1,721,083 research outputs found
A Data Compression Strategy for the Efficient Uncertainty Quantification of Time-Domain Circuit Responses
Full text linkThis paper presents an innovative modeling strategy for the construction of efficient and compact surrogate models for the uncertainty quantification of time-domain responses of digital links. The proposed approach relies on a two-step methodology. First, the initial dataset of available training responses is compressed via principal component analysis (PCA). Then, the compressed dataset is used to train compact surrogate models for the reduced PCA variables using advanced techniques for uncertainty quantification and parametric macromodeling. Specifically, in this work sparse polynomial chaos expansion and least-square support-vector machine regression are used, although the proposed methodology is general and applicable to any surrogate modeling strategy. The preliminary compression allows limiting the number and complexity of the surrogate models, thus leading to a substantial improvement in the efficiency. The feasibility and performance of the proposed approach are investigated by means of two digital link designs with 54 and 115 uncertain parameters, respectively
A Probabilistic Machine Learning Approach for the Uncertainty Quantification of Electronic Circuits Based on Gaussian Process Regression
Full text linkThis paper introduces a probabilistic machine learning framework for the uncertainty quantification (UQ) of electronic circuits based on Gaussian process regression (GPR). As opposed to classical surrogate modeling techniques, GPR inherently provides information on the model uncertainty. The main contribution of this work is twofold. First, it describes how, in an UQ scenario, the model uncertainty can be combined with the uncertainty of the input design parameters to provide confidence bounds for the statistical estimates of the system outputs, such as moments and probability distributions. These confidence bounds allows assessing the accuracy of the predicted statistics. Second, in order to deal with dynamic multi-output systems, principal component analysis (PCA) is effectively employed to compress the time-dependent output variables into a smaller set of components, for which the training of individual GPR models becomes feasible. The uncertainty on the principal components is then propagated back to the original output variables. Several application examples, ranging from a trivial RLC circuit to real-life designs, are used to illustrate and validate the advocated approach
Potenziare gli apprendimenti in matematica
No full textLe competenze matematiche rivestono un ruolo cruciale nell’affrontare sfide decisive in alcuni settori chiave come quello scientifico, tecnologico e sociale. Le indagini internazionali hanno mostrato differenze rilevanti fra paesi circa le competenze degli allievi in questo ambito, con una crescita costante del profitto degli studenti dell’area asiatica. In particolare, il metodo adottato a Singapore si è dimostrato efficace per l’insegnamento della matematica. Il volume presenta il programma EIS (enattivo, iconico, simbolico), un adattamento del modello Singapore alla realtà scolastica italiana, che ne riprende i tre momenti essenziali (concreto, pittorico, astratto). Il testo descrive le evidenze alla base della validità dell’approccio, i principi che ne guidano l’implementazione, la struttura, l’impianto metodologico-didattico, le modalità di applicazione in classe e i risultati di una prima sperimentazione sul territorio italiano
Progettare la media education. Dall'idea all'azione, nella scuola e nei servizi educativi
No full textChe rapporto c’è tra media education e formazione? Nella “società dell’informazione”, la media education è la formazione. Chi si occupa di media education non può prescindere da competenze specifiche di progettazione formativa e chi si occupa di progettazione formativa non può che trarre giovamento da specifiche competenze di media education, se vuole proporre interventi formativi solidamente ancorati alle modalità odierne di diffusione del sapere.
Nato da un lungo lavoro di équipe e da una pluriennale esperienza sul campo, questo volume cerca di accompagnare il media educator – insegnante, educatore, formatore – in tutti quei momenti che si svolgono “dietro le quinte” e che rendono possibile (ed efficace) il suo intervento in aula: progettazione, ricerca dei finanziamenti, monitoraggio, valutazione e documentazione degli interventi.
Partendo dal presupposto che “non vi è nulla di più pratico di una buona teoria”, i modelli proposti intendono sia guidare il principiante a sviluppare progetti non improvvisati ed estemporanei, sia offrire all’esperto una base teorica con cui analizzare e rielaborare la propria esperienza sul campo, attivando un processo di riflessione virtuosa e crescita professionale
Effects of the Enactive, Iconic, Symbolic (EIS) Intervention on Student Math Skills in Primary School
Full text link«Enactive, Iconic, Symbolic» (EIS) is a recently developed program modeled after instructional methodologies used in the Singapore math approach. The intervention emphasizes sequential mastery of math concepts, problem solving, and the use of the Concrete to Pictorial to Abstract approach (CPA). This quasi-experimental study evaluates the impact of EIS program on student math performance to explore the applicability of the Singapore approach in the Italian context and define the most appropriate methods for future large-scale evaluations. Eleven third- through fifth-grade treatment classes were matched comparison classes using propensity score matching, with mathematics performance measured before and after the intervention. A two-level random intercept hierarchical linear model was used to estimate treatment impact. We found no statistical significance effects of EIS after 16-20 weeks, ranging between 0.12 to 0.35 standard deviation units. The findings suggest the need for further investigations through largescale evaluations
A Hierarchical Approach to the Stochastic Analysis of Transmission Lines via Polynomial Chaos
Full text linkPolynomial chaos-based techniques recently became popular tools for signal integrity investigations that include the effects of parameter variability. Most of the available approaches are limited by the "curse of dimensionality", apply only to Gaussian correlations, or they are hindered by the lack of explicit parametrization or knowledge of the input random parameters. This paper presents a hierarchical approach for transmission line analysis, according to which line voltages and currents are mod-eled as polynomial chaos expansions that are function of the per-unit-length parameters, rather than of the underlying geometrical and material parameters. This new approach exhibits some useful advantages such as non-parametricity (with respect to physical parameters), higher accuracy for low expansion orders, and a potential for dimensionality reduction. An application example involving the transient analysis of a stripline interconnect is used to illustrate the feasibility of the advocated approach and discuss its performance
Compressed Complex-Valued Least Squares Support Vector Machine Regression for Modeling of the Frequency-Domain Responses of Electromagnetic Structures
Full text linkThis paper deals with the development of a Machine Learning (ML)-based regression for the construction of complex-valued surrogate models for the analysis of the frequency-domain responses of electromagnetic (EM) structures. The proposed approach relies on the combination of two-techniques: (i) the principal component analysis (PCA) and (ii) an unusual complex-valued formulation of the Least Squares Support Vector Machine (LS-SVM) regression. First, the training and test dataset is obtained from a set of parametric electromagnetic simulations. The spectra collected in the training set are compressed via the PCA by exploring the correlation among the available data. In the next step, the compressed dataset is used for the training of compact set of complex-valued surrogate models and their accuracy is evaluated on the test samples. The effectiveness and the performance of the complex-valued LS-SVM regression with three kernel functions are investigated on two application examples consisting of a serpentine delay structure with three parameters and a high-speed link with four parameters. Moreover, for the last example, the performance of the proposed approach is also compared with those provided by a real-valued multi-output feedforward Neural Network model
Quale strada intraprendere per la formazione degli insegnanti secondari?
Full text linkA proposal for secondary teacher training cannot avoid the comparison with the relevant critical issues, highlighted by the current literature, such as: the advanced age of young graduates that start teaching; the poor reputation of this profession; the absence of an equivalence in terms of training and role between the classroom teacher and the support teacher; the excessively abstract training, with a few correspondence to the real problems of teaching (and with internship models mostly inert, understood as a period to be “consumed” only in the school context). This paper reflects the proposal created within the SApIE association (www.sapie.it). It critically examines the past solutions, the hypotheses on the table, it tries to suggest a new path capable of answering these problems and, also, it involves an organic reconfiguration and enhancement of didactic and experimental pedagogical knowledge.Una proposta per la formazione degli insegnanti secondari non può prescindere dal confronto con le rilevanti criticità, ormai a lungo evidenziate dalla letteratura corrente, quali: a) età avanzata in cui i giovani laureati iniziano ad insegnare; b) scarsa reputazione della professione; c) assenza di una equivalenza di formazione e di ruolo tra insegnante curricolare e di sostegno; d) formazione eccessivamente astratta, con scarsa rispondenza ai problemi reali della didattica (e con modelli di tirocinio per lo più inerti, intesi come periodo da “consumare” in un contesto scolastico). Il lavoro qui presentato rispecchia la proposta nata all’interno dell’associazione SApIE (www.sapie.it). Esso riesamina criticamente le soluzioni passate, le ipotesi sul tappeto e suggerisce una nuova strada capace di rispondere a questi problemi, che comporta anche una riconfigurazione e valorizzazione organica dei saperi pedagogici didattici e sperimentali
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