Abstract
Event/data-based systems are controlled by events, their local data state may change in reaction to events. Numerous methods and notations for specifying such reactive systems have been designed, though with varying focus on the different development steps and their refinement relations. We first briefly review some of such methods, like temporal/modal logic, TLA, UML state machines, symbolic transition systems, CSP, synchronous languages, and Event-B with their support for parallel composition and refinement. We then present E. -logic for covering a broad range of abstraction levels of event/data-based systems from abstract requirements to constructive specifications in a uniform foundation. E. -logic uses diamond and box modalities over structured events adopted from dynamic logic, for recursive process specifications it offers (control) state variables and binders from hybrid logic. The semantic interpretation relies on event/data transition systems; specification refinement is defined by model class inclusion. Constructive operational specifications given by state transition graphs can be characterised by a single E. -sentence. Also a variety of implementation constructors is available in E. -logic to support, among others, event refinement and parallel composition. Thus the whole development process can rely on E. -logic and its semantics as a common basis.

Abstract
The optimal Coalition Structure Generation (CSG) problem for a given set of agents finds a partition of the agent set that maximises social welfare. The CSG problem is an NP-hard optimisation problem, where the search space grows exponentially. The exact and approximation algorithms focus on finding an optimal solution or a solution within a known bound from the optimum. However, as the number of agents increases linearly, the search space increases exponentially and a practical option here is to use heuristic algorithms. Heuristic algorithms are suitable for solving the optimisation problems because of their less computational complexity. TACOS is a heuristic method for the CSG problem that finds high-quality solutions quickly using a neighbourhood search performed with a memory. However, some of the neighbourhood searches by TACOS can be performed simultaneously. Therefore, this paper proposes a parallel version of the TACOS algorithm (P-TACOS) for the CSG problem, intending to find a better solution than TACOS. We evaluated P-TACOS using eight (8) benchmark data distributions. Results show that P-TACOS achieves better results for all eight (8) data distributions. P-TACOS achieves the highest gain, 74.23%, for the Chisquare distribution and the lowest gain, 0.01%, for the Normal distribution. We also examine how often P-TACOS generates better results than TACOS. In the best case, it generates better results for 92.30% of the time (for the Rayleigh and Agent-based Normal distributions), and in the worst case, 38.46% of the time (for the Weibull distribution).

Abstract
Modern electrical distribution networks are prone to more severe voltage fluctuations due to the presence of variable loads such as electric vehicles and renewable energy generation units. These fluctuations decrease both the quality of power and the hosting capability of the grid. In such a condition, a Dynamic Voltage Compensator (DVC) can be used to stabilize the voltage of the LV networks. DVC is generally designed to resolve voltage fluctuations reflected from MV systems maintaining the voltage on a constant value. However, it will more effectively improve the voltage quality in the grid if the reference voltage is dynamically adjusted based on measurements inside the LV system. On the other hand, the more complex measurement and coordination strategy may lead to the inapplicability of the methods. Hence, voltage reference adjustment strategies should be developed to conform to the availability of data and measurements inside the grid. Accordingly, in this paper, novel voltage reference adjustment strategies have been developed for DVC based on the measurements at the installation point of the device. In order to examine the proposed methods, they are applied to an LV grid with real measured data and the results are discussed. Based on the provided simulation results, the developed dynamic reference voltage adjustment strategies can successfully improve the quality of voltage and improve the hosting capacity of the LV network. © 2023 IEEE.

Abstract

Abstract
The study of the evacuation of buildings in emergency fire situations has deserved the attention of researchers for decades, particularly regarding the real-time guiding of occupants in their way to exit the building. However, finding solutions to guide the occupants evacuating a building requires a thorough knowledge of that domain. Using ontological models to model the knowledge of a domain allows the understanding of that domain to be shared. This paper presents an ontological model that pretends to reinforce and deepen knowledge of the domain under study and help develop solutions and systems capable of guiding the occupants during a building evacuation. The ontology was developed following the METHONTOLOGY methodology, and for implementation, the Protege tool was used. The ontological model was successfully submitted to a thorough evaluation process and is publicly available on the Web.

Abstract
The global overview of the challenges faced in trying to minimise the risks of organisations in the face of cyber-attacks is arduous for any organisation. Defining an appropriate risk management model that proactively minimises cybersecurity incidents is a critical challenge. Many malicious attacks occur daily, and there is only sometimes an adequate response. There is a significant investment in research to identify the main factors that may cause such incidents, always trying to have the most appropriate response and, consequently, potentiating the response capacity and success. At the same time, several different methodologies evaluate risk management and the maturity level of organisations. Due to the lack of predictive models based on data (evidence), there is a significant investment in research to identify the main factors that may cause such incidents, starting to design models based on AI-Artificial Intelligence. This research will go in the direction of developing a user-friendly model supporting the assessment of the methodological aspects of an organisation. © 2023, IGI Global.