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Wyniki wyszukiwania dla: ADAPTIVE PROJECT MANAGEMENT
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Multistage generalized adaptive notch filter with improved accuracy
PublikacjaGeneralized adaptive notch filters (GANFs) are estimators of coefficients of quasi-periodically time-varying systems. Current state of the art GANFs can deliver highly accurate estimates of system variations’ frequency, but underperform in terms of accuracy of the coefficient estimates. The paper proposes a novel multistage GANF with accuracy improved in this aspect. The processing pipeline consists of three stages. The preliminary...
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Automatic Optimization Of Adaptive Notch Filter’s Frequency Tracking
PublikacjaEstimation of instantaneous frequency of narrowband com- plex sinusoids is often performed using lightweight algo- rithms called adaptive notch filters. However, to reach high performance, these algorithms require careful tuning. The paper proposes a novel self-tuning layer for a recently intr o- ducedadaptive notch filtering algorithm. Analysis shows th at, under Gaussian random-walk type assumptions, the resultin g solution converges...
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Adaptive Optimal Discrete-Time Output-Feedback Using an Internal Model Principle and Adaptive Dynamic Programming
PublikacjaIn order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming (ADP) technique based on the internal model principle (IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback, merely the measurement of input and output data. More specifically, based on the IMP, the output control problem can first be converted into a stabilization...
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On adaptive selection of estimation bandwidth for analysis of locally stationary multivariate processes
PublikacjaWhen estimating the correlation/spectral structure of a locally stationary process, one should choose the so-called estimation bandwidth, related to the effective width of the local analysis window. The choice should comply with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive estimation variance. The paper presents a novel method...
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ADAPTIVE IDENTIFICATION OF TIME-VARYING IMPULSE RESPONSE OF UNDERWATER ACOUSTIC COMMUNICATION CHANNEL
PublikacjaThe transmission properties of underwater acoustic communication channel can change dynamically due to the movement of acoustic system transmitter and receiver or underwater objects reflecting transmitted signal. The time-varying impulse response measurement and estimation are necessary to match the physical layer of data transmission to instantaneous channel propagation conditions. Using the correlative measurement method, impulse...
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Adaptive Hounsfield Scale Windowing in Computed Tomography Liver Segmentation
PublikacjaIn computed tomography (CT) imaging, the Hounsfield Unit (HU) scale quantifies radiodensity, but its nonlinear nature across organs and lesions complicates machine learning analysis. This paper introduces an automated method for adaptive HU scale windowing in deep learning-based CT liver segmentation. We propose a new neural network layer that optimizes HU scale window parameters during training. Experiments on the Liver Tumor...
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Power System Stabilizer as a Part of a Generator MPC Adaptive Predictive Control System
PublikacjaIn this paper, a model predictive controller based on a generator model for prediction purposes is proposed to replace a standard generator controller with a stabilizer of a power system. Such a local controller utilizes an input-output model of the system taking into consideration not only a generator voltage Ug but also an additional, auxiliary signal (e.g., α, Pg, or ωg). This additional piece of information allows for taking...
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Bi-GRU-APSO: Bi-Directional Gated Recurrent Unit with Adaptive Particle Swarm Optimization Algorithm for Sales Forecasting in Multi-Channel Retail
PublikacjaIn the present scenario, retail sales forecasting has a great significance in E-commerce companies. The precise retail sales forecasting enhances the business decision making, storage management, and product sales. Inaccurate retail sales forecasting can decrease customer satisfaction, inventory shortages, product backlog, and unsatisfied customer demands. In order to obtain a better retail sales forecasting, deep learning models...
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Computational Simulation of the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis chapter investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organisational culture results in better mistake management and thus better organisational learning, (2) Effective organisational 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...
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Multiresolution analysis and adaptive estimation on a sphere using stereographic wavelets
PublikacjaWe construct an adaptive estimator of a density function on d dimensional unit sphere Sd (d ≥ 2), using a new type of spherical frames. The frames, or as we call them, stereografic wavelets are obtained by transforming a wavelet system, namely Daubechies, using some stereographic operators. We prove that our estimator achieves an optimal rate of convergence on some Besov type class of functions by adapting to unknown smoothness....
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AUTOMATIC OPTIMIZATION OF ADAPTIVE NOTCH FILTER’S FREQUEN CY TRACKING
PublikacjaEstimation of instantaneous frequency of narrowband com- plex sinusoids is often performed using lightweight algo- rithms called adaptive notch filters. However, to reach high performance, these algorithms require careful tuning. The paper proposes a novel self-tuning layer for a recently intr o- ducedadaptive notch filtering algorithm. Analysis shows th at, under Gaussian random-walk type assumptions, the resultin g solution converges...
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A New Adaptive Method for the Extraction of Steel Design Structures from an Integrated Point Cloud
PublikacjaThe continuous and intensive development of measurement technologies for reality modelling with appropriate data processing algorithms is currently being observed. The most popular methods include remote sensing techniques based on reflected-light digital cameras, and on active methods in which the device emits a beam. This research paper presents the process of data integration from terrestrial laser scanning (TLS) and image data...
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Konzepte zur Energieeffizienzsteigerung bei Internet-Zugangsgeräten
PublikacjaThe key issue of this paper is the power management of Internet access devices. The paper commences with an outline on the energy consumption of today's IT devices. It is followed by a description of options to increase energy efficiency of computers. The paper proves that in practice network cards and other IT network components, such as modems, network access points, switches and routers have the maximum energy consumption -...
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Core loss resistance impact on sensorless speed control of an induction motor using hybrid adaptive sliding mode observer
PublikacjaInduction motors (IMs) experience power losses when a portion of the input power is converted to heat instead of driving the load. The combined effect of copper losses, core losses, and mechanical losses results in IM power losses. Unfortunately, the core losses in the motor, which have a considerable impact on its energy efficiency, are not taken into account by the generally employed dynamic model in the majority of the studies. Due...
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Novel adaptive flux observer for wide speed range sensorless control of induction motor
PublikacjaA new adaptive flux observer of induction motor is presented in the paper. The Lyapunov theory is utilized for derivation of the adaptation law of rotor flux angular speed, which acts as unknown parameter in an augmented induction motor model. In the field weakening region, where stray fluxes are comparable with rotor flux magnitude, the air-gap flux stabilization is proposed. An air-gap flux multiscalar model is derived for stator...
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Adaptive prediction of stock exchange indices by state space wavelet networks
PublikacjaThe paper considers the forecasting of the Warsaw Stock Exchange price index WIG20 by applying a state space wavelet network model of the index price. The approach can be applied to the development of tools for predicting changes of other economic indicators, especially stock exchange indices. The paper presents a general state space wavelet network model and the underlying principles. The model is applied to produce one session...
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Estimation of Housing Demand with Adaptive Neuro-Fuzzy Inference Systems (ANFIS)
PublikacjaIt has always been important to anticipate the demand for a product. To determine the demand for any product, the parameters such as the economic situation and the demands of the rival products are used generally. Especially in the housing sector, which is the locomotive sector for emerging countries, it is critical to anticipate housing demand and its relationship with economic variables. Because of that, economists, real estate...
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Niezgodność przekonań i działań menedżerów wobec pracowników w wieku 55+
PublikacjaArtykuł dotyczy problematyki postaw i działań menadżerów wobec pracowników w wieku 55+. W literaturze dotyczącej zarządzania wiekiem przytaczane są wyniki badań na temat cech charakteryzujących starszych pracowników. Porównuje się je czasami z cechami przypisywanymi pracownikom młodym. Cel prezentowanych w artykule badań sformułowany został nieco inaczej i dotyczył zweryfikowania zbieżności zalet przypisywanych starszym pracownikom...
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Model-Based Adaptive Machine Learning Approach in Concrete Mix Design
PublikacjaConcrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...
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Locally Adaptive Cooperative Kalman Smoothing and Its Application to Identification of Nonstationary Stochastic Systems
PublikacjaOne of the central problems of the stochastic approximation theory is the proper adjustment of the smoothing algorithm to the unknown, and possibly time-varying, rate and mode of variation of the estimated signals/parameters. In this paper we propose a novel locally adaptive parallel estimation scheme which can be used to solve the problem of fixed-interval Kalman smoothing in the presence of model uncertainty. The proposed solution...
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An adaptive approach to non-destructive evaluation (NDE) of cast irons containing precipitated graphite particles with the help of magnetoacoustic emission
PublikacjaPhysical properties of cast irons strongly depend on both their microstructure and the presence of casting defects. The paper analyses the possibility of application of magnetoacoustic emission (MAE) for nondestructive detection of flawed cast iron components. The investigated samples containing dross, chunky graphite and lamellar graphite were compared with the reference, flawless, spheroidal cast iron sample. The optimisation...
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Employment of a Nonlinear Adaptive Control System for Improved Control of Dissolved Oxygen in Sequencing Batch Reactor
PublikacjaA proper control in a complex system, such as Wastewater Treatment Plant (WWTP) with each year is becoming increasingly important. High quality control can minimize an environmental impact as well as reduce operational costs of the WWTP. One of the core issues is providing adequate dissolved oxygen (DO) concetration for microorganisms used in a treatment process. An aeration process of the wastewater realised by an system consisting...
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High performance super-twisting sliding mode control for a maritime autonomous surface ship (MASS) using ADP-Based adaptive gains and time delay estimation
PublikacjaThis research addresses two kinds of problems related to optimal trajectory tracking of a Maritime Autonomous Surface Ship (MASS): those caused by the time-varying external disturbances including winds, waves and ocean currents as well as those resulting from inherent dynamical uncertainties. As the paper shows, an accurate and robust optimal controller can successfully deal with both issues. An improved Optimal Adaptive Super-Twisting...
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High performance super-twisting sliding mode control for a maritime autonomous surface ship (MASS) using ADP-Based adaptive gains and time delay estimation
PublikacjaThis research addresses two kinds of problems related to optimal trajectory tracking of a Maritime Autonomous Surface Ship (MASS): those caused by the time-varying external disturbances including winds, waves and ocean currents as well as those resulting from inherent dynamical uncertainties. As the paper shows, an accurate and robust optimal controller can successfully deal with both issues. An improved Optimal Adaptive Super-Twisting...
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How can Systems Thinking Help Us Handling the COVID-19 Crisis?
PublikacjaPurpose: COVID-19 pandemic outbreak remains one of the most influential events in the global economy over the recent years. While being primarily public health-related, it has a tremendous impact on many other aspects, such as public transport, education, and business management. Many businesses were forced to introduce rapid changes to their business models in order to survive. The aim of this paper is to show the complexity and...
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Frequency Guided Generalized Adaptive Notch Filtering - Tracking Analysis and Optimization
PublikacjaGeneralized adaptive notch filters (GANFs) are estimators of coefficients of quasi-periodically time-varying systems, encountered e.g., in RF applications when Doppler effect takes place. Current state of the art GANFs can deliver highly accurate estimates of system variations’ frequency, but underperform in terms of accuracy of system coefficient estimates. The paper proposes a novel multistage GANF with improved coefficient...
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Various cases of preservation and adaptive reuse Heritage Buildings in the Port of Gdynia
PublikacjaThe port of Gdynia contains a diverse range of heritage assets, starting with its spatial layout which is an urban concept designed in the first half of the 1920s. It is important to point out, this historically-shaped harbor space is preserved in its general idea and still functioning in port activities. Another significant element is the structural, technological solution which was the basis for constructing the entire port area...
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Digital Innovations and Smart Solutions for Society And Economy: Pros and Cons
PublikacjaRecent developments in artificial intelligence (AI) may involve significant potential threats to personal data privacy, national security, and social and economic stability. AI-based solutions are often promoted as “intelligent” or “smart” because they are autonomous in optimizing various processes. Be-cause they can modify their behavior without human supervision by analyzing data from the environ-ment, AI-based systems may be...
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Expedited Design Closure of Antennas By Means Of Trust-Region-Based Adaptive Response Scaling
PublikacjaIn the letter, a reliable procedure for expedited design optimization of antenna structures by means of trust-region adaptive response scaling (TR-ARS) is proposed. The presented approach exploits two-level electromagnetic (EM) simulation models. A predicted high-fidelity model response is obtained by applying nonlinear frequency and amplitude correction to the low-fidelity model. The surrogate created this way is iteratively rebuilt...
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SYNTHESIZING MEDICAL TERMS – QUALITY AND NATURALNESS OF THE DEEP TEXT-TO-SPEECH ALGORITHM
PublikacjaThe main purpose of this study is to develop a deep text-to-speech (TTS) algorithm designated for an embedded system device. First, a critical literature review of state-of-the-art speech synthesis deep models is provided. The algorithm implementation covers both hardware and algorithmic solutions. The algorithm is designed for use with the Raspberry Pi 4 board. 80 synthesized sentences were prepared based on medical and everyday...
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efficient fractional delay hilbert transform filter in the farrow structure
PublikacjaIn this paper the design and application of a Fractional Delay Hilbert Transform Filter (FDHTF) into an adaptive sub-sample delay estimation between two separated sinusoidal signals is considered. The FDHTF incorporates the functions of Hilbertian and variable fractional delay filtering of the incoming signal simultaneously, in one stage. In traditional approach each of these operations was performed separately. Obtained value...
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Application of artificial intelligence into/for control of flexible manufacturing cell
PublikacjaThe application of artificial intelligence in technological processes control is usually limited. One problem is how to respond to changes in the environment of manufacturing system. A way to overcome the above shortcoming is to use fuzzy logic for representation of the inexact information. In this paper fundamentals of artificial intelligence and fuzzy logic are introduced from a theoretical point of view. Still more the fuzzy...
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Indirect adaptive controller based on a self-structuring fuzzy system for nonlinear modeling and control
PublikacjaIn this paper, a unified nonlinear modeling and control scheme is presented. A self-structuring Takagi-Sugeno (T-S) fuzzymodel is used to approximate the unknown nonlinear plant based on I/O data collected on-line. Both the structure and theparameters of the T-S fuzzy model are updated by an on-line clustering method and a recursive least squares estimation(RLSE) algorithm. The rules of the fuzzy model can be added, replaced or...
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Self-optimizing generalized adaptive notch filters - comparison of three optimization strategies
PublikacjaThe paper provides comparison of three different approaches to on-line tuning of generalized adaptive notch filters (GANFs) the algorithms used for identification/tracking of quasi-periodically varying dynamic systems. Tuning is needed to adjust adaptation gains, which control tracking performance of ANF algorithms, to the unknown and/or time time-varying rate of system nonstationarity. Two out ofthree compared approaches are classical...
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Compact global association based adaptive routing framework for personnel behavior understanding
PublikacjaPersonnel behavior understanding under complex scenarios is a challenging task for computer vision. This paper proposes a novel Compact model, which we refer to as CGARPN that incorporates with Global Association relevance and Adaptive Routing Pose estimation Network. Our framework firstly introduces CGAN backbone to facilitate the feature representation by compressing the kernel parameter space compared with typical algorithms,...
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Stable indirect adaptive control based on discrete-time T-S fuzzy model
PublikacjaThis paper presents an indirect adaptive fuzzy control scheme for uncertain nonlinear asymptotically stable plants.A discrete-time T-S fuzzy input-output model is employed to approximate the unknown plant dynamics. The T-S fuzzy model is fed with its own states, which are indeed its past outputs, rather than the measurements from the plants. Entirely based on this model, a feedback linearization control law is designed by using...
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Stable indirect adaptive control based on discrete-time T-S fuzzy model
PublikacjaThis paper presents an indirect adaptive fuzzy control scheme for uncertain nonlinear asymptotically stable plants.A discrete-time T-S fuzzy input-output model is employed to approximate the unknown plant dynamics. The T-S fuzzy model is fed with its own states, which are indeed its past outputs, rather than the measurements from the plants. Entirely based on this model, a feedback linearization control law is designed by using...
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EM‐driven constrained miniaturization of antennas using adaptive in‐band reflection acceptance threshold
PublikacjaNumerical optimization of geometry parameters is a critical stage of the design process of compact antennas. It is also challenging because size reduction is constrained by the necessity of fulfilling imposed electrical performance requirements. Furthermore, full‐wave electromagnetic (EM) analysis needs to be used for reliable performance evaluation of the antenna structure, which is computationally expensive. In this paper, an...
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Rapid Microwave Design Optimization in Frequency Domain Using Adaptive Response Scaling
PublikacjaIn this paper, a novel methodology for cost-efficient microwave design optimization in the frequency domain is proposed. Our technique, referred to as adaptive response scaling (ARS), has been developed for constructing a fast replacement model (surrogate) of the high-fidelity electromagnetic-simulated model of the microwave structure under design using its equivalent circuit (low-fidelity model). The basic principle of ARS is...
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Two-Step Model Based Adaptive Controller for Dissolved Oxygen Control in Sequencing Wastewater Batch Reactor
PublikacjaDissolved Oxygen (DO) concentration is a crucial parameter for efficient operation of biological processes taking place in the activated sludge Wastewater Treatment Plant (WWTP). High-quality DO control is difficult to achieve because of complex nonlinear behavior of the plant and substantial influent disturbances. A method to improve the Direct Model Reference Adaptive Control (DMRAC) technology in application to DO tracking for...
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Designing a ship course controller by applying the adaptivebackstepping method
PublikacjaThe article discusses the problem of designing a proper and efficient adaptive course-keeping control system for a seagoingship based on the adaptive backstepping method. The proposed controller in the design stage takes into account thedynamic properties of the steering gear and the full nonlinear static maneuvering characteristic. The adjustable parametersof the achieved nonlinear control structure were tuned up by using the...
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The adaptive spatio-temporal clustering method in classifying direct labor costs for the manufacturing industry
PublikacjaEmployee productivity is critical to the profitability of not only the manufacturing industry. By capturing employee locations using recent advanced tracking devices, one can analyze and evaluate the time spent during a workday of each individual. However, over time, the quantity of the collected data becomes a burden, and decreases the capabilities of efficient classification of direct labor costs. However, the results obtained...
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ADAPTIVE METHOD FOR THE SOLUTION OF 1D AND 2D ADVECTION-DIFFUSION EQUATIONS USED IN ENVIRONMENTAL ENGINEERING
PublikacjaThe paper concerns the numerical solution of one-dimensional (1D) and two-dimensional (2D) advection-diffusion equations. For the numerical solution of the 1D advection-diffusion equation a method, originally proposed for solution of the 1D pure advection equation, has been developed. A modified equation analysis carried out for the proposed method allowed increasing of the resulting solution accuracy and consequently, to reduce...
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Dynamically positioned ship steering making use of backstepping method and artificial neural networks
PublikacjaThe article discusses the issue of designing a dynamic ship positioning system making use of the adaptive vectorial backstepping method and RBF type arti cial neural networks. In the article, the backstepping controller is used to determine control laws and neural network weight adaptation laws. e arti cial neural network is applied at each time instant to approximate nonlinear functions containing parametric uncertainties....
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Identification of quasi-periodically varying systems with quasi-linear frequency changes
PublikacjaThe problem of identification of linear quasi-periodically varying systems is considered. This problem can be solved using generalized adaptive notch filtering (GANF) algorithms. It is shown that accuracy of system parameter estimation can be increased if the results obtained from GANF are further processed using a cascade of appropriately designed filters. The resulting generalized adaptive notch smoothing (GANS) algorithms can...
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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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An Adaptive Network Model for a Double Bias Perspective on Learning from Mistakes within Organizations
PublikacjaAlthough making mistakes is a crucial part of learning, it is still often being avoided in companies as it is considered as a shameful incident. This goes hand in hand with a mindset of a boss who dominantly believes that mistakes usually have negative consequences and therefore avoids them by only accepting simple tasks. Thus, there is no mechanism to learn from mistakes. Employees working for and being influenced by such a boss...
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An optimized dissolved oxygen concentration control in SBR with the use of adaptive and predictive control schemes
PublikacjaThis paper addresses the problem of optimizing control of the aeration process in a water resource recovery facility (WRRF) using sequencing batch reactor (SBR), one that affects the efficiency of wastewater treatment by stimulating metabolic reactions of microorganisms through dissolved oxygen (DO) level control, and accounts for the predominant part of operating costs. Two independent approaches to DO control algorithm design...
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Application of autoencoder to traffic noise analysis
PublikacjaThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
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Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning
PublikacjaThe Lombard effect is a phenomenon that results in speech intelligibility improvement when applied to noise. There are many distinctive features of Lombard speech that were recalled in this dissertation. This work proposes the creation of a system capable of improving speech quality and intelligibility in real-time measured by objective metrics and subjective tests. This system consists of three main components: speech type detection,...