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Testbed analysis of video and VoIP transsmission performance in IEEE 802.11 b/g/n networks
PublikacjaThe aim of the work is to analyze capabilities and limitations of different implementations of IEEE 802.11 technologies (IEEE 802.11 b/g/n), utilized for both video streaming and VoIP calls directed to mobile devices. Our preliminary research showed that results obtained with currently popular simulation tools can be drastically different than these possible in real-world environment, so, in order to correctly evaluate performance...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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The point estimate method in a reticulated shell reliability analysis
PublikacjaThe objective of this paper is to present an application of the point estimate method (PEM) that can determine the probabilistic moments for engineering structures. The method is reasonably robust and adequately accurate for a wide range of practical problems. It is a special case of numerical quadrature based on orthogonal polynomials. The main advantage of this method is that, unlike FORM or SORM, it is not necessary to carry...
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Influence of User Mobility and Antenna Placement on System Loss in B2B Networks
PublikacjaIn this paper, the influence of user mobility and on-body antenna placement on system loss in body-to-body communications in indoor and outdoor environments and different mobility scenarios is studied, based on system loss measurements at 2.45 GHz. The novelty of this work lies on the proposal of a classification model to characterise the effect of user mobility and path visibility on system loss, allowing to identify the best...
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Comparison of the effectiveness of automatic EEG signal class separation algorithms
PublikacjaIn this paper, an algorithm for automatic brain activity class identification of EEG (electroencephalographic) signals is presented. EEG signals are gathered from seventeen subjects performing one of the three tasks: resting, watching a music video and playing a simple logic game. The methodology applied consists of several steps, namely: signal acquisition, signal processing utilizing z-score normalization, parametrization and...
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Multidecadal (1960-2011) shoreline changes in Isbjornhamna (Hornsund, Svalbard)
PublikacjaAsection of a gravel−dominated coast in Isbjørnhamna (Hornsund, Svalbard) was analysed to calculate the rate of shoreline changes and explain processes controlling coastal zone development over last 50 years. Between 1960 and 2011, coastal landscape of Isbjørn− hamna experienced a significant shift from dominated by influence of tide−water glacier and protected by prolonged sea−ice conditions towards storm−affected and rapidly...
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Things You Might Not Know about the k-Nearest Neighbors Algorithm
PublikacjaRecommender Systems aim at suggesting potentially interesting items to a user. The most common kind of Recommender Systems is Collaborative Filtering which follows an intuition that users who liked the same things in the past, are more likely to be interested in the same things in the future. One of Collaborative Filtering methods is the k Nearest Neighbors algorithm which finds k users who are the most similar to an active user...
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Preparation, characterization and anti-colitis activity of curcumin-asafoetida complex encapsulated in turmeric nanofiber
PublikacjaUlcerative colitis (UC) is a main form of inflammatory bowel disease (IBD). Asafoetida (ASF) and turmeric have traditionally been used for the treatment of various inflammatory diseases, including UC, because ASF is rich in sulfur compounds and turmeric contains curcumin (CUR). Turmeric nanofiber (TNF), the modified cell wall component of turmeric is considered to play important role in the human diet, health and can be used as...
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Fuzzy Gaussian Decision Tree
PublikacjaThe Decision Tree algorithm is one of the first machine learning algorithms developed. It is used both as a standalone model and as an ensemble of many cooperating trees like Random Forest, AdaBoost, Gradient Boosted Trees, or XGBoost. In this work, a new version of the Decision Tree was developed for classifying real-world signals using Gaussian distribution functions and a fuzzy decision process. The research was carried out...
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Detection of Water on Road Surface with Acoustic Vector Sensor
PublikacjaThis paper presents a new approach to detecting the presence of water on a road surface, employing an acoustic vector sensor. The proposed method is based on sound intensity analysis in the frequency domain. Acoustic events, representing road vehicles, are detected in the sound intensity signals. The direction of the incoming sound is calculated for the individual spectral components of the intensity signal, and the components...
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Hydrodynamic Model of the New Waterway through the Vistula Spit
PublikacjaThe decision to build a new waterway (strait) in the Polish part of the Vistula Spit was made in 2017. The new connection between the Gulf of Gdańsk and the Vistula Lagoon is planned as an artificial navigable channel with a lock and a small port. During storm surges and wind tides in the gulf or in the lagoon, sluicing will be re-quired for vessels to tackle the Vistula Spit. This procedure does not require significant water flow...
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Bifractal receiver operating characteristic curves: a formula for generating receiver operating characteristic curves in credit-scoring contexts
PublikacjaThis paper formulates a mathematical model for generating receiver operating characteristic (ROC) curves without underlying data. Credit scoring practitioners know that the Gini coefficient usually drops if it is only calculated on cases above the cutoff. This fact is not a mathematical necessity, however, as it is theoretically possible to get an ROC curve that keeps the same Gini coefficient no matter how big a share of lowest...
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Leveraging Activation Maps for Improved Acoustic Events Detection and Classification
PublikacjaThis paper presents a novel approach to enhance the accuracy of deep learning models for acoustic event detection and classification in real-world environments. We introduce a method that leverages activation maps to identify and address model overfitting, combined with an expert-knowledge-based event detection algorithm for data pre-processing. Our approach significantly improved classification performance, increasing the F1 score...
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UAV measurements and AI-driven algorithms fusion for real estate good governance principles support
PublikacjaThe paper introduces an original method for effective spatial data processing, particularly important for land administration and real estate governance. This approach integrates Unmanned Aerial Vehicle (UAV) data acquisition and processing with Artificial Intelligence (AI) and Geometric Transformation algorithms. The results reveal that: (1) while the separate applications of YOLO and Hough Transform algorithms achieve building detection...
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Real-Time Sensor-Based Human Activity Recognition for eFitness and eHealth Platforms
PublikacjaHuman Activity Recognition (HAR) plays an important role in the automation of various tasks related to activity tracking in such areas as healthcare and eldercare (telerehabilitation, telemonitoring), security, ergonomics, entertainment (fitness, sports promotion, human–computer interaction, video games), and intelligent environments. This paper tackles the problem of real-time recognition and repetition counting of 12 types of...
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Information Extraction from Polish Radiology Reports using Language Models
PublikacjaRadiology reports are vital elements of directing patient care. They are usually delivered in free text form, which makes them prone to errors, such as omission in reporting radiological findings and using difficult-to-comprehend mental shortcuts. Although structured reporting is the recommended method, its adoption continues to be limited. Radiologists find structured reports too limiting and burdensome. In this paper, we propose...
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Mobile Networks' Analysis in Terms of QoS Performance Assessment
PublikacjaQuality of service (QoS) assessment is one of the basic processes carried out by mobile network operators (MNOs) and regulators of the telecommunications market. Usually, professional companies carry out measurements for various country areas and use cases (scenarios). In this paper, we show exemplary measurement results carried out in drive tests in the vicinity of the Polish capital by a professional company. The measurement...
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Soil and groundwater contamination as a result of sewage sludge land application
PublikacjaThe leaching of chemical compounds (N-NO3, N-NH4, Norg, P-PO4, Ptot) and trace elements (Cd, Cu, Cr, Ni, Zn, and Pb) from sewage sludge and their migration through the soil profile was the subject of the study. The column experiments were carried out under atmospheric conditions corresponding to naturally occurring storm events - sewage sludge amended soil was irrigated with high rates of water. The column filter media used in...
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A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
PublikacjaMachine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It is challenging due to difficulty in distinguishing a true CMB from its mimics, however, if successfully solved it would streamline the radiologists work. To deal with this complex three-dimensional...
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Detection and Model of Thermal Traces Left after Aggressive Behavior of Laboratory Rodents
PublikacjaAutomation of complex social behavior analysis of experimental animals would allow for faster, more accurate and reliable research results in many biological, pharmacological, and medical fields. However, there are behaviors that are not only difficult to detect for the computer, but also for the human observer. Here, we present an analysis of the method for identifying aggressive behavior in thermal images by detecting traces...
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Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublikacjaCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
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A Tutorial on AGREEprep an Analytical Greenness Metric for Sample Preparation
PublikacjaSample preparation is a key step in the analytical procedure and a critical component for achieving analytical greenness. AGREEprep is the first metric intended for evaluating the environmental impact of sample preparation methods. The approach consists of ten steps of assessment that correspond to the ten principles of green sample preparation and uses a user-friendly open-source software to calculate and visualize the results....
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Effective method for determining environmental loads on supporting structures for offshore wind turbines
PublikacjaThis paper presents a description of an effective method for determining loads due to waves, current and wind acting on the supporting structures of the offshore wind turbines. This method is dedicated to the structures consisting of the cylindrical or conical elements as well as (truncates) pyramids of polygon with a large number of sides (8 or more). The presented computational method is based on the Morison equation, which was...
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Effective method for determining environmental loads on supporting structures for offshore wind turbines
PublikacjaThis paper presents a description of an effective method for determining loads due to waves and current acting on the supporting structures of the offshore wind turbines. This method is dedicated to the structures consisting of the cylindrical or conical elements as well as (truncates) pyramids of polygon with a large number of sides (8 or more). The presented computational method is based on the Morison equation, which was originally...
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Modified GAPI (MoGAPI) Tool and Software for the Assessment of Method Greenness: Case Studies and Applications
PublikacjaThe green analytical procedure index (GAPI) has been widely used to assess the greenness of different steps in analytical methodology. In the GAPI index, the different stages of the chemical analysis process are depicted using five pentagrams divided in subsections, labeled green, yellow, or red according to the degree of greenness. This GAPI tool provides a quick overview of the environmental impact and safety of the procedure....
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublikacjaCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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Machine-aided detection of SARS-CoV-2 from complete blood count
PublikacjaThe current gold standard for SARS-CoV-2 detection methods lacks the functionality to perform population screening. Complete blood count (CBC) tests are a cost-effective way to reach a wide range of people – e.g. according to the data of the Central Statistical Office of Poland from 2016, there are 3,000 blood diagnostic laboratories in Poland, and 46% of Polish people have at least one CBC test per year. In our work, we show...
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Blue applicability grade index (BAGI) and software: a new tool for the evaluation of method practicality
PublikacjaIn this work, blue applicability grade index (BAGI) is proposed as a new metric tool for evaluating the practicality of an analytical method. BAGI can be considered complementary to the well-established green metrics, and it is mainly focused on the practical aspects of White Analytical Chemistry. This tool evaluates ten main attributes including the type of analysis, the number of analytes that are simultaneously determined, the...
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Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublikacjaText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
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Ice Phenomena in River Mouths
PublikacjaRiver outlets located in tideless areas are analyzed in this paper. First, ice processes in the St Clair River mouth are presented. The river mouth, called St. Clair Flats is a typical river delta located on the shore of Lake St. Clair. Based on this example ice jam formation in river delta has been analyzed followed by a presentation of the main mechanism of ice jam formation. The Vistula River mouth is a man-made, artificial...
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CNN-CLFFA: Support Mobile Edge Computing in Transportation Cyber Physical System
PublikacjaIn the present scenario, the transportation Cyber Physical System (CPS) improves the reliability and efficiency of the transportation systems by enhancing the interactions between the physical and cyber systems. With the provision of better storage ability and enhanced computing, cloud computing extends transportation CPS in Mobile Edge Computing (MEC). By inspecting the existing literatures, the cloud computing cannot fulfill...
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Morphology and internal structure of small-scale washovers formed in the coastal zone of the semi-enclosed tideless basin, Gulf of Gdańsk, Baltic Sea
PublikacjaThis study explores the morphological features and internal structure of small-scale washovers along the southeastern Baltic Sea coast, providing insights into these most widespread yet often neglected deposits in the recent research of geomorphological and sedimentary record of storm surges. A 15-year-long record of morphological changes of the coast was acquired from regional orthophotos to analyse their geometry and spatial...
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Total impact of oxidative stress genes on cardiovascular events—a 7-year follow-up study
PublikacjaCardiovascular (CV) events are the number one cause of lifetime disability and deaths worldwide. It is well known that traditional risk factors do not fully correlate with clinical outcomes; therefore, searching for other markers that would explain CV events occurrence seems essential. Of importance, one of the main factors at the origin of CV events is oxidative stress, causing inflammation and atherosclerotic plaque instability....
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Quality Evaluation of Speech Transmission via Two-way BPL-PLC Voice Communication System in an Underground Mine
PublikacjaIn order to design a stable and reliable voice communication system, it is essential to know how many resources are necessary for conveying quality content. These parameters may include objective quality of service (QoS) metrics, such as: available bandwidth, bit error rate (BER), delay, latency as well as subjective quality of experience (QoE) related to user expectations. QoE is expressed as clarity of speech and the ability...
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The evaluation of eGlasses eye tracking module as an extension for Scratch
PublikacjaIn this paper we present the possibility of using eGlasses eye tracking module as an extension for Scratch programming tool which is a visual programming language supporting computer skills learning. The main concept behind this project is to setup the interface for rapid interaction design. Eye tracking is a powerful tool for hands free communication but for that requires a dedicated software. This software is rarely tailored...
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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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The possibility of estimating the height of the ionospheric inhomogeneities based on TEC variations maps obtained from dense GPS network
PublikacjaA state of the ionosphere can be effectively studied using electromagnetic signals received from global navigation satellite systems (GNSS). Utilization of the dual frequency observations allows estimating values of the total electron content (TEC). They can be used for a number of scientific studies such as detection and monitoring of traveling ionospheric disturbances or plasma bubbles. Moreover, maps of TEC variations allow...
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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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Vehicle type recognition: a case study of MobileNetV2 for an image Classification task
PublikacjaThe goal of the research was to demonstrate the full data science lifecycle through a use case of the MobileNetv2 model for vehicle image Classification task using various validation and test sets, each with different difficulty level. Diverse model variations were employed, each designed to recognize images of ground vehicles and classify them into one of five possible classes: car, truck, motorcycle, bicycle, or bus. In terms...
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Anterior prefrontal EEG theta activities indicate memory and executive functions in epilepsy patients
PublikacjaObjective: Cognitive deficits are one of the most debilitating comorbidities in epilepsy and other neurodegenerative, neuropsychiatric, and neurodevelopmental brain disorders. Current diagnostic and therapeutic options are limited and lack objective measures of the underlying neural activities. In this study, electrophysiological biomarkers that reflect cognitive functions in clinically validated batteries were determined to aid...
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AGREEMIP: The Analytical Greenness Assessment Tool for Molecularly Imprinted Polymers Synthesis
PublikacjaMolecular imprinting technology is well established in areas where a high selectivity is required, such as catalysis, sensing, and separations/sample preparation. However, according to the Principles of Green Chemistry, it is evident that the various steps required to obtain molecularly imprinted polymers (MIPs) are far from ideal. In this regard, greener alternatives to the synthesis of MIPs have been proposed in recent years....
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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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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublikacjaMobility 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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RE-SHAPING THE LAND AND WATER CONNECTIONS AND ITS ROLE IN ACHIEVING LANDSCAPE AND ECOLOGICAL SYSTEMS’ CONTINUITY ON THE POST-INDUSTRIAL TERRITORIES
PublikacjaThis paper delves into recently applied strategies of creating new water areas and modifying the existing ones as a part of the transformation processes of post-industrial territories. It proves that while the pursuit for unique architectural and urban space values remains an important factor contributing to such modifications, they may also play an important role in reclaiming ecological systems continuity. On the basis of theoretical...
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Modeling protein structures with the coarse-grained UNRES force field in the CASP14 experiment
PublikacjaThe UNited RESidue (UNRES) force field was tested in the 14th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP14), in which larger oligomeric and multimeric targets were present compared to previous editions. Three prediction modes were tested (i) ab initio (the UNRES group), (ii) contact-assisted (the UNRES- contact group), and (iii) template-assisted (the UNRES-template...
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Youth attitude to entrepreneurship in Eastern and Central European countries: Gender aspect
PublikacjaCurrent business conditions pose new challenges to youth entrepreneurship, which is a significant component of countries’ economic growth. In addition, Generation Z differs from previous generations and requires new approaches. In this context, a comprehensive study of the peculiarities and various aspects of youth entrepreneurship development is highly-demanded and relevant. Furthermore, the lower representation of women among...
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Segmentation Quality Refinement in Large-Scale Medical Image Dataset with Crowd-Sourced Annotations
PublikacjaDeployment of different techniques of deep learning including Convolutional Neural Networks (CNN) in image classification systems has accomplished outstanding results. However, the advantages and potential impact of such a system can be completely negated if it does not reach a target accuracy. To achieve high classification accuracy with low variance in medical image classification system, there is needed the large size of the...
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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublikacjaHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublikacjaRenal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...