Potato, a vital food and cash crop, necessitates precise identification area estimation for effective planting planning, market regulation, yield forecasting. However, extracting large-scale crop areas using satellite remote sensing is fraught with challenges, such as low spatial resolution, cloud interference, revisit cycle limitations, impeding the creation of high-quality time–series datasets. In this study, we developed high-resolution vegetation index by calculating coordination...

Potato is a major food crop in China. Its development and nutritional state can be inferred by the content of chlorophyll its canopy. However, existing study on applying feature extraction optimization algorithms to determine canopy SPAD (Soil–Plant Analytical Development) values potatoes at various fertility stages inadequate not very reliable. Using Pearson selection algorithm Competitive Adaptive Reweighted Sampling (CARS) method, Vegetation Index (VI) with highest correlation was...

Vulnerability detection in software source code is crucial ensuring security. Existing models face challenges with dataset class imbalance and long training times. To address these issues, this paper introduces a multi-feature screening integrated sampling model (MFISM) to enhance vulnerability efficiency accuracy. The key innovations include (i) utilizing abstract syntax tree (AST) representation of extract potential vulnerability-related features through multiple feature techniques; (ii)...

Literature on cross-cultural differences in cognition suggests that categorization, as an information processing and organization strategy, was more often used by Westerners than East Asians, particularly for older adults. This study examines East-West cultural memory categorically processed items sources young Canadians native Chinese with a conceptual source task (Experiment 1) reality monitoring 2). In Experiment 1, participants encoded photographic faces of their own ethnicity were...

With the increasingly severe challenge of Software Supply Chain (SSC) security, rising trend in guarding against security risks has attracted widespread attention. Existing techniques still face challenges both accuracy and efficiency when detecting malware SSC. To meet this challenge, paper introduces two novel models, named Bayesian Optimization-based Support Vector Machine (BO-SVM) Long Short-Term Memory–BO-SVM (LSTM-BO-SVM). The BO-SVM model is constructed on an SVM foundation, with its...

Early blight and ladybug beetle infestation are important factors threatening potato yields. The current research on disease classification using the spectral differences between healthy disease-stressed leaves of plants has achieved good progress in a variety crops, but less been conducted early potato. This paper proposes CARS-SPA-GA feature selection method. First, raw data visible/near-infrared light region were preprocessed. Then, wavelengths selected via competitive adaptive reweighted...

Research has shown that observers in a multiple-object tracking task are poor at recognizing the identity of successfully tracked objects (Z. W. Pylyshyn, 2004). Employing same paradigm, we examined processing and its relationship with performance for human faces. Experiment 1 showed although recognition was poorer after target faces were learned dynamic display, identification still much higher than chance level. The experiment also found on average about two face identities can be...

The travelling salesman problem (TSP) is a classic of combinatorial optimization and has applications in planning, scheduling, searching many scientific engineering fields. Genetic algorithms (GA) ant colony (ACO) have been successfully used solving TSPs associated the last two decades. However, both GA ACO difficulty regularly reaching global optimal solutions for TSPs. In this paper, we propose new hybrid algorithm, system-assisted genetic algorithm (ASaGA) to handle problem. main change...

Chlorophyll-a (Chl-a) is an important parameter of water bodies, but due to the complexity optics in it currently difficult accurately predict Chl-a concentration bodies by traditional methods. In this paper, Sentinel-2 remote sensing images used as data source combined with measured data, and Ulansuhai Lake taken study area. An adaptive ant colony exhaustive optimization (A-ACEO) algorithm proposed for feature selection a novel intelligent optimizing support vector regression (SVR) genetic...

Human beings are very quick and efficient at categorizing nature scenes. Recent functional MRI studies found that the neural activation in response to line-drawings was similar color photographs (e.g., Walter et al., 2011). However, it remains unclear whether time course of braining activity different images. The present study aimed investigate how scene categorization reflected event-related potentials (ERPs). Color six natural categories (beaches, city streets, forests, highways, mountains...

Abstract Chlorophyll-a (Chl-a) is an important parameter in water bodies. Due to the complexity of optics bodies, it difficult accurately predict Chl-a concentrations bodies by current traditional methods. In this paper, using Sentinel-2 remote sensing images as data source combined with measured data, taking Wuliangsu Lake study area, a new intelligent algorithm proposed for prediction concentration, which uses adaptive ant colony exhaustive optimization (A-ACEO) feature selection and gray...

Sugarcane is the primary crop in global sugar industry, yet it remains highly susceptible to a wide range of diseases that significantly impact its yield and quality. An effective solution required solve issues given by manual identification plant diseases, which time-consuming wasteful, as well low detection accuracy. This paper proposes development robust deep ensemble convolutional neural network (DECNN) model for accurate sugarcane leaf diseases. Initially, several transfer learning (TL)...

Ant colony optimization algorithm is an important swarm intelligence algorithm. It has been applied to many fields of combinatorial because its parallel, distributed computing and running speed. But, ant some shortcomings. For example, searching process may stagnate. Local search a good method when cooperate with other algorithms. But hybrid local methods will increase the time. This paper devises hierarchical parallel for TSPs computes 4 processors. Computation results show that can improve...

The pairwise sequence alignment algorithm, Needleman-Wunsch is one of the most basic algorithms in biological information processing.However, algorithm based on dynamic programming gets optimal results with high time complexity and space complexity,which impractical.This paper proposes an improved Needleman-Wunsch, demonstrates by experiment.With same score accuracy, we compare analyze running before after improvement.The experimental show that can reduce algorithm. IntroductionSequence core...

In order to guarantee the tag identification accuracy and efficiency in mobile radio frequency system, it is necessary estimate tags’ arrival rate before performing identification. This research aims develop a novel estimation method based on improved grey model(1,1) sliding window mechanism. By establishing dynamic model, this article emphasizes importance of system. Using mechanism weighted coefficients method, with (WGMSW(1,1)) proposed traditional model(1,1). For experimental...