Filtry
wszystkich: 2799
-
Katalog
- Publikacje 2270 wyników po odfiltrowaniu
- Czasopisma 60 wyników po odfiltrowaniu
- Konferencje 40 wyników po odfiltrowaniu
- Wydawnictwa 1 wyników po odfiltrowaniu
- Osoby 75 wyników po odfiltrowaniu
- Projekty 7 wyników po odfiltrowaniu
- Kursy Online 23 wyników po odfiltrowaniu
- Wydarzenia 8 wyników po odfiltrowaniu
- Dane Badawcze 315 wyników po odfiltrowaniu
wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: DEEP NEURAL NETWORK
-
Traffic Type Influence on QoS Network Performance of Streaming Traffic Class
PublikacjaFeasibility study on QoS routing proved that the traffic type influence the network performance. The performance is defined here as a number of packets serviced by the network. In the paper additional element - buffers lengths used in service system was verified in terms of dependencies with routing performance. We present results obtained by simulation for many simulation scenarios. Analysis was done for two different network...
-
The application of neural networks in forecasting the influence of traffic-induced vibrations on residential buildings
PublikacjaTraffic-induced vibrations may cause the cracking of plaster, damage to structural elements and, in extreme cases, may even lead to the structural collapse of residential buildings. The aim of this article is to analyse the effectiveness of a method of forecasting the impact of vibrations on residential buildings using the concept of artificial intelligence. The article presents several alternative forecasting systems for which...
-
A method of the UMTS-FDD network design based on universal load characteristics
PublikacjaIn the paper an original method of the UMTS radio network design was presented. The method is based on simple way of capacity-coverage trade-off estimation for WCDMA/FDD radio interface. This trade-off is estimated by using universal load characteristics and normalized coverage characteristics. The characteristics are useful for any propagation environment as well as for any service performance requirements. The practical applications...
-
Deep Features Class Activation Map for Thermal Face Detection and Tracking
PublikacjaRecently, capabilities of many computer vision tasks have significantly improved due to advances in Convolutional Neural Networks. In our research, we demonstrate that it can be also used for face detection from low resolution thermal images, acquired with a portable camera. The physical size of the camera used in our research allows for embedding it in a wearable device or indoor remote monitoring solution for elderly and disabled...
-
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...
-
Multi Queue Approach for Network Services Implemented for Multi Core CPUs
PublikacjaMultiple core processors have already became the dominant design for general purpose CPUs. Incarnations of this technology are present in solutions dedicated to such areas like computer graphics, signal processing and also computer networking. Since the key functionality of network core components is fast package servicing, multicore technology, due to multi tasking ability, seems useful to support packet processing. Dedicated...
-
Brand loyalty creation in the social network. Does the product category matter?
PublikacjaThe final goal of all marketers’ effort is to achieve a high level of loyalty toward their brands. Social network brand sites are increasingly attracting the attention of scientists and managers intrigued by their potential application for brand loyalty creation. The aim of this research, based on European sample, is to fill the gap in understanding the product category loyalty and brand loyalty relation as an output of brand identification...
-
Global Digital Technology Convergence: Driving Diffusion via Network Effects
PublikacjaSince the 1970s, we have witnessed unprecedented diffusion of digital technologies in both speed and geographic coverage. These technologies are pervasive and disruptive, and lead to profound shifts and transformations in societies and economies. Many claim that emerging network externalities are the principal phenomenon driving the process of technology diffusion and determining its in-time dynamics. This book analyses the unique...
-
Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks
PublikacjaObject detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...
-
Non-isolated resonant quasi-Z-source network DC–DC converter
PublikacjaA novel non-isolated resonant quasi-impedance (quasi-Z)-source network DC–DC converter is proposed. The resonant impedance source network is derived from the quasi-Z-source network by including the autotransformer-based resonant cell instead of the second inductor of the quasi-Z-network. The leakage inductance of the autotransformer and two resonant capacitors connected in series with the autotransformer windings constitute a high-frequency...
-
Automated detection of pronunciation errors in non-native English speech employing deep learning
PublikacjaDespite significant advances in recent years, the existing Computer-Assisted Pronunciation Training (CAPT) methods detect pronunciation errors with a relatively low accuracy (precision of 60% at 40%-80% recall). This Ph.D. work proposes novel deep learning methods for detecting pronunciation errors in non-native (L2) English speech, outperforming the state-of-the-art method in AUC metric (Area under the Curve) by 41%, i.e., from...
-
Evaluation of a sat-type fairness mechanism implemented in a dual-ring network
PublikacjaThe fairness problem was presented. Popular fairness concepts and measures were shown. The RPR fairness mechanism and the SAT mechanism were described. A modification of the SAT algorithm, adapted to the possibilities of Ethernet cards used for implementation of a dual-ring RPR-based network, was proposed. Performance of the proposed modification was measured. Jain's and Chen's fairness indexes were calculated. Effectiveness comparison...
-
OPTICAL STRAIN MEASUREMENT OF CONCRETE VERSUS MANUAL EXTENSOMETER MEASUREMENT BASED ON THE TEST RC DEEP BEAM IN A COMPLEX STATE OF STRESS
PublikacjaThe purpose of this study is to compare the strain measurement techniques of concrete in R-C element subjected to the monotonic load up to the failure. In the analysis manual extensometer methods of measurements and the optical system ARAMIS for non-contact three-dimensional measurements of deformation was used. The test sample was a cantilever deep beam loaded throughout the depth which was a part of the reinforced concrete deep...
-
Modeling of traffic safety indictors on Polish national road network
PublikacjaAlthough decreased from 2001 to 2013, Poland’s road deaths improved at a slower rate than the rest of the EU, leaving Poland as one of the worst road safety performing countries in the EU. The national road network in Poland, despite the dynamic transformation and development, still does not conform to the EU safety standards. Similar situation exists in other EU countries, particularly those in Central and Eastern Europe. Safety...
-
Deep eutectic solvents in analytical sample preconcentration Part B: Solid-phase (micro)extraction
PublikacjaOne of the key challenges of modern analytical chemistry is the monitoring of trace amounts of contaminants using sensitive and selective instrumental techniques. Due to the variety and complexity of some samples, it is often necessary to properly prepare a sample and to perform a preconcentration of trace amounts of analytes. In line with the principles of Green Analytical Chemistry (GAC), it is important for an analytical procedure...
-
Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublikacjaThe 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...
-
Time Synchronization between the eNBs in E-UTRAN under the Asymmetric IP Network
PublikacjaIn this paper, we present a method for a time synchronization between the two eNodeBs (eNBs) in E-UTRAN (Evolved Universal Terrestrial Radio Access) network. The...
-
Assessment and design of greener deep eutectic solvents – A multicriteria decision analysis
PublikacjaDeep eutectic solvents (DES) are often considered as green solvents because of their properties, such as negligible vapor pressure, biodegradability, low toxicity or natural origin of their components. Due to the fact that DES are cheaper than ionic liquids, they have gained many applications in a short period of time. However, claims about their greenness sometimes seem to be exaggerated. Especially, bearing in mind lots of data...
-
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....
-
DISTRIBUTION OF FLOWS IN A CHANNEL NETWORK UNDER STEADY FLOW CONDITIONS
PublikacjaThe article presents an algorithm for calculating the distribution of flow in a junction of open channel network under steady flow conditions. The article presents a simplified calculation algorithm used to estimate the distribution of flow in a network of channels under steady flow conditions. The presented algorithm is based on the continuity equation and a simplified energy equation. To describe the relationship between the...
-
Network Graph Transformation Providing Fast Calculation of Paths for Resilient Routing
PublikacjaProtection of transmission against failures can be appropriately dealt with by alternative paths. However, common schemes (e.g., Bhandaris scheme) are characterized by a remarkable delay while determining the transmission paths. This in turn may have a serious impact on serving dynamic demands (characterized by relatively short duration time). As a remedy to this problem, we introduce an approach to pre-compute the sets of disjoint...
-
Hydrophobic deep eutectic solvents as “green” extraction media for polycyclic aromatic hydrocarbons in aqueous samples
PublikacjaThe paper presents novel nonionic and hydrophobic deep eutectic solvents which were synthesized from natural compounds, i.e., thymol, ±camphor, decanoic and 10-undecylenic acids. Fundamental physicochemical properties of the synthesized deep eutectic solvents were determined, followed by their application as extractants in ultrasound-assisted dispersive liquid-liquid microextraction to isolate and enrich polycyclic aromatic hydrocarbons...
-
Efficient Extraction of Fermentation Inhibitors by Means of Green Hydrophobic Deep Eutectic Solvents
PublikacjaThe methods for hydrogen yield efficiency improvements, the gaseous stream purification in gaseous biofuels generation, and the biomass pretreatment are considered as the main trends in research devoted to gaseous biofuel production. The environmental aspect related to the liquid stream purification arises. Moreover, the management of post-fermentation broth with the application of various biorefining techniques gains importance....
-
The Methodology of identifying the place to install shunt compensators in the transmission network
PublikacjaThis methodology of selection and localization of static com- paper presents pensators in wide network. Proposed method is based on analysis of voltage area power profiles in the nodes of the power grid, and designating locations, In Which Voltages ex- cessively tend to change in time. Practical way of modeling the SVC device in PLANS program you Presented, as well as some example results of research.
-
Multi-Camera Vehicle Tracking Using Local Image Features and Neural Networks
PublikacjaA method for tracking moving objects crossing fields of view of multiple cameras is presented. The algorithm utilizes Artificial Neural Networks (ANNs). Each ANN is trained to recognize images of one moving object acquired by a single camera. Local image features calculated in the vicinity of automatically detected interest points are used as object image parameters. Next, ANNs are employed to identify the same objects captured...
-
Network-centric warfare: a strategy for homeland security
PublikacjaPojawienie się międzynarodowego terroryzmu skutkuje nowym podejście do identyfikacji potencjalnych zagrożeń dla bezpieczeństwa krajowego. Powstał strategiczny dylemat - jak zidentyfikować przeciwnika? Utworzono pojęcie asymetrycznego zagrożenia i, w konsekwencji, asymetrycznej wojny. Z dużym prawdopodobieństwem można założyć, że kolejne zagrożenia będą dotyczyć takich elementów krajowej infrastruktury, jak źródła energii, elektrownie,...
-
Experimental and predicted physicochemical properties of monopropanolamine-based deep eutectic solvents
PublikacjaIn this work, the novel deep eutectic solvents (DESs) based on 3-amino-1-propanol (AP) as hydrogen bond donor (HBD) and tetrabutylammonium bromide (TBAB) or tetrabutylammonium chloride (TBAC) or tetraethylammonium chloride (TEAC) as hydrogen bond acceptors (HBAs) were synthesized with different molar ratios of 1: 4, 1: 6 and 1: 8 salt to AP. Fourier Transform Infrared Spectroscopy measurements were performed to provide an evidence...
-
Experimental and predicted physicochemical properties of monopropanolamine-based deep eutectic solvents
PublikacjaIn this work, the novel deep eutectic solvents (DESs) based on 3-amino-1-propanol (AP) as hydrogen bond donor (HBD) and tetrabutylammonium bromide (TBAB) or tetrabutylammonium chloride (TBAC) or tetraethylammonium chloride (TEAC) as hydrogen bond acceptors (HBAs) were synthesized with different molar ratios of 1:4, 1:6 and 1:8 salt to AP. Fourier Transform Infrared Spectroscopy measurements were performed to provide an evidence...
-
Closer look into the structures of tetrabutylammonium bromide–glycerol-based deep eutectic solvents and their mixtures with water
PublikacjaIn recent years, deep eutectic solvents (DES) and it’s mixture with water have become more and more attention as green solvents used in chemistry. However, there are only a few theoretical studies on the mechanisms of pure DES and DES-water complex formation. Therefore, the structural properties of tetrabutylammonium bromide–glycerol-based deep eutectic solvents and their mixtures with water have been investigated by means of Molecular...
-
Cross-layer mDNS/ARP integration for IEEE 802.11s Wireless mesh Network
PublikacjaPopularization of mobile computing devices created a need for robust, efficient and ubiquitous methods of communication and network access. At the same time, evolution and standardization of Wireless Local Area Network (WLAN) technologies made them an attractive solution for building of complex network systems. Moreover, growing maturity of WLAN standards such as IEEE 802.11 allows for introduction of WLAN architectures other than...
-
Cryptographic Protocols' Performance and Network Layer Security of RSMAD
PublikacjaW artykule omówiono architekturę bezpieczeństwa warstwy sieciowej Radiowego Systemu Monitorowania i Akwizycji Danych z urządzeń fotoradarowych (w skrócie RSMAD). Bezpieczeństwo w warstwie sieciowej tego systemu jest zapewniane przede wszystkim dzięki wykorzystaniu Virtual Private Network (w skrócie VPN). W tym celu zaimplementowano dwa protokoły IPsec i L2TP.Zastosowane mechanizmy ochrony danych, w tym typy i parametry VPNów zostały...
-
Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
PublikacjaIonic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship...
-
Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublikacjaHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
-
Simulation Model for Application of the SDN Concept in IMS/NGN Network Transport Stratum
PublikacjaThe paper presents a simulation model allowing examination of cooperation between two currently used telecommunication networks concepts: IP Multimedia Subsystem/Next Generation Network (IMS/NGN) and Software-Defined Networking (SDN). Application of the SDN architecture elements in IMS/NGN networks will enable unified control and management of transport resources for various transport technologies and equipment manufacturers. However,...
-
Application of Artificial Neural Networks to Predict Insulation Properties of Lightweight Concrete
PublikacjaPredicting the properties of concrete before its design and application process allows for refining and optimizing its composition. However, the properties of lightweight concrete are much harder to predict than those of normal weight concrete, especially if the forecast concerns the insulating properties of concrete with artificial lightweight aggregate (LWA). It is possible to use porous aggregates and precisely modify the composition...
-
Selfie and Personal Branding Phenomena in the Context of the Network Economy. A Literature Review
PublikacjaSelf-taken pictures called “selfies” shared in social media have become a worldwide phenomenon. This is due to the increased need of human being to share to other people their daily lives and to build their own personal brand in the networked world. Despite that, the subject of personal branding has not been sufficiently discussed in academic marketing literature over the past decade. The objective of the study is to present the...
-
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...
-
Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublikacjaEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
-
Solubility advantage of sulfanilamide and sulfacetamide in natural deep eutectic systems: experimental and theoretical investigations
PublikacjaObjective: The aim of this study was to explore the possibility of using natural deep eutectic solvents (NADES) as solvation media for enhancement of solubility of sulfonamides, as well as gaining some thermodynamic characteristics of the analyzed systems. Significance: Low solubility of many active pharmaceutical ingredients is a well-recognized difficulty in pharmaceutical industry, hence the need for different strategies addressing...
-
Voltage variations and their reduction in a rural low-voltage network with PV sources of energy
PublikacjaRenewable sources of energy (RES), especially photovoltaic (PV) micro-sources, are very popular in many countries. This way of clean power production is applied on a wide scale in Poland as well. The Polish legal regulations and tariffs specify that every prosumer in a low-voltage network may feed this network with a power not higher than the maximum declared consumed power. In power networks with RES, the voltage level changes...
-
Injury Prediction Models for Onshore Road Network Development
PublikacjaIntegrating different modes of transport (road, rail, air and water) is important for port cities. To accommodate this need, new transport hubs must be built such as airports or sea ports. If ports are to grow, they must be accessible, a feature which is best achieved by building new roads, including fast roads. Poland must develop a network of fast roads that will provide good access to ports. What is equally important is to upgrade...
-
Planning a Cost-Effective Delay-Constrained Passive Optical Network for 5G Fronthaul
PublikacjaWith the rapid growth in the telecommunications industry moving towards 5G and beyond (5GB) and the emergence of data-hungry and time-sensitive applications, Mobile Network Operators (MNOs) are faced with a considerable challenge to keep up with these new demands. Cloud radio access network (CRAN) has emerged as a cost-effective architecture that improves 5GB performance. The fronthaul segment of the CRAN necessitates a high-capacity...
-
DAB+ Coverage Analysis: a New Look at Network Planning using GIS Tools
PublikacjaFor many years, the matter of designing a transmitter network, optimized for best signal coverage, has been a subject of intense research. In the last decade, numerous researchers and institutions used GIS and spatial analysis tools for network planning, especially transmitter location. Currently, many existing systems operate in a strictly two-dimensional manner, not taking into account the three-dimensional nature of the analyzed...
-
Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublikacjaDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
-
Experimental and Theoretical Insights into the Intermolecular Interactions in Saturated Systems of Dapsone in Conventional and Deep Eutectic Solvents
PublikacjaSolubility is not only a crucial physicochemical property for laboratory practice but also provides valuable insight into the mechanism of saturated system organization, as a measure of the interplay between various intermolecular interactions. The importance of these data cannot be overstated, particularly when dealing with active pharmaceutical ingredients (APIs), such as dapsone. It is a commonly used anti-inflammatory and...
-
Selected issues related to the toxicity of ionic liquids and deep eutectic solvents—a review
PublikacjaGreen Chemistry plays a more and more important role in implementing rules of sustainable development to prevent environmental pollution caused by technological processes, while simultaneously increasing the production yield. Ionic liquids (ILs) and deep eutectic solvents (DESs) constitute a very broad group of substances. Apart from many imperfections, ILs and DESs have been the most promising discoveries in the world of Green...
-
Application of deep eutectic solvents for separation and determination of bioactive compounds in medicinal plants
PublikacjaThe medicinal plants industry, particularly in regard to products rich in biologically active substances for maintaining health, has grown by leaps and bounds in the last decade, with sales of over-the-counter drugs containing these substances growing by billions of dollars. Attention has thus also been paid to the safety and effectiveness of these medicines. We are currently witnessing a rapid increase in the number of publications...
-
Deodorization of model biogas by means of novel non-ionic deep eutectic solvent
PublikacjaThe paper presents new non-ionic deep eutectic solvent (DES) composed of natural and non-toxic components i.e. guaiacol, camphor and levulinic acid in 1:1:3 molar ratio as a promising absorbent for removal of selected volatile organic compounds (VOCs) including dichloromethane, toluene, hexamethyldisiloxane and propionaldehyde from model biogas. The affi nity of DES for VOCs was determined as vapour-liquid coeffi cients and the...
-
VOCs absorption from gas streams using deep eutectic solvents – A review
PublikacjaVolatile organic compounds (VOCs) are one of the most severe atmospheric pollutants. They are mainly emitted into the atmosphere from anthropogenic sources such as automobile exhaust, incomplete fuel combustion, and various industrial processes. VOCs not only cause hazards to human health or the environment but also adversely affect industrial installation components due to their specific properties, i.e., corrosive and reactivity....
-
Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
PublikacjaOne of the ways to improve the fuel economy of heavy duty trucks is to operate the combustion engine in its most efficient operating points. To do that, a mathematical model of the engine is required, which shows the relations between engine speed, torque and fuel consumption in transient states. In this paper, easy accessible exploitation data collected via CAN bus of the heavy duty truck were used to obtain a model of a diesel...