scholarly journals Modification of the Algorithm for Selecting a Variable Parameter of the Gaussian Interpolation Function

2020 ◽  
pp. 21-28
Author(s):  
Yuliia V. Sydorenko ◽  
◽  
Mykola V. Horodetskyi ◽  
Keyword(s):  
Variable Parameter ◽  
Interpolation Function ◽  
Lagrange Polynomial ◽  
Tabular Data ◽  
Mathematical Functions ◽  
Optimal Value ◽  
Gaussian Interpolation

The paper presents an algorithm for selecting the optimal value of the variable parameter α of the Gaussian interpolation function to obtain the smallest possible error when interpolating the tabular data. The results of the algorithm are checked on a sample of elementary mathematical functions. For comparison, the interpolation data of the Lagrange polynomial are given. The paper presents the results of Gaussian interpolation at different α, conclusions are made about the need to applying the algorithm for selecting of its optimal value.

Dynamic Damping and Stiffness Characteristics of the Rolling Tire

2001 ◽  
Vol 29 (4) ◽  
pp. 258-268 ◽  
Author(s):  
G. Jianmin ◽  
R. Gall ◽  
W. Zuomin
Keyword(s):  
Dynamic Behavior ◽  
Variable Parameter ◽  
Low Frequency ◽  
Vertical Load ◽  
Frequency Range ◽  
Inflation Pressure ◽  
Vehicle Simulation ◽  
Dynamic Damping ◽  
Speed Range ◽  
Stiffness Characteristics

Abstract A variable parameter model to study dynamic tire responses is presented. A modified device to measure terrain roughness is used to measure dynamic damping and stiffness characteristics of rolling tires. The device was used to examine the dynamic behavior of a tire in the speed range from 0 to 10 km/h. The inflation pressure during the tests was adjusted to 160, 240, and 320 kPa. The vertical load was 5.2 kN. The results indicate that the damping and stiffness decrease with velocity. Regression formulas for the non-linear experimental damping and stiffness are obtained. These results can be used as input parameters for vehicle simulation to evaluate the vehicle's driving and comfort performance in the medium-low frequency range (0–100 Hz). This way it can be important for tire design and the forecasting of the dynamic behavior of tires.

Risk assessment models with functionally different influences on natural and technical systems

2020 ◽  
Vol 89 ◽  
pp. 8-19
Author(s):  
V. A. Minaev ◽  
◽  
N. G. Topolsky ◽  
A. O. Faddeev ◽  
R. O. Stepanov ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Differential Equations ◽  
Research Area ◽  
Practical Implementation ◽  
Model Assessment ◽  
Mathematical Functions ◽  
Effective Response ◽  
Risk Assessment Models ◽  
Technical Systems ◽  
Material Values

Introduction. The complex combination of natural and technogenic factors that lead to dangerous threats to the health and life of the population, as well as to material values, creates a need to develop special mathematical models for risk assessment in the relevant territories. Herewith it is important to take into account the significant differences between these factors. The new areas of research are models that describe natural and technogenic risks using differential equations that reflect different types of functions. The article presents the development of this research area. Goals and objectives. The goal of the article is to create a model for risk assessment in natural and technical systems (PTS), based on taking into account the influences of different natural and technogenic factors on them. Objectives include justification, construction and practical implementation of the mathematical model of risk assessment in the form of differential equations system. Methods include interpretation of the considered influences on PTS in terms of risks and assessment of the dynamic interaction of natural and technogenic factors in the form of inhomogeneous differential equations. Results and discussion. Solutions for models of assessing complex natural and technogenic risks in relation to two cases that differ in NTS are found: functionally different external natural and technogenic influences on PTS, which are understood as their type, in which the effects of both natural and technogenic factors are described by different mathematical functions. Conclusions. The first model considers parabolic (reflecting threats whose intensity gradually decreases with distance from the epicenter) and linear types of influences (reflecting sudden threats). The second model considers parabolic and hyperbolic (reflecting threats, the intensity of which decreases sharply over time) types of influences. It is concluded that it is necessary to create a special computer album of complex influences on the PTS in order to prevent "replay" of various situations and develop the most effective response to emerging dangers from the EMERCOM units and other structures. Key words: model, assessment, natural and technogenic risks, functionally different influences, counteraction, EMERCOM units.

Optimization of K Value in KNN Algorithm for Spam and Ham Email Classification

2020 ◽  
Vol 4 (2) ◽  
pp. 377-383
Author(s):  
Eko Laksono ◽  
Achmad Basuki ◽  
Fitra Bachtiar
Keyword(s):  
Frequency Distribution ◽  
Confusion Matrix ◽  
High Accuracy ◽  
K Value ◽  
A Value ◽  
Optimal Value ◽  
Classification Evaluation ◽  
Email Spam ◽  
Email Classification

There are many cases of email abuse that have the potential to harm others. This email abuse is commonly known as spam, which contains advertisements, phishing scams, and even malware. This study purpose to know the classification of email spam with ham using the KNN method as an effort to reduce the amount of spam. KNN can classify spam or ham in an email by checking it using a different K value approach. The results of the classification evaluation using confusion matrix resulted in the KNN method with a value of K = 1 having the highest accuracy value of 91.4%. From the results of the study, it is known that the optimization of the K value in KNN using frequency distribution clustering can produce high accuracy of 100%, while k-means clustering produces an accuracy of 99%. So based on the results of the existing accuracy values, the frequency distribution clustering and k-means clustering can be used to optimize the K-optimal value of the KNN in the classification of existing spam emails.

Optimization of Cutting Parameters in Milling Process Using Genetic Algorithm and ANOVA (March 2020)

2020 ◽  
Vol 38 (10A) ◽  
pp. 1489-1503
Author(s):  
Marwa Q. Ibraheem
Keyword(s):  
Genetic Algorithm ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Optimal Value ◽  
Optimization Of Cutting Parameters

In this present work use a genetic algorithm for the selection of cutting conditions in milling operation such as cutting speed, feed and depth of cut to investigate the optimal value and the effects of it on the material removal rate and tool wear. The material selected for this work was Ti-6Al-4V Alloy using H13A carbide as a cutting tool. Two objective functions have been adopted gives minimum tool wear and maximum material removal rate that is simultaneously optimized. Finally, it does conclude from the results that the optimal value of cutting speed is (1992.601m/min), depth of cut is (1.55mm) and feed is (148.203mm/rev) for the present work.

FORMULATION AND SOLUTION OF OPTIMIZATION PROBLEM REDUNDANCY SYSTEM COMPRISING SITUATION CENTER

2019 ◽  
pp. 44-50
Author(s):  
A.V. Alekseev
Keyword(s):  
Analytical Model ◽  
Quality Indicators ◽  
Significant Influence ◽  
Optimization Problem ◽  
Sampling Theorem ◽  
Sampling Frequency ◽  
Generalized Sampling ◽  
Optimal Value ◽  
Situation Center ◽  
Situation Centers

The analysis of the concept, properties and features of heterogeneous redundancy in modern complex ergatic systems, including those included in the situation centers (SC). On the basis of the qualimetric paradigm, the generalized analytical model of quality and optimization of quality by private, group, summary and aggregated quality indicators is justified. Practical ways of realization of the model and methods of optimization of the objects which are a part of SC and them as a whole at the expense of reduction of structural, functional and other types of redundancy under the obligatory condition of non-reduction of the required value of quality are given. On the example of the generalized sampling theorem when choosing the optimal value of the sampling frequency of the real bandpass signal, the criticality and significant influence on the redundancy of data in their further processing in the SC is shown.

Neutrophil/lymphocyte Ratio after Flow Citometry Periferic Blood Cell Detection - Predictive Marker of Anastomotic Fistula in Colorectal Cancer Surgery

2020 ◽  
Vol 71 (6) ◽  
pp. 295-306
Author(s):  
Dumitru Radulescu ◽  
Vlad Dumitru Baleanu ◽  
Andrei Nicolaescu ◽  
Marius Lazar ◽  
Marius Bica ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Patients ◽  
Rectal Surgery ◽  
Predictive Marker ◽  
Fistula Formation ◽  
Cell Detection ◽  
Colon And Rectal Surgery ◽  
Optimal Value ◽  
Anastomotic Fistula ◽  
Colorectal Cancer Patients

Anastomotic fistula is a dreadful complication of colon and rectal surgery that can put life into danger, being common after colorectal surgery. The preoperative lymphocyte neutrophil ratio (NLR) is known as a prognostic marker for colorectal cancer patients. The existence of a predictive marker of anastomotic fistula in colorectal cancer patients is not fully undestood, so we proposed to investigate the utility of preoperative NLR as a predictor of anastomotic fistula formation. This study the Neutrophils and lymphocytes were detected from periferic blood using flow citometry. We retrospectively evaluated 161 patients with colorectal cancer, who were treated curatively, in which at least one anastomosis was performed, comparing NLR values between patients who had fistula and those with normal healing, then comparing the group with low NLR, with the group with increased NLR, after finding the optimal value of NLR using the ROC curve.The optimal value of the NLR after establishing the cutoff value was 3.07. Between the low NLR group (n=134) and the high NLR group (n=27), were observed statistically significant differences in fistula (p [0.001) and death (p=0.001). The odds ratio for failure in the group with increased NLR was 10.37, which means that patients with NLR]3.54 have a chance of developing anastomotic fistula greater than 10.37 comparable to patients with lower NLR. We suggest the preoperative use of NLR can be used as a predictive marker of anastomotic fistula than can increase the quality of preoperative preparation and therefore the establishment of the optimal surgical technique that can lead to anastomotic fistula risk decrease.

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