1,431 research outputs found
Semantic Guided Level-Category Hybrid Prediction Network for Hierarchical Image Classification
Hierarchical classification (HC) assigns each object with multiple labels
organized into a hierarchical structure. The existing deep learning based HC
methods usually predict an instance starting from the root node until a leaf
node is reached. However, in the real world, images interfered by noise,
occlusion, blur, or low resolution may not provide sufficient information for
the classification at subordinate levels. To address this issue, we propose a
novel semantic guided level-category hybrid prediction network (SGLCHPN) that
can jointly perform the level and category prediction in an end-to-end manner.
SGLCHPN comprises two modules: a visual transformer that extracts feature
vectors from the input images, and a semantic guided cross-attention module
that uses categories word embeddings as queries to guide learning
category-specific representations. In order to evaluate the proposed method, we
construct two new datasets in which images are at a broad range of quality and
thus are labeled to different levels (depths) in the hierarchy according to
their individual quality. Experimental results demonstrate the effectiveness of
our proposed HC method.Comment: 3 figure
VCD: Visual Causality Discovery for Cross-Modal Question Reasoning
Existing visual question reasoning methods usually fail to explicitly
discover the inherent causal mechanism and ignore jointly modeling cross-modal
event temporality and causality. In this paper, we propose a visual question
reasoning framework named Cross-Modal Question Reasoning (CMQR), to discover
temporal causal structure and mitigate visual spurious correlation by causal
intervention. To explicitly discover visual causal structure, the Visual
Causality Discovery (VCD) architecture is proposed to find question-critical
scene temporally and disentangle the visual spurious correlations by
attention-based front-door causal intervention module named Local-Global Causal
Attention Module (LGCAM). To align the fine-grained interactions between
linguistic semantics and spatial-temporal representations, we build an
Interactive Visual-Linguistic Transformer (IVLT) that builds the multi-modal
co-occurrence interactions between visual and linguistic content. Extensive
experiments on four datasets demonstrate the superiority of CMQR for
discovering visual causal structures and achieving robust question reasoning.Comment: 12 pages, 6 figures. arXiv admin note: substantial text overlap with
arXiv:2207.1264
Control of Fluid Dynamics by Nanoparticles in Laser Melting
Effective control of fluid dynamics is of remarkable scientific and practical significance. It is hypothesized that nanoparticles could offer a novel means to control fluid dynamics. In this study, laser melting was used to investigate the feasibility of tuning fluid dynamics by nanoparticles and possibly breaking existing limits of conventional laser processing techniques. Alumina nanoparticles reinforced nickel samples, fabricated through electrocodeposition, were used for laser melting experiments. Since the melt pool surface is controlled by the fluid dynamics, surface topographies were carefully studied to reveal the nanoparticle effect on the fluid dynamics. Characterizations of surface topographies and microstructures of pure Ni and Ni/Al2O3 nanocomposite were carried out before and after laser melting. The surface roughness of the Ni/Al2O3 nanocomposite sample was reduced significantly by laser melting, which broke the existing limit of laser surface polishing of pure Ni. It is believed that the nanoparticles increased the viscosity of the molten metal, thereby enhancing the viscous damping of the capillary oscillations in the melt pool, to produce a much smoother surface. Moreover, the experimental study also revealed that the viscosity enhancement by the nanoparticles effectively suppressed the thermocapillary flows which would introduce artificial asperities on a surface. The experimental results suggest that nanoparticles are effective in controlling melt pool dynamics and overcoming the existing limits of laser processing. The new methodology, fluid dynamics control by nanoparticles, opens a new pathway to enrich liquid based processes for broad applications
Two-Link Flexible Manipulator Modeling and Tip Trajectory Tracking Based on Absolute Nodal Coordinate Method
Abstract It has been demonstrated that the absolute nodal coordinate formulation (ANCF) proposed recently in literature can be used to exactly describe the flexible multibody system unlike traditional methods such as the floating coordinate method and assumed mode method. Therefore, in this paper a new dynamic modeling technique for a two-link flexible manipulator based on absolute nodal coordinate method is proposed. The link shear effect was taken into account by using the 2D ANCF shear beam element. The resulting state equation can be explicitly described by generalized coordinate since the system mass matrix is constant in the ANCF framework. The proposed method is validated through the two-link flexible manipulator tip circle and square trajectory tracking control simulations by using a simple PD controller. To improve computational efficiency, the invariant matrix method and the Broyden quasi-Newton method are introduced. To improve the tracking accuracy, different PD parameters in different simulation periods are used. The simulation results indicate that modeling and controlling the flexible manipulator based on the ANCF is effective
Prevalence and risk factors of abnormal left ventricular geometrical patterns in untreated hypertensive patients
BACKGROUND: The various prevalence of LVH and abnormal LV geometry have been reported in different populations. So far, only a few reports are available on the prevalence of LV geometric patterns in a large Chinese untreated hypertensive population. METHODS: A total of 9,286 subjects (5167 men and 4119 women) completed the survey and 1641 untreated hypertensive patients (1044 males and 597 females) enrolled in the present study. The LV geometry was classified into four patterns: normal; abnormal,defined as concentric remodeling;concentric or eccentric hypertrophy based on the values of left ventricular mass index (LVMI) and relative wall thickness (RWT). Logistic regression model was applied to determine the odds ratio (OR) and 95% confidence intervals (CI) of the risk factors of left ventricular hypertrophy. RESULTS: The prevalence of LVH was 20.2% in untreated hypertensive patients, much higher in women (30.8%) than in men (14.2%) (P < 0.01). The prevalence of LV geometrical patterns was 34.9%, 11.1%, 9.1% for concentric remodeling, concentric and eccentric hypertrophy,respectively. After adjustment by using Logistic regression model, the risk factors for LVH and abnormal LV geometry were age, female, systolic blood pressure, and body mass index. And low high density lipoprotein maybe a positive factor. CONCLUSIONS: The prevalence of LVH and abnormal LV geometric patterns was higher in women than in men and increased with age. It is crucial to improve the awareness rate of hypertension and control the risk factors of CV complications in untreated hypertensive population
The Optimal Design Method and Standardized Mathematical Model of Tooth Profile Modification of Spur Gear
The paper reports a tooth profile modification method of spur gear. After establishing a standardized mathematical model for optimized tooth profile and simulating meshing process with ANSYS finite element analysis, we obtained 625 groups of gear models with different modification parameters. The group with minimum transmission errors owns the optimal parameters. Genetic algorithm was adopted in the entire process for the purpose of reducing the variation of transmission errors in meshing process. The arc and parabolic modification were doing the same processing. After comparing the transmission errors fluctuation produced by the meshing process of gear of nonmodification with arc modification and parabolic modification, we found that the best modification effects of arc modification and parabolic modification were both reduced by 90%. The modification method makes the gear drive process more stable and efficient, and it is also promising in general application for gear drive
Impacts of geomechanical damage on waterflood-induced fracture propagation in deeply deposited tight oil reservoirs
Waterflood-induced fractures can enhance the production of deep tight oil reservoirs. However, if waterflood-induced fractures propagate fast, they connect injection wells to production wells earlier, inhibiting the production of tight oil reservoirs. In the present research, the fast propagation mechanism of waterflood-induced fractures was mainly investigated. The changes in sandstone mechanical properties by water were investigated by laboratory experiments, and the relationship of the geomechanical damage of sandstones with water saturation was quantified. Flow-geomechanics-coupled numerical simulations were performed to analyze the impacts of water flooding on stress distribution in a deeply deposited tight oil reservoir. Based on the fracture mechanics theory, the propagation length of the waterflood-induced fracture was calculated and the characteristics of waterflood-induced fracture propagation were analyzed. Experimental results revealed that water changed the mineral composition and microscopic structure of sandstones. This phenomenon decreased the Young’s modulus and tensile strength of sandstones and increased the Poisson’s ratio. The changing magnitude of these properties increased with the rise of water saturation, and the maximum changing magnitude reached 70%. The water saturation distribution became heterogeneous after waterflooding, causing a heterogeneous distribution of mechanical properties. The stress around the fracture tip and the fracture propagation length were significantly affected by these property changes. After the geomechanical damage, the fracture propagation pressure decreased by about 20%. Moreover, the initial fracture length enhanced the propagation length of the waterflood-induced fracture. These results suggest that the propagation of waterflood-induced fractures becomes more significant during waterflooding; thus, the injection pressure should be reduced to avoid fast fracture propagation
- …