基于SVM的维吾尔文文本分类研究

文本自动分类技术在提高文本信息利用的有效性和准确性上具有重要的现实意义和广阔的应用前景。随着Internet上维吾尔文信息的迅速发展,维吾尔文文本分类成为处理和组织这些大量文本数据的关键技术。研究维吾尔文文本分类相关技术和方法,针对维吾尔文文本在向量空间模型表示下的高维性,本文采用词干提取和χ2统计量相结合的方法对表示空间进行降维。采用SVM算法构造了维吾尔文文本分类器。针对维吾尔文文本分类语料进行的实验结果表明,SVM分类器的MacroF1值达到了84.6%,明显好于kNN方法。     

Modeling the effect of elastane linear density,fabric thread density,and weave float on the stretch,recovery, and compression properties of bi-stretch woven fabrics for compression garments

The aim of this study was to investigate the effect of elastane linear density, thread density, and weave float on the stretch, recovery, and compression properties of bi-stretch woven fabrics for compression garments. Fabric samples were produced using elastane core-spun cotton yarns both in the warp and weft. The elastane linear density, fabric thread density, and weave float size were used as input variables while fabric contraction, subgarment pressure, fabric stretch, and recovery were taken as response variables. Two different elastane linear densities, i.e. 44 and 78 dtex, two different thread densities, and three different weave designs, i.e. 1/1 plain, 2/2 z-twill, and 3/3 z-twill were used. The results of fabric samples were analyzed in Minitab statistical software. The coefficients of determinations (R-sq values) of the regression equations showed good prediction ability of the developed statistical models. The findings of the study may be helpful in deciding appropriate manufacturing specifications of bi-stretch fabrics to attain specific stretch, recovery, and compression properties.     

Linking phosphorus sequestration to carbon humification in wetland soils by 31P and 13C NMR spectroscopy

Phosphorus sequestration in wetland soils is a prerequisite for long-term maintenance of water quality in downstream aquatic systems, but can be compromised if phosphorus is released following changes in nutrient status or hydrological regimen. The association of phosphorus with relatively refractory natural organic matter (e.g., humic substances) might protect soil phosphorus from such changes. Here we used hydrofluoric acid (HF) pretreatment to remove phosphorus associated with metals or anionic sorption sites, allowing us to isolate a pool of phosphorus associated with the soil organic fraction. Solution (31)P and solid state (13)C NMR spectra for wetland soils were acquired before and after hydrofluoric acid pretreatment to assess quantitatively and qualitatively the changes in phosphorus and carbon functional groups. Organic phosphorus was largely unaffected by HF treatment in soils dominated by refractory alkyl and aromatic carbon groups, indicating association of organic phosphorus with stable, humified soil organic matter. Conversely, a considerable decrease in organic phosphorus following HF pretreatment was detected in soils where O-alkyl groups represented the major fraction of the soil carbon. These correlations suggest that HF treatment can be used as a method to distinguish phosphorus fractions that are bound to the inorganic soil components from those fractions that are stabilized by incorporation into soil organic matter.     

Cellulose templating method for the preparation of La0.8Sr0.2Ga0.83Mg0.17O2.815 (LSGM) solid oxide electrolyte

La_0.8Sr_0.2Ga_0.83Mg_0.17O_2.815 (LSGM) materials are synthesized with a fast and facile cellulose templating method for the first time and characterized by XRD, EIS, Archimedes method and SEM–EDS. LSGM powders with a phase purity of 91.7 mol% are obtained after the calcination at 1300 °C for 12 h. SEM–EDS results indicate possible decomposition and reconstruction of the LSGM phase due to the diffusion of Sr-rich species to the grain boundaries for the sample sintered at 1500 °C for 6 h. Maximum conductivity value is found to be 4.2 × 10^?2 S cm^?1 at 800 °C for the sample calcined at 1300 °C for 12 h and sintered at 1400 °C for 6 h. Phase purity, stability and relative density are the important factors for obtaining high performance LSGM electrolytes. Therefore, cellulose templating method is a promising candidate for the preparation of LSGM electrolytes.     

Reinforced concrete deep beam shear strength capacity modelling using an integrative bio-inspired algorithm with an artificial intelligence model

The design and sustainability of reinforced concrete deep beam are still the main issues in the sector of structural engineering despite the existence of modern advancements in this area. Proper understanding of shear stress characteristics can assist in providing safer design and prevent failure in deep beams which consequently lead to saving lives and properties. In this investigation, a new intelligent model depending on the hybridization of support vector regression with bio-inspired optimization approach called genetic algorithm (SVR-GA) is employed to predict the shear strength of reinforced concrete (RC) deep beams based on dimensional, mechanical and material parameters properties. The adopted SVR-GA modelling approach is validated against three different well established artificial intelligent (AI) models, including classical SVR, artificial neural network (ANN) and gradient boosted decision trees (GBDTs). The comparison assessments provide a clear impression of the superior capability of the proposed SVR-GA model in the prediction of shear strength capability of simply supported deep beams. The simulated results gained by SVR-GA model are very close to the experimental ones. In quantitative results, the coefficient of determination (R²) during the testing phase (R² = 0.95), whereas the other comparable models generated relatively lower values of R² ranging from 0.884 to 0.941. All in all, the proposed SVR-GA model showed an applicable and robust computer aid technology for modelling RC deep beam shear strength that contributes to the base knowledge of material and structural engineering perspective.

     

An efficient recommender system algorithm using trust data

The Journal of Supercomputing - Smart services are a concept that provides services to the citizens in an efficient manner. The online shopping and recommender system can play an important role for...     

The effects of immunological castration against GnRH with recombinant OL protein (Ovalbumin-LHRH-7) on carcass and meat quality characteristics,histological appearance of testes and pituitary gland in Kıvırcık male lambs

The aims of the study were to investigate the effects of immunization against GnRH using OL protein (Ovalbumin-LHRH-7) on feedlot performance, carcass, meat quality and some reproductive traits in K?v?rc?k ram lambs. Ram lambs in the immunization (I, n = 7) group were immunized against GnRH using OL protein and boosted 2 weeks later. Control (C, n = 7) group was not treated. The animals were kept at pasture for 6 weeks after the first immunization, subjected to a 70 day fattening program, and then slaughtered. Growth performance, various carcass and meat quality characteristics were not affected from the immunization. GnRH immunization induced GnRH antibody production, suppressed testosterone production and testicular growth (P < 0.01). Testicular structure was negatively affected from the immunization, but not pituitary. These results suggest that immunization against GnRH with OL could be an alternative castration technique in ram lambs without negatively affecting carcass and meat quality characteristics.     

Development of an RF Conditioning System for Charged-Particle Accelerators

Charged-particle accelerators use various vacuum windows on their accelerating radio-frequency (RF) cavities to throughput very high RF power. Before being placed on the cavities, the windows should be cleaned, baked, and fully RF conditioned to prevent a poor vacuum from outgassing, as well as other forms of contamination. An example is the coaxial fundamental power coupler (FPC) with an annular alumina ceramic window for each of the 81 superconducting RF cavities in the Spallation Neutron Source (SNS) linear accelerator. The FPCs needed to be tested up to 650-kW peak in a traveling wave and 2.6 MW with standing wave peaks in 1.3 and 60 pulses/s at 805 MHz. In this paper, an Experimental-Physics-and-Industrial-Control-System-based RF conditioning system for the SNS RF test facility is presented. This paper summarizes the hardware and software design strategies, provides the results obtained, and describes the future research scope.     

Characteristics of CFRP retrofitted hollow brick infill walls of reinforced concrete frames

The mechanical characteristics of infill walls retrofitted with carbon fiber reinforced polymer (CFRP) sheets are really important for the realistic prediction of seismic performance of the vulnerable reinforced concrete (RC) frames retrofitted through CFRP strengthened infill walls. In this study, 36 hollow brick wall specimens were tested either under uniaxial compression or diagonal tension before and after retrofitting externally with CFRP sheets. The test parameters are the dimensions of the walls, the orientation of holes of bricks, the type of mortar, the amount of CFRP sheets and the details of strengthening application. At the end of the tests, a significant contribution of CFRP sheets on the mechanical characteristics of hollow brick walls was observed in terms of several important structural design parameters such as Young and shears moduli, axial and shears strengths as well as the deformation capacity. Finally, the strength and deformability characteristics of the walls and frames retrofitted with CFRP sheets were predicted analytically. The predictions were in good agreement with the experimental data.