Multi-Agent Path Finding via Tree LSTM

In recent years, Multi-Agent Path Finding (MAPF) has attracted attention from the fields of both Operations Research (OR) and Reinforcement Learning (RL). However, in the 2021 Flatland3 Challenge, a competition on MAPF, the best RL method scored only 27.9, far less than the best OR method. This paper proposes a new RL solution to Flatland3 Challenge, which scores 125.3, several times higher than the best RL solution before. We creatively apply a novel network architecture, TreeLSTM, to MAPF in our solution. Together with several other RL techniques, including reward shaping, multiple-phase training, and centralized control, our solution is comparable to the top 2-3 OR methods.Comment: Appear in AAAI23-MAP

The Optimization and Mathematical Modeling of Quality Attributes of Parboiled Rice Using a Response Surface Method

The response surface methodology was used to optimize the hydrothermal processing conditions based on the rice quality parameters of the Rong Youhua Zhan rice variety (Indica). The effect of soaking temperature (29.77, 40, 55, 70, and 80.23°C), soaking time (67.55, 90, 120, 150, and 170.45 min), and steaming time (1.59, 5, 10, 15, and 18.41 min), each tested at five levels, on percentage of head rice yield (HRY), hardness, cooking time, lightness, and color were determined, with R2 values of 0.96, 0.94, 0.90, 0.88, and 0.94, respectively. HRY, hardness, cooking time, and color increased with process severity while lightness decreased, although HRY decreased after reaching a maximum. The predicted optimum soaking temperature, soaking time, and steaming time were 69.88°C, 150 min, and 6.73 min, respectively, and the predicted HRY, hardness, cooking time, lightness, and color under these conditions were 73.43%, 29.95 N, 32.14 min, 83.03 min, and 12.24 min, respectively, with a composite desirability of 0.9658. The parboiling industry could use the findings of the current study to obtain the desired quality of parboiled rice. This manuscript will be helpful for researchers working on commercializing parboiled rice processes in China as well as in other countries

Perturbed stochastic fractal search for solar PV parameter estimation

Following the widespread use of solar energy all over the world, the design of high quality photovoltaic (PV) cells has attracted strong research interests. To properly evaluate, control and optimize solar PV systems, it is crucial to establish a reliable and accurate model, which is a challenging task due to the presence of non-linearity and multi-modality in the PV systems. In this work, a new meta-heuristic algorithm (MHA), called perturbed stochastic fractal search (pSFS), is proposed to estimate the PV parameters in an optimization framework. The novelty lies in two aspects: (i) employ its own searching operators, i.e., diffusion and updating, to achieve a balance between the global exploration and the local exploitation; and (ii) incorporate a chaotic elitist perturbation strategy to improve the searching performance. To examine the effectiveness of pSFS, this method is applied to solve three PV estimation problems for different PV models, including single diode, double diode and PV modules. Experimental results and statistical analysis show that the proposed pSFS has improved estimation accuracy and robustness compared with several other algorithms recently developed

Experimental study of drying characteristics and mathematical modeling for air drying of germinated brown rice

In view of existing problems in the drying process of germinated brown rice (GBR), the self-made hot air drying test system was utilized. The drying medium temperature and wind speed were selected as the drying parameters, and different constraints were set for the test. The effects of the drying medium temperature and wind speed on the drying rate and unit energy consumption were examined, and the drying mathematical models of GBR were established. The results perceived that as the temperature rose, and the wind speed increased, the drying rate increased accordingly. When the temperature was above 95°C, wind speed exceeded 3.6 m/s; the drying rate would not change deliberately. When the temperature of the drying medium rose, the change rate during the drying preheating stage and the deceleration stage increased sharply, whereas the drying rate in the constant-speed drying stage increased, and the drying time was greatly shortened. Unit energy consumption decreased with the increase of temperature and increased with increasing wind speed. Furthermore, when the drying temperature was ranged between 50°C and 80°C, the unit energy consumption changed meaningfully; when the medium temperature was between 80°C and 110°C, the unit heat consumption turned slowly. Wang and Singh’s model could best simulate the drying process of GBR within the experimental settings. And then comparing the RMSE and under the various dry conditions, the data of Wang and Singh model were between 1.6% - 2.8% and 2.5×10-4 - 5×10-4. The R2 values of the model were higher than 0.98

An Introduction of Biomimetic System and Heat Pump Technology in Food Drying Industry

Drying of food products is a relatively complex, nonlinear, and dynamic process due to simultaneous heat and mass transfer, rapid moisture evaporation, and biological and chemical reactions. Therefore, the monitoring of food quality during the drying process using bio-inspired technologies can play a vital role. The demand for high-quality dried food products and the rapid growth of energy in food processing are attracting new and renewable sources of energy. Energy efficiency, improved food product quality, and less environmental impact are always the main priorities of any drying system development. In-depth knowledge of biomimetic systems and drying kinetics would be helpful to design new dryers and technologies. Due to the excellent features (controllable drying temperature, drying time, drying air velocity, and relative humidity), heat pump drying systems have been used widely to ensure food and agricultural product quality. This chapter helps to understand the relationship between bio-inspired technologies and the role of heat pump technology in the food drying industry in terms of cost-effectiveness, energy saving, and better food product quality

An Intelligent Method for Pork Freshness Identification Based on EfficientNet Model

A method for measuring pork freshness based on images and the EfficientNet framework was established. A total of 2 500 images of pork with different freshness were collected as original dataset and processed by image enhancement to construct a new dataset of 60 000 images. First, EfficientNet was trained with the CIFAR-10 dataset to determine the basic structure and initial weights of the model. Then, the model was trained and improved using the constructed dataset to make the model suitable for five classification problems. Finally, the established model was tested, verified, and compared with the current mainstream convolutional neural network (CNN) models of Alexnet, VGG16 and ResNet50. The results showed that the average correct recognition rate of the EfficientNet model was as high as 98.62%, which was significantly better than that of the Alexnet, VGG16 and ResNet50 models. The correct recognition rate of the EfficientNetB2 model was 99.22%, and the training time was only 157 min. The comprehensive performance of the EfficientNetB2 model was the best, making it the most suitable method for pork freshness identification. In order to improve its generalization ability, the optimizer algorithm of the EfficientNetB2 model was improved, and the performances of stochastic gradient descent (SGD), adaptive moment estimation (Adam), root mean square propagation (RMSProp) and rectified adaptive moment estimation (RAdam) were compared. The results showed that the RAdam optimizer failed to further improve the accuracy of the model but instead helped to improve its generalization capability, which will of practical significance for engineering applications

Characterization of marine-terrigenous transitional Taiyuan formation shale reservoirs in Hedong coal field, China

To better understand the basic characteristics of Marine-terrigenous Transitional Taiyuan formation shale (TYS) reservoirs in Hedong coal field, a series of reservoir evaluation experiments were conducted on 33 core samples, which were collected from an exploration shale gas well (SL-1). The results show that organic matters in TYS are Type III gas prone kerogen and are in the high-maturity stage with an average Ro value of 1.87% (ranging from 1.71% to 2.10%). The total organic carbon (TOC) is ranging from 0.29% to 11.87% with an average value of 2.91% and gas content is from 0.41% to 2.96 ml/g, which indicates that TYS still has certain hydrocarbon generation potential despite a mass generation of hydrocarbons occurred during the geological history. X-ray diffraction analysis shows that TYS is composed mainly of quartz minerals and clay minerals with an average brittleness index of 46.5%, which is relatively favorable for hydraulic fracture. Pore size of TYS ranges from a few nanometers to hundreds of nanometers. The permeability is irrelevant with porosity and its values are all lower than 0.1 md. The average value of Brunauer- Emmett-Teller surface area and Barrett-Joyner-Halendar volumes are 8.57 m2 /g and 1.84 cm3 /100g, respectively. Similar to previous studies, TOC content is a decisive control on gas adsorption capacity in this study.Cited as: Li, K., Chen, G., Li, W., Wu, X., Tan, J., Qu, J. Characterization of marine-terrigenous transitional Taiyuan formation shale reservoirs in Hedong coal field, China. Advances in Geo-Energy Research, 2018, 2(1): 72-85, doi: 10.26804/ager.2018.01.0

Ru doping induced spin frustration and enhancement of the room-temperature anomalous Hall effect in La2/3Sr1/3MnO3 films

In transition-metal-oxide heterostructures, the anomalous Hall effect (AHE) is a powerful tool for detecting the magnetic state and revealing intriguing interfacial magnetic orderings. However, achieving a larger AHE at room temperature in oxide heterostructures is still challenging due to the dilemma of mutually strong spin-orbit coupling and magnetic exchange interactions. Here, we exploit the Ru doping-enhanced AHE in LSMRO epitaxial films. As the B-site Ru doping level increases up to 20 percent, the anomalous Hall resistivity at room temperature can be enhanced from nOhmcm to uOhmcm scale. Ru doping leads to strong competition between ferromagnetic double-exchange interaction and antiferromagnetic super-exchange interaction. The resultant spin frustration and spin-glass state facilitate a strong skew-scattering process, thus significantly enhancing the extrinsic AHE. Our findings could pave a feasible approach for boosting the controllability and reliability of oxide-based spintronic devices

Skeletal Muscle Regeneration on Protein-Grafted and Microchannel-Patterned Scaffold for Hypopharyngeal Tissue Engineering

In the field of tissue engineering, polymeric materials with high biocompatibility like polylactic acid and polyglycolic acid have been widely used for fabricating living constructs. For hypopharynx tissue engineering, skeletal muscle is one important functional part of the whole organ, which assembles the unidirectionally aligned myotubes. In this study, a polyurethane (PU) scaffold with microchannel patterns was used to provide aligning guidance for the seeded human myoblasts. Due to the low hydrophilicity of PU, the scaffold was grafted with silk fibroin (PU-SF) or gelatin (PU-Gel) to improve its cell adhesion properties. Scaffolds were observed to degrade slowly over time, and their mechanical properties and hydrophilicities were improved through the surface grafting. Also, the myoblasts seeded on PU-SF had the higher proliferative rate and better differentiation compared with those on the control or PU-Gel. Our results demonstrate that polyurethane scaffolds seeded with myoblasts hold promise to guide hypopharynx muscle regeneration

FRACTAL FEATURE ANALYSIS OF BEEF MARBLING PATTERNS

Abstract: The purpose of this study is to investigate fractal behavior of beef marbling patterns and to explore relationships between fractal dimensions and marbling scores. Authors firstly extracted marbling images from beef rib-eye crosssection images using computer image processing technologies and then implemented the fractal analysis on these marbling images based on the pixel covering method. Finally box-counting fractal dimension (BFD) and informational fractal dimension (IFD) of one hundred and thirty-five beef marbling images were calculated and plotted against the beef marbling scores. The results showed that all beef marbling images exhibit fractal behavior over the limited range of scales accessible to analysis. Furthermore, their BFD and IFD are closely related to the score of beef marbling, suggesting that fractal analyses can provide us a potential tool to calibrate the score of beef marbling