935 resultados para test data generation
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Air traffic management research lacks a framework for modelling the cost of resilience during disturbance. There is no universally accepted metric for cost resilience. The design of such a framework is presented and the modelling to date is reported. The framework allows performance assessment as a function of differential stakeholder uptake of strategic mechanisms designed to mitigate disturbance. Advanced metrics, cost- and non-cost-based, disaggregated by stakeholder sub-types, are described. A new cost resilience metric is proposed and exemplified with early test data.
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In establishing the reliability of performance-related design methods for concrete – which are relevant for resistance against chloride-induced corrosion - long-term experience of local materials and practices and detailed knowledge of the ambient and local micro-climate are critical. Furthermore, in the development of analytical models for performance-based design, calibration against test data representative of actual conditions in practice is required. To this end, the current study presents results from full-scale, concrete pier-stems under long-term exposure to a marine environment with work focussing on XS2 (below mid-tide level) in which the concrete is regarded as fully saturated and XS3 (tidal, splash and spray) in which the concrete is in an unsaturated condition. These exposures represent zones where concrete structures are most susceptible to ionic ingress and deterioration. Chloride profiles and chloride transport behaviour are studied using both an empirical model (erfc function) and a physical model (ClinConc). The time dependency of surface chloride concentration (Cs) and apparent diffusivity (Da) were established for the empirical model whereas, in the ClinConc model (originally based on saturated concrete), two new environmental factors were introduced for the XS3 environmental exposure zone. Although the XS3 is considered as one environmental exposure zone according to BS EN 206-1:2013, the work has highlighted that even within this zone, significant changes in chloride ingress are evident. This study aims to update the parameters of both models for predicting the long term transport behaviour of concrete subjected to environmental exposure classes XS2 and XS3.
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This letter presents novel behaviour-based tracking of people in low-resolution using instantaneous priors mediated by head-pose. We extend the Kalman Filter to adaptively combine motion information with an instantaneous prior belief about where the person will go based on where they are currently looking. We apply this new method to pedestrian surveillance, using automatically-derived head pose estimates, although the theory is not limited to head-pose priors. We perform a statistical analysis of pedestrian gazing behaviour and demonstrate tracking performance on a set of simulated and real pedestrian observations. We show that by using instantaneous `intentional' priors our algorithm significantly outperforms a standard Kalman Filter on comprehensive test data.
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The development of alkali-activated binders with superior engineering properties and longer durability has emerged as an alternative to ordinary portland cement (OPC). It is possible to use alkali-activated natural pozzolans to prepare environmentally friendly geopolymer cement leading to the concept of sustainable development. This paper presents a summary of an experimental work that was conducted to determine mechanical strength, modulus of elasticity, ultrasonic pulse velocity, and shrinkage of different concrete mixtures prepared with alkali-activated Iranian natural pozzolans—namely Taftan andesite and Shahindej dacite, both with and without calcining. Test data were used for Taftan pozzolan to identify the effects of water-binder ratios (w/b) and curing conditions on the properties of the geopolymer concrete, whereas the influence of material composition was studied by activating Shahindej pozzolan both in the natural and calcined states. The results show that alkali-activated natural pozzolan (AANP) concretes develop moderate-to-high mechanical strength with a high modulus of elasticity and a shrinkage much lower than with OPC.
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As noted in Part 1 of this report, the objective of the investigation was to apply principles of first-arrival seismic refraction to the problem of more quickly determining in-place dry density in highway materials. Part 2 of the report, contained herein, presents the results of both additional laboratory development of test techniques, plus extensive field test data.
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Thesis (Ph.D.)--University of Washington, 2016-08
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This thesis evaluates the rheological behaviour of asphalt mixtures and the corresponding extracted binders from the mixtures containing different amounts of Reclaimed Asphalt (RA). Generally, the use of RA is limited to certain amounts. The study materials are Stone Mastic Asphalts including a control sample with 0% RA, and other samples with RA rates of 30%, 60% and 100%. Another set of studied mixtures are Asphalt Concretes (AC) types with again a control mix having 0% RA rate and the other mixtures designs containing 30%, 60% and 90% of reclaimed asphalt which also contain additives. In addition to the bitumen samples extracted from asphalt mixes, there are bitumen samples directly extracted from the original RA. To characterize the viscoelastic behaviour of the binders, Dynamic Shear Rheometer (DSR) tests were conducted on bitumen specimens. The resulting influence of the RA content in the bituminous binders are illustrated through master curves, black diagrams and Cole-Cole plots with regressing these experimental data by the application of the analogical 2S2P1D and the analytical CA model. The advantage of the CA model is in its limited number of parameters and thus is a simple model to use. The 2S2P1D model is an analogical rheological model for the prediction of the linear viscoelastic properties of both asphalt binders and mixtures. In order to study the influence of RA on mixtures, the Indirect Tensile Test (ITT) has been conducted. The master curves of different mixture samples are evaluated by regressing the test data points to a sigmoidal function and subsequently by comparing the master curves, the influence of RA materials is studied. The thesis also focusses on the applicability and also differences of CA model and 2S2P1D model for bitumen samples and the sigmoid function for the mixtures and presents the influence of the RA rate on the investigated model parameters.
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Background and Objectives: The measurement of salivary immunoglobulin A is a useful and non-invasive method for measuring stress. Personality traits and rumination act as possible mediators in the relationship between psychological stressors and the immune system. This study was aimed to evaluate the levels of salivary IgA under psychological stress and its relationship with rumination and five personality traits in medical students. Methods: In this cross- sectional study, 45 medical students who intended to participate in the final exam were selected by simple random sampling. Two months before the exam, in the basal conditions, the NEO Personality Inventory-Short Form and Emotional Control Questionnaire (ECQ) were completed. Saliva samples were taken from students in both the basal conditions and exam stress conditions. Salivary IgA was measured by an ELISA test. Data was analyzed using paired samples T-test, Pearson correlation analysis, and stepwise regression. Results: A significant reduction of salivary IgA levels was found in exam stress conditions. Also, a significant negative correlation was found between traits of neuroticism and rumination with salivary IgA, as well as a significant positive correlation between of openness to experience and emotional inhibition with salivary IgA. Openness to experience and emotional inhibition may predict a substantial variance (34%) of salivary IgA under exam stress. Conclusions: Salivary IgA is reduced in response to exam stress. In addition, the rumination and personality traits may reduce or increase stress effects on the immune system, particularly the salivary IgA.
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With the increasing complexity of today's software, the software development process is becoming highly time and resource consuming. The increasing number of software configurations, input parameters, usage scenarios, supporting platforms, external dependencies, and versions plays an important role in expanding the costs of maintaining and repairing unforeseeable software faults. To repair software faults, developers spend considerable time in identifying the scenarios leading to those faults and root-causing the problems. While software debugging remains largely manual, it is not the case with software testing and verification. The goal of this research is to improve the software development process in general, and software debugging process in particular, by devising techniques and methods for automated software debugging, which leverage the advances in automatic test case generation and replay. In this research, novel algorithms are devised to discover faulty execution paths in programs by utilizing already existing software test cases, which can be either automatically or manually generated. The execution traces, or alternatively, the sequence covers of the failing test cases are extracted. Afterwards, commonalities between these test case sequence covers are extracted, processed, analyzed, and then presented to the developers in the form of subsequences that may be causing the fault. The hypothesis is that code sequences that are shared between a number of faulty test cases for the same reason resemble the faulty execution path, and hence, the search space for the faulty execution path can be narrowed down by using a large number of test cases. To achieve this goal, an efficient algorithm is implemented for finding common subsequences among a set of code sequence covers. Optimization techniques are devised to generate shorter and more logical sequence covers, and to select subsequences with high likelihood of containing the root cause among the set of all possible common subsequences. A hybrid static/dynamic analysis approach is designed to trace back the common subsequences from the end to the root cause. A debugging tool is created to enable developers to use the approach, and integrate it with an existing Integrated Development Environment. The tool is also integrated with the environment's program editors so that developers can benefit from both the tool suggestions, and their source code counterparts. Finally, a comparison between the developed approach and the state-of-the-art techniques shows that developers need only to inspect a small number of lines in order to find the root cause of the fault. Furthermore, experimental evaluation shows that the algorithm optimizations lead to better results in terms of both the algorithm running time and the output subsequence length.
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In this thesis, tool support is addressed for the combined disciplines of Model-based testing and performance testing. Model-based testing (MBT) utilizes abstract behavioral models to automate test generation, thus decreasing time and cost of test creation. MBT is a functional testing technique, thereby focusing on output, behavior, and functionality. Performance testing, however, is non-functional and is concerned with responsiveness and stability under various load conditions. MBPeT (Model-Based Performance evaluation Tool) is one such tool which utilizes probabilistic models, representing dynamic real-world user behavior patterns, to generate synthetic workload against a System Under Test and in turn carry out performance analysis based on key performance indicators (KPI). Developed at Åbo Akademi University, the MBPeT tool is currently comprised of a downloadable command-line based tool as well as a graphical user interface. The goal of this thesis project is two-fold: 1) to extend the existing MBPeT tool by deploying it as a web-based application, thereby removing the requirement of local installation, and 2) to design a user interface for this web application which will add new user interaction paradigms to the existing feature set of the tool. All phases of the MBPeT process will be realized via this single web deployment location including probabilistic model creation, test configurations, test session execution against a SUT with real-time monitoring of user configurable metric, and final test report generation and display. This web application (MBPeT Dashboard) is implemented with the Java programming language on top of the Vaadin framework for rich internet application development. The Vaadin framework handles the complicated web communications processes and front-end technologies, freeing developers to implement the business logic as well as the user interface in pure Java. A number of experiments are run in a case study environment to validate the functionality of the newly developed Dashboard application as well as the scalability of the solution implemented in handling multiple concurrent users. The results support a successful solution with regards to the functional and performance criteria defined, while improvements and optimizations are suggested to increase both of these factors.
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Nowadays there is almost no crime committed without a trace of digital evidence, and since the advanced functionality of mobile devices today can be exploited to assist in crime, the need for mobile forensics is imperative. Many of the mobile applications available today, including internet browsers, will request the user’s permission to access their current location when in use. This geolocation data is subsequently stored and managed by that application's underlying database files. If recovered from a device during a forensic investigation, such GPS evidence and track points could hold major evidentiary value for a case. The aim of this paper is to examine and compare to what extent geolocation data is available from the iOS and Android operating systems. We focus particularly on geolocation data recovered from internet browsing applications, comparing the native Safari and Browser apps with Google Chrome, downloaded on to both platforms. All browsers were used over a period of several days at various locations to generate comparable test data for analysis. Results show considerable differences not only in the storage locations and formats, but also in the amount of geolocation data stored by different browsers and on different operating systems.
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Personality traits have been studied for some decades in fish species. Yet, most often, studies focused on juveniles or adults. Thus, very few studies tried to demonstrate that traits could also be found in fish larvae. In this study, we aimed at identifying personality traits in Northern pike (Exos lucius) larvae. Twenty first-feeding larvae aged 21 days post hatch (16.1 +/− 0.4 mm in total length, mean +/− SD) were used to establish personality traits with two tests: a maze and a novel object. These tests are generally used for evaluating the activity and exploration of specimens as well as their activity and boldness, respectively. The same Northern pike twenty larvae were challenged in the two tests. Their performances were measured by their activity, their exploratory behaviour and the time spent in the different arms of the maze or near the novel object. Then, we used principal component analysis (PCA) and a hierarchical ascendant classification (HAC) for analysis of each data set separately. Finally, we used PCA reduction for the maze test data to analyse the relationship between a synthetic behavioural index (PCA1) and morphometric variables. Within each test, larvae could be divided in two sub groups, which exhibited different behavioural traits, qualified as bold (n = 7 for the maze test and n = 13 for the novel object test) or shy (n = 9 for the maze test and n = 11 for the novel object test). Nevertheless, in both tests, there was a continuum of boldness/shyness. Besides, some larvae were classified differently between the two tests but 40 % of the larvae showed cross context consistency and could be qualified as bold and/or proactive individuals. This study showed that it is possible to identify personality traits of very young fish larvae of a freshwater fish species.
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The effect of isothermal aging on the harmonic vibration durability of Sn3.0Ag0.5Cu solder interconnects is examined. Printed wiring assemblies with daisy-chained leadless chip resistors (LCRs) are aged at 125°C for 0, 100, and 500 hours. These assemblies are instrumented with accelerometers and strain gages to maintain the same harmonic vibration profile in-test, and to characterize PWB behavior. The tested assemblies are excited at their first natural frequencies until LCRs show a resistance increase of 20%. Dynamic finite element models are employed to generate strain transfer functions, which relate board strain levels observed in-test to respective solder strain levels. The transfer functions are based on locally averaged values of strains in critical regions of the solder and in appropriate regions of the PWB. The vibration test data and the solder strains from FEA are used to estimate lower-bound material fatigue curves for SAC305 solder materials, as a function of isothermal pre-aging.
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Accurate estimation of road pavement geometry and layer material properties through the use of proper nondestructive testing and sensor technologies is essential for evaluating pavement’s structural condition and determining options for maintenance and rehabilitation. For these purposes, pavement deflection basins produced by the nondestructive Falling Weight Deflectometer (FWD) test data are commonly used. The nondestructive FWD test drops weights on the pavement to simulate traffic loads and measures the created pavement deflection basins. Backcalculation of pavement geometry and layer properties using FWD deflections is a difficult inverse problem, and the solution with conventional mathematical methods is often challenging due to the ill-posed nature of the problem. In this dissertation, a hybrid algorithm was developed to seek robust and fast solutions to this inverse problem. The algorithm is based on soft computing techniques, mainly Artificial Neural Networks (ANNs) and Genetic Algorithms (GAs) as well as the use of numerical analysis techniques to properly simulate the geomechanical system. A widely used pavement layered analysis program ILLI-PAVE was employed in the analyses of flexible pavements of various pavement types; including full-depth asphalt and conventional flexible pavements, were built on either lime stabilized soils or untreated subgrade. Nonlinear properties of the subgrade soil and the base course aggregate as transportation geomaterials were also considered. A computer program, Soft Computing Based System Identifier or SOFTSYS, was developed. In SOFTSYS, ANNs were used as surrogate models to provide faster solutions of the nonlinear finite element program ILLI-PAVE. The deflections obtained from FWD tests in the field were matched with the predictions obtained from the numerical simulations to develop SOFTSYS models. The solution to the inverse problem for multi-layered pavements is computationally hard to achieve and is often not feasible due to field variability and quality of the collected data. The primary difficulty in the analysis arises from the substantial increase in the degree of non-uniqueness of the mapping from the pavement layer parameters to the FWD deflections. The insensitivity of some layer properties lowered SOFTSYS model performances. Still, SOFTSYS models were shown to work effectively with the synthetic data obtained from ILLI-PAVE finite element solutions. In general, SOFTSYS solutions very closely matched the ILLI-PAVE mechanistic pavement analysis results. For SOFTSYS validation, field collected FWD data were successfully used to predict pavement layer thicknesses and layer moduli of in-service flexible pavements. Some of the very promising SOFTSYS results indicated average absolute errors on the order of 2%, 7%, and 4% for the Hot Mix Asphalt (HMA) thickness estimation of full-depth asphalt pavements, full-depth pavements on lime stabilized soils and conventional flexible pavements, respectively. The field validations of SOFTSYS data also produced meaningful results. The thickness data obtained from Ground Penetrating Radar testing matched reasonably well with predictions from SOFTSYS models. The differences observed in the HMA and lime stabilized soil layer thicknesses observed were attributed to deflection data variability from FWD tests. The backcalculated asphalt concrete layer thickness results matched better in the case of full-depth asphalt flexible pavements built on lime stabilized soils compared to conventional flexible pavements. Overall, SOFTSYS was capable of producing reliable thickness estimates despite the variability of field constructed asphalt layer thicknesses.
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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, 2015.