Search results for: color grading, film production, mood models, emotions detection
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Marek Czachor prof. dr hab.
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Thermodynamic Analysis of Negative CO2 Emission Power Plant Using Aspen Plus, Aspen Hysys, and Ebsilon Software
PublicationAbstract: The article presents results of thermodynamic analysis using a zero-dimensional mathematical models of a negative CO2 emission power plant. The developed cycle of a negative CO2 emission power plant allows the production of electricity using gasified sewage sludge as a main fuel. The negative emission can be achieved by the use this type of fuel which is already a “zeroemissive” energy source. Together with carbon capture...
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A Panel Analysis of the Impact of Green Transformation and Globalization on the Labor Share in the National Income
PublicationThis study aims to examine the impact of green transition and globalization processes on changes in the labour share. The study covers 76 national economies diversified in development, global production share and energy transition stage from 2000 to 2018. Based on the Total Economy Database data, panel models of the relationship between green transition, globalization and the labour share in the national income were estimated....
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Computer-assisted pronunciation training—Speech synthesis is almost all you need
PublicationThe research community has long studied computer-assisted pronunciation training (CAPT) methods in non-native speech. Researchers focused on studying various model architectures, such as Bayesian networks and deep learning methods, as well as on the analysis of different representations of the speech signal. Despite significant progress in recent years, existing CAPT methods are not able to detect pronunciation errors with high...
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The usefulness of Toxoplasma gondii MIC1-MAG1-SAG1 chimeric antigen in the serodiagnosis of ovine toxoplasmosis
PublicationToxoplasmosis is a zoonotic disease caused by the protozoan Toxoplasma gondii, which infects humans and most warm-blooded animals throughout the world. Although human toxoplasmosis in healthy adults is usually asymptomatic, a serious disease can occur in the case of congenital infection and immunocompromised individuals. Among food animals, sheep, along with goats and pigs, possess the highest incidence of T. gondii cysts in meat,...
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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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Integrated Application of GPR and Ultrasonic Testing in the Diagnostics of a Historical Floor
PublicationThe paper presents the results of integrated ground penetrating radar (GPR) and ultrasonic testing (UT) measurements conducted on a historical floor in St. Nicholas’ Church, Gdańsk, Poland. The described inspection was the first stage of the technical state assessment of the building. The aim of the study was the detection of underfloor air gaps, which were observed in a few trial pits. The condition of the ground under the floor...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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The impact of initial and boundary conditions on severe weather event simulations using a high-resolution WRF model. Case study of the derecho event in Poland on 11 August 2017
PublicationPrecise simulations of severe weather events are a challenge in the era of changing climate. By performing simulations correctly and accurately, these phenomena can be studied and better understood. In this paper, we have verified how different initial and boundary conditions affect the quality of simulations performed using the Weather Research and Forecasting Model (WRF). For our analysis, we chose...
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Training of Deep Learning Models Using Synthetic Datasets
PublicationIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Visual Lip Contour Detection for the Purpose of Speech Recognition
PublicationA method for visual detection of lip contours in frontal recordings of speakers is described and evaluated. The purpose of the method is to facilitate speech recognition with visual features extracted from a mouth region. Different Active Appearance Models are employed for finding lips in video frames and for lip shape and texture statistical description. Search initialization procedure is proposed and error measure values are...
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Exploring the Usability and User Experience of Social Media Apps through a Text Mining Approach
PublicationThis study aims to evaluate the applicability of a text mining approach for extracting UUX-related issues from a dataset of user comments and not to evaluate the Instagram (IG) app. This study analyses textual data mined from reviews in English written by IG mobile application users. The article’s authors used text mining (based on the LDA algorithm) to identify the main UUX-related topics. Next, they mapped the identified topics...
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Assessment of the Effective Variants Leading to Higher Efficiency for the Geothermal Doublet, Using Numerical Analysis‒Case Study from Poland (Szczecin Trough)
PublicationNumerical models of geothermal doublet allows us to reduce the high risk associated with the selection of the most eective location of a production well. Furthermore, modeling is a suitable tool to verify possible changes in operational geothermal parameters, which guarantees liveliness of the system. An appropriate selection of software as well as the methodology used to generate numerical models significantly aects the quality...
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Ordered titanium templates functionalized by gold films for biosensing applications – Towards non-enzymatic glucose detection
PublicationRecently, metal nanostructures evoke much interest due to application potential in highly sensitive detectors in biochemistry and medical diagnostics. In this work we report on preparation and characteristics of thin (1–100 nm) Au films deposited onto highly ordered structured titanium templates for SERS (Surface Enhanced Raman Spectroscopy) and electrochemical sensing. The Ti templates are formed by selective removal of TiO2 nanotubes...
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Sustainable nitrogen removal in anammox-mediated systems: Microbial metabolic pathways, operational conditions and mathematical modelling
PublicationAnammox-mediated systems have attracted considerable attention as alternative cost-effective technologies for sustainable nitrogen (N) removal from wastewater. This review comprehensively highlights the importance of understanding microbial metabolism in anammox-mediated systems under crucial operation parameters, indicating the potentially wide applications for the sustainable treatment of N-containing wastewater. The partial...
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Method for the determination of carboxylic acids in industrial effluents using dispersive liquid-liquid microextraction with injection port derivatization gas chromatography–mass spectrometry
PublicationThe paper presents a new method for the determination of 15 carboxylic acids in samples of postoxidative effluents from the production of petroleum bitumens using ion-pair dispersive liquid-liquid microextraction and gas chromatography coupled to mass spectrometry with injection port derivatization. Several parameters related to the extraction and derivatization efficiency were optimized. Under optimized experimental conditions,the...
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Signal conditioning for examination of shallow-water acoustic noise correlation properties
PublicationThe article describes the process of signal conditioning for examination of acoustic noise correlation properties in shallow water. Knowledge of these properties is very important for the design processes of passive and active hydroacoustic systems. This paper focuses on the above issue from the point of view of passive sonar. In sonar systems, signal processing algorithms operate on both useful acoustic signals, and accompanying...
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Adaptacyjny system oświetlania dróg oraz inteligentnych miast
PublicationPrzedmiotem rozprawy jest zbadanie praktycznej możliwości wykrywania w czasie rzeczywistym anomalii w systemie oświetlenia drogowego w oparciu o analizę danych ze inteligentnych liczników energii. Zastosowanie inteligentnych liczników energii elektrycznej (Smart Meter) w systemach oświetlenia drogowego stwarza nowe możliwości w zakresie automatycznej diagnostyki takich niepożądanych zjawisk jak awarie lamp, odstępstwa od harmonogramu...
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Modeling lignin extraction with ionic liquids using machine learning approach
PublicationLignin, 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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Computer Simulation in Predicting Biochemical Processes and Energy Balance at WWTPs
PublicationNowadays, the use of mathematical models and computer simulation allow analysis of many different technological solutions as well as testing various scenarios in a short time and at low financial budget in order to simulate the scenario under typical conditions for the real system and help to find the best solution in design or operation process. The aim of the study was to evaluate different concepts of biochemical processes and...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublicationThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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End-Of-Life Management of Photovoltaic Solar Modules
PublicationThe PV industry continues to push its credentials as a technology that addresses one of the fundamental challenges of our times – climate change. There are however two major concerns about this technology: first, the potential negative environmental impacts of energy used in the production stage and second, the possible shortage of the valuable materials in the future. The currently dominant semiconductor used in photovoltaic modules...
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Comparison of heat transfer characteristics in surface cooling using microjets with water, ethanol and HFE7100 as test fluids
PublicationAccurate control of cooling parameters is required in ever wider range of technical applications. It is known that reducing the dimensions of the size of nozzle leads to an increase in the economy of cooling and improves its quality. Present study describes research related to the design and construction of the nozzles and microjet study, which may be applied in many technical applications such as in metallurgy, electronics, etc....
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Application of dynamic headspace and gas chromatography coupled to mass spectrometry (DHS-GC-MS) for the determination of oxygenated volatile organic compounds in refinery effluents
PublicationThe paper presents a new procedure for the determination of oxygenated volatile organic compounds (O-VOCs) in postoxidative effluents from the production of petroleum asphalt using dynamic headspace coupled to gas chromatography-mass spectrometry in the selected ion monitoring (SIM) mode (DHSGC-MS). Among the GC capillary columns tested, a polar SLB-IL111 column with the ionic liquid stationary phase was found to be superior due...
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Diagnostyka ultradźwiękowa mostowej belki prefabrykowanej typu T metodą młoteczkową
PublicationZastosowanie prefabrykacji w budowie obiektów mostowych pozwala optymalizować zużycie energii i materiałów i tym samym redukować koszty budowanego obiektu. Prefabrykowane belki sprężone mogą występować jako elementy kablobetonowe wykonywane bezpośrednio na placu budowy lub powstawać w zakładzie prefabrykacji jako elementy strunobetonowe. Elementy prefabrykowane wytwarzane w warunkach przemysłowych muszą spełniać wymagania wysokiej trwałości,...
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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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Investigation of poly(3,4-ethylenedioxythiophene) deposition method influence on properties of ion-selective electrodes based on bis(benzo-15-crown-5) derivatives
PublicationGlassy carbon electrodes modified by conductive polymers and membrane with derivatives of bis(benzo-15-crown-5) were tested as solid contact ion selective electrodes for K+ ions concentration determination. PEDOT with PSS, Cl- and ClO4- counter ions was electrochemically deposited onto glassy carbon substrates using four different electrochemical approaches (potentiostatic, galvanostatic, potentiodynamic and potentiostatic pulses)....
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Light-improved glucose sensing on ordered Au-Ti heterostructure
PublicationNon-enzymatic electrochemical platforms sensitive towards glucose presence have attracted a worldwide attention during last decades. We report on influence of solar light onto response of gold-titanium heterostructures prepared via controllable approach. The material based on Au nanoparticles orderly distributed over the structured titanium foil was obtained by electrochemical anodization followed by chemical etching, magnetron...
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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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Toxoplasma gondii Recombinant Antigens in the Serodiagnosis of Toxoplasmosis in Domestic and Farm Animals
PublicationToxoplasmosis is caused by an intracellular protozoan, Toxoplasma gondii, and is a parasitic disease that occurs in all warm-blooded animals, including humans. Toxoplasmosis is one of the most common parasitic diseases of animals and results in reproductive losses. Toxoplasmosis in humans is usually caused by eating raw or undercooked meat or consuming dairy products containing the parasite. Diagnosis of toxoplasmosis is currently...
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Method for the simultaneous determination of monoaromatic and polycyclic aromatic hydrocarbons in industrial effluents using dispersive liquid-liquid microextraction with GC-MS
PublicationWe present a new method for simultaneous determination of 22 monoaromatic and polycyclic aromatic hydrocarbons in postoxidative effluents from the production of petroleum bitumen using dispersive liquid-liquid microextraction coupled to gas chromatography and mass spectrometry. The eight extraction parameters including the type and volume of extraction and disperser solvent, pH, salting out effect, extraction and centrifugation...
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Development and validation of a model that includes two ultrasound parameters and the plasma D-dimer level for predicting malignancy in adnexal masses: an observational study
PublicationBackground: Pre-operative discrimination of malignant from benign adnexal masses is crucial for planning additional imaging, preparation, surgery and postoperative care. This study aimed to define key ultrasound and clinical variables and develop a predictive model for calculating preoperative ovarian tumor malignancy risk in a gynecologic oncology referral center. We compared our model to a subjective ultrasound assessment (SUA)...
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Novel ABTS-dot-blot method for the assessment of antioxidant properties of food packaging
PublicationThe new ABTS-dot-blot method for the direct determination of antioxidant activity of active packaging that is in contact with foodstuffs has been developed. The usefulness of the new method was verified with the use of agarose, pork gelatin, bacterial cellulose and cellulose-chitosan films with incorporated standard antioxidant – Trolox or plant phytochemicals derived from three types of berry juices (chokeberry, blue-berried honeysuckle,...
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Optimization of Bread Production Using Neuro-Fuzzy Modelling
PublicationAutomation of food production is an actively researched domain. One of the areas, where automation is still not progressing significantly is bread making. The process still relies on expert knowledge regarding how to react to procedure changes depending on environmental conditions, quality of the ingredients, etc. In this paper, we propose an ANFIS-based model for changing the mixer speed during the kneading process. Although the...
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REVIEW OF CURRENT RESEARCH ON CHITOSAN AS A RAW MATERIAL IN THREE-DIMENSIONAL PRINTING TECHNOLOGY IN BIOMEDICAL APPLICATIONS
PublicationThree-dimensional (3D) biomaterial manufacturing strategies show an extraordinary driving force for the development of innovative solutions in the biomedical sector, including drug delivery systems, disease modelling and tissue and organ engineering. Due to its remarkable and promising biological and structural properties, chitosan has been widely studied for decades in several potential applications in the biomedical field. However,...
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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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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublicationThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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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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Towards an experience based collective computational intelligence for manufacturing
PublicationKnowledge based support can play a vital role not only in the new fast emerging information and communication technology based industry, but also in traditional manufacturing. In this regard, several domain specific research endeavors have taken place in the past with limited success. Thus, there is a need to develop a flexible domain independent mechanism to capture, store, reuse, and share manufacturing knowledge. Consequently,...
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Impact of Visual Image Quality on Lymphocyte Detection Using YOLOv5 and RetinaNet Algorithms
PublicationLymphocytes, a type of leukocytes, play a vital role in the immune system. The precise quantification, spatial arrangement and phenotypic characterization of lymphocytes within haematological or histopathological images can serve as a diagnostic indicator of a particular lesion. Artificial neural networks, employed for the detection of lymphocytes, not only can provide support to the work of histopathologists but also enable better...
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Processing of LiDAR and Multibeam Sonar Point Cloud Data for 3D Surface and Object Shape Reconstruction
PublicationUnorganised point cloud dataset, as a transitional data model in several applications, usually contains a considerable amount of undesirable irregularities, such as strong variability of local point density, missing data, overlapping points and noise caused by scattering characteristics of the environment. For these reasons, further processing of such data, e.g. for construction of higher order geometric models of the topography...
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Flood Classification in a Natural Wetland for Early Spring Conditions Using Various Polarimetric SAR Methods
PublicationAbstract--- One of the major limitations of remote sensing flood detection is the presence of vegetation. Our study focuses on a flood classification using Radarsat-2 Quad-Pol data in a natural floodplain during leafless, dry vegetation (early spring) state. We conducted a supervised classification of a data set composed of nine polarimetric decompositions and Shannon entropy followed by the predictors' importance estimation to...
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Improving methods to calculate the loss of ecosystem services provided by urban trees using LiDAR and aerial orthophotos
PublicationIn this paper we propose a methodology for combining remotely sensed data with field measurements to assess selected tree parameters (diameter at breast height (DBH) and tree species) required by the i-Tree Eco model to estimate ecosystem services (ES) provided by urban trees. We determined values of ES provided by trees in 2017 in Racibórz (a city in South Poland) and estimated the loss of ES from January 1, 2017 to March 5, 2017,...
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Hydrophobic deep eutectic solvents as “green” extraction media for polycyclic aromatic hydrocarbons in aqueous samples
PublicationThe paper presents novel nonionic and hydrophobic deep eutectic solvents which were synthesized from natural compounds, i.e., thymol, ±camphor, decanoic and 10-undecylenic acids. Fundamental physicochemical properties of the synthesized deep eutectic solvents were determined, followed by their application as extractants in ultrasound-assisted dispersive liquid-liquid microextraction to isolate and enrich polycyclic aromatic hydrocarbons...
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Net-zero carbon condition in wastewater treatment plants: A systematic review of mitigation strategies and challenges
PublicationThe wastewater sector accounts for up to 7 and 10% of anthropogenic CH4 and N2O emissions, respectively. Nowadays wastewater treatment plants are going through a paradigm shift to approach a net-zero carbon condition. Numerous ongoing measures have taken place to identify the sources of greenhouse gases and minimize the carbon footprint. This paper systematically reviews all known practices leading towards net-zero carbon wastewater...
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublicationNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification
PublicationDeveloping of theoretical tools can be very helpful for supporting new pollutant detection. Nowadays, a combination of mass spectrometry and chromatographic techniques are the most basic environmental monitoring methods. In this paper, two organochlorine compound mass spectra classification systems were proposed. The classification models were developed within the framework of artificial neural networks (ANNs) and fast 1D and...
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MultiRegional PCA for leakage detection and localisation in DWDS - Chojnice case study
PublicationThis chapter considers pipe leakage detection and localisation in Drinking Water Distribution Systems (DWDS) by using a novel approach the MultiRegional Principal Component Analysis (MR-PCA). The MR-PCA is an extension of well known PCA method. The main idea of MR-PCA consists in designing a number of regional PCA models and analysing their responses caused by the pipe faults. Moreover, DWDS is decomposed into suitable subnetworks...
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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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Using Convolutional Neural Networks for Corneal Arcus Detection Towards Familial Hypercholesterolemia Screening
PublicationFamilial 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...