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Search results for: deep-level mining
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A Five-Leg Three-Level Dual-Output Inverter
PublicationClassical 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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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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Mining e-mail message sequences from log data
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Introducing the concept of Decisional DNA-Based web content mining
PublicationPrzedstawiono 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 Knowledge of Respiratory Rate Quantification and Abnormal Pattern Prediction
PublicationThe 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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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn 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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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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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublicationTo 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
PublicationThe 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
Publicationconvolutional 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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Measurements in civil engineering, transport, environmental engineering, mining and power engineering 22/23
e-Learning CoursesThe course is primarily open to all PhD students at Gdansk University of Technology. This course is compulsory for PhD students assigned to Civil Engineering and Transport as well as Environmental Engineering, Mining and Power Engineering tracks at Doctoral School of GUT. This course allows the PhD students to obtain the knowledge related to the experimental equipment and types of experiments carried out at GUT in the field of...
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Measurements in civil engineering, transport, environmental engineering, mining and power engineering 23/24
e-Learning CoursesThe course is primarily open to all PhD students at Gdansk University of Technology. This course is compulsory for PhD students assigned to Civil Engineering and Transport as well as Environmental Engineering, Mining and Power Engineering tracks at Doctoral School of GUT. This course allows the PhD students to obtain the knowledge related to the experimental equipment and types of experiments carried out at GUT in the field of...
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The Method of a Two-Level Text-Meaning Similarity Approximation of the Customers’ Opinions
PublicationThe 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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Theory and implementation of a virtualisation level Future Internet defence in depth architecture
PublicationAn 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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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublicationData 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
PublicationQualitative 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
PublicationIn 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
PublicationThe 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
PublicationThe 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
PublicationRemote 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
PublicationBiogas 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
PublicationThe 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
PublicationIn 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
PublicationThis 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
PublicationWaste 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
PublicationThe 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
PublicationThe 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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CANADIAN MINING JOURNAL
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Journal of Mining Institute
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Advances in Information Mining
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Journal of Sustainable Mining
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Journal of Mining and Environment
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Scientific Mining Journal
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JOURNAL OF MINING SCIENCE
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Mining Metallurgy & Exploration
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Archives of Mining Sciences
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Hybridized PWM Strategy for Three- and Multiphase Three-Level NPC Inverters
PublicationA 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
PublicationDespite 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
PublicationPerformance 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
PublicationThe 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...
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Deep eutectic solvents in analytical sample preconcentration Part B: Solid-phase (micro)extraction
PublicationOne of the key challenges of modern analytical chemistry is the monitoring of trace amounts of contaminants using sensitive and selective instrumental techniques. Due to the variety and complexity of some samples, it is often necessary to properly prepare a sample and to perform a preconcentration of trace amounts of analytes. In line with the principles of Green Analytical Chemistry (GAC), it is important for an analytical procedure...
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Fuzzy regresion approach to road safety analysis at regional level
PublicationRoad safety modelling on regional level of NUTS 2 in the EU is the complex issue and authors of this article indicate this in previous publications. NUTS 2 are basic regions for the application of regional policies (0.8-3 m inhabitants). During multivariate models development they discovered that it is difficult to make regression model well described all regions, even if they are from one country. In the first step Poisson model...
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Assessment and design of greener deep eutectic solvents – A multicriteria decision analysis
PublicationDeep eutectic solvents (DES) are often considered as green solvents because of their properties, such as negligible vapor pressure, biodegradability, low toxicity or natural origin of their components. Due to the fact that DES are cheaper than ionic liquids, they have gained many applications in a short period of time. However, claims about their greenness sometimes seem to be exaggerated. Especially, bearing in mind lots of data...
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A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
PublicationMachine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It is challenging due to difficulty in distinguishing a true CMB from its mimics, however, if successfully solved it would streamline the radiologists work. To deal with this complex three-dimensional...
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Methods of deep modification of low-bearing soil for the foundation of new and spare air runways
PublicationAfter analyzing the impact of aircraft on the airport pavement (parking spaces, runways, startways), it was considered advisable to consider the problem of deep improvement or strengthening of its subsoil. This is especially true for low-bearing soil. The paper presents a quick and effective method of strengthening the subsoil intended for the construction of engineering structures used for civil...
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Hydrophobic deep eutectic solvents as “green” extraction media for polycyclic aromatic hydrocarbons in aqueous samples
PublicationThe paper presents novel nonionic and hydrophobic deep eutectic solvents which were synthesized from natural compounds, i.e., thymol, ±camphor, decanoic and 10-undecylenic acids. Fundamental physicochemical properties of the synthesized deep eutectic solvents were determined, followed by their application as extractants in ultrasound-assisted dispersive liquid-liquid microextraction to isolate and enrich polycyclic aromatic hydrocarbons...