Abstract:

As urban areas face increasing challenges, integrating smart infrastructure, particularly IoT and AI technologies, has become vital for enhancing resilience. This study focuses on Baltimore as a case study to explore how scalable and adaptable smart infrastructure solutions can address diverse urban needs within a mid-sized U.S. city. Through a comprehensive review of Baltimore’s socioeconomic indicators and the development of a composite resilience score, this paper identifies key factors that facilitate or hinder the scalability and adaptability of smart infrastructure in economically and demographically varied urban contexts. The resilience score provides a quantitative measure of urban resilience, enabling the analysis of trends and dependencies among socioeconomic indicators over time. Findings reveal critical roles for both community engagement and policy support in adapting technologies to local needs, while economic and technical factors influence the scalability of IoT and AI projects. Based on these insights, the study proposes a framework that offers practical guidance for expanding Baltimore’s smart infrastructure in ways that are economically feasible, technically viable, and socially inclusive. This framework aims to assist Baltimore’s policymakers, urban planners, and technologists in advancing resilient, scalable solutions that align with the city's unique infrastructure needs and resource constraints.

Abstract: This study explores the use of a nonlinear vibration absorber to mitigate aeroelastic effects on a wing operating near the ground. An aeroelastic model, based on a typical airfoil section, equipped with a nonlinear tuned vibration absorber (NLTVA), is established to study the interactions between the airfoil’s dynamics, aerodynamics, and the nonlinear energy dissipation mechanisms. Geometric nonlinearity is incorporated into the airfoil's dynamics to account for possible large wing deflection and rotation. The flow is modeled based on the nonlinear unsteady discrete vortex method with the ground effect simulated using the mirror image method. Stability analyses are conducted to study the influence of NLTVA parameters on flutter instability and bifurcation behavior of the airfoil near the ground. The numerical results demonstrate that the NLTVA effectively delays the onset of flutter and promotes a supercritical bifurcation in the presence of ground effect. Optimally tuning the NLTVA’s linear parameters significantly increases flutter speed, while selecting the optimal nonlinear parameter is key to preventing subcritical behavior near the ground and reducing post-flutter limit cycle oscillations amplitude. Overall, this study highlights the potential of the NLTVA in enhancing the aeroelastic stability of flying vehicles with highly flexible wings, especially under the influence of ground effects during takeoff and landing.

Abstract: Companies around the world play an important role in the economic and sustainable development of the regions or areas where they participate. In particular, SME industries are a driver of the economy, social development and environmental care in Mexico, which is why it is necessary to identify how, from the business exercise, it is possible to positively impact its environment without losing its central objective, which is the generation of profitability. In this way, the purpose of this document is to show the development of the implementation of a methodology to adapt sustainability, from the economic, social, environmental and technological point of view, of an electronic components company located in the Northern Border Region of Mexico. Regarding its methodology, it is a five-step proposal: analysis, design, development, evaluation and standardization, being a complex process marked by iterative or cyclical steps. In the case study, special attention was paid to the development of strategy and implementation of indicators. The document highlights the supporting factors and the challenges experienced. While top management support, the presence of a project team and high employee involvement were identified as key supporting factors, the lack of dedicated resources and the lack of time to implement them exert a negative influence on the development process. The results presented here should help other SMEs in developing a sustainability adaptation methodology. In conclusion, the scientific discourse on sustainability adaptation, supporting factors and relevant challenges are added.

Abstract: Transformers are essential machines in electrical energy distribution systems, which is why more efficient technologies for power transformers have been developed for decades. This has not been the case for mall transformers used in low voltage circuits, in literature there is little knowledge about his efficiency. This work seek to determine the efficiency of conventional transformers used in low voltage through a methodology that includes an analytical method and experimental tests. Three transformers in the Dominican Republic market are selected, two of 900 VA and one of 1500 VA, all step-downs of approximately 120 V/25 V. The initial load is a resistive load of 18.4 Ω. The results indicate that the efficiencies are in the range of 47 to 86.5%, considering variations in the load. The highest efficiency of the transformers was in the demand range of 12 to 24% of the nominal demand. In general, losses in the excitation branch in the core represent at least 90% of the losses, while losses in the windings represent the remaining part. Based on the results, a more exhaustive evaluation of the efficiency of small transformers is suggested, as well as economically evaluating the replacement of transformers with more efficient ones.

Abstract:

This research aimed to evaluate the comparative biogas yields of waste (peels) of selected relevant fibrous materials from the West African region: Cassava, plantain, a mixture of cassava, plantain and yam. Three models: The Boyle model, the Modified Boyle’s model, and the Buswell and Müller’s model were used to determine the theoretical maximum biomethane potentials (TMBP), while the Hohenheim biogas yield test (D-HBT) was used to undertake a batch test of anaerobic digestion. With an operating temperature of 37±0.5 ℃, the samples were co-digested with digested sewage sludge (DSS) for 39 days. Comparisons are drawn between the TBMPs and the experimental results, the experimental results of the different substrates and the experimental results and figures reported in literature. From the experimental results, plantain peels had the highest biogas yield (468±72 ml/g _oTS), followed by a mixture of yam, cassava and plantain peels (362±31 ml/g _oTS) and cassava peels obtained the least biogas yield (218±19 ml/g _oTS). TMBPS of 204.04, 209.03 and 217.45 CH₄ ml/g _oTS were obtained for plantain peels, a mixture of yam, cassava and plantain peels and cassava peels respectively, evaluated using the Boyle’s model. For all the samples, the TMBPS (205.56, 209.03 and 218.45 CH₄ ml/g _oTS respectively) obtained using the Buswell and Mueller model were slightly higher than those obtained by both the Boyle and the modified Boyle’s model (163.23, 167.22 and 174.76 CH₄ ml/g _oTS respectively).

Abstract: Accurate flow measurement is critical for hydraulic systems because it represents a crucial parameter in the control of fluid power systems and enables calculating hydraulic power when combined with pressure data, which is valuable for applications such as predictive maintenance. Existing flow sensors in fluid power systems typically operate invasively, disturbing the flow and providing inaccurate results, especially under transient conditions. A conventional method involves calculating the flow rate using the pressure difference along a pipe via the Hagen-Poiseuille law, which is limited to steady, laminar, incompressible flow. This paper presents a novel soft sensor with an analytical model for transient pipe flow based on two pressure signals, thus eliminating the need for an actual volumetric flow sensor. The soft sensor was derived in previous research and validated with a distributed parameter simulation. This work uses a constructed test rig to validate the soft sensor with real-world experiments. The results highlight the potential of the soft sensor to accurately and computationally efficiently measure transient pipe volumetric flow based on two pressure signals.

Abstract: We present a novel high-resolution complex field extraction technique utilizing the U-Net-based architecture to effectively overcome the inherent resolution limitations of polarization camera with micro-polarized array. Our method extracts high-resolution complex field information, achieving a resolution comparable to that of the original polarization camera. Enabling the parallel phase-shifting digital holography technique, we extracted high-resolution complex field information from four high-resolution phase-shifted interference patterns predicted by our network directly at the hologram plane. Being independent of numerical propagation in dataset acquisition, our network reconstructs objects at various depths without DC and conjugate noise. By training the network with real-valued interference patterns and using only a single pair of low- and high-resolution input and ground truth interference patterns, we simplify computational complexity and improve efficiency. Our simulations demonstrate the network's robustness to variations in random phase distributions and transverse shifts in the input patterns. Validation results show that images have been successfully reconstructed with improved quality and enhanced spatial resolution.

Abstract:

RF signals are widely used in various applications such as telecommunications, wireless communication systems, and radar systems. These signals can be manipulated using phase shifters that adjust the signal's phase. This adjustment is essential for beam shaping, signal cancellation, and frequency synthesis in antenna arrays. By controlling the phase of the RF signal, phase shifters help manipulate electromagnetic waves for various applications. Therefore, as Gallo points out, phase shifters are essential for manipulating and controlling high-frequency signals. This manipulation and control is essential to improving the performance of wireless communication and radar systems and can improve signal reception and transmission.The study examines different types of phase shifters, conducts a comparative analysis of different phase shifter topologies and technologies, and highlights their respective advantages and limitations in applications. In addition, the review includes a specific study of liquid metal phase shifters. Finally, the article outlines future research directions for liquid metal phase shifters, It emphasizes the need for innovative design strategies to keep pace with the evolving wireless communications and telecommunications fields. Therefore, this article can serve as a reference for the milestones in RF phase shifter research.

Abstract: Precision depth estimation plays a key role in many applications, including 3D scene reconstruction, virtual reality, autonomous driving and human-computer interaction. Recent advancements in deep learning technologies, the monocular depth estimation has surpassed the traditional stereo camera systems, bringing new possibilities in 3D sensing. In this paper, by using single camera, we propose an end-to-end supervised monocular depth estimation autoencoder which contains a CNN-ViT encoder and an adaptive fusion decoder, to obtain high-precision depth maps. In the CNN-ViT encoder, we construct a multi-scale feature extractor by mixing residual configurations of vision transformers to enhance both local and global information. In the adaptive fusion decoder, we introduce adaptive fusion modules to effectively merge features of the encoder and decoder together. Lastly, the model is trained using a loss function that aligns with human perception to enable it to focus on the depth values of foreground objects. Experimental results demonstrate the effective prediction of the depth map from a single-view color image by the proposed RVTAF autoencoder.

Abstract: Results suggest that the Grand Inga project will be resilient to negative climate impacts during its initial phases (1-5). The system demonstrates security and insensitivity to adverse changes, both for existing (Phase 1-2) and planned (Phase 3-5) hydropower components. The study indicates that climate change effects become apparent only in later phases (6-8), with predominantly positive impacts, potentially increasing the generation potential of the hydropower system. Overall, the Grand Inga hydropower project appears robust against adverse climate influences throughout the majority of its development phases.