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Wyniki wyszukiwania dla: hearing disorders
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Modeling lignin extraction with ionic liquids using machine learning approach
PublikacjaLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
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Informal Workplace Learning and Employee Development. Growing in the Organizational New Normal
PublikacjaThe new paradigm in employee development assumes that employees should proactively direct their learning and growth. Most workplace learning is basically informal and occurs through daily work routines, peer-to-peer interactions, networking, and typically brings about significant positive outcomes to both individuals and organizations. Yet, workplace learning always occurs in a pre-defined context and this context has recently...
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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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Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines
PublikacjaThe acquisition of high-quality data and annotations is essential for the training of efficient machine learning algorithms, while being an expensive and time-consuming process. Although the process of data processing and training and testing of machine learning models is well studied and considered in the literature, the actual procedures of obtaining data and their annotations in collaboration with physicians are in most cases...
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Using deep learning to increase accuracy of gaze controlled prosthetic arm
PublikacjaThis paper presents how neural networks can be utilized to improve the accuracy of reach and grab functionality of hybrid prosthetic arm with eye tracing interface. The LSTM based Autoencoder was introduced to overcome the problem of lack of accuracy of the gaze tracking modality in this hybrid interface. The gaze based interaction strongly depends on the eye tracking hardware. In this paper it was presented how the overall the...
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Exploring DAD and ADD Methods for Dealing with Urban Heat Island Effect
PublikacjaThe Urban Heat Island (UHI) effect in the context of climate change and temperature fluctuations is an increasing challenge for contemporary cities. Numerous activities focus on mitigation and adaptation to the UHI effect using both appropriately selected design strategies and technological solutions. However, not all of these technologies support the postulates of ecological and low-carbon cities. Their design, implementation,...
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Can the Pandemic Be a Catalyst of Spatial Changes Leading Towards the Smart City?
PublikacjaThe worldwide spread of Covid‐19 infections has had a pervasive influence on cities and the lives of their residents. The current crisis has highlighted many urban problems, including those related to the functionality of urban structures, which directly affect the quality of life. Concurrently, the notion of “smart cities” is becoming a dominant trend in the discourse on urban development. At the intersection of these two phenomena,...
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TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
PublikacjaTensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...
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Distance learning trends: introducing new solutions to data analysis courses
PublikacjaNowadays data analysis of any kind becomes a piece of art. The same happens with the teaching processes of statistics, econometrics and other related courses. This is not only because we are facing (and are forced to) teach online or in a hybrid mode. Students expect to see not only the theoretical part of the study and solve some practical examples together with the instructor. They are waiting to see a variety of tools, tutorials,...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublikacjaThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublikacjaIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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IT support for OKNO broadband Internet-based distant learning system at WUT
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Novel Analytic-Numerical Model of Free Convection: with Leading Edge Considered
PublikacjaA novel solution of the free convection boundary problem is represented in analytical form for velocity and temperature for an isothermal vertical plate, as an example. These fields are built as a Taylor Series in the x coordinate with coefficients as functions of the vertical coordinate (y). We restrict ourselves by cubic approximation for both functions. The basic Navier-Stokes and Fourier-Kirchhoff equations and boundary conditions...
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Reduction of vibrations of steel structure models with Polymeric Bearings - experimental study
PublikacjaEarthquake-induced ground motions are the most severe and unpredictable threats to the structures all around the world. Therefore, designing earthquake protective systems has become an extremely challenging problem in civil engineering. Base isolation is one of the most popular and widely adopted methods of protecting structures against earthquake forces. The present paper reports the results obtained from the shaking table experimental...
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Water-Lubricated Sintered Bronze Journal Bearings—Theoretical and Experimental Research
PublikacjaWater lubricated bearings are used from many years in shipbuilding, hydro power and other industries because of their advantages such as: extensive serviceable life, low coefficient of friction, longevity of shaft sleeve, good abrasion resistance, low maintenance required, unit simplicity, no danger of pollution and low price. Various types of water lubricated sliding bearings have been tested at the Technical University of Gdansk...
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On the Possibilities of Decreasing Power Loss in Large Tilting Pad Thrust Bearings
PublikacjaJournal Menu About this Journal Abstracting and Indexing Aims and Scope Article Processing Charges Articles in Press Author Guidelines Bibliographic Information Citations to this Journal Contact Information Editorial Board Editorial Workflow Free eTOC Alerts Publication Ethics Submit a Manuscript Table of Contents Abstract Full-Text PDF Full-Text HTML...
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Experimental comparison of hydrodynamic thrust bearings with different pad surface materials
PublikacjaBabbitt is the material most frequently used as the pad surface material for hydrodynamic bearings operating at usual operating conditions. It shows many advantages important for safe bearing operation, as for example: low friction coefficient, corrosion resistance, fair mechanical properties and outstanding conformability. On the other hand, it is not free from disadvantages, such as limited fatigue strength or limited resistance...
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Induction Motor Bearings Diagnostic Using MCSA and Normalized Tripple Covariance
PublikacjaDiagnosis of induction motors, conducted remotely by measuring and analyzing the supply current is attractive with the lack of access to the engine. So far there is no solution, based on analysis of current, the credibility of which allow use in industry. Statistics of IM bearing failures of induction motors indicate, that they constitute more than 40% of IM damage, therefore bearing diagnosis is so important. The article provides...
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Modular machine learning system for training object detection algorithms on a supercomputer
PublikacjaW pracy zaprezentowano architekturę systemu służącego do tworzenia algorytmów wykorzystujących metodę AdaBoost i służących do wykrywania obiektów (np. twarzy) na obrazach. System został podzielony na wyspecjalizowane moduły w celu umożliwienia łatwej rozbudowy i efektywnego zrównoleglenia implementacji przeznaczonej dla superkomputera. Na przykład, system może być rozszerzony o nowe cechy i algorytmy ich ekstrakcji bez konieczności...
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Beesybees-Agent-Based, Adaptive & Learning Workflow Execution Module for BeesyCluster
PublikacjaPrezentujemy projekt oraz implementację adaptacyjnego i uczącego się modułu przeznaczonego dowykonywania scenariuszy w środowisku BeesyCluster. BeesyCluster pozwala na modelowaniescenariuszy w formie acyklicznego grafu skierowanego, w którym wierzchołki oznaczają zadania,a krawędzie określają zależności między nimi. Przedstawiamy także kooperatywne wykonaniescenariusza przez grupę agentów zdolnych do zbierania, składowania i korzystania...
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A proposal for knowledge sharing in the e-Decisional community using Decisional DNA
PublikacjaZaproponowano model platformy wspomagającej wymianę wiedzy w społeczeństwie decyzyjnym opartym na decyzyjnym DNA.
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Learning from Imbalanced Data Using Over-Sampling and the Firefly Algorithm
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Deep learning approach for delamination identification using animation of Lamb waves
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Deep learning super-resolution for the reconstruction of full wavefield of Lamb waves
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OmicSelector: automatic feature selection and deep learning modeling for omic experiments
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A Prototype of Educational Agent in Distance Learning Environment - Virtual Student Assistant
PublikacjaW zdalnym nauczaniu pojawia się wiele systemów wspierających, z których niezwykle ciekawym przykładem są agenty edukacyjne. Wśród wielu rodzajów agentów edukacyjnych wyróżnia się osobistych asystentów, których rolą jest organizacyjna pomoc osobie zdobywającej wiedzę. Artykuł jest poświęcony zaimplementowanemu na Wydziale ETI Politechniki Gdańskiej prototypowi agenta edukacyjnego o nazwie WAS (Wirtualny Asystent Studenta). Pokazana...
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Relationships between Trust and Collaborative Culture in The Context of Tacit Knowledge Sharing
PublikacjaThe literature review presents a lot of theoretical and empirical evidence that Trust affects Collaborative Culture. The opposite also proves to be true: Collaborative Culture influences Trust. The main hypothesis presented in this paper says that both these factors are strongly correlated and modify each other. This study examines the mutual relationship of the said variables in the context of Tacit Knowledge Sharing based on...
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Security information sharing for smart grids: Developing the right data model
PublikacjaThe smart grid raises new security concerns which require novel solutions. It is commonly agreed that to protect the grid the effective collaboration and information sharing between the relevant stakeholders is prerequisite. Developing a security information sharing platform for the smart grid is a new research direction which poses several challenges related to the highly distributed and heterogeneous character of the grid. In...
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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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A COMPARISON OF WEAR PROPERTIES OF WATER LUBRICATED NBR AND PTFE SLIDING BEARINGS
PublikacjaThe excessive wear of a journal shaft can be caused by many factors, for example, working conditions (e.g., temperaturę, slip speed, the type of lubricant), pressure, the type of material used on the bearings and shafts and their roughness, as well as contamination remaining in the system. This paper presents the roughness profiles co-operating with a rubber (NBR) and polytetrafluoroethylene (PTFE) bushes. The conditions of cooperation...
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Knowledge Sharing and Organizational Culture Dimensions: Does Job Satisfaction Matter?
PublikacjaThe aim of this study is to examine how job satisfaction influences the relationship between company performance, knowledge sharing, and organizational culture, perceived through the prism of Hofstede’s cultural dimensions, controlled by company size and staff position. A survey of 910 Polish employees (mainly knowledge workers) with different roles and experiences across different industries was conducted. The data were analyzed...
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MCSA with Normalized Triple Covariance as a bearings diagnostic indicator in an induction motor
PublikacjaStatistics of bearing failures in induction motors indicate, that they constitute more than 40% of IM damage, therefore bearing diagnosis is very important. Vibration methods for bearing diagnostics have one major disadvantage - they require the availability of the machine for sensors installation. This is the reason for seeking new methods based on motor supply current analysis. Diagnosis of induction motors, conducted remotely...
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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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Limitations of Emotion Recognition from Facial Expressions in e-Learning Context
PublikacjaThe paper concerns technology of automatic emotion recognition applied in e-learning environment. During a study of e-learning process the authors applied facial expressions observation via multiple video cameras. Preliminary analysis of the facial expressions using automatic emotion recognition tools revealed several unexpected results, including unavailability of recognition due to face coverage and significant inconsistency...
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E-learning - prawdziwa czy fikcyjna koncepcja edukacyjnego rozwoju uczelni
PublikacjaNie można zaprzeczyć, że wykorzystanie narzędzi multimedialnych oraz Internetu pozwala na dodanie istotnych, z punku widzenia dydaktyki, komponentów edukacyjnych tworzących kompetencje i umiejętności zawodowe, a także te czysto akademickie. Trzeba rozważyć, czy wszystkie strony procesu dydaktycznego na uczelni są przygotowane do e−learningu. Oczywistym wymogiem jest posiadanie odpowiedniej bazy sprzętowej i przygotowanej kadry...
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Security Requirements and Controls for Incident Information Sharing in the Polish Power System
PublikacjaAmong the strategies of protecting information assets of the power system, sharing of information about current cybersecurity incidents between energy operators appears to be a prerequisite. Exchange of information leads to the effective detection of attacks and exploited vulnerabilities as well as the identification of countermeasures. This paper presents the results of continuation of our works on developing a secure and efficient...
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Autonomous pick-and-place system based on multiple 3Dsensors and deep learning
PublikacjaGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Model-Based Adaptive Machine Learning Approach in Concrete Mix Design
PublikacjaConcrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...
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Deep learning based thermal image segmentation for laboratory animals tracking
PublikacjaAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublikacjaCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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Deep learning approach on surface EEG based Brain Computer Interface
PublikacjaIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublikacjaA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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Smart platforms for collaborative urban design and peer-to-peer sharing of resources
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Deep learning for ultra-fast and high precision screening of energy materials
PublikacjaSemiconductor materials for energy storage are the core and foundation of modern information society and play important roles in photovoltaic system, integrated circuit, spacecraft technology, lighting applications, and other fields. Unfortunately, due to the long experiment period and high calculation cost, the high-precision band gap (the basic characteristic parameter) of semiconductor is difficult to obtain, which hinders the...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublikacjaThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Beyond quid pro quo: good soldiers and characteristics of their helping behaviours
PublikacjaPurpose – Good soldiers are people who engage in citizenship behaviours “to do good” instead of “to look good”. The purpose of this article is to explore the motivations behind and the specific characteristics of behaviours of the good soldiers in the context of work using social exchange theory (SET) as a theoretical framework. Design/methodology/approach – 47 dyadic interviews with 94 individuals from three organisations...
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublikacjaObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
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Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results
PublikacjaThe continuous growth of the computing power of processors, as well as the fact that computational clusters can be created from combined machines, allows for increasing the complexity of algorithms that can be trained. The process, however, requires expanding the basis of the training sets. One of the main obstacles in music classification is the lack of high-quality, real-life recording database for every instrument with a variety...
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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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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...