Electroretinogram Analysis In Patients With Non-Proliferative Diabetic Retinopathy

Purpose: Non-proliferative diabetic retinopathy (NPDR) is the earliest stage of diabetic eye disease. Microscopic changes occur in the blood vessels of the eye in NPDR. The changes typically do not produce symptoms and are not visible to the naked eye. This paper aims to investigate a method for distinguishing NPDR based on Electroretinogram (ERG).Method: The ERG responses were recorded in 20 eyes from 14 patients with NPDR and 20 eyes from 20 healthy subjects as the control group. The responses of three standard stimuli were collected for both groups. Time-domain parameters, including amplitudes and implicit time, and a nonlinear criterion, were used to differentiate the groups. Results: This study showed that implicit time and amplitude of b-wave in dark-adapted 10.0 ERG and amplitude and implicit time of light-adapted flicker 30 Hz could distinguish between controls and NPDR groups. Theta values obtained for dark-adapted 10.0 ERG (p=0.0019), light-adapted 3.0 ERG (p=0.0021), and light-adapted flicker 30 Hz (p=0.0023) had significant differences between the groups. Conclusion: The proposed features have made it possible to distinguish between healthy and NPDR eyes. Choosing an appropriate method can effectively evaluate inner retinal dysfunction, especially in diabetic retinopathy.

Neural network method of the decision Of the nonlinear problem of optimum distribution of the non-uniform resource

Given article is devoted features of the decision of a problem of integer nonlinear programming, by means of developed neural network method and algorithm of nonlinear optimization of means «decision Search» tabular processor Microsoft Excel. In offered neural network method the task in view decision is made by means of a recurrent neural network (RNN) matrix architecture with m neurons in each line and n neurons in each column. All neurons such network are connected with each other by communications, and the signal from an exit neuron can move on its input. Neural network method is characterized by that on inputs mentioned RNN the entrance vector of values of parameters of optimized nonlinear criterion function of a problem of distribution of a non-uniform resource moves, calculation of values of weight factors connected among themselves neurons is carried out and signal RNN is formed. This signal by means of nonlinear function will be transformed to the discrete target signal characterizing values quasi-optimal of the decision of the mentioned problem which size changes from 0 to 1. The estimation of efficiency of the decision of a considered problem was carried out at its various values of an indicator of efficiency on the basis of developed imitating model RNN. As indicators of efficiency of application offered neural network method were used – an average relative error and time of the decision of a problem. The value received by means of algorithm of nonlinear optimization of means was accepted to the exact decision «decision Search» tabular processor Microsoft Excel. The analysis of the received results of the experimental researches, offered neural network method, has allowed to make the conclusion that in comparison with an existing method of nonlinear optimization of tabular processor Microsoft Excel use offered neural network method allows essentially (in 9,4 times) to lower time of the decision of a problem dimension 10 × 8 (m × n) and thus to provide accuracy of its decision not less than 99,8 %.

Stability of Rock Slope with Geo-Material Described by Nonlinear Criterion

Paper had to be removed at authors request

Numerical Modeling for the Stress Displacement Distribution of Tunnel after Excavation

The tunnel excavation is often existed in civil engineering, in which the minimum roof thickness of tunnel is an important index in tunnel construction and design. Some work have been done on this field, by analytical analysis method and numerical simulation method based on linear criterion. In order to add some conclusions to the roof thickness prediction by nonlinear criterions, in the present paper, the calculation model for excavation of tunnel is built by numerical method, the nonlinear criterion is applied to describe the failure situation of the surrounding rock mass; then, according to the reduction method for thickness of roof, the thickness of the roof after excavation in tunnel is analyzed with the nonlinear criterion, to give some guidance for the real practice.