A practical statistical technique to improve seal integrity and reliability of microelectronic packages

2002 ◽  
Author(s):  
T.R. Narasimhan ◽  
E.H. Trotter
Keyword(s):  
Statistical Technique ◽  
Seal Integrity ◽  
Microelectronic Packages

Organizational Change in medium and large companies of Sugamuxi Valley

1970 ◽  
Vol 15 (1) ◽  
Author(s):  
José Javier González Millán ◽  
Miryam Teresa Rodríguez Díaz ◽  
Oscar Ulises González Millán
Keyword(s):  
Organizational Change ◽  
Change Management ◽  
Organizational Structure ◽  
Descriptive Analysis ◽  
Statistical Technique ◽  
Management Processes ◽  
Low Culture

To characterize the change management processes, barriers, policies and factors that currently favor medium and large companies of the Sugamuxi Valley. The type and method of study was descriptive – explanatory. The statistical technique used was descriptive analysis using 561 surveys in medium (22) and large (18) Sugamuxi Valley companies. The biggest barriers were: adherence to rules (51.2%), multidisciplinary professions (51%), imposing the criteria of the oldest workers (47.4%) and organizational structure (43.9 %). The stimuli were: support for patents and innovations (93%), support for artistic activities (90%) and scholarships for study (90%), event registration training (79.7%) and transportation to events (82.4%). The research reveals a low culture of change, with a lack of incentives and business forms of adaptability and flexibility.Este artículo muestra la carácterización de los procesos de gestión del cambio, barreras, políticas y factores que actualmente favorecen a las medianas y grandes empresas del Valle de Sugamuxi. El tipo y método de estudio utilizado fue descriptivo - explicativo. La técnica estadística utilizada fue el análisis descriptivo mediante 561 encuestas en medianas (22) y grandes (18) empresas del Valle de Sugamuxi. Los mayores obstáculos fueron: la adhesión a las normas (51,2 %), profesiones multidisciplinares (51 %), imposición de los criterios de los trabajadores más antiguos (47,4 %) y la estructura organizacional (43,9 %). Los estímulos fueron: el apoyo a las patentes e innovaciones (93%), apoyo a las actividades artísticas (90%) y becas de estudio (90 %), registro en eventos de capacitación (79,7 %) y transporte a los eventos (82.4 %). La investigación revela una baja cultura de cambio, con falta de incentivos y formas de negocio de adaptabilidad y flexibilidad.Este artigo apresenta a caracterização dos processos de gestão de mudança, barreiras, políticas e fatores que atualmente favorecem às médias e grandes empresas do Valle de Sugamuxl. O tipo e método de estudo utilizado foi o descritivo – explicativo. A técnica estatística utilizada foi a análise descritiva mediante 561 enquetes em médias (22) e grandes (18) empresas no Valle de Sugamuxl. Os maiores obstáculos foram: a adesão às normas (51,2 %), profissões multidisciplinares (51 %), imposição dos critérios dos trabalhadores mais antigos (47,4 %), e a estrutura organizacional (43,9 %). Os estímulos foram: o apoio às patentes e inovações (93%), apoio às atividades artísticas (90%), bolsas de estudo (90%), registro em eventos de treinamento (79,7%), e transporte aos eventos (82,4%). A pesquisa revela uma cultura com poucos índices de mudança, com falta de incentivos e formas de negócios de adaptabilidade e flexibilidade.

Endocarp Structural Components of Insect Resistance in Almond

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 526d-526
Author(s):  
M. Freeman ◽  
C. Walters ◽  
M.A. Thorpe ◽  
T. Gradziel
Keyword(s):  
Insect Resistance ◽  
Insect Pests ◽  
Stone Fruit ◽  
Structural Components ◽  
Insect Infestation ◽  
Insect Feeding ◽  
Kernel Development ◽  
X Ray ◽  
Seal Integrity ◽  
Structural Barrier

Almond, as with other stone fruit, possesses a highly lignified endocarp or shell. The dominant hard-shelled trait (D-) is positively associated with greater resistant to insect infestation than nuts expressing the paper-shelled (dd) trait. Hard-shelled genotypes have undesirable effects, including a lower kernel meat-to-nut crack-out ratio, greater kernel damage during mechanical shelling, and a reduction in plant energy available to kernel development. Histogenic analysis shows that the almond endocarp, unlike peach, has a tri-partite structure. Insect feeding studies have subsequently demonstrated that the inner endocarp layer, which is similar in both hard and paper-shelled types, is the most important structural barrier to insect infestation. Shell-seal integrity and X-ray studies have confirmed that discontinuities at the inner endocarp suture seal are the primary, though not the sole site of entry for insect pests. Paper-shelled almond selections with highly lignified and well-sealed inner endocarps show resistance levels comparable to hard shelled types but with crack-out ratios 30% to 40% higher. Pseudo-paper-shelled types have also been selected, in which a highly lignified outer endocarp is formed, but is retained by the fruit hull at dehiscence. An understanding of endocarp morphology and development is thus important in breeding for insect resistance as well as the commercial utilization of both kernel and hull.

Optimization and Quality by Design Approach for Piroxicam Fast Dissolving Tablet Formulations Using Box-Behnken Design

2020 ◽  
Vol 15 (2) ◽  
pp. 152-165
Author(s):  
Harekrishna Roy ◽  
Sisir Nandi ◽  
Ungarala Pavani ◽  
Uppuluri Lakshmi ◽  
Tamma Saicharan Reddy ◽  
...  
Keyword(s):  
Quality By Design ◽  
Methyl Cellulose ◽  
Statistical Technique ◽  
Quadratic Model ◽  
Contour Plot ◽  
Compression Technique ◽  
Disintegration Time ◽  
Box Behnken Design ◽  
The Impact ◽  
The Relationship

Background: The present study deals with the formulation and optimization of piroxicam fast dissolving tablets and analyzes the impact of an independent variable while selecting the optimized formulation utilizing Quality by Design (QbD) and Box-Behnken Design (BBD). Methods: Seventeen formulations were prepared by direct compression technique by altering the proportion of cross carmellose sodium, spray dried lactose and hydro propyl methyl cellulose (HPMC K4M). The BBD statistical technique was used to optimize formulations and correlate the relationship among all the variables. Also, the powder mixture characteristics and tablet physiochemical properties such as hardness, friability, drug content, Disintegration Time (DT) and dissolution test were determined using 900 ml of 0.1N HCl (pH-1.2) at 37 ± 0.5°C. Results: Significant quadratic model and second order polynomial equations were established using BBD. To find out the relationship between variables and responses, 3D response surface and 2D contour plot was plotted. A perturbation graph was also plotted to identify the deviation of the variables from the mean point. An optimized formula was prepared based on the predicted response and the resulting responses were observed to be close with the predicted value. Conclusion: The optimized formulation with the desired parameter and formulation with variables and responses can be obtained by BBD and could be used in the large experiment with the involvement of a large number of variables and responses.

scholarly journals The future is coming: promising perspectives regarding the use of machine learning in renal transplantation

2019 ◽  
Vol 41 (2) ◽  
pp. 284-287
Author(s):  
Pedro Guilherme Coelho Hannun ◽  
Luis Gustavo Modelli de Andrade
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Graft Function ◽  
Statistical Technique ◽  
Daily Routine ◽  
Learning Approaches ◽  
Post Transplantation ◽  
Chronic Allograft Rejection ◽  
Institutional Experience ◽  
Learning Principles

Abstract Introduction: The prediction of post transplantation outcomes is clinically important and involves several problems. The current prediction models based on standard statistics are very complex, difficult to validate and do not provide accurate prediction. Machine learning, a statistical technique that allows the computer to make future predictions using previous experiences, is beginning to be used in order to solve these issues. In the field of kidney transplantation, computational forecasting use has been reported in prediction of chronic allograft rejection, delayed graft function, and graft survival. This paper describes machine learning principles and steps to make a prediction and performs a brief analysis of the most recent applications of its application in literature. Discussion: There is compelling evidence that machine learning approaches based on donor and recipient data are better in providing improved prognosis of graft outcomes than traditional analysis. The immediate expectations that emerge from this new prediction modelling technique are that it will generate better clinical decisions based on dynamic and local practice data and optimize organ allocation as well as post transplantation care management. Despite the promising results, there is no substantial number of studies yet to determine feasibility of its application in a clinical setting. Conclusion: The way we deal with storage data in electronic health records will radically change in the coming years and machine learning will be part of clinical daily routine, whether to predict clinical outcomes or suggest diagnosis based on institutional experience.

scholarly journals Effects of Increase in the Cost of Building Materials on the Delivery of Affordable Housing in South Africa

2021 ◽  
Vol 13 (4) ◽  
pp. 1772
Author(s):  
Bimpe Alabi ◽  
Julius Fapohunda
Keyword(s):  
South Africa ◽  
Affordable Housing ◽  
Building Materials ◽  
Statistical Technique ◽  
Project Managers ◽  
Maintenance Cost ◽  
Cost Increase ◽  
Sequential Mixed Methods ◽  
Adequate Provision ◽  
The Cost

Adequate provision of affordable human settlements is a huge challenge in South Africa since its independence. This paper investigates the effects of the cost increase of building materials on affordable housing delivery in South Africa. With potential solutions for cost minimisation of building materials, with the aim of achieving affordable housing delivery in South Africa are provided. This study uses a sequential mixed methods approach, wherein surveys were conducted among the construction professionals (project managers, site managers architects, site engineers, quantity surveyors, contractors, building materials suppliers, and government workers) in the construction industry within Cape Town, South Africa, who were considered as the research participants. The qualitative data obtained from the survey exercise were analysed using content analysis, while the quantitative data were analysed using a descriptive statistical technique on SPSS. The findings attained show fluctuation in construction cost and a rise in maintenance cost (caused by poor workmanship) as significant effects in the cost increase of building materials for affordable housing delivery. Adequate application of the recommendations given in this study will minimise the effects of high cost of building materials and enhance affordable housing delivery. Appropriate handling of the findings given in this study will reduce the effects of the high cost of building materials and augment timely delivery of affordable housing and stakeholders’ satisfaction.

scholarly journals Structural equation modeling to shed light on the controversial role of climate on the spread of SARS-CoV-2

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alessia Spada ◽  
Francesco Antonio Tucci ◽  
Aldo Ummarino ◽  
Paolo Pio Ciavarella ◽  
Nicholas Calà ◽  
...  
Keyword(s):  
Structural Equation Modeling ◽  
Population Density ◽  
Structural Equation ◽  
Climatic Factors ◽  
Demographic Data ◽  
Factor Loading ◽  
Statistical Technique ◽  
Global Scale ◽  
Equation Modeling ◽  
Relevant Role

AbstractClimate seems to influence the spread of SARS-CoV-2, but the findings of the studies performed so far are conflicting. To overcome these issues, we performed a global scale study considering 134,871 virologic-climatic-demographic data (209 countries, first 16 weeks of the pandemic). To analyze the relation among COVID-19, population density, and climate, a theoretical path diagram was hypothesized and tested using structural equation modeling (SEM), a powerful statistical technique for the evaluation of causal assumptions. The results of the analysis showed that both climate and population density significantly influence the spread of COVID-19 (p < 0.001 and p < 0.01, respectively). Overall, climate outweighs population density (path coefficients: climate vs. incidence = 0.18, climate vs. prevalence = 0.11, population density vs. incidence = 0.04, population density vs. prevalence = 0.05). Among the climatic factors, irradiation plays the most relevant role, with a factor-loading of − 0.77, followed by temperature (− 0.56), humidity (0.52), precipitation (0.44), and pressure (0.073); for all p < 0.001. In conclusion, this study demonstrates that climatic factors significantly influence the spread of SARS-CoV-2. However, demographic factors, together with other determinants, can affect the transmission, and their influence may overcome the protective effect of climate, where favourable.

Shrink-fit shear and seal integrity of tubular connections

2021 ◽  
pp. 104027
Author(s):  
Malcolm A. Goodman ◽  
Gang Tao ◽  
Cam Matthews
Keyword(s):  
Seal Integrity ◽  
Shrink Fit

scholarly journals Response transformations for random effect and variance component models

2020 ◽  
pp. 1471082X2096691
Author(s):  
Amani Almohaimeed ◽  
Jochen Einbeck
Keyword(s):  
Maximum Likelihood ◽  
Random Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Random Effect ◽  
Statistical Technique ◽  
Response Distribution ◽  
Level Data ◽  
Variance Component Models ◽  
Response Transformation

Random effect models have been popularly used as a mainstream statistical technique over several decades; and the same can be said for response transformation models such as the Box–Cox transformation. The latter aims at ensuring that the assumptions of normality and of homoscedasticity of the response distribution are fulfilled, which are essential conditions for inference based on a linear model or a linear mixed model. However, methodology for response transformation and simultaneous inclusion of random effects has been developed and implemented only scarcely, and is so far restricted to Gaussian random effects. We develop such methodology, thereby not requiring parametric assumptions on the distribution of the random effects. This is achieved by extending the ‘Nonparametric Maximum Likelihood’ towards a ‘Nonparametric profile maximum likelihood’ technique, allowing to deal with overdispersion as well as two-level data scenarios.

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