STA分析:认知多系统模型分析的新方法

认知研究领域(如记忆、学习)通常通过分离效应来验证或推定存在多个加工系统,但是这种仅仅通过分离效应直接推定存在多系统的方法存在不足.状态痕迹模型分析(STA)具有更大的适应范围.所谓STA模型分析是一个可以确定影响心理变量的数目,调节一个或多个自变量对两个或多个因变量影响的方法.文章从STA模型分析的分析过程、状态痕迹分析与一般线性模型方法之间的关系,以及STA方法的适应等方面加以阐述,以期更好地探讨认知加工过程.

新疆煤炭基地多系统耦合协调发展指标体系

作为全国第14个大型煤炭基地,新疆煤炭资源的开发、经济发展和生态环境的协调对新疆乃至全国具有重要的现实意义。论文在分析新疆煤炭生产基地发展现状的基础上,构建了新疆资源-经济-环境协调发展评价指标体系,运用多系统耦合协调模型,对新疆的经济发展、能源开发和生态环境的协调发展程度进行了测算、分析,并从优化经济系统、建立资源与生态补偿机制、建立煤炭工业的排污收费和交易系统的角度提出了新疆煤炭煤炭资源开发、经济社会、环境协调发展的建议措施。

从多系统年代学(Multi-System Geochronology)透视云开地块古生代—中生代的构造演化

云开地块位于华南板块南缘,经历了麻粒岩—高角闪岩相的高级变质作用,是华南地区为数不多的高级变质地体。研究表明,云开地块在古生代到中生代经历了复杂的构造演化过程,分别记录了早古生代末期、早中生代、晚中生代早期和晚中生代晚期的构造影响。这些构造事件在多系统年代学图上具有很好的表现,系统地揭示了云开地块的地质演化历史。

基于多系统DEA模型的大学产业合作系统R&D效率评价

大学产业合作是科技创新的重要推动力,将大学与产业在合作过程中的独立性和关联性考虑在内,建立了包含两个子系统的系统评价模型,并运用多系统DEA模型对30个省市的大学产业合作系统及两个子系统的R&D效率进行实证分析。研究发现,大学产业合作系统的R&D效率并非单纯受区域经济的影响,而与高校、企业双方在大学产业合作中的独立性、合作程度以及对大学产业合作的重视程度等密切相关。

Simulation of Restraint System Performance upon the Occupant's Response During Impact

Aim To study the influence of restraint system performance upon the occupant's response during impact, and provide a scientific base for occupant restraint system design. Methods \ In the light of basic theory of multibody system dynamics and impact dynamics on the basis of classical theory of impact, R W method is adopted to construct the vehicle occupant system model consisting of fourteen rigid bodies, thirty seven DOFs and slip joints for the simulation. A software named SVC3D(3 dimensional simulation of vehicle crash) is developed in the FORTRAN language. Results\ The results of simulation have a good coincidence with those of tests and the restraint system with low elongation webbing and equipped with pretensioner provides better restraint effect for the occupant. Conclusion\ The model of vehicle occupant multibody system and SVC3D are suitable for use. Occupant should be belted with low elongation webbing to a certain degree and occupant restraint system should be equipped with pretensioner.

A Study on the Multi-Compartment Linear Circulation Pharmacokinetic Model for the Targeting Drug Delivery System

By analyzing the observed phenomena and the data collected in the study, a multi-compartment linear circulation model for targeting drug delivery system was developed and the function formulas of the drug concentration-time in blood and target organ by computing were figured out. The drug concentration-time curve for target organ can be plotted with reference to the data of drug concentration in blood according to the model. The pharmacokinetic parameters of the drug in target organ could also be obtained. The practicability of the model was further checked by the curves of drug concentration-time in blood and target organ(liver) of liver-targeting nanoparticles in animal tests. Based on the liver drug concentration-time curves calculated by the function formula of the drug in target organ, the pharmacokinetic behavior of the drug in target organ(liver) was analyzed by statistical moment, and its pharmacokinetic parameters in liver were obtained. It is suggested that the (relative targeting index( can be used for quantitative evaluation of the targeting drug delivery systems.

HIERARCHIC GREY QUASI-PREFERRED ANALYSIS MODEL AND ITS APPLICATION

The grey quasi-preferred analysis (GQPA) is one of important methods for realizing system analysis to conquer the limitations of the existing GQPA model, without any considerations to the difference of the different behavioral factor′s importance. It could not be used to analyze the complex system with multi-hierarchy correlation factors, the weighted synthetic method for calculating abstract incidence degrees between the system beha-vioral characteristics and correlative factors in different hierarchies is given out,and the hierarchic grey quasi-preferred analysis (HGQPA) model is established. The effectiveness of the HGQPA model is tested by the scientific-technical system of Jiangsu Province. The depth and the range of the application of GQPA are developed, and the HGQPA model is regarded as a new approach to systemically analyze the complex systems with multi-hierarchy correlation factors.

An improved constrained model predictive control approach for Hammerstein-Wiener nonlinear systems

Many industry processes can be described as Hammerstein-Wiener nonlinear systems. In this work, an improved constrained model predictive control algorithm is presented for Hammerstein-Wiener systems. In the new approach, the maximum and minimum of partial derivative for input and output nonlinearities are solved in the neighbourhood of the equilibrium. And several parameter-dependent Lyapunov functions, each one corresponding to a different vertex of polytopic descriptions models, are introduced to analyze the stability of Hammerstein-Wiener systems, but only one Lyapunov function is utilized to analyze system stability like the traditional method. Consequently, the conservation of the traditional quadratic stability is removed, and the terminal regions are enlarged. Simulation and field trial results show that the proposed algorithm is valid. It has higher control precision and shorter blowing time than the traditional approach.

On Possible S-Wave Bound States for an N-↑N System Within a Constituent Quark Model

We try to apply a constituent quark model (a variety chiral constituent quark model) and the resonating group approach for the multi-quark problems to compute the effective potential between the NN- in S-wave (the quarks in the nucleons N and N-, and the two nucleons relatively as well, are in S wave) so as to see the possibility if there may be a tight bound state of six quarks as indicated by a strong enhancement at threshold of pp- in J/ψ and B decays. The effective potential which we obtain in terms of the model and approach shows if the experimental enhancement is really caused by a tight S-wave bound state of six quarks, then the quantum number of the bound state is very likely to be I = 1, JPC= 0-+.

A systematic strategy for multi-period heat exchanger network retrofit under multiple practical restrictions

A systematic strategy for retrofit of the multi-period heat exchanger network （HEN） on the basis of the multi- objective optimization is developed. In this three-stage procedure, a simplified multi-objective optimization model of the multi-period lIEN is first established and then solved to target the retrofit, aiming to minimizing the total annual cost and total annual CO2 emissions. The obtained Pareto front represents series of retrofit targets under different emission limitations, from which the most desirable one can be selected. The matching of the existing and the required heat exchangers is further implemented to finalize the retrofit, which will meet the practical retrofit requirements and matching restrictions. The application of the proposed procedure is illustrated through a case study of a HEN in a vacuum gas oil hydro-treating unit.

Consensus of Multi-Agent Systems with Prestissimo Scale-Free Networks

In this paper, the relations of the network topology and the moving consensus of multi-agent systems are studied. A consensus-prestissimo scale-free network model with the static preferential-consensus attachment is presented on the rewired link of the regular network. The effects of the static preferential-consensus BA network on the algebraic connectivity of the topology graph are compared with the regular network. The robustness gain to delay is analyzed for variable network topology with the same scale. The time to reach the consensus is studied for the dynamic network with and without communication delays. By applying the computer simulations, it is validated that the speed of the convergence of multi-agent systems can be greatly improved in the preferential-consensus BA network model with different configuration.

Multi-objective intelligent coordinating optimization blending system based on qualitative and quantitative synthetic model

A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0%, which effectively stabilizes the agglomerate compositions and the permeability.

Theoretical coupling longitudinal-transverse model and experimental verification of transverse vibration of rope for multi-rope friction hoisting system

Using the mass of time-varying length balance rope focused on the hoisting conveyance, the coupling longi- tudinal-transverse model of mine friction hoist was established by using of the Hamilton＇s principle. The modified Galerkin＇s method was used to discretize partial differential Eqs. The mine hoisting system was used to the example to analysis the relation between the load, velocity and transverse vibration of rope. The in situ tests were illustrated to evaluate the proposed mathematical model. The results showed that the modeling method can well represent the transverse vibration of rope.

NOVEL MULTIMEDIA TRAFFIC MODELING BASED CAC SCHEME FOR CDMA COMMUNICATION SYSTEMS

As the radio spectrum is a very scarce resource,the Call Admission Control (CAC) is one of the most important parts in radio resource management. The Code Division Multiple Access (CDMA) based next generation wireless communications systems will support the transmission of multimedia traffic,such as voice,video and data,thus the CAC,which can support the multimedia traffic and guarantee the Quality of Service (QoS) of different traffic,has gained broad attention. In this paper,a novel multimedia traffic modeling method and a corresponding dynamic QoS based CAC are proposed. The analysis and simulation results show that the proposed CAC scheme can guarantee the QoS to different traffic demand,and improve the system performance significantly.

The ‘Two oceans and one sea' extended range numerical prediction system with an ultra-high resolution atmosphere-ocean-land regional coupled model

The‘Two Oceans and One Sea’area(West Pacific,Indian Ocean,and South China Sea;15°S–60°N,39°–178°E)is a core strategic area for the‘21st Century Maritime Silk Road’project,as well as national defense.With the increasing demand for disaster prevention and mitigation,the importance of 10–30-day extended range prediction,between the conventional short-term(around seven days)and the climate scale(longer than one month),is apparent.However,marine extended range prediction is still a‘blank point’in China,making the early warning of marine disasters almost impossible.Here,the authors introduce a recently launched Chinese national project on a numerical forecasting system for extended range prediction in the‘Two Oceans and One Sea’area based on a regional ultra-high resolution multi-layer coupled model,including the scientific aims,technical scheme,innovation,and expected achievements.The completion of this prediction system is of considerable significance for the economic development and national security of China.

A two-step rectification algorithm for airborne linear images with POS data

Rectification for airborne linear images is an indispensable preprocessing step. This paper presents in detail a two-step rectification algorithm. The first step is to establish the model of direct georeference position using the data provided by the Po- sitioning and Orientation System (POS) and obtain the mathematical relationships between the image points and ground reference points. The second step is to apply polynomial distortion model and Bilinear Interpolation to get the final precise rectified images. In this step, a reference image is required and some ground control points (GCPs) are selected. Experiments showed that the final rectified images are satisfactory, and that our two-step rectification algorithm is very effective.

Evaluation and Performance of the APSIM Crop Growth Model for German Winter Wheat, Maize and Fieldpea Varieties in Monocropping and Intercropping Systems

Competition for solar radiation between plants grown in multi-species cropping systems can severely limit crop production of individual species within that system. There are various approaches for modeling light interception within mixed-cropping and row or strip intercropping systems. To extend the knowledge about model behavior and different model approaches under interspecific competition conditions, the Agricultural Production Systems Simulator （APSIM） was evaluated and calibrated for field experiments previously described and simulated by the Decision Support System for Agrotechnology Transfer （DSSAT）. Initially the APSIM plant model was successfully modified to simulate wheat, maize and fieldpea monocultures in the European agro-ecological zone. Once calibrated, the APSIM model was then used to simulate a strip relay intercropping maize/wheat and maize/fieldpea system. In DSSAT, a shading algorithm was introduced to modify the daily weather input in order to take competition for solar radiation into account. In contrast, APSIM simulates interspecific competition using a modified Beer＇s law for multi-component canopy conditions. After a re-evaluation of the model regarding a minimum change of crop coefficients and variables, APSIM was able to simulate dry matter and grain yield of German maize, wheat and fieldpea varieties adequately. However, APSIM is a point-based model, and many of the processes that influence strip cropping cannot be accommodated by adjusting Beer＇s Law alone. So far none of the tested frameworks successfully modeled strip or relay intercropping. The processes governing growth in the numerous and very diversifying intercropping systems are complex and at this point in time have not been captured in sufficient detail.

A hybrid discrete particle swarm optimization-genetic algorithm for multi-task scheduling problem in service oriented manufacturing systems

To cope with the task scheduling problem under multi-task and transportation consideration in large-scale service oriented manufacturing systems(SOMS), a service allocation optimization mathematical model was established, and then a hybrid discrete particle swarm optimization-genetic algorithm(HDPSOGA) was proposed. In SOMS, each resource involved in the whole life cycle of a product, whether it is provided by a piece of software or a hardware device, is encapsulated into a service. So, the transportation during production of a task should be taken into account because the hard-services selected are possibly provided by various providers in different areas. In the service allocation optimization mathematical model, multi-task and transportation were considered simultaneously. In the proposed HDPSOGA algorithm, integer coding method was applied to establish the mapping between the particle location matrix and the service allocation scheme. The position updating process was performed according to the cognition part, the social part, and the previous velocity and position while introducing the crossover and mutation idea of genetic algorithm to fit the discrete space. Finally, related simulation experiments were carried out to compare with other two previous algorithms. The results indicate the effectiveness and efficiency of the proposed hybrid algorithm.

Task Assignment for Forest Fire Suppression by Multiple UAVs

This paper presents a scenario of forest fire suppression using UAVs （Unmanned Aerial Vehicles） and addresses task assignment algorithm to coordinate UAVs. Forest fires are a major problem in many nations and fast extinguishing forest fires brings a lot of ecological advantages so proper use of firefighting resources is very critical. In this sense, multi UAVs forest fire suppression system can be effective way to prevent fire outbreaks. In multi agent system, an appropriate task assignment according to the SA （Situational Awareness） is the most essential to conduct mission. We should consider real time re-planning or re-scheduling of multi UAVs team because environmental situations such as wind are changeable and that changes affect the forest fire spreading. Furthermore, we have to think about convergence to a consistent SA because it may take too much time. CBBA （Consensus-Based Bundle Algorithm） is robust decentralized task assignment tool so it can be implemented in real time re-planning application. A simulation model which is the main topic in this paper shows that multi UAVs can be properly operated to suppress forest fires even if there are unpredictable random factors and partial disconnection. The simulation model includes concrete operating scenarios and recursive task re-assign algorithm until fires in the whole area are suppressed.

Performance Analysis for Multimedia Communication Systems with a Multilayer Queuing Network Model

Software performance evaluation in multimedia communication systems is typically formulated into a multi-layered client-server queuing network(MLCSQN) problem. However, the existing analytical methods to MLCSQN model cannot provide satisfactory solution in terms of accuracy, convergence and consideration of interlocking effects. To this end, this paper proposes a heuristic solving method for MLCSQN model to boost the performance prediction of distributed multimedia software systems. The core concept of this method is referred to as the basic model, which can be further decomposed into two sub-models: client sub-model and server sub-model. The client sub-model calculates think time for server sub-model, and the server sub-model calculates waiting time for client sub-model. Using a breadthfirst traversal from leaf nodes to the root node and vice versa, the basic model is then adapted to MLCSQN, with net sub-models iteratively resolved. Similarly, the interlocking problem is effectively addressed with the help of the basic model. This analytical solver enjoys advantages of fast convergence, independence on specific average value analysis(MVA) methods and eliminating interlocking effects.Numerical experimental results on accuracy and computation efficiency verify its superiority over anchors.