摘要：In the article titled“In-Depth Computational Analysis of Natural and artificial Carbon Fixation Pathways”[1],there were errors in Figures 7–*** the label of Figure 9,it reads:“Glyceraldehyde-3-phosphate was chosen as a product for the pathways,”but this is corrected to“Pyruvate was chosen as a product and formate as a substrate for the pathways.”In the lower panels of Figures 7,8,and 10,the labels“MOG/rCCC”and“CETCH cycle”in the figure key should be ***,in these figures,the panel indicators(a)and(b)were missing.

摘要：有机-无机杂化钙钛矿具有优异的光电性能,如大的光吸收系数、高载流子迁移率等,是理想的光电器件用光吸收材料.然而,杂化钙钛矿薄膜光电器件的性能受多方面因素的影响,例如致密程度、晶界等,同时其内部光激发电子-空穴对的复合也会降低器件的光电流和光响应度.本文以化学气相沉积法生长的高质量石墨烯薄膜为模板,通过两步化学气相沉积制备了甲胺铅碘/石墨烯异质结,并以此制备了柔性光探测器.首先,在生长体系中引入碘化铅,在石墨烯表面外延生长得到高质量的碘化铅;之后,引入甲基碘化铵,得到了具有大晶粒尺寸、致密的甲胺铅碘薄膜.进一步,以此复合薄膜为光吸收层,制备了柔性光探测器,其光响应度达到107 A/W.石墨烯的存在会抑制其中电子-空穴对的复合,从而提高器件的光电流.最后,在人类视觉系统的启发下,设计了柔性光电探测器阵列(24×24)图像传感器;其中,复合薄膜充当了视网膜中的视锥细胞.此图像传感器具有形状识别和颜色辨别的能力,在人造视网膜、生物医学成像、遥感和光通信高性能光电器件的构建方面具有应用潜力.

摘要：Every society has an outlook on the future-postindustrialization,postinternet,and now *** as artists and curators vcurators venture into topics scuh as robotics,artificial intelligence,and otlier technologies shaping our Zeitgeist,the Inside-Out Museum's recent exhibition.

摘要：The paper presents the Quasi Newton model of artificial Neural Network for design of circular microstrip antenna (MSA). In this model, a closed form expression is used for accurate determination of the resonant frequency of circular microstrip patch antenna. The calculated resonant frequency results are in good agreement with the experimental results reported elsewhere. The results show better agreement with the trained and tested data of ANN models. The results are verified by the experimental results to produce accurate ANN models. This presents ANN model practically as an alternative method to the detailed electromagnetic design of circular microstrip antenna.

摘要：In this paper, a design optimization for the reinforced concrete plane frame structure has been done in order to minimize the cost of the concrete and steel for beams and columns by adopting the artificial Neural Network (ANN) computational model trough the NeuroShell-2 software program. The design procedure conforms to the ACI-318-08 Code. The variables used for design optimization are the width, depth and the area of reinforced steel, including longitudinal reinforcement and shear reinforcement. A three-bay two-story RC frame is modeled with selecting different span length and different load cases. Acceptable design results are obtained from more than 50 examples which are subjected to all the constraints of the ACI Code, using different cross-section sizes and these results are used to train the NeuroShell-2 program. The results obtained demonstrate the efficiency of the ANN procedure for the multi story RC frame design.

摘要：Assessment is an important part of learning process. It can be defined as the process of gathering information for the purpose of making judgments about a current state of affairs presumably for the purpose of enhancing future outcomes [1]. It determines whether or not the goals of education are being met. Typically, most assessment tools give a numerical score as the result of the assessment. This may not be enough to improve the student’s progress. In this paper we defined main problems in current assessment tools and proposed a new assessment model that uses notions in knowledge space theory to overcome the shortage of the current assessment models. The experiment result showed that this new prototype made the assessment process easier and more effective. However, assessment affects decisions about grades, instructional needs and curriculum. This is an important phase of the learning process being showed in this paper in knowledge states framework. Future research will focus on making the tool behave intelligently to improve students’ learning momentum.

摘要：Brain-like computer research and development have been growing rapidly in recent years. It is necessary to design large scale dynamical neural networks (more than 106 neurons) to simulate complex process of our brain. But such kind of task is not easy to achieve only based on the analysis of partial differential equations, especially for those complex neural models, e.g. Rose-Hindmarsh (RH) model. So in this paper, we develop a novel approach by combining fuzzy logical designing with Proximal Support Vector Machine Classifiers (PSVM) learning in the designing of large scale neural networks. Particularly, our approach can effectively simplify the designing process, which is crucial for both cognition science and neural science. At last, we conduct our approach on an artificial neural system with more than 108 neurons for haze-free task, and the experimental results show that texture features extracted by fuzzy logic can effectively increase the texture information entropy and improve the effect of haze-removing in some degree.

摘要：This paper presents a comprehensive review of various traditional systems of crude oil distillation column design, modeling, simulation, optimization and control methods. artificial neural network (ANN), fuzzy logic (FL) and genetic algorithm (GA) framework were chosen as the best methodologies for design, optimization and control of crude oil distillation column. It was discovered that many past researchers used rigorous simulations which led to convergence problems that were time consuming. The use of dynamic mathematical models was also challenging as these models were also time dependent. The proposed methodologies use back-propagation algorithm to replace the convergence problem using error minimal method.

摘要：This paper, two artificial Neural Network (ANN) models using radial basis function (RBF) nets are developed for the design of Aperture Coupled Microstrip Antennas (ACMSA) for different number of design parameters. The effect of increasing the number of design parameters on the ANN model is also discussed in this work. The performances of the models when compared are found that on decreasing the number of design parameters, accuracy of the model is in-creased. The results given by the prepared models are comparable with the results of the IE3D software. So, these models are accurate enough to measure the design parameters of ACMSAs. Thus the neural network approach elimi-nates the long time consuming process of finding various designing parameters using costly software packages.

摘要：本文从仿生学的观点，学习生物体的原理，研究微型机器人的机构和控制问题，是开发微型机电系统的一个关键技术。介绍了生物体运动的基本特征，并从学习生物体运动的设计原理出发，对一种具有与人体肌肉类似特性的空气压人工筋进行了实验研究，表明它有可能成为一种新颖的柔性进机器人的驱动器，在医疗及微小空间作业的特种机器人中获得应用。