Wear life characterization of the grinding wheel for electrolytic in-process dressing (ELID) grinding of ball bearing raceways: a new perspective based on a moving normal distribution curve of the grit state variation

2018 ◽  
Vol 96 (5-8) ◽  
pp. 1919-1928 ◽  
Author(s):  
M. L. Wu ◽  
C. Z. Ren ◽  
K. F. Zhang
Keyword(s):  
Normal Distribution ◽  
Distribution Curve ◽  
Ball Bearing ◽  
Grinding Wheel ◽  
Elid Grinding ◽  
Normal Distribution Curve ◽  
Wear Life ◽  
State Variation ◽  
New Perspective

scholarly journals PEMODELAN DISTRIBUSI TINGKAT IMBAL HASIL INDEKS HARGA DI TUJUH BURSA ASIA

2017 ◽  
Vol 14 (1) ◽  
pp. 1
Author(s):  
Brady Rikumahu
Keyword(s):  
Normal Distribution ◽  
Distribution Curve ◽  
Financial Time Series ◽  
Laplace Distribution ◽  
Standard Theory ◽  
Financial Time ◽  
Normal Distribution Curve ◽  
Specific Distribution ◽  
Return Distributions ◽  
Using Data

This paper examines the return distributions of 7 markets in the Asian region, namely Hongkong, Indonesia, Malaysia, Korea, Japan, Shanghai, and Singapore, to find out whether the return distributions in those markets follow a specific distribution. Using data from January 2000 to September 2009, the return distributions of each market were constructed and was first fitted to the normal distribution to find out whether or not each market behaves according to the standard theory of finance and investment – which stated that the financial time series follow a random walk – and thus would fit the normal distribution. The result of fitting the return distributions of the 7 markets to normal distribution shows that none of the return distributions follows the normal distribution as evident from the leptokurtic phenomena marked by the excess kurtosis compared to the normal distribution curve and also from the fatter than normal distribution tails and the existence of returns that lie outside the area predictedby the normal distribution.The return distributions were then fitted to a series of theoretical probability distribution. Each of the distribution was fitted to the theoretical. The results are: the Hongkong and Shanghai markets follow the Laplace distribution while the other five markets: Indonesia, Malaysia, Korea, Japan, and Singapore follow the Johnson SU distribution.

scholarly journals POST EXAM ANALYSIS SELECTION OF HIGH AND LOW EXAM RESULT GROUPS BY NORMAL DISTRIBUTION CURVE

2021 ◽  
Vol 13 (1) ◽  
pp. 39-46
Author(s):  
Faiz Marikar
Keyword(s):  
Normal Distribution ◽  
Standard Error ◽  
Distribution Curve ◽  
Standard Normal Distribution ◽  
Constructive Feedback ◽  
Normal Distribution Curve ◽  
Significant Difference ◽  
Difficulty Index ◽  
Standard Error Of Measurement ◽  
Error Of Measurement

The key factor of an assessment is to minimize the errors by having a good reliability and validity of the assessment yardstick. To achieve high score in the test examinee must be aware about assessment cycle and use it in appropriate way in post exam analysis. Outcome of the results can be utilized as a constructive feedback in any given program. This cross-sectional study was conducted at department of Biochemistry, University of Rajarata. Multiple choice questions, structured essay type questions, objective structured practical examination, and continuous assessment was used in this study. Total number of students are 180 and was assessed for difficulty index, discrimination index, reliability, and standard error of measurement. In this study sample for analysis was used basically the examiner divides students into two groups (‘high’ and ‘low’) according to the score sheet of each student. Most of them are doing in a wrong way basically they divide high and low clusters as 25% each and considered upper quartile and lower quartile. In this study we compared it with the standard normal distribution curve where high and low groups are considered as 16% where is the standard. There is no significant difference among both clusters, and we recommend using the standard 16% as the high and low groups in post examination analysis. Keywords: difficulty index, post examination analysis, reliability of the examination, standard error of measurement

scholarly journals AUTOMATIC DETECTION AND RECOGNITION OF CRATERS BASED ON THE SPECTRAL FEATURES OF LUNAR ROCKS AND MINERALS

2017 ◽  
Vol XLII-3/W1 ◽  
pp. 199-204
Author(s):  
L. Ye ◽  
X. Xu ◽  
D. Luan ◽  
W. Jiang ◽  
Z. Kang
Keyword(s):  
Normal Distribution ◽  
Distribution Curve ◽  
Lunar Regolith ◽  
Spectral Characteristics ◽  
Impact Craters ◽  
Simple Type ◽  
Curve Type ◽  
Normal Distribution Curve ◽  
Profile Fitting ◽  
The Impact

Crater-detection approaches can be divided into four categories: manual recognition, shape-profile fitting algorithms, machine-learning methods and geological information-based analysis using terrain and spectral data. The mainstream method is Shape-profile fitting algorithms. Many scholars throughout the world use the illumination gradient information to fit standard circles by least square method. Although this method has achieved good results, it is difficult to identify the craters with poor "visibility", complex structure and composition. Moreover, the accuracy of recognition is difficult to be improved due to the multiple solutions and noise interference. Aiming at the problem, we propose a method for the automatic extraction of impact craters based on spectral characteristics of the moon rocks and minerals: 1) Under the condition of sunlight, the impact craters are extracted from MI by condition matching and the positions as well as diameters of the craters are obtained. 2) Regolith is spilled while lunar is impacted and one of the elements of lunar regolith is iron. Therefore, incorrectly extracted impact craters can be removed by judging whether the crater contains "non iron" element. 3) Craters which are extracted correctly, are divided into two types: simple type and complex type according to their diameters. 4) Get the information of titanium and match the titanium distribution of the complex craters with normal distribution curve, then calculate the goodness of fit and set the threshold. The complex craters can be divided into two types: normal distribution curve type of titanium and non normal distribution curve type of titanium. We validated our proposed method with MI acquired by SELENE. Experimental results demonstrate that the proposed method has good performance in the test area.

Differential Response of Corn Hybrids and Inbreds to Metolachlor

Weed Science ◽  
1990 ◽  
Vol 38 (6) ◽  
pp. 563-566 ◽  
Author(s):  
Loston Rowe ◽  
Elmer Rossman ◽  
Donald Penner
Keyword(s):  
Great Lakes ◽  
Normal Distribution ◽  
Distribution Curve ◽  
Differential Response ◽  
The Other ◽  
Laboratory Studies ◽  
Corn Hybrids ◽  
Normal Distribution Curve ◽  
Site Of Action

Greenhouse studies were conducted to determine the response of 200 corn hybrids and 29 inbreds to metolachlor applied at 4.5 kg ai ha−1. Both hybrids and inbreds varied in their response to the herbicide. The distribution of injury revealed a normal distribution curve with most of the hybrids having a midlevel of tolerance. Some hybrids were very tolerant, while others were quite sensitive. Laboratory studies were conducted to evaluate absorption and metabolism of14C-metolachlor for a subset of tolerant and sensitive hybrids. There was no observed difference in the product of metolachlor metabolism in the tolerant and sensitive hybrids. The observed variability in metolachlor tolerance among hybrids appeared due to differences in the amount of metolachlor absorption and metabolism and differences at the site of metolachlor action. The tolerant ‘Great Lakes 584’ hybrid absorbed significantly less14C-metolachlor than did the sensitive ‘Pioneer 3744’, while the tolerant ‘Cargill 7567’ metabolized significantly faster more14C-metolachlor than the other hybrids. The internal concentrations of available14C-metolachlor were the same for the tolerant Cargill 7567 and the sensitive ‘Northrup King 9283’ after 8 h, indicating differences at the site of action of metolachlor for these two hybrids.

scholarly journals Comparative analysis of software for the study of statistical methods of control of product quality

2019 ◽  
Vol 20 (4) ◽  
pp. 293-301
Author(s):  
Roman V. Kozhanov ◽  
Evgeniya R. Kozhanova ◽  
Lyubov A. Sorokina
Keyword(s):  
Quality Control ◽  
Comparative Analysis ◽  
Product Quality ◽  
Normal Distribution ◽  
Statistical Methods ◽  
Product Life Cycle ◽  
Distribution Curve ◽  
Educational Institution ◽  
Product Quality Control ◽  
Normal Distribution Curve

The article discusses the comparative analysis of software (MS Excel, Mathcad and Matlab) for the study of statistical methods of product quality control necessary for the training of future specialists in the field of product quality. The choice is determined by the presence of this software in the educational institution. Statistical methods of product quality control are mandatory elements of modern quality management systems implemented at Russian enterprises, the competitiveness of which largely depends on the ability of the company's personnel to apply these methods in practice at all stages of the product life cycle. The analysis of product quality begins with the construction of a histogram to identify avoidable and irremediable defects and compare it with the normal distribution curve. The process of forming the shape of the normal distribution curve can be traced in the construction of control maps based on a scatter plot of the sample. The next step is the construction of dot diagrams, on the basis of which control maps are built (in our case - the control map of Shewhart). The final step in training is the construction of Pareto diagrams to identify the causes of defects with ABC analysis. The authors conducted a comparative analysis of software products MS Excel, Mathcad and Matlab for the implementation of basic statistical methods of product quality control. For training it is proposed to choose MS Excel because of the availability of the Data Analysis package, free analogues that are widely used in enterprises, the ability to store the original data and use them in other programs (data import).

scholarly journals Using conversions and treatments to understand students’ engagement with problems based on the normal distribution curve

Pythagoras ◽  
2012 ◽  
Vol 33 (1) ◽  
Author(s):  
Sarah Bansilal
Keyword(s):  
Normal Distribution ◽  
South African ◽  
Core Curriculum ◽  
Distribution Curve ◽  
School Level ◽  
Success Rates ◽  
High School Level ◽  
Normal Distribution Curve ◽  
Representation Systems ◽  
Students Success

Including probability and statistics in the core curriculum of mathematics in South African schools has made it necessary to train teachers to teach statistics at high school level. This study concentrates on practising mathematics teachers who were students in an in-service programme. The purpose of the study was to investigate students’ success rates on different questions of a multi-part task based on the normal distribution curve. The theory that I used to understand the students’ difficulties is Duval’s theory about movement within and between semiotic representation systems, called treatment transformations and conversion transformations respectively. The first two parts of the problem were unknown percentage problems and involved a treatment followed by a conversion. The third was an unknown value problem and required a conversion before the students could undertake a treatment transformation. The findings reveal that the success rates the students achieved in treatment transformations were higher than those they achieved in conversion transformations. The study also revealed that the direction of the conversions played a role in success rates. Recognising the different challenges the two types of transformations pose requires that teachers pay particular attention to actions that involve movement between different representation systems.

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