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Wyniki wyszukiwania dla: GENETIC ALGORITHMS, OPTIMIZATION METHODS, MATHEMATICAL PROGRAMMING, ELECTROMAGNETIC ANALYSIS
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Application of mechanistic and data-driven models for nitrogen removal in wastewater treatment systems
PublikacjaIn this dissertation, the application of mechanistic and data-driven models in nitrogen removal systems including nitrification and deammonification processes was evaluated. In particular, the influential parameters on the activity of the Nitrospira activity were assessed using response surface methodology (RSM). Various long-term biomass washout experiments were operated in two parallel sequencing batch reactor (SBR) with a different...
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Reducing the Environmental Impact of the Public Water Transportation Systems by Parametric Design and Optimization of Vessels’ Hulls. Study of the Gdańsk’s Electric Passenger Ferry (2015-2016).
PublikacjaThe paper presents the potential and risks of utilizing Rhinoceros and Grasshopper software for parametric design and multi-varietal optimization of the hull of a small sustainable ferry. The sustainability criteria, parametric design flowchart and optimizing methods are described. As the result, the advantages and disadvantages of this approach obtained in the research-by-design process conducted by an intercollegiate team at...
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The new investing effectiveness evaluation multi-criteria method in modern supply systems
PublikacjaThe important problem in the processes of modelling and programming the development of sustainable energy sector is the multi-criteria manner of assessing the effectiveness of investments. The goal of this paper is to show how to take into account the impact of investments in multidimensional modelling decision-making processes. This goal can be achieved through the development, presentation, and use of a new multi-criteria method...
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A Novel Approach to Fully Nonlinear Mathematical Modeling of Tectonic Plates
PublikacjaThe motion of the Earth's layers due to internal pressures is simulated in this research with an efficient mathematical model. The Earth, which revolves around its axis of rotation and is under internal pressure, will change the shape and displacement of the internal layers and tectonic plates. Applied mathematical models are based on a new approach to shell theory involving both two and three-dimensional approaches. It is the...
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublikacjaThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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Model Order Reduction for Problems With Dispersive Surface Boundary Conditions
PublikacjaThis letter proposes a new scheme for reduced-order finite-element modeling of electromagnetic structures with nonlinear, dispersive surface boundary conditions, which optimally exploits the numerically stable and efficient MOR framework for second-order systems provided by SAPOR method. The presented results of numerical experiments for an example of a waveguide filter demonstrate the superior accuracy of the resulting reduced models...
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Reliable Greedy Multipoint Model-Order Reduction Techniques for Finite-Element Analysis
PublikacjaA new greedy multipoint model-order reduction algorithm for fast frequency-domain finite-element method simulations of electromagnetic problems is proposed. The location of the expansion points and the size of the projection basis are determined based on a rigorous error estimator. Compared to previous multipoint methods, the quality of the error estimator is significantly improved by ensuring the orthogonality of the projection...
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Impact of optimization of ALS point cloud on classification
PublikacjaAirborne laser scanning (ALS) is one of the LIDAR technologies (Light Detection and Ranging). It provides information about the terrain in form of a point cloud. During measurement is acquired: spatial data (object’s coordinates X, Y, Z) and collateral data such as intensity of reflected signal. The obtained point cloud is typically applied for generating a digital terrain model (DTM) and a digital surface model (DSM). For DTM...
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Mixed integer nonlinear optimization of biological processes in wastewater sequencing batch reactor
PublikacjaWastewater treatment plays a key role for humanity. The waste entering lakes, rivers, and seas deteriorates daily quality of life. Therefore, it is very important to improve the efficiency of wastewater treatment. From a control point of view, a biological wastewater treatment plant is a complex, non-linear, multidimensional, hybrid control system. The paper presents the design of the optimizing hierarchical control system applied...
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Enhancing rheological muscle models with stochastic processes
PublikacjaPurpose: Biological musculoskeletal systems operate under variable conditions. Muscle stiffness, activation signals, and loads change during each movement. The presence of noise and different harmonic components in force production significantly influences the behaviour of the muscular system. Therefore, it is essential to consider these factors in numerical simulations. Methods: This study aims to develop a rheological mathematical...
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Software for calculation of noise maps implemented on the supercomputer
PublikacjaThis paper presents investigation results relevant to the implementation of the algorithms for the calculation of noise maps. The aim of the implementation of the algorithms on the computer cluster is explained. Selected implementation details of the software called the noise propagation model are described. The interaction of the software with the data acquisition system is presented. Noise maps obtained by exploitation of the...
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Service Recommendation on WIKI-WS Platform
PublikacjaThe article presents the issues of recaommendation services for users. The commonly used solutions include known classes of recommendation systems and information about their area of use and the most frequently used algorithms. the issue of choosing the services has been described based on the Wiki-WS platform including a model of cooperation with the recommendation system. The conclusion from the analysis of the proposed model...
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublikacjaThe importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such...
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Optimization algorithm and filtration using the adaptive TIN model at the stage of initial processing of the ALS point cloud
PublikacjaAirborne laser scanning (ALS) provides survey results in the form of a point cloud. The ALS point cloud is a source of data used primarily for constructing a digital terrain model (DTM). To generate a DTM, the set of ALS observations must be first subjected to the point cloud processing methodology. A standard methodology is composed of the following stages: acquisition of the ALS data, initial processing (including filtration),...
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CLASSIFICATION OF RESTRAINTS IN THE OPTIMIZATION PROBLEM OF A COLD-FORMED PROFILE
PublikacjaThis work describes the restraints in the optimization problem. This is an important and complicated issue because it requires taking into account a vast range of information related to the design and production. In order to describe the relations of a specific optimization problem, it is essential to adopt appropriate criteria and to collect information on all kinds of restraints, i.e. boundary conditions. The following paper...
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Model-based testing for execution algorithms in the simulation of cyber-physical systems
PublikacjaThe understanding of simulation semantics of a hybrid system is a challenge for computational engineers as it requires expertise in computer science, engineering, numerical methods, and mathematics at once. The testing methods for the execution of a simulation are being researched but not yet applied on the industrial level. Consequently, the semantics of the simulation becomes a critical artifact in the system development process....
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Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublikacjaThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...
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Impact of Visual Image Quality on Lymphocyte Detection Using YOLOv5 and RetinaNet Algorithms
PublikacjaLymphocytes, a type of leukocytes, play a vital role in the immune system. The precise quantification, spatial arrangement and phenotypic characterization of lymphocytes within haematological or histopathological images can serve as a diagnostic indicator of a particular lesion. Artificial neural networks, employed for the detection of lymphocytes, not only can provide support to the work of histopathologists but also enable better...
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The Experimental Determination of Bearings Dynamic Coefficients in a Wide Range of Rotational Speeds, Taking into Account the Resonance and Hydrodynamic Instability
PublikacjaMethods for the experimental determination of dynamic coefficients are commonly used for the analysis of various types of bearings, including hydrodynamic, aerodynamic and foil bearings. There are currently several algorithms that allow estimating bearing dynamic coefficients. Such algorithms usually use various excitation techniques applied to rotor–bearings systems. So far only a small number of scientific publications show how...
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Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublikacjaIn recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have gained significant attention due to their exceptional properties, including lightweight construction, high specific strength, and stiffness. These attributes have found application in structures, infrastructures, wind power equipment, and various advanced civil products. However, the production process and the extensive testing required for...
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Loss Minimization-Based Sensorless Control of High-Speed Induction Motor Considering Core Loss
PublikacjaThis paper presents loss-minimizing sensorless control (LMC) strategies utilized to optimize the energy of high-speed induction motor (HSIM) drives. A machine’s ability to operate effectively depends on the estimation of its electrical losses. Although copper losses account for the majority of electrical losses in electrical machines, core loss also contributes a major part, particularly in high-speed induction motors. A review...
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Constructing a map of an anonymous graph: applications of universal sequences
PublikacjaWe study the problem of mapping an unknown environmentrepresented as an unlabelled undirected graph. A robot (or automaton)starting at a single vertex of the graph G has to traverse the graph and return to its starting point building a map of the graph in the process. We are interested in the cost of achieving this task (whenever possible) in terms of the number of edge traversal made by the robot. Another optimization criteria...
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Harmony Search for Self-configuration of Fault–Tolerant and Intelligent Grids
PublikacjaIn this paper, harmony search algorithms have been proposed to self-configuration of fault-tolerant grids for big data processing. Self-configuration of computer grids lies in the fact that new computer nodes are automatically configured by software agents and then integrated into the grid. A base node works due to several configuration parameters that define some aspects of data communications and energy power consumption. We...
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New method of IEEE 802.15.4a UWB Impulse Radio Spectrum Shaping
PublikacjaThis paper presents a new technique of IEEE 802.15.4a ultra-wideband signal spectrum control, based on changes in sequences of transmitted pulses with very short duration time. Basic parameters of UWB signal and outline of proposed spectrum shaping methods are briefly described. The main part of the paper presents influence of signal and algorithms parameters on the results of spectrum shaping.
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SIMPLIFIED MODELING OF STRESS AND DEFLECTION LIMIT STATES OF UNDERGROUND TANKS
PublikacjaFuel tanks are designed with regard to standard actions and operating conditions. The work analyses the impact of corrosion and other means to variation of stresses and deformation of a horizontal underground tank shell. The computations are preliminary. Due to the long computational time of the entire tank the analysis is restricted to its part only. The full analysis is bound to assess structural reliability, further allowing...
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Green energy extraction for sustainable development: A novel MPPT technique for hybrid PV-TEG system
PublikacjaThe Photovoltaic (PV) module converts only a small portion of irradiance into electrical energy. Most of the solar energy is wasted as heat, resulting in a rise in PV cell temperature and a decrease in solar cell efficiency. One way to harvest this freely available solar thermal energy and improve PV cell efficiency is by integrating PV systems with thermoelectric generators (TEG). This cogeneration approach of the hybrid PV-TEG...
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Design centering of compact microwave components using response features and trust regions
PublikacjaFabrication tolerances, as well as uncertainties of other kinds, e.g., concerning material parameters or operating conditions, are detrimental to the performance of microwave circuits. Mitigating their impact requires accounting for possible parameter deviations already at the design stage. This involves optimization of appropriately defined statistical figures of merit such as yield. Alt-hough important, robust (or tolerance-aware)...
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Scheduling of compatible jobs on parallel machines
PublikacjaThe dissertation discusses the problems of scheduling compatible jobs on parallel machines. Some jobs are incompatible, which is modeled as a binary relation on the set of jobs; the relation is often modeled by an incompatibility graph. We consider two models of machines. The first model, more emphasized in the thesis, is a classical model of scheduling, where each machine does one job at time. The second one is a model of p-batching...
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Rapid antenna design optimization using shape-preserving response prediction
PublikacjaAn approach to rapid optimization of antennas using the shape-preserving response-prediction (SPRP) technique and coarsediscretization electromagnetic (EM) simulations (as a low-fidelity model) is presented. SPRP allows us to estimate the response of the high-fidelity EM antenna model, e.g., its reflection coefficient versus frequency, using the properly selected set of so-called characteristic points of the low-fidelity model...
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Objective relaxation algorithm for reliable simulation-driven size reduction of antenna structure
PublikacjaThis letter investigates reliable size reduction of antennas through electromagnetic-driven optimization. It is demonstrated that conventional formulation of the design task by direct footprint miniaturization with imposing constraints on electrical performance parameters may not lead to optimum results. The reason is that—in a typical antenna structure—only a few geometry parameters explicitly determine the antenna footprint,...
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An Approach to Bass Enhancement in Portable Computers Employing Smart Virtual Bass Synthesis Algorithms
PublikacjaThe aim of this paper is to present a novel approach to the Virtual Bass Synthesis (VBS) algorithms applied to portable computers. The developed algorithms are related to intelligent, rule-based setting of synthesis parameters according to music genre of an audio excerpt and to the type of a portable device in use. To find optimum synthesis parameters of the VBS algorithms, subjective listening tests based on a parametric procedure...
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Data augmentation for improving deep learning in image classification problem
PublikacjaThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Tolerance-Aware Multi-Objective Optimization of Antennas by Means of Feature-Based Regression Surrogates
PublikacjaAssessing the immunity of antenna design to fabrication tolerances is an important consideration, especially when the manufacturing process has not been predetermined. At the same time, the antenna parameter tuning should be oriented toward improving the performance figures pertinent to both electrical (e.g., input matching) and field properties (e.g., axial ratio bandwidth) as much as possible. Identification of available trade-offs...
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Rapid Multi-Criterial Antenna Optimization by Means of Pareto Front Triangulation and Interpolative Design Predictors
PublikacjaModern antenna systems are designed to meet stringent performance requirements pertinent to both their electrical and field properties. The objectives typically stay in conflict with each other. As the simultaneous improvement of all performance parameters is rarely possible, compromise solutions have to be sought. The most comprehensive information about available design trade-offs can be obtained through multi-objective optimization...
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Wielokryterialna analiza porównawcza lokalizacji źródeł wytwórczych energii elektrycznej
PublikacjaArtykuł przedstawia ranking lokalizacji czterech źródeł wytwórczych energii elektrycznej: biogazowni rolniczej, biogazowni utylizacyjnej oraz dwóch elektrowni fotowoltaicznych, wykonany przy użyciu połączonych metod Analitycznego Procesu Hierarchicznego (AHP) oraz taksonomii numerycznej. Omówiono zalety połączenia metod, przedstawiono przykład zastosowania oraz wskazano kryteria o największym i najmniejszym wpływie na realizację...
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Utilization of a Non-Linear Error Function in a Positioning Algorithm for Distance Measurement Systems Designed for Indoor Environments
PublikacjaA new positioning algorithm for distance measurement systems is outlined herein. This algorithm utilizes a non-linear error function which allows us to improve the positioning accuracy in highly difficult indoor environments. The non-linear error function also allows us to adjust the performance of the algorithm to the particular environmental conditions. The well-known positioning algorithms have limitations, mentioned by their...
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublikacjaPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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Experimentally feasible semi-device-independent certification of four-outcome positive-operator-valued measurements
PublikacjaRecently the quantum information science community devoted a lot of attention to the theoretical and practical aspects of generalized measurements, the formalism of all possible quantum operations leading to acquisition of classical information. On the other hand, due to imperfections present in quantum devices, and limited thrust to them, a trend of formulating quantum information tasks in a semi-device-independent manner emerged....
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Redukcja czasu analizy MZP przez ograniczenie rozmiaru rozwiązania
PublikacjaAnaliza drzew niezdatności jest uznaną metodą analizy bezpieczeństwa systemów. Notacja ECSDM pozwala definiować zależności czasowe między zdarzeniami drzewa oraz przeanalizować je w celu określenia zależności pomiędzy zdarzeniami z Minimalnych Zbiorów Przyczyn (MZP). Dzięki wprowadzeniu klasyfikacji zdarzeń z MZP można wyodrębnić zależności czasowe istotne dla zapobiegania wywoływania hazardu przez konkretny MZP. Pozostałe zależności...
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Improved method for real-time speech stretching
Publikacjan algorithm for real-time speech stretching is presented. It was designed to modify input signal dependently on its content and on its relation with the historical input data. The proposed algorithm is a combination of speech signal analysis algorithms, i.e. voice, vowels/consonants, stuttering detection and SOLA (Synchronous-Overlap-and-Add) based speech stretching algorithm. This approach enables stretching input speech signal...
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Optimization of Nuclear Power Share in the Structure of Electricity Production in Poland in Time Perspective by 2060
PublikacjaThe author of this paper presented the results of a system analysis using MARKAL model, aiming at the optimization of nuclear power share in power generation structure in Poland in time perspective by 2060. Optimization criterion is the minimization of the objective function, i.e. the total cost of energy system, taking into account constraints related to CO2, SOx and NOx emissions and obligatory shares of electricity from renewable...
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Influence of accelerometer signal pre-processing and classification method on human activity recognition
PublikacjaA study of data pre-processing influence on accelerometer-based human activity recognition algorithms is presented. The frequency band used to filter-out the accelerometer signals and the number of accelerometers involved were considered in terms of their influence on the recognition accuracy. In the test four methods of classification were used: support vector machine, decision trees, neural network, k-nearest neighbor.
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Capillary gas chromatography using a -cyclodextrin forenantiomeric separation of methylamphetamine, its precursors andchloro intermediates after optimization of the derivatization reaction
PublikacjatThe enantiomeric ratio of methylamphetamine (MAMP) is closely related to the optical activity of precur-sors and reagents used for the synthesis and this knowledge can provide useful information concerningthe origins and synthetic methods used for illicit manufacture. The information can be utilized for reg-ulation of the precursors and investigation of the manufacturing sources but this requires analyticalprocedures to determine...
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Mathematical modelling: Lessons from composite indicators
PublikacjaWe discuss here composite indicators as mathematical models, which can be looked at through the lenses of the five rules discussed in this volume. Composite indicators sit between analysis and advocacy, and their use has social and political implications. For this reason, the lenses of the manifesto can be used to build them better, to make them more transparent, as well as to inspect incumbent indicators for methodological or...
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A piece of corporate finance
PublikacjaThe handbook presents the subject of financial liquidity and CVP analysis. The handbook uses different types of information: definitions of the issues; “real life” examples illustrating a given theoretical issue in practice; mathematical formulas necessary to calculate a certain value; types of method used. In addition to traditional resources such as drawings, diagrams, tables and photos, the handbook also includes resources of...
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Machine learning applied to acoustic-based road traffic monitoring
PublikacjaThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Machine learning applied to acoustic-based road traffic monitoring
PublikacjaThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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On Fast Multi-objective Optimization of Antenna Structures Using Pareto Front Triangulation and Inverse Surrogates
PublikacjaDesign of contemporary antenna systems is a challenging endeavor, where conceptual developments and initial parametric studies, interleaved with topology evolution, are followed by a meticulous adjustment of the structure dimensions. The latter is necessary to boost the antenna performance as much as possible, and often requires handling several and often conflicting objectives, pertinent to both electrical and field properties...
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Problems with microprocessor voltage-to-frequency and frequency-to-voltage converters implementation
PublikacjaThe article presents the problems of digital voltage-to-frequency and frequency-to-voltage processing. Transducer systems implemented in microprocessor technology are presented, the timing of signals and functioning algorithms are discussed. An analysis of processing errors has been performed and the results of experimental studies of realized systems are presented.
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Performance Evaluation of Preemption Algorithms in MPLS Networks
PublikacjaPreemption is a traffic engineering technique in Multiprotocol Switching Networks that enables creation of high priority paths when there is not enough free bandwidth left on the route. Challenging part of any preemption method is to select the best set of paths for removal. Several heuristic methods are available but no wider comparison had been published before. In this paper, we discuss the dilemmas in implementing preemption...