促进教育均衡 共享品质教育

杭州市通过"名校集团化"输出学校品牌、办学理念、管理方式、干部师资等方式,带动新办学校、相对薄弱学校、民办学校、农村学校共同发展,迅速提高了办学水平和教育质量,解决了教育均衡发展的问题,成为促进教育资源优质化、均衡化。

Kinematic Analysis of Elliptic-Gear & Eccentric Slider-Crank & Uniform-Pitch Screw Weft-Insertion Mechanism

In order to analyze the kinematic performances of elliptic-gear & eccentric slider-crank & uniform-pitch screw weft-insertion mechanism proposed by us,kinematic mathematic models of the mechanism were established,and an aided analytic software was compiled.Influences of some important parameters on the kinematic characteristics of the mechanism were analyzed.A group of preferable parameters were obtained according to the software and some requirements.Comparisons of kinematic performances were made between the proposed mechanism and the variable-pitch screw insertion mechanism of C401 rapier loom manufactured by Vamatex Corp in Italy.The results show that the proposed mechanism can meet the requirements of inserting wefts.

Iterative learning control of SOFC based on ARX identification model

This paper presents an application of iterative learning control (ILC) technique to the voltage control of solid oxide fuel cell (SOFC) stack. To meet the demands of the control system design, an autoregressive model with exogenous input (ARX) is established. Firstly, by regulating the variation of the hydrogen flow rate proportional to that of the current, the fuel utilization of the SOFC is kept within its admissible range. Then, based on the ARX model, three kinds of ILC controllers, i.e. P-, PI- and PD-type are designed to keep the voltage at a desired level. Simulation results demonstrate the potential of the ARX model applied to the control of the SOFC, and prove the excellence of the ILC controllers for the voltage control of the SOFC.

A BOOSTING APPROACH FOR INTRUSION DETECTION

Intrusion detection can be essentially regarded as a classification problem,namely,dis-tinguishing normal profiles from intrusive behaviors. This paper introduces boosting classification algorithm into the area of intrusion detection to learn attack signatures. Decision tree algorithm is used as simple base learner of boosting algorithm. Furthermore,this paper employs the Principle Com-ponent Analysis (PCA) approach,an effective data reduction approach,to extract the key attribute set from the original high-dimensional network traffic data. KDD CUP 99 data set is used in these ex-periments to demonstrate that boosting algorithm can greatly improve the classification accuracy of weak learners by combining a number of simple “weak learners”. In our experiments,the error rate of training phase of boosting algorithm is reduced from 30.2% to 8% after 10 iterations. Besides,this paper also compares boosting algorithm with Support Vector Machine (SVM) algorithm and shows that the classification accuracy of boosting algorithm is little better than SVM algorithm’s. However,the generalization ability of SVM algorithm is better than boosting algorithm.

Stability analysis via the concept of Lyapunov exponents―a case study

The dynamics characteristics of the robotic arm system are usually highly nonlinear and strongly coupling,which will make it difficult to analyze the stability by the methods of solving kinetic equations or constructing Lyapunov function,especially,these methods cannot calculate the quantitative relationship between mechanical structures or control input and dynamics parameters and stability.The theoretical analysis process from symbol dynamics modeling of the robotic arm system to the movement stability is studied by using the concept of Lyapunov exponents method. To verify the algorithm effectiveness,the inner relation between its joint input torque and stability or chaotic and stable motion of the 2-DOF robotic arm system is analyzed quantitatively. As compared with its counterpart of Lyapunov's direct method,the main advantage of the concept of Lyapunov exponents is that the methods for calculating the exponents are constructive to provide an effective analysis tool for analyzing robotic arm system movement stability of nonlinear systems.

Efficient Selection of Linearly Independent Atomic Features for Accurate Machine Learning Potentials

Machine learning potentials are promising in atomistic simulations due to their comparable accuracy to first-principles theory but much lower computational cost.However,the reliability,speed,and transferability of atomistic machine learning potentials depend strongly on the way atomic configurations are represented.A wise choice of descriptors used as input for the machine learning program is the key for a successful machine learning representation.Here we develop a simple and efficient strategy to automatically select an optimal set of linearly-independent atomic features out of a large pool of candidates,based on the correlations that are intrinsic to the training data.Through applications to the construction of embedded atom neural network potentials for several benchmark molecules with less redundant linearly-independent embedded density descriptors,we demonstrate the efficiency and accuracy of this new strategy.The proposed algorithm can greatly simplify the initial selection of atomic features and vastly improve the performance of the atomistic machine learning potentials.

Cutting-Edge Reproductive Medicine and Ethics in Japan

Although the Japan Society of Obstetrics and Gynecology （JSOG） endorses new-type PGD using CGH for only carriers of balanced chromosomal translocations, it is against the ethical guidelines of the JSOG to decide whether or not embryos should be implanted due to aneuploidy discovered as a result of new-type PGD. In the author＇s opinion, it should be at the discretion of the JSOG＇s own randomized controlled trials, which should involve multiple facilities, whether or not a scientific basis can be found for the value of the new-type PGD in cases of recurrent miscarriage, in cases of implantation failure, and in cases where the women are of advanced maternal age. Dr. Netsu＇s 36 cases of selective reduction may be against the Japanese Maternal Health Protection Law that prohibits abortion due to congenital disease, but with the backdrop that there are many abortions that are performed as a result of parental convenience in Japan, it is difficult to understand the difference between the over 300,000 abortions that are performed every year in Japan and Dr. Netsu＇s prescribed surgery which is designed to selectively reduce fetuses with congenital disease for the purpose of evading physical danger for women with multiple gestations.

Interactions between invasive plants and heavy metal stresses:a review

Global changes have altered the distribution pattern of the plant communities,including invasive species.Anthropogenic contamination may reduce native plant resistance to the invasive species.Thus,the focus of the current review is on the contaminant biogeochemical behavior among native plants,invasive species and the soil within the plant-soil ecosystem to improve our understanding of the interactions between invasive plants and environmental stressors.Our studies together with synthesis of the literature showed that(i)the impacts of invasive species on environmental stress were heterogeneous,(ii)the size of the impact was variable and(iii)the influence types were multidirectional even within the same impact type.However,invasive plants showed self-protective mechanisms when exposed to heavy metals(HMs)and provided either positive or negative influence on the bioavailability and toxicity of HMs.On the other hand,HMs may favor plant invasion due to the widespread higher tolerance of invasive plants to HMs together with the‘escape behavior’of native plants when exposed to toxic HM pollution.However,there has been no consensus on whether elemental compositions of invasive plants are different from the natives in the polluted regions.A quantitative research comparing plant,litter and soil contaminant contents between native plants and the invaders in a global context is an indispensable research focus in the future.