Filters
total: 10398
filtered: 9447
-
Catalog
Chosen catalog filters
displaying 1000 best results Help
Search results for: SYMPTOM-BASED PREDICTION
-
Lattice filter based multivariate autoregressive spectral estimation with joint model order and estimation bandwidth adaptation
PublicationThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a multivariate nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running...
-
Exergy and Energy Analyses of Microwave Dryer for Cantaloupe Slice and Prediction of Thermodynamic Parameters Using ANN and ANFIS Algorithms
PublicationThe study targeted towards drying of cantaloupe slices with various thicknesses in a microwave dryer. The experiments were carried out at three microwave powers of 180, 360, and 540 W and three thicknesses of 2, 4, and 6 mm for cantaloupe drying, and the weight variations were determined. Artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) were exploited to investigate energy and exergy indices of...
-
Ship Dynamic Positioning Based on Nonlinear Model Predictive Control
PublicationThe presented work explores the simulation test results of using nonlinear model predictive control algorithm for ship dynamic positioning. In the optimization task, a goal function with a penalty was proposed with a variable prediction step. The results of the proposed control algorithm were compared with backstepping and PID. The effect of estimation accuracy on the control quality with the implemented algorithms was investigated....
-
On Memory-Based Precise Calibration of Cost-Efficient NO2 Sensor Using Artificial Intelligence and Global Response Correction
PublicationNitrogen dioxide (NO2) is a prevalent air pollutant, particularly abundant in densely populated urban regions. Given its harmful impact on health and the environment, precise real-time monitoring of NO2 concentration is crucial, particularly for devising and executing risk mitigation strategies. However, achieving precise measurements of NO2 is challenging due to the need for expensive and cumbersome equipment. This has spurred...
-
Ladder-Based Synthesis and Design of Low-Frequency Buffer-Based CMOS Filters
PublicationBuffer-based CMOS filters are maximally simplified circuits containing as few transistors as possible. Their applications, among others, include nano to micro watt biomedical sensors that process physiological signals of frequencies from 0.01 Hz to about 3 kHz. The order of a buffer-based filter is not greater than two. Hence, to obtain higher-order filters, a cascade of second-order filters is constructed. In this paper, a more...
-
Mathematical modeling and prediction of pit to crack transition under cyclic thermal load using artificial neural network
PublicationThe formation of pitting is a major problem in most metals, which is caused by extremely localized corrosion that creates small holes in metal and subsequently, it changes into cracks under mechanical load, thermo-mechanical stress, and corrosion process factors. This research aims to study pit to crack transition phenomenon of steel boiler heat tubes under cyclic thermal load, and mathematical modeling...
-
The Green Approach to the Synthesis of Bio-Based Thermoplastic Polyurethane Elastomers with Partially Bio-Based Hard Blocks
PublicationBio-based polymeric materials and green routes for their preparation are current issues of many research works. In this work, we used the diisocyanate mixture based on partially bio-based diisocyanate origin and typical petrochemical diisocyanate for the preparation of novel bio-based thermoplastic polyurethane elastomers (bio-TPUs). We studied the influence of the diisocyanate mixture composition on the chemical structure, thermal,...
-
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...
-
Prediction of the structures of proteins with the UNRES force field, including dynamic formation and breaking of disulfide bonds
Publication -
Fragmental Method KowWIN as the Powerful Tool for Prediction of Chromatographic Behavior of Novel Bioactive Urea Derivatives
Publication -
Prediction Model for Hemorrhagic Complications after Laparoscopic Sleeve Gastrectomy: Development of SLEEVE BLEED Calculator
Publication -
EXPERIMENTAL VERIFICATION OF THE METHOD OF FLOW BOILING AND FLOW CONDENSATION HEAT TRANSFER PREDICTION FOR SELECTED FLUIDS
PublicationIn the paper presented are the results of calculations using authors own model to predict heat transfer coefficient during flow boiling of different refrigerants. The experimental data from various research studies from literature were collected. Calculations were conducted for a full range of quality variation and a wide range of mass velocity. The aim of the study was to test the sensitivity of the in- house developed model....
-
Scale effect in the self-propulsion prediction for Ultra Large Container Ship with contra-rotating propellers
PublicationThis article addresses the problem of the scale effect for an Ultra Large Container Ship (ULCS) with a novel twin-crp-pod propulsion system. Twin-crp-pod steering-propulsion arrangement is an innovative solution that gains from three well-known systems: twin-propeller, contra-rotating propellers and pod propulsors. It is expected that applying the twin-crp-pod system to the analysed Ultra Large Container Ship will increase propulsion...
-
Advanced Scalar-valued Intensity Measures for Residual Drift Prediction of SMRFs with Fluid Viscous Dampers
PublicationMaximum Residual Inter-story Drift Ratio (RIDRmax) plays an important role to specify the state of a structure after severe earthquake and the possibility of repairing the structure. Therefore, it is necessary to predict the RIDRmax of Steel Moment-Resisting Frames (SMRFs) with high reliability by employing powerful Intensity Measures (IMs). This study investigates the efficiency and sufficiency of scalar-valued IMs for predicting...
-
From the pills to environment – Prediction and tracking of non-steroidal anti-inflammatory drug concentrations in wastewater
PublicationThe extend of environment pollution by pharmaceuticals is in a stage that required more automatic and integrated solutions. The non-steroidal anti-inflammatory drugs (NSAIDs) are one of the most popular pharmaceutical in the world and emerging pollutants of natural waters. The aim of the paper was to check the correlation of the sales data of selected NSAIDs (ibuprofen, naproxen, diclofenac) and their concentration in the WWTP...
-
A green route for high-performance bio-based polyurethanes synthesized from modified bio-based isocyanates
PublicationThe need for sustainability and a circular economy leads to the development of innovative greener materials and technologies. This paper is focused on a novel class of bio-based polyurethanes (PUs) synthesized with the use of bio-monomers including bio-based isocyanates. The novelty of this work is related to the usage of bio-based modified isocyanate via a two-step solvent-free synthesis of novel cast bio-based poly(ester-urethanes)...
-
Implementation and performance evaluation of the agent-based algorithm for ANN training
Publication -
Distributed System For Noise Threat Evaluation Based On Psychoacoustic Measurements
PublicationAn innovative system designed for the continuous monitoring of acoustic climate of urban areas was presentedin the paper. The assessment of environmental threats is performed using online data, acquired through a grid ofengineered monitoring stations collecting comprehensive information about the acoustic climate of urban areas.The grid of proposed devices provides valuable data for the purpose of long and short time acoustic climateanalysis....
-
Inseparability criteria based on matrices of moments
PublicationInseparability criteria for continuous and discrete bipartite quantum states based on moments of annihilationand creation operators are studied by developing the idea of Shchukin-Vogel criterion Phys. Rev. Lett. 95,230502 2005. If a state is separable, then the corresponding matrix of moments is separable too. Thus, wederive generalized criteria based on the separability properties of the matrix of moments. In particular, acriterion...
-
Improved Consensus-Fragment Selection in Template-Assisted Prediction of Protein Structures with the UNRES Force Field in CASP13
Publication -
Evaluation of the scale-consistent UNRES force field in template-free prediction of protein structures in the CASP13 experiment
Publication -
Impact of Feature Selection Methods on the Predictive Performance of Software Defect Prediction Models: An Extensive Empirical Study
Publication -
Solubility of sulfanilamide in binary solvents containing water: Measurements and prediction using Buchowski-Ksiazczak solubility model
Publication -
Comparative Analysis of microRNA-Target Gene Interaction Prediction Algorithms - The Attempt to Compare the Results of Three Algorithms
Publication -
Quantitative Soil Characterization for Biochar–Cd Adsorption: Machine Learning Prediction Models for Cd Transformation and Immobilization
Publication -
Principles for the Application of Vibration Intensity Scale for the Prediction and Assessment of Impact of Actions of Exploitation Mine on Buildings and People
Publication -
Plasma Amino Acids May Improve Prediction Accuracy of Cerebral Vasospasm after Aneurysmal Subarachnoid Haemorrhage
Publication -
Prediction of Thymine Dimer Repair by Electron Transfer from Photoexcited 8-Aminoguanine or Its Deprotonated Anion
Publication -
Experimental investigations and prediction of WEDMed surface of nitinol SMA using SinGAN and DenseNet deep learning model
Publication -
Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
PublicationIonic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship...
-
Comparison of selected parametric methods for prediction of inland waterways ship hull resistance in towing tank test
PublicationIn the paper selected approximate methods for calculation of inland waterways ship resistance and their verification by towing tests, compared on the example of a small urban ferry, are presented. The test results are made for both the bare hull and the hull with appendages (skeg, azimuthal propeller). Significant differences between results of the theoretical methods and experimental ones, especially in the case of the model with...
-
Model of Volunteer Based Systems.
PublicationThere are two main approaches to processing tasks requiring high amounts of computational power. One approach is using clusters of mostly identical hardware, placed in dedicated locations. The other approach is outsourcing computing resources from large numbers of volunteers connected to the Internet. This chapter attempts to formulate a mathematical model of the volunteer based approach to distributed computations and apply it...
-
Adaptive Hyperparameter Tuning within Neural Network-based Efficient Global Optimization
PublicationIn this paper, adaptive hyperparameter optimization (HPO) strategies within the efficient global optimization (EGO) with neural network (NN)-based prediction and uncertainty (EGONN) algorithm are proposed. These strategies utilize Bayesian optimization and multiarmed bandit optimization to tune HPs during the sequential sampling process either every iteration (HPO-1itr) or every five iterations (HPO-5itr). Through experiments using...
-
Segmented bio-based polyurethane composites containing powdered cellulose obtained from novel bio-based diisocyanate mixtures
PublicationA considerable number of research works focus on the positive influence of cellulose on the properties of polymer-based composites and their wide range of application possibilities. The present work is focused on the synthesis of novel bio-based polyurethane (bio-PU) composites filled with powdered cellulose (microcellulose, MC) in an amount of 5 wt.%. Bio-PU composites were synthesized via a non-solvent prepolymer method. First,...
-
Modeling Volunteer Based Systems
PublicationThere are two main approaches to processing tasks requiring high amounts of computational power. One approach is using clusters of mostly identical hardware, placed in dedicated locations [1, 2, 3]. The other approach is outsourcing computing resources from large numbers of volunteers connected to the Internet [7]. This chapter presents an application of a mathematical model of the volunteer computing presented in Volume 1 of this...
-
Project-Based Collaborative Research and Training Roadmap for Manufacturing Based on Industry 4.0
PublicationThe importance of the economy being up to date with the latest developments, such as Industry 4.0, is more evident than ever before. Successful implementation of Industry 4.0 principles requires close cooperation of industry and state authorities with universities. A paradigm of such cooperation is described in this paper stemming from university partners with partly overlapping and partly complementary areas of expertise in manufacturing....
-
Fundamentals of Physics-Based Surrogate Modeling
PublicationChapter 1 was focused on data-driven (or approximation-based) modeling methods. The second major class of surrogates are physics-based models outlined in this chapter. Although they are not as popular, their importance is growing because of the challenges related to construction and handling of approximation surrogates for many real-world problems. The high cost of evaluating computational models, nonlinearity of system responses,...
-
Computationally-Efficient Statistical Design and Yield Optimization of Resonator-Based Notch Filters Using Feature-Based Surrogates
PublicationModern microwave devices are designed to fulfill stringent requirements pertaining to electrical performance, which requires, among others, a meticulous tuning of their geometry parameters. When moving up in frequency, physical dimensions of passive microwave circuits become smaller, making the system performance increasingly susceptible to manufacturing tolerances. In particular, inherent inaccuracy of fabrication processes affect...
-
Polybrominated diphenyl ether (PBDE) concentrations in dust from various indoor environments in Gdańsk, Poland: Prediction of concentrations in indoor air and assessment of exposure of adults
PublicationMonitoring of polybrominated diphenyl ethers (PBDEs) in indoor environments involves the determination of their concentrations in air, airborne particles, and settled dust. Each of these is a source of human exposure to PBDEs. In this study, we attempted to model PBDEs concentrations in various typical indoor environments on the basis of real PBDEs measurements in dust collected from them. The analytical procedure for determining...
-
NUMERICAL ANALYSIS OF SPECIES DIFFUSION AND METHANOL DECOMPOSITION IN THERMOCATALYTIC REACTOR BASED ON THE INTERMETALLIC PHASE OF Ni3Al FOR LOW REYNOLDS NUMBERS
PublicationNumerical modelling of hydrogen production by means of methanol decomposition in a thermocatalytic reactor using corrugated foil made of the Ni3Al intermetallic phase is shown in the paper. Experimental results of the flow analysis of mixtures containing helium and methanol in a thermocatalytic reactor with microchannels were used for the initial calibration of the CFD calculations (calculations based on the Computational Fluid...
-
A Population-Based Method with Selection of a Search Operator
PublicationThis paper presents a method based on a population in which the parameters of individuals can be processed by operators from various population-based algorithms. The mechanism of selecting operators is based on the introduction of an additional binary parameters vector located in each individual, on the basis of which it is decided which operators are to be used to modify individuals’ parameters. Thus, in the proposed approach,...
-
Safety-based approach in multifunctional building design
PublicationABSTRACT: The modern trend in design of the public buildings is to create multifunctional environments in one building, hosting a variety of functions. Multifunctional buildings entertain large number of visitors. The complexity and vulnerability of this type of public space are the main reasons to use within their design process the performance based approach including the recognition of hazards. Safety and reliability approach...
-
Content-Based Approach to Automatic Recommendation of Music
PublicationThis paper presents a content-based approach to music recommendation. For this purpose, a database which contains more than 50000 music excerpts acquired from public repositories was built. Datasets contain tracks of distinct performers within several music genres. All music pieces were converted to mp3 format and then parameterized based on MPEG-7, mel-cepstral and time-related dedicated parameters. All feature vectors are stored...
-
Performance of various risk prediction models in a large lung cancer screening cohort in Gdańsk, Poland—a comparative study
Publication -
Application of reversed-phase thin layer chromatography and QSRR modelling for prediction of protein binding of selected β-blockers
Publication -
A subdomain model for armature reaction field and open‐circuit field prediction in consequent pole permanent magnet machines
PublicationIn this paper, the machine quantity, such as electromagnetic torque, self and mutual inductances, and electromotive force, is analytically calculated for non-overlapping winding consequent pole slotted machine for open-circuit field and armature reaction. The sub-domain approach of (2-D) analytical model is developed using Maxwell's equations and divide the problem into slots, slot-openings, airgap and magnets region, the magnet...
-
Sonochemical Based Processes for Treatment of Water and Wastewater
PublicationSonochemical Based Processes for Treatment of Water and Wastewater - Opportunities and Challenges – A Future Perspective.
-
Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
-
GRAPHENE-BASED SUPERCAPACITORS APPLICATION FOR ENERGY STORAGE
PublicationRecent advances in graphene-based supercapacitor technology for energy storage application were summarized. The comparison of different types of electrode materials in such supercapacitors was performed. The supercapacitors with graphene-based electrodes exhibit outstanding performance: high charge-discharge rate, high power density, high energy density and long cycle-life, what makes them suitable for various applications, e.g....
-
Supporting Assurance by Evidence-based Argument Services
PublicationStructured arguments based on evidence are used in many domains, including systems engineering, quality assurance and standards conformance. Development, maintenance and assessment of such arguments is addressed by TRUST-IT methodology outlined in this paper. The effective usage of TRUST-IT requires an adequate tool support. We present a platform of software services, called NOR-STA, available in the Internet, supporting key activities...