Forms and functions of inorganic carbon in the Jiaozhou Bay sediments

Inorganic carbon forms and their influencing factors, mutual transformation and contribution to carbon cycling in the Jiaozhou Bay sediments were discussed. The results show that inorganic carbon in sediments could be divided into five forms: NaCl form, NH3 center dot H2O form, NaOH form, NH2OH center dot HCl form and HCl form. Thereinto, NH2OH center dot HCl form and HCl form account for more than 70% of total inorganic carbon. There was close relationship among every form of inorganic carbon and their correlativity was clearly different with different sedimentary environment except the similar strong positive correlation among NH2OH center dot HCl form, HCl form and total inorganic carbon in all regions of the Jiaozhou Bay. All forms of inorganic carbon were influenced by organic carbon, pH, Eh, Es, nitrogen and phosphorus in sediments, but their influence had different characteristics in different regions. Every farm of inorganic carbon transformed into each other continuously during early diagenesis of sediments and the common phenomenon was that NaCl form, NH3 center dot H2O form, NaOH form and NH2OH center dot HCl form might transform into steady HCl form. NaCl form, NH3 center dot H2O form, NaOH form and NH2OH center dot HCl form could participate in carbon recycle and they are potential carbon source; HCl form may be buried for a long time in sediments, and it may be one of the final resting places of atmospheric CO2. Inorganic carbon which entered into sediments was about 4.98 x 10(10) g in the Jiaozhou Bay every year, in which about 1.47x10(10) g of inorganic carbon might be buried for a long time and about 3.51. x 10(10) g of inorganic carbon might return into seawater and take part in carbon recycling.

基于神经网络的水泥生料配料多目标优化设计方法

为了降低生料成分的不确定性给水泥生料质量控制系统带来的影响,提出了率值补偿的控制策略.分别为三率值创建目标函数,并利用状态空间搜索策略解决多目标优化问题.针对初始样本空间不能覆盖所有样本的问题,提出了基于神经网络的估算模型,对初始样本空间进行拓扑.通过估价函数对状态空间中的状态量进行评价,得到最优的率值状态量;根据率值对原料配比进行调整,最后使率值偏差得到补偿,同时使给配比造成的波动最小.工业实验结果表明,生料的质量合格率由原来的30%提高到50%,该系统能有效地对配料过程进行优化控制.证明了基于神经网络的状态空间搜索策略为水泥生料配料多目标寻优问题提供了一种可行的方法。

Robust Learning Control for Manipulators with Uncertainty Disturbances Based on Internal Model

In this paper, a disturbance controller is designed for making robotic system behave as a decoupled linear system according to the concept of internal model. Based on the linear system, the paper presents an iterative learning control algorithm to robotic manipulators. A sufficient condition for convergence is provided. The selection of parameter values of the algorithm is simple and easy to meet the convergence condition. The simulation results demonstrate the effectiveness of the algorithm..

运动距离效应的认知编码机制

Among the cognitive studies of action, an important behavioral method is used to observe Reaction Time (RT) and Movement Time (MT) as the functions of motor parameters. RT is measured from the beginning of target presentation to the initiation of a movement, which is regarded as the programming of the ongoing movement. MT is measured from the initiation to the end of the movement, which is regarded as the execution of the movement. However, the relationship between RT and motor parameters remains uncertain till now. Under the uncertainty many related issues cannot be settled for long period, especially the issues as whether the amplitude effect appears during RT, or what should the amplitude effect be during RT. The present study aimed to find out the amplitude effect and the related cognitive process under different experimental conditions. First, we discussed the potential composition of RT and suggested that RT that normally measured in previous experiments might not reflect motor programming very well. Then we designed a series experiments to observe the relationship between RT and motor programming by using different Index of Difficulty (ID), different instructions in which speed and accuracy were emphasized respectively, different vision condition during movement execution and Go/NoGo paradigm. Meanwhile, we compared the amplitude effect under the respective RT to make the specific conclusion about the amplitude effect, and the relationship between RT and MT as well. The main findings are showed as following. 1) Because of the existing of “preview”, “visual feedback control” and “speed-accuracy tradeoff”, RT reflects motor programming differently under different experimental conditions. 2) Under different experimental conditions, the amplitude effect on RT varies. RT could be too short to exhibit the amplitude effect. Or the amplitude effect could be that more RT is needed for shorter movement when RT is prolonged. Or the amplitude effect could be that more RT is needed for longer movement when RT is further prolonged. 3) Under the present experimental conditions, the amplitude effect on MT showed consistently that longer movement needs longer MT. 4) Under the present experimental conditions, the relationship between RT and MT is a kind of compensation. The present study has important theoretic significance. The cognitive process of action is an important part of human cognitive behavior. The related studies could be very helpful for human people to know about themselves and the relation between themselves and the surroundings as well. Keywords motor programming; amplitude effect; Reaction Time (RT); Movement Time (MT)

Feature Matching for Object Localization in the Presence of Uncertainty

We consider the problem of matching model and sensory data features in the presence of geometric uncertainty, for the purpose of object localization and identification. The problem is to construct sets of model feature and sensory data feature pairs that are geometrically consistent given that there is uncertainty in the geometry of the sensory data features. If there is no geometric uncertainty, polynomial-time algorithms are possible for feature matching, yet these approaches can fail when there is uncertainty in the geometry of data features. Existing matching and recognition techniques which account for the geometric uncertainty in features either cannot guarantee finding a correct solution, or can construct geometrically consistent sets of feature pairs yet have worst case exponential complexity in terms of the number of features. The major new contribution of this work is to demonstrate a polynomial-time algorithm for constructing sets of geometrically consistent feature pairs given uncertainty in the geometry of the data features. We show that under a certain model of geometric uncertainty the feature matching problem in the presence of uncertainty is of polynomial complexity. This has important theoretical implications by demonstrating an upper bound on the complexity of the matching problem, an by offering insight into the nature of the matching problem itself. These insights prove useful in the solution to the matching problem in higher dimensional cases as well, such as matching three-dimensional models to either two or three-dimensional sensory data. The approach is based on an analysis of the space of feasible transformation parameters. This paper outlines the mathematical basis for the method, and describes the implementation of an algorithm for the procedure. Experiments demonstrating the method are reported.

Algebraic Functions For Recognition

In the general case, a trilinear relationship between three perspective views is shown to exist. The trilinearity result is shown to be of much practical use in visual recognition by alignment --- yielding a direct method that cuts through the computations of camera transformation, scene structure and epipolar geometry. The proof of the central result may be of further interest as it demonstrates certain regularities across homographies of the plane and introduces new view invariants. Experiments on simulated and real image data were conducted, including a comparative analysis with epipolar intersection and the linear combination methods, with results indicating a greater degree of robustness in practice and a higher level of performance in re-projection tasks.

On the Relationship Between Generalization Error, Hypothesis Complexity, and Sample Complexity for Radial Basis Functions

In this paper, we bound the generalization error of a class of Radial Basis Function networks, for certain well defined function learning tasks, in terms of the number of parameters and number of examples. We show that the total generalization error is partly due to the insufficient representational capacity of the network (because of its finite size) and partly due to insufficient information about the target function (because of finite number of samples). We make several observations about generalization error which are valid irrespective of the approximation scheme. Our result also sheds light on ways to choose an appropriate network architecture for a particular problem.

Residual Vibration Reduction in Computer Controlled Machines

Control of machines that exhibit flexibility becomes important when designers attempt to push the state of the art with faster, lighter machines. Three steps are necessary for the control of a flexible planet. First, a good model of the plant must exist. Second, a good controller must be designed. Third, inputs to the controller must be constructed using knowledge of the system dynamic response. There is a great deal of literature pertaining to modeling and control but little dealing with the shaping of system inputs. Chapter 2 examines two input shaping techniques based on frequency domain analysis. The first involves the use of the first deriviate of a gaussian exponential as a driving function template. The second, acasual filtering, involves removal of energy from the driving functions at the resonant frequencies of the system. Chapter 3 presents a linear programming technique for generating vibration-reducing driving functions for systems. Chapter 4 extends the results of the previous chapter by developing a direct solution to the new class of driving functions. A detailed analysis of the new technique is presented from five different perspectives and several extensions are presented. Chapter 5 verifies the theories of the previous two chapters with hardware experiments. Because the new technique resembles common signal filtering, chapter 6 compares the new approach to eleven standard filters. The new technique will be shown to result in less residual vibrations, have better robustness to system parameter uncertainty, and require less computation than other currently used shaping techniques.

Error Detection and Recovery for Robot Motion Planning with Uncertainty

Robots must plan and execute tasks in the presence of uncertainty. Uncertainty arises from sensing errors, control errors, and uncertainty in the geometry of the environment. The last, which is called model error, has received little previous attention. We present a framework for computing motion strategies that are guaranteed to succeed in the presence of all three kinds of uncertainty. The motion strategies comprise sensor-based gross motions, compliant motions, and simple pushing motions.

On Motion Planning with Uncertainty

Robots must successfully plan and execute tasks in the presence of uncertainty. Uncertainty arises from errors in modeling, sensing, and control. Planning in the presence of uncertainty constitutes one facet of the general motion planning problem in robotics. This problem is concerned with the automatic synthesis of motion strategies from high level task specification and geometric models of environments. In order to develop successful motion strategies, it is necessary to understand the effect of uncertainty on the geometry of object interactions. Object interactions, both static and dynamic, may be represented in geometrical terms. This thesis investigates geometrical tools for modeling and overcoming uncertainty. The thesis describes an algorithm for computing backprojections o desired task configurations. Task goals and motion states are specified in terms of a moving object's configuration space. Backprojections specify regions in configuration space from which particular motions are guaranteed to accomplish a desired task. The backprojection algorithm considers surfaces in configuration space that facilitate sliding towards the goal, while avoiding surfaces on which motions may prematurely halt. In executing a motion for a backprojection region, a plan executor must be able to recognize that a desired task has been accomplished. Since sensors are subject to uncertainty, recognition of task success is not always possible. The thesis considers the structure of backprojection regions and of task goals that ensures goal recognizability. The thesis also develops a representation of friction in configuration space, in terms of a friction cone analogous to the real space friction cone. The friction cone provides the backprojection algorithm with a geometrical tool for determining points at which motions may halt.

Determination of heat capacities and thermodynamic properties of 2-(chloromethylthio)benzothiazole by an adiabatic calorimeter

The molar heat capacities of 2-(chloromethylthio)benzothiazole (molecular formula C8H6ClNS2, CA registry no. 28908-00-1) were measured with an adiabatic calorimeter in the temperature range between (80 and 350) K. The construction and procedures of the calorimeter were described in detail. The performance of the calorimetric apparatus was evaluated by heat capacity measurements on alpha-Al2O3. The deviation of experiment heat capacities from the corresponding smoothed values lies within 0.3%, whereas the uncertainty is within +/-0.5%, compared with that of the recommended reference data over the whole experimental temperature range. A fusion transition was found from the C-p-T curve of 2-(chloromethylthio)benzothiazole. The melting temperature and the molar enthalpy and entropy of fusion of the compound were determined to be T-m = (315.11 +/- 0.04) K, Delta(fus)H(m) = (17.02 +/- 0.03) kJ(.)mol(-1), and Delta(fus)S(m) = (54.04 +/- 0.05) J(.)mol(-1.)K(-1), respectively. The thermodynamic functions (H-T - H-298.15) and (S-T - S-298.15) were also derived from the heat capacity data. The molar fraction purity of the 2-(chloromethylthio)benzothiazole sample used in the present calorimetric study was determined to be 99.21 by fraction melting.

Modelling uncertainty in agricultural image analysis

C.M. Onyango, J.A. Marchant and R. Zwiggelaar, 'Modelling uncertainty in agricultural image analysis', Computers and Electronics in Agriculture 17 (3), 295-305 (1997)

Boundary triplets and M-functions for non-selfadjoint operators, with applications to elliptic PDEs and block operator matrices

B.M. Brown, M. Marletta, S. Naboko, I. Wood: Boundary triplets and M-functions for non-selfadjoint operators, with applications to elliptic PDEs and block operator matrices, J. London Math. Soc., June 2008; 77: 700-718. The full text of this article will be made available in this repository in June 2009 Sponsorship: EPSRC,INTAS

Characteristic Functions for Ergodic Tuples

Gohm, Rolf; Dey, S., 'Characteristic function for ergodic tuples', Integral Equations and Operator Theory 58(1) pp.43-63 RAE2008

Hybrid simulation of ion cyclotron resonance in the solar wind: evolution of velocity distribution functions

Li, Xing; Habbal, S.R., (2005) 'Hybrid simulation of ion cyclotron resonance in the solar wind: evolution of velocity distribution functions', Journal of Geophysical Research 110(A10) pp.A10109 RAE2008