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Search results for: ARTIFICIAL INTELLIGENCE, CHATGPT
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Galvanostatic impedance measurements for the efficient adsorption isotherm construction in corrosion inhibitor studies
PublicationWe present an approach towards an accurate and time-efficient adsorption isotherm determination to evaluate the corrosion inhibitor interaction in electrolytic environments. The approach is based on dynamic impedance spectroscopy measurements in galvanostatic mode (g-DEIS). The studied corrosion inhibitor is continuously injected between the secondary cell and the corrosion cell. The efficiency corresponding to instantaneous inhibitor...
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Degradation of electrical performance of a crystalline photovoltaic module due to dust deposition in northern Poland
PublicationThe reduction in power output caused by the accumulation of dust on the photovoltaic module surface is an important problem and should receive much more attention in the literature. This study was an evaluation of the performance degradation of crystalline photovoltaic modules due to natural and simulated dust deposition. Dust is created from powdered grains of sand and particles of different bodies. Dust originates from different...
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Self-organising maps in the analysis of strains of human abdominal wall to identify areas of similar mechanical behaviour.
PublicationThe study refers to the application of a type of artificial neural network called the Self-Organising Map (SOM) for the identification of areas of the human abdominal wall that behave in a similar mechanical way. The research is based on data acquired during in vivo tests using the digital image correlation technique (DIC). The mechanical behaviour of the human abdominal wall is analysed during changing intra-abdominal pressure....
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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...
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Analytical chemistry in technical approaches: immobilization of biosorbent waste containing heavy metals in cemented materials
PublicationAn ecologically safe and economically justified method of stabilization of the used biosorbents was developed. Sorbent contaminated with heavy metals has been successfully solidified/stabilized using a hydraulic binder. The test results indicated that up to 1% of the biosorbent residue used could be added without compromising the compressive strength of the mortar. The compressive strength of the modified mortars did not change...
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Comparison of the paracetamol electrochemical determination using boron-doped diamond electrode and boron-doped carbon nanowalls
PublicationTwo different type of electrodes, boron-doped diamond electrode (BDD) and boron-doped carbon nanowalls (B:CNW) electrode, were used for the electrochemical determination of paracetamol using the cyclic voltammetry and the differential pulse voltammetry in phosphate buffered saline, pH = 7.0. The main advantage of these electrodes is their utilization without any additional modification of the electrode surface. The peak current...
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Cząsteczki mikroRNA - nowy biologicznie aktywny składnik mleka kobiecego
PublicationCząsteczki mikroRNA są krótkimi, niekodującymi oligonukleotydami odpowiadającymi za potranskrypcyjną regulację ekspresji genów. W wyniku ich aktywności kontrolowanych jest wiele procesów komórkowych oraz szlaków sygnalizacyjnych. Od 2010 roku wiadomo, że wchodzą one w skład mleka kobiecego, które obecnie uznaje się za jedno z najbogatszych pokarmowych źródeł mikroRNA. Funkcje tych cząsteczek w organizmie karmionego mlekiem matki...
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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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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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Automatic Singing Voice Recognition EmployingNeural Networks and Rough Sets
PublicationCelem badań jest automatyczne rozpoznawanie głosów śpiewaczych w kategorii rodzaju i jakości technicznej śpiewu. W artykule opisano stworzoną bazę danych głosów, która zawiera próbki głosu śpiewaków profesjonalnych i amatorskich. W dalszej części opisano parametry zdefiniowane w oparciu o zjawiska biomechaniczne w narządzie głosu podczas śpiewania. W oparciu o stworzone macierze parametrów wytrenowano i porównano automatyczne klasyfikatory...
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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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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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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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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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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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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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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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Smart Knowledge Engineering for Cognitive Systems: A Brief Overview
PublicationCognition in computer sciences refers to the ability of a system to learn at scale, reason with purpose, and naturally interact with humans and other smart systems, such as humans do. To enhance intelligence, as well as to introduce cognitive functions into machines, recent studies have brought humans into the loop, turning the system into a human–AI hybrid. To effectively integrate and manipulate hybrid knowledge, suitable technologies...
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Technological vs. Non-Technological Mindsets: Learning From Mistakes, and Organizational Change Adaptability to Remote Work
PublicationThe permanent implementation of the change in working methods, e.g., working in the virtual space, is problematic for some employees and, as a result, for management leaders. To explore this issue deeper, this study assumes that mindset type: technological vs. non-technological, may influence the organizational adaptability to change. Moreover, the key interest of this research is how non-technological mindsets...
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S09-4 The development of the Physical Activity Environment Policy Index (PA-EPI): a tool for monitoring and benchmarking government policies and actions to improve physical activity
PublicationBackground Insufficient physical activity (PA) is a global issue for health. A multifaceted response, including government action, is essential to improve population levels of PA. The purpose of this study was to develop the ‘Physical Activity Environment Policy Index’ (PA-EPI) monitoring framework to assess government policies and actions for creating a healthy PA environment. Methods An iterative process was undertaken. This...
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The Physical Activity Environment Policy Index for monitoring government policies and actions to improve physical activity
PublicationBackground A multifaceted response, including government action, is essential to improve population levels of physical activity (PA). This article describes the development process of the ‘Physical Activity Environment Policy Index’ (PA-EPI) monitoring framework, a tool to assess government policies and actions for creating a healthy PA environment. Methods An iterative process was undertaken. This involved a review of policy...
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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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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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Advanced Sensor for Non-Invasive Breast Cancer and Brain Cancer Diagnosis Using Antenna Array with Metamaterial-Based AMC
PublicationMicrowave imaging techniques can identify abnormal cells in early development stages. This study introduces a microstrip patch antenna coupled with artificial magnetic conductor (AMC) to realize improved sensor for non-invasive (early-stage) breast cancer and brain cancer diagnosis. The frequency selectivity of the proposed antenna has been increased by the presence of AMC by creating an additional resonance at 2.276 GHz associated...
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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Influence of an Interview Location on Opinions about the Ecosystem Services Provided by Trees
PublicationCollecting opinions regarding environmental management is essential, particularly in urban areas where space is limited, and interests often collide. However, the impact of the conditions in which the research is conducted on opinions and preferences elicited via surveys and interviews about the environment is usually taken for granted. The recent development of computer-aided survey methods allows a simulation of an environment,...
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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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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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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...