Filters
total: 1363
filtered: 1273
-
Catalog
Chosen catalog filters
displaying 1000 best results Help
Search results for: ACCURACY
-
Histogram of Gradients with Cell Average Intensity for Human Detection
PublicationThe modification of the descriptor in human detector using Histogram of Oriented Gradients and support vector machine is presented. The proposed modification requires inserting the average cell intensitiesresulting with the increase of the length of the descriptor from 3780 to 4200 values, but it is easy to compute and instantly gives 14-26% of miss rate improvement at 10^-4 False Positives Per Window (FPPW). The modification...
-
Computational methods for calculation of binding free energy for ligand-receptor complexes
PublicationAccurate description of the molecular complexes energetic influence is required for understanding of many biological functions carried out by proteins. Therefore, estimation of binding free energy for ligand-receptor complexes is of highest importance for structure-based ligand design and drug discovery approaches.Experimental methods of determination of difference in Gibbs'es free energy have many limitations. Thus, computational...
-
Role of distillation in determination of SCFAs in samples of different origin
PublicationShort-chain fatty acids (SCFAs) are very volatile compounds and choosing an appropriate isolation and enrichement technique is a key to their determination. Distillation is one of methods which can be applied. There are many types of distillation. The simplest ones are direct, steam and fractional distillation, but they are not used very often and have some drawbacks. However, many modifications of basic distillation have been...
-
Orthotropic membrane as a mechanical model of surgical implant in abdominal hernia repair
PublicationEven though the incisional hernia repair surgery is a well known procedure, mechanical properties of the tissue-implant system are unknown so the implantation of the repairing mesh is quite intuitive and, recurrences of the illness still take place. The main objective of the study is to define an operated hernia model that can be used for surgery planning and the assessment of the repair persistence. The load applied to the structure...
-
A Power-Efficient Digital Technique for Gain and Offset Correction in Slope ADCs
PublicationIn this brief, a power-efficient digital technique for gain and offset correction in slope analog-to-digital converters (ADCs) has been proposed. The technique is especially useful for imaging arrays with massively parallel image acquisition where simultaneous compensation of dark signal non-uniformity (DSNU) as well as photo-response non-uniformity (PRNU) is critical. The presented approach is based on stopping the ADC clock by...
-
Monitoring the BTEX Volatiles during 3D Printing with Acrylonitrile Butadiene Styrene (ABS) Using Electronic Nose and Proton Transfer Reaction Mass Spectrometry
PublicationWe describe a concept study in which the changes of concentration of benzene, toluene, ethylbenzene, and xylene (BTEX) compounds and styrene within a 3D printer enclosure during printing with different acrylonitrile butadiene styrene (ABS) filaments were monitored in real-time using a proton transfer reaction mass spectrometer and an electronic nose. The quantitative data on the concentration of the BTEX compounds, in particular...
-
Flexural behavior of composite structural insulated panels with magnesium oxide board facings
PublicationThe current report is devoted to the flexural analysis of a composite structural insulated panel (CSIP) with magnesium oxide board facings and expanded polystyrene (EPS) core, that was recently introduced to the building industry. An advanced nonlinear FE model was created in the ABAQUS environment, able to simulate the CSIP’s flexural behavior in great detail. An original custom code procedure was developed, which allowed to include...
-
Detection of moving objects in images combined from video and thermal cameras
PublicationAn algorithm for detection of moving objects in video streams from the monitoring cameras is presented. A system composed of a standard video camera and a thermal camera, mounted in close proximity to each other, is used for object detection. First, a background subtraction is performed in both video streams separately, using the popular Gaussian Mixture Models method. For the next processing stage, the authors propose an algorithm...
-
Spatial Calibration of a Dual PTZ-Fixed Camera System for Tracking Moving Objects in Video
PublicationA dual camera setup is proposed, consisting of a fixed (stationary) camera and a pan-tilt-zoom (PTZ) camera, employed in an automatic video surveillance system. The PTZ camera is zoomed in on a selected point in the fixed camera view and it may automatically track a moving object. For this purpose, two camera spatial calibration procedures are proposed. The PTZ camera is calibrated in relation to the fixed camera image, using interpolated...
-
Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
PublicationA problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is based on a well-known NeuroEvolution of Augmenting Topologies (NEAT) algorithm. The NEAT algorithm has been adjusted by allowing additional connections within an artificial neural network and...
-
OVERALL SET OF BANDSAW TEETH VERSUS METHODS OF MEASUREMENTS
PublicationThis article deals with the impact of the manual methods of measurement on the overall set measurement results. It describes the results of the measurement of bandsaw teeth kerf with the use of a micrometer and a digital calliper. It is commonly known that the cutting process causes the wear of cutting tools. The wear of the cutting edge depends on the cutting conditions as well as on the mechanical properties of the processed...
-
Bending and buckling formulation of graphene sheets based on nonlocal simple first-order shear deformation theory
PublicationThis paper presents a formulation based on simple first-order shear deformation theory (S-FSDT) for large deflection and buckling of orthotropic single-layered graphene sheets (SLGSs). The S-FSDT has many advantages compared to the classical plate theory (CPT) and conventional FSDT such as needless of shear correction factor, containing less number of unknowns than the existing FSDT and strong similarities with the CPT. Governing...
-
Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublicationMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
-
Fault detection and diagnostics of complex dynamic systems using Gaussian Process Models - nuclear power plant case study
PublicationThe article examines the use of Gaussian Process Models to simulate the dynamic processes of a Pressurized Water nuclear Reactor for fault detection and diagnostics. The paper illustrates the potential of Gaussian Process Models as a tool for monitoring and predicting various fault conditions in Pressurized Water nuclear Reactor power plants, including reactor coolant flow and temperature variations, deviations from nominal working...
-
Parallel implementation of a Sailing Assistance Application in a Cloud Environment
PublicationSailboat weather routing is a highly complex problem in terms of both the computational time and memory. The reason for this is a large search resulting in a multitude of possible routes and a variety of user preferences. Analysing all possible routes is only feasible for small sailing regions, low-resolution maps, or sailboat movements on a grid. Therefore, various heuristic approaches are often applied, which can find solutions...
-
Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublicationTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
-
Crank–Nicolson FDTD Method in Media Described by Time-Fractional Constitutive Relations
PublicationIn this contribution, we present the Crank-Nicolson finite-difference time-domain (CN-FDTD) method, implemented for simulations of wave propagation in media described by time-fractional (TF) constitutive relations. That is, the considered constitutive relations involve fractional-order (FO) derivatives based on the Grünwald-Letnikov definition, allowing for description of hereditary properties and memory effects of media and processes....
-
Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublicationIn this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern,...
-
Monitoring of absorptive model biogas purification process using sensor matrices and gas chromatography
PublicationThis study examined the process of purifying model biogas using a new type of absorbent based on a Deep Eutectic Solvent (DES) and a commercially available absorbent (Genosorb) to remove acetone, toluene, and cyclohexane. The main aim of the research was to control the purification efficiency using gas chromatography (GC) and an alternative method based on sensor matrices (SM). As a result of comparing the multidimensional SM signals...
-
Temperature Measurements at Tyre Tread Rubber on Sandpaper Oscillatory Sliding Contacts Using Acicular Grindable Thermocouples
PublicationThe tribological performance of tyre–road contacts depends crucially on the contact temperature. This study investigates the reliability and accuracy of acicular grindable thermocouples possessing an original needle-shaped wearable part as applied to measuring temperature at the oscillatory sliding contact between a rubber tyre tread sample and a sandpaper. A linear oscillatory tribometer is used to imitate the sliding phase of...
-
A simple and efficient hybrid discretization approach to alleviate membrane locking in isogeometric thin shells
PublicationThis work presents a new hybrid discretization approach to alleviate membrane locking in isogeometric finite element formulations for Kirchhoff–Love shells. The approach is simple, and requires no additional dofs and no static condensation. It does not increase the bandwidth of the tangent matrix and is effective for both linear and nonlinear problems. It combines isogeometric surface discretizations with classical Lagrange-based...
-
Optimal placement of IMU sensor for the detection of children activity
PublicationIn this paper an investigation to determine the optimal placement of IMU sensors for the purpose of children characteristic activity detection is presented. The article compares four different placement of two IMU sensors on human body. Ten healthy volunteers participated within the study. Data were collected firstly from two wireless 9-axial IMU sensors placed at the left and right wrists, then sensors were placed at lower back...
-
Toward Human Chromosome Knowledge Engine
PublicationHuman chromosomes carry genetic information about our life. Chromosome classification is crucial for karyotype analysis. Existing chromosome classification methods do not take into account reasoning, such as: analyzing the relationship between variables, modeling uncertainty, and performing causal reasoning. In this paper, we introduce a knowledge engine for reasoning-based human chromosome classification that stores knowledge...
-
Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublicationBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
-
Computer Supported Analysis of the Human Body Surface Area
PublicationRecent scientific studies show the growing importance of the coefficients: BSA and TBSA, as an alternative to the widely used BMI. The relevant indicators are widely used in medicine, including such areas as: the treatment of burns, chemotherapy, dermatology and toxicology; as benchmarks when calculating doses of drugs and fluids. The particular problems concerning this subject are: the change of the reference parameter value which...
-
Calculation of Vibrational Resonance Raman Spectra of Molecules Using Quantum Chemistry Methods
PublicationThe understanding and interpretation of experimental resonance Raman (RR) spectra can strongly benefit from theoretical simulations. These can be achieved by combining quantum chemistry (QC) methods to calculate the electronic and vibrational molecular properties, together with appropriate models and approximations to compute the Raman intensities. This chapter presents the main and most commonly employed approaches to calculate...
-
Sensitivity analysis of free torsional vibration frequencies of thin-walled laminated beams under axial load
PublicationThe paper addresses sensitivity analysis of free torsional vibration frequencies of thin-walled beams of bisymmetric open cross-section made of unidirectional fibre-reinforced laminate. The warping effect and the axial end load are taken into account. The consideration is based upon the classical theory of thin-walled beams of non-deformable cross-section. The first-order sensitivity variation of the frequencies is derived with...
-
An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key
PublicationThe topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...
-
Comprehensive dimension scaling of multi-band antennas for operating frequencies and substrate parameters
PublicationIn this paper, low-cost and comprehensive redesign of multi-band antennas with respect to the operating frequencies and material parameters of the substrate is presented. Our approach exploits an inverse surrogate model identified based on a set of reference designs optimized at the level of coarse-discretization EM simulations of the antenna at hand. An iterative correction procedure is also implemented to account for the initial...
-
Autonomous Ship Utility Model Parameter Estimation Utilising Extended Kalman Filter
PublicationIn this paper, a problem of autonomous ship utility model identification for control purposes is considered. In particular, the problem is formulated in terms of model parameter estimation (one-step-ahead prediction). This is a complex task due to lack of measurements of the parameter values, their time-variability and structural uncertainty introduced by the available models. In this work, authors consider and compare two utility...
-
A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublicationThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
-
Towards Improving Optimised Ship Weather Routing
PublicationThe aim of the paper is to outline a project focusing on the development of a new type of ship weather routing solution with improved uncertainty handling, through better estimation of ship performance and responses to sea conditions. Ensemble forecasting is considered to take into account the uncertainty levels that are typical of operations in a stochastic environment. Increased accuracy of weather prediction is achieved through...
-
CNN Architectures for Human Pose Estimation from a Very Low Resolution Depth Image
PublicationThe paper is dedicated to proposing and evaluating a number of convolutional neural network architectures for calculating a multiple regression on 3D coordinates of human body joints tracked in a single low resolution depth image. The main challenge was to obtain a high precision in case of a noisy and coarse scan of the body, as observed by a depth sensor from a large distance. The regression network was expected to reason about...
-
Multibeam Echosounder and LiDAR in Process of 360-Degree Numerical Map Production for Restricted Waters with HydroDron
PublicationIn order to increase the safety of inland navigation and facilitate the monitoring of the coastal zone of restricted waters, a model of multi-sensory fusion of data from hydroacoustic and optoelectronic systems mounted on the autonomous survey vessel HydroDron will be developed. In the research will be used the LiDAR laser scanner and multibeam echosounder. To increase the visual quality and map accuracy, additionally side scan...
-
Multi-domain and Context-Aware Recommendations Using Contextual Ontological User Profile
PublicationRecommender Systems (RS) became popular tools in many Web services like Netflix, Amazon, or YouTube, because they help a~user to avoid an information overload problem. One of the types of RS are Context-Aware RS (CARS) which exploit contextual information to provide more adequate recommendations. Cross-Domain RS (CDRS) were created as a response to the data sparsity problem which occurs when only few users can provide reviews or...
-
TEMPERATURE INFLUENCE ON TIRE ROLLING RESISTANCE MEASUREMENTS QUALITY
PublicationGlobal warming makes it necessary to reduce energy consumption, which in the case of motor vehicles, is connected, among other things, with reduction of resistive forces acting on a vehicle during its motion. One of the most important components of those forces is rolling resistance, which is very difficult to measure, especially in road conditions. The article deals with issues related to the influence of the thermal state of...
-
SHEAR YIELD STRESSES AND FRACTURE TOUGHNESS OF SCOTS PINE (PINUS SYLVESTRIS L.) ACCORDING TO THE RAW MATERIAL PROVENANCE
PublicationIn this paper values of the fracture toughness and of shear yield stress in the shear zone of Scots pine are presented. Tests of cutting were carried on samples of Scotch pine (Pinus sylvestris L.) wood of five provenances from Poland. These experimentally cutting tests were carried on the sash gang saw PRW-15M and the values of cutting power were obtained. The values of fracture toughness and shear yield stress based on Atkins’s...
-
Modeling energy consumption of parallel applications
PublicationThe paper presents modeling and simulation of energy consumption of two types of parallel applications: geometric Single Program Multiple Data (SPMD) and divide-and-conquer (DAC). Simulation is performed in a new MERPSYS environment. Model of an application uses the Java language with extension representing message exchange between processes working in parallel. Simulation is performed by running threads representing distinct process...
-
Evaluation of applicability of classic methods of a fault loop impedance measurement to circuits with residual current devices
PublicationMeasurement of fault loop impedance in low voltage grids and systems is in most cases performed to verify the effectiveness of protection against electric shock by automatic disconnection of supply. For the sake of measurement accuracy, it is advisable to perform it using large current. Unfortunately, in circuits with residual current devices which are very widely used nowadays, a large measurement current may trigger those devices...
-
Learning design of a blended course in technical writing
PublicationBlending face-to-face classes with e-learning components can lead to a very successful outcome if the blend of approaches, methods, content, space, time, media and activities is carefully structured and approached from both the student’s and the tutor’s perspective. In order to blend synchronous and asynchronous e-learning activities with traditional ones, educators should make them inter-dependent and develop them according to...
-
Comparative analysis of various transformation techniques for voiceless consonants modeling
PublicationIn this paper, a comparison of various transformation techniques, namely Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT) and Discrete Walsh Hadamard Transform (DWHT) are performed in the context of their application to voiceless consonant modeling. Speech features based on these transformation techniques are extracted. These features are mean and derivative values of cepstrum coefficients, derived from each transformation....
-
Performance Evaluation of GAM in Off-Body Path Loss Modelling for Body Area Networks
PublicationThis paper addresses the performance evaluation of an off-body path loss model, based on measurements at 2.45 GHz, which has been developed with the use of the Generalised Additive Model, allowing to model a non-linear dependence on different predictor variables. The model formulates path loss as a function of distance, antennas’ heights, antenna orientation angle and polarisation, results showing that performance is very sensitive...
-
Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublicationThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...
-
Power control system structure of doubly‐fed induction generator connected to current source converter
PublicationThe power control system structures for a doubly-fed generator (DFIG) are proposed. The classical field oriented control and the feedback control with the multi-scalar variables were considered. The generator is working in the AC grid connection mode. The rotor side of the generator is connected to the current source converter (CSC); the stator is directly related to the AC grid. The static feedback linearization using the multi-scalar...
-
Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
-
Badania eksperymentalne i symulacyjne dynamiki modelowego odcinka sieci trakcyjnej
PublicationW pracy przedstawiono główne założenia i strukturę opracowanego modelu matematycznego odcinka kolejowej górnej sieci trakcyjnej, opartego na metodzie energetycznej Lagrange’a. W celu wyznaczenia wybranych parametrów modelu, jak również dla oceny stopnia zgodności odwzorowania przez utworzony program symulacyjny stanów statycznych i dynamicznych sieci zbudowano laboratoryjny model odcinka sieci jezdnej z użyciem rzeczywistych jej...
-
Sterowanie predykcyjne i fuzja danych w systemie dynamicznego pozycjonowania statku
PublicationRozprawa doktorska poświęcona jest badaniu zastosowania fuzji danych oraz sterowania predykcyjnego w systemie dynamicznego pozycjonowania statku. W pierwszej części pracy przedstawiono historię rozwoju systemów dynamicznego pozycjonowania, różne metody estymacji położenia statku, metody sterowania oraz cel i tezę pracy. Następnie zaprezentowano model matematyczny statku, kinematykę oraz dynamikę. W kolejnej części przedstawiono...
-
Automated Detection of Sleep Apnea and Hypopnea Events Based on Robust Airflow Envelope Tracking in the Presence of Breathing Artifacts. - [IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS]
PublicationThe paper presents a new approach to detection of apnea/hypopnea events, in the presence of artifacts and breathing irregularities, from a single channel airflow record. The proposed algorithm, based on a robust envelope detector , identifies segments of signal affected by a high amplitude mo d- ulation corresponding to apnea/hypopnea events. It is show n that a robust airflow envelope - free of breathing artifacts - improves effectiveness...
-
Theoretical study of the photoelectron spectrum of ethyl formate: Ab initio and density functional theory investigation
PublicationThe first ionization energy and associated photoelectron spectrum of ethyl formate are investigated with quantum chemistry calculations. The geometries, harmonic vibrational frequencies and first ionization energy are computed at the Hartree-Fock (HF) and at the second order Moller-Plesset perturbation theory (MP2). Moreover, accurate ionization energies are obtained with the Coupled-Cluster theory including singles and doubles...
-
Efficient model order reduction for FEM analysis of waveguide structures and resonators
PublicationAn efficient model order reduction method for three-dimensional Finite Element Method (FEM) analysis of waveguide structures is proposed. The method is based on the Efficient Modal Order Reduction (ENOR) algorithm for creating macro-elements in cascaded subdomains. The resulting macro-elements are represented by very compact submatrices, leading to significant reduction of the overall number of unknowns. The efficiency of the model...