Probabilistic electricity price forecasting (EPF) relies on several uncertainty-quantification paradigms whose behavior under regime shift is not well understood. Conformalized …
Reliable probabilistic electricity price forecasting constitutes an essential prerequisite for optimal battery scheduling in deregulated energy markets. This study presents a …
The exponential growth of IoT deployments introduces new challenges in real-time network security and behavioral monitoring. Existing Intrusion Detection Systems (IDS) and activity …
Modern Internet of Things (IoT) environments are monitored via a large number of IoT enabled sensing devices, with the data acquisition and processing infrastructure setting …
Twitter is one of the most popular social networks attracting millions of users, while a considerable proportion of online discourse is captured. It provides a simple usage …
Venous thromboembolism (VTE) is the third most common cardiovascular condition. Some high risk patients diagnosed with VTE need immediate treatment and monitoring in intensive care …
Classification of impulsive events produced from the acoustic stimulation of everyday objects opens the door to exciting interactive applications, as for example, gestural control …
Internet-of-Things (IoT) aims at interconnecting thousands or millions of smart objects/devices in a seamless way by sensing, processing and analyzing huge amount of data obtained …
The growth of the global middle class provokes significant increment in product consumption. As the available resources are limited, Circular Economy (CE) raises as a promising …
This paper addresses the problem of joint wideband localization and acquisition of acoustic sources. The source locations as well as acquisition of the original source signals are …
Matrix completion is the process of estimating missing entries from a matrix using some prior knowledge. Typically, the prior knowledge is that the matrix is low-rank. In this …
Reconstruction of missing features promotes robustness in speaker recognition applications under noisy conditions. In this paper, we aim at enhancing the reliability of speech …
Speaker identification is a key component in many practical applications and the need of finding algorithms, which are robust under adverse noisy conditions, is extremely …
In this work, we examine the problem of noise robust speaker identification under short training sessions restrictions. In order to improve the identification performance, the …
In this paper two methods for noise-robust text-independent speaker identification are described and compared against a baseline method for speaker identification based on the …
Audio signals are represented via the sinusoidal model as a summation of a small number of sinusoids. This approach introduces sparsity to the audio signals in the frequency …
In this paper, the Sinusoids plus Noise Model (briefly SNM) is applied in a novel manner, in order to efficiently encode spot audio signals. These are the microphone recordings of …
This paper focuses on high-fidelity multichannel audio coding based on an enhanced adaptation of the well-known sinusoidal plus noise model (SNM). Sinusoids cannot be used per se …
This paper focuses on high-fidelity multichannel audio modeling based on an enhanced adaptation of the well-known sinusoidal plus noise model (SNM). Sinusoids cannot be used per se …
This paper describes a novel methodology for automatic musical genre classification based on a feature extraction/statistical similarity measurement approach. First, we perform a …