Pohang Canal Dataset: A Multimodal Maritime Dataset for Autonomous Navigation in Restricted Waters

This paper presents a multimodal maritime dataset and the data collection procedure used to gather it, which aims to facilitate autonomous navigation in restricted water environments. The dataset comprises measurements obtained using various perception and navigation sensors, including a stereo camera, an infrared camera, an omnidirectional camera, three LiDARs, a marine radar, a global positioning system, and an attitude heading reference system. The data were collected along a 7.5-km-long route that includes a narrow canal, inner and outer ports, and near-coastal areas in Pohang, South Korea. The collection was conducted under diverse weather and visual conditions. The dataset and its detailed description are available for free download at https://sites.google.com/view/pohang-canal-dataset.Comment: Submitted to IJRR as a data paper for revie

The use of confidence regions to determine objective criteria for analysis of single parameter histograms of mean fluorescence intensity

Several methods have been proposed for comparing fluorescence intensity curves obtained from flow cytometry analysis. The one comparison method that is most often used is the Kolmogorov-Smirnov (K-S) test, which is known to find statistically significant differences between curves even when clinical or scientific differences are doubtful. In the field of flow cytometry, the combination of the gating process and either Overton Subtraction or K-S test yields a histogram subtraction technique for analysis of flow cytometric frequency data. In order to help biologists assess the results of a K-S or other test for the difference between mean fluorescence intensity curves, we have proposed a method of producing bootstrap-based confidence bands around the difference in histograms to show the range of intensity channels for which a difference between histograms may be identified. As an illustration of the method, we obtain and display confidence bands for histogram differences between pumping cell subsets. The confidence bands are constructed using both pointwise and simultaneous confidence bands. We compare the results of these two approaches. Furthermore, for descriptive purposes, the confidence bands produced were found to provide a useful descriptive display to aid in the interpretation of results. Flow cytometry is a major research tool for immunology and, by extension, infectious diseases and public health. Our statistical methodology is applicable to flow cytometry research in a variety of settings

Kernel-convoluted Deep Neural Networks with Data Augmentation

The Mixup method (Zhang et al. 2018), which uses linearly interpolated data, has emerged as an effective data augmentation tool to improve generalization performance and the robustness to adversarial examples. The motivation is to curtail undesirable oscillations by its implicit model constraint to behave linearly at in-between observed data points and promote smoothness. In this work, we formally investigate this premise, propose a way to explicitly impose smoothness constraints, and extend it to incorporate with implicit model constraints. First, we derive a new function class composed of kernel-convoluted models (KCM) where the smoothness constraint is directly imposed by locally averaging the original functions with a kernel function. Second, we propose to incorporate the Mixup method into KCM to expand the domains of smoothness. In both cases of KCM and the KCM adapted with the Mixup, we provide risk analysis, respectively, under some conditions for kernels. We show that the upper bound of the excess risk is not slower than that of the original function class. The upper bound of the KCM with the Mixup remains dominated by that of the KCM if the perturbation of the Mixup vanishes faster than $O(n^{-1/2})$ where $n$ is a sample size. Using CIFAR-10 and CIFAR-100 datasets, our experiments demonstrate that the KCM with the Mixup outperforms the Mixup method in terms of generalization and robustness to adversarial examples

A Feasible Configuration of AFDX Networks for Real-Time Flows in Avionics Systems

REACTION 2013. 2nd International Workshop on Real-time and distributed computing in emerging applications. December 3rd, 2013, Vancouver, Canada.AFDX (Avionics Full Duplex Switched Ethernet) Networks have been proposed to meet unique ADN (Aircraft Data Networks) characteristics and then standardized as a Part 7 in ARNIC 664. As for this new communication technology, some research works have been conducted to address design issues such as optimizing virtual links as well as analytic modeling including response time. Despite of their research efforts, configuration problem for both MTU (Maximum Transmission Unit) and BAG (Bandwidth Allocation Gap) over virtual links in AFDX networks remains unsolved yet. In this paper, we propose how to set MTU and BAG value on each virtual link according to both application requirements and AFDX switch constraints. We define a new problem of feasible configurations of virtual links in an AFDX switch and propose an algorithm to derive feasible BAG and MTU pairs based on the branch-and-bound technique. Throughout simulations, we evaluate the proposed algorithm and analyze the effect of parameters in AFDX networks.This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. NRF- 2012R1A1A1015096) and BK21+ Program

Persistent metallic Sn-doped In2O3 epitaxial ultrathin films with enhanced infrared transmittance

Infrared transparent electrodes (IR-TEs) have recently attracted much attention for industrial and military applications. The simplest method to obtain high IR transmittance is to reduce the electrode film thickness. However, for films several tens of nanometres thick, this approach unintentionally suppresses conduction due to surface electron scattering. Here, we demonstrate low sheet resistance (<400 Ω □−1 at room temperature) and high IR transmittance (>65% at the 2.5-μm wavelength) in Sn-doped In2O3 (ITO) epitaxial films for the thickness range of 17−80 nm. A combination of X-ray spectroscopy and ellipsometry measurements reveals a persistent electronic bandstructure in the 8-nm-thick film compared to much thicker films. This indicates that the metallicity of the film is preserved, despite the ultrathin film configuration. The high carrier mobility in the ITO epitaxial films further confirms the film’s metallicity as a result of the improved crystallinity of the film and the resulting reduction in the scattering defect concentration. Thus, ITO shows great potential for IR-TE applications of transparent photovoltaic and optoelectronic devices. © 2020, The Author(s).1

Learning Topology-Specific Experts for Molecular Property Prediction

Recently, graph neural networks (GNNs) have been successfully applied to predicting molecular properties, which is one of the most classical cheminformatics tasks with various applications. Despite their effectiveness, we empirically observe that training a single GNN model for diverse molecules with distinct structural patterns limits its prediction performance. In this paper, motivated by this observation, we propose TopExpert to leverage topology-specific prediction models (referred to as experts), each of which is responsible for each molecular group sharing similar topological semantics. That is, each expert learns topology-specific discriminative features while being trained with its corresponding topological group. To tackle the key challenge of grouping molecules by their topological patterns, we introduce a clustering-based gating module that assigns an input molecule into one of the clusters and further optimizes the gating module with two different types of self-supervision: topological semantics induced by GNNs and molecular scaffolds, respectively. Extensive experiments demonstrate that TopExpert has boosted the performance for molecular property prediction and also achieved better generalization for new molecules with unseen scaffolds than baselines. The code is available at https://github.com/kimsu55/ToxExpert.Comment: 11 pages with 8 figure

Spontaneous generation and active manipulation of real-space optical vortex

Optical vortices host the orbital nature of photons, which offers an extra degree of freedom in photonic applications. Unlike vortices in other physical entities, optical vortices require structural singularities, which restrict their abilities in terms of dynamic and interactive characteristics. In this study, we present the spontaneous generation and external magnetic field-induced manipulation of an optical vortex and antivortex. A gradient-thickness optical cavity (GTOC) consisting of an Al/SiO2/Ni/SiO2 multilayer structure realised the distinct transition between the trivial and non-trivial topological phases, depending on the magneto-optic effects of the Ni layer. In the non-trivial topological phase, the mathematical singularities generating the optical vortex and antivortex pair in the reflected light existed in the generalised parameter space of the thicknesses of the top and bottom SiO2 layers, which is bijective to the real space of the GTOC. Coupled with the magnetisation, the optical vortex and antivortex in the GTOC experienced an effective spin-orbit interaction and showed topology-dependent dynamics under external magnetic fields. We expect that field-induced engineering of optical vortices will pave the way for the study of topological photonic interactions and their applications.Comment: 22 pages, 4 figure

Optimal Configuration of Virtual Links for Avionics Network Systems

As the bandwidth and scalability constraints become important design concerns in airborne networks, a new technology, called Avionics Full Duplex Switched Ethernet (AFDX), has been introduced and standardized as a part 7 in ARNIC 664. However, since previous research interests for AFDX are mainly bounded for analyzing the response time where flows information is given, configuration problem for both Maximum Transmission Unit (MTU) and Bandwidth Allocation Gap (BAG) over virtual links in AFDX networks has not been addressed yet even though it has great impact on required bandwidth. Thus, in this paper, we present two configuration approaches to set MTU and BAG values on virtual links efficiently while meeting the requirement of AFDX. The first is to search available feasible configuration (MTU, BAG) pairs to satisfy application requirements as well as AFDX switch constraints, and the second is to get an optimal pair to minimize required bandwidth through well-known branch-and-bound algorithm. We analyze the complexity of the proposed algorithm and then evaluate the proposed algorithm by simulation. Finally, we prove that the proposed schemes are superior to general approach in the aspects of speed and required bandwidth in AFDX networks