanie stanu nawierzchni drogowej z wykorzystaniem uczenia maszynowego
PublikacjaW artykule opisano budowę systemu informowania o stanie nawierzchni drogowej z wykorzystaniem metod cyfrowego przetwarzania obrazów oraz uczenia maszynowego. Efektem wykonanych prac badawczych jest eksperymentalna platforma, pozwalająca na rejestrację uszkodzeń na drogach, system do analizy, przetwarzania i klasyfikacji danych oraz webowa aplikacja użytkownika do przeglądu stanu nawierzchni w wybranej lokalizacji.
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Examination of 5G NR, LTE, and NB-IoT Radio Interfaces and Their Vulnerabilities to Interference
PublikacjaModern cellular wireless communication systems of the fourth (4G) and fifth generation (5G) face a problem of various types of interference or intentional jamming. Consequently, a degradation of the services provided and an incorrect network operation may occur. In this paper, configuration of the networks’ physical layer is investigated, with the said investigation preceded by the measurement of parameters of commercial networks...
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Prediction of Pile Shaft Capacity in Tension Based on Some Direct CPT Methods—Vistula Marshland Test Site
PublikacjaThis paper presents different CPT methodologies for the prediction of the pile shaft resistance in tension on the example of three reference screw piles of the Jazowa test site in Poland. The shaft capacity was estimated based on the cone resistance, sleeve friction and CPT excess pore water pressure. Three piles with diameter 0.4 m and the length varied from 8 m to 14.6 m were subjected to static load tests in tension. Their...
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Controlled grafting of vinylic monomers on polyolefins: a robust mathematical modeling approach
PublikacjaExperimental and mathematical modeling analyses were used for controlling melt free-radical grafting of vinylic monomers on polyolefins and, thereby, reducing the disturbance of undesired cross-linking of polyolefins. Response surface, desirability function, and artificial intelligence methodologies were blended to modeling/optimization of grafting reaction in terms of vinylic monomer content, peroxide initiator concentration,...
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublikacjaPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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Flexible Knowledge–Vision–Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning
PublikacjaThis work is part of an effort to develop of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. The paper focuses on hazards resulted from the non-use of personal protective equipment (PPE). The objective is to test the capability of the platform to adapt to different industrial environments by simulating the process of randomly selecting...
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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublikacjaAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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Utilising AI Models to Analyse the Relationship between Battlefield Developments in the Russian-Ukrainian War and Fluctuations in Stock Market Values
PublikacjaThis study examines the impact of battlefield developments in the ongoing Russian–Ukrainian war, which to date has lasted over 1000 days, on the stock prices of defence corporations such as BAE Systems, Booz Allen Hamilton, Huntington Ingalls, and Rheinmetall AG. Stock prices were analysed alongside sentiment data extracted from news articles, and processed using machine learning models leveraging natural...
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Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
PublikacjaIn recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication...
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Uczenie maszynowe do samoorganizacji systemów rozproszonych w zastosowaniach gospodarczych
PublikacjaW pracy omówiono uczenie maszynowe do samoorganizacji systemów rozproszonych w zastosowaniach gospodarczych ze szczególnym uwzględnieniem sieci neuronowych do predykcji finansowych oraz szacowania ratingu przedsiębiorstw. Oprócz sieci neuronowych, istotną rolę w przygotowaniu i testowaniu informatycznych systemów finansowych może pełnić programowanie genetyczne. Z tego powodu omówiono uczenie maszynowe w aplikacjach konstruowanych...
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The non-invasive evaluation of heart function in patients with an acute myocardial infarction: The role of impedance cardiography
PublikacjaBackground: The purpose of this study was to analyze hemodynamic changes in patients treated with percutaneous coronary intervention (PCI) at an early stage of acute myocardial infarction (AMI) and at one-month follow-up. Methods: Patients with AMI (n = 27) who underwent PCI were analyzed using impedance cardiography (ICG). ICG data were collected continuously (beat by beat) during the whole PCI procedure and thereafter at every...
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Computer-Aided Detection of Hypertensive Retinopathy Using Depth-Wise Separable CNN
PublikacjaHypertensive retinopathy (HR) is a retinal disorder, linked to high blood pressure. The incidence of HR-eye illness is directly related to the severity and duration of hypertension. It is critical to identify and analyze HR at an early stage to avoid blindness. There are presently only a few computer-aided systems (CADx) designed to recognize HR. Instead, those systems concentrated on collecting features from many retinopathy-related...
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Fluid structure interaction study of non-Newtonian Casson fluid in a bifurcated channel having stenosis with elastic walls
PublikacjaFluid–structure interaction (FSI) gained a huge attention of scientists and researchers due to its applications in biomedical and mechanical engineering. One of the most important applications of FSI is to study the elastic wall behavior of stenotic arteries. Blood is the suspension of various cells characterized by shear thinning, yield stress, and viscoelastic qualities that can be assessed by using non-Newtonian models. In this...
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Monitoring of Chlorine Concentration in Drinking Water Distribution Systems Using an Interval Estimator
PublikacjaThis paper describes the design of an interval observer for the estimation of unmeasured quality state variables in drinking water distribution systems. The estimator utilizes a set bounded model of uncertainty to produce robust interval bounds on the estimated state variables of the water quality. The bounds are generated by solving two differential equations. Hence the numerical efficiency is sufficient for on-line monitoring...
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DOP and Pseudorange Error Estimation in Mobile GNSS Systems for Android OS Applications
PublikacjaIn the near past, GNSS (Global Navigation Satellite Systems) were only offered for a narrow group of recipients. Nowadays, thanks to mobile devices, they are available to anyone and everywhere. Personal navigation, searching for POI (Point of Interest), etc., had become a basic essential activity. Thanks to the widespread and availability of smartphones each user can obtain information considering his or her location even in an...
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DOP and Pseudorange Error Estimation in Urban Environments for Mobile Android GNSS Applications
PublikacjaJust a couple of years ago, GNSS (Global Navigation Satellite Systems) were available only for a narrow group of users. Currently, with the outbreak of mobile devices, they are accessible to anyone and everywhere. Urban navigation or searching for POIs (Points of Interest) had become an everyday activity. With the availability of consumer electronics and wireless technologies, each user can obtain information considering his or...
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Integrated model for the fast assessment of flood volume: Modelling – management, uncertainty and sensitivity analysis
PublikacjaThe specific flood volume is an important criterion for assessing the performance of sewage networks. It has been shown that its value is greatly influenced by the layout of the sewers in the catchment area, which is usually expressed by a fractal dimension. Currently, only mechanistic models (such as SWMM) enable the determination of the impact of the layout of the sewers on flooding volume, but they require additional and robust...
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Prediction of pile shaft capacity in tension based on some direct CPT methods – Vistula Marshland test site
PublikacjaThis paper presents different CPT methodologies for the prediction of the pile shaft resistance in tension on the example of three reference screw piles of the Jazowa test site in Poland. The shaft capacity was estimated based on the cone resistance, sleeve friction and CPT excess pore water pressure. Three piles with a diameter of 0.4 m and the length...
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The hydrogen bond network structure within the hydration shell around simple osmolytes: Urea, tetramethylurea, and trimethylamine-N-oxide, investigated using both a fixed charge and a polarizable water model
PublikacjaDespite numerous experimental and computer simulation studies, a controversy still exists regarding the effect of osmolytes on the structure of surrounding water. There is a question, to what extent some of the contradictory results may arise from differences in potential models used to simulate the system or parameters employed to describe physical properties of the mixture and interpretation of the results. Bearing this in mind,...
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The hydrogen bond network structure within the hydration shell around simple osmolytes: Urea, tetramethylurea, and trimethylamine-N-oxide, investigated using both a fixed charge and a polarizable water model
PublikacjaDespite numerous experimental and computer simulation studies, a controversy still exists regarding the effect of osmolytes on the structure of surrounding water. There is a question, to what extent some of the contradictory results may arise from differences in potential models used to simulate the system or parameters employed to describe physical properties of the mixture and interpretation of the results. Bearing this in mind,...
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublikacjaObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublikacjaArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
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Diagnosis of damages in family buildings using neural networks
PublikacjaThe article concerns a problem of damages in family buildings, which result from traffic-induced vibrations. These vibrations arise from various causes and their size is influenced by many factors. The most important is the type of a road, type and weight of vehicles that run on the road, type and condition of the road surface, the distance from the house to the source of vibrations and many others which should be taken into account....
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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublikacjaIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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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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Sathwik Prathapagiri
OsobySathwik was born in 2000. In 2022, he completed his Master’s of Science in Biological Sciences and Bachelor’s of Engineering in Chemical Engineering in an integrated dual degree program from Birla Institute Of Technology And Science, Pilani, India. During his final year, he worked as a research intern under Dr Giri P Krishnan at Bazhenov lab, University of California San Diego school of medicine to pursue his Master’s Thesis on...
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Wykorzystanie sztucznych sieci neuronowych do wykrywania i rozpoznawania tablic rejestracyjnych na zdjęciach pojazdów
PublikacjaW artykule przedstawiono koncepcję algorytmu wykrywania i rozpoznawania tablic rejestracyjnych (AWiRTR) na obrazach cyfrowych pojazdów. Detekcja i lokalizacja tablic rejestracyjnych oraz wyodrębnienie z obrazu tablicy rejestracyjnej poszczególnych znaków odbywa się z wykorzystaniem podstawowych technik przetwarzania obrazu (przekształcenia morfologiczne, wykrywanie krawędzi) jak i podstawowych danych statystycznych obiektów wykrytych...
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ANALYSIS OF POSSIBILITIES FOR THE USE OF VOLUME-DELAY FUNCTIONS IN THE PLANNING MODULE OF THE TRISTAR SYSTEM
PublikacjaTravel time is a measure commonly used for traffic flow modelling and traffic control. It also helps to evaluate the quality of traffic control systems in urban areas. Traffic control systems that use traffic models to predict changes and disruptions in vehicle flows have to use vehicle speed-prediction models. Travel time estimation studies the effects of traffic volumes on a street section at an average speed. The TRISTAR Integrated...
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Optimization algorithm and filtration using the adaptive TIN model at the stage of initial processing of the ALS point cloud
PublikacjaAirborne laser scanning (ALS) provides survey results in the form of a point cloud. The ALS point cloud is a source of data used primarily for constructing a digital terrain model (DTM). To generate a DTM, the set of ALS observations must be first subjected to the point cloud processing methodology. A standard methodology is composed of the following stages: acquisition of the ALS data, initial processing (including filtration),...
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WRF-METEOPG: numerical weather forecast data for Poland - Days 218-224, Year 2021
Dane BadawczeWRF-METEOPG is a numerical weather forecast system developed at the Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Poland. The system was built on the basis of the Weather Research and Forecast model version 4.2 and implemented at Centre of Informatics Tricity Academic Supercomputer & Network. Physics parametrization...
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WRF-METEOPG: numerical weather forecast data for Poland - Days 239-245, Year 2021
Dane BadawczeWRF-METEOPG is a numerical weather forecast system developed at the Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Poland. The system was built on the basis of the Weather Research and Forecast model version 4.2 and implemented at Centre of Informatics Tricity Academic Supercomputer & Network. Physics parametrization...
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WRF-METEOPG: numerical weather forecast data for Poland - Days 225-231, Year 2021
Dane BadawczeWRF-METEOPG is a numerical weather forecast system developed at the Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Poland. The system was built on the basis of the Weather Research and Forecast model version 4.2 and implemented at Centre of Informatics Tricity Academic Supercomputer & Network. Physics parametrization...
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WRF-METEOPG: numerical weather forecast data for Poland - Days 267-273, Year 2021
Dane BadawczeWRF-METEOPG is a numerical weather forecast system developed at the Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Poland. The system was built on the basis of the Weather Research and Forecast model version 4.2 and implemented at Centre of Informatics Tricity Academic Supercomputer & Network. Physics parametrization...
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WRF-METEOPG: numerical weather forecast data for Poland - Days 281-287, Year 2021
Dane BadawczeWRF-METEOPG is a numerical weather forecast system developed at the Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Poland. The system was built on the basis of the Weather Research and Forecast model version 4.2 and implemented at Centre of Informatics Tricity Academic Supercomputer & Network. Physics parametrization...
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WRF-METEOPG: numerical weather forecast data for Poland - Days 295-301, Year 2021
Dane BadawczeWRF-METEOPG is a numerical weather forecast system developed at the Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Poland. The system was built on the basis of the Weather Research and Forecast model version 4.2 and implemented at Centre of Informatics Tricity Academic Supercomputer & Network. Physics parametrization...
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WRF-METEOPG: numerical weather forecast data for Poland - Days 211-217, Year 2021
Dane BadawczeWRF-METEOPG is a numerical weather forecast system developed at the Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Poland. The system was built on the basis of the Weather Research and Forecast model version 4.2 and implemented at Centre of Informatics Tricity Academic Supercomputer & Network. Physics parametrization...
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WRF-METEOPG: numerical weather forecast data for Poland - Days 302-308, Year 2021
Dane BadawczeWRF-METEOPG is a numerical weather forecast system developed at the Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Poland. The system was built on the basis of the Weather Research and Forecast model version 4.2 and implemented at Centre of Informatics Tricity Academic Supercomputer & Network. Physics parametrization...
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WRF-METEOPG: numerical weather forecast data for Poland - Days 253-259, Year 2021
Dane BadawczeWRF-METEOPG is a numerical weather forecast system developed at the Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Poland. The system was built on the basis of the Weather Research and Forecast model version 4.2 and implemented at Centre of Informatics Tricity Academic Supercomputer & Network. Physics parametrization...
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WRF-METEOPG: numerical weather forecast data for Poland - Days 274-280, Year 2021
Dane BadawczeWRF-METEOPG is a numerical weather forecast system developed at the Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Poland. The system was built on the basis of the Weather Research and Forecast model version 4.2 and implemented at Centre of Informatics Tricity Academic Supercomputer & Network. Physics parametrization...
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WRF-METEOPG: numerical weather forecast data for Poland - Days 246-252, Year 2021
Dane BadawczeWRF-METEOPG is a numerical weather forecast system developed at the Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Poland. The system was built on the basis of the Weather Research and Forecast model version 4.2 and implemented at Centre of Informatics Tricity Academic Supercomputer & Network. Physics parametrization...