At Marginalen Bank, there are several microservices containing endpoints that are covered bytest automation. The documentation of which microservices and endpoints that are covered byautomated tests is currently done manually and is proven to contain mistakes. In the documentation, the test coverage for all microservices together and for every individual microserviceis presented. Marginalen Bank needs a way to automate this process with a system that cantake care of test coverage documentation and present the calculated data. Therefore, the purpose of this research is to find a way to create a real-time auto-test monitoring system thatautomatically detects and monitors microservices, endpoints, and test automation to documentand present test automation coverage on a website. The system is required to daily detect andupdate the documentation to be accurate and regularly find eventual changes. The implemented system that detects and documents the test automation coverage is calledTest Autobahn. For the system to detect all microservices, a custom hosted service was implemented that registers microservices. All microservices with the custom hosted service installedand extended to registers to Test Autobahn when deployed on a server. For the system todetect all endpoints of each microservice, a custom middleware was implemented that exposesall endpoints of a microservice with it installed. For the microservices to be able to install theseand get registered, a NuGet package containing the custom hosted service and the custom middleware, was created. To detect test automations, custom attributes models were created thatare supposed to be inserted into each test automation project. The custom attributes are placedin every test class and method within a project, to mark which microservice and endpoint thatis being tested within every automated test. The attributes of a project can be read throughthe assembly. To read the custom attributes within every test automation project, a consoleapplication, called Test Autobahn Automation Detector (TAAD), was implemented. TAADreads the assembly to detect the test automations and sends them to Test Autobahn. Test Autobahn couples the found test automation to the corresponding microservices and endpoints.TAAD is installed and ran on the build pipeline in Azure DevOps for each test automationproject to register the test automations. To daily detect and update the documentation of the test coverage, Quartz.NET hosted serviceis used. With Quartz.NET implemented, Test Autobahn can execute a specified job on a schedule. Within the job, Test Autobahn detects microservices and endpoints and calculates the testautomation coverage for the detection. The calculation of the test coverage from the latestdetection is presented on the webpage, containing both the test coverage for all microservicestogether and the test coverage for each microservice. According to the evaluations, the systemseems to function as anticipated, and the documentation is displaying the expected data.

The present study was designed to examine the relationship between Mednick's Remote Associates Test and Pettigrew's Category-Width Test. The sample was made up of 36 educational psychology students enrolled in the Utah State Summer School. The correlation for males and females was made independently. Although the males showed a higher correlation between the two tests than did the females (males, .296 and females, .058), the correlations were not statistically significant. No full explanation was given for the lack of correlation between the category-width scores and the RAT scores except for the qualification that the RAT may be measuring a different type of creativity than what the category-width test is measuring.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第21462号 / 工博第4537号 / 新制||工||1707(附属図書館) / 京都大学大学院工学研究科マイクロエンジニアリング専攻 / (主査)教授 田畑 修, 教授 鈴木 基史, 准教授 土屋 智由, 教授 平方 寛之 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

No description available.

The purpose of this study was to develop a personalized step test and a valid regression model that used non-exercise data and data collected during the step test to estimate VO2max in males and females 18 to 30 years of age. All participants (N= 80) successfully completed a step test with the starting step rate and step height being determined by the self-reported perceived functional ability (PFA) score and participant's height, respectively. All participants completed a maximal graded exercise test (GXT) to measure VO2max. Multiple linear regression analysis yielded the following equation (R = 0.90, SEE = 3.43 mL/kg/min): 45.938 + 9.253(G) - 0.140(KG) + 0.670(PFA) + 0.429(FSR) - 0.149(45sRHR) to predict VO2max (mL/kg/min) where: G is gender (0=female;1=male), KG is body mass in kg, PFA is the sum of the two PFA questions, FSR is the final step rate (step-ups/min), and 45sRHR is the recovery heart rate 45 seconds following the conclusion of the step test. Each independent variable was significant (p < 0.05) in predicting VO2max and the resulting regression equation accounted for roughly 83% (R2=0.8281) of the shared variance of measured VO2max. Based on the standardized B-weights, gender (0.606) explained the largest proportion of variance in VO2max values followed by PFA (0.315), body mass (-0.256), FSR (-0.248), and the 45sRHR (-0.238). The cross validation statistics (RPRESS = 0.88, SEEPRESS = 3.57 (mL/kg/min-1) show minimal shrinkage in the accuracy of the regression model. This study presents a relatively accurate model to predict VO2max from a submaximal step test that is convenient, easy to administer, and individualized.

Very limited research studies have been conducted to examine bond of glass fibre reinforced polymer (GFRP) bars with high concrete strength. The current research project aims to compare between bond measured from a pull-out test and a hinged beam test for GFRP bars embedded in high strength concrete. Different parameters influencing bond such as GFRP bar diameter, embedment length and surface configuration were investigated in both test methods, while the bar position, i.e. top or bottom, was only studied in hinged beams. Seventy-two pull-out cubes, eight pull-out prisms and twenty-four hinged beams reinforced with GFRP bars were constructed and tested to failure. Twelve pull-out cubes and four hinged beams reinforced with steel bars were also tested for comparison purposes. The results showed that bond stress – slip curves obtained from various testing methods were similar, consisting of high initial stiffness, followed by nonlinear ascending and softening branches. In addition, it was found that the experimental bond strength obtained from hinged beams was higher than both bond strengths measured by the pull-out cube and pull-out prism. However, when a finite element analysis was conducted for hinged beams, it was shown that the tensile force in the reinforcing bar estimated by equilibrium conditions is overestimated as the large deformation of hinged beams at failure was not considered. Therefore, if the tensile force obtained from the finite element analysis is used to calculate the bond strength, it would be similar to that obtained from pull-out cube and prism. Moreover, it was found that the distribution of tensile and bond stresses was nonlinear along the GFRP embedment length and bond stress at the vicinity of the free end increased with increasing the load due to redistribution of bond stresses along the embedment length. Bond strengths were compared against the prediction methods provided in ACI-440.1R, CSA-S806, CSA-S6 and JSCE 1997. In general, all design codes showed conservative results for all specimens tested and ACI predictions gave a good agreement with experimental data compared to other codes. Artificial neural network models were developed to predict bond strength of GFRP bars in concrete. These models used bar diameter, embedment length, concrete compressive strength and concrete cover as input variables. The developed ANN models showed to be able to predict bond strength of GFRP bars in concrete and, therefore, were used to conduct a parametric study. / Higher Education Institute, Government of Libya

Repeated testing produces superior recall (especially at a delay) compared to rereading, a phenomenon known as the testing effect. Three studies present evidence for a test question effect that benefits recall of information participants encounter when reading a test. After reading a two-page passage, participants either reread the passage or took fill-in-the-blank practice tests that contained additional information that was later tested. The same procedure was used for a different two-page prose passage as well. A large and unexpected benefit for information read on practice tests was observed. On the 48-hour delayed final test, recall of information reread on practice tests was superior to information reread in prose passages, a finding that is not predicted by current theories of the testing effect. Additionally, recall of information reread on practice tests did not differ significantly from tested information.

When given a multiple-choice test over unfamiliar material, students may score significantly above chance levels. This performance may be explained by prior knowledge of the material or by “test-wiseness,” determining the correct answer by using cues present in the test. Participants answered questions from an introductory psychology test-bank in two formats: a question stem with a single alternative and a traditional four alternative multiple-choice, reporting what sources of information they used to answer each question. For the single-alternative condition, participants had an accuracy of 42.2%, 17.2% higher than the base chance of 25%, with an average accuracy of 40.75% for the multiple-choice condition. Participants who stated they had previously learnt the material showed no significant difference in accuracy than those who stated they had guessed. These findings suggest that tests may have inflated scores which reflect test-wiseness and prior knowledge more than formal learning of the test materials.

No description available.

No description available.