Speech Emotion Recognition (SER) is an important part of speech-based Human-Computer Interface (HCI) applications. Previous SER methods rely on the extraction of features and training an appropriate classifier. However, most of those features can be affected by emotionally irrelevant factors such as gender, speaking styles and environment. Here, an SER method has been proposed based on a concat...

BACKGROUND Few studies have examined mental health consumers' motives for seeking advocacy assistance. AIMS This study aimed to identify factors that influenced mental health consumers' use of advocacy services. METHODS The analysis was based on 60 case records that were sourced from a community advocacy service. Each record was dichotomously coded across 11 variables to generate a series o...

The (k, a)-generalized wavelet transform is a novel addition to the class of transforms, which has gained respectable status in realm time-frequency signal analysis within short period time. Since study both theoretically interesting and practically useful, this article, we investigated several subjects for transform. First, analyze concentration on sets finite measure. In particular, prove Don...

The problem of recognition and classification biomedical signals is a complex related to the interdisciplinary field computer science medicine. Within framework project implementation development new defibrillation equipment, it necessary solve problems analyzing electrocardiogram obtain diagnostic solution with possibility assigning specific condition pathological patient. This article present...

Penelitian ini bertujuan untuk menganalisis kemampuan pemahaman konsep geometri siswa sekolah dasar yang dilaksanakan dengan model pembelajaran blended learning melalui pemodelan RASCH. Pemodelan RASCH mampu mengidentifikasi terhadap suatu dianalisis dalam menjawab soal. memberikan gambaran secara jelas bagi guru pengukuran dimiliki tepat. yakni deskriptif kualitatif pada analisas Terdapat 27 d...

Sleep apnea is a common symptomatic disease affecting nearly 1 billion people around the world. The gold standard approach for determining severity of sleep full-night polysomnography conducted in laboratory, which very costly and cumbersome. In this work, we propose novel scalogram-based convolutional neural network (SCNN) to detect obstructive (OSA) using single-lead electrocardiogram (ECG) s...

The use of linear phase Gabor transform wavelets is demonstrated as a robust analysis technique capable of making explicit many elements of human rhythm perception behaviour. Transforms over a continuous time-frequency plane (the scalogram) spanning rhythmic frequencies (0.1 to 100Hz) capture the multiple periodicities implied by beats at diierent temporal relationships. Wavelets represent well...

An arrhythmia is an irregular heartbeat that causes abnormal heart rhythms. Manual analysis of electrocardiogram (ECG) signals not sufficient to quickly detect cardiac arrhythmias. This study proposes a deep learning approach based on convolutional neural network (CNN) architecture for the classification arrhythmias (ARR), congestive failure (CHF), and normal sinus rhythm (NSR). First, ECG sign...

Listening to lung sounds through auscultation is vital in examining the respiratory system for abnormalities. Automated analysis of can be beneficial health systems low-resource settings where there a lack skilled physicians. In this work, we propose lightweight convolutional neural network (CNN) architecture classify diseases from individual breath cycles using hybrid scalogram-based features ...