Efficient and sustainable improvement of a system of production and commercialization of Essential Molle Oil (Schinus Molle)

Rodríguez, Raquel Medina; Oré, Jorge Luis Breña; Vargas, Doris Esenarro

doi:10.17993/3cemp.2021.100448.43-75

Cited by 9 publications

(6 citation statements)

References 11 publications

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“…Zhang et al [33] used the research method of the fnancial risk early warning model in the random efect model and proposed the risk analysis and prediction index system and built the company's fnancial risk early warning model. Rodríguez et al [34] used an experimental approach to study the relationship between efcient production cycle design and the environmental sustainability of Schinus molle plant metabolites. Trough the comparison of the control group and the experimental group, the hypothesis test of the mean diference and Wilcoxon statistics shows that the green business model has a positive relationship with environmental sustainability.…”

Section: Basic Modelmentioning

confidence: 99%

Oligopoly Modeling between Public and Private Companies with Complementarity

Chen

2023

Discrete Dynamics in Nature and Society

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This study investigated the coexistence of public and private companies using a complementary model to explore mixed oligopoly strategies. Compared to the traditional theory of mixed oligopoly, the main difference of this study is that it revealed that the products produced by both companies are completely complementary. The five findings of the study were as follows: First, under the premise of having one firm classified as a public firm, although it can reach the equilibrium of the maximum solution for social welfare, this causes a loss. Second, more seriously, the private firm would view this as a huge incentive and aggressively pursue to be the price leader, which may result in a greater loss for the public firm. Third, the asymmetry of the model of the complementary mixed oligopoly is of note; that is, when the private firm is in aggressive pursuit to be the price leader, it can elevate its profit margin, but when the public firm is aggressively pursuing be the price leader, this would not result in better profits. Fourth, if the public firm is under budgetary constraints, then the private firm would have no incentive to aggressively pursue being the price leader. Fifth, if the price of the product between the public firm and the private firm is a “strategic substitute,” the coexistence of the public firm and the private firm will be better than total privatization.

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Section: Basic Modelmentioning

confidence: 99%

Oligopoly Modeling between Public and Private Companies with Complementarity

Chen

2023

Discrete Dynamics in Nature and Society

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“…From Figure 4, we can see that the exponential function and the power function are more in line with our design purpose. Therefore, We take the starting and ending points of the new scale initially formulated in the section, remove the ultra-low achievement segments below the starting point, and remove the ultra-high score segments above the stopping point, and use the exponential function and power function to fit the simplified scale in origin9.0, and take the best fitting effect among the many fitting results [31][32]. Then use the function with the best fit, still using the interval of each score segment in the original score table, and bring the scores of the original score table into the fitting function to find the corresponding score, which is the result we get in this section using the progressive idea.…”

Section: Neural Network Development Of the Allometric Rating Scalementioning

confidence: 99%

Construction of an efficient evaluation model for athletic athletes' competitive ability based on deep neural network algorithm

Niu¹

2023

3C Empresa

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This paper analyzes the data of this year's athletes' physical fitness test scores and manages the classification of different physical qualities of the farmer. In order to reduce the manual calculation and increase the prediction efficiency, as well as to unify the scoring criteria of previous years, this paper proposes a comprehensive performance prediction model based on deep neural network algorithm. First, principal component analysis is used to transform multiple attributes with strong correlation into independent attributes that are not related to each other, and to reduce the time and space for model training by eliminating redundancy. Second, a back propagation (BP) neural network algorithm is used to build a physical fitness test prediction model, and the model is applied to the test dataset for model performance evaluation. Finally, the physical fitness test model was applied to other years for comprehensive performance prediction, and the differences between the model prediction results and the actual teachers' manual calculation results were observed. The results showed very good prediction results for 2021, in which 92.95% of the data had an absolute value of error less than 2 and only 0.06% had an absolute value of error greater than 4, which indicated that the prediction performance of the model was extremely significant. At the same time, a new athletic athletic scoring standard was also developed based on the neural network BP model to provide a more scientific theoretical basis and guidance for the evaluation of athletic ability of athletes.

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“…Among them, pests are a very important factor, containing many kinds of pests (plant pathogens, pests, weeds and rodents, etc. ), which affect the yield and quality of cultivated plants and have an impact on fossil energy reserves [ 3 , 4 , 5 , 6 , 7 , 8 ]. Agricultural pests are usually classified as insects and mites that cause damage to various plants, and insects are the largest number of pests that affect crops.…”

Section: Introductionmentioning

confidence: 99%

High-Performance Plant Pest and Disease Detection Based on Model Ensemble with Inception Module and Cluster Algorithm

Cheng

Cui

et al. 2023

Plants

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Protecting crop yields is the most important aspect of agricultural production, and one of the important measures in preserving yields is the control of crop pests and diseases; therefore, the identification of crop pests and diseases is of irreplaceable importance. In recent years, with the maturity of computer vision technology, more possibilities have been provided for implementing plant disease detection. However, although deep learning methods are widely used in various computer vision tasks, there are still limitations and obstacles in practical applications. Traditional deep learning-based algorithms have some drawbacks in this research area: (1) Recognition accuracy and computational speed cannot be combined. (2) Different pest and disease features interfere with each other and reduce the accuracy of pest and disease diagnosis. (3) Most of the existing researches focus on the recognition efficiency and ignore the inference efficiency, which limits the practical production application. In this study, an integrated model integrating single-stage and two-stage target detection networks is proposed. The single-stage network is based on the YOLO network, and its internal structure is optimized; the two-stage network is based on the Faster-RCNN, and the target frame size is first clustered using a clustering algorithm in the candidate frame generation stage to improve the detection of small targets. Afterwards, the two models are integrated to perform the inference task. For training, we use transfer learning to improve the model training speed. Finally, among the 37 pests and 8 diseases detected, this model achieves 85.2% mAP, which is much higher than other comparative models. After that, we optimize the model for the poor detection categories and verify the generalization performance on open source datasets. In addition, in order to quickly apply this method to real-world scenarios, we developed an application embedded in this model for the mobile platform and put the model into practical agricultural use.

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Efficient and sustainable improvement of a system of production and commercialization of Essential Molle Oil (Schinus Molle)

Cited by 9 publications

References 11 publications

Oligopoly Modeling between Public and Private Companies with Complementarity

Oligopoly Modeling between Public and Private Companies with Complementarity

Construction of an efficient evaluation model for athletic athletes' competitive ability based on deep neural network algorithm

High-Performance Plant Pest and Disease Detection Based on Model Ensemble with Inception Module and Cluster Algorithm

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