The role of different grid search computer algorithms for the determination of the thermodynamic properties of water and steam in the p-T and P-S planes has been investigated via experimental and analytical methods. The results show that the spline interpolation grid search algorithm and the power grid search algorithm are more efficient, stable and clear than other algorithms.

Plant disease is one of the major threats to food security. Accurate diagnosis of plant diseases can benefit the agricultural production. For the purpose of real-time plant disease diagnostics, the deep learning models are employed. In this study, we present an accurate identification method for common diseases of tomatoes based on deep-learning methods. The devising of multi-resolution detector, in line with bounding box generating and assigning, facilitates the feature extracting process of detection. The employment of an dropout and ADAMW (Adaptive moment estimation with decoupled weight decay) optimizer further resolve the overfitting problem. Using the collected images of healthy and diseased tomatoes, our detector is trained to identify 10 different diseases. Experimental results showed that the disease identification method proposed in this study could accurately and rapidly identify common diseases of tomato with an average accuracy of 85.03%and a recognition speed of 61 frames per second, which was superior to other models under the same conditions and was beneficial for tomato disease control work.

With the improvement of people's living standards, people's pursuit of clothing is becoming more and more diverse. As the main way to shape the external curve of the human body and reflect the texture of clothing materials, pleating technology is widely used in clothing. Different wrinkle expression techniques can often be seen in garment production and press conferences. Many designers are inseparable from the use of folding technology in their creation. The decoration of clothing is also constantly enriched. Diversified and multitype fabrics will bring great differences and influence to clothing and even affect the trend. Based on the computer animation technology, through the analysis of the principle of three-dimensional folds, this paper explores the formation of geometric patterns from two-dimensional plane fabric laying to three-dimensional, mainly through the techniques of pleating, kneading, lattice pleating, and pleating, so as to knead, stack or stack the fabrics orderly or randomly and naturally. The folded intersection area and nonfolded area are formed to form the basis of three-dimensional geometric folds. The simulation results show that the computer animation technology can effectively support the three-dimensional fold garment pattern design, select different materials for regional folding, present obvious three-dimensional geometric pattern folds, understand the expression forms of folds, and explain the application of folds in garment design, so as to provide some reference for fold garment design.

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