An Example of a Supporting Combination by Using GA to Evolve More Advanced and Deeper CNN Architecture

It has become an annual tradition for Convolutional Neural Networks(CNNs)to continuously improve their performance in image classification and other applications.These advancements are often attributed to the adoption of more intricate network architectures,such as modules and skip connections,as well as the practice of stacking additional layers to create increasingly complex networks.However,the quest to identify the most optimizedmodel is a daunting task,given that stateof the artConvolutionalNeuralNetwork(CNN)models aremanually engineered.In this research paper,we leveraged a conventional Genetic Algorithm(GA)to craft optimized Convolutional Neural Network(CNN)architectures and pinpoint the ideal set of hyper parameters for image classification tasks using the MNIST dataset.Our experimentation with the MNIST dataset yielded remarkable results.Compared to earlier semi-automatic and automated approaches,our proposed GA demonstrated its efficiency by swiftly identifying the perfect CNN design,accomplishing this feat in just 6 GPU days while achieving an outstanding accuracy of 95.50%.

Severe accident risks from external events

This paper reviews the early development of design requirements for seismic events in USA early developing nuclear electric generating fleet. Notable safety studies,including WASH-1400,Sandia Siting Study and the NUREG1150 probabilistic risk study,are briefly reviewed in terms of their relevance to extreme accidents arising from seismic and other severe accident initiators. Specific characteristic about the nature of severe accidents in nuclear power plant (NPP) are reviewed along with present day state-of-art analysis methodologies (methods for estimation of leakages and consequences of releases (MELCOR) and MELCOR accident consequence code system (MACCS)) that are used to evaluate severe accidents and to optimize mitigative and protective actions against such accidents. It is the aim of this paper to make nuclear operating nations aware of the risks that accompany a much needed energy resource and to identify some of the tools,techniques and landmark safety studies that serve to make the technology safer and to maintain vigilance and adequate safety culture for the responsible management of this valuable but unforgiving technology.

Synthesis and structure of a praseodymium (Ⅲ) complex with carboxylate ligand：A thermal and spectroscopic study

One Pr（Ⅲ） lanthanide ion complex was initially synthesized and characterized by TGA-DSC in air atmosphere, as well as characterized by CHN elemental analysis, defining the stoichiometric ratio as Pr（DMBz）3. The gaseous products evolved during the thermal decomposition were also monitored in N2 atmosphere employing TGA/FT-IR system. A crystal structure is obtained by state-of-the-art powder X-rays diffraction methods measured in conventional laboratory equipment and refined by the Rietveld method, which defined it as a monoclinic system of the space group P21/C with a polymeric crystal structure, [Pr（DMBZ）3]n. FT-IR theoretical spectrum and time-dependent density functional theory（TD-DFT） were calculated from TGA-DSC and crystalline system data. The experimental and theoretical FT-IR spectra present a high correlation degree when the main stretching bands are compared, while the energy transfer（HOMO - LUMO） in their neighborhoods suggests the main contributions of the light-emitting states.