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Influence of input data on airflow network accuracy in residential buildings with natural wind - and stack - driven ventilation.
PublikacjaW artykule omówiono wpływ danych wejściowych na dokładność modelu przepływu sieciowego powietrza w budynkach mieszkalnych z naturalną i kominową wentylacją. Zastosowano połączony model AFN-BES. Wyniki numeryczne omówiono dla 8 różnych przypadków z różnymi danymi ciśnienia wiatru. Wyniki pokazały, że ogromny wpływ danych wejściowych dotyczących ciśnienia wiatru na wyniki numeryczne.
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Comparison of selected clustering algorithms of raw data obtained by interferometric methods using artificial neural networks
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Multicast Traffic Throughput Maximization through Dynamic Modulation and Coding Scheme Assignment in Wireless Sensor Networks
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Fast service restoration under shared protection at lightpath level in survivable WDM mesh grooming networks
PublikacjaW artykule zaproponowano nowe podejście do optymalizacji rozdziału zasobów w przeżywalnych sieciach optycznych z agregacją strumieni ruchu. Zaproponowana metoda bazuje na wierzchołkowym kolorowaniu grafu konfliktów. Jest pierwszym podejściem, dedykowanym sieciom optycznym z agregację strumieni ruchu z pełną zdolnością do konwersji długości fal, która nie powoduje wydłużenia ściezek zabezpieczjących, a więc zapewnia szybkie odtwarzanie...
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Towards the 4th industrial revolution: networks, virtuality, experience based collective computational intelligence, and deep learning
PublikacjaQuo vadis, Intelligent Enterprise? Where are you going? The authors of this paper aim at providing some answers to this fascinating question addressing emerging challenges related to the concept of semantically enhanced knowledge-based cyber-physical systems – the fourth industrial revolution named Industry 4.0.
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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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Probability estimation of the city’s energy efficiency improvement as a result of using the phase change materials in heating networks
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An Off-Body Narrowband and Ultra-Wide Band Channel Model for Body Area Networks in a Ferry Environment
PublikacjaIn the article an off-body narrowband and ultra-wide band channel model for Body Area Networks in a ferry environment is described. A mobile, heterogeneous measurement stand, that consists of three types of devices: miniaturized mobile nodes, stationary reference nodes and a data acquisition server was developed. A detailed analysis of both radio channels parameters in untypical indoor environment was carried out. An analysis of...
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An Off-Body Narrowband and Ultra-Wide Band Channel Model for Body Area Networks in a Ferryboat Environment
PublikacjaIn the article an off-body narrowband and ultra-wide band channel model for body area networks in a ferryboat environment is described. Considering the limited number of publications there is a need to develop an off-body channel model, which will facilitate the design of radio links, both from the multimedia services provider and the security point of view, for body area networks in this atypical environment. A mobile heterogeneous...
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Modulo N Backoff Scheme for effective QoS differentiation and increased bandwidth utilization in IEEE 802.11 networks
PublikacjaThe paper presents a new "modulo N" channel access scheme for wireless Local Area Networks (WLANs). The novel solution derives from the Distributed Coordination Function (DCF) of the IEEE 802.11 standard, further elaborated as Enhanced Distribution Channel Access (EDCA) by the 802.11e draft specification. The main innovation concerns improvement of the binary exponential backoff scheme used for collision avoidance in 802.11 networks....
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Blood Pressure Estimation Based on Blood Flow, ECG and Respiratory Signals Using Recurrent Neural Networks
PublikacjaThe estimation of systolic and diastolic blood pressure using artificial neural network is considered in the paper. The blood pressure values are estimated using pulse arrival time, and additionally RR intervals of ECG signal together with respiration signal. A single layer recurrent neural network with hyperbolic tangent activation function was used. The average blood pressure estimation error for the data obtained from 21 subjects...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublikacjaThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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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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Social networks as a context for small business? A new look at an enterprise in the context of a smallness and newness liability syndrome
PublikacjaIn this paper we aim to propose and outline key ingredients to a small enterprise success, emerging from the social capital of small business owner-managers and their business networks. We employ resource based view of an organization as well as an embeddedness perspective along with new approach transaction costs to outline the pillars of an advantage of a small business entity. The analysis of survey data leads us to conclusion,...
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Selfishness Detection in Mobile Ad Hoc Networks: How Dissemination of Indirect Information Turns into Strategic Issue
PublikacjaDla środowiska sieci mobilnej ad hoc przedyskutowano wymienność pomiędzy wydatkiem energetycznym węzła egoistycznego a obniżaniem jego metryki reputacyjnej. Badania symulacyjne wskazują, że atakom polegającym na selektywnym usuwaniu pakietów można przeciwdziałać poprzez datacentryczny system reputacyjny bazujący na potwierdzeniach końcowych, który nakazuje jednakowo uaktualniać metryki reputacyjne dla wszystkich węzłów na źle zachowującej...
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Design, Realization and Measurements of Enhanced Performance 2.4 GHz ESPAR Antenna for Localization in Wireless Sensor Networks
PublikacjaThis paper presents the design, realization and measurements of an Electronically Steerable Parasitic Array Radiator (ESPAR) antenna with enhanced performance of estimating the incoming signal direction. Designed antenna is dedicated for 2.4 GHz ISM applications with emphasis on Wireless Sensor Networks (WSN). Proposed antenna provides different radiation patterns by proper configuration of the parasitic elements. Thus, several...
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Risk Modelling with Bayesian Networks - Case Study: Construction of Tunnel under the Dead Vistula River in Gdansk
PublikacjaThe process of decision-making in public procurement of construction projects during the preparation and implementation phases ought to be supported by risk identification, assessment, and management. In risk assessment one has to take into account factors that lead to risk events (background info), as well as the information about the risk symptoms (monitoring info). Typically once the risks have been assessed a decision-maker...
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Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-Learned Features
PublikacjaNematodes Caenorhabditis elegans (C. elegans) have been used as model organisms in a wide variety of biological studies, especially those intended to obtain a better understanding of aging and age-associated diseases. This paper focuses on automating the analysis of C. elegans imagery to classify the muscle age of nematodes based on the known and well established IICBU dataset. Unlike many modern classification methods, the proposed...
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Fabrication of toughened plastic using styrene butadiene rubber-poly (methyl methacrylate) interpenetrating polymer networks
PublikacjaA standard set of interpenetrating polymeric networks (IPNs) has been contrived using an elastomerstyrene butadiene rubber and a thermoplastic poly (methyl methacrylate) through sequential polymerization protocol. This low-cost material can be hopefully engaged as a toughened plastic with cocontinuous morphology. Different morphological protocols including Raman imaging are effectively utilized to envisage the effect of blend ratio...
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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublikacjaIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
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Two- and three-dimensional elastic networks with rigid junctions: modeling within the theory of micropolar shells and solids
PublikacjaFor two- and three-dimensional elastic structures made of families of flexible elastic fibers undergoing finite deformations, we propose homogenized models within the micropolar elasticity. Here we restrict ourselves to networks with rigid connections between fibers. In other words, we assume that the fibers keep their orthogonality during deformation. Starting from a fiber as the basic structured element modeled by the Cosserat...
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Mathematical modeling and prediction of pit to crack transition under cyclic thermal load using artificial neural network
PublikacjaThe formation of pitting is a major problem in most metals, which is caused by extremely localized corrosion that creates small holes in metal and subsequently, it changes into cracks under mechanical load, thermo-mechanical stress, and corrosion process factors. This research aims to study pit to crack transition phenomenon of steel boiler heat tubes under cyclic thermal load, and mathematical modeling...
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<title>Selection of GRNN network parameters for the needs of state vector estimation of maneuvering target in ARPA devices</title>
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Optimal Selection of Input Features and an Acompanying Neural Network Structure for the Classification Purposes - Skin Lesions Case Study
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Longitudinal drug synergy assessment using convolutional neural network image-decoding of glioblastoma single-spheroid cultures
PublikacjaAbstract Background In recent years, drug combinations have become increasingly popular to improve therapeutic outcomes in various diseases, including difficult to cure cancers such as the brain cancer glioblastoma. Assessing the interaction between drugs over time is critical for predicting drug combination effectiveness and minimizing the risk of therapy resistance. However, as viability readouts of drug combination experiments...
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Performance analysis of an rfid-based 3d indoor positioning system combining scene analysis and neural network methods
PublikacjaThe main purpose of this research is to improve localization accuracy of an active Radio Frequency Identification, RFID tag, in 3D indoor space. The paper presents a new RFID based 3D Indoor Positioning System which shows performance improvement. The proposed positioning system combines two methods: the Scene Analysis technique and Artificial Neural Network. The results of both simulation using Log-Distance Path Loss Model and...
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Using Statistical Methods to Estimate The Worst Case Response Time of Network Software Running on Indeterministic Hardware Platforms
PublikacjaIn this paper we investigate whether the statistical Worst Case Execution Time (WCET) estimation methods devised for embedded platforms can be successfully applied to find the Worst Case Response Time (WCRT) of a network application running on a complex hardware platform such as a contemporary commercial off-the-shelf (COTS) system. Establishing easy-to-use timing validation techniques is crucial for real-time applications and...
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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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Novel Adaptive Method for Data Streams Allocation Based on the Estimate of Radio Channel Parameters in Heterogeneous WBAN Network
PublikacjaThe new adaptive method for data streams allocation in heterogeneous Wireless Body Area Networks and meas-urement equipment is presented. The results obtained using the developed method compared with the selected algorithms likely to be used in those networks. The pro-posed adaptive data streams allocation method based on radio channel parameters makes it even twice as efficient to use in terms of resources usage in a WBAN heterogeneous...
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Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study
PublikacjaMalignant melanomas are the most deadly type of skin cancers however detected early enough give a high chances for successful treatment. The last years saw the dynamic growth of interest of automatic computer-aided skin cancer diagnosis. Every month brings new research results on new approaches to this problem, new methods of preprocessing, new classifiers, new ideas to follow etc. In particular, the rapid development of dermatoscopy,...
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublikacjaMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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Modeling of TEC Variations Based on Signals from Near Zenith GNSS Satellite Observed by Dense Regional Network
PublikacjaCurrently the substantial successes in high-resolution ionospheric mapping is declared in many publications. Nevertheless, up to now there are no examples of dynamic visualization of TEC disturbances on regional scale with as high resolution as tropospheric models. Over the years, ionosphere has been modeling basing on the simple assumption, that it is a thin layer, which surrounds the Earth at some arbitrary height. However, the...
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Adaptive Algorithm of a Tap-Changer Controller of the Power Transformer Supplying the Radial Network Reducing the Risk of Voltage Collapse
Publikacjahe development of renewable energy, including wind farms, photovoltaic farms as well as prosumer installations, and the development of electromobility pose new challenges for network operators. The results of these changes are, among others, the change of network load profiles and load flows determining greater volatility of voltages. Most of the proposed solutions do not assume a change of the transformer regulator algorithm....
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader's behavior must align for the best learning effects....
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning effects....
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Artificial neural network prophecy of ion exchange process for Cu (II) eradication from acid mine drainage
PublikacjaThe removal of heavy metal ions from wastewater was found to be significant when the cation exchange procedure was used effectively. The model of the cation exchange process was built using an artificial neural network (ANN). The acid mine drainage waste’s Cu(II) ion was removed using Indion 730 cation exchange resin. Experimental data from 252 cycles were recorded. In a column study, 252 experimental observations validated the...
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QUASI-DISTRIBUTED NETWORK OF LOW-COHERENCE FIBER-OPTIC FABRY-PÉROT SENSORS WITH CAVITY LENGTH-BASED ADDRESSING
PublikacjaDistributed measurement often relies on sensor networks. In this paper, we present the construction of low coherent fiber-optic Fabry-Pérot sensors connected into a quasi-distributed network. We discuss the mechanism of spectrum modulation in this type of sensor and the constraints of assembly of such sensors in the network. Particular attention was paid to separate the signals from individual sensors, which can be achieved by...
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The possibility of estimating the height of the ionospheric inhomogeneities based on TEC variations maps obtained from dense GPS network
PublikacjaA state of the ionosphere can be effectively studied using electromagnetic signals received from global navigation satellite systems (GNSS). Utilization of the dual frequency observations allows estimating values of the total electron content (TEC). They can be used for a number of scientific studies such as detection and monitoring of traveling ionospheric disturbances or plasma bubbles. Moreover, maps of TEC variations allow...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublikacjaDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Contact force network evolution in active earth pressure state of granular materials: photo‑elastic tests and DEM
PublikacjaArtykuł omawia ewolucję sieci sił kontaktowych w materiałach granulowanych podczas quasi-statycznego stanu aktywnego. Doświadczenia foto sprężyste zostały wykonane dla kulek szklanych. Doświadczenia zostały symulowane stosując metodę elementów dyskretnych (DEM). Model DEM prawidłowo przewidział strukturę sił kontaktowych i ich wielkość, lokalizację odkształceń oraz obszary zmian fazowych.
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A robust optimization model for affine/quadratic flow thinning: A traffic protection mechanism for networks with variable link capacity
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Application of neural networks for identification of forcedness having effect on magnitude of turbine rotor vibration using rotor trajectory.
PublikacjaW pracy dokonano analizy zastosowania sieci neuronowych do wyznaczenia wartości wymuszeń wpływających na wielkość drgań wirnika używając trajektorii jako parametr określający drgania. Badania przeprowadzono na powietrznej, jednostopniowej turbinie modelowej. Przemieszczenia poziome i pionowe wirnika turbiny mierzono przy pomocy systemu pomiarowego i rejestrowano na oscyloskopie cyfrowym. Przeprowadzono pomiary trajektorii ruchu...
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Modelling relation between oxidation resistance and tribological properties of non-toxic lubricants with the use of artificial neural networks
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Frequency-Variant Double-Zero Single-Pole Reactive Coupling Networks for Coupled-Resonator Microwave Bandpass Filters
PublikacjaIn this work, a family of frequency-variant reactive coupling (FVRC) networks is introduced and discussed as new building blocks for the synthesis of coupled-resonator bandpass filters with real or complex transmission zeros (TZs). The FVRC is a type of nonideal frequency-dependent inverter that has nonzero elements on the diagonal of the impedance matrix, along with a nonlinear frequency-variation profile of its transimpedance...
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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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A new approach to inter-layer sharing providing differentiated protection services in survivable IP-MPLS/WDM networks
PublikacjaArtykuł omawia zagadnienie ochrony transmisji o charakterze połączeniowym w sieciach wielowarstwowych IP-MPLS/WDM. W szczególności prezentuje nową metodę współdzielenia międzywarstwowego zasobów ścieżek zabezpieczających gwarantującą szybkie odtwarzanie uszkodzonych połączeń (nawet o 40% szybciej w porównaniu z powszechnie stosowaną metodą).
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Rearrangeable clos networks C(n,r_1,n^2-1,n,r_2) with certain restrictions for connections
PublikacjaW pracy została zaproponowana nowa metoda sprawdzania przestrajalności pól Closa dla połączeń jeden do wiele. W rozważaniach zakładamy grupowanie połączeń.In the article we will propose new method of checking rearrangeability of multicast Clos networks. In the literature there is no precise method for checking rearrangeability. We focused on three-stage Clos networks without any constraints about fan-out capability. We show the...
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Long Short-Term Memory (LSTM) neural networks in predicting fair price level in the road construction industry
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A new fuzzy model of multi-criteria decision support based on Bayesian networks for the urban areas' decarbonization planning
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INTER-LAYER SHARING OF BACKUP PATH CAPACITIES PROVIDING FAST SERVICE RECOVERY IN IP-MPLS/WDM NETWORKS
PublikacjaIn this paper, we investigate the issue of providing the transmission continuity in IP-MPLS/WDM networks in the presence of failures of nodes/links. Special focus is put on assuring fast restoration of flows affected after a failure in a scenario assuming sharing the backup path capacities in order to decrease the overall bandwidth consumption. In particular, we propose a new approach to inter-layer sharing of link capacity reserved...