Search results for: machine learning optimization techniques
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Shape and force control of cable structures with minimal actuators and actuation
PublicationShape adjustment and stress control can be considered as one of the effective parameters in prestressed cable structures since such structures are widely constructed nowadays due to their characteristics. The assembly errors and applied loads hugely affect the cables’ nodal positions and stress due to their delicacy. The former could disturb the shape, which affects the appearance and the function of the structure. In contrast,...
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Tuning the photocatalytic performance through magnetization in Co-Zn ferrite nanoparticles
PublicationIn this work, the link between the photocatalytic performance of Co-Zn ferrite nanoparticles and the net magnetic moment is analyzed. CoxZn1-xFe2O4 nanoparticles (0 ≤ x ≤ 1) were synthesized by co-precipitation method and different physicochemical techniques were employed to characterize the samples (X-ray diffraction, Transmission Electron Microscopy (TEM), BET surface area, Diffuse Reflectance Spectroscopy (DRS), Photoluminescence spectroscopy,...
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Mohsan Ali Master of Science in Computer Science
PeopleMohsan Ali is a researcher at the University of the Aegean. He won the Marie-Curie Scholarship in 2021 in the field of open data ecosystem (ODECO) to pursue his PhD degree at the University of the Aegean. Currently, he is working on the technical interoperability of open data in the information systems laboratory; this position is funded by ODECO. His areas of expertise are open data, open data interoperability, data science, natural...
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Online sound restoration system for digital library applications
PublicationAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Advantageous conditions of saccharification of lignocellulosic biomass for biofuels generation via fermentation processes
PublicationProcessing of lignocellulosic biomass includes four major unit operations: pre-treatment, hydrolysis, fermentation and product purifcation prior to biofuel generation via anaerobic digestion. The microorganisms involved in the fermentation metabolize only simple molecules, i.e., monosugars which can be obtained by carrying out the degradation of complex polymers, the main component of lignocellulosic biomass. The object of this...
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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublicationAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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Analysis of nonlinear eigenvalue problems for guides and resonators in microwave and terahertz technology
PublicationThis dissertation presents developed numerical tools for investigating waveguides and resonators' properties for microwave and terahertz technology. The electromagnetics analysis requires solving complex eigenvalue problems, representing various parameters such as resonant frequency or propagation coefficient. Solving equations with eigenvalue boils down to finding the roots of the determinant of the matrix. At the beginning, one...
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The contactless method of chip-to-chip high-speed data transmission monitoring
PublicationThis paper presents a technique of decoupling differential signals transmitted in a pair of microstrip lines on a printed circuit board (PCB), using dedicated coupler for high speed data transmission monitoring in chip-to-chip interconnections. The coupler used for signal probing is overlayed on the pair of microstrip lines under test, and provides a signal to the next blocks of the measurement system without disturbing transmission...
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Reduced-Cost Constrained Modeling of Microwave and Antenna Components: Recent Advances
PublicationElectromagnetic (EM) simulation models are ubiquitous in the design of microwave and antenna components. EM analysis is reliable but CPU intensive. In particular, multiple simulations entailed by parametric optimization or uncertainty quantification may considerably slow down the design processes. In order to address this problem, it is possible to employ fast metamodels. Here, the popular solution approaches are approximation...
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublicationSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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Moduł Warsztaty - narzędzie w procesie edukacji na uczelni wyższej
PublicationObecnie istnieje bardzo szeroka gama narzędzi informatycznych, które wspierają proces edukacji przy wykorzystaniu internetu na uczelniach wyższych. Wśród nieodpłatnych narzędzi powszechnie znana jest platforma Moodle. W artykule zaprezentowano jeden z jej modułów – Warsztaty. Przedstawiono jego funkcjonalność. Opisano jego zalety i wady w nauczaniu łączącym techniki online i tradycyjne na uczelni wyższej (blended-learning). W artykule...
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Implementing artificial intelligence in forecasting the risk of personal bankruptcies in Poland and Taiwan
PublicationResearch background: The global financial crisis from 2007 to 2012, the COVID-19 pandemic, and the current war in Ukraine have dramatically increased the risk of consumer bankruptcies worldwide. All three crises negatively impact the financial situation of households due to increased interest rates, inflation rates, volatile exchange rates, and other significant macroeconomic factors. Financial difficulties may arise when the...
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Advanced seismic control strategies for smart base isolation buildings utilizing active tendon and MR dampers
PublicationThis paper investigates the seismic behaviour of a five-storey shear building that incorporates a base isolation system. Initially, the study considers passive base isolation and employs a multi-objective archived-based whale optimization algorithm called MAWOA to optimize the parameters of base isolation. Subsequently, a novel model is proposed, which incorporates an interval type-2 Takagi-Sugeno fuzzy logic controller (IT2TSFLC)...
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Investigation on domestic fruits seed oils in personal care emulsion systems
PublicationThe use of fruit seed oils in personal care products is of significance to both their function and image. Poland is an important processor of fruit products within the EU, and thus has a large availability of seeds from domestic fruits, which are normally considered to be a waste material. Unfortunately, current literature is scarce of the suitability of these oils for topical use in the form of cosmetic emulsions. Published data...
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Application of artificial intelligence into/for control of flexible manufacturing cell
PublicationThe application of artificial intelligence in technological processes control is usually limited. One problem is how to respond to changes in the environment of manufacturing system. A way to overcome the above shortcoming is to use fuzzy logic for representation of the inexact information. In this paper fundamentals of artificial intelligence and fuzzy logic are introduced from a theoretical point of view. Still more the fuzzy...
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Smartphones as tools for equitable food quality assessment
PublicationBackground: The ubiquity of smartphones equipped with an array of sophisticated sensors, ample processing power, network connectivity and a convenient interface makes them a promising tool for non-invasive, portable food quality assessment. Combined with the recent developments in the areas of IoT, deep learning algorithms and cloud computing, they present an opportunity for advancing wide-spread, equitable and sustainable food...
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Towards New Mappings between Emotion Representation Models
PublicationThere are several models for representing emotions in affect-aware applications, and available emotion recognition solutions provide results using diverse emotion models. As multimodal fusion is beneficial in terms of both accuracy and reliability of emotion recognition, one of the challenges is mapping between the models of affect representation. This paper addresses this issue by: proposing a procedure to elaborate new mappings,...
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Accurate simulation-driven modeling and design optimization of compact microwave structures
PublicationCost efficient design optimization of microwave structures requires availability of fast yet reliable replacement models so that multiple evaluations of the structure at hand can be executed in reasonable timeframe. Direct utilization of full-wave electromagnetic (EM) simulations is often prohibitive. On the other hand, accurate data-driven modeling normally requires a very large number of training points and it is virtually infeasible...
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Design of reverse curves adapted to the satellite measurements
PublicationThe paper presents a new method for designing railway route in the direction change area adapted to the Mobile Satellite Measurements technique. The method may be particularly useful in the situations when both tangents cannot be connected in an elementary way using a circular arc with transition curves. Thus, the only solution would be the application of two circular arcs of opposite curvature signs, that is, the use of an inverse...
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Controlling crystallites orientation and facet exposure for enhanced electrochemical properties of polycrystalline MoO3 films
PublicationThis study focuses on the development and optimization of MoO3 films on commercially available FTO substrates using the pulsed laser deposition (PLD) technique. By carefully selecting deposition conditions and implementing post-treatment procedures, precise control over crystallite orientation relative to the substrate is achieved. Deposition at 450 °C in O2 atmosphere results in random crystallite arrangement, while introducing...
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Time-Gating method with automatic calibration for accurate measurements of electrically small antenna radiation patterns in Non-Anechoic environments
PublicationNon-anechoic sites represent a cheap alternative to measurements of antennas in dedicated facilities. However, due to a high noise—from the external EM signal sources and multipath interferences—the quality of radiation patterns obtained in non-anechoic conditions is poor. The characteristics can be corrected using a time-gating method (TGM), which involves filtering of the noise based on temporal analysis of the measured signals....
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The Design of Cavity Resonators and Microwave Filters Applying Shape Deformation Techniques
PublicationThis article introduces shape deformation as a new approach to the computer-aided design (CAD) of high-frequency components. We show that geometry deformation opens up new design possibilities and offers additional degrees of freedom in the 3-D modeling of microwave structures. Such design flexibility is highly desirable if the full potential of additive manufacturing (AM) is to be exploited in the fabrication of RF and microwave...
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Computer controlled systems - 2022/2023
e-Learning Coursesmateriały wspierające wykład na studiach II stopnia na kierunku ACR pod tytułem komputerowe systemy automatyki 1. Computer system – controlled plant interfacing technique; simple interfacing and with both side acknowledgement; ideas, algorithms, acknowledge passing. 2. Methods of acknowledgement passing: software checking and passing, using interrupt techniques, using readiness checking (ready – wait lines). The best solution...
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CCS-lecture-2023-2024
e-Learning Coursesmateriały wspierające wykład na studiach II stopnia na kierunku ACR pod tytułem komputerowe systemy automatyki 1. Computer system – controlled plant interfacing technique; simple interfacing and with both side acknowledgement; ideas, algorithms, acknowledge passing. 2. Methods of acknowledgement passing: software checking and passing, using interrupt techniques, using readiness checking (ready – wait lines). The best solution optimization...
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Online sound restoration system for digital library applications.
PublicationAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks
PublicationEstimation of vital signs using image processing techniques have already been proved to have a potential for supporting remote medical diagnostics and replacing traditional measurements that usually require special hardware and electrodes placed on a body. In this paper, we further extend studies on contactless Respiratory Rate (RR) estimation from extremely low resolution thermal imagery by enhancing acquired sequences using Deep...
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Categorization of emotions in dog behavior based on the deep neural network
PublicationThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
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Mechatronic Design Towards Investigation of the Temporo-Mandibular Joint Behaviour
PublicationA significant problem of the temporo-mandibular joint (TMJ) research is lack of data concerning geometry and position of TMJ discs. It leads to necessity of developing a driving method of the process optimization, which is based on chosen techniques of mechatronic design. In particular, the latter concerns a technique of experimentally supported virtual prototyping. On this stage, the research is characterized by well-verified...
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The importance of anchoring ligands of binuclear sensitizers on electron transfer processes and photovoltaic action in dye-sensitized solar cells
PublicationThe relatively low photon-to-current conversion efficiency of dye-sensitized solar cells is their major drawback limiting widespread application. Light harvesting, followed by a series of electron transfer processes, is the critical step in photocurrent generation. An in-depth understanding and fine optimization of those processes are crucial to enhance cell performance. In this work, we synthesize two new bi-ruthenium sensitizers...
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Bi-GRU-APSO: Bi-Directional Gated Recurrent Unit with Adaptive Particle Swarm Optimization Algorithm for Sales Forecasting in Multi-Channel Retail
PublicationIn the present scenario, retail sales forecasting has a great significance in E-commerce companies. The precise retail sales forecasting enhances the business decision making, storage management, and product sales. Inaccurate retail sales forecasting can decrease customer satisfaction, inventory shortages, product backlog, and unsatisfied customer demands. In order to obtain a better retail sales forecasting, deep learning models...
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The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification
PublicationDeveloping of theoretical tools can be very helpful for supporting new pollutant detection. Nowadays, a combination of mass spectrometry and chromatographic techniques are the most basic environmental monitoring methods. In this paper, two organochlorine compound mass spectra classification systems were proposed. The classification models were developed within the framework of artificial neural networks (ANNs) and fast 1D and...
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Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images
PublicationIn remote sensing images, change detection (CD) is required in many applications, such as: resource management, urban expansion research, land management, and disaster assessment. Various deep learning-based methods were applied to satellite image analysis for change detection, yet many of them have limitations, including the overfitting problem. This research proposes the Feature Weighted Attention (FWA) in Bidirectional Long...
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Protection and viability of fruit seeds oils by nanostructured lipid carrier (NLC) nanosuspensions
PublicationIn this paper, we focused on the development of nanostructured lipid carriers (NLCs) for dermal application. The NLC matrix was designed as a protective reservoir of biological active compounds that naturally occur in domestic fruit seed oils. Over the years, emulsions, as a popular physicochemical form of personal care products, were refined in order to obtain the best possible penetration into the skin of any bioactive compound...
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Optimization of electrochemical doping approach resulting in highly photoactive iodine-doped titania nanotubes
PublicationThe paper focuses on the optimization procedure concerning the synthesis method resulting in highly ordered titania nanotubes doped with iodine atoms. The doping process was based on the electrochemical treatment of a titania nanotube layer immersed in a potassium iodide (KI) solution acting as an iodine precursor. A number of endeavors were undertaken in order to optimize the doping conditions. Electrolyte concentration, reaction...
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Design of a Shape-Memory-Alloy-Based Carangiform Robotic Fishtail with Improved Forward Thrust
PublicationShape memory alloys (SMAs) have become the most common choice for the development of mini- and micro-type soft bio-inspired robots due to their high power-to-weight ratio, ability to be installed and operated in limited space, silent and vibration-free operation, biocompatibility, and corrosion resistance properties. Moreover, SMA spring-type actuators are used for developing different continuum robots, exhibiting high degrees...
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A Development of a Capacitive Voltage Divider for High Voltage Measurement as Part of a Combined Current and Voltage Sensor
PublicationThis article deals with the development of capacitive voltage divider for high voltage measurements and presents a method of analysis and optimization of its parameters. This divider is a part of a combined voltage and current sensor for measurements in high voltage power networks. The sensor allows continuous monitoring of the network distribution status and performs a quick diagnosis and location of possible network failures....
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Low-Cost Unattended Design of Miniaturized 4 × 4 Butler Matrices with Nonstandard Phase Differences
PublicationDesign of Butler matrices dedicated to Internet of Things and 5th generation (5G) mobile systems—where small size and high performance are of primary concern—is a challenging task that often exceeds capabilities of conventional techniques. Lack of appropriate, unified design approaches is a serious bottleneck for the development of Butler structures for contemporary applications. In this work, a low-cost bottom-up procedure for...
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Antenna Modeling Using Variable-Fidelity EM Simulations and Constrained Co-Kriging
PublicationUtilization of fast surrogate models has become a viable alternative to direct handling of fullwave electromagnetic (EM) simulations in EM-driven design. Their purpose is to alleviate the difficulties related to high computational cost of multiple simulations required by the common numerical procedures such as parametric optimization or uncertainty quantification. Yet, conventional data-driven (or approximation) modeling techniques...
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Identyfikacja instrumentu muzycznego z nagrania fonicznego za pomocą sztucznych sieci neuronowych
PublicationCelem rozprawy jest zbadanie algorytmów do identyfikacji instrumentów występujących w sygnale polifonicznym z wykorzystaniem sztucznych sieci neuronowych. W części teoretycznej przywołano podstawy przetwarzania sygnałów fonicznych w kontekście ekstrakcji parametrów sygnałów wykorzystywanych w treningu sieci neuronowych. Dodatkowo dokonano analizy rozwoju metod uczenia maszynowego z uwzględnieniem podziału na sieci neuronowe pierwszej,...
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Enzyme Conjugation - A Promising Tool for Bio-catalytic and Biotransformation Applications – A Review
PublicationEnzymes have revolutionized conventional industrial catalysts as more efficient, eco-friendly, and sustainable substitutes that can be used in different biotechnological processes, food, and pharmaceutical industries. Yet, the enzymes from nature are engineered to make them adapt and enhance their durability in the industrial environment. One promising approach involves the combined use of multiple enzymes that catalyze highly...
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Optimal Design of Transmitarray Antennas via Low-Cost Surrogate Modelling
PublicationOver the recent years, reflectarrays and transmitarrays have been drawing a considerable attention due to their attractive features, including a possibility of realizing high gain and pencil-like radiation patterns without the employment of complex feeding networks. Among the two, transmitarrays seem to be superior over reflectarrays in terms of achieving high radiation efficiency without the feed blockage. Notwithstanding, the...
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Parallel Programming for Modern High Performance Computing Systems
PublicationIn view of the growing presence and popularity of multicore and manycore processors, accelerators, and coprocessors, as well as clusters using such computing devices, the development of efficient parallel applications has become a key challenge to be able to exploit the performance of such systems. This book covers the scope of parallel programming for modern high performance computing systems. It first discusses selected and...
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Cost-Efficient Surrogate Modeling of High-Frequency Structures Using Nested Kriging with Automated Adjustment of Model Domain Lateral Dimensions
PublicationSurrogate models are becoming popular tools of choice in mitigating issues related to the excessive cost of electromagnetic (EM)-driven design of high-frequency structures. Among available techniques, approximation modeling is by far the most popular due to its versatility. In particular, the surrogates are exclusively based on the sampled simulation data with no need to involve engineering insight or problem-specific knowledge....
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublicationThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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The High Quality Business School Academic Teacher of the 21st Century – Polish Students’ Perspective
PublicationThe literature shows that the success and competence of future managers depend on the quality of their academic teachers. Moreover high quality study requires high quality lecturing/teaching that creates an environment in which deep learning outcomes are made possible for students. The aim was to identify the characteristics of the academic teacher working at business schools, according to the expectations of Polish students...
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Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublicationIn this study, in order to characterize the buried object via deep-learning-based surrogate modeling approach, 3-D full-wave electromagnetic simulations of a GPR model has been used. The task is to predict simultaneously and independent of each characteristic parameters of a buried object of several radii at different positions (depth and lateral position) in various dispersive subsurface media. This study has analyzed variable...
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Segmentation Quality Refinement in Large-Scale Medical Image Dataset with Crowd-Sourced Annotations
PublicationDeployment of different techniques of deep learning including Convolutional Neural Networks (CNN) in image classification systems has accomplished outstanding results. However, the advantages and potential impact of such a system can be completely negated if it does not reach a target accuracy. To achieve high classification accuracy with low variance in medical image classification system, there is needed the large size of the...
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A Comprehensive Approach to Azo Dichlorotriazine Dye Treatment: Assessing the Impact of Physical, Chemical, and Biological Treatment Methods through Statistical Analysis of Experimental Data
PublicationThis exploration investigates integrated treatment systems combining advanced oxidation processes (Fenton and photo-Fenton) with biological methods for the effective elimination of stubborn organic compounds in simulated textile wastewater composed of azo Dichlorotriazine dye. A comprehensive optimization of key process factors including catalyst dosage, hydrogen peroxide quantity, irradiation duration, etc. was systematically...
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Hydrochars as a bio-based adsorbent for heavy metals removal: A review of production processes, adsorption mechanisms, kinetic models, regeneration and reusability of hydrochar
PublicationThe spread of heavy metals throughout the ecosystem has extremely endangered human health, animals, plants, and natural resources. Hydrochar has emerged as a promising adsorbent for removing heavy metals from water and wastewater. Hydrochar, obtained from hydrothermal carbonization of biomass, owns unique physical and chemical properties that are highly potent in capturing heavy metals via surface complexation, electrostatic interactions,...
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Net-zero carbon condition in wastewater treatment plants: A systematic review of mitigation strategies and challenges
PublicationThe wastewater sector accounts for up to 7 and 10% of anthropogenic CH4 and N2O emissions, respectively. Nowadays wastewater treatment plants are going through a paradigm shift to approach a net-zero carbon condition. Numerous ongoing measures have taken place to identify the sources of greenhouse gases and minimize the carbon footprint. This paper systematically reviews all known practices leading towards net-zero carbon wastewater...