Search Results (3,802)

In intelligent human–robot interaction scenarios, rapidly and accurately searching and recognizing specific targets is essential for enhancing robot operation and navigation capabilities, as well as achieving effective human–robot collaboration. This paper proposes an improved YOLO-World method with an integrated attention mechanism for text-guided object detection, aiming to boost visual detection accuracy. The method incorporates SPD-Conv modules into the YOLOV8 backbone to enhance low-resolution image processing and feature representation for small and medium-sized targets. Additionally, EMA is introduced to improve the visual feature representation guided by the text, and spatial attention focuses the model on image areas related to the text, enhancing its perception of specific target regions described in the text. The improved YOLO-World method with attention mechanism is detailed in the paper. Comparative experiments with four advanced object detection algorithms on COCO and a custom dataset show that the proposed method not only significantly improves object detection accuracy but also exhibits good generalization capabilities in varying scenes. This research offers a reference for high-precision object detection and provides technical solutions for applications requiring accurate object detection, such as human–robot interaction and artificial intelligence robots. Full article

Urban commercial streets are a crucial component of urban life, serving as the central hubs of commercial activity and providing vital spaces for both residents and visitors to engage in various activities. Walkability is commonly used as a key indicator of environmental quality, playing a significant role in improving residents’ health, community interaction, and environmental quality of life. Therefore, promoting the development of a high-quality walking environment in commercial districts is crucial for fostering urban economic growth and the creation of livable cities. However, existing studies predominantly focus on the impact of the built environment on walkability at the urban scale, with limited attention given to commercial streets, particularly the influence of their physical features on walking-need perceptions. In this study, we utilized Google Street-View Panorama (GSVP) images of the Tenjin commercial district and applied the Semantic Differential (SD) method to assess four walking-need perceptions of visual walkability perception, including usefulness, comfort, safety, and attractiveness. Additionally, deep-learning-based semantic segmentation was employed to extract and calculate the physical features of the Tenjin commercial district. Correlation and regression analysis were used to investigate the impact of these physical features on the four walking-need perceptions. The results showed that the different walking-need perceptions in the Tenjin commercial district are attractiveness > safety > comfort > usefulness. Furthermore, the results show that there are significant spatial distribution differences in walking-need perceptions in the Tenjin commercial district. Safety perception is more prominent on primary roads, all four walking-need perceptions in the secondary roads at a high level, and the tertiary roads have generally lower scores for all walking-need perceptions. The regression analysis indicates that walkable space and the landmark visibility index have a significant impact on usefulness, street cleanliness emerges as the most influential factor affecting safety, greenness is identified as the primary determinant of comfort, while the landmark visibility index exerts the greatest influence on attractiveness. This study expands the existing perspectives on urban street walkability by focusing on street-level analysis and proposes strategies to enhance the visual walkability perception of commercial streets. These findings aim to better meet pedestrian needs and provide valuable insights for future urban planning efforts. Full article

This study explores the potential of large language models as interfaces for conducting sequence analysis on log data from interactive E-Books. As studies show, qualitative methods are not sufficient to comprehensively study the process of interaction with interactive E-Books. The quantitative method of educational data mining (EDM) has been considered as one of the most promising approaches for studying learner interactions with E-Books. Recently, sequence analysis showed potential in identifying typical patterns of interaction from log data collected from the Estonian Interactive E-Book Platform Opiq, allowing one to see the types of sessions from students in different grades, clusters of students based on the amount of the content they studied, and the interaction type they preferred. The main goal of the present study is to understand how teachers can utilize insights from CustomGPT to enhance their understanding of students’ interaction strategies with digital learning environments (DLEs) such as Opiq, and what the potential areas for further development of such tools are. We specified the process for developing a chatbot for transferring teachers’ queries into sequence analysis results and gathered feedback from teachers, allowing us both to estimate current design solutions to make sequence analysis results available and to find potential vectors of its development. Participants provided explicit feedback on CustomGPT, appreciating its potential for group and individual analysis, while suggesting improvements in visualization clarity, legend design, descriptive explanations, and personalized tips to better meet their needs. Potential areas of development, such as integrating personalized learning statistics, enhancing visualizations and reports for individual progress and mitigating AI hallucinations by expanding training data, are described. Full article

This study analyzes the influence of the Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) on the Mars Environmental Dynamics Analyzer (MEDA) station located on board the Perseverance rover (Mars 2020). A novel visualization methodology was developed using a hydrodynamic towing tank and 3D-printed models created through additive manufacturing. This experimental approach, not previously applied in this context, proved to be a cost-effective alternative for studying thermal interactions while providing accurate preliminary insights into the behavior of thermal plumes under Martian-like conditions. Key factors such as the extremely low Reynolds number, an increasing temperature of the model, and atmospheric properties similar to those in Mars were incorporated. The findings suggest that the MMRTG’s thermal plume may significantly influence MEDA’s performance due to the plume’s height and its interaction with the surrounding environment. Full article

Aiming at the problems of serious information redundancy, complex inter-modal information interaction, and difficult multimodal fusion faced by the audio–visual speech recognition system when dealing with complex multimodal information, this paper proposes an adaptive fusion transformer algorithm (AFT-SAM) based on a sparse attention mechanism. The algorithm adopts the sparse attention mechanism in the feature-encoding process to reduce excessive attention to non-important regions and dynamically adjusts the attention weights through adaptive fusion to capture and integrate the multimodal information more effectively and reduce the impact of redundant information on the model performance. Experiments are conducted on the audio–visual speech recognition dataset LRS2 and compared with other algorithms, and the experimental results show that the proposed algorithm in this paper has significantly lower WERs in the audio-only, visual-only, and audio–visual bimodal cases. Full article

The Kuralay-II system (K-IIS) plays a pivotal role in modeling sophisticated nonlinear wave processes, particularly in the field of optics. This study introduces novel soliton solutions for the K-IIS, derived using the Riccati–Bernoulli sub-ODE method combined with Bäcklund transformation and conformable fractional derivatives. The obtained solutions are expressed in trigonometric, hyperbolic, and rational forms, highlighting the adaptability and efficacy of the proposed approach. To enhance the understanding of the results, the solutions are visualized using 2D representations for fractional-order variations and 3D plots for integer-type solutions, supported by detailed contour plots. The findings contribute to a deeper understanding of nonlinear wave–wave interactions and the underlying dynamics governed by fractional-order derivatives. This work underscores the significance of fractional calculus in analyzing complex wave phenomena and provides a robust framework for further exploration in nonlinear sciences and optical wave modeling. Full article

This study explores the optimization of a Cu–Al₂O₃/water hybrid nanofluid within an irregular wavy enclosure under inclined periodic MHD effects. Hybrid nanofluids, with different mixture ratios of copper (Cu) and alumina (Al₂O₃) nanoparticles in water, are used in this study. Numerical simulations using the Galerkin residual-based finite-element method (FEM) are conducted to solve the governing PDEs. At the same time, artificial neural networks (ANNs) and response surface methodology (RSM) are employed to optimize thermal performance by maximizing the average Nusselt number (Nu_av), the key indicator of thermal transport efficiency. Thermophysical properties such as viscosity and thermal conductivity are evaluated for validation against experimental data. The results include visual representations of heatlines, streamlines, and isotherms for various physical parameters. Additionally, Nu_av, friction factors, and thermal efficiency index are analyzed using different nanoparticle ratios. The findings show that buoyancy and MHD parameters significantly influence heat transfer, friction, and thermal efficiency. The addition of Cu nanoparticles improves heat transport compared to Al₂O₃ nanofluid, demonstrating the superior thermal conductivity of the Cu–Al₂O₃/water hybrid nanofluid. The results also indicate that adding Al₂O₃ nanoparticles to the Cu/water nanofluid diminishes the heat transport rate. The waviness of the geometry shows a significant impact on thermal management as well. Moreover, the statistical RSM analysis indicates a high R² value of 98.88% for the response function, which suggests that the model is well suited for predicting Nu_av. Furthermore, the ANN model demonstrates high accuracy with a mean squared error (MSE) of 0.00018, making it a strong alternative to RSM analysis. Finally, this study focuses on the interaction between the hybrid nanofluid, a wavy geometry, and MHD effects, which can optimize heat transfer and contribute to energy-efficient cooling or heating technologies. Full article

Background: In pediatric surgery, a comprehensive knowledge of the child’s anatomy is crucial to optimize surgical outcomes and minimize complications. Recent advancements in medical imaging and technology have introduced innovative tools that enhance surgical planning and decision-making. Methods: This study explores the integration of mixed reality technology, specifically the HoloLens 2 headset, for visualization and interaction with three-dimensional (3D) anatomical reconstructions obtained from computed tomography (CT) scans. Our prospective observational study, conducted at IRCCS (Scientific Hospitalization and Care Institute) Sant’Orsola-Malpighi University Hospital in Bologna, engaged ten pediatric surgeons, who assessed three types of anatomical malformations (splenic cysts, pulmonary cystic adenomatoid malformations, and pyelo-ureteral junction stenosis) and planned surgeries using both traditional 2D CT scans and 3D visualizations via HoloLens 2, followed by completing a questionnaire to evaluate the utility of each of these imaging techniques in surgical planning. Results: The statistical analysis revealed that the 3D visualizations significantly outperformed the 2D CT scans in clarity and utility (p < 0.05). The results indicated significant improvements in anatomy understanding and surgical precision. The immersive experience provided by HoloLens 2 enabled surgeons to better identify critical landmarks, understand spatial relationships, and prevent surgical challenges. Furthermore, this technology facilitated collaborative decision-making and streamlined surgical workflows. Conclusions: Despite some challenges in ease of use, HoloLens 2 showed promising results in reducing the learning curve for complex procedures. This study underscores the transformative potential of mixed reality technology in pediatric surgery, advocating for further research and development to integrate these advancements into routine clinical practice. Full article

The impact of natural hazards on the Puerto Rican electric system significantly affects the well-being of its population, particularly affecting populations in remote areas. The present study aims to identify the most affected geographic regions using a complementary approach that leverages open source governmental data. By harnessing the power of comprehensive data and utilizing a graphical analysis tool—a set of open access dashboards with maps and graphs—positive change can be fostered, providing stakeholders with comprehensive data for informed decision-making. The dashboards facilitate the identification, association, and analysis of different metrics such as customers without services, SAIDI (System Average Interruption Duration Index), SAIFI (System Average Interruption Frequency Index), and CHoLES (Customers Hours of Lost Electric Service). Additionally, the dashboard provides information on the progress of the net metering, demonstrating the rapid integration of PV (photovoltaic) and BES (battery energy storage) systems. Interactive dashboards for stakeholders to analyze key metrics such as SAIDI, SAIFI and CHoLES were designed and built using an interactive data visualization platform. Full article

The replacement of historical load-bearing wooden elements made from not commonly used species such as Populus tremula L. presents significant challenges. As these species are seldomly used in modern construction, a knowledge gap exists regarding their implementation in accordance with current building codes. This study investigates the mechanical properties of European aspen (Populus tremula L.) from central Slovakia as a potential replacement for historical structures. Notably, poplar species, including European aspen, have historically been utilized for construction across various landscapes in Europe. We conducted experimental testing on visually graded aspen timber to determine the dynamic modulus of elasticity (MOE_dyn,ultr), modulus of elasticity (MOE), modulus of rupture (MOR), and density. The results were analyzed and compared to established standards for structural timber. Notably, the 5th percentileof the strength distribution (f_0.05) was determined to be 28.78 MPa, while the characteristic strength (f_k) was 26.23 MPa, and the modulus of elasticity (E_g12) was 13.60 MPa. The correlation between MOR and dynamic MOE facilitated the determination of MOR by non-destructive testing (NDT) using the Sylvatest Duo^®. This simple linear model could grade 49% of boards into the higher strength class C30. The additional parameters and their interactions in multiregresssion models improved the predictability of the bending strength of aspen. The advanced model graded 68% of boards into C30. These characteristics, along with aspen’s growth potential, make it a promising candidate for replacing damaged structural elements in historical constructions. Our findings contribute to the understanding of the potential of European aspen as a structural timber, highlighting its viability as a fast-growing hardwood species. Full article

The technological leap in the digital age has triggered a higher demand for emotional experiences. Since vision has long been recognized as the most important source of information for people to perceive the city, the visual characteristics of the urban built environment have an important impact on the emotional experience it creates. This study takes the facades and external environments of the representative urban public building category, museums, as the research objects, to explore how different types of built environment elements that make up the museum’s facade and surrounding environment affect the people’s emotional experience by affecting the urban visual quality. Tobii Pro Fusion devices and emotion scales are used for the collection of multimodal data. A total of 298 participants aged between 20 and 25 were recruited to participate in the experiment voluntarily and 229 valid data were finally obtained. The results show that different types of museum facades and external environmental elements have different effects on visual quality and people’s emotional experience: (1) Interactive elements show the most significant impact on visual quality and emotional experience. (2) The impact of artificial elements on visual quality is related to their size and spatial composition on the museum facade. When artificial elements have uniqueness, regionality, and symbolism associated with the museum, they are more likely to trigger people’s emotional experiences. (3) Visual quality is significantly correlated with people’s emotional experience through both preconscious and conscious emotional cognition. The results reveal the impact of different types and characteristics of built environment elements on the visual quality of the urban environment and proves the important role of visual quality in students’ emotional experience, further illustrating that designing and creating a good visual environment is conducive to promoting a humanistic urban environment. Meanwhile, this study also promotes a method of urban visual quality research and evaluation from an emotional perspective, providing a more scientific and objective way for the intervention of “emotions” in built environment research. Full article

Background: Patellofemoral pain (PFP) significantly affects patients’ daily activities and consequently reduces their quality of life. Custom-made foot orthoses (FOs) are a common method of medical treatment that positively influences biomechanical factors such as the kinematics of the lower extremity and reduces pain perception in patients. However, there is a gap in research regarding the influence of different FO treatments on knee pain. Therefore, this study addresses the impact of biomechanical foot orthoses (BMFOs) and sensorimotor foot orthoses (SMFOs) on patients with foot deformity and PFP. Methods: A total of 26 participants (9 men, 17 women; 27.7 ± 10.7 years; 175.0 ± 0.1 cm; 75.7 ± 18.8 kg; BMI: 24.7 ± 5.6) took part in this randomized controlled clinical trial. In the pre-test, knee pain was evaluated using the Kujala Anterior Knee Pain Scale after the physician’s anamnesis and plantar pressure measurement. A 3-month intervention with SMFO and BMFO was performed, and weekly development was evaluated using 11-item visual analog scales (VASs). Repeated measures analyses of variance were used to assess differences between time of measurements (ToMs) and the interaction effect between ToMs and treatment groups (SMFO, BMFO). Results: Statistical analysis revealed no statistically significant interaction between ToMs and treatment groups but a significant main effect on Kujala anterior knee pain scores (M_Diff = 10.189; p = 0.014) and 12-week VAS (p = 0.001). Conclusions: The findings indicate that both treatment approaches effectively alleviated perceived knee pain in the PFP sample with foot deformity, with neither approach demonstrating superior efficacy. This trial was registered in the WHO International Clinical Trials Registry Platform (ICTRP) and German Clinical Trials Register (DRKS00035082). Full article

Developing balance and coordination skills is essential for children, especially those aged 4–8, but limited Health and Physical Education (HPE) programs in schools hinder effective training. Game-based learning and Augmented Reality (AR) technologies offer promising ways to enhance these skills by providing immersive HPE experiences. An AR exercise-game prototype was developed to train children’s balance and coordination, with 19 children aged 4 to 9 testing the prototype. Post-activity surveys revealed high engagement and interactivity ratings. The difficultly of the current prototype was found to be appropriately challenging for 4- to 6-year-olds. Feedback emphasized a preference for interactive, challenging elements, suggesting improvements in difficulty customization, visuals, and technical stability. Competitive play between multiple children testing the prototype encouraged repeated attempts, but also highlighted the need for improved tracking solutions and lab setup. Overall, the innovative design shows educational potential but requires further large-scale testing on a refined version to assess its effectiveness in balance and coordination training. Full article

The social complexity hypothesis suggests that complex social interactions drive the evolution of sophisticated communicative signals. While the relationship between social communication and the complexity of sound and color signals has been extensively studied, the correlation between social communication and movement-based visual signal complexity remains underexplored. In this study, we selected the Asian agamid lizard, Phrynocephalus vlangalii, as our model system. Through a combination of controlled experiments, behavioral observations, and signal quantification, we examined the relationship between social communications and variation in movement-based visual signals and tested our social complexity hypothesis. Our experiments revealed that males significantly decreased the tail coil duration during the mating season to deal with high social interaction. Conversely, females significantly increased the tail display duration and variation in mean tail coil amplitude in line with the intensity of parental care, and tail display duration showed a significant and positive correlation with female reproductive investment. These findings suggest that social communication plays an important role in shaping the changes in movement-based visual signals, providing new evidence for the social complexity hypothesis. Full article

Protecting cultural heritage buildings poses significant research challenges. Effective damage prevention hinges on a thorough understanding of structural behavior and the continuous monitoring of its changes over time. Advanced visualization tools are essential to provide adequate awareness of the monitoring systems installed over the years while guaranteeing a quick, basic analysis of their data. This paper addresses a crucial gap in structural health monitoring (SHM), particularly in managing complex structures and systems, by responding to the growing need for tools that not only represent 3D models enriched with heterogeneous data and metadata but also facilitate detailed analysis of sensor recordings. In response to this challenge, it proposes the integration of a 3D informational model and an interactive web-based platform for monitoring data, creating a comprehensive management tool. Piazza del Duomo UNESCO Site in Pisa serves as an ideal test case due to its historical significance, structural complexity, and the wealth of monitoring data collected over time. With their interactive architecture, the two developed integrated visualization tools that could offer an effective solution for data management and visualization in other heritage contexts, particularly in cases where the monitoring system consists of numerous sensors and has evolved substantially over the years. Full article