Understanding the Radiation Effects on Fiber Optic Sensors

In this dissertation, the effects of radiation (gamma, neutron or mixed gamma and neutron) on optical fiber sensors are studied and new techniques for real-time measurement of radiation-induced macroscopic changes in optical fibers are presented. It is crucial among the research and development efforts in the nuclear energy field to conduct experiments in Advanced Test Reactor (ATR) to support lifetime extension, novel fuels and materials development, better fuel management, and enhanced safety of existing as well as future nuclear power plants (NPP). Due to their unparalleled and unique advantages over traditional sensors, optical fiber sensors are deemed potential candidates for their use in nuclear environments. However, optical fibers are susceptible to high levels of ionizing radiation emitted by fission reactors which are characterized by the highest levels of gamma dose, high flux of neutrons and potentially high temperatures depending on location in a reactor core. It is essential to accurately determine the information related to physical parameters such as temperature, pressure, and strain in nuclear environments for the safety of the existing and future NPPs. This dissertation starts with inverting a transmission mode long period grating (LPG) to reflection mode using a novel and cost-effective metal coating method since transmission mode LPG limits it applications in tight spaces or in nuclear fields. To understand the metal coating and metal coverage effects on the reflection spectrum of LPG, modeling work was performed, and it was validated by experimental work. We have shown that the sensitivity of LPGs to physical parameters in both transmission and reflection modes are almost the same. Next, we have modeled the radiation effects on different fiber optic sensors, proposed empirical models, and performed numerical analysis to understand the effects of nuclear environments on fiber optic sensors. We analyzed the real-time data from fiber Bragg gratings (FBGs) exposed to high neutron fluence and high temperature environments within the ATR at Idaho National Laboratory (INL). We have found that incoming radiation significantly drifts the characteristic signal of FBGs, leading to a temperature measurement error when FBGs are dedicated to temperature sensing. It is well known that neutron and gamma irradiation compacts silica optical fibers, resulting in a macroscopic change in the refractive index (RI) and geometric structure. The change in RI and linear compaction in a radiation environment is caused by three well-known mechanisms: (1) radiation induced attenuation (RIA), (2) radiation induced compaction (RIC), and (3) radiation induced emission (RIE). While RIA degrades the signal strength by creating different types of color centers in the silica fiber, RIC alters the density, and hence RI by displacing the host material atoms. However, Kramers-Kronig relation states that absorption, and hence the RIA, also modifies the RI of the silica fiber. Apart from RIA and RIC, other phenomena such as temperature, dose rate, stress relaxation, and dopant compositions exchange may change the RI. To overcome these problems, we have proposed an effective technique to measure the change in RI and compaction of optical fiber due to any specific phenomena the fiber is subjected to, including RIC, RIA, dopant diffusion, temperatures, dose, dose rate, etc. By knowing the individual contribution of RI and fiber length to the signal drift, it is possible to reduce the radiation induced signal drift in optical fiber sensors and provide accurate information regarding the temperature inside a radiation environment. Fission gas detection in nuclear environments is another important aspect that needs to be focused on. Pressure induced by fission gases during irradiation may lead to loss of coolant accident (LOCA), which can cause severe damage to the NPPs. We have modeled and fabricated optical fiber-based sensors to enable real-time monitoring of fission gases, which allows understanding the implications of fission gas release during an accident, important for safe and high performance

Robust Diagnostics and Estimation in Heteroscedastic Regression Model in the Presence of Outliers

The violation of the assumption of homoscedasticity in OLS method, usually called heteroscedasticity, gravely misleads the inferential statistics. The current study has considered the situation when outliers occur in heteroscedastic data. Hence, the main focus of this research is to take remedial measures on the violation of the assumption of homoscedasticity in the presence of outliers. This thesis also concerns on the normality assumption of the errors of regression model in the presence of outliers. It is now evident that outliers have great impact on the existing normality tests, heteroscedasticity tests, and the estimators for heteroscedastic model. We propose the Robust Rescaled Moment (RRM) test for testing the normality of the regression residuals when there is an evidence of outlier(s). The results of the study signify that the RRM test offers substantial improvements over other existing tests in the presence of outliers. For the detection of heteroscedasticity in the presence of outliers, a modified version of the classical Goldfeld-Quandt (MGQ) test is proposed which is most powerful than the classical tests of heteroscedasticity. Most statistics practitioners assume that the forms of the heteroscedastic error structures are known which may lead to inefficient estimates if it is not correctly specified. In this respect, a Leverage Based Near-Neighbor (LBNN) method is proposed, where prior information on the structure of the heteroscedastic error is not required. The findings indicate that the LBNN is very efficient for correcting the problem of heteroscedastic errors with unknown structure. We also examine the effect of outliers on the existing remedial measures of heteroscedasticity. Hence, in this thesis, a one step M-type of Robust Weighted Least Squares Method (RWLS) and the Two-Step Robust Weighted Least Squares (TSRWLS) are developed. Finally, the new robust wild bootstrap techniques which are resistant to outliers are proposed. The proposed techniques are based on the weighted residuals which incorporated the MM estimator, robust location, robust scale and the bootstrap sampling schemes of Wu (1986) and Liu (1988). All procedures, in this thesis, are examined by using real data and Monte Carlo simulation studies. The comparative studies among the classical and proposed robust methods reveal that all the proposed robust methods outperform the classical methods

A critical analysis of deportation as crimes against the humanity

The Myanmar government has used deportation as an oppressive instrument against the Rohingya minority, resulting in forced displacement, loss of identity, and significant trauma. As the host country, Bangladesh has faced unprecedented hurdles in dealing with the enormous flood of refugees, but it has also been accused of forced repatriation. The Rohingya Muslim minority in Bangladesh has been subjected to systematic and widespread deportation, resulting in serious human rights violations. This critical analysis investigates deportation as a crime against humanity and its consequences for the afflicted community. This study delves into the legal frameworks surrounding crimes against humanity, focusing on international human rights conventions and the Rome Statute. The analysis demonstrates that the deportation of the Rohingya people constitutes a violation of fundamental human rights, including the right to life, liberty, and security of person, as well as the prohibition of torture and persecution. The article also examines how states, international organizations, and the general public can confront and prevent these crimes. It evaluates the responses of many parties critically, focusing emphasis on the necessity of accountability, justice, and victim support. Keywords: crimes against the humanity, Rohingya crisis DOI: 10.7176/JLPG/137-06 Publication date:October 31st 202

K. Ali Flour Mills relationship with it’s retailers

This internship report is submitted in a partial fulfillment of the requirements for the degree of Master of Business Administration, 2015.Cataloged from PDF version of Internship report.Includes bibliographical references (page 32).“Relationship marketing is a strategy designed to foster customer loyalty, interaction and long-term engagement. It is designed to develop strong connections with customers by providing them with information directly suited to their needs and interests and by promoting open communication.” Relationship marketing differs from other forms of marketing in that it recognizes the long term value of customer relationships and extends communication beyond intrusive advertising and sales promotional messages. One of the things of most value to our company is its relationships with customers, employees, suppliers, distributors, dealers, and retailers. Our relationship capital is the sum of the knowledge, experience, and trust we have with our customers, employees, suppliers, and distribution partners. These relationships are often worth more than the physical assets of our company. Relationships determine the future value of the firm. Any slips in these relationships will hurt our performance. We keep a relationship score-card that describes the strengths, weaknesses, opportunities, and threats in regard to the relationships. K. Ali flour mills is a company which produces high quality flour ( atta, moida, suji and vushi). We always try to have better relationship with our customers. Customer Relationship Management is an upright concept or strategy to solidify relations with our customers and at the same time reducing cost and enhancing productivity and profitability in business. A CRM system is a centralized collection of all data sources of our organization and provides an atomistic real time vision of customer information. A CRM system is vast and significant, but it can be implemented for our business. The main goal is to assist the customers efficiently. Creating and nurturing a strong relationship with our customers is the key to the ongoing success of our business. A strong customer relationship not only means that our clients are likely to keep doing business with us over the long-term, it also means that the chances of that customer recommending us and our products to others are greatly enhanced.Md. Sohel RanaM. Business Administratio

Evaluating Productivity of Microfinance Institutions Evidence from Palestine and Jordan

Microfinance institutions (MFIs) have been recognized to eradicate poverty through the provision of financial services to the poor in war-torn Palestine and Jordan. To continuously provide banking and financial support to the poor, MFIs need to achieve sustainability by attaining sufficient productivity for long-term economic viability. Hence, this study evaluates the productivity of 13 MFIs in Palestine and Jordan by employing the Malmquist Productivity Index with five years data from 2007 to 2011. The microfinance industry observed overall 2.6% Total Factor Productivity (TFP) progress per annum and the decomposition of TFP revealed that the productivity progress was mainly due to progress in technological change. The result also showed a slight decline in the scale efficiency of MFIs. Overall, Palestinian MFIs seem to perform better than Jordanian MFIs

Design and Construction of a Tesla Transformer by using Microwave Oven Transfer for Experimentation

This paper has focused on the step-by-step design of a high frequency medium size (1-3 kW) air-cored resonance transformer commonly called tesla coil, that can be easily used for measurements and general research. Therefore, the task is to minimize the number of stochastic and unknown parameters influencing the device functionality and pointing out pros and cons of each solution. The physical dimension of the tesla transformer has been chosen due to cost effectiveness and availability of the regarding components. This design has mainly two units’ viz., a power supply and tesla coil. The power supply which fed the Tesla coil having voltage rating 12kV and current rating 120mA has been designed by using three microwave oven components. These components are assembled as dual MOTs voltage doubler circuit and necessary simulation has been carried out by using MicroSim Schematics for the verification of performance. Keywords:Microwave Oven , Transformer, Multi mini Capacitors, MicroSim Schematics, Toroid, Tesla Coil CAD

Advanced auxetic fibrous structures and composites for industrial applications

This paper reports an overview of advanced auxetic fibrous structures and composites for various industrial applications. Most recent developments in the area of auxetic fibres, yarns, textile structures and composites are reviewed. Innovations in terms of materials, design and structures, processing technologies and innovative applications have been critically reviewed.This work is supported by Portuguese National Funding, through FCT - Fundação para a Ciência e a Tecnologia, through the project grant, PTDC/CTM-POL/5814/2014.info:eu-repo/semantics/publishedVersio

Statistical significance of rank regression

Rank regression, which is quite simple to use some form of monotonic relationship between X and Y. Since the rank regression is a nonparametric approach so there are essentially no confidence interval, hypothesis tests, prediction intervals, and interpretation of regression coefficients. In this article, we proposed a bootstrap statistical significance measure of the rank regression by formulating a bootstrap interval for the rank regression parameters. If the rank regression parameters from the original data are not within the bootstrap interval, the rank regression parameters are considered significance. Numerical examples show that the merit of using this proposed bootstrap interval

Diagnostic robust generalised potentials based on GM6 to identify high leverage points in simultaneous regression model

High leverage points (HLPs) are outliers for observations in the X‑variables. Much work has been focused on the detection of high leverage points (HLPs) in multiple linear regression but no research has been done on the detection of HLPs in simultaneous equation models (SEM). Like multiple linear regression, the detection of HLPs in SEM is also important because of their responsibility for producing inefficient estimates. Since no such research has been done, we make the first attempt to propose a diagnostic method by adapting the diagnostic robust generalised potential (DRGP) to identify HLPs in SEM. Numerical examples and simulation results indicate that our proposed method is very successful in identifying HLPs in SEM

Towards the Design of a Wideband Reflective Long Period Grating Distributed Sensor

In this paper, we computationally investigate the effects of metal coating length and coating coverage on the reflected spectrum of a long period grating (LPG) over a broad bandwidth. Simulation results indicate that coating the tail end of the fiber between the LPG and the end facet of the fiber provides a reflected spectrum that mimics the LPG transmission spectrum shape over a 400 nmbandwidth. Based on single LPG simulation results, we present the design of a distributed LPG structure containing a multiple number (n) of LPGs in reflection mode for the first time. Simulation results for n = 1, 2, and 3 are presented here to demonstrate the concept of a distributed reflective LPG design. It is expected that such a sensor will open a new window for distributed sensing using reflective LPGs