Non-Intrusive Distributed Tracing of Wireless IoT Devices with the FlockLab 2 Testbed

Testbeds for wireless IoT devices facilitate testing and validation of distributed target nodes. A testbed usually provides methods to control, observe, and log the execution of the software. However, most of the methods used for tracing the execution require code instrumentation and change essential properties of the observed system. Methods that are non-intrusive are typically not applicable in a distributed fashion due to a lack of time synchronization or necessary hardware/software support. In this article, we present a tracing system for validating time-critical software running on multiple distributed wireless devices that does not require code instrumentation, is non-intrusive and is designed to trace the distributed state of an entire network. For this purpose, we make use of the on-chip debug and trace hardware that is part of most modern microcontrollers. We introduce a testbed architecture as well as models and methods that accurately synchronize the timestamps of observations collected by distributed observers. In a case study, we demonstrate how the tracing system can be applied to observe the distributed state of a flooding-based low-power communication protocol for wireless sensor networks. The presented non-intrusive tracing system is implemented as a service of the publicly accessible open source FlockLab 2 testbed.

The visualization of a graph semantics of imperative languages

This work aims to present the software support for teaching in the field of formal semantics of imperative programming languages. The main part focuses on a software tool that provides a visual representation of the individual steps of the calculation in categorical semantics, which can also be referred to as graph semantics. The use of software tools in teaching to visually represent computational steps considerably facilitates understanding by students and can also serve as a good basis for supporting distance learning. Our program works in the standard form: after reading the correct user input, a visual representation of the meaning of the program is generated in the form of a category of states, which is displayed as an oriented graph. For better extensibility, the program is implemented as a web application.

Multi-Criteria Optimization of Mechanized Earth Processes and Its Impact on Economic and Environmental Sustainability

The optimization of mechanized construction processes has a very important impact on economic and environmental sustainability. Our analyses evaluate key factors that affect the quality, environment, and economics of mechanized earth processes. This paper also presents approaches in this area in Slovakia and abroad, and existing mathematical models for the optimal design of earthmoving machinery. The main goals of our paper are the proposal of a method of machine selection for excavation including a multi-criteria optimization method with software support and application and verification of this method in a model example. A total of nine scientific methods applied in our paper are analyzed. The key results of the research work in terms of the set goals are given in the Conclusion, where the key research results are summarized. The results of the research work presented in the paper have a direct impact on economic and environmental sustainability, which can be achieved already in the phase of construction preparation. Applications of information technologies in multi-criteria optimization of the selection of construction machines for earth processes enables their use in the BIM (building information modeling) model.

Statistics Teaching Practice at Czech Universities with Emphasis on Statistical Software

This paper aims to reveal the beliefs of students and fresh university graduates about teaching statistics during their university studies with focus on using statistical software. The objective is to detect the approach of faculties to statistics education and to find out which didactic materials and teaching methods are mainly used. Students’ opinions are captured by means of a questionnaire survey and analysed both quantitatively and qualitatively. The results show the increasing importance of quantitative research and the necessity of improving statistical thinking. Unfortunately, the teaching methods used in various statistical courses are outdated and unattractive for most students. They call for an active and modern approach. Teaching statistics with the statistical software support seems to be the right way to make statistics accessible to students. The recommendation is to take students’ notions into account when preparing statistical courses.

Sustainable International Expansion via Cooperation Networks in the Manufacturing Industries

For the manufacturing industry in particular, networks lead to an increasing interaction between different actors representing a complementary response to insecurity arising from internationalization subjects. The aim of this study is to understand how cooperation networks contribute to the international sustainability of the manufacturing industry. To carry out this study, a qualitative methodology was chosen through semi-structured interviews with eight companies in the manufacturing sector from different areas. The interviews were handled with NVIVO software support. Regarding the findings, it is unanimous that cooperation networks are essential for the internationalization of the manufacturing industry. In general, the companies that participated in the study believe that the networks helped to reduce costs and to have access to certain resources that were essential for the success of internationalization. Furthermore, the findings suggest that the size of the country and the low purchasing power were some of the substantial factors that triggered the process of searching for new markets. It also became evident that there are barriers that need to be taken into account at the time of internationalization and that cooperation with other companies can help to overcome them. This study provides empirical evidence on the importance of cooperation networks for the internationalization of companies in the manufacturing industry. Furthermore, this study demonstrates the main motivations, strategies and barriers for these companies to internationalize.

SimBetaReg Web-Tool: The Easiest Way to Implement the Beta and Simplex Regression Models

When the response variable is defined on the (0,1) interval, the beta and simplex regression models are commonly used by researchers. However, there is no software support for these models to make their implementation easy for researchers. In this study, we developed a web-tool, named SimBetaReg, to help researchers who are not familiar with programming to implement the beta and simplex regression models. The developed application is free and works independently from the operating systems. Additionally, we model the incidence ratios of COVID-19 with educational and civic engagement indicators of the OECD countries using the SimBetaReg web-tool. Empirical findings show that when the educational attainment, years in education, and voter turnout increase, the incidence ratios of the countries decrease.

dfgcompare: a library to support process variant analysis through Markov models

Background Data-driven process analysis is an important area that relies on software support. Process variant analysis is a sort of analysis technique in which analysts compare executed process variants, a.k.a. process cohorts. This comparison can help to identify insights for improving processes. There are a few software supports to enable process cohort comparison based on the frequencies of process activities and performance metrics. These metrics are effective in cohort analysis, but they cannot support cohort comparison based on the probability of transitions among states, which is an important enabler for cohort analysis in healthcare. Results This paper defines an approach to compare process cohorts using Markov models. The approach is formalized, and it is implemented as an open-source python library, named dfgcompare. This library can be used by other researchers to compare process cohorts. The implementation is also used to compare caregivers’ behavior when prescribing drugs in the Stockholm Region. The result shows that the approach enables the comparison of process cohorts in practice. Conclusions We conclude that dfgcompare supports identifying differences among process cohorts.

Digital information system for inland water transport vessels based on AIS

The most important role in ensuring navigation safety on inland waterways is played by the timely provision of navigators with timely and reliable navigational, meteorological and track information, as well as safety information. To solve this problem, the complexes of automatic identification stations’ coastal and ship networks deployed currently can be used. This communication channel (with free traffic for inland waterway transport) is currently used extremely ineffectively due to a small number of serviced vessels. The article substantiates the structure of a digital information system based on deployed networks of automatic identification stations for inland navigation vessels and its functional purpose. The issues of algorithmic and software support development for the process of preparation, transmission, reception and processing of transmitted information are considered. The structure of the database and algorithms for the formalized information packets’ formation in the direction of bank-to-ship are proposed. The formats of address and broadcast messages are presented. A variant of transmitting differential corrections to ships from control-correcting stations via networks of automatic identification stations without using the currently used radio channel is considered. The options for the dialog boxes of the digital information system for the dispatcher and the navigator are given.

NUScon: a community-driven platform for quantitative evaluation of nonuniform sampling in NMR

Although the concepts of nonuniform sampling (NUS​​​​​​​) and non-Fourier spectral reconstruction in multidimensional NMR began to emerge 4 decades ago (Bodenhausen and Ernst, 1981; Barna and Laue, 1987), it is only relatively recently that NUS has become more commonplace. Advantages of NUS include the ability to tailor experiments to reduce data collection time and to improve spectral quality, whether through detection of closely spaced peaks (i.e., “resolution”) or peaks of weak intensity (i.e., “sensitivity”). Wider adoption of these methods is the result of improvements in computational performance, a growing abundance and flexibility of software, support from NMR spectrometer vendors, and the increased data sampling demands imposed by higher magnetic fields. However, the identification of best practices still remains a significant and unmet challenge. Unlike the discrete Fourier transform, non-Fourier methods used to reconstruct spectra from NUS data are nonlinear, depend on the complexity and nature of the signals, and lack quantitative or formal theory describing their performance. Seemingly subtle algorithmic differences may lead to significant variabilities in spectral qualities and artifacts. A community-based critical assessment of NUS challenge problems has been initiated, called the “Nonuniform Sampling Contest” (NUScon), with the objective of determining best practices for processing and analyzing NUS experiments. We address this objective by constructing challenges from NMR experiments that we inject with synthetic signals, and we process these challenges using workflows submitted by the community. In the initial rounds of NUScon our aim is to establish objective criteria for evaluating the quality of spectral reconstructions. We present here a software package for performing the quantitative analyses, and we present the results from the first two rounds of NUScon. We discuss the challenges that remain and present a roadmap for continued community-driven development with the ultimate aim of providing best practices in this rapidly evolving field. The NUScon software package and all data from evaluating the challenge problems are hosted on the NMRbox platform.

Rejection sampling for Bayesian uncertainty evaluation using the Monte Carlo techniques of GUM-S1

Supplement 1 to the GUM (GUM-S1) extends the GUM uncertainty framework to nonlinear functions and non-Gaussian distributions. For this purpose, it employs a Monte Carlo method that yields a probability density function for the measurand. This Monte Carlo method has been successfully applied in numerous applications throughout metrology. However, considerable criticism has been raised against the type A uncertainty evaluation of GUM-S1. Most of the criticism could be addressed by including prior information about the measurand which, however, is beyond the scope of GUM-S1. We propose an alternative Monte Carlo method that will allow prior information about the measurand to be included. The proposed method is based on a Bayesian uncertainty evaluation and applies a simple rejection sampling approach using the Monte Carlo techniques of GUM-S1. The range of applicability of the approach is explored theoretically and in terms of examples. The results are promising, leading us to conclude that many metrological applications could benefit from this approach. Software support is provided to ease its implementation.