英语极性引导性附加问句型模规则、意义的研究

本文第一部分探讨了英语极性引导性附加问句型模特点和规则,具体分析了单一陈述句,复杂句包括主从复合句、关系分句、补语从句和并列句所构成的附加问句的语言特点和规则的归纳.第二部分讨论了由极性、语调、主句中的推测及发话者对期望的回答交互作用所产生的四种可能性.附加问句的研究对语言类型学和英语教学研究有实际的价值.

Soil Quality Assessment Using Weighted Fuzzy Association Rules

Fuzzy association rules (FARs) can be powerful in assessing regional soil quality, a critical step prior to land planning and utilization; however, traditional FARs mined from soil quality database, ignoring the importance variability of the rules, can be redundant and far from optimal. In this study, we developed a method applying different weights to traditional FARs to improve accuracy of soil quality assessment. After the FARs for soil quality assessment were mined, redundant rules were eliminated according to whether the rules were significant or not in reducing the complexity of the soil quality assessment models and in improving the comprehensibility of FARs. The global weights, each representing the importance of a FAR in soil quality assessment, were then introduced and refined using a gradient descent optimization method. This method was applied to the assessment of soil resources conditions in Guangdong Province, China. The new approach had an accuracy of 87%, when 15 rules were mined, as compared with 76% from the traditional approach. The accuracy increased to 96% when 32 rules were mined, in contrast to 88% from the traditional approach. These results demonstrated an improved comprehensibility of FARs and a high accuracy of the proposed method.

A Novel Deep Neural Network Compression Model for Airport Object Detection

A novel deep neural network compression model for airport object detection has been presented.This novel model aims at disadvantages of deep neural network,i.e.the complexity of the model and the great cost of calculation.According to the requirement of airport object detection,the model obtains temporal and spatial semantic rules from the uncompressed model.These spatial semantic rules are added to the model after parameter compression to assist the detection.The rules can improve the accuracy of the detection model in order to make up for the loss caused by parameter compression.The experiments show that the effect of the novel compression detection model is no worse than that of the uncompressed original model.Even some of the original model false detection can be eliminated through the prior knowledge.

Self-Organized Criticality Analysis of Earthquake Model Based on Heterogeneous Networks

The original Olami-Feder-Christensen （OFC） model, which displays a robust power-law behavior, is a quasistatic two-dimensional version of the Burridge-Knopoff spring-block model of earthquakes. In this paper, we introduce a modified OFC model based on heterogeneous network, improving the redistribution rule of the original model. It can be seen as a generalization of the originM OFC model We numerically investigate the influence of the parameters θandβ, which respectively control the intensity of the evolutive mechanism of the topological growth and the inner selection dynamics in our networks, and find that there are two distinct phases in the parameter space （θ,β）. Meanwhile, we study the influence of the control parameter a either. Increasing a, the earthquake behavior of the model transfers from local to global.

Active suspension control of a one-wheel car model using single input rule modules fuzzy reasoning and a disturbance observer

This paper presents the construction of an active suspension control of a one-wheel car model using fuzzy reasoning and a disturbance observer. The one-wheel car model to be treated here can be approximately described as a nonlinear two degrees of freedom system subject to excitation from a road profile. The active control is designed as the fuzzy control inferred by using single input rule modules fuzzy reasoning, and the active control force is released by actuating a pneumatic actuator. The excitation from the road profile is estimated by using a disturbance observer, and the estimate is denoted as one of the variables in the precondition part of the fuzzy control rules. A compensator is inserted to counter the performance degradation due to the delay of the pneumatic actuator. The experimental result indicates that the proposed active suspension system improves much the vibration suppression of the car model. Key words One-wheel car model - Active suspension system - Single input rule modules fuzzy reasoning - Pneumatic actuator - Disturbance observer Document code A CLC number TH16

Incremental learning of the triangular membership functions based on single-pass FCM and CHC genetic model

In order to improve the efficiency of learning the triangular membership functions( TMFs) for mining fuzzy association rule( FAR) in dynamic database,a single-pass fuzzy c means( SPFCM)algorithm is combined with the real-coded CHC genetic model to incrementally learn the TMFs. The cluster centers resulting from SPFCM are regarded as the midpoint of TMFs. The population of CHC is generated randomly according to the cluster center and constraint conditions among TMFs. Then a new population for incremental learning is composed of the excellent chromosomes stored in the first genetic process and the chromosomes generated based on the cluster center adjusted by SPFCM. The experiments on real datasets show that the number of generations converging to the solution of the proposed approach is less than that of the existing batch learning approach. The quality of TMFs generated by the approach is comparable to that of the batch learning approach. Compared with the existing incremental learning strategy,the proposed approach is superior in terms of the quality of TMFs and time cost.

QUANTITATIVE ANALYSIS AND FRACTAL MODELING ON THE MOSAIC STRUCTURE OF LANDSCAPE IN THE CENTRAL AREA OF SHANGHAI METROPOLIS

The mosaic structure of landscape of the central area of Shanghai Metropolis is studied by quantitative methods of landscape ecology based on Remote Sensing (RS) and Geographic Information System (GIS) in this paper. Firstly, landscapes are classified into eight categories: residential quarter, industrial quarter, road, other urban landscape, farmland, village and small town, on-building area, river and other water bodies (such as lake, etc.). Secondly, a GIS is designed and set up based on the remote sensing data and field investigation, and a digital map of landscape mosaic is made. Then the indexes of diversity, dominance, fragmentation and isolation, and fractal dimension of each type of landscape in different periods are calculated by using spatial analysis method of GIS. With reference to the calculated results, a series of relative issues are discussed.

Automated soil resources mapping based on decision tree and Bayesian predictive modeling

This article presents two approaches for automated building of knowledge bases of soil resources mapping. These methods used decision tree and Bayesian predictive modeling, respectively to generate knowledge from training data. With these methods, building a knowledge base for automated soil mapping is easier than using the conventional knowledge acquisition approach. The knowledge bases built by these two methods were used by the knowledge classifier for soil type classification of the Longyou area, Zhejiang Province, China using TM bi-temporal imageries and GIS data. To evaluate the performance of the resultant knowledge bases, the classification results were compared to existing soil map based on field survey. The accuracy assessment and analysis of the resultant soil maps suggested that the knowledge bases built by these two methods were of good quality for mapping distribution model of soil classes over the study area.

COMPLEXITY AND CHAOTIC DYNAMICS OF ROCK FAULTING

Fault is a complex dynamic system controlled by the coupling of rock texture, reaction, fluid flow,stress, and rock deformation mechanism. A coupled reaction-transport- mechanical dynamic model for fault system is established and described in this paper. An example is presented for the Shuikoushan deposit, Hunan. The results of dynamic simulation indicate that the evolution and magnitude of fracture permeability of different rocks are different, and that faulting can enhance the spatial heterogeneity of rock permeability and facilitate fluid flow and mineralization in local fault zone. The pressure for a fault usually shows a variation mode of aperiodic oscillation with time, which reflects the chaotic behavior of the evolution of a fault.

Universality Class in Abelian Sandpile Models with Stochastic Toppling Rules

We present a stochastic critical slope sandpile model, where the amount of grains that fall in an overturning event is stochastic variable. The model is local, conservative, and Abelian. We apply the moment analysis to evaluate critical exponents and finite size scaling method to consistently test the obtained results. Numerical results show that this model, Oslo model, and one-dimensional Abelian Manna model have the same critical behavior although the three models have different stochastic toppling rules, which provides evidences suggesting that Abelian sandpile models with different stochastic toppling rules are in the same universality class.

A Distributed Optimal Scheme Based on Local QoS for Web Service Composition

The goal of web service composition is to choose an optimal scheme according to Quantity of Service （QoS） which selects instances in a distributed network. The networks are clustered with some web services such as ontologies, algorithms and rule engines with similar function and interfaces. In this scheme, web services acted as candidate service construct a distributed model which can＇t obtain the global services＇ information. The model is utilized to choose instances according to local QoS information in the progress of service composition. Some QoS matrixes are used to record and compare the instance paths and then choose a better one. Simulation result has proven that our ~pproach has a tradeoff between efficiency and ~quality.

Muon g - 2 in the Littlest Higgs Model

In this paper the anomalous magnetic dipole moment ofmuon in the littlest Higgs （LH） model is studied at one-loop level. We discuss the dependence of the contributions on the global symmetry breaking scale f, mizing angles c` and , and the Higgs triplet vacuum expectation value v＇ in the electroweak precision data preferring ranges. We find that the LH model can give a relatively small, but non-negligible extra weak contribution to the muon anomalous magnetic moment and can reduce the deviation of △aμ from 2.6σ for the SM to 2.5σ for the LH model.

Effect of Ship Bow Overhang on Water Shipping for Ship Advancing in Regular Head Waves

This paper presents the results of an experimental investigation dealing with the effect of bow overhang extensions on the quantity of shipping water over the foredeck in case of ships advancing in regular head waves. To perform this investigation, a series of free-running tests was conducted in regular waves using an experimental model of a multipurpose cargo ship to quantify the amount of shipping water. The tests were performed on five bow overhang variants with several combinations of wavelength and ship speed conditions. It was observed that the quantity of shipping water was affected by some parameters such as wavelength, ship speed, and bow shape in terms of an overhang extension. The results show the significant influence of an overhang extension, which is associated with the bow flare shape, on the occurrence of water shipping. These results involve the combined incoming regular waves and model speed.

Energy Dissipation Within the Wave Run-Up at Stepped Revetments

To understand the processes and energy dissipation performance caused by turbulence during the wave run-up over a stepped revetment,hydraulic model tests with steady flow conditions are conducted and correlated with unsteady flow conditions of the wave run-up within a short time frame.Under irregular waves,the run-up reduction over a stepped revetment is dependent on the Iribarren number and decreases for decreasing Iribarren numbers.Velocity gradients are found to be similar in a steady and unsteady flow regime near the pseudo-bottom.

Application of Three-Dimensional Visual Simulation in Tidal Defense Engineering

Any tidal defense engineering involves the collection and analysis of massive information about engineering structures and their surrounding environment. Traditional method, which is carried out mainly by means of twodimensional drawings and textures, is not efficient and intuitive enough to analyze the whole project and reflect its spatial relationship. Three-dimensional visual simulation provides an advanced technical means of solving this problem. In this paper, triangular irregular network (TIN) model simplified by non-uniform rational B-splines (NURBS) technique was used to establish the digital terrain model (DTM) of a super large region. Simulation of dynamic water surface was realized by combining noise function with sine wave superposition method. Models of different objects were established with different modeling techniques according to their characteristics. Application of texture mapping technology remarkably improved the authenticity of the models. Taking the tidal defense engineering in the new coastal region of Tianjin as a case study, three-dimensional visual simulation and dynamic roaming of the study area were realized, providing visual analysis and visible demonstration method for the management and emergency decision-making associated with construction.

Scaling Behavior of an Aggregation-Migration Model

We study the kinetic behavior of a two-species aggregation-migration model in which an irreversible aggregation occurs between any two clusters of the same species and a reversible migration occurs simultaneously between two different species. For a simple model with constant aggregation rates and with the migration rates and , we find that the evolution behavior of the system depends crucially on the values of the indexes υ1 and υ2. The aggregate size distribution of either species obeys a conventional scaling law for most cases. Moreover, we also generalize the two-species system to the multi-species case and analyze its kinetic behavior under the symmetrical conditions.

Enhancing Domain Knowledge with Semantic Models of Web Documents

The paper considers the problem of semantic processing of web documents by designing an approach, which combines extracted semantic document model and domain- related knowledge base. The knowledge base is populated with learnt classification rules categorizing documents into topics. Classification provides for the reduction of the dimensio0ality of the document feature space. The semantic model of retrieved web documents is semantically labeled by querying domain ontology and processed with content-based classification method. The model obtained is mapped to the existing knowledge base by implementing inference algorithm. It enables models of the same semantic type to be recognized and integrated into the knowledge base. The approach provides for the domain knowledge integration and assists the extraction and modeling web documents semantics. Implementation results of the proposed approach are presented.

The organization of societal conflicts by pavement ants Tetramorium caespitum： an agent-based model of amine-mediated decision making

Ant colonies self-organize to solve complex problems despite the simplicity of an individual ant＇s brain. Pavement ant Tetramorium caespitum colonies must solve the problem of defending the ter- ritory that they patrol in search of energetically rich forage. When members of 2 colonies randomly interact at the territory boundary a decision to fight occurs when： 1） there is a mismatch in nest- mate recognition cues and 2） each ant has a recent history of high interaction rates with nestmate ants. Instead of fighting, some ants will decide to recruit more workers from the nest to the fighting location, and in this way a positive feedback mediates the development of colony wide wars. In ants, the monoamines serotonin （5-HT） and octopamine （OA） modulate many behaviors associated with colony organization and in particular behaviors associated with nestmate recognition and ag- gression. In this article, we develop and explore an agent-based model that conceptualizes how in- dividual changes in brain concentrations of 5-HT and OA, paired with a simple threshold-based de- cision rule, can lead to the development of colony wide warfare. Model simulations do lead to the development of warfare with 91% of ants fighting at the end of 1 h. When conducting a sensitivity analysis, we determined that uncertainty in monoamine concentration signal decay influences the behavior of the model more than uncertainty in the decision-making rule or density. We conclude that pavement ant behavior is consistent with the detection of interaction rate through a single timed interval rather than integration of multiple interactions.

Conflict detection and resolution for authorization policies in workflow systems

The specification of authorization policies in access control models proposed so far cannot satisfy the requirements in workflow management systems(WFMSs).Furthermore,existing approaches have not provided effective conflict detection and resolution methods to maintain the consistency of authorization polices in WFMSs.To address these concerns,we propose the definition of authorization policies in which context constraints are considered and the complicated requirements in WFMSs can be satisfied.Based on the definition,we put forward static and dynamic conflict detection methods for authorization policies.By defining two new concepts,the precedence establishment rule and the conflict resolution policy,we provide a flexible approach to resolving conflicts.

A 2.5D finite element approach for predicting ground vibrations generated by vertical track irregularities

Dynamic responses of track structure and wave propagation in nearby ground vibration become significant when train operates on high speeds. A train-track-ground dynamic interaction analysis model based on the 2.5D finite element method is developed for the prediction of ground vibrations due to vertical track irregularities. The one-quarter car mode,1 is used to represent the train as lumped masses connected by springs. The embankment and the underlying ground are modeled by the 2.5D finite element approach to improve the computation efficiency. The Fourier transform is applied in the direction of train＇s movement to express the wave motion with a wave-number. The one-quarter car model is coupled into the global stiffness matrix describing the track-ground dynamic system with the displacement compatibility condition at the wheel-rail interface, including the irregularities on the track surface. Dynamic responses of the track and ground due to train＇s moving loads are obtained in the wave-number domain by solving the governing equation, using a conventional finite element procedure. The amplitude and wavelength are identified as two major parameters describing track irregularities. The irregularity amplitude has a direct impact on the vertical response for low-speed trains, both for short wavelength and long wavelength irregularities. Track irregularity with shorter wavelength can generate stronger track vibration both for low-speed and high-speed cases. For low-speed case, vibrations induced by track irregularities dominate far field responses. For high-speed case, the wavelength of track irregularities has very little effect on ground vibration at distances far from track center, and train＇s wheel axle weights becomes dominant.