Test Set Diameter: Quantifying the Diversity of Sets of Test Cases

A common and natural intuition among software testers is that test cases need to differ if a software system is to be tested properly and its quality ensured. Consequently, much research has gone into formulating distance measures for how test cases, their inputs and/or their outputs differ. However, common to these proposals is that they are data type specific and/or calculate the diversity only between pairs of test inputs, traces or outputs. We propose a new metric to measure the diversity of sets of tests: the test set diameter (TSDm). It extends our earlier, pairwise test diversity metrics based on recent advances in information theory regarding the calculation of the normalized compression distance (NCD) for multisets. An advantage is that TSDm can be applied regardless of data type and on any test-related information, not only the test inputs. A downside is the increased computational time compared to competing approaches. Our experiments on four different systems show that the test set diameter can help select test sets with higher structural and fault coverage than random selection even when only applied to test inputs. This can enable early test design and selection, prior to even having a software system to test, and complement other types of test automation and analysis. We argue that this quantification of test set diversity creates a number of opportunities to better understand software quality and provides practical ways to increase it.Comment: In submissio

Testing for threshold effects in regression models

In this article, we develop a general method for testing threshold effects in regression models, using sup-likelihood-ratio (LR)-type statistics. Although the sup-LR-type test statistic has been considered in the literature, our method for establishing the asymptotic null distribution is new and nonstandard. The standard approach in the literature for obtaining the asymptotic null distribution requires that there exist a certain quadratic approximation to the objective function. The article provides an alternative, novel method that can be used to establish the asymptotic null distribution, even when the usual quadratic approximation is intractable. We illustrate the usefulness of our approach in the examples of the maximum score estimation, maximum likelihood estimation, quantile regression, and maximum rank correlation estimation. We establish consistency and local power properties of the test. We provide some simulation results and also an empirical application to tipping in racial segregation. This article has supplementary materials online.

A Joint Analysis of GPS Displacement and GRACE Geopotential Data for Simultaneous Estimation of Geocenter Motion and Gravitational Field

Gravitational potential data from GRACE are being used to study mass redistribution within and between the atmosphere, hydrosphere, cryosphere, and solid Earth. The GRACE data are made available in a reference frame with its origin at the center of mass of the Earth system (geocenter) while many other geophysical models and data sets refer to a reference frame attached to the Earth's surface. Changes in the offset between these reference frames (geocenter motion) must be accounted for when GRACE data are used to quantify surface mass changes. In this study, we developed a technique for coestimation of geocenter motion and gravitational potential field seamlessly from degree 1 to 90 by simultaneously inverting a set of globallydistributed GPS displacement time series and the temporallyvarying GRACE gravity data. We found that the effect of geocenter motion was evident particularly in the GPS time series of horizontal displacements. Our estimates of geocenter motion are most consistent with the Satellite Laser Ranging (SLR) results within 1 mm in X and Z components and a submillimeter in Y component, when compared to monthly variability averaged over the period of 20032016. The overall magnitude of the degree1 (l = 1) surface mass load is estimated to be ~3 cm in equivalent water height annually migrating southwestward from Europe (DecemberJanuary) to the South Pacific (JuneJuly). Our results also show that dense GPS network data improve water storage recovery in major river basins in the United States and Europe by contributing significantly to the recovery of higherdegree (l ~20) geopotential coefficients

Concept design of a fast sail assisted feeder container ship

A fast sail assisted feeder container ship concept has been developed for the 2020 container market in the South East Asian and Caribbean regions.The design presented has met the requirements of an initial economic study, with a cargo capacity of 1270 twenty-foot equivalent unit containers, meeting the predictions of container throughput derived from historical data. In determining suitable vessel dimensions, account has also been taken for port and berthing restrictions, and considering hydrodynamic performance. The vessel has been designed for a maximum speed of 25 knots, allowing it to meet the demand for trade whilst reducing the number of ships operating on the routes considered.The design development of the fast feeder concept has involved rigorous analyses in a number of areas to improve the robustness of the final design. Model testing has been key to the development of the concept, by increasing confidence in the final result. This is due to the fact that other analysis techniques are not always appropriate or accurate. Two hull forms have been developed to meet requirements whilst utilising different propulsor combinations. This has enabled evaluation of efficiency gains resulting from different hydrodynamic phenomena for each design. This includes an evaluation of the hydrodynamic performance when utilising the sail system. This has been done using a combination of model test results and data from regression analysis. The final propulsor chosen is a contra-rotating podded drive arrangement. Wind tunnel testing has been used to maximise the performance of a Multi-wing sail system by investigating the effects of wing spacing, stagger and sail-container interactions. This has led to an increase in lift coefficient of 32% from initial predictions. The savings in power requirement due to the sail system are lower than initially predicted. However, another benefit of their installation, motion damping, has been identified. Whilst this has not been fully investigated, additional fuel savings are possible as well as improved seakeeping performance.The design is shown to be environmentally sustainable when compared to existing vessels operating on the proposed routes. This is largely due to the use of low-carbon and zero-sulphur fuel (liquefied natural gas) and improvements in efficiency regarding operation. This especially relates to cargo handling and scheduling. Green house gas emissions have been predicted to fall by 42% and 40% in the two regions should the design be adopted. These savings are also due to the use of the Multi-wing sail system, which contributes to reductions in power requirement of up to 6% when the vessel operates at its lower speed of 15 knots. It is demonstrated that the fast feeder is also economically feasible, with predicted daily cost savings of 27% and 33% in the South East Asian and Caribbean regions respectively. Thus the fast feeder container ship concept is a viable solution for the future of container transhipment. <br/

Concept design of a fast sail assisted feeder container ship

An environmentally sustainable fast sail-assisted feeder-container ship concept, with a maximum speed of 25 knots, has been developed for the 2020 South East Asian and Caribbean container markets. The use of low-carbon and zero-sulphur fuel (liquefied natural gas) and improvements in operational efficiency (cargo handling and scheduling) mean predicted Green house gas emissions should fall by 42% and 40% in the two selected operational regions. The adoption of a Multi-wing sail system reduces power requirement by up to 6% at the lower ship speed of 15 knots. The predicted daily cost savings are respectively 27% and 33% in South East Asian and the Caribbean regions.Two hull forms with a cargo capacity of 1270TEU utilising different propulsion combinations were initially developed to meet operational requirements. Analysis &amp; tank testing of different hydrodynamic phenomena has enabled identification of efficiency gains for each design. The final propulsion chosen is a contra-rotating podded drive arrangement. Wind tunnel testing improved Multi-wing sail performance by investigating wing spacing, wing stagger and sail-container interactions. The associated lift coefficient was increased by 32%. Whilst savings in sail-assisted power requirement are lower than initially predicted an unexpected identified benefit was motion damping.The fast feeder-container ship is a proposed as a viable future method of container transhipment

Machine learning-based predictive model for prevention of metabolic syndrome

Metabolic syndrome (MetS) is a chronic disease caused by obesity, high blood pressure, high blood sugar, and dyslipidemia and may lead to cardiovascular disease or type 2 diabetes. Therefore, the detection and prevention of MetS at an early stage are imperative. Individuals can detect MetS early and manage it effectively if they can easily monitor their health status in their daily lives. In this study, a predictive model for MetS was developed utilizing solely noninvasive information, thereby facilitating its practical application in real-world scenarios. The model\u27s construction deliberately excluded three features requiring blood testing, specifically those for triglycerides, blood sugar, and HDL cholesterol. We used a large-scale Korean health examination dataset (n = 70, 370; the prevalence of MetS = 13.6%) to develop the predictive model. To obtain informative features, we developed three novel synthetic features from four basic information: waist circumference, systolic and diastolic blood pressure, and gender. We tested several classification algorithms and confirmed that the decision tree model is the most appropriate for the practical prediction of MetS. The proposed model achieved good performance, with an AUC of 0.889, a recall of 0.855, and a specificity of 0.773. It uses only four base features, which results in simplicity and easy interpretability of the model. In addition, we performed calibrations on the prediction probability and calibrated the model. Therefore, the proposed model can provide MetS diagnosis and risk prediction results. We also proposed a MetS risk map such that individuals could easily determine whether they had metabolic syndrome

Systems approach to investigating host-pathogen interactions in infections with the biothreat agent Francisella. Constraints-based model of Francisella tularensis

<p>Abstract</p> <p>Background</p> <p><it>Francisella tularensis </it>is a prototypic example of a pathogen for which few experimental datasets exist, but for which copious high-throughout data are becoming available because of its re-emerging significance as biothreat agent. The virulence of <it>Francisella tularensis </it>depends on its growth capabilities within a defined environmental niche of the host cell.</p> <p>Results</p> <p>We reconstructed the metabolism of <it>Francisella </it>as a stoichiometric matrix. This systems biology approach demonstrated that changes in carbohydrate utilization and amino acid metabolism play a pivotal role in growth, acid resistance, and energy homeostasis during infection with <it>Francisella</it>. We also show how varying the expression of certain metabolic genes in different environments efficiently controls the metabolic capacity of <it>F. tularensis</it>. Selective gene-expression analysis showed modulation of sugar catabolism by switching from oxidative metabolism (TCA cycle) in the initial stages of infection to fatty acid oxidation and gluconeogenesis later on. Computational analysis with constraints derived from experimental data revealed a limited set of metabolic genes that are operational during infection.</p> <p>Conclusions</p> <p>This integrated systems approach provides an important tool to understand the pathogenesis of an ill-characterized biothreat agent and to identify potential novel drug targets when rapid target identification is required should such microbes be intentionally released or become epidemic.</p

A Normal Form for Spider Diagrams of Order

We develop a reasoning system for an Euler diagram based visual logic, called spider diagrams of order. We de- fine a normal form for spider diagrams of order and provide an algorithm, based on the reasoning system, for producing diagrams in our normal form. Normal forms for visual log- ics have been shown to assist in proving completeness of associated reasoning systems. We wish to use the reasoning system to allow future direct comparison of spider diagrams of order and linear temporal logic

On Quantizing Implicit Neural Representations

The role of quantization within implicit/coordinate neural networks is still not fully understood. We note that using a canonical fixed quantization scheme during training produces poor performance at low-rates due to the network weight distributions changing over the course of training. In this work, we show that a non-uniform quantization of neural weights can lead to significant improvements. Specifically, we demonstrate that a clustered quantization enables improved reconstruction. Finally, by characterising a trade-off between quantization and network capacity, we demonstrate that it is possible (while memory inefficient) to reconstruct signals using binary neural networks. We demonstrate our findings experimentally on 2D image reconstruction and 3D radiance fields; and show that simple quantization methods and architecture search can achieve compression of NeRF to less than 16kb with minimal loss in performance (323x smaller than the original NeRF).Comment: 10 pages, 10 figure