Coloring Problem Research Articles

Sorghum Spike Detection Method Based on Gold Feature Pyramid Module and Improved YOLOv8s

In order to solve the problems of high planting density, similar color, and serious occlusion between spikes in sorghum fields, such as difficult identification and detection of sorghum spikes, low accuracy and high false detection, and missed detection rates, this study proposes an improved sorghum spike detection method based on YOLOv8s. The method involves augmenting the information fusion capability of the YOLOv8 model’s neck module by integrating the Gold feature pyramid module. Additionally, the SPPF module is refined with the LSKA attention mechanism to heighten focus on critical features. To tackle class imbalance in sorghum detection and expedite model convergence, a loss function incorporating Focal-EIOU is employed. Consequently, the YOLOv8s-Gold-LSKA model, based on the Gold module and LSKA attention mechanism, is developed. Experimental results demonstrate that this improved method significantly enhances sorghum spike detection accuracy in natural field settings. The improved model achieved a precision of 90.72%, recall of 76.81%, mean average precision (mAP) of 85.86%, and an F1-score of 81.19%. Comparing the improved model of this study with the three target detection models of YOLOv5s, SSD, and YOLOv8, respectively, the improved model of this study has better detection performance. This advancement provides technical support for the rapid and accurate recognition of multiple sorghum spike targets in natural field backgrounds, thereby improving sorghum yield estimation accuracy. It also contributes to increased sorghum production and harvest, as well as the enhancement of intelligent harvesting equipment for agricultural machinery.

Photovoltaic windows based on ultrathin transition-metal dichalcogenides: Natural indoor illumination spectra and energy-saving potential

Semitransparent photovoltaic windows are attractive for building-integrated applications because they can regulate natural indoor illumination while generating power. In this work, we assess the potential of transition metal dichalcogenide (TMDC) semitransparent solar cells as emerging technology for this application. We model a semitransparent ultrathin photovoltaic device containing a MoS2 or WSe2 absorber and find that it can be optimized to produce a balanced absorption of the sunlight spectrum because of the unique optical properties of these materials, eliminating the common problem of the undesired coloring of the transmitted light. The device also exhibits high angular absorptance. We estimate a potential saving between 16 % (winter) and 23 % (summer) in the electricity consumption of a high-rise office building located in Madrid, Spain, by implementing TMDCs semitransparent windows with an average photopic transmission (APT) of 24 %. Notably, this is compatible with a high quality in the transmitted light: the color rendering index (CRI) of the PV windows exceeds 90 for an APT between 23 % and 65 %. These results, along with the fact that TMDCs can be deposited using low-cost, scalable methods, indicate that TMDCs hold great potential for developing color-neutral, power-generating building glazing.

Self‐reduction triggered color tuning of Eu3+‐doped aluminosilicate glass for solid‐state white illumination

AbstractRare earth‐doped transparent glass, boasting high transmittance and excellent luminescent properties, holds great potential in the field of all‐inorganic solid‐state white illumination. Currently reported single‐structure solid‐state white lighting usually has the problems of low color rendering index (CRI) and high correlated color temperature (CCT) due to the lacking of red light emission. In this work, a novel single‐structure MgO–Al2O3–SiO2–Eu2O3 (MAS: Eu) glass with color tuning was prepared by the simple glass melting process. Interestingly, the prepared Eu3+‐doped aluminosilicate glass possessed a unique capability to achieve color emission under different excitation wavelengths. The reason for this was attributed to the good self‐reduction capability of the MAS glass, which effectively reduced Eu3+ to Eu2+ under an air atmosphere. Meanwhile, only by regulating the Eu3+ doping concentration, the MAS glass also achieved a tunable emission from blue to white to red light under 380 nm excitation. The acquisition of white light was realized through the multispectral emission of blue–green light emitted by Eu2+ and orange–red light emitted by Eu3+. Remarkably, the single‐structure MAS glass doped with 8 wt.% Eu3+ successfully achieved high‐quality white light and high thermal stability, exhibiting a high CRI of 86, a low CCT of 2761 K, good chromaticity parameters of (0.407 and 0.3192), and the emission intensity at 423 K remains above 86.35% that of room temperature. Meanwhile, the doped Eu3+ exceeded 12 wt.%, without any observable concentration quenching. Moreover, the MAS: Eu glass showed a high transmittance of 90 and a moderate thermal conductivity of 1.45 W/mK (epoxy resin ∼0.17 W/mK). These results would dramatically inspire the development of high‐quality solid‐state white lighting applications.

DBSF-Net: Infrared Image Colorization Based on the Generative Adversarial Model with Dual-Branch Feature Extraction and Spatial-Frequency-Domain Discrimination

Thermal infrared cameras can image stably in complex scenes such as night, rain, snow, and dense fog. Still, humans are more sensitive to visual colors, so there is an urgent need to convert infrared images into color images in areas such as assisted driving. This paper studies a colorization method for infrared images based on a generative adversarial model. The proposed dual-branch feature extraction network ensures the stability of the content and structure of the generated visible light image; the proposed discrimination strategy combining spatial and frequency domain hybrid constraints effectively improves the problem of undersaturated coloring and the loss of texture details in the edge area of the generated visible light image. The comparative experiment of the public infrared visible light paired data set shows that the algorithm proposed in this paper has achieved the best performance in maintaining the consistency of the content structure of the generated image, restoring the image color distribution, and restoring the image texture details.

Injective coloring of subclasses of chordal graphs

An injective k-coloring of a graph G=(V,E) is a function f:V→{1,2,…,k} such that for every pair of vertices u and v having a common neighbor, f(u)≠f(v). The injective chromatic number χi(G) of a graph G is the minimum k for which G admits an injective k-coloring. Given a graph G and a positive integer k, Decide Injective Coloring Problem is to decide whether G admits an injective k-coloring. Decide Injective Coloring Problem is known to be NP-complete for chordal graphs. In this paper, we strengthen this result by proving that Decide Injective coloring Problem remains NP-complete for undirected path graphs, a proper subclass of chordal graphs. Moreover, we show that it is not possible to approximate the injective chromatic number of an undirected path graph within a factor of n1/3−ε in polynomial time for every ε>0 unless ZPP = NP. On the positive side, we prove that the injective chromatic number of an interval graph is either Δ(G) or Δ(G)+1, where Δ(G) is the maximum degree of G. We also characterize the interval graphs having χi(G)=Δ(G) and χi(G)=Δ(G)+1. As a consequence of this characterization, we obtain a linear time algorithm to find the injective chromatic number of an interval graph.

High dynamic range image tone mapping based on variational image decomposition and color correction

Tone mapping aims to reproduce high dynamic range (HDR) images on low dynamic range (LDR) display devices. The layer-decomposition-based tone mapping algorithms usually decompose HDR images into base and detail layers and process them accordingly. Since the detail layer is not refined again, these algorithms may suffer from halo artifacts, relatively dull color, and over-enhancement problems. To solve these problems, we introduce the variational image decomposition model and color correction into the field of tone mapping, and propose a tone mapping algorithm that combines the three-part variational image decomposition model with a color correction scheme based on minimum color loss. In contrast to traditional layer-decomposition-based tone mapping algorithms, we employ the three-part decomposition model that decomposes the HDR image into three components: a cartoon component, a texture component, and a high-frequency detail component. The cartoon component is compressed using a gamma function, while the texture and high-frequency detail components are each enhanced using the nonlinear stretching functions. This approach allows for better detail enhancement while preserving the smoothness of the image. In addition, we further use the color correction scheme based on minimum color loss to solve the color problem caused by the layer-decomposition-based tone mapping algorithms. Experimental results show that our proposed tone mapping algorithm can reduce the halo artifacts and preserve the edge details while outperforming some state-of-the-art tone mapping algorithms.

Study on Synergistic Radiation Yellow Light of Strontium Nitrate/Barium Nitrate-Based Illuminant

ABSTRACT In order to change the problem of a single yellow light color emitted by sodium salt illuminant. Based on the principle of color-light mixing and the mechanism of synergistic radiation of double-dyeing flame agents, four groups of strontium nitrate/barium nitrate-based yellow light illuminant formulations with different ratios were designed, which were calculated and comparatively analyzed by REAL and MATLAB software through experiments. From the experimental results, it can be seen that the virtual main wavelength of strontium nitrate/barium nitrate-based yellow light illuminant was adjusted in the range of 579 nm-591 nm, and the color ranged from light yellow to golden yellow, among which the best formulation was strontium nitrate/barium nitrate/magnesium/worm gum/polyvinyl chloride with the ratio of 50.25/16.25/13.5/2.5/17.5. The oxygen balance of this formulation was −0.130 g-g-1, and the combustion temperature was 2790.88 K. The color light emitters were Sr, SrO, SrOH, SrCl, Ba, BaO, BaOH, BaCl, the color coordinates were (0.5256, 0.3988), the virtual dominant wavelength was 591 nm, the color purity was 0.79, and the luminescence intensity was 247,893.18 cd, and the combustion time was 6.8s.

A Greedy Probabilistic Heuristic for Graph Black-and-White Anticoloring

Given a graph $G$ and positive integers $b$ and $w$, the Black-and-White Coloring problem asks about the existence of a partial vertex-coloring of $G$, with $b$ vertices colored black and $w$ white, such that there is no edge between a black and a white vertex. The problem is known to be NP-complete. In this paper, we deal with the optimization version, mainly for random graphs. Using the method of conditional expectations, we develop a heuristic with a good performance. We also obtain theoretical results on some of the relevant quantities, and compare the performance of the heuristic with that of several others.

Addressing cities’ color issues and planning urban colors with regional features to preserve the history and culture of cities: the case of Suzhou, Wuxi, and Changzhou (China)

ABSTRACT Although there are many remarkable examples of color traditions from different parts of the world, many cities still face color-related issues, such as lack of regionality and clutter. Since the color issues of different cities vary, the solutions must also be different. This paper examines the old urban areas of Suzhou, Wuxi, and Changzhou in China as a case study to investigate how to solve urban color problems and shape the architectural color with regional characteristics. By exploring the spatial distribution of color categories and the interval distribution of color attribute values, this paper finds that the increase in colored buildings (especially along the main roads) and the excessive chromaticity of new buildings affect the regionality of urban colors. Therefore, we propose restoring urban color by establishing color zoning and controlling chromaticity to increase cultural diversity, promote economic vitality, and enhance people’s sense of belonging. The planning of urban color and the establishment of color patterns with regional characteristics are of positive significance for the development of urban history, culture, and habitat.

Dual-wavelength superscattering in plasmonic core-shell nanostructures for transparent structural color

Structural coloration generates some of the most vibrant colors in nature and has numerous applications. Inspired by the recently reported transparent displays relying on wavelength-selective scattering, we address the novel problem of transparent structural color, which requires nanoparticles to have a narrow-band and broad-angle scattering response. Although superscattering beyond the single-channel limit has important prospects for enhancing transparent displays, it has not yet been reported. Here, we propose a simple dielectric-gold core–shell nanoparticle capable of superscattering at blue (λ = 450 nm) and green (λ = 532 nm) wavelengths, along with a dipolar surface plasmon resonance (SPR) at the red wavelength (λ = 640 nm), making it suitable for full-color transparent displays. We demonstrate that the superscattering at λ = 450 nm arises from the overlap of the epsilon-near-zero (ENZ) dipolar and quadrupolar modes. Furthermore, the coupling of conventional quadrupolar and dipolar modes can also enhance the scattering efficiency at λ = 532 nm, breaking the single-channel limit. Lastly, we show that the optimized nanoparticles can confine the scattering light within the forward hemisphere at λ = 450 nm and 532 nm, due to the interaction of quadrupolar and dipolar modes. Additionally, they exhibit dipole far-field radiation characteristics at λ = 640 nm with a wide angular beamwidth > 60°. The simple structural nature and unique scattering properties of proposed dielectric-gold core–shell nanoparticles hold promise applications in full-color transparent displays, spectroscopy, and biomedical imaging.

A Comparative Study of Cat Swarm Algorithm for Graph Coloring Problem: Convergence Analysis and Performance Evaluation

The Graph Coloring Problem (GCP) is a significant optimization challenge widely suitable to solve scheduling problems. Its goal is to specify the minimum colors (k) required to color a graph properly. Due to its NP-completeness, exact algorithms become impractical for graphs exceeding 100 vertices. As a result, approximation algorithms have gained prominence for tackling large-scale instances. In this context, the Cat Swarm algorithm, a novel population-based metaheuristic in the domain of swarm intelligence, has demonstrated promising convergence properties compared to other population-based algorithms. This research focuses on designing and implementing the Cat Swarm algorithm to address the GCP. By conducting a comparative study with established algorithms, our investigation revolves around quantifying the minimum value of k required by the Cat Swarm algorithm for each graph instance. The evaluation metrics include the algorithm's running time in seconds, success rate, and the mean count of iterations or assessments required to reach a goal.

On Students' Computational Thinking Skills for Solving SRAC and its Theoretical Framework on Multi-Step Time Series Forecasting on River Erosion using GNN under RBL-STEM Learning Stages

Computational thinking involves the use of computer science principles to solve complex problems, extending beyond simple programming to various life applications. In today’s educational landscape, the promotion of these skills in the classroom is critical, yet students’ computational thinking skills remain underdeveloped due to inadequate learning models. Key indicators of computational thinking include problem decomposition, algorithmic thinking, pattern recognition, abstraction, and generalization. This study presents RBL-STEM learning activities aimed at enhancing students’ computational thinking through solving the Strong Rainbow Antimagic Coloring or SRAC problem and applying it to multi-step time series forecasting on river erosion using Graph Neural Networks or GNN. The research adopts a qualitative narrative method, beginning with the development of a prototype for multi-step time series forecasting on river erosion using SRAC and GNN, and progressing to the formulation of RBL-STEM learning steps. The results include a comprehensive RBL-STEM learning framework ready for implementation in future research. Learning framework offers student and educator a structured approach to integrating STEM on real life issues. By employing RBL-STEM, students are encouraging to solve river erosion problem systematically based on RBL stages. These finding suggest that the implementation of RBL-STEM with innovative mathematical problems such as SRAC can enhance students’ combinatorial skills, leading to practical solutions for everyday issues through education.

PSANet: Automatic colourisation using position‐spatial attention for natural images

AbstractDue to the richness of natural image semantics, natural image colourisation is a challenging problem. Existing methods often suffer from semantic confusion due to insufficient semantic understanding, resulting in unreasonable colour assignments, especially at the edges of objects. This phenomenon is referred to as colour bleeding. The authors have found that using the self‐attention mechanism benefits the model's understanding and recognition of object semantics. However, this leads to another problem in colourisation, namely dull colour. With this in mind, a Position‐Spatial Attention Network(PSANet) is proposed to address the colour bleeding and the dull colour. Firstly, a novel new attention module called position‐spatial attention module (PSAM) is introduced. Through the proposed PSAM module, the model enhances the semantic understanding of images while solving the dull colour problem caused by self‐attention. Then, in order to further prevent colour bleeding on object boundaries, a gradient‐aware loss is proposed. Lastly, the colour bleeding phenomenon is further improved by the combined effect of gradient‐aware loss and edge‐aware loss. Experimental results show that this method can reduce colour bleeding largely while maintaining good perceptual quality.

Code and Data Repository for Solving the Minimum Sum Coloring Problem: Alternative Models, Exact Solvers, and Metaheuristics

This repository provides data for the problem and scripts for the models. The main folders are 'data', 'scripts', and 'results'. 'data': This folder includes minimum sum graph coloring data sets. 'src': Our metaheuristic solver Q-Card can be found in this folder. 'scripts': This folder provides a running script. 'results': This folder provides the results.

Solving the Minimum Sum Coloring Problem: Alternative Models, Exact Solvers, and Metaheuristics

Solving the Minimum Sum Coloring Problem: Alternative Models, Exact Solvers, and Metaheuristics

Solving QUBO problems with cP systems

P systems with compound terms (cP systems) have been proposed by Radu Nicolescu in 2018. These expressive cP systems have been used to solve well-known NP-complete problems efficiently, such as the Hamiltonian path, traveling salesman, 3-coloring, and software verification problems. In this paper, we use cP systems to provide an efficient parallel solution to the integer-valued quadratic unconstrained Boolean optimization (QUBO) problem.

Dealing with inequality constraints in large-scale semidefinite relaxations for graph coloring and maximum clique problems

Dealing with inequality constraints in large-scale semidefinite relaxations for graph coloring and maximum clique problems

A CMOS-compatible oscillation-based VO2 Ising machine solver

Phase-encoded oscillating neural networks offer compelling advantages over metal-oxide-semiconductor-based technology for tackling complex optimization problems, with promising potential for ultralow power consumption and exceptionally rapid computational performance. In this work, we investigate the ability of these networks to solve optimization problems belonging to the nondeterministic polynomial time complexity class using nanoscale vanadium-dioxide-based oscillators integrated onto a Silicon platform. Specifically, we demonstrate how the dynamic behavior of coupled vanadium dioxide devices can effectively solve combinatorial optimization problems, including Graph Coloring, Max-cut, and Max-3SAT problems. The electrical mappings of these problems are derived from the equivalent Ising Hamiltonian formulation to design circuits with up to nine crossbar vanadium dioxide oscillators. Using sub-harmonic injection locking techniques, we binarize the solution space provided by the oscillators and demonstrate that graphs with high connection density (η > 0.4) converge more easily towards the optimal solution due to the small spectral radius of the problem’s equivalent adjacency matrix. Our findings indicate that these systems achieve stability within 25 oscillation cycles and exhibit power efficiency and potential for scaling that surpasses available commercial options and other technologies under study. These results pave the way for accelerated parallel computing enabled by large-scale networks of interconnected oscillators.

Integrating glycolysis and enzymatic catalyst to convert waste poly(ethylene terephthalate) into terephthalic acid

The current society has an increasing demand for poly(ethylene terephthalate) (PET). Due to its high crystallinity and hydrophobicity, PET could be hardly degraded for high-value utilization. Besides, the escalating accumulation of waste PET has also led to significant environmental issues. In this study, a convenient and cost-efficient industrial strategy featuring the integration of glycolysis and enzymatic catalysis has been developed for the selective conversion of PET into terephthalic acid (TPA), which provides a method for colored waste PET degradation. Without the need for complex purifying processes, the products of glycolysis directly initiate the next round of the enzymatic system. Through this system, a total yield of 72.47 % of bis-2-(hydroxyethyl) terephthalate(BHET) and mono-(2-hydroxyethyl) terephthalate(MHET) was produced by glycolysis loading sodium bicarbonate (NaHCO3) catalyst, and the enzyme system almost completely converted a substrate concentration of 100 g/L within 48 h, producing 50.36 g/L TPA. Besides, the product problem of pink color in the air after acidification caused by cobalt ions was solved by resin adsorption. In general, the glycolysis and enzymatic catalysis system in this study has prospects for commercial application due to its value for colored waste PET recycling, which reduces the environmental burden caused by waste PET.

Bisimplicial separators

AbstractA minimal separator of a graph is a set such that there exist vertices with the property that separates from in , but no proper subset of does. For an integer , we say that a minimal separator is ‐simplicial if it can be covered by cliques and denote by the class of all graphs in which each minimal separator is ‐simplicial. We show that for each , the class is closed under induced minors, and we use this to show that the Maximum Weight Stable Set problem can be solved in polynomial time for . We also give a complete list of minimal forbidden induced minors for . Next, we show that, for , every nonnull graph in has a ‐simplicial vertex, that is, a vertex whose neighborhood is a union of cliques; we deduce that the Maximum Weight Clique problem can be solved in polynomial time for graphs in . Further, we show that, for , it is NP‐hard to recognize graphs in ; the time complexity of recognizing graphs in is unknown. We also show that the Maximum Clique problem is NP‐hard for graphs in . Finally, we prove a decomposition theorem for diamond‐free graphs in (where the diamond is the graph obtained from by deleting one edge), and we use this theorem to obtain polynomial‐time algorithms for the Vertex Coloring and recognition problems for diamond‐free graphs in , and improved running times for the Maximum Weight Clique and Maximum Weight Stable Set problems for this class of graphs.