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Search results for: accuracy analysis
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Comprehensive determination of flavouring additives and nicotine in e-cigarette refill solutions. Part I: Liquid chromatography-tandem mass spectrometry analysis
PublicationLiquid chromatography-tandem mass spectrometry with electrospray ionization (HPLC-ESI–MS/MS) methods were developed for the simultaneous determination of 42 flavouring compounds and nicotine in liquids for e-cigarettes. The chromatographic separation was performed using an Ace® Ultracore™ SuperC18™ (100 × 2.1 mm, 2.5 μm) column in both acidic and alkaline pH conditions to separate all the compounds. A simple “dilute & shoot” approach...
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Recent Advances in Accelerated Multi-Objective Design of High-Frequency Structures using Knowledge-Based Constrained Modeling Approach
PublicationDesign automation, including reliable optimization of engineering systems, is of paramount importance for both academia and industry. This includes the design of high-frequency structures (antennas, microwave circuits, integrated photonic components), where the appropriate adjustment of geometry and material parameters is crucial to meet stringent performance requirements dictated by practical applications. Realistic design has...
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Rapid Design Centering of Multi-Band Antennas Using Knowledge-Based Inverse Models and Response Features
PublicationAccounting for manufacturing tolerances as well as uncertainties concerning operating conditions and material parameters is one of the important yet often neglected aspects of antenna development. Appropriate quantification of uncertainties allows for estimating the fabrication yield but also to carry out robust design (e.g., yield maximization). For reliability reasons, statistical analysis should be executed at the accuracy level...
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Optimization of vortex-assisted supramolecular solvent-based liquid liquid microextraction for the determination of mercury in real water and food samples
PublicationA novel method was developed for sample preparation for spectrophotometric determination of Hg(II) in water and food samples. The method was based on vortex-assisted supramolecular solvent-assisted liquid-liquid microextraction (VA-SUPRASs-LLME). Analytical parameters such as pH, chelating agent, solvent type and volume, vortex time and salting out effect were optimized. Surface and normal probability plots were drawn for the variables...
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Analysis of the Dynamic Height Distribution at the Estuary of the Odra River Based on Gravimetric Measurements Acquired with the Use of a Light Survey Boat—A Case Study
PublicationLaCoste) for determining the dynamic height along the Odra River, in northwest Poland. The gravity measurement campaign described in this article was conducted on a small, hybrid-powered survey vessel (overall length: 9.5 m). We discuss a method for processing the results of gravimetric measurements performed on a mobile platform affected by strong external disturbances. Because measurement noise in most cases consists of signals...
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Utilizing UAV and orthophoto data with bathymetric LiDAR in google earth engine for coastal cliff degradation assessment
PublicationThis study introduces a novel methodology for estimating and analysing coastal cliff degradation, using machine learning and remote sensing data. Degradation refers to both natural abrasive processes and damage to coastal reinforcement structures caused by natural events. We utilized orthophotos and LiDAR data in green and near-infrared wavelengths to identify zones impacted by storms and extreme weather events that initiated mass...
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Domain adaptation for inpainting-based face recognition studies
PublicationRecent inpainting methods have demonstrated im-pressive outcomes in filling missing parts of images, especially for reconstructing facial areas obscured by occlusions. However, studies show that these models are not adequately effective in real-world applications, primarily due to data bias and the distribution of faces in images. This research focuses on domain adaptation of the commonly used Labeled Faces in the Wild (LFW) dataset,...
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Review of Segmentation Methods for Coastline Detection in SAR Images
PublicationSynthetic aperture radar (SAR) images acquired by airborne sensors or remote sensing satellites contain the necessary information that can be used to investigate various objects of interest on the surface of the Earth, including coastlines. The coastal zone is of great economic importance and is also very densely populated. The intensive and increasing use of coasts and changes of coastlines motivate researchers to try to assess...
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Clinical studies of detecting COVID-19 from exhaled breath with electronic nose
PublicationThe COVID‑19 pandemic has attracted numerous research studies because of its impact on society and the economy. The pandemic has led to progress in the development of diagnostic methods, utilizing the polymerase chain reaction (PCR) as the gold standard for coronavirus SARS‑CoV‑2 detection. Numerous tests can be used at home within 15 min or so but of with lower accuracy than PCR. There is still a need for point‑of‑care tests available...
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The Influence of Workpiece Hardness on Plate Temperature during One Side Lapping
PublicationLapping leads to a surface with low roughness and high precision. Because of required parts accuracy tool flatness is the key to the successful machining. To avoid its excessive thermal expansion, plate temperature research was taken. The goal was to determine the correlation between the basic lapping conditions and wheel temperature. In work Bulsara et al. authors developed model to estimate the maximum and average temperature...
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Development of a liquid chromatography–tandem mass spectrometryprocedure for determination of endocrine disrupting compounds infish from Mediterranean rivers
PublicationA new, sensitive and rapid method based on QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe)approach followed by ultra high performance liquid chromatography coupled with tandem mass spec-trometry (UHPLC–MS/MS) was developed for the determination of nineteen endocrine disruptors (EDCs)and related compounds belonging to different classes in various fish species. Matrix effect on the analyti-cal performance was evaluated,...
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Expedite EM-driven generation of Pareto-optimal trade-off curves for variable-turn on-chip inductors
PublicationThis work presents a novel approach to computationally efficient Pareto front identification for variable-turn on-chip inductors. The final outcome is a set of solutions that correspond to the best trade-offs between conflicting design objectives. Here, we consider minimising inductor area and, simultaneously, maximising its quality factor, while maintaining a specified inductance value at a given operating frequency. As opposed...
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Simulation-Driven Antenna Modeling by Means of Response Features and Confined Domains of Reduced Dimensionality
PublicationIn recent years, the employment of full-wave electromagnetic (EM) simulation tools has become imperative in the antenna design mainly for reliability reasons. While the CPU cost of a single simulation is rarely an issue, the computational overhead associated with EM-driven tasks that require massive EM analyses may become a serious bottleneck. A widely used approach to lessen this cost is the employment of surrogate models, especially...
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Improved Design Closure of Compact Microwave Circuits by Means of Performance Requirement Adaptation
PublicationNumerical optimization procedures have been widely used in the design of microwave components and systems. Most often, optimization algorithms are applied at the later stages of the design process to tune the geometry and/or material parameter values. To ensure sufficient accuracy, parameter adjustment is realized at the level of full-wave electromagnetic (EM) analysis, which creates perhaps the most important bottleneck due to...
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Neural network training with limited precision and asymmetric exponent
PublicationAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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Wykorzystanie metafor w identyfikacji i kształtowaniu postaw przedsiębiorczych
PublicationEdukacja przedsiębiorcza odgrywa coraz większą rolę w promowaniu i kształtowaniu zachowań oraz kompetencji przedsiębiorczych młodego pokolenia. W tym kontekście szczególnie podkreśla się znaczenie wykorzystywania nowych, interaktywnych metod i form kształcenia, niezwykle istotnych dla jednego z aspektów edukacji przedsiębiorczej, jakim jest kształcenie kreatywności i proaktywności. Zastosowanie metafor spełnia wymagania stawiane...
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Energy efficiency of electric multiple units in suburban operation
PublicationThis thesis presents approach to analysis of energy efficiency of a suburban rail network, using novel models developed on the Matlab/Simulink basis. Necessary features and requirements for such models were determined thru in-depth review of the source literature in all applicable fields: electrified transportation systems, electric multiple units construction, vehicle drivetrains and finally, existing simulation methods. Existing...
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Determination of benzodiazepines and Z-hypnotic drugs in whole blood samples by GC–MS/MS: Method development, validation and application
PublicationBenzodiazepines (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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Variable-Fidelity Simulation Models and Sparse Gradient Updates for Cost-Efficient Optimization of Compact Antenna Input Characteristics
PublicationDesign of antennas for the Internet of Things (IoT) applications requires taking into account several performance figures, both electrical (e.g., impedance matching) and field (gain, radiation pattern), but also physical constraints, primarily concerning size limitation. Fulfillment of stringent specifications necessitates the development of topologically complex structures described by a large number of geometry parameters that...
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Assessment of the Impact of GNSS Processing Strategies on the Long-Term Parameters of 20 Years IWV Time Series
PublicationAdvanced processing of collected global navigation satellite systems (GNSS) observations allows for the estimation of zenith tropospheric delay (ZTD), which in turn can be converted to the integrated water vapour (IWV). The proper estimation of GNSS IWV can be affected by the adopted GNSS processing strategy. To verify which of its elements cause deterioration and which improve the estimated GNSS IWV, we conducted eight reprocessings...
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Relation of the polymorphism of cyp51A sequence and the susceptibility of Aspergillus fumigatus isolates to triazoles determined by commercial gradient test (Etest) and by reference methods
PublicationThe aim of this study was to evaluate the accuracy of commercial gradient test (Etest) in the detection of triazole resistant Aspergillus fumigatus isolates using reference microdilution methods and the analysis of sequences of the cyp 51A gene. The study was performed on twenty clinical isolates which were identified as Aspergillus fumigatus based on the DNA sequences of the ITS1-2 fragment of ribosomal DNA and the β-tubulin gene,...
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Determination of t8/5 cooling times for underwater local dry welding of steel
PublicationKnowledge of thermal history is the basic condition for studying the structure - properties of welded joints. The determinant of thermal history is the thermal cycle, whose in-situ measurements are still a big challenge. Water as the welding environment complicates this issue even more. The article presents a method to determine an equation for calculating t8/5 cooling times for underwater gas metal arc welding of unalloyed steels...
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A Robust Random Forest Model for Classifying the Severity of Partial Discharges in Dielectrics
PublicationPartial Discharges (PDs) are a common source of degradation in electrical assets. It is essential that the extent of the deterioration level of insulating medium is correctly identified, to optimize maintenance schedules and prevent abrupt power outages. Temporal PD signals received from damaged insulation, collected through the IEC-60270 method is the gold standard for PD detection. Temporal signals may be transformed to the frequency...
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Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-Learned Features
PublicationNematodes 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...
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Quality of graphical markers for the needs of eyewear devices
Publicationin this paper we propose to cast the problem of identification of people, objects or places into an application for smart glasses that decodes information from graphical markers. We focus on analyzing different factors that can have influence on the processes of the automatic recognition of information from a code. The research we present aims at reviewing recognition performances in function of: size of a marker, distance from/to...
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Deep learning-based waste detection in natural and urban environments
PublicationWaste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems are addressed in this article by...
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Magnetic Signature Description of Ellipsoid-Shape Vessel Using 3D Multi-Dipole Model Fitted on Cardinal Directions
PublicationThe article presents a continuation of the research on the 3D multi-dipole model applied to the reproduction of magnetic signatures of ferromagnetic objects. The model structure has been modified to improve its flexibility - model parameters determined by optimization can now be located in the cuboid contour representing the object's hull. To stiffen the model, the training dataset was expanded to data collected from all four cardinal...
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Increasing the Geometrical and Interpretation Quality of Unmanned Aerial Vehicle Photogrammetry Products Using Super-Resolution Algorithms
PublicationUnmanned aerial vehicles (UAVs) have now become very popular in photogrammetric and remote-sensing applications. Every day, these vehicles are used in new applications, new terrains, and new tasks, facing new problems. One of these problems is connected with flight altitude and the determined ground sample distance in a specific area, especially within cities and industrial and construction areas. The problem is that a safe flight...
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NUMERICAL ESTIMATION OF HULL HYDRODYNAMIC DERIVATIVES IN SHIP MANOUVERING PREDICTION
PublicationOperating in crowded waterways pose a risk of accidents and disasters due to maneuvering limitations of the ship. In order to predict ship’s maneuvering characteristics at the design stage, model tests are often executed as the most accurate prediction tool. Two approaches can be distinguished here: free running model tests and numerical simulations based on planar motion model with the use of hydrodynamic derivatives obtained...
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Offshore benthic habitat mapping based on object-based image analysis and geomorphometric approach. A case study from the Slupsk Bank, Southern Baltic Sea
PublicationBenthic habitat mapping is a rapidly growing field of underwater remote sensing studies. This study provides the first insight for high-resolution hydroacoustic surveys in the Slupsk Bank Natura 2000 site, one of the most valuable sites in the Polish Exclusive Zone of the Southern Baltic. This study developed a quick and transparent, automatic classification workflow based on multibeam echosounder and side-scan sonar surveys to...
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Nowa metoda diagnostyki stanu technicznego nakładek stykowych
PublicationThe current collection system, which consists of the overhead contact line and a current collector, is particularly important in electric rail vehicles, where their reliability is concerned. Faultless current collection is conditioned not only by suitable construction of these elements but also by their proper maintenance. Retaining permanent electrical contact is essential in DC systems, where current demand is relatively high. In...
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SegSperm - a dataset of sperm images for blurry and small object segmentation
Open Research DataMany deep learning applications require figure-ground segmentation. The performance of segmentation models varies across modalities and acquisition settings.
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Data from 76- to 81-GHz mmWave Sensor located at S7 road
Open Research DataThe set consists data recorded employing IWR1642 mmWave sensor from Texas Instruments. The purpose of the experiment was to detect vehicles and their speed in real conditions – at S7 road, near Dworek village (54°14'40.0"N 18°59'59.0"E).
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The application of non-destructive methods in the diagnostics of the approach pavement at the bridges
PublicationThe article presents the possibility of using non-destructive methods of road pavement diagnostics as an alternative to traditional means to assess the reasons for premature cracks adjacent to bridge objects. Two scanning methods were used: laser scanning to measure geometric surface deformation and ground penetrating radar (GPR) inspection to assess the road pavement condition. With the use of a laser scanner, an effective tool...
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Spectral Finite Element Method in Condition Monitoring and Damage Detection
PublicationIt is well known that the dynamic behaviour of engineering structures may carry very important and crucial information that can be further used for the assessment of their condition as well as detection of any damage induced. The current interest in monitoring techniques based on the propagation of guided elastic waves requires that numerical techniques used for modelling the phenomena associated must shift into the realm of high...
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Antenna Optimization Using Machine Learning with Reduced-Dimensionality Surrogates
PublicationIn modern times, antenna design has become more demanding than ever. The escalating requirements for performance and functionality drive the development of intricately structured antennas, where parameters must be meticulously adjusted to achieve peak performance. Often, global adjustments to geometry are necessary for optimal results. However, direct manipulation of antenna responses evaluated with full-wave electromagnetic (EM)...
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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublicationHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
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Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublicationIntroduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...
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Tool Wear Monitoring Using Improved Dragonfly Optimization Algorithm and Deep Belief Network
PublicationIn recent decades, tool wear monitoring has played a crucial role in the improvement of industrial production quality and efficiency. In the machining process, it is important to predict both tool cost and life, and to reduce the equipment downtime. The conventional methods need enormous quantities of human resources and expert skills to achieve precise tool wear information. To automatically identify the tool wear types, deep...
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Development of an AI-based audiogram classification method for patient referral
PublicationHearing loss is one of the most significant sensory disabilities. It can have various negative effects on a person's quality of life, ranging from impeded school and academic performance to total social isolation in severe cases. It is therefore vital that early symptoms of hearing loss are diagnosed quickly and accurately. Audiology tests are commonly performed with the use of tonal audiometry, which measures a patient's hearing...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublicationMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Design-Oriented Two-Stage Surrogate Modeling of Miniaturized Microstrip Circuits with Dimensionality Reduction
PublicationContemporary microwave design heavily relies on full-wave electromagnetic (EM) simulation tools. This is especially the case for miniaturized devices where EM cross-coupling effects cannot be adequately accounted for using equivalent network models. Unfortunately, EM analysis incurs considerable computational expenses, which becomes a bottleneck whenever multiple evaluations are required. Common simulation-based design tasks include...
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Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
PublicationThe purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....
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On Inadequacy of Sequential Design of Experiments for Performance-Driven Surrogate Modeling of Antenna Input Characteristics
PublicationDesign of contemporary antennas necessarily involves electromagnetic (EM) simulation tools. Their employment is imperative to ensure evaluation reliability but also to carry out the design process itself, especially, the adjustment of antenna dimensions. For the latter, traditionally used parameter sweeping is more and more often replaced by rigorous numerical optimization, which entails considerable computational expenses, sometimes...
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Can Web Search Queries Predict Prices Change on the Real Estate Market?
PublicationThis study aims to explore whether the intensity of internet searches, according to the Google Trends search volume index (SVI), is a predictor of changes in real estate prices. The motivation of this study is the possibility to extend the understanding of the extra predictive power of Google search engine query volume of future housing price change (shift direction) by (i) the introduction of a research approach that combines...
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Analysis of heat transfer and AuNPs-mediated photo-thermal inactivation of E. coli at varying laser powers using single-phase CFD modeling
PublicationPurpose In the wake of the COVID-19 pandemics, the demand for innovative and effective methods of bacterial inactivation has become a critical area of research, providing the impetus for this study. The purpose of this research is to analyze the AuNPs-mediated photothermal inactivation of E. coli. Gold nanoparticles irradiated by laser represent a promising technique for combating bacterial infection that combines high-tech and...
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Buckling analysis of piezo-magnetoelectric nanoplates in hygrothermal environment based on a novel one variable plate theory combining with higher-order nonlocal strain gradient theory
PublicationIn the present investigation, a new first-order shear deformation theory (OVFSDT) on the basis of the in-plane stability of the piezo-magnetoelectric composite nanoplate (PMEN) has been developed, and its precision has been evaluated. The OVFSDT has many advantages compared to the conventional first-order shear deformation theory (FSDT) such as needless of shear correction factors, containing less number of unknowns than the existing...
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Wiktoria Wojnicz dr hab. inż.
PeopleDSc in Mechanics (in the field of Biomechanics) - Lodz Univeristy of Technology, 2019 PhD in Mechanics (in the field of Biomechanics) - Lodz Univeristy of Technology, 2009 (with distinction) List of papers (2009 - ) Wojnicz W., Wittbrodt E., Analysis of muscles' behaviour. Part I. The computational model of muscle. Acta of Bioengineering and Biomechanics, Vol. 11, No.4, 2009, p. 15-21 Wojnicz W., Wittbrodt E., Analysis of...
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Automatic recognition of males and females among web browser users based on behavioural patterns of peripherals usage
PublicationPurpose The purpose of this paper is to answer the question whether it is possible to recognise the gender of a web browser user on the basis of keystroke dynamics and mouse movements. Design/methodology/approach An experiment was organised in order to track mouse and keyboard usage using a special web browser plug-in. After collecting the data, a number of parameters describing the users’ keystrokes, mouse movements and clicks...