A neural network control system with parallel adaptive enhancementsapplicable to nonlinear servomechanisms

In this paper, we present a technique for using an additional parallel neural network to provide adaptive enhancements to a basic fixed neural network-based nonlinear control system. This proposed parallel adaptive neural network control system is applicable to nonlinear dynamical systems of the type commonly encountered in many practical position control servomechanisms. Properties of the controller are discussed, and it is shown that if Gaussian radial basis function networks are used for the additional parallel neural network, uniformly stable adaptation is assured and the approximation error converges to zero asymptotically. In the paper, the effectiveness of the proposed parallel adaptive neural network control system is demonstrated in real-time implementation experiments for position control in a servomechanism with asymmetrical loading and changes in the load     

Impact of nonuniform graded dopant profile in polysilicon gate on gate leakage current

In a MOSFET, a nonuniform, graded vertical dopant profile in the polysilicon gate causes a potential drop at the polysilicon/oxide interface. In this paper, the effect of this potential drop on the gate leakage current has been evaluated for the first time. The extent of variations of this affected gate leakage current with gate oxide thickness, gate length, and gate and drain bias conditions have been assessed with device simulation for an nMOS at 0.13 /spl mu/m low-voltage process. The results provide a guideline to the severity of this effect from the point of view of device and circuit operation and standby power consumption.     

A model for the seismic reliability assessment of electric power transmission systems

A comprehensive model to evaluate the seismic reliability of electric power transmission systems is presented. The model provides information on the probability of structural failure of critical equipment at the major substations, from which the corresponding probabilities of power disruption to a given service area are determined. With the proposed methodology earthquake ground motions are defined as stochastic processes, and seismic capacities of electrical equipment are determined on the basis of available test data and simple modeling, from which fragility functions of critical equipment and specific substations are developed. Probabilities of power disruption resulting from network disconnectivity and abnormal power flow are assessed through Monte Carlo simulation. As a case study, the proposed model is applied to the electric power network in San Francisco and vicinity under the 1989 Loma Prieta earthquake, and the probabilities of power interruption are contrasted with the actual power failures observed during that earthquake.     

复合功能陶瓷中的晶界渗流模型

在复合陶瓷材料中提出了晶界控制的渗液模，考虑晶界效应对渗流阀值的影响，采用ＭｏｎｔｅＣａｒｌｏ模拟，计算得到三维ＦＣＣ晶格点阵的渗流阀值约为４．５％。该结果与实验数据符合得很好。     

Railgun performance with a two-stage light-gas gun injector

Results obtained with the HELEOS (hypervelocity experimental launcher for equation of state) railgun, which uses a two-stage light-gas gun (2SLGG) as an injector, are presented. The high-velocity 2SLGG injector preaccelerates projectiles up to ~7 km/s. The high injection velocity reduces the exposure duration of the railgun barrel to the passing high temperature plasma armature, thereby reducing the ablation and subsequent armature growth. The 2SLGG also provides a column of cool, high-pressure hydrogen gas to insulate the rails behind the projectile, thereby eliminating restrike. A means to form an armature behind the injected projectile has been developed. In preliminary tests, the third-stage railgun has successfully increased the projectile velocity by 1.35 km/s. Extensive diagnostics have been used to determine the behavior of the armature and track the launcher's performance. Insome cases, velocity increases in the railgun section have been achieved, which are in close agreement with theoretical predictions, whereas in other experiments deviations from theoretical have been observed. The reasons for and implications of these results are addressed. Recent tests are reported     

Ultrahigh-performance planar β-Ga_2O_3 solar-blind Schottky photodiode detectors

The low dark current, high responsivity and high specific detectivity could be preferably achieved in detectors based on junctions, owing to the efficient constraint of carriers. Compared with the other junctions, planar Schottky junctions have simple structures and technological demands and are easy integrated. Herein, in this work, we prepared the β-Ga_2O_3 thin film by metalorganic chemical vapor deposition method to construct planar Ti/β-Ga_2O_3/Ni Schottky photodiode detectors with different onstate resistances. Fortunately, all the devices exhibit state-of-the-art performances, such as responsivity of 175–1372 A W~(-1),specific detectivity of 10~(14) Jones and external quantum efficiency of 85700%–671500%. In addition, the dependences of device performances on the on-state resistances indicate that the higher dark currents, photocurrents and photoresponsivities may well be obtained when on-state resistance is smaller, due to the less external power is used to overcome the impendence and condensance at the Ti/β-Ga_2O_3 and Ni/β-Ga_2O_3 interfaces, but contributing to higher electric current flow both in the dark and under illuminations.     

Catalase (CAT) Gene Family in Rapeseed (Brassica napus L.): Genome-Wide Analysis,Identification, and Expression Pattern in Response to Multiple Hormones and Abiotic Stress Conditions

Catalase (CAT) is an antioxidant enzyme expressed by the CAT gene family and exists in almost all aerobic organisms. Environmental stresses induce the generation of reactive oxygen species (ROS) that eventually hinder plant growth and development. The CAT enzyme translates the hydrogen peroxide (H₂O₂) to water (H₂O) and reduce the ROS levels to shelter the cells’ death. So far, the CAT gene family has not been reported in rapeseed (Brassica napus L.). Therefore, a genome-wide comprehensive analysis was conducted to classify the CAT genes in the rapeseed genome. The current study identified 14 BnCAT genes in the rapeseed genome. Based on phylogenetic and synteny analysis, the BnCATs belong to four groups (Groups I–IV). A gene structure and conserved motif analysis showed that Group I, Group II, and Group IV possess almost the same intron/exon pattern, and an equal number of motifs, while Group III contains diverse structures and contain 15 motifs. By analyzing the cis-elements in the promoters, we identified five hormone-correlated responsive elements and four stress-related responsive elements. Further, six putative bna-miRNAs were also identified, targeting three genes (BnCAT4, BnCAT6, and BnCAT8). Gene ontology (GO) enrichment analysis showed that the BnCAT genes were largely related to cellular organelles, ROS response, stimulus response, stress response, and antioxidant enzymes. Almost 10 BnCAT genes showed higher expression levels in different tissues, i.e., root, leaf, stem, and silique. The expression analysis showed that BnCAT1–BnCAT3 and BnCAT11–BnCAT13 were significantly upregulated by cold, salinity, abscisic acid (ABA), and gibberellic acid (GA) treatment, but not by drought and methyl jasmonate (MeJA). Notably, most of the genes were upregulated by waterlogging stress, except BnCAT6, BnCAT9, and BnCAT10. Our results opened new windows for future investigations and provided insights into the CAT family genes in rapeseed.     

Support vector regression methodology for prediction of input displacement of adaptive compliant robotic gripper

The prerequisite for new versatile grippers is the capability to locate and perceive protests in their surroundings. It is realized that automated controllers are profoundly nonlinear frameworks, and a faultless numerical model is hard to get, in this way making it troublesome to control utilizing tried and true procedure. Here, a design of an adaptive compliant gripper is presented. This design of the gripper has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize specific shapes of the grasping objects. Since the conventional control strategy is a very challenging task, soft computing based controllers are considered as potential candidates for such an application. In this study, the polynomial and radial basis function (RBF) are applied as the kernel function of Support Vector Regression (SVR) to estimate and predict optimal inputs displacement of the gripper according to experimental tests and shapes of grasping objects. Instead of minimizing the observed training error, SVR _poly and SVR _rbf attempt to minimize the generalization error bound so as to achieve generalized performance. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the SVR approach compared to other soft computing methodology.     

一种新的无双线性对的无证书安全签密方案

针对现有的无证书签密方案存在安全性不高、计算效率较低等诸多不足, 在Sharmila签密方案的基础上, 设计了一种新的无双线性对的无证书安全签密方案, 并在随机预言模型下证明了方案具有机密性和不可伪造性。同时, 该方案不需要双线性对和指数运算, 并且在确保安全性的前提下, 仅比现有的最高效签密方案多出两次点乘运算。