Usability Evaluation Approach of Educational Resources Software Using Mixed Intelligent Optimization

Aiming at the problems of strong subjectivity and uncertain fuzziness of attribute weights in the software usability evaluation approach, an evaluation approach based on mixed intelligent optimization was proposed, which combines subjective and objective methods to measure software usability for educational resources software. Firstly, the usability evaluation index system of educational resources software was established, and the basic probability assignment was generated by the interval method from the historical sample data. Then the weight optimization problem was adapted to the smooth optimization problem by the maximum entropy function method, and the hybrid social cognitive optimization (HSCO) algorithm was introduced to solve the optimal weights of evidence. Finally, the software usability level was fused by DS evidence theory. The experimental results show that the educational resources software usability evaluation approach can objectively and truly reflect the usability of the software. It provides an efficient way to evaluate the usability of the software

LOREN: Logic-Regularized Reasoning for Interpretable Fact Verification

Given a natural language statement, how to verify its veracity against a large-scale textual knowledge source like Wikipedia? Most existing neural models make predictions without giving clues about which part of a false claim goes wrong. In this paper, we propose LOREN, an approach for interpretable fact verification. We decompose the verification of the whole claim at phrase-level, where the veracity of the phrases serves as explanations and can be aggregated into the final verdict according to logical rules. The key insight of LOREN is to represent claim phrase veracity as three-valued latent variables, which are regularized by aggregation logical rules. The final claim verification is based on all latent variables. Thus, LOREN enjoys the additional benefit of interpretability -- it is easy to explain how it reaches certain results with claim phrase veracity. Experiments on a public fact verification benchmark show that LOREN is competitive against previous approaches while enjoying the merit of faithful and accurate interpretability. The resources of LOREN are available at: https://github.com/jiangjiechen/LOREN.Comment: Accepted to AAAI 202

The Impact of the COVID-19 Pandemic on the Global Value Chain of the Manufacturing Industry

This paper adopts the GDYN model to estimate the dynamic impact of the COVID-19 pandemic on global manufacturing industry and the value chain. Our simulation finds that (1) In the short run, the low-tech manufacturing industries will suffer greater shocks, with a decline of output growth in 2021 by 6.0%. The growth rate of the high-tech manufacturing industry showed an increasing trend of 3.7% in 2021. (2) In the post-epidemic period, the total manufacturing output will return to the baseline level, from which the growth rate of low-tech manufacturing will rebound, demonstrating a V-shaped development trajectory. (3) From the perspective of Global Value Chain (GVC), the participation in GVCs of manufacturers in countries along the Belt and Road, the European Union and the United States will weaken, while China’s manufacturing industry has witnessed an obvious improvement in export competitiveness. The import added value of China has decreased, which shows that its ability to meet domestic demand has been improving. This indicates that the COVID-19 pandemic is providing a crucial opportunity for China to upgrade its manufacturing value chain, which contributes to the accelerated construction of a new dual-cycle development pattern

Study on the Fluid-Solid Coupling Heat Transfer in the Stator of Large Synchronous Condenser Considering Complex Transposition Structure

To solve the problem in which it is difficult to consider the complex transposition structure of the stator winding in the stator fluid-solid coupling analysis of a large synchronous condenser, a three-dimensional stator fluid-solid coupling model considering the transposition structure of the stator winding is established in this paper. Based on the heat transfer characteristics of the transposition insulation in the slot portion and involute insulation in the end portion, a non-uniform grid division method is proposed to solve the three-dimensional fluid-solid coupling model. Then, taking a 300 Mvar synchronous condenser as an example, the stator fluid distribution and temperature distribution were calculated and analyzed, and the results were compared with the non-transposition model and short-circuit type test data. The results show that the transposition structure affects the temperature distribution trend, temperature value and location of the highest temperature of the stator winding. The calculated results obtained using the transposition model were closer to the test data. Finally, the stator temperatures under no-load, over-excited, and no-excited operating conditions were calculated and compared. The results show that the stator temperature distribution trends and values are significantly affected by operating conditions. The stator temperature under the over-excited condition was the highest, and that under the no-load condition was the lowest

A BCS-GDE Multi-objective Optimization Algorithm for Combined Cooling, Heating and Power Model with Decision Strategies

District energy systems can not only reduce energy consumption but also set energy supply dispatching schemes according to demand. In addition to economic cost, energy consumption and pollutant are more worthy of attention when evaluating combined cooling, heating and power (CCHP) models. In this paper, the CCHP model is established with the objective of economic cost, primary energy consumption, and pollutant emissions. The mathematical expression of the CCHP system is proposed, and a multi-objective optimization model with constraints is established. According to different usage requirements, two decision-making strategies are designed, which can adapt to different scenarios. Besides, a generalized differential evolution with the best compromise solution processing mechanism (BCS-GDE) algorithm is proposed to optimize the CCHP model for the first time. The algorithm provides the optimal energy scheduling scheme by optimizing the production capacity of different capacity equipment. The simulation is conducted in three application scenarios: hotels, offices, and residential buildings. The simulation results show that the model established in this paper can reduce economic cost by 72%, primary energy consumption by 73%, and pollutant emission by 88%. Concurrently, the Wilcoxon signed-rank test shows that BCSGDE is significantly better than OMOPSO, NSGA-II, and SPEA2 with greater than 95% confidence.Comment: Accpeted by Applied Thermal Engineering. arXiv admin note: substantial text overlap with arXiv:2108.0739

Precision Seeding Compensation and Positioning Based on Multisensors

The current multi-row planter always leads to uneven seeding spacing between rows while seeding in curve paths, which causes uneven growth, a cost increase of production and management, and reduced yield. With the development of smart farming technology, a curve seeding compensation and precise positioning model is proposed in the paper to calculate the real-time speed and position of each seeding unit based on the information from multisensors, such as GNSS and IMU, and to predict the next seeding position to achieve uniform seeding on the curve and improve the unit yield of crops. MATLAB Simulink simulation experiments show that the seeding pass rate of the model is 99.97% when the positioning accuracy is ±0.01 m and the traction speed is 1 m/s, and the seeding pass rate of the five-row seeder is as high as 99.81% when the traction speed is 3 m/s, which verifies the effectiveness and practicality of the model