Multi-Granular Trend Detection for Time-Series Analysis

Time series (such as stock prices) and ensembles (such as model runs for weather forecasts) are two important types of one-dimensional time-varying data. Such data is readily available in large quantities but visual analysis of the raw data quickly becomes infeasible, even for moderately sized data sets. Trend detection is an effective way to simplify time-varying data and to summarize salient information for visual display and interactive analysis. We propose a geometric model for trend-detection in one-dimensional time-varying data, inspired by topological grouping structures for moving objects in two- or higher-dimensional space. Our model gives provable guarantees on the trends detected and uses three natural parameters: granularity, support-size, and duration. These parameters can be changed on-demand. Our system also supports a variety of selection brushes and a time-sweep to facilitate refined searches and interactive visualization of (sub-)trends. We explore different visual styles and interactions through which trends, their persistence, and evolution can be explored

Mesh sensitivity in discrete element simulation of flexible protection structures

The Discrete Element Method (DEM) has been employed in recent years to simulate flexible protection structures undergoing dynamic loading due to its inherent aptitude for dealing with inertial effects and large deformations. The individual structural elements are discretized with an arbitrary number of discrete elements, connected by spring-like remote interactions. In this work, we implement this approach using the parallel bond contact model and compare the numerical results at different discretization intervals with the analytical solutions of classical beam theory. Successively, we use the same model to simulate the punching test of a steel wire mesh and quantify the influence of a different number of elements on the macroscopic response

Res2Net: A New Multi-scale Backbone Architecture

Representing features at multiple scales is of great importance for numerous vision tasks. Recent advances in backbone convolutional neural networks (CNNs) continually demonstrate stronger multi-scale representation ability, leading to consistent performance gains on a wide range of applications. However, most existing methods represent the multi-scale features in a layer-wise manner. In this paper, we propose a novel building block for CNNs, namely Res2Net, by constructing hierarchical residual-like connections within one single residual block. The Res2Net represents multi-scale features at a granular level and increases the range of receptive fields for each network layer. The proposed Res2Net block can be plugged into the state-of-the-art backbone CNN models, e.g., ResNet, ResNeXt, and DLA. We evaluate the Res2Net block on all these models and demonstrate consistent performance gains over baseline models on widely-used datasets, e.g., CIFAR-100 and ImageNet. Further ablation studies and experimental results on representative computer vision tasks, i.e., object detection, class activation mapping, and salient object detection, further verify the superiority of the Res2Net over the state-of-the-art baseline methods. The source code and trained models are available on https://mmcheng.net/res2net/.Comment: 11 pages, 7 figure

Magnetic pattern at supergranulation scale: the Void Size Distribution

The large-scale magnetic pattern of the quiet sun is dominated by the magnetic network. This network, created by photospheric magnetic fields swept into convective downflows, delineates the boundaries of large scale cells of overturning plasma and exhibits voids in magnetic organization. Such voids include internetwork fields, a mixed-polarity sparse field that populate the inner part of network cells. To single out voids and to quantify their intrinsic pattern a fast circle packing based algorithm is applied to 511 SOHO/MDI high resolution magnetograms acquired during the outstanding solar activity minimum between 23 and 24 cycles. The computed Void Distribution Function shows a quasi-exponential decay behavior in the range 10-60 Mm. The lack of distinct flow scales in such a range corroborates the hypothesis of multi-scale motion flows at the solar surface. In addition to the quasi-exponential decay we have found that the voids reveal departure from a simple exponential decay around 35 Mm.Comment: 6 pages, 8 figures, to appear in Astronomy and Astrophysic

Pair separation of magnetic elements in the quiet Sun

The dynamic properties of the quiet Sun photosphere can be investigated by analyzing the pair dispersion of small-scale magnetic fields (i.e., magnetic elements). By using $25$ hr-long Hinode magnetograms at high spatial resolution ($0".3$), we tracked $68,490$ magnetic element pairs within a supergranular cell near the disk center. The computed pair separation spectrum, calculated on the whole set of particle pairs independently of their initial separation, points out what is known as a super-diffusive regime with spectral index $\gamma=1.55\pm0.05$, in agreement with the most recent literature, but extended to unprecedented spatial and temporal scales (from granular to supergranular). Furthermore, for the first time, we investigated here the spectrum of the mean square displacement of pairs of magnetic elements, depending on their initial separation $r_0$. We found that there is a typical initial distance above (below) which the pair separation is faster (slower) than the average. A possible physical interpretation of such a typical spatial scale is also provided

Silicon Photomultipliers in Particle and Nuclear Physics

Following first large-scale applications in highly granular calorimeters and in neutrino detectors, Silicon Photomultipliers have seen a wide adoption in accelerator-based particle and nuclear physics experiments. Today, they are used for a wide range of different particle detector types, ranging from calorimeters and trackers to particle identification and veto detectors, large volume detectors for neutrino physics and timing systems. This article reviews the current state and expected evolution of these applications, highlighting strengths and limitation of SiPMs and the corresponding design choices in the respective contexts. General trends and adopted technical solutions in the applications are discussed.Comment: 17 pages, 18 figures, review paper published in Nuclear Instruments and Methods A; v2 correcting a missing figure link in tex