On Enforcing Dyadic-type Homogeneous Binary Function Product Constraints in MatBase

Homogeneous binary function products are frequently encountered in the sub-universes modeled by databases,spanning from genealogical trees and sports to education and healthcare,etc.Their properties must be discovered and enforced by the software applications managing such data to guarantee plausibility.The(Elementary)Mathematical Data Model provides 17 types of dyadic-based homogeneous binary function product constraint categories.MatBase,an intelligent data and knowledge base management system prototype,allows database designers to simply declare them by only clicking corresponding checkboxes and automatically generates code for enforcing them.This paper describes the algorithms that MatBase uses for enforcing all 17 types of homogeneous binary function product constraint,which may also be employed by developers without access to MatBase.

RESEARCH ON THE CONSTRAINT MAPPING FROM FUNCTION TO ASSEMBLY

Assembly sketch is not only the visualization of abstract function, but alsothe template of detail design. Two kinds of information are needed to create assembly sketch:structure and assembly constraint. Most researches are aimed at bow to obtain Structures fromfunction, but the problem of how to obtain assembly constraint from function is ignored. Followingthe definition of assembly unit and the classification of function, a hierarchical mapping methodfrom function to assembly constraint is put forward, and the mapping method includes two steps. Thefirst step is the mapping from function to assembly semantics which is assembly expression andaccordant with engineer's design habit. The second one is the mapping from assembly semantics tobasic assembly constraints that are convenient for computer to handle. The mapping method is appliedto DDMS (design, drafting and management system) successfully.

Functionally Graded Cellular Structure Design Using the Subdomain Level Set Method with Local Volume Constraints

Functional graded cellular structure(FGCS)usually shows superiormechanical behaviorwith lowdensity and high stiffness.With the development of additivemanufacturing,functional graded cellular structure gains its popularity in industries.In this paper,a novel approach for designing functionally graded cellular structure is proposed based on a subdomain parameterized level set method(PLSM)under local volume constraints(LVC).In this method,a subdomain level set function is defined,parameterized and updated on each subdomain independently making the proposed approach much faster and more cost-effective.Additionally,the microstructures on arbitrary two adjacent subdomains can be connected perfectly without any additional constraint.Furthermore,the local volume constraint for each subdomain is applied by virtue of the augmented Lagrange multiplier method.Finally,several numerical examples are given to verify the correctness and effectiveness of the proposed approach in designing the functionally graded cellular structure.From the optimized results,it is also found that the number of local volume constraints has little influence on the convergence speed of the developed approach.

Rheological Behaviour for Polymer Melts and Concentrated SolutionsPart Ⅱ: Material Function with Nagai Chain Constraints and Determination of Their Parameters from Flow Curves

An integral constitutive equation and a set of material functions for describing the strain history of polymer melts were formulated in terms of the Cauchy-Green and Finger tensors. A simple memory function and the dependence of ηo and τt on M3.4 were derived from the theory of non-linear viscoelasticity with constraints of entanglements for polymer melts and substituted into the Oldroye-Walters-Fredickson constitutive equation. An integral constitutive equation for polymer melts was consequently obtained. Some material functions of the constitutive equation related to certain 'test flow' are examined as follows : (1) simple steady shear flow; (2) steady elongation flow; (3) small-amplitude oscillatory shear flow; (4) stress growth upon the inception of steady shear elongation flow; (5) stress relaxation (modulus and compllance). These theoretical relations for simple steady shear flow were compared with experimental data from our laboratory and references for various polymer melts and concentrated solutions. A good agreement between the theory and experiment was achieved.

Robust elastic impedance inversion using L1-norm misfit function and constraint regularization

The classical elastic impedance （EI） inversion method, however, is based on the L2-norm misfit function and considerably sensitive to outliers, assuming the noise of the seismic data to be the Guassian-distribution. So we have developed a more robust elastic impedance inversion based on the Ll-norm misfit function, and the noise is assumed to be non-Gaussian. Meanwhile, some regularization methods including the sparse constraint regularization and elastic impedance point constraint regularization are incorporated to improve the ill-posed characteristics of the seismic inversion problem. Firstly, we create the Ll-norm misfit objective function of pre-stack inversion problem based on the Bayesian scheme within the sparse constraint regularization and elastic impedance point constraint regularization. And then, we obtain more robust elastic impedances of different angles which are less sensitive to outliers in seismic data by using the IRLS strategy. Finally, we extract the P-wave and S-wave velocity and density by using the more stable parameter extraction method. Tests on synthetic data show that the P-wave and S-wave velocity and density parameters are still estimated reasonable with moderate noise. A test on the real data set shows that compared to the results of the classical elastic impedance inversion method, the estimated results using the proposed method can get better lateral continuity and more distinct show of the gas, verifying the feasibility and stability of the method.

Constraint-induced movement therapy promotes brain functional reorganization in stroke patients with hemiplegia

Stroke patients with hemiplegia exhibit flexor spasms in the upper limb and extensor spasms in the lower limb, and their movement patterns vary greatly. Constraint-induced movement therapy is an upper limb rehabilitation technique used in stroke patients with hemiplegia; however, studies of lower extremity rehabilitation are scarce. In this study, stroke patients with lower limb hemiplegia underwent conventional Bobath therapy for 4 weeks as baseline treatment, followed by constraint-induced movement therapy for an additional 4 weeks. The 10-m maximum walking speed and Berg balance scale scores significantly improved following treatment, and lower extremity motor function also improved. The results of functional MRI showed that constraint-induced movement therapy alleviates the reduction in cerebral functional activation in patients, which indicates activation of functional brain regions and a significant increase in cerebral blood perfusJon. These results demonstrate that constraint-induced movement therapy promotes brain functional reorganization in stroke patients with lower limb hemiplegia.

Taking into Account of Functional Constraints in Optimization of Modes of Power Systems by Genetic Algorithms

The development of the capabilities of computational tools has created up new possibilities for the effective use of a number of classical mathematical methods and algorithms for solving many important problems in the power engineering. In particular, a set of algorithms are developed to optimize the modes of electric power systems based on genetic algorithms. At the same time, the issues of taking into account functional constraints in solving such problems by genetic algorithms need to be improved. In accordance with it in this article the problems of taking into account of different constraints in optimization of modes of power systems using genetic algorithms are considered. The algorithm of optimization by genetic algorithm taking into account of functional constraints in forms of equality and inequality by penalty functions is proposed. The results of research of proposed algorithm’s efficiency in example of optimization of mode of power system with 8 buses, 4 thermal power plants and 3 transmission lines with controlled power flow are presented.

A Penalty Function Algorithm with Objective Parameters and Constraint Penalty Parameter for Multi-Objective Programming

In this paper, we present an algorithm to solve the inequality constrained multi-objective programming (MP) by using a penalty function with objective parameters and constraint penalty parameter. First, the penalty function with objective parameters and constraint penalty parameter for MP and the corresponding unconstraint penalty optimization problem (UPOP) is defined. Under some conditions, a Pareto efficient solution (or a weakly-efficient solution) to UPOP is proved to be a Pareto efficient solution (or a weakly-efficient solution) to MP. The penalty function is proved to be exact under a stable condition. Then, we design an algorithm to solve MP and prove its convergence. Finally, numerical examples show that the algorithm may help decision makers to find a satisfactory solution to MP.

Functional magnetic resonance imaging evaluation of brain function reorganization in cerebral stroke patients after constraint-induced movement therapy

In this study, stroke patients received constraint-induced movement therapy for 3 weeks. Before and after constraint-induced movement therapy, the flexibility of their upper limbs on the affected side was assessed using the Wolf motor function test, and daily use of their affected limbs was assessed using the movement activities log, and cerebral functional reorganization was assessed by functional magnetic resonance imaging. The Wolf motor function test score and the movement activities log quantity and quality scores were significantly increased, while action performance time in the Wolf motor function test was significantly decreased after constraint-induced movement therapy. By functional magnetic resonance imaging examination, only scattered activation points were visible on the affected side before therapy. In contrast, the volume of the activated area was increased after therapy. The activation volume in the sensorimotor area was significantly different before and after therapy, and the activation area increased and appeared adjusted. In addition to the activated area around the lesions being decreased, there were also some new activated areas, including the supplementary movement area, premotor area and the ipsilateral sensorimotor area. Our findings indicate that constraint-induced movement therapy significantly improves the movement ability and daily use of the affected upper limbs in stroke patients and promotes cerebral functional reorganization.

Elastoplastic response of functionally graded cemented carbides due to thermal loading

Finite dement formulations are used to simulate the evolution of the elastoplastic response of functionally graded cemented carbides （FGCC） due to thermal loading. The geometry of specimens is an axisymmetric solid cylinder with a two-dimensional gradient. The elastoplastic constitutive relationship is developed by constraint factors. Numerical results show that compressive stresses occur in the surface zone and tensile stresses in the cobalt rich zone when the temperature drops from the initial stress-free temperature of 800 to 0℃. The maximum value of the surface compressive stress is 254 MPa and the maximum value of the tensile stress is 252 MPa in the cobalt rich zones. When the cobalt concentration difference in the specimens is equal to or greater than 0.3, there is pronounced plastic flow in cobalt rich zone. When the temperature heats up from 0 to 800 ℃, the total plastic strain reaches 0.001 4. Plastic flow has a significant effect on the reduction of thermal stress concentration.

A New Evolutionary Algorithm for Function Optimization

A new algorithm based on genetic algorithm(GA) is developed for solving function optimization problems with inequality constraints. This algorithm has been used to a series of standard test problems and exhibited good performance. The computation results show that its generality, precision, robustness, simplicity and performance are all satisfactory.

Adaptive Control Based on Neural Networks for an Uncertain 2-DOF Helicopter System With Input Deadzone and Output Constraints

In this paper, a study of control for an uncertain2-degree of freedom(DOF) helicopter system is given. The2-DOF helicopter is subject to input deadzone and output constraints. In order to cope with system uncertainties and input deadzone, the neural network technique is introduced because of its capability in approximation. In order to update the weights of the neural network, an adaptive control method is utilized to improve the system adaptability. Furthermore, the integral barrier Lyapunov function(IBLF) is adopt in control design to guarantee the condition of output constraints and boundedness of the corresponding tracking errors. The Lyapunov direct method is applied in the control design to analyze system stability and convergence. Finally, numerical simulations are conducted to prove the feasibility and effectiveness of the proposed control based on the model of Quanser's 2-DOF helicopter.

THE TANGENT CONES ON CONSTRAINT QUALIFICATIONS IN OPTIMIZATION PROBLEMS

This article proposes a few tangent cones,which are relative to the constraint qualifications of optimization problems.With the upper and lower directional derivatives of an objective function,the characteristics of cones on the constraint qualifications are presented.The interrelations among the constraint qualifications,a few cones involved, and level sets of upper and lower directional derivatives are derived.

Regularized inversion for coseismic slip distribution with active constraint balancing

Estimating the spatial distribution of coseismic slip is an ill-posed inverse problem, and solutions may be extremely oscillatory due to measurement errors without any constraints on the coseismic slip distribution. In order to obtain stable solution for coseismic slip inversion, regularization method with smoothness-constrained was imposed. Trade-off parameter in regularized inversion, which balances the minimization of the data misfit and model roughness, should be a critical procedure to achieve both resolution and stability. Then, the active constraint balancing approach is adopted, in which the trade-off parameter is regarded as a spatial variable at each model parameter and automatically determined via the model resolution matrix and the spread function. Numerical experiments for a synthetical model indicate that regularized inversion using active constraint balancing approach can provides stable inversion results and have low sensitivity to the knowledge of the exact character of the Gaussian noise. Regularized inversion combined with active constraint balancing approach is conducted on the 2005 Nias earthquake. The released moment based on the estimated coseismic slip distribution is 9.91×1021 N·m, which is equivalent to a moment magnitude of 8.6 and almost identical to the value determined by USGS. The inversion results for synthetic coseismic uniform-slip model and the 2005 earthquake show that smoothness-constrained regularized inversion method combined with active constraint balancing approach is effective, and can be reasonable to reconstruct coseismic slip distribution on fault.

Anti-Disturbance Control for Tethered Aircraft System With Deferred Output Constraints

In this paper,we investigate the peaking issue of extended state observers and the anti-disturbance control problem of tethered aircraft systems subject to the unstable flight of the main aircraft,airflow disturbances and deferred output constraints.Independent of exact initial values,a modified extended state observer is constructed from a shifting function such that not only the peaking issue inherently in the observer is circumvented completely but also the accurate estimation of the lumped disturbance is guaranteed.Meanwhile,to deal with deferred output constraints,an improved output constrained controller is employed by integrating the shifting function into the barrier Lyapunov function.Then,by combining the modified observer and the improved controller,an anti-disturbance control scheme is presented,which ensures that the outputs with any bounded initial conditions satisfy the constraints after a pre-specified finite time,and the tethered aircraft tracks the desired trajectory accurately.Finally,both a theoretical proof and simulation results verify the effectiveness of the proposed control scheme.

Improved geologic surface approximation using a multiquadric method with additional constraints

Geologic surface approximation is profoundly affected by the presence, density and location of scattered geologic input data. Many studies have recognized the importance of utilizing varied sources of information when reconstructing a surface. This paper presents an improved geologic surface approximation method using a multiquadric function and borehole data. Additional information, i.e., inequality elevation and dip-strikes data extracted from outcrops or mining faces, is introduced in the form of physical constraints that control local changes in the estimated surface. Commonly accepted hypothesis states that geologic surfaces can be approximated to any desired degree of exactness by the summation of regular, mathematically defined, surfaces: in particular displaced quadric forms. The coefficients of the multiquadric functions are traditionally found by a least squares method. The addition of physical constraints in this work makes such an approach into a non-deterministic polynomial time problem. Hence we propose an objective function that represents the quality of the estimated surface and that includes the additional constraints by incorporation of a penalty function. Maximizing the smoothness of the estimated surface and its fitness to the additional constraints then allows the coefficients of the multiquadric function to be obtained by iterative methods. This method was implemented and demonstrated using data collected from the 81'st coal mining area of the Huaibei Coal Group.

Moult intensity constraints along the complete moult sequence of the House Sparrow(Passer domesticus)

Sequence and intensity are two essential components of bird moult.While the moult sequences of remex tracts are highly homogenous across passerines,other tracts apparently show a high variability.Moreover,order of moult activation among tracts are insufficiently known.Likewise,dynamics of moult intensity as moult progresses remains poorly known.Here,we provide detailed quantitative description of moult sequence and intensity in the House Sparrow(Passer domesticus).To understand their role,we tested two hypotheses on the:1) protection function of moult sequence,and 2) aerodynamic and physiological constraints on moult intensity.We scored percentage growth of 313 captured sparrows using the mass of the feathers of each tract(also length for remiges)to monitor moult intensity throughout the complete moult progress,which is defined as the fraction of new and growing feathers in a moulting bird relative to the total plumage.Moult sequence was highly variable both within wing coverts and among feather tracts,with moult sequence differing among all birds to some degree.We only found support for the protection function between greater coverts and both tertials and secondaries.Remex-moult intensity conformed to theoretical predictions,therefore lending support to the aerodynamic-constraint hypothesis.Furthermore,remex-moult speed plateaued during the central stages of moult progress.However,overall plumage-moult speed did not fit predictions of the physiological-constraint hypothesis,showing that the remex moult is only constrained by aerodynamics.Our results indicate that aerodynamic loss is not simply the inevitable effect of moult,but that moult is finely regulated to reduce aerodynamic loss.We propose that the moult of the House Sparrow is controlled through sequence and intensity adjustments in order to:1) avoid body and wing growth peaks;2) fulfil the protection function between some key feather tracts;3) reduce detrimental effects on flight ability;4) keep remex sequence fixed;and 5) relax remex replacement to last the whole moult duration.

Hybrid Predictive Control Based on High-Order Differential State Observers and Lyapunov Functions for Switched Nonlinear Systems

In this paper, a hybrid predictive controller is proposed for a class of uncertain switched nonlinear systems based on high-order differential state observers and Lyapunov functions. The main idea is to design an output feedback bounded controller and a predictive controller for each subsystem using high-order differential state observers and Lyapunov functions, to derive a suitable switched law to stabilize the closed-loop subsystem, and to provide an explicitly characterized set of initial conditions. For the whole switched system, based on the high-order differentiator, a suitable switched law is designed to ensure the whole closed-loop’s stability. The simulation results for a chemical process show the validity of the controller proposed in this paper.

An Improved Control Vector Iteration Approach for Nonlinear Dynamic Optimization. II. Problems with Path Constraints

This paper considers dealing with path constraints in the framework of the improved control vector iteration （CVI） approach. Two available ways for enforcing equality path constraints are presented, which can be directly incorporated into the improved CVI approach. Inequality path constraints are much more difficult to deal with, even for small scale problems, because the time intervals where the inequality path constraints are active are unknown in advance. To overcome the challenge, the ll penalty function and a novel smoothing technique are in-troduced, leading to a new effective approach. Moreover, on the basis of the relevant theorems, a numerical algo-rithm is proposed for nonlinear dynamic optimization problems with inequality path constraints. Results obtained from the classic batch reaCtor operation problem are in agreement with the literature reoorts, and the comoutational efficiency is also high.

The Optimal Conditions of the Linear Fractional Programming Problem with Constraint

In this article,the authors discuss the optimal conditions of the linear fractionalprogramming problem and prove that a locally optional solution is a globally optional solution and the locally optimal solution can be attained at a basic feasible solution withconstraint condition.