Symmetric cross-entropy multi-threshold color image segmentation based on improved pelican optimization algorithm.

To address the problems of low accuracy and slow convergence of traditional multilevel image segmentation methods, a symmetric cross-entropy multilevel thresholding image segmentation method (MSIPOA) with multi-strategy improved pelican optimization algorithm is proposed for global optimization and image segmentation tasks. First, Sine chaotic mapping is used to improve the quality and distribution uniformity of the initial population. A spiral search mechanism incorporating a sine cosine optimization algorithm improves the algorithm's search diversity, local pioneering ability, and convergence accuracy. A levy flight strategy further improves the algorithm's ability to jump out of local minima. In this paper, 12 benchmark test functions and 8 other newer swarm intelligence algorithms are compared in terms of convergence speed and convergence accuracy to evaluate the performance of the MSIPOA algorithm. By non-parametric statistical analysis, MSIPOA shows a greater superiority over other optimization algorithms. The MSIPOA algorithm is then experimented with symmetric cross-entropy multilevel threshold image segmentation, and eight images from BSDS300 are selected as the test set to evaluate MSIPOA. According to different performance metrics and Fridman test, MSIPOA algorithm outperforms similar algorithms in global optimization and image segmentation, and the symmetric cross entropy of MSIPOA algorithm for multilevel thresholding image segmentation method can be effectively applied to multilevel thresholding image segmentation tasks.

Three-dimensional continuous picking path planning based on ant colony optimization algorithm.

Fruit-picking robots are one of the important means to promote agricultural modernization and improve agricultural efficiency. With the development of artificial intelligence technology, people are demanding higher picking efficiency from fruit-picking robots. And a good fruit-picking path determines the efficiency of fruit-picking. Currently, most picking path planning is a point-to-point approach, which means that the path needs to be re-planned after each completed path planning. If the picking path planning method of the fruit-picking robot is changed from a point-to-point approach to a continuous picking method, it will significantly improve its picking efficiency. The optimal sequential ant colony optimization algorithm(OSACO) is proposed for the path planning problem of continuous fruit-picking. The algorithm adopts a new pheromone update method. It introduces a reward and punishment mechanism and a pheromone volatility factor adaptive adjustment mechanism to ensure the global search capability of the algorithm, while solving the premature and local convergence problems in the solution process. And the multi-variable bit adaptive genetic algorithm is used to optimize its initial parameters so that the parameter selection does not depend on empirical and the combination of parameters can be intelligently adjusted according to different scales, thus bringing out the best performance of the ant colony algorithm. The results show that OSACO algorithms have better global search capability, higher quality of convergence to the optimal solution, shorter generated path lengths, and greater robustness than other variants of the ant colony algorithm.

α-Acylation of Alkenes by a Single Photocatalyst.

A direct strategy for the difunctionalization of alkenes, with acylation occurring at the more substituted alkene position, would be attractive for complex ketone synthesis. We report herein a reaction driven by a single photocatalyst that enables α-acylation in this way with the introduction of a fluoromethyl, alkyl, sulfonyl or thioether group at the ß-position of the alkene with high chemo- and regioselectivity under extremely mild conditions. Crucial to the success of this method are rate differences in the kinetics of radical generation through single-electron transfer (SET) between different radical precursors and the excited photocatalyst (PC*). Thus, the ß-position of the alkene is first occupied by the group derived from the radical precursor that can be generated most readily, and α-keto acids could be used as an electrophilic reagent for the α-acylation of alkenes.

Direct 1,2-Dicarbonylation of Alkenes towards 1,4-Diketones via Photocatalysis.

1,4-Dicarbonyl compounds are intriguing motifs and versatile precursors in numerous pharmaceutical molecules and bioactive natural compounds. Direct incorporation of two carbonyl groups into a double bond at both ends is straightforward, but also challenging. Represented herein is the first example of 1,2-dicarbonylation of alkenes by photocatalysis. Key to success is that N(n-Bu)4+ not only associates with the alkyl anion to avoid protonation, but also activates the α-keto acid to undergo electrophilic addition. The α-keto acid is employed both for acyl generation and electrophilic addition. By tuning the reductive and electrophilic ability of the acyl precursor, unsymmetric 1,4-dicarbonylation is achieved for the first time. This metal-free, redox-neutral and regioselective 1,2-dicarbonylation of alkenes is executed by a photocatalyst for versatile substrates under extremely mild conditions and shows great potential in biomolecular and drug molecular derivatization.