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The purpose of this paper is to examine extreme value charts and analyse means based on half logistic distribution.

Variable control charts with subgroup observations based on the extreme values at each subgroup are constructed without specially going to any subgroup statistic. The control chart constants depend on the probability model of the extreme order statistic of each subgroup and the size of the subgroup. Accordingly the proposed chart is normal as extreme value chart. As a by‐product the technique of analysis of means for a skewed population is exemplated through half logistic distribution and extreme value control charts. The results are illustrated by examples on live data.

H.L.D is found to be better test for the data of the three examples, ANOM gave a larger (complete) homogeneity of data than those of Ott.

Supposing arithmetic means of k subgroups of size “n” each drawn from a half logistic model. If these subgroup means are used to develop control charts to assess whether the population from which these subgroups are drawn is operating with admissible quality variations. Depending on the basic population model, we may use the control chart constants developed by the authors or the popular Shewart constants given in any SQC text book. Generally the authors say that the process is in control if all the subgroup means fall within the control limits. Otherwise it is said that the process lacks control.

Half logistic distribution is a better model, exhibiting significant linear relation between sample and population quantiles.

Many universities now offer courses online using learning management systems (LMS). Numerous studies have been conducted to assess the effectiveness of the LMS but few studies have examined how student online behavior within the course, or what they think about the online course, are related to their actual learning outcomes. The paper aims to discuss this issue.

In this study, student activity in an online business course was captured though learning analytics and assignments to determine if online activity and reflective learning impact final grade. A post-positivist ideology was employed. The dependent variable was the grade resulting from five assignments assessed using rubrics. Correlation, t-tests, multiple regression, surface response regression, General Linear Model (GLM)/F-tests, text analytics, analysis of means (ANOM), and cluster analysis were used to test the hypotheses.

Four statistically significant predictors of online student learning performance were identified: course logins, lesson reading, lesson quiz activity, and lesson quiz scores. This four factor model captured 78 percent of variance on course grade which is a strong effect and larger than comparative studies using learning analytics with online courses. Text analytics and ANOM conducted on student essays identified 17 reflective learning keywords that were grouped into five clusters to explain online student behavior.

First, from a pedagogy standpoint, encouraging students to complete more online lessons including quizzes, generally promotes learning, resulting in higher grades, which is a win:win for students and for the university. Second, from an IT perspective, the student pre and post testing resulted in statistically significant increase of IT-course knowledge, which puts students on a solid foundation to begin an online business course. Additionally, the link between students voicing IT problems but nonetheless scoring very well on the course certainly implies the development of IT self-efficacy, developed partly through the pre and post testing process. A clear link was established between course learning objectives and student learning performance by using a unique text analytics procedure.

The mixed-methods research design started with hypothesis testing using parametric and nonparametric techniques. Once a statistically significant predictive GLM was developed, qualitative data were collected from what the students thought as expressed in their last essay assignment. Text analytics was used to identify and statistically weight the 17 most frequent reflective learning keywords from student essays. A visual word cloud was presented. Parametric statistics were then used to partition the reflective learning keywords into grade boundaries. Nonparametric cluster analysis was used to group similar reflective keyword-grade associations together to form five clusters. The five clusters helped to explain student online behavior.

The purpose of this paper is to present the multi-objective optimization of the dynamic response of isotropic and laminated composite folded plates. The dynamic analysis has been carried out using the finite element method based on the first-order shear deformation theory.

Hamilton’s principle has been employed for the derivation of the governing equations. Natural frequencies are obtained using the eigenvalue extraction method. The optimal combination of the crank angle, lamination scheme and boundary conditions on the natural frequencies of folded plates for their safe and optimal dynamic design has been obtained. The analysis has been carried out using finite element approach based on FSDT to obtain the dynamic equation of single- and double-fold laminated plates. In total, 15 experiments as per Taguchi’s standard L₁₅ orthogonal array have been performed. Further, standard deviation (SD) based TOPSIS method is used to perform multi-response optimization of folded plates in order to rank the combination of the input parameters.

SD integrated with TOPSIS reveals that Experiment No. 8 (crank angle=90° and anti-symmetric lamination scheme=0°/90°/0°/90°), Experiment No. 14 (crank angle=150° and anti-symmetric lamination scheme=0^o/90^o/0^o/90^o), Experiment No. 2 (crank angle=30° and anti-symmetric lamination scheme=0°/90°/0°/90°) and Experiment No. 3 (crank angle=30° and symmetric lamination scheme=0°/90°/0°/90°) occupy rank 1 for one fold, one end clamped, one fold, two ends clamped, two folds, one end clamped and two folds, two ends clamped conditions, respectively, in order to maximize the modal response corresponding to the fundamental mode.

SD-based technique for order of preference by similarity to ideal solution (TOPSIS) method is used to rank the process parameters. The optimum combination of the input parameters on the multi-response optimization of dynamics of the folded plates has also been evaluated using the analysis of mean (ANOM).

The purpose of this research paper is to optimize the process parameters of selective laser sintering process, and the sintered parts of PA2200 prototypes are built with minimum surface roughness within the range of 10-12 microns using the Taguchi design of experiments approach.

In this research paper, a 3D model is created using catia V5 and exported to rapid prototype machine, and the 3D model file was repaired by using Magics software to remove the facets and saved with file extension .stl (standard triangulation language).Taguchi design of experiments approach L9 orthogonal array was selected with three factors at three levels each and total nine experiments were conducted with the quality index lower-the-better signal-to-noise ratio to produced better quality prototypes by optimizing the process parameters like laser power, layer thickness and temperature and tested on surface tester for surface roughness. The experimental results of surface roughness were compared with Regression Analysis, S/N Ratio, Analysis of Mean and predicted model on sintered prototypes.

The experimental results obtained after testing on the surface tester compared with mathematical model for the quality index lower-the-better signal-noise ratio with optimal process parameters operating at Temperature at level 3, Layer thickness at level 3, and Laser power at level 3, regression analysis, and predictive model the output response variable surface roughness, is with in the range of 9-10.5 microns are all most same and from ANOM (Analysis of Mean), temperature at leve1, layer thickness at level 2, laser power at level 2 is 9 -9.6 microns.

The process parameters such as beam diameter and table speed were not considered on output response variable surface roughness in this research paper.

All the experiments were conducted and the parts are produced by using the material PA2200 in the powder from and sintered by Co₂ laser by varying the process parameters with optimal settings to produce minimum surface roughness the out put from this paper is the influence of process parameters on surface roughness can be predicted at optimal settings with in less time and cost.

This paper explores the ability of the capital asset pricing model, as well as the firm specific factors, to explain the cross‐sectional relationship between average stock returns and risk in Athens Stock Exchange (ASE). The objective of this study is to investigate the cross‐section of stock returns in the Greek stock market for the period from July 1993 to June 2001. A methodology similar to that of Fama and French (1992) is employed, by taking into account the constraints imposed by a smaller sample both in time and in terms of number of stocks. Our findings indicate that in the Greek stock market there is not a positive relation between risk, measured by β, and average returns. On the other hand, there is a “size effect” on the cross‐sectional variation in average stock returns.

This chapter focusses on the ethical issues raised by different types of surveillance and the varied ways in which surveillance can be covert. Three case studies are presented which highlight different types of surveillance and different ethical concerns. The first case concerns the use of undercover police to infiltrate political activist groups over a 40-year period in the UK. The second case study examines a joint operation by US and Australian law enforcement agencies: the FBI’s operation Trojan Shield and the AFP’s Operation Ironside. This involved distributing encrypted phone handsets to serious criminal organisations which included a ‘backdoor’ secretly sending encrypted copies of all messages to law enforcement. The third case study analyses the use of emotional artificial intelligence systems in educational digital learning platforms for children where technology companies collect, store and use intrusive personal data in an opaque manner. The authors discuss similarities and differences in the ethical questions raised by these cases, for example, the involvement of the state versus private corporations, the kinds of information gathered and how it is used.

The purpose of this paper is to analyze the case of a manufacturing firm situated in an industrial city of India, focusing on supply chain management issues of the concerned organization from two operational perspectives: supply side (or the procurement side) and the distribution side of the system.

The authors first considered the outsourcing decision‐making problem in a static environment using analytical expression by means of a variable fraction of demand. Next, the authors extended the scope of this problem by considering outsourcing decisions in a dynamic environment, using the sequential decision‐making approach with various operational and inventory factors. Finally, the authors carried out the study of the distribution side of the supply chain of industry using discrete event simulation.

It was observed that, in the case study organization, because of the rather unstructured approach in dealing with the outsourcing perspective, the authors suggested the adoption of a more scientific approach in computation of fraction of demand to be outsourced. Further, since the distribution network typically experienced high inventory levels throughout the supply chain, it was decided upfront to optimize this performance measure.

The primary objectives of this exercise are to: address the operational concerns of a real‐life manufacturing environment; apply the theoretical models in a realistic environment, and compare the results of theory with practice; and provide actionable managerial recommendations.

This research models the impact of patient perceptions of care quality on overall patient satisfaction in a rural healthcare organization over a three-year time period. The purpose of this paper is to determine if the factors that influence perceptions of service quality change over time and if the change affects overall patient satisfaction.

Data were collected for three fiscal years (2012-2014) using a 36-question, Likert-scaled attitudinal survey. Multiple regression analysis was performed to identify which constructs of five different service quality dimensions were statistically significant in predicting overall patient satisfaction. Paired comparison of means and ANOVA F-tests highlighted significant differences across years and demographics.

Multiple regression models of overall patient satisfaction over a three-year time period had significant repeat variables, indicating salience of the dimensions and constructs of service quality that predict patient satisfaction. However, some dimensions of service quality did not remain significant from one year to another, indicating there may be a gap in the patient service cycle over an extended time frame.

This paper explored the sequential relationship between patient satisfaction survey data and perceptions of service quality over a multi-year time frame. The research focussed on outpatient medical clinics, while the majority of previous studies have focussed on acute care or inpatient stays. A longitudinal study is especially relevant for outpatient clinics where continuity of care is important.

The purpose of this article is to investigate the variables affecting heat transfer from the surfaces of a tall building and also the extent of the impact of each of them. Another purpose of this paper is to provide a suitable model for estimating the heat transfer coefficient of the external surfaces of the building according to the impact of variables.

In this study, the Taguchi's approach in the design of the experiments was used to reduce the number of experiments. Percent contributions factors into the overall and surface-averaged Nu of a square prism were obtained by the (ANOVA). The change in Nu by changing either of T, P, angle of attack and V were investigated by the (ANOM). The most significant factors affecting the value Nu were also identified to facilitate the design of thermal systems by eliminating the factors imposing no significant effect on the response in the molding phase. The set of conditions under which the air properties remained unchanged was identified. Five correlations were formulated to predict Nu.

Models used in BES, in which the effects of T, P, A and geometrical effects are not accounted for, are not reliable. The air pressure was found to impose no significant effect on the overall Nu of the considered square prism. Studied in the range of 274–303 K, the air temperature imposed a significant effect on the overall Nu. The results of ANOVA show the significant role of Re to predict Nu of tall buildings.

This article is taken from a doctoral dissertation.

The purpose of this study is to examine the relationship of corporate governance and corporate profitability on corporate value with corporate social responsibility (CSR) disclosure as the intervening variable.

The population of this study was all companies listed in Indonesia, China and India Stock Exchange in 2013-2016. The inferential statistics used in this study applied the partial least square-based (PLS-based) structural equation model (SEM) method with PLS. The PLS method was selected based on the consideration that there was a construct formed with reflective indicators in this study.

In Indonesia, corporate governance and corporate profitability have a significant and positive effect on CSR disclosure. Similarly, CSR disclosure and corporate profitability have a significant and positive impact on corporate value. Corporate governance indirectly influences corporate value, through mediation CSR disclosure. In China, corporate governance and corporate profitability have a significant and positive effect on CSR disclosure. Similarly, CSR disclosure and corporate governance have a significant and positive impact on corporate value. Corporate profitability indirectly affects corporate value, through mediation CSR disclosure. In India, corporate governance and corporate profitability have a significant and positive effect on CSR disclosure. The same thing is seen that CSR disclosure has a significant and positive effect on corporate value. Corporate governance and corporate profitability influence indirectly corporate value, through mediation CSR disclosure.

The study is one of the few studies to investigate and compare the relationship between corporate governance, corporate profitability, CSR and corporate value. The originality of this study is on the reason that many studies that have been conducted still indicated the inconsistency in the results and diversity of the indicators, so that a similar study was conducted by involving the indicators used for measuring the corporate governance variable, which were the proportion of independent commissioners and audit committee. Meanwhile, for the corporate profitability variable, ROA and ROE were used as the indicators. The originality of this study is that it is a comparative study in three countries in Asia, namely, China, India and Indonesia. The three countries have the highest population and highest economic growth in the past five years.