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Search results for: animals, emotions, emotions detection, neural network,
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Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study
PublicationMalignant melanomas are the most deadly type of skin cancers however detected early enough give a high chances for successful treatment. The last years saw the dynamic growth of interest of automatic computer-aided skin cancer diagnosis. Every month brings new research results on new approaches to this problem, new methods of preprocessing, new classifiers, new ideas to follow etc. In particular, the rapid development of dermatoscopy,...
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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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Mathematical modeling and prediction of pit to crack transition under cyclic thermal load using artificial neural network
PublicationThe formation of pitting is a major problem in most metals, which is caused by extremely localized corrosion that creates small holes in metal and subsequently, it changes into cracks under mechanical load, thermo-mechanical stress, and corrosion process factors. This research aims to study pit to crack transition phenomenon of steel boiler heat tubes under cyclic thermal load, and mathematical modeling...
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Detection of Alzheimer's disease using Otsu thresholding with tunicate swarm algorithm and deep belief network
PublicationIntroduction: Alzheimer’s Disease (AD) is a degenerative brain disorder characterized by cognitive and memory dysfunctions. The early detection of AD is necessary to reduce the mortality rate through slowing down its progression. The prevention and detection of AD is the emerging research topic for many researchers. The structural Magnetic Resonance Imaging (sMRI) is an extensively used imaging technique in detection of AD, because...
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FPGA-Based Real-Time Implementation of Detection Algorithm for Automatic Traffic Surveillance Sensor Network
PublicationArtykuł opisuje sprzętową implementację w układzie FPGA algorytmu wykrywającego pojazdy, przeznaczonego do zastosowania w autonomicznej sieci sensorowej. Zadaniem algorytmu jest detekcja poruszających się pojazdów w obrazie z kamery pracującej w czasie rzeczywistym. Algorytm ma na celu oszacowanie parametrów ruchu ulicznego, takich jak liczba pojazdów, ich kierunek ruchu i przybliżona prędkość, przy wykorzystaniu sprzętu sieci...
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A new analyzer based on pellistor sensor with neural network data postprocessing for measurement of hydrocarbons in lower explosive limit range
PublicationW pracy przedstawiono rezultaty pierwszego etapu badań nad nowym typem analizatora do oznaczania stężenia wodoru i lotnych węglowodorów w zakresie dolnej granicy wybuchowości. Analizator ten zbudowano w oparciu o pojedynczy czujnik pelistorowy z układem przetwarzania danych wykorzystującym sztuczną sieć neuronową.
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A review on application of artificial neural network (ANN) for performance and emission characteristics of diesel engine fueled with biodiesel-based fuels
PublicationBiodiesel has been emerging as a potential and promising biofuel for the strategy of reducing toxic emissions and improving engine performance. Computational methods aiming to offer numerical solutions were inevitable as a study methodology which was sometimes considered the only practical method. Artificial neural networks (ANN) were data-processing systems, which were used to tackle many issues in engineering and science, especially...
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Application of Generalized Regression Neural Network and Gaussian Process Regression for Modelling Hybrid Micro-Electric Discharge Machining: A Comparative Study
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Prediction of skin color, tanning and freckling from DNA in Polish population: linear regression, random forest and neural network approaches
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Artificial neural network model of hardness, porosity and cavitation erosion wear of APS deposited Al2O3 -13 wt% TiO2 coatings
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Recurrent Neural Network Based Adaptive Variable-Order Fractional PID Controller for Small Modular Reactor Thermal Power Control
PublicationThis paper presents the synthesis of an adaptive PID type controller in which the variable-order fractional operators are used. Due to the implementation difficulties of fractional order operators, both with a fixed and variable order, on digital control platforms caused by the requirement of infinite memory resources, the fractional operators that are part of the discussed controller were approximated by recurrent neural networks...
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WYKORZYSTANIE SIECI NEURONOWYCH DO SYNTEZY MOWY WYRAŻAJĄCEJ EMOCJE
PublicationW niniejszym artykule przedstawiono analizę rozwiązań do rozpoznawania emocji opartych na mowie i możliwości ich wykorzystania w syntezie mowy z emocjami, wykorzystując do tego celu sieci neuronowe. Przedstawiono aktualne rozwiązania dotyczące rozpoznawania emocji w mowie i metod syntezy mowy za pomocą sieci neuronowych. Obecnie obserwuje się znaczny wzrost zainteresowania i wykorzystania uczenia głębokiego w aplikacjach związanych...
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Emotion Recognition - the need for a complete analysis of the phenomenon of expression formation
PublicationThis article shows how complex emotions are. This has been proven by the analysis of the changes that occur on the face. The authors present the problem of image analysis for the purpose of identifying emotions. In addition, they point out the importance of recording the phenomenon of the development of emotions on the human face with the use of high-speed cameras, which allows the detection of micro expression. The work that was...
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Using Deep Neural Network Methods for Forecasting Energy Productivity Based on Comparison of Simulation and DNN Results for Central Poland—Swietokrzyskie Voivodeship
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Using Deep Neural Network Methods for Forecasting Energy Productivity Based on Comparison of Simulation and DNN Results for Central Poland – Swietokrzyskie Voivodeship
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Application of PSO-artificial neural network and response surface methodology for removal of methylene blue using silver nanoparticles from water samples
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Particle swarm optimization–artificial neural network modeling and optimization of leachable zinc from flour samples by miniaturized homogenous liquid–liquid microextraction
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Human emotion recognition with biosignals
PublicationThis chapter presents issues in the field of affective computing. Basic preliminary information for the recognition of emotions is given and models of emotions, various ways of evoking emotions, as well as their theoretical foundations are discussed. The particular attention is given to the use of physiological signals in recognizing emotions. This subject is outlined further below by presenting selected biosignals, their relationship...
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Zastosowanie algorytmu ewolucyjnego do uczenia neuronowego regulatora napięcia generatora synchronicznego. Evolutionary algorithm for training a neural network of synchronous generator voltage controller
PublicationNajpopularniejsza metoda uczenia wielowarstwowych sieci neuronowych -metoda wstecznej propagacji błędu - charakteryzuje się słabą efektywnością. Z tego względu podejmowane są próby stosowania innych metod do uczenia sieci. W pracy przedstawiono wyniki uczenia sieci realizującej regulator neuronowy, za pomocą algorytmu ewolucyjnego. Obliczenia symulacyjne potwierdziły dobrą zbieżność algorytmu ewolucyjnego w tym zastosowaniu.
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Using Physiological Signals for Emotion Recognition
PublicationRecognizing user’s emotions is the promising area of research in a field of human-computer interaction. It is possible to recognize emotions using facial expression, audio signals, body poses, gestures etc. but physiological signals are very useful in this field because they are spontaneous and not controllable. In this paper a problem of using physiological signals for emotion recognition is presented. The kinds of physiological...
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Emotion Recognition Using Physiological Signals
PublicationIn this paper the problem of emotion recognition using physiological signals is presented. Firstly the problems with acquisition of physiological signals related to specific human emotions are described. It is not a trivial problem to elicit real emotions and to choose stimuli that always, and for all people, elicit the same emotion. Also different kinds of physiological signals for emotion recognition are considered. A set of...
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Emotion monitoring system for drivers
PublicationThis article describes a new approach to the issue of building a driver monitoring system. Actual systems focus, for example, on tracking eyelid and eyebrow movements that result from fatigue. We propose a different approach based on monitoring the state of emotions. Such a system assumes that by using the emotion model based on our own concept, referred to as the reverse Plutchik’s paraboloid of emotions, the recognition of emotions...
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Productivity Enhancement by Prediction of Liquid Steel Breakout during Continuous Casting Process in Manufacturing of Steel Slabs in Steel Plant Using Artificial Neural Network with Backpropagation Algorithms
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Computational Approaches to Modeling Artificial Emotion – An Overview of the Proposed Solutions
PublicationCybernetic approach to modeling artificial emotion through the use of different theories of psychology is considered in this paper, presenting a review of twelve proposed solutions: ActAffAct, FLAME, EMA, ParleE, FearNot!, FAtiMA, WASABI, Cathexis, KARO, MAMID, FCM, and xEmotion. The main motivation for this study is founded on the hypothesis that emotions can play a definite utility role of scheduling variables in the construction...
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Facial emotion recognition using depth data
PublicationIn this paper an original approach is presented for facial expression and emotion recognition based only on depth channel from Microsoft Kinect sensor. The emotional user model contains nine emotions including the neutral one. The proposed recognition algorithm uses local movements detection within the face area in order to recognize actual facial expression. This approach has been validated on Facial Expressions and Emotions Database...
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Emotion Recognition for Affect Aware Video Games
PublicationIn this paper the idea of affect aware video games is presented. A brief review of automatic multimodal affect recognition of facial expressions and emotions is given. The first result of emotions recognition using depth data as well as prototype affect aware video game are presented
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Applicability of Emotion Recognition and Induction Methods to Study the Behavior of Programmers
PublicationRecent studies in the field of software engineering have shown that positive emotions can increase and negative emotions decrease the productivity of programmers. In the field of affective computing, many methods and tools to recognize the emotions of computer users were proposed. However, it has not been verified yet which of them can be used to monitor the emotional states of software developers. The paper describes a study carried...
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Bimodal Emotion Recognition Based on Vocal and Facial Features
PublicationEmotion recognition is a crucial aspect of human communication, with applications in fields such as psychology, education, and healthcare. Identifying emotions accurately is challenging, as people use a variety of signals to express and perceive emotions. In this study, we address the problem of multimodal emotion recognition using both audio and video signals, to develop a robust and reliable system that can recognize emotions...
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Psychometric properties of the polish version of the job-related affective well-being scale
PublicationObjectives: The aim of this study was to verify psychometric properties of the Polish version of the Job-related Affective Well-being Scale (JAWS). Specifically, theoretical 4-factor structure (based on the dimensions of pleasure and arousal) and reliability of the original – 20-item JAWS (van Katwyk et al., 2000) and the shortened – 12-item (Schaufeli and Van Rhenen, 2006) versions were tested. Material and Methods: Two independent...
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Is it too late now to say we’re sorry? Examining anxiety contagion and crisis communication strategies using machine learning
PublicationIn this paper, we explore the role of perceived emotions and crisis communication strategies via organizational computer-mediated communication in predicting public anxiety, the default crisis emotion. We use a machine-learning approach to detect and predict anxiety scores in organizational crisis announcements on social media and the public’s responses to these posts. We also control for emotional and language tones in organizational...
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Subjective tests for gathering knowledge for applying color grading to video clips automatically
PublicationThe analysis of film music concerning caused emotions may allow for a more accurate adaptation of the color of the film in the context of color grading. Therefore, this paper aims to gather knowledge on the correlation between the applied color palette to a video clip, music associated with a particular shot, and emotions evoked. For that purpose, subjective tests are prepared in which several video clips are presented with or...
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Subjective tests for gathering konwledge for applaying color grading to video clips automatically
PublicationThe analysis of film music concerning caused emotions may allow for a more accurate adaptation of the color of the film in the context of color grading. Therefore, this paper aims to gather knowledge on the correlation between the applied color palette to a video clip, music associated with a particular shot,and emotions evoked. For that purpose, subjective tests are prepared in which several video clips are presented with...
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A review of emotion recognition methods based on keystroke dynamics and mouse movements
PublicationThe paper describes the approach based on using standard input devices, such as keyboard and mouse, as sources of data for the recognition of users’ emotional states. A number of systems applying this idea have been presented focusing on three categories of research problems, i.e. collecting and labeling training data, extracting features and training classifiers of emotions. Moreover the advantages and examples of combining standard...
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Be fearless: Positive affect as a mediator between venturesomeness and self-efficacy in future entrepreneurs and managers
PublicationIntroduction and objectives Self-efficacy, personality and different affect states in entrepreneurs and managers are important factors for effectiveness and well-being. The aim of the study was to examine in young adults during entrepreneurship-related education, the relationships between venturesomeness and self-efficacy, and the mediating effects of positive affect and positive emotions (joviality, self-assurance, attentiveness)...
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DevEmo—Software Developers’ Facial Expression Dataset
PublicationThe COVID-19 pandemic has increased the relevance of remote activities and digital tools for education, work, and other aspects of daily life. This reality has highlighted the need for emotion recognition technology to better understand the emotions of computer users and provide support in remote environments. Emotion recognition can play a critical role in improving the remote experience and ensuring that individuals are able...
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Remote Estimation of Video-Based Vital Signs in Emotion Invocation Studies
PublicationAbstract— The goal of this study is to examine the influence of various imitated and video invoked emotions on the vital signs (respiratory and pulse rates). We also perform an analysis of the possibility to extract signals from sequences acquired with cost-effective cameras. The preliminary results show that the respiratory rate allows for better separation of some emotions than the pulse rate, yet this relation highly depends...
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Robot-Based Intervention for Children With Autism Spectrum Disorder: A Systematic Literature Review
PublicationChildren with autism spectrum disorder (ASD) have deficits in the socio-communicative domain and frequently face severe difficulties in the recognition and expression of emotions. Existing literature suggested that children with ASD benefit from robot-based interventions. However, studies varied considerably in participant characteristics, applied robots, and trained skills. Here, we reviewed robot-based interventions targeting...
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Mining inconsistent emotion recognition results with the multidimensional model
PublicationThe paper deals with the challenge of inconsistency in multichannel emotion recognition. The focus of the paper is to explore factors that might influence the inconsistency. The paper reports an experiment that used multi-camera facial expression analysis with multiple recognition systems. The data were analyzed using a multidimensional approach and data mining techniques. The study allowed us to explore camera location, occlusions...
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Automatic labeling of traffic sound recordings using autoencoder-derived features
PublicationAn approach to detection of events occurring in road traffic using autoencoders is presented. Extensions of existing algorithms of acoustic road events detection employing Mel Frequency Cepstral Coefficients combined with classifiers based on k nearest neighbors, Support Vector Machines, and random forests are used. In our research, the acoustic signal gathered from the microphone placed near the road is split into frames and converted...
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Using Different Information Channels for Affect-Aware Video Games - A Case Study
PublicationThis paper presents the problem of creating affect-aware video games that use different information channels, such as image, video, physiological signals, input devices, and player’s behaviour, for emotion recognition. Presented case studies of three affect-aware games show certain conditions and limitations for using specific signals to recognize emotions and lead to interesting conclusions.
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Detection of Toxoplasma gondii in meat - available techniques
PublicationToxoplasma gondii, which belongs to the phylum Apicomplexa, is an absolute intercellular parasite that infects a wide range of hosts, including warm-blooded animals and humans. An infection with this parasite causes toxoplasmosis, which in most cases remains latent. However, this disease is a major threat to immunocompromised people and pregnant women. In extreme cases, it can damage nervous system or case fatal abortion. Infected...
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Detection of Face Position and Orientation Using Depth Data
PublicationIn this paper an original approach is presented for real-time detection of user's face position and orientation based only on depth channel from a Microsoft Kinect sensor which can be used in facial analysis on scenes with poor lighting conditions where traditional algorithms based on optical channel may have failed. Thus the proposed approach can support, or even replace, algorithms based on optical channel or based on skeleton...
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Positivity and job burnout in emergency personnel: examining linear and curvilinear relationship
PublicationThe aim of this study was to examine whether the relationship between the ratio of job-related positive to negative emotions (positivity ratio) and job burnout is best described as linear or curvilinear. Participants were 89 police officers (12% women) and 86 firefighters. The positivity ratio was evaluated using the Job-related Affective Wellbeing Scale (Van Katwyk, Fox, Spector, & Kelloway, 2000). Exhaustion and disengagement,...
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Comparative study of neural networks used in modeling and control of dynamic systems
PublicationIn this paper, a diagonal recurrent neural network that contains two recurrent weights in the hidden layer is proposed for the designing of a synchronous generator control system. To demonstrate the superiority of the proposed neural network, a comparative study of performances, with two other neural network (1_DRNN) and the proposed second-order diagonal recurrent neural network (2_DRNN). Moreover, to confirm the superiority...
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Style Transfer for Detecting Vehicles with Thermal Camera
PublicationIn this work we focus on nighttime vehicle detection for intelligent traffic monitoring from the thermal camera. To train a Convolutional Neural Network (CNN) detector we create a stylized version of COCO (Common Objects in Context) dataset using Style Transfer technique that imitates images obtained from thermal cameras. This new dataset is further used for fine-tuning of the model and as a result detection accuracy on images...
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Neural Architecture Search for Skin Lesion Classification
PublicationDeep neural networks have achieved great success in many domains. However, successful deployment of such systems is determined by proper manual selection of the neural architecture. This is a tedious and time-consuming process that requires expert knowledge. Different tasks need very different architectures to obtain satisfactory results. The group of methods called the neural architecture search (NAS) helps to find effective architecture...
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Zastosowanie sieci neuronowych do detekcji impulsów o znanym kształcie w obecności silnego szumu i trendu
PublicationDetekcja impulsów w odebranym sygnale radiowym, zwłaszcza w obecności silnego szumu oraz trendu, jest trudnym zadaniem. Artykuł przedstawia propozycje rozwiązań wykorzystujących sieci neuronowe do detekcji impulsów o znanym kształcie w obecności silnego szumu i trendu. Na potrzeby realizacji tego zadania zaproponowano dwie architektury. W pracy przedstawiono wyniki badań wpływu kształtu impulsu, mocy zakłóceń szumowych oraz trendu...
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Przegląd robotów humanoidalnych
PublicationW artykule przedstawiono przegląd najpopularniejszych robotów humanoidalnych, wyróżniając ich ważniejsze cechy i porównując podstawowe charakterystyki, biorąc przy tym pod uwagę pożądane kognitywne aspekty rozwoju robotyki. Wśród osiągalnych cech rozmaitych rozwiązań aparatów humanoidalnych dostępnych na rynku – wyróżnia się głównie liczbę stopni swobody, rodzaj zastosowanego układu lokomocji oraz możliwości wyrażania mimiki twarzy,...
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The determinants of the Region's and its SMEs' Competitive Position in the Context of Mega Events - the Case of the Euro 2012
PublicationIn this paper a modified Preuss model was used to assess the factors to enhance the competitiveness of the region and the SMEs located in the region. To accomplish the above, six types of event-structure were applied: infrastructure, knowledge, networks, culture, image and emotions. They were described in detail in reference to the case of Euro 2012 in Poland in general and Pomeranian region in particular. Finally the Authors take...
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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...