Integrated In-vehicle Monitoring System Using 3D Human Pose Estimation and Seat Belt Segmentation

Recently, along with interest in autonomous vehicles, the importance of monitoring systems for both drivers and passengers inside vehicles has been increasing. This paper proposes a novel in-vehicle monitoring system the combines 3D pose estimation, seat-belt segmentation, and seat-belt status classification networks. Our system outputs various information necessary for monitoring by accurately considering the data characteristics of the in-vehicle environment. Specifically, the proposed 3D pose estimation directly estimates the absolute coordinates of keypoints for a driver and passengers, and the proposed seat-belt segmentation is implemented by applying a structure based on the feature pyramid. In addition, we propose a classification task to distinguish between normal and abnormal states of wearing a seat belt using results that combine 3D pose estimation with seat-belt segmentation. These tasks can be learned simultaneously and operate in real-time. Our method was evaluated on a private dataset we newly created and annotated. The experimental results show that our method has significantly high performance that can be applied directly to real in-vehicle monitoring systems.Comment: AAAI 2022 workshop AI for Transportation accepte

Lightweight Monocular Depth Estimation via Token-Sharing Transformer

Depth estimation is an important task in various robotics systems and applications. In mobile robotics systems, monocular depth estimation is desirable since a single RGB camera can be deployable at a low cost and compact size. Due to its significant and growing needs, many lightweight monocular depth estimation networks have been proposed for mobile robotics systems. While most lightweight monocular depth estimation methods have been developed using convolution neural networks, the Transformer has been gradually utilized in monocular depth estimation recently. However, massive parameters and large computational costs in the Transformer disturb the deployment to embedded devices. In this paper, we present a Token-Sharing Transformer (TST), an architecture using the Transformer for monocular depth estimation, optimized especially in embedded devices. The proposed TST utilizes global token sharing, which enables the model to obtain an accurate depth prediction with high throughput in embedded devices. Experimental results show that TST outperforms the existing lightweight monocular depth estimation methods. On the NYU Depth v2 dataset, TST can deliver depth maps up to 63.4 FPS in NVIDIA Jetson nano and 142.6 FPS in NVIDIA Jetson TX2, with lower errors than the existing methods. Furthermore, TST achieves real-time depth estimation of high-resolution images on Jetson TX2 with competitive results.Comment: ICRA 202

Epigallocatechin-3-gallate protects toluene diisocyanate-induced airway inflammation in a murine model of asthma

AbstractEpigallocatechin-3-gallate (EGCG), a major form of tea catechin, has anti-allergic properties. To elucidate the anti-allergic mechanisms of EGCG, we investigated its regulation of matrix metalloproteinase (MMP-9) expression in toluene diisocyanate (TDI)-inhalation lung tissues as well as TNF-α and Th2 cytokine (IL-5) production in BAL fluid. Compared with untreated asthmatic mice those administrated with EGCG had significantly reduced asthmatic reaction. Also, increased reactive oxygen species (ROS) generation by TDI inhalation was diminished by administration of EGCG in BAL fluid. These results suggest that EGCG regulates inflammatory cell migration possibly by suppressing MMP-9 production and ROS generation, and indicate that EGCG may be useful as an adjuvant therapy for bronchial asthma

Effect of Crystallization Modes in TIPS-Pentacene/Insulating Polymer Blends on the Gas Sensing Properties of Organic Field-Effect Transistors

Blending organic semiconductors with insulating polymers has been known to be an effective way to overcome the disadvantages of single-component organic semiconductors for high-performance organic field-effect transistors (OFETs). We show that when a solution processable organic semiconductor (6,13-bis(triisopropylsilylethynyl)pentacene, TIPS-pentacene) is blended with an insulating polymer (PS), morphological and structural characteristics of the blend films could be significantly influenced by the processing conditions like the spin coating time. Although vertical phase-separated structures (TIPS-pentacene-top/PS-bottom) were formed on the substrate regardless of the spin coating time, the spin time governed the growth mode of the TIPS-pentacene molecules that phase-separated and crystallized on the insulating polymer. Excess residual solvent in samples spun for a short duration induces a convective flow in the drying droplet, thereby leading to one-dimensional (1D) growth mode of TIPS-pentacene crystals. In contrast, after an appropriate spin-coating time, an optimum amount of the residual solvent in the film led to two-dimensional (2D) growth mode of TIPS-pentacene crystals. The 2D spherulites of TIPS-pentacene are extremely advantageous for improving the field-effect mobility of FETs compared to needle-like 1D structures, because of the high surface coverage of crystals with a unique continuous film structure. In addition, the porous structure observed in the 2D crystalline film allows gas molecules to easily penetrate into the channel region, thereby improving the gas sensing properties

Key Intrinsic Connectivity Networks for Individual Identification With Siamese Long Short-Term Memory

In functional magnetic resonance imaging (fMRI) analysis, many studies have been conducted on inter-subject variability as well as intra-subject reproducibility. These studies indicate that fMRI could have unique characteristics for individuals. In this study, we hypothesized that the dynamic information during 1 min of fMRI was unique and repetitive enough for each subject, so we applied long short-term memory (LSTM) using initial time points of dynamic resting-state fMRI for individual identification. Siamese network is used to obtain robust individual identification performance without additional learning on a new dataset. In particular, by adding a new structure called region of interest–wise average pooling (RAP), individual identification performance could be improved, and key intrinsic connectivity networks (ICNs) for individual identification were also identified. The average performance of individual identification was 97.88% using the test dataset in eightfold cross-validation analysis. Through the visualization of features learned by Siamese LSTM with RAP, ICNs spanning the parietal region were observed as the key ICNs in identifying individuals. These results suggest the key ICNs in fMRI could represent individual uniqueness

Neural Correlates of Transient Mal de Debarquement Syndrome: Activation of Prefrontal and Deactivation of Cerebellar Networks Correlate With Neuropsychological Assessment

Background: Mal de debarquement syndrome (MdDS) is characterized by a subjective perception of self-motion after exposure to passive motion, mostly after sea travel. A transient form of MdDS (t-MdDS) is common in healthy individuals without pathophysiological certainty. In the present cross-sectional study, the possible neuropsychiatric and functional neuroimaging changes in local fishermen with t-MdDS were evaluated. Methods: The present study included 28 fishermen from Buan County in South Korea; 15 (15/28, 53.6%) participants experienced t-MdDS for 1–6 h, and 13 were asymptomatic (13/28, 46.4%). Vestibular function tests were performed using video-oculography, the video head impulse test, and ocular and cervical vestibular-evoked myogenic potentials. Visuospatial function was also assessed by the Corsi block test. Brain imaging comprised structural MRI, resting-state functional MRI, and [18F]FDG PET scans. Results: The results of vestibular function tests did not differ between the fishermen with and those without t-MdDS. However, participants with t-MdDS showed better performance in visuospatial memory function than those without t-MdDS (6.40 vs. 5.31, p-value = 0.016) as determined by the Corsi block test. Structural brain MRIs were normal in both groups. [18F]FDG PET showed a relative hypermetabolism in the bilateral occipital and prefrontal cortices and hypometabolism in the vestibulocerebellum (nodulus and uvula) in participants with t-MdDS compared to those without t-MdDS. Resting-state functional connectivities were significantly decreased between the vestibular regions of the flocculus, superior temporal gyrus, and parietal operculum and the visual association areas of the middle occipital gyrus, fusiform gyrus, and cuneus in participants with t-MdDS. Analysis of functional connectivity of the significant regions in the PET scans revealed decreased connectivity between the prefrontal cortex and visual processing areas in the t-MdDS group. Conclusion: Increased visuospatial memory, altered metabolism in the prefrontal cortex, visual cognition cortices, and the vestibulocerebellum, and decreased functional connectivity between these two functional areas might indicate reductions in the integration of vestibular input and enhancement of visuospatial attention in subjects with t-MdDS. Current functional neuroimaging similarities from transient MdDS via chronic MdDS to functional dizziness and anxiety disorders suggest a shared mechanism of enhanced self-awareness as a kind of continuum or as overlap disorders

Electrical conductivity enhancement of epitaxially grown TiN thin films

Titanium nitride (TiN) presents superior electrical conductivity with mechanical and chemical stability and compatibility with the semiconductor fabrication process. Here, we fabricated epitaxial and polycrystalline TiN (111) thin films on MgO (111), sapphire (001), and mica substrates at 640oC and room temperature by using a DC sputtering, respectively. The epitaxial films show less amount of surface oxidation than the polycrystalline ones grown at room temperature. The epitaxial films show drastically reduced resistivity (~30 micro-ohm-cm), much smaller than the polycrystalline films. Temperature-dependent resistivity measurements show a nearly monotonic temperature slope down to low temperature. These results demonstrate that high temperature growth of TiN thin films leads to significant enhancement of electrical conductivity, promising for durable and scalable electrode applications.Comment: 14 pages, 3 figure