Filtry
wszystkich: 16122
-
Katalog
- Publikacje 11159 wyników po odfiltrowaniu
- Czasopisma 511 wyników po odfiltrowaniu
- Konferencje 226 wyników po odfiltrowaniu
- Wydawnictwa 1 wyników po odfiltrowaniu
- Osoby 307 wyników po odfiltrowaniu
- Wynalazki 2 wyników po odfiltrowaniu
- Projekty 24 wyników po odfiltrowaniu
- Laboratoria 1 wyników po odfiltrowaniu
- Aparatura Badawcza 1 wyników po odfiltrowaniu
- Kursy Online 391 wyników po odfiltrowaniu
- Wydarzenia 32 wyników po odfiltrowaniu
- Dane Badawcze 3467 wyników po odfiltrowaniu
wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: AIR POLLUTION, LOW-COST SENSOR CALIBRATION, MACHINE LEARNING, DATA PRE-PROCESSING, NEURAL NETWORKS
-
Cost minimization in wireless networks with a bounded and unbounded number of interfaces
PublikacjaPraca dotyczy problemu minimalizacji energii poprzez selektywne odłączanie urządzeń komunikacyjnych w wielointerfejsowych sieciach bezprzewodowych w taki sposób, by zapewnić realizację wymaganego grafu połączeń. Sformułowano problem optymalizacyjny, podano wyniki dotyczące jego trudności i zaproponowano algorytmy optymalizacyjne. Rozważono zarówno wariant, w którym liczba interfejsów komunikacyjnych jest parametrem stałym (narzuconym...
-
Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublikacjaBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
-
Modeling of Surface Roughness in Honing Processes by UsingFuzzy Artificial Neural Networks
PublikacjaHoning processes are abrasive machining processes which are commonly employed to improve the surface of manufactured parts such as hydraulic or combustion engine cylinders. These processes can be employed to obtain a cross-hatched pattern on the internal surfaces of cylinders. In this present study, fuzzy artificial neural networks are employed for modeling surface roughness parameters obtained in finishing honing operations. As...
-
Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-Learned Features
PublikacjaNematodes Caenorhabditis elegans (C. elegans) have been used as model organisms in a wide variety of biological studies, especially those intended to obtain a better understanding of aging and age-associated diseases. This paper focuses on automating the analysis of C. elegans imagery to classify the muscle age of nematodes based on the known and well established IICBU dataset. Unlike many modern classification methods, the proposed...
-
Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublikacjaControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
-
Marine Fuel Sulphur Limit Impact on Air Pollution
PublikacjaThe article presents calculation of Sulphur oxides percentage drop rate in marine industry recorded after 01.01.2020 when new limits, provided by International Maritime Organizations legislation, became effective. Ships’ SOx global emission was estimated and compared between 4th quarter 2019 and 1st quarter 2020. For more accurate estimation 3 seaside cities with big harbors were selected for statistical analysis. Noticeable...
-
Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results
PublikacjaThe continuous growth of the computing power of processors, as well as the fact that computational clusters can be created from combined machines, allows for increasing the complexity of algorithms that can be trained. The process, however, requires expanding the basis of the training sets. One of the main obstacles in music classification is the lack of high-quality, real-life recording database for every instrument with a variety...
-
Architectural Modifications to Enhance Steganalysis with Convolutional Neural Networks
PublikacjaThis paper investigates the impact of various modifications introduced to current state-of-the-art Convolutional Neural Network (CNN) architectures specifically designed for the steganalysis of digital images. Usage of deep learning methods has consistently demonstrated improved results in this field over the past few years, primarily due to the development of newer architectures with higher classification accuracy compared to...
-
Low-Cost Behavioral Modeling of Antennas by Dimensionality Reduction and Domain Confinement
PublikacjaBehavioral modeling has been rising in importance in modern antenna design. It is primarily employed to diminish the computational cost of procedures involving massive full-wave electromagnetic (EM) simulations. Cheaper alternative offer surrogate models, yet, setting up data-driven surrogates is impeded by, among others, the curse of dimensionality. This article introduces a novel approach to reduced-cost surrogate modeling of...
-
Design of Cost-Efficient Optical Fronthaul for 5G/6G Networks: An Optimization Perspective
PublikacjaCurrently, 5G and the forthcoming 6G mobile communication systems are the most promising cellular generations expected to beat the growing hunger for bandwidth and enable the fully connected world presented by the Internet of Everything (IoE). The cloud radio access network (CRAN) has been proposed as a promising architecture for meeting the needs and goals of 5G/6G (5G and beyond) networks. Nevertheless, the provisioning of cost-efficient...
-
Characteristics of an image sensor with early-vision processing fabricated in standard 0.35 µm CMOS technology
PublikacjaThe article presents measurement results of prototype integrated circuits for acquisition and processing of images in real time. In order to verify a new concept of circuit solutions of analogue image processors, experimental integrated circuits were fabricated. The integrated circuits, designed in a standard 0.35 µm CMOS technology, contain the image sensor and analogue processors that perform low-level convolution-based image...
-
A Novel Iterative Decoding for Iterated Codes Using Classical and Convolutional Neural Networks
PublikacjaForward error correction is crucial for communication, enabling error rate or required SNR reduction. Longer codes improve correction ratio. Iterated codes offer a solution for constructing long codeswith a simple coder and decoder. However, a basic iterative code decoder cannot fully exploit the code’s potential, as some error patterns within its correction capacity remain uncorrected.We propose two neural network-assisted decoders:...
-
Application of Feed Forward Neural Networks for Modeling of Heat Transfer Coefficient During Flow Condensation for Low and High Values of Saturation Temperatur
PublikacjaMost of the literature models for condensation heat transfer prediction are based on specific experimental parameters and are not general in nature for applications to fluids and non-experimental thermodynamic conditions. Nearly all correlations are created to predict data in normal HVAC conditions below 40°C. High temperature heat pumps operate at much higher parameters. This paper aims to create a general model for the calculation...
-
Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublikacjaThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
-
Application 2D Descriptors and Artificial Neural Networks for Beta-Glucosidase Inhibitors Screening
PublikacjaBeta-glucosidase inhibitors play important medical and biological roles. In this study, simple two-variable artificial neural network (ANN) classification models were developed for beta-glucosidase inhibitors screening. All bioassay data were obtained from the ChEMBL database. The classifiers were generated using 2D molecular descriptors and the data miner tool available in the STATISTICA package (STATISTICA Automated Neural...
-
Journal of Air Pollution and Health
Czasopisma -
On Rapid Design Optimization and Calibration of Microwave Sensors Based on Equivalent Complementary Resonators for High Sensitivity and Low Fabrication Tolerance
PublikacjaThis paper presents the design, optimization, and calibration of multivariable resonators for mi-crowave dielectric sensors. An optimization technique for circular complementary split ring reso-nator (CC-SRR) and square complementary split ring resonator (SC-SRR) is presented to achieve the required transmission response in a precise manner. The optimized resonators are manufac-tured using a standard photolithographic technique...
-
The role and importance of WIMAX mobile system as a high-performance data transfer technology in wireless sensor networks for wide area monitoring applications
PublikacjaThe study discuses basic features and functional design of WiMAX Mobile system, based on the IEEE 802.16e (Release 1.5 Rev. 2.0) standard. The analysis has been made in terms of ability to use this system to transmit video stream related to monitoringof large agglomeration areas. What is more, the study includes comparison of technical parameters of WiMAX Mobile system with competitive systems such as: HSPA+ and UMTS-LTE, which...
-
Simple and low-cost wireless voting system
PublikacjaThis paper presents the concept of a simple and low-cost wireless voting system working in the 868 MHz frequency band. The described system is dedicated to general shareholders assemblies but it can be easily adapted for other applications. The main advantage is its simplicity and mobility as it consists solely of three components - voting modules, a base station and a PC application from which the whole system is mamaged. This...
-
Simple and low-cost wireless voting system
PublikacjaThis paper presents the concept of a simple and low-cost wireless voting system working on the 868 MHz frequency band. Described system is dedicated to general shareholders assemblies but it can be easily adapted for other applications. The main advantage is its simplicity and mobility as it consists solely of three components - voting modules, base station and a PC application from which the whole system is managed. This architecture...
-
Impact of air pollution on depression and suicide
Publikacja -
Monitoring and analytics of atmospheric air pollution
PublikacjaPrzedstawiono podstawowe informacje dotyczące: celów i zadań monitoringu i analityki powietrza atmosferycznego, specyficznych wymogów jakie muszą spełniać monitory zanieczyszczeń, tendencji rozwojowych w zakresie kontroli jakości powietrza atmosferycznego oraz klasyfikacji metod i technik pomiarowych.
-
Response of a New Low-Coherence Fabry-Perot Sensor to Hematocrit Levels in Human Blood
PublikacjaIn this paper, a low-coherence Fabry-Perot sensor with a spectrally measured signal processing response to the refractive index of liquids is presented. Optical fiber sensors are potentially capable of continuous measuring hematocrit levels in blood. Low-coherence Fabry-Perot interferometric sensors offer a robust solution, where information about the measurand is encoded in the full spectrum of light reflected from the sensing...
-
USING ARTIFICIAL NEURAL NETWORKS FOR PREDICTING SHIP FUEL CONSUMPTION
PublikacjaIn marine vessel operations, fuel costs are major operating costs which affect the overall profitability of the maritime transport industry. The effective enhancement of using ship fuel will increase ship operation efficiency. Since ship fuel consumption depends on different factors, such as weather, cruising condition, cargo load, and engine condition, it is difficult to assess the fuel consumption pattern for various types...
-
NEURAL PROCESSING LETTERS
Czasopisma -
High precision and accuracy using low cost GNSS receivers and supporting technologies
PublikacjaThis chapter focuses on methods and techniques of positioning, based on the highly accurate and precise Global Navigation Satellite System (GNSS), which are available at a relatively low price. In this context, a comparison of different positioning methods provided by the free and open source software (FOSS) package called RTKLIB is given. Other aspects related to price reduction are also considered, including availability and...
-
Magdalena Apollo dr inż.
Osoby2017 - PhD in Civil Engineering, thesis: Risk management in construction investments related to urban regeneration projects, Gdansk University of Technology IX 2012–VI 2013 - Postgraduate Studies at Gdynia Maritime University: Research Project Management (IPMA D Certificate) 2010 – MSc in Management and Marketing, Gdansk University of Technology 2007 – MSc in Civil Engineering, Gdansk University of Technology 2007-2010 - structural...
-
The Transmission Protocol of Sensor Ad Hoc Networks
PublikacjaThis paper presents a secure protocol for a radio Ad Hoc sensor network. This network uses the TDMA multiple access method. The transmission rate on the radio channel is 57.6 kbps. The paper presents the construction of frames, types of packets and procedures for the authentication, assignment of time slots available to the node, releasing assigned slots and slots assignment conflict detection.
-
Low-Cost Flight Simulator with Possibility of Modeling of Flight Controls Failures
PublikacjaThe goal of this paper is to present a development of a low cost flight simulator, that allows to simulate flight controls failures. Cessna 172 has been chosen as an example of a general aviation aircraft and the flight model has been implemented in Simulink. The model allows for easy integration of an experimental autopilot, using various strategies. Aerodynamic coefficients have been calculated using software called DATCOM. Such...
-
A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublikacjaThis article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the...
-
Low cost microwave X-band generator
PublikacjaA low cost microwave X-band generator for educational purposes was designed and built. Its simple construction and user's interface makes it suitable for a student laboratory.The generator is based on a single frequency conversion concept. It uses a digitally tunable PLL chip for intermediate frequency generation and an active frequency multiplier for frequency conversion. The generator covers 9,7 - 11 GHz part of the X frequency...
-
Evaluation of RTKLIB's Positioning Accuracy Using low-cost GNSS Receiver and ASG-EUPOS
PublikacjaThe paper focuses on a comparison of different positioning methods provided by free and open source software (FOSS) package called RTKLIB. The RTKLIB supports real‐time and post‐processed positioning. The most important modes of operation tested by the authors are Kinematic, Static, Fixed and Precise Point Positioning (PPP). The data for evaluation were obtained from low‐cost Global Navigation Satellite System (GNSS) receiver....
-
Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublikacjaBackground. Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. Objectives. First, deep eutectic solvents...
-
On the low-cost design of abbreviated multisection planar matching transformer
PublikacjaA numerically demanding wideband matching transformer composed of three nonuniform transmission lines (NUTLs) has been designed and optimized at a low computational cost. The computational feasibility of the design has been acquired through the exploitation of low-fidelity NUTL models in most steps of the design procedure and an implicit space mapping optimization engine, providing high accuracy results with only a handful of EM...
-
Optimal Design of Transmitarray Antennas via Low-Cost Surrogate Modelling
PublikacjaOver the recent years, reflectarrays and transmitarrays have been drawing a considerable attention due to their attractive features, including a possibility of realizing high gain and pencil-like radiation patterns without the employment of complex feeding networks. Among the two, transmitarrays seem to be superior over reflectarrays in terms of achieving high radiation efficiency without the feed blockage. Notwithstanding, the...
-
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....
-
Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublikacjaCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
-
MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublikacjaAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
-
ENVIRONMENTAL POLLUTION
Czasopisma -
GIS for processing multidimensional marine data in SAAS model
PublikacjaGeographic Information Systems (GIS) have always been a useful tool for visualization and processing of geospatial data. However, their capabilities of analysis non-standard information such as hydroacoustic soundings has thus far been very limited. This paper proposes a general-purpose GIS which uses techniques such as OLAP, WCS and WCPS for processing of multidimensional spatio-temporal data. The versatility of the GIS is exemplified...
-
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...
-
International Journal of Sensor Networks
Czasopisma -
ACM Transactions on Sensor Networks
Czasopisma -
Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublikacjaNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
-
INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH
PublikacjaThe Lombard effect is an involuntary increase in the speaker’s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters...
-
Post processing and selecting data obtain with parametric sub-bottom profiler SES-2000 Standard during sounding the Gulf of Gdansk
PublikacjaThe main goal of the paper is to describe the results of sounding the Gulf of Gdansk seabed using a parametric sub-bottom profiler SES-2000 Standard. Quality of obtained during trials data depends inter alia on proper location of antenna to reduce influence of pitch, roll, heave and ship noise (bubbles from propeller and a hull flow, vibration from main engine and peripheral devices). Furthermore calibration of complementary units...
-
Constrained aerodynamic shape optimization using neural networks and sequential sampling
PublikacjaAerodynamic shape optimization (ASO) involves computational fluid dynamics (CFD)-based search for an optimal aerodynamic shape such as airfoils and wings. Gradient-based optimization (GBO) with adjoints can be used efficiently to solve ASO problems with many design variables, but problems with many constraints can still be challenging. The recently created efficient global optimization algorithm with neural network (NN)-based prediction...
-
From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublikacjaRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
-
Hybrid Processing by Turning and Burnishing of Machine Components
PublikacjaThe paper presents a method of hybrid manufacturing process of long 5 shafts and deep holes by simultaneous turning and burnishing method. The tech- 6 nological results of the research focus on the influence of the basic technological 7 parameters of this process on the surface roughness of piston rods of hydraulic 8 cylinders. Research results are presented in the graphs as well as mathematical 9 formula. Set of samples were made...
-
Breast MRI segmentation by deep learning: key gaps and challenges
PublikacjaBreast MRI segmentation plays a vital role in early diagnosis and treatment planning of breast anomalies. Convolutional neural networks with deep learning have indicated promise in automating this process, but significant gaps and challenges remain to address. This PubMed-based review provides a comprehensive literature overview of the latest deep learning models used for breast segmentation. The article categorizes the literature...