Search results for "LEARNING"
showing 10 items of 6669 documents
Inducing Rules of Ensemble Music Performance : A Machine Learning Approach
2013
Previous research in expressive music performance has described how solo musicians intuitively shape each note in relation to local/global score contexts. However, expression in ensemble performances, where each individual voice is played simultaneously with other voices, has been little explored. We present an exploratory study in which the performance of a string quartet is recorded and analysed by a computer. We use contact microphones to acquire four audio signals from which a set of audio descriptors is extracted individually for each musician. Moreover, we use motion capture to extract bowing descriptors (bow velocity/force) from each of the four performers. The gathered multimodal da…
A Spotlight on the Role of Radiomics and Machine-Learning Applications in the Management of Intracranial Meningiomas: A New Perspective in Neuro-Onco…
2022
Background: In recent decades, the application of machine learning technologies to medical imaging has opened up new perspectives in neuro-oncology, in the so-called radiomics field. Radiomics offer new insight into glioma, aiding in clinical decision-making and patients’ prognosis evaluation. Although meningiomas represent the most common primary CNS tumor and the majority of them are benign and slow-growing tumors, a minor part of them show a more aggressive behavior with an increased proliferation rate and a tendency to recur. Therefore, their treatment may represent a challenge. Methods: According to PRISMA guidelines, a systematic literature review was performed. We included selected a…
Performance Evaluation of EEG Based Mental Stress Assessment Approaches for Wearable Devices
2021
Mental stress has been identified as the root cause of various physical and psychological disorders. Therefore, it is crucial to conduct timely diagnosis and assessment considering the severe effects of mental stress. In contrast to other health-related wearable devices, wearable or portable devices for stress assessment have not been developed yet. A major requirement for the development of such a device is a time-efficient algorithm. This study investigates the performance of computer-aided approaches for mental stress assessment. Machine learning (ML) approaches are compared in terms of the time required for feature extraction and classification. After conducting tests on data for real-t…
Determinantes Sociales de la Salud, Modos de Transporte, y su Relación con Riesgo de Accidentalidad en Jóvenes residentes de la Región Metropolitana …
2022
Antecedentes y tema de trabajo: La movilidad y la circulación determinan dinámicas que caracterizan la vida humana. Estas actividades son tan importantes que se consideran un derecho humano universal, constituyéndose en fuente de constante preocupación para investigadores, gobiernos e instituciones. Las limitaciones al ejercicio de este derecho son un detrimento para la calidad de vida, especialmente cuando conlleva un número inaceptable de muertes y lesiones que hoy se consideran de carácter pandémico. Los eventos desfavorables para la movilidad y la circulación suelen denominarse como “suceso”, “incidente”, “choque”, “colisión”, y quizás el termino más empleado sea “accidente”. Ni experto…
Audiovisual processing of Chinese characters elicits suppression and congruency effects in MEG
2019
Learning to associate written letters/characters with speech sounds is crucial for reading acquisition. Most previous studies have focused on audiovisual integration in alphabetic languages. Less is known about logographic languages such as Chinese characters, which map onto mostly syllable-based morphemes in the spoken language. Here we investigated how long-term exposure to native language affects the underlying neural mechanisms of audiovisual integration in a logographic language using magnetoencephalography (MEG). MEG sensor and source data from 12 adult native Chinese speakers and a control group of 13 adult Finnish speakers were analyzed for audiovisual suppression (bimodal responses…
Compensated transfer entropy as a tool for reliably estimating information transfer in physiological time series
2013
We present a framework for the estimation of transfer entropy (TE) under the conditions typical of physiological system analysis, featuring short multivariate time series and the presence of instantaneous causality (IC). The framework is based on recognizing that TE can be interpreted as the difference between two conditional entropy (CE) terms, and builds on an efficient CE estimator that compensates for the bias occurring for high dimensional conditioning vectors and follows a sequential embedding procedure whereby the conditioning vectors are formed progressively according to a criterion for CE minimization. The issue of IC is faced accounting for zero-lag interactions according to two a…
Dynamics of brain activation during learning of syllable-symbol paired associations.
2019
| openaire: EC/H2020/641652/EU//ChildBrain Initial stages of reading acquisition require the learning of letter and speech sound combinations. While the long-term effects of audio-visual learning are rather well studied, relatively little is known about the short-term learning effects at the brain level. Here we examined the cortical dynamics of short-term learning using magnetoencephalography (MEG) and electroencephalography (EEG) in two experiments that respectively addressed active and passive learning of the association between shown symbols and heard syllables. In experiment 1, learning was based on feedback provided after each trial. The learning of the audio-visual associations was c…
Comparison of machine learning and logistic regression as predictive models for adverse maternal and neonatal outcomes of preeclampsia: A retrospecti…
2022
IntroductionPreeclampsia, one of the leading causes of maternal and fetal morbidity and mortality, demands accurate predictive models for the lack of effective treatment. Predictive models based on machine learning algorithms demonstrate promising potential, while there is a controversial discussion about whether machine learning methods should be recommended preferably, compared to traditional statistical models.MethodsWe employed both logistic regression and six machine learning methods as binary predictive models for a dataset containing 733 women diagnosed with preeclampsia. Participants were grouped by four different pregnancy outcomes. After the imputation of missing values, statistic…
Convolutional Neural Network Based Sleep Stage Classification with Class Imbalance
2022
Accurate sleep stage classification is vital to assess sleep quality and diagnose sleep disorders. Numerous deep learning based models have been designed for accomplishing this labor automatically. However, the class imbalance problem existing in polysomnography (PSG) datasets has been barely investigated in previous studies, which is one of the most challenging obstacles for the real-world sleep staging application. To address this issue, this paper proposes novel methods with signal-driven and image-driven ways of noise addition to balance the imbalanced relationship in the training dataset samples. We evaluate the effectiveness of the proposed methods which are integrated into a convolut…
Emigracja a proces uczenia się małżonków
2022
Wstąpienie Polski do struktur Unii Europejskiej zapoczątkowało emigrację poakcesyjną Polaków, dla której charakterystyczne było pojawienie się nowych kierunków wyjazdów emigracyjnych. Jednym z najbardziej popularnych stała się Wielka Brytania. Wyjazd emigracyjny jest wydarzeniem znaczącym w biografii człowieka i całej jego rodziny. W świetle koncepcji Agnieszki Bron (2000, 2006), wiąże się on z licznymi napięciami, ambiwalencją, poczuciem bezradności i zawieszenia (tzw. floating), a jednocześnie jest wydarzeniem o potencjale edukacyjnym. Celem badań uczyniono wyjaśnienie procesu uczenia się małżonków doświadczających emigracji. Przeprowadzono badania biograficzne z wykorzystaniem autobiogra…