608 research outputs found
GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks
In the last decade, supervised deep learning approaches have been extensively
employed in visual odometry (VO) applications, which is not feasible in
environments where labelled data is not abundant. On the other hand,
unsupervised deep learning approaches for localization and mapping in unknown
environments from unlabelled data have received comparatively less attention in
VO research. In this study, we propose a generative unsupervised learning
framework that predicts 6-DoF pose camera motion and monocular depth map of the
scene from unlabelled RGB image sequences, using deep convolutional Generative
Adversarial Networks (GANs). We create a supervisory signal by warping view
sequences and assigning the re-projection minimization to the objective loss
function that is adopted in multi-view pose estimation and single-view depth
generation network. Detailed quantitative and qualitative evaluations of the
proposed framework on the KITTI and Cityscapes datasets show that the proposed
method outperforms both existing traditional and unsupervised deep VO methods
providing better results for both pose estimation and depth recovery.Comment: ICRA 2019 - accepte
Acoustic Faraday effect in TbGaO
The transverse acoustic wave propagating along the [100] axis of the cubic
TbGaO (acoustic mode) is doubly degenerate. A magnetic
field applied in the direction of propagation lifts this degeneracy and leads
to the rotation of the polarization vector - the magneto-acoustic Faraday
rotation. Here, we report on the observation and analysis of the
magneto-acoustic Faraday-effect in TbGaO in static and pulsed
magnetic fields. We present also a theoretical model based on magnetoelastic
coupling of 4 electrons to both, acoustic and optical phonons and an
effective coupling between them. This model explains the observed linear
frequency dependence of the Faraday rotation angle
Physiological Responses, Performance, Behaviour, and Welfare of Garut Sheep Cared using Semi-Intensive System in Indonesia
Sheep farming in Indonesia still relies on the intensive system which is very labor-intensive, movement restrictions, and reduced quantity of sheep can be kept, developed countries, on the other hand, have evolved a semi-intensive system that may minimize the number of staff while still providing welfare to the sheep. This study aimed to compare the performance, physiological responses, behavior, and welfare of reared Garut sheep in semi-intensive management with outdoor pen and full indoor pen treatments, employing a T-test experimental design using ten replicates (n=10). This experiment used 20 ewes sheep (one-year-old) with an average body weight of 18.74±2.53 kg. This experiment found no difference in dry matter intake (gram/head/day) or average daily gain (gram/head/day) between both treatments (P0.05). When compared to ewes with full indoor pen, ewes with access to outdoor pen had better physiological status especially heart rate and respiratory rate, particularly in the morning and afternoon (P0.05). The ratio of blood N/L for ewes with an outdoor pen showed better results (P0.05), and the rearing environment also did not show any difference nor induce stress on livestock with access to outdoor pen (P0.05). Ewes' welfare increases and they become more active after being provided access to outdoor pen. In conclusion, a semi-intensive system with an outside enclosure enhances Garut ewes' performance while also improving their physiological health and welfare index fulfillment. This approach has to be promoted throughout Indonesia for better farming management
Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity
In federated learning, data heterogeneity is a critical challenge. A
straightforward solution is to shuffle the clients' data to homogenize the
distribution. However, this may violate data access rights, and how and when
shuffling can accelerate the convergence of a federated optimization algorithm
is not theoretically well understood. In this paper, we establish a precise and
quantifiable correspondence between data heterogeneity and parameters in the
convergence rate when a fraction of data is shuffled across clients. We prove
that shuffling can quadratically reduce the gradient dissimilarity with respect
to the shuffling percentage, accelerating convergence. Inspired by the theory,
we propose a practical approach that addresses the data access rights issue by
shuffling locally generated synthetic data. The experimental results show that
shuffling synthetic data improves the performance of multiple existing
federated learning algorithms by a large margin
Fibromuscular Dysplasia with Spontaneous Coronary Artery Disease Presenting as Acute Myocardial Infarction
A 40-year-old female presented to a rural hospital with crushing substernal chest pain. An initial electrocardiogram showed ST elevation in lead II and aVF with elevated troponin I. She was immediately transferred to a tertiary care hospital. An emergent coronary angiogram did not show any significant coronary artery disease. On the second day, the patient experienced recurrence of severe chest pain with ST elevations in leads I, aVL, V5-V6, ST depressions in V1-V3, T-wave inversion over V2-V5. The troponin I level increased to \u3e 40 ng/ml (normal 0.0 to 0.04 ng/ml). An emergent angiogram was performed revealing local dissection of the mid to distal left main coronary artery and a totally occluded diagonal artery. It was deemed unsafe to perform percutaneous coronary intervention because it was a non-flow limiting left main coronary artery dissection and was difficult to cannulate with the guide catheter. Subsequently, an elective angiogram was performed after a 48-hour interval to evaluate the progression of dissection and to make a definitive decision for revascularization versus medical management. On the third angiogram, stenosis seen in the diagonal branch on the previous angiogram progressed to dissection, and local dissection of the left main coronary artery seen on the previous angiogram spontaneously resolved. The patient was symptom-free and hemodynamically stable. It was decided to manage the patient conservatively due to the spontaneous resolution of occlusion in the diagonal artery and dissection of the left main coronary artery. The patient was started on conservative medical treatment. A magnetic resonance angiography of the right internal carotid artery revealed a “string of beads” appearance, which confirmed the diagnosis of fibromuscular dysplasia. She was followed closely in the clinic and has remained asymptomatic for the past one year
The Connectivity Fingerprint of the Human Frontal Cortex, Subthalamic Nucleus, and Striatum
Within the cortico basal ganglia (BG)–thalamic network, the direct and indirect pathways comprise of projections from the cortex to the striatum (STR), whereas the hyperdirect pathway(s) consist of cortical projections toward the subthalamic nucleus (STN). Each pathway possesses a functionally distinct role for action selection. The current study quantified and compared the structural connectivity between 17 distinct cortical areas with the STN and STR using 7 Tesla diffusion weighted magnetic resonance imaging (dMRI) and resting-state functional MRI (rs-fMRI) in healthy young subjects. The selection of these cortical areas was based on a literature search focusing on animal tracer studies. The results indicate that, relative to other cortical areas, both the STN and STR showed markedly weaker structural connections to areas assumed to be essential for action inhibition such as the inferior frontal cortex pars opercularis. Additionally, the cortical connectivity fingerprint of the STN and STR indicated relatively strong connections to areas related to voluntary motor initiation such as the cingulate motor area and supplementary motor area. Overall the results indicated that the cortical–STN connections were sparser compared to the STR. There were two notable exceptions, namely for the orbitofrontal cortex and ventral medial prefrontal cortex, where a higher tract strength was found for the STN. These two areas are thought to be involved in reward processing and action bias
Top loaded TM01δ Mode Cylindrical Dielectric Resonator for Complex Permittivity Characterization of Liquids
This paper reports on a technique of using a very high quality factor cylindrical dielectric resonator operating in TM01δ mode to characterize liquids available in trace quantities. The proposed measurement technique is based on the resonant perturbation theory and the resonator is used as a sensor to determine complex permittivity of solvents at 10.5GHz. Owing to a very high unloaded quality factor of about 5000 the proposed sensor can characterize low to medium loss materials with high accuracy. Small quantities of isopropanol and ethanol have been characterized for their solution ratio when mixed with different quantities of distilled water. Low cost and versatility of the proposed structure make it a prime choice for pharmaceutical industry where high standards of purity need to be ensured
Role of proline, K/Na ratio and chlorophyll content in salt tolerance of wheat (Triticum aestivum
Abstract Studies to determine the role of proline, K/Na ratio and chlorophyll contents in salt tolerance of wheat genotypes were conducted in lysimeters using hydroponics technique. Seeds were allowed to germinate under normal condition (1.5 dS m -1 ) and salinity treatment of 12 dS m -1 was imposed after one week of germination. Crop was irrigated at the interval of two weeks or whenever required with 1/4 th Hoagland nutrient solution of respective concentrations. Results clearly indicated that wheat genotypes with higher proline, K/Na ratio and chlorophyll contents had higher grain yield. On the basis of yield reduction, three genotypes viz. Lu-26s, Sarsabz and KTDH were found tolerant. These genotypes also maintained the higher concentration of proline, K/Na ratio and chlorophyll contents under saline conditions
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