线型自由液面静电纺丝装置设计

针对目前静电装置产量低、纺丝不稳定的问题,为了实现纳米纤维大规模生产,设计了一种线型自由液面静电纺丝装置,并对其线型喷头进行静电场模拟。运用SolidWorks对自由液面静电纺丝装置进行了总体的设计,在此基础上,运用有限元分析软件COMSOL建立电纺装置模型,并进行了有限元仿真分析,结果表明,电极丝喷头的静电场分布均匀,高压电势分布面积较大,使成丝更为简单稳定。通过静电纺丝实验调整设备及纺丝工艺参数,扫描电子显微镜(SEM)观察结果表明线型自由液面静电纺丝装置能够实现生产纳米纤维,利用该装置成功制备了PVDF纳米纤维,直径可达150~250 nm。

Precise Calculation System of Total Mix Ration for Lactating Cow

[Objective] The paper was to precisely predict nutrient requirements and optimize ration formula, and explore the inherent feature of ration optimization of dairy cow. [Method] Based on cornell net carbohydrate and protein system （CNCPS） with integrating dynamic prediction models on main nutrient requirements of dairy cattle recommended by NRC （2001） and the CNCPS parameter database accumu- lated by Chinese feed database, the ration nutrient requirement dynamic calculation and total mixed ration （TMR） formula optimizing system for Holstein dairy cow was developed using FOXPRO database system and parametric linear programming algo- rithm. [Result] By optimizing a specific cow ration and analyzing its completed nutri- ents, the results showed that this system could entirely consider a lots of nutrient balances, such as concentrate fraction and forage fraction balance, rumen degrad- able protein and rumen undergradable protein balance, crude protein and lactation net energy balance, fibrous substances （ADF, NDF） and non-fiber carbohydrates （NFC） balance, calcium and phosphate balance, electrolytes balance and trace ele- ment balance etc., and could also calculate intestinal amino acid flow in terms of different models. [Conclusion] By using dynamic mathematical equations and comput- erized program, it can be realized for the ration formula design of lactating cow with all-round interoperable but mutual-constraining each other among ration nutrients.

Necessary and Sufficient Conditions in Smooth Programming with Generalized Convexity

Hanson and Mond have grven sets of necessary and sufficient conditions for optimality in constrained optimization by introducing classes of generalized functions, called type Ⅰ functions. Recently, Bector definded univex functions, a new class of functions that unifies several concepts of generalized convexity. In this paper, additional conditions are attached to the Kuhn Tucker conditions giving a set of conditions which are both necessary and sufficient for optimality in constrained optimization, under appropriate constraint qualifications.

A Solvable Model in Two—Dimensional Gravity Coupled to a Nonlinear Matter Field

The two-dimensional gravity model with a coupling constant and a vanishing cosmological constant coupled to a nonlinear matter field is investigated. We found that the classical equations of motion are exactly solvable and the static solutions of the induced metric and scalar curvature can be obtained analytically. These solutions may be used to describe the naked singularity at the origin.

Infeasibility Diagnosis on the Linear Programming Model of Production Planning in Refinery

In order to effectively diagnose the infeasible linear programming (LP) model of production planning in refinery, the article proposed three stages strategy based on constraints’ classification and infeasibility analysis. Generally, infeasibility sources involve structural inconsistencies and data errors, and the data errors are further classified intoⅠ, Ⅱ and Ⅲ. The three stages strategy are: (1) Check data when they are inputted to detect data error Ⅰ and repair them; (2) Inspect data whether they are accorded with material balance before solving the LP model to identify data error Ⅱ and repair them; (3) Find irreducible inconsistent system of infeasible LP model and give diagnosis information priority-ranked to recognize data error Ⅲ and structural inconsistencies. These stages could be automatically executed by computer, and the approach has been applied to diagnose the infeasible model well in our graphic I/O petro-chemical industry modeling system.

On-line Fault Diagnosis in Industrial Processes Using Variable Moving Window and Hidden Markov Model

An integrated framework is presented to represent and classify process data for on-line identifying abnormal operating conditions. It is based on pattern recognition principles and consists of a feature extraction step, by which wavelet transform and principal component analysis are used to capture the inherent characteristics from process measurements, followed by a similarity assessment step using hidden Markov model (HMM) for pattern comparison. In most previous cases, a fixed-length moving window was employed to track dynamic data, and often failed to capture enough information for each fault and sometimes even deteriorated the diagnostic performance. A variable moving window, the length of which is modified with time, is introduced in this paper and case studies on the Tennessee Eastman process illustrate the potential of the proposed method.

Relationship between coal size reduction and energy input in Hardgrove mill

Hardgrove grindability index （HGI） is an important indicator of coal grindability, and is one of the most important parameters to determine the capacity of coal pulverizer in power station. However, HGI is an empirical grindability index without linkages to any known physical parameters. To investigate the effect of energy input on the grinding in Hardgrove mill. a T20WN torque meter was installed on the shaft of a modified Hardgrove mill to record the torque driving the mill. Samples from four kinds of coals with HGI ranging from 36 to 72 were prepared according to the procedure of standard HGI test and ground in a modified Hardgrove mill at different revolutions. The relation of sample size reduction degree to specific comminution energy （Ecs） was studied with Shi-Kojovic model, The results show that Shi-Kojovic model predicted well the coal size reduction degree with Ecs in Hardgrove mill. The griadability index given by Shi-Kojovic model has a similar trend with HGI. The relation of sample size reduction degree to Ecs reveals that HGI has a non-linear relationship with effective specific energy in Hardgrove mill, which explains the non-linear relation of HG1 to industrial pulverizer capacity.

Characteristics of ventilation coefficient and its impact on urban air pollution

The temporal variation of ventilation coefficient was estimated and a simple model for the prediction of urban ventilation coefficient in Changsha was developed. Firstly, Pearson correlation analysis was used to investigate the relationship between meteorological parameters and mixing layer height during 2005-2009 in Changsha, China. Secondly, the multi-linear regression model between daytime and nighttime was adopted to predict the temporal ventilation coefficient. Thirdly, the validation of the model between the predicted and observed ventilation coefficient in 2010 was conducted. The results showed that ventilation coefficient significantly varied and remained high during daytime, while it stayed relatively constant and low during nighttime. In addition, the diurnal ventilation coefficient was distinctly negatively correlated with PM10 (particle with the diameter less than 10 μm) concentration in Changsha, China. The predicted ventilation coefficient agreed well with the observed values based on the multi-linear regression models during daytime and nighttime. The urban temporal ventilation coefficient could be accurately predicted by some simple meteorological parameters during daytime and nighttime. The ventilation coefficient played an important role in the PM10 concentration level.

QoS Provisioning Energy Saving Dynamic Access Policy for Overlay Cognitive Radio Networks with Hidden Markov Channels

Dynamic spectrum access policy is crucial in improving the performance of over- lay cognitive radio networks. Most of the previ- ous works on spectrum sensing and dynamic spe- ctrum access consider the sensing effective- ness and spectrum utilization as the design cri- teria, while ignoring the energy related issues and QoS constraints. In this article, we propose a QoS provisioning energy saving dynamic acc- ess policy using stochastic control theory con- sidering the time-varying characteristics of wir- eless channels because of fading and mobility. The proposed scheme determines the sensing action and selects the optimal spectrum using the corresponding power setting in each decis- ion epoch according to the channel state with the objective being to minimise both the flame error rate and energy consumption. We use the Hidden Markov Model （HMM） to model a wir- eless channel, since the channel state is not dir- ectly observable at the receiver, but is instead embedded in the received signal. The proced- ure of dynamic spectrum access is formulated as a Markov decision process which can be sol- ved using linear programming and the primal- dual index heuristic algorithm, and the obta- ined policy has an index-ability property that can be easily implemented in real systems. Sim- ulation results are presented to show the per- formance improvement caused by the propo- sed approach.

Improving Linear Type Traits to Improve Production Sustainability and Longevity in Purebred Sahiwal Cattle

In order to determine various traits which need to be improved for improving the productive life span and longevity, purebred Sahiwal cows available at bull mother experimental farm and cattle breeding farm located at Veterinary College, Durg, Chhattisgarh, India were used. For present investigation, 17 linear type traits were measured, scaled and scored as per the guidelines of International Committee for Animal Recording （2001）. The average score point （ASP） under 1-9 point scale score system along with respective observed group for different linear type traits were stature （6.88; taller）, chest width （5.30; intermediate）, body depth （4.11; intermediate）, rump angle （4.27; intermediate）, rump width （5.09; intermediate）, rear leg set-side view （4.55; intermediate）, rear leg set-rear view （5.95; intermediate）, foot angle （5.66; intermediate）, udder depth （5.71; intermediate）, rear udder height （4.90; intermediate）, udder balance （5.27; intermediate）, udder cleft （3.75; intermediate）, fore udder attachment （5.55; intermediate）, teat length （3.54; intermediate）, fore teat placement （5.33; intermediate）, rear teat placement （6.37; intermediate） and teat thickness （2.76; narrow）. For most of the traits, ASP which lies near midpoint （i.e. near five） is known to be ideal for dairy type cattle. Moreover, some traits also showed the presence of undesirable ASP. Hence, the traits such as body depth, rump angle, foot angle, udder depth, rear udder height, udder cleft, fore udder attachment, teat length, and teat thickness needs to be improved for improving the production sustainability and herd life of Sahiwal cattle. Thus, present investigation gives explicit clue to incorporate these conformation traits in selection program of this valuable germplasm commonly found in Southern part of Asia （India, Pakistan, Srilanka, etc.）.

An optimal filter based MPC for systems with arbitrary disturbances

In this study, a linear model predictive control(MPC) approach with optimal filters is proposed for handling unmeasured disturbances with arbitrary statistics. Two types of optimal filters are introduced into the framework of MPC to relax the assumption of integrated white noise model in existing approaches. The introduced filters are globally optimal for linear systems with unmeasured disturbances that have unknown statistics. This enables the proposed MPC to better handle disturbances without access to disturbance statistics. As a result, the effort required for disturbance modeling can be alleviated. The proposed MPC can achieve offset-free control in the presence of asymptotically constant unmeasured disturbances. Simulation results demonstrate that the proposed approach can provide an improved disturbance ?rejection performance over conventional approaches when applied to the control of systems with unmeasured disturbances that have arbitrary statistics.

The Saturation Model and Its Application on Partition Equilibria for Main Types of Heterogeneous Systems

Within the model, a definition of novel saturation and dilution degree is presented. A novel expression of equilibrium constant is derived by including interactions between components to reversible processes running between the components particles under a dynamic equilibrium. For partition equilibria, three types of basic processes are proposed and corresponding partition isotherms were derived. The isotherms are applied to the components partition between two phases for main heterogenous systems types. For construction and prediction ternary phase diagrams, a new method, the Component Binding by Saturation Model （CBSM） method, is proposed. Applying the partition isotherms derived, new extraction, evaporation and adsorption isotherms are expressed. Directly, or after an approximation, from the new adsorption isotherms, well-known adsorption isotherms are obtained.

Assessing seawater quality with a variable fuzzy recognition model

With the rapid development of the marine economy industry, human exploitation of marine resources is increasing, which is contributing to the growing trend of eutrophication and frequent occurrence of red tide. Accordingly, investigations of seawater quality have attracted a great deal of attention. This study was conducted to construct a seawater environmental quality assessment model based on the variable fuzzy recognition model. The uncertainty and ambiguity of the seawater quality assessment were then considered, combining the monitoring values of evaluation indicators with the standard values of seawater quality. Laizhou Bay was subsequently selected for a case study. In this study, the correct variable model for different parameters was obtained according to the linear and nonlinear features of evaluation objects. Application of the variable fuzzy recognition model for Laizhou Bay, water quality evaluation and comparison with performance obtained using other approaches revealed that the generated model is more reliable than traditional methods, can more reasonably determine the water quality of various samples, and is more suitable for evaluation of a multi-index, multi-level, nonlinear marine environment system; accordingly, the generated model will be an effective tool for seawater quality evaluation.

Generalized Nonlinear Irreducible Auto-Correlation and Its Applications in Nonlinear Prediction Models Identification

There is still an obstacle to prevent neural network from wider and more effective applications, i.e., the lack of effective theories of models identification. Based on information theory and its generalization, this paper introduces a universal method to achieve nonlinear models identification. Two key quantities, which are called nonlinear irreducible auto-correlation (NIAC) and generalized nonlinear irreducible auto-correlation (GNIAC), are defined and discussed. NIAC and GNIAC correspond with intrinstic irreducible auto-(dependency) (IAD) and generalized irreducible auto-(dependency) (GIAD) of time series respectively. By investigating the evolving trend of NIAC and GNIAC, the optimal auto-regressive order of nonlinear auto-regressive models could be determined naturally. Subsequently, an efficient algorithm computing NIAC and GNIAC is discussed. Experiments on simulating data sets and typical nonlinear prediction models indicate remarkable correlation between optimal auto-regressive order and the highest order that NIAC-GNIAC have a remarkable non-zero value, therefore demonstrate the validity of the proposal in this paper.

On the Regional Enlarged Observability for Linear Parabolic Systems

In this paper, we study the notion of the enlarged observability for distributed parabolic systems, where the aim is to reconstruct the initial state between two prescribed profiles P1 and P2 in an internal subregion c0 of the evolution domain f2. We give some definitions and properties of this concept, and then we solve the problem of the reconstruction of initial state using the Hilbert Uniqueness Method （HUM）. This leads to several interesting results which are performed through numerical example and simulations.

Non-Linear Dependence in Oil Price Behavior

In this paper, the authors analyze the adequacy of GARCH-type models to analyze oil price behavior by applying two types of non-parametric tests, the Hinich portmanteau test for non-linear dependence and a frequency-dominant test of time reversibility, the reverse test based on the bispectrum, to explore the high-order spectrum properties of the Mexican oil price series. The results suggest strong evidence of a non-linear structure and time irreversibility. Therefore, it does not comply with the i.i.d （independent and identically distributed） property. The non-linear dependence, however, is not consistent throughout the sample period, as indicated by a windowed test, suggesting episodic nonlinear dependence. The results imply that GARCH models cannot capture the series structure.

A self-organized locator obtaining method driven by local minima

The scalability of routing architectures for large networks is one of the biggest challenges that the Internet faces today.Greedy routing,in which each node is assigned a locator used as a distance metric,recently received increased attention from researchers and is considered as a potential solution for scalable routing.In this paper,LMD—a local minimum driven method is proposed to compute the topology-based locator.To eliminate the negative effect of the " quasi" greedy property—transfer routes longer than the shortest routes,a two-stage routing strategy is introduced,which combines the greedy routing with source routing.The greedy routing path discovered and compressed in the first stage is then used by the following source-routing stage.Through extensive evaluations,based on synthetic topologies as well as on a snapshot of the real Internet AS(autonomous system)topology,it is shown that LMD guarantees 100%delivery rate on large networks with low stretch.

Distributed multichannel medium access control protocol without common control channel for single-hop cognitive radio networks

A novel distributed cognitive radio multichannel medium access protocol without common control channel was proposed.The protocol divided a transmission interval into two parts for exchanging control information and data,respectively.In addition to evaluating system saturation throughput of the proposed protocol,a three-dimensional multi channel Markov chain model to describe the sate of the cognitive users (CUs) in dynamic spectrum access was presented.The proposed analysis was applied to the packet transmission schemes employed by the basic,RTS/CTS access mechanism adopted in the normal IEEE 802.11.Analyzing the advantage of the two methods,a hybrid access mechanism was proposed to improve the system throughput.The simulation results show that the experiment results are close to the value computed by the model (less than 5%),and the proposed protocol significantly improves the performance of the system throughput by borrowing the licensed spectrum.By analyzing the dependence of throughput on system parameters,hybrid mechanism dynamically selecting access mechanism can maintain high throughput.

Integral Operator Solving Process of the Boundary Value Problem of Abstract Kinetic Equation with the First Kind of Critical Parameter and Generalized Periodic Boundary Conditions

In this paper the concepts of the boundary value problem of abstract kinetic equation with the first kind of critical parameter γ 0 and generalized periodic boundary conditions are introduced in a Lebesgue space which consists of functions with vector valued in a general Banach space, and then describe the solution of these abstract boundary value problem by the abstract linear integral operator of Volterra type. We call this process the integral operator solving process.

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For a class of mixed initial-boundary value problem for general quasilinear hyperbolic systems, this paper establishes the local exact boundary controllability with boundary controls only acting on one end. As an application, the authors show the local exact boundary controllability for a kind of nonlinear vibrating string problem.