Reliability modeling and optimization of MEMS elements in various devices using multi-scale concepts IEEE Conference Publication

A research instrument is created comprising all of the refined construct items, and is administered to a pilot test group of representative respondents from the target population. Data collected is tabulated and subjected to correlational analysis or exploratory factor analysis using a software program such as SAS or SPSS for assessment of convergent and discriminant validity. Items that do not meet the expected norms of factor loading (same-factor loadings higher than 0.60, and cross-factor loadings less than 0.30) should be dropped at this stage. The remaining scales are evaluated for reliability using a measure of internal consistency such as Cronbach alpha. Scale dimensionality may also be verified at this stage, depending on whether the targeted constructs were conceptualized as being unidimensional or multi-dimensional. Next, evaluate the predictive ability of each construct within a theoretically specified nomological network of construct using regression analysis or structural equation modeling.

After you delete an item and re-run the reliability analysis, look to see if any other items have alpha-if-item-deleted scores that are higher than the new overall alpha. Peng Y.B., Zhou T., Li J. Surrogate modeling immersed probability density evolution method for structural reliability analysis in high dimensions. With the development in global economic and transportation engineering, the traffic loads on brides have been growing steadily, which become potential safety hazards for existing bridges. In particular, long-span suspension bridges support heavy traffic volumes and simultaneous truck loads on the bridge deck, and thus the safety and serviceability of the bridge deserves investigation. In this book, a multiscale reliability method is presented for the safety assessment of long-span bridges.

Multi-scale reliability-based design optimisation framework for fibre-reinforced composite laminates

Li L.X., Chen G.H., Fang M.X., Yang D.X. Reliability analysis of structures with multimodal distributions based on direct probability integral method. For the situation that the limit state surface divides the whole uncertainty domain into two parts, two cases can be, respectively, researched as shown in Figure 6. The first case is that the whole intersection is located in the safe domain as shown in Figure 6a, while the second is that the intersection is divided by the limit state surface as shown in Figure 6b.

Before conducting reliability analysis, an approximated single-ellipsoid model is established to describe the overlapping region between the intersected components of the multi-CEM. The structural reliability indexes are computed by combining the multi-CEM with FOAM/SOAM. Finally, similar to the conventional ellipsoidal model, a ratio of the multidimensional volume between the safe domain and the whole uncertainty domain is introduced https://wizardsdev.com/ to measure the reliability of structures. In Section 3, the non-probabilistic reliability analysis of structures based on the multi-CEM is detailed. Two numerical examples are given in Section 4, and an engineering problem is analyzed in Section 5. Uncertainties are normally unavoidable in engineering practice, which should be taken into account in the structural design and optimization so as to reduce the relevant risks.

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The relationship between reliability and sample size requirements is less direct, but metrics with higher reliability also reduce sample size requirements. Guo X., Bai W., Zhang W.S. Confidence extremal structural response analysis of truss structures under static load uncertainty via sdp relaxation. Jiang C., Han X., Liu G.R. Optimization of multi-scale analysis structures with uncertain constraints based on convex model and satisfaction degree of interval. Wang C., Matthies H.G. A modified parallelepiped model for non-probabilistic uncertainty quantification and propagation analysis. Zhang D.Q., Han X., Jiang C., Liu J., Li Q. Time-dependent reliability analysis through response surface method.

One of the primary sources is the observer’s (or researcher’s) subjectivity. If employee morale in a firm is measured by watching whether the employees smile at each other, whether they make jokes, and so forth, then different observers may infer different measures of morale if they are watching the employees on a very busy day or a light day . Two observers may also infer different levels of morale on the same day, depending on what they view as a joke and what is not. Sometimes, reliability may be improved by using quantitative measures, for instance, by counting the number of grievances filed over one month as a measure of morale. Of course, grievances may or may not be a valid measure of morale, but it is less subject to human subjectivity, and therefore more reliable.

Validity and Reliability of the Research Instrument; How to Test the Validation of a Questionnaire/Survey in Research Works

The other key elements of scale evaluation are validity and generalizability. In this article, I will discuss the process of measuring the reliability of scale items using SPSS and the m-Banking dataset. Systematic error is an error that is introduced by factors that systematically affect all observations of a construct across an entire sample in a systematic manner. Unlike random error, which may be positive negative, or zero, across observation in a sample, systematic errors tends to be consistently positive or negative across the entire sample. Hence, systematic error is sometimes considered to be “bias” in measurement and should be corrected.

For this reason, it is usually necessary to make some subjective assumptions about the distribution characteristics of parameters in the uncertainty analysis based on the probability method. Nevertheless, some studies have shown that the small deviation of parameter probability distribution can lead to large error of uncertainty analysis results . To this end, to investigate efficient structural reliability analysis methods using non-probabilistic models is of great significance. An efficient FEA-based multi-scale reliability framework used in this study is extended and combined with a proposed sequential optimisation strategy to produce an efficient, flexible and accurate RBDO framework for fibre-reinforced composite laminate components.

Reliability Analysis: Step-by-Step Guide

Inter-rater reliability is assessed to examine the extent to which judges agreed with their classifications. Ambiguous items that were consistently missed by many judges may be reexamined, reworded, or dropped. The best items (say 10-15) for each construct are selected for further analysis.

• In contrast, by shifting the central tendency measure, systematic error reduces the validity of measurement.
• By increasing variability in observations, random error reduces the reliability of measurement.
• Convergent validity can be established by comparing the observed values of one indicator of one construct with that of other indicators of the same construct and demonstrating similarity between values of these indicators.
• While when the limit state function is strongly nonlinear, the SOAM is suggested, so as to improve the calculation accuracy.
• The UX-Lite has remarkably low variability given its two items that, with one item each, measure the constructs of perceived ease and perceived usefulness .

In split-half reliability, the items on the scale are divided into two halves and the resulting half scores are correlated. In alternative-forms reliability, two equivalent forms of the scale are constructed and the same respondents are measured at two different times, with a different form being used each time. The goal of psychometric analysis is to estimate and minimize if possible the error variance var, so that the observed score X is a good measure of the true score T.

SPSS eTutor: Constructing Scales and Checking Their Reliability

For example, a typical five-point item had a standard deviation of 1 (25% of max range). The 25th percentile (a smaller-than-average standard deviation) was about 21% of the range, and the 75th percentile (a larger-than-average standard deviation) was 28% of the range. These percentages tended to be just a bit lower for items with more points. A journal paper, titled “Multi-scale seismic reliability assessment of networks by centrality-based selective recursive decomposition algorithm” was recently published inEarthquake Engineering and Structural Dynamics. The paper was co-authored by Mr. Dongkyu Lee (Ph.D. student, SSRG) andProf.