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Search results for: AIR QUALITY, POLLUTANT DETECTION, NITROGEN DIOXIDE, SENSOR CORRECTION, MACHINE LEARNING, ARTIFICIAL NEURAL NETWORKS
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Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China
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Machine Learning Methods in Damage Prediction of Masonry Development Exposed to the Industrial Environment of Mines
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublicationTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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The effect of reduced pressure on carbon dioxide flow boiling heat transfer in minichannels
Publication. In the paper presented are the results of the study on the effect of reduced pressure on flow boiling heat transfer data in minichannels as well as conventional ones. That effect renders that most of heat transfer correlations fail to return appropriate results of predictions. Mostly they have been developed for the reduced pressures from the range 0.1-0.3. The special correction has been postulated to the in-house model of flow...
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International Journal of Distributed Sensor Networks
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Lifelong Learning Idea in Architectural Education
PublicationThe recent advances in IT and technology are forcing changes in the approach to educating society. In the 20th century, life-long learning was understood as educating adults in order to improve their occupational qualifications. Life-long learning allows the needs of the present-day world to be addressed through providing the individual with education at every stage of his/her life various forms. The search for a new model...
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Broken Rotor Symptons in the Sensorless Control of Induction Machine
PublicationInverter fed sensorless controlled variable speed drives with induction machine are widely used in the industry applications, also in wind power generation and electric vehicles. On-line self diagnostic systems implementation is needed for early stage fault detection and avoiding a critical fault. Diagnostic algorithms in modern DSP-based controllers can operate simultaneously with control system functions. In the closed-loop controlled...
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Correction: Surgeons’ perspectives on artificial intelligence to support clinical decision-making in trauma and emergency contexts: results from an international survey
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Is Artificial Intelligence Ready to Assess an Enterprise’s Financial Security?
PublicationThis study contributes to the literature on financial security by highlighting the relevance of the perceptions and resulting professional judgment of stakeholders. Assessing a company’s financial security using only economic indicators—as suggested in the existing literature—would be inaccurate when undertaking a comprehensive study of financial security. Specifically, indices and indicators based on financial or managerial reporting...
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Guest editorial: learning, scheduling, resource optimization, and evolution in smart artificial systems: challenges and support
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublicationTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
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A Novel Method for the Deblurring of Photogrammetric Images Using Conditional Generative Adversarial Networks
PublicationThe visual data acquisition from small unmanned aerial vehicles (UAVs) may encounter a situation in which blur appears on the images. Image blurring caused by camera motion during exposure significantly impacts the images interpretation quality and consequently the quality of photogrammetric products. On blurred images, it is difficult to visually locate ground control points, and the number of identified feature points decreases...
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Musical Instrument Identification Using Deep Learning Approach
PublicationThe work aims to propose a novel approach for automatically identifying all instruments present in an audio excerpt using sets of individual convolutional neural networks (CNNs) per tested instrument. The paper starts with a review of tasks related to musical instrument identification. It focuses on tasks performed, input type, algorithms employed, and metrics used. The paper starts with the background presentation, i.e., metadata...
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Application of mechanistic and data-driven models for nitrogen removal in wastewater treatment systems
PublicationIn this dissertation, the application of mechanistic and data-driven models in nitrogen removal systems including nitrification and deammonification processes was evaluated. In particular, the influential parameters on the activity of the Nitrospira activity were assessed using response surface methodology (RSM). Various long-term biomass washout experiments were operated in two parallel sequencing batch reactor (SBR) with a different...
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Zirconia-based mixed potential sensor with Pt electrode prepared by spin-coating of polymeric precursor
PublicationMany types of yttria-stabilized zirconia (YSZ) based gas sensors have been explored extensively in recent years. Great attention have been directed to mixed-potential-type gas sensors. It is due to growing concerns with environmental issues. Not without a significance is the fact of very attractive performance of this type of sensor allowing to detect low concentration of pollutant gases. In this paper two types of YSZ based mixed-potential...
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Data Quality Assurance 2024
e-Learning CoursesData quality assurance / Zapewnianie jakości danych 2023 Prowadzący: Paweł Weichbroth Wykład: odbywają się zdalnie. Projekt w drugiej połowie semestru Kod dostępu do przedmiotu w eNauczanie będzie przekazany podczas pierwszego wykładu
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublicationBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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Practical issues for the implementation of survivability and recovery techniques in optical networks
PublicationFailures in optical networks are inevitable. They may occur during work being done for the maintenance of other infrastructures, or on a larger scale as the result of an attack or large-scale disaster. As a result, service availability, an important aspect of Quality of Service (QoS), is often degraded. Appropriate fault recovery techniques are thus crucial to meet the requirements set by the Service Level Agreements (SLAs) between...
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Toward Intelligent Recommendations Using the Neural Knowledge DNA
PublicationIn this paper we propose a novel recommendation approach using past news click data and the Neural Knowledge DNA (NK-DNA). The Neural Knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for news recommendation tasks on the MIND benchmark dataset. By taking advantages of NK-DNA, deep...
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Influence of operation temperature instability on gas sensor performance
PublicationGas sensors based on the semiconducting metal-oxides, such as SnO2, have been found to be very useful for detecting a wide range of gases. The reversible interactions of the gas with the surface of the sensing layer made of semiconducting metal-oxides are responsible for changes of sensor resistance which is usually used as a measure of sensor response. Semiconductor gas sensors are commercially available and applied in numerous...
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Histogram of Oriented Gradients with Cell Average Brightness for Human Detection
PublicationA modification of the descriptor in a human detector using Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM) is presented. The proposed modification requires inserting the values of average cell brightness resulting in the increase of the descriptor length from 3780 to 3908 values, but it is easy to compute and instantly gives ≈ 25% improvement of the miss rate at 10‒4 False Positives Per Window (FPPW). The...
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Modeling the Networks - ed. 2021/2022
e-Learning CoursesThe goal of this course is to present optimization problems for road networks, where the road network is a set of n distinct lines, or n distinct (open or closed) line segments, in the plane, such that their union is a connected region.
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Abdominal Aortic Aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks
PublicationOne of the most common imaging methods for diagnosing an abdominal aortic aneurysm, and an endoleak detection is computed tomography angiography. In this paper, we address the problem of aorta and thrombus semantic segmentation, what is a mandatory step to estimate aortic aneurysm diameter. Three end-to-end convolutional neural networks were trained and evaluated. Finally, we proposed an ensemble of deep neural networks with underlying...
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Throughput vs. Resilience in Multi-hop Wireless Sensor Networks with Periodic Packet Traffic
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Modelling changes in the energy efficiency of buildings using neural networks on the example of Zielona Góra
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Prediction of Early Childhood Caries Based on Single Nucleotide Polymorphisms Using Neural Networks
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Edyta Gołąb-Andrzejak dr hab.
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublicationThe 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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A study on transverse shear correction for laminated sandwich panels
PublicationThe paper presents a study on an application of the First Order Shear Deformation Theory in a linear static analysis of elastic sandwich panels. A special attention has been given to the issue of the transverse shear correction. Two benchmark examples of sandwich plate problems with known reference solutions have been selected for a comparative analysis performed with own Finite Element codes. Interesting results allowed for drawing...
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How to guide photocatalytic applications of titanium dioxide co-doped with nitrogen and carbon by modulating the production of reactive oxygen species
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Hardware-Software Implementation of a Sensor Network for CityTraffic Monitoring Using the FPGA- and ASIC-Based Sensor Nodes
PublicationArtykuł opisuje prototypową sieć sensorową do monitorowania ruchu pojazdów w mieście. Węzły sieci sensorowej, wyposażone w kamerę o niskiej rozdzielczości, obserwują ulice i wykrywają poruszające się obiekty. Detekcja obiektów jest realizowana w oparciu o własny algorytm segmentacji obrazów, wykorzystujący podwójne odejmowanie tła, wykrywanie krawędzi i cieni, działający na dedykowanym systemie mikroelektronicznym typu ''System...
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Categorization of emotions in dog behavior based on the deep neural network
PublicationThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
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Data quality assurance - 2023
e-Learning CoursesData quality assurance / Zapewnianie jakości danych 2023 Prowadzący: Andrzej Wardziński Wykład: od 13 marca, poniedziałki 13:15 sala NE Audytorium 2 Projekt w drugiej połowie semestru Kod dostępu do przedmiotu w eNauczanie będzie przekazany podczas pierwszego wykładu
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Deep neural network architecture search using network morphism
PublicationThe paper presents the results of the research on neural architecture search (NAS) algorithm. We utilized the hill climbing algorithm to search for well-performing structures of deep convolutional neural network. Moreover, we used the function preserving transformations which enabled the effective operation of the algorithm in a short period of time. The network obtained with the advantage of NAS was validated on skin lesion classification...
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Optimised Robust Placement of Hard Quality Sensors for Robust Monitoring of Quality in Drinking Water Distribution Systems
PublicationA problem of optimised robust placement of the hard quality sensors in Drinking Water Distribution Systems under several water demand scenarios for robust quality monitoring is formulated. Numerical algorithms to solve the problem are derived. The optimality is meant as achieving at the same time a desired trade off between the sensor capital and maintenance costs and resulting robust estimation accuracy of the monitoring algorithm...
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Detection of the Oocyte Orientation for the ICSI Method Automation
PublicationAutomation or even computer assistance of the popular infertility treatment method: ICSI (Intracytoplasmic Sperm Injection) would speed up the whole process and improve the control of the results. This paper introduces a preliminary research for automatic spermatozoon injection into the oocyte cytoplasm. Here, the method for detection a correct orientation of the polar body of the oocyte is presented. Proposed method uses deep...
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Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer
PublicationIn this study, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting (LightGBM) algorithms were used to model-predict the drying characteristics of banana slices with an indirect solar drier. The relationships between independent variables (temperature, moisture, product type, water flow rate, and mass of product) and dependent variables (energy consumption and size reduction) were established. For energy consumption,...
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Properties of Nasicon-based CO2 sensor with Bi8Nb2O17 reference electrode
PublicationGas sensors are useful for the carbon dioxide concentration monitoring in many applications. The major challenge is to develop a potentiometric sensor working without the necessity of a reference gas and without a need of the reference electrode encapsulation. Important issue is a selection of reference electrode material, which should provide stable reference potential. For example as reference electrode material in sensor based...
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Adaptive Wavelet-Based Correction of Non-Anechoic Antenna Measurements
PublicationNon-anechoic measurements represent an affordable alternative to evaluation of antenna performance in expensive, dedicated facilities. Due to interferences and noise from external sources of EM radiation, far-field results obtained in non-ideal conditions require additional post-processing. Conventional correction algorithms rely on manual tuning of parameters, which make them unsuitable for reliable testing of prototypes. In this...
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Modelling in machine design (PG_00057377)
e-Learning Coursesgoal of the subject is to show how simple enginnering models reflect the reality and how contemporary FEM calulations can illustrate the operation of machine elements
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublicationControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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Knowledge sharing and knowledge hiding in light of the mistakes acceptance component of learning culture- knowledge culture and human capital implications
PublicationPurpose: This study examines the micromechanisms of how knowledge culture fosters human capital development. Method: An empirical model was developed using the structural equation modeling method (SEM) based on a sample of 321 Polish knowledge workers employed in different industries. Findings: This study provides direct empirical evidence that tacit knowledge sharing supports human capital, whereas tacit knowledge hiding does...
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Efficiency of pollutant removal by five multistage constructed wetlands in a temperate climate
PublicationIn recent years, an increase in interest in hybrid constructed wetland systems (HCWs) has beenobserved. These systems are composed of two or more filters with different modes of sewage flow.Based on over eight years of monitoring, carried out at five local HCWs located in the PomeraniaRegion of Northern Poland, the effective removal of organic matter (from 74.9 to 95.5% COD) in theloading range 1.5-17.0 g COD·m-2·d-1 was confirmed....
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The impact of the AC922 Architecture on Performance of Deep Neural Network Training
PublicationPractical deep learning applications require more and more computing power. New computing architectures emerge, specifically designed for the artificial intelligence applications, including the IBM Power System AC922. In this paper we confront an AC922 (8335-GTG) server equipped with 4 NVIDIA Volta V100 GPUs with selected deep neural network training applications, including four convolutional and one recurrent model. We report...
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Consumerism and the Quality of Life
PublicationHigh level of consumption, driven by marketing activities, the pleasure and joy of possession and the accumulation of material goods are often associated with prosperity, sense of happiness and fulfilment in life. On a broader scale, economic indicators related to production and consumption are used to define the well-being and quality of life in societies. Unfortunately, the phenomenon of consumerism entails negative social and...
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Progressing Pollutant Elution from Snowpack and Evolution of its Physicochemical Properties During Melting Period— a Case Study From the Sudetes, Poland
PublicationMain aim of the work assumed recognition of physicochemical changes in snowpack occurring during the melting period. Properties of snow cover had been identified at two sites in Western Sudetes mountains (860 and 1228 m asl) in SW Poland since the end of January, and monitored until the disappearance of snow in late Spring. Snow pit measurements and sample collection at both sites were made followed by chemical analyses with the...
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Autoencoder application for anomaly detection in power consumption of lighting systems
PublicationDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...
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MANAGING LEARNING PROCESS WITH E-LEARNING TOOL
PublicationThis article presents one possibility to employ Moodle, the free e-Leaning platform, to organize learning understood as a process. Behavioral approach and application to massive courses are assumed. A case study is presented, where the introduction of Moodle resulted in better student performance in homework
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A calibration model for gas sensor array in varying environmental conditions
PublicationAbstract: Gas-analyzing systems based on gas sensors, commonly referred to as electronic noses, are the systems which enable the recognition of volatile compounds in their working environment and provide the on-line results of analysis. The most commonly used type of sensors in such systems is semiconductor gas sensors. They are considered to be the most reliable in the long-term applications (more than 1 year), however,...
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A calibration model for gas sensor array in varying environmental conditions
PublicationAbstract: Gas-analyzing systems based on gas sensors, commonly referred to as electronic noses, are the systems which enable the recognition of volatile compounds in their working environment and provide the on-line results of analysis. The most commonly used type of sensors in such systems is semiconductor gas sensors. They are considered to be the most reliable in the long-term applications (more than 1 year), however,...