9 pubblicazioni classificate nel seguente modo:

Nr. doc. Classificazioni
5 1 Contributo su Rivista
3 4 Contributo in Atti di Convegno (Proceeding)
1 2 Contributo in Volume
Anno Risorsa
2021 A grapevine leaves dataset for early detection and classification of esca disease in vineyards through machine learning
Autore/i: Alessandrini, M.; Calero Fuentes Rivera, R.; Falaschetti, L.; Pau, D.; Tomaselli, V.; Turchetti, C.
Classificazione: 1 Contributo su Rivista
Abstract: Esca is one of the most common disease that can severely damage grapevine. This disease, if not properly treated in time, is the cause of vegetative stress or death of the attacked plant, with the consequence of losses in production as well as a rising risk of propagation to the closer grapevines. Nowadays, the detection of Esca is carried out manually through visual surveys usually done by agronomists, requiring enormous amount of time. Recently, image processing, computer vision and machine learning methods have been widely adopted for plant diseases classification. These methods can minimize the time spent for anomaly detection ensuring an early detection of Esca disease in grapevine plants that helps in preventing it to spread in the vineyards and in minimizing the financial loss to the wine producers. In this article, an image dataset of grapevine leaves is presented. The dataset holds grapevine leaves images belonging to two classes: unhealthy leaves acquired from plants affected by Esca disease and healthy leaves. The data presented has been collected to be used in a research project jointly developed by the Department of Information Engineering, Polytechnic University of Marche, Ancona, Italy and the STMicroelectronics, Italy, under the cooperation of the Umani Ronchi SPA winery, Osimo, Ancona, Marche, Italy. The dataset could be helpful to researchers who use machine learning and computer vision algorithms to develop applications that help agronomists in early detection of grapevine plant diseases. The dataset is freely available at http://dx.doi.org/10.17632/89cnxc58kj.1
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/287679 Collegamento a IRIS

2021 Singular Value Decomposition in Embedded Systems Based on ARM Cortex-M Architecture
Autore/i: Alessandrini, Michele; Biagetti, Giorgio; Crippa, Paolo; Falaschetti, Laura; Manoni, Lorenzo; Turchetti, Claudio
Classificazione: 1 Contributo su Rivista
Abstract: Singular value decomposition (SVD) is a central mathematical tool for several emerging applications in embedded systems, such as multiple-input multiple-output (MIMO) systems, data analytics, sparse representation of signals. Since SVD algorithms reduce to solve an eigenvalue problem, that is computationally expensive, both specific hardware solutions and parallel implementations have been proposed to overcome this bottleneck. However, as those solutions require additional hardware resources that are not in general available in embedded systems, optimized algorithms are demanded in this context. The aim of this paper is to present an efficient implementation of the SVD algorithm on ARM Cortex-M. To this end, we proceed to (i) present a comprehensive treatment of the most common algorithms for SVD, providing a fairly complete and deep overview of these algorithms, with a common notation, (ii) implement them on an ARM Cortex-M4F microcontroller, in order to develop a library suitable for embedded systems without an operating system, (iii) find, through a comparative study of the proposed SVD algorithms, the best implementation suitable for a low-resource bare-metal embedded system, (iv) show a practical application to Kalman filtering of an inertial measurement unit (IMU), as an example of how SVD can improve the accuracy of existing algorithms and of its usefulness on a such low-resources system. All these contributions can be used as guidelines for embedded system designers. Regarding the second point, the chosen algorithms have been implemented on ARM Cortex-M4F microcontrollers with very limited hardware resources with respect to more advanced CPUs. Several experiments have been conducted to select which algorithms guarantee the best performance in terms of speed, accuracy and energy consumption.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/286171 Collegamento a IRIS

2020 Understanding the complex of suicide in depression: From research to clinics
Autore/i: Orsolini, L.; Latini, R.; Pompili, M.; Serafini, G.; Volpe, U.; Vellante, F.; Fornaro, M.; Valchera, A.; Tomasetti, C.; Fraticelli, S.; Alessandrini, M.; La Rovere, R.; Trotta, S.; Martinotti, G.; Di Giannantonio, M.; De Berardis, D.
Classificazione: 1 Contributo su Rivista
Abstract: Objective Amongst psychiatric disorders, major depressive disorder (MDD) is the most prevalent, by affecting approximately 15–17of the population and showing a high suicide risk rate equivalent to around 15%. The present comprehensive overview aims at evaluaing main research studies in the field of MDD at suicide risk, by proposing as well as a schematic suicide risk stratification and usefuflow-chart for planning suicide preventive and therapeutic interventions for clinicians. Methods A broad and comprehensive overview has been here conducted by using PubMed/Medline, combining the search strategy of free text terms and exploded MESH headings for the topics of ‘Major Depressive Disorder’ and ‘Suicide’ as following: ((suicide [Title/Abstract]) AND (major depressive disorder [Title/Abstract])). All articles published in English through May 31, 2019 were summarized in a comprehensive way. Results Despite possible pathophysiological factors which may explain the complexity of suicide in MDD, scientific evidence supposed the synergic role of genetics, exogenous and endogenous stressors (i.e., interpersonal, professional, financial, as well as psychiatric disorders), epigenetic, the hypothalamic-pituitary-adrenal stress-response system, the involvement of the monoaminergic neurotransmitter systems, particularly the serotonergic ones, the lipid profile, neuro-immunological biomarkers, the Brain-derived neurotrophic factor and other neuromodulators. Conclusion The present overview reported that suicide is a highly complex and multifaceted phenomenon in which a large plethora of mechanisms could be variable implicated, particularly amongst MDD subjects. Beyond these consideration, modern psychiatry needs a better interpretation of suicide risk with a more careful assessment of suicide risk stratification and planning of clinical and treatment interventions. Psychiatry Investig 2020;17(3):207-221.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/276954 Collegamento a IRIS

2016 Optimizing linear routing in the ToLHnet protocol to improve performance over long RS-485 buses
Classificazione: 1 Contributo su Rivista
Abstract: As the adoption of sensing and control networks rises to encompass the most diverse fields, the need for simple, efficient interconnection between many different devices will become ever more pressing. Though wireless communication is certainly appealing, current technological limits still prevent its usage where high reliability is needed or where the electromagnetical environment is not really apt to let radio waves through. In these cases, a wired link, based on a robust and well-consolidated standard such as an RS-485 bus, might prove to be a good choice. In this paper, we present an extension to the routing strategy originally implemented in the recently proposed “tree or linear hopping network” (ToLHnet) protocol, aimed at better handling the special but important case of linear routing over a (possibly very long) wired link, such as an RS-485 bus. The ToLHnet protocol was especially developed to suit the need of low complexity for deployments on large control networks. Indeed, using it over RS-485 already makes it possible to overcome many of the traditional limitations regarding cable length, without requiring segmenting the bus to install repeaters. With the extension here proposed, it will also be possible to simultaneously reduce latency (i.e., increase throughput, should it matter) for short-distance communications over the same cable, largely increasing the overall network efficiency, with a negligible increase in the complexity of the nodes’ firmware.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/236329 Collegamento a IRIS

2014 A Speech Interaction System for an Ambient Assisted Living Scenario
Ambient Assisted Living
Autore/i: M. Alessandrini; G. Biagetti; A. Curzi; C. Turchetti
Editore: Springer International Publishing
Classificazione: 2 Contributo in Volume
Abstract: In this work we describe a speech recognition system aimed at controlling various apparatus of an intelligent home. The system is especially tailored, and ad-hoc optimizations and strategies have been implemented, to make it suitable to operate unobtrusively in the ambient, requiring that the user only installs small and cheap audio front-ends that will capture his spoken commands. A recognition back-end, running either as a network service reached over the Internet or on a PC in the user’s home, performs the hard work of processing the data and turning it into commands, which are sent back to the desired actuator in the home. A case study involving the voice control of a DALI lighting system is presented, together with ideas and results on how to improve recognition accuracy and command spotting efficiency of a system which, by its very nature, might have to deal with audio captured from a distance and great amounts of background noise and unrelated sounds.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/205829 Collegamento a IRIS

2013 A garbage model generation technique for embedded speech recognisers
Proceedings of the 2013 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA 2013)
Autore/i: Michele Alessandrini; Giorgio Biagetti; Alessandro Curzi; Claudio Turchetti
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In this paper we present a simple but effective technique to help the designer of a voice-operated appliance add out-of-grammar command rejection capabilities, with a minimal effort and without overly degrading the recognition accuracy. Given the desired operational grammar of the appliance, and starting from a generic pre-trained acoustic model and comprehensive dictionary, we use a speech recogniser to identify suitable decoys to be added to the target grammar. These decoys will capture most of the spoken out-of-vocabulary words, and with appropriate changes to the desired grammar, will make the rejection of unintended commands quite easy. An evaluation of the performance of the proposed approach has been carried out on a sample appliance we developed, and tested with several users, under different acoustic conditions, in a command-spotting scenario. The reported results show that the proposed approach largely outperforms the standard phone loop-based approach.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/158106 Collegamento a IRIS

2013 A Speech Interaction System for an Ambient Assisted Living Scenario
Atti del 4º Forum Italiano per l'Ambient Assisted Living (FORITAAL 2013)
Autore/i: Michele Alessandrini; Giorgio Biagetti; Alessandro Curzi; Claudio Turchetti
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/163548 Collegamento a IRIS

2011 Semi-automatic acoustic model generation from large unsynchronized audio and text chunks
Proceedings of the 12th Annual Conference of the International Speech Communication Association
Autore/i: Alessandrini M.; Biagetti G.; Curzi A.; Turchetti C.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In this paper an effective technique to train an acoustic model from large and unsynchronized audio and text chunks is presented. Given such a speech corpus, an algorithm to automatically segment each chunk into smaller fragments and to synchronize those to the corresponding text is defined. These smaller fragments are more suitable to be used in standard model training algorithms for usage in automatic speech recognition systems. The proposed approach is particularly suitable to bootstrap language models without relying neither on specialized training material nor borrowing from models trained for other similar languages. Extensive experimentation using the CMU Sphinx 4 recognizer and the SphinxTrain model generator in a setting designed for large-vocabulary continuous speech recognition shows the effectiveness of the approach.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/62801 Collegamento a IRIS

2004 SiSMA - A tool for efficient analysis of analog CMOS integrated circuits affected by device mismatch
Autore/i: Giorgio, Biagetti; Simone, Orcioni; Claudio, Turchetti; Paolo, Crippa; Michele, Alessandrini
Classificazione: 1 Contributo su Rivista
Abstract: In this paper a simulator for the statistical analysis of analog CMOS integrated circuits affected by technological tolerance effects, including device mismatch, is presented. The tool, able to perform dc, ac, and transient analyses, is based on a rigorous formulation of circuit equations starting from the modified nodal analysis and including random current sources to take into account technological tolerances. Statistical simulation of specific circuits shows that the simulator requires a simulation time several orders of magnitude lower than that required by Monte Carlo analysis, while ensuring a good accuracy.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/52193 Collegamento a IRIS

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