A Tentative Study of Local Colorism Writing Style through Mark Twain's Work

Local colorism as a trend first came to prominence in the late 19th century in America. The local colorists were devoted to capturing the unique customs, manners, speech, folklore and other qualities of a particular regional community, usually in humorous short stories. The most famous local colorist was Mark Twain. His fiction The Adventures of Huckleberry Finn, published in 1884, was regarded as"the first great novel in America", as well as the most classical work of local colorism.

Design and fabrication of structural color by local surface plasmonic meta-molecules

In this paper, we propose a new form of nanostructures with Al film deposited on a patterned dielectric material for generating structural color, which is induced by local surface plasmonic resonant(LSPR) absorption in sub-wavelengthindented hole/ring arrays. Unlike other reported results obtained by using focus ion beam(FIB) to create metallic nanostructures, the nano-sized hole/ring arrays in Al film in this work are replicated by high resolution electron beam lithography(EBL) combined with self-aligned metallization. Clear structural color is observed and systematically studied by numerical simulations as well as optical characterizations. The central color is strongly related to the geometric size, which provides us with good opportunities to dye the colorless Al surface by controlling the hole/ring dimensions(both diameter and radius), and to open up broad applications in display, jewelry decoration, green production of packing papers, security code,and counterfeits prevention.

A New Method of Color Edge Detection Based on Local Structure Analysis

Human's real life is within a colorful world. Compared to the gray images, color images contain more information and have better visual effects. In today's digital image processing, image segmentation is an important section for computers to "understand" images and edge detection is always one of the most important methods in the field of image segmentation. Edges in color images are considered as local discontinuities both in color and spatial domains. Despite the intensive study based on integration of single-channel edge detection results, and on vector space analysis, edge detection in color images remains as a challenging issue.

PRELIMINARY APPLICATION OF COLOR DOPPLER FLOW IMAGING IN THE LOCALIZATION OF PARATHYROID ADENOMAS

From December 1991 to April 1993, we performed color Doppler flow imaging (CDFI) in 11 patients with parathyroid adenoma, and all cases were confirmed by operation and pathology. In all the parathyroid adenomas,vessels were clearly revealed at the periphery of the upper pole and/or anterior periphery, where arterial signals were elicited. These arteries had branches into the adenomas and originated from inferior thyroid arteries on the same side in most cases. The internal flow signals were increased markedly as compared to normal thyroid, and high-velocity arterial signals were detected. Because of the thyroid' s rich blood supply and landmark peripheral vessels, CDFI can distinguish parathyroid foci from thyroid nodules, lymph nodes, and normal tissues and provide a sound basis for the diagnosis of small parathyroid foci.

Face Detection and Localization in Color Images: An Efficient Neural Approach

Automatic face detection and localization is a key problem in many computer vision tasks. In this paper, a simple yet effective approach for detecting and locating human faces in color images is proposed. The contribution of this paper is twofold. First, a particular reference to face detection techniques along with a background to neural networks is given. Second, and maybe most importantly, an adaptive cubic-spline neural network is designed to be used to detect and locate human faces in uncontrolled environments. The experimental results conducted on our test set show the effectiveness of the proposed approach and it can compare favorably with other state-of-the-art approaches in the literature.

Local Colorism American Novels of 19th Century

Local Colorism can be seen as a new literature type, which sprung up in 1920s. As a literature trend, local novels open a new road for realistically sentimental novels of view literature. Therefore, this paper is aim to study the Local Colorism American Novels of 19th Century, especially in west and south of American. American southern literature and western literature although established respectively unique sense of place suffer from complex history. And it proves that American literature has been increasingly building it popularity and a new type of literature.

Hybrid Color Texture Features Classification Through ANN for Melanoma

Melanoma is of the lethal and rare types of skin cancer.It is curable at an initial stage and the patient can survive easily.It is very difficult to screen all skin lesion patients due to costly treatment.Clinicians are requiring a correct method for the right treatment for dermoscopic clinical features such as lesion borders,pigment networks,and the color of melanoma.These challenges are required an automated system to classify the clinical features of melanoma and non-melanoma disease.The trained clinicians can overcome the issues such as low contrast,lesions varying in size,color,and the existence of several objects like hair,reflections,air bubbles,and oils on almost all images.Active contour is one of the suitable methods with some drawbacks for the segmentation of irre-gular shapes.An entropy and morphology-based automated mask selection is pro-posed for the active contour method.The proposed method can improve the overall segmentation along with the boundary of melanoma images.In this study,features have been extracted to perform the classification on different texture scales like Gray level co-occurrence matrix(GLCM)and Local binary pattern(LBP).When four different moments pull out in six different color spaces like HSV,Lin RGB,YIQ,YCbCr,XYZ,and CIE L*a*b then global information from different colors channels have been combined.Therefore,hybrid fused texture features;such as local,color feature as global,shape features,and Artificial neural network(ANN)as classifiers have been proposed for the categorization of the malignant and non-malignant.Experimentations had been carried out on datasets Dermis,DermQuest,and PH2.The results of our advanced method showed super-iority and contrast with the existing state-of-the-art techniques.

长城色彩折射的建造技艺、管理制度与民族智慧

与宫殿、寺庙、石窟等建筑遗产相比,长城在材料色彩方面“乏善可陈”,甚至还出现专有名词“长城灰”,将长城的色彩特征固化。本文通过无人机采集明长城全线图像并引入图像类人工智能提取其主色调,首次量化各段长城色彩、绘制全线色彩地图,证明长城“富彩”;并结合材料成分分析、史料挖掘,首次揭示色彩背后蕴含的长城材料色彩法则、色彩质量评价标准与奖励办法,以及以色立威、以建止战的核心意图。这一成果尝试填补古代建筑色彩研究的长城缺环、揭示长城作为军事遗产的材料色彩艺术造诣,挖掘出未开发长城段新的遗产景观资源,从全新的视角助推长城国家文化公园建设。

基于持续学习的中医舌色苔色协同分类方法

中医(traditional Chinese medicine, TCM)舌诊客观化研究中需要分析的舌象特征很多,不同的舌象特征往往采用单独的方法进行分析,导致分析系统的整体实现复杂度大幅增加。为此,基于持续学习的思想,提出一种中医舌色苔色协同分类方法,该方法将舌色分类作为旧任务,将苔色分类作为新任务,充分利用2个任务的相似性和相关性,仅通过一个网络结构就同时实现舌色和苔色的准确分类。首先,设计一种基于全局-局部混合注意力机制(global local hybrid attention, GLHA)的双分支网络结构,将网络高层语义特征与低层特征相融合,提升特征的表达能力;然后,提出基于正则化和回放相结合的持续学习策略,使得该网络在学习新任务知识的同时有效防止对旧任务知识的遗忘。在2个自建的中医舌象特征分析数据集上的实验结果表明,提出的协同分类方法可以获得与单个任务相当的分类性能,同时可以将2个分类任务的整体复杂度降低一半左右。其中,舌色分类准确率分别达到93.92%和92.97%,精确率分别达到93.69%和92.87%,召回率分别达到93.96%和93.16%;苔色分类准确率分别达到90.17%和90.26%,精确率分别达到90.05%和90.17%,召回率分别达到90.24%和90.29%。

电致变色材料微纳结构设计及多波段调控应用研究进展

电致变色材料具有在外电场下光响应性质可逆变化的特性,由于其响应可控、能耗小、多波段可兼容等优势在光热管理应用方面极具发展潜力。然而,传统的电致变色材料存在调控慢、变色单一、调控波段窄的局限性,限制了电致变色技术的进一步发展。近年来,微纳结构化的电致变色材料实现了循环性能改善、灵活的响应光谱选择性等优势,成为一种行之有效的调控手段并引起了研究者重点关注。本文介绍了电致变色器件(ECD)的基本结构,并围绕扩散动力学、结构色设计、局域表面等离激元共振机理对近几年ECD结构设计的研究进展进行重点论述,分析了多波段兼容响应ECD潜在的应用前景。最后,总结了电致变色材料目前面临的挑战并展望其未来发展方向。

基于语义和几何一致性的视觉SLAM回环检测算法

回环检测是消除同时定位与地图构建(simultaneous localization and mapping,SLAM)系统中累计误差的关键所在,在光照条件或视角变化较大的情况下,传统的基于外观的回环检测方法往往失效。针对这种情况,在ORBSLAM2的框架基础上提出一种物体级的回环检测方法。利用目标检测获得的语义信息和特征点信息构建物体级语义地图。将语义地图抽象成拓扑图并将地标抽象成节点,用颜色直方图描述节点信息,结合节点间的几何关系,基于语义和几何一致性约束,提出一种图匹配方法实现回环检测。当检测到回环时,通过物体对齐的方式进行回环校正。在公开的TUM和USTC数据集上进行实验,结果表明提出的系统精度较ORBSLAM2平均提高了49.58%,并且构建的语义地图显示出良好的定位效果。

纳米级光学超分辨成像技术研究及展望

荧光显微成像技术能够将细胞生理活动可视化,是现代生命科学研究的重要手段。超分辨成像技术的出现将研究推进到亚细胞结构层次,而具有纳米级分辨率的单分子定位成像技术成为了研究细胞器、大分子复合物空间分布及相互作用的有力工具。继2014年超分辨成像技术获得诺贝尔化学奖后,《自然》(Nature)发布的2024年值得关注的七大技术中再次将纳米级分辨率光学成像技术作为热点进行介绍,超高分辨率成像技术是重要的前沿研究领域。本文首先简要介绍了荧光显微成像技术的发展历史、荧光显微镜的基础概念、超分辨成像技术的基本概况,之后着重介绍了单分子超分辨成像技术的研究进展,并在最后对该技术的发展及应用做了展望。

Adaptive Segmentation for Unconstrained Iris Recognition

In standard iris recognition systems,a cooperative imaging framework is employed that includes a light source with a near-infrared wavelength to reveal iris texture,look-and-stare constraints,and a close distance requirement to the capture device.When these conditions are relaxed,the system’s performance significantly deteriorates due to segmentation and feature extraction problems.Herein,a novel segmentation algorithm is proposed to correctly detect the pupil and limbus boundaries of iris images captured in unconstrained environments.First,the algorithm scans the whole iris image in the Hue Saturation Value(HSV)color space for local maxima to detect the sclera region.The image quality is then assessed by computing global features in red,green and blue(RGB)space,as noisy images have heterogeneous characteristics.The iris images are accordingly classified into seven categories based on their global RGB intensities.After the classification process,the images are filtered,and adaptive thresholding is applied to enhance the global contrast and detect the outer iris ring.Finally,to characterize the pupil area,the algorithm scans the cropped outer ring region for local minima values to identify the darkest area in the iris ring.The experimental results show that our method outperforms existing segmentation techniques using the UBIRIS.v1 and v2 databases and achieved a segmentation accuracy of 99.32 on UBIRIS.v1 and an error rate of 1.59 on UBIRIS.v2.

朝那鸡MC1R基因G274A和A427G多态位点与羽色性状的关联分析

为了研究宁夏地方品种鸡朝那鸡的黑色素皮质激素1受体(melanocortin 1 receptor, MC1R)基因G274A和A427G多态位点与羽色性状的关联性,试验选择120日龄健康的朝那鸡150只(红羽、黑羽和白羽各50只)为试验对象,采用高分辨熔解曲线(high resolution melting, HRM)分析技术对朝那鸡MC1R基因G274A和A427G位点进行基因型分型检测,并且对基因型和羽色性状进行了关联分析。结果表明:试验朝那鸡群体MC1R基因G274A位点有GG、GA、AA三种基因型,其中AA基因型个体数量最多,等位基因A为优势等位基因,多态信息含量(PIC)为0.286 7,表现为中度多态(0.25≤PIC≤0.50),说明MC1R基因位点为G274A的朝那鸡群体选育潜力较高;A427G位点有AA、AG两种基因型,其中AA基因型个体数量最多,等位基因A为优势等位基因,PIC为0.062 3,表现为低度多态(PIC<0.25),说明MC1R基因位点为A427G的朝那鸡群体选育潜力较低;这两个位点均处于Hardy-Weinberg平衡状态(P>0.05)。G274A位点不同基因型间的羽色性状差异显著(P<0.05),黑羽群体中未发现GG基因型个体,红羽和白羽群体中GG基因型个体数量较GA、AA基因型个体少,AA基因型是红羽和黑羽群体中的优势基因型;A427G位点不同基因型间的羽色性状差异极显著(P<0.01),三个羽色群体中均未发现GG基因型个体,红羽群体均为AA基因型,黑羽和白羽群体中AA基因型个体数量较AG基因型多。说明MC1R基因这两个位点可作为朝那鸡羽色纯化的遗传标记应用于品种纯度鉴定和分子育种中。

地方土特产包装设计中的色彩应用策略研究——以罗浮山“五行茶”为例

为探索地方土特产包装设计的色彩应用策略,分析其应用现状,并提出应用的创新意义。本研究对罗浮山“五行茶”进行地方土特产包装设计实践探讨,对客观人文色彩、主观情感色彩、世界观里中国色彩等三种不同的策略从理论、侧重与可行性上进行对比分析,以期为后续地方土特产色彩设计相关研究提供一些有价值的参考。

基于约束Kubelka-Munk模型与梯度局部优化算法耦合的色剂配色方法

针对人工实现快速、准确的色剂配色非常困难的问题,本研究提出了一个基于约束Kubelka-Munk模型与梯度局部优化算法耦合的色剂配色方法,实现涂料和印刷行业半透明和不透明色剂的配方预测。在此方法中,先利用梯度局部优化算法求解在基色色剂和冲淡剂混合基础上的目标函数,计算出基色色剂的吸收系数(K)和散射系数(S)。然后,为了实现任意目标色剂中基色色剂的混合配比,利用基色色剂与冲淡剂的吸收系数与散射系数物理属性对Kubelka-Munk模型进行约束,并通过最小化目标色剂与基色色剂之间的吸收系数与散射系数比值,构建了约束Kubelka-Munk模型,用于预测半透明着色剂和不透明色剂的配方。配方差、光谱反射率差,以及色差的实验结果表明,与传统的Kubelka-Munk模型相比,该方法建立的模型预测混色效果更优。

重返生命之源,重塑日常诗意--《城堡之外》中的乡土叙事研究

《城堡之外》通过展现四个家族几代人近百年间的悲欢离合,追溯了现代个体与故乡及历史之间切割不断的血脉关联。小说呈现出都市与乡村两种空间的对立,在都市人焦灼的精神状态与古罗村宁静神秘的栖居生活所形成的对照视域中钩沉历史,反思“家园”与“栖居”的意义;又在时间维度中对话传统,通过勾连个人经验与家族记忆之间的关系,实现“归家”的状态。而小说对传统习俗的描写揭示了日常生活在工业化历史进程中被遮蔽的通俗诗意,为我们修复传统与现代之间的断裂并重新抵达生活的真实指明了方向。

鲁迅乡土小说空间诗学发生探源

鲁迅是勘探现代乡土小说空间诗学发生的最好样本。从其空间观发生、形成路径来看,是不断将个人空间体验与乡土、民族、国家、世界等大概念交织在一起,空间板块渐次裂变,结构层次逐层丰富,而后又在整一的空间观念中返回到最小板块起点的空间认知漫游旅程。鲁迅在熔铸了刻骨铭心生命体验的空间哲学基础上建构起自己的空间诗学。多维、综合的诗学体系表征了乡土中国的社会结构、现代知识分子的生存际遇、人类的精神困境,以诗学方式呼应了西方马克思主义空间生产理论,也为今天的乡土小说书写提供了高度与向度的范例。

基于加权融合的水下视觉图像增强算法

针对水下视觉同步定位与地图构建(SLAM)前端特征提取与特征匹配效果差的问题,提出一种用于水下视觉SLAM前端的基于加权融合的图像增强算法。该算法建立在2个图像的融合处理基础上,第1个图像经过基于自适应伽马校正和动态范围拉伸的水下图像亮度增强处理,第2个图像经过基于颜色判断和颜色补偿的灰度世界白平衡处理;通过计算2个图像的显著性权重和饱和性权重,对输入图像进行线性加权融合,得到最终的增强图像。通过水下彩色图像质量评价(UCIQE)和水下图像质量测量(UIQM)方法评估无参考水下增强图像质量,并用南卡罗来纳大学开源数据集测试所提算法的应用效果,结果表明:处理后,水下图像质量高、提取特征点数目多,可以显著提高水下视觉SLAM前端特征提取与特征匹配的效果。

基于局部特征和视觉词袋模型的大豆叶片病害识别

病害检测对提高大豆作物产量至关重要。针对传统视觉法诊断大豆作物病害而导致病害识别效率和分类准确率不高的问题,提出一种基于局部描述符和视觉词袋技术以数据表征大豆叶片图像的分类算法,同时保留有关潜在疾病的视觉信息。采用SIFT、DSIFT、PHOW和SURF 4种算法对大豆叶片的霜霉病、锈病TAN和锈病RB进行分类识别。结果表明,局部描述符PHOW表现出最佳的分类识别结果,其正确分类率为96.25%。进一步研究PHOW在不同颜色空间下的大豆病害识别效果。结果表明,与灰度图像相比,使用HSV、Opponent颜色空间可有效提升对大豆叶片病害检测的正确分类率,其正确分类率分别可达99.83%和99.58%,验证采用局部描述符和视觉词袋技术识别大豆叶片病害方法的可行性和高效性,并为其他作物的病害识别提供一种通用的分类识别方法。