EXISTENCE OF SOLUTION AND APPROXIMATE CONTROLLABILITY OF A SECOND-ORDER NEUTRAL STOCHASTIC DIFFERENTIAL EQUATION WITH STATE DEPENDENT DELAY

This paper has two sections which deals with a second order stochastic neutral partial differential equation with state dependent delay. In the first section the existence and uniqueness of mild solution is obtained by use of measure of non-compactness. In the second section the conditions for approximate controllability are investigated for the distributed second order neutral stochastic differential system with respect to the approximate controllability of the corresponding linear system in a Hilbert space. Our method is an extension of co-author N. Sukavanam’s novel approach in [22]. Thereby, we remove the need to assume the invertibility of a controllability operator used by authors in [5], which fails to exist in infinite dimensional spaces if the associated semigroup is compact. Our approach also removes the need to check the invertibility of the controllability Gramian operator and associated limit condition used by the authors in [20], which are practically difficult to verify and apply. An example is provided to illustrate the presented theory.

Bayesian estimation for nonlinear stochastic hybrid systems with state dependent transitions

The Bayesian approach is considered as the most general formulation of the state estimation for dynamic systems. However, most of the existing Bayesian estimators of stochastic hybrid systems only focus on the Markov jump system, few liter- ature is related to the estimation problem of nonlinear stochastic hybrid systems with state dependent transitions. According to this problem, a new methodology which relaxes quite a restrictive as- sumption that the mode transition process must satisfy Markov properties is proposed. In this method, a general approach is presented to model the state dependent transitions, the state and output spaces are discreted into cell space which handles the nonlinearities and computationally intensive problem offline. Then maximum a posterior estimation is obtained by using the Bayesian theory. The efficacy of the estimator is illustrated by a simulated example .

Modified DS np Chart Using Generalized Multiple Dependent State Sampling under Time Truncated Life Test

This study presents the design of a modified attributed control chart based on a double sampling(DS)np chart applied in combination with generalized multiple dependent state(GMDS)sampling to monitor the mean life of the product based on the time truncated life test employing theWeibull distribution.The control chart developed supports the examination of the mean lifespan variation for a particular product in the process of manufacturing.Three control limit levels are used:the warning control limit,inner control limit,and outer control limit.Together,they enhance the capability for variation detection.A genetic algorithm can be used for optimization during the in-control process,whereby the optimal parameters can be established for the proposed control chart.The control chart performance is assessed using the average run length,while the influence of the model parameters upon the control chart solution is assessed via sensitivity analysis based on an orthogonal experimental design withmultiple linear regression.A comparative study was conducted based on the out-of-control average run length,in which the developed control chart offered greater sensitivity in the detection of process shifts while making use of smaller samples on average than is the case for existing control charts.Finally,to exhibit the utility of the developed control chart,this paper presents its application using simulated data with parameters drawn from the real set of data.

PERIODIC SOLUTIONS OF BAM NETWORKS WITH STATE DEPENDENT DELAYS

We use Krasnosel'skii's fixed point theorem to show that the following BAM networks with state dependent delays has a periodic solution.

A Novel Multiple Dependent State Sampling Plan Based on Time Truncated Life Tests Using Mean Lifetime

The design of a new adaptive version of the multiple dependent state(AMDS)sampling plan is presented based on the time truncated life test under the Weibull distribution.We achieved the proposed sampling plan by applying the concept of the double sampling plan and existing multiple dependent state sampling plans.A warning sign for acceptance number was proposed to increase the probability of current lot acceptance.The optimal plan parameters were determined simultaneously with nonlinear optimization problems under the producer’s risk and consumer’s risk.A simulation study was presented to support the proposed sampling plan.A comparison between the proposed and existing sampling plans,namely multiple dependent state(MDS)sampling plans and a modified multiple dependent state(MMDS)sampling plan,was considered under the average sampling number and operating characteristic curve values.In addition,the use of two real datasets demonstrated the practicality and usefulness of the proposed sampling plan.The results indicated that the proposed plan is more flexible and efficient in terms of the average sample number compared to the existing MDS and MMDS sampling plans.

Designing Adaptive Multiple Dependent State Sampling Plan for Accelerated Life Tests

A novel adaptive multiple dependent state sampling plan(AMDSSP)was designed to inspect products from a continuous manufacturing process under the accelerated life test(ALT)using both double sampling plan(DSP)and multiple dependent state sampling plan(MDSSP)concepts.Under accelerated conditions,the lifetime of a product follows the Weibull distribution with a known shape parameter,while the scale parameter can be determined using the acceleration factor(AF).The Arrhenius model is used to estimate AF when the damaging process is temperature-sensitive.An economic design of the proposed sampling plan was also considered for the ALT.A genetic algorithm with nonlinear optimization was used to estimate optimal plan parameters to minimize the average sample number(ASN)and total cost of inspection(TC)under both producer’s and consumer’s risks.Numerical results are presented to support the AMDSSP for the ALT,while performance comparisons between the AMDSSP,the MDSSP and a single sampling plan(SSP)for the ALT are discussed.Results indicated that the AMDSSP was more flexible and efficient for ASN and TC than the MDSSP and SSP plans under accelerated conditions.The AMDSSP also had a higher operating characteristic(OC)curve than both the existing sampling plans.Two real datasets of electronic devices for the ALT at high temperatures demonstrated the practicality and usefulness of the proposed sampling plan.

The Dependence of Chimera States on Initial Conditions

A chimera state consisting of both coherent and incoherent groups is a fascinating spatial pattern in non-locally coupled identical oscillators. It is thought that random initial conditions hardly evolve to chimera states. In this work, we study the dependence of chimera states on initial conditions. We show that random initial conditions may lead to chimera states and the chance of realizing chimera states becomes increasing when the model parameters axe moving away from the boundary of their stable regime.

Nonlinear observer-based optimal control of an active transfemoral prosthesis

This paper designs a joint controller/observer framework using a state dependent Riccati equation(SDRE)approach for an active transfemoral prosthesis system.An integral state control technique is utilized to design a tracking controller for a robot/prosthesis system.This framework promises a systematic flexible design using which multiple design specifications such as robustness,state estimation,and control optimality are achieved without the need for model linearization.Performance of the proposed approach is demonstrated through simulation studies,which show improvements versus a robust adaptive impedance controller and an extended Kalman filter-based state estimation method.Numerical results confirm the benefits of our method over the above-mentioned approaches with regard to control optimality and state estimation.

ANALYSIS AND COMPUTATIONAL ALGORITHM FOR QUEUES WITH STATE-DEPENDENT VACATIONS Ⅱ： M（n）/G/1/K

We study a single-server queueing system with state-dependent arrivals and general service distribution, or simply M（n）/G/1/K, where the server follows an N policy and takes multiple vacations when the system is empty. We provide a recursive algorithm using the supplementary variable technique to numerically compute the stationary queue length distribution of the system. The only input requirements are the Laplace-Stieltjes transforms of the service time distribution and the vacation time distribution, and the state-dependent arrival rate. The computational complexity of the algorithm is O（K^3）.

大连市领导干部科技素质的调查报告

With the method of questionary, the author has carried out careful investigation concerning the qualities of science and technology of Dalian municipal leading officials. It has basiclly reflected the degree of understanding and grasping of the policies and knowledge of science and technology by the leading officials in Dalian municipal organizations and cause units. Some of the questions have been proved by the experts which have rather strong effectiveness and comparably.

Unified description of different soils based on the superloading and subloading concepts

Geotechnical engineering often involves different types of geomaterials,such as sandy soil and clayey soil.Existing studies have confirmed that these soils have some common features,i.e.their mechanical behaviors depend not only on the inherent characteristics but also on their initial states.To describe the main mechanical behaviors of different soils within a simple and reasonable constitutive framework is of great significance for the numerical analysis on geotechnical engineering.This paper first introduces a model based on the concepts of superloading and subloading,which considers the“state dependence”(effects of overconsolidation and structure)of soil and only adds two material parameters compared with the Cam-Clay model.Secondly,conventional triaxial tests are systematically carried out on four types of soils(i.e.sand,silty clay,clay,and intermediate soil)with different initial void ratios,and the mechanical similarities and differences of these soils are discussed uniformly.After that,six material parameters of these soils are uniformly determined based on the concepts of superloading and subloading,and then used in constitutive calculations to verify the feasibility.The calculated results show a good agreement with test data,indicating that the model based on the concepts of superloading and subloading has great potential for describing the general mechanical behaviors of different soils within a unified framework.This work is expected to be applied to constitutive selection and parameter determination in the geotechnical numerical analysis of complex soil profiles.

Guided transmission of oxygen ions through Al_2O_3 nanocapillaries

The transmissions of oxygen ions through Al2O3 nanocapillaries each 50 nm in diameter and 10 μm in length at a series of different tilt angles are measured, where the ions with energies ranging from 10 to 60 keⅤ and charge states from 1 up to 6 are involved. The angular distribution and the transmission yields of transported ions are investigated. Our results indicate both the existence of a guiding effect when ions pass through the capillary and a significant dependence of the ion transmission on the energy and the charge state of the ions. The guiding effects are observed to be enhanced at lower projectile energies and higher charge states. Meanwhile, the results also exhibit that the transmission yields increase as the tilt angle decreases at a given energy and charge state.

Conceptual Modelling and Data Based Techniques to Understand Urban Water Use and Wastewater Production

A systems approach is used to describe the generation and variation of wastewater in an urban area. This is a multivariable system and its combined response at the outlet of this system, which is usually the entrance ofa wastewater treatment plant, depends on a number of environmental （precipitation and temperature） as well as social （size of the urban area, population changes, water consumption per capita） variables. There is a large number of available models and tools for describing the urban water system, however, the interactions between the individual components are rarely considered within the same modelling framework. In this paper a parsimonious methodology is proposed in order to understand and estimate the wastewater generation and its characteristics in an urban area using any information provided by the available data. The model incorporates both the flows of stormwater discharge and wastewater production that arrive to the wastewater treatment plant. A state dependent variable is introduced to simulate the consumptive uses in the urban area. Data availability and system＇s complexity affect the ability to achieve enhanced model performance, however, in the presented case study, preliminary results from the application of the presented model in the Greater Athens Area illustrate the potential of the conceptual modelling approach.

ASYMPTOTIC BEHAVIOR OF TIME-DEPENDENT SOLUTIONS TO SEMICONDUCTOR EQUATIONS

This paper considers the relationship between the time dependent solutions and the steady state solutions of semiconductor equations under the thermal equilibrium conditions. The asymptotic behavior of the time dependent solution is obtained.

Temperature dependence of circular DNA topological states and a solution to a single molecular experiment problem

Circular double stranded DNA has different topological states which are defined by their linking numbers. Equilibrium distribution of linking numbers can be obtained by closing

Accurate Determination for the Energy & Temperature Dependence of Electron Capture CrossSection of Si-SiO_2 Interface States Using a New Method

A new technique for accurate determination of the electron and hole capture cross-sections of interface states at the insulator-semiconductor interface has been developed through measuring the initial time variation in the carrier filling capacitance transient, and full consideration is given to the charge-potential feedback effect on carrier capture process. A simplified calculation of the effect is also given. The interface states have been investigated with this technique at the Si-SiO_2 interface in an n-type Si MOS diode. The results show that the electron capture cross-section strongly depends on both temperature and energy.

Model-based and Fuzzy Logic Approaches to Condition Monitoring of Operational Wind Turbines

It is common for wind turbines to be installed in remote locations on land or offshore, leading to difficulties in routine inspection and maintenance. Further, wind turbines in these locations are often subject to harsh operating conditions. These challenges mean there is a requirement for a high degree of maintenance. The data generated by monitoring systems can be used to obtain models of wind turbines operating under different conditions, and hence predict output signals based on known inputs. A model-based condition monitoring system can be implemented by comparing output data obtained from operational turbines with those predicted by the models, so as to detect changes that could be due to the presence of faults. This paper discusses several techniques for model-based condition monitoring systems: linear models, artificial neural networks, and state dependent parameter "pseudo" transfer functions.The models are identified using supervisory control and data acquisition(SCADA) data acquired from an operational wind firm. It is found that the multiple-input single-output state dependent parameter method outperforms both multivariate linear and artificial neural network-based approaches. Subsequently, state dependent parameter models are used to develop adaptive thresholds for critical output signals. In order to provide an early warning of a developing fault, it is necessary to interpret the amount by which the threshold is exceeded, together with the period of time over which this occurs. In this regard, a fuzzy logic-based inference system is proposed and demonstrated to be practically feasible.

Now decision theory

The spirit of now in nowcasting suggests expanding the current to include the near future.Decision theory is then developed by incorporating the consequences of actions into the present.With the future falling into the present discounting it is no longer permitted.Value functions are then observed to be determinate only up to scale and shift that are then locked down by fixing values arbitrarily in two selected states,much like declaring water to freeze and boil at zero and a hundred degrees celsius.The locked down value functions associated policy functions are seen to exist in decision contexts in where the only time is now.Examples are studied in univariate and multivariate dimensions for the decision state space and the dimension of shocks delivering state transitions.The policy functions are expanded from realisitic training sets to the full state space using Gaussian Process Regression.They are implemented on real data with reported performances.