Density Weighted Averaging Operator and Application

Exploring structural characteristics implied in initialdecision making information is an important issue in the process of aggregation. In this paper we provide a new family of aggregation operator called density weighted averaging operator（abbreviated as DWA operator）, which carries out the aggregation by classification. In this case, not only the hidden structural characteristics can be identified, some commonly known aggregation operators can also be incorporated into the function of the DWA operator. We further discuss the basic properties of this new operator, such as commutativity, idempotency, boundedness and monotonicity withcertain condition. Afterwards, two important issues related to the DWA operator are investigated, including the arguments partition and the determination of density weights. At last a numerical example regarding performance evaluation of employees is developed to illustrate the using of this new operator.

Specification of Density Functional Approximation by Radial Distribution Function of Bulk Fluid

A systematic methodology is proposed to deal with the weighted density approximation version of clas-sical density functional theory by employing the knowledge of radial distribution function of bulk fluid. The presentmethodology results from the concept of universality of the free energy density functional combined with the test particlemethod. It is shown that the new method is very accurate for the predictions of density distribution ofa hard sphere fluidat different confining geometries. The physical foundation of the present methodology is also applied to the quantumdensity functional theory.

Effects of the Dicranopteris linearis root system and initial moisture content on the soil disintegration characteristics of gully erosion

Benggang erosion is caused by a special type of gully erosion in southern China that seriously endangers the local ecology and environment.In this study,typical Benggang collapsing-wall soils were used as the study area to investigate the effects of different initial moisture contents and dicranopteris linearis root weight densities,as well as their interactions on disintegration in orthogonal test method.The results showed that the rate of soil disintegration decreased as a linear function of the initial moisture content.The soil disintegration rate tended to rise and then fall as the root weight density increased,reflecting an optimum root weight density of 0.75-1.00 g/100 cm3.The incorporation of dicranopteris linearis roots was most effective for soil consolidation in the shallow layers of soil.In addition,the disintegration rate of the collapsing-wall soils increases as the soil layer deepened.The dicranopteris linearis root system and initial moisture content had an interactive effect that was more pronounced in deeper soils.However,the combined effect of these processes was always dominated by the initial moisture content.Moderate initial soil moisture content(0.20-0.24 g/g)and the addition of a high root density in dicranopteris linearis(0.75-1.00 g/100 cm3)were the optimal combinations that reduced the disintegration rate.In conclusion,maintaining a suitable natural moisture content in collapsing-wall soils and taking measures that use plants to consolidate soil can effectively prevent and control the occurrence of Benggang erosion.The results of this study provided further insight into the factors that influence soil disintegration and offered a scientific basis for soil erosion management in the southern China.

Structure and Mechanical Properties of Polypropylene Hernia Meshes with Various Weight

Polypropylene( PP) is a kind of stable material with excellent mechanical properties. Meshes made of PP have lots of obvious advantages. In this paper,5 PP hernia meshes with different warp-knitting structures which can be sorted into one light-weight hernia mesh,two standard-weight hernia meshes and two heavyweight hernia meshes were chosen to have a serious of mechanical test,including weight density,thickness,pore size,porosity,tensile strength,bursting strength,stitch tear strength,tear strength and bending rigidity. The respective relationship between mechanical performance and weight density were analyzed. The results revealed that heavy-weight hernia meshes had the biggest thickness( 0. 834 mm),the smallest pore size( 462 μm) and the smallest porosity( 58. 40%). The mechanical performance demonstrated that the tensile strength increased more than 800 N,the stitch tear strength increased more than 40 N,the bursting strength increased more than750 N and the tear strength increased more than 40 N by enlarging the weight density by 100-150 g/m^2. However, heavy-weight hernia meshes had problems of high bending rigidity,unevenness and anisotropy. Standard-weight hernia meshes with 70-140 g/m^2 not only met the demand of the mechanical properties,but also had good flexibility and structure parameters,which could be considered as an ideal hernia mesh.

An Intelligent Early Warning Method of Press-Assembly Quality Based on Outlier Data Detection and Linear Regression

Focusing on controlling the press-assembly quality of high-precision servo mechanism,an intelligent early warning method based on outlier data detection and linear regression is proposed.Linear regression is used to deal with the relationship between assembly quality and press-assembly process,then the mathematical model of displacement-force in press-assembly process is established and a qualified press-assembly force range is defined for assembly quality control.To preprocess the raw dataset of displacement-force in the press-assembly process,an improved local outlier factor based on area density and P weight(LAOPW)is designed to eliminate the outliers which will result in inaccuracy of the mathematical model.A weighted distance based on information entropy is used to measure distance,and the reachable distance is replaced with P weight.Experiments show that the detection efficiency of the algorithm is improved by 5.6 ms compared with the traditional local outlier factor(LOF)algorithm,and the detection accuracy is improved by about 2%compared with the local outlier factor based on area density(LAOF)algorithm.The application of LAOPW algorithm and the linear regression model shows that it can effectively carry out intelligent early warning of press-assembly quality of high precision servo mechanism.

Progressive Failure Analysis of Quasi-isotropic Self-reinforced Polyethylene Composites by Comparing Unsupervised and Supervised Classifications of Acoustic Emission Data

Unsupervised and supervised pattern recognition( PR)techniques are used to classify the acoustic emission( AE) data originating from the quasi-isotropic self-reinforced polyethylene composites,in order to identify the various mechanisms in the multiangle-ply thermoplastic composites. Ultra-high molecular weight polyethylene / low density polyethylene( UHMWPE / LDPE)composites were made and tested under quasi-static tensile load. The failure process was monitored by the AE technique. The collected AE signals were classified by unsupervised and supervised PR techniques, respectively. AE signals were clustered with unsupervised PR scheme automatically and mathematically. While in the supervised PR scheme,the labeled AE data from simple lay-up UHMWPE / LDPE laminates were utilized as the reference data.Comparison was drawn according to the analytical results. Fracture surfaces of the UHMWPE / LDPE specimens were observed by a scanning electron microscope( SEM) for some physical support. By combining both classification results with the observation results,correlations were established between the AE signal classes and their originating damage modes. The comparison between the two classifying schemes showed a good agreement in the main damage modes and their failure process. It indicates both PR techniques are powerful for the complicated thermoplastic composites. Supervised PR scheme can lead to a more precise classification in that a suitable reference data set is input.

Inference of change-point in single index models

Single index models are widely used in medicine, econometrics and some other fields. In this paper, we consider the inference of a change point problem in single index models. Based on density-weighted average derivative estimation (ADE) method, we propose a statistic to test whether a change point exists or not. The null distribution of the test statistic is obtained using a permutation technique. The permuted statistic is rigorously shown to have the same distribution in the limiting sense under both null and alternative hypotheses. After the null hypothesis of no change point is rejected, an ADE-based estimate of the change point is proposed under assumption that the change point is unique. A simulation study confirms the theoretical results.

Optimization of magnetic resonance sequences in lymph node staging of nasopharyngeal carcinoma

Background Detection rate of retropharyngeal lymph node metastasis in patients with nasopharyngeal carcinoma （NPC） needs to be improved. The purpose of this study was to compare three magnetic resonance （MR） sequences for detecting lymph nodes in patients with NPC. Methods Between July 2007 and March 2008, MR staging of pre-treated tumor was conducted on 120 patients with pathologically confirmed NPC. The outcome of three different sequences for MR NPC staging were compared： coronal short T1 inversion recovery （STIR）, axial proton density fat-suppressed （PDWI fs）, and coronal contrast enhanced fast spin echo T1 weighted fat-suppressed （CE FSE TlWl fs）. Nodal classification method （1999） was applied to count the number of retropharyngeal and cervical lymph nodes discovered by each MR sequence. Paired t tests were used for statistical analysis. Results A total of 2575 lymph nodes were found using coronal STIR sequence; 1816 lymph nodes for coronal CE FSE TIWI fs sequence and 2638 lymph nodes for axial PDWl fs sequence. Significant differences existed in the number of lymph nodes detected by axial PDWI fs and coronal CE FSE T1WI fs sequence （paired t test, P 〈0.05）, with the former sequence getting higher numbers. Statistical differences also existed between coronal STIR and coronal CE FSE TlWl fs sequence （paired ttest, P 〈0.05）, with the former sequence getting higher numbers. No significant difference was found between coronal STIR sequence and axial PDWI fs sequence （paired ttest, P 〉0.05）. Conclusions For the detection of retropharyngeal and cervical lymph nodes, coronal STIR sequence and axial PDWI fs sequence have similar performance and both sequences showed better detection than CE FSE TIWI fs sequence. Furthermore, by combining coronal STIR sequence and axial PDWI fs sequence, we can improve the detection of lymph nodes in NPC N-staging before treatment, especially for lymph nodes located in the thoracic entrance.