Abstract
As connected and autonomous vehicles become more complex, protecting them against advanced cyber-attacks becomes more difficult. This paper proposes a hardware-based authentication mechanism to protect sensor data acquisition in vehicular networks and embedded systems. The scheme ensures that only authentic sensors and microcontrollers can communicate with the processing unit by adding trusted hardware components, such as trusted platform modules (TPM) and physical unclonable functions (PUF). The system uses lightweight embedded platforms, such as ESP32 and Raspberry Pi with ROS 2, which allow scalable and tamper-proof real-time communication. An exhaustive study of cryptography and hardware-based authentication systems is presented, from elliptic curve cryptography to chaotic map functions, to put the proposed solution in a proper perspective. The system is modularly extensible and adaptable to new technologies, such as blockchains and new encryption protocols, and provides a robust and future-proof solution for securing vehicles and sensor-based IoT sets.

Abstract

Abstract
Renewable Energy Communities (RECs) are a promising driver for energy system decarbonization, engaging end consumers in energy markets, promoting local renewable generation and affordability, and enhancing community resilience. This paper presents a methodology for planning REC by optimally sizing distributed energy resources (DERs), including conventional resources such as photovoltaic (PV) systems and battery energy storage systems (BESSs), but also power-to-hydrogen (P2H) systems composed of an electrolyzer (EC), hydrogen tank, and fuel cell (FC). A mixed-integer linear programming (MILP) model is used to minimize DER investments and REC operational costs, using a reduced input data set based on clustering techniques to decrease complexity and improve computational efficiency. Then, a detailed MILP operation model is used to assess the REC performance with the newly sized DERs under different scenarios using conventional indicators such as the net present value (NPV) and the payback period. A sensitivity analysis is also conducted on electricity costs, EC costs and the hydrogen selling price for an external combined heat and power (CHP) client. Results show that integrating P2H systems increases NPV and provides new revenue opportunities, thereby reinforcing their role as a complementary technology to PV and BESS within RECs.

Abstract
The rise of Connected and Autonomous Vehicles (CAVs) brings distinctive features, challenges, and opportunities which require security frameworks for real-time threat mitigation. This paper presents a Security Operations Center (SOC) designed for the Internet of Vehicles (IoV). This SOC design merges Intrusion Detection Systems (IDS) and Security Information and Event Management (STEM) systems to monitor vehicle communications and adjacent infrastructure, classify network traffic as usual or malicious, and ensure threat detection and safe mitigation. The framework also addresses the General Data Protection Regulation (GDPR), complying with data protection laws by enabling user controls and granting the right to be forgotten. Our approach is intended to be a first step in providing a comprehensive solution in network security for intelligent transportation systems, offering a foundation for future implementation and exploration of secure vehicle environments.

Abstract
This paper solves the resource-constrained project scheduling problem (RCPSP) with a satisfiability problem (SAT) solver. This paper builds further on various existing SAT models for this well-known project scheduling problem and extends them with two methods to satisfy the resource constraints. Specifically, we use the wellknown minimal forbidden sets and compare them with the so-called covers that are traditionally used in SAT implementations. Moreover, we also implement an existing binary decision trees approach under various settings and extend the model with networks with adders, so far never used for solving the RCPSP, to guarantee that resource constraints are satisfied. The algorithms are tested under different settings on a set of 13,413 project instances with diverse network and resource structures, and the experiments demonstrate that a combination of these approaches help in finding better solutions within a reasonable time. Moreover, 393 new lower bounds, 62 new upper bounds, and 290 optimally solved instances (including 18 from the PSPLIB) have been discovered, which, to the best of our knowledge, had not been found before. The strong performance of the new algorithm motivated additional experiments, and the preliminary results suggest several promising directions for future research.

Abstract
-This study focuses on providing meaningful information to vulnerable road users (VRUs) to support their objectives and perceptions while navigating urban spaces, employing a novel route planning concept. Through three focus group sessions, a comprehensive survey was conducted to identify the needs and concerns of VRUs, leading to the development of an integrated and collaborative mobile application for active mobility. The application encompasses route calculation, prioritizing safety, comfort, civic participation, and empathy. The solution aims to bridge citizen users and city managers, facilitating alerts, historical information on safety and comfort, and collaborative problem-solving and sharing of urban attractions. A prototype of the concept was developed and extensively tested by potential users, and subjective evaluation and feedback demonstrated the usefulness and added value of the integrated and collaborative approach. This study highlights the proposed solution relevance and differentiation from official alerts, user experiences, and civic participation, positioning it as a comprehensive solution for active mobility.