Accuracy Booster: Performance Boosting using Feature Map Re-calibration

Convolution Neural Networks (CNN) have been extremely successful in solving intensive computer vision tasks. The convolutional filters used in CNNs have played a major role in this success, by extracting useful features from the inputs. Recently researchers have tried to boost the performance of CNNs by re-calibrating the feature maps produced by these filters, e.g., Squeeze-and-Excitation Networks (SENets). These approaches have achieved better performance by Exciting up the important channels or feature maps while diminishing the rest. However, in the process, architectural complexity has increased. We propose an architectural block that introduces much lower complexity than the existing methods of CNN performance boosting while performing significantly better than them. We carry out experiments on the CIFAR, ImageNet and MS-COCO datasets, and show that the proposed block can challenge the state-of-the-art results. Our method boosts the ResNet-50 architecture to perform comparably to the ResNet-152 architecture, which is a three times deeper network, on classification. We also show experimentally that our method is not limited to classification but also generalizes well to other tasks such as object detection.Comment: IEEE Winter Conference on Applications of Computer Vision (WACV), 202

Implications of Globalization for the Output-inflation Relationship: An Assessment

During the past two decades, a growing body of research has explored the implications of increased trade and financial openness for the relationship between output and inflation. This paper reviews proposed theoretical channels through which the degree of openness might ultimately affect the output-inflation trade-off and surveys the empirical studies that have sought to determine the net effect of greater openness on this trade-off. In addition, the paper utilizes a single cross-country data set to evaluate, taking into account recent developments in the literature, the likely sign and significance of this net effect. In particular, we find current data imply that there is a negative and significant relationship between openness and the sacrifice ratio, regardless of the transmission channel that is proposed

Ferromagnetism in nanoscale BiFeO3

A remarkably high saturation magnetization of ~0.4mu_B/Fe along with room temperature ferromagnetic hysteresis loop has been observed in nanoscale (4-40 nm) multiferroic BiFeO_3 which in bulk form exhibits weak magnetization (~0.02mu_B/Fe) and an antiferromagnetic order. The magnetic hysteresis loops, however, exhibit exchange bias as well as vertical asymmetry which could be because of spin pinning at the boundaries between ferromagnetic and antiferromagnetic domains. Interestingly, like in bulk BiFeO_3, both the calorimetric and dielectric permittivity data in nanoscale BiFeO_3 exhibit characteristic features at the magnetic transition point. These features establish formation of a true ferromagnetic-ferroelectric system with a coupling between the respective order parameters in nanoscale BiFeO_3.Comment: 13 pages including 4 figures; pdf only; submitted to Appl. Phys. Let

Understanding conformational dynamics from macromolecular crystal diffuse scattering

All macromolecular crystals contain some extent of disorder. The diffraction from such crystals contains diffuse scattering in addition to Bragg peaks and this scattering contains information about correlated displacements in the constituent molecules. While much work has been performed recently in decoding the dynamics of the crystalline ordering, the goal of understanding the internal dynamics of the molecules within a unit cell has been out-of-reach. In this article, we propose a general framework to extract the internal conformational modes of a macromolecule from diffuse scattering data. We combine insights on the distribution of diffuse scattering from short- and long-range disorder with a Bayesian global optimization algorithm to obtain the best fitting internal motion modes to the data. To illustrate the efficacy of the method, we apply it to a publicly available dataset from triclinic lysozyme. Our mostly parameter-free approach can enable the recovery of a much richer, dynamic structure from macromolecular crystallography

Regional Disparity of Covid-19 Infections: An Investigation using State Level Indian Data

Using the state level panel data for India, we establish that Covid infections are clustered in more urbanized, and prosperous states. Poverty lowers cases showing evidence of herd immunity of poor which stands in sharp contrast with the developed part of the world. Our dynamic panel regression results indicate that Covid infections are persistent across states and unlocking has aggravated the infections. We also find that richer and more urbanised states with better health infrastructure and governance perform more tests. The policy lesson from this exercise is that the authorities should monitor immunization and Covid protocols in densely populated urban areas

An effectual template bank for the detection of gravitational waves from inspiralling compact binaries with generic spins

We report the construction of a three-dimensional template bank for the search for gravitational waves from inspiralling binaries consisting of spinning compact objects. The parameter space consists of two dimensions describing the mass parameters and one "reduced-spin" parameter, which describes the secular (non-precessing) spin effects in the waveform. The template placement is based on an efficient stochastic algorithm and makes use of the semi-analytical computation of a metric in the parameter space. We demonstrate that for "low-mass" ($m_1 + m_2 \lesssim 12\,M_\odot$) binaries, this template bank achieves effective fitting factors $\sim0.92$--$0.99$ towards signals from generic spinning binaries in the advanced detector era over the entire parameter space of interest (including binary neutron stars, binary black holes, and black hole-neutron star binaries). This provides a powerful and viable method for searching for gravitational waves from generic spinning low-mass compact binaries. Under the assumption that spin magnitudes of black-holes [neutron-stars] are uniformly distributed between 0--0.98 [0 -- 0.4] and spin angles are isotropically distributed, the expected improvement in the average detection volume (at a fixed signal-to-noise-ratio threshold) of a search using this reduced-spin bank is $\sim20-52\%$, as compared to a search using a non-spinning bank.Comment: Minor changes, version appeared in Phys. Rev.

Optimal taxation policy maximum-entropy approach

The object of this paper is firstly to present entropic measure of income inequality and secondly to develop maximum entropy approaches for the optimal reduction of income inequality through taxation.

Multi-objective possibilistic model for portfolio selection with transaction cost

AbstractIn this paper, we introduce the possibilistic mean value and variance of continuous distribution, rather than probability distributions. We propose a multi-objective Portfolio based model and added another entropy objective function to generate a well diversified asset portfolio within optimal asset allocation. For quantifying any potential return and risk, portfolio liquidity is taken into account and a multi-objective non-linear programming model for portfolio rebalancing with transaction cost is proposed. The models are illustrated with numerical examples

Numerical simulation of heat transfer and fluid flow in coaxial laser cladding process for direct metal deposition

The coaxial laser cladding process is the heart of direct metal deposition (DMD). Rapid materials processing, such as DMD, is steadily becoming a tool for synthesis of materials, as well as rapid manufacturing. Mathematical models to develop the fundamental understanding of the physical phenomena associated with the coaxial laser cladding process are essential to further develop the science base. A three-dimensional transient model was developed for a coaxial powder injection laser cladding process. Physical phenomena including heat transfer, melting and solidification phase changes, mass addition, and fluid flow in the melt pool, were modeled in a self-consistent manner. Interactions between the laser beam and the coaxial powder flow, including the attenuation of beam intensity and temperature rise of powder particles before reaching the melt pool were modeled with a simple heat balance equation. The level-set method was implemented to track the free surface movement of the melt pool, in a continuous laser cladding process. The governing equations were discretized using the finite volume approach. Temperature and fluid velocity were solved for in a coupled manner. Simulation results such as the melt pool width and length, and the height of solidified cladding track were compared with experimental results and found to be reasonably matched.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87766/2/024903_1.pd