Search results for "Learning"
showing 10 items of 6669 documents
La enseñanza basada en preguntas : La ley de Ampère y el término de Maxwell
2020
Frecuentemente a los maestros de Física y de Matemáticas se les recomienda una enseñanza activa de estas áreas del conocimiento, que consiste en una interacción continua entre el maestro y el estudiante. Con una metáfora de un interrogatorio adecuado, se pretende mostrar al docente una manera de orientar al estudiante en su aprendizaje, motivándolo a recuperar conocimientos previos o causándole un conflicto cognitivo que lo lleve a reformular su aprendizaje. Esta manera de proceder didácticamente se ha llamado enseñanza basada en preguntas, cuya primera referencia histórica nos remite a la Grecia antigua. En este trabajo se presenta la enseñanza de la ley de Ampère con la generalización de …
A novel strategy for solving the stochastic point location problem using a hierarchical searching scheme
2014
Stochastic point location (SPL) deals with the problem of a learning mechanism (LM) determining the optimal point on the line when the only input it receives are stochastic signals about the direction in which it should move. One can differentiate the SPL from the traditional class of optimization problems by the fact that the former considers the case where the directional information, for example, as inferred from an Oracle (which possibly computes the derivatives), suffices to achieve the optimization-without actually explicitly computing any derivatives. The SPL can be described in terms of a LM (algorithm) attempting to locate a point on a line. The LM interacts with a random environme…
Discrete Learning Control with Application to Hydraulic Actuators
2015
In this paper the robustness of a class of learning control algorithms to state disturbances, output noise, and errors in initial conditions is studied. We present a simple learning algorithm and exhibit, via a concise proof, bounds on the asymptotic trajectory errors for the learned input and the corresponding state and output trajectories. Furthermore, these bounds are continuous functions of the bounds on the initial condition errors, state disturbance, and output noise, and the bounds are zero in the absence of these disturbances.
Multiobjective optimization and decision making in engineering sciences
2021
AbstractReal-world decision making problems in various fields including engineering sciences are becoming ever more challenging to address. The consideration of various competing criteria related to, for example, business, technical, workforce, safety and environmental aspects increases the complexity of decision making and leads to problems that feature multiple competing criteria. A key challenge in such problems is the identification of the most preferred trade-off solution(s) with respect to the competing criteria. Therefore, the effective combination of data, skills, and advanced engineering and management technologies is becoming a key asset to a company urging the need to rethink how…
A Short-Term Data Based Water Consumption Prediction Approach
2019
A smart water network consists of a large number of devices that measure a wide range of parameters present in distribution networks in an automatic and continuous way. Among these data, you can find the flow, pressure, or totalizer measurements that, when processed with appropriate algorithms, allow for leakage detection at an early stage. These algorithms are mainly based on water demand forecasting. Different approaches for the prediction of water demand are available in the literature. Although they present successful results at different levels, they have two main drawbacks: the inclusion of several seasonalities is quite cumbersome, and the fitting horizons are not very large. With th…
On utilizing an enhanced object partitioning scheme to optimize self-organizing lists-on-lists
2020
With the advent of “Big Data” as a field, in and of itself, there are at least three fundamentally new questions that have emerged, namely the Artificially Intelligence (AI)-based algorithms required, the hardware to process the data, and the methods to store and access the data efficiently. This paper (The work of the second author was partially supported by NSERC, the Natural Sciences and Engineering Council of Canada. We are very grateful for the feedback from the anonymous Referees of the original submission. Their input significantly improved the quality of this final version.) presents some novel schemes for the last of the three areas. There have been thousands of papers written rega…
Optimization and sensitivity analysis of existing deep learning models for pavement surface monitoring using low-quality images
2022
Automated pavement distress detection systems have become increasingly sought after by road agencies to in crease the efficiency of field surveys and reduce the likelihood of insufficient road condition data. However, many modern approaches are developed without practical testing using real-world scenarios. This paper ad dresses this by practically analyzing Deep Learning models to detect pavement distresses using French Secondary road surface images, given the issues of limited available road condition data in those networks. The study specifically explores several experimental and sensitivity-testing strategies using augmentation and hyper- parameter case studies to bolster practical mode…
Stabilization and controller design of 2D discrete switched systems with state delays under asynchronous switching
2013
Published version of a paper from the journal: Abstract and Applied Analysis. Also available from Hindawi:http://dx.doi.org/10.1155/2013/961870. Open Access This paper is concerned with the problem of robust stabilization for a class of uncertain two-dimensional (2D) discrete switched systems with state delays under asynchronous switching. The asynchronous switching here means that the switching instants of the controller experience delays with respect to those of the system. The parameter uncertainties are assumed to be norm-bounded. A state feedback controller is proposed to guarantee the exponential stability. The dwell time approach is utilized for the stability analysis and controller …
The Patras blended strategy model for deep and meaningful learning in quality life-long distance education
2019
Life‑long learning is currently being embraced as a central process that could disrupt traditional educational paths. Apparently, the (ideal) type of learning often promoted is deep and meaningful learning, though it is not always required to be so. Deep learning goes beyond superficial knowledge assimilation of unlinked facts; it aims at developing deep disciplinary understanding, transformative knowledge, personal meaning, emotional intelligence, critical thinking, creativity and metacognitive skills. Meaningful learning occurs when learning is active, constructive, intentional, authentic, and cooperative. Technology enhanced teaching and learning methods should prove their potential to t…
Finnish pre-service teachers’ perceptions of their strategic learning skills and collaboration dispositions
2019
To support the development of pupils’ 21st-century skills, teachers themselves must also be competent in these skills and learn them during pre-service teacher education. The aim of this study is to investigate what kind of profiles emerge among Finnish first-year pre-service teachers’ (N = 872) in terms of perceptions of their strategic learning skills and collaboration dispositions and what background variables explain membership of the profiles found. Latent profile analysis showed five student profiles corresponding to perceived strategic learning skills and collaboration dispositions. The most robust factor explaining the membership of the profiles was life satisfaction. Pre-service te…