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Search results for: DEEP%20NEURAL%20NETWORKS
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Hybrid Processing by Turning and Burnishing of Machine Components
PublicationThe paper presents a method of hybrid manufacturing process of long 5 shafts and deep holes by simultaneous turning and burnishing method. The tech- 6 nological results of the research focus on the influence of the basic technological 7 parameters of this process on the surface roughness of piston rods of hydraulic 8 cylinders. Research results are presented in the graphs as well as mathematical 9 formula. Set of samples were made...
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Detailed studies of superconducting properties of Y2Pd1.25Ge2.75
PublicationWe report a successful synthesis of a high-purity intermetallic germanide Y2Pd1.25Ge2.75, crystallizing in the disordered variant of the AlB2-type structure. A single-phase sample was obtained via arc-melting by deliberately tuning the composition out of the ideal 2:1:3 ratio. Specific heat, electrical resistivity and magnetization measurements show that the compound is a weakly-coupled (λ e-p = 0.58) type-II superconductor with...
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Towards a modification of a regulatory framework aiming at bunker oil spill prevention from ships - A design aspect of bunker tanks vents location guided by CFD simulations
PublicationAlthough accidental bunker oil spills at seaway are relatively rare events, they can be pose real threat to the natural marine environment. One of the reasons for the bunker spill to occur is a design failure; one of the ways it can demonstrate is an improper location or height of vent heads, leading to a bunker oil discharge during heavy rolling, due to sloshing phenomenon. Design of a ship and her systems is guided by various...
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Method for Clustering of Brain Activity Data Derived from EEG Signals
PublicationA method for assessing separability of EEG signals associated with three classes of brain activity is proposed. The EEG signals are acquired from 23 subjects, gathered from a headset consisting of 14 electrodes. Data are processed by applying Discrete Wavelet Transform (DWT) for the signal analysis and an autoencoder neural network for the brain activity separation. Processing involves 74 wavelets from 3 DWT families: Coiflets,...
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A general approach to study molecular fragmentation and energy redistribution after an ionizing event
PublicationWe propose to combine quantum chemical calculations, statistical mechanical methods, and photoionization and particle collision experiments to unravel the redistribution of internal energy of the furan cation and its dissociation pathways. This approach successfully reproduces the relative intensity of the different fragments as a function of the internal energy of the system in photoelectron–photoion coincidence experiments and...
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Experimental study on the selected aspects of bow thruster generated flow field at ship zero-speed conditions
PublicationThe paper presents the results of experimental study on the interaction between the bow thrusters understood as the flow field changes generated by bow tunnel thruster in deep water conditions operated as a single and twin units. The research was limited to zero-speed case for the ship dead in the water. The influence of the hull form and jet spread between the neighbouring thrusters for several combinations of the applied bow...
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Comparison of the exponential thermal transient parameterization methods with the SMTP method in the unipedicled DIEP flap computer modelling and simulation
PublicationThe aim of this paper is to compare the spatial contrast of the image descriptors obtained via three different thermal transient parameterization methods in Active Dynamic Thermography. The thermal constants and amplitude values of the one- and two- exponential parametrization are compared to the Simplified Magnitude-Temporal Parametrization method (SMTP). The comparison is performed using the data obtained by simulating the cold...
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Grade of service determination methodology in IP networks with SIP protocol
PublicationAlthough Grade of Service is very important in VoIP providers evaluation, We wasn't able to find any paper regarding the topic of measuring GoS variables for IP networks utilizing SIP, which are defined like for PSTN/ISDN/GSM networks (post-selection delay, answering delay, release delay, or probability of end-to-end blocking). Due to the lack of research in this field, it was necessary to start from defining measures and cover...
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Non-invasive blood glucose monitoring with Raman spectroscopy: prospects for device miniaturization
PublicationThe number of patients with diabetes has reached over 350 million, and still continues to increase. The need for regular blood glucose monitoring sparks the interest in the development of modern detection technologies. One of those methods, which allows for noninvasive measurements, is Raman spectroscopy. The ability of infrared light to penetrate deep into tissues allows for obtaining measurements through the skin without its...
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublicationRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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Comparison of the Ability of Neural Network Model and Humans to Detect a Cloned Voice
PublicationThe vulnerability of the speaker identity verification system to attacks using voice cloning was examined. The research project assumed creating a model for verifying the speaker’s identity based on voice biometrics and then testing its resistance to potential attacks using voice cloning. The Deep Speaker Neural Speaker Embedding System was trained, and the Real-Time Voice Cloning system was employed based on the SV2TTS, Tacotron,...
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Sensors and Sensor’s Fusion in Autonomous Vehicles
PublicationAutonomous vehicle navigation has been at the center of several major developments, both in civilian and defense applications. New technologies such as multisensory data fusion, big data processing, and deep learning are changing the quality of areas of applications, improving the sensors and systems used. New ideas such as 3D radar, 3D sonar, LiDAR, and others are based on autonomous vehicle revolutionary development. The Special...
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Neural network model of ship magnetic signature for different measurement depths
PublicationThis paper presents the development of a model of a corvette-type ship’s magnetic signature using an artificial neural network (ANN). The capabilities of ANNs to learn complex relationships between the vessel’s characteristics and the magnetic field at different depths are proposed as an alternative to a multi-dipole model. A training dataset, consisting of signatures prepared in finite element method (FEM) environment Simulia...
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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublicationThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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Is Germany a Hub of ‘Factory Europe’ for CEE Countries?
PublicationThe goal of the paper is to decompose gross exports and imports to/from Germany for seven selected economies in Central and Eastern Europe (CEE): the Czech Republic, Estonia, Hungary, Lithuania, Latvia, Poland and Slovakia for 2000 and 2014, in order to identify the role of Germany in absorbing, reflecting and redirecting CEE trade. The authors use a gross trade decomposition proposed by Bonin and Mancini (2017), which is the extended...
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An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key
PublicationThe topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...
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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublicationThis work is part of an effort for the development of a Cognitive Vision Platform for Hazard Control (CVP-HC) for applications in industrial workplaces, adaptable to a wide range of environments. The paper focuses on hazards resulted from the nonuse of personal protective equipment (PPE). Given the results of previous analysis of supervised techniques for the problem of classification of a few PPE (boots, hard hats, and gloves...
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Review of the Complexity of Managing Big Data of the Internet of Things
PublicationTere is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing feld of the Internet of Tings (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description...
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Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention
PublicationThis paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction and data augmentation based on Neural Text-To-Speech (TTS). In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus. We propose an attention-based deep learning model that automatically de...
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The Influence of the Cuboid Float’s Parameters on the Stability of a Floating Building
PublicationUsually, the concept of sufficient stability of a floating structure is connected with the capacity to keep a small heel angle despite the moment of heeling. The variable responsible for these characteristics is the initial metacentric height, which is the relation between the hydrostatic features of the pontoon and the mass properties of the entire object. This article answers the questions of how heavy the floating system should...
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Syntheses and structures of the first terminal phosphanylphosphido complex of hafnium [cp2hf(cl){η1-(me3si)p-p(net2)2}] and the firstzirconocene-phosphanylphosphinidene dimer [cp2zr{μ2-p-p(net2)2}2zrcp2]
PublicationReactions of (Et2N)2P-P(SiMe3)Li with [Cp2MCl2] (M= Zr, Hf) in toluene or pentane yield the related terminal phosphanylphosphido complexes [Cp2M(Cl){η1-(Me3Si)P-P(NEt2)2}]. The solid statestructure of [Cp2Hf(Cl){η1-(Me3Si)P-P(NEt2)2}] was established by single crystal X-ray diffraction. The reaction of (Et2N)2P-P(SiMe3)Li with [Cp2ZrCl2] in THF or DME solutions leads to the formationof deep red crystals of the first neutral diamagnetic...
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Hybrid DUMBRA: an efficient QoS routing algorithm for networks with DiffServ architecture
PublicationDynamic routing is very important issue of current packet networks. It may support the QoS and help utilize available network resources. Unfortunately current routing mechanisms are not sufficient to fully support QoS. Although many research has been done in this area no generic QoS routing algorithm has been proposed that could be used across all network structures. Existing QoS routing algorithms are either dedicated to limited...
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Dynamic soil improvement by hybrid technologies
PublicationHybrid method of subsoil improvement for road embankment foundation is described. This method is composed of two wellknown methods: dynamic replacement (DR) and microblasting (DDC) one (Deep Dynamic Compaction). The method was used for both the strengthening of the fully saturated organic subsoil as well as for acceleration of the consolidation of the organic layers. The practice ensures the expected results. A proper example on...
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Surfactants application in sample preparation techniques: Insights, trends, and perspectives
PublicationSince the implementation of Green Chemistry into analytical practice, significant efforts have been made to improve the sustainability of chemical analysis. These include reducing the use of hazardous chemicals and solvents, minimizing waste, and improving energy efficiency. Surfactants can be applied in chemical analysis as an environmentally friendly alternative to conventional solvents and chemicals. The use of surfactants can...
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Hybrid cross-linked chitosan/protonated-proline:glucose DES membranes with superior pervaporation performance for ethanol dehydration
PublicationThis work explores a protonated L-proline:glucose (molar ratio 5:1) deep eutectic solvent (DES) in fabricating biopolymer membranes utilizing chitosan (CS). Initially, the miscibility of CS and DES to prepare homogeneous dense blend membranes has been investigated. Different techniques, such as scanning electron microscopy, contact angle (CA), atomic force microscopy (AFM), Fourier transformed infrared spectroscopy (FTIR) and swelling...
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Intelligent Audio Signal Processing − Do We Still Need Annotated Datasets?
PublicationIn this paper, intelligent audio signal processing examples are shortly described. The focus is, however, on the machine learning approach and datasets needed, especially for deep learning models. Years of intense research produced many important results in this area; however, the goal of fully intelligent signal processing, characterized by its autonomous acting, is not yet achieved. Therefore, a review of state-of-the-art concerning...
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IFE: NN-aided Instantaneous Pitch Estimation
PublicationPitch estimation is still an open issue in contemporary signal processing research. Nowadays, growing momentum of machine learning techniques application in the data-driven society allows for tackling this problem from a new perspective. This work leverages such an opportunity to propose a refined Instantaneous Frequency and power based pitch Estimator method called IFE. It incorporates deep neural network based pitch estimation...
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Monitoring of absorptive model biogas purification process using sensor matrices and gas chromatography
PublicationThis study examined the process of purifying model biogas using a new type of absorbent based on a Deep Eutectic Solvent (DES) and a commercially available absorbent (Genosorb) to remove acetone, toluene, and cyclohexane. The main aim of the research was to control the purification efficiency using gas chromatography (GC) and an alternative method based on sensor matrices (SM). As a result of comparing the multidimensional SM signals...
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Multi-task Video Enhancement for Dental Interventions
PublicationA microcamera firmly attached to a dental handpiece allows dentists to continuously monitor the progress of conservative dental procedures. Video enhancement in video-assisted dental interventions alleviates low-light, noise, blur, and camera handshakes that collectively degrade visual comfort. To this end, we introduce a novel deep network for multi-task video enhancement that enables macro-visualization of dental scenes. In particular,...
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublicationThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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Molybdenum-uranium-vanadium geochemistry in the lower Paleozoic Alum Shale of Scandinavia: Implications for vanadium exploration
PublicationThis paper investigates the hyper-enrichments of molybdenum (Mo), uranium (U), and vanadium (V) in the lower Paleozoic, Alum Shale of Denmark, Sweden, Norway, and Estonia. Molybdenum and U are mainly associated with organic matter and the highest contents are found in the Furongian part of the Alum Shale. This Furongian hyper-enrichment of Mo and U commenced with the Steptoean Positive Carbon Isotope Excursion (SPICE) event. The...
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Numerical and experimental study on effect of boundary conditions during testing of stiffened plates subjected to compressive loads
PublicationThis study analyses the effect of boundary conditions during testing on the structural behaviour stiffened plates with different thicknesses subjected to compressive loads. The goal of the compressive tests is to analyse the ultimate strength of a stiffened plate. During the test, relevant physical quantities are measured and investigated. The supporting structure's behaviour is investigated by analysing the force-displacements...
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Data Acquisition and Processing for GeoAI Models to Support Sustainable Agricultural Practices
PublicationThere are growing opportunities to leverage new technologies and data sources to address global problems related to sustainability, climate change, and biodiversity loss. The emerging discipline of GeoAI resulting from the convergence of AI and Geospatial science (Geo-AI) is enabling the possibility to harness the increasingly available open Earth Observation data collected from different constellations of satellites and sensors...
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Electron scattering from tin tetrachloride (SnCl4) molecules
PublicationAbsolute grand-total cross section (TCS) for electron scattering from a tin tetrachloride, SnCl4, molecule was measured at electron-impact energies ranging from 0.6 to 300 eV, in the linear electron-transmission experiment. The measured TCS energy dependence shows two very pronounced enhancements peaking near 1.2 eV and around 9.5 eV, separated with a deep minimum centered close to 3 eV. The low energy structure is attributed to...
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Artificial intelligence for software development — the present and the challenges for the future
PublicationSince the time when first CASE (Computer-Aided Software Engineering) methods and tools were developed, little has been done in the area of automated creation of code. CASE tools support a software engineer in creation the system structure, in defining interfaces and relationships between software modules and, after the code has been written, in performing testing tasks on different levels of detail. Writing code is still the task...
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Self-Association of Amphotericin B: Spontaneous Formation of Molecular Structures Responsible for the Toxic Side Effects of the Antibiotic
PublicationAmphotericin B (AmB) is a lifesaving antibiotic used to treat deep-seated mycotic infections. Both the pharmaceutical activity and highly toxic side effects of the drug rely on its interaction with biomembranes, which is governed by the molecular organization of AmB. In the present work we present detailed analysis of self-assembly of AmB molecules in different environments, interesting from the physiological standpoint, based...
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A Triplet-Learnt Coarse-to-Fine Reranking for Vehicle Re-identification
PublicationVehicle re-identification refers to the task of matching the same query vehicle across non-overlapping cameras and diverse viewpoints. Research interest on the field emerged with intelligent transportation systems and the necessity for public security maintenance. Compared to person, vehicle re-identification is more intricate, facing the challenges of lower intra-class and higher inter-class similarities. Motivated by deep...
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Perspectives on the replacement of harmful organic solvents in analytical methodologies: a framework toward the implementation of a generation of eco-friendly alternatives
PublicationVolatile organic solvents derived from non-renewable fossil feedstocks are commonplace in analytical laboratories. In spite of their convenient performance in countless unit operations, their environmental, health and safety issues represent a major area of concern. The progressive replacement of organic solvents obtained from fossil resources by eco-friendly alternatives would involve remarkable advances within the framework of...
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Multiclass AdaBoost Classifier Parameter Adaptation for Pattern Recognition
PublicationThe article presents the problem of parameter value selection of the multiclass ``one against all'' approach of an AdaBoost algorithm in tasks of object recognition based on two-dimensional graphical images. AdaBoost classifier with Haar features is still used in mobile devices due to the processing speed in contrast to other methods like deep learning or SVM but its main drawback is the need to assembly the results of binary...
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Lipids and Food Quality
PublicationThis chapter deals with lipids present in food as well as their chemical, biological, and functional properties. The chapter begins with a presentation of the main groups of lipids including their chemical structure and physical properties. The physical properties of lipids affecting food processing are covered. Then, the role of lipids in human nutrition is presented. This is followed by a description of the undesirable changes...
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Merging Proline:Xylitol Eutectic Solvent in Crosslinked Chitosan Pervaporation Membranes for Enhanced Water Permeation in Dehydrating Ethanol
PublicationThe scope of this research aims at merging a new deep eutectic mixture (DES) into a biopolymer-based membrane for a pervaporation application in dehydrating ethanol. Herein, an L-proline:xylitol (at 5:1) eutectic mixture was successfully synthesized and blended with chitosan (CS). A complete characterization of the hybrid membranes, in terms of morphology, solvent uptake, and hydrophilicity, has been conducted. As part of their...
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Textile reinforced concrete members subjected to tension, bending, and in-plane loads: Experimental study and numerical analyses
PublicationTextile reinforced concrete has raised increasing research interest during the last years, mainly due to its potential to be used for freeform shell structures involving complex load situations. Yet, most experimental work has focused on test setups with primarily uniaxial loading. In the current work, such setups are complemented with a novel test setup of deep beams, including in-plane bending and shear. Further, nonlinear finite...
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Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review
PublicationBackground: In the context of Warehouse Management Systems, knowledge related to motion trajectory prediction methods utilizing machine learning techniques seems to be scattered and fragmented. Objective: This study seeks to fill this research gap by using a systematic literature review approach. Methods: Based on the data collected from Google Scholar, a systematic literature review was performed, covering the period from 2016...
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Electrocatalytic oxidation of methanol, ethylene glycol and glycerine in alkaline media on TiO2 nanotubes decorated with AuCu nanoparticles for an application in fuel cells
PublicationIn this work, we present the catalytic and photocatalytic activity of AuCu nanostructures obtained on TiO2 nanotubes toward methanol, ethylene glycol and glycerine oxidation. The electrode material is prepared by anodization of Ti foil, thin AuCu layer sputtering and rapid thermal treatment under argon atmosphere. Scanning electron microscopy images confirmed the presence of ordered tubular architecture of TiO2 as well as nanoparticles...
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Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublicationThis work addresses artificial-intelligence-based buried object characterization using 3-D full-wave electromagnetic simulations of a ground penetrating radar (GPR). The task is to characterize cylindrical shape, perfectly electric conductor (PEC) object buried in various dispersive soil media, and in different positions. The main contributions of this work are (i) development of a fast and accurate data driven surrogate modeling...
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Architectural Modifications to Enhance Steganalysis with Convolutional Neural Networks
PublicationThis paper investigates the impact of various modifications introduced to current state-of-the-art Convolutional Neural Network (CNN) architectures specifically designed for the steganalysis of digital images. Usage of deep learning methods has consistently demonstrated improved results in this field over the past few years, primarily due to the development of newer architectures with higher classification accuracy compared to...
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Exploring Neural Networks for Musical Instrument Identification in Polyphonic Audio
PublicationThe purpose of this paper is to introduce neural network-based methods that surpass state-of-the-art (SOTA) models, either by training faster or having simpler architecture, while maintaining comparable effectiveness in musical instrument identification in polyphonic music. Several approaches are presented, including two authors’ proposals, i.e., spiking neural networks (SNN) and a modular deep learning model named FMCNN (Fully...
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Detecting Objects of Various Categories in Optical Remote Sensing Imagery Using Neural Networks
PublicationThe effective detection of objects in remote sensing images is of great research importance, so recent years have seen a significant progress in deep learning techniques in this field. However, despite much valuable research being conducted, many challenges still remain. A lot of research projects focus on detecting objects of a single category (class), while correctly detecting objects of different categories is much harder. The...
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Hybridization of valuation procedures as a medicine supporting the real estate market and sustainable land use development during the covid-19 pandemic and afterwards
PublicationCurrently we are facing the pandemic situation that occur all over the world. Regardless the country or even the region, the negative consequences that are expected could be very big and the level of crisis is not predictable. This situation is the challenge for the real estate market as well. Due to this fact, the authors believe that there is the time when deep transformation of approaches, procedures and awareness related to...
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MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publication—Machine Learning (ML) methods have been used with varying degrees of success on protein prediction tasks, with two inherent limitations. First, prediction performance often depends upon the features extracted from the proteins. Second, experimental data may be insufficient to construct reliable ML models. Here we introduce MP3vec, a transferable representation for protein sequences that is designed to be used specifically for sequence-to-sequence...