scholarly journals Technology of Quick-Frozen Flour Fish Culinary Products

2022 ◽  
Author(s):  
Valentina Pavlova ◽  
Irina Saenkova ◽  
Yulia Shokina ◽  
Grigoriy Shokin
Keyword(s):  
Mass Fraction ◽  
High Efficiency ◽  
A Priori ◽  
Cholesterol Content ◽  
Organoleptic Evaluation ◽  
Amine Nitrogen ◽  
Long Term Storage ◽  
Functional Product ◽  
Simulation Results ◽  
Priori Information

In this article, the results of the development of the functional fish culinary product “Thorny Skate and Cod Pie” are presented. A traditional recipe was used for making the yeast dough for the pie. The pie filling recipe was designed using Fuzzy Logic in the Matlab software package.Optimized parametersfor the selected sensory evaluation of the pie were calculated. On the basis of a priori information, key components of the filling (including the fraction of the fish components and skate meat) were chosen as the factors of interest. According to the simulation results, the optimal values werea 50/50 percentage for the first and the second factor respectively, and this providedthe maximum organoleptic assessment (five points on a five-point scale). The simulation results were compared with the results of the organoleptic evaluation of the pie made according to the optimized recipe, and their sufficient convergence was shown. The indicators of mass fraction of amine nitrogen and nitrogen of volatile bases was studied, as well as the microbiological safety indicators of flour fish culinary products, in accordance with the requirements of the Technical Regulations of the Eurasian Economic Union 040/2016 ”On the safety of fish products”. The results showed a high efficiency of the shock freezing of the semi-finished product, brought to semi-readiness, for long-term storage (120 days at a temperature no higher than minus 18 ∘C), without reducing the quality or safety of the pie. The product had a cholesterol content from 220 to 260 mg%, which allowed it to be classified as functional. The nutritional values of the product (mass fraction of protein, fat, carbohydrates, and amino acid composition) are presented. Keywords: thornyskate, functional product, pie with thornyskate and cod, shock freezing

A Neural Root Finder of Polynomials Based on Root Moments

2004 ◽  
Vol 16 (8) ◽  
pp. 1721-1762 ◽  
Author(s):  
De-Shuang Huang ◽  
Horace H.S. Ip ◽  
Zheru Chi
Keyword(s):  
Learning Algorithm ◽  
A Priori ◽  
Feedforward Neural Networks ◽  
A Priori Information ◽  
Backpropagation Algorithm ◽  
Constrained Learning ◽  
Roots Of Polynomials ◽  
Simulation Results ◽  
Priori Information ◽  
Coefficient Method

This letter proposes a novel neural root finder based on the root moment method (RMM) to find the arbitrary roots (including complex ones) of arbitrary polynomials. This neural root finder (NRF) was designed based on feedforward neural networks (FNN) and trained with a constrained learning algorithm (CLA). Specifically, we have incorporated the a priori information about the root moments of polynomials into the conventional backpropagation algorithm (BPA), to construct a new CLA. The resulting NRF is shown to be able to rapidly estimate the distributions of roots of polynomials. We study and compare the advantage of the RMM-based NRF over the previous root coefficient method—based NRF and the traditional Muller and Laguerre methods as well as the mathematica roots function, and the behaviors, the accuracies of the resulting root finders, and their training speeds of two specific structures corresponding to this FNN root finder: the log σand the σ FNN. We also analyze the effects of the three controlling parameters {δP0 θp η} with the CLA on the two NRFs theoretically and experimentally. Finally, we present computer simulation results to support our claims.

scholarly journals Images denoising in case impulse noise using spline approximation

2018 ◽  
Vol 226 ◽  
pp. 04045 ◽  
Author(s):  
Dmitriy A. Bezuglov ◽  
Viacheslav V. Voronin ◽  
Vladimir A. Krutov
Keyword(s):  
Impulse Noise ◽  
High Efficiency ◽  
Autonomous Robots ◽  
A Priori ◽  
Spline Approximation ◽  
Experimental Studies ◽  
Image Filtering ◽  
Spline Functions ◽  
Priori Information

Analytical equations of a new spline approximation method for filtering impulse noise in images are obtained. The proposed method differs from the known ones: when filtering images, one-dimensional sequential spline functions are used for direct and inverse transformations, and the processing is performed in rows and columns. In this work, experimental studies based on computer simulation using special test images on the background of impulse noise were conducted. Experimental studies have shown the operability and high efficiency of the developed method, which allow to improve the quality of image filtering by up to 10 dB. In this case, the properties of spline functions make it possible to abandon the use of various masks, that is, to abandon inefficient linear methods of image filtering. The method can be used to create digital image processing systems in the industry, to create autonomous robots, under observation conditions that complicate the registration process, and in the absence of a priori information about the form of background noise.

Research on Adaptive Unscented Kalman Filter for Integrated Navigation

2013 ◽  
Vol 753-755 ◽  
pp. 2582-2585
Author(s):  
Tian Lai Xu
Keyword(s):  
Kalman Filter ◽  
Unscented Kalman Filter ◽  
A Priori ◽  
Integrated Navigation ◽  
A Priori Information ◽  
Statistical Parameters ◽  
Adaptive Unscented Kalman Filter ◽  
Unknown System ◽  
Simulation Results ◽  
Priori Information

The accuracy of filtering deteriorates in condition that a priori information used in unscented Kalman filter (UKF) does not accord with the actual conditions. To improve the accuracy of filtering when the noise statistical properties are not known exactly in navigational data fusion, an adaptive UKF is proposed. In the filtering process, the statistical parameters of unknown system noises are adjusted online if filtering abnormality exists. Simulation results show that the proposed algorithm increases the accuracy compared with the standard UKF algorithm for integrated navigation.

scholarly journals Special aspects of using a new non-stationary random processes analysis approach in the conditions of a priori uncertainty of the useful signal function

2019 ◽  
Vol 30 ◽  
pp. 03002
Author(s):  
Vladimir Marchuk
Keyword(s):  
Additive Noise ◽  
High Efficiency ◽  
A Priori ◽  
Statistical Characteristics ◽  
Signal Function ◽  
Useful Signal ◽  
Priori Information ◽  
The Time Domain ◽  
A Priori Uncertainty ◽  
Stationary Random Processes

The paper considers the use of a new method of signal processing in the time domain under conditions of a limited amount of a priori information about the useful signal function and the statistical characteristics of additive noise. Research have shown its high efficiency in processing signals both local and global, using it to detect anomalous measurements, eliminating the systematic component in the case of a onesided law of the distribution of additive noise and a number of others.

Detection of Landmarks by Mobile Autonomous Robots Based on Estimating the Color Parameters of the Surrounding Area

2021 ◽  
pp. 224-257
Author(s):  
Oleksandr Poliarus ◽  
Yevhen Poliakov
Keyword(s):  
High Efficiency ◽  
Autonomous Robots ◽  
A Priori ◽  
Optimal Estimation ◽  
Night Vision ◽  
Landmark Detection ◽  
Generalized Variance ◽  
Video Cameras ◽  
Color Parameters ◽  
Priori Information

Remote detection of landmarks for navigation of mobile autonomous robots in the absence of GPS is carried out by low-power radars, ultrasonic and laser rangefinders, night vision devices, and also by video cameras. The aim of the chapter is to develop the method for landmarks detection using the color parameters of images. For this purpose, the optimal system of stochastic differential equations was synthesized according to the criterion of the generalized variance minimum, which allows to estimate the color intensity (red, green, blue) using a priori information and current measurements. The analysis of classical and nonparametric methods of landmark detection, as well as the method of optimal estimation of color parameters jumps is carried out. It is shown that high efficiency of landmark detection is achieved by nonparametric estimating the first Hilbert-Huang modes of decomposition of the color parameters distribution.

Algorithm for evaluation the navigation complex of a carrier-based aircraft

2020 ◽  
pp. 176-180
Keyword(s):  
High Efficiency ◽  
A Priori ◽  
Statistical Characteristics ◽  
Navigation Systems ◽  
Aircraft Carrier ◽  
Input Noise ◽  
Aircraft Landing ◽  
Kalman Adaptive Filter ◽  
Satellite Navigation Systems ◽  
Priori Information

The features of an aircraft landing approach on a moving aircraft carrier are studied. The main measuring systems used in landing approach for a carrier-based aircraft are inertial and satellite navigation systems. Joint signals processing in the navigation system is carried out by using an adaptive Kalman filter that can operate in the absence of a priori information about the statistical characteristics of the input noise. Kalman adaptive filter is based on using the properties of the updated sequence. The simulation results according to the semi-natural experiment showed its high efficiency.

Smooth Collision Avoidance Trajectories: A Dynamic Collision Avoidance Algoritm for Mobile Robots

1999 ◽  
Author(s):  
Jeffrey L. Newcomer
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Collision Avoidance ◽  
A Priori ◽  
A Priori Information ◽  
Action Simulation ◽  
Generation Algorithm ◽  
On Line ◽  
Simulation Results ◽  
Priori Information

Abstract This paper presents an algorithm for generating Smooth Collision Avoidance Trajectories (SCAT). SCAT generation is a method that allows a mobile robot that is moving along a pre-planned path to alter a section of its path, so that it may smoothly exit the original path, avoid a predicted collision, and return to the original path smoothly and on schedule. The SCAT generation algorithm is an improvement over off-line methods, as it requires minimal a priori information, and is more robust than pre-planned methods by its very nature. The SCAT algorithm is also an improvement over on-line schemes that only alter velocity along a pre-planned path, as it is able to avoid collisions in cases that those methods cannot. Details of the SCAT generation algorithm are developed herein, followed by examples of the algorithm in action. Simulation results show that the SCAT algorithm is very dependable, given that it can be provided with reasonably accurate in-formation about the location of dynamic obstacles in its vicinity.

Innovative Approach to Information Search by Example of a Patent Analysis of an Important Substitution Plan

2020 ◽  
pp. 143-157
Author(s):  
Maria A. Milkova
Keyword(s):  
Information Search ◽  
Topic Modeling ◽  
Cognitive Biases ◽  
A Priori ◽  
Import Substitution ◽  
Innovative Approach ◽  
Iterative Search ◽  
Comprehensive Picture ◽  
Priori Information ◽  
Selection Of

Nowadays the process of information accumulation is so rapid that the concept of the usual iterative search requires revision. Being in the world of oversaturated information in order to comprehensively cover and analyze the problem under study, it is necessary to make high demands on the search methods. An innovative approach to search should flexibly take into account the large amount of already accumulated knowledge and a priori requirements for results. The results, in turn, should immediately provide a roadmap of the direction being studied with the possibility of as much detail as possible. The approach to search based on topic modeling, the so-called topic search, allows you to take into account all these requirements and thereby streamline the nature of working with information, increase the efficiency of knowledge production, avoid cognitive biases in the perception of information, which is important both on micro and macro level. In order to demonstrate an example of applying topic search, the article considers the task of analyzing an import substitution program based on patent data. The program includes plans for 22 industries and contains more than 1,500 products and technologies for the proposed import substitution. The use of patent search based on topic modeling allows to search immediately by the blocks of a priori information – terms of industrial plans for import substitution and at the output get a selection of relevant documents for each of the industries. This approach allows not only to provide a comprehensive picture of the effectiveness of the program as a whole, but also to visually obtain more detailed information about which groups of products and technologies have been patented.

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