基于S[T]输出基和P/R输入基的混联立方机构

基于传统的串联机构单一运动副输出基灵活性和并联机构多运动副输出基稳定性的优点提出一种新型混联S[T]输出基,该输出基的球铰组成构件贯穿连接虎克铰后,仍以球铰组成构件作为输出构件,可以实现空间三维转动。通过在新型混联S[T]输出基两端增加由3个移动副P或/和转动副R的串联支链,并将机构布局在一空间立方体上,得到具有三维空间转动活动能力的3自由度机构构型27种,得到具有三维空间转动和一维空间移动活动能力的3种组合情形下的4自由度机构构型27种,得到具有三维空间转动和二维空间移动活动能力的3种组合情形的5自由度机构构型9种,得到具有三维空间转动和三维空间移动活动能力的6自由度机构构型1种,S[T]输出基和P/R输入基与立方体框架相结合,得到3,4,5少自由度空间混联立方机构构型63种,6自由度空间混联立方机构构型1种,所有64种机构构型的输入驱动数目均满足移动副数目少于或等于6,转动副数目少于或等于6,且任意一种构型中移动副和转动副的总数和为6。基于S[T]输出基和P/R输入基构建的空间混联立方机构进行混联机床的研究具有一定的理论意义与实用价值。

激光熔铸过程中涂层物料吸收系数及输入基材热量的研究

提出了用静态粉末床原理测量涂层表观吸收系数和输入基材热量的方法，并讨论了熔铸过程中粉末粒度、扫描速度及光束辐照状态等工艺参数对涂层表观吸收系数和输入基材热量的影响。实验结果表明，粉末粒度及光束辐照状态对涂层表观吸收系数和输入基材的热量有较大的影响。

一种共基差分低噪声放大器设计

在无线通信终端中,低噪声放大器是射频接收系统中的第一级有源电路,对系统性能有重要影响。在深入分析噪声的基础上,提出一种采用共基差分输入结构的低噪声放大器,电路包括可控增益放大器和增益控制电路。该结构的低噪声放大器的输出电压直接反映到自动增益控制电路的输入端,根据输出电压幅值的大小,自动增益控制电路的输出电压反馈到低噪声放大器的增益控制电路比较器的输入端,进而影响放大器的总体增益。基于JAZZ 0.35μmBICMOS工艺设计放大器电路结构,并对电路进行了仿真和分析,结果表明设计的放大器可以更加有效地抑制噪声,低噪声放大器能提供25 dB的增益,噪声系数小于1 dB,灵敏度达到2μV。

ALGORITHMS AND ARCHITECTURE IMPLEMENTATIONS OF MIMO OFDM BASEBAND RECEIVER BASED ON THE SIMD DSP CORE

This letter presents a programmable single-chip architecture for Multi-lnput and Multi-Output （M1MO） OFDM baseband receiver. The architecture comprises a Single Instruction Multiple Data （SIMD） DSP core and three coprocessors that are used for synchronization, FFT and channel decoder. In this MIMO OFDM system, the Zero Correlation Zone （ZCZ） code is used as the synchronization word preamble of packet in the physical layer in order to avoid the interference from other transmitting antennas. Furthermore, a simple channel estimation algorithm is proposed which is appropriate tbr the SIMD DSP computation.

High-Gain Approach Based Full-Order Observers for Linear Systems with Unknown Inputs

In this paper, a full-order observer which can be fully decoupled from the unknown inputs as the conventional full-order observer does is designed by using auxiliary outputs, but the requirement of the matching condition is removed. The procedure of calculating the parameter matrices of the full-order observer is also presented. Compared with the existing auxiliary outputs based sliding-mode observers, the designed observer has a simpler design procedure, which is systematic and does not involve solving linear matrix inequalities. The simulation results show that the proposed method is effective.

Multivariable Control Performance Assessment Based on Generalized Minimum Variance Benchmark

This paper is concerned with the control performance assessment based on the multivariable generalized minimum variance benchmark.An explicit expression for the feedback controller-invariant(the generalized minimum variance)term of the multivariable control system is obtained,which is used as a standard benchmark for the assessment of the control performance for multi input multi output(MIMO)process.The proposed approach is based on the multivariable minimum variance benchmark.In comparison with the minimum variance benchmark, the developed method is more reasonable and practical for the control performance assessment of multivariable systems.The approach is illustrated by a simulation example and an industrial application.

Practical Model of Sea Ice Thickness of Bohai Sea Based on MODIS Data

Sea ice thickness is one of the most important input parameters in the studies on sea ice disaster prevention and mitigation. It is also the most important content in remote sensing monitoring of sea ice. In this study, a practical model of sea ice thickness(PMSIT) was proposed based on the Moderate Resolution Imaging Spectroradiometer(MODIS) data. In the proposed model, the MODIS data of the first band were used to estimate sea ice thickness and the difference between the second-band reflectance and the fifth-band reflectance in the MODIS data was calculated to obtain the difference attenuation index(DAI) of each pixel. The obtained DAI was used to estimate the integrated attenuation coefficient of the first band of the MODIS at the pixel level. Then the model was used to estimate sea ice thickness in the Bohai Sea with the MODIS data and then validated with the actual sea ice survey data. The validation results showed that the proposed model and corresponding parameterization scheme could largely avoid the estimation error of sea ice thickness caused by the spatial and temporal heterogeneity of sea ice extinction and allowed the error of 18.7% compared with the measured sea ice thickness.

Amplitude phase control for electro-hydraulic servo system based on normalized least-mean-square adaptive filtering algorithm

The electro-hydraulic servo system was studied to cancel the amplitude attenuation and phase delay of its sinusoidal response,by developing a network using normalized least-mean-square (LMS) adaptive filtering algorithm.The command input was corrected by weights to generate the desired input for the algorithm,and the feedback was brought into the feedback correction,whose output was the weighted feedback.The weights of the normalized LMS adaptive filtering algorithm were updated on-line according to the estimation error between the desired input and the weighted feedback.Thus,the updated weights were copied to the input correction.The estimation error was forced to zero by the normalized LMS adaptive filtering algorithm such that the weighted feedback was equal to the desired input,making the feedback track the command.The above concept was used as a basis for the development of amplitude phase control.The method has good real-time performance without estimating the system model.The simulation and experiment results show that the proposed amplitude phase control can efficiently cancel the amplitude attenuation and phase delay with high precision.

Object and Its Worry about Existence

The presented work describes principles of functioning of the object as a philosophical category on the basis of principles discovered in different, concrete objects. At the beginning, a supposition is thus made that principles are common and describe the fundamental mode of the organization of matter. The regeneration of its elements is the basic goal of the control of an object. The control systems try to allow elements to optimize their state depending on circumstances and occasionally in advance. The input system is the first one from these systems. It controls the input of material for the regeneration and at the same time is the source of primary information concerning its state in the environment and its development in time. The system of the control of the distribution of the energy named TOT is another element of the control. The system named EM0 controls the process of the regeneration on the basis of information about the successfulness of elements involved into the regeneration. Finally, the system named EM 1 controls the dynamics of the boundary of the object on the basis of information describing the tension on this boundary. The second goal of the control of an object, besides the regeneration, is to optimize the existence of the object as whole. New global criteria arise and are used throughout the process of the control for this sake.

Use of Artificial Intelligence in the Issue of Protection against Negative Impact of Floods

The paper follows possible specification of a control algorithm of a WS （water management system） during floods using the procedures of AI （artificial intelligence）. The issue of minimizing negative impacts of floods represents influencing and controlling a dynamic process of the system where the main regulation elements are water reservoirs. Control of water outflow from reservoirs is implicitly based on the used model （titled BW） based on FR （fuzzy regulation）. Specification of a control algorithm means dealing with the issue of preparing a knowledge base for the process of tuning fuzzy regulators based on an I/O （input/output） matrix obtained by optimization of the target behaviour of WS. Partial results can be compared with the regulation outputs when specialized tuning was used for the fuzzy regulator of the control algorithm. Basic approaches follow from the narrow relation on BW model use to simulate floods, without any connection to real water management system. A generally introduced model allows description of an outflow dynamic system with stochastic inputs using submodels of robust regression in the outflow module. The submodels are constructed on data of historical FS （flood situations）.

A real-time data smoothness method based on xPC-Target

A method of real-time data smoothness which is applied in a hardware-in-the-loop （HIL） simulation platform for a plug-in hybrid electric vehicle synthetical power device is described. The input signal of the platform comes from a AC/DC switch power with output containing noises. A linear slide average arithmetic is applied to smooth the noises. To average a certain number input sample signals, this method can decrease the noises voltage level, which meet the requirement of the simulation platform. The efficiency and signal delay time are presented to describe the result of this method, and a statistical index is used to judge the arithmetic＇ s efficiency. The tests results show that the arithmetic fit the requirement of the HIL simulation platform.

Fast garment simulation with aid of hybrid bones

A data-driven method was proposed to realistically animate garments on human poses in reduced space. Firstly, a gradient based method was extended to generate motion sequences and garments were simulated on the sequences as our training data. Based on the examples, the proposed method can fast output realistic garments on new poses. Our framework can be mainly divided into offline phase and online phase. During the offline phase, based on linear blend skinning(LBS), rigid bones and flex bones were estimated for human bodies and garments, respectively. Then, rigid bone weight maps on garment vertices were learned from examples. In the online phase, new human poses were treated as input to estimate rigid bone transformations. Then, both rigid bones and flex bones were used to drive garments to fit the new poses. Finally, a novel formulation was also proposed to efficiently deal with garment-body penetration. Experiments manifest that our method is fast and accurate. The intersection artifacts are fast removed and final garment results are quite realistic.

Map-based control method for vehicle stability enhancement

This work proposes a map-based control method to improve a vehicle's lateral stability, and the performance of the proposed method is compared with that of the conventional model-referenced control method. Model-referenced control uses the sliding mode method to determine the compensated yaw moment; in contrast, the proposed map-based control uses the compensated yaw moment map acquired by vehicle stability analysis. The vehicle stability region is calculated by a topological method based on the trajectory reversal method. A 2-DOF vehicle model and Pacejka's tire model are used to evaluate the proposed map-based control method. The properties of model-referenced control and map-based control are compared under various road conditions and driving inputs. Model-referenced control uses a control input to satisfy the linear reference model, and it generates unnecessary tire lateral forces that may lead to worse performance than an uncontrolled vehicle with step steering input on a road with a low friction coefficient. However, map-based control determines a compensated yaw moment to maintain the vehicle within the stability region,so the typical responses of vehicle enable to converge rapidly. The simulation results with sine and step steering show that map-based control provides better the tracking responsibility and control performance than model-referenced control.

Bottleneck Prediction Method Based on Improved Adaptive Network-based Fuzzy Inference System (ANFIS) in Semiconductor Manufacturing System

Semiconductor manufacturing (SM) system is one of the most complicated hybrid processes involved continuously variable dynamical systems and discrete event dynamical systems. The optimization and scheduling of semiconductor fabrication has long been a hot research direction in automation. Bottleneck is the key factor to a SM system, which seriously influences the throughput rate, cycle time, time-delivery rate, etc. Efficient prediction for the bottleneck of a SM system provides the best support for the consequent scheduling. Because categorical data (product types, releasing strategies) and numerical data (work in process, processing time, utilization rate, buffer length, etc.) have significant effect on bottleneck, an improved adaptive network-based fuzzy inference system (ANFIS) was adopted in this study to predict bottleneck since conventional neural network-based methods accommodate only numerical inputs. In this improved ANFIS, the contribution of categorical inputs to firing strength is reflected through a transformation matrix. In order to tackle high-dimensional inputs, reduce the number of fuzzy rules and obtain high prediction accuracy, a fuzzy c-means method combining binary tree linear division method was applied to identify the initial structure of fuzzy inference system. According to the experimental results, the main-bottleneck and sub-bottleneck of SM system can be predicted accurately with the proposed method.

Research on Seismic Behavior of Sloping Field Building Structure

The paper set up 3D solid overall superstructure model of Foundation and Box foundation on Rock Slope Subgrade base using the ABAQUS, and the establish the infinite element boundary, superstructure displacement of Box foundation and foundation at Rock Slope Subgrade was studied by inputting different direction of earthquake response. The results show that, for the mountain frame structure, influence on the horizontal displacement of the vertical under the action of alone big earthquake, and vertical seismic action on horizontal displacement effect is smaller by mutual function of horizontal and vertical seismic, basically is same as response under the action of horizontal earthquake alone; for step shaped box foundation, the change trend of mutual function of horizontal and vertical earthquake was the complete opposite of the maximum story drift each layer under the one-way horizontal earthquake, which indicate the presence of vertical earthquake wave effect on the box foundation displacement cannot be ignored.

Euler-Lagrange Modeling and Passivity Based Control of Buck Converters with Input Filter

In this paper, buck converters with input filter are modeled using the Euler Lagrange formalism and then build a PBC （passivity based controller）. The model is validated, by comparing its response with those of two switched circuits： sylnmetric and asymmetric. In the former, both switches are realized by MOSFETS while in the second one of them is realized by a diode. It is then showed by simulation and, explained with energy-based arguments why the obtained model thoroughly represents only the symmetric circuit. The model is then used to build a passivity-based control law. As this control law assumes the stability of the zero dynamic, conditions under which this hypothesis is satisfied, are first given. It is shown by simulation with switched circuits the robustness of the proposed controller against load variations. Then, a prediction of the source variations is included in the controller in order to render it robust against source variations.

Peak identification for ChlP-seq data with no controls

Chromatin immtmoprecipitation followed by sequencing （ChlP-sec0 is increasingly being used for genome-wide profiling of transcriptional regulation, as this technique enables dissection of the gene regulatory networks. With input as control, a variety of statistical methods have been proposed for identifying the enriched regions in the genome, i.e., the transcriptional factor binding sites and chromatin modifications. However, when there are no controls, whether peak calling is still reliable awaits systematic evaluations. To address this question, we used a Bayesian framework approach to show the effectiveness of peak calling without controls （PCWC）. Using several different types of ChlP-seq data, we demonstrated the relatively high accuracy of PCWC with less than a 5% false discovery rate （FDR）. Compared with previously published methods, e.g., the model-based analysis of ChlP-seq （MACS）, PCWC is reliable with lower FDR. Furthermore, to interpret the biological significance of the called peaks, in combination with microarray gene expression data, gene ontology annotation and subsequent motif discovery, our results indicate PCWC possesses a high efficiency. Additionally, using in silico data, only a small number of peaks were identified, suggesting the significantly low FDR for PCWC.

A novel crosslinkable electron injection/transporting material for solution processed polymer light-emitting diodes

A novel crosslinkable water/alcohol soluble conjugated polymer PFN-C containing oxetane groups and aminoalkyl groups in the side chains has been developed and used as highly efficient electron injection and transporting material for polymer light-emitting diodes (PLEDs). The unique solubility in polar solvents and crosslinkable ability of PFN-C render it a good can- didate for solution processed multilayer PLEDs. It was found that PFN-C can greatly enhance the electron injection from high work-function metal cathode, due to its pendant amino groups. As a result, PLEDs with PFN-C/Al cathode exhibited compara- ble device performance to the devices with Ba/Al cathode. The resulting green light-emitting device showed promising perfor- mance with a maximum luminance efficiency of 13.53 cd A-1.

Going Behind the Scenes： The Input Hypothesis Revisited

Few studies have to date gone behind the scenes to unveil the hidden metaphor-metonymy structure underpinning the input hypothesis （ Krashen 1981 ） despite overt attention paid to it over the years. In an effort to use a fine-grained metaphor-analysis approach（ e. g. , Lakoffand Johnson 1980, 1999） to revisit the input hypothesis, this study looks into its thrust--the causal effect of comprehensible input upon comprehension--in the hope of charting out its hidden organization. By discovering a theme of CAUSATION pivoted on space-based metaphors and metonyrnies, the present study brings to relief two fallacies committed in the input hypothesis. First, the heavy dependence on the prototypicaUy physical-spatial hierarchy leads to a red-herring fallacy, whose inconsistency defies rather than supports its statement about comprehensible input as the overriding cause. Second, although there is no denying that comprehensible input is a significant source of language gains, to enthrone it as the sole causal variable to the exclusion of all the other important variables, especially the agency of the 1.2 learner who should have been positioned in the spotlight in the first place, is another fallacy of immense magnitude.

Complex duality quantum computers acting on pure and mixed states

The aim of this paper is to establish a mathematical fundamental of complex duality quantum computers(CDQCs) acting on vector-states(pure states) and operator-states(mixed states),respectively.A CDQC consists of a complex divider,a group of quantum gates represented by unitary operators,or quantum operations represented by completely positive and trace-preserving mappings,and a complex combiner.It is proved that the divider and the combiner of a CDQC are an isometry and a contraction,respectively.It is proved that the divider and the combiner of a CDQC acting on vector-states are dual,and in the finite dimensional case,it is proved that the divider and the combiner of a CDQC acting on operator-states(matrix-states) are also dual.Lastly,the loss of an input state passing through a CDQC is measured.