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Wyniki wyszukiwania dla: MACHINE CONTROL
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Properties of Old Concrete Built in the Former Leipziger Palace
PublikacjaThis research aims to determine the mechanical, chemical, and physical properties of old concrete used in the former Leipziger Palace in Wrocław, Poland. The cylindrical specimens were taken from the basement concrete walls using a concrete core borehole diamond drill machine. The determination of the durability and strength of old concrete was based on specified chosen properties of the old concrete obtained through the following...
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Metal–Organic Frameworks (MOFs) for Cancer Therapy
PublikacjaMOFs exhibit inherent extraordinary features for diverse applications ranging from catalysis, storage, and optics to chemosensory and biomedical science and technology. Several procedures including solvothermal, hydrothermal, mechanochemical, electrochemical, and ultrasound techniques have been used to synthesize MOFs with tailored features. A continued attempt has also been directed towards functionalizing MOFs via “post-synthetic...
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublikacjaFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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Detection of Anomalies in the Operation of a Road Lighting System Based on Data from Smart Electricity Meters
PublikacjaSmart meters in road lighting systems create new opportunities for automatic diagnostics of undesirable phenomena such as lamp failures, schedule deviations, or energy theft from the power grid. Such a solution fits into the smart cities concept, where an adaptive lighting system creates new challenges with respect to the monitoring function. This article presents research results indicating the practical feasibility of real‐time...
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Energy-Aware Scheduling for High-Performance Computing Systems: A Survey
PublikacjaHigh-performance computing (HPC), according to its name, is traditionally oriented toward performance, especially the execution time and scalability of the computations. However, due to the high cost and environmental issues, energy consumption has already become a very important factor that needs to be considered. The paper presents a survey of energy-aware scheduling methods used in a modern HPC environment, starting with the...
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Emission of 1.3–10 nm airborne particles from brake materials
PublikacjaOperation of transport vehicle brakes makes a significant contribution to airborne particulate matter in urban areas, which is subject of numerous studies due to the environmental concerns. We investigated the presence and number fractions of 1.3–10 nm airborne particles emitted from a low-metallic car brake material (LM), a non-asbestos organic car brake material (NAO) and a train brake cast iron against a cast iron. Particles...
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Efficiency of Artificial Intelligence Methods for Hearing Loss Type Classification: an Evaluation
PublikacjaThe evaluation of hearing loss is primarily conducted by pure tone audiometry testing, which is often regarded as golden standard for assessing auditory function. If the presence of hearing loss is determined, it is possible to differentiate between three types of hearing loss: sensorineural, conductive, and mixed. This study presents a comprehensive comparison of a variety of AI classification models, performed on 4007 pure tone...
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Experimentally Aided Operational Virtual Prototyping to Predict Best Clamping Conditions for Face Milling of Large-Size Structures
PublikacjaVibrations occurring during milling operations are one of the main issues disturbing the pursuit of better efficiency of milling operations and product quality. Even in the case of a stable cutting process, vibration reduction is still an important goal. One of the possible solutions to obtain it is selection of the favorable conditions for clamping the workpiece to the machine table. In this paper, a method for predicting and...
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A new multi-process collaborative architecture for time series classification
PublikacjaTime 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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Bimodal deep learning model for subjectively enhanced emotion classification in films
PublikacjaThis research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio-video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented....
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Advances and Trends in Non-Conventional, Abrasive and Precision Machining 2021
PublikacjaIn the modern, rapidly evolving industrial landscape, the quest for machining and production processes consistently delivering superior quality and precision is more pronounced than ever. This necessity and imperative are driven by the increasing complexity in the design and manufacturing of mechanical components, an evolution in lockstep with the swift advancements in material science. The real challenge of this evolution lies...
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Potential of Explainable Artificial Intelligence in Advancing Renewable Energy: Challenges and Prospects
PublikacjaModern machine learning (ML) techniques are making inroads in every aspect of renewable energy for optimizationand model prediction. The effective utilization of ML techniques for the development and scaling up of renewable energy systemsneeds a high degree of accountability. However, most of the ML approaches currently in use are termed black box since their work isdifficult to comprehend. Explainable artificial intelligence (XAI)...
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Utilising AI Models to Analyse the Relationship between Battlefield Developments in the Russian-Ukrainian War and Fluctuations in Stock Market Values
PublikacjaThis study examines the impact of battlefield developments in the ongoing Russian–Ukrainian war, which to date has lasted over 1000 days, on the stock prices of defence corporations such as BAE Systems, Booz Allen Hamilton, Huntington Ingalls, and Rheinmetall AG. Stock prices were analysed alongside sentiment data extracted from news articles, and processed using machine learning models leveraging natural...
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Zeiss calibration dataset for high-precision 3D measurement of large industrial components
Dane BadawczeThe dataset is a collection of images, 2D image points, and 3D points. It serves to calibrate a multi-camera robot system for high-precision measurements of large industrial components (more than 1m x 1m). In particular, the system uses a 3D scanner mounted on a robot manipulator and multiple cameras attached to an external frame outside of the robot...
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The influence oil additives on spread cracks in silicon nitride
PublikacjaThe paper presents an experimental study of the influence of oil additives (Cl, S, P, cerium dioxide (CeO2)) on spread cracks in silicon nitride. The additives Cl, S, P are bound in molecules in liquid form soluble in the base oil. The CeO2 is purely in powder form in suspension. The use of CeO2 powder was made based on the good results of polishing of silicon nitride. A ceramic angular contact ball bearing was modelled using a...
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Improving performance of large thrust bearings through modeling and experimentation
PublikacjaLarge thrust bearings are highly loaded machine elements and their failures cause serious losses. Start ups and stoppages of the bearing under load are specially critical regimes of operation. Load carrying capacity depends on the profile of the oil gap. In transient states this profile is also changing. In the design of large thrust bearings minimizing thermo-elastic deformations is an important goal, which can be accomplished...
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Objectivization of phonological evaluation of speech elements by means of audio parametrization
PublikacjaThis study addresses two issues related to both machine- and subjective-based speech evaluation by investigating five phonological phenomena related to allophone production. Its aim is to use objective parametrization and phonological classification of the recorded allophones. These allophones were selected as specifically difficult for Polish speakers of English: aspiration, final obstruent devoicing, dark lateral /l/, velar nasal...
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Moisture content during and after high- and normal-temperature drying processes of wood
PublikacjaThe aim of the article is to present the results of moisture content of wood during and after the high-temperature steam and air–steam mixture drying processes and after an open air-drying process. The knowledge of moisture content changes of wood in the process of its drying is one of the important parameters to economy drying process and to keep the quality of dried wood. Wood samples, namely, spruce (Picea abies K.) and beech...
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Medical Image Dataset Annotation Service (MIDAS)
PublikacjaMIDAS (Medical Image Dataset Annotation Service) is a custom-tailored tool for creating and managing datasets either for deep learning, as well as machine learning or any form of statistical research. The aim of the project is to provide one-fit-all platform for creating medical image datasets that could easily blend in hospital's workflow. In our work, we focus on the importance of medical data anonimization, discussing the...
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Internet photogrammetry as a tool for e-learning
PublikacjaAlong with Internet development, there were interactive applications which allow for remote sensing and photogrammetric analysis. An example of an application that can provide Earth images and make it possible to measure distances in these images is Google Earth. The authors, who have experience from 2001-2015 argue that it is possible and it is important to create more advanced photogrammetric network applications. In this there...
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Adaptive system for recognition of sounds indicating threats to security of people and property employing parallel processing of audio data streams
PublikacjaA system for recognition of threatening acoustic events employing parallel processing on a supercomputing cluster is featured. The methods for detection, parameterization and classication of acoustic events are introduced. The recognition engine is based onthreshold-based detection with adaptive threshold and Support Vector Machine classifcation. Spectral, temporal and mel-frequency descriptors are used as signal features. The...
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Music information retrieval—The impact of technology, crowdsourcing, big data, and the cloud in art.
PublikacjaThe exponential growth of computer processing power, cloud data storage, and crowdsourcing model of gathering data bring new possibilities to music information retrieval (mir) field. Mir is no longer music content retrieval only; the area also comprises the discovery of expressing feelings and emotions contained in music, incorporating other than hearing modalities for helping this issue, users’ profiling, merging music with social...
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Chemical, Physical, and Mechanical Properties of 95-Year-Old Concrete Built-In Arch Bridge
PublikacjaThis research aimed to determine the durability and strength of an old concrete built-in arch bridge based on selected mechanical, physical, and chemical properties of the concrete. The bridge was erected in 1925 and is located in Jagodnik (northern Poland). Cylindrical specimens were taken from the side ribs connected to the top plate using a concrete core borehole diamond drill machine. The properties of the old concrete were...
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A Critical Reanalysis of Uncontrollable Washboarding Phenomenon in Metal Band Sawing
PublikacjaThe article analyzes the cutting process of hard bars. Investigations conducted in industrial conditions demonstrated the presence of surface errors in the machined workpieces in the form of washboard patterns. The purpose of this study was to analyze the results of cutting on band sawing machines with different band saw blades. The cutting processes were conducted on three different horizontal band sawing machine types. Analyzed...
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Exploring the influence of personal factors on physiological responses to mental imagery in sport
PublikacjaImagery is a well-known technique in mental training which improves performance efficiency and influences physiological arousal. One of the biomarkers indicating the amount of physiological arousal is skin conductance level (SCL). The aim of our study is to understand how individual differences in personality (e.g. neuroticism), general imagery and situational sport anxiety are linked to arousal measuring with SCL in situational...
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How Can We Identify Electrophysiological iEEG Activities Associated with Cognitive Functions?
PublikacjaElectrophysiological activities of the brain are engaged in its various functions and give rise to a wide spectrum of low and high frequency oscillations in the intracranial EEG (iEEG) signals, commonly known as the brain waves. The iEEG spectral activities are distributed across networks of cortical and subcortical areas arranged into hierarchical processing streams. It remains a major challenge to identify these activities in...
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Privacy-Preserving, Scalable Blockchain-Based Solution for Monitoring Industrial Infrastructure in the Near Real-Time
PublikacjaThis paper proposes an improved monitoring and measuring system dedicated to industrial infrastructure. Our model achieves security of data by incorporating cryptographical methods and near real-time access by the use of virtual tree structure over records. The currently available blockchain networks are not very well adapted to tasks related to the continuous monitoring of the parameters of industrial installations. In the database...
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Effective density of airborne wear particles from car brake materials
PublikacjaPeople living in urban environments are subject to high health risks due to various anthropogenic sources of airborne particulate matter, including wear of transport vehicle brakes. Studies of airborne particles often require an estimate of the effective particle density, a property that allows correct matching of mass and size characteristics measured by different aerosol instruments. In this study we investigated the effective...
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Porosity and shape of airborne wear microparticles generated by sliding contact between a low-metallic friction material and a cast iron
PublikacjaThe wear of brakes in transport vehicles is one of the main anthropogenic sources of airborne particulate matter in urban environments. The present study deals with the characterisation of airborne wear microparticles from a low-metallic friction material / cast iron pair used in car brakes. Particles were generated by a pin-on-disc machine in a sealed chamber at sliding velocity of 1.3 m/s and contact pressure of 1.5 MPa. They...
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University Students’ Research on Artificial Intelligence and Knowledge Management. A Review and Report of Multi-case Studies
PublikacjaLeading technologies are very attractive for students preparing their theses as the completion of their studies. Such an orientation of students connected with professional experiences seems to be a crucial motivator in the research in the management and business areas where these technologies condition the development of professional activities. The goal of the paper is the analysis of students’ thesis topics defended in the last...
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Desirability-based optimization of dual-fuel diesel engine using acetylene as an alternative fuel
Publikacjahe study examined the dual-fuel engine performance employing acetylene gas as primary fuel and diesel as pilot fuel. The engine's operational parameters were adjusted using the Box-Behnken design, and the results were recorded. The best operating settings were yielded as 81.25 % engine load, 4.48 lpm acetylene gas flow rate and the compression ratio were 18. At this optimized setting the BTE was 27.1 % and the engine emitted 360...
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An Empirical Study of a Dynamic Stop Loss Strategy with Deep Reinforcement Learning on the NASDAQ Stock Market
PublikacjaThe objective of this paper is to empirically investigate the efficacy of using Deep Reinforcement Learning (DRL) to maximize investment returns by incorporating expected optimal closing prices of long positions into a daily strategy. This paper extends existing research on the impact of stop-loss orders on investment strategy results and brings contribution of these orders to trading strategies into a completely new perspective....
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Teaching High–performance Computing Systems – A Case Study with Parallel Programming APIs: MPI, OpenMP and CUDA
PublikacjaHigh performance computing (HPC) education has become essential in recent years, especially that parallel computing on high performance computing systems enables modern machine learning models to grow in scale. This significant increase in the computational power of modern supercomputers relies on a large number of cores in modern CPUs and GPUs. As a consequence, parallel program development based on parallel thinking has become...
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Structural insights, biocatalytic characteristics, and application prospects of lignin-modifying enzymes for sustainable biotechnology
PublikacjaLignin modifying enzymes (LMEs) have gained widespread recognition in depolymerization of lignin polymers by oxidative cleavage. LMEs are a robust class of biocatalysts that include lignin peroxidase (LiP), manganese peroxidase (MnP), versatile peroxidase (VP), laccase (LAC), and dye-decolorizing peroxidase (DyP). Members of the LMEs family act on phenolic, non-phenolic substrates and have been widely researched for valorization...
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HIERARCHICAL CYCLES IN MODERN POWER SYSTEMS – EXERGY ANALYSIS UNDER PART LOADS
PublikacjaThe aim of the paper is to investigate thermodynamic efficiency of advanced hierarchic power cyclesunder partial loads by using of exergy analyze. Advanced hierarchical power systems arecomposed of few energy conversion cycles, most common are steam and gas cycles in various configurations, but they may contain fuel cells, ORC, lithium bromide absorption chillers and others. Moreover hierarchical cycles can be powered by several...
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Diagnostic system of wheeled tractors detecting four defect's categories
PublikacjaIn a classical approach to damage diagnosis, the technical condition of an analyzed machine is identified based on the measured symptoms, such as performance, thermal state or vibration parameters. In wheeled tractor the fundamental importance has monitoring and diagnostics during exploitation concerning technical inspection and fault element localizations. The main functions of a diagnostic system are: monitoring tractor components...
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Programowo-sprzętowa platforma symulacyjna - Hardware In the Loop - zaawansowanego układu sterowania poziomem wody w pionowej wytwornicy pary elektrowni jądrowej
PublikacjaW artykule przedstawiono koncepcję programowo-sprzętowej platformy symulacyjnej wykorzystującej technikę symulacji w pętli sprzętowej HIL (ang. Hardware In The Loop simulation), wykorzystanej dla potrzeb projektowania i weryfikacji w czasie rzeczywistym (ang. Real Time) zaawansowanych algorytmów sterowania poziomem wody w pionowej wytwornicy pary elektrowni jądrowej. Jej głównymi elementami sa: środowisko czasu rzeczywistego Matlab/Simulink...
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Multicomponent ionic liquid CMC prediction
PublikacjaWe created a model to predict CMC of ILs based on 704 experimental values published in 43 publications since 2000. Our model was able to predict CMC of variety of ILs in binary or ternary system in a presence of salt or alcohol. The molecular volume of IL (Vm), solvent-accessible surface (Sˆ), solvation enthalpy (DsolvGN), concentration of salt (Cs) or alcohol (Ca) and their molecular volumes (Vms and Vma, respectively) were chosen...
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Programowo-sprzętowa platforma symulacyjna - Hardware In the Loop - zaawansowanego układu sterowania poziomem wody w pionowej wytwornicy pary elektrowni jądrowej
PublikacjaW artykule przedstawiono koncepcję programowo-sprzętowej platformy symulacyjnej wykorzystującej technikę symulacji w pętli sprzętowej HIL (ang. Hardware In The Loop simulation), wykorzystanej dla potrzeb projektowania i weryfikacji w czasie rzeczywistym (ang. Real Time) zaawansowanych algorytmów sterowania poziomem wody w pionowej wytwornicy pary elektrowni jądrowej. Jej głównymi elementami są: środowisko czasu rzeczywistego Matlab/Simulink...
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The Influence of Workpiece Hardness on Plate Temperature during One Side Lapping
PublikacjaLapping leads to a surface with low roughness and high precision. Because of required parts accuracy tool flatness is the key to the successful machining. To avoid its excessive thermal expansion, plate temperature research was taken. The goal was to determine the correlation between the basic lapping conditions and wheel temperature. In work Bulsara et al. authors developed model to estimate the maximum and average temperature...
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A System for Heart Sounds Classification
PublikacjaThe future of quick and efficient disease diagnosis lays in the development of reliable non-invasive methods. As for the cardiac diseases – one of the major causes of death around the globe – a concept of an electronic stethoscope equipped with an automatic heart tone identification system appears to be the best solution. Thanks to the advancement in technology, the quality of phonocardiography signals is no longer an issue. However,...
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The experimental identification of the dynamic coefficients of two hydrodynamic journal bearings operating at constant rotational speed and under nonlinear conditions.
PublikacjaHydrodynamic bearings are commonly used in ship propulsion systems. Typically, they are calculated using numerical or experimental methods. This paper presents an experimental study through which it has been possible to estimate 24 dynamic coefficients of two hydrodynamic slide bearings operating under nonlinear conditions. During the investigation, bearing mass coefficients are identified by means of a newly developed algorithm....
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Review of Segmentation Methods for Coastline Detection in SAR Images
PublikacjaSynthetic aperture radar (SAR) images acquired by airborne sensors or remote sensing satellites contain the necessary information that can be used to investigate various objects of interest on the surface of the Earth, including coastlines. The coastal zone is of great economic importance and is also very densely populated. The intensive and increasing use of coasts and changes of coastlines motivate researchers to try to assess...
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Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublikacjaThe growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...
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Axial-Flux Permanent-Magnet Dual-Rotor Generator for a Counter-Rotating Wind Turbine
PublikacjaCoaxial counter-rotating propellers have been widely applied in ships and helicopters for improving the propulsion efficiency and offsetting system reactive torques. Lately, the counter-rotating concept has been introduced into the wind turbine design. Distributed wind power generation systems often require a novel approach in generator design. In this paper, prototype development of axial-flux generator with a counter-rotating...
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A note on the applications of artificial intelligence in the hospitality industry: preliminary results of a survey
PublikacjaIntelligent technologies are widely implemented in different areas of modern society but specific approaches should be applied in services. Basic relationships refer to supporting customers and people responsible for services offering for these customers. The aim of the paper is to analyze and evaluate the state-of-the art of artificial intelligence (AI) applications in the hospitality industry. Our findings show that the major...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublikacjaResearchers 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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Detecting Lombard Speech Using Deep Learning Approach
PublikacjaRobust 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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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublikacjaSatellite 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...
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Preferred Benchmarking Criteria for Systematic Taxonomy of Embedded Platforms (STEP) in Human System Interaction Systems
PublikacjaThe rate of progress in the field of Artificial Intelligence (AI) and Machine Learning (ML) has significantly increased over the past ten years and continues to accelerate. Since then, AI has made the leap from research case studies to real production ready applications. The significance of this growth cannot be undermined as it catalyzed the very nature of computing. Conventional platforms struggle to achieve greater performance...