Filters
total: 354
filtered: 344
Search results for: ADAPTIVE CONTROL
-
An image processing approach for fatigue crack identification in cellulose acetate replicas
PublicationThe cellulose acetate replication technique is an important method for studying material fatigue. However, extracting accurate information from pictures of cellulose replicas poses challenges because of distortions and numerous artifacts. This paper presents an image processing procedure for effective fatigue crack identification in plastic replicas. The approach employs thresholding, adaptive Gaussian thresholding, and Otsu binarization...
-
SYNTHESIZING MEDICAL TERMS – QUALITY AND NATURALNESS OF THE DEEP TEXT-TO-SPEECH ALGORITHM
PublicationThe main purpose of this study is to develop a deep text-to-speech (TTS) algorithm designated for an embedded system device. First, a critical literature review of state-of-the-art speech synthesis deep models is provided. The algorithm implementation covers both hardware and algorithmic solutions. The algorithm is designed for use with the Raspberry Pi 4 board. 80 synthesized sentences were prepared based on medical and everyday...
-
Maritime traffic situation awareness analysis via high-fidelity ship imaging trajectory
PublicationSituation awareness provides crucial yet instant information to maritime traffic participants, and significant attentions are paid to implement traffic situation awareness task via various maritime data source (e.g., automatic identification system, maritime surveillance video, radar, etc.). The study aims to analyze traffic situation with the support of ship imaging trajectory. First, we employ the dark channel prior model to...
-
Spectrum Sensing Based on Hybrid Spectrum Handoff in Cognitive Radio Networks
PublicationThe rapid advancement of wireless communication combined with insufficient spectrum exploitation opens the door for the expansion of novel wireless services. Cognitive radio network (CRN) technology makes it possible to periodically access the open spectrum bands, which in turn improves the effectiveness of CRNs. Spectrum sensing (SS), which allows unauthorized users to locate open spectrum bands, plays a fundamental part in CRNs....
-
Ternary Bismuthide SrPtBi2: Computation and Experiment in Synergism to Explore Solid-State Materials
PublicationA combination of theoretical calculation and the experimental synthesis to explore the new ternary compound is demonstrated in the Sr–Pt–Bi system. Because Pt–Bi is considered as a new critical charge-transfer pair for superconductivity, it inspired us to investigate the Sr–Pt–Bi system. With a thorough calculation of all the known stable/metastable compounds in the Sr–Pt–Bi system and crystal structure predictions, the thermodynamic...
-
Pathogenesis of psoriasis in the “omic” era. Part II. Genetic, genomic and epigenetic changes in psoriasis
PublicationPsoriasis is a multifactorial disease in which genetic, environmental and epigenetic factors regulating gene expression play a key role. In the “genomic era”, genome-wide association studies together with target genotyping platforms performed in different ethnic populations have found more than 50 genetic susceptible markers associated with the risk of psoriasis which have been identified so far. Up till now, the strongest association...
-
Study Analysis of Transmission Efficiency in DAB+ Broadcasting System
PublicationDAB+ is a very innovative and universal multimedia broadcasting system. Thanks to its updated multimedia technologies and metadata options, digital radio keeps pace with changing consumer expectations and the impact of media convergence. Broadcasting analog and digital radio services does vary, concerning devices on both transmitting and receiving side, as well as content processing mechanisms. However, the biggest difference is...
-
Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
-
Constant-Factor Approximation Algorithm for Binary Search in Trees with Monotonic Query Times
PublicationWe consider a generalization of binary search in linear orders to the domain of weighted trees. The goal is to design an adaptive search strategy whose aim is to locate an unknown target vertex of a given tree. Each query to a vertex v incurs a non-negative cost ω(v) (that can be interpreted as the duration of the query) and returns a feedback that either v is the target or the edge incident to v is given that is on the path towards...
-
Detection of Anomalies in the Operation of a Road Lighting System Based on Data from Smart Electricity Meters
PublicationSmart meters in road lighting systems create new opportunities for automatic diagnostics of undesirable phenomena such as lamp failures, schedule deviations, or energy theft from the power grid. Such a solution fits into the smart cities concept, where an adaptive lighting system creates new challenges with respect to the monitoring function. This article presents research results indicating the practical feasibility of real‐time...
-
Gender as a moderator between Present-Hedonistic time perspective and depressive symptoms or stress during COVID-19 lock-down
PublicationAlthough numerous studies have addressed the impact of the COVID-19 lock-downs on psychological distress, scarce data is available relating to the role of Present-Hedonistic (PH) time perspective and gender differences in the development of depressive symptoms and stress during the period of strict social distancing. We hypothesized that gender would moderate the relationship between PH and depressiveness or stress levels, such...
-
Predicting Value of Binding Constants of Organic Ligands to Beta-Cyclodextrin: Application of MARSplines and Descriptors Encoded in SMILES String
PublicationThe quantitative structure–activity relationship (QSPR) model was formulated to quantify values of the binding constant (lnK) of a series of ligands to beta–cyclodextrin (β-CD). For this purpose, the multivariate adaptive regression splines (MARSplines) methodology was adopted with molecular descriptors derived from the simplified molecular input line entry specification (SMILES) strings. This approach allows discovery of regression...
-
Contactless hearing aid designed for infants
PublicationIt is a well known fact that language development through home intervention for a hearing-impaired infant should start in the early months of a newborn baby's life. The aim of this paper is to present a concept of a contactless digital hearing aid designed especially for infants. In contrast to all typical wearable hearing aid solutions (ITC, ITE, BTE), the proposed device is mounted in the infant's bed with any parts of its set-up...
-
The Unfolded Protein Response: A Double-Edged Sword for Brain Health
PublicationEfficient brain function requires as much as 20% of the total oxygen intake to support normal neuronal cell function. This level of oxygen usage, however, leads to the generation of free radicals, and thus can lead to oxidative stress and potentially to age-related cognitive decay and even neurodegenerative diseases. The regulation of this system requires a complex monitoring network to maintain proper oxygen homeostasis. Furthermore,...
-
Does pandemic denial help or harm? Belief in COVID-19 and experience of it affect psychological consequences of using neurotic defence mechanisms
PublicationObjective: The COVID-19 pandemic may activate thoughts of death, leading to aversive psychological states. In such situations, defence mechanisms emerge; however, their adaptability depends on many factors. The aim of the study was to investigate the relationship between neurotic defence style and depressive symptoms. We assumed that the sense of coherence underlies this correlation and investigated how both believing (or not)...
-
Underfrequency Load Shedding: An Innovative Algorithm Based on Fuzzy Logic
PublicationIn contemporary power systems, the load shedding schemes are typically based on disconnecting a pre-specified amount of load after the frequency drops below a predetermined value. The actual conditions at the time of disturbance may largely dier from the assumptions, which can lead to non-optimal or ineective operation of the load shedding scheme. For many years, increasing the eectiveness of the underfrequency load shedding (UFLS)...
-
Digital Innovations and Smart Solutions for Society And Economy: Pros and Cons
PublicationRecent developments in artificial intelligence (AI) may involve significant potential threats to personal data privacy, national security, and social and economic stability. AI-based solutions are often promoted as “intelligent” or “smart” because they are autonomous in optimizing various processes. Be-cause they can modify their behavior without human supervision by analyzing data from the environ-ment, AI-based systems may be...
-
Comparison of target strength (TS) distributions obtained by means of the use of direct and indirect techniques in sea cages
PublicationThe aim of this study is to verify the reliability of a processing application developed for the indirect measurement of target strength (TS), with a view to the integration into a single-beam system for its utilization in fish farms. Dorsal and ventral measurements are carried out for gilt-head sea-bream (Spams Aurata) for 5 size classes using a split-beam EK60 echosounder and single-beam data obtained from one of the channels...
-
Multi-fidelity aerodynamic design trade-off exploration using point-by-point Pareto set identification
PublicationAerodynamic design is inherently a multi-objective optimization (MOO) problem. Determining the best possible trade-offs between conflicting aerodynamic objectives can be computationally challenging when carried out directly at the level of high-fidelity computational fluid dynamics simulations. This paper presents a computationally cheap methodology for exploration of aerodynamic design trade-offs. In particular, point-by-point...
-
Evaluation of Partial Nitritation/Anammox (PN/A) Process Performance and Microorganisms Community Composition under Different C/N Ratio
PublicationA one-stage partial nitritation/anammox (PN/A) process with intermittent aeration is possible under sidestream conditions, but implementation in a mainstream is a challenge due to increased Carbon/Nitrogen (C/N) ratios in domestic wastewater. This study investigated the effect of C/N ratios on process efficiency and the effect of narrowing non-aeration time on process improvement at high chemical oxygen demand (COD) load. An increase...
-
Application of autoencoder to traffic noise analysis
PublicationThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
-
Stationary underwater channel experiment: Acoustic measurements and characteristics in the Bornholm area for model validations
PublicationThe underwater acoustical channel is time-variant, and even on small time scales there is often existing no ‘acoustical frozen ocean’. Popular is the use of WSSUS-channel transmission modeling (Wide-Sense Stationary Uncorrelated Scattering) for the stochastic description of bandpass signals in GSM mobile phones with moving participants; since this results in a halved number of model parameters. For underwater sound applications...
-
Management Strategy for Seaports Aspiring to Green Logistical Goals of IMO: Technology and Policy Solutions
PublicationRecently, because of serious global challenges including the consumption of energy and climate change, there has been an increase in interest in the environmental effect of port operations and expansion. More interestingly, a strategic tendency in seaport advancement has been to manage the seaport system using a model which balances environmental volatility and economic development demands. An energy efficient management system...
-
3D Object Shape Reconstruction from Underwater Multibeam Data and Over Ground Lidar Scanning
PublicationThe technologies of sonar and laser scanning are an efficient and widely used source of spatial information with regards to underwater and over ground environment respectively. The measurement data are usually available in the form of groups of separate points located irregularly in three-dimensional space, known as point clouds. This data model has known disadvantages, therefore in many applications a different form of representation,...
-
Tolerance Optimization of Antenna Structures by Means of Response Feature Surrogates
PublicationFabrication tolerances and other types of uncertainties, e.g., the lack of precise knowledge of material parameters, have detrimental effects on electrical and field performance of antenna systems. In the case of input characteristics these are particularly noticeable for narrow- and multi-band antennas where deviations of geometry parameters from their nominal values lead to frequency shifts of the operating frequency bands. Improving...
-
Assessment of OpenMP Master–Slave Implementations for Selected Irregular Parallel Applications
PublicationThe paper investigates various implementations of a master–slave paradigm using the popular OpenMP API and relative performance of the former using modern multi-core workstation CPUs. It is assumed that a master partitions available input into a batch of predefined number of data chunks which are then processed in parallel by a set of slaves and the procedure is repeated until all input data has been processed. The paper experimentally...
-
How can systems thinking help us in the COVID‐19 crisis?
PublicationThe COVID-19 pandemic outbreak remains one of the most influential events in the global economy over the recent years. While being primarily public health related, it has a tremendous impact on many other aspects, including business management. Many businesses were forced to introduce rapid changes to their business models in order to survive. The aim of this paper is to show the complexity and interrelations of changes triggered...
-
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...
-
Pupil detection supported by Haar feature based cascade classifier for two-photon vision examinations
PublicationThe aim of this paper is to present a novel method, called Adaptive Edge Detection (AED), of extraction of precise pupil edge coordinates from eye image characterized by reflections of external illuminators and laser beams. The method is used for monitoring of pupil size and position during psychophysical tests of two-photon vision performed by dedicated optical set-up. Two-photon vision is a new phenomenon of perception of short-pulsed...
-
INDUSTRIAL HERITAGE IN “SACRIFICE ZONES”. THE POTENTIAL OF BOCAMINA I & II THERMOELECTRIC IN CORONEL, CHILE
PublicationThis work aims to present the recovery potential of the Chilean Sacrifice Zones, urban areas affected by high amounts of pollution caused by industrial activities. It centers in the case of “Bocamina I & II”, two Thermoelectric based in the city of Coronel, southern Chile. A settlement historically related to the mining processes. These plants operated for decades supplying the national energy grid and are seen as both symbols...
-
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...
-
Machining process sequencing and machine assignment in generative feature-based CAPP for mill-turn parts
PublicationProcess selection and sequencing, as one of the most complex issues when evaluated from a mathematical point of view and crucial in CAPP, still attract research attention. For the current trend of intelligent manufacturing, machining features (MFs) are the information carriers for workpiece geometry and topology representation. They are basically derived from CAD models and are used by downstream engineering applications. A feature-based...
-
A fast time-frequency multi-window analysis using a tuning directional kernel
PublicationIn this paper, a novel approach for time-frequency analysis and detection, based on the chirplet transform and dedicated to non-stationary as well as multi-component signals, is presented. Its main purpose is the estimation of spectral energy, instantaneous frequency (IF), spectral delay (SD), and chirp rate (CR) with a high time-frequency resolution (separation ability) achieved by adaptive fitting of the transform kernel. We...
-
An Efficient Noisy Binary Search in Graphs via Median Approximation
PublicationConsider a generalization of the classical binary search problem in linearly sorted data to the graph-theoretic setting. The goal is to design an adaptive query algorithm, called a strategy, that identifies an initially unknown target vertex in a graph by asking queries. Each query is conducted as follows: the strategy selects a vertex q and receives a reply v: if q is the target, then =, and if q is not the target, then v is a...
-
An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublicationThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
-
Analytical progress on symmetric geometric discord: Measurement-based upper bounds
PublicationQuantum correlations may be measured by means of the distance of the state to the subclass ofstates having well defined classical properties. In particular, a geometric measure of asymmetricdiscord [Daki´c et al., Phys. Rev. Lett. 105, 190502 (2010)] was recently defined as the Hilbert-Schmidt distance of a given two-qubit state to the closest classical-quantum (CQ) correlated state.We analyze a geometric measure of symmetric...
-
On the Role of Polarimetric Decomposition and Speckle Filtering Methods for C-Band SAR Wetland Classification Purposes
PublicationPrevious wetlands studies have thoroughly verified the usefulness of data from synthetic aperture radar (SAR) sensors in various acquisition modes. However, the effect of the processing parameters in wetland classification remains poorly explored. In this study, we investigated the influence of speckle filters and decomposition methods with different combinations of filter and decomposition windows sizes on classification accuracy....
-
Type III Responses to Transient Inputs in Hybrid Nonlinear Neuron Models
PublicationExperimental characterization of neuronal dynamics involves recording both of spontaneous activity patterns and of responses to transient and sustained inputs. While much theoretical attention has been devoted to the spontaneous activity of neurons, less is known about the dynamic mechanisms shaping their responses to transient inputs, although these bear significant physiological relevance. Here, we study responses to transient...
-
Rapid design optimization of antennas using variable-fidelity EM models and adjoint sensitivities
PublicationPurpose – Development of techniques for expedited design optimization of complex and numerically expensive electromagnetic (EM) simulation models of antenna structures validated both numerically and experimentally. The paper aims to discuss these issues. Design/methodology/approach – The optimization task is performed using a technique that combines gradient search with adjoint sensitivities, trust region framework, as well as...
-
Regenarative tourism – between theory and practice
PublicationPurpose: The aim of this article is to present a shift in thinking in terms of implementing the systems and practices needed to transition to a regenerative approach in tourism. The article aims to provide concrete ways to change thinking and move towards a regenerative paradigm in the tourism industry. Design/methodology/approach: This viewpoint paper defines regenerative tourism and explores its principles and the possibilities...
-
How can Systems Thinking Help Us Handling the COVID-19 Crisis?
PublicationPurpose: COVID-19 pandemic outbreak remains one of the most influential events in the global economy over the recent years. While being primarily public health-related, it has a tremendous impact on many other aspects, such as public transport, education, and business management. Many businesses were forced to introduce rapid changes to their business models in order to survive. The aim of this paper is to show the complexity and...
-
Merging extremum seeking and self-optimizing narrowband interference canceller - overdetermined case
PublicationActive cancellation systems rely on destructive interference to achieve rejection of unwanted disturbances entering the system of interest. Typical practical applications of this method employ a simple single input, single output arrangement. However, when a spatial wavefield (e.g. acoustic noise or vibration) needs to be controlled, multichannel active cancellation systems arise naturally. Among these, the so-called overdetermined...
-
Active Suppression of Nonstationary Narrowband Acoustic Disturbances
PublicationIn this chapter, a new approach to active narrowband noise control is presented. Narrowband acoustic noise may be generated, among others, by rotating parts of electro-mechanical devices, such as motors, turbines, compressors, or fans. Active noise control involves the generation of “antinoise”, i.e., the generation of a sound that has the same amplitude, but the opposite phase, as the unwanted noise, which causes them to interfere...
-
Industrial Heritage in sacrifice zones, The potential of Bocamina I & II Thermoelectric in Coronel, Chile
PublicationThis work aims to present the recovery potential of the Chilean Sacrifice Zones, urban areas affected by high amounts of pollution caused by industrial activities. It centers in the case of “Bocamina I & II”, two Thermoelectric based in the city of Coronel, southern Chile. A settlement historically related to the mining processes. These plants operated for decades supplying the national energy...