Study on Performance and Processability of Sirofil Lightweight Worsted Fabric

The lightweight worsted fabric made of Sirofil yarn was developed and its textile performance was studied. By means of conventional testing, KES and FAST, it is concluded that with the coordination of proper fabric design and processing technique, the performance of this innovative fabric is superior to that of the conventional lightweight fabric Furthermore, it is predicted from the relevant parameters that its processability in the following suit manufacture is very desirable.

Principles and Chief Technologies in Developing Light-weighted Worsted Fabrics

More and more light-weighted fabrics are being required by the market, especially for the worsted manufacture.In the past, such fabrics are produced mainly through changing the structure of woven goods or by using finer yarns. But these possibilities are very limited. In this paper, new devices are discussed: (1) on the yarn level- to use single yarns instead of conventional doubled ones, to decrease number of fibers in yarn cross sections beth during spinning and after finishing; (2) on the fiber level - to use finer fibers in blends with wool and modification of the wool fibers; (3) on the macromolecule level - to stretch the macromolecules in alpha keratin, to get super fine wool fibers.

LANZHOU NO.3 WORSTED CO. LTD

The Lanzhou No.3 Worsted Co. Ltd.is one of the backbone enterprises inChina’s textiles industry. In recentyears, proceeding from the enterprise’ssituation, the Company has comprehensivelyconducted the economic operation of asimulated market, shifted its operationalideology, and development pattern by takingscience and technology as the mainstay,

OPTIMAL BIRKHOFF INTERPOLATION AND BIRKHOFF NUMBERS IN SOME FUNCTION SPACES

This paper investigates the optimal Birkhoff interpolation and Birkhoff numbers of some function spaces in space L∞[-1,1]and weighted spaces Lp,ω[-1,1],1≤p<∞,with w being a continuous integrable weight function in(-1,1).We proved that the Lagrange interpolation algorithms based on the zeros of some polynomials are optimal.We also show that the Lagrange interpolation algorithms based on the zeros of some polynomials are optimal when the function values of the two endpoints are included in the interpolation systems.

Worst泪道探针联合改良泪道穿线插管法在复杂性泪小管断裂吻合术中的应用

目的:探讨Worst泪道探针联合改良泪道穿线插管法在复杂性泪小管断裂吻合术中的应用价值。方法:回顾性研究。选取2019-03-01/2021-03-31遵义医科大学第二附属医院眼科收治的复杂性外伤性泪小管断裂患者68例68眼。根据手术方式分为两组,A组患者36例36眼采用Worst泪道探针寻找泪小管断端并联合改良泪道穿线插管法治疗,B组患者32例32眼采用显微镜下寻找泪小管断端,双路插管法吻合泪小管术治疗。比较两组患者临床疗效、术中寻找泪小管断端成功率、寻找泪小管断端时间、手术时间、疼痛程度、术后眼部异物感及并发症情况。结果:A组患者临床疗效总有效率高于B组(94%vs 38%),术中寻找泪小管断端成功率高于B组(100%vs 47%),寻找泪小管断端时间、手术时间均短于B组,疼痛程度评分低于B组(均P<0.05)。术后随访6mo~1a,A组患者术后眼部异物感评分、泪小点撕裂及形态变化发生率、溢泪程度均低于B组(均P<0.05)。结论:Worst泪道探针联合改良泪道穿线插管法治疗复杂性外伤性泪小管断裂能更精确找到泪小管断端,缩短手术时间,减轻患者疼痛及术后眼部异物感,提高临床疗效,降低并发症发生率。

Light-Weighted Decision Support Framework for Selecting Cloud Service Providers

Multi-criteria decision making(MCDM)is a technique used to achieve better outcomes for some complex business-related problems,whereby the selection of the best alternative can be made in as many cases as possible.This paper proposes a model,the multi-criteria decision support method,that allows both service providers and consumers to maximize their profits while preserving the best matching process for resource allocation and task scheduling.The increasing number of service providers with different service provision capabilities creates an issue for consumers seeking to select the best service provider.Each consumer seeks a service provider based on various preferences,such as price,service quality,and time to complete the tasks.In the literature,the problem is viewed from different perspectives,such as investigating how to enhance task scheduling and the resource allocation process,improve consumers’trust,and deal with network problems.This paper offers a novel model that considers the preferences of both service providers and consumers to find the best available service provider for each consumer.First,the model adopts the best-worst method(BWM)to gather and prioritize tasks based on consumers’and service providers’preferences.Then,the model calculates and matches similarities between the sets of tasks from the consumer’s side with the sets of tasks from the provider’s side to select the best service provider for each consumer using the two proposed algorithms.The complexity of the two algorithms is found to be O(n3).

Prioritizing real estate enterprises based on credit risk assessment:an integrated multi‑criteria group decision support framework

Credit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and creditworthiness.In the context of real estate enterprises,credit risk assessment provides a basis for banks and other financial institutions to choose suitable investment objects.Additionally,it encourages real estate enterprises to abide by market norms and provide reliable information for the standardized management of the real estate industry.However,Chinese real estate companies are hesitant to disclose their actual operating data due to privacy concerns,making subjective evalu-ation approaches inevitable,occupying important roles in accomplishing Chinese real estate enterprise credit risk assessment tasks.To improve the normative and reliability of credit risk assessment for Chinese real estate enterprises,this study proposes an integrated multi-criteria group decision-making approach.First,a credit risk assessment index for Chinese real estate enterprises is established.Then,the proposed framework combines proportional hesitant fuzzy linguistic term sets and preference ranking organization method for enrichment evaluation II methods.This approach is suitable for processing large amounts of data with high uncertainty,which is often the case in credit risk assessment tasks of Chinese real estate enterprises involving massive subjec-tive evaluation information.Finally,the proposed model is validated through a case study accompanied by sensitivity and comparative analyses to verify its rationality and feasibility.This study contributes to the research on credit assessment for Chinese real estate enterprises and provides a revised paradigm for real estate enterprise credit risk assessment.

Worst泪道探针加硅胶管环管支撑泪小管断裂吻合术的临床观察

目的:探讨外伤性泪小管断裂吻合的有效方法。方法:32例外伤引起下泪小管断裂患者,利用Worst泪道探针加硅胶管环管支撑治疗,手术1次吻合成功。随访0.5～1a。结果:31例治愈,术后随访泪道通畅,无流泪。因睑外翻不成功1例。结论:采用Worst泪道探针加硅胶管环管支撑泪小管断裂吻合术治疗泪小管断裂方法简便效果好。

基于DEA的上市公司信用风险评估理论与实证研究

基于Nomal/Worst DEA概念下的DEA模型,在输入和输出指标上的选取,既区别于一般的DEA模型,同时又克服了DMA类信用评估方法在选取判别定点上的缺陷;而分层层次的选择更能体现实际的特点,因此该模型在对上市公司的信用风险评估中具有较高的精确性和操作性。

电路容差分析的计算机仿真方法

计算机仿真是电路容差分析的一种有效、可靠、快捷的方法。举例说明用电路分析软件OrCAD/PSpice9进行最坏情况分析(WorstCaseAnalysis)和蒙托卡诺分析(MonteCarlo)的具体方法和步骤。

EDA技术中的电路容差分析方法及其应用

在当今电子电路设计与生产实践中,基于EDA技术的容差分析及其应用具有非常重要的意义,是保证产品合格率与降低成本的重要依据。Monte Carlo容差分析法是主要的容差分析方法之一,也是目前EDA技术中普遍使用的容差分析方法。该方法为统计取样法,其理论基础是概率论中的大数定理,其基本原理是根据指定的分布规律在器件参数容差范围内随机地选取元器件及电路工作条件参数,再经大量计算,分析出电路性能的统计规律。所举分析实例意在详细说明应用通用电路仿真程序Micro-Cap 6进行Monte Carlo分析和Worst Case分析的具体方法和过程。

Full ranking procedure based on best and worst frontiers

In the traditional data envelopment analysis （DEA） structure, the efficiency score for one decision making unit （DMU） is calculated by measuring the distance of the evaluated DMU to the best practice frontier. Recent researches have provided the reasonability of considering the worst practice frontier as a supple- ment to the traditional DEA techniques. The existing researches take only one type of frontier into account, and they cannot com- pare the evaluated DMU with both the best and the worst perform- ing DMUs. A DEA-based procedure is developed to consider the best and the worst frontiers in the same scenario where the ratio of two distances （RDS） measure is proposed. The principal appli- cation of this approach is for ranking, and, as a complement tool, for performance evaluation. The proposed approach can be used in a wide range of applications such as the performance evaluation of employees and others. Finally, a bookstore data set is used to illustrate the proposed approach.

COMPUTATIONAL COMPLEXITY IN WORST, STOCHASTIC AND AVERAGE CASE SETTING ON FUNCTIONAL APPROXIMATION PROBLEM OF MULTIVARIATE

The order of computational complexity of all bounded linear functional ap proximation problem is determined for the generalized Sobolev class Wp?（Id）, Nikolskii class H|∞k（Id） in the worst （deterministic）, stochastic and average case setting, from which it is concluded that the bounded linear functional approximation problem for the classes Wp?（Id） and H∞k（Id） is intractable in worst case setting, but is tractable with respect to stochastic and average case setting.

WORST SUBCARRIER AVOIDING WATER-FILLING SUBCARRIER ALLOCATION SCHEME FOR OFDM-BASED CRN

Efficient and reliable subcarrier power joint allocation is served as a promising problem in cognitive OFDM-based Cognitive Radio Networks (CRN). This paper focuses on optimal subcarrier allocation for OFDM-based CRN. We mainly propose subcarrier allocation scheme denoted as Worst Subcarrier Avoiding Water-filling (WSAW), which is based on Rate Adaptive (RA) criterion and three constraints are considered in CRN. The algorithm divides the assignment procedure into two phases. The first phase is an initial subcarrier allocation based on the idea of avoiding selecting the worst subcarrier in order to maximize the transmission rate; while the second phase is an iterative adjustment process which is realized by swapping pairs of subcarriers between arbitrary users. The proposed scheme could assign subcarriers in accordance with channel coherence time. Hence, real time subcarrier allocation could be implemented. Simulation results show that, comparing with the similar existing algorithms, the proposed scheme could achieve larger capacity and a near-optimal BER performance.

Weakness Ranking Method for Subsystems of Heavy-Duty Machine Tools Based on FMECA Information

Heavy-duty machine tools are composed of many subsystems with different functions,and their reliability is governed by the reliabilities of these subsystems.It is important to rank the weaknesses of subsystems and identify the weakest subsystem to optimize products and improve their reliabilities.However,traditional ranking methods based on failure mode effect and critical analysis(FMECA)does not consider the complex maintenance of products.Herein,a weakness ranking method for the subsystems of heavy-duty machine tools is proposed based on generalized FMECA information.In this method,eight reliability indexes,including maintainability and maintenance cost,are considered in the generalized FMECA information.Subsequently,the cognition best worst method is used to calculate the weight of each screened index,and the weaknesses of the subsystems are ranked using a technique for order preference by similarity to an ideal solution.Finally,based on the failure data collected from certain domestic heavy-duty horizontal lathes,the weakness ranking result of the subsystems is obtained to verify the effectiveness of the proposed method.An improved weakness ranking method that can comprehensively analyze and identify weak subsystems is proposed herein for designing and improving the reliability of complex electromechanical products.

Parallel machine covering with limited number of preemptions

In this paper, we investigate the/-preemptive scheduling on parallel machines to maximize the minimum machine completion time, i.e., machine covering problem with limited number of preemptions. It is aimed to obtain the worst case ratio of the objective value of the optimal schedule with unlimited preemptions and that of the schedule allowed to be preempted at most i times. For the m identical machines case, we show the worst case ratio is 2m-i-1/m and we present a polynomial time algorithm which can guarantee the ratio for any 0 〈 i 〈2 m - 1. For the /-preemptive scheduling on two uniform machines case, we only need to consider the cases of i = 0 and i = 1. For both cases, we present two linear time algorithms and obtain the worst case ratios with respect to s, i.e., the ratio of the speeds of two machines.

Lower bounds and modified LPT algorithm for k-partitioning problems with partition matroid constraint

In this paper, the k-partitioning problem with partition matroid constraint is considered. LPT algorithm is modified to fit the problem and its worst-ease performance is analyzed. The lower bounds of optimal solution for the min-max problem are given.