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Search results for: deep learning renewable energy sources photovoltaics buildings long short-term memory micro-grids
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Single-Phase 15-Level Switched-Capacitor Boost Multilevel Inverter Topology for Renewable Energy Applications
PublicationGalvanic isolation is a vital part of a grid-connected solar PV system. With the growth of multilevel inverters for grid-connected applications, the multilevel inverters having isolation are not sufficiently discussed in the literature. In this paper, a 15-level isolated multilevel inverter topology requiring only thirteen switches is proposed. The envisaged configuration includes two cells, designated as upper and lower cells....
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Impact of Investments and R&D Costs in Renewable Energy Technologies on Companies’ Profitability Indicators: Assessment and Forecast
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Pupil size reflects successful encoding and recall of memory in humans
PublicationPupil responses are known to indicate brain processes involved in perception, attention and decision-making. They can provide an accessible biomarker of human memory performance and cognitive states in general. Here we investigated changes in the pupil size during encoding and recall of word lists. Consistent patterns in the pupil response were found across and within distinct phases of the free recall task. The pupil was most...
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Recuperator with microjet technology as a proposal for heat recovery from low-temperature sources
PublicationA tendency to increase the importance of so called dispersed generation, based on the local energy sources and the working systems uti- lizing both the fossil fuels and the renewable energy resources is observed nowadays. Generation of electricity on industrial or domestic scale together with production of heat can be obtained for example through employment of the ORC systems. It is mentioned in the EU directive 2012/27/EU for...
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Assessing the attractiveness of human face based on machine learning
PublicationThe 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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Heat Transfer of the Multicolor-Laser-Sources-Irradiated Nanoparticles in Reference to Thermal Processes
PublicationUnlike the standard materials, metallic nanoparticles offer enhancing the heat convertion rate which implies the maximum and average temperature boost significantly in the considered system. The work’s purpose is to examine heat transfer in the metallic nanoparticles which have been deposited on a glassy substrate, enabling the nanostructures thermoablation. Furthermore, the functionalized substrate is irradiated with multicolor-laser-sources,...
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Modernization of historic healthcare buildings
PublicationThe practice of transforming and adapting the existing healthcare facilities to meet the growing demands of modern medicine applies not only to buildings of historical value. Of course, one can set a time point from which hospitals, erected mostly with industrialized technologies, undergo upgrades for better or worse effect. Existing healthcare buildings or facilities, including historic ones, have to be refurbished and adapted...
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Nonradiative long range energy transfer in donor-acceptor systems with excluded volume
PublicationW pracy analizowano bezpromienisty długozasięgowy transfer energii w układach donor-akceptor z uwzględnieniem objętości wyłączonej. Stwierdzono, że zanik fluorescencji pierwotnie wzbudzonych donorów jest wolniejszy, jeżeli uwzględnia się objętość wyłączoną. Ten efekt jest znacznie wzmocniony, gdy akceptory znajdują się w pewnej objętości niedostępnej dla donorów. Analizę numeryczną przeprowadzono stosując metodę symulacji Monte...
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Hotspot of human verbal memory encoding in the left anterior prefrontal cortex
PublicationBackground: Treating memory and cognitive deficits requires knowledge about anatomical sites and neural activities to be targeted with particular therapies. Emerging technologies for local brain stimulation offer attractive therapeutic options but need to be applied to target specific neural activities, at distinct times, and in specific brain regions that are critical for memory formation. Methods: The areas that are critical...
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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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Electrical Stimulation Modulates High Gamma Activity and Human Memory Performance
PublicationDirect electrical stimulation of the brain has emerged as a powerful treatment for multiple neurological diseases, and as a potential technique to enhance human cognition. Despite its application in a range of brain disorders, it remains unclear how stimulation of discrete brain areas affects memory performance and the underlying electrophysiological activities. Here, we investigated the effect of direct electrical stimulation...
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Magnetic Field Generated by Short Circuit Current in the 110 kV Power System
PublicationElectric fields within tissues induced by magnetic fields including transients or short-term peaks should not be time averaged and be regarded as instantaneous values as established in the ICNIRP (International Commission on Non - Ionizing Radiation Protection) guidelines. Measurements of power lines magnetic fields with regard to human beings exposure are carried out typically with maximum current load at current balance condition...
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The Impact of Forms of Buildings on the Air Exchange in Their Environment. Based on the Example of Urban Development in Warsaw
PublicationPossibilities for energy-efficient, natural ventilation of buildings in an urban environment depend on the airflow around them. This chapter deals with the issue of dependence of air exchange in urban spaces on the building forms used in them and on relative position of these buildings. The authors focused on the problem of air stagnation in dense urban development. This phenomenon increases the energy demand of buildings. The...
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Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublicationIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
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The literature review on boundary conditions of use for non-residential buildings
PublicationThis paper describes the results of qualitative and quantitative literature reviews on boundary conditions within educational buildings, emphasising the users' perspective. The reviews were performed before and during the COVID-19 pandemic using Scopus, Taylor& Francis, Web of Science databases. The boundary conditions understood as special characteristics for use and or precondition, determining specific features of buildings...
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Deep Eutectic Solvents and Their Uses for Air Purification
PublicationChemical compounds released into the air by the activities of industrial plants and emitted from many other sources, including in households (paints, waxes, cosmetics, disinfectants, plastic (PVC) flooring), may affect the environment and human health. Thus, air purification is an important issue in the context of caring for the condition of the environment. Deep eutectic solvents (DESs) as liquids with environmentally friendly...
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Deep eutectic solvents – Ideal solution for clean air or hidden danger?
PublicationThe industrial sector is one of the fastest-growing sources of greenhouse gases, due to its excessive energy consumption to meet the rapidly growing demand for energy-intensive products. The use of deep eutectic solvents (DESs) has been studied extensively in order to cope with these harmful gases, but their usage can be an issue in respect to ecological reasons. Do deep eutectic solvents harm the atmosphere? Yes, these solvents...
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Short‐term outcome following concurrent surgical treatment of ureteral ectopia and intrapelvic urinary bladder in nine neutered bitches
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Electromagnetic Simulations with 3D FEM and Intel Optane Persistent Memory
PublicationAbstract—Intel Optane persistent memory has the potential to induce a change in how high-performance calculations requiring a large system memory capacity are conducted. This article presents what this change may look like in the case of factorization of large sparse matrices describing electromagnetic problems arising in the 3D FEM analysis of passive highfrequency components. In numerical tests, the Intel oneAPI MKL PARDISO was...
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Use of Modified Cuckoo Search algorithm in the design process of integrated power systems for modern and energy self-sufficient farms
PublicationIn the face of increasingly stringent pollutant emission regulations, designing an agricultural holding becomes a difficult challenge of connecting a large number of coefficients that describe an energy system of a farm in regard to its ecological and economic efficiency. One way to cope with this issue is to design an energy self-sufficient farm that integrates various technologies, including renewable energy. However, the selection...
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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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On time-dependent nonlinear dynamic response of micro-elastic solids
PublicationA new approach to the mechanical response of micro-mechanic problems is presented using the modified couple stress theory. This model captured micro-turns due to micro-particles' rotations which could be essential for microstructural materials and/or at small scales. In a micro media based on the small rotations, sub-particles can also turn except the whole domain rotation. However, this framework is competent for a static medium....
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The Effects of Cellular Membrane Damage on the Long-Term Storage and Adhesion of Probiotic Bacteria in Caco-2 Cell Line
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Long-term follow-up of MCL patients treated with single-agent ibrutinib: updated safety and efficacy results
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Radioimmunotherapy Confers Long-Term Survival to Lymphoma Patients with Acceptable Toxicity: Registry Analysis by the International Radioimmunotherapy Network
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Matrix metalloproteinase 9 (MMP-9) is indispensable for long term potentiation in the central and basal but not in the lateral nucleus of the amygdala
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Long-term exposure to urban air pollution and the relationship with life expectancy in cohort of 3.5 million people in Silesia
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The metagenomic approach to characterization of the microbial community shift during the long-term cultivation of anammox-enriched granular sludge
PublicationA metagenomic approach was used to investigate how the microbial community composition changes when an anammox-based granular sludge reactor is seeded with nitritation-anammox biomass from a wastewater treatment plant. In the seed sample, the abundance of Candidatus Kuenenia stuttgartiensis was similar to Candidatus Jettenia caeni (12.63 vs. 11.68%). This biomass was typical in terms of microbial nitrogen conversion; both ammonia...
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Genes regulating biochemical pathways of oxygen metabolism in porcine oviductal epithelial cells during long-term IVC
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Variability in gelatinase expression in the walls of vessels used as aortocoronary conduits may impact long-term graft patency
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The pharmacokinetics of dexmedetomidine during long-term infusion in critically ill pediatric patients. A Bayesian approach with informative priors
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Cytokeratin 8 in venous grafts: A factor of unfavorable long-term prognosis in coronary artery bypass grafting patients
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Remote Sensing Methods In the Study of the Impact of Long-Term Process of Sulphur Mining on Environmental Changes of the Carpathian Foreland
PublicationThe paper presents research on the extent of impact of sulphur mining process and post-mining activities upon properties of selected elements of the environment, as well as the assessment of the influence of indirect effects resulting from many years' process of exploitation of sulphur deposits in the areas of the Carpathian Foreland (south-east Poland). Within the scope of research conducted, the assessment of the extent of...
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Long-term effects of device-guided slow breathing in stable heart failure patients with reduced ejection fraction
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Long-Term Follow-Up after Laparoscopic Uterovestibular Anastomosis in Patients with Cervical Atresia and Complete Absence of the Vagina
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Oversizing the photovoltaic generator capacity in a micro photovoltaic plant
PublicationA significant part of photovoltaic micro installations in Poland is characterized by photovoltaic generator oversizing in relation to the inverter. The idea of oversizing, however, still raises doubts among some plant owners. In the paper, the energy yield of installation with an oversized and not oversized photovoltaic generator is presented on selected examples, showing the legitimacy of oversizing.
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Application of Shape Memory Alloys in Retrofitting of Masonry and Heritage Structures Based on Their Vulnerability Revealed in the Bam 2003 Earthquake
PublicationFor decades, one of the most critical considerations of civil engineers has been the construction of structures that can sufficiently resist earthquakes. However, in many parts of the globe, ancient and contemporary buildings were constructed without regard for engineering; thus, there is a rising necessity to adapt existing structures to avoid accidents and preserve historical artefacts. There are various techniques for retrofitting...
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Human verbal memory encoding is hierarchically distributed in a continuous processing stream
PublicationProcessing of memory is supported by coordinated activity in a network of sensory, association, and motor brain regions. It remains a major challenge to determine where memory is encoded for later retrieval. Here we used direct intracranial brain recordings from epilepsy patients performing free recall tasks to determine the temporal pattern and anatomical distribution of verbal memory encoding across the entire human cortex. High...
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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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Ionic Liquids and Deep Eutectic Mixtures: Sustainable Solvents for Extraction Processes
PublicationIn recent years, ionic liquids and deep eutectic mixtures have demonstrated great potential in extraction processes relevant to several scientific and technological activities. This review focuses on the applicability of these sustainable solvents in a variety of extraction techniques, including but not limited to liquid- and solid-phase (micro) extraction, microwave-assisted extraction, ultrasound-assisted extraction and pressurized...
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Application of Shape Memory Alloys in Pipeline Couplings for Shipbuilding
PublicationThe aim of the study is to analyse shape memory alloy (SMA) pipeline joints in limited space applications for all kinds of ships. Generally, the space available in various areas on ships is strictly limited and service works usually meet many obstacles. If we consider a pipeline, the flange joints always require a larger free space around the pipe than the pipe alone. A simultaneous problem can occur with the propeller shaft line...
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Detection of Alzheimer's disease using Otsu thresholding with tunicate swarm algorithm and deep belief network
PublicationIntroduction: Alzheimer’s Disease (AD) is a degenerative brain disorder characterized by cognitive and memory dysfunctions. The early detection of AD is necessary to reduce the mortality rate through slowing down its progression. The prevention and detection of AD is the emerging research topic for many researchers. The structural Magnetic Resonance Imaging (sMRI) is an extensively used imaging technique in detection of AD, because...
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Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model
PublicationThis work attempts to meet the challenges associated with the classification of LIDAR point clouds by means of deep learning. In addition to achieving high accuracy, the designed system should allow the classification of point clouds covering an area of several dozen square kilometers within a reasonable time interval. Therefore, it must be characterized by fast processing and efficient use of memory. Thus, the most popular approaches...
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Recuperator with microjet technology as a proposal for heat recovery from low-temperature sources
PublicationA tendency to increase the importance of so called dispersed generation, based on the local energy sources and the working systems utilizing both the fossil fuels and the renewable energy resources is observed nowadays. Generation of electricity on industrial or domestic scale together with production of heat can be obtained for example through employment of the ORC systems. It is mentioned in the EU directive 2012/27/EU for cogenerative...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublicationIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Efficient sampling of high-energy states by machine learning force fields
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Speech Analytics Based on Machine Learning
PublicationIn this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...
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TB11 test for short w-beam road barrier
PublicationFEM (Finite Element Method) is well-suited and widely used tool for simulating a range of phenomena: from these with simple and static behaviour, up to those complicated, highly nonlinear and involving many contacts. In present paper we use one of the advantages of FEM: parametric study could be easily performed and is more economical than series of in-situ tests. If recommended practices is carefully followed, results obtained...
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Direct electrical brain stimulation of human memory: lessons learnt and future perspectives
PublicationModulation of cognitive functions supporting human declarative memory is one of the grand challenges of neuroscience, and of vast importance for a variety of neuropsychiatric, neurodegenerative and neurodevelopmental diseases. Despite a recent surge of successful attempts at improving performance in a range of memory tasks, the optimal approaches and parameters for memory enhancement have yet to be determined. On a more fundamental...
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A memory efficient and fast sparse matrix vector product on a Gpu
PublicationThis paper proposes a new sparse matrix storage format which allows an efficient implementation of a sparse matrix vector product on a Fermi Graphics Processing Unit (GPU). Unlike previous formats it has both low memory footprint and good throughput. The new format, which we call Sliced ELLR-T has been designed specifically for accelerating the iterative solution of a large sparse and complex-valued system of linear equations arising...