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Wyniki wyszukiwania dla: cross-sensitivity, multiple linear regression, artificial neural networks
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Light pollution from illuminated bridges as a potential barrier for migrating fish–Linking measurements with a proposal for a conceptual model
PublikacjaIlluminated bridges have become important assets to navigable aquatic systems. However, if artificial light at night (ALAN) from illuminated bridges reaches aquatic habitats, such as rivers, it can threaten the river's natural heterogeneity and alter the behavioural responses of migratory fish. Here, via a pilot study, we quantified levels of ALAN at illuminated bridges that cross a river and, propose a conceptual model to estimate...
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Automatic Singing Voice Recognition EmployingNeural Networks and Rough Sets
PublikacjaCelem badań jest automatyczne rozpoznawanie głosów śpiewaczych w kategorii rodzaju i jakości technicznej śpiewu. W artykule opisano stworzoną bazę danych głosów, która zawiera próbki głosu śpiewaków profesjonalnych i amatorskich. W dalszej części opisano parametry zdefiniowane w oparciu o zjawiska biomechaniczne w narządzie głosu podczas śpiewania. W oparciu o stworzone macierze parametrów wytrenowano i porównano automatyczne klasyfikatory...
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Cross-layer integration of network mechanisms for increasing efficiency of multimedia session support in IEEE 802.11s environment
PublikacjaWith an IEEE 802.11 wireless networks operating in Point-to-Multipoint mode being the most popular WLAN access technology employed today, it can be expected that a Wireless Mesh Network (WMN) based on the technology can provide significant advantages for such network systems. The IEEE 802.11s standard amendment provides the comprehensive set of mechanisms required to implement and deploy a WMN utilizing this widely popular technology....
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Degradation of electrical performance of a crystalline photovoltaic module due to dust deposition in northern Poland
PublikacjaThe reduction in power output caused by the accumulation of dust on the photovoltaic module surface is an important problem and should receive much more attention in the literature. This study was an evaluation of the performance degradation of crystalline photovoltaic modules due to natural and simulated dust deposition. Dust is created from powdered grains of sand and particles of different bodies. Dust originates from different...
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An objective isogeometric mixed finite element formulation for nonlinear elastodynamic beams with incompatible warping strains
PublikacjaWe present a stable mixed isogeometric finite element formulation for geometrically and materially nonlinear beams in transient elastodynamics, where a Cosserat beam formulation with extensible directors is used. The extensible directors yield a linear configuration space incorporating constant in-plane cross-sectional strains. Higher-order (incompatible) strains are introduced to correct stiffness, whose additional degrees of...
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In silico modelling for predicting the cationic hydrophobicity and cytotoxicity of ionic liquids towards the Leukemia rat cell line, Vibrio fischeri and Scenedesmus vacuolatus based on molecular interaction potentials of ions
PublikacjaIn this study we present prediction models for estimating in silico the cationic hydrophobicity and the cytotoxicity (log [1/EC50]) of ionic liquids (ILs) towards the Leukemia rat cell line (IPC-81), the marine bacterium Vibrio fischeri and the limnic green algae Scenedesmus vacuolatus using linear free energy relationship (LFER) descriptors computed by COSMO calculations. The LFER descriptors used for the prediction model (i.e....
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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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Audio Feature Analysis for Precise Vocalic Segments Classification in English
PublikacjaAn approach to identifying the most meaningful Mel-Frequency Cepstral Coefficients representing selected allophones and vocalic segments for their classification is presented in the paper. For this purpose, experiments were carried out using algorithms such as Principal Component Analysis, Feature Importance, and Recursive Parameter Elimination. The data used were recordings made within the ALOFON corpus containing audio signal...
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Predicting the peak structural displacement preventing pounding of buildings during earthquakes
PublikacjaThe aim of the present paper is to verify the effectiveness of the artificial neural network (ANN) in predicting the peak lateral displacement of multi-story building during earthquakes, based on the peak ground acceleration (PGA) and building parameters. For the purpose of the study, the lumped-mass multi-degree-of-freedom structural model and different earthquake records have been considered. Firstly, values of stories mass and...
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Preprocessing of Document Images Based on the GGD and GMM for Binarization of Degraded Ancient Papyri Images
PublikacjaThresholding of document images is one of the most relevant operations that influence the final results of their further analysis. Although many image binarization methods have been proposed during recent several years, starting from global thresholding, through local and adaptive methods, to more sophisticated multi-stage algorithms and the use of deep convolutional neural networks, proper thresholding of degraded historical...
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Investigating Feature Spaces for Isolated Word Recognition
PublikacjaMuch attention is given by researchers to the speech processing task in automatic speech recognition (ASR) over the past decades. The study addresses the issue related to the investigation of the appropriateness of a two-dimensional representation of speech feature spaces for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and timefrequency signal representation...
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Individual entrepreneurial orientation: comparison of business and STEM students
PublikacjaAbstract Purpose – The purpose of this study is to determine whether there are differences in Individual Entrepreneurial Orientation (IEO) between students who are doing their major in business studies and the ones whose areas of study are science, technology, engineering, and mathematics (STEM). Design/methodology/approach – The current research investigates which factors and components contribute to EO orientation development...
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Electrophoretic Deposition and Characterization of Chitosan/Eudragit E 100 Coatings on Titanium Substrate
PublikacjaCurrently, a significant problem is the production of coatings for titanium implants, which will be characterized by mechanical properties comparable to those of a human bone, high corrosion resistance, and low degradation rate in the body fluids. This paper aims to describe the properties of novel chitosan/Eudragit E 100 (chit/EE100) coatings deposited on titanium grade 2 substrate by the electrophoretic technique (EPD). The deposition...
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Magnetically sensitive fiber probe with nitrogen-vacancy center nanodiamonds integrated in a suspended core
PublikacjaEfficient collection of photoluminescence arising from spin dynamics of nitrogen vacancy (NV) centers in diamond is important for practical applications involving precise magnetic field or temperature mapping. These goals may be realized by the integration of nanodiamond particles with optical fibers and volumetric doping of the particles alongside the fiber core. That approach combines the advantages of robust axial fixation of...
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Nadmiarowe zgony podczas pandemii COVID-19 w Polsce i ocena skuteczności szczepień
PublikacjaZ powodu pandemii COVID-19 zmarły miliony ludzi na całym świecie. Jak wynika z wielu badań, szczepienia przeciw chorobie wywołanej wirusem SARS-CoV-2 okazały się środ-kiem ograniczającym skalę zachorowań i liczbę zgonów. Celem badania omawianego w artyku-le jest pomiar skali pandemii w Polsce za pomocą liczby nadmiarowych zgonów w podregio-nach według klasyfikacji NUTS 3 i w grupach wieku, a następnie określenie zależności pomiędzy...
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Advanced Sensor for Non-Invasive Breast Cancer and Brain Cancer Diagnosis Using Antenna Array with Metamaterial-Based AMC
PublikacjaMicrowave imaging techniques can identify abnormal cells in early development stages. This study introduces a microstrip patch antenna coupled with artificial magnetic conductor (AMC) to realize improved sensor for non-invasive (early-stage) breast cancer and brain cancer diagnosis. The frequency selectivity of the proposed antenna has been increased by the presence of AMC by creating an additional resonance at 2.276 GHz associated...
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Condition-Based Monitoring of DC Motors Performed with Autoencoders
PublikacjaThis paper describes a condition-based monitoring system estimating DC motor degradation with the use of an autoencoder. Two methods of training the autoencoder are evaluated, namely backpropagation and extreme learning machines. The root mean square (RMS) error in the reconstruction of successive fragments of the measured DC motor angular-frequency signal, which is fed to the input of autoencoder, is used to determine the health...
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Improving depth maps of plants by using a set of five cameras
PublikacjaObtaining high-quality depth maps and disparity maps with the use of a stereo camera is a challenging task for some kinds of objects. The quality of these maps can be improved by taking advantage of a larger number of cameras. The research on the usage of a set of five cameras to obtain disparity maps is presented. The set consists of a central camera and four side cameras. An algorithm for making disparity maps called multiple...
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Wear Resistance Enhancement of Al6061 Alloy Surface Layer by Laser Dispersed Carbide Powders
PublikacjaIn this paper, results of the experimental study on improving wear resistance in sliding friction of Al-based alloy are presented. The technique used involves the formation of a metal matrix composite (MMC) in the alloy surface layer by laser dispersion of carbide powders such as WC, TiC and SiC. For WC and TiC MMC surface coatings fabricated under conditions typical for most of the technologically relevant solid-state lasers (wavelength...
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Historical carpentry corner log joints—Numerical analysis within stochastic framework
PublikacjaThe paper presents the results of numerical analysis performed on historical, traditional carpentry corner logjoints of two basic topologies: the short-corner dovetail connection and the saddle notch connection. These types of carpentry joints are commonly used in currently preserved objects of wooden architecture. All connections have been modelled in pinewood, which has been defined in the Finite Element software MSC.Marc/Mentat...
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Beam Steerable MIMO Antenna Based on Conformal Passive Reflectarray Metasurface for 5G Millimeter-Wave Applications
PublikacjaA conformal reflectarray fed by a dual-band multiple-input multiple-output (MIMO) antenna is proposed for low-cost beam steering applications in 5G Millimeter-wave frequency bands. The beam steering is accomplished by selecting a specific port in the MIMO antenna. Each MIMO port is associated with a beam that points in a different direction due to a conformal reflectarray. This novel reflectarray antenna design has the advantages...
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Massively parallel linear-scaling Hartree–Fock exchange and hybrid exchange–correlation functionals with plane wave basis set accuracy
PublikacjaWe extend our linear-scaling approach for the calculation of Hartree–Fock exchange energy using localized in situ optimized orbitals [Dziedzic et al., J. Chem. Phys. 139, 214103 (2013)] to leverage massive parallelism. Our approach has been implemented in the ONETEP (Order-N Electronic Total Energy Package) density functional theory framework, which employs a basis of non-orthogonal generalized Wannier functions (NGWFs) to achieve...
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Expedited Geometry Scaling of Compact Microwave Passives by Means of Inverse Surrogate Modeling
PublikacjaIn this paper, the problem of geometry scaling of compact microwave structures is investigated. As opposed to conventional structures (i.e., constructed using uniform transmission lines), re-design of miniaturized circuits (e.g., implemented with artificial transmission lines, ATSs) for different operating frequencies is far from being straightforward due to considerable cross-couplings between the circuit components. Here, we...
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublikacjaDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
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Bio-based semi-aromatic polyesters for coating applications
PublikacjaLinear and branched bio-based semi-aromatic (co)polyesters were evaluated as resins for solvent-basedand powder coatings. Dimethyl-2,5-furandicarboxylate (DMF), 2,3-butanediol and various multifunc-tional comonomers were used to synthesize amorphous hydroxyl-end-capped (co)polyesters. The resinswere cross-linked using the -caprolactam blocked trimer of isophorone diisocyanate. Both the solvent-based and powder coatings proved to...
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A Probabilistic Optimisation Approach to the Equitable Controller Location Problem
PublikacjaThe ability of the Software-Defined Network (SDN) to transport traffic flows depends, in particular, on the SDN switches being able to communicate with SDN controllers, which are responsible for the setup of network connections and the configuration of switches. Since in principle the number of SDN controllers is limited they must be installed in a set of carefully selected node locations. Whereas the problem of controller placement...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublikacjaResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Detecting Lombard Speech Using Deep Learning Approach
PublikacjaRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublikacjaResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublikacjaThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...
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Online sound restoration system for digital library applications.
PublikacjaAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublikacjaSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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Occurrence of antimicrobial resistant bacteria in environment and the statistical analysis of this phenomenon
PublikacjaIntroduction: In this study the occurrence of antimicrobial resistance patterns among fecal indicators (Escherichia coli and Enterococcus spp.) was analyzed in water and wastewater samples. The trends in antimicrobial resistance were analyzed using basic statistical methods. Methods: Samples were obtained from two local watercourses (Oliwski Stream and Reda River) as well as from the wastewater treatment plant (WWTP) Gdansk - Wschod....
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News that Moves the Market: DSEX-News Dataset for Forecasting DSE Using BERT
PublikacjaStock market is a complex and dynamic industry that has always presented challenges for stakeholders and investors due to its unpredictable nature. This unpredictability motivates the need for more accurate prediction models. Traditional prediction models have limitations in handling the dynamic nature of the stock market. Additionally, previous methods have used less relevant data, leading to suboptimal performance. This study...
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Intensification of catechin extraction from the bark of Syzygium cumini using ultrasonication: Optimization, characterization, degradation analysis and kinetic studies
PublikacjaCatechin is a prominent polyphenolic component that possesses various medicinal properties. Present work communicates the intensification and optimization of catechin extraction from the bark of Syzygium cumini tree using stirred reactor, soxhlet, ultrasonic bath, and ultrasonic horn technique. The optimization of several parameters such as type of solvent, solid to solvent ratio (1:100 w/v), speed of agitation (300 RPM), extraction...
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Dependent self-employed individuals: are they different from paid employees?
PublikacjaThis study focuses on dependent self-employment, which covers a situation where a person works for the same employer as a typical worker while on a self-employment contractual basis, i.e., without a traditional employment contract and without certain rights granted to "regular" employees. The research exploits the individual-level dataset of 35 European countries extracted from the 2017 edition of the European Labour Force Survey...
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Belief in the importance of socially responsible behaviors – the significance of trust and personal experiences with COVID-19
PublikacjaA vast number of studies have shown that trust is related to socially desirable traits and behaviors. In the present research we have investigated the relationship between generalized trust and beliefs about the importance of socially responsible behaviors (SRB) during the pandemic – namely, following the sanitary regime and getting vaccinated. Basing on the previous findings we assumed that trustful people...
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Fighting Administrative Corruption with Digital Government in Sub-Saharan Africa
PublikacjaAdministrative corruption is a pervasive problem and a major threat to economic and social development around the world, especially in Sub-Saharan Africa which lags behind other regions in various development indicators and is seen as one of the most corrupt regions globally. This paper examines a hypothesis that digital government – the use of digital technology to transform public administration organizations and their relationships...
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Changing Attitudes in Cross Cultural Diversity through International Senior Capstone Projects
PublikacjaIn this global world, today’s engineer is likely to have to work in global international teams with colleagues from other nationalities. The challenge for many engineering curricula is how to include, in a realistic way, this global dimension and increase the student’s awareness of the issues that are encountered. In the Purdue University Engineering Technology program, an international capstone project was created to increase...
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Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublikacjaThe growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...
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Tailor-Made Polysaccharides for Biomedical Applications
PublikacjaPolysaccharides (PSAs) are carbohydrate-based macromolecules widely used in the biomedical field, either in their pure form or in blends/nanocomposites with other materials. The relationship between structure, properties, and functions has inspired scientists to design multifunctional PSAs for various biomedical applications by incorporating unique molecular structures and targeted bulk properties. Multiple strategies, such as...
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Quality Expectations of Mobile Subscribers
PublikacjaMobile systems, by nature, have finite resources. Radio spectrum is limited, expensive and shared between many users and services. Mobile broadband networks must support multiple applications of voice, video and data on a single IP-based infrastructure. These converged services each have unique traffic holding and quality requirements. A positive user experience must be obtained through efficient partitioning of the available wireless...
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A Microwave Sensor with Operating Band Selection to Detect Rotation and Proximity in the Rapid Prototyping Industry
PublikacjaThis paper presents a novel sensor for detecting and measuring angular rotation and proximity, intended for rapid prototyping machines. The sensor is based on a complementary split-ring resonator (CSRR) driven by a conductor-backed coplanar waveguide. The sensor has a planar topology, which makes it simple and cost-effective to produce and accurate in measuring both physical quantities. The sensor has two components, a rotor, and...
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Determination of benzodiazepines and Z-hypnotic drugs in whole blood samples by GC–MS/MS: Method development, validation and application
PublikacjaBenzodiazepines (BZDs) and Z-drugs are widely used as anxiolytics, sedative hypnotics, anticonvulsants and muscle relaxants. “Designer benzodiazepines” (DBZDs) are a new psychoactive substance class consisting of benzodiazepine derivatives that are not allowed for medical use and are known for being used recreationally. From a toxicologist standpoint, the huge number of such substances implicate a necessity for developing fast...
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Jolanta Kowal dr hab.
OsobyJolanta Kowal has a Post-doctoral Degree in Social Sciences (dr hab., DSc) in the field of economics and finance, an assistant professor, researcher, and lecturer in the Institute of Psychology of Wroclaw University, and a professor of the Gdańsk University of Technology, Poland, a Jungian analyst. Jolanta from 2014 held functions in the Board of the Polish Chapter of the Association for Information Systems (PLAIS) (President 2015-2018,...
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Maxillary sinus aeration analysis using computational fluid dynamics
PublikacjaThe maxillary sinus aeration using the computational fluid dynamics (CFD) method based on individual adult patients’ computed tomography (CT) scans were analyzed. The analysis was based on CT images of 4 patients: one with normal nose anatomy and three with nasal septal deviation (NSD) and concha bullosa (CB). The CFD simulation was performed using the Reynolds-Average Simulation approach and turbulence closure based on linear...
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Thermal Image Processing for Respiratory Estimation from Cubical Data with Expandable Depth
PublikacjaAs healthcare costs continue to rise, finding affordable and non-invasive ways to monitor vital signs is increasingly important. One of the key metrics for assessing overall health and identifying potential issues early on is respiratory rate (RR). Most of the existing methods require multiple steps that consist of image and signal processing. This might be difficult to deploy on edge devices that often do not have specialized...
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Light4Health eLearning Course: health research for interior lighting design. Re-thinking design approaches based on science
PublikacjaThis paper presents the results of 'Light4Health' (L4H), a three-year EU Erasmus+ Strategic Partnership grant project (2019-2021), which investigated, systematized and taught health-related research on the impact of natural and artificial light on human health and well-being relevant to indoor lighting design. The objective was to re-think evidence-based lighting design approaches for residential, working/educational, and healthcare...
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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...
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An ANN-Based Approach for Prediction of Sufficient Seismic Gap between Adjacent Buildings Prone to Earthquake-Induced Pounding
PublikacjaEarthquake-induced structural pounding may cause major damages to structures, and therefore it should be prevented. This study is focused on using an artificial neural network (ANN) method to determine the sufficient seismic gap in order to avoid collisions between two adjacent buildings during seismic excitations. Six lumped mass models of structures with a different number of stories (from one to six) have been considered in...