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It has long been recognized that academic success is a result of both cognitive and non-cognitive dimensions acting together. Consequently, any intelligent learning platform designed to improve learning outcomes (LOs) must provide actionable inputs to the learner in these dimensions. However, operationalizing such inputs in a production setting that is scalable is not trivial. We develop an Embibe Score Quotient model (ESQ) to predict test scores based on observed academic, behavioral and test-taking features of a student. ESQ can be used to predict the future scoring potential of a student as well as offer personalized learning nudges, both critical to improving LOs. Multiple machine learning models are evaluated for the prediction task. In order to provide meaningful feedback to the learner, individualized Shapley feature attributions for each feature are computed. Prediction intervals are obtained by applying non-parametric quantile regression, in an attempt to quantify the uncertainty in the predictions. We apply the above modelling strategy on a dataset consisting of more than a hundred million learner interactions on the Embibe learning platform. We observe that the Median Absolute Error between the observed and predicted scores is 4.58% across several user segments, and the correlation between predicted and observed responses is 0.93. Game-like what-if scenarios are played out to see the changes in LOs, on counterfactual examples. We briefly discuss how a rational agent can then apply an optimal policy to affect the learning outcomes by treating the above model like an Oracle., Comment: 9 pages, 10 figures

The paper is concerned with identifying transfer functions of individual input channels in minimal realization form of a Multi-Input Single Output (MISO) from the input-output data corrupted by the error in all the variables. Such a framework is commonly referred to as error-in-variables (EIV). A common approach in the existing methods for identification of MISO systems is to estimate a non-minimal order transfer function under a subset of simplistic assumptions like homoskedastic error variances, known order, and delay. In this work, we deal with the challenging problem of identifying order, delay in each input of minimal realization form separately while estimating the transfer functions. We also estimate the heteroskedastic noise variances in each of the multiple inputs and output variables. An automated approach for the identification of MISO systems of minimal realization form in the EIV framework is proposed. Numerical case studies are presented to illustrate the efficacy of the proposed algorithm in identifying the transfer function along with the order, delay, and noise variances., Comment: Accepted in ACODS2020. Other related works can be found on https://d-maurya.github.io/web/

We introduce a multi-coiled acoustic metasurface providing a quasi-perfect absorption (reaching 99.99% in experiments) at extremely low-frequency of 50 Hz, and simultaneously featuring an ultrathin thickness down to {\lambda}/527 (1.3 cm). In contrast to the state of the art, this original conceived multi-coiled metasurface offers additional degrees of freedom capable to tune the acoustic impedance effectively without increasing the total thickness. We provide analytical derivation, numerical simulation and experimental demonstrations for this unique absorber concept, and discuss its physical mechanism which breaks the quarter-wavelength resonator theory. Furthermore, based on the same conceptual approach, we propose a broadband lowfrequency metasurface absorber by coupling unit cells exhibiting different properties.

We theoretically and experimentally propose two designs of broadband low-frequency acoustic metasurface absorbers (Sample I/Sample II) for the frequency ranges of 458Hz~968Hz and 231Hz~491Hz (larger than 1 octave), with absorption larger than 0.8, and having the ultra-thin thickness of 5.2cm and 10.4cm respectively ({\lambda}/15 for the lowest working frequency and {\lambda}/7.5 for the highest frequency). The designed supercell consists of 16 different unit cells corresponding to 16 eigen frequencies for resonant absorptions. The coupling of multiple resonances leads to broadband absorption effect in the full range of the targeted frequency spectrum. In particular, we propose to combine gradient-change channel and coiled structure to achieve simultaneous impedance matching and minimal occupied space, leading to the ultra-thin thickness of the metasurface absorbers. Our conceived ultra-thin low-frequency broadband absorbers may lead to pragmatic implementations and applications in noise control field.

We propose a novel numerical approach for the optimal design of wide-area heterogeneous electromagnetic metasurfaces beyond the conventionally used unit-cell approximation. The proposed method exploits the combination of Rigorous Coupled Wave Analysis (RCWA) and global optimization techniques (two evolutionary algorithms namely the Genetic Algorithm (GA) and a modified form of the Artificial Bee Colony (ABC with memetic search phase method) are considered). As a specific example, we consider the design of beam deflectors using all-dielectric nanoantennae for operation in the visible wavelength region; beam deflectors can serve as building blocks for other more complicated devices like metalenses. Compared to previous reports using local optimization approaches our approach improves device efficiency; transmission efficiency is especially improved for wide deflection angle beam deflectors. The ABC method with memetic search phase is also an improvement over the more commonly used GA as it reaches similar efficiency levels with upto 35% reduction in computation time. The method described here is of interest for the rapid design of a wide variety of electromagnetic metasurfaces irrespective of their operational wavelength.

High-transmissivity all-dielectric metasurfaces have recently attracted attention towards the realization of ultra-compact optical devices and systems. Silicon based metasurfaces, in particular, are highly promising considering the possibility of monolithic integration with VLSI circuits. Realization of silicon based metasurfaces operational in the visible wavelengths remains a challenge. A numerical study of silicon metasurfaces based on stepped truncated cone shaped nanoantenna elements is presented. Metasurfaces based on the stepped conical geometry can be designed for operation in the 700nm to 800nm wavelength window and achieve full cycle phase response (0 to pi with an improved transmittance in comparison with previously reported cylindrical geometry [1]. A systematic parameter study of the influence of various geometrical parameters on the achievable amplitude and phase coverage is reported.