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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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Mixed integer nonlinear optimization of biological processes in wastewater sequencing batch reactor
PublicationWastewater treatment plays a key role for humanity. The waste entering lakes, rivers, and seas deteriorates daily quality of life. Therefore, it is very important to improve the efficiency of wastewater treatment. From a control point of view, a biological wastewater treatment plant is a complex, non-linear, multidimensional, hybrid control system. The paper presents the design of the optimizing hierarchical control system applied...
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KNOWING WHEN TO SAY NO / SAPERE QUANDO DIRE NO
PublicationEver since we began illuminating the exterior of the slender skyscrapers built during the of 20s and 30s in XX century, urban lighting has been considered a way to beautify cities, and make them more visually prominent and safe. At that time, we knew so little about the impact of lighting on humans, flora and fauna, so it never occurred to lighting designers then, that their actions would have harmful consequences. In those days,...
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublicationAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
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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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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 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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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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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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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublicationAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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Molecularly imprinted polymers for the detection of volatile biomarkers
PublicationIn the field of cancer detection, the development of affordable, quick, and user-friendly sensors capable of detecting various cancer biomarkers, including those for lung cancer (LC), holds utmost significance. Sensors are expected to play a crucial role in the early-stage diagnosis of various diseases. Among the range of options, sensors emerge as particularly appealing for the diagnosis of various diseases, owing to their cost-effectiveness,...
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Design and Experimental Validation of a Metamaterial-Based Sensor for Microwave Imaging in Breast, Lung, and Brain Cancer Detection
PublicationThis study proposes an innovative geometry of a microstrip sensor for high-resolution microwave imaging (MWI). The main intended application of the sensor is early detection of breast, lung, and brain cancer. The proposed design consists of a microstrip patch antenna fed by a coplanar waveguide with a metamaterial layer-based lens implemented on the back side, and an artificial magnetic conductor (AMC) realized on as a separate...
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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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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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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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ChatGPT Application vis-a-vis Open Government Data (OGD): Capabilities, Public Values, Issues and a Research Agenda
PublicationAs a novel Artificial Intelligence (AI) application, ChatGPT holds pertinence not only for the academic, medicine, law, computing or other sectors, but also for the public sector-case in point being the Open Government Data (OGD) initiative. However, though there has been some limited (as this topic is quite new) research concerning the capabilities ChatGPT in these sectors, there has been no research about the capabilities it...
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The potential interaction of environmental pollutants and circadian rhythm regulations that may cause leukemia
PublicationTumor suppressor genes are highly affected during the development of leukemia, including circadian clock genes. Circadian rhythms constitute an evolutionary molecular machinery involving many genes, such as BMAL1, CLOCK, CRY1, CRY2, PER1, PER2, REV-ERBa, and RORA, for tracking time and optimizing daily life during day-night cycles and seasonal changes. For circulating blood cells many of these genes coordinate their proliferation,...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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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...
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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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How Machine Learning Contributes to Solve Acoustical Problems
PublicationMachine learning is the process of learning functional relationships between measured signals (called percepts in the artificial intelligence literature) and some output of interest. In some cases, we wish to learn very specific relationships from signals such as identifying the language of a speaker (e.g. Zissman, 1996) which has direct applications such as in call center routing or performing a music information retrieval task...
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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...
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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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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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Determination of long-chain aldehydes using a novel quartz crystal microbalance sensor based on a biomimetic peptide
PublicationThere is an increasingly popular trend aimed at improvement of fundamental metrological parameters of sensors via implementation of materials mimicking biological olfactory systems. This study presents investigation on usefulness of the peptide mimicking HarmOBP7 region as a receptor element of the piezoelectric sensor for selective analysis of long-chain aldehydes. Identification of odorant binding proteins creates new possibilities...
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EVALUATION OF LIQUID-GAS FLOW IN PIPELINE USING GAMMA-RAY ABSORPTION TECHNIQUE AND ADVANCED SIGNAL PROCESSING
PublicationLiquid-gas flows in pipelines appear in many industrial processes, e.g. in the nuclear, mining, and oil industry. The gamma-absorption technique is one of the methods that can be successfully applied to study such flows. This paper presents the use of thegamma-absorption method to determine the water-air flow parameters in a horizontal pipeline. Three flow types were studied in this work: plug, transitional plug-bubble,...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublicationA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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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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The value of less Light – Sustainable architectural lighting design
PublicationSince its beginning, the art of external illumination has substantially influ-enced the creation and the perception of architecture and the night-time urban environment. In her lecture, the author examines and defines the significant interdisciplinary conditions related to architectural lighting design that have evolved over the years, starting from the first simple exterior lighting projects to the more modern, complex concepts...
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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...
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RMS-based damage identification in adhesive joint between concrete beam and steel plate using ultrasonic guided waves
PublicationAdhesive joints have numerous applications in many branches of industry, such as civil engineering, automotive, aerospace and shipbuilding. As with most structural elements, adhesive joints can experience any damage mechanism, which induces the need for diagnostic testing. Ultrasonic waves are widely used for non-destructive inspection of many structures and their elements, including adhesive joints. Guided wave propagation method...
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Assessment of ecotoxicity and total volatile organic compound (TVOC) emissions from food and children's toy products
PublicationThe development of new methods for identifying a broad spectrum of analytes, as well as highly selective tools to provide the most accurate information regarding the processes and relationships in the world, has been an area of interest for researchers for many years. The information obtained with these tools provides valuable data to complement existing knowledge but, above all, to identify and determine previously unknown hazards. Recently,...
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Assessment of toxic and endocrine potential of substances migrating from selected toys and baby products
PublicationAnalysis of literature data shows that there is limited information about the harmful biological effects of mixture of compounds from the EDC group that are released from the surface of toys and objects intended for children and infants. One of the tools that can be used to obtain such information is appropriate bioanalytical tests. The aim of this research involved determining whether tests that use living organisms as an active...
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The effect of groyne field on trapping macroplastic. Preliminary results from laboratory experiments
PublicationMacroplastic, a precursor of microplastic pollution, has become a new scope of research interest. However, the physical processes of macroplastic transport and deposition in rivers are poorly understood, which makes the decisions of where to locate macroplastic trapping infrastructure difficult. In this research, we conducted a series of experiments in a laboratory channel, exploring the impact of groynes and flexible artificial...
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The Effect of Varying the Light Spectrum of a Scene on the Localisation of Photogrammetric Features
PublicationIn modern digital photogrammetry, an image is usually registered via a digital matrix with an array of colour filters. From the registration of the image until feature points are detected on the image, the image is subjected to a series of calculations, i.e., demosaicing and conversion to greyscale, among others. These algorithms respond differently to the varying light spectrum of the scene, which consequently results in the feature...
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OrphaGPT: An Adapted Large Language Model for Orphan Diseases Classification
PublicationOrphan diseases (OD) represent a category of rare conditions that affect only a relatively small number of individuals. These conditions are often neglected in research due to the challenges posed by their scarcity, making medical advancements difficult. Then, the ever-evolving medical research and diagnosis landscape calls for more attention and innovative approaches to address the complex challenges of rare diseases and OD. Pre-trained...
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Urban Lighting Research Transdisciplinary Framework—A Collaborative Process with Lighting Professionals
PublicationOver the past decades, lighting professionals have influenced the experience of the night by brightly illuminating streets, buildings, skylines, and landscapes 24/7. When this became the accepted norm, a dual perspective on night-time was shaped and the visual enjoyment of visitors after dusk was prioritized over natural nightscapes (nocturnal landscapes). During this time, researchers of artificial light at night (ALAN) observed...
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Development of an AI-based audiogram classification method for patient referral
PublicationHearing loss is one of the most significant sensory disabilities. It can have various negative effects on a person's quality of life, ranging from impeded school and academic performance to total social isolation in severe cases. It is therefore vital that early symptoms of hearing loss are diagnosed quickly and accurately. Audiology tests are commonly performed with the use of tonal audiometry, which measures a patient's hearing...
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Numerical Modelling for Prediction of Compression Index from Soil Index Properties in Jimma town, Ethiopia
PublicationIn this study, correlations are developed to predict compression index (Cc) from index parameters so that one can be able to model Jimma soils with compression index using simple laboratory tests. Undisturbed and disturbed soil samples from twelve different locations in Jimma town were collected. Laboratory tests like specific gravity, grain size analysis, Atterberg limit, and one-dimensional consolidation test for a total of twenty-four...
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublicationBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Olfactory receptor-based biosensors as potential future tools in medical diagnosis
PublicationThe detection of biomarkers is the future of non-invasive medical diagnosis and screening. Discovery and identification of reliable disease specific volatile organic compounds is dependent on repeatable, accurate analysis of trace level gaseous analytes mainly in breath samples. Natural variety of the olfactory systems and the compounds capable of gas molecules binding creates wide possibilities of acquisition and implementation...
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Application of Wavelet Transform and Fractal Analysis for Esophageal pH-Metry to Determine a New Method to Diagnose Gastroesophageal Reflux Disease
PublicationIn this paper, a new method for analysing gastroesophageal reflux disease (GERD) is shown. This novel method uses wavelet transform (WT) and wavelet-based fractal analysis (WBFA) on esophageal pH-metry measurements. The esophageal pH-metry is an important diagnostic tool supporting the physician’s work in diagnosing some forms of reflux diseases. Interpreting the results of 24-h pH-metry monitoring is time-consuming, and the conclusions...
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Forecasting risks and challenges of digital innovations
PublicationForecasting and assessment of societal risks related to digital innovation systems and services is an urgent problem, because these solutions usually contain artificial intelligence algorithms which learn using data from the environment and modify their behaviour much beyond human control. Digital innovation solutions are increasingly deployed in transport, business and administrative domains, and therefore, if abused by a malicious...
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THE ROLE OF DAYLIGHT IN ARCHITECTURAL CREATIONS OF CONTEMPORARY CULTURAL FACILITIES
PublicationThe paper studies the role of light in architectural creations of contemporary buildings of representative function. Based on the selected projects and completed buildings dedicated to culture and art, it analyzes and systematizes the examples of using light to obtain visual effects that mark the architecture with a universal and timeless message. The method of research is case study and critical analysis of literature. Light plays...