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Industrial embedded systems often require specialized hardware. However, software engineers have access to such domain-specific hardware only at the continuous integration (CI) stage and have to use simulated hardware otherwise. This results in a higher proportion of compilation errors at the CI stage than in other types of systems, warranting a deeper study. To this end, we create a CI diagnostics solution called ``Shadow Job'' that analyzes our industrial CI system. We collected over 40000 builds from 4 projects from the product source code and categorized the compilation errors into 14 error types, showing that the five most common ones comprise 89 % of all compilation errors. Additionally, we analyze the resolution time, size, and distance for each error type, to see if different types of compilation errors are easier to localize or repair than others. Our results show that the resolution time, size, and distance are independent of each other. Our research also provides insights into the human effort required to fix the most common industrial compilation errors. We also identify the most promising directions for future research on fault localization., Comment: 12 pages, 10 figures, ICST 2024

We generalise the known fact that for binomial $X_{n,k} \sim \mathrm{Bin}(n, k/n)$ one has $\inf_{k>1,n} \mathrm{P}(X_{n,k} \geq k) \geq \lim_{k \to 1+}\mathrm{P}(X_{2,k} \geq k) = 1/4$ to cover probabilities of exceeding a constant shift away from the mean. The proof is very short and the theorem yields the original result as a special case, as well as proving that an analogous result holds for the Poisson distribution. We furthermore prove a similar property holds for the family of beta distributions near their mode. Thanks to the connection between Binomial and Beta distributions, this allows us to shed some further light on the original result regarding Binomial probabilities., Comment: 19 pages, 2 figures

We give a distributed variant of an adaptive histogram estimation procedure previously developed by the first author. The procedure is based on regular pavings and is known to have numerous appealing statistical and arithmetical properties. The distributed version makes it possible to process data sets significantly bigger than previously. We provide prototype implementation under a permissive license.

In this paper, we present a rigorous modular statistical approach for arguing safety or its insufficiency of an autonomous vehicle through a concrete illustrative example. The methodology relies on making appropriate quantitative studies of the performance of constituent components. We explain the importance of sufficient and necessary conditions at the component level for the overall safety of the vehicle as well as the cost-saving benefits of the approach. A simple concrete automated braking example studied illustrates how separate perception system and operational design domain statistical analyses can be used to prove or disprove safety at the vehicle level., Comment: Various minor linguistic, typographical, and notational improvements. To appear in the SAE International Journal of Connected and Automated Vehicles, 4(1):2021, doi:10.4271/12-04-01-0004

Given $n$ independent and identically distributed observations and measuring the value of obtaining an additional observation in terms of Le Cam's notion of deficiency between experiments, we show for certain types of non-parametric experiments that the value of an additional observation decreases at a rate of $1/\sqrt{n}$. This is distinct from the known typical decrease at a rate of $1/n$ for parametric experiments and the non-decreasing value in the case of very large experiments. In particular, the rate of $1/\sqrt{n}$ holds for the experiment given by observing samples from a density about which we know only that it is bounded from below by some fixed constant. Thus there exists an experiment where the value of additional observations tends to zero but for which no estimator that is consistent (in total variation distance) exists., Comment: Improved introduction as well as various minor typographic and linguistic fixes, 29 pages, 3 figures

The convex transform order is one way to make precise comparison between the skewness of probability distributions on the real line. We establish a simple and complete characterisation of when one Beta distribution is smaller than another according to the convex transform order. As an application, we derive monotonicity properties for the probability of Beta distributed random variables exceeding the mean or mode of their distribution. Moreover, we obtain a simple alternative proof of the mode-median-mean inequality for unimodal distributions that are skewed in a sense made precise by the convex transform order. This new proof also gives an analogous inequality for the anti-mode of distributions that have a unique anti-mode. Such inequalities for Beta distributions follow as special cases. Finally, some consequences for the values of distribution functions of Binomial distributions near to their means are mentioned., Comment: To appear in Statistica Neerlandica, fixed typos and small changes to comply with journal guidelines

A wide range of applications in marine ecology extensively uses underwater cameras. Still, to efficiently process the vast amount of data generated, we need to develop tools that can automatically detect and recognize species captured on film. Classifying fish species from videos and images in natural environments can be challenging because of noise and variation in illumination and the surrounding habitat. In this paper, we propose a two-step deep learning approach for the detection and classification of temperate fishes without pre-filtering. The first step is to detect each single fish in an image, independent of species and sex. For this purpose, we employ the You Only Look Once (YOLO) object detection technique. In the second step, we adopt a Convolutional Neural Network (CNN) with the Squeeze-and-Excitation (SE) architecture for classifying each fish in the image without pre-filtering. We apply transfer learning to overcome the limited training samples of temperate fishes and to improve the accuracy of the classification. This is done by training the object detection model with ImageNet and the fish classifier via a public dataset (Fish4Knowledge), whereupon both the object detection and classifier are updated with temperate fishes of interest. The weights obtained from pre-training are applied to post-training as a priori. Our solution achieves the state-of-the-art accuracy of 99.27\% on the pre-training. The percentage values for accuracy on the post-training are good; 83.68\% and 87.74\% with and without image augmentation, respectively, indicating that the solution is viable with a more extensive dataset., Comment: arXiv admin note: substantial text overlap with arXiv:1904.02768

The software industry has seen an increasing interest in test automation. In this paper, we present a test automation maturity survey serving as a self-assessment for practitioners. Based on responses of 151 practitioners coming from above 101 organizations in 25 countries, we make observations regarding the state of the practice of test automation maturity: a) The level of test automation maturity in different organizations is differentiated by the practices they adopt; b) Practitioner reported the quite diverse situation with respect to different practices, e.g., 85\% practitioners agreed that their test teams have enough test automation expertise and skills, while 47\% of practitioners admitted that there is lack of guidelines on designing and executing automated tests; c) Some practices are strongly correlated and/or closely clustered; d) The percentage of automated test cases and the use of Agile and/or DevOps development models are good indicators for a higher test automation maturity level; (e) The roles of practitioners may affect response variation, e.g., QA engineers give the most optimistic answers, consultants give the most pessimistic answers. Our results give an insight into present test automation processes and practices and indicate chances for further improvement in the present industry.

The deployment of machine learning algorithms on resource-constrained edge devices is an important challenge from both theoretical and applied points of view. In this article, we focus on resource-efficient randomly connected neural networks known as Random Vector Functional Link (RVFL) networks since their simple design and extremely fast training time make them very attractive for solving many applied classification tasks. We propose to represent input features via the density-based encoding known in the area of stochastic computing and use the operations of binding and bundling from the area of hyperdimensional computing for obtaining the activations of the hidden neurons. Using a collection of 121 real-world datasets from the UCI Machine Learning Repository, we empirically show that the proposed approach demonstrates higher average accuracy than the conventional RVFL. We also demonstrate that it is possible to represent the readout matrix using only integers in a limited range with minimal loss in the accuracy. In this case, the proposed approach operates only on small n-bits integers, which results in a computationally efficient architecture. Finally, through hardware Field-Programmable Gate Array (FPGA) implementations, we show that such an approach consumes approximately eleven times less energy than that of the conventional RVFL., Comment: 7 pages, 7 figures

Test automation is important in software industry but self-assessment instruments for assessing its maturity are not sufficient. The two objectives of this study are to synthesize what an organization should focus to assess its test automation; develop a self-assessment instrument (a survey) for assessing test automation maturity and scientifically evaluate it. We carried out the study in four stages. First, a literature review of 25 sources was conducted. Second, the initial instrument was developed. Third, seven experts from five companies evaluated the initial instrument. Content Validity Index and Cognitive Interview methods were used. Fourth, we revised the developed instrument. Our contributions are as follows: (a) we collected practices mapped into 15 KAs that indicate where an organization should focus to assess its test automation; (b) we developed and evaluated a self-assessment instrument for assessing test automation maturity; (c) we discuss important topics such as response bias that threatens self-assessment instruments. Our results help companies and researchers to understand and improve test automation practices and processes., Comment: 10 pages

Our understanding and ability to effectively monitor and manage coastal ecosystems are severely limited by observation methods. Automatic recognition of species in natural environment is a promising tool which would revolutionize video and image analysis for a wide range of applications in marine ecology. However, classifying fish from images captured by underwater cameras is in general very challenging due to noise and illumination variations in water. Previous classification methods in the literature relies on filtering the images to separate the fish from the background or sharpening the images by removing background noise. This pre-filtering process may negatively impact the classification accuracy. In this work, we propose a Convolutional Neural Network (CNN) using the Squeeze-and-Excitation (SE) architecture for classifying images of fish without pre-filtering. Different from conventional schemes, this scheme is divided into two steps. The first step is to train the fish classifier via a public data set, i.e., Fish4Knowledge, without using image augmentation, named as pre-training. The second step is to train the classifier based on a new data set consisting of species that we are interested in for classification, named as post-training. The weights obtained from pre-training are applied to post-training as a priori. This is also known as transfer learning. Our solution achieves the state-of-the-art accuracy of 99.27% accuracy on the pre-training. The accuracy on the post-training is 83.68%. Experiments on the post-training with image augmentation yields an accuracy of 87.74%, indicating that the solution is viable with a larger data set.

Phase retrieval and the twin-image problem in digital in-line holographic microscopy can be resolved by iterative reconstruction routines. However, recovering the phase properties of an object in a hologram needs an object plane to be chosen correctly for reconstruction. In this work, we present a novel multi-wavelength Gerchberg-Saxton algorithm to determine the object plane using single-shot holograms recorded with multiple wavelengths in an in-line holographic microscope. For micro-sized objects, we verify the object positioning capabilities of the method for various shapes and derive the phase information using synthetic and experimental data. Experimentally, we built a compact digital in-line holographic microscopy setup around a standard optical microscope with a regular RGB-CCD camera and acquire holograms of micro-spheres, E. coli and red blood cells, that are illuminated using three lasers operating at 491 nm, 532 nm and 633 nm, respectively. We demonstrate that our method provides accurate object plane detection and phase retrieval under noisy conditions, e.g., using low-contrast holograms without background normalization. This method allows for automatic positioning and phase retrieval suitable for holographic particle velocimetry, and object tracking in biophysical or colloidal research.

Wide field-of-view imaging of fast processes in a microscope requires high light intensities motivating the use of lasers as light sources. However, due to their long spatial coherence length lasers are inappropriate for such applications as they produce coherent noise and parasitic reflections, such as speckle, degrading image quality. Therefore, we provide a step-by-step guide for constructing a speckle-free and high contrast laser illumination setup using a rotating ground glass diffuser driven by a stepper motor. The setup is easy to build, cheap and allows a significant light throughput of 48 %, which is 40 % higher in comparison to a single lens collector commonly used in reported setups. This is achieved by using only one objective to collect the scattered light from the ground glass diffuser. We validate the stability and performance of our setup in terms of image quality, motor-induced vibrations and light throughput. To highlight the latter, we record Brownian motion of micro-particles using a 100x oil immersion objective and a high-speed camera operating at 2 000 Hz with a laser output power of only 22 mW. Moreover, by reducing the objective magnification to 50x sampling rates up to 10 000 Hz are realized. To help readers with basic or advanced optics knowledge realizing this setup we provide; a full component list, 3D-printing CAD files, setup protocol, and the code for running the stepper motor.

We present a versatile and fast MATLAB program (UmUTracker) that automatically detects and tracks particles by analyzing video sequences acquired by either light microscopy or digital in-line holographic microscopy. Our program detects the 2D lateral positions of particles with an algorithm based on the isosceles triangle transform, and reconstructs their 3D axial positions by a fast implementation of the Rayleigh-Sommerfeld model using a radial intensity profile. To validate the accuracy and performance of our program, we first track the 2D position of polystyrene particles using bright field and digital holographic microscopy. Second, we determine the 3D particle position by analyzing synthetic and experimentally acquired holograms. Finally, to highlight the full program features, we profile the microfluidic flow in a 100 micrometer high flow chamber. This result agrees with computational fluid dynamic simulations. On a regular desktop computer UmUTracker can detect, analyze, and track multiple particles at 5 frames per second for a template size of 201 x 201 in a 1024 x 1024 image. To enhance usability and to make it easy to implement new functions we used object-oriented programming. UmUTracker is suitable for studies related to: particle dynamics, cell localization, colloids and microfluidic flow measurement., Comment: Manuscript including supplementary materials

Particle tracking is common in many biophysical, ecological, and micro-fluidic applications. Reliable tracking information is heavily dependent on of the system under study and algorithms that correctly determines particle position between images. However, in a real environmental context with the presence of noise including particular or dissolved matter in water, and low and fluctuating light conditions, many algorithms fail to obtain reliable information. We propose a new algorithm, the Circular Symmetry algorithm (C-Sym), for detecting the position of a circular particle with high accuracy and precision in noisy conditions. The algorithm takes advantage of the spatial symmetry of the particle allowing for subpixel accuracy. We compare the proposed algorithm with four different methods using both synthetic and experimental datasets. The results show that C-Sym is the most accurate and precise algorithm when tracking micro-particles in all tested conditions and it has the potential for use in applications including tracking biota in their environment., Comment: Manuscript including supplementary materials

Detection of circular objects in digital images is an important problem in several vision applications. Circle detection using randomized sampling has been developed in recent years to reduce the computational intensity. Randomized sampling, however, is sensitive to noise that can lead to reduced accuracy and false-positive candidates. This paper presents a new circle detection method based upon randomized isosceles triangles sampling to improve the robustness of randomized circle detection in noisy conditions. It is shown that the geometrical property of isosceles triangles provide a robust criterion to find relevant edge pixels and thereby efficiently provide an estimation of the circle center and radii. The estimated results given by the isosceles triangles sampling from each connected component of edge map were analyzed using a simple clustering approach for efficiency. To further improve on the accuracy we applied a two-step refinement process using chords and linear error compensation with gradient information of the edge pixels. Extensive experiments using both synthetic and real images were presented and results were compared to leading state-of-the-art algorithms and showed that the proposed algorithm: are efficient in finding circles with a low number of iterations; has high rejection rate of false-positive circle candidates; and has high robustness against noise, making it adaptive and useful in many vision applications., Comment: Manuscript, 31 pages, 11 figures

Simulations of tethered cells in viscous sub-layers are frequently performed using the Stokes drag force, but without taking into account contributions from surface corrections, lift forces, buoyancy, the Basset force, the cells finite inertia, or added mass. In this work, we investigate to which extent such contributions influence, under a variety of hydrodynamic conditions, the force at the anchor point of a tethered cell and the survival probability of a bacterium that is attached to a host by either a slip or a catch bond via a tether with a few different biomechanical properties. We show that a consequence of not including some of these contributions is that the force to which a bond is exposed can be significantly underestimated; in general by ~32-46 %, where the influence of the surface corrections dominate (the parallel and normal correction coefficients contribute with ~5-8 or 23-26 %, respectively). The Basset force is a major contributor, up to 20 %, for larger cells and shear rates. The lift force and inertia contribute when cells with radii >3 micrometer reside in shear rates >2000 1/s. Buoyancy contributes significantly for cells with radii >3 micrometer in shear rates <10 1/s. Since the lifetime of a bond depends strongly on the force, both the level of approximations and the biomechanical model of the tether significantly affect the survival probability of tethered bacteria. For a cell attached with a FimH-mannose bond and an extendable tether in a shear rate of 3000 1/s, neglecting the surface correction coefficients or the Basset force can imply that the survival probability is overestimated by more than an order of magnitude. This work thus shows that in order to quantitatively assess bacterial attachment forces and survival probabilities, both the fluid forces and the tether properties need to be modeled accurately., Comment: 23 pages

Type 1 fimbriae mediate adhesion of uropathogenic Escherichia coli (UPEC) to host cells. It has been hypothesized that fimbriae can, by their ability to uncoil under exposure to force, reduce fluid shear stress on the adhesin-receptor interaction by which the bacterium adheres to the surface. In this work we develop a model that describes how the force on the adhesin-receptor interaction of a type 1 fimbriae varies as a bacterium is affected by a time dependent fluid flow mimicking in vivo conditions. The model combines in vivo hydrodynamic conditions with previously assessed biomechanical properties of the fimbriae. Numerical methods are used to solve for the motion and adhesion force under the presence of time dependent fluid profiles. It is found that a bacterium tethered with a type 1 pilus will experience significantly reduced shear stress for moderate to high flow velocities and that the maximum stress the adhesin will experience is limited to ~120 pN, which is sufficient to activate the conformational change of the FimH adhesin into its stronger state but also lower than the force required for breaking it under rapid loading. Our model thus supports the assumption that the type 1 fimbriae shaft and the FimH adhesin-receptor interaction are optimized to each other, and that they give piliated bacteria significant advantages in rapidly changing fluidic environments.

Biopolymers are vital structures for many living organisms; for a variety of bacteria, adhesion polymers play a crucial role for the initiation of colonization. Some bacteria express, on their surface, attachment organelles (pili) that comprise subunits formed into stiff helix-like structures that possess unique biomechanical properties. These helix-like structures possess a high degree of flexibility that gives the biopolymers a unique extendibility. This has been considered beneficial for piliated bacteria adhering to host surfaces in the presence of a fluid flow. We show in this work that helix-like pili have the ability to act as efficient dampers of force that can, for a limited time, lower the load on the force-mediating adhesin-receptor bond on the tip of an individual pilus. The model presented is applied to bacteria adhering with a single pilus of either of the two most common types expressed by uropathogenic Escherichia coli, P or type 1 pili, subjected to realistic flows. The results indicate that for moderate flows (~25 mm/s) the force experienced by the adhesin-receptor interaction at the tip of the pilus can be reduced by a factor of ~6 and ~4, respectively. The uncoiling ability provides a bacterium with a "go with the flow" possibility that acts as a damping. It is surmised that this can be an important factor for the initial part of the adhesion process, in particular in turbulent flows, and thereby be of use for bacteria in their striving to survive a natural defense such as fluid rinsing actions., Comment: 31 pages, 5 figures

We present a coarse grained rigid multibody model of a subunit assembled helix-like polymer, e.g., adhesion pili expressed by bacteria, that is capable of describing the polymers force-extension response. With building blocks representing individual subunits the model appropriately describes the complex behavior of pili expressed by the gram-negative uropathogenic Escherichia coli bacteria under the action of an external force. Numerical simulations show that the dynamics of the model, which include both the effects of unwinding and rewinding, are in good quantitative agreement with the characteristic force-extension response as observed experimentally for type 1 and P pili. By tuning the model, it is also possible to reproduce the force-extension response in the presence of anti-shaft antibodies, which dramatically changes the mechanical properties. Thus, the model and the results in this work give enhanced understanding of how a pilus unwinds under action of external forces and provide new perspective of the complex bacterial adhesion processes., Comment: 25 pages, 5 figures

Let $\mu^z$ be the measure obtained by sweeping out the Monge-Amp\`ere measure of the pluricomplex Green function with pole at $z. $ We prove that $\mu^z$ vanish on Levi flat parts of the boundary for 1) every relatively compact analytic polyhedron in complex space, 2) product domains of hyperconvex sets in Stein manifolds.

Let $u$ be a plurisubharmonic function, defined on a neighbourhood of a point $x,$ such that the complex Monge-Amp\`ere operator is well-defined on $u.$ Suppose also that $u$ has a weak singularity, in the sense that the Lelong number of $u$ at $x$ vanish. Is it true that the residual mass of the measure $(dd^c{u})^n$ vanish at $x$? To our knowledge there is no known example that falsifies the posed question. In this paper some partial results are obtained. We find that for a significant subset of plurisubharmonic functions with well defined Monge-Amp\`ere mass vanishing Lelong number does implies vanishing residual mass of the Monge-Amp\`ere measure.

In the paper by V.V. Nesvizhevsky et al., Phys. Rev. D 67, 102002 (2003), it is argued that the lowest quantum state of neutrons in the Earth's gravitational field has been experimentally identified. While this is most likely correct, it is imperative to investigate all alternative explanations of the result in order to close all loopholes, as it is the first experiment ever claimed to have observed gravitational quantum states. Here we show that geometrical effects in the experimental setup can mimic the results attributed to gravity. Modifications of the experimental setup to close these possible loopholes are suggested., Comment: 4 pages, to appear in Phys.Rev.D

We discuss an experiment conducted by Nesvizhevsky et al. As it is the first experiment claimed to have observed gravitational quantum states, it is imperative to investigate all alternative explanations of the result. In a student project course in applied quantum mechanics, we consider the possibility of quantummechanical effects arising from the geometry of the experimental setup, due to the "cavity" formed. We try to reproduce the experimental result using geometrical arguments only. Due to the influence of several unknown parameters our result is still inconclusive., Comment: 10 pages, 4 figures, Student project in applied quantum mechanics

Hope theory integrates the conceptualization of goals, along with the strategies to achieve those goals, and the motivation to pursue those goals. In a 6-year longitudinal study, individual differences in hope, as measured by the Hope Scale scores of entering college freshmen, predicted better overall grade point averages. Hopeful thinking in college academics is discussed. (Contains 63 references.) (GCP)