The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The empirical results of investigating vocal correlate of depression in female adults are presented in that the certain acoustical property of spoken sound based on spectral entropy is capable of relating the affect change in speech with the symptom severity in diagnostic speakers. Studied sub-band entropies achieved the 93% correct classification in classifying two classes of depressed and remitted...
Fetal heart rate (fHR) is used to evaluate the fetal well-being during the delivery. It provides information of fetal status and allows doctors to detect ongoing hypoxia. The routine intrapartal evaluation is based on description of macroscopic morphological features of the fHR baseline. FHR contains more information than is used so far, therefore in this work we have focused on evaluation of nonlinear...
Chronic pain is a common long-term condition that changes patients' physical and emotional functioning. Currently, the integrated biopsychosoical approach is the mainstay treatment for patients with chronic pain. Self reporting (the use of questionnaires) is one of the most common methods to evaluate treatment outcome. Nevertheless, a large number of questions (for example 329 questions in this study)...
Sentiment classification is an applied technology with great significance. It can help people find right reviews in a more efficient way. In this paper, we present a novel efficient method for BBS sentiment classification. Through extracting sentiment-bearing words from WordNet using the maximum entropy, a ranking criterion based on a function of the probability of having Polarity or not is introduced...
Document classification is an important task in the field of document management. Bayesian model needs the feature independent assumption; artificial neural network suffers from the overfitting problem; support vector machine (SVM) does not do well in real-value feature. This paper proposes to combine entropy and machine learning techniques for document classification. Firstly, the cross entropy and...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.