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Article
Publication date: 13 February 2019

Xudong Sun and Ke Zhu

The purpose of this paper is to initiate investigations to develop near infrared (NIR) spectroscopy coupled with spectral dimensionality reduction and multivariate

Abstract

Purpose

The purpose of this paper is to initiate investigations to develop near infrared (NIR) spectroscopy coupled with spectral dimensionality reduction and multivariate calibration methods to rapidly measure cotton content in blend fabrics.

Design/methodology/approach

In total, 124 and 41 samples were used to calibrate models and assess the performance of the models, respectively. The raw spectra are transformed into wavelet coefficients. Multivariate calibration methods of partial least square (PLS), extreme learning machine (ELM) and least square support vector machine (LS-SVM) were employed to develop the models using 100 wavelet coefficients. Through comparing the performance of PLS, ELM and LS-SVM models with new samples, the optimal model of cotton content was obtained with the LS-SVM model.

Findings

The correlation coefficient of prediction (rp) and root mean square errors of prediction were 0.99 and 4.37 percent, respectively. The results suggest that NIR spectroscopy, combining with the LS-SVM method, has significant potential to quantitatively analyze cotton content in blend fabrics.

Originality/value

It may have commercial and regulatory potential to avoid time-consuming work, costly and laborious chemical analysis for cotton content in blend fabrics.

Details

International Journal of Clothing Science and Technology, vol. 31 no. 3
Type: Research Article
ISSN: 0955-6222

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Article
Publication date: 7 March 2016

Xudong Sun, Mingxing Zhou and Yize Sun

– The purpose of this paper is to develop near infrared (NIR) techniques coupled with multivariate calibration methods to rapid measure cotton content in blend fabrics.

Abstract

Purpose

The purpose of this paper is to develop near infrared (NIR) techniques coupled with multivariate calibration methods to rapid measure cotton content in blend fabrics.

Design/methodology/approach

In total, 124 and 41 samples were used to calibrate models and assess the performance of the models, respectively. Multivariate calibration methods of partial least square (PLS), extreme learning machine (ELM) and least square support vector machine (LS-SVM) were employed to develop the models. Through comparing the performance of PLS, ELM and LS-SVM models with new samples, the optimal model of cotton content was obtained with LS-SVM model. The correlation coefficient of prediction (r p ) and root mean square errors of prediction were 0.98 and 4.50 percent, respectively.

Findings

The results suggest that NIR technique combining with LS-SVM method has significant potential to quantitatively analyze cotton content in blend fabrics.

Originality/value

It may have commercial and regulatory potential to avoid time consuming work, costly and laborious chemical analysis for cotton content in blend fabrics.

Details

International Journal of Clothing Science and Technology, vol. 28 no. 1
Type: Research Article
ISSN: 0955-6222

Keywords

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Book part
Publication date: 1 December 2008

Wenbo Hu and Alec N. Kercheval

Portfolio credit derivatives, such as basket credit default swaps (basket CDS), require for their pricing an estimation of the dependence structure of defaults, which is…

Abstract

Portfolio credit derivatives, such as basket credit default swaps (basket CDS), require for their pricing an estimation of the dependence structure of defaults, which is known to exhibit tail dependence as reflected in observed default contagion. A popular model with this property is the (Student's) t-copula; unfortunately there is no fast method to calibrate the degree of freedom parameter.

In this paper, within the framework of Schönbucher's copula-based trigger-variable model for basket CDS pricing, we propose instead to calibrate the full multivariate t distribution. We describe a version of the expectation-maximization algorithm that provides very fast calibration speeds compared to the current copula-based alternatives.

The algorithm generalizes easily to the more flexible skewed t distributions. To our knowledge, we are the first to use the skewed t distribution in this context.

Details

Econometrics and Risk Management
Type: Book
ISBN: 978-1-84855-196-1

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Article
Publication date: 19 April 2011

S.K. Bag, P.P. Srivastav and H.N. Mishra

The purpose of this paper is to develop FT‐NIR technique for determination of moisture content in bael pulp.

Abstract

Purpose

The purpose of this paper is to develop FT‐NIR technique for determination of moisture content in bael pulp.

Design/methodology/approach

Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 70 to 95 per cent (wb). The prediction models based on partial least squares (PLS) regression, were developed in the near‐infrared region (4,000‐2,500cm‐1). Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre‐processing (vector normalization, minimum‐maximum normalization and multiplicative scatter correction) methods.

Findings

The best calibration model was developed with min‐max normalization (MMN) spectral pre‐processing (R2=99.3). The MMN pre‐processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.993 was obtained for the calibration model developed. The developed results indicated that FTNIR spectroscopy could be used for rapid detection of moisture content in bael pulp samples without any sample destruction.

Originality/value

The research in this paper is useful for the quick detection of moisture content of bael fruit pulp during processing.

Details

British Food Journal, vol. 113 no. 4
Type: Research Article
ISSN: 0007-070X

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Article
Publication date: 30 July 2021

Bing Zhang, Raiyan Seede, Austin Whitt, David Shoukr, Xueqin Huang, Ibrahim Karaman, Raymundo Arroyave and Alaa Elwany

There is recent emphasis on designing new materials and alloys specifically for metal additive manufacturing (AM) processes, in contrast to AM of existing alloys that were…

Abstract

Purpose

There is recent emphasis on designing new materials and alloys specifically for metal additive manufacturing (AM) processes, in contrast to AM of existing alloys that were developed for other traditional manufacturing methods involving considerably different physics. Process optimization to determine processing recipes for newly developed materials is expensive and time-consuming. The purpose of the current work is to use a systematic printability assessment framework developed by the co-authors to determine windows of processing parameters to print defect-free parts from a binary nickel-niobium alloy (NiNb5) using laser powder bed fusion (LPBF) metal AM.

Design/methodology/approach

The printability assessment framework integrates analytical thermal modeling, uncertainty quantification and experimental characterization to determine processing windows for NiNb5 in an accelerated fashion. Test coupons and mechanical test samples were fabricated on a ProX 200 commercial LPBF system. A series of density, microstructure and mechanical property characterization was conducted to validate the proposed framework.

Findings

Near fully-dense parts with more than 99% density were successfully printed using the proposed framework. Furthermore, the mechanical properties of as-printed parts showed low variability, good tensile strength of up to 662 MPa and tensile ductility 51% higher than what has been reported in the literature.

Originality/value

Although many literature studies investigate process optimization for metal AM, there is a lack of a systematic printability assessment framework to determine manufacturing process parameters for newly designed AM materials in an accelerated fashion. Moreover, the majority of existing process optimization approaches involve either time- and cost-intensive experimental campaigns or require the use of proprietary computational materials codes. Through the use of a readily accessible analytical thermal model coupled with statistical calibration and uncertainty quantification techniques, the proposed framework achieves both efficiency and accessibility to the user. Furthermore, this study demonstrates that following this framework results in printed parts with low degrees of variability in their mechanical properties.

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Article
Publication date: 3 October 2016

Leovardo Mata and José Antonio Núñez Mora

The purpose of this paper is to analyze the dependence between the Chinese and Market Integrated Latin America (MILA) stock markets.

Abstract

Purpose

The purpose of this paper is to analyze the dependence between the Chinese and Market Integrated Latin America (MILA) stock markets.

Design/methodology/approach

The authors adjust the multivariate probability distribution Variance Gamma (VG) on data yields from the Hang Seng Index (HSI) and MILA and they use the estimated parameters under VG to find a robust estimator of the correlation matrix yields.

Findings

The degree of dependence between stock indices from China, Peru, Mexico, Colombia and Chile. In addition, the impact of the change in the HSI affects mostly the movements of the selective stock price index (IPSA) and equally affects the index of the Mexican stock exchange (IPC) and Lima Stock Exchange (S&P/BVL). The effect on index of the Colombia Stock Exchange (COLCAP) is not significant.

Research limitations/implications

Over time there are different structural changes so the time has been restricted to the years 2000-2015, but could extend the analysis to other time periods and sectors of listed companies in the indices.

Practical implications

The results can guide policy makers to assess the effect of a random crash on stock markets and measure the level of risk from other markets.

Social implications

The results can generate a greater understanding of the relationship between the stock markets of China and the emerging countries of Latin America.

Originality/value

The value of this paper is to focus on alternative methodology to calculate the correlation matrix yields and measure the dependence between the Chinese and MILA stock markets.

Details

Journal of Chinese Economic and Foreign Trade Studies, vol. 9 no. 3
Type: Research Article
ISSN: 1754-4408

Keywords

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Abstract

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Handbook of Transport Geography and Spatial Systems
Type: Book
ISBN: 978-1-615-83253-8

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Article
Publication date: 1 May 2000

David West and Paul Mangiameli

In treating both sewage and storm runoff, wastewater treatment plants are important to maintaining a healthy environment. If the plant operations managers do not respond…

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Abstract

In treating both sewage and storm runoff, wastewater treatment plants are important to maintaining a healthy environment. If the plant operations managers do not respond correctly to plant conditions, environmental damage resulting in the deterioration of human health may be the result. Unfortunately, there are no formal models to help these managers; they rely upon their own intuition to manage the plants. The purpose of this paper is to investigate the effectiveness of various models, originally used for manufacturing, to detect process conditions in wastewater treatment facilities. We compare and contrast the performance of five statistical models and three neural network architectures. The data used in the research is 527 daily measurements of 38 sensor readings of the process state variables of an urban wastewater treatment plant.

Details

International Journal of Operations & Production Management, vol. 20 no. 5
Type: Research Article
ISSN: 0144-3577

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Article
Publication date: 3 September 2020

Weiwei Wu, Zhouzhou Wang, Shuang Ding, Aiping Song and Dejia Zhu

The effects of infiltrant-related factors during post-processing on mechanical performance are fully considered for three-dimensional printing (3DP) technology. The…

Abstract

Purpose

The effects of infiltrant-related factors during post-processing on mechanical performance are fully considered for three-dimensional printing (3DP) technology. The factors contain infiltrant type, infiltrating means, infiltrating frequency and time interval of infiltrating.

Design/methodology/approach

A series of printing experiments are conducted and the parts are processed with different conditions by considering the above mentioned four parameters. Then the mechanical performances of the parts are tested from both macroscopic and microscopic papers. In the macroscopic view, the compressive strength of each printed part is measured by the materials testing machine – Instron 3367. In the microscopic view, scanning electron microscope and energy dispersion spectrum are used to obtain microstructure images and element content results. The pore size distributions of the parts are measured further to illustrate that if the particles are bound tightly by infiltrant. Then, partial least square (PLS) is used to conduct the analysis of the influencing factors, which can solve the small-sample problem well. The regression analysis and the influencing degree of each factor are explored further.

Findings

The experimental results show that commercial infiltrant has an outstanding performance than other super glues. The infiltrating action will own higher compressive strength than the brushing action. The higher infiltrating frequency and inconsistent infiltrating time interval will contribute to better mechanical performance. The PLS analysis shows that the most important factor is the infiltrating method. When compare the fitted value with the actual value, it is clear that when the compressive strength is higher, the fitting error will be smaller.

Practical implications

The research will have extensive applicability and practical significance for powder-based additive manufacturing.

Originality/value

The impact of the infiltrating-related post-processing on the performance of 3DP technology is easy to be ignored, which is fully taken into consideration in this paper. Both macroscopic and microscopic methods are conducted to explore, which can better explain the mechanical performance of the parts. Furthermore, as a small-sample method, PLS is used for influencing factors analysis. The variable importance in the projection index can explain the influencing degree of each parameter.

Details

Rapid Prototyping Journal, vol. 26 no. 9
Type: Research Article
ISSN: 1355-2546

Keywords

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Abstract

Details

Dynamics of Financial Stress and Economic Performance
Type: Book
ISBN: 978-1-78754-783-4

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