Cause-effect graphs are a commonly used black-box testing method, and many different algorithms for converting system requirements to cause-effect graph specifications and deriving test case suites have been proposed. However, in order to test the efficiency of black-box testing algorithms on a variety of cause-effect graphs containing different numbers of nodes, logical relations and dependency constraints, a dataset containing a collection of cause-effect graph specifications created by authors of existing papers is necessary. This paper presents CEGSet, the first collection of existing cause-effect graph specifications. The dataset contains a total of 65 graphs collected from the available relevant literature. The specifications were created by using the ETF-RI-CEG graphical software tool and can be used by future authors of papers focusing on the cause-effect graphing technique. The collected graphs can be re-imported in the tool and used for the desired purposes. The collection also includes the specification of system requirements in the form of natural language from which the cause-effect graphs were derived where possible. This will encourage future work on automatizing the process of converting system requirements to cause-effect graph specifications.

In this paper, an analysis of depolarisation in Body Area Networks for Body-to-Infrastructure communications based on a measurement campaign in the 5.8 GHz band in an indoor environment is performed. Measurements were made with an off-body antenna transmitting linearly polarised signals and dual-polarised receiving antennas carried by the user on the body. A Normal Distribution with a mean of 2.0 dB and a standard deviation of 4.3 dB is found to be the best fit for modelling cross-polarisation discrimination. The average correlation between the signals received by the orthogonally polarised antennas is below 0.5, showing that polarisation diversity can be used. A model is proposed for the average value of the standard deviation of the cross-polarisation discrimination ratio as a function of the transmitted polarisation, the mobility of users and link dynamics.

Technical advances as well as continuously evolving business demands are reshaping the need for flexible connectivity in industrial control systems. A way to achieve such needs is by using a service-oriented approach, where a connectivity service middleware provides controller as well as protocol-specific interfaces. The Message Queuing Telemetry Transport (MQTT) protocol is a widely used protocol for device-to-device communication in the Internet of Things (IoT). However it is not commonly integrated in industrial control systems. To address this gap, this paper describes the development and implementation of a prototype of a connectivity service middleware for MQTT within an industrial private control network. The prototype implementation is done in the context of an industrial controller, and used in a simulated modular automation system. Furthermore, various deployment scenarios are evaluated with respect to response time and scalability of the connectivity service.

For many years now MATLAB has been considered the academia standard when it comes to technical computing and simulation. Many university and college courses rely on multiple tool-boxes and ad-dons that MATLAB provides. With its relatively simple syntax, and large user community it has been, for so many years, a logical choice for academia. However, more often than not, students fresh out of university have been facing a new software that has very quickly become an industry standard in many areas of electrical engineering. On a simple example of DC motor control, this paper aims to showcase advantages of early adoption and using LabViewfor programming and simulation purposes in academia.

This paper analyses court cases which qualified as organised crime in Bosnia and Herzegovina (B&H). The final judgments were analysed according to the following criteria: the number of defendants; the continuity of membership within the crime organisation; the existence of criminal structure; the existence of a developed plan of activities; the type and number of the offences committed; influence on public authorities, the judiciary, and citizens; and sentences imposed on the defendants. This paper seeks to identify the extent to which court judgments are based on these criteria. A secondary analysis of the data related to the organised crime cases heard in the Court of Bosnia and Herzegovina in the period between 2015 and 2018 was conducted. This analysis encompassed 21 organised crime cases in which 27 judgments were pronounced. In the observed period (2015-2018), we identified two organised criminal groups that meet the criteria analysed. The identified number of organised criminal groups is minimal in relation to the total number of organised crime cases processed. Our findings contradict the prevailing view in public discourse that organised crime is a widespread security threat in BiH. The findings of our research demonstrated the existence of legal gaps, reflected in the lack of clear criteria on the basis of which OCGs can be distinguish from other forms of criminal activity. Legal and institutional weaknesses create opportunities for OCGs to operate and create a sense of insecurity among citizens in the already complex security environment in B&H.

Abstract: The degradation of the environment is one of the most urgent challenges today. Since the industrial revolution, we have only known the model of linear economy that deals with the relationship between growth and consumption with the creation of large amounts of waste. As an alternative, a new the concept of the mod-ern economy, the circular economy. The underlying assumptions of such a system are characterised by a ten-dency towards efficient use, and recycling and re-use of resources asit would limit the negative environmental impacts of the economy, while reducing costs in economic activities with the aim of economic growth. Our goal in this paper is to highlight the role and significance of the Circular Economy and natural resources in the process of creation of competitive advantages in a globaly connected world as well as in Bosnia and Herzegovina. Our companies have preferred the mass production method of material wealth based on the mass consumption of natural resources as the main economic development method while pursuing high economic growth and maximum economic profit. These days, this economic development method faces various limitations. Many problems, such as mass generation of wastes exceeding the natural purification capacity, enormous damage environment, deepening of natural disasters and global warming, various disputes surrounding natural resources. This analysis highlights that the use of circular economy tools can help economic policy makers and researchers to take into account the impact on the environment during strategic planning activities and projections of economic growth in BiH.

A search is presented for a heavy resonance $Y$ decaying into a Standard Model Higgs boson $H$ and a new particle $X$ in a fully hadronic final state. The full Large Hadron Collider Run 2 dataset of proton-proton collisions at $\sqrt{s}= 13$ TeV collected by the ATLAS detector from 2015 to 2018 is used, and corresponds to an integrated luminosity of 139 fb$^{-1}$. The search targets the high $Y$-mass region, where the $H$ and $X$ have a significant Lorentz boost in the laboratory frame. A novel signal region is implemented using anomaly detection, where events are selected solely because of their incompatibility with a learned background-only model. It is defined using a jet-level tagger for signal-model-independent selection of the boosted $X$ particle, representing the first application of fully unsupervised machine learning to an ATLAS analysis. Two additional signal regions are implemented to target a benchmark $X$ decay into two quarks, covering topologies where the $X$ is reconstructed as either a single large-radius jet or two small-radius jets. The analysis selects Higgs boson decays into $b\bar{b}$, and a dedicated neural-network-based tagger provides sensitivity to the boosted heavy-flavor topology. No significant excess of data over the expected background is observed, and the results are presented as upper limits on the production cross section $\sigma(pp \rightarrow Y \rightarrow XH \rightarrow q\bar{q}b\bar{b}$) for signals with $m_Y$ between 1.5 and 6 TeV and $m_X$ between 65 and 3000 GeV.

The paper evaluates statistical significance of the differences in the feature values necessary to differentiate the signals corresponding to cardiac arrhythmia (AR) and atrial fibrillation (AF). The initial set of heart rate variability (HRV) features includes time and frequency domain metrics, as well as geometric metrics based on the Poincare diagram. Due to non-uniformity of the heart rate signal, frequency domain features are calculated using two approaches: the Lomb-Scargle method for spectral analysis for non-uniform signals, and Welch method for uniform signals, but after the signal interpolation and resampling. Selection of an appropriate statistical test was depending on the distribution of feature values. Normal distribution allowed use of parametric ANOVA test and otherwise non-parametric Wilcoxon–Mann–Whitney test were used. The statistical tests indicated statistically significant difference between the two observed groups of signals of interest with respect to the evaluated feature. The success of the classification depends on the well-chosen features according to their importance. In the paper, statistical tests resulted in selection of 27 features out of the initial 51. The proposed set of features could be used for the classification between the AR and AF signals to assist diagnosis of the mentioned heart diseases.

Advances in applied mechanics have facilitated a better understanding of the recycling of heat and work in the troposphere. This goal is important to meet practical needs for better management of climate science. Achieving this objective may require the application of quantum principles in action mechanics, recently employed to analyze the reversible thermodynamics of Carnot’s heat engine cycle. The testable proposals suggested here seek to solve several problems including (i) the phenomena of decreasing temperature and molecular entropy but increasing Gibbs energy with altitude in the troposphere; (ii) a reversible system storing thermal energy to drive vortical wind flow in anticyclones while frictionally warming the Earth’s surface by heat release from turbulence; (iii) vortical generation of electrical power from translational momentum in airflow in wind farms; and (iv) vortical energy in the destructive power of tropical cyclones. The scalar property of molecular action (@t ≡ ∫mvds, J-sec) is used to show how equilibrium temperatures are achieved from statistical equality of mechanical torques (mv2 or mr2ω2); these are exerted by Gibbs field quanta for each kind of gas phase molecule as rates of translational action (d@t/dt ≡ ∫mr2ωdϕ/dt ≡ mv2). These torques result from the impulsive density of resonant quantum or Gibbs fields with molecules, configuring the trajectories of gas molecules while balancing molecular pressure against the density of field energy (J/m3). Gibbs energy fields contain no resonant quanta at zero Kelvin, with this chemical potential diminishing in magnitude as the translational action of vapor molecules and quantum field energy content increases with temperature. These cases distinguish symmetrically between causal fields of impulsive quanta (Σhν) that energize the action of matter and the resultant kinetic torques of molecular mechanics (mv2). The quanta of these different fields display mean wavelengths from 10−4 m to 1012 m, with radial mechanical advantages many orders of magnitude greater than the corresponding translational actions, though with mean quantum frequencies (v) similar to those of radial Brownian movement for independent particles (ω). Widespread neglect of the Gibbs field energy component of natural systems may be preventing advances in tropospheric mechanics. A better understanding of these vortical Gibbs energy fields as thermodynamically reversible reservoirs for heat can help optimize work processes on Earth, delaying the achievement of maximum entropy production from short-wave solar radiation being converted to outgoing long-wave radiation to space. This understanding may improve strategies for management of global changes in climate.

In the present paper, we study the high-order above-threshold ionization of noble-gas atoms using a bi-elliptic orthogonal two-color (BEOTC) field. We give an overview of the SFA theory and calculate the differential ionization rate for various values of the laser field parameters. We show that the ionization rate strongly depends on the ellipticity and the relative phase between two field components. Using numerical optimization, we find the values of ellipticity and relative phase that maximize the ionization rate at energies close to the cutoff energy. To explain the obtained results, we present, to the best of our knowledge, for the first time the quantum-orbit analysis in the BEOTC field. We find and classify the saddle-point (SP) solutions and study their contributions to the total ionization rate. We analyze quantum orbits and corresponding velocities to explain the contribution of relevant SP solutions.

In the interest of both enabling long-term autonomous monitoring of at-risk marine environments and raising awareness and capabilities among citizens, a heterogeneous system of marine robots was developed, integrated, and deployed on a mission in the Adriatic Sea. This paper details a use-case scenario for a team of marine robotic agents for the purpose of cooperative marine litter detection and mapping, while also including interested citizens in the loop and allowing them to serve as operators. Two Autonomous Surface Vehicles (ASVs), a Remotely Operated Vehicle (ROV), and a Smart Buoy were deployed in a real marine environment to demonstrate the cooperative abilities of this system.

Social networks have become an integral part of modern society, allowing users to express their thoughts, opinions, and feelings, and engage in discussions on various topics. The vast amount of user-generated content on these platforms provides a valuable source of data for sentiment analysis (SA), which is the computational analysis of opinions and sentiments expressed in text. However, most existing deep learning models for SA rely on minimizing the cross-entropy loss, which does not incorporate any knowledge of the sentiment of labels themselves. To address this limitation, a novel approach that utilizes an optimal transport-based loss function to improve sentiment analysis performance was proposed. Optimal transport (OT) metrics are fundamental theoretical properties for histogram comparison, and the proposed loss function uses the cost of the OT plan between ground truth and outputs of the classifier. The experimental results demonstrate that this approach can significantly reduce miss detections between positive and negative classes and suggest that using an OT-based loss function can effectively overcome the deficiency of existing SA models and improve their performance in real-world applications.

By creating a dependable, transparent, and cost-effective system for forecasting and ongoing environmental impact monitoring of exploration and exploitation activities in the deep sea, TRIDENT seeks to contribute to the sustainable exploitation of seabed mineral resources. In order to operate autonomously in remote locations under harsh conditions and send real-time data to authorities in charge of granting licenses and providing oversight, this system will create and integrate new technology and innovative solutions. The efficient monitoring and inspection system that will be created will abide by national and international legal frameworks. At the sea surface, mid-water, and the bottom, TRIDENT will identify all pertinent physical, chemical, geological, and biological characteristics that must be monitored. It will also look for data gaps and suggest procedures for addressing them. These are crucial actions to take in order to produce accurate indicators of excellent environmental status, statistically robust environmental baselines, and thresholds for significant impact, allowing for the standardization of methods and tools. In order to monitor environmental parameters on mining and reference areas at representative spatial and temporal scales, the project consortium will thereafter develop and test an integrated system of stationary and mobile observatory platforms outfitted with the most recent automatic sensors and samplers. The system will incorporate high-capacity data processing pipelines able to gather, transmit, process, and display monitoring data in close to real-time to facilitate prompt actions for preventing major harm to the environment. Last but not least, it will offer systemic and technological solutions for predicting probable impacts of applying the developed monitoring and mitigation techniques.

The concept of brand personality plays a crucial role in brand literature as consumers tend to anthropomorphize brands by attributing human characteristics to them. The creation of a brand personality that resonates with consumers leads to greater customer satisfaction and loyalty over the long term. This study investigates the mediating potential of brand personality dimensions, speci cally Competence and Sophistication, in the relationship between brand communication (both controlled and uncontrolled) as an antecedent and brand loyalty as an outcome. Using a sample of 340 users of a cosmetic brand, we employed structural equation modeling to analyze the data. Our results indicate that controlled communication signi cantly in uences both the Competence and Sophistication dimensions of brand personality, and that there are signi cant indirect effects of both controlled and uncontrolled communication through reference groups on loyalty mediated by personality dimensions. These ndings provide valuable insights for brand managers and marketers seeking to enhance brand loyalty by developing effective communication strategies that align with the desired brand personality dimensions.

This paper studies the dynamics of a class of host-parasitoid models with host refuge and the strong Allee effect upon the host population. Without the parasitoid population, the Beverton–Holt equation governs the host population. The general probability function describes the portion of the hosts that are safe from parasitism. The existence and local behavior of solutions around the equilibrium points are discussed. We conclude that the extinction equilibrium will always have its basin of attraction which implies that the addition of the host refuge will not save populations from extinction. By taking the host intrinsic growth rate as the bifurcation parameter, the existence of the Neimark–Sacker bifurcation can be shown. Finally, we present numerical simulations to support our theoretical findings.