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Wyniki wyszukiwania dla: deep neural network
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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...
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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...
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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.
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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....
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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,...
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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...
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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,...
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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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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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....
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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...
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Deep Eutectic Solvents for Starch Treatment
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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...
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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...
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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...
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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...
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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...
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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...
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Modeling of Surface Roughness in Honing Processes by UsingFuzzy Artificial Neural Networks
PublikacjaHoning processes are abrasive machining processes which are commonly employed to improve the surface of manufactured parts such as hydraulic or combustion engine cylinders. These processes can be employed to obtain a cross-hatched pattern on the internal surfaces of cylinders. In this present study, fuzzy artificial neural networks are employed for modeling surface roughness parameters obtained in finishing honing operations. As...
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Effect of choline chloride based natural deep eutectic solvents on aqueous solubility and thermodynamic properties of acetaminophen
PublikacjaIn this work, natural deep eutectic solvents (NADESs) containing choline chloride as hydrogen bond acceptor and 1,2-propanediol, malic acid and tartaric acid as hydrogen bond donors have been synthesized and applied to enhance the aqueous solubility of model sparingly water-soluble drug – acetaminophen. The results indicate that the greatest impact on the solubility of acetaminophen have deep eutectic solvents based on 1,2-propanediol...
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Autonomous pick-and-place system based on multiple 3Dsensors and deep learning
PublikacjaGrasping 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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Effect of temperature and composition on physical properties of deep eutectic solvents based on 2-(methylamino)ethanol – measurement and prediction
PublikacjaNovel deep eutectic solvents were synthesized using 2-(methylamino)ethanol as hydrogen bond donor with tetrabutylammonium bromide or tetrabutylammonium chloride or tetraethylammonium chloride as hydrogen bond acceptors. Mixtures were prepared at different molar ratios of 1:6, 1:8 and 1:10 salt to alkanolamine and then Fourier Transform Infrared Spectroscopy measurements were performed to confirm hydrogen bonds interactions between...
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Technology brands in the digitally-based and network economy. Setting the background
PublikacjaThis chapter defines and draws a general picture on Digital Technologies and Technology Brands’ meaning in the current economy. It contextualises the role and channels of digital technology’s impact on their shaping technology brands in network economy. It briefly explains why digital, innovative technologies constitute a perfect background and environment for technology brands of global scope. It discusses the place of technology...
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Personality Type and Neural Circulatory Control
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Artificial Neural Networks for Comparative Navigation
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Neural Networks and the Evolution of Environmental Change
PublikacjaZmiany środowiskowe na Ziemii są odwieczne i liczą około 4 miliardy lat. Homo sapiens wpłynął na każdy aspekt środowiska ziemskiego w wyniku rozwoju ludzkości na przestrzeni ostatnich milionów lat. Ale nic tak nie wpłynęło na wzrost i szybkość zmian na Ziemi jak ludzka aktywność w ciągu ostatnich dwóch stuleci. Po raz pierwszy zmiany ekosystemów były tak intensywne i zachodziły na tka wielką skalę i z taką szybkością jak nigdy...
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Neural simulator of steam power unit.
PublikacjaZbadano możliwości zbudowania neuronowego symulatora turbinowego bloku energetycznego. Zamodelowano ten obieg i sprawdzono konfiguracje sztucznych sieci neuronowych (SSN) zapewniające dużą dokładność symulatora neuronowego. Zwrócono uwagę na problemy dotyczące węzłów siłowni, w których następuje mieszanie się strumieni czynnika o zróżnicowanych parametrach cieplno-przepływowych. Wskazano na zastosowanie takiego symulatora w diagnostyce.
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Neural reliability model of diesel engines
PublikacjaW artykule przedstawiono wyniki weryfikacji hipotezy zakładającej celowość zastosowania modelu niezawodnościowego silnika tłokowego z zapłonem samoczynnym w postaci sztucznej sieci neuronowej. Weryfikację przeprowadzono w oparciu o wyniki badań eksploatacyjnych.
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Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements
PublikacjaThis article presents the process of the construction and testing a remote, fully autonomous system for measuring the operational parameters of fans. The measurement results obtained made it possible to create and verify mathematical models using linear regression and neural networks. The process was implemented as part of the first stage of an innovative project. The article presents detailed steps of constructing a system to...
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Deep learning for ultra-fast and high precision screening of energy materials
PublikacjaSemiconductor materials for energy storage are the core and foundation of modern information society and play important roles in photovoltaic system, integrated circuit, spacecraft technology, lighting applications, and other fields. Unfortunately, due to the long experiment period and high calculation cost, the high-precision band gap (the basic characteristic parameter) of semiconductor is difficult to obtain, which hinders the...
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Hydrophobic (deep) eutectic solvents (HDESs) as extractants for removal of pollutants from water and wastewater – A review
PublikacjaDeep eutectic solvents (DESs) are a new generation of solvents that attracted increasing attention in diverse applications. In last years, growing number of studies on hydrophobic (deep) eutectic solvents (HDESs) as an alternative extractants for various chemicals from aqueous environments have been reported. This article provides an overview on the usage of HDESs in liquid–liquid extraction (LLE) of different pollutants from water...
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EFFICIENCY OF HEALTHCARE SYSTEMS IN EUROPEAN COUNTRIES - THE DEA NETWORK APPROACH
PublikacjaHealthcare systems in Europe are constantly undergoing reforms which adapt them to social, economic and political requirements. The aim of this article is to examine the efficiency of healthcare systems in 30 European countries in 2014. The Network Data Envelopment Analysis (NDEA) model was used. The efficiency of the countries’ overall health systems and their two main components were examined: the public health system and the...
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Smart Grid in Practise - Implementation of the Billaterall Supply in Gdynia Trolleybus Network
PublikacjaSince 2001, trolleybus system in Gdynia has been involved in many activities related to the reduction of power consumption, both in terms of implementation and research and development. In 2011 was introduced the first supercapacitor storage energy system. In PKT started applications of Smart Grid technologies in supply network: the bilateral supply. The paper presents results of these this novel investitions.
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A city is not a tree: a multi-city study on street network and urban life
PublikacjaChristopher Alexander, a British-American scholar, differentiated an old (natural) city from a new (planned) one by structure. The former resembles a “semilattice”, or a complex system encompassing many interconnected sub-systems. The latter is shaped in a graph-theoretical “tree”, which lacks the structural complexity as its sub-systems are compartmentalized into a single hierarchy. This structural distinction explains why, or...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublikacjaMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Deep Eutectic Solvents as Agents for Improving the Solubility of Edaravone: Experimental and Theoretical Considerations
PublikacjaIn this study, both practical and theoretical aspects of the solubility of edaravone (EDA) in Deep Eutectic Solvents (DESs) were considered. The solubility of edaravone in some media, including water, can be limited, which creates the need for new efficient and environmentally safe solvents. The solubility of EDA was measured spectrophotometrically and the complex intermolecular interactions within the systems were studied with...
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Deep Eutectic Solvents as Agents for Improving the Solubility of Edaravone: Experimental and Theoretical Considerations
PublikacjaIn this study, both practical and theoretical aspects of the solubility of edaravone (EDA) in Deep Eutectic Solvents (DESs) were considered. The solubility of edaravone in some media, including water, can be limited, which creates the need for new efficient and environmentally safe solvents. The solubility of EDA was measured spectrophotometrically and the complex intermolecular interactions within the systems were studied with...
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Surface effects of network materials based on strain gradient homogenized media
PublikacjaThe asymptotic homogenization of periodic network materials modeled as beam networks is pursued in this contribution, accounting for surface effects arising from the presence of a thin coating on the surface of the structural beam elements of the network. Cauchy and second gradient effective continua are considered and enhanced by the consideration of surface effects. The asymptotic homogenization technique is here extended to...
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KEMR-Net: A Knowledge-Enhanced Mask Refinement Network for Chromosome Instance Segmentation
PublikacjaThis article proposes a mask refinement method for chromosome instance segmentation. The proposed method exploits the knowledge representation capability of Neural Knowledge DNA (NK-DNA) to capture the semantics of the chromosome’s shape, texture, and key points, and then it uses the captured knowledge to improve the accuracy and smoothness of the masks. We validate the method’s effectiveness on our latest high-resolution chromosome...
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Superhydrophobic sponges based on green deep eutectic solvents for spill oil removal from water
PublikacjaThe paper described a new method for crude oil-water separation by means of superhydrophobic melamine sponges impregnated by deep eutectic solvents (MS-DES). Due to the numerous potential of two-component DES formation, simple and quick screening of 156 non-ionic deep eutectic solvents using COSMO-RS (Conductor-like Screening Model for Real Solvents) computational model was used. DES which were characterized by high solubility...
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OOA-modified Bi-LSTM network: An effective intrusion detection framework for IoT systems
PublikacjaCurrently, the Internet of Things (IoT) generates a huge amount of traffic data in communication and information technology. The diversification and integration of IoT applications and terminals make IoT vulnerable to intrusion attacks. Therefore, it is necessary to develop an efficient Intrusion Detection System (IDS) that guarantees the reliability, integrity, and security of IoT systems. The detection of intrusion is considered...
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Nonadditivity of quantum and classical capacities for entanglement breaking multiple-access channels and the butterfly network
PublikacjaWe analyze quantum network primitives which are entanglement breaking. We show superadditivity of quantum and classical capacity regions for quantum multiple-access channels and the quantum butterfly network. Since the effects are especially visible at high noise they suggest that quantum information effects may be particularly helpful in the case of the networks with occasional high noise rates. The present effects provide a qualitative...
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Testing Situation Awareness Network for the Electrical Power Infrastructure
PublikacjaThe contemporary electrical power infrastructure is exposed to new types of threats. The cause of such threats is related to the large number of new vulnerabilities and architectural weaknesses introduced by the extensive use of Information and Communication Technologies (ICT) in such complex critical systems. The power grid interconnection with the Internet exposes the grid to new types of attacks, such as Advanced Persistent...