Abstract
The harbour infrastructures have some structures that still need regular inspection. However, the nature of this environment presents a number of challenges when it comes to determining an accurate vehicle position and consequently performing successful image similarity detection. In addition, the underwater environment is highly dynamic, making place recognition harder because the appearance of a place can change over time. In these close-range operations, the visual sensors have a major impact. There are some factors that degrade the quality of the captured images, but image preprocessing steps are increasingly used. Therefore, in this paper, a purely visual similarity detection with enhancement technique is proposed to overcome the inherent perceptual problems in a port scenario. Considering the lack of available data in this context and to facilitate the variation of environmental parameters, a harbour scenario was simulated using the Stonefish simulator. The experiments were performed on some predefined trajectories containing the poor visibility conditions typical of these scenarios. The place recognition approach improves the performance by up to 10% compared to the results obtained with captured images. In general, it provides a good balance in coping with turbidity and light incidence at low computational cost and achieves a performance of about 80%.

Abstract

Abstract
Smart inverter functionalities can enable higher penetration levels of inverter-based distributed energy resources. The smart inverter voltage-reactive power (Volt-VAr) control function adjusts the injection and/or absorption of reactive power as a function of the voltage at the connection point through the control curve set-points. In this work, an optimization problem is formulated to increase the photovoltaic capacity in distribution systems by determining the best Volt-VAr control curve set-points of the photovoltaic inverter.A simulation-based optimization framework is proposed, which uses the Particle Swarm Optimization algorithm in the optimization stage, while power flows are executed in the simulation stage through OpenDSS. The performance assessment is performed under a real-world distribution feeder of an Ecuadorian electric utility. The proposed method found both the maximum installed capacity of a photovoltaic power plant and the best Volt-VAr control settings for a set of candidate locations. Results showed the most suitable feeder location for the installation of a single photovoltaic power plant. Besides, the Volt-VAr control curve settings determined by the optimization method increased the maximum installed capacity by 45.21% compared to the case when the photovoltaic inverter operates with a unity power factor.

Abstract
Some structures in the harbour environment need to be inspected regularly. However, these scenarios present a major challenge for the accurate estimation of a vehicle's position and subsequent recognition of similar images. In these scenarios, visibility can be poor, making place recognition a difficult task as the visual appearance of a local feature can be compromised. Under these operating conditions, imaging sonars are a promising solution. The quality of the captured images is affected by some factors but they do not suffer from haze, which is an advantage. Therefore, a purely acoustic approach for unsupervised recognition of similar images based on forward-looking sonar (FLS) data is proposed to solve the perception problems in harbour facilities. To simplify the variation of environment parameters and sensor configurations, and given the need for online data for these applications, a harbour scenario was recreated using the Stonefish simulator. Therefore, experiments were conducted with preconfigured user trajectories to simulate inspections in the vicinity of structures. The place recognition approach performs better than the results obtained from optical images. The proposed method provides a good compromise in terms of distinctiveness, achieving 87.5% recall considering appropriate constraints and assumptions for this task given its impact on navigation success. That is, it is based on a similarity threshold of 0.3 and 12 consistent features to consider only effective loops. The behaviour of FLS is the same regardless of the environment conditions and thus this work opens new horizons for the use of these sensors as a great aid for underwater perception, namely, to avoid degradation of navigation performance in muddy conditions.

Abstract
The present paper presents the implementation of next-generation centralized Protection, Automation, and Control (PAC) solution for Medium Voltage (MV) power grids, developed in the scope of the SCALE project [1]. The main goals of the project are the development, testing, and field pilot deployment of an innovative, fully digital PAC system for Substation Automation (SAS), centralizing in a single device the functionalities of several bay-level Intelligent Electronic Devices (IED). The envisioned system, comprised of a Centralized Protection and Control (CPC) device and Merging Units (MU)/Process Interface Units (PIU), constitutes a highly flexible, resilient, future-proof solution that relies both on modern IEC 61850 standards and on legacy industrial protocols to guarantee multi-vendor interoperability and continued integration with multi-generation devices inside and outside of the substation. Centralizing SAS functionalities in a single device provides access to a wide range of data and measurements that unlocks technologically advanced substation-centric network automation applications. © The Institution of Engineering and Technology 2023.

Abstract
Energy efficiency is a non-functional requirement that developers must consider, particularly when building software for battery-operated devices like mobile ones: a long-lasting battery is an essential requirement for an enjoyable user experience.In previous studies, it has been shown that many mobile applications include inefficiencies that cause battery to be drained faster than necessary. Some of these inefficiencies result from software patterns that have been catalogued, and for which more energy-efficient alternatives are also known.The existing catalogues, however, assume as a fundamental requirement that one has access to the source code of an application in order to be able to analyse it. This requirement makes independent energy analysis challenging, or even impossible, e.g. for a mobile user or, most significantly, an App Store trying to provide information on how efficient an application being submitted for publication is.We study the viability of looking for known energy patterns in applications by decompiling them and analysing the resulting code. For this, we decompiled and analysed 420 open-source applications by extending an existing tool, which is now capable of transparently decompiling and analysing android applications. With the collected data, we performed a comparative study of the presence of four energy patterns between the source code and the decompiled code.We performed two types of analysis: (i) comparing the total number of energy pattern detections; (ii) comparing the similarity between energy pattern detections. When comparing the total number of detections in source code against decompiled code, we found that 79.29% of the applications reported the same number of energy pattern detections.To test the similarity between source code and APKs, we calculated, for each application, a similarity score based on our four implemented detectors. Of all applications, 35.76% achieved a perfect similarity score of 4, and 89.40% got a score of 3 or more out of 4. Furthermore, only two applications got a score of 0.When viewed in tandem, the results of the two analyses we performed point in a promising direction. They provide initial evidence that static analysis techniques, typically used in source code, can be a viable method to inspect APKs when access to source code is restricted, and further research in this area is worthwhile.