Analysis of Internet Financial Risks Based on Deep Learning and BP Neural Network

Computational Economics - The study aims to analyze and forecast Internet financial risks based on the model based on deep learning and the Back Propagation Neural Network (BPNN). First, the theory...     

Effect of Sintering Temperature on Magnetic and Electrical Properties of GdBaCo<Subscript>2</Subscript><Emphasis Type="Italic">O</Emphasis><Subscript>5 + <Emphasis Type="Italic">δ</Emphasis></Subscript>

In this study, we report the results of an investigation into the sintering temperature dependence of magnetic and transport properties for GdBaCo₂ O _{5 + δ} synthesized through a sol-gel method. The lowering of sintering temperature leads to the increase of oxygen content and the reduction of grain size. The increase of oxygen content results in the enhancement of magnetic interactions and the weakening of Coulomb repulsion effect, while the reduction of grain size improves the magnetoresistance effect. Metal-insulator transition accompanied with spin-state transition is observed in all samples.     

Comparison of gas sensing properties based on hollow and porous α-Fe<Subscript>2</Subscript>O<Subscript>3</Subscript> nanotubes

Hollow and porous α-Fe₂O₃ nanotubes were successfully synthesized by single nozzle electrospinning method followed by annealing treatment. The crystal structures and morphologies of the as-prepared materials were characterized by X-ray diffraction and scanning electron microscopy, respectively. The as-prepared materials were applied to construct gas sensor devices which gas sensing properties were further investigated. The obtained results revealed that porous α-Fe₂O₃ nanotube gas sensors exhibit a markedly enhanced gas sensing performance compared with hollow α-Fe₂O₃ nanotube gas sensors, which was about three times higher to 100 ppm acetone at 240 °C. Interestingly, hollow and porous α-Fe₂O₃ nanotube gas sensors both showed fast response–recovery time and good selectivity, but the porous ones possessed the shorter recovery time. The improved properties could be attributed to the unique morphology of porous nanotubes. Thus, further improvement of performance in metal-oxide-semiconductors materials could be realized by preparation the unique porous structures of nanotubes. Moreover, it is expected that porous metal-oxide-semiconductors nanotubes could be further design as promising candidates for gas sensing materials.     

Optimization of silicon solar cell fabrication based on neural network and genetic programming modeling

This study describes techniques for the cascade modeling and the optimization that are required to conduct the simulator-based process optimization of solar cell fabrication. Two modeling approaches, neural networks and genetic programming, are employed to model the crucial relation for the consecutively connected two processes in solar cell fabrication. One model (Model 1) is used to map the five inputs (time, amount of nitrogen and DI water in surface texturing and temperature and time in emitter diffusion) to the two outputs (reflectance and sheet resistance) of the first process. The other model (Model 2) is used to connect the two inputs (reflectance and sheet resistance) to the one output (efficiency) of the second process. After modeling of the two processes, genetic algorithms and particle swarm optimization were applied to search for the optimal recipe. In the first optimization stage, we searched for the optimal reflectance and sheet resistance that can provide the best efficiency in the fabrication process. The optimized reflectance and sheet resistance found by the particle swarm optimization were better than those found by the genetic algorithm. In the second optimization stage, the five input parameters were searched by using the reflectance and sheet resistance values obtained in the first stage. The found five variables such as the texturing time, amount of nitrogen, DI water, diffusion time, and temperature are used as a recipe for the solar cell fabrication. The amount of nitrogen, DI water, and diffusion time in the optimized recipes showed considerable differences according to the modeling approaches. More importantly, repeated applications of particle swarm optimization yielded process conditions with smaller variations, implying greater consistency in recipe generation.     

Physiological and psychophysical responses in handling maximum acceptable weights under different footwear--floor friction conditions

A study on combined manual materials-handling tasks performed on floors under three friction levels was conducted. Eight male subjects participated in the study. The maximum acceptable weight of handling, including lifting, carrying for 3m, lowering, and walking 3m back at twice per minute was determined. The subject then performed the same tasks for 10 min. Heart rate, Vo2, energy efficiency, perceived sense of slip, and rating of perceived exertion for whole body strain were measured. The results showed that the effects of friction level on the maximum acceptable weights of handling, perceived sense of slip, Vo2, and energy efficiency were statistically significant (p相似文献   

WWW上路径模式发掘的研究

本文从互连网发展的趋势入手,对路径模式发掘进行了研究。先简要介绍数据库发掘的概况及网上数据发掘的特点,后结合关联法和组合概率法,并以算法和实例详细对之进行分析。     

纳米SiO2材料的应用

本文根据纳米的奇异特性,简要综述纳米ＳｉＯ２在各个领域中的应用。