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wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: DEEP LEARNING RENEWABLE ENERGY SOURCES PHOTOVOLTAICS BUILDINGS LONG SHORT-TERM MEMORY MICRO-GRIDS
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Deep learning based thermal image segmentation for laboratory animals tracking
PublikacjaAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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Modelling Long‐Term Transition from Coal‐Reliant to Low‐Emission Power Grid and District Heating Systems in Poland
PublikacjaEnergy systems require technological changes towards climate neutrality. In Poland, where the power system is dominated by outdated coal-fired power plants, efforts to minimize the environmental impact are associated with high costs. Therefore, optimal paths for the development of the energy sector should be sought in order to achieve ambitious long-term strategic goals, while minimizing the negative impact on the consumers’ home...
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Latest Insights on Novel Deep Eutectic Solvents (DES) for Sustainable Extraction of Phenolic Compounds from Natural Sources
PublikacjaPhenolic compounds have long been of great importance in the pharmaceutical, food, and cosmetic industries. Unfortunately, conventional extraction procedures have a high cost and are time consuming, and the solvents used can represent a safety risk for operators, consumers, and the environment. Deep eutectic solvents (DESs) are green alternatives for extraction processes, given their low or non-toxicity, biodegradability, and reusability....
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Selected Artificial Intelligence Methods in the Risk Analysis of Damage to Masonry Buildings Subject to Long-Term Underground Mining Exploitation
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Energy Transition in Poland—Assessment of the Renewable Energy Sector
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Reducing Air Pollutant Emissions from the Residential Sector by Switching to Alternative Energy Sources in Single-Family Homes
PublikacjaThe paper discusses a scenario for adapting residential buildings to the requirements of the EU climate and energy package. It analyzes the option of reducing pollutant emissions to ambient air by switching to alternative energy sources in a typical single-family residential building. The most common sources of energy in central heating and ventilation systems and water heating systems were compared, and the analyzed energy carriers...
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublikacjaIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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Long-term outcomes of stapled hemorrhoidopexy
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High Energy Quality of Buildings 2022/23
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High Energy Quality of Buildings 2023/24
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High Energy Quality of Buildings 2024/25
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NEUROBIOLOGY OF LEARNING AND MEMORY
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Journal of Long-Term Effects of Medical Implants
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublikacjaIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Entropic Measures of Complexity of Short-Term Dynamics of Nocturnal Heartbeats in an Aging Population
PublikacjaTwo entropy-based approaches are investigated to study patterns describing differences in time intervals between consecutive heartbeats. The first method explores matrices arising from networks of transitions constructed following events represented by a time series. The second method considers distributions of ordinal patterns of length three, whereby patterns with repeated values are counted as different patterns. Both methods provide...
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NEW ORGANIC MATERIALS FOR PHOTOVOLTAICS
PublikacjaThis report presents the results of investigations carried out for polymer- and low-weightmolecular materials prepared in the form of thin films by various methods, namely the thermalvacuum evaporation and chemical vapour deposition. The influence of the technologicalconditions on the structure, surface morphology, and electronic properties of selected organic thinfilms, including polyazomethines, phthalocyanines, and perylene...
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Micro- and nanodosimetry
Kursy OnlineMicro- and nanodosimetry (Mikro- i nanodozymetria) dla studentów studiów II stopnia WFTIMS
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ENERGY
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Sustainable Energy Grids & Networks
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Smart Grids and Sustainable Energy
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Boundary conditions for non-residential buildings from the user’s perspective: literature review
PublikacjaBackground and objective: This paper aims to review the boundary conditions (B/C) in specific categories (energy, building use, and lighting) within non-residential buildings to pave the way to a better understanding of users’ requirements and needs of the built environment. For this paper, B/C are understood as unique preconditions, specific characteristics for use, determining specific features of buildings, enabling an accurate...
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Low-power device simulator for micro-energy measurement methods testing
PublikacjaThe paper presents low-power device simulator designed for testing of micro-energy measurement methods. Such kind methods can be used for evaluation of power systems based on Energy Harvesting. The device allows to set the current consumption characteristic over the time, thus making possible playing the role of different types of low-power devices e.g. simulating sensor network node.
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublikacjaThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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Effect of long term service at elevated temperatures on mechanical properties of Manaurite XM reformer tubes
PublikacjaMicrostructure transformations occur in the Manaurite XM cast steel tubes during long-term operation in the reformer furnace were revealed and described. The rela tionship between mechanical properties, an increase of internal diameter of the tube and microstructure degradation is discussed. Static tensile test was performed on two types of samples with different shapes. It has been shown differences in the results of tests...
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Deep learning for recommending subscription-limited documents
PublikacjaDocuments recommendation for a commercial, subscription-based online platform is important due to the difficulty in navigation through a large volume and diversity of content available to clients. However, this is also a challenging task due to the number of new documents added every day and decreasing relevance of older contents. To solve this problem, we propose deep neural network architecture that combines autoencoder with...
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Renewable Energy Focus
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Synergistic Effects of Bitumen Plasticization and Microwave Treatment on Short-Term Devulcanization of Ground Tire Rubber
PublikacjaGround tire rubber (GTR) was mechano-chemically modified with road bitumen 160/220 and subsequently treated using a microwave radiation. The combined impact of bitumen 160/220 content and microwave treatment on short-term devulcanization of GTR was studied by thermal camera, wavelength dispersive X-ray fluorescence spectrometry (WD-XRF), static headspace, and gas chromatography-mass spectrometry (SHS-GC-MS), thermogravimetric analysis...
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The effect of long-term service at elevated temperatures on structure and mechanical properties of Cr-Mo-V steel
PublikacjaPurpose: of this paper is to reveal the microstructural changes in 13HMF steel exposed to long-term service at elevated temperatures. The degradation of bainite structure was determined and carbides morphology has been examined. The influence of carbides evolution was discussed in dependence of creep rupture strength and mechanical properties of the steel.
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Application of MARKAL model to optimisation of electricity generation structure in Poland in the long-term time horizon Part I - concept of the model
PublikacjaIn this paper, which inaugurates a series of papers on this subject, a concept is proposed of a power system development model with regard to the technological structure of electricity generation in Poland, in the long-term time perspective – until 2060. The model is based on the mathematical structure of the MARKAL optimization package. The paper presents a brief description of the tool used in the model research. In addition,...
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Bimodal deep learning model for subjectively enhanced emotion classification in films
PublikacjaThis research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio-video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented....
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublikacjaTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublikacjaData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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Deep Learning Approaches in Histopathology
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Pathological brain network activity: memory impairment in epilepsy
PublikacjaOur thinking, memory and cognition in general, relies upon precisely timed interactions among neurons forming brain networks that support cognitive processes. The surgical evaluation of drug-resistant epilepsy using intracranial electrodes provides a unique opportunity to record directly from human brain and to investigate the coordinated activity of cognitive networks. In this issue of Neurology®, Kleen and colleagues1 implicate...
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Energy roadmaps for the city of Gdańsk
PublikacjaThe paper presents energy roadmaps for Gdansk in three time perspectives: short-term (the year 2012), medium-term (2020) and long-term (2050). The paper is a result of the research carried out under the PATH-TO-RES project, supported by European Commission programme SAVE Altener Intelligent Energy Europe.
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Rafał Leszczyna dr hab. inż.
OsobyDr hab. inż. Rafał Leszczyna jest profesorem uczelni na Wydziale Zarządzania i Ekonomii Politechniki Gdańskiej. W lipcu 2020 r., na podstawie osiągnięcia naukowego w obszarze zarządzania cyberbezpieczeństwem infrastruktur krytycznych w sektorze elektroenergetycznym, uzyskał stopień doktora habilitowanego w dziedzinie nauk inżynieryjno-technicznych, dyscyplina informatyka techniczna i telekomunikacja. W latach 2004–2008 pracował...
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Decision support system for design of long distance heat transportation system
PublikacjaDistrict Heating (DH) systems are commonly supplied using local heat sources. Nowadays, modern insulation materials allow for effective and economically viable heat transportation over long distances (over 20 km). The paper proposes a Decision Support System (DSS) for optimized selection of design and operating parameters of a long distance Heat Transportation System (HTS). The method allows for evaluation of feasibility and effectiveness...
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LOS and NLOS identification in real indoor environment using deep learning approach
PublikacjaVisibility conditions between antennas, i.e. Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) can be crucial in the context of indoor localization, for which detecting the NLOS condition and further correcting constant position estimation errors or allocating resources can reduce the negative influence of multipath propagation on wireless communication and positioning. In this paper a deep learning (DL) model to classify LOS/NLOS...
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Long-term Hindcast Simulation of Currents, Sea Level, Water Temperature and Salinity in the Baltic Sea
PublikacjaThis dataset contains the results of numerical modelling of currents, sea level, water temperature and salinity over a period of 50 years (1958–2007) in the Baltic Sea. A long-term hindcast simulation was performed using a three-dimensional hydrodynamic model (PM3D) based on the Princeton Ocean Model (POM). The spatial resolution was 3 nautical miles, i.e. about 5.5 km. Currents, water temperature, and salinity were recorded...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublikacjaComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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Deep learning-based waste detection in natural and urban environments
PublikacjaWaste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems are addressed in this article by...
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Long-Term Vegetarian Diet and Iron Deficiency
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The long-term studies of osmotic membrane distillation
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Long-term performance of membrane distillation process
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Examples of Taxation on Real Estate Properties as an Long-term Investment Asset. Description of Situation in Selected European Countries
PublikacjaReal estate properties have become the alternative asset for long-term savings and investments. Such investment however is strictly related to risk inter alia taxation policy. The following article describes and discusses both theoretical and practical aspects of long-term investment taxation imposed on real estate market in selected European countries. The article presents the analyses of the taxes including its functions, mechanisms...
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Reality of short-term causality of Islamic and conventional banking term deposit rates in Pakistan
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Classifying Emotions in Film Music - A Deep Learning Approach
PublikacjaThe paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...
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Analysis of electricity generation variability in 2019 with special consideration of electrical energy generation from wind sources.
PublikacjaThis article presents issues related to the broadly understood development of wind energy. The state of the art of wind energy in the world has been discussed. This paper also shows issues related to factors affecting the development of renewable energy sources and their impact on the natural environment on the basis of available research. The focus is, however, on the critical analysis of phenomena in the data of the Transmission...
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Financial determinants of corporate reputation: A short-term approach
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Asymmetric features of short-term blood pressure variability
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