For a family of Szasz-Mirakyan type operators we prove that they preserve convex-type functions and that a monotonicity property verified by Cheney and Sharma in the case Szasz-Mirakyan operators ...holds for the variation study here. We also verify that several modulus of continuity are preserved.
In some old results, we find estimates the best approximation \(E_{n,p}(f)\) of a periodic function satisfying \(f^{(r)}\in\mathbb{L}^p_{2\pi}\) in terms of the norm of \(f^{(r)}\) (Favard ...inequality). In this work, we look for a similar result under the weaker assumption \(f^{(r)}\in \mathbb{L}^q_{2\pi}\), with \(1<q<p<\infty\). We will present inequalities of the form \(E_{n,p}(f)\leq C(n)\Vert D^{(r)}f\Vert_q\), where \(D^{(r)}\) is a differential operator. We also study the same problem in spaces of non-periodic functions with a Jacobi weight.
In a previous paper the author presented a Kantorovich modification of Baskakov operators which reproduce affine functions and he provided an upper estimate for the rate of convergence in polynomial ...weighted spaces.
In this paper, for the same family of operators, a strong inverse inequality is given for the case of approximation in norm.
We present upper and lower estimates of the error of approximation of periodic functions by Fejér means in the Lebesgue spaces
. The estimates are given in terms of a
-functional for
and in terms of ...the first modulus of continuity in the case
. We pay attention to the involved constants.
Insect flight is a strongly nonlinear and actuated dynamical system. As such, strategies for understanding its control have typically relied on either model-based methods or linearizations thereof. ...Here we develop a framework that combines model predictive control on an established flight dynamics model and deep neural networks (DNN) to create an efficient method for solving the inverse problem of flight control. We turn to natural systems for inspiration since they inherently demonstrate network pruning with the consequence of yielding more efficient networks for a specific set of tasks. This bio-inspired approach allows us to leverage network pruning to optimally sparsify a DNN architecture in order to perform flight tasks with as few neural connections as possible, however, there are limits to sparsification. Specifically, as the number of connections falls below a critical threshold, flight performance drops considerably. We develop sparsification paradigms and explore their limits for control tasks. Monte Carlo simulations also quantify the statistical distribution of network weights during pruning given initial random weights of the DNNs. We demonstrate that on average, the network can be pruned to retain a small amount of original network weights and still perform comparably to its fully-connected counterpart. The relative number of remaining weights, however, is highly dependent on the initial architecture and size of the network. Overall, this work shows that sparsely connected DNNs are capable of predicting the forces required to follow flight trajectories. Additionally, sparsification has sharp performance limits.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Thin films of colloidal semiconductor nanocrystals (NCs) are inherently metatstable materials prone to oxidative and photothermal degradation driven by their large surface-to-volume ratios and high ...surface energies. The fabrication of practical electronic devices based on NC solids hinges on preventing oxidation, surface diffusion, ripening, sintering, and other unwanted physicochemical changes that can plague these materials. Here we use low-temperature atomic layer deposition (ALD) to infill conductive PbSe NC solids with metal oxides to produce inorganic nanocomposites in which the NCs are locked in place and protected against oxidative and photothermal damage. Infilling NC field-effect transistors and solar cells with amorphous alumina yields devices that operate with enhanced and stable performance for at least months in air. Furthermore, ALD infilling with ZnO lowers the height of the inter-NC tunnel barrier for electron transport, yielding PbSe NC films with electron mobilities of 1 cm2 V–1 s–1. Our ALD technique is a versatile means to fabricate robust NC solids for optoelectronic devices.
•The crystallization of cane sugar is a highly complex process.•Monitoring cane sugar crystal growth is difficult and generally depends on the experience of the operator.•Multiscale time series ...analysis identifies information about the intrinsic phenomena of crystallization.•Multiscale analysis can be used as an inexpensive and simple qualitative tool for monitoring cane sugar crystal growth.
This work presents a proposal for the indirect monitoring of cane sugar crystallization using the multiscale analysis of temperature, pH, and torque time series. The time series were obtained at different crystallizer operating conditions; an experimental design considering four cooling profiles and three seed sizes was performed. Three multiscale methodologies (i.e., Detrended Fluctuation Analysis (DFA), R/S analysis, and Power Spectral Density (PSD)) were applied, identifying that the analyzed time series exhibit fractal behavior in three characteristic scale intervals, which suggests that the time series fluctuations may be a response to the interactions between transport phenomena inherent in the cane sugar crystallization process. By calculating the dynamic fractal dimension for the different characteristic scale intervals, correlations between the fractal dimension (FD) and the experimental measures of the key variables were identified, i.e., average crystal size,% volume, and formed mass crystal with FD calculated by temperature, pH, and torque time-series, respectively. Temperature, pH, and torque measurements are inexpensive, easy to implement, and can be obtained in real-time. The results suggest that multiscale time series analysis captured during the cane sugar crystallization has a high potential for indirect online monitoring with low economic and computational costs.
During the current global crisis unleashed by the severe acute respiratory syndrome coronavirus 2 outbreak, surgical departments have considerably reduced the amount of elective surgeries. This ...decrease leads to less time in the surgical room to develop and improve the surgical skills of residents. In this study, we developed a training program to obtain and maintain microsurgical skills at home, using a smartphone camera and low-cost materials, affordable for everyone.
Using a smartphone camera as a magnification device, 6 participants performed 5 exercises (coloring grids, grouping colors, unraveling of a gauze, knots with suture threads, and tower of Hanoi), both with the dominant and with the nondominant hand, for 4 weeks. We compared performance at the beginning and at the end of the training process. Each participant filled out an anonymous survey.
When we compared the performance at the beginning and at the end of the training process, we found significant improvements (P = 0.05) with the dominant as well as the nondominant hand in all the exercises. All participants were satisfied or very satisfied with the definition of the objectives of the training process, material availability, the exercises performed, the choice of the time to train, and general satisfaction with the training program.
We developed a microsurgical skills training program to be performed at home, which can be easily reproduced. It allows residents to improve manual coordination skills and is regarded as a feasible adjunct for ongoing training for surgical residents.
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