Search Results (1,293)

Semantic change detection technology based on remote sensing data holds significant importance for urban and rural planning decisions and the monitoring of ground objects. However, simple convolutional networks are limited by the receptive field, cannot fully capture detailed semantic information, and cannot effectively perceive subtle changes and constrain edge information. Therefore, a dynamic graph reasoning network with layer-by-layer semantic decomposition for semantic change detection in remote sensing data is developed in response to these limitations. This network aims to understand and perceive subtle changes in the semantic content of remote sensing data from the image pixel level. On the one hand, low-level semantic information and cross-scale spatial local feature details are obtained by dividing subspaces and decomposing convolutional layers with significant kernel expansion. Semantic selection aggregation is used to enhance the characterization of global and contextual semantics. Meanwhile, the initial multi-scale local spatial semantics are screened and re-aggregated to improve the characterization of significant features. On the other hand, at the encoding stage, the weight-sharing approach is employed to align the positions of ground objects in the change area and generate more comprehensive encoding information. Meanwhile, the dynamic graph reasoning module is used to decode the encoded semantics layer by layer to investigate the hidden associations between pixels in the neighborhood. In addition, the edge constraint module is used to constrain boundary pixels and reduce semantic ambiguity. The weighted loss function supervises and optimizes each module separately to enable the network to acquire the optimal feature representation. Finally, experimental results on three open-source datasets, such as SECOND, HIUSD, and Landsat-SCD, show that the proposed method achieves good performance, with an SCD score reaching 35.65%, 98.33%, and 67.29%, respectively. Full article

The Latin American and Caribbean (LAC) region faces persistent challenges of inequality, climate change vulnerability, and deteriorating air quality. The Aburrá Valley, where Medellín is located, is a narrow tropical valley with complex topography, strong thermal inversions, and unstable atmospheric conditions, all of which exacerbate the accumulation of pollutants. In Medellín, ${\mathrm{NO}}_2$ concentrations have remained nearly unchanged over the past eight years, consistently approaching critical thresholds, despite the implementation of air quality control strategies. These persistent high concentrations are closely linked to the variability of the atmospheric boundary layer (ABL) and are often intensified by prolonged dry periods. This study focuses on a representative street canyon in Medellín that has undergone recent urban interventions, including the construction of new public spaces and pedestrian areas, without explicitly considering their impact on ${\mathrm{NO}}_x$ dispersion. Using Computational Fluid Dynamics (CFD) simulations, this work evaluates the influence of urban morphology on ${\mathrm{NO}}_x$ accumulation. The results reveal that areas with high Aspect Ratios (AR > 0.65) and dense vegetation exhibit reduced wind speeds at the pedestrian level—up to 40% lower compared to open zones—and higher ${\mathrm{NO}}_2$ concentrations, with maximum simulated values exceeding 50 μg/m³. This study demonstrates that the design of pedestrian corridors in complex urban environments like Medellín can unintentionally create pollutant accumulation zones, underscoring the importance of integrating air quality considerations into urban planning. The findings provide actionable insights for policymakers, emphasizing the need for comprehensive modeling and field validation to ensure healthier urban spaces in cities affected by persistent air quality issues. Full article

This paper explores the impact of applying a powder additive in the form of halloysite and mullite on the thermal protection properties of a composite. The authors used CES R70 epoxy resin with CES H72 hardener, modified by varying the amount of powder additive. The composite samples were exposed to a mixture of combustible gases at a temperature of approximately 1000 °C. The primary parameters analyzed during this study were the temperature on the rear surface of the sample and the ablative mass loss of the tested material. The temperature increase on the rear surface of the sample, which was exposed to the hot stream of flammable gases, was measured for 120 s. Another key parameter considered in the data analysis was the ablative mass loss. The charred layer of the sample played a crucial role in this process, as it helped block oxygen diffusion from the boundary layer of the original material. This charred layer absorbed thermal energy until it reached a temperature at which it either oxidized or was mechanically removed due to the erosive effects of the heating factor. The incorporation of mullite reduced the rear surface temperature from 58.9 °C to 49.2 °C, and for halloysite, it was reduced the rear surface temperature to 49.8 °C. The ablative weight loss dropped from 57% to 18.9% for mullite and to 39.9% for halloysite. The speed of mass ablation was reduced from 77.9 mg/s to 25.2 mg/s (mullite) and 52.4 mg/s (halloysite), while the layer thickness loss decreased from 7.4 mm to 2.8 mm (mullite) and 4.4 mm (halloysite). This research is innovative in its use of halloysite and mullite as functional additives to enhance the ablative resistance of polymer composites under extreme thermal conditions. This novel approach not only contributes to a deeper understanding of composite behavior at high temperatures but also opens up new avenues for the development of advanced thermal protection systems. Potential applications of these materials include aerospace structures, fire-resistant components, and protective coatings in environments exposed to intense heat and flame. Full article

This study investigates the flow dynamics and local scour around a Reef Cube^® artificial reef deployed in Torbay, UK, using computational fluid dynamics. The flow is modelled using Reynolds-Averaged Navier–Stokes (RANS) equations with a k-ω SST turbulence model. A novel hydro-morphodynamic model employing the generalized internal boundary method in HELYX (OpenFOAM-based) is used to simulate scour development. Model performance was validated against experimental data for flow fields, bed shear stress, and local scour. Flow simulations across various scenarios demonstrated that parameters such as the orientation angle and arrangement of Reef Cubes significantly influence flow patterns, bed shear stress, and habitat suitability. The hydro-morphodynamic model was used to simulate scouring around a reef cube in the Torbay marine environment. Results indicate that typical tidal flow velocity flow in the region is barely sufficient to initiate sediment motion, whereas extreme flow events, represented by doubling the mean flow velocity, significantly accelerate scour development, producing holes up to ten times deeper. These findings underscore the importance of considering extreme flow conditions in scour analyses due to their potential impact on the stability and failure risk of AR projects. Full article

We developed a microscale airflow modeling system with detailed building and terrain data to better understand the urban microclimate. Building shapes and heights, and terrain elevation data were integrated to construct a high-resolution urban surface geometry. The system, based on computational fluid dynamics using OpenFOAM, can resolve complex flow structures around built environments. Inflow boundary conditions were generated using logarithmic wind profiles derived from Automatic Weather System (AWS) observations under neutral stability. After validation with wind-tunnel data for a single block, the system was applied to airflow modeling around a university campus in Seoul using AWS data from four nearby stations. The results demonstrated that the system captured key flow characteristics such as channeling, wake, and recirculation induced by complex terrain and building configurations. In particular, easterly inflow cases with high-rise buildings on the leeward side of a mountain exhibited intensified wakes and internal recirculations, with elevated centers influenced by tall structures. This modeling framework, with further development, could support diverse urban applications for microclimate and air quality, facilitating urban resilience. Full article

In this study, we examined the microclimates at eight entrances to a karst system distributed between an elevation of 812 and 906 m in Southern Spain. The karst system, characterised by subvertical open tectonic joints that form narrow shafts, developed on the slope of a mountainous area with a Mediterranean climate and strong chimney effect, resulting in an intense airflow throughout the year. The airflows modify the entrance temperatures, creating a distinctive pattern in each opening that changes with the seasons. The objective of this work is to characterise the outflows and find simple temperature-based parameters that provide information about the karst interior. The entrances were monitored for five years (2017–2022) with temperature–humidity dataloggers at different depths. Other data collected include discrete wind measurements and outside weather data. The most significant parameters identified were the characteristic temperature (T_y), recorded at the end of the outflow season, and the rate of cooling/warming, which ranges between 0.1 and 0.9 °C/month. These parameters allowed the entrances to be grouped based on the efficiency of heat exchange between the outside air and the cave walls, which depends on the rock-boundary geometry. This research demonstrates that simple temperature studies with data recorded at selected positions will allow us to understand geometric aspects of inaccessible karst systems. Dynamic high-airflow cave systems could become a natural source of evidence for climate change and its effects on the underground world. Full article

This study presents a detailed analysis of the influence of hole presence and size on the behavior of CFRP composite plates subjected to axial compression. The plates were manufactured by an autoclave method from eight-ply laminate in a symmetrical fiber arrangement [45°/−45°/90°/0°₂/90°/−45°/45°]. Four central hole plates of 0 mm (reference), 2 mm, 4 mm, and 8 mm in diameter were analyzed. Tests were conducted using a Cometech universal testing machine in combination with the ARAMIS digital image correlation (DIC) system, enabling the non-contact measurement of real-time displacements and local deformations in the region of interest. The novel feature of this work was its dual use of independent measurement methods—machine-based and DIC-based—allowing for the assessment of boundary condition effects and grip slippage on failure load accuracy. The experiments were carried out until complete structural failure, enabling a post-critical analysis of material behavior and failure modes for different geometric configurations. The study investigated load–deflection and load–shortening curves, failure mechanisms, and ultimate loads. The results showed that the presence of a hole leads to localized deformation, a change in the failure mode, and a nonlinear reduction in load-carrying capacity—by approximately 30% for the largest hole. These findings provide complementary data for the design of thin-walled composite components with technological openings and serve as a robust reference for numerical model validation. Full article

This paper presents a novel approach to determine dynamic safety and comfort zones in human–robot interactions (HRIs), with a focus on service robots operating in dynamic environments with people. The proposed proxemic model leverages the golden ratio-based comfort zone distribution and ISO safety standards to define adaptive proxemic boundaries for robots around humans. Unlike traditional fixed-threshold approaches, this novel method proposes a gradual and context-sensitive modulation of robot behaviour based on human position, orientation, and relative velocity. The system was implemented on an NVIDIA Jetson Xavier NX platform using a ZED 2i stereo depth camera Stereolabs, New York, USA and tested on two mobile robotic platforms: Go1 Unitree, Hangzhou, China (quadruped) and Scout Mini Agilex, Dongguan, China (wheeled). The initial verification of proposed proxemic model through experimental comfort validation was conducted using two simple interaction scenarios, and subjective feedback was collected from participants using a modified Godspeed Questionnaire Series. The results show that the participants felt comfortable during the experiments with robots. This acceptance of the proposed methodology plays an initial role in supporting further research of the methodology. The proposed solution also facilitates integration into existing navigation frameworks and opens pathways towards socially aware robotic systems. Full article

The numerical modelling of the melt flow in Si crystal growth plays an important role for improving the resistivity distribution of crystals grown in industrial processes. However, recent series of experiments have shown that the existing numerical model—a finite volume solver with incompressible laminar approximation of the melt flow—is not always accurate enough to describe the experimental results for 4″ crystals. To improve the simulation results, material properties have been revised. For some of them, such as the Marangoni or thermal expansion coefficients, the literature suggests different values varying by more than a factor of two. Therefore, simulations using different combinations of parameters were run to perform parameter calibration. The study demonstrated that the description of induced heat on the open melting front needs to be modified to obtain the shape of phase boundaries that provides the best agreement to the experiment. It was concluded that new values should be assigned to several material properties in the model, most importantly the Marangoni coefficient $M=-1.2·{10}^{-4}{\displaystyle \frac{\mathrm{N}}{\mathrm{m}·\mathrm{K}}}$, and that an appropriate turbulence model may help to describe the dopant transport more precisely. Full article

Unveiling temperature patterns within agricultural products remains the most important indicator for their quality assessment during post-harvest treatments. Temperature control and monitoring within vented packages is essential for preserving the quality of perishable goods, such as tomato fruits, by preventing localized temperature maxima that can accelerate spoilage. This study proposes a modeling and simulation approach to systematically investigate how ventilation design choices influence internal airflow distribution and the resulting cooling performance. Our analysis compares three distinct venting configurations (single top vent, single middle vent, and two vents) across two package boundary conditions: an open-top system allowing for dual air exits through the open top boundary and the outlet vent(s), respectively, and a closed-top system with a single exit pathway through the outlet vent(s). All scenarios are simulated to assess airflow patterns, velocity magnitudes, and temperature uniformity within different package designs. Full article

This work uses the MATLAB Reservoir Simulation Toolbox (MRST) to reduce the 3D reservoir model into a 2D version in order to investigate CO₂ storage in the Aurora model using the vertical equilibrium (VE) model. For this purpose, we used an open-source reservoir simulator, MATLAB Reservoir Simulation Toolbox (MRST). MRST is an open-source reservoir simulator, with supplementary modules added to enhance its versatility in addition to a core set of procedures. A fully implicit discretization is used in the numerical formulation of MRST-co2lab enabling the integration of simulators with vertical equilibrium (VE) models to create hybrid models. This model is then compared with the Eclipse model in terms of properties and simulation results. The relative permeability of water and gas can be compared to verify that the model fits the original Eclipse model. Comparing the fluid viscosities used in MRST and Eclipse also reveals comparable tendencies. However, reservoir heterogeneity is the reason for variations in CO₂ plume morphologies. The upper layers of the Eclipse model have lower permeability than the averaged MRST model, which has a substantial impact on CO₂ transport. According to the study, after 530 years, about 17 MT of CO₂ might be stored, whereas 28 MT might escape the reservoir, since after 530 years CO₂ plume reaches completely the open northern boundary. Additionally, a sensitivity analysis study has been conducted on permeability, porosity, residual gas saturation, rock compressibility, and relative permeability curves which are the five uncertain factors in this model. Although plume migration is highly sensitive to permeability, porosity, and rock compressibility variation, it shows a slight change with residual gas saturation and relative permeability curve in this study. Full article

This study proposes a computational framework that transforms eye-tracking analysis from statistical description to cognitive structure modeling, aiming to reveal the organizational features embedded in the viewing process. Using the designers’ observation of a traditional Chinese landscape painting as an example, the study draws on the goal-oriented nature of design thinking to suggest that such visual exploration may exhibit latent structural tendencies, reflected in patterns of fixation and transition. Rather than focusing on traditional fixation hotspots, our four-dimensional framework (Region, Relation, Weight, Time) treats viewing behavior as structured cognitive networks. To operationalize this framework, we developed a data-driven computational approach that integrates fixation coordinate transformation, K-means clustering, extremum point detection, and linear interpolation. These techniques identify regions of concentrated visual attention and define their spatial boundaries, allowing for the modeling of inter-regional relationships and cognitive organization among visual areas. An adaptive buffer zone method is further employed to quantify the strength of connections between regions and to delineate potential visual nodes and transition pathways. Three design-trained participants were invited to observe the same painting while performing a think-aloud task, with one participant selected for the detailed demonstration of the analytical process. The framework’s applicability across different viewers was validated through consistent structural patterns observed across all three participants, while simultaneously revealing individual differences in their visual exploration strategies. These findings demonstrate that the proposed framework provides a replicable and generalizable method for systematically analyzing viewing behavior across individuals, enabling rapid identification of both common patterns and individual differences in visual exploration. This approach opens new possibilities for discovering structural organization within visual exploration data and analyzing goal-directed viewing behaviors. Although this study focuses on method demonstration, it proposes a preliminary hypothesis that designers’ gaze structures are significantly more clustered and hierarchically organized than those of novices, providing a foundation for future confirmatory testing. Full article

This study investigates the performance of B-series marine propellers enhanced through geometric modifications, namely face camber ratio (FCR) and cupping percentage modifications, using a machine learning (ML)-driven optimization framework. A large dataset of over 7000 open-water propeller configurations is curated, incorporating variations in blade number, expanded area ratio (EAR), pitch-to-diameter ratio (P/D), FCR, and cupping percentage. A multi-layer artificial neural network (ANN) is trained to predict thrust, torque, and open-water efficiency (η_o) with a high coefficient of determination (R²), greater than 0.9999. The ANN is integrated into an optimization algorithm to identify optimal propeller designs for the KRISO Container Ship (KCS) using empirical constraints for cavitation and tip speed. Unlike prior studies that rely on boundary element method (BEM)-ML hybrids or multi-fidelity simulations, this study introduces a geometry-coupled analysis of FCR and cupping—parameters often treated independently—and applies empirical cavitation and acoustic (tip speed) limits to guide the design process. The results indicate that incorporating 1.0–1.5% cupping leads to a significant improvement in efficiency, up to 9.3% above the reference propeller, while maintaining cavitation safety margins and acoustic limits. Conversely, designs with non-zero FCR values (0.5–1.5%) show a modest efficiency penalty (up to 4.3%), although some configurations remain competitive when compensated by higher EAR, P/D, or blade count. The study confirms that the combination of cupping with optimized geometric parameters yields high-efficiency, cavitation-safe propellers. Furthermore, the ML-based framework demonstrates excellent potential for rapid, accurate, and scalable propeller design optimization that meets both performance and regulatory constraints. Full article

Why have thinkers like Ralph Waldo Emerson and Zhuang Zi, across different cultures, sought something beyond the self? Whether through God, nature, or abstract ideals, the longing for transcendence has been a recurring theme across philosophical and religious traditions. This impulse reflects what Aldous Huxley termed the “perennial philosophy”—the idea that all spiritual traditions share a common metaphysical core. Within this framework, Emerson and Zhuang Zi offer remarkably similar insights into the transformative power of silence and stillness. For Emerson, these quiet states connect the individual with the Over-Soul, a universal spirit that transcends the ego. For Zhuang Zi, they enable alignment with the Dao, the natural flow of the universe. In both philosophies, silence and stillness serve as transformative practices that dissolve the boundaries of the self and open it to a deeper, more unified reality. By comparing Emerson’s Over-Soul and Zhuang Zi’s Dao, this essay shows how both thinkers suggest that true peace arises not from striving but from surrendering to the quiet depths of being. Their shared emphasis on contemplative stillness reveals its enduring value as a spiritual practice across diverse philosophical landscapes. Full article

In this article, through the application of the q-Sălăgean operator associated with functions characterized by bounded boundary rotation, we propose a few new subclasses of bi-univalent functions that utilize the q-Sălăgean operator with bounded boundary rotation in the open unit disk $\mathbb{E}$. For these classes, we establish the initial bounds for the coefficients $|a_2|$ and $|a_3|$. Additionally, we have derived the well-known Fekete–Szegö inequality for this newly defined subclasses. Full article