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Damage Detection Strategies in Structural Health Monitoring of Overhead Power Transmission System
PublicationOverhead power transmission lines, their supporting towers, insulators and other elements create a highly distributed system that is vulnerable to damage. Typical damage scenarios cover cracking of foundation, breakage of insulators, loosening of rivets, as well as cracking and breakage of lines. Such scenarios may result from various factors: groundings, lightning strikes, floods, earthquakes, aeolian vibrations, conductors galloping,...
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Assembly of 1D Granular Structures from Sulfonated Polystyrene Microparticles
PublicationBeing able to systematically modify the electric properties of nano- and microparticles opens up new possibilities for the bottom-up fabrication of advanced materials such as the fabrication of one-dimensional (1D) colloidal and granular materials. Fabricating 1D structures from individual particles offers plenty of applications ranging from electronic sensors and photovoltaics to artificial flagella for hydrodynamic propulsion....
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Structural insights, biocatalytic characteristics, and application prospects of lignin-modifying enzymes for sustainable biotechnology
PublicationLignin modifying enzymes (LMEs) have gained widespread recognition in depolymerization of lignin polymers by oxidative cleavage. LMEs are a robust class of biocatalysts that include lignin peroxidase (LiP), manganese peroxidase (MnP), versatile peroxidase (VP), laccase (LAC), and dye-decolorizing peroxidase (DyP). Members of the LMEs family act on phenolic, non-phenolic substrates and have been widely researched for valorization...
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How Can We Identify Electrophysiological iEEG Activities Associated with Cognitive Functions?
PublicationElectrophysiological activities of the brain are engaged in its various functions and give rise to a wide spectrum of low and high frequency oscillations in the intracranial EEG (iEEG) signals, commonly known as the brain waves. The iEEG spectral activities are distributed across networks of cortical and subcortical areas arranged into hierarchical processing streams. It remains a major challenge to identify these activities in...
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Exploring the influence of personal factors on physiological responses to mental imagery in sport
PublicationImagery is a well-known technique in mental training which improves performance efficiency and influences physiological arousal. One of the biomarkers indicating the amount of physiological arousal is skin conductance level (SCL). The aim of our study is to understand how individual differences in personality (e.g. neuroticism), general imagery and situational sport anxiety are linked to arousal measuring with SCL in situational...
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Light pollution from illuminated bridges as a potential barrier for migrating fish–Linking measurements with a proposal for a conceptual model
PublicationIlluminated bridges have become important assets to navigable aquatic systems. However, if artificial light at night (ALAN) from illuminated bridges reaches aquatic habitats, such as rivers, it can threaten the river's natural heterogeneity and alter the behavioural responses of migratory fish. Here, via a pilot study, we quantified levels of ALAN at illuminated bridges that cross a river and, propose a conceptual model to estimate...
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Self-Organising map neural network in the analysis of electromyography data of muscles acting at temporomandibular joint.
PublicationThe temporomandibular joint (TMJ) is the joint that via muscle action and jaw motion allows for necessary physiological performances such as mastication. Whereas mandible translates and rotates [1]. Estimation of activity of muscles acting at the TMJ provides a knowledge of activation pattern solely of a specific patient that an electromyography (EMG) examination was carried out [2]. In this work, a Self-Organising Maps (SOMs)...
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Adjusting the Stiffness of Supports during Milling of a Large-Size Workpiece Using the Salp Swarm Algorithm
PublicationThis paper concerns the problem of vibration reduction during milling. For this purpose, it is proposed that the standard supports of the workpiece be replaced with adjustable stiffness supports. This affects the modal parameters of the whole system, i.e., object and its supports, which is essential from the point of view of the relative tool–workpiece vibrations. To reduce the vibration level during milling, it is necessary to...
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Bio-inspired approaches for explosives detection
PublicationDue to unique abilities of the animals regarding analysis of complex gas substances, they still remain a gold standard in analysis of explosives. Unusual capabilities of biological chemosensory systems, including both vertebrates and invertebrates, stimulate elaboration of the devices mimicking their activity and operation parameters as precisely as possible. The electronic analogues are a subject of investigation in many research...
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Lighting Design for the 21st Century Applied research in lighting practice
PublicationFor those who are unfamiliar with research, it’s important to know there are two categories. Fundamental (or basic) research and applied research. Basic research often discusses scientific ideas/theories, whereas, applied research explores testing these ideas in practice to develop technology or techniques. It’s applied research which most interests lighting practitioners. Great lighting design that creates a pleasant and beneficial...
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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...
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Influence of Storage Time and Temperature on the Toxicity, Endocrine Potential, and Migration of Epoxy Resin Precursors in Extracts of Food Packaging Materials
PublicationThe aim of the present study was to establish a standard methodology for the extraction of epoxy resin precursors from several types of food packages (cans, multi-layered composite material, and cups) with selected simulation media (distilled water, 5% ethanol, 3% dimethyl sulfoxide, 5% acetic acid, artificial saliva) at different extraction times and temperatures (factors). Biological analyses were conducted to determine the acute...
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Diagnosis of damages in family buildings using neural networks
PublicationThe article concerns a problem of damages in family buildings, which result from traffic-induced vibrations. These vibrations arise from various causes and their size is influenced by many factors. The most important is the type of a road, type and weight of vehicles that run on the road, type and condition of the road surface, the distance from the house to the source of vibrations and many others which should be taken into account....
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Ontology-Aided Software Engineering
PublicationThis thesis is located between the fields of research on Artificial Intelligence (AI), Knowledge Representation and Reasoning (KRR), Computer-Aided Software Engineering (CASE) and Model Driven Engineering (MDE). The modern offspring of KRR - Description Logic (DL) [Baad03] is considered here as a formalization of the software engineering Methods & Tools. The bridge between the world of formal specification (governed by the mathematics)...
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Elective seminar: Designing Urban Lighting for the Built Environment – from Theory to Practice
e-Learning CoursesGoal of the course: Understanding the basic design issues related to illumination of the exterior spaces in the built environment Course content / class schedule: 1.Student will learn the difference between Functional versus Decorative lighting in exterior spaces 2. Student will learn how artificial lighting can shape the appearance of an urban space 3. Student will learn necessary tools (luminaires, light sources,...
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The supramolecular organization of self-assembling chlorosomal bacteriochlorophyll c, d, or e mimics
PublicationBacteriochlorophylls (BChls) c, d, and e are the main light-harvesting pigments of green photosynthetic bacteria that self-assemble into nanostructures within the chlorosomes forming the most efficient antennas of photosynthetic organisms. All previous models of the chlorosomal antennae, which are quite controversially discussed because no single crystals could be grown so far from these organelles, involve a strong hydrogen-bonding...
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Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych
PublicationAutomation and improvement of diagnostic process is a vital element of medicine development and patient’s condition self-control. For a long time different ECG signal classification methods exist and are successfully applied, nevertheless their accuracy is not always satisfying enough. The lack of identification of an existing abnormality, which is very similar to a normal heartbeat is the biggest issue - for example premature...
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Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych
PublicationAutomation and improvement of diagnostic process is a vital element of medicine development and patient’s condition self-control. For a long time different ECG signal classification methods exist and are successfully applied, nevertheless their accuracy is not always satisfying enough. The lack of identification of an existing abnormality, which is very similar to a normal heartbeat is the biggest issue - for example premature...
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Expedited Geometry Scaling of Compact Microwave Passives by Means of Inverse Surrogate Modeling
PublicationIn this paper, the problem of geometry scaling of compact microwave structures is investigated. As opposed to conventional structures (i.e., constructed using uniform transmission lines), re-design of miniaturized circuits (e.g., implemented with artificial transmission lines, ATSs) for different operating frequencies is far from being straightforward due to considerable cross-couplings between the circuit components. Here, we...
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PRELIMINARY RESULTS FROM APPLICATION PHOSLOCK® TO REMOVE PHOSPHORUS COMPOUNDS FROM WASTEWATER
PublicationThe aim of the study is to assess the removal effectiveness of phosphorus compoundsby using lanthanum-modified bentonite. This material was produced by the Australian company Phoslock® Water Solutions Pty Ltd. According to the company, Phoslock® has substantial capacity to bound phosphate anions. The investigation was carried out in steady conditions in laboratory model with beakers. The results of the study are related to the...
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Electrophoretic deposition (EPD) of nanohydroxyapatite - nanosilver coatings on Ti13Zr13Nb alloy
PublicationTitanium and its alloys are the biomaterials most frequently used in medical engineering, especially as parts of orthopedic and dental implants. The surfaces of titanium and its alloys are usually modified to improve their biocompatibility and bioactivity, for example, in connection with the deposition of hydroxyapatite coatings. The objective of the present research was to elaborate the technology of electrophoretic deposition...
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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Preferred Benchmarking Criteria for Systematic Taxonomy of Embedded Platforms (STEP) in Human System Interaction Systems
PublicationThe rate of progress in the field of Artificial Intelligence (AI) and Machine Learning (ML) has significantly increased over the past ten years and continues to accelerate. Since then, AI has made the leap from research case studies to real production ready applications. The significance of this growth cannot be undermined as it catalyzed the very nature of computing. Conventional platforms struggle to achieve greater performance...
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Explainable machine learning for diffraction patterns
PublicationSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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Neural network training with limited precision and asymmetric exponent
PublicationAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...
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Condition-Based Monitoring of DC Motors Performed with Autoencoders
PublicationThis paper describes a condition-based monitoring system estimating DC motor degradation with the use of an autoencoder. Two methods of training the autoencoder are evaluated, namely backpropagation and extreme learning machines. The root mean square (RMS) error in the reconstruction of successive fragments of the measured DC motor angular-frequency signal, which is fed to the input of autoencoder, is used to determine the health...
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Digital Transformation of Terrestrial Radio: An Analysis of Simulcasted Broadcasts in FM and DAB+ for a Smart and Successful Switchover
PublicationThe process of digitizing radio is far from over. It is an important interdisciplinary aspect, involving Big Data and AI (Artificial Intelligence) when it comes to classifying and handling content, and an organizational challenge in the Industry 4.0 concept. There exist several methods for delivering audio signals, including terrestrial broadcasting and internet streaming. Among them, the DAB+ (Digital Audio Broadcasting plus)...
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Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublicationRemote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Elimination of Impulsive Disturbances From Archive Audio Signals Using Bidirectional Processing
PublicationIn this application-oriented paper we consider the problem of elimination of impulsive disturbances, such as clicks, pops and record scratches, from archive audio recordings. The proposed approach is based on bidirectional processing—noise pulses are localized by combining the results of forward-time and backward-time signal analysis. Based on the results of specially designed empirical tests (rather than on the results of theoretical analysis),...
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The optimisation of analytical parameters for routine profiling of antioxidants in complex mixture by HPLC coupled post-column derivatisation
PublicationIntroduction: The wide application of natural and artificial antioxidants in food, cosmetic and pharmaceutical industry as well as the recognition of the importance of food antioxidants for supporting human health created demand for reliable and industrially applicable methods of determining antioxidative activity. This requirement can be fullfilled with the recently proposed HPLC-post-column derivatisation approach enabling the...
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Social media for e-learning of citizens in smart city
PublicationThe rapid development of social media can be applied for citizens’ e-learning in a smart city. Big cities have to cope with several open issues like a growing population or a traffic congestion. Especially, a home and public space is supposed to be used in more efficient way. Sustainable homes and buildings can be planned with using some modern techniques. Even currently, there is a huge problem with a lack of key resources like...
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The treatment of wastewater containing pharmaceuticals in microcosm constructed wetlands: the occurrence of integrons (int1–2) and associated resistance genes (sul1–3, qacEΔ1)
PublicationThe aim of this study was to analyze the occurrence of sulfonamide resistance genes (sul1–3) and other genetic elements as antiseptic resistance gene (qacEΔ1) and class 1 and class 2 integrons (int1–2) in the upper layer of substrate and in the effluent of microcosm constructed wetlands (CWs) treating artificial wastewater containing diclofenac and sulfamethoxazole (SMX), which is a sulfonamide antibiotic. The bacteria in the substrate...
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Green engineered biomaterials for bone repair and regeneration: Printing technologies and fracture analysis
PublicationDespite the exceptional self-regeneration properties of bone, severe injuries often require additional surgical intervention such as using artificial bone constructs. These structures need to meet a number of criteria regarding their structure, performance, alongside the rate and the mechanism of erosion and fracture when implanted, for stimulating the regeneration of defected bone and, more critically providing support in the...
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Pedestrian detection in low-resolution thermal images
PublicationOver one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use...
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Light4Health eLearning Course: health research for interior lighting design. Re-thinking design approaches based on science
PublicationThis paper presents the results of 'Light4Health' (L4H), a three-year EU Erasmus+ Strategic Partnership grant project (2019-2021), which investigated, systematized and taught health-related research on the impact of natural and artificial light on human health and well-being relevant to indoor lighting design. The objective was to re-think evidence-based lighting design approaches for residential, working/educational, and healthcare...
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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...
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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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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...
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Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review
PublicationFiber-reinforced concrete (FRC) is extensively used in diverse structural engineering applications, and its mechanical properties are crucial for designing and evaluating its performance. The compressive, flexural, splitting tensile, and shear strengths of FRCs are among the most important attributes, which have been discussed more extensively than other properties. The accurate prediction of these properties, which are required...
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The study on the appearance of deformation defects in the yacht lamination process using an AI algorithm and expert knowledge
PublicationThis article describes the application of the A-priori algorithm for defining the rule-based relationships between individual defects caused during the lamination process, affecting the deformation defect of the yacht shell. The data from 542 yachts were collected and evaluated. For the proper development of the algorithm, a technological process of the yacht lamination supported by expert decisions was described. The laminating...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublicationOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublicationCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
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Application of unmanned USV surface and AUV underwater maritime platforms for the monitoring of offshore structures at sea
PublicationThe operation of offshore structures at sea requires the implementation of advanced systems for their permanent monitoring. There is a set of novel technologies that could be implemented to deliver a higher level of effective and safe operation of these systems. A possible novel solution may be the application of a new maritime unmanned (USV) surface and underwater vehicles/platforms (AUV). Application of such vehicles/platforms...
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Electrophoretic Deposition and Characterization of Chitosan/Eudragit E 100 Coatings on Titanium Substrate
PublicationCurrently, a significant problem is the production of coatings for titanium implants, which will be characterized by mechanical properties comparable to those of a human bone, high corrosion resistance, and low degradation rate in the body fluids. This paper aims to describe the properties of novel chitosan/Eudragit E 100 (chit/EE100) coatings deposited on titanium grade 2 substrate by the electrophoretic technique (EPD). The deposition...
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Audio Feature Analysis for Precise Vocalic Segments Classification in English
PublicationAn approach to identifying the most meaningful Mel-Frequency Cepstral Coefficients representing selected allophones and vocalic segments for their classification is presented in the paper. For this purpose, experiments were carried out using algorithms such as Principal Component Analysis, Feature Importance, and Recursive Parameter Elimination. The data used were recordings made within the ALOFON corpus containing audio signal...
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The mechanisms of degradation of titanium dental implants
PublicationTitanium dental implants show very good properties, unfortunately there are still issues regarding material wear due to corrosion, implant loosening, as well as biological factors—allergic reactions and inflammation leading to rejection of the implanted material. In order to avoid performing reimplantation operations, changes in the chemical composition and/or modifications of the surface layer of the materials are used. This research...
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Development of novel (BiO)2OHCl/BiOBr enriched with boron doped-carbon nanowalls for photocatalytic cytostatic drug degradation: Assessing photocatalytic process utilization in environmental condition
PublicationIn this work, a series of novel (BiO)2OHCl/BiOBr-x%B:DGNW (x = 0%, 1%, 1.5%, 2%) composites with different content of boron-doped diamond/graphene nanowalls (B:DGNW) were fabricated by simple solvothermal synthesis. A boron-doped diamond/graphene nanowalls (B:DGNW) were prepared by CVD method. A series of analyses: XRD, XPS, SEM, and TEM showed that the photocatalyst (BiO)2OHCl/BiOBr-x%B:DGNW with a “flower-like” morphology was...
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Predicting the peak structural displacement preventing pounding of buildings during earthquakes
PublicationThe aim of the present paper is to verify the effectiveness of the artificial neural network (ANN) in predicting the peak lateral displacement of multi-story building during earthquakes, based on the peak ground acceleration (PGA) and building parameters. For the purpose of the study, the lumped-mass multi-degree-of-freedom structural model and different earthquake records have been considered. Firstly, values of stories mass and...
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Seven Different Lighting Conditions in Photogrammetric Studies of a 3D Urban Mock-Up
PublicationOne of the most important elements during photogrammetric studies is the appropriate lighting of the object or area under investigation. Nevertheless, the concept of “adequate lighting” is relative. Therefore, we have attempted, based on experimental proof of concept (technology readiness level—TRL3), to verify the impact of various types of lighting emitted by LED light sources for scene illumination and their direct influence...