Abstract
In this article the influence of the maximum partition size on the performance of a discrete version of the Bat Algorithm (BA) is studied. The Bat Algorithm is a population-based meta-heuristic based on swarm intelligence developed for continuous problems with exceptional results. Thus, it has a set of parameters that must be studied in order to enhance the performance of the meta-heuristic. This paper aims to investigate whether the maximum size of the partitions used for the search operations throughout the algorithm should not also be considered as a parameter. First, a literature review was conducted, with special focus on the parameterization of the meta-heuristics and each of the parameters currently used in the algorithm, followed by its implementation in VBA in Microsoft Excel. After a thorough parameterization of the discrete algorithm, different maximum partition sizes were applied to 30 normally distributed instances to draw broader conclusions. In addition, they were also tested for different sizes of the problem to see if they had an influence on the results obtained. Finally, a statistical analysis was carried out, where it was possible to conclude that there was no maximum partition value for which superiority could be proven, and so the size of the partition should be considered a parameter in the bat algorithm and included in the parametrization of BA. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Sectorization is the partition of a set or region into smaller parts, taking into account certain objectives. Sectorization problems appear in real-life situations, such as school or health districting, logistic planning, maintenance operations or transportation. The diversity of applications, the complexity of the problems and the difficulty in finding good solutions warrant sectorization as a relevant research area. Decision Support Systems (DSS) are computerised information systems that may provide quick solutions to decision-makers and researchers and allow for observing differences between various scenarios. The paper is an overview of the development of a DSS for Sectorization, its extent, architecture, implementation steps and benefits. It constitutes a quite general system, for it handles various types of problems, which the authors grouped as (i) basic sectorization problems; (ii) sectorization problems with service centres; (iii) re-sectorization problems; and (iv) dynamic sectorization problems. The new DSS is expected to facilitate the resolution of various practitioners’ problems and support researchers, academics and students in sectorization. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
The first edition of the Implicit Author Characterization from Texts for Search and Retrieval (IACT'23) aims at bringing to the forefront the challenges involved in identifying and extracting from texts implicit information about authors (e.g., human or AI) and using it in IR tasks. The IACT workshop provides a common forum to consolidate multi-disciplinary efforts and foster discussions to identify the wide-ranging issues related to the task of extracting implicit author-related information from the textual content, including novel tasks and datasets. We will also discuss the ethical implications of implicit information extraction. In addition, we announce a shared task focused on automatically determining the literary epochs of written books.

Abstract
This paper proposes a new decentralized framework for distribution system operators (DSO) to evaluate the network feasibility of the aggregators' bids and remunerate them in case of providing network support services. Compared to other state-of-the-art approaches, this framework is characterized as being more efficient in terms of communication and computational requirements, which is a great advantage for real world applications. The new framework includes a novel optimization model to decide if aggregators' bids should be curtailed or not to ensure network security and minimize DSO costs. To evaluate and compare the proposed DSO framework against the current one, we used the IEEE 69-bus network with three aggregators of distributed energy resources (DER) from the Iberian electricity market. Our experiments show that the proposed DSO framework ensures distribution network security, while the current framework in place in the Iberian Peninsula does not. In addition, we also studied three curtailment policies for the new DSO framework. The results show that minimizing curtailment costs is the most cost-effective policy for the DSO, compared to the other two policies focused on minimizing linear and squared curtailments.

Abstract
This paper presents a proof system for reasoning about execution time bounds for a core imperative programming language. Proof systems are defined for three different scenarios: approximations of the worst-case execution time, exact time reasoning, and less pessimistic execution time estimation using amortized analysis. We define a Hoare logic for the three cases and prove its soundness with respect to an annotated cost-aware operational semantics. Finally, we define a verification conditions (VC) generator that generates the goals needed to prove program correctness, cost, and termination. Those goals are then sent to the Easycrypt toolset for validation. The practicality of the proof system is demonstrated with an implementation in OCaml of the different modules needed to apply it to example programs. Our case studies are motivated by real-time and cryptographic software.

Abstract
Unmanned Aerial Vehicles (UAVs) are increasingly used as cost-effective and flexible Wi-Fi Access Points (APs) and cellular Base Stations (BSs) to enhance Quality of Service (QoS). In disaster management scenarios, UAV-based networks provide on-demand wireless connectivity when traditional infrastructures fail. In obstacle-rich environments like urban areas, reliable high-capacity communications links depend on Line-of-Sight (LoS) availability, especially at higher frequencies. Positioning UAVs to consider obstacles and enable LoS communications represents a promising solution that requires further exploration and development. The main contribution of this paper is the Traffic- and Obstacle-aware UAV Positioning Algorithm (TOPA). TOPA takes into account the users' traffic demand and the need for LoS between the UAV and the ground users in the presence of obstacles. The network performance achieved when using TOPA was evaluated through ns-3 simulations. The results show up to 100% improvement in the aggregate throughput without compromising fairness.