scholarly journals SELECTION OF THE PARAMETERS OF THE GENERALIZED DISPERSION ALGORITHM FOR MULTIVARIATE STATISTICAL CONTROL OF THE PROCESS SCATTERING

2021 ◽  
Vol 23 (1) ◽  
pp. 79-83
Author(s):  
A.V. Alekseeva ◽  
◽  
V.N. Klyachkin ◽  
Keyword(s):  
Performance Indicators ◽  
Optimization Problem ◽  
Unstable State ◽  
Statistical Control ◽  
Multivariate Statistical ◽  
Generalized Variance ◽  
Process Indicators ◽  
The Stability ◽  
Process Disturbances ◽  
Selection Of

To control the stability of the functioning of aviation equipment units based on the results of monitoring a group of indicators, methods of statistical processes control can be used. In the presence of significant correlations between performance indicators, multivariate methods are used. In this case, the control of the average level of the process is carried out on the basis of the Hotelling algorithm, the control of multivariate scattering is carried out using the generalized variance algorithm. If, according to the conditions of the process, it is necessary to ensure the fastest detection of a violation, then the optimization problem of finding such values of the sample size, sampling frequency and position of the control boundaries is solved that minimizes the average time of the unstable state of the process. The initial data are the number of process indicators monitored, the target value of the generalized variance (estimated from experimental data), the characteristic of the permissible increase in scattering, the intensity of process disturbances (parameter of the Poisson distribution); time to search for a violation after its detection and time to calculate the sample element.

scholarly journals OPTIMIZATION OF PARAMETERS OF GENERALIZED DISPERSION ALGORITHM AT STATISTICAL PROCESS CONTROL

2021 ◽  
Vol 3 (65) ◽  
pp. 41-47
Author(s):  
Vladimir N. Klyachkin ◽  
◽  
Anastasiya V. Alekseeva ◽  
Keyword(s):  
Production Process ◽  
Optimization Problem ◽  
Unstable State ◽  
Statistical Control ◽  
Optimal Parameters ◽  
Multivariate Statistical ◽  
Statistical Process ◽  
Generalized Variance ◽  
Process Indicators ◽  
Set Optimization Problem

When monitoring a real production process using statistical methods, the question of early detection of violations arises. In most cases, several indicators are monitored simultaneously in the production process, and a change in the values of some indicators leads to a change in others. If there is a dependence of indicators for their monitoring, multivariate statistical control tools are used, in particular generalized variance chart. By varying the parameters of the chart, its efficiency can be significantly increased, this allows minimizing the time the process is in an unstable state.Applying the approach of A. Duncan, which he developed for Shewhart charts, a formula for the expectation of the duration of an unstable state of a process was obtained and a Python program was developed to minimize it. To test the set optimization problem, the calculation of the data of two process indicators is given and the optimal parameters of the generalized variance chart are obtained, at which the duration of the process in an unstable state is minimal.

scholarly journals Optimization Methods and Algorithms for Calculating the Construction of Non-Rigid Pavement for Technological Quarries Roads

2019 ◽  
Vol 134 ◽  
pp. 01007
Author(s):  
Anna Tailakova ◽  
Alexander Pimonov
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Dynamic Programming ◽  
Computational Experiment ◽  
Optimization Problem ◽  
Optimization Methods ◽  
Rigid Pavement ◽  
The Stability ◽  
Optimal Construction ◽  
Selection Of

Previously developed by the authors of the optimization model for calculating the construction of non-rigid pavement of public roads is proposed to be used for the calculation of the construction of pavement technological career roads. The article describes the optimization methods and algorithms for calculating the construction of pavement. Possibilities of using methods of coordinate-wise descent, multi-start, dynamic programming for the selection of the optimal construction of pavement are presented. Application of genetic algorithms for the decision of an optimization problem of calculation of a construction of pavements on the basis of comparison of their efficiency with efficiency of search methods is proved. Described results of computational experiment of selection of genetic algorithm operators to reduce the volume of calculations and ensure the stability of the results.

CRITERIONS FOR THE EFFECTIVENESS OF SOCIALLY IMPORTANT INVESTMENT PROJECTS AND THEIR FORMULAS ADOPTED IN RUSSIAN PRACTICE

2020 ◽  
Vol 2 (8) ◽  
pp. 58-64
Author(s):  
A. F. AGEEVA ◽  
Keyword(s):  
Performance Indicators ◽  
Payback Period ◽  
Internal Rate Of Return ◽  
Investment Projects ◽  
Regulatory Documents ◽  
Project Analysis ◽  
Analytical Work ◽  
Methodological Approaches ◽  
Further Development ◽  
Selection Of

The article analyzes domestic guidelines for assessing the effectiveness of investment projects reflected in the regulatory documentation, both current and invalid. Considered are methodological approaches to calculating key performance indicators of investment projects - net discounted income, internal rate of return, discounted payback period and profitability index. The results of the analysis and recommendations for the further development of national regulatory documents for project analysis and methodological approaches to assessing the effectiveness of socially significant investment projects are presented. The results of the analytical work presented in the article are planned to be used to create a methodology for the selection of socially significant projects for the provision of state support.

scholarly journals Spatio-temporal selection of reference genes in the two congeneric species of Glycyrrhiza

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuping Li ◽  
Xiaoju Liang ◽  
Xuguo Zhou ◽  
Yu An ◽  
Ming Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Developmental Stage ◽  
Reference Genes ◽  
Developmental Stages ◽  
Individual Factors ◽  
Congeneric Species ◽  
Spatio Temporal ◽  
The Stability ◽  
Different Tissues ◽  
Selection Of

AbstractGlycyrrhiza, a genus of perennial medicinal herbs, has been traditionally used to treat human diseases, including respiratory disorders. Functional analysis of genes involved in the synthesis, accumulation, and degradation of bioactive compounds in these medicinal plants requires accurate measurement of their expression profiles. Reverse transcription quantitative real-time PCR (RT-qPCR) is a primary tool, which requires stably expressed reference genes to serve as the internal references to normalize the target gene expression. In this study, the stability of 14 candidate reference genes from the two congeneric species G. uralensis and G. inflata, including ACT, CAC, CYP, DNAJ, DREB, EF1, RAN, TIF1, TUB, UBC2, ABCC2, COPS3, CS, R3HDM2, were evaluated across different tissues and throughout various developmental stages. More importantly, we investigated the impact of interactions between tissue and developmental stage on the performance of candidate reference genes. Four algorithms, including geNorm, NormFinder, BestKeeper, and Delta Ct, were used to analyze the expression stability and RefFinder, a comprehensive software, provided the final recommendation. Based on previous research and our preliminary data, we hypothesized that internal references for spatio-temporal gene expression are different from the reference genes suited for individual factors. In G. uralensis, the top three most stable reference genes across different tissues were R3HDM2, CAC and TUB, while CAC, CYP and ABCC2 were most suited for different developmental stages. CAC is the only candidate recommended for both biotic factors, which is reflected in the stability ranking for the spatio (tissue)-temporal (developmental stage) interactions (CAC, R3HDM2 and DNAJ). Similarly, in G. inflata, COPS3, R3HDM2 and DREB were selected for tissues, while RAN, COPS3 and CS were recommended for developmental stages. For the tissue-developmental stage interactions, COPS3, DREB and ABCC2 were the most suited reference genes. In both species, only one of the top three candidates was shared between the individual factors and their interactions, specifically, CAC in G. uralensis and COPS3 in G. inflata, which supports our overarching hypothesis. In summary, spatio-temporal selection of reference genes not only lays the foundation for functional genomics research in Glycyrrhiza, but also facilitates these traditional medicinal herbs to reach/maximize their pharmaceutical potential.

scholarly journals Designing Strong Privacy Metrics Suites Using Evolutionary Optimization

2021 ◽  
Vol 24 (2) ◽  
pp. 1-35
Author(s):  
Isabel Wagner ◽  
Iryna Yevseyeva
Keyword(s):  
Optimization Problem ◽  
Evolutionary Optimization ◽  
Multiple Objectives ◽  
Shared Value ◽  
Vehicular Communications ◽  
Open Problems ◽  
Value Range ◽  
Genomic Privacy ◽  
Metaheuristic Optimization Algorithms ◽  
Selection Of

The ability to measure privacy accurately and consistently is key in the development of new privacy protections. However, recent studies have uncovered weaknesses in existing privacy metrics, as well as weaknesses caused by the use of only a single privacy metric. Metrics suites, or combinations of privacy metrics, are a promising mechanism to alleviate these weaknesses, if we can solve two open problems: which metrics should be combined and how. In this article, we tackle the first problem, i.e., the selection of metrics for strong metrics suites, by formulating it as a knapsack optimization problem with both single and multiple objectives. Because solving this problem exactly is difficult due to the large number of combinations and many qualities/objectives that need to be evaluated for each metrics suite, we apply 16 existing evolutionary and metaheuristic optimization algorithms. We solve the optimization problem for three privacy application domains: genomic privacy, graph privacy, and vehicular communications privacy. We find that the resulting metrics suites have better properties, i.e., higher monotonicity, diversity, evenness, and shared value range, than previously proposed metrics suites.

scholarly journals Latency-Optimal Computational Offloading Strategy for Sensitive Tasks in Smart Homes

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2347
Author(s):  
Yanyan Wang ◽  
Lin Wang ◽  
Ruijuan Zheng ◽  
Xuhui Zhao ◽  
Muhua Liu
Keyword(s):  
Queue Length ◽  
Optimization Problem ◽  
Time Slot ◽  
Smart Homes ◽  
Back Pressure ◽  
Smart Devices ◽  
Smart Device ◽  
Simulation Results ◽  
Computational Offloading ◽  
The Stability

In smart homes, the computational offloading technology of edge cloud computing (ECC) can effectively deal with the large amount of computation generated by smart devices. In this paper, we propose a computational offloading strategy for minimizing delay based on the back-pressure algorithm (BMDCO) to get the offloading decision and the number of tasks that can be offloaded. Specifically, we first construct a system with multiple local smart device task queues and multiple edge processor task queues. Then, we formulate an offloading strategy to minimize the queue length of tasks in each time slot by minimizing the Lyapunov drift optimization problem, so as to realize the stability of queues and improve the offloading performance. In addition, we give a theoretical analysis on the stability of the BMDCO algorithm by deducing the upper bound of all queues in this system. The simulation results show the stability of the proposed algorithm, and demonstrate that the BMDCO algorithm is superior to other alternatives. Compared with other algorithms, this algorithm can effectively reduce the computation delay.

Stabilization of networked switched affine systems with event-triggered strategy

2021 ◽  
pp. 014233122110213
Author(s):  
Dandan Li ◽  
Zhiqiang Zuo ◽  
Yijing Wang
Keyword(s):  
Affine Systems ◽  
Switching Law ◽  
Event Time ◽  
Sliding Motion ◽  
State Dependent ◽  
Event Triggering ◽  
Stability Issue ◽  
The Stability ◽  
Event Based ◽  
Selection Of

Using an event-based switching law, we address the stability issue for continuous-time switched affine systems in the network environment. The state-dependent switching law in terms of the region function is firstly developed. We combine the region function with the event-triggering mechanism to construct the switching law. This can provide more candidates for the selection of the next activated subsystem at each switching instant. As a result, it is possible for us to activate the appropriate subsystem to avoid the sliding motion. The Zeno behavior for the switched affine system can be naturally ruled out by guaranteeing a positive minimum inter-event time between two consecutive executions of the event-triggering threshold. Finally, two numerical examples are given to demonstrate the effectiveness of the proposed method.

scholarly journals Cats in the forest: predicting habitat adaptations from humerus morphometry in extant and fossil Felidae (Carnivora)

Paleobiology ◽  
10.1666/12001 ◽  
2013 ◽  
Vol 39 (3) ◽  
pp. 323-344 ◽  
Author(s):  
Carlo Meloro ◽  
Sarah Elton ◽  
Julien Louys ◽  
Laura C. Bishop ◽  
Peter Ditchfield
Keyword(s):  
Morphological Variability ◽  
Olduvai Gorge ◽  
Environmental Predictors ◽  
Linear Measurements ◽  
Multivariate Statistical ◽  
Linear Discriminant ◽  
Related Group ◽  
Discriminant Analyses ◽  
The Stability ◽  
The Relationship

Mammalian carnivores are rarely incorporated in paleoenvironmental reconstructions, largely because of their rarity within the fossil record. However, multivariate statistical modeling can be successfully used to quantify specific anatomical features as environmental predictors. Here we explore morphological variability of the humerus in a closely related group of predators (Felidae) to investigate the relationship between morphometric descriptors and habitat categories. We analyze linear measurements of the humerus in three different morphometric combinations (log-transformed, size-free, and ratio), and explore four distinct ways of categorizing habitat adaptations. Open, Mixed, and Closed categories are defined according to criteria based on traditional descriptions of species, distributions, and biome occupancy. Extensive exploratory work is presented using linear discriminant analyses and several fossils are included to provide paleoecological reconstructions.We found no significant differences in the predictive power of distinct morphometric descriptors or habitat criteria, although sample splitting into small and large cat guilds greatly improves the stability of the models. Significant insights emerge for three long-canine cats:Smilodon populator,Paramachairodus orientalis, andDinofelissp. from Olduvai Gorge (East Africa).S. populatorandP. orientalisare both predicted to have been closed-habitat adapted taxa. The false “sabertooth”Dinofelissp. from Olduvai Gorge is predicted to be adapted to mixed habitat. The application of felid humerus ecomorphology to the carnivoran record of Olduvai Gorge shows that the older stratigraphic levels (Bed I, 1.99–1.79 Ma) included a broader range of environments than Beds II or V, where there is an abundance of cats adapted to open environments.

General Method for Optimizing Composite Patch Repairs

2015 ◽  
Vol 1120-1121 ◽  
pp. 670-674
Author(s):  
Abdelmadjid Ait Yala ◽  
Abderrahmanne Akkouche
Keyword(s):  
Mechanical Properties ◽  
Stress Intensity Factor ◽  
Stress Intensity ◽  
Intensity Factor ◽  
Optimization Problem ◽  
Composite Patch ◽  
Matlab Program ◽  
Patch Repairs ◽  
Selection Of ◽  
General Method

The aim of this work is to define a general method for the optimization of composite patch repairing. Fracture mechanics theory shows that the stress intensity factor tends towards an asymptotic limit K∞.This limit is given by Rose’s formula and is a function of the thicknesses and mechanical properties of the cracked plate, the composite patch and the adhesive. The proposed approach consists in considering this limit as an objective function that needs to be minimized. In deed lowering this asymptote will reduce the values of the stress intensity factor hence optimize the repair. However to be effective this robust design must satisfy the stiffness ratio criteria. The resolution of this double objective optimization problem with Matlab program allowed us determine the appropriate geometric and mechanical properties that allow the optimum design; that is the selection of the adhesive, the patch and their respective thicknesses.

Sign in / Sign up

Export Citation Format

Share Document