Canonical retinotopic shifts under an inverse force field explain predictive remapping

ABSTRACTSaccadic eye-movements allow us to bring visual objects of interest to high-acuity central vision. Although saccades cause large displacements of retinal images, our percept of the visual world remains stable. Predictive remapping — the ability of cells in retinotopic brain areas to transiently exhibit spatio-temporal retinotopic shifts beyond the spatial extent of their classical receptive fields — has been proposed as a primary mechanism that mediates this seamless visual percept. Despite the well documented effects of predictive remapping, no study to date has been able to provide a mechanistic account of the neural computations and architecture that actively mediate this ubiquitous phenomenon. Borne out by the spatio-temporal dynamics of peri-saccadic sensitivity to probe stimuli in human subjects, we propose a novel neurobiologically inspired phenomenological model in which the underlying peri-saccadic attentional and oculomotor signals manifest as three temporally overlapping forces that act on retinotopic brain areas. These three forces – a compressive one toward the center of gaze, a convergent one toward the saccade target and a translational one parallel to the saccade trajectory – act in an inverse force field and specify the spatio-temporal window of predictive remapping of population receptive fields.

Thai Sign Language Image Recognition for the Hearing-Impaired using Radial Inverse Force Histogram combined with Max-Min Boundary

Sign language image recognition is also a very interesting research topic. Because it can be applied to help normal people understand and use it as a communication tool for the hearing impaired. The objectives of this research were to: 1) study and analyze Thai Sign Language image recognition image data for hearing impaired, 2) develop Thai Sign Language image recognition system for hearing impaired by using new techniques, and 3) measure the efficiency of Thai sign language image recognition for hearing impaired using Radial Inverse Force Histogram and the Maximum and Minimum boundary values. The results of the research were as follows: 1) The study and analysis of image data of Thai Sign Language Image Recognition In this research, 62,694 sign language images were used, divided into 2 parts: 1) American Sign Language images, which consisted of 36 groups of images, namely 26 groups of letters (AZ) and 10 groups of numbers (0-9), and Part 2) Picture of Thai Sign Language consisting of 61 groups of images, including 44 groups of letters (ก-ฮ), 7 groups of vowels and 10 groups of numbers (0-9). Each group of pictures is rotated, enlarged, and Image promotion There were 6 sub-groups of images in various forms, divided into 2 parts: 70% of the images for training and 30% of the images for testing. 3) The results of measuring the efficiency of image recognition. It is divided into two parts: American Sign Language Image Recognition and Thai Sign Language Image Recognition. Compared with the Angular histogram method, the mean image accuracy was 0.86, the recall of the mean American sign language was 0.91, and the accuracy of the Thai Sign Language was 0.78. The recognition performance for Thai Sign Language images averaged 0.89, while the recognition efficiency was achieved when using radial inverse force histograms in combination with image similarity measurements with maximum-minimum boundary values. Accuracy for Mean American Sign Language was 0.99 and Remembrance for Mean American Sign was 1.00, while Accuracy for Mean Thai Sign Language was 0.89. Mean Remembrance for Thai Sign Language was 0.96. The results of the visual recognition performance measurement of both the American Sign Language and the Thai Sign Language images were very good compared to the Angular Histogram method.

Splitting the one-Dimensional Wave Equation, Part II: Additional Data are Given by an End Displacement Measurement

In this research, an unknown space-dependent force function in the wave equation is studied. This is a natural continuation of [1] and chapter 2 of [2] and [3], where the finite difference method (FDM)/boundary element method (BEM), with the separation of variables method, were considered. Additional data are given by the one end displacement measurement. Moreover, it is a continuation of [3], with exchanging the boundary condition, where are extra data, by the initial condition. This is an ill-posed inverse force problem for linear hyperbolic equation. Therefore, in order to stabilize the solution, a zeroth-order Tikhonov regularization method is provided. To assess the accuracy, the minimum error between exact and numerical solutions for the force is computed for various regularization parameters. Numerical results are presented and a good agreement was obtained for the exact and noisy data.

Uncorrelated blocked force determination on plate and shell structures

Inverse force determination is commonly used to determine input forces when they are not directly measurable. If transfer functions are measured with the source component attached, the inversely determined forces are, by definition, blocked forces. The primary advantage of using blocked forces is that the receiving structure may be modified and blocked forces, in theory, are unchanged. In this research, blocked forces are determined for a plastic engine cover connected to a base plate and a compressor attached to two different structures. At lower frequencies, blocked forces are determined using routine approaches where phase is included in both transfer function and operational response measurements. At high frequencies, it is demonstrated that predictions are improved if phase is ignored and blocked forces are assumed to be uncorrelated with respect to each other. It is also shown that the uncorrelated blocked forces are still valid even when changes are made to the receiving structure.

Mathematical modeling and parametric study of magnetic negative stiffness dampers

This article presents mathematical modeling and parametric study of a type of magnetic negative stiffness dampers. A magnetic negative stiffness damper uses the interaction forces and movement of magnets inside a conductive pipe to achieve inverse force–deformation response and create frequency dependent damping. One advantage of magnetic negative stiffness dampers over other conventional dampers is that they do not add stiffness to the system and hence will not increase the force in the structural members to which the magnetic negative stiffness damper is attached. Using nonlinear regression analysis, simple formulas to describe the magnetic force and electromagnetic damping of a specific type of magnetic negative stiffness dampers are derived. A parametric study is then performed to show that maximum negative stiffness is obtained when the height-to-diameter (aspect) ratio of the magnets is in the range of 0.3–0.4, and for design applications upper bound values for the clear spacing-to-radius ratio and aspect ratio of the magnets are determined to be 3 and 2, respectively. The highest value of damping coefficient is found to correspond to a magnet aspect ratio of 1.6, and for design purpose the pipe wall thickness should be set equal to the height of the magnet. Based on a pushover analysis of three frames modeled as single-degree-of-freedom systems, it is found that the frame with the magnetic negative stiffness damper experiences lower base shear at the expense of a slightly higher residual drift. The effect of base shear reduction is more pronounced when the target displacement is small.