This book was proposed and organized as a means to present recent developments in the field of testing of materials and elements in civil engineering. For this reason, the articles highlighted in ...this editorial relate to different aspects of testing of different materials and elements in civil engineering, from building materials to building structures. The current trend in the development of testing of materials and elements in civil engineering is mainly concerned with the detection of flaws and defects in concrete elements and structures, and acoustic methods predominate in this field. As in medicine, the trend is towards designing test equipment that allows one to obtain a picture of the inside of the tested element and materials. Interesting results with significance for building practices were obtained.
This book was proposed and organized as a means to present recent developments in the field of testing of materials and elements in civil engineering. For this reason, the articles highlighted in ...this editorial relate to different aspects of testing of different materials and elements in civil engineering, from building materials to building structures. The current trend in the development of testing of materials and elements in civil engineering is mainly concerned with the detection of flaws and defects in concrete elements and structures, and acoustic methods predominate in this field. As in medicine, the trend is towards designing test equipment that allows one to obtain a picture of the inside of the tested element and materials. Interesting results with significance for building practices were obtained.
Numerical data that are normally distributed can be analyzed with parametric tests, that is, tests which are based on the parameters that define a normal distribution curve. If the distribution is ...uncertain, the data can be plotted as a normal probability plot and visually inspected, or tested for normality using one of a number of goodness of fit tests, such as the Kolmogorov-Smirnov test. The widely used Student's t-test has three variants. The one-sample t-test is used to assess if a sample mean (as an estimate of the population mean) differs significantly from a given population mean. The means of two independent samples may be compared for a statistically significant difference by the unpaired or independent samples t-test. If the data sets are related in some way, their means may be compared by the paired or dependent samples t-test. The t-test should not be used to compare the means of more than two groups. Although it is possible to compare groups in pairs, when there are more than two groups, this will increase the probability of a Type I error. The one-way analysis of variance (ANOVA) is employed to compare the means of three or more independent data sets that are normally distributed. Multiple measurements from the same set of subjects cannot be treated as separate, unrelated data sets. Comparison of means in such a situation requires repeated measures ANOVA. It is to be noted that while a multiple group comparison test such as ANOVA can point to a significant difference, it does not identify exactly between which two groups the difference lies. To do this, multiple group comparison needs to be followed up by an appropriate post hoc test. An example is the Tukey's honestly significant difference test following ANOVA. If the assumptions for parametric tests are not met, there are nonparametric alternatives for comparing data sets. These include Mann-Whitney U-test as the nonparametric counterpart of the unpaired Student's t-test, Wilcoxon signed-rank test as the counterpart of the paired Student's t-test, Kruskal-Wallis test as the nonparametric equivalent of ANOVA and the Friedman's test as the counterpart of repeated measures ANOVA.
The second edition of the International Test Commission Guidelines for Translating and Adapting Tests was prepared between 2005 and 2015 to improve upon the first edition, and to respond to advances ...in testing technology and practices. The 18 guidelines are organized into six categories to facilitate their use: pre-condition (3), test development (5), confirmation (4), administration (2), scoring and interpretation (2), and documentation (2). For each guideline, an explanation is provided along with suggestions for practice. A checklist is provided to improve the implementation of the guidelines. This paper was written by the International Test Commission (ITC), including Dave Bartram, Giray Berberoglu, Jacques Grégoire, Ronald Hambleton, Jose Muniz, and Fons van de Vijver.
Administration of high-stakes language proficiency tests has been disrupted in many parts of the world as a result of the 2019 novel coronavirus pandemic. Institutions that rely on test scores have ...been forced to adapt, and in many cases this means using scores from a different test, or a new online version of an existing test, that can be taken at home. The switch to accepting at-home proficiency tests for high-stakes decisions raises many concerns for stakeholders, such as technological demands, exam security, and validity of score use. Along these lines, this thematic review addresses such concerns and features brief reviews of seven options in at-home proficiency testing: ACTFL Assessments, Duolingo English Test, IELTS Indicator, LanguageCert, TEF Express, TOEFL iBT Special Home Edition, and Versant. Considering at-home testing more broadly, we discuss key considerations for selecting an at-home test. We close with speculation on how at-home tests may shape language testing going forward: Beyond adapting to the current pandemic, at-home testing might address longstanding issues in access to language testing services and the representation of real-world communication practices in language tests.
This paper deals with the monitoring of the performance of a photovoltaic plant, without using the environmental parameters such as the solar radiation and the temperature. The main idea is to ...statistically compare the energy performances of the arrays constituting the PV plant. In fact, the environmental conditions affect equally all the arrays of a small-medium-size PV plant, because the extension of the plant is limited, so any comparison between the energy distributions of identical arrays is independent of the solar radiation and the cell temperature, making the proposed methodology very effective for PV plants not equipped with a weather station, as it often happens for the PV plants located in urban contexts and having a nominal peak power in the 3÷50 kWp range, typically installed on the roof of a residential or industrial building. In this case, the costs of an advanced monitoring system based on the environmental data are not justified, consequently, the weather station is often also omitted. The proposed procedure guides the user through several inferential statistical tools that allow verifying whether the arrays have produced the same amount of energy or, alternatively, which is the worst array. The procedure is effective in detecting and locating abnormal operating conditions, before they become failures.
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