ROBUST STATISTICAL METHODS FOR NON-NORMAL QUALITY ASSURANCE DATA ANALYSIS IN TRANSPORTATION PROJECTS

The American Association of Highway and Transportation Officials (AASHTO) and Federal Highway Administration (FHWA) require the use of the statistically based quality assurance (QA) specifications for construction materials. As a result, many of the state highway agencies (SHAs) have implemented the use of a QA specification for highway construction. For these statistically based QA specifications, quality characteristics of most construction materials are assumed normally distributed, however, the normality assumption can be violated in several forms. Distribution of data can be skewed, kurtosis induced, or bimodal. If the process shows evidence of a significant departure from normality, then the quality measures calculated may be erroneous. In this research study, an extended QA data analysis model is proposed which will significantly improve the Type I error and power of the F-test and t-test, and remove bias estimates of Percent within Limit (PWL) based pay factor calculation. For the F-test, three alternative tests are proposed when sampling distribution is non-normal. These are: 1) Levene’s test; 2) Brown and Forsythe’s test; and 3) O’Brien’s test. One alternative method is proposed for the t-test, which is the non-parametric Wilcoxon - Mann – Whitney Sign Rank test. For PWL based pay factor calculation when lot data suffer non-normality, three schemes were investigated, which are: 1) simple transformation methods, 2) The Clements method, and 3) Modified Box-Cox transformation using “Golden Section Search” method. The Monte Carlo simulation study revealed that both Levene’s test and Brown and Forsythe’s test are robust alternative tests of variances when underlying sample population distribution is non-normal. Between the t-test and Wilcoxon test, the t-test was found significantly robust even when sample population distribution was severely non-normal. Among the data transformation for PWL based pay factor, the modified Box-Cox transformation using the golden section search method was found to be the most effective in minimizing or removing pay bias. Field QA data was analyzed to validate the model and a Microsoft® Excel macro based software is developed, which can adjust any pay consequences due to non-normality

Bim- A Female Beyond the Average Indian Womanhood in Anita Desai’s Clear Light of Day

Bim (Bimala) is the protagonist of Anita Desai’s novel Clear Light of Day. Unlike the general Indian womenfolk, she is contemplative about her position and dares to fight against the traditional norms regarding females in Indian society. In doing so, she is not bothered about the consequences. Bim is highly sensitive and intelligent and endeavours to discover a relief from the sufferings created by the accepted notions of the society about women. In a sense, Bim is a feminist and somebody who surpasses the average Indian womanhood. This paper aims at examining the ways which make Bim a distinguished female character unmatched by most of her contemporaries in the society in which she lives. Keywords: Traditional,  norms, Indian society, feminist and womanhood. DOI: 10.7176/JLLL/56-03 Publication date:May 31st 201

The Guide- A Brilliant Manifestation of Sub-continental and Universal Elements

Indianness and Narayan’s writings are almost synonymous. In fact, India with its landscape, culture, conventions and customs becomes picturesque in his writings including The Guide. Again to a large extent, the country India is an ideal representative of the sub-continent India. But universality in The Guide (1958) cannot be ignored because the country India and India as a sub-continent undoubtedly symbolize many features of the world. This paper attempts at examining Narayan’s creation of characters who represent both sub-continental and universal elements. Keywords: Sub-continental, Universal, Relationship, Beliefs, Values

Syllabus: Architectural CAD [ENTC 2160]

https://dc.etsu.edu/entc-2160-oer/1000/thumbnail.jp

Engineering Faculty and Staff Inclusive Excellence Training: Broadening Engineering Pedagogy For All

As our classrooms become more and more diverse, the need for cultural competency in engineering faculty is more important than ever. Cross-cultural competency has been named among the 10 most important skills for the future workforce. Historically there is a lack of cultural diversity at East Tennessee State University. The university did not offer any formal training opportunity for faculty and staff in cultural competency. As such, faculty effort in cultural pedagogy is minimal resulting in persistent achievement gaps among culturally diverse students. In this project we have developed and implemented an inclusive excellence cultural competency training program primarily for engineering faculty and staff primarily in the College of Business and Technology. The project aimed to train these faculty and staff in cultural competency so that they can implement inclusive pedagogy and communication in and out of their classrooms. Cross-Cultural Adaptability Inventory and post workshop assessment were used to measure the efficacy of the training program. Assessment data showed that the training program improved faculty and staff’s awareness in wide variety areas of cultural proficiency and provided them with a toolbox of ideas to implement them in their classes and workplaces. Lessons learned are: 1) To make an institution a culturally inclusive institution diversity, equity and inclusion need to be part of the organization DNA and leadership buy-in and advocacy is a must; 2) Whenever possible, create developmental approaches that engage faculty and staff with different levels of content over a period of time and 3) Provide flexibility in training delivery

Factors Affecting the Audit Quality in Bangladesh

Main Objectives: The study mainly focused on different factors which actually affects the audit quality. The principal goal of the report is to comprehend the association between quality and various variables of audit influencing it. Background Problems: In Bangladesh, a series of market crash and manipulated financial statements questioned the audit quality which as a consequence degraded market confidence. Identification of the influential factors towards audit quality can be the steppingstone towards facing the problematic situation. Novelty: 11 factors along with new factor like external manager review was incorporated to work with and to see the impact of each factors. This was unique in nature as the combination of factors were not researched before. Research Methods: Descriptive statistics and Regression model were used for the analysis. The samples were collected randomly which mainly included article students of different firms. Paper based survey was conducted to bring out the responses. The regression model helped us to formulate the significant components which mostly affected the essence of auditing and its nature.  Finding /Results: Audit quality was perceived high, and the respondents assumed that audit review by an external manager of the team had considerable amount of influence over audit quality followed by internal control. It was also visualized that number of client/assignments of a firm inversely impact the audit quality. Contributions: The influential factors were identified which can be studied or regulated to retain the reliability and confidence of the market which is significantly influenced by the audit quality. Conclusion: It can be concluded that the study was successful in identifying the factors affecting the audit quality in Bangladesh which creates an avenue for the concerns to look into the subject for improvisation

Module 03C: Dimensioning

https://dc.etsu.edu/entc-2160-oer/1027/thumbnail.jp

Dedicated Filter for Robust Occupancy Grid Mapping

Sensor based perception of the environment is an emerging area of the mobile robot research where sensors play a pivotal role. For autonomous mobile robots, the fundamental requirement is the convergent of the range information in to high level internal representation. Internal representation in the form of occupancy grid is commonly used in autonomous mobile robots due to its various advantages. There are several sensors such as vision sensor, laser rage finder, and ultrasonic and infrared sensors etc. play roles in mapping. However the sensor information failure, sensor inaccuracies, noise, and slow response are the major causes of an error in the mapping. To improve the reliability of the mobile robot mapping multisensory data fusion is considered as an optimal solution. This paper presents a novel architecture of sensor fusion frame work in which a dedicated filter (DF) is proposed to increase the robustness of the occupancy grid for indoor environment. The technique has been experimentally verified for different indoor test environments. The proposed configuration shows improvement in the occupancy grid with the implementation of dedicated filters

Multisensor Data Fusion and Integration for Mobile Robots: A Review

One of the most important and useful feature of autonomous mobile robots is their ability to adopt themselves to operate in unstructured environment. Today robots are performing autonomously in industrial floor, office environments, as well as in crowded public places where the robots need to maintain their localization and mapping parameters.The basic requirement of an intelligent mobile robot is to develop and maintain localization and mapping parameters to complete the complex missions. In such situations, several difficulties arise in due to the inaccuracies and uncertainties in sensor measurements. Various techniques are there to handle such noises where the multisensor data fusion is not the exceptional one.From the last two decades, multisensor data fusions in mobile robots become a dominant paradigm  due to its potential advantages like reduction in uncertainty, increase in accuracy and reliability and reduction of cost.This paper presents the reviews of autonomous mobile robots and role of multisenosr data fusion