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Search results for: cross-sensitivity, multiple linear regression, artificial neural networks
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Journey towards light – evolutionary adaptations of humans, flora and fauna. Guidelines for safe and healthy illumination
PublicationThe paper examines using relatively recent discoveries on how evolution has embedded within all living organisms a natural sensitivity towards their native environment, in particular luminance levels and specific wavelengths of light. The studies conducted so far indicate that lighting installations that are visible after dark impact on humans, flora and fauna and influence our evolutionary dispositions, possibly with negative...
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Endoscopic Video Classification with the Consideration of Temporal Patterns
PublicationThe article describes a novel approach to automatic recognition and classification of diseases in endoscopic videos. Current directions of research in this field are discussed. Most presented methods focus on processing single frames and do not take into consideration the temporal relationship between continuous classifications. Existing approaches that consider the temporal structure of an incoming frame sequence are focused on...
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Numerically efficient algorithm for compact microwave device optimization with flexible sensitivity updating scheme
PublicationAn efficient trust-region algorithm with flexible sensitivity updating management scheme for electromagnetic (EM)-driven design optimization of compact microwave components is proposed. During the optimization process, updating of selected columns of the circuit response Jacobian is performed using a rank-one Broyden formula (BF) replacing finite differentiation (FD). The FD update is omitted for directions sufficiently well aligned...
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A new multi-process collaborative architecture for time series classification
PublicationTime series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...
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Online sound restoration system for digital library applications
PublicationAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Computed aided system for separation and classification of the abnormal erythrocytes in human blood
PublicationThe human peripheral blood consists of cells (red cells, white cells, and platelets) suspended in plasma. In the following research the team assessed an influence of nanodiamond particles on blood elements over various periods of time. The material used in the study consisted of samples taken from ten healthy humans of various age, different blood types and both sexes. The markings were leaded by adding to the blood unmodified...
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5G/6G optical fronthaul modeling: cost and energy consumption assessment
PublicationIn fifth generation (5G) and the future beyond 5G (6G) radio access networks (RANs), the cost of fronthaul deployment is a main challenge for mobile network operators. Depending on different constraints, there are various solutions to deploy an efficient fronthaul. Fiber-optic-based fronthaul offers long-term support with regard to a rapid increase in capacity demands. When fiber connections, either point-to-point (P2P) or point-to-multipoint...
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Load introduction to composite columns revisited—Significance of force allocation and shear connection stiffness
PublicationThe AISC 360-16 Specification recommends that the design shear force between parts of a composite column in the load introduction area shall be calculated based on the force allocation at ultimate limit state. Applicability of this straightforward method to the load levels that usually arise in slender composite columns is questionable, as this capacity-based force allocation is only true when the axial force is equal to the plastic...
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Enhancing Economic Development Through ICT-Based Governance: Evidence for Developing Countries
Publicationhis shows novel empirical evidence on how e-government solutions enhance the emergence of inclusive societies, increase institutional quality, and through that channels dynamize economic development in developing countries. With this aim we examine digital development inequalities adopting 2 core ICT indicators: mobile cellular telephony and Internet users; and gross per capita income and Human Development Index to show the level...
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublicationThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...
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Impact of rotor geometry optimization on the off-design ORC turbine performance
PublicationThe paper describes the method of CFD based Nelder-Mead optimization of a 10 kW single-stage axial turbine operating in an ORC system working on R7100. The total-to-static isentropic efficiency is defined as an objective function. Multi-point linear regression is carried out to determine the significance of the objective function arguments and to pick up the set of particular variables and characteristic quantities (e.g. flow angles)...
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Towards New Mappings between Emotion Representation Models
PublicationThere are several models for representing emotions in affect-aware applications, and available emotion recognition solutions provide results using diverse emotion models. As multimodal fusion is beneficial in terms of both accuracy and reliability of emotion recognition, one of the challenges is mapping between the models of affect representation. This paper addresses this issue by: proposing a procedure to elaborate new mappings,...
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INTER-LAYER SHARING OF BACKUP PATH CAPACITIES PROVIDING FAST SERVICE RECOVERY IN IP-MPLS/WDM NETWORKS
PublicationIn this paper, we investigate the issue of providing the transmission continuity in IP-MPLS/WDM networks in the presence of failures of nodes/links. Special focus is put on assuring fast restoration of flows affected after a failure in a scenario assuming sharing the backup path capacities in order to decrease the overall bandwidth consumption. In particular, we propose a new approach to inter-layer sharing of link capacity reserved...
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Influence of Fragment Size on the Time and Temperature of Ethylene Vinyl Acetate Lamination Decomposition in the Photovoltaic Module Recycling Process
PublicationPhotovoltaics is a commercially available and reliable technology with significant potential for long-term growth in nearly all global regions. Several research institutes and companies are working on recycling concepts for thin film modules and modules with crystalline cells. The establishment of recycling and reuse technologies appropriate and applicable to all photovoltaics (PV) modules is a key issue to be addressed as part...
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Exploiting multi-interface networks: Connectivity and Cheapest Paths
PublicationLet G = (V,E) be a graph which models a set of wireless devices (nodes V) that can communicate by means of multiple radio interfaces, according to proximity and common interfaces (edges E). The problem of switching on (activating) the minimum cost set of interfaces at the nodes in order to guarantee the coverage of G was recently studied. A connection is covered (activated) when the endpoints of the corresponding edge share at...
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Physics augmented classification of fNIRS signals
PublicationBackground. Predictive classification favours performance over semantics. In traditional predictive classification pipelines, feature engineering is often oblivious to the underlying phenomena. Hypothesis. In applied domains such as functional Near Infrared Spectroscopy (fNIRS), the exploitation of physical knowledge may improve the discriminative quality of our observation set. Aims. Give exemplary evidence that intervening the...
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Multiple output differential OTA with linearizing bulk-driven active-error feedback loop for continuous-time filter applications
PublicationA CMOS circuit realization of a highly linear multiple-output differential operational transconductance amplifier (OTA) has been proposed. The presented approach exploits a differential pair as an input stage with both the gate and the bulk terminals as signal ports. For the proposed OTA, improved linearity is obtained by means of the active-error feedback loop operating at the bulk terminals of the input stage. SPICE simulations...
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Multiple output CMOS current amplifier
PublicationIn this paper the multiple output current amplifier basic cell is proposed. The triple output current mirror and current follower circuit are described in detail. The cell consists of a split nMOS differential pair and accompanying biasing current sources. It is suitable for low voltage operation and exhibits highly linear DC response. Through cell devices scaling, not only unity, but also any current gains are achievable. As...
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Unmasking the COVID-19 Pandemic Prevention Gains: Excess Mortality Reversal in 2022
PublicationObjectives: The purpose of this study was to assess the long-term effectiveness of COVID-19 pandemic prevention measures in saving lives after European governments began to lift restrictions. Study design: Excess mortality interrupted time series.Methods: Country-level weekly data on deaths were fitted to the Poisson mixed linear model to estimate excess deaths. Based on this estimate, the percentage of excess deaths...
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Badania połączeń spawanych rurociągu wody pitnej we Włocławku, ang. Welding joints tests in drinking water pipeline.
PublicationCelem badań opisanych w pracy było określenie przyczyn korozji powstałej w strefie wpływu ciepła (SWC) w obwodowych połączeniach spawanych w rurociągu wody pitnej. Materiałem, z którego wykonano rurociąg to stal 304/304L. W obszarze złącza spawanego stwierdzono wżery inicjowane od niezgodności geometrycznych, gdzie mogły gromadzić się osady zwiększające udział chlorków bezpośrednio przy powierzchni rury, promujące tym procesy korozyjne....
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Automatic Singing Voice Recognition EmployingNeural Networks and Rough Sets
PublicationCelem badań jest automatyczne rozpoznawanie głosów śpiewaczych w kategorii rodzaju i jakości technicznej śpiewu. W artykule opisano stworzoną bazę danych głosów, która zawiera próbki głosu śpiewaków profesjonalnych i amatorskich. W dalszej części opisano parametry zdefiniowane w oparciu o zjawiska biomechaniczne w narządzie głosu podczas śpiewania. W oparciu o stworzone macierze parametrów wytrenowano i porównano automatyczne klasyfikatory...
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Light pollution from illuminated bridges as a potential barrier for migrating fish–Linking measurements with a proposal for a conceptual model
PublicationIlluminated bridges have become important assets to navigable aquatic systems. However, if artificial light at night (ALAN) from illuminated bridges reaches aquatic habitats, such as rivers, it can threaten the river's natural heterogeneity and alter the behavioural responses of migratory fish. Here, via a pilot study, we quantified levels of ALAN at illuminated bridges that cross a river and, propose a conceptual model to estimate...
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Cross-layer integration of network mechanisms for increasing efficiency of multimedia session support in IEEE 802.11s environment
PublicationWith an IEEE 802.11 wireless networks operating in Point-to-Multipoint mode being the most popular WLAN access technology employed today, it can be expected that a Wireless Mesh Network (WMN) based on the technology can provide significant advantages for such network systems. The IEEE 802.11s standard amendment provides the comprehensive set of mechanisms required to implement and deploy a WMN utilizing this widely popular technology....
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublicationThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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Degradation of electrical performance of a crystalline photovoltaic module due to dust deposition in northern Poland
PublicationThe reduction in power output caused by the accumulation of dust on the photovoltaic module surface is an important problem and should receive much more attention in the literature. This study was an evaluation of the performance degradation of crystalline photovoltaic modules due to natural and simulated dust deposition. Dust is created from powdered grains of sand and particles of different bodies. Dust originates from different...
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublicationAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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Audio Feature Analysis for Precise Vocalic Segments Classification in English
PublicationAn approach to identifying the most meaningful Mel-Frequency Cepstral Coefficients representing selected allophones and vocalic segments for their classification is presented in the paper. For this purpose, experiments were carried out using algorithms such as Principal Component Analysis, Feature Importance, and Recursive Parameter Elimination. The data used were recordings made within the ALOFON corpus containing audio signal...
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Predicting the peak structural displacement preventing pounding of buildings during earthquakes
PublicationThe aim of the present paper is to verify the effectiveness of the artificial neural network (ANN) in predicting the peak lateral displacement of multi-story building during earthquakes, based on the peak ground acceleration (PGA) and building parameters. For the purpose of the study, the lumped-mass multi-degree-of-freedom structural model and different earthquake records have been considered. Firstly, values of stories mass and...
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In silico modelling for predicting the cationic hydrophobicity and cytotoxicity of ionic liquids towards the Leukemia rat cell line, Vibrio fischeri and Scenedesmus vacuolatus based on molecular interaction potentials of ions
PublicationIn this study we present prediction models for estimating in silico the cationic hydrophobicity and the cytotoxicity (log [1/EC50]) of ionic liquids (ILs) towards the Leukemia rat cell line (IPC-81), the marine bacterium Vibrio fischeri and the limnic green algae Scenedesmus vacuolatus using linear free energy relationship (LFER) descriptors computed by COSMO calculations. The LFER descriptors used for the prediction model (i.e....
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Investigating Feature Spaces for Isolated Word Recognition
PublicationMuch attention is given by researchers to the speech processing task in automatic speech recognition (ASR) over the past decades. The study addresses the issue related to the investigation of the appropriateness of a two-dimensional representation of speech feature spaces for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and timefrequency signal representation...
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Condition-Based Monitoring of DC Motors Performed with Autoencoders
PublicationThis paper describes a condition-based monitoring system estimating DC motor degradation with the use of an autoencoder. Two methods of training the autoencoder are evaluated, namely backpropagation and extreme learning machines. The root mean square (RMS) error in the reconstruction of successive fragments of the measured DC motor angular-frequency signal, which is fed to the input of autoencoder, is used to determine the health...
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Advanced Sensor for Non-Invasive Breast Cancer and Brain Cancer Diagnosis Using Antenna Array with Metamaterial-Based AMC
PublicationMicrowave imaging techniques can identify abnormal cells in early development stages. This study introduces a microstrip patch antenna coupled with artificial magnetic conductor (AMC) to realize improved sensor for non-invasive (early-stage) breast cancer and brain cancer diagnosis. The frequency selectivity of the proposed antenna has been increased by the presence of AMC by creating an additional resonance at 2.276 GHz associated...
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Individual entrepreneurial orientation: comparison of business and STEM students
PublicationAbstract Purpose – The purpose of this study is to determine whether there are differences in Individual Entrepreneurial Orientation (IEO) between students who are doing their major in business studies and the ones whose areas of study are science, technology, engineering, and mathematics (STEM). Design/methodology/approach – The current research investigates which factors and components contribute to EO orientation development...
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Electrophoretic Deposition and Characterization of Chitosan/Eudragit E 100 Coatings on Titanium Substrate
PublicationCurrently, a significant problem is the production of coatings for titanium implants, which will be characterized by mechanical properties comparable to those of a human bone, high corrosion resistance, and low degradation rate in the body fluids. This paper aims to describe the properties of novel chitosan/Eudragit E 100 (chit/EE100) coatings deposited on titanium grade 2 substrate by the electrophoretic technique (EPD). The deposition...
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Improving depth maps of plants by using a set of five cameras
PublicationObtaining high-quality depth maps and disparity maps with the use of a stereo camera is a challenging task for some kinds of objects. The quality of these maps can be improved by taking advantage of a larger number of cameras. The research on the usage of a set of five cameras to obtain disparity maps is presented. The set consists of a central camera and four side cameras. An algorithm for making disparity maps called multiple...
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Wear Resistance Enhancement of Al6061 Alloy Surface Layer by Laser Dispersed Carbide Powders
PublicationIn this paper, results of the experimental study on improving wear resistance in sliding friction of Al-based alloy are presented. The technique used involves the formation of a metal matrix composite (MMC) in the alloy surface layer by laser dispersion of carbide powders such as WC, TiC and SiC. For WC and TiC MMC surface coatings fabricated under conditions typical for most of the technologically relevant solid-state lasers (wavelength...
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Magnetically sensitive fiber probe with nitrogen-vacancy center nanodiamonds integrated in a suspended core
PublicationEfficient collection of photoluminescence arising from spin dynamics of nitrogen vacancy (NV) centers in diamond is important for practical applications involving precise magnetic field or temperature mapping. These goals may be realized by the integration of nanodiamond particles with optical fibers and volumetric doping of the particles alongside the fiber core. That approach combines the advantages of robust axial fixation of...
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Nadmiarowe zgony podczas pandemii COVID-19 w Polsce i ocena skuteczności szczepień
PublicationZ powodu pandemii COVID-19 zmarły miliony ludzi na całym świecie. Jak wynika z wielu badań, szczepienia przeciw chorobie wywołanej wirusem SARS-CoV-2 okazały się środ-kiem ograniczającym skalę zachorowań i liczbę zgonów. Celem badania omawianego w artyku-le jest pomiar skali pandemii w Polsce za pomocą liczby nadmiarowych zgonów w podregio-nach według klasyfikacji NUTS 3 i w grupach wieku, a następnie określenie zależności pomiędzy...
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Beam Steerable MIMO Antenna Based on Conformal Passive Reflectarray Metasurface for 5G Millimeter-Wave Applications
PublicationA conformal reflectarray fed by a dual-band multiple-input multiple-output (MIMO) antenna is proposed for low-cost beam steering applications in 5G Millimeter-wave frequency bands. The beam steering is accomplished by selecting a specific port in the MIMO antenna. Each MIMO port is associated with a beam that points in a different direction due to a conformal reflectarray. This novel reflectarray antenna design has the advantages...
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Massively parallel linear-scaling Hartree–Fock exchange and hybrid exchange–correlation functionals with plane wave basis set accuracy
PublicationWe extend our linear-scaling approach for the calculation of Hartree–Fock exchange energy using localized in situ optimized orbitals [Dziedzic et al., J. Chem. Phys. 139, 214103 (2013)] to leverage massive parallelism. Our approach has been implemented in the ONETEP (Order-N Electronic Total Energy Package) density functional theory framework, which employs a basis of non-orthogonal generalized Wannier functions (NGWFs) to achieve...
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Expedited Geometry Scaling of Compact Microwave Passives by Means of Inverse Surrogate Modeling
PublicationIn this paper, the problem of geometry scaling of compact microwave structures is investigated. As opposed to conventional structures (i.e., constructed using uniform transmission lines), re-design of miniaturized circuits (e.g., implemented with artificial transmission lines, ATSs) for different operating frequencies is far from being straightforward due to considerable cross-couplings between the circuit components. Here, we...
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Historical carpentry corner log joints—Numerical analysis within stochastic framework
PublicationThe paper presents the results of numerical analysis performed on historical, traditional carpentry corner logjoints of two basic topologies: the short-corner dovetail connection and the saddle notch connection. These types of carpentry joints are commonly used in currently preserved objects of wooden architecture. All connections have been modelled in pinewood, which has been defined in the Finite Element software MSC.Marc/Mentat...
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublicationDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
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Bio-based semi-aromatic polyesters for coating applications
PublicationLinear and branched bio-based semi-aromatic (co)polyesters were evaluated as resins for solvent-basedand powder coatings. Dimethyl-2,5-furandicarboxylate (DMF), 2,3-butanediol and various multifunc-tional comonomers were used to synthesize amorphous hydroxyl-end-capped (co)polyesters. The resinswere cross-linked using the -caprolactam blocked trimer of isophorone diisocyanate. Both the solvent-based and powder coatings proved to...
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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublicationThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...
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Detecting Lombard Speech Using Deep Learning Approach
PublicationRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Online sound restoration system for digital library applications.
PublicationAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...