Abstract
The reliability of power converters in photovoltaic systems is critical to the overall system reliability. This paper proposes a novel active thermal-controlled algorithm that aims to reduce the rate of junction temperature increase, therefore, increasing the reliability of the device. The algorithm works alongside a normal perturb and observe maximum power point tracking algorithm, taking control when certain temperature criteria are met. In conjunction with a neural network, the algorithm is applied to long-term real mission profile data. This would grant a better understanding of the real-world trade-offs between energy generated and lifetime improvement when using the proposed algorithm, as well as shortening study cycle times. The neural network, when applied to 365 days of data, was 28 times faster than using standard electrothermal modeling, and the lifetime consumption was predicted with greater than 96.5% accuracy. Energy generated was predicted with greater than 99.5% accuracy. The proposed algorithm resulted in a 3.3% reduction in lifetime consumption with a 1.0% reduction in the total energy generated. There is a demonstrated trade-off between lifetime consumption reduction and energy-generated reduction. The results are also split by environmental conditions. Under very variable conditions, the algorithm resulted in a 4.4% reduction in lifetime consumption with a 1.4% reduction in the total energy generated.

Abstract
ydata-profiling is an open-source Python package for advanced exploratory data analysis that enables users to generate data profiling reports in a simple, fast, and efficient manner, fostering a standardized and visual understanding of the data. Beyond traditional descriptive properties and statistics, ydata-profiling follows a Data-Centric AI approach to exploratory analysis, as it focuses on the automatic detection and highlighting of complex data characteristics often associated with potential data quality issues, such as high ratios of missing or imbalanced data, infinite, unique, or constant values, skewness, high correlation, high cardinality, non-stationarity, seasonality, duplicate records, and other inconsistencies. The source code, documentation, and examples are available in the GitHub repository: https://github.com/ydataai/ydata-profiling.

Abstract
Offshore wind farms are becoming the main alternative to fossil fuels and the future key to mitigating climate change by achieving energy sustainability. With favorable indicators in almost every environmental index, these structures operate under varying and dynamic environmental conditions, leading to efficiency losses and sudden failures. For these reasons, it's fundamental to promote the development of autonomous solutions to monitor the health condition of the construction parts, preventing structural damage and accidents. This paper introduces a new simulation environment for testing and training autonomous inspection techniques under a more realistic offshore wind farm scenario. Combining the Gazebo simulator with ROS, this framework can include multi-robots with different sensors to operate in a customizable simulation environment regarding some external elements (fog, wind, buoyancy...). The paper also presents a use case composed of a 3D LiDAR-based technique for autonomous wind turbine inspection with UAV, including point cloud clustering, model estimation, and the preliminary results under this simulation framework using a mixed environment (offshore simulation with a real UAV platform).

Abstract
Worldwide power and energy systems are changing significantly [...]

Abstract
This paper examines the idea of Industry 4.0 from the perspective of the molds industry, a vital industry in today's industrial panorama. Several technologies, particularly in the area of machining equipment, have been introduced as a result of the industry's constant modernization. This technological diversity makes automatic interconnection with production management software extremely difficult, as each brand and model requires different, mostly proprietary, interfaces and communication protocols. In the methodology presented in this paper, a development of monitoring solutions for machining devices is defined supporting the leading equipment and operations used by molds industry companies. OPC UA is employed for high-level communication between the various systems for a standardized approach. The approach combines various machine interfaces on a single system to cover a significant subset of machining equipment currently used by the molds industry, as a key result of this paper and given the variety of monitoring systems and communication protocols. This type of all-in-one approach will provide production managers with the information they need to monitor and improve the complete manufacturing process.

Abstract
Nowadays, cities face severe problems related to traffic management and mobility in general. Therefore, technologies have been developed that can handle these situations and somehow mitigate the caused impact, such as CCTV cameras. However, the techniques for analyzing the images collected by these cameras are increasingly complex and have numerous applications, being dispersed in the literature. Therefore, this article fills an important research gap by presenting a systematic review of the literature on the possible applications of data collected from CCTV cameras and the image analysis and processing techniques that have been developed and proposed in recent years. This systematic review followed the PRISMA statement guidelines and checklist, and three databases were searched, namely Scopus, Web of Science, and Inspec. From the analysis performed, the following applications were identified: Image/video analysis and traffic estimation, pedestrian detection, traffic data analysis, and forecasting, and traffic management. Regarding the image analysis and processing techniques YOLO (only look once), GMM (Gaussian mixture method), morphological methods, fuzzy logic, and other proprietary methods stand out. After a thorough analysis of traffic data, most works still implemented relatively trivial traffic management systems to generate a series of actions to be eventually applied to traffic controllers. Additionally, it was realized that these techniques could be implemented in industrial products from a future perspective. © 2023, Aracne Editrice. All rights reserved.