Is our understanding of measurement evolving?

Traditionally understood as a quantitative empirical process, in the last decades measurement has been reconsidered in its aims, scope, and structure, so that the basic questions are again important: what kind of knowledge do we obtain from a measurement? what is the source of the acknowledged special efficacy of measurement? A preliminary analysis is proposed here from an evolutionary perspective.

Pengalaman Spiritual dan Kebahagiaan menurut Nyai Hajah Masriyah Amva

<p class="06IsiAbstrak">This study aims to describe spiritual experiences and happiness according to Nyai Hajah Masriyah Amva, a female cleric and caregiver at the Kebon Jambu Al-Islamy Islamic Boarding School in Ciwaringin, Cirebon, West Java. This research is included in library research using qualitative methods. The results of this study prove that the spiritual experience carried out by Nyai Hajah Masriyah Amva has led her to true happiness. The happiness that Masriyah Amva gets is an empirical process she goes through and then pushes her to do a 'hijrah' or self-transcendence that goes beyond the physical world or the real environment to the Supreme Reality, God. By making God the pinnacle of transcendence, Masriyah finds true happiness. With God, he feels that he is always near to Him and at the same time becomes his support so that he feels no longer alone anywhere and anytime.</p>

Asymptotic methods of testing statistical hypotheses

<p>For a long time, the goodness of fit (GOF) tests have been one of the main objects of the theory of testing of statistical hypotheses. These tests possess two essential properties. Firstly, the asymptotic distribution of GOF test statistics under the null hypothesis is free from the underlying distribution within the hypothetical family. Secondly, they are of omnibus nature, which means that they are sensitive to every alternative to the null hypothesis. GOF tests are typically based on non-linear functionals from the empirical process. The first idea to change the focus from particular functionals to the transformation of the empirical process itself into another process, which will be asymptotically distribution free, was first formulated and accomplished by {\bf Khmaladze} \cite{Estate1}. Recently, the same author in consecutive papers \cite{Estate} and \cite{Estate2} introduced another method, called here the {\bf Khmaladze-2} transformation, which is distinct from the first Khmaladze transformation and can be used for an even wider class of hypothesis testing problems and is simpler in implementation. This thesis shows how the approach could be used to create the asymptotically distribution free empirical process in two well-known testing problems. The first problem is the problem of testing independence of two discrete random variables/vectors in a contingency table context. Although this problem has a long history, the use of GOF tests for it has been restricted to only one possible choice -- the chi-square test and its several modifications. We start our approach by viewing the problem as one of parametric hypothesis testing and suggest looking at the marginal distributions as parameters. The crucial difficulty is that when the dimension of the table is large, the dimension of the vector of parameters is large as well. Nevertheless, we demonstrate the efficiency of our approach and confirm by simulations the distribution free property of the new empirical process and the GOF tests based on it. The number of parameters is as big as $30$. As an additional benefit, we point out some cases when the GOF tests based on the new process are more powerful than the traditional chi-square one. The second problem is testing whether a distribution has a regularly varying tail. This problem is inspired mainly by the fact that regularly varying tail distributions play an essential role in characterization of the domain of attraction of extreme value distributions. While there are numerous studies on estimating the exponent of regular variation of the tail, using GOF tests for testing relevant distributions has appeared in few papers. We contribute to this latter aspect a construction of a class of GOF tests for testing regularly varying tail distributions.</p>

Asymptotic methods of testing statistical hypotheses

<p>For a long time, the goodness of fit (GOF) tests have been one of the main objects of the theory of testing of statistical hypotheses. These tests possess two essential properties. Firstly, the asymptotic distribution of GOF test statistics under the null hypothesis is free from the underlying distribution within the hypothetical family. Secondly, they are of omnibus nature, which means that they are sensitive to every alternative to the null hypothesis. GOF tests are typically based on non-linear functionals from the empirical process. The first idea to change the focus from particular functionals to the transformation of the empirical process itself into another process, which will be asymptotically distribution free, was first formulated and accomplished by {\bf Khmaladze} \cite{Estate1}. Recently, the same author in consecutive papers \cite{Estate} and \cite{Estate2} introduced another method, called here the {\bf Khmaladze-2} transformation, which is distinct from the first Khmaladze transformation and can be used for an even wider class of hypothesis testing problems and is simpler in implementation. This thesis shows how the approach could be used to create the asymptotically distribution free empirical process in two well-known testing problems. The first problem is the problem of testing independence of two discrete random variables/vectors in a contingency table context. Although this problem has a long history, the use of GOF tests for it has been restricted to only one possible choice -- the chi-square test and its several modifications. We start our approach by viewing the problem as one of parametric hypothesis testing and suggest looking at the marginal distributions as parameters. The crucial difficulty is that when the dimension of the table is large, the dimension of the vector of parameters is large as well. Nevertheless, we demonstrate the efficiency of our approach and confirm by simulations the distribution free property of the new empirical process and the GOF tests based on it. The number of parameters is as big as $30$. As an additional benefit, we point out some cases when the GOF tests based on the new process are more powerful than the traditional chi-square one. The second problem is testing whether a distribution has a regularly varying tail. This problem is inspired mainly by the fact that regularly varying tail distributions play an essential role in characterization of the domain of attraction of extreme value distributions. While there are numerous studies on estimating the exponent of regular variation of the tail, using GOF tests for testing relevant distributions has appeared in few papers. We contribute to this latter aspect a construction of a class of GOF tests for testing regularly varying tail distributions.</p>

Development of an empirical process model for adjusted porosity in laser-based powder bed fusion of Ti-6Al-4V

A promising approach to address the mismatch of bone and implant stiffness, leading to the stress-shielding phenomenon, is the application of functionally graded materials with adjusted porosity. Although defect formation and porosity in laser-based powder bed fusion of metals (PBF-LB/M) are already widely investigated, so far there is little research on the influences and parameter interactions regarding the pore characteristics. This work therefore aims to provide an empirical process model for the generation of gas porosity in the PBF-LB process of Ti-6Al-4V. Parts with closed locally adjusted porosity of $\sim $ ∼ 6 % achieved through gaseous pores instead of lack of fusion defects or lattice structures were built by PBF-LB. Parameter variation and evaluation of relative density, pore size and sphericity was done in accordance with the design of experiments approach. A parameter set for maximum gas porosity (laser power of 189 W, scanning speed of 375 mm/s, hatch spacing of 150 μm) was determined for a constant layer thickness of 30 μm and a spot diameter of 35 μm. Tensile tests were conducted with specimens consisting of a core with maximum gas porosity or lack of fusion porosity, respectively, and a dense skin as well as fully dense specimens. Whereas lack of fusion defects can lead to significant reduction of stiffness of 32.2 %, the elastic modulus remained unchanged at 110.0 GPa when implementing spherical pores. Nevertheless, the found superior strength and ductility of specimens with gas porous core (> 1100 MPa and > 0.05 mm/mm, respectively) underline the advantages of adjusted porosity for the application in functionally graded materials and lightweight applications.

Analysis of a dream series by the Dream Coding System developed by Ulrich Moser

This paper serves psychotherapeutic process research and shows the process of change in a psychodynamic, individual psychological psychotherapy by means of a theory-based content analysis of the dreams reported in this therapy. The analysis of the patient’s dreams is carried out according to the dream coding method by Ulrich Moser and Vera Hortig (2019). The guiding question is about changes in positioning and interactions of the dream elements, how can they be determined and how (within the framework of the underlying dream generation theory) the influence of these changes on the patient’s ability to regulate affect can be assessed. Dream coding according to Moser and Hortig uses only the manifest dream and can be regarded as a research tool that rests, among other things, on psychoanalytic concepts, while at the same time taking into account more recent findings in dream and affect research. Its focus is on the coding of the present dream experience and the transformation of dream elements both within individual dreams and in the course of an entire dream series. It allows, without knowledge of the biographical anamnesis and without using psychoanalytic interpretation methods, to recognize changes in the dream structure and the affect regulation produced by it. The coding system thus also offers the possibility of making comparisons regarding the therapeutic changes achieved and thus (at least potentially) the effectiveness of different treatment methods (cf. Leuzinger-Bohleber, 2008, p. 7 f.). The coding of several dreams, i.e. the manifest dream content as a dream series highlighted the patient’s inner psychic change process: while the safety principle dominated the beginning, involvement increased and the use of the elements was more flexible and the interactions more mixed, to approach the initial dream again towards the end of the dream series. The coding indicates that the patient was able to increase her self-efficacy due to better containment of the emergent (dysfunctional) affects. This coding procedure serves as a promising empirical process assessment for carrying out single case studies.

A goodness-of-fit test based on Kendall’s process: Durante's bivariate copula models

The proposed goodness-of-fit testing procedures for copula models are fairly recent. The new test statistics or omnibus tests are functional of an empirical process motivated by the theoretical and empirical versions of Kendall’s or Spearman's dependence function. In this paper, we propose a fitting procedure for a symmetric and flexible copula model with a non-zero singular component using the Kendall process. The conditions under which this empirical process weakly converges are satisfied. Using a parametric bootstrap method that allows to compute approximate p-values, it is empirically shown that tests based on the Cramer-von Mises distance keeps the prescribed value for the nominal level under the null hypothesis. Simulation studies that demonstrate the power of the fit test are presented.