Set Of Colors Research Articles

Ultraviolet vision in anemonefish improves colour discrimination.

In many animals, ultraviolet (UV) vision guides navigation, foraging, and communication, but few studies have addressed the contribution of UV signals to colour vision, or measured UV discrimination thresholds using behavioural experiments. Here, we tested UV colour vision in an anemonefish (Amphiprion ocellaris) using a five-channel (RGB-V-UV) LED display. We first determined that the maximal sensitivity of the A. ocellaris UV cone was ∼386 nm using microspectrophotometry. Three additional cone spectral sensitivities had maxima at ∼497, 515 and ∼535 nm. We then behaviourally measured colour discrimination thresholds by training anemonefish to distinguish a coloured target pixel from grey distractor pixels of varying intensity. Thresholds were calculated for nine sets of colours with and without UV signals. Using a tetrachromatic vision model, we found that anemonefish were better (i.e. discrimination thresholds were lower) at discriminating colours when target pixels had higher UV chromatic contrast. These colours caused a greater stimulation of the UV cone relative to other cone types. These findings imply that a UV component of colour signals and cues improves their detectability, which likely increases the prominence of anemonefish body patterns for communication and the silhouette of zooplankton prey.

John Fiske's Semiotic Analysis of Moral Education in “Budi Pekerti” Film

This study used qualitative research with John Fiske's semiotic approach. This research aimed to reveal the reality, representation, and ideology regarding moral education in the film by Wregas Bhanuteja entitled “Budi Pekerti”. The film had a high artistic aesthetic and was full of meaning. Film is an audio-visual media that combines both elements, namely narrative and cinematic. This study employed the semiotic method by John Fiske as the research method. The signs shown in this film pointed to moral education which was currently a crisis in Indonesia. Reality, representation, and ideology regarding moral education were conveyed through conversations, choice of color tones, settings, soundtracks, and scenes. The results of the study showed that the film depicted current reality especially regarding the moral values in the society in Indonesia context. This also showed how current development of information and technology has strong correlation with people’s behavior especially related to moral values.

Neighbor Distinguishing Colorings of Graphs with the Restriction for Maximum Average Degree

Neighbor distinguishing colorings of graphs represent powerful tools for solving the channel assignment problem in wireless communication networks. They consist of two forms of coloring: neighbor distinguishing edge coloring, and neighbor distinguishing total coloring. The neighbor distinguishing edge (total) coloring of a graph G is an edge (total) coloring with the requirement that each pair of adjacent vertices contains different color sets. The neighbor distinguishing edge (total) chromatic number of G is the smallest integer k in cases where a neighbor distinguishing edge (total) coloring exists through the use of k colors in G. The maximum average degree of G is the maximum of the average degree of its non-empty subgraphs. In this paper, we characterize the neighbor distinguishing edge (total) chromatic numbers of graphs with a maximum average degree less than four by means of the discharging method.

Cognitively Congruent Color Palettes for Mapping Spatial Emotional Data. Matching Colors to Emotions.

Emotions are touchstones of humans’ everyday life experiences. Maps of emotions inform a variety of research from urban planning and disaster response to marketing studies. Emotions are most often shown on maps with colors. Previous research suggests that humans have subjective associations between colors and emotions that impact objective task performance. Thus, a mismatch between the emotion associated with a color and the emotion it represents may bias the viewer’s attention, perception, and understanding of the map. There are no guidelines that can help cartographers and designers choose matching colors to display spatial emotional data. This study aimed to address this gap by suggesting cognitively congruent color palettes—color sets matched to emotions in a way that is aligned with color-emotion associations. To obtain the set of candidate congruent colors and identify appropriate color-to-emotion assignments, two user experiments were conducted with participants in the United States. In the first, participants picked a representative color for 23 discrete emotions. In the second experiment, for each candidate color from a set derived from the results of the first experiment, participants selected the best-matching emotions. The probability of the emotion being selected served as a measure of how representative the color is of that emotion. Due to the many-to-many nature of associations between colors and emotions, suitable color choices were incorporated into a dynamic palette generation tool. This tool solves the color assignment problem and produces a suitable color palette depending on the combination of selected emotions.

Rainbow subgraphs in edge‐colored complete graphs: Answering two questions by Erdős and Tuza

AbstractAn edge‐coloring of a complete graph with a set of colors is called completely balanced if any vertex is incident to the same number of edges of each color from . Erdős and Tuza asked in 1993 whether for any graph on edges and any completely balanced coloring of any sufficiently large complete graph using colors contains a rainbow copy of . This question was restated by Erdős in his list of “Some of my favourite problems on cycles and colourings.” We answer this question in the negative for most cliques by giving explicit constructions of respective completely balanced colorings. Further, we answer a related question concerning completely balanced colorings of complete graphs with more colors than the number of edges in the graph .

Fabric colour measurement in the small region of CIELab colour space using a scanner‐based subtractive clustering fuzzy inference system

AbstractDigital devices are increasingly being used in the colour measurement of textile‐made materials. Proper scanner characterisation is crucial for accurate and consistent colour measurement. In the present study a fuzzy inference system based on subtractive clustering, called FIS_SC method, for the colorimetric characterisation of a scanner to measure the colour of the fabrics in a small region of a colour space is proposed. The results of the proposed method for 16 colour sets were obtained and compared with the results of the scanner characterisation using polynomial regression and neural network method. It was shown that the FIS_SC method successfully characterised the scanner in the small colour space, so that its mean of the colour difference was lower than the polynomial regression and neural network methods in almost all colour sets.

Color origin and its sedimentary and paleoenvironmental significance of the Permian-Triassic strata in the Ordos Basin, China

The Permian-Triassic strata in the Ordos Basin deposit a colorful set of strata. Although there have been many studies on oil and gas resources here, little attention has been paid to the genesis mechanism of its color. To analyze the color origin of the Permian-Triassic claystones and to clarify the dialectical relationship between rock color and sedimentary environment, petrological and geochemical methods such as polarization microscope, scan electron microscope, X-ray diffractometer, and inductively coupled plasma-mass spectrometer are used. The results indicate that the minerals with different colors, composition, and content serve as colorants in sedimentary rocks, with the predominant dyeing component in dark claystones being the organic matter, whereas red beds primarily acquire their color from hematite and other ferric minerals. In addition, different rock colors correspond to distinct chemical composition variations. The black-gray rocks of the Yanchang and Shihezi Formations have high total organic carbon content, Fe2+/Fe3+, V/Cr, and low CaO/(MgO × Al2O3) and Sr/Cu, whereas the red-brown rocks of the Liujiagou and Heshanggou Formations exhibit the opposite. Therefore, different colors of the rocks stem from their different mineral and chemical compositions, which in turn influenced by the changes in the paleoclimate, paleoenvironment, and tectonic movements. Comprehensive analysis of color, mineral, and chemical composition reveals the evolution process of paleoclimate and paleoenvironment in the Ordos Basin from the late Permian to Triassic, beginning with a warm humid climate characterized by a weak oxidation environment in the Shihezi and Shiqianfeng Formations, transitioning to a hot arid climate in the Liujiagou and Heshanggou Formations, and returning to a warm humid climate with a weak oxidation environment in the Zhifang and Yanchang Formations. This evolution history aligns with the global tectonic and climate evolution. Overall, systematic analysis of sedimentary rock color can provide an important basis for the study of the paleoclimate and paleoenvironment.

Generating Harmonious Colors through the Combination of n-Grams and K-means

Among the many approaches to studying color harmony tried so far, a relatively recent method is to leverage a large number of human-created and ranked color palettes, such as those hosted at colourlovers.com. Analysis of these large datasets could provide insights into the nature of color harmony but is usually overwhelming because of the sheer number of slightly differing colors. It is possible to quantize the colors in these color palettes to a manageable set of discrete colors without significantly affecting the harmony perception of the palette. Considering the quantized colors as words and the palettes as sentences, it is possible to form and compute the probabilities of n-Grams in the sentences. In this study, we create bigrams and trigrams from the corpus of highly ranked color palettes and use them to predict new color combinations. Respondents were asked to like or dislike the patterns colored with these color combinations. It was found that the new color combinations thus formed were almost as harmonious and pleasing as the originals.

Optimization of clothing style and color design mode and innovation of technique under symbiosis mode

Abstract In this paper, we combine the thesaurus matching through the clothing style feature mining method, get the conditional probability index through great likelihood estimation, use iterative scale training parameters, and calculate the similarity mean of the belonging feature values. To identify and classify clothing styles, texture features are extracted from clothing styles, and the optimal training sample set of popular clothing colors is selected. The highest data mining algorithm in symbiotic mode has an accuracy rate of 96.4% for short-skirt clothing styles, a statistical result of 82.61 for tie-dye clothing techniques, and a maximum color threshold of 0.14. Symbiotic mode achieves a visual effect of distinctive features, which leads to optimal clothing styles and color innovations.

Supra-Quantum Dot Assemblies to Maximize Color-Based Multiplexed Fluorescence Detection with a Smartphone Camera.

Photoluminescence (PL) imaging and bioanalysis with smartphone-based devices are of growing interest for point-of-care/point-of-need diagnostics. Strategies for maximizing sensitivity have been explored in this context, but color multiplexing has been very limited, with its maximum level unexplored. Here, we evaluated color multiplexing with smartphone-based PL imaging by using supra-nanoparticle assemblies of quantum dots (supra-QDs). These materials were prepared as composite colors that were tailored to the red-green-blue (RGB) color space of smartphone cameras by coassembling different ratios of R-, G-, and B-emitting QDs on a silica nanoparticle scaffold. The supra-QDs were characterized and used to label cell-sized objects that were measured under flow with a smartphone-based device. Each color followed an approximately linear trajectory in the RGB space, and training of support vector machine models enabled color classification with overall accuracies ≥87% for 10-color multiplexing and better accuracies for fewer colors. Most misclassification occurred at low signal levels, such that establishing a nonclassifiable zone near the origin of RGB color space improved the overall 10-color classification accuracy to ≥94%. Similar improvements in accuracy with greater retention of data were possible with a probabilistic rather than a radial threshold. Simulations that were parameterized by experimental data suggested that ≥14-color multiplexing with accuracies ≥90% should be possible with an optimized supra-QD color set. This study is an important foundation for advancing RGB color-based multiplexing for imaging and analyses with smartphone cameras and related charge-coupled device and CMOS color image sensor technologies.

Two-distance vertex-distinguishing index of sparse graphs

Abstract The two-distance vertex-distinguishing index χ d 2 ′ ( G ) {\chi }_{d2}^{^{\prime} }\left(G) of graph G G is defined as the smallest integer k k , for which the edges of G G can be properly colored using k k colors. In this way, any pair of vertices at distance of two have distinct sets of colors. The two-distance vertex-distinguishing edge coloring of graphs can be used to solve some network problems. In this article, we used the method of discharging to prove that if G G is a graph with mad ( G ) < 8 3 \left(G)\lt \frac{8}{3} , then χ d 2 ′ ( G ) ≤ max { 7 , Δ + 2 } {\chi }_{d2}^{^{\prime} }\left(G)\le \max \left\{7,\Delta +2\right\} , which improves the result that a graph G G of Δ ( G ) ≥ 4 \Delta \left(G)\ge 4 has χ d 2 ′ ( G ) ≤ Δ ( G ) + 2 {\chi }_{d2}^{^{\prime} }\left(G)\le \Delta \left(G)+2 if mad ( G ) < 5 2 \left(G)\lt \frac{5}{2} , and χ d 2 ′ ( G ) ≤ Δ ( G ) + 3 {\chi }_{d2}^{^{\prime} }\left(G)\le \Delta \left(G)+3 if mad ( G ) < 8 3 \left(G)\lt \frac{8}{3} .

An Experimental Evaluation of Kernel Density Estimation to Choose Categorical Map Colours

ABSTRACT When selecting categorical map colours, colour conventions should be respected to leverage semantic–colour resonance to facilitate cartographic communication. Given a set of sample colours, kernel density estimation (KDE) can be used to estimate each colour's probability density (appropriateness) to represent the category. How to couple bandwidth and kernel to estimate better appropriateness remains unknown. To fill this gap, an experiment was designed to explore best pairs of bandwidth and kernel capturing users' assessments. We gathered six groups of colour samples from 10 well-accepted land use atlases and 30 randomly sampled test colours; we then applied KDE to estimate the appropriateness of test colours using all possible pairs of bandwidth and kernel, and invited participants to score each test colour. Results show that pair of rule-of-thumb bandwidth and Gaussian kernel yields the best estimates. Our findings are generalizable to diverse colours and can serve as a complement to design colours.

A comparative study of evolutionary computation and swarm-based methods applied to color quantization

Color Quantization (CQ) is a complex and hard problem because selecting the best set of colors from many available colors and using that set to obtain a good quality image is an NP-complete problem. The use of evolutionary computation and swarm-based methods to solve search and optimization problems has increased dramatically in recent years. This article compares some of these methods in order to solve the CQ problem. The following methods were used to generate CQ images: Particle swarm optimization, Artificial bee colony, Adaptive differential evolution, Success-history based adaptive differential evolution (with and without linear population size reduction), Cuckoo search, Firefly algorithm and Shuffled-frog leaping algorithm. For the first two methods, two variants were considered. Thus, a total of ten metaheuristics were compared with four classical CQ methods (Variance-based, Median-cut, Binary splitting and Wu’s methods) applying them to a set of benchmark images and considering four different palette sizes (32, 64, 128, and 256 colors). Three error measures were considered to compare the methods: the mean squared error, the mean absolute error and the peak signal-to-noise ratio. Some of the swarm-based methods analyzed include a recently proposed CQ method using ants. Although they have a slow computational speed in the experimental studies, the ant-based methods are significantly better than all other methods according to the Wilcoxon signed rank test. In general, despite their speed, classical methods underperform the other ten methods both qualitatively and quantitatively.

Spectroscopy from Photometry: A Population of Extreme Emission Line Galaxies at 1.7 ≲ z ≲ 6.7 Selected with JWST Medium Band Filters

We use JWST/NIRCam medium band photometry in a single pointing of the Canadian NIRISS Unbiased Cluster Survey to identify 118 extreme emission-line galaxies (EELGs) over 1.7 ≲ z ≲ 6.7, selected using a set of color cuts that target galaxies with extreme [O iii] + Hβ and Hα emission. We show that our medium band color selections are able to select galaxies based on emission-line EW, which is advantageous to more commonly used selections since it does not require strong continuum emission, and can select galaxies with faint or red continuum fluxes. The median EWs of our sample is EW(Hα) = 893 Å and EW ([O III] + Hβ) = 1255 Å and includes some objects with EW ([O III] + Hβ) ∼ 3000 Å. These systems are mostly compact with low stellar mass (median ), low metallicity (median Z = 0.14 Z ⊙), little dust (median A V = 0.18 mag), and high SSFR (median SSFR = 1.18 × 10−8 yr−1). Additionally, galaxies in our sample show increasing EW(Hα) and EW([O iii] + Hβ) with redshift, an anticorrelation of EW(Hα) with stellar mass, and no correlation between EW([O iii] + Hβ) and stellar mass. Finally, we present NIRSpec spectroscopy of 15 of the EELGs in our sample. These spectra confirm the redshifts and EWs of the EELGs calculated from the medium bands, which demonstrates the accuracy and efficiency of our color selections. Overall, we show that there are significant advantages to using medium band photometry to identify and study EELGs at a wide range of redshifts.

Methods for Efficient Unfolding of Colored Petri Nets

Colored Petri nets offer a compact and user friendly representation of the traditional Place/Transition (P/T) nets and colored nets with finite color ranges can be unfolded into the underlying P/T nets, however, at the expense of an exponential explosion in size. We present two novel techniques based on static analysis in order to reduce the size of unfolded colored nets. The first method identifies colors that behave equivalently and groups them into equivalence classes, potentially reducing the number of used colors. The second method overapproximates the sets of colors that can appear in places and excludes colors that can never be present in a given place. Both methods are complementary and the combined approach allows us to significantly reduce the size of multiple colored Petri nets from the Model Checking Contest benchmark. We compare the performance of our unfolder with state-of-the-art techniques implemented in the tools MCC, Spike and ITS-Tools, and while our approach is competitive w.r.t. unfolding time, it also outperforms the existing approaches both in the size of unfolded nets as well as in the number of answered model checking queries from the 2021 Model Checking Contest.

Comparative study of feature extraction algorithms for panorama stitching

Panorama stitching is a fascinating and rapidly advancing research field. By integrating many photographs that were taken from various angles and viewpoints, with various exposure and color settings, a seamless image is primarily the aim of panorama stitching. This paper investigates the performance of three widely used feature extraction algorithms Speeded-Up Robust Features (SURF), Scale-Invariant Feature Transform (SIFT), and Oriented FAST and Rotated BRIEF (ORB) for panorama stitching. The study compares these algorithms in terms of accuracy, robustness, and speed. Results indicate that while SURF and SIFT produce more accurate and robust results than ORB, they require longer processing time. The study evaluates the approach on a real-world dataset and demonstrates its effectiveness in creating seamless and visually appealing panoramas. This study provides valuable insights into the trade-offs between different feature extraction algorithms and presents a practical solution for panorama stitching applications.

The effect of the environment on the color variation of the shell of species Cochlicella barbara

This study aimed to identify the colors in which the shell of the snails is colored and the reasons for this multicolor. After choosing some areas of Baghdad, it was found that the species Cochlicella barbara appears in more than one color; we studied it for over two years, and it was found that this species has two sets of colors: a –colored group that appears in winter and the darker colors that appears in summer. It was found from the study of the environmental conditions that the temperature difference had the most significant effect on the appearance of the colors of this species. Keywords: Gastropoda, Cochlicella barbara, color pattern, shell polymorphism.

Adjacent vertex distinguishing edge choosability of 1-planar graphs with maximum degree at least 23

For a simple graph G, an adjacent vertex distinguishing edge k-coloring of G is a mapping ϕ: E(G)→{1,2,…,k} such that ϕ(e1)≠ϕ(e2) for every adjacent edges e1 and e2 in E(G) and Cϕ(u)≠Cϕ(v) for each edge uv∈E(G), where Cϕ(v) (or Cϕ(u)) denotes the set of colors assigned to the edges incident with v (or u). For each edge e∈E(G), let L(e) be a list of possible colors that can be used on e. If, whenever we give a list assignment L={L(e)||L(e)|=k,e∈E(G)}, there exists an adjacent vertex distinguishing edge k-coloring ϕ such that ϕ(e)∈L(e) for each edge e∈E(G), then we say that ϕ is a list adjacent vertex distinguishing edge k-coloring. The smallest k for which such a coloring exists is called the adjacent vertex distinguishing edge choosability of G, denoted by cha′(G). A graph is 1-planar if it can be drawn on the plane so that each edge is crossed by at most one other edge. There is almost no result yet about cha′(G) if G is a 1-planar graph. We prove that cha′(G)≤Δ+3 for every 1-planar graph G with maximum degree Δ≥23.

Infinite Wordle and the mastermind numbers

AbstractI consider the natural infinitary variations of the games Wordle and Mastermind, as well as their game‐theoretic variations Absurdle and Madstermind, considering these games with infinitely long words and infinite color sequences and allowing transfinite game play. For each game, a secret codeword is hidden, which the codebreaker attempts to discover by making a series of guesses and receiving feedback as to their accuracy. In Wordle with words of any size from a finite alphabet of n letters, including infinite words or even uncountable words, the codebreaker can nevertheless always win in n steps. Meanwhile, the mastermind number , defined as the smallest winning set of guesses in infinite Mastermind for sequences of length ω over a countable set of colors without duplication, is uncountable, but the exact value turns out to be independent of , for it is provably equal to the eventually different number , which is the same as the covering number of the meager ideal . I thus place all the various mastermind numbers, defined for the natural variations of the game, into the hierarchy of cardinal characteristics of the continuum.

Analyzing the Digital Inheritance of Nanyang Branding Painting from the Perspective of Cultural Anthropology

Nanyang branding painting has a development history of more than 2,000 years since it was introduced at the end of the Western Han Dynasty, during which many legends about branding painting have been passed down. The characteristics of branding painting are the use of plant carbonation mechanism, the use of temperature-controlled techniques, hot branding as the main, set of colours as a supplement, not using other colours of the art expression methods. By sketching and baking on bamboo, wood, rice paper, silk and other materials, branding painting aptly combines the various expression techniques of traditional painting art and modern branding techniques, resulting in a unique artistic style. In the modern living environment, Nanyang branding painting can play the function of enriching the life of beauty painting, spreading Chinese culture and cultivating aesthetic sentiment, therefore, this paper will analyse the dissemination and development of Nanyang branding painting art on the digital platform from the perspective of cultural anthropology.