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Search results for: ADAPTIVE ALGORITHM
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Hybrid SONIC: joint feedforward–feedback narrowband interference canceler
PublicationSONIC (self-optimizing narrowband interference canceler) is an acronym of a recently proposed active noise control algorithm with interesting adaptivity and robustness properties. SONIC is a purely feedback controller, capable of rejecting nonstationary sinusoidal disturbances (with time-varying amplitude and/or frequency) in the presence of plant (secondary path) uncertainty. We show that although SONIC can work reliably without...
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Ripple oscillations in the left temporal neocortex are associated with impaired verbal episodic memory encoding
PublicationBACKGROUND: We sought to determine if ripple oscillations (80-120 Hz), detected in intracranial electroencephalogram (iEEG) recordings of patients with epilepsy, correlate with an enhancement or disruption of verbal episodic memory encoding. METHODS: We defined ripple and spike events in depth iEEG recordings during list learning in 107 patients with focal epilepsy. We used logistic regression models (LRMs) to investigate the...
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Medley filters - simple tools for efficient signal smoothing
PublicationMedley filters are defined as convex combinations of elementary smoothing filters (averaging, median) with different smoothing bandwidths. It is shown that when adaptive weights of such a mixture are evaluated using the recently proposed Bayesian rules, one obtains a tool which often outperforms the state-of-the-art wavelet-based smoothing algorithms. Additionally, unlike wavelet-based procedures, medley filters can easily cope...
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On bidirectional preestimates and their application to identification of fast time-varying systems
PublicationWhen applied to the identification of time-varying systems, such as rapidly fading telecommunication channels, adaptive estimation algorithms built on the local basis function (LBF) principle yield excellent tracking performance but are computationally demanding. The subsequently proposed fast LBF (fLBF) algorithms, based on the preestimation principle, allow a substantial reduction in complexity without significant performance...
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Parallel frequency tracking with built-in performance evaluation
PublicationThe problem of estimation of instantaneous frequency of a nonstationary complex sinusoid (cisoid) buried in wideband noise is considered. The proposed approach employs a bank of adaptive notch filters, extended with a nontrivial performance assessment mechanism which automatically chooses the best performing filter in the bank. Additionally, a computationally attractive method of implementing the bank is proposed. The new structure...
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Dynamic fracture of brittle shells in a space-time adaptive isogeometric phase field framework
PublicationPhase field models for fracture prediction gained popularity as the formulation does not require the specification of ad-hoc criteria and no discontinuities are inserted in the body. This work focuses on dynamic crack evolution of brittle shell structures considering large deformations. The energy contributions from in-plane and out-of-plane deformations are separately split into tensile and compressive components and the resulting...
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ANALYSIS OF IMPACT of SHIP model parameters on changes of control quality index in ship dynamic positioning system
PublicationIn this work there is presented an analysis of impact of ship model parameters on changes of control quality index in a ship dynamic positioning system designed with the use of a backstepping adaptive controller. Assessment of the impact of ship model parameters was performed on the basis of Pareto-Lorentz curves and ABC method in order to determine sets of the parameters which have either crucial, moderate or low impact on objective...
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Generalized Savitzky–Golay filters for identification of nonstationary systems
PublicationThe problem of identification of nonstationary systems using noncausal estimation schemes is consid-ered and a new class of identification algorithms, combining the basis functions approach with localestimationtechnique,isdescribed.Unliketheclassicalbasisfunctionestimationschemes,theproposedlocal basis function estimators are not used to obtain interval approximations of the parametertrajectory, but provide a sequence of point...
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QoS Resource Reservation Mechanisms for Switched Optical Networks
PublicationThe paper regards the problem of resource reservation mechanisms for Quality of Service support in switched optical networks. The authors propose modifications and extensions for resources reservation strategy algorithms with resources pools, link capacity threshold and adaptive advance reservation approach. They examine proposed solutions in Automatically Switched Optical Network with Generalized Multi-Protocol Label Switching...
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Core loss resistance impact on sensorless speed control of an induction motor using hybrid adaptive sliding mode observer
PublicationInduction 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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On adaptive covariance and spectrum estimation of locally stationary multivariate processes
PublicationWhen estimating the correlation/spectral structure of a locally stationary process, one has to make two important decisions. First, one should choose the so-called estimation bandwidth, inversely proportional to the effective width of the local analysis window, in the way that complies with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive...
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Reliable EM-driven size reduction of antenna structures by means of adaptive penalty factors
PublicationMiniaturization has become of paramount importance in the design of modern antenna systems. In particular, compact size is essential for emerging application areas such as internet of things, wearable and implantable devices, 5G technology, or medical imaging. On the other hand, reduction of physical dimensions generally has a detrimental effect on antenna performance. From the perspective of numerical optimization, miniaturization...
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New results on estimation bandwidth adaptation
PublicationThe problem of identification of a nonstationary autoregressive signal using non-causal estimation schemes is considered. Noncausal estimators can be used in applications that are not time-critical, i.e., do not require real-time processing. A new adaptive estimation bandwidth selection rule based on evaluation of pseudoprediction errors is proposed, allowing one to adjust tracking characteristics of noncausal estimators to unknown...
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Accuracy of Trajectory Tracking Based on Nonlinear Guidance Logic for Hydrographic Unmanned Surface Vessels
PublicationA new trend in recent years for hydrographic measurement in water bodies is the use of unmanned surface vehicles (USVs). In the process of navigation by USVs, it is particularly important to control position precisely on the measuring profile. Precise navigation with respect to the measuring profile avoids registration of redundant data and thus saves time and survey costs. This article addresses the issue of precise navigation...
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Local basis function estimators for identification of nonstationary systems
PublicationThe problem of identification of a nonstationary stochastic system is considered and solved using local basis function approximation of system parameter trajectories. Unlike the classical basis function approach, which yields parameter estimates in the entire analysis interval, the proposed new identification procedure is operated in a sliding window mode and provides a sequence of point (rather than interval) estimates. It is...
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Diagnostyka i identyfikacja procesu przy użyciu AdMS-PCA
PublicationArtykuł dotyczy diagnostyki i identyfikacji procesu przy użyciu adaptacyjnego, wieloskalowego rozszerzenia PCA - Adaptive Multiscale Principal Component Analysis (AdMS-PCA). Przeprowadzona została analiza własności AdMS-PCA istotnych dla diagnostyki i identyfikacji. Zauważono wadę części adaptacyjnej metody, która ogranicza jej praktyczne zastosowanie. Zaproponowano modyfikację poprzez wprowadzenie algorytmu nadzorującego adaptację....
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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
PublicationPhysical 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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Automotive Validation Functions for On-line Test Evaluation of Hybrid Real-time Systems
PublicationThe aim of this paper is to present the means of black-box on-line test evaluation for hybrid real-time systems. The described procedures can be used for the model-based testing process so as to improve its effectiveness. In particular, intelligent automotive validation functions are considered, which are divided into different types depending on the nature of the evaluated issue. All provided definitions are specified on the meta-model...
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Elimination of Impulsive Disturbances From Stereo Audio Recordings Using Vector Autoregressive Modeling and Variable-order Kalman Filtering
PublicationThis paper presents a new approach to elimination of impulsive disturbances from stereo audio recordings. The proposed solution is based on vector autoregressive modeling of audio signals. Online tracking of signal model parameters is performed using the exponential ly weighted least squares algo- rithm. Detection of noise pulses an d model-based interpolation of the irrevocably distorted sampl es is realized using an adaptive, variable-order...
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Sonar Pulse Detection Using Chirp Rate Estimation and CFAR Algorithms
PublicationThis paper presents a new approach to sonar pulse detection. The method uses chirp rate estimators and algorithms for the adaptive threshold, commonly used in radiolocation. The proposed approach allows detection of pulses of unknown parameters, which may be used in passive hydrolocation or jamming detection in underwater communication. Such an analysis is possible thanks to a new kind of imaging, which presents signal energy in...
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Worm Gear Drives with Improved Kinematic Accuracy
PublicationThis paper presents the fundamentals of the design and applications of new worm gear drive solutions, which enable the minimisation of backlash and are characterised by higher kinematic accuracy. Different types of worm surfaces are briefly outlined. Technological problems concerning the principles of achieving a high degree of precision in machining are also described. Special attention is paid to the shaping of conical helical...
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Power System Stabilizer as a Part of a Generator MPC Adaptive Predictive Control System
PublicationIn 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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Auto adaptation of mobile device characteristics to various acoustic conditions
PublicationThe proposed methodology of auto adaptation of the mobile device characteristics to various acoustic conditions is presented in the paper. The first goal of this study was to determine the parameters of the acoustic path of the mobile device, for both transmitting (speaker) and receiver (microphone). Results of the measurement of characteristics of mobile devices were presented. Information about characteristics of individual parts...
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On adaptive selection of estimation bandwidth for analysis of locally stationary multivariate processes
PublicationWhen 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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The difficult heritage. The reuse of former prison buildings
PublicationIn recent years, there has been a trend to reuse abandoned buildings. Adaptive re-use allows preservation of the original structure and implements a new function to it. Such activity could help to preserve the historic value of buildings; moreover, many other advantages can be found in educational, ecological and economic fields. However, the question arises of whether every object can be freely adapted. This article examines the...
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MRAS-Based Switching Linear Feedback Strategy for Sensorless Speed Control of Induction Motor Drives
PublicationThis paper presents a newly designed switching linear feedback structure of sliding mode control (SLF-SMC) plugged with an model reference adaptive system (MRAS) based sensorless fieldoriented control (SFOC) for induction motor (IM). Indeed, the performance of the MRAS depends mainly on the operating point and the parametric variation of the IM. Hence, the sliding mode control (SMC) could be considered a good control alternative...
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On optimal tracking of rapidly varying telecommunication channels
PublicationWhen parameters of mobile telecommunication channels change rapidly, classical adaptive filters, such as exponentially weighted least squares algorithms or gradient algorithms, fail to estimate them with sufficient accuracy. In cases like this, one can use identification methods based on explicit models of parameter changes such as the method of basis functions (BF). When prior knowledge about parameter changes is available the...
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Speed Observer Structure of Induction Machine Based on Sliding Super-Twisting and Backstepping Techniques
PublicationThis paper presents an analysis of the two speed observer structures which are based on the backstepping and sliding super twisting approach. The observer stabilizing functions result from the Lyapunov theorem. To obtain the observer tuning gains the observer structure is linearized near the equilibrium point. The rotor angular speed is obtained from non-adaptive dependence. In the sensorless control system structure the classical...
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Application of sliding switching functions in backstepping based speed observer of induction machine
PublicationThe paper presents an analysis of the speed observer which is based on the backstepping and sliding mode approach. The speed observer structure is based on the extended mathematical model of an induction machine. The observer structure is based on the measured phase stator currents and transformed to ( αβ ) coordinate system. The stator voltage vector components are treated as known values. Additionally, such an observer structure...
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Regularized Local Basis Function Approach to Identification of Nonstationary Processes
PublicationThe problem of identification of nonstationary stochastic processes (systems or signals) is considered and a new class of identification algorithms, combining the basis functions approach with local estimation technique, is described. Unlike the classical basis function estimation schemes, the proposed regularized local basis function estimators are not used to obtain interval approximations of the parameter trajectory, but provide...
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Multiple Cues-Based Robust Visual Object Tracking Method
PublicationVisual object tracking is still considered a challenging task in computer vision research society. The object of interest undergoes significant appearance changes because of illumination variation, deformation, motion blur, background clutter, and occlusion. Kernelized correlation filter- (KCF) based tracking schemes have shown good performance in recent years. The accuracy and robustness of these trackers can be further enhanced...
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Adaptive Hounsfield Scale Windowing in Computed Tomography Liver Segmentation
PublicationIn 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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A new look at the statistical identification of nonstationary systems
PublicationThe paper presents a new, two-stage approach to identification of linear time-varying stochastic systems, based on the concepts of preestimation and postfiltering. The proposed preestimated parameter trajectories are unbiased but have large variability. Hence, to obtain reliable estimates of system parameters, the preestimated trajectories must be further filtered (postfiltered). It is shown how one can design and optimize such...
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Multistage generalized adaptive notch filter with improved accuracy
PublicationGeneralized 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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Computational Simulation of the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublicationThis 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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Respiration rate estimation using non-linear observers in application to wastewater treatment plant
PublicationA problem of respiration rate estimation using two new non-linear observers for a wastewater treatment plant is addressed in this paper. In particular, a non-linear adaptive Luenberger-like observer and a super twisting sliding mode observer have been derived to produce stable and bounded estimates of the respiration rate. During the synthesis of the particular observer, an appropriate mathematical utility model was used. The observability...
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublicationThis 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
PublicationThis 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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Multiresolution analysis and adaptive estimation on a sphere using stereographic wavelets
PublicationWe 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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Porównanie wybranych algorytmów systemu APR dla potrzeb redukcji poboru mocy cyfrowych układów CMOS
PublicationPraca dotyczy porównania czterech wybranych algorytmów wchodzacych w skład systemu APR (ang. Adaptive Power Reduction). Przeprowadzono weryfikację zmodyfikowanych heurystycznych algorytmów IIOI, UNILO i MAREL oraz nowego algorytmu hybrydowego (HSA) dla potrzeb syntezy wysokiego poziomu (HLS od ang. High Level Synthesis) z redukcją poboru mocy układów cyfrowych CMOS. Pozwalają one na zwiększenie poziomu redukcji mocy rozpraszanej...
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Konzepte zur Energieeffizienzsteigerung bei Internet-Zugangsgeräten
PublicationThe 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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Adaptive prediction of stock exchange indices by state space wavelet networks
PublicationThe 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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Development and tuning of irregular divide-and-conquer applications in DAMPVM/DAC
PublicationThis work presents implementations and tuning experiences with parallel irregular applications developed using the object oriented framework DAM-PVM/DAC. It is implemented on top of DAMPVM and provides automatic partitioning of irregular divide-and-conquer (DAC) applications at runtime and dynamic mapping to processors taking into account their speeds and even loads by other user processes. New implementations of parallel applications...
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Integrating modelling, simulation and data management tools to create a planning support system for the improvement of air quality by urban planning solutions
PublicationThe urbanization pressure requires urban planners, designers, and policy makers to be more responsive to the challenges related to improving the quality of the urban environment and the living conditions of the inhabitants. One of the many environmental issues that need to be taken into account is urban air pollution. As the process of urban ventilation and air pollution dis-persion is significantly affected by the urban layout,...
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The “autumn effect” in the gold market—does it contradict the Adaptive Market Hypothesis?
PublicationThe present study aims to verify the autumn effect in the gold market, first presented 10 years ago by Dirk Baur in the paper “The autumn effect of gold” and to investigate the calendar effects occurring for other precious metals. This empirical research is presented in a way to place the results obtained in the context of the Efficient Market Hypothesis (EMH) and the more current Adaptive Market Hypothesis (AMH). The study was...
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Student model representation for pedagogical virtual mentors
PublicationThe paper concerns technological aspects of virtual mentors construction, especially concentrating on the student model representation. The article distinguishes several types of information that is gathered by the pedagogical agents and other educational platforms, including student knowledge model, student progress tracking, interaction process patterns and learner preferences. A set of technologies used for the student model...
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Semi complex navigation with an active optical gesture sensor
PublicationThis paper presents the methods of diversified touchless interactions between a user and a mobile platform utilizing the optical gesture sensor. The sensor uses 8 photodiodes to measure the reflected light in the active mode (using embedded LEDs) or it measures shadows caused by fingers in the passive mode. Several algorithms were implemented: automatic mode switching, adaptive illumination level compensation, resolution improvements...
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Detection and localization of selected acoustic events in 3D acoustic field for smart surveillance applications
PublicationA method for automatic determination of position of chosen sound events such as speech signals and impulse sounds in 3-dimensional space is presented. The events are localized in the presence of sound reflections employing acoustic vector sensors. Human voice and impulsive sounds are detected using adaptive detectors based on modified peak-valley difference (PVD) parameter and sound pressure level. Localization based on signals...
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Transmission parameters of underwater communication channels
PublicationThe underwater environment is tough and demanding as a communication channel for ultrasonic signals. The channel transmission characteristics in marine and inland waters depend much on local bathymetry and changing weather conditions. The architecture and performance of a reliable underwater acoustic communication (UAC) system should allow real-time adaptation of its transmission parameters to a large variety of possible channel...
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Estimation of the Ultimate Strength of FRP Strips-to-Masonry Substrates Bond
PublicationFiber-Reinforced Polymers (FRP) were developed as a new method over the past decades due to their many beneficial mechanical properties, and they are commonly applied to strengthen masonry structures. In this paper, the Artificial Neural Network (ANN), K-fold Cross-Validation (KFCV) technique, Multivariate Adaptive Regression Spline (MARS) method, and M5 Model Tree (M5MT) method were utilized to predict the ultimate strength of...