V2CE: Video to Continuous Events Simulator

Dynamic Vision Sensor (DVS)-based solutions have recently garnered significant interest across various computer vision tasks, offering notable benefits in terms of dynamic range, temporal resolution, and inference speed. However, as a relatively nascent vision sensor compared to Active Pixel Sensor (APS) devices such as RGB cameras, DVS suffers from a dearth of ample labeled datasets. Prior efforts to convert APS data into events often grapple with issues such as a considerable domain shift from real events, the absence of quantified validation, and layering problems within the time axis. In this paper, we present a novel method for video-to-events stream conversion from multiple perspectives, considering the specific characteristics of DVS. A series of carefully designed losses helps enhance the quality of generated event voxels significantly. We also propose a novel local dynamic-aware timestamp inference strategy to accurately recover event timestamps from event voxels in a continuous fashion and eliminate the temporal layering problem. Results from rigorous validation through quantified metrics at all stages of the pipeline establish our method unquestionably as the current state-of-the-art (SOTA).Comment: 6 pages, 7 figure

Pseudo 3D viscoelastic winding model

A pseudo 3D winding model that has considered orthotropic viscoelastic effects during winding and storage has been developed and implemented in a code revised from the 2D viscoelastic winding code developed by Qualls and Good [1]. The model discretizes the web into smaller segments of equal width, each having a constant web thickness within a segment. Tension is assigned to each segment using Hakiel's approach [2]; the tension is updated after the winding of each lap based on the deformed radius of the segment relative to the relaxed radius profile of that lap. In each segment, a 2D winding model is applied. The pseudo 3D model is capable of dealing with (1) a varying thickness profile in both CMD (cross machine direction) and MD (machine direction); (2) winding tension variation with the winding laps; and (3) varying core stiffness in the CMD. Moreover, with the consideration of viscoelastic behavior in the web the effects of winding conditions, such as winding speed and tension, on the wound roll stress can be determined. The model is especially suitable for viscoelastic materials with relatively short characteristic relaxation times, such as plastic webs with glass transition temperature close to room temperature. Numerical methods were used to determine the stress distributions in the wound roll. The pseudo 3D viscoelastic winding model was validated by comparing results on the dimensional changes of a web in three situations. They include (1) the formation of cambered web (in-plane imperfection) due to linearly varying thickness; and (2) the formation of localized baggy lanes due to an edge burr following slitting; and (3) the formation of baggy web (out-of-plane imperfection) due to increased web thickness in the middle of the web. Simulation results compare favorably with experimental data.Mechanical and Aerospace Engineerin

Comprehensive evaluation of deep and graph learning on drug-drug interactions prediction

Recent advances and achievements of artificial intelligence (AI) as well as deep and graph learning models have established their usefulness in biomedical applications, especially in drug-drug interactions (DDIs). DDIs refer to a change in the effect of one drug to the presence of another drug in the human body, which plays an essential role in drug discovery and clinical research. DDIs prediction through traditional clinical trials and experiments is an expensive and time-consuming process. To correctly apply the advanced AI and deep learning, the developer and user meet various challenges such as the availability and encoding of data resources, and the design of computational methods. This review summarizes chemical structure based, network based, NLP based and hybrid methods, providing an updated and accessible guide to the broad researchers and development community with different domain knowledge. We introduce widely-used molecular representation and describe the theoretical frameworks of graph neural network models for representing molecular structures. We present the advantages and disadvantages of deep and graph learning methods by performing comparative experiments. We discuss the potential technical challenges and highlight future directions of deep and graph learning models for accelerating DDIs prediction.Comment: Accepted by Briefings in Bioinformatic

Study of Peeling of Single Crystal Silicon by Intense Pulsed Ion Beam

The surface peeling process induced by intense pulsed ion beam (IPIB) irradiation was studied. Single crystal silicon specimens were treated by IPIB with accelerating voltage of 350 kV current density of 130 A/cm2. It is observed that under smaller numbers of IPIB shots, the surface may undergo obvious melting and evaporation..

Ultra-efficient frequency comb generation in AlGaAs-on-insulator microresonators

Recent advances in nonlinear optics have revolutionized integrated photonics, providing on-chip solutions to a wide range of new applications. Currently, state of the art integrated nonlinear photonic devices are mainly based on dielectric material platforms, such as Si₃N₄ and SiO₂. While semiconductor materials feature much higher nonlinear coefficients and convenience in active integration, they have suffered from high waveguide losses that prevent the realization of efficient nonlinear processes on-chip. Here, we challenge this status quo and demonstrate a low loss AlGaAs-on-insulator platform with anomalous dispersion and quality (Q) factors beyond 1.5 × 10⁶. Such a high quality factor, combined with high nonlinear coefficient and small mode volume, enabled us to demonstrate a Kerr frequency comb threshold of only ∼36 µW in a resonator with a 1 THz free spectral range, ∼100 times lower compared to that in previous semiconductor platforms. Moreover, combs with broad spans (>250 nm) have been generated with a pump power of ∼300 µW, which is lower than the threshold power of state-of the-art dielectric micro combs. A soliton-step transition has also been observed for the first time in an AlGaAs resonator

Study of Peeling of Single Crystal Silicon by Intense Pulsed Ion Beam

The surface peeling process induced by intense pulsed ion beam (IPIB) irradiation was studied. Single crystal silicon specimens were treated by IPIB with accelerating voltage of 350 kV current density of 130 A/cm2. It is observed that under smaller numbers of IPIB shots, the surface may undergo obvious melting and evaporation..

Study on Ablation Products of Zinc by Intense Pulsed Ion Beam Irradiation

As a kind of flash heat source, intense pulse ion beam can be used for material surface modification. The ablation effect has important influence on interaction between IPIB and material. Therefore, the understanding of ablation mechanism is of great significance to IPIB application..

Study of the intense pulsed electron beam energy spectrum from BIPPAB-450

Intense pulsed particle beams have been widely used and studied as an effective method for material surface modification in the past several decades. Beihang Intense Pulsed PArticle Beams 450 accelerator (BIPPAB-450) can produce Intense Pulsed Ion Beams (IPIB) and Electron Beams (IPEB) in two modes with different Magnetically Insulated Diodes (MID). For IPEB, the pulse duration, accelerating voltage, total beam current are 100ns, up to 450keV and 3kA, respectively..