我国男子百米跑一级运动员体能结构特征的研究

百米跑运动属于典型的体能类速度性竞技项目。以 90年代以来我国男子百米跑一级运动员 19人为研究对象 ,采用文献资料法、问卷调查法、专家访谈法、测试法与数理统计法等研究方法 ,运用分层逐步回归分析筛选出了有效反映我国男子百米跑一级运动员体能水平的 10项指标。对百米跑运动员体能各指标与百米跑成绩间的关系进行了灰色关联分析 。

Modified multiple-component scattering power decomposition for PolSAR data based on eigenspace of coherency matrix

A modified multiple-component scattering power decomposition for analyzing polarimetric synthetic aperture radar(PolSAR)data is proposed.The modified decomposition involves two distinct steps.Firstly,ei⁃genvectors of the coherency matrix are used to modify the scattering models.Secondly,the entropy and anisotro⁃py of targets are used to improve the volume scattering power.With the guarantee of high double-bounce scatter⁃ing power in the urban areas,the proposed algorithm effectively improves the volume scattering power of vegeta⁃tion areas.The efficacy of the modified multiple-component scattering power decomposition is validated using ac⁃tual AIRSAR PolSAR data.The scattering power obtained through decomposing the original coherency matrix and the coherency matrix after orientation angle compensation is compared with three algorithms.Results from the experiment demonstrate that the proposed decomposition yields more effective scattering power for different PolSAR data sets.

Leaf Area Calculation Model of E.urophylla and E.grandis×E.urophylla

[Objective] The aim was to build an optimal leaf area measurement model of E. urophylla and E. grandis×E.urophylla. [Method] The correlation between leaf area and leaf＇s eigenvalue of E. urophylla and E. grandis×E.urophylla were studied. [Result] There was certain difference in leaf characteristics values between the 2 species. The leaf areas of E. urophylla and E. grandis×E.urophylla both had significant correlation with leaf length,leaf width,leaf perimeter,leaf length × leaf width,the ratio of leaf length to leaf width,shape factor,etc.,so the factors could be constructed into a regression model with leaf area. Among them,the best 2 models for leaf area calculation which were built by leaf length × leaf width of E. urophylla and E. grandis×E.urophylla both had relatively high accuracy and practical applications. [Conclusion] The research provides a simple and effective leaf area measurement method for studies on the 2 tree species.

The analysis of frequency-dependent characteristics for fluid detection: a physical model experiment

According to the Chapman multi-scale rock physical model, the seismic response characteristics vary for different fluid-saturated reservoirs. For class I AVO reservoirs and gas-saturation, the seismic response is a high-frequency bright spot as the amplitude energy shifts. However, it is a low-frequency shadow for the Class III AVO reservoirs saturated with hydrocarbons. In this paper, we verified the high-frequency bright spot results of Chapman for the Class I AVO response using the frequency-dependent analysis of a physical model dataset. The physical model is designed as inter-bedded thin sand and shale based on real field geology parameters. We observed two datasets using fixed offset and 2D geometry with different fluid- saturated conditions. Spectral and time-frequency analyses methods are applied to the seismic datasets to describe the response characteristics for gas-, water-, and oil-saturation. The results of physical model dataset processing and analysis indicate that reflection wave tuning and fluid-related dispersion are the main seismic response characteristic mechanisms. Additionally, the gas saturation model can be distinguished from water and oil saturation for Class I AVO utilizing the frequency-dependent abnormal characteristic. The frequency-dependent characteristic analysis of the physical model dataset verified the different spectral response characteristics corresponding to the different fluid-saturated models. Therefore, by careful analysis of real field seismic data, we can obtain the abnormal spectral characteristics induced by the fluid variation and implement fluid detection using seismic data directly.

Elastic Behaviors of Adsorbed Protein-like Chains

Elastic behaviors of protein-like chains are investigated by Pruned-Enriched-Rosenbluth method and modified orientation-dependent monomer-monomer interactions model. The protein-like chain is pulled away from the attractive surface slowly with elastic force acting on it. Strong adsorption interaction and no adsorption interaction are both considered. We calculate the characteristic ratio and shape factor of protein-like chains in the process of elongation. The conformation change of the protein-like chain is well depicted. The shape of chain changes from “rod” to “sphere” at the beginning of elongation. Then, the shape changes from “sphere” to “rod”. In the end, the shape becomes a “sphere” as the chain leaves away from the surface. In the meantime, we discuss average Helmoholtz free energy per bond, average energy per bond, average adsorbed energy per bond, average α-helical energy per bond, average β-sheet energy per bond and average contact energy per bond. On the other hand, elastic force is also studied. It is found that elastic force has a long plateau during the tensile elongation when there exists adsorption interaction. This result is consistent with SMFS experiment of general polymers. Energy contribution to elastic force and contact energy contribution to elastic force are both discussed. These investigations can provide some insights into the elastic behaviors of adsorbed protein chains.

Zonal disintegration phenomenon in enclosing rock mass surrounding deep tunnels—mechanism and discussion of characteristic parameters

The mechanism of the zonal disintegration phenomenon(ZDP) was realized based on the analysis of the stressedstrained state of the rock mass in the vicinity of the maximum stress zone, which resides in the creep instability failure of rock mass due to the development of a plastic zone and transfer of the maximum stress zone within the rock mass.Some characteristic parameters of the ZDP are discussed theoretically.In first instance, the analytical critical depth condition for the occurrence of ZDP was obtained, which depends on the characteristics and stress concentration coefficient of the rock mass.Secondly, based on creep theory, the expression of the outer radius of the undisturbed zones in the deep rock mass was obtained with the use of an improved Burgers rheological model, which indicated that the radius depends on the characteristics of the rock mass and the depth of excavation and increases quasi-linearly with the rise of creep compliance of the rock mass.Finally, the formula for the distance of the most remote fissured zone away from the working periphery was derived, which increases logarithmically with the increase in the ratio of the in-situ stress and ultimate strength of rock mass.The distances between fissured zones are discussed in qualitative terms.

Nonlinear dynamic characteristics model of labyrinth seal based on Muszynska model

An accurate seal forces model is the foundation to analyze the rotor-seal systems. In this paper, the Navier-Stokes equation and energy equation are solved to simulate the interior flow field in the labyrinth seal gap. The leakage rate is compared with the experimental results in the literatures. The ：4maximum error is 4% , which proves that the method of employing CFD to simulate the interior flow field of labyrinth seal gap is reliable. Based on this, the interior flow field and fluid exciting force of stage teeth labyrinth seal are studied. By coupling with the Muszynska model, the method of defining the experience loss parameters in Muszynska model is proposed. The results indicate that the experience parameters obtained by the proposed method can depict the nonlinear exciting force of labyrinth seal better.

Spatial Structure Characteristics Detecting of Landform based on Improved 3D Lacunarity Model

The spatial structure characteristics of landform are the foundation of geomorphologic classification and recognition.This paper proposed a new method on quantifying spatial structure characteristics of terrain surface based on improved 3D Lacunarity model.Lacunarity curve and its numerical integration are used in this model to improve traditional classification result that different morphological types may share the close value of indexes based on global statistical analysis.Experiments at four test areas with different landform types show that improved 3D Lacunarity model can effectively distinguish different morphological types per texture analysis.Higher sensitivity in distinguishing the tiny differences of texture characteristics of terrain surface shows that the quantification method by 3D Lacu-narity model and its numerical integration presented in this paper could contribute to improving the accuracy of land-form classifications and relative studies.

A robust feature extraction approach based on an auditory model for classification of speech and expressiveness

Based on an auditory model, the zero-crossings with maximal Teager energy operator (ZCMT) feature extraction approach was described, and then applied to speech and emotion recognition. Three kinds of experiments were carried out. The first kind consists of isolated word recognition experiments in neutral (non-emotional) speech. The results show that the ZCMT approach effectively improves the recognition accuracy by 3.47% in average compared with the Teager energy operator (TEO). Thus, ZCMT feature can be considered as a noise-robust feature for speech recognition. The second kind consists of mono-lingual emotion recognition experiments by using the Taiyuan University of Technology (TYUT) and the Berlin databases. As the average recognition rate of ZCMT approach is 82.19%, the results indicate that the ZCMT features can characterize speech emotions in an effective way. The third kind consists of cross-lingual experiments with three languages. As the accuracy of ZCMT approach only reduced by 1.45%, the results indicate that the ZCMT features can characterize emotions in a language independent way.

Qualification of Three Analytical Wake Models

The decrease of wind velocity （wake losses） in downstream area of wind turbine is generally quantified using wake models. The overall estimated power of wind farm varies according to reliability of wake model used, however it＇s unclear which model is most appropriate and able to give a high performance in predicting wind velocity deficit. In this subject, a qualification of three analytical wake models （Jensen, lshihara and Frandsen） based on three principal criteria is presented in this paper： （i） the parsimony which characterizes the inverse of model complexity, （ii） the accuracy of estimation in which wake model is compared with the experimental data and （iii） imprecision that is related to assumptions and uncertainty on the value of variables considered in each model. This qualitative analysis shows the inability of wake models to predict wind velocity deficit due to the big uncertainty of variables considered and it sensitivity to wind farm characteristic.

Effects of temperature fluctuations on cuttlebone formation of cuttlefish Sepia esculenta

The morphological characteristics and the cuttlebone formation of Sepia esculenta exposed to different water temperature fluctuations were investigated under laboratory conditions. Temperature fluctuation cycles （15 cycles, 60 d in total） consisted of the following three regimes of 4 d duration： keeping water temperature in 26℃ for 3 d （Group A）, 2 d （Group B）, 0 d （Group C, control）; then keeping water temperature in 16℃ for the next 1, 2, 4 d. No significant difference in the survival rate was observed between the control and temperature fluctuation groups （P〉0.05）. Lamellar depositions in a temperature fluctuation cycle were 2.45±0.02 for Group A, 2.00±0.02 for Group B, and 1.78±0.02 for Group C （P〈0.05）. The relationship between age and number of lamellas in the cuttlebone of S. esculenta under each water temperature fluctuation could be described as the linear model and the number of lamellas in the cuttlebone did not correspond to actual age. Group A had the highest cuttlebone growth index （CGI）, the lowest locular index （LI）, and inter-streak distances comparing with those of control group. However, the number of lamellas and LI or CGI showed a quadratic relationship for each temperature fluctuation group. In addition, temperature fluctuations caused the breakage of cuttlebone dark rings, which was considered a thermal mark. The position of the breakage in the dark rings was random. This thermal mark can be used as supplementary information for marking and releasing techniques.

Estimating van Genuchten Model Parameters of Undisturbed Soils Using an Integral Method

The van Genuchten model is the most widely used soil water retention curve （SWRC） model. Two undisturbed soils （clay and loam） were used to evaluate the accuracy of the integral method to estimate van Genuchten model parameters and to determine SWRCs of undisturbed soils. SWRCs calculated by the integral method were compared with those measured by a high speed centrifuge technique. The accuracy of the calculated results was evaluated graphically, as well as by root mean square error （RMSE）, normalized root mean square error （NRMSE） and Willmott＇s index of agreement （1）. The results obtained from the integral method were quite similar to those by the centrifuge technique. The RMSEs （4.61 ×10^-5 for Eum-Orthic Anthrosol and 2.74 × 10^-4 for Los-Orthic Entisol） and NRMSEs （1.56 × 10^-4 for Eum- Orthic Anthrosol and 1.45 ×10^-3 for Los-Orthic Entisol） were relatively small. The 1 values were 0.973 and 0.943 for Eum-Orthic Anthrosol and Los-Orthic Entisol, respectively, indicating a good agreement between the integral method values and the centrifuge values. Therefore, the integral method could be used to estimate SWRCs of undisturbed clay and loam soils.

A Robust Collaborative Recommendation Algorithm Based on k-distance and Tukey M-estimator

The existing collaborative recommendation algorithms have lower robustness against shilling attacks.With this problem in mind,in this paper we propose a robust collaborative recommendation algorithm based on k-distance and Tukey M-estimator.Firstly,we propose a k-distancebased method to compute user suspicion degree(USD).The reliable neighbor model can be constructed through incorporating the user suspicion degree into user neighbor model.The influence of attack profiles on the recommendation results is reduced through adjusting similarities among users.Then,Tukey M-estimator is introduced to construct robust matrix factorization model,which can realize the robust estimation of user feature matrix and item feature matrix and reduce the influence of attack profiles on item feature matrix.Finally,a robust collaborative recommendation algorithm is devised by combining the reliable neighbor model and robust matrix factorization model.Experimental results show that the proposed algorithm outperforms the existing methods in terms of both recommendation accuracy and robustness.

Relationship Between Urban Road Traffic Characteristics and Road Grade Based on a Time Series Clustering Model： A Case Study in Nanjing, China

With the increasing number of vehicles in large-and medium-sized cities challenges in urban traffic management, control, and road planning are being faced. Taxi GPS trajectory data is a novel data source that can be used to study the potential dynamic traffic characteristics of urban roads, and thus identify locations that show a notable lack of road planning. Considering that road traffic characteristics on their own are insufficient for a comprehensive understanding of urban traffic, we develop a road traffic characteristic time series clustering model to analyze the relationship between urban road traffic characteristics and road grade based on existing taxi trajectory data. We select the main urban area of Nanjing as our study area and use the taxi trajectory data of a single month for evaluating our method. The experiments show that the clustering model exhibit good performance and can be successfully used for road traffic characteristic classification. Moreover, we analyze the correlation between traffic characteristics and road grade to identify road segments with planning designs that do not match the actual traffic demands.

A Novel Feature-based Method for Sentiment Analysis of Chinese Product Reviews

Sentiment analysis of online reviews and other user generated content is an important research problem for its wide range of applications.In this paper,we propose a feature-based vector model and a novel weighting algorithm for sentiment analysis of Chinese product reviews.Specifically,an opinionated document is modeled by a set of feature-based vectors and corresponding weights.Different from previous work,our model considers modifying relationships between words and contains rich sentiment strength descriptions which are represented by adverbs of degree and punctuations.Dependency parsing is applied to construct the feature vectors.A novel feature weighting algorithm is proposed for supervised sentiment classification based on rich sentiment strength related information.The experimental results demonstrate the effectiveness of the proposed method compared with a state of the art method using term level weighting algorithms.

Analysis of nonlinearities and effects in direct drive electro-hydraulic position servo system

The direct drive electro-hydraulic servo system is a new approach hydraulic system. It is much smaller and easier controlled than traditional systems and is a perfect energy saver. This paper will briefly introduce the popular nonlinearities in the electro-hydraulic system and analyse the effect of nonlinearities in direct drive electro-hydraulic position servo system by means of simulation research. Some valuable conclusions are given.

Landslide susceptibility mapping using Genetic Algorithm for the Rule Set Production(GARP) model

Investigation on landslide phenomenon is necessary for understanding and delineating the landslide prone and safer places for different land use practices. On this basis, a new model known as genetic algorithm for the rule set production was applied in order to assess its efficacy to obtain a better result and a more precise landslide susceptibility map in Klijanerestagh area of Iran. This study considered twelve landslide conditioning factors(LCF) like altitude, slope, aspect, plan curvature, profile curvature, topographic wetness index(TWI), distance from rivers, faults, and roads, land use/cover, and lithology. For modeling purpose, the Genetic Algorithm for the Rule Set Production(GARP) algorithm was applied in order to produce the landslide susceptibility map. Finally, to evaluate the efficacy of the GARP model, receiver operating characteristics curve as well as the Kappa index were employed. Based on these indices, the GARP model predicted the probability of future landslide incidences with the area under the receiver operating characteristics curve(AUC-ROC) values of 0.932, and 0.907 for training and validating datasets, respectively. In addition, Kappa values for the training and validating datasets were computed as 0.775, and 0.716, respectively. Thus, it can be concluded that the GARP algorithm can be a new but effective method for generating landslide susceptibility maps(LSMs). Furthermore, higher contribution of the lithology, distance from roads, and distance from faults was observed, while lower contribution was attributed to soil, profile curvature, and TWI factors. The introduced methodology in this paper can be suggested for other areas with similar topographical and hydrogeological characteristics for land use planning and reducing the landslide damages.

Experimental investigation into stress-relief characteristics with upward large height and upward mining under hard thick roof

According to geological conditions of No. 3 and No. 4 coal seams （namely A3 and B4） of the Pan＇er coal mine and the parameters of panels 11223, 11224, and 11124 with fully-mechanical coal mining, we built 2D similar material simulation and FLAC3D numerical simulation models to investigate the development of mining-induced stress and the extraction effect of pressure-relief gas with large height and upward mining. Based on a comprehensive analysis of experimental data and observations, we obtained the deformation and breakage characteristics of strata overlying the coal seam, the development patterns of the mining-induced stress and fracture, and the size of the stress-relief area. The stress-relief effect was investigated and analyzed in consideration with mining height and three thick hard strata. Because of the group of three hard thick strata located in the main roof and the residual stress of mined panel 11124, the deformation, breakage, mining-induced stress and fracture development, and the stress-relief coefficient were discontinuous and asymmetrical. The breakage angle of the overlying strata, and the compressive and expansive zones of coal deformation were mainly controlled by the number, thickness, and strength of the hard stratum. Compared with the value of breakage angle derived by the traditional empirical method, the experimental value was lower than the traditional results by 3°-4°below the hard thick strata group, and by 13°-19° above the hard thick strata group. The amount of gas extracted from floor drainage roadway of B4 over 17 months was variable and the amount of gas per month differed considerably, being much smaller when panel 11223 influenced the area of the three hard thick strata. Generally, the stress-relief zone of No. 4 coal seam was small under the influence of the hard thick strata located in the main roof, which played an important role in delaying the breakage time and increasing the breakage space. In this study we gained understanding of the stress-relief mechanism influenced by the hard thick roof. The research results and engineering practice show that the main roof of the multiple hard thick strata is a critical factor in the design of panel layout and roadways for integrated coal exploitation and gas extraction, provides a theoretical basis for safe and high-efficient mining of coal resources.

Ensemble learning HMM for motion recognition and retrieval by Isomap dimension reduction

Along with the development of motion capture technique, more and more 3D motion databases become available. In this paper, a novel approach is presented for motion recognition and retrieval based on ensemble HMM (hidden Markov model) learning. Due to the high dimensionality of motion’s features, Isomap nonlinear dimension reduction is used for training data of ensemble HMM learning. For handling new motion data, Isomap is generalized based on the estimation of underlying eigen- functions. Then each action class is learned with one HMM. Since ensemble learning can effectively enhance supervised learning, ensembles of weak HMM learners are built. Experiment results showed that the approaches are effective for motion data recog- nition and retrieval.

Sparsity-Assisted Intelligent Condition Monitoring Method for Aero-engine Main Shaft Bearing

Weak feature extraction is of great importance for condition monitoring and intelligent diagnosis of aeroengine.Aimed at achieving intelligent diagnosis of aero-engine main shaft bearing,an enhanced sparsity-assisted intelligent condition monitoring method is proposed in this paper.Through analyzing the weakness of convex sparse model,i.e.the tradeoff between noise reduction and feature reconstruction,this paper proposes an enhanced-sparsity nonconvex regularized convex model based on Moreau envelope to achieve weak feature extraction.Accordingly,a sparsity-assisted deep convolutional variational autoencoders network is proposed,which achieves the intelligent identification of fault state through training denoised normal data.Finally,the effectiveness of the proposed method is verified through aero-engine bearing run-to-failure experiment.The comparison results show that the proposed method is good at abnormal pattern recognition,showing a good potential for weak fault intelligent diagnosis of aero-engine main shaft bearings.