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Search results for: RANDOM FIELD
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Snapshot of micro-animals and associated biotic and abiotic environmental variables on the edge of the south-west Greenland ice sheet
PublicationMicroinvertebrates play a role as top consumers on glaciers. In this study we tested what kind of cryoconite material the animals inhabit (mud vs granules) on the edge of the Greenland ice sheet (GrIS) in the south-west. We also tested the links between the densities of micro-fauna in cryoconite material and selected biotic (algae, cyanobacteria, bacterial abundances) and abiotic (water depth, pH, ion content, radionuclides) factors....
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Estimation of Coherence Bandwidth for Underwater Acoustic Communication Channel
PublicationA shallow underwater acoustic communication channel is characterized by strong multipath propagation. The signal reaching the receiver consists of a direct waveform and a number of its delayed and suppressed replica. A significant time dispersion of the transmitted signal and selective fading of its spectrum are observed. Coherence bandwidth defines maximal bandwidth, wherein the channel amplitude characteristic remains constant...
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Effect of User Mobility upon Trust Building among Autonomous Content Routers in an Information-Centric Network
PublicationThe capability of proactive in-network caching and sharing of content is one of the most important features of an informationcentric network (ICN). We describe an ICN model featuring autonomous agents controlling the content routers. Such agents are unlikely to share cached content with other agents without an incentive to do so. To stimulate cooperation between agents, we adopt a reputation and trust building scheme that is able...
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ON EGNOS MONITORING IN LOCAL CONDITIONS
PublicationAny SBAS system should deliver to the user corrections to pseudoranges as well as information about the system integrity. In theory, as soon as the system is permanently monitored by RIMS stations, it is impossible to deliver the fault information to the user. However many observations shows that accuracy of EGNOS service in the same time are different in different places, which shows the influence of local conditions on them....
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Properties of dimension witnesses and their semidefinite programming relaxations
PublicationIn this paper we develop a method for investigating semi-device-independent randomness expansion protocols that was introduced in Li et al. [H.-W. Li, P. Mironowicz, M. Pawłowski, Z.-Q. Yin, Y.-C. Wu, S. Wang, W. Chen, H.-G. Hu, G.-C. Guo, and Z.-F. Han, Phys. Rev. A 87, 020302(R) (2013)]. This method allows us to lower bound, with semi-definite programming, the randomness obtained from random number generators based on dimension...
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Coherent-wave Monte Carlo method for simulating light propagation in tissue
PublicationSimulating propagation and scattering of coherent light in turbid media, such as biological tissues, is a complex problem. Numerical methods for solving Helmholtz or wave equation (e.g. finite-difference or finite-element methods) require large amount of computer memory and long computation time. This makes them impractical for simulating laser beam propagation into deep layers of tissue. Other group of methods, based on radiative...
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A multiparameter simulation-driven analysis of ship response when turning concerning a required number of irregular wave realizations
PublicationThe growing implementation of Decision Support Systems on modern ships, digital-twin technology, and the introduction of autonomous vessels cause the marine industry to seek accurate modeling of vessel response. Despite the contemporary 6DOF models can be used to predict ship motions in irregular waves, the impact of their stochastic realization is usually neglected and remains under-investigated. Especially in the case of turning, differences...
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Stability Assessment of Coastal Cliffs Incorporating Laser Scanning Technology and a Numerical Analysis
PublicationWe investigated the cli coast in Jastrzebia Gora, Poland. The measurements that were taken between 2014 and 2018 by applying terrestrial, mobile, and airborne laser scanning describe a huge geometric modification involving dislocations in a 2.5 m range. Dierential maps and a volumetric change analysis made it possible to identify the most deformed cli’s location. Part of the monitoring of coastal change involved the measurement...
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Electronic nose algorithm design using classical system identification for odour intensity detection
PublicationThe two elements considered crucial for constructing an efficient environmental odour intensity monitoring systems are sensors and algorithms typically addressed to as electronic nose sensor (e-nose). Due to operational complexity of biochemical sensors developed in human bodies algorithms based on computational methods of artificial intelligence are typically considered superior to classical model based approaches in development...
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Application of autoencoder to traffic noise analysis
PublicationThe 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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Behavior Based Complete Coverage Task of Unknown Area by an Autonomous Mobile Robot SCORPION with Static Obstacles in Environment
PublicationIn the paper the behavior based control system of an autonomous mobile robot SCORPION is presented to execute the one of the most difficult navigation task, which is the complete coverage task of unknown area with static obstacles in the environment. The main principle assumed to design control system was that the robot should cover all area only once, if it possible, to optimize the length of path and energy consumption. All commercial...
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Bibliometric analysis of artificial intelligence in wastewater treatment: Current status, research progress, and future prospects
PublicationWastewater treatment is an important topic for improving water quality and environmental protection, and artificial intelligence has become a powerful tool for wastewater treatment. This work provides research progress and a literature review of artificial intelligence applied to wastewater treatment based on the visualization of bibliometric tools. A total of 3460 publications from 2000 to 2023 were obtained from the Web of Science...
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A nosocomial outbreak of Candida parapsilosis in southern Sweden verified by genotyping
PublicationIn a haematology ward, Candida parapsilosis was found in blood cultures from 4 patients within a month. As C. parapsilosis is known to have a restricted genetic diversity, a combined methodological approach was adopted to establish a possible epidemiological relationship among the isolates (n = 9). Multilocus sequence typing and random amplified polymorphic DNA analysis suggested a clonal origin of the isolates. The clonal origin...
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Normalized Partial Scattering Cross Section for Performance Evaluation of Low-Observability Scattering Structures
PublicationThe development of diffusion metasurfaces created new opportunities to elevate the stealthiness of combat aircraft. Despite the potential significance of metasurfaces, their rigorous design methodologies are still lacking, especially in the context of meticulous control over the scattering of electromagnetic (EM) waves through geometry parameter tuning. Another practical issue is insufficiency of the existing performance metrics,...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Drill holes decrease cancellous bone strength: A comparative study of 33 paired osteoporotic human and 9 paired artificial bone samples
PublicationThis study was designed to compare compressive strength of cancellous bone retrieved from the femoral head in a specimen with and without guide wire hole, with comparison to synthetic bone samples. Femoral heads retrieved from 33 patients who sustained femoral neck fractures and underwent hip arthroplasty were cut into cuboids leaving two matching samples from the same femoral head. Similar samples were prepared from synthetic femurs....
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Improving the procedure of probabilistic load testing design of typical bridges based on structural response similarities
PublicationThis paper concerns load testing of typical bridge structures performed prior to operation. In-situ tests of a two-span post-tensioned bridge loaded with three vehicles of 38-ton mass each formed the input of this study. On the basis of the results of these measurements, an advanced FEM model of the structure was developed for which the sensitivity analysis was performed for chosen uncertainty sources. Three uncorrelated random...
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Nanosilver-loaded PMMA bone cement doped with different bioactive glasses – evaluation of cytocompatibility, antibacterial activity, and mechanical properties
PublicationNanosilver-loaded PMMA bone cement (BC-AgNp) is a novel cement developed as a replacement for conventional cements. Despite favorable properties and antibacterial activity, BC-AgNp still lacks biodegradability and bioactivity. Hence, we investigated the doping with bioactive glasses (BGs) to create a new bioactive BC characterized by time-varying porosity and gradual release of nanosilver. The BC Cemex was used as the base material...
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Limiting distribution of the three-state semi-Markov model of technical state transitions of ship power plant machines and its applicability in operational decision-making.
PublicationThe article presents the three-state semi-Markov model of the process {W(t): t 0} of state transitions of a ship power plant machine, with the following interpretation of these states: s1 – state of full serviceability, s2 – state of partial serviceability, and s3 – state of unserviceability. These states are precisely defined for the ship main engine (ME). A hypothesis is proposed which explains the possibility of application...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Assessment of Wide-Sense Stationarity of an Underwater Acoustic Channel Based on a Pseudo-Random Binary Sequence Probe Signal
PublicationThe performances of Underwater Acoustic Communication (UAC) systems are strongly related to the specific propagation conditions of the underwater channel. Designing the physical layer of a reliable data transmission system requires a knowledge of channel characteristics in terms of the specific parameters of the stochastic model. The Wide-Sense Stationary Uncorrelated Scattering (WSSUS) assumption simplifies the stochastic description...
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Semantic Analysis and Text Summarization in Socio-Technical Systems
PublicationIn this chapter the authors present the results of the development the methodology for increasing the reliability of the functioning of the Socio-Technical System. The existed methods and algorithms for processing unstructured (textual) information were studied. Taking into account noted above strengths and weaknesses of Discriminant and Probabilistic approaches of Latent Semantic Relations analysis in of the summarization projection...
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AUTOMATED SYSTEM FOR FLUCTUATION ENHANCED GAS SENSING
PublicationResistance gas sensors exhibit random phenomena (resistance noise) which can be utilized to improve gas sensitivity and selectivity. That new emerging technique has to be investigated to recognize optimal parameters for gas detection. It means that a measurement system has to have ability of numerous parameters adjustment (e.g., sampling frequency, heater voltage, polarization current, voltage noise amplification). That fact induced...
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Application of multisensoral remote sensing data in the mapping of alkaline fens Natura 2000 habitat
PublicationThe Biebrza River valley (NE Poland) is distinguished by largely intact, highly natural vegetation patterns and very good conservation status of wetland ecosystems. In 20132014, studies were conducted in the upper Biebrza River basin to develop a remote sensing method for alkaline fen classification a protected Natura 2000 habitat (code 7230) using remote sensing technologies. High resolution airborne true colour (RGB) and...
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Reduced-Cost Microwave Modeling Using Constrained Domains and Dimensionality Reduction
PublicationDevelopment of modern microwave devices largely exploits full-wave electromagnetic (EM) simulations. Yet, simulation-driven design may be problematic due to the incurred CPU expenses. Addressing the high-cost issues stimulated the development of surrogate modeling methods. Among them, data-driven techniques seem to be the most widespread owing to their flexibility and accessibility. Nonetheless, applicability of approximation-based...
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Experimental certification of more than one bit of quantum randomness in the two inputs and two outputs scenario
PublicationOne of the striking properties of quantum mechanics is the occurrence of the Bell-type non-locality. They are a fundamental feature of the theory that allows two parties that share an entangled quantum system to observe correlations stronger than possible in classical physics. In addition to their theoretical significance, non-local correlations have practical applications, such as device-independent randomness generation, providing...
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A Robust Random Forest Model for Classifying the Severity of Partial Discharges in Dielectrics
PublicationPartial Discharges (PDs) are a common source of degradation in electrical assets. It is essential that the extent of the deterioration level of insulating medium is correctly identified, to optimize maintenance schedules and prevent abrupt power outages. Temporal PD signals received from damaged insulation, collected through the IEC-60270 method is the gold standard for PD detection. Temporal signals may be transformed to the frequency...
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Generalization of Phylogenetic Matching Metrics with Experimental Tests of Practical Advantages
PublicationThe ability to quantify a dissimilarity of different phylogenetic trees is required in various types of phylogenetic studies, for example, such metrics are used to assess the quality of phylogeny construction methods and to define optimization criteria in supertree building algorithms. In this article, starting from the already described concept of matching metrics, we define three new metrics for rooted phylogenetic trees. One...
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Intermolecular Interactions as a Measure of Dapsone Solubility in Neat Solvents and Binary Solvent Mixtures
PublicationDapsone is an effective antibacterial drug used to treat a variety of conditions. However, the aqueous solubility of this drug is limited, as is its permeability. This study expands the available solubility data pool for dapsone by measuring its solubility in several pure organic solvents: N-methyl-2-pyrrolidone (CAS: 872-50-4), dimethyl sulfoxide (CAS: 67-68-5), 4-formylmorpholine (CAS: 4394-85-8), tetraethylene pentamine (CAS:...
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Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
PublicationThe purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublicationDue to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublicationNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Probabilistyczna ocena wrażliwości stanów granicznych konstrukcji inżynierskich na imperfekcje geometryczne i materiałowe
PublicationTematem pracy jest analiza probabilistyczna wrażliwości mechanicznej odpowiedzi konstrukcji inżynierskich na imperfekcje geometryczne oraz zmianę własności materiałów. Z tematem tym ściśle związany jest problem estymacji niezawodności konstrukcji, również szeroko opisany w rozprawie. W pracy dokonano przeglądu metod wykorzystywanych w analizie probabilistycznej oraz zaproponowano procedury wykorzystujące te metody w analizie wrażliwości...
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Low-Cost Modeling of Microwave Components by Means of Two-Stage Inverse/Forward Surrogates and Domain Confinement
PublicationFull-wave electromagnetic (EM) analysis is one of the most important tools in the design of modern microwave components and systems. EM simulation permits reliable evaluation of circuits at the presence of cross-coupling effects or substrate anisotropy, as well as for accounting for interactions with the immediate environment. However, repetitive analyses required by EM-driven procedures, such as parametric optimization or statistical...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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A New Adaptive Method for the Extraction of Steel Design Structures from an Integrated Point Cloud
PublicationThe 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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Instructor Presence in Video Lectures: Preliminary Findings From an Online Experiment
PublicationMotivation. Despite the widespread use of video lectures in online and blended learning environments, there is still debate whether the presence of an instructor in the video helps or hinders learning. According to social agency theory, seeing the instructor makes learners believe that s/he is personally teaching them, which leads to deeper cognitive processing and, in turn, better learning outcomes. Conversely, according to cognitive...
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Compressive Sensing Approach to Harmonics Detection in the Ship Electrical Network
PublicationThe contribution of this paper is to show the opportunities for using the compressive sensing (CS) technique for detecting harmonics in a frequency sparse signal. The signal in a ship’s electrical network, polluted by harmonic distortions, can be modeled as a superposition of a small number of sinusoids and the discrete Fourier transform (DFT) basis forms its sparse domain. According to the theory of CS, a signal may be reconstructed...
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Implementation of Non-Probabilistic Methods for Stability Analysis of Nonlocal Beam with Structural Uncertainties
PublicationIn this study, a non-probabilistic approach based Navier’s Method (NM) and Galerkin Weighted Residual Method (GWRM) in term of double parametric form has been proposed to investigate the buckling behavior of Euler-Bernoulli nonlocal beam under the framework of the Eringen's nonlocal elasticity theory, considering the structural parameters as imprecise or uncertain. The uncertainties in Young’s modulus and diameter of the beam are...
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Amplifying the Randomness of Weak Sources Correlated With Devices
PublicationThe problem of device-independent randomness amplification against no-signaling adversaries has so far been studied under the assumption that the weak source of randomness is uncorrelated with the (quantum) devices used in the amplification procedure. In this paper, we relax this assumption, and reconsider the original protocol of Colbeck and Renner using a Santha-Vazirani (SV) source. To do so, we introduce an SV-like condition...
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Bounds on the Cover Time of Parallel Rotor Walks
PublicationThe rotor-router mechanism was introduced as a deterministic alternative to the random walk in undirected graphs. In this model, a set of k identical walkers is deployed in parallel, starting from a chosen subset of nodes, and moving around the graph in synchronous steps. During the process, each node maintains a cyclic ordering of its outgoing arcs, and successively propagates walkers which visit it along its outgoing arcs in...
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IN VITRO PROPAGATION OF RHODODENDRON TOMENTOSUM - AN ENDANGERED ESSENTIAL OIL BEARING PLANT FROM PEATLAND
PublicationRhododendron tomentosum Harmaja (formerly Ledum palustre L.) is a medicinal peat bog plant native to northern Europe, Asia and North America. This plant has a distinctive aroma thanks to the presence of essential oil, to which it also owes its anti-inflammatory, analgesic, antimicrobial and insecticidal properties. However, in Europe R. tomentosum is classified as an endangered species, mainly due to degradation of peatlands. In...
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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublicationThis study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...
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Investigation of Weigh-in-Motion Measurement Accuracy on the Basis of Steering Axle Load Spectra
PublicationWeigh-in-motion systems are installed in pavements or on bridges to identify and reduce the number of overloaded vehicles and minimise their adverse eect on road infrastructure. Moreover, the collected trac data are used to obtain axle load characteristics, which are very useful in road infrastructure design. Practical application of data from weigh-in-motion has become more common recently, which calls for adequate attention to...
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Intracranial hemorrhage detection in 3D computed tomography images using a bi-directional long short-term memory network-based modified genetic algorithm
PublicationIntroduction: Intracranial hemorrhage detection in 3D Computed Tomography (CT) brain images has gained more attention in the research community. The major issue to deal with the 3D CT brain images is scarce and hard to obtain the labelled data with better recognition results. Methods: To overcome the aforementioned problem, a new model has been implemented in this research manuscript. After acquiring the images from the Radiological...
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Meso‐scale analyses of size effect in brittle materials using DEM
PublicationThe paper describes numerical meso-scale results of a size effect on strength, brittleness and fracture in brittle materials like concrete. The discrete element method (DEM) was used to simulate the size effect during quasi-static splitting tension with the experimental-based meso-structure. The two-dimensional (2D) calculations were carried out on concrete cylindrical specimens with two diameters wherein two different failure...
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On the Role of Polarimetric Decomposition and Speckle Filtering Methods for C-Band SAR Wetland Classification Purposes
PublicationPrevious wetlands studies have thoroughly verified the usefulness of data from synthetic aperture radar (SAR) sensors in various acquisition modes. However, the effect of the processing parameters in wetland classification remains poorly explored. In this study, we investigated the influence of speckle filters and decomposition methods with different combinations of filter and decomposition windows sizes on classification accuracy....
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Intelligent Decision Forest Models for Customer Churn Prediction
PublicationCustomer churn is a critical issue impacting enterprises and organizations, particularly in the emerging and highly competitive telecommunications industry. It is important to researchers and industry analysts interested in projecting customer behavior to separate churn from non‐churn consumers. The fundamental incentive is a firm’s intent desire to keep current consumers, along with the exorbitant expense of gaining new ones....
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A facile structural manipulation strategy to prepare ultra-strong, super-tough, and thermally stable polylactide/nucleating agent composites
PublicationPolylactide (PLA) is a biodegradable thermoplastic widely used in diferent felds, but it should be adequately modifed considering high-performance applications. However, the current processes for developing PLA materials achieve high strength at the expense of toughness or ductility of the materials. Therefore, there is need to develop new strategies for generation of PLA materials with high strength, great toughness, good ductility,...
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Spatio-temporal filtering for determination of common mode error in regional GNSS networks
PublicationThe spatial correlation between different stations for individual components in the regional GNSS networks seems to be significant. The mismodelling in satellite orbits, the Earth orientation parameters (EOP), largescale atmospheric effects or satellite antenna phase centre corrections can all cause the regionally correlated errors. This kind of GPS time series errors are referred to as common mode errors (CMEs). They are usually...