With an increased societal focus on a sustainable economy and a healthy population, well-being of knowledge workers has become an important topic. This paper investigates techniques to support a knowledge worker to manage his well-being. A possible solution is to monitor the workers’ behaviour and use this information for giving feedback as soon as his well-being is threatened. Knowledge worker...

background: we designed an algorithmic model based on the logistic regression analysis and a non-algorithmic model based on the artificial neural network (ann). materials and methods: the ability of these models was compared together in clinical application to differentiate malignant from benign breast tumors in a study group of 161 patients' records. each patient’s record consisted of 6 s...

The introduction of deep neural networks has significantly improved automatic speech recognition performance. For realworld use, automatic speech recognition systems must cope with varying background conditions and unseen acoustic data. This work investigates the performance of traditional deep neural networks under varying acoustic conditions and evaluates their performance with speech recorde...

The classification problem of determining if a surveillance camera sees persons is tackled with two neural models: the Self-Organizing Map (SOM) with supervision as in a classical conditioning analogy and Multi Layer Perceptrons (MLP). The first model, that we call Conditioning-SOM (C-SOM) allowed a quick selection of input features with a good tradeoff between computational cost and classifica...

In this paper, a fault diagnosis system based on discrete wavelet transform (DWT) and artificial neural networks (ANNs) is designed to diagnose different types of fault in gears and bearings. DWT is an advanced signal-processing technique for fault detection and identification. Five features of wavelet transform RMS, crest factor, kurtosis, standard deviation and skewness of discrete wavelet co...

We present a novel formulation of the multiple object tracking problem which integrates low and mid-level features. In particular, we formulate the tracking problem as a quadratic program coupling detections and dense point trajectories. Due to the computational complexity of the initial QP, we propose an approximation by two auxiliary problems, a temporal and spatial association, where the tem...