Strategies for Applying LED Lights in Night Space Lighting for Bridges

LED lights have been widely used in urban night space lighting in recent years as they are small,energy-saving,and efficient.This article explores the use of LEDs in bridge night space lighting and their application strategies.The aim is to offer valuable insights and references for urban planners and bridge lighting designers in China.By advancing the application of LED technology in bridge night lighting,the goal is to enhance the city’s nighttime ambiance,making the bridge an iconic landmark and a defining feature of the city.

HB-Continuous Mappings in L-Topological Space

In this paper, we introduce and study the notion of HB-closed sets in L-topological space. Then, HB-convergence theory for L-molecular nets and L-ideals is established in terms of HB-closedness. Finally, we give a new definition of fuzzy H-continuous [1] which is called HB-continuity on the basis of the notion of H-bounded L-subsets in L-topological space. Then we give characterizations and properties by making use of HB-converges theory of L-molecular nets and L-ideals.

Space Color Design of Medical and Nursing Institutions Based on Adaptive Aging Characteristics

With the acceleration of China’s aging process and the rapid development of social economy,the government’s strong support for the integration of medical and nursing has made the construction of medical and nursing buildings more efficient.At the same time,the need for old-age care is more diversified and hierarchical,and the life cycle is more obvious.Designing an aging color environment for the elderly with different visual abilities in medical care buildings has become a problem for investors,operators and designers.This paper takes the indoor color of medical and nursing buildings as the research object,and combines the characteristics of the elderly’s visual acuity and the ratio and efficacy of indoor colors to investigate two high-end medical and nursing institutions in Beijing and Nanjing.Based on the physical,psychological and behavioral needs,this paper explores the appropriate aging color design method for the living space of the elderly in the medical institutions,aiming to make a meagre effort for the in-depth research and practice of indoor environment design of medical institutions in the future.

IAACS: Image aesthetic assessment through color composition and space formation

Background Determining how an image is visually appealing is a complicated and subjective task. This motivates the use of a machine-learning model to evaluate image aesthetics automatically by matching the aesthetics of the general public. Although deep learning methods have successfully learned good visual features from images,correctly assessing the aesthetic quality of an image remains a challenge for deep learning. Methods To address this, we propose a novel multiview convolutional neural network to assess image aesthetics assessment through color composition and space formation(IAACS). Specifically, from different views of an image––including its key color components and their contributions, the image space formation, and the image itself––our network extracts the corresponding features through our proposed feature extraction module(FET) and the Image Net weight-based classification model. Result By fusing the extracted features, our network produces an accurate prediction score distribution for image aesthetics. The experimental results show that we have achieved superior performance.

结合主动光源和改进YOLOv5s模型的夜间柑橘检测方法

【目的】解决夜间环境下遮挡和较小柑橘难以准确识别的问题,实现采摘机器人全天候智能化作业。【方法】提出一种结合主动光源的夜间柑橘识别方法。首先,通过分析主动光源下颜色特征不同的夜间柑橘图像,选择最佳的光源色并进行图像采集。然后,提出一种夜间柑橘检测模型BI-YOLOv5s,该模型采用双向特征金字塔网络(Bi-FPN)进行多尺度交叉连接和加权特征融合,提高对遮挡和较小果实的识别能力;引入Coordinate attention(CA)注意力机制模块,进一步加强对目标位置信息的提取;采用融入Transformer结构的C3TR模块,在减少计算量的同时更好地提取全局信息。【结果】本文提出的BI-YOLOv5s模型在测试集上的精准率、召回率、平均准确率分别为93.4%、92.2%和97.1%,相比YOLOv5s模型分别提升了3.2、1.5和2.3个百分点。在所采用的光源色环境下,模型对夜间柑橘识别的正确率为95.3%,相比白光环境下提高了10.4个百分点。【结论】本文提出的方法对夜间环境下遮挡和小目标柑橘的识别具有较高的准确性,可为夜间果蔬智能化采摘的视觉精准识别提供技术支持。

Color Measurement of Segmented Printed Fabric Patterns in Lab Color Space from RGB Digital Images

Colors of textile materials are the first parameter of quality evaluated by consumers and a key component considered in selecting printed fabric. In the textiles industry, digital printed fabric analysis is one of the basic elements in successfully utilizing a color mechanism scheme and objectively evaluating fabric color alterations. Precise color measurement, however, is mostly used in sample analysis and quality inspection which help to produce reproducible or similar product. It is important that for quality inspection, the color of the product should be measured as a necessary requirement of quality control whether the product is to be accepted or not. Presented in this study is an unsupervised segmentation of printed fabrics patterns using mean shift algorithm and color measurements over the segmented regions of printed fabric patterns. The results established a consistent and reliable color measurement of multiple color patterns and appearance with the established range without any interactions.

Deer Body Adaptive Threshold Segmentation Algorithm Based on Color Space

In large-scale deer farming image analysis,K-means or maximum between-class variance(Otsu)algorithms can be used to distinguish the deer from the background.However,in an actual breeding environment,the barbed wire or chain-link fencing has a certain isolating effect on the deer which greatly interferes with the identification of the individual deer.Also,when the target and background grey values are similar,the multiple background targets cannot be completely separated.To better identify the posture and behaviour of deer in a deer shed,we used digital image processing to separate the deer from the background.To address the problems mentioned above,this paper proposes an adaptive threshold segmentation algorithm based on color space.First,the original image is pre-processed and optimized.On this basis,the data are enhanced and contrasted.Next,color space is used to extract the several backgrounds through various color channels,then the adaptive space segmentation of the extracted part of the color space is performed.Based on the segmentation effect of the traditional Otsu algorithm,we designed a comparative experiment that divided the four postures of turning,getting up,lying,and standing,and successfully separated multiple target deer from the background.Experimental results show that compared with K-means,Otsu and hue saturation value(HSV)+K-means,this method is better in performance and accuracy for adaptive segmentation of deer in artificial breeding scenes and can be used to separate artificially cultivated deer from their backgrounds.Both the subjective and objective aspects achieved good segmentation results.This article lays a foundation for the effective identification of abnormal behaviour in sika deer.

Combination of effective color information and machine learning for rapid prediction of soil water content

Soil water content(SWC)is one of the critical indicators in various fields such as geotechnical engineering and agriculture.To avoid the time-consuming,destructive,and laborious drawbacks of conventional SWC measurements,the image-based SWC prediction is considered based on recent advances in quantitative soil color analysis.In this study,a promising method based on the Gaussian-fitting gray histogram is proposed for extracting characteristic parameters by analyzing soil images,aiming to alleviate the interference of complex surface conditions with color information extraction.In addition,an identity matrix consisting of 32 characteristic parameters from eight color spaces is constituted to describe the multi-dimensional information of the soil images.Meanwhile,a subset of 10 parameters is identified through three variable analytical methods.Then,four machine learning models for SWC prediction based on partial least squares regression(PLSR),random forest(RF),support vector machines regression(SVMR),and Gaussian process regression(GPR),are established using 32 and 10 characteristic parameters,and their performance is compared.The results show that the characteristic parameters obtained by Gaussian-fitting can effectively reduce the interference from soil surface conditions.The RGB,CIEXYZ,and CIELCH color spaces and lightness parameters,as the inputs,are more suitable for the SWC prediction models.Furthermore,it is found that 10 parameters could also serve as optimal and generalizable predictors without considerably reducing prediction accuracy,and the GPR model has the best prediction performance(R^(2)≥0.95,RMSE≤2.01%,RPD≥4.95,and RPIQ≥6.37).The proposed image-based SWC predictive models combined with effective color information and machine learning can achieve a transient and highly precise SWC prediction,providing valuable insights for mapping soil moisture fields.

Color spaces of safflower (Carthamus tinctorius L.) for quality assessment

Objective:In this study,safflower(Carthamus tinctorius L.)was taken as a representative example to examine the application of color characteristics to evaluate quality.Methods:A computer vision system was established for the objective and nondestructive assessment of color using image processing algorithms.Color parameters were investigated based on the RGB,L*a*b and HSV color spaces.The content of hydroxysafflor yellow A(HSYA),a major bioactive constituent of safflower,was determined by high-performance liquid chromatography.The relationship between HSYA content and color values was investigated by Pearson correlation analysis.A multiple linear regression model was established to predict the HSYA content from color values.Results:The red color and lightness of safflower were found to be significantly related to HSYA content.The prediction equation obtained by multiple regression was reliable with an R2 value of 0.805(P<.01).Conclusion:The results suggest that the computer vision technique could be used as a promising and non-destructive technology for color measurement and quality evaluation of CHM.

基于Space L的公共交通网络拓扑结构特性分析

遵循复杂网络建模的一般方法,构建了Space L网络模型。以成都市公共交通网络为例进行了节点度与度分布、平均路径长度、聚集系数、点权和边权等拓扑特征分析。结果表明,在L空间下成都市公交网络的聚集系数大、特征路径长度小,具有典型“小世界特征”;节点度的累积概率分布呈指数变化,表明成都市公交网络是一个随机进化增长网络;从点权边权可以得到高笋塘—火车北站公交站路段可以考虑布局换乘枢纽。基于Space L,从蓄意攻击和随机攻击两个方面分析成都公交网络的鲁棒性,得出保障网络运行安全的关键站点,进而优化城市公交网络和枢纽布局。

A Study on the Influence of Luminance L* in the L*a*b* Color Space during Color Segmentation

In this paper an evaluation of the influence of luminance L* at the L*a*b* color space during color segmentation is presented. A comparative study is made between the behavior of segmentation in color images using only the Euclidean metric of a* and b* and an adaptive color similarity function defined as a product of Gaussian functions in a modified HSI color space. For the evaluation synthetic images were particularly designed to accurately assess the performance of the color segmentation. The testing system can be used either to explore the behavior of a similarity function (or metric) in different color spaces or to explore different metrics (or similarity functions) in the same color space. From the results is obtained that the color parameters a* and b* are not independent of the luminance parameter L* as one might initially assume.

手机直连NGSO卫星业务中扩展L频段频率协调方案研究

在目前非对地静止轨道(NGSO)卫星移动业务用频越来越紧张的趋势下,针对手机直连NGSO卫星业务频率协调工作复杂的问题,首先对手机直连NGSO卫星系统的用频现状及趋势进行分析,其次重点对手机直连NGSO卫星业务在扩展L频段和其他同频空间业务的频率协调方案进行分析和研究。通过分析手机直连NGSO卫星业务在扩展L频段的频率协调态势确定需要与之开展频率协调工作的空间业务,基于和每一项空间业务的频率协调方案进行研究并给出协调方案建议,同时还对具体协调方案中涉及的干扰分析计算进行举例。以上研究均可作为手机直连NGSO卫星业务系统开展同频频率协调相关研究及下一步手机直连NGSO卫星关键技术研究等相关工作的参考。

分裂的δ-Jordan李color三系的结构

研究了分裂的δ-Jordan李color三系的结构,定义了分裂的δ-Jordan李color三系的概念,利用分裂的δ-Jordan李color三系的根连通的性质,得到具有对称根系的分裂的δ-Jordan李color三系的分解:T=U+∑[α]∈Λ1/~I[α],其中U是T0的子空间,I[α]是T的理想,并且满足如果[α]≠[β],那么{I[α],T,I[β]}={I[α],I[β],T}={T,I[α],I[β]}=0。

L-拓扑空间中的SPC-连通性

研究了L-拓扑空间中的SPC-连通性.首先借助强半开集和强半闭集引入SPC-连通性的概念,并研究了SPC-连通性的等价刻画;其次讨论了SPC-连通性的一些性质以及证明了SPC-连通性是拓扑不变性;最后讨论了SPC-连通性与连通性之间的关系,得出:在L-拓扑空间中,SPC-连通一定是连通的,反之不成立,进而丰富和完善了L-拓扑空间中的连通性理论.

Energy-Saving Effect of Discolored Decorative Boards in Flexible Interior Space

Green,energy conservation and environmental protection have increasingly become the theme of the sustained and healthy development of cities against the background of new urbanization,which indicates that the problem of building energy consumption has received growing attention.This paper explores the impact of energy-saving decorations in flexible interior space on energy-saving effect of buildings so as to broaden the horizon of energy conservation in building,thereby alleviating the problem of energy shortage in China.

Modified Multispectral Space for Color Representation

Conventional multispectral space for color representation is modified by algorithm of cluster analysis and principal component analysis. Results show that the newer modified multispectral space not only keeping the structure of the original space but eliminating zero crosses as well its accuracy of color representation is higher than the conventional.

基于MATLAB的人脸图像分割算法研究

对基于MATLAB的人脸图像分割算法进行研究,利用颜色空间的不同色度特性,将给定的人脸图像按照不同色度划定的取值范围进行人脸和背景的分割。给出了三种颜色空间的基本原理,包括RGB颜色空间,HSV颜色空间,YCrCb颜色空间,对RGB颜色空间转换到HSV颜色空间和YCrCb颜色空间进行描述,并采用MATLAB软件完成图像的颜色空间转换。基于两种颜色空间完成不同类型人脸图像的图像分割,并对分割效果进行对比分析。