Deeper Learning Methods and Modalities in Higher Education: A 20-year Review

Deep Learning or Deeper Learning (DL) theory has gained traction as a helpful framework for designing higher education curricula in face-to-face (F2F), hybrid, and online settings. Although many research studies have been published testing DL methods in higher education, it is difficult to apply the results without an overview. This review applies a scientifically-informed search approach to select a sample of 127 peer-reviewed articles (representing 176 experimental groups) published from 1999 through 2019 on the topic of DL in higher education, classifies and extracts data from them, and presents a descriptive analysis of the findings

Finite element analysis of protective bicycle helmet & dummy head under dynamic loading

Cycling is a good activities particularly for recreation, exercise, and transportation. However, cycling related to the head injury is a significant contributor to hospitalization and death. Previous literatures indicates that the available helmets have less effective in preventing head injuries among cyclists. Moreover, most of the available helmets have been tested for only a few loading conditions. Therefore, the purpose of this study is to use finite element models to evaluate the protective effect of a helmet against various impact velocities. The head and helmet model has been developed using computational software. This study focus on the explicit dynamic analysis which performed in ANSY-WORKBENCH with loading condition in term of various impact velocity impacted on front and side of the head model. The results indicates the differences between the frontal and side simulations. They have been compared to identify the protective effect of the helmet and head

Magnetorheological landing gear: 2. Validation using experimental data

Aircraft landing gears are subjected to a wide range of excitation conditions with conflicting damping requirements. A novel solution to this problem is to implement semi-active damping using magnetorheological (MR) fluids. In part 1 of this contribution, a methodology was developed that enables the geometry of a flow mode MR valve to be optimized within the constraints of an existing passive landing gear. The device was designed to be optimal in terms of its impact performance, which was demonstrated using numerical simulations of the complete landing gear system. To perform the simulations, assumptions were made regarding some of the parameters used in the MR shock strut model. In particular, the MR fluid's yield stress, viscosity, and bulk modulus properties were not known accurately. Therefore, the present contribution aims to validate these parameters experimentally, via the manufacture and testing of an MR shock strut. The gas exponent, which is used to model the shock strut's nonlinear stiffness, is also investigated. In general, it is shown that MR fluid property data at high shear rates are required in order to accurately predict performance prior to device manufacture. Furthermore, the study illustrates how fluid compressibility can have a significant influence on the device time constant, and hence on potential control strategies

Cytomorphological Studies on Stem of Luffa echinata Roxb

Luffa echinata Roxb., commonly known as Bindal in Hindi is used for its hypoglycemic activity in the indigenous system of medicine. No pharmacognostical study on stem is reported in the literature till date; therefore, it was decided to study macroscopical and cytomorphological characters in detail to bring out salient diagnostic features. The stem pieces available in the market are 1.5–17 cm long and 5–8 mm in diameter, showing yellowish-brown to brownish-black surface with longitudinal furrows, fracture is fibrous, and taste is bitter. Mature stem shows single-layered epidermis, seven layers of collenchyma below five ridges but one to two layers of parenchyma in rest of the region beneath the epidermis, continuous wide wavy layer of pericycle composed of three to eight layers of fiber. There are five conjoint bi-collateral open vascular bundles one below each ridge and additional four medullary vascular bundles in the pith each facing furrows