小视角对颜色差别阀的影响

在均匀颜色空间的颜色差别计箅中,亮度和色彩的作用是相关且不同的,尤其是在目标尺度对人眼张角(亦称视角)小于30角度分的条件下观察,由于亮度差和色彩差受视角变化的影响程度不同步,使得人眼颜色差别分辨阈亦不确定。本文通过一定的试验和计算,探讨了在不同的亮度差和色彩差的情况下,颜色差别阈受视角影响的变化规律。     

BNCT优化网格设计及相关算法研究

用MCNP蒙特卡罗程序模拟了硼中子俘获治疗(BNCT)3种国际基准网格模型, 并与 修正的Snyder椭球模型进行了比较. 在此基础上, 给出了一种保质量守恒、内存量少、易于产生输入文件的4种基本材料成分的BNCT网格模型. 计算结果表明, 在4mm网格下, 新模型可以达到基准模型的精度; 根据解析模型剂量随深度的变化规律, 研究构造了多网格组合模型, 在重要区域计算精度不损失的条件下, 计算时间大大缩短. 最后研究给出了一个既保证精度、又在可接受的时间内完成剂量计算的模型、样本数和相应的算法, 它基本上满足临床BNCT的要求.     

透射式跑道能见度激光测量仪的研究

介绍了一种利用激光测量跑道水平及斜视能见度的智能化仪器。该仪器主要由光学系统、信号放大与处理系统及显示系统三部分组成。简要介绍了该仪器的基本结构、工作原理和主要技术指标，讨论了其中的技术难点及其相应的解决办法。     

公安110报警指挥系统组网设计

１１０是电话网中的匪警特服号，现代信息化社会的发展要求１１０接警响应迅速而准确，本文介绍了公安１１０报警指挥系统的组成原理，给出了该系统与公共市话网和公安专网的组网实现方法，并对工程设计中的系统可靠性问题进行了详细的讨论，该系统也可用于１１９报警等其待服业务。     

Spectrophotometric and titrimetric determination of gallium in minerals and ores using semimethylthymol blue

The composition, overall stability constant and molar absorptivity of the chelate of gallium(III) ion with semimethylthymol blue, SMTB, were determined spectrophotometrically in acetate buffer (pH 4.5–5). A violet Ga(SMTB) chelate was formed with logarithmic overall stability constant of 18.0±0.1 (I=0.1) and molar absorptivity of 4.25×10⁴l mol^–1cm^–1 (_max 580 nm). SMTB is proposed as a new reagent for the spectrophotometric determination of micro-molar amounts of gallium(III). The colour development depends on time, temperature, pH and buffer species. The interference of different cations, anions and organic acids on gallium(III) determination was also investigated. Beer's law was obeyed for 3.5–31.3 gGa(III)/25ml (0.14–1.25 g ml^–1). SMTB was used for the spectrophotometric determination of gallium in different grade minerals and ores and the results were of acceptable error and relative standard deviation. Comparison between the two suggested methods and atomic absorption spectrometry for Ga(III) determination was carried out.     

Interaction of chromophore, 11-<Emphasis Type="Italic">cis</Emphasis>-retinal,with amino acid residues of the visual pigment rhodopsin in the region of protonated Schiff base: A molecular dynamics study

A molecular dynamics study of the dark adapted visual pigment rhodopsin molecule was carried out. The interaction of the chromophore group, 11-cis-retinal, with the nearest amino acid residues in the chromophore center of the molecule, namely, in the region of the protonated Schiff base linkage, was analyzed. Most likely, the interaction of the CH=NH bond with the negatively charged amino acid residue Glu113 cannot be described as a simple electrostatic interaction of two oppositely charged groups. One can propose that not only Glu113 but also Glu181 and Ser186 are involved in stabilization of the protonated Schiff base linkage. Accord-ing to calculations, Glu181 interacts, as the counter-ion, with the Schiff base indirectly via Ser186. The intramolecular mechanisms of protonated Schiff base stabilization in rhodopsin are discussed. Published in Russian in Izvestiya Akademii Nauk. Seriya Khimicheskaya, No. 1, pp. 19–27, January, 2007.     

Ion-pair adsorption film colorimetry — A new simple method for ppb level of aluminum ion in water sample

A new, highly sensitive and simple colorimetric method for trace aluminum(III) with 2,2-dihydroxyazobenzene, H₂L, is described, based on the ion-pair adsorption of the anionic Al chelate, [A1L₂ ^–, with crystal violet cation, CV⁺, on the surface of Polyvinylchloride film plasticized with dioctylphthalate. The blue violet species, CV⁺[A1L₂]^–, is enriched onto the transparent film, leading to a remarkable enhancement of the sensitivity, and the detection limits are 3 ng/ml by spectrophotometry and 5 ng/ml by visual colorimetry, respectively. Using spectrophotometer, a linear calibration curve is obtained over the concentration range of 0 to 50 ng/ml of Al. Further, the color system, consisting of red ([A1L₂]^–), yellow (H₂L), and blue violet (CV⁺), gave clear color changes suitable for visual determination of aluminum with an applicable range of 0 to above 3000 ng/ml. The four different color zones are khaki for 0–5 ng/ml, reddish-brown for 5–200 ng/ml, blue violet for 200 ng/ml-3g/ml, and colorless for more than 3g/ml. The proposed method has been successfully applied for the determination of aluminum in tap waters.     

结合视觉Transformer和CNN的道路裂缝检测方法

提出了一种结合视觉Transformer和CNN的道路裂缝检测方法。利用CNN来捕获局部的细节信息,同时利用视觉Transformer来捕获全局特征。通过设计的Fusion特征融合模块将两者提取的特征有机地结合在一起,从而解决了单独使用CNN或视觉Transformer方法存在的局限。最终将结果传递至交互式解码器,生成道路裂缝的检测结果。实验结果表明,无论是在公开的数据集上还是在自建的数据集上,相较于单独使用CNN或视觉Transformer的方法,所提出的方法在道路裂缝检测任务中有更好的效果。     

Infrared-Visible Image Fusion Based on Semantic Guidance and Visual Perception

Infrared-visible fusion has great potential in night-vision enhancement for intelligent vehicles. The fusion performance depends on fusion rules that balance target saliency and visual perception. However, most existing methods do not have explicit and effective rules, which leads to the poor contrast and saliency of the target. In this paper, we propose the SGVPGAN, an adversarial framework for high-quality infrared-visible image fusion, which consists of an infrared-visible image fusion network based on Adversarial Semantic Guidance (ASG) and Adversarial Visual Perception (AVP) modules. Specifically, the ASG module transfers the semantics of the target and background to the fusion process for target highlighting. The AVP module analyzes the visual features from the global structure and local details of the visible and fusion images and then guides the fusion network to adaptively generate a weight map of signal completion so that the resulting fusion images possess a natural and visible appearance. We construct a joint distribution function between the fusion images and the corresponding semantics and use the discriminator to improve the fusion performance in terms of natural appearance and target saliency. Experimental results demonstrate that our proposed ASG and AVP modules can effectively guide the image-fusion process by selectively preserving the details in visible images and the salient information of targets in infrared images. The SGVPGAN exhibits significant improvements over other fusion methods.     

Highly Accurate Visual Method of Mars Terrain Classification for Rovers Based on Novel Image Features

It is important for Mars exploration rovers to achieve autonomous and safe mobility over rough terrain. Terrain classification can help rovers to select a safe terrain to traverse and avoid sinking and/or damaging the vehicle. Mars terrains are often classified using visual methods. However, the accuracy of terrain classification has been less than 90% in read operations. A high-accuracy vision-based method for Mars terrain classification is presented in this paper. By analyzing Mars terrain characteristics, novel image features, including multiscale gray gradient-grade features, multiscale edges strength-grade features, multiscale frequency-domain mean amplitude features, multiscale spectrum symmetry features, and multiscale spectrum amplitude-moment features, are proposed that are specifically targeted for terrain classification. Three classifiers, K-nearest neighbor (KNN), support vector machine (SVM), and random forests (RF), are adopted to classify the terrain using the proposed features. The Mars image dataset MSLNet that was collected by the Mars Science Laboratory (MSL, Curiosity) rover is used to conduct terrain classification experiments. The resolution of Mars images in the dataset is 256 × 256. Experimental results indicate that the RF classifies Mars terrain at the highest level of accuracy of 94.66%.