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Wyniki wyszukiwania dla: UNRESCOARSE GRAINING
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Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach
PublikacjaLine heating is one of the alternative methods of forming metals and this kind of forming uses the heating torch as a source of heat input. During the process, many parameters are considered like the size of the substrate, thickness, cooling method, source power intensity, the travel speed of the power source, the sequence of heating, and so on. It is important to analyze the factors affecting the...
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Modeling lignin extraction with ionic liquids using machine learning approach
PublikacjaLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
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Challenges and Perspectives of Nature-Based Wastewater Treatment and Reuse in Rural Areas of Central and Eastern Europe
Publikacjan Central and Eastern Europe, about one-third of the population lives in small settlements (<2000 PE). Since the current European Urban Wastewater Treatment Directive (91/271/EEC) does not clearly regulate the collection and treatment of wastewater from these settlements, countries solve the problem individually. Simple and robust technologies such as nature-based treatment systems could be the solution and are widely applied in...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublikacjaIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Do the young employees perceive themselves as digitally competent and does it matter?
PublikacjaPurpose – The study aims to examine the digital competence of young employees (under 30 years of age) who graduated from the technical university. Self-assessment of selected digital competencies was examined along with the determination of a self-efficacy level in the area of using digital competencies. Design/methodology/approach – Quantitative research was conducted using the computer-assisted web interview method on a sample...
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Efficient Surrogate Modeling and Design Optimization of Compact Integrated On-Chip Inductors Based on Multi-Fidelity EM Simulation Models
PublikacjaHigh-performance and small-size on-chip inductors play a critical role in contemporary radio-frequency integrated circuits. This work presents a reliable surrogate modeling technique combining low-fidelity EM simulation models, response surface approximations based on kriging interpolation, and space mapping technology. The reported method is useful for the development of broadband and highly accurate data-driven models of integrated...
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An audio-visual corpus for multimodal automatic speech recognition
Publikacjareview of available audio-visual speech corpora and a description of a new multimodal corpus of English speech recordings is provided. The new corpus containing 31 hours of recordings was created specifically to assist audio-visual speech recognition systems (AVSR) development. The database related to the corpus includes high-resolution, high-framerate stereoscopic video streams from RGB cameras, depth imaging stream utilizing Time-of-Flight...
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Multicomponent ionic liquid CMC prediction
PublikacjaWe created a model to predict CMC of ILs based on 704 experimental values published in 43 publications since 2000. Our model was able to predict CMC of variety of ILs in binary or ternary system in a presence of salt or alcohol. The molecular volume of IL (Vm), solvent-accessible surface (Sˆ), solvation enthalpy (DsolvGN), concentration of salt (Cs) or alcohol (Ca) and their molecular volumes (Vms and Vma, respectively) were chosen...
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Reliable Surrogate Modeling of Antenna Input Characteristics by Means of Domain Confinement and Principal Components
PublikacjaA reliable design of contemporary antenna structures necessarily involves full-wave electromagnetic (EM) analysis which is the only tool capable of accounting, for example, for element coupling or the effects of connectors. As EM simulations tend to be CPU-intensive, surrogate modeling allows for relieving the computational overhead of design tasks that require numerous analyses, for example, parametric optimization or uncertainty...
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Performance-driven yield optimization of high-frequency structures by kriging surrogates
PublikacjaUncertainty quantification is an important aspect of engineering design, as manufacturing toler-ances may affect the characteristics of the structure. Therefore, quantification of these effects is in-dispensable for adequate assessment of the design quality. Toward this end, statistical analysis is performed, for reliability reasons, using full-wave electromagnetic (EM) simulations. Still, the computational expenditures associated...
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Electronic nose algorithm design using classical system identification for odour intensity detection
PublikacjaThe two elements considered crucial for constructing an efficient environmental odour intensity monitoring systems are sensors and algorithms typically addressed to as electronic nose sensor (e-nose). Due to operational complexity of biochemical sensors developed in human bodies algorithms based on computational methods of artificial intelligence are typically considered superior to classical model based approaches in development...
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Transfer learning in imagined speech EEG-based BCIs
PublikacjaThe Brain–Computer Interfaces (BCI) based on electroencephalograms (EEG) are systems which aim is to provide a communication channel to any person with a computer, initially it was proposed to aid people with disabilities, but actually wider applications have been proposed. These devices allow to send messages or to control devices using the brain signals. There are different neuro-paradigms which evoke brain signals of interest...
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Predicting emotion from color present in images and video excerpts by machine learning
PublikacjaThis 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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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publikacja(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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Optical and chemical characterization of thin TiNx films deposited by DC-magnetron sputtering
PublikacjaThin titanium nitride (tinx) films were deposited on silicon substrates by means of a reactive dc-magnetron plasma. Layers were synthesized under various conditions of discharge power and nitrogen flows in two operation modes of the magnetron (the so-called "balanced" and "unbalanced" modes). The optical constants of the tinx films were investigated by spectroscopic ellipsometry (se). X-ray photoelectron spectroscopy (xps) was...
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State-of-the-art ideas for engineering laboratory classes – virtual reality framework
PublikacjaNowadays challenges in science and technology are a driving force in the development of contemporary solutions in education. Virtual reality brings to an edge human imagination. In this paper, authors propose a framework for civil engineering laboratory classes which brings a new quality in this area. The framework shows how to provide learners with an environment where they can realize the health and safety hazards of construction...
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Billiard in a rotating half-plane
PublikacjaThe main objective of this research is to study the properties of a billiard system in an unbounded domain with moving boundary. We consider a system consisting of an infinite rod (a straight line) and a ball (a massless point) on the plane. The rod rotates uniformly around one of its points and experiences elastic collisions with the ball. We define a mathematical model for the dynamics of such a system and write down asymptotic...
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Jednofazowy falownik napięcia z aktywnym obwodem odsprzęgającym
PublikacjaZnanym zagadnieniem w jednofazowych falownikach napięcia jest pobieranie ze źródła napięcia stałego składowej przemiennej o częstotliwości dwukrotnie większej od częstotliwości generowanej przez falownik. Jednym z rozwiązań problemu jest stosowanie dużej baterii kondensatorów elektrolitycznych, lecz lepszym sposobem z punktu widzenia niezawodności i gęstości mocy przekształtnika jest stosowanie aktywnych układów odsprzęgania mocy....
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublikacjaDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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Machine Learning Techniques in Concrete Mix Design
PublikacjaConcrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which the most popular are methods derived from The Three Equation Method. One of the most important features of concrete is compressive strength, which...
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Morphology, Thermo-Mechanical Properties and Biodegradibility of PCL/PLA Blends Reactively Compatibilized by Different Organic Peroxides
PublikacjaReactive blending is a promising approach for the sustainable development of bio-based polymer blends and composites, which currently is gaining more and more attention. In this paper, biodegradable blends based on poly(ε-caprolactone) (PCL) and poly(lactic acid) (PLA) were prepared via reactive blending performed in an internal mixer. The PCL and PLA content varied in a ratio of 70/30 and 55/45. Reactive modification of PCL/PLA...
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The Multiplatform Environment for Simulation and Features Estimation of Mixed-Signal Devices
PublikacjaThe use of simulation laboratories is gaining popularity in thedomains of engineering programs. However, the experience in teaching showsthat the simulation itself is not very effective in didactic processes. Teachingprocesses in thefield of specialist subjects, designed for students of technicaluniversities, should be based on direct operations performed by the student onreal devices. At the same time, at the later stages of didactic...
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May Staphylococcus lugdunensis Be an Etiological Factor of Chronic Maxillary Sinuses Infection?
PublikacjaStaphylococcus lugdunensis is an opportunistic pathogen found in the healthy human skin microbiome bacterial community that is able to cause infections of diverse localization, manifestation, and course, including laryngological infections, such as necrotizing sinusitis. Chronic maxillary sinusitis is a disease present in up to one third of European and American populations, and its etiology is not fully described. Within this...
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Microbiological Survey in Two Arctic Fjords: Total Bacterial Number and Biomass Comparison of Hornsund and Kongsfjorden
PublikacjaTwo microbiological parameters: total bacterial number (TBN) and biomass (BBM) were studied in two Arctic fjords: Hornsund and Kongsfjorden. Samples were collected from three sampling points in each fjord, from various water depth layers: from the surface to 75 m depth. Total bacterial number and biomass were examined using the DAPI staining and direct count method. The greater amount of bacteria, as well as highest bacterial biomass...
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Microbiological Survey in Two Arctic Fjords: Total Bacterial Number and Biomass Comparison of Hornsund and Kongsfjorden
PublikacjaTwo microbiological parameters: total bacterial number (TBN) and biomass (BBM) were studied in two Arctic fjords: Hornsund and Kongsfjorden. Samples were collected from three sampling points in each fjord, from various water depth layers: from the surface to 75 m depth. Total bacterial number and biomass were examined using the DAPI staining and direct count method. The greater amount of bacteria, as well as highest bacterial biomass...
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Digital fingerprinting for color images based on the quaternion encryption scheme
PublikacjaIn this paper we present a new quaternion-based encryption technique for color images. In the proposed encryption method, images are written as quaternions and are rotated in a three-dimensional space around another quaternion, which is an encryption key. The encryption process uses the cipher block chaining (CBC) mode. Further, this paper shows that our encryption algorithm enables digital fingerprinting as an additional feature....
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Cyanogenic Compounds and Estrogen Disruptors
PublikacjaBalanced diet consists largely of plants containing cyanogenic compounds in the form of the more common cyanogenic glycosides and sometimes lipids. Maize, wheat, rye, apples, barley, oats, sugar cane and yet many other plants consumed by humans contain cyanogenic compounds. However the risk of poisoning is negligible as it is very easy to remove the toxic HCN by grinding and drying in air or soaking in water and an additional...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublikacjaThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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sp2-rich dendrite-like carbon nanowalls as effective electrode for environmental monitoring of explosive nitroaromatic
PublikacjaNitroaromatic compounds are commonly used explosive materials that pose a risk to human health and ecosystems due to their acute toxicity and carcinogenicity. Nitroaromatics have numerous pathways into the environment via discarded munitions (e.g. into the Baltic Sea after World War II), after use in mining operations, and in industrial run-off from factories producing these compounds (which are produced across the world to date)....
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News that Moves the Market: DSEX-News Dataset for Forecasting DSE Using BERT
PublikacjaStock market is a complex and dynamic industry that has always presented challenges for stakeholders and investors due to its unpredictable nature. This unpredictability motivates the need for more accurate prediction models. Traditional prediction models have limitations in handling the dynamic nature of the stock market. Additionally, previous methods have used less relevant data, leading to suboptimal performance. This study...
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublikacjaThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Gesture Recognition With the Linear Optical Sensor and Recurrent Neural Networks
PublikacjaIn this paper, the optical linear sensor, a representative of low-resolution sensors, was investigated in the multiclass recognition of near-field hand gestures. The recurrent neural network (RNN) with a gated recurrent unit (GRU) memory cell was utilized as a gestures classifier. A set of 27 gestures was collected from a group of volunteers. The 27 000 sequences obtained were divided into training, validation, and test subsets....
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Detecting type of hearing loss with different AI classification methods: a performance review
PublikacjaHearing is one of the most crucial senses for all humans. It allows people to hear and connect with the environment, the people they can meet and the knowledge they need to live their lives to the fullest. Hearing loss can have a detrimental impact on a person's quality of life in a variety of ways, ranging from fewer educational and job opportunities due to impaired communication to social withdrawal in severe situations. Early...
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Assessing the attractiveness of human face based on machine learning
PublikacjaThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
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Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
PublikacjaIonic 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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Performance-Based Nested Surrogate Modeling of Antenna Input Characteristics
PublikacjaUtilization of electromagnetic (EM) simulation tools is mandatory in the design of contemporary antenna structures. At the same time, conducting designs procedures that require multiple evaluations of the antenna at hand, such as parametric optimization or yield-driven design, is hindered by a high cost of accurate EM analysis. To certain extent, this issue can be addressed by utilization of fast replacement models (also referred...
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Smart Approach for Glioma Segmentation in Magnetic Resonance Imaging using Modified Convolutional Network Architecture (U-NET)
PublikacjaSegmentation of a brain tumor from magnetic resonance multimodal images is a challenging task in the field of medical imaging. The vast diversity in potential target regions, appearance and multifarious intensity threshold levels of various tumor types are few of the major factors that affect segmentation results. An accurate diagnosis and its treatment demand strict delineation of the tumor affected tissues. Herein, we focus on...
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Graph Representation Integrating Signals for Emotion Recognition and Analysis
PublikacjaData reusability is an important feature of current research, just in every field of science. Modern research in Affective Computing, often rely on datasets containing experiments-originated data such as biosignals, video clips, or images. Moreover, conducting experiments with a vast number of participants to build datasets for Affective Computing research is time-consuming and expensive. Therefore, it is extremely important to...
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Functional safety and cyber security analysis for life cycle management of industrial control systems in hazardous plants and oil port critical infrastructure including insurance
PublikacjaThis report addresses selected methodological aspects of proactive reliability, functional safety and cyber security management in life cycle of industrial automation and control systems (IACS) in hazardous plants and oil port critical installations based on the analysis of relevant hazards / threats and evaluation of related risks. In addition the insurance company point of view has been also considered, because nowadays the insurer,...
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Psychosocial risks associated with the profession of train driver
PublikacjaExcellent competencies as well as a good physical and mental health are required in train drivers’ profession. Despite the changes in the structure of employment the train drivers above 46 years and job tenure longer than 30 years are the largest group. The generation gap is becoming more pronounced, and its fulfilment will not be easy. It is related not only to training of new personnel but also promotion of healthy work environment...
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Using Convolutional Neural Networks for Corneal Arcus Detection Towards Familial Hypercholesterolemia Screening
PublikacjaFamilial hypercholesterolemia (FH) is a highly undiagnosed disease. Among FH patients, the onset of premature coronary artery disease is 13 times higher than in the general population. Early diagnosis and treatment is essential to prevent cardiovascular diseases and their complications, and to prolong life. One of the clinical criteria of FH is the occurrence of a corneal arcus (CA) among patients, especially those under 45 years...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublikacjaTreatment 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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The Effectiveness of Basic Resuscitation Activities Carried out by Combat Paramedics of the Police, as Exemplified by Polish Counterterrorist Units
PublikacjaThe tasks carried out by Police officers are often accompanied by dangerous situations that threaten the life and health of the people involved, the police themselves, and bystanders. It concerns especially counter-terrorism police units whose activities are aimed at terrorists and particularly dangerous criminals, and their course is violent and aggressive. In conjunction with the inability to bring civilian rescue services into...
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Magnetic Signature Description of Ellipsoid-Shape Vessel Using 3D Multi-Dipole Model Fitted on Cardinal Directions
PublikacjaThe article presents a continuation of the research on the 3D multi-dipole model applied to the reproduction of magnetic signatures of ferromagnetic objects. The model structure has been modified to improve its flexibility - model parameters determined by optimization can now be located in the cuboid contour representing the object's hull. To stiffen the model, the training dataset was expanded to data collected from all four cardinal...
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Reduced-Cost Two-Level Surrogate Antenna Modeling using Domain Confinement and Response Features
PublikacjaElectromagnetic (EM) simulation tools have become indispensable in the design of contemporary antennas. Still, the major setback of EM-driven design is the associated computational overhead. This is because a single full-wave simulation may take from dozens of seconds up to several hours, thus, the cost of solving design tasks that involve multiple EM analyses may turn unmanageable. This is where faster system representations (surrogates)...
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Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images
PublikacjaIn 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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Pedestrian detection in low-resolution thermal images
PublikacjaOver 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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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublikacjaMany 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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Rapid Design of 3D Reflectarray Antennas by Inverse Surrogate Modeling and Regularization
PublikacjaReflectarrays (RAs) exhibit important advantages over conventional antenna arrays, especially in terms of realizing pencil-beam patterns without the employment of the feeding networks. Unfortunately, microstrip RA implementations feature narrow bandwidths, and are severely affected by losses. A considerably improved performance can be achieved for RAs involving grounded dielectric layers, which are also easy to manufacture using...