Abstract
By leveraging the advances in wireless communications networks and their ubiquitous nature, sensing through communication technologies has flourished in recent years. In particular, Human-to-Machine Interfaces have been exploiting WiFi IEEE 802.11 networks to obtain information that allows Human Activity Recognition. In this paper, we propose a classification model to perform Person Identification (PI) through Body Velocity Profile time series, obtained by combining Channel State Information containing gesture knowledge from multiple Access Points. Through this model, we investigate the impact of different gestures on PI classification performance and explore how informing the model about the input gesture can enhance classification accuracy. This information may enable the network to adjust to the absence of features capable of adequately characterizing the desired classes in certain gestures. A simplified stacking model is also presented, capable of combining the softmax outputs of K previously proposed individual models. By having the individual models' evaluations of a gesture and the gesture information relating to it, the number of gestures considered was shown to significantly improve the performance of the PI classification task. This enhancement increased 17% of the average F1 scores when compared to the individual model tested on the same data.

Abstract

Abstract
Background: In many urban areas, 80% to 90% of pollutant emissions are generated by road traffic, particularly from heavy vehicles. With the anticipated surge in e-commerce logistics, the need for effective urban mobility control measures has become urgent, focusing on traffic restrictions and efficient enforcement tools. This work introduces Log-ON, a multi-stakeholder information system designed to facilitate the implementation and management of sustainable traffic restrictions. Methods: The proposed system was developed through extensive literature reviews, expert consultations, and feedback from logistics fleet managers. User-centered mock-ups were created for various stakeholders, including the public, regulatory authorities, logistics operators, and enforcement agencies, ensuring that the system effectively addresses a diverse set of needs. Results: By taking into account a wide range of influencing factors, Log-ON functions as a decision-support tool designed to optimize access restrictions for vehicles, particularly heavy vehicles, in urban environments. Conclusions: Log-ON's adoption promises significant improvements in urban mobility by reducing traffic-related pollution and fostering healthier, cleaner cities. However, traffic restrictions could increase delivery costs, potentially disrupting logistics operations. To address this, the development of new business models for last-mile delivery is essential, ensuring that sustainable traffic management strategies align with the economic challenges faced by logistics providers.

Abstract
Since creating universally capable robots is challenging for a single manufacturer, a diverse fleet of robots from various manufacturers is utilized. However, these heterogeneous fleets encounter communication and interoperability issues. As a result, there is a growing need for a standardized interface that is capable of communicating, controlling and managing a diverse fleet without these interoperability issues. This paper presents a translation software module capable of controlling an autonomous mobile robot and communicating with a ROS-based robot fleet manager using the VDA5050 Standard and exchanging information via the MQTT communication protocol, aiming at flexibility and control across different robot brands. The effectiveness of the software in controlling a mobile robot via the VDA5050 standard was demonstrated by the results. It accurately analysed data from the Robot Fleet Manager, converted it into VDA 5050 JSON messages and skilfully translated it back into ROS messages. The robot's behavior remained consistent before and after the VDA5050 implementation.

Abstract
This research examined factors that help microfinance achieve sustained poverty reduction based on a systematic literature review (SLR). A search was conducted on the SCOPUS database up to December 2023. After analyzing hundreds of documents, a subset of 30 articles was subject to in-depth analysis, exploring factors and corresponding measurement indicators for sustainable poverty reduction in microfinance contexts. This article emphasizes that sustained poverty reduction is a gradual process requiring ongoing efforts from both Microfinance Institutions (MFIs) and governments. Two key success factors are empowering borrowers and ensuring the microfinance programs themselves are profitable. When implemented in an integrated and coordinated manner, these factors can empower individuals to escape poverty by fostering self-employment and income generation, ultimately reducing dependence on external support. Additionally, the study highlights the role of personality traits in influencing long-term entrepreneurial success. The findings provide valuable tools for MFIs and policymakers. MFIs gain a practical framework to guide their interventions towards sustained poverty reduction. Policymakers can leverage the identified factors and indicators when designing and implementing microfinance policies with a long-term focus on poverty alleviation. This study breaks new ground by presenting an operational framework that categorizes and integrates two critical factor groups: empowerment and beneficiary profitability. Furthermore, it links these factors to corresponding measurement indicators within a unified framework, enabling a more holistic assessment of poverty reduction efforts. © 2024 by the authors.

Abstract
In the global transformation towards a sustainable energy system, the implementation of energy efficiency measures and demand flexibility play a crucial role. Dynamic window shading of building facades poses a great potential to reduce, shift, and modulate a building's electricity consumption by blocking solar heat gains and thereby avoiding expensive Heating, Ventilation, and Air-Conditioning (HVAC) operation to cool the building. However, the installation of dynamic facade systems is often cost-prohibitive with expensive building wiring and interconnection. An integrated direct current (DC) nanogrid is proposed instead, which eliminates any electrical interconnection, by combining all components - generation, storage, and shading element into a self-contained unit. This study seeks to assess the unique design criteria of such Integrated Facade Node (IFN) system given infrequent but high-power use, coincidence of dynamic facade operation with solar renewable photovoltaic (PV) power generation, and unusual placement of the PV generator along the building facade. Optimal IFN sizes based on a deterministic sizing algorithm for a south facing building perimeter are analyzed and installation cost savings of $64,000 (65%) for a medium office building, with the potential to increase up to 91%, are presented.