Designing Haptic Interfaces to Uncover Gestural Patterns in Children

Children with sensory processing differences such as Autism Spectrum Disorder (ASD) may have different gestural patterns compared to their neurotypical peers. However, the evaluation of sensory differences is complicated and subjective, especially when it\u27s related to the tactile sense. Haptic interfaces (i.e., tools that transmit information through touch) allow changing vibrotactile patterns to stimulate children\u27s tactile senses, affecting how children interact with the interface. Therefore, haptic interfaces can be used to collect data on how users interact with them and uncover their gestural patterns. However, it is unclear how to design active haptic interfaces vibration using touch (e.g., mobile phone), wearables (e.g., smartwatch), or ultrasonic (e.g., Stratos) to support the data collection of gesture interaction. As the first step in this work, we proposed the design of Feel and Touch, a haptic game that could be developed for different haptic interfaces, such as mobile, wearable, and ultrasonic. In future work, we proposed to develop the game in the three interfaces and evaluate their usefulness and effectiveness in collecting gestural data, especially for children with ASD. We would like to thank: Ivonne Monarca and Monica Tentori from CICESE Research center

Cold Air Mass Analysis of the Record-Breaking Cold Surge Event over East Asia in January 2016

An extreme cold surge event caused record-breaking low temperatures in East Asia during 20-25 January 2016. The planetary- and synoptic-scale feature of the event is investigated quantitatively using the isentropic cold air mass analysis with a threshold potential temperature of 280 K. Because cold air mass is an adiabatically conservative quantity, it is suitable for tracing and examining the extreme cold surges. We further introduced a metric named mean wind of cold air mass, which divides the factor of cold air mass evolution into convergence and advection parts. The new metric allowed us to trace the evolution of the cold air mass with dynamic consistency for a period of more than a week.  A thick cold air mass built up over southern Sakha by a convergent cold air mass flow during 16-18 January. It migrated westward and reached Lake Baikal. On 20 January, an intense Siberian High developed, with an eastward-moving mid-upper-level ridge, producing a strong surface pressure gradient over the coastal regions of the Asian continent. This ridge and a cutoff low to the adjacent east formed a northerly flow in the mid-upper troposphere. The resultant southward flow through the troposphere blew the cold air mass over 480 hPa in thickness to the subtropical region of East Asia, causing strong cold surges there on 24 and 25 January.  The abnormality of the event is further quantified using extreme value theory. The cold air mass gradually became rare along the path of the cold air mass from Lake Baikal to eastern China, which experienced as thick a cold air mass as once in 200 years. The cold air mass itself shows little change in thickness. Therefore, the migration of a cold air mass over 540 hPa in thickness from northern Siberia is the major cause of this cold surge extreme

A Structure-Guided Diffusion Model for Large-Hole Image Completion

Image completion techniques have made significant progress in filling missing regions (i.e., holes) in images. However, large-hole completion remains challenging due to limited structural information. In this paper, we address this problem by integrating explicit structural guidance into diffusion-based image completion, forming our structure-guided diffusion model (SGDM). It consists of two cascaded diffusion probabilistic models: structure and texture generators. The structure generator generates an edge image representing plausible structures within the holes, which is then used for guiding the texture generation process. To train both generators jointly, we devise a novel strategy that leverages optimal Bayesian denoising, which denoises the output of the structure generator in a single step and thus allows backpropagation. Our diffusion-based approach enables a diversity of plausible completions, while the editable edges allow for editing parts of an image. Our experiments on natural scene (Places) and face (CelebA-HQ) datasets demonstrate that our method achieves a superior or comparable visual quality compared to state-of-the-art approaches. The code is available for research purposes at https://github.com/UdonDa/Structure_Guided_Diffusion_Model.Comment: BMVC2023. Code: https://github.com/UdonDa/Structure_Guided_Diffusion_Mode

Breakdown of the weak coupling limit in quantum annealing

Reverse annealing is a variant of quantum annealing, in which the system is prepared in a classical state, reverse-annealed to an inversion point, and then forward-annealed. We report on reverse annealing experiments using the D-Wave 2000Q device, with a focus on the $p=2$ $p$-spin problem, which undergoes a second order quantum phase transition with a gap that closes polynomially in the number of spins. We concentrate on the total and partial success probabilities, the latter being the probabilities of finding each of two degenerate ground states of all spins up or all spins down, the former being their sum. The empirical partial success probabilities exhibit a strong asymmetry between the two degenerate ground states, depending on the initial state of the reverse anneal. To explain these results, we perform open-system simulations using master equations in the limits of weak and strong coupling to the bath. The former, known as the adiabatic master equation (AME), with decoherence in the instantaneous energy eigenbasis, predicts perfect symmetry between the two degenerate ground states, thus failing to agree with the experiment. In contrast, the latter, known as the polaron transformed Redfield equation (PTRE), is in close agreement with experiment. Thus our results present a challenge to the sufficiency of the weak system-bath coupling limit in describing the dynamics of current experimental quantum annealers, at least for reverse annealing on timescales of a microsecond or longer.Comment: arXiv admin note: substantial text overlap with arXiv:2107.0723

LiDAR Spoofing Meets the New-Gen: Capability Improvements, Broken Assumptions, and New Attack Strategies

LiDAR (Light Detection And Ranging) is an indispensable sensor for precise long- and wide-range 3D sensing, which directly benefited the recent rapid deployment of autonomous driving (AD). Meanwhile, such a safety-critical application strongly motivates its security research. A recent line of research finds that one can manipulate the LiDAR point cloud and fool object detectors by firing malicious lasers against LiDAR. However, these efforts face 3 critical research gaps: (1) considering only one specific LiDAR (VLP-16); (2) assuming unvalidated attack capabilities; and (3) evaluating object detectors with limited spoofing capability modeling and setup diversity. To fill these critical research gaps, we conduct the first large-scale measurement study on LiDAR spoofing attack capabilities on object detectors with 9 popular LiDARs, covering both first- and new-generation LiDARs, and 3 major types of object detectors trained on 5 different datasets. To facilitate the measurements, we (1) identify spoofer improvements that significantly improve the latest spoofing capability, (2) identify a new object removal attack that overcomes the applicability limitation of the latest method to new-generation LiDARs, and (3) perform novel mathematical modeling for both object injection and removal attacks based on our measurement results. Through this study, we are able to uncover a total of 15 novel findings, including not only completely new ones due to the measurement angle novelty, but also many that can directly challenge the latest understandings in this problem space. We also discuss defenses.Comment: The first 3 authors are co-firs