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Search results for: AIR QUALITY, POLLUTANT DETECTION, NITROGEN DIOXIDE, SENSOR CORRECTION, MACHINE LEARNING, ARTIFICIAL NEURAL NETWORKS
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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Throughput vs. Resilience in Multi-hop Wireless Sensor Networks with Periodic Packet Traffic
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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Traffic Remapping Attacks in Ad Hoc Networks
PublicationAd hoc networks rely on the mutual cooperation of stations. As such, they are susceptible to selfish attacks that abuse network mechanisms. Class-based QoS provisioning mechanisms, such as the EDCA function of IEEE 802.11, are particularly prone to traffic remapping attacks, which may bring an attacker better QoS without exposing it to easy detection. Such attacks have been studied in wireless LANs, whereas their impact in multihop...
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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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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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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,...
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Application of Feed Forward Neural Networks for Modeling of Heat Transfer Coefficient During Flow Condensation for Low and High Values of Saturation Temperatur
PublicationMost of the literature models for condensation heat transfer prediction are based on specific experimental parameters and are not general in nature for applications to fluids and non-experimental thermodynamic conditions. Nearly all correlations are created to predict data in normal HVAC conditions below 40°C. High temperature heat pumps operate at much higher parameters. This paper aims to create a general model for the calculation...
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Damage detection in plates based on Lamb wavefront shape reconstruction
PublicationMany of the current studies in the area of damage detection using elastic wave propagation are based on deploying sensor networks with a large number of piezoelectric transducers to detect small-size cracks. A major limitation of these studies is that cracks are usually larger and have different shapes in real cases. Moreover, using a large number of sensing nodes for damage detection is both costly and computationally intensive....
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Exploiting multi-interface networks: Connectivity and Cheapest Paths
PublicationLet G = (V,E) be a graph which models a set of wireless devices (nodes V) that can communicate by means of multiple radio interfaces, according to proximity and common interfaces (edges E). The problem of switching on (activating) the minimum cost set of interfaces at the nodes in order to guarantee the coverage of G was recently studied. A connection is covered (activated) when the endpoints of the corresponding edge share at...
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Pollutant deposition via dew in urban and rural environment, Cracow, Poland
PublicationThis study is a comparative analysis of dew in rural and urban environment. Dew samples were collected between May and October, 2009 in two reference stations in southern Poland: Cracow and Gaik-Brzezowa. The investigation included comparison of volume and chemistry of the collected samples. Due to its formation mechanisms, dew is a good indicator of air pollution. Following parameters were analyzed in 159 collected samples: pH,...
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Effect of transregional transport of pollutants on atmospheric air quality in the Tricity area of Poland
PublicationDwuwymiarowa analiza wariancji wyników oznaczania jonów nieorganicznych, pH oraz przewodnictwa konduktometrycznego w próbkach wód opadowych zebranych w rejonie Trójmiasta pokazała, że transregionalny transport substancji zanieczyszczających środowisko ma wpływ na jakość powietrza w tym rejonie. W całym Trójmieście wahania stężeń analitów w wodach opadowych nie są spowodowane w znacznym stopniu przez lokalizacje miejsc pobierania...
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Association between changes in air quality and hospital admissions during the holi festival
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Numerical investigations of effect of indoor air quality on thermal comfort in residential buildings.
PublicationArtykuł przedstawia wyniki numeryczne MES odnośnie wpływu koncentracji CO2 w lokalnej strefie powietrza w budynkach mieszkalnych naturalnie wentylowanych na zachowanie mieszkańców. Obliczenia wykonano w 2 wymiarach. Zbadano wpływ położenia mieszkańców i prędkości wchodzącego powietrza.
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Nitrogen conversion during treatment of various type of wastewater in multistage treatment wetlands
PublicationThe objective of this investigation was to recognize nitrogen speciation during wastewater treatment in three multistage TWs (MTWs), which are assuming more a most effective in nitrogen removal than single stage TWs. Carried out investigations and analysis enable for determination of conditions, relationships and processes responsible for nitrogen conversions in subsequent stages of MTWs. In treated wastewater and reject water...
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Suppression of distortions in signals received from Doppler sensor for vehicle speed measurement
PublicationDoppler sensors are commonly used for movement detection and speed measurement. However, electromagnetic interference and imperfections in sensor construction result in degradation of the signal to noise ratio. As a result, detection of signals reflected from moving objects becomes problematic. The paper proposes an algorithm for reduction of distortions and noise in the signal received from a simple, dual-channel type of a Doppler...
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Prototype of electrochemical sensor for measurements of volatile organic compounds in gases
PublicationThe paper presents a laboratory prototype of an electrochemical sensor for measurements of volatile organic compounds (VOCs) in gases, utilizing ionic liquids and commercial screen printed electrodes by DropSens. The following ionic liquids have been tested as the electrolyte and redox reaction environment: 1-butyl, 3-methylimidazolium dicyanoamide ([BMIM][N(CN)2]), 1-octyl, 3-methylimidazolium tetrafluoroborate ([OMIM][BF4]),...
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Chapter 8 – Active Sampling of Air
PublicationThis chapter reviews the literature information on analytical techniques and laboratory equipment used for active sampling of air (atmospheric and indoor) in regular monitoring research. It describes popular analytical devices applied for sample collection using various types of polymeric bags, e.g. Tedlar bags, Teflon or Nafion bags, and/or stainless steel vacuum containers. It reviews literature data about the application of...