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Search results for: FACIAL RECOGNITION, DROWSINESS, REAL-TIME MONITORING, MACHINE LEARNING, NEURAL NETWORKS, DRIVER, FATIGUE
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Graph Representation Integrating Signals for Emotion Recognition and Analysis
PublicationData reusability is an important feature of current research, just in every field of science. Modern research in Affective Computing, often rely on datasets containing experiments-originated data such as biosignals, video clips, or images. Moreover, conducting experiments with a vast number of participants to build datasets for Affective Computing research is time-consuming and expensive. Therefore, it is extremely important to...
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Emotion Recognition and Its Applications
PublicationThe paper proposes a set of research scenarios to be applied in four domains: software engineering, website customization, education and gaming. The goal of applying the scenarios is to assess the possibility of using emotion recognition methods in these areas. It also points out the problems of defining sets of emotions to be recognized in different applications, representing the defined emotional states, gathering the data and...
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The Influence of Selecting Regions from Endoscopic Video Frames on The Efficiency of Large Bowel Disease Recognition Algorithms
PublicationThe article presents our research in the field of the automatic diagnosis of large intestine diseases on endoscopic video. It focuses on the methods of selecting regions of interest from endoscopic video frames for further analysis by specialized disease recognition algorithms. Four methods of selecting regions of interest have been discussed: a. trivial, b. with the deletion of characteristic, endoscope specific additions to the...
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublicationAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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MSRL and the Real-Life Processes of Capturing and Implementing the "Urban Innovation"
PublicationResult of the MSRL workshop, five research projects, reflect on a broader process of exchange of the ideas between the cities, that is occurring in the real life and became one of the driving factors of the urban development nowadays. The objective of the MSRL research - concepts, which help to advance the development of the cities, support the improvement of the quality of urban environment or meet the future challenges, can be...
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Current air quality analytics and monitoring: A review
PublicationThis review summarizes the different tools and concepts that are commonly applied in air quality monitoring. The monitoring of atmosphere is extremely important as the air quality is an important problem for large communities. Main requirements for analytical devices used for monitoring include a long period of autonomic operation and portability. These instruments, however, are often characterized by poor analytical performance....
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Edge-Computing based Secure E-learning Platforms
PublicationImplementation of Information and Communication Technologies (ICT) in E-Learning environments have brought up dramatic changes in the current educational sector. Distance learning, online learning, and networked learning are few examples that promote educational interaction between students, lecturers and learning communities. Although being an efficient form of real learning resource, online electronic resources are subject to...
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CURRENT SITUATION ON THE POLAND REAL ESTATE MARKET
PublicationIn recent years the polish real estate market has been characterised by a significant increase in supply and demand. This was facilitated by a number of macroeconomic factors. In recent years, housing has been commissioned as 30 years ago. Therefore, the depth analysis issue of the causes and consequences for the Polish economy of these trends is now relevant. Among the reasons are significant economic growth, low interest rates...
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Rough Sets Applied to Mood of Music Recognition
PublicationWith the growth of accessible digital music libraries over the past decade, there is a need for research into automated systems for searching, organizing and recommending music. Mood of music is considered as one of the most intuitive criteria for listeners, thus this work is focused on the emotional content of music and its automatic recognition. The research study presented in this work contains an attempt to music emotion recognition...
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An audio-visual corpus for multimodal automatic speech recognition
Publicationreview of available audio-visual speech corpora and a description of a new multimodal corpus of English speech recordings is provided. The new corpus containing 31 hours of recordings was created specifically to assist audio-visual speech recognition systems (AVSR) development. The database related to the corpus includes high-resolution, high-framerate stereoscopic video streams from RGB cameras, depth imaging stream utilizing Time-of-Flight...
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Fatigue behaviour of SLM maraging steel under variable-amplitude loading
PublicationOne of the most challenging issues for additive manufactured materials is fatigue endurance. Engineering components often operate under complex, variable amplitude loadings, in which existing technological imperfections promote fatigue cracks growth and damage of elements eventually. In this study the effects of different variable-amplitude strain levels on fatigue life, 18Ni300 steel was tested. The work presents various behaviours...
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Parameters optimization in medicine supporting image recognition algorithms
PublicationIn this paper, a procedure of automatic set up of image recognition algorithms' parameters is proposed, for the purpose of reducing the time needed for algorithms' development. The procedure is presented on two medicine supporting algorithms, performing bleeding detection in endoscopic images. Since the algorithms contain multiple parameters which must be specified, empirical testing is usually required to optimise the algorithm's...
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Longitudinal drug synergy assessment using convolutional neural network image-decoding of glioblastoma single-spheroid cultures
PublicationAbstract Background In recent years, drug combinations have become increasingly popular to improve therapeutic outcomes in various diseases, including difficult to cure cancers such as the brain cancer glioblastoma. Assessing the interaction between drugs over time is critical for predicting drug combination effectiveness and minimizing the risk of therapy resistance. However, as viability readouts of drug combination experiments...
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Classifying Emotions in Film Music - A Deep Learning Approach
PublicationThe paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...
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Optimizing Construction Engineering Management Using Metaheuristic Methods and Bayesian Networks
PublicationThe construction of buildings invariably involves time and costs, and disruptions impact ongoing construction projects. Crisis situations in management strategies, structural confusion, and finan-cial miscalculations often arise due to misguided decision-making. This article proposes a method that combines the learning of Bayesian Networks and heuristic techniques to optimize deci-sion-making processes in construction scheduling....
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
PublicationThe paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator. The study includes variations of the order of each fractional operator. The recurrent neural network architecture based on GRU (Gated Recurrent Unit) cells functioned as a neural approximation for selected...
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Effect of selective laser treatment on initiation of fatigue crack in the main part of an undercarriage drag strut
PublicationThis paper presents the results of material characterization and a fatigue test conducted for a laser-re-melted drag strut used in an aircraft landing gear. The drag strut was re-melted with a CO2 laser beam. Eight re-melted paths were made in the form of spiral lines along the axis of the drag strut. Next, the drag strut was subjected to variable loads on a testing machine simulating loads occurring when an aircraft lands. The...
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublicationMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublicationThis study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...
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TOXIC GASES IDENTIFICATION USING SINGLE ELECTROCATALYTIC SENSOR RESPONSES AND ARTIFICIAL NEURAL NETWORK
PublicationThe need for precise detection of toxic gases drives development of new gas sensors structures and methods of processing the output signals from the sensors. In literature, artificial neural networks are considered as one of the most effective tool for the analysis of gas sensors or sensors arrays responses. In this paper a method of toxic gas components identification using a electrocatalytic gas sensor as a detector and an artificial...
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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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Evaluation of the Commercial Electrochemical Gas Sensors for the Monitoring of CO in Ambient Air
PublicationAir pollution is a growing concern of civilized world, which has a significant impact on human health and the environment. Recent studies highlight that the exposure to polluted air can increase the incidence of diseases and deteriorate the quality of life. Hence, it is necessary to develop tools for real-time air quality monitoring. For air pollution monitoring a wide range of stationary gas and particulate analysers can be used....
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Operational causes of fatigue failures within the passages of gas turbine engines
PublicationThe short profile of a fatigue wear process of gas turbine engine's constructional elements has been introduced in the article. The primary causes of a fatigue cracks formation within the mechanical system as well as within the passages of the engine have been showed. Especial attention was devoted to the low-cycle fatigue, what is associated with unsteady thermal-flow processes being worked out in the passages.The selected damages...
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Dependable Integration of Medical Image Recognition Components
PublicationComputer driven medical image recognition may support medical doctors in the diagnosis process, but requires high dependability considering potential consequences of incorrect results. The paper presentsa system that improves dependability of medical image recognition by integration of results from redundant components. The components implement alternative recognition algorithms of diseases in thefield of gastrointestinal endoscopy....
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ON EGNOS MONITORING IN LOCAL CONDITIONS
PublicationAny SBAS system should deliver to the user corrections to pseudoranges as well as information about the system integrity. In theory, as soon as the system is permanently monitored by RIMS stations, it is impossible to deliver the fault information to the user. However many observations shows that accuracy of EGNOS service in the same time are different in different places, which shows the influence of local conditions on them....
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Load effect impact on the exploitation of concrete machine foundations used in the gas and oil industry
PublicationMachine foundations is a critical topic in the gas and oil industry, which design and exploitation require extensive technical knowledge. Machine foundations are the constructions which are intended for mounting on it a specific type of machine. The foundation has to transfer dynamic and static load from machine to the ground. The primary difference between machine foundations and building foundations is that the machine foundations...
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Neural Modelling of Steam Turbine Control Stage
PublicationThe paper describes possibility of steam turbine control stage neural model creation. It is of great importance because wider application of green energy causes severe conditions for control of energy generation systems operation Results of chosen steam turbine of 200 MW power measurements are applied as an example showing way of neural model creation. They serve as training and testing data of such neural model. Relatively simple...
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The networking of the justice system as part of public court networks
PublicationThe goal of this paper is to look at the organizational structure of the justice system and provide the answer to the basic question of the possible network relations, their force, and imapct. As part od the paper, I have defined public inetrorganisational court network, dividing them into regulatory inter-organisational networks nad voluntary inetrorganisational networks. Emphasis has also been placed on the benefits and threats...
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ENERGY ANALYSIS OF PROPULSION SHAFT FATIGUE PROCESS IN ROTATING MECHANICAL SYSTEM PART I TESTING SIGNIFICANCE OF INFLUENCE OF SHAFT MATERIAL FATIGUE EXCITATION PARAMETERS
PublicationThe article discusses the problem of mathematical modelling of energy conversion processes in a rotating mechanical system for the purpose of identifying fatigue states of propulsion shafts in this system. A simplified physical model of the analysed system, constructed in an appropriate scale, has made the basis for the experimental research. The research programme took into consideration mechanical fatigue excitation of the model...
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Identification of acoustic event of selected noise sources in a long-term environmental monitoring systems
PublicationABSTRACT Undertaking long-term acoustic measurements on sites located near an airport is related to a problem of large quantities of recorded data, which very often represents information not related to flight operations. In such areas, usually defined as zone of limited use, often other sources of noise exist, such as roads or railway lines treated is such context as acoustic background. Manual verification of such recorded data...
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Employing Blended E-Learning to Improve Rate of Assignments Handing-In
PublicationIt has been observed that students hand in homework assignments at a notably low rate in introductory C programming course. A survey has revealed that the real issue was not student learning but instructor work organization. Based on survey results, the physical course has been complemented with an e-learning component to guide the homework process. Assignment handing-in rate significantly improved, as e-learning allowed the homework...
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Double Fed Induction Machine Drives
PublicationContents of the Chapter 22:Machine model.Properties of the DFM.Steady state machine operation.Control rules and decoupled control.Decoupling based on MM machine model.Decoupling based on vector model.Decoupling based on rotor current equation.Overall control system.Control system based on MM model.Control system based on vector model.Estimation of variables.Calculation of the angle between stator and rotor.Remarks about digital...
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Guido: a musical score recognition system
PublicationThis paper presents an optical music recognition system Guido that can automatically recognize the main musical symbols of music scores that were scanned or taken by a digital camera. The application is based on object model of musical notation and uses linguistic approach for symbol interpretation and error correction. The system offers musical editor with a partially automatic error correction.
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Multidimentional innovation as a driver of economic development. European country study
PublicationArtykuł stanowi analizę innowacyjności w ujęciu wielowymiarowym, jako jednym z głównych czynników poziomu rozwoju gospodarczego kraju. Autorzy wykorzystują Summary Innovation Index jako miary wielowymiarowje innowacyjnosci kraju. Zdefiniowane zostaje pojęcie luki innowacyjnej.
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Technical diagnostics and monitoring of traction current collectors
PublicationNew evaluation methods of the technical condition of rolling stock current collectors are proposed in this paper. The method of automatic measurement of the pantograph static force characteristic, realized when the vehicle runs through the test section of the track with especially prepared overhead line height distribution, has been practically implemented by the Polish Railways. The method of testing the slipper spring suspension...
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A Study of Cross-Linguistic Speech Emotion Recognition Based on 2D Feature Spaces
PublicationIn this research, a study of cross-linguistic speech emotion recognition is performed. For this purpose, emotional data of different languages (English, Lithuanian, German, Spanish, Serbian, and Polish) are collected, resulting in a cross-linguistic speech emotion dataset with the size of more than 10.000 emotional utterances. Despite the bi-modal character of the databases gathered, our focus is on the acoustic representation...
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Detection of Cystic Fibrosis Symptoms Based on X-Ray Images Using Machine Learning- Pilot Study
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Universal Predictors of Dental Students’ Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
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Quantitative Soil Characterization for Biochar–Cd Adsorption: Machine Learning Prediction Models for Cd Transformation and Immobilization
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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublicationOne of the important factors determining the biochemical processes in bioreactors is the quality of the wastewater inflow to the wastewater treatment plant (WWTP). Information on the quality of wastewater, sufficiently in advance, makes it possible to properly select bioreactor settings to obtain optimal process conditions. This paper presents the use of classification models to predict the variability of wastewater quality at...
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Flap Monitoring Techniques: A Review
PublicationPostoperative tissue flap vitality monitoring enables early detection of clinical complications, allowing for intervention. Timely re-operation can prevent the need for extensive correction procedures, thus reducing healthcare costs and hospitalisation time. Statistics show that monitoring can increase the success rate of flap survival to 95\% or higher. However, despite the significant progress in monitoring techniques, major...
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Accelerometer-based Human Activity Recognition and the Impact of the Sample Size
PublicationThe presented study focused on the recognition of eight user activities (e.g. walking, lying, climbing stairs) basing on the measurements from an accelerometer embedded in a mobile device. It is assumed that the device is carried in a specific location of the user’s clothing. Three types of classifiers were tested on different sizes of the samples. The influence of the time window (the duration of a single trial) on selected activities...
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1D convolutional context-aware architectures for acoustic sensing and recognition of passing vehicle type
PublicationA network architecture that may be employed to sensing and recognition of a type of vehicle on the basis of audio recordings made in the proximity of a road is proposed in the paper. The analyzed road traffic consists of both passenger cars and heavier vehicles. Excerpts from recordings that do not contain vehicles passing sounds are also taken into account and marked as ones containing silence....
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Comparison of selected clustering algorithms of raw data obtained by interferometric methods using artificial neural networks
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Microsphere structure application for supercapacitor in situ temperature monitoring
PublicationConstant, real-time temperature monitoring of the supercapacitors for efficient energy usage is in high demand and seems to be crucial for further development of those elements. A fiber-optic sensor can be an effective optoelectronic device dedicated for in-situ temperature monitoring of supercapacitors. In this work, the application of the fiber-optic microstrucutre with thin zinc oxide (ZnO) coating fabricated in the atomic layer...
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Genetic Algorithm Approach for Gains Selection of Induction Machine Extended Speed Observer
PublicationThe subject of this paper is gains selection of an extended induction machine speed observer. A high number of gains makes manual gains selection difficult and due to nonlinear equations of the observer, well-known methods of gains selection for linear systems cannot be applied. A method based on genetic algorithms has been proposed instead. Such an approach requires multiple fitness function calls; therefore, using a quality index...
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Social learning in cluster initiatives
PublicationPurpose – The purpose of the paper is to portray social learning in cluster initiatives (CIs), namely: 1) to explore, with the lens of the communities of practice (CoPs) theory, in what ways social learning occurs in CIs; 2) to discover how various CoPs emerge and evolve in CIs to facilitate a collective journey in their learning process. Subsequently, the authors address the research questions: In what ways does social learning...
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Real-time proliferation of porcine cumulus cells is related to the protein levels and cellular distribution of Cdk4 and Cx43
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The Possibilities of Improving the Fatigue Durabilityof the Ship Propeller Shaft by Burnishing Process
PublicationHeavily loaded structural elements operating in a corrosive environment are usuallyquickly destroyed. An example of such an element is a ship propeller operating in a seawaterenvironment. This research presents a fatigue resistance test performed on elements operating inseawater. Different processing parameters applied on the samples in particular were compared withthe specimens whose surface had been burnished differently and...
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Neural Network-Based Sequential Global Sensitivity Analysis Algorithm
PublicationPerforming global sensitivity analysis (GSA) can be challenging due to the combined effect of the high computational cost, but it is also essential for engineering decision making. To reduce this cost, surrogate modeling such as neural networks (NNs) are used to replace the expensive simulation model in the GSA process, which introduces the additional challenge of finding the minimum number of training data samples required to...