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Wyniki wyszukiwania dla: DEEP-LEVEL MINING
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Deep eutectic solvents – Ideal solution for clean air or hidden danger?
PublikacjaThe industrial sector is one of the fastest-growing sources of greenhouse gases, due to its excessive energy consumption to meet the rapidly growing demand for energy-intensive products. The use of deep eutectic solvents (DESs) has been studied extensively in order to cope with these harmful gases, but their usage can be an issue in respect to ecological reasons. Do deep eutectic solvents harm the atmosphere? Yes, these solvents...
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Reflections on the relationship-level between national- and voivodship-level planning In Poland
PublikacjaPrzedstawiono stan i ocenę procesu planowania, przesłanki i zamierzenia zmian oraz wybrane propozycje w zakresie relacji między planowaniem krajowym a planowaniem rozwoju i zagospodarowania przestrzennego na poziomie województwa.
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Deep Instance Segmentation of Laboratory Animals in Thermal Images
PublikacjaIn this paper we focus on the role of deep instance segmentation of laboratory rodents in thermal images. Thermal imaging is very suitable to observe the behaviour of laboratory animals, especially in low light conditions. It is an non-intrusive method allowing to monitor the activity of animals and potentially observe some physiological changes expressed in dynamic thermal patterns. The analysis of the recorded sequence of thermal...
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublikacjaWe present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...
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Deep eutectic solvents based assay for extraction and determination of zinc in fish and eel samples using FAAS
PublikacjaA new assay based on effective (high recovery) extraction by means of deep eutectic solvents (DESs) was developed for ppb level determination of zinc in fishes and eel samples. Choline chloride and Phenol in a 1:2 M ratio was selected as optimal DES-based extraction solvent. 8-Hydroxy quinoline was used as a chelating agent for zinc ions. The optimized conditions were found at pH value of 8, ligand concentration of 10 mg/L, THF...
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Level of public finances decentralization in European Union countries
PublikacjaResearch background: Despite of the universality of the implementation in democratic countries the principle of decentralization resulting from the belief that it is an instrument to improve the efficiency of public funds management, both the scope of public services and the level of decentralization in individual countries are not identical. Purpose of the article: Comparison the scope of fiscal decentralization...
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Integrity level verification for safety-related functions
PublikacjaThis article describes methods for safety integrity level (SIL) verification of safety-related functions with regard to probabilistic criteria given international standards IEC 61508 and IEC 61511. These functions are to be realized using the electrical, electronic and programmable electronic (E/E/PE) systems or safety instrumented systems (SIS). Some methods are proposed for quantitative probabilistic modelling taking into account...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublikacjaIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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The impact of the shape of deep drilled well screen openings on the filtration process in full saturation conditions
PublikacjaThe authors propose a supplementary method of modelling seepage flow around the deep drilled well screen. The study applies 3D numerical modelling (FEM) in order to provide an in-depth analysis of the seepage process. The analysis of filtration parameters (flow distribution q(x,t) and pressure distribution p) was conducted using the ZSoil.PC software system. The analysis indicates that the shape of perforation is of secondary importance...
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublikacjaThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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Modelling selected road safety measures at the regional level in Europe
PublikacjaRegions are Europe’s basic levels of management. The literature was reviewed to identify regional safety analyses and some of the factors that are important for road safety in the regions. Next, data were collected atthe regional NUTS 2 level in Europe for the years 1999-2008. An analysis of the data helped identify f actors which have the strongest bearing on fatalities and other safety measures. This paper presents the initial...
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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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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublikacjaBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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Sensitivity of the Baltic Sea level prediction to spatial model resolution
Publikacjahe three-dimensional hydrodynamic model of the Baltic Sea (M3D) and...
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Evaluation of Facial Pulse Signals Using Deep Neural Net Models
PublikacjaThe reliable measurement of the pulse rate using remote photoplethysmography (PPG) is very important for many medical applications. In this paper we present how deep neural networks (DNNs) models can be used in the problem of PPG signal classification and pulse rate estimation. In particular, we show that the DNN-based classification results correspond to parameters describing the PPG signals (e.g. peak energy in the frequency...
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Enhanced method of DS-CDMA low level singnals detection
PublikacjaThe following article comprises three main parts. The first one generally describes two methods of low level signals detection which are in the interest of this study. The signal spectrum averaging technique is shown as well as the method exploiting averaged spectrum of the signal raised to the power of 2n (nN). Additionally, this section briefly presents proposed enhancements and modifications of these two solutions, which allow...
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MODEL OF MULTILEVEL STOCHASTIC ANALYSIS OF ROAD SAFETY ON REGIONAL LEVEL
PublikacjaIn this paper multilevel approach to the issue of road safety level on the road network of European regions, classified as NUTS 2 in statistical databases of the European Union, has been presented. Following the pattern of many publications on road safety it has been assumed that the risk calculated as the number of death casualties in road accidents per 100,000 inhabitants of a given region has Poisson distribution. Therefore,...
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A Five-Leg Three-Level Dual-Output Inverter
PublikacjaClassical 3-level dual-output inverter, 3-L DOI, involves two similar 3-level inverters that provides a pair of 3-phase output voltages with same or different frequencies from common input voltage source. Flexibility of either operation of the constituting inverters is evident in this DOI; but total duplication of power switches is a major drawback. State of the art coupled 3-L DOIs reduce this drawback by providing series-shared...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublikacjaIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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The method of strengthening the church building in terms of the planned mining exploitation
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On a Certain Research Gap in Big Data Mining for Customer Insights
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A POLICY OF DEVELOPMENT OF POST-MINING LAND ON THE EXAMPLE OF ZIELONA GÓRA
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Introducing the concept of Decisional DNA-Based web content mining
PublikacjaPrzedstawiono koncepcje zastosowania struktury reprezentacji wiedzy opartej na decyzyjnym DNA w procesie wyszukiwania informacji w internecie. Dokonano analizy eksperymentow tak wspomaganego wyszukiwania oraz sformulowano wnioski na temat przyszlych badan prowadzacych do dalszej integracji procesu wyszukiwania z doswiadczeniami zdobytymi w trakcie tego wyszukiwania.
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Mining e-mail message sequences from log data
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Mining Knowledge of Respiratory Rate Quantification and Abnormal Pattern Prediction
PublikacjaThe described application of granular computing is motivated because cardiovascular disease (CVD) remains a major killer globally. There is increasing evidence that abnormal respiratory patterns might contribute to the development and progression of CVD. Consequently, a method that would support a physician in respiratory pattern evaluation should be developed. Group decision-making, tri-way reasoning, and rough set–based analysis...
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublikacjaThe 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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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublikacjaTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublikacjaThe paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...
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Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition
Publikacjaconvolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...
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Theory and implementation of a virtualisation level Future Internet defence in depth architecture
PublikacjaAn EU Future Internet Engineering project currently underway in Poland defines three parallel internets (PIs). The emerging IIP system (IIPS, abbreviating the project’s Polish name), has a four-level architecture, with level 2 responsible for creation of virtual resources of the PIs. This paper proposes a three-tier security architecture to address level 2 threats of unauthorised traffic injection and IIPS traffic manipulation...
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The Method of a Two-Level Text-Meaning Similarity Approximation of the Customers’ Opinions
PublikacjaThe method of two-level text-meaning similarity approximation, consisting in the implementation of the classification of the stages of text opinions of customers and identifying their rank quality level was developed. Proposed and proved the significance of major hypotheses, put as the basis of the developed methodology, notably about the significance of suggestions about the existence of analogies between mathematical bases of...
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublikacjaData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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Deep slot effect in the squirrel-cage induction motors with scalar (V/F) control
PublikacjaQualitative characteristics of the electrical drive considerably depend on identification accuracy of math model parameters. In particular, it is depend on detection accuracy of stator active resistance r1 that is used in calculation of flux linkages, rotary speed in sensorless control systems. Paper provides analysis of influence of stator deep slot effect to stator active resistance value
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublikacjaIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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Multi-level Virtualization and Its Impact on System Performance in Cloud Computing
PublikacjaThe results of benchmarking tests of multi-level virtualized environments are presented. There is analysed the performance impact of hardware virtualization, container-type isolation and programming level abstraction. The comparison is made on the basis of a proposed score metric that allows you to compare different aspects of performance. There is general performance (CPU and memory), networking, disk operations and application-like...
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Deep Learning Approaches in Histopathology
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Extractive detoxification of hydrolysates with simultaneous formation of deep eutectic solvents
PublikacjaThe hydrolysis of lignocellulosic biomass results in the production of so-called fermentation inhibitors, which reduce the efficiency of biohydrogen production. To increase the efficiency of hydrogen production, inhibitors should be removed from aqueous hydrolysate solutions before the fermentation process. This paper presents a new approach to the detoxification of hydrolysates with the simultaneous formation of in-situ deep eutectic...
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Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublikacjaRemote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...
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Purification of model biogas from toluene using deep eutectic solvents
PublikacjaBiogas from landfills and wastewater treatment facilities typically contain a wide range of volatile organic compounds (VOCs), that can cause severe operational problems when biogas is used as fuel. Among the contaminants commonly occur aromatic compounds, i.e. benzene, ethylbenzene, toluene and xylenes (BTEX). In order to remove BTEX from biogas, different processes can be used. A promising process for VOCs removal is their absorption...
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Categorization of emotions in dog behavior based on the deep neural network
PublikacjaThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
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Low-Level Music Feature Vectors Embedded as Watermarks
PublikacjaIn this paper a method consisting in embedding low-level music feature vectors as watermarks into a musical signal is proposed. First, a review of some recent watermarking techniques and the main goals of development of digital watermarking research are provided. Then, a short overview of parameterization employed in the area of Music Information Retrieval is given. A methodology of non-blind watermarking applied to music-content...
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Selective Harmonic Elimination PWM For a Cascaded Multi-level Inverter
PublikacjaThis paper deals with the selective harmonic elimination pulse width modulation (SHE-PWM) technique. This technique is used for the elimination of selected dominant low order harmonics in the multi-level inverter output voltage. The presence of these harmonics is the essential drawback of such kind of inverters; especially when it is used for the control of different AC drivers. The SHE-PWM is based...
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Deep learning-based waste detection in natural and urban environments
PublikacjaWaste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems are addressed in this article by...
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Country‐level and individual‐level predictors of men's support for gender equality in 42 countries
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Three-Level Z-Source Neutral-Point-Clamped Inverter
PublikacjaThe paper describes construction and the principles of activity, attributes and potential of 3-phase Z-type inverters. The paper focuses on the basic system and suggested 3-level system of a NPC type Z-inverter, which was elaborated by authors. Simplified theoretical analysis of both systems has been verified by detailed simulation research. In the last section of the article, the possibility to build multilevel Z- inverters based...
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublikacjaThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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Hybridized PWM Strategy for Three- and Multiphase Three-Level NPC Inverters
PublikacjaA simple hybridized pulsewidth modulation (PWM) algorithm for three- and multiphase three-level neutral point clamped (NPC) inverters is proposed. The proposed solution is based on classical space vector PWM (SVPWM) algorithms for two-level inverters but can also be based on sinusoidal PWM with min–max injection. An additional level of output voltage is obtained by modifying the resulting switching patterns taking into account...
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Automated detection of pronunciation errors in non-native English speech employing deep learning
PublikacjaDespite significant advances in recent years, the existing Computer-Assisted Pronunciation Training (CAPT) methods detect pronunciation errors with a relatively low accuracy (precision of 60% at 40%-80% recall). This Ph.D. work proposes novel deep learning methods for detecting pronunciation errors in non-native (L2) English speech, outperforming the state-of-the-art method in AUC metric (Area under the Curve) by 41%, i.e., from...
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On Software Unit Testing For Security and Performance Gain At Unit Level
PublikacjaPerformance and security are software (SW) application attributes situated on the opposite corners of system design. In the most drastic example the most secure component is the one totally isolated from the outside world, with communication performance reduced to zero level (e.g. disconnected physically from the network, placed inside a Faraday cage to eliminate possible wireless accessibility). On the other hand the most performance-optimized...
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OPTICAL STRAIN MEASUREMENT OF CONCRETE VERSUS MANUAL EXTENSOMETER MEASUREMENT BASED ON THE TEST RC DEEP BEAM IN A COMPLEX STATE OF STRESS
PublikacjaThe purpose of this study is to compare the strain measurement techniques of concrete in R-C element subjected to the monotonic load up to the failure. In the analysis manual extensometer methods of measurements and the optical system ARAMIS for non-contact three-dimensional measurements of deformation was used. The test sample was a cantilever deep beam loaded throughout the depth which was a part of the reinforced concrete deep...