基于深度学习的视频跟踪研究进展综述

近年来深度学习迅猛发展，颠覆了语音识别、图像分类、文本理解等领域的算法设计思路。深度学习因其具备强大的特征提取能力，在图像识别领域的成绩尤为突出。然而深度学习与视频监控领域的结合并不多，由于深度模型具有多层网络结构，算法复杂度大，训练和更新模型时比较耗时，很难满足实时性要求。回顾了深度学习的发展史，介绍了最近10年来国内外深度学习主要模型，论述了基于深度学习的目标跟踪算法，指出了各算法的优缺点，最后对当前该领域存在的问题和发展前景进行了总结和展望。     

Iron mediated cathodic electrosynthesis of hausmannite nanoparticles

A novel synthetic route has been proposed to prepare hausmannite nanoparticles. The synthetic route comprises an iron mediated constant current cathodic electrodeposition of manganite and heat treatment of the latter to obtain hausmannite. The obtained nanostructures have been characterized using X-ray Diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectrometry (EDX) and Fourier transform Infrared Spectrometry (FTIR). The role of iron in the formation of manganite precursor has been studied by cyclic voltammetry (CV) and differential thermal analysis (DTA). A formation mechanism based on iron mediated formation of Mn³⁺ and subsequent cathodic reduction of the disproportionated products has been proposed accordingly. The prepared nanoparticles exhibited specific capacitance of 143 F g⁻¹ in 0.5 M Na₂SO₄ solution. The retained specific capacity was 87% after 2000 cycles.     

An efficient video summarization for surveillance system using normalized k-means and quick sort method

There has been a vast augmentation in quantity of Video Content (VC) generated amid the last some years. The Video Summarization (VS) approach is introduced for managing the VC. Prevailing VS techniques have endeavored to render the VS but the systems have Execution Time (ET) as well as condensing the video's content in domain specific manner. To triumph over such disadvantages, this paper proposed efficient VS for surveillance system using normalized k-means along with quick sort method. The proposed technique comprises eight stages, like split video into frames, pre-sampling, provide ID number, feature extraction, Feature Selection (FS), clustering, extract frames, video summary. Initially, the video frames are pre-sampled utilizing the proposed Three Step Cross Searching Algorithm (TSCS) technique. Then, give the ID number for every frame. Next, the features are extracted as of the frames. Then, the necessary features are selected using Entropy based Spider Monkey Algorithms (ESMA). In next stage, the features are grouped using Normalized K-Means (N-Kmeans) algorithm for identifying best candidate frames. Then select the minimum distance value based cluster set is the Key Frame (KF) selection. At last, the video is orderly summarized using quick sort method. Finally, in experimental evaluation the proposed work is compared with the prevailing methods. The proposed VS gave better outcome than the existing approaches.     

Time-domain viscoelastic constitutive model based on concurrent fitting of frequency-domain characteristics

A numerical procedure for constructing the multiaxial viscoelastic model for polymeric packaging material over a wide range of temperature is presented. By using the proposed best-fitting procedure, experimentally measured frequency-domain Young's and shear storage moduli are used to calculate the time-domain bulk and shear relaxation moduli which describe the three-dimensional constitutive behavior of a viscoelastic solid. The numerical procedure incorporates restrictions that ensure that the derived time-domain material function is physics compatible. The proposed procedure was applied to construct the viscoelastic constitutive models of epoxy molding compounds (EMCs), and compared to results obtained by using approximate-formula based direct conversion procedure. It was shown that, without using the proposed procedure, the directly calculated time-dependent Poisson's ratio oscillates significantly in the rubbery regime and is physically inadmissible. To validate the constitutive model constructed by using the proposed procedure, a numerical finite element model that incorporates the viscoelastic constitutive model of the EMC was applied to simulate warpage of an overmolded package under the solder reflow process and compared to experimental shadow Moiré measurements.     

Image Super-Resolution Based on Generative Adversarial Networks: A Brief Review

Single image super resolution (SISR) is an important research content in the field of computer vision and image processing. With the rapid development of deep neural networks, different image super-resolution models have emerged. Compared to some traditional SISR methods, deep learning-based methods can complete the superresolution tasks through a single image. In addition, compared with the SISR methods using traditional convolutional neural networks, SISR based on generative adversarial networks (GAN) has achieved the most advanced visual performance. In this review, we first explore the challenges faced by SISR and introduce some common datasets and evaluation metrics. Then, we review the improved network structures and loss functions of GAN-based perceptual SISR. Subsequently, the advantages and disadvantages of different networks are analyzed by multiple comparative experiments. Finally, we summarize the paper and look forward to the future development trends of GAN-based perceptual SISR.     

Zinc doped Fe2O3 for boosting Electrocatalytic Nitrogen Fixation to ammonia under mild conditions

Artificial nitrogen fixation is emerging as a promising approach for synthesis of ammonia at mild conditions. Inspired by biological nitrogen fixation based on bacteria containing iron, zinc doped Fe₂O₃ nanoparticles are proposed as an efficient and earth abundant electrocatalyst for converting N₂ to NH₃. In neutral media, it achieves a maximum Faradaic efficiency (FE) of 10.4% and a large NH₃ yield rate of 15.1 μg h^?1 mg^?1_cat. at ?0.5 V vs. reversible hydrogen electrode. This catalyst also exhibits excellent selectivity and stability. Theoretical calculations suggest the reaction follows the associative enzymatic mechanism and it has a barrier of as low as 0.68 eV.     

Enhanced transduction coefficient in piezoelectric PZT ceramics by mixing powders calcined at different temperatures

Large transduction coefficient ($d_{33}\times g_{33}$) is difficult to obtain in piezoelectric ceramics because these two parameters show opposite trends with compositional modifications. Herein, the Pb(Zr_0.53Ti_0.47)O₃ ceramic powders were calcinated under different temperatures (A:830 °C, B:860 °C, and C:890 °C), and then mixed together according to different weight ratios (1A:1B:1C, 1A:2B:1C, 1A:2B:3C and 3A:2B:1C) for ceramics preparation. Both d₃₃ and g₃₃ are improved successfully, and the transduction coefficient with the weight ratio of 1A:2B:3C reaches up to 17,500 × 10⁻¹⁵ m²/N, which is 60 % higher than that with the powders calcinated under 830 °C, and at least twice those of commercial PZT-4, PZT-5A and PZT-8 ceramics. The improved transduction coefficient is owing to the enhanced piezoelectric constant and spontaneous polarization resulted from the increased grain size, relative density and the fraction of tetragonal phase. These results indicate that this is a simple but effective way to tailor the transduction coefficient in piezoelectric ceramics.     

Compiler compatible 5.66 Mb/mm2 8T 1R1W register file in 14 nm FinFET technology

1-read/1-write (1R1W) register file (RF) is a popular memory configuration in modern feature rich SoCs requiring significant amount of embedded memory. A memory compiler is constructed using the 8T RF bitcell spanning a range of instances from 32 b to 72 Kb. An 8T low-leakage bitcell of 0.106 μm² is used in a 14 nm FinFET technology with a 70 nm contacted gate pitch for high-density (HD) two-port (TP) RF memory compiler which achieves 5.66 Mb/mm² array density for a 72 Kb array which is the highest reported density in 14 nm FinFET technology. The density improvement is achieved by using techniques such as leaf-cell optimization (eliminating transistors), better architectural planning, top level connectivity through leaf-cell abutment and minimizing the number of unique leaf-cells. These techniques are fully compatible with memory compiler usage over the required span. Leakage power is minimized by using power-switches without degrading the density mentioned above. Self-induced supply voltage collapse technique is applied for write and a four stack static keeper is used for read Vmin improvement. Fabricated test chips using 14 nm process have demonstrated 2.33 GHz performance at 1.1 V/25 °C operation. Overall V_min of 550 mV is achieved with this design at 25 °C. The inbuilt power-switch improves leakage power by 12x in simulation. Approximately 8% die area of a leading 14 nm SoC in commercialization is occupied by these compiled RF instances.     

High birefringence photonic bandgap fiber with elliptical air holes

In this paper, we proposed a high birefringence photonic bandgap fiber (PBGF) with elliptical air holes in cladding and circular air hole in core. The forbidden gaps of the honeycomb structure are calculated when the circular air holes are deformed to the elliptical shape. And the birefringence of the PBGFs is investigated by using a full-vector finite element method (FEM) and the numerical results are presented.