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Search results for: deep learning renewable energy sources photovoltaics buildings long short-term memory micro-grids
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Alternative sources of energy from agricultural biomass - an European perspective
PublicationNośniki energii pochodzące z rolnictwa dzielą się na nośniki pierwotne oraz nośniki wtórne. Nośniki pierwotne to drewno, słoma oraz osady ściekowe (analogiczne do torfu niskiego). Nośniki wtórne to biogaz, bioetanol, biodiesel, biowodór oraz gaz pirolityczny. Omawia się zasoby energetyczne biomasy w Unii Europejskiej.
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Modified sliding mode control for seamless integration of P.V. energy in A.C. grid
PublicationSolar energy is a potentially abundant and reliable source of renewable energy. While it can undoubtedly increase grid reliability and efficiency, the inverted voltage generated from PV. sources may introduce distortion into the AC. grid. The proposed control mechanism, modified sliding mode control (MSMC), can seamlessly integrate the inverter output generated by obtaining DC. voltage from the boost converter linked with the PV....
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Mean annual and seasonal circulation patterns and long-term variability of currents in the Baltic Sea
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Transmission system model in the track-vehicle relationship based on Long Term Evolution technology
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Stochastic Integration and Long Term Predictor Estimation under Noisy Conditions for Speech Enhancement
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Proof-of-concept study on improved efficacy of rHuEPO administered as a long-term infusion in rats
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A potency of plasminogen activation system in long-term prognosis of endometrial cancer: a pilot study
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Efficient long-term conservation of Taraxacum pieninicum synthetic seeds in slow growth conditions
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Studies on the behaviour of titanium activation foils during long-term exposure at the JET tokamak
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Evaluation of Whole-Cell and Acellular Pertussis Vaccines in the Context of Long-Term Herd Immunity
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Cleaning of Ultrafiltration Membranes: Long-Term Treatment of Car Wash Wastewater as a Case Study
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Evaluation of a short-term group psychotherapy used as part of the rehabilitation process in nursing home patients
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Short-Term Effects of Intra-Articular Hyaluronic Acid Administration in Patients with Temporomandibular Joint Disorders
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The effects of short-term group psychodynamic psychotherapy on the personality traits of patients treated in a daily ward
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Large scale complementary solar and wind energy sources coupled with pumped-storage hydroelectricity for Lower Silesia (Poland)
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Towards an Understanding of the Stability Assessment of Floating Buildings
PublicationOne of the most important aspects of the design of floating facilities such as ships, floating offshore structures or floating houses is stability. Its impact on both general safety and operational aspects renders it a fundamental consideration already in preliminary design stages. Usually, the concept of sufficient stability of floating buildings is associated with the ability to keep an allowed heel angle and residual freeboard,...
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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublicationAs the demand for cloud computing services increases, optimizing resource allocation and energy consumption has become a key factor in achieving sustainability in cloud environments. This paper presents a novel approach to address these challenges through an optimized virtual machine (VM) migration strategy that employs a game-theoretic approach based on particle swarm optimization (PSO) (PSO-GTA). The proposed approach leverages...
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Contemporary Spaces of Memory - Towards Transdisciplinarity in Architecture
PublicationThe paper explores new phenomena in the contemporary practice of commemoration implemented through architecture. Architectural objects related to memory can be a place where new trends and phenomena appear earlier than in other architectural objects. The text is an attempt to prove that these new spaces of memory are a kind of laboratory where new ideas taking place in architecture and related disciplines are being tested. Research...
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Deep learning approach for delamination identification using animation of Lamb waves
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Deep learning super-resolution for the reconstruction of full wavefield of Lamb waves
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OmicSelector: automatic feature selection and deep learning modeling for omic experiments
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublicationObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
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Autonomous pick-and-place system based on multiple 3Dsensors and deep learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Deep learning approach on surface EEG based Brain Computer Interface
PublicationIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Deep Learning-Based Cellular Nuclei Segmentation Using Transformer Model
PublicationAccurate segmentation of cellular nuclei is imperative for various biological and medical applications, such as cancer diagnosis and drug discovery. Histopathology, a discipline employing microscopic examination of bodily tissues, serves as a cornerstone for cancer diagnosis. Nonetheless, the conventional histopathological diagnosis process is frequently marred by time constraints and potential inaccuracies. Consequently, there...
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Using deep learning to increase accuracy of gaze controlled prosthetic arm
PublicationThis paper presents how neural networks can be utilized to improve the accuracy of reach and grab functionality of hybrid prosthetic arm with eye tracing interface. The LSTM based Autoencoder was introduced to overcome the problem of lack of accuracy of the gaze tracking modality in this hybrid interface. The gaze based interaction strongly depends on the eye tracking hardware. In this paper it was presented how the overall the...
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Alternative Approach to Convolution Term of Viscoelasticity in Equations of Unsteady Pipe Flow
PublicationIn the paper the selected aspects concerning description of viscoelastic behavior of pipe walls during unsteady flow are analyzed. The alternative convolution expression of the viscoelastic term is presented and compared with the corresponding term referring to unsteady friction. Both approaches indicate similarities in the forms of impulse response functions and the parameter properties. The flow memory was introduced into convolution...
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Investigating BiMeVOx compounds as potential photoelectrochemical and electrochemical materials for renewable hydrogen production
PublicationIn this study, BiMeVOx compounds (where Me: Co, Mo, Ce, Zr) were synthesized and characterized as potential photoelectrochemical materials for solar water splitting, the hydrogen evolution reaction (HER), and oxygen evolution reaction (OER). The analysis confirmed the successful formation of phase BiMeVOx compounds with the desired crystal structure. Among the tested materials, BiCoVOx(800) showed the highest photocurrent density...
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Biomass as a reliable renewable energy source in the fulfilling the white paper poland-eu requirements
PublicationZgodnie z wytycznymi z Białej Księgi Unii Europejskiej, wzrost wykorzystania odnawialnych źródeł energii powinien osiągnąć 7,5% w 2010 r. i 14% w 2020 r. o ogólnym zużyciu energii w Polsce. Analizę sytuacji energetycznej Polska w przeszłości i przewidywania zmian globalnych i regionalnych w odniesieniu do produkcji i zużycia energii, prowadzą do wniosku, że biomasa może być możliwym źródłem energii odnawialnej dla realizacji tych...
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POLAND’S ENERGY DEPENDENCE AT THE TURN OF THE 21ST CENTURY
PublicationThe following article is an attempt to assess Poland's energy independence in the years 1993-2020. The main aim of the paper is to present Poland's dependence on raw materials from foreign partners - in the field of imports of electricity, natural gas, crude oil, non-renewable energy resources, i.e., hard coal and lignite, and the country's dynamics in the amount of imports. In addition, the aim of the work is to answer research...
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Evaluation of long‑term immunity and protection against T. gondii after immunization with multivalent recombinant chimeric T. gondii proteins
PublicationToxoplasmosis caused by the opportunistic, cosmopolitan protozoan Toxoplasma gondii is one of the most common parasitoses in the world. Although it may prove dangerous or even fatal for immunocompromised individuals, immunoprophylaxis for humans is still nonexistent. Thus, the aim of the current work was to assess the ability of two immunogenic recombinant chimeric T. gondii proteins, SAG2-GRA1-ROP1 (SGR) and SAG1-MIC1-MAG1-GRA2...
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MEMORY EFFECT ANALYSIS USING PIECEWISE CUBIC B-SPLINE OF TIME FRACTIONAL DIFFUSION EQUATION
PublicationThe purpose of this work is to study the memory effect analysis of Caputo–Fabrizio time fractional diffusion equation by means of cubic B-spline functions. The Caputo–Fabrizio interpretation of fractional derivative involves a non-singular kernel that permits to describe some class of material heterogeneities and the effect of memory more effectively. The proposed numerical technique relies on finite difference approach and cubic...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublicationThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Short-Term Blood Flow Restriction Increases Power Output and Bar Velocity During the Bench Press
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Minimum mean square error estimation of speech short-term predictor parameters under noisy conditions
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Short-term changes in thickness and temperature of the active layer in summer in the Kaffiøyra region, NW Spitsbergen, Svalbard
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Spatial Variation in Long-Term Trends in a Metapopulation of the Globally Threatened Aquatic WarblerAcrocephalus paludicolain Poland
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Long-term efficacy of 90Y-DOTATATE in patients with nonresectable pancreatic and small bowel neuroendocrine neoplasms
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An integrated assessment of the long-term impact of municipal sewage sludge on the chemical and biological properties of soil
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Long-term effect of ZnO and CuO nanoparticles on soil microbial community in different types of soil
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Long-term operating conditions for different sorption materials to capture phosphate from domestic wastewater
PublicationThis paper presents the results of a study on the possibility of applying various configured filters filled with a mixture of Rockfos® and Leca® material for the effective capture of phosphate from domestic wastewater. The tests were carried out for two years at two wastewater flow rates (20 and 40 L/day) in three pairs of filtration columns with a volume of filter material equal to 20 liters each. Columns 1A and 1B were filled...
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Fluorescent Submicron-Sized Poly(heptafluoro-n-butyl methacrylate) Particles with Long-Term Stability
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Fasting Hyperglycemia and Long-term Outcome in Patients with Acute Ischemic Stroke Treated with Mechanical Thrombectomy
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Effect of long-term cold storage on physicochemical attributes and bioactive components of kiwi fruit cultivars
PublicationVarious kiwi fruit cultivars, bred in Korea, were kept in cold storage for 8–24 weeks for possible increase of their quality. Firmness significantly decreased at initial time in all cultivars.The rate of softeningwas the slowest in “Hayward”, followed by “Hort16A”, “Haenam”, “Daheung”, “Bidan”, “Hwamei”, and “SKK 12”. Sensory value increased with decreasing of firmness. Soluble solids content increased with storage time while acidity gradually...
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Low-Cost and Highly-Accurate Behavioral Modeling of Antenna Structures by Means of Knowledge-Based Domain-Constrained Deep Learning Surrogates
PublicationThe awareness and practical benefits of behavioral modeling methods have been steadily growing in the antenna engineering community over the last decade or so. Undoubtedly, the most important advantage thereof is a possibility of a dramatic reduction of computational expenses associated with computer-aided design procedures, especially those relying on full-wave electromagnetic (EM) simulations. In particular, the employment of...
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublicationThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublicationThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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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 Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublicationWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...