Smaller Output Beam Divergence in the Slowly Opened Q-Switch Operation

The mechanism of the slowly opened Q-switch operation was investigated thoroughly. Maximum energy extraction from the resonator could be optimized, and the smallest output beam divergence could be achieved. In this article, we present a detailed analysis that has numerically verified the mode-selection mechanism in the slowly opened Q-switch operation, and the degree of the smaller output laser beam divergence that has been achieved. The mechanism of the slowly opened Q-switch operation is the inherent advantage of the passive saturable absorber in this operation. We can use the maximum energy extraction and the smallest output beam divergence results of the slowly opened Q-switch operation to design and optimize various passive saturable absorbers: plastic dye sheets, LiF:F₂⁻ color center crystals, Cr4⁺: YAG crystals, RG1000 color glass filters, and the single crystal semiconductor saturable absorber wafers that are in developed in our microchip laser systems.     

Ising-like field theory

A field theory model onR ² in which the basic fields are Ising spins instead of Gaussian spins is examined. Using statistical mechanics techniques we discuss the ultraviolet and the infrared problems. In particular we discuss a technique yielding the asymptotic expansion in of the ground state energy, as 0, without using the cluster expansion.Supported in part by Consiglio Nazionale delle Ricerche.     

Addendum to “Spatiotemporal evolution in a (2+1) -dimensional chemotaxis model” [Physica A 391 (2012) 107–112]

After our article, Physica A 391 (2012) 107–112, had been published online, T. Hillen told us about a theorem by Osaki, relevant for our numerical simulations.     

A combined approach of Kullback–Leibler divergence and background subtraction for moving object detection in thermal video

In this work, a robust method for moving object detection in thermal video frames has been proposed by including Kullback–Leibler divergence (KLD) based threshold and background subtraction (BGS) technique. A trimmed-mean based background model has been developed that is capable enough to reduce noise or dynamic component of the background. This work assumed that each pixel has normally distributed. The KLD has computed between background pixel and a current pixel with the help of Gaussian mixture model. The proposed threshold is useful enough to classify the state of each pixel. The post-processing step uses morphological tool for edge linking, and then the flood-fill algorithm has applied for hole-filling, and finally the silhouette of targeted object has generated. The proposed methods run faster and have validated over various real-time based problematic thermal video sequences. In the experimental results, the average value of F₁-score, area under the curve, the percentage of correct classification, Matthew’s correlation coefficient show higher values whereas total error and percentage of the wrong classification show minimum values. Moreover, the proposed-1 method achieved higher accuracy and execution speed with minimum false alarm rate that has been compared with proposed-2 as well as considered peer methods in the real-time thermal video.     

915 nm宽条形半导体激光器输出特性

为了研究温升对915 nm宽条形应变量子阱半导体激光器输出特性的影响,搭建了基于半导体制冷片(TEC)的双向温控平台对其进行了测试。首先,改变激光器的外表面温度,测量其在不同注入电流时的光功率和波长,并利用CCD相机测量其慢轴发散角。然后,利用计算机仿真软件对激光器的工作状态进行稳态模拟,从而获得了其对应的热分布情况,通过将模拟得到的数据与实验测量的结果进行比较,获得了两者趋于一致的结论:当热功率从2.1 W升高至20.0 W时,慢轴发散角从2.6°增大至5.0°,同时波长发生红移,热透镜焦距减小;激光器波长随温度变化关系的系数约为0.4 nm/℃,器件热阻为1.5 K/W。因此,为了同时获得高的输出功率和稳定的输出波长,有必要将激光器外表面温度精确控制在某一数值,否则波长将会发生漂移;此外,在设计制作高功率半导体激光器时,通过适当增加条宽并采用散热良好的封装结构,可以减小对慢轴发散角的影响。     

Network Bending: Expressive Manipulation of Generative Models in Multiple Domains

This paper presents the network bending framework, a new approach for manipulating and interacting with deep generative models. We present a comprehensive set of deterministic transformations that can be inserted as distinct layers into the computational graph of a trained generative neural network and applied during inference. In addition, we present a novel algorithm for analysing the deep generative model and clustering features based on their spatial activation maps. This allows features to be grouped together based on spatial similarity in an unsupervised fashion. This results in the meaningful manipulation of sets of features that correspond to the generation of a broad array of semantically significant features of the generated results. We outline this framework, demonstrating our results on deep generative models for both image and audio domains. We show how it allows for the direct manipulation of semantically meaningful aspects of the generative process as well as allowing for a broad range of expressive outcomes.     

Wavelet Bases for Confinements of the Infrared Divergence

We propose the construction of wavelet bases with pseudo-polynomials adapted to the homogeneous Sobolev spaces , s−n/2∈ℕ. They provide a confinement of the infrared divergence by decomposing as a direct sum X ⊕ Y where X is a “small” space which carries the divergence and Y can be embedded in . In the case of we also construct such an orthonormal basis, which provides a confinement of the Mumford process.     

Lukasiewicz 命题逻辑系统一种新的理论的相容度

根据演绎定理和完备性定理,应用公式真度理论在Lukasiewicz命题模糊逻辑系统中讨论理论Γ的相容性,根据矛盾式■是Γ-结论的真度的大小,提出了一种新的极指标和相容度的概念.给出了理论Γ相容、不相容及其它相关结论的充分必要条件,并且获得了相容度与发散度之间联系的重要关系式.     

GDP vs. LDP: A Survey from the Perspective of Information-Theoretic Channel

The existing work has conducted in-depth research and analysis on global differential privacy (GDP) and local differential privacy (LDP) based on information theory. However, the data privacy preserving community does not systematically review and analyze GDP and LDP based on the information-theoretic channel model. To this end, we systematically reviewed GDP and LDP from the perspective of the information-theoretic channel in this survey. First, we presented the privacy threat model under information-theoretic channel. Second, we described and compared the information-theoretic channel models of GDP and LDP. Third, we summarized and analyzed definitions, privacy-utility metrics, properties, and mechanisms of GDP and LDP under their channel models. Finally, we discussed the open problems of GDP and LDP based on different types of information-theoretic channel models according to the above systematic review. Our main contribution provides a systematic survey of channel models, definitions, privacy-utility metrics, properties, and mechanisms for GDP and LDP from the perspective of information-theoretic channel and surveys the differential privacy synthetic data generation application using generative adversarial network and federated learning, respectively. Our work is helpful for systematically understanding the privacy threat model, definitions, privacy-utility metrics, properties, and mechanisms of GDP and LDP from the perspective of information-theoretic channel and promotes in-depth research and analysis of GDP and LDP based on different types of information-theoretic channel models.