A Moment Inequality for Overall Decreasing Life Class of Life Distributions w...inventionjournals
:A moment inequality is derived for the system whose life distribution is in an overall decreasing life (ODL) class of life distributions. A new nonparametric test statistic for testing exponentiality against ODL is investigated based on this inequality. The asymptotic normality of the proposed statistic is presented. Pitman's asymptotic efficiency, power and critical values of this test are calculated to assess the performance of the test. Real examples are given to elucidate the use of the proposed test statistic in the reliability analysis. Wealso proposed a test for testing exponentiality versus ODL for right censored data and the power estimates of this test are also simulated for censored data for some commonly used distributions in reliability. Finally, real data are used as an example for practical problems.
Estos acetatos sirven de contexto para analizar cómo La Piola, una manera de entender las TIC en educación, permite repensar las estrategias y métodos de educar ingenieros
These slides - based on the webinar featuring Ingo Mierswa, CTO at RapidMiner, John Myers, managing research director at leading IT analyst firm Enterprise Management Associates (EMA), and Lyndsay Wise, research director at EMA - provide an overview of how to close the loop between predictive insights and action using big data analytics.
A Moment Inequality for Overall Decreasing Life Class of Life Distributions w...inventionjournals
:A moment inequality is derived for the system whose life distribution is in an overall decreasing life (ODL) class of life distributions. A new nonparametric test statistic for testing exponentiality against ODL is investigated based on this inequality. The asymptotic normality of the proposed statistic is presented. Pitman's asymptotic efficiency, power and critical values of this test are calculated to assess the performance of the test. Real examples are given to elucidate the use of the proposed test statistic in the reliability analysis. Wealso proposed a test for testing exponentiality versus ODL for right censored data and the power estimates of this test are also simulated for censored data for some commonly used distributions in reliability. Finally, real data are used as an example for practical problems.
Estos acetatos sirven de contexto para analizar cómo La Piola, una manera de entender las TIC en educación, permite repensar las estrategias y métodos de educar ingenieros
These slides - based on the webinar featuring Ingo Mierswa, CTO at RapidMiner, John Myers, managing research director at leading IT analyst firm Enterprise Management Associates (EMA), and Lyndsay Wise, research director at EMA - provide an overview of how to close the loop between predictive insights and action using big data analytics.
Study of Dynamic Analysis for Immersed Tube Tunnelijceronline
The main aim of the project is to connect the two coats of the Dharamtar creek i.e. Rewas in Alibaug and Karanja in Uran by an immersed tunnel. The construction of proposed immersed tunnel will reduce the travel time from Mumbai to Alibaug from 3 hours to 1 hour. But this reduction in time includes the consideration of the sea-link from Sewri to Nhava Seva (Uran).Which was proposed by government and is already under construction. Thus construction of this immersed tunnel will ease the transportation of the city. In this study, a preliminary analysis of IZMIR immersed tube is carried out for validating purpose. The static analysis of the tunnel was made in finite element program. The vertical displacement of the tube unit under static loads was calculated. Afterwards, the seismic analysis was made to investigate stresses developed due to both racking and axial deformation of the tunnel during an earthquake. It was found that, maximum stress due to axial deformation is longer than compressive strength of the concrete. The high stresses in the tube occur, because of the tube stiffness.
FAST ALGORITHMS FOR UNSUPERVISED LEARNING IN LARGE DATA SETScsandit
The ability to mine and extract useful information automatically, from large datasets, is a
common concern for organizations (having large datasets), over the last few decades. Over the
internet, data is vastly increasing gradually and consequently the capacity to collect and store
very large data is significantly increasing.
Existing clustering algorithms are not always efficient and accurate in solving clustering
problems for large datasets.
However, the development of accurate and fast data classification algorithms for very large
scale datasets is still a challenge. In this paper, various algorithms and techniques especially,
approach using non-smooth optimization formulation of the clustering problem, are proposed
for solving the minimum sum-of-squares clustering problems in very large datasets. This
research also develops accurate and real time L2-DC algorithm based with the incremental
approach to solve the minimum
