Search Results (40)

The rise of digital platforms has transformed heritage interpretation from a single official narrative to multi-stakeholder participation. This study investigates how such platforms mediate the formation of a sense of place at the Kulangsu World Heritage Site (WHS). Data were collected from official narrative texts and user-generated content (UGC) on Dianping and Ctrip, and analyzed using high-frequency word statistics and semantic network analysis. The results reveal a clear divergence between official narratives, which emphasize Outstanding Universal Value (OUV), and tourist perceptions, which focus on visual landmarks and “check-in” practices shaped by the “digital gaze.” Moreover, the sense of place is shown to be a dynamic process, co-constructed through pre-visit expectations, on-site experiences, and post-visit reflections. The findings also highlight a transformation in tourists’ roles, shifting from passive cultural consumers to active participants in the co-construction of heritage values, with digital platforms serving as critical mediators. Theoretically, the study advances digital heritage scholarship by clarifying the mechanism of the digital gaze and the dynamic nature of sense of place. Practically, it underscores the importance of integrating official narratives with UGC to strengthen OUV communication, foster broader public engagement, and support the sustainable development of WHSs. Full article

As smart campus construction continues to advance, traditional safety monitoring and environmental sensing systems are increasingly showing limitations in sensitivity, anti-interference capability, and deployment flexibility. Optical fiber sensing (OFS) technology, with its advantages of high sensitivity, passive operation, immunity to electromagnetic interference, and long-distance distributed sensing, provides a novel solution for real-time monitoring and early warning of critical campus infrastructure. This review systematically examines representative applications of OFS technology in smart campus scenarios, including structural health monitoring of academic buildings, laboratory environmental sensing, and intelligent campus security. By analyzing the technical characteristics of various types of optical fiber sensors, the paper explores emerging developments and future potential of OFS in supporting intelligent campus construction. Finally, the feasibility of building data acquisition, transmission, and visualization platforms based on OFS systems is discussed, highlighting their promising roles in campus safety operations, the integration of teaching and research, and intelligent equipment management. Full article

Mid-infrared passive spectroscopic imaging is a novel non-invasive and remote sensing method based on Planck’s law. It enables the acquisition of component-specific information from the human body by measuring naturally emitted thermal radiation in the mid-infrared region. Unlike active methods that require an external light source, our passive approach harnesses the body’s own emission, thereby enabling safe, long-term monitoring. In this study, we successfully demonstrated the simultaneous, non-invasive measurements of blood glucose and lactate levels of the human body using this method. The measurements, conducted over approximately 80 min, provided emittance data derived from mid-infrared passive spectroscopy that showed a temporal correlation with values obtained using conventional blood collection sensors. Furthermore, to evaluate localized metabolic changes, we performed k-means clustering analysis of the spectral data obtained from the upper arm. This enabled visualization of time-dependent lactate responses with spatial resolution. These results demonstrate the feasibility of multi-component monitoring without physical contact or biological sampling. The proposed technique holds promise for translation to medical diagnostics, continuous health monitoring, and sports medicine, in addition to facilitating the development of next-generation healthcare technologies. Full article

Desert encroachment significantly threatens the living and activity space of humanity, and undertaking human-directed vegetation restoration is one of the effective ways to prevent desert expansion. In the process of desert vegetation restoration, counting the number of tree saplings for rapidly assessing the survival rate of vegetation (such as Haloxylon ammodendron) is a critical task within the restoration process. However, traditional ground-based statistical methods are resource-intensive and time-consuming. This paper proposed a novel unsupervised fine segmentation framework driven by Grounding DINO prompt generation and optimization segment anything model, termed GDPGO-SAM, designed for the segmentation of desert vegetation from UAV-derived remote sensing imagery, thereby facilitating the rapid inventory of tree saplings counts. The framework combines the Grounding DINO object detector and the pre-trained visual model SAM, employing a task-prior-based prompt optimization mechanism to effectively capture the innate features of desert vegetation. This method achieves zero-sample instance segmentation of desert vegetation with an overall accuracy (OA) of 96.56%, a mean Intersection over Union (mIoU) of 81.50%, and a kappa coefficient (kappa) of 0.782, successfully overcoming the limitations of traditional supervised models that rely on passive memorization rather than true recognition. This research significantly enhances the precision of vegetation extraction and canopy depiction, providing strong support for the management of desert vegetation restoration and combating desert expansion. Full article

In this narrative historical review, we take a closer look at the role of tactile/haptic stimulation in enhancing people’s immersion (and sense of presence) in a variety of entertainment experiences, including virtual reality (VR). An important distinction is highlighted between those situations in which digital tactile stimulation and/or haptic feedback are delivered to those (i.e., users/audience members) who passively experience the stimulation and those cases, including VR, where the user actively controls some aspects of the tactile stimulation/haptic feedback that they happen to be experiencing. A further distinction is drawn between visual and/or auditory VR, where some form of tactile/haptic stimulation is added, and what might be classed as genuinely haptic VR, where the active user/player experiences tactile/haptic stimulation that is effortlessly interpreted in terms of the objects and actions in the virtual world. We review the experimental evidence that has assessed the impact of adding a tactile/haptic element to entertainment experiences, including those in VR. Finally, we highlight some of the key challenges to the growth of haptic VR in the context of multisensory entertainment experiences: these include those of a technical, financial, psychological (namely, the fact that tactile/haptic stimulation often needs to be interpreted and can reduce the sense of immersion in many situations), psycho-physiological (such as sensory overload or fatigue), physiological (e.g., relating to the large surface area of the skin that can potentially be stimulated), and creative/artistic nature. Full article

To enhance the synchronous detection of the horizontal and vertical positions of the torch in swing arc narrow gap welding, a torch pose detection (TPD) method is proposed. This approach utilizes passive visual sensing to capture images of the arc on the groove sidewall, using advanced image processing methods to extract and fit the arc contour. The coordinates of the arc contour center point and the highest point are determined through the arc contour fitting line. The torch center position is calculated from the average horizontal coordinates of the arc contour centers in adjacent welding images, while the height position is determined from the vertical coordinate of the arc’s highest point. Experimental validation in both variable and constant groove welding conditions demonstrated the TPD method’s accuracy within 0.32 mm for detecting the torch center position. This method eliminates the need to construct the wire centerline, which was a requirement in previous approaches, thereby reducing the impact of wire straightness on detection accuracy. The proposed TPD method successfully achieves simultaneous detection of the torch center and height positions, laying the foundation for intelligent detection and adaptive control in swing arc narrow gap welding. Full article

With the rapid development of vision sensing, artificial intelligence, and robotics technology, one of the challenges we face is installing more advanced vision sensors on welding robots to achieve intelligent welding manufacturing and obtain high-quality welding components. Depth perception is one of the bottlenecks in the development of welding sensors. This review provides an assessment of active and passive sensing methods for depth perception and classifies and elaborates on the depth perception mechanisms based on monocular vision, binocular vision, and multi-view vision. It explores the principles and means of using deep learning for depth perception in robotic welding processes. Further, the application of welding robot visual perception in different industrial scenarios is summarized. Finally, the problems and countermeasures of welding robot visual perception technology are analyzed, and developments for the future are proposed. This review has analyzed a total of 2662 articles and cited 152 as references. The potential future research topics are suggested to include deep learning for object detection and recognition, transfer deep learning for welding robot adaptation, developing multi-modal sensor fusion, integrating models and hardware, and performing a comprehensive requirement analysis and system evaluation in collaboration with welding experts to design a multi-modal sensor fusion architecture. Full article

Semiconductor electronics is transforming computing, communication, energy harvesting, automobiles, biotechnology, and other electronic device landscapes. This transformation has been brought about by the ability to sense, receive, manipulate, and transmit data from the diverse systems of vertical stacks of semiconductor layers and microdevices. Though the discrete design details of each semiconductor may be extremely complex, the fundamental processing steps of each semiconductor device align well with the photolithography procedure. When these semiconductor layers are stacked using photolithography, the signal noise between the device features and layers is restricted by passivation or dielectric insulation provided by SiO₂ layers. Depending on the type of functionality and the data-sensing mechanism of the semiconductors used, SiO₂ layers have an intended fitness for their purpose. The purpose of SiO₂ layers can be summarized as the encapsulation of the semiconductor device, making part of the semiconductor layer inert, i.e., passivated, creating a hard mask to negate the impact of subsequent processes like ion implantation or diffusion, insulating a part of the layer as in an intermetallic dielectric or gate dielectric, and improving adhesion of the subsequent deposition. The functionality of the adhesion of SiO₂ is by far a less-studied area. The adhesive characteristics of SiO₂ for subsequent deposition and the thickness of SiO₂ affect stress distribution. Stresses due to SiO₂ thin films, which can range from a few nanometers to a few microns thick depending on the functionality, are modeled in this research. The stresses in SiO₂ films may cause delamination or discontinuity, affecting the performance and reliability of the optical or semiconductor devices they are built into. The classical molecular dynamics (MD) simulation technique was employed to investigate the stress characteristics of deposited films by leveraging the outcomes of atomistic modeling. A cluster made of fused silica was employed as a substrate. For the simulation of the SiO₂ deposition process, silicon atoms with high energies and low-energy oxygen atoms were injected. This model was carefully controlled to ensure the stoichiometric conditions. In this analysis, we used the open-source code LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) and the Ovito (Open Visualization) tool. The research in this paper focuses on SiO₂ thin-film simulation to validate analytical and experimental stress. Full article

Mobile service robots often have to work in dynamic and cluttered environments. Multiple safety hazards exist for robots in such work environments, which visual sensors may not detect in time before collisions or robotic damage. An alternative hazard alert system using tactile methods is explored to pre-emptively convey surrounding spatial information to robots working in complex environments or under poor lighting conditions. The proposed method for robot-inclusive tactile paving is known as Passive Auto-Tactile Heuristic (PATH) tiles. These robot-inclusive tactile paving tiles are implemented in spatial infrastructure and are aimed to allow robots to pre-emptively recognize surrounding hazards even under poor lighting conditions and potentially provide improved hazard cues to visually impaired people. A corresponding Tactile Sensing Module (TSM) was used for the digital interpretation of the PATH tiles and was mounted onboard a mobile audit robot known as Meerkat. The experiment yielded a 71.6% improvement in pre-emptive hazard detection capabilities with the TSM using a customized Graph Neural Network (GNN) model. Full article

The use of photogrammetry technology for aboveground biomass (AGB) stock estimation in tropical savannas is a challenging task and is still at a preliminary stage. This work aimed to use metrics derived from point clouds, constructed using photogrammetric imaging obtained by an RGB camera on board a remotely piloted aircraft (RPA), to generate a model for estimating AGB stock for the shrubby-woody stratum in savanna areas of Central Brazil (Cerrado). AGB stock was estimated using forest inventory data and an allometric equation. The photogrammetric digital terrain model (DTM) was validated with altimetric field data, demonstrating that the passive sensor can identify topographic variations in sites with discontinuous canopies. The inventory estimated an average AGB of 18.3 (±13.3) Mg ha⁻¹ at the three sampled sites. The AGB model selected was composed of metrics used for height at the 10th and 95th percentile, with an adjusted R² of 93% and a relative root mean squared error (RMSE) of 16%. AGB distribution maps were generated from the spatialization of the metrics selected for the model, optimizing the visualization and our understanding of the spatial distribution of forest AGB. The study represents a step forward in mapping biomass and carbon stocks in tropical savannas using low-cost remote sensing platforms. Full article

The employment of unmanned aerial vehicles (UAVs) has greatly facilitated the lives of humans. Due to the mass manufacturing of consumer unmanned aerial vehicles and the support of related scientific research, it can now be used in lighting shows, jungle search-and-rescues, topographical mapping, disaster monitoring, and sports event broadcasting, among many other disciplines. Some applications have stricter requirements for the autonomous positioning capability of UAV clusters, requiring its positioning precision to be within the cognitive range of a human or machine. Global Navigation Satellite System (GNSS) is currently the only method that can be applied directly and consistently to UAV positioning. Even with dependable GNSS, large-scale clustering of drones might fail, resulting in drone cluster bombardment. As a type of passive sensor, the visual sensor has a compact size, a low cost, a wealth of information, strong positional autonomy and reliability, and high positioning accuracy. This automated navigation technology is ideal for drone swarms. The application of vision sensors in the collaborative task of multiple UAVs can effectively avoid navigation interruption or precision deficiency caused by factors such as field-of-view obstruction or flight height limitation of a single UAV sensor and achieve large-area group positioning and navigation in complex environments. This paper examines collaborative visual positioning among multiple UAVs (UAV autonomous positioning and navigation, distributed collaborative measurement fusion under cluster dynamic topology, and group navigation based on active behavior control and distributed fusion of multi-source dynamic sensing information). Current research constraints are compared and appraised, and the most pressing issues to be addressed in the future are anticipated and researched. Through analysis and discussion, it has been concluded that the integrated employment of the aforementioned methodologies aids in enhancing the cooperative positioning and navigation capabilities of multiple UAVs during GNSS denial. Full article

The San Andrés landslide on El Hierro (Canary Islands) represents a rare opportunity to study an incipient volcanic island flank collapse with an extensive onshore part. The presented research improves the knowledge of the internal structure and rock characteristics of a mega-landslide before its complete failure. The investigation combines multiple geophysical measurement techniques (active and passive seismic) and remotely sensed, high spatial resolution surveys (unmanned aerial vehicle) with in situ and laboratory geotechnical descriptions to characterize the rock properties inside and outside the San Andrés landslide. The available geophysical and geological data have been integrated into 3D geomodels to enhance their visual interpretation. The onshore geophysical investigations helped detect the possible San Andrés landslide sliding surfaces at depths between 320 m and 420 m, with a rather planar geometry. They also revealed that rocks inside and outside of the landslide had similar properties, which suggests that the previous fast movements of the landslide did not affect the bulk properties of the displaced rocks as the failure chiefly occurred along the weakened sliding plane. Uniaxial strength tests on basalt rocks further indicate a high variability and spatial heterogeneity of the rock strength properties due to the different types of volcanic rocks and their texture. The new information on the rock properties and structural setting of the San Andrés landslide can now be used to develop realistic geotechnical slope models of the onshore part of the flank collapse that are possibly applicable for slope stability or deformation calculations. It will also help assess related hazards marked by a low occurrence probability and a high impact potential. Full article

Hydrogen, due to corrosion processes, can degrade high strength steels (HSS) through embrittlement and stress corrosion cracking mechanisms. Scanning Kelvin probe (SKP) mapping of surface potential was applied, to visualize the locations with an increased subsurface concentration of hydrogen in mild steel and martensitic HSS. This work can help to determine the reasons behind hydrogen localization in a steel microstructure, leading to embrittlement and hydrogen-assisted cracking. Cathodic charging was used to insert hydrogen, which decreased the steel potential. Hydrogen effusion in air passivates steel, increasing the potential of HSS and mild steel. The passivation of steels was monitored depending on different conditions of cathodic pre-charging and the amount of absorbed hydrogen. The SKP could determine the area of diffusible hydrogen and the area of cracks. In addition, low potential locations linked to the hydrogen trapped in the deformed HSS microstructure were also determined, which delayed the steel passivation. Mild steel showed a uniform potential distribution related to interstitial hydrogen, without potential extremes attributed to locally accumulated hydrogen. Thus, SKP sensing can detect locations containing increased concentrations of hydrogen and sensitive to steel cracking. Full article

For obtaining a spatial map of the distribution of nitrogen nutrients from oil palm plantations, a quite complex Leaf Sampling Unit (LSU) is required. In addition, sample analysis in the laboratory is time consuming and quite expensive, especially for large plantation areas. Monitoring the nutrition of oil palm plants can be achieved using remote-sensing technology. The main obstacles of using passive sensors in multispectral imagery are cloud cover and shadow noise. This research used C-SAR Sentinel equipped with active sensors that can overcome cloud barriers. A model to estimate leaf nitrogen nutrient status was constructed using random forest regression (RFR) based on multiple polarization (VV-VH) and local incidence angle (LIA) data on Sentinel-1A imagery. A sample of 1116 LSU data from different islands (i.e., Sumatra, Java, and Kalimantan) was used to develop the proposed estimation model. The performance evaluation of the model obtained the averaged MAPE, correctness, and MSE of 9.68%, 90.32% and 11.03%, respectively. Spatial maps of the distribution of nitrogen values in certain oil palm areas can be produced and visualized on the web so that they can be accessed easily and quickly for various purposes of oil palm management such as fertilization planning, recommendations, and monitoring. Full article

Current literature and guidelines on sustainable design often debate on the advantages of natural ventilation (NV) and mechanical ventilation (MV) on indoor environment and energy consumption. The present systematic review explores the existing literature comparing NV and MV on the indoor comfort and well-being points of view. The findings emphasize that thermo-hygrometric comfort is the main driver of occupants’ ventilation behavior, while ventilation design is mainly led by indoor air quality targets. Moreover, more recent papers (especially after COVID-19 outbreak) emphasize the necessity of a health-based approach, contrasting airborne pathogens transmission. In this sense, MV is more frequently recommended in public spaces, while hybrid ventilation (HV) is often suggested as a solution to both ensure proper indoor conditions and energy savings. The concept of well-being is currently under-explored, as the present literature only refers to comfort. The same happens with topics such as visual, acoustic, and multi-domain comfort, as well as passive techniques such as night cooling, or analysis of specific environments such as healthcare facilities. Current knowledge would benefit from an expansion of future research in these directions. The choice of the best ventilation solution cannot ignore the context, type, and condition of energy efficient buildings, in order to properly take into account occupants’ well-being. Full article