The widespread decline of honey bee (Apis mellifera L.) colonies registered in recent years has raised great attention to the need gathering deeper knowledge about this phenomenon, by observing colonies’ activity identify possible causes, and design corresponding countermeasures. In fact, bees have well-known positive effects on both environment human life, their preservation becomes critical not only for ecological reasons, but also social economic development rural communities. Smart...

Lithium-ion batteries (LIBs) can play a crucial role in the decarbonization process that is being tackled worldwide; millions of electric vehicles are already provided with or directly powered by LIBs, and large number them will flood markets within next 8–10 years. Proper disposal strategies required, sustainable environmental impacts need to be considered. Despite still finding little applicability industrial field, recycling could become one most options handle end life LIBs. This review...

The human activity monitoring technology is one of the most important technologies for ambient assisted living, surveillance-based security, sport and fitness activities, healthcare elderly people. performed in two steps: acquisition body signals classification activities being performed. This paper presents a low-cost wearable wireless system specifically designed to acquire surface electromyography (sEMG) accelerometer when performing as well applications.The proposed consists several...

The absence of the queen in a beehive is very strong indicator need for beekeeper intervention. Manually searching an arduous recurrent task beekeepers that disrupts normal life cycle and can be source stress bees. Sound signalling different states beehive, including bee. In this work, we apply machine learning methods to automatically recognise using audio as input. We investigate both support vector machines convolutional neural networks state recognition, data beehives collected from...

Sport, fitness, as well rehabilitation activities, often require the accomplishment of repetitive movements. The correctness exercises is related to capability maintaining required cadence and muscular force. Failure maintain force, also known muscle fatigue, accompanied by a shift in spectral content surface electromyography (EMG) signal toward lower frequencies. This paper presents novel approach for simultaneously obtaining exercise repetition frequency evaluating functions time, only...

The wide diffusion of Full and Hybrid Electric Vehicles is stimulating research on electric energy storage systems Battery Management Systems (BMS). management system must ensure many complex features such as charge control, battery-capacity monitoring, remaining run-time information charge-cycle counting. An optimization the BMS can allow an improvement security vehicle, performance engine, extension life battery. main objective this work to develop a simulation environment based SystemC...

This paper proposes an improvement in cross-correlation methods derived from the Lee–Schetzen method, order to obtain a lower mean square error output for wider range of input variances. In particular, each Wiener kernel is identified with different variance and new formulas conversion Volterra representation are presented.

The market for lithium-ion batteries is growing exponentially. performance of battery cells due to improving production technology, but request even more rapidly. Modeling and characterization single an efficient simulation environment fundamental the development management system. present work devoted defining a novel lumped electrothermal circuit cell, extraction procedure parameters cell from experiments, in SystemC-WMS pack. model was validated against experimental measurements obtained...

This paper presents a technique for parametric model estimation of the motor unit action potential (MUAP) from surface electromyography (sEMG) signal by using homomorphic deconvolution. The cepstrum-based deconvolution removes effect stochastic impulse train, which originates sEMG signal, power spectrum itself. In this way, only information on MUAP shape and amplitude were maintained, then, used to estimate parameters time-domain order validate effectiveness technique, signals recorded...

This paper presents a flexible low-cost wireless system specifically designed to acquire fitness metrics both from surface electromyographic (sEMG) and electrocardiographic (ECG) signals. The system, that can be easily extended capture process many other biological signals as well the motion-related body signals, consists of several ultralight sensing nodes acquire, amplify, digitize, transmit or mechanical one more base stations through 2.4 GHz radio link using custom-made communication...

European self-sufficiency in the battery sector is one of major EU needs. The key lithium-ion batteries (LIBs) materials demand expected to increase next decade as a consequence increment LIBs production and massive amount spent will flood global markets. Hence, these waste streams would be potential source secondary raw valorized, under principle circular economy. governments first, then companies second, are addressing many efforts improving legislation on accumulators. This study explores...

Speaker identification plays a crucial role in biometric person as systems based on human speech are increasingly used for the recognition of people. Mel frequency cepstral coefficients (MFCCs) have been widely adopted decades processing to capture speech-specific characteristics with reduced dimensionality. However, although their ability decorrelate vocal source and tract filter make them suitable recognition, they greatly mitigate speaker variability, specific characteristic that...

Last years increase in bee mortality has underlined the necessity of an intensive hive monitoring order to better understand problems which are seriously affecting honey health. Sound emitted inside a beehive is one key parameters for non-invasive their health condition. In this context, proposed work aims at analyzing bees' sound introducing features extraction useful classification techniques and determine dangerous situations. Several experiments on real scenario have been performed...

The Low Complexity Enhancement Video Coding (LCEVC) specification is a recent standard approved by the ISO/IEC JTC 1/SC 29/WG04 (MPEG) Coding. main goal of LCEVC to provide standalone toolset for enhancement any other existing codec. It works on top coding schemes, resulting in multi-layer video technology, but unlike scalable codecs, adds layers completely independent from base video. technology takes as input decoded at lower resolution and up two sub-layers residuals encoded with...

The multiple-variance method is a cross-correlation that exploits input signals with different powers for the identification of nonlinear system by means Volterra series.It overcomes problem locality solution traditional methods, based on mean square error minimization or cross-correlation, well approximate only inputs have approximately same power signal.The permits to improve performance models systems high dynamic, like audio amplifiers.This used, first time, identify three tube...

An accurate management of the interactions among end user, electric vehicle, and charging station during recharge is fundamental for diffusion mobility. The paper proposes an extension Open Charge Point Protocol standard with aim including user in optimization process. negotiates central a reservation giving his/her preference flexibility. system provides different solutions based on user’s This negotiation allows power grid considering requests constraints. complete architecture has been...

Sleep is extremely important for physical and mental health. Although polysomnography an established approach in sleep analysis, it quite intrusive expensive. Consequently, developing a non-invasive non-intrusive home monitoring system with minimal influence on patients, that can reliably accurately measure cardiorespiratory parameters, of great interest. The aim this study to validate unobtrusive parameter based accelerometer sensor. This includes special holder install the under bed...

Automatic classification of electrocardiogram (ECG) signals is Paramount importance in the detection a wide range heartbeat abnormalities as aid to improve diagnostic achieved by cardiologists. In this paper an effective multi-class beat classifier, based on statistical identification minimum-complexity model, proposed. The classifier trained extracting from ECG signal multivariate random vector means truncated Karhunen-Loève transform (KLT) representation. resulting model thus estimated...