Search Results (96)

This study analyzes hydrodynamics and mass transfer in a packed-bed reactor (PBR) by comparing two representations of bed geometry. The first is a pseudo-homogeneous approach using effective parameters, such as a radial porosity distribution. The second is a heterogeneous approach with resolved particles in the CAD domain. Both models simulate single-phase flow and mass transfer of urea and NH₃ for an enzymatic reaction across a wide Reynolds number range $\left(5\le {\mathrm{Re}}_p\le 750\right)$. The pseudo-homogeneous model incorporated a detailed porosity distribution, derived from the heterogeneous model’s solids layout, which aligned well with literature, including classical correlations for radial porosity in packed beds. Additionally, hydrodynamic predictions were benchmarked against established pressure-drop correlations for confined packed beds, supporting the physical consistency of the particle-resolved framework. This non-uniform porosity informed local variations in permeability and dispersion coefficients. Velocity, pressure, and concentration fields from both approaches were compared to quantify predictive quality. Results indicate that a well-configured pseudo-homogeneous model can closely match heterogeneous model predictions, achieving similar accuracy in many flow regimes, with accumulated average relative errors below 8%. However, its performance varies with flow conditions. The optimal pseudo-homogeneous model (showing the highest predictive consistency with the particle-resolved simulations) was then used for transient simulations. These dynamic results support the preliminary sizing and conceptual design of a device for nutrient recovery from human urine for agricultural use, demonstrating the utility of simplified models for complex reactor design while acknowledging that full experimental validation under real urine-matrix conditions remains beyond the scope of the present study. Full article

Eye tracking in virtual reality (VR) head-mounted displays poses substantial engineering challenges, particularly under immersive display configurations with large fields of view (FOV), where optical layout, illumination, and image acquisition impose nontrivial system constraints. To address these design constraints, we present an integrated near-eye eye-tracking prototype tailored for immersive VR headsets, combining customized hardware components and a real-time software pipeline. The proposed system integrates optimized near-eye illumination and image acquisition with a pupil detection module and a deep learning-based gaze-vector estimation model, forming a real-time software pipeline for stable end-to-end gaze mapping under fixed calibration conditions. Under identical system settings, calibration procedures, and gaze-point mapping conditions, we evaluate the proposed gaze-vector estimation model through a controlled model-level ablation. The attention-enhanced model achieves an average angular deviation of 1.15°, corresponding to a 61.4% relative reduction compared with a baseline ResNet-152 model without attention. To demonstrate the usability of the system outputs at the application level, we further implement a real-time visualization example that integrates pupil diameter, gaze vectors, and blink events to depict the temporal evolution of eye-movement signals. This work provides a cost-effective and reproducible engineering reference for near-eye eye-movement acquisition and visualization in immersive VR settings and serves as a technical foundation for subsequent interaction design or behavioral analysis studies. Full article

Static honeypot deployment and one-shot attack-path analysis often become ineffective against adaptive adversaries because fixed decoy layouts are easy to fingerprint and risk estimates quickly go stale. This paper presents a unified, mathematically grounded TrapManager framework that couples graph representation learning with budget-constrained combinatorial optimization for dynamic cyber deception. We model attacker progression on vulnerability-based attack graphs and learn context-aware node embeddings using a Graph Attention Network (GAT) that fuses vulnerability-driven risk signals (e.g., CVSS-derived node scores) with structural features. The learned representations are used to estimate edge plausibility and rank candidate source–target routes at the path level. Given limited resources, we formulate pointTrap placement as a Mixed-Integer Programming (MIP) problem that maximizes the expected interception of high-risk paths while penalizing deployment cost under explicit budget constraints, including mandatory coverage of the top-ranked critical paths. To enable online adaptiveness, a pointTrap-triggered, event-driven feedback mechanism locally amplifies risk around alerted regions, updates path weights without retraining the GAT, and re-solves the MIP for rapid redeployment. Experiments on MulVAL-generated benchmark attack graphs and cross-domain transfer settings demonstrate fast convergence, strong discrimination between attack and non-attack edges, and early interception within a small number of hops even with minimal decoy budgets. Overall, the proposed framework provides a scalable and resource-efficient approach to closed-loop attack-path defense by integrating attention-based learning and integer optimization. Full article

General-purpose large language models excel at open-domain question answering, but in railway operation and maintenance (O&M) scenarios they still suffer from hallucinated knowledge and poor domain adaptation. In practice, railway O&M knowledge mainly arises from two heterogeneous sources: spatio-temporal data such as train trajectories, which are organized along the spatial layout of railway lines, and domain documents such as operating rules, which exhibit varying degrees of structural regularity. Traditional retrieval-augmented generation (RAG) systems usually flatten these multi-source data into a single unstructured text space and perform global retrieval in one embedding space, which easily introduces noisy context and makes it difficult to precisely target knowledge for specific lines, sections, or equipment states. To overcome these limitations, we propose CARAG, a context-aware RAG framework tailored to railway O&M data. CARAG treats domain documents and spatial data as a unified knowledge substrate and builds a spatial knowledge graph with concept and instance levels. On top of this knowledge graph, a GraphReAct-based multi-turn interaction mechanism guides the LLM to reason and act over the concept knowledge graph, dynamically navigating to spatially and semantically relevant candidate regions, within which vector retrieval and instance-level graph retrieval are performed. Experiments show that CARAG significantly outperforms baseline RAG methods on RAGAS metrics, confirming the effectiveness of structure-guided multi-step reasoning for question answering over multi-source heterogeneous railway O&M data. Full article

This paper presents an optimization framework for determining safe and efficient evacuation paths in complex industrial facilities. The proposed approach models the evacuation process through a timed flow network that captures both the structural characteristics of the layout and the temporal evolution of emergency conditions. The formulation accommodates real-time updates, enabling dynamic re-routing when certain areas or connections become inaccessible. Computational experiments on large-scale instances demonstrate the scalability of the model and its ability to provide complete evacuation plans under increasing demand. The results confirm predictable relationships between population size, time horizon, and evacuation completion, supporting its use as a decision support tool for both strategic planning and operational response. Full article

Accurate six-degree-of-freedom (6-DoF) camera pose estimation is essential for augmented reality, robotics navigation, and indoor mapping. Existing pipelines often depend on detailed floorplans, strict Manhattan-world priors, and dense structural annotations, which lead to failures in ambiguous room layouts where multiple rooms appear in a query image and their boundaries may overlap or be partially occluded. We present Render-Rank-Refine, a two-stage framework operating on coarse semantic meshes without requiring textured models or per-scene fine-tuning. First, panoramas rendered from the mesh enable global retrieval of coarse pose hypotheses. Then, perspective views from the top-k candidates are compared to the query via rotation-invariant circular descriptors, which re-ranks the matches before final translation and rotation refinement. Our method increases camera localization accuracy compared to the state-of-the-art SPVLoc baseline by reducing the translation error by 40.4% and the rotation error by 29.7% in ambiguous layouts, as evaluated on the Zillow Indoor Dataset. In terms of inference throughput, our method achieves 25.8–26.4 QPS, (Queries Per Second) which is significantly faster than other recent comparable methods, while maintaining accuracy comparable to or better than the SPVLoc baseline. These results demonstrate robust, near-real-time indoor localization that overcomes structural ambiguities and heavy geometric assumptions. Full article

The deparser stage in the Protocol-Independent Switch Architecture (PISA) is often overshadowed by parser and match-action optimizations. Yet, it remains a critical performance bottleneck in P4-programmable FPGA data planes. Challenges associated with the deparser stem from dynamic header layouts, variable emission orders, and alignment constraints, which often necessitate resource-intensive designs, such as wide, dynamic crossbar routing. While compile-time specialization techniques can reduce logic usage, they sacrifice runtime adaptability: any change to the protocol graph, including adding, removing, or reordering headers, requires full hardware resynthesis and re-implementation, limiting their practicality for evolving or multi-tenant workloads. This work presents a unified FPGA-targeted deparser architecture that merges templated and overlay concepts within a hardware–software co-design framework. At design time, template parameters define upper bounds on protocol complexity, enabling resource-efficient synthesis tailored to specific workloads. Within these bounds, runtime reconfiguration is supported through overlay control tables derived from static deparser DAG analysis, which capture the per-path emission order, header alignments, and offsets. These tables drive protocol-agnostic, chunk-based emission blocks that eliminate the overhead of crossbar interconnects, thereby significantly reducing complexity and resource usage. The proposed design sustains high throughput while preserving the flexibility needed for in-field updates and long-term protocol evolution. Full article

Background: Pediatric oropharyngeal dysphagia screening protocols remain limited in acute and critical care settings due to the lack of psychometrically valid and reliable tools. Objectives: The eDelphi methodology was employed to establish content validity for the Children’s Oral Feeding Screener (COFS), a novel, nurse-led oropharyngeal dysphagia screening tool for hospitalized children in acute and critical care (0–16 years). Methods: The two-round eDelphi study was completed using Qualtrics^®. A multidisciplinary, international steering-group guided tool conceptualization, elements for rating in the eDelphi, and oversaw consensus decisions. Experienced speech pathologists in pediatric acute and/or critical care were invited as panelists and rated tool content regarding (a) clinical presentations requiring immediate referral for dysphagia assessment; (b) oral trial component/s; and (c) signs observed during oral trials suggesting dysphagia. Items were rated on a 10-point Likert scale, and panelists could give open-ended feedback. Items not reaching pre-defined consensus (>75%) were re-presented in round two. Results: Fifty panelists participated in round one and 41 in round two, primarily from Australia (n = 19; 46%) and the United Kingdom (n = 13; 34%). Half (n = 22; 54%) had >10 years’ experience. Based on consensus scores, panelists’ qualitative feedback, and steering group decision, final items included eight clinical presentations, three oral trial elements (cup, bottle, breastfeeding) with three associated oral trial protocols, and fourteen signs suggestive of dysphagia. Other feedback led to changes to headings and the format of the COFS layout. Conclusions: Content validity for items in the three components of the COFS was established. Further work is now required to explore other psychometric properties (construct validity, sensitivity/specificity, and feasibility) in clinical settings. Full article

The transition to electric aircraft for zero-emission transport requires integrating thermal management systems for high-performance batteries without incurring significant weight, balance, or aerodynamic penalties. This study focuses on the aerodynamic penalties associated with air-cooling systems that can compound the presently unavoidable reduction in endurance imposed by current battery energy density limitations. Building on previous research into battery installation layouts and internal cooling flows, this study is the first to investigate the lift-to-drag (L/D) optimisation for the multiple wing-mounted inlets and outlets necessary for air-cooling batteries in the wing of an electrified aircraft. Wing leading-edge inlets and NACA (National Advisory Committee for Aeronautics) ducts were analysed by systematically varying their layout, number, and dimensions. The analysis evaluated their effects on the wing’s lift, drag, and moment to maximise the L/D. Multiple highly efficient simulation test designs were developed to screen for the main factors to identify the best inlet and outlet configuration, resulting in 66 different Computational Fluid Dynamics (CFD) simulations in Ansys Fluent. Following this, three CFD verification cases of the best configuration were conducted to verify the cooling effect by combining both internal and external flow simulations with heat generation. Compared to the baseline wing of the carbon combustion aircraft, the best configuration caused a 1.75% reduction in L/D, range, and endurance. While the aerodynamic penalty is now minimised, the internal battery pack layout requires further optimisation to re-establish uniform cooling across the battery pack. Designers may still be able to separate the CFD analysis of the internal and external flow regimes with idealised inlets and outlets; however, more whole-field CFD iterations are needed to guide such subdivision to a viable and safe design for wing-mounted batteries. Further, the margins are such that wing-mounted electrification warrants careful instrumented validation in an aircraft. These findings provide crucial design guidance for sustainable aviation, particularly to enable after-market electrification projects. Full article

Successful health promotion involves messages that are quickly captured and held long enough to permit eligibility, credibility, and calls to action to be coded. This research develops an exploratory eye-tracking atlas of breast cancer screening ads viewed by midlife women and a replicable pipeline that distinguishes early capture from long-term processing. Areas of Interest are divided into design-influential categories and graphed with two complementary measures: first hit and time to first fixation for entry and a tie-aware pairwise dominance model for dwell that produces rankings and an “early-vs.-sticky” quadrant visualization. Across creatives, pictorial and symbolic features were more likely to capture the first glance when they were perceptually dominant, while layouts containing centralized headlines or institutional cues deflected entry to the message and source. Prolonged attention was consistently focused on blocks of text, locations, and badges of authoring over ornamental pictures, demarcating the functional difference between capture and processing. Subgroup differences indicated audience-sensitive shifts: Older and household families shifted earlier toward source cues, more educated audiences shifted toward copy and locations, and younger or single viewers shifted toward symbols and images. Internal diagnostics verified that pairwise matrices were consistent with standard dwell summaries, verifying the comparative approach. The atlas converts the patterns into design-ready heuristics: defend sticky and early pieces, encourage sticky but late pieces by pushing them toward probable entry channels, de-clutter early but not sticky pieces to convert to processing, and re-think pieces that are neither. In practice, the diagnostics can be incorporated into procurement, pretesting, and briefs by agencies, educators, and campaign managers in order to enhance actionability without sacrificing segmentation of audiences. As an exploratory investigation, this study invites replication with larger and more diverse samples, generalizations to dynamic media, and associations with downstream measures such as recall and uptake of services. Full article

Single Event Transients (SETs) in clock-distribution networks are a major source of soft errors in synchronous systems. We present a practical framework that assesses SET risk early in the design cycle, before layout and parasitics, using a Vulnerability Function (VF) derived from Verilog fault injection. This framework guides targeted Engineering Change Orders (ECOs), such as clock-net remapping, re-routing, and the selective insertion of SET filters, within a reproducible open-source flow (Yosys, OpenROAD, OpenSTA). A new analytical Soft Error Rate (SER) model for clock trees is also proposed, which decomposes contributions from the root, intermediate levels, and leaves, and is calibrated by SPICE-measured propagation probabilities, area, and particle flux. When coupled with throughput, this model yields a frequency-aware system-level Bit Error Rate (${BER}_{sys}$). The methodology was validated on a First-In First-Out (FIFO) memory, demonstrating a significant vulnerability reduction of approximately 3.35× in READ mode and 2.67× in WRITE mode. Frequency sweeps show monotonic decreases in both clock-tree vulnerability and ${BER}_{sys}$ at higher clock frequencies, a trend attributed to temporal masking and throughput effects. Cross-node SPICE characterization between 65 nm and 28 nm reveals a technology-dependent effect: for the same injected charge, the 28 nm process produces a shorter root-level pulse, which lowers the propagation probability relative to 65 nm and shifts the optimal clock-tree partition. These findings underscore the framework’s key innovations: a technology-independent, early-stage VF for ranking critical clock nets; a clock-tree SER model calibrated by measured propagation probabilities; an ECO loop that converts VF insights into concrete hardening actions; and a fully reproducible open-source implementation. The paper’s scope is architectural and pre-layout, with extensions to broader circuit classes and a full electrical analysis outlined for future work. Full article

With accelerated urbanization and the pursuit of the “dual carbon” goals, shared bicycles have re-emerged as a green travel option. This study focuses on the central urban area of Nanjing and develops a carbon emissions reduction (CER) estimation model for shared bicycles. By analyzing spatio-temporal dimensions, it systematically assesses carbon reduction benefits and highlights the synergy with metro-connected travel. Key findings are as follows: (1) shared bicycles primarily support short-distance commuting, with a daily cycling pattern exhibiting a bi-modal distribution and a pronounced peak period demand; (2) cycling trips concentrate in densely populated and commercially vibrant zones, with a spatial pattern of central aggregation and multi-point diffusion; (3) each kilometer cycled by a shared bicycle reduces carbon emissions by about 96.19 g, with daily reductions of around 42.72 t and annual reductions up to 15,591.04 t; (4) the CER benefits of bicycle–metro integration are especially pronounced, contributing nearly 45.00% during peak periods; and (5) factors such as travel mode shifts, metro station layouts, and the development of electric vehicles continue to influence the CER benefits of shared bicycles. This work provides scientific evidence to inform urban green travel policies and transportation infrastructure optimization in cities. Full article

Urban green space, a vital part of urban ecosystems, offers inhabitants essential ecosystem services, and ensuring its fair distribution is essential to preserving their ecological well-being. This study uses Kaifeng City in Henan Province as the research object and aims to address the unique conflict between the preservation of well-known historical and cultural cities and the development of greening. It does this by integrating streetscape big data (2925 sampling points) and point of interest (POI) density data (57,266 records) and using the DeepLab-ResNeSt269 semantic segmentation model in conjunction with spatial statistical techniques (Moran’s Index, Locational Entropy and Theil Index Decomposition) to quantitatively analyze the spatial equity of the green view index (GVI) in Kaifeng City. The results of the study show that (1) The Theil Index reveals that the primary contradiction in Kaifeng City’s distribution pattern—low GVI in the center and high in the periphery—is the micro-street scale difference, suggesting that the spatial imbalance of the GVI is primarily reflected at the micro level rather than the macro urban area difference. (2) The distribution of the GVI in Kaifeng City exhibits a significant spatial polarization phenomenon, with the proportion of low-value area (35.40%) being significantly higher than that of high-value area (25.10%) and the spatial clustering being evident (Moran’s Index 0.3824). Additionally, the ancient city area and the new city area exhibit distinct spatial organization patterns. (3) POI density and GVI had a substantial negative correlation (r = −0.085), suggesting a complicated process of interaction between green space and urban functions. The study reveals that the fairness of green visibility in historical and cultural cities presents the characteristics of differentiated distribution in different spatial scales, which provides a scientific basis for the optimization of greening spatial layouts in historical and cultural cities while preserving the traditional landscape. Full article

Background/Objective: The global acceleration of population aging presents profound challenges to the physical, psychological, and social well-being of older adults. As traditional exercise programs face limitations in accessibility, personalization, and sustained social support, there is a critical need for innovative, inclusive, and community-integrated digital movement solutions. This study aimed to develop and evaluate Movement Poomasi, a hybrid digital healthcare application designed to promote physical activity, improve digital accessibility, and strengthen social connectedness among older adults. Methods: From March 2023 to November 2023, Movement Poomasi was developed through an iterative user-centered design process involving domain experts in physical therapy and sports psychology. In this study, the term UI/UX—short for user interface and user experience—refers to the overall design and interaction framework of the application, encompassing visual layout, navigation flow, accessibility features, and user engagement optimization tailored to older adults’ sensory, cognitive, and motor characteristics. The application integrates adaptive exercise modules, senior-optimized UI/UX, voice-assisted navigation, and peer-interaction features to enable both home-based and in-person movement engagement. A two-phase usability validation was conducted. A 4-week pilot test with 15 older adults assessed the prototype, followed by a formal 6-week study with 50 participants (≥65 years), stratified by digital literacy and activity background. Quantitative metrics—movement completion rates, session duration, and engagement with social features—were analyzed alongside semi-structured interviews. Statistical analysis included ANOVA and regression to examine usability and engagement outcomes. The application has continued iterative testing and refinement until May 2025, and it is scheduled for re-launch under the name Wello! in August 2025. Results: Post-implementation UI refinements significantly increased navigation success rates (from 68% to 87%, p = 0.042). ANOVA revealed that movement selection and peer-interaction tasks posed greater cognitive load (p < 0.01). A strong positive correlation was found between digital literacy and task performance (r = 0.68, p < 0.05). Weekly participation increased by 38%, with 81% of participants reporting enhanced social connectedness through group challenges and hybrid peer-led meetups. Despite high satisfaction scores (mean 4.6 ± 0.4), usability challenges remained among low-literacy users, indicating the need for further interface simplification. Conclusions: The findings underscore the potential of hybrid digital platforms tailored to older adults’ physical, cognitive, and social needs. Movement Poomasi demonstrates scalable feasibility and contributes to reducing the digital divide while fostering active aging. Future directions include AI-assisted onboarding, adaptive tutorials, and expanded integration with community care ecosystems to enhance long-term engagement and inclusivity. Full article

This study examines two proximate yet theologically and spatially disparate religious spaces in Seoul: the Jeoldusan Martyrs’ Shrine (Korean: 절두산 순교 성지; hereafter “Jeoldusan Martyrs’ Shrine”) and the Yanghwajin Protestant Cemetery (Korean: 양화진 묘원; hereafter “Yanghwajin Cemetery”). We propose the concept of isomorphic heterotopias and discuss the logic of intersecting memories. Drawing on Foucault’s concept of heterotopia and cultural memory theory, the study finds that the Jeoldusan Martyrs’ Shrine, through architectural enclosure, the exhibition of relics, and pilgrimage rituals, foregrounds the vertical redemption of martyrs’ flesh and faith, reinforcing ecclesiastical discourse and collective salvation narratives. In contrast, at Yanghwajin Cemetery, through dispersed tombstone layouts, egalitarian epitaph inscriptions, and public commemorative activities, the study finds that the site presents the dialectic of the martyr spirit within a secular spiritual space and individual testimonies. Despite their spatial heterogeneity, their geographic proximity generates a dialogical memory field: the vertical sacrality of the shrine is refracted through the cemetery’s horizontality, while the cemetery’s public spirit resonates with the shrine’s liturgical framework. This dialogical memory field, shaped by shared physical environments and common public narrative platforms—generates a long-term coexistence without convergence, producing a spatial relationship of “non-integrative entanglement” born of antagonism. At the same time, these sites are not isolated spatial fragments; rather, through urban governance, they are woven into the same memory politics network, forming an “isomorphic heterotopia.” Through politically inflected discursive narratives, both sites facilitate multidirectional flows of memory, preserving their respective “canons” while re-contextualizing each other within the same urban memory network. In doing so, they engage in an ongoing process of mutual rereading and co-construction, producing a re-contextualization of spatial memory and shaping a “composite historical sensibility” that, in turn, contributes to the city’s character. Full article