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The traditional total variation (TV) models in wavelet domain use thresholding directly in coefficients selection and show that Gibbs' phenomenon exists. However, the nonzero coefficient index set selected by hard thresholding techniques may not be the best choice to obtain the least oscillatory reconstructions near edges. This paper aims to propose an image denoising method based on TV and grey theory in the wavelet domain to solve the defect of traditional methods.

In this paper, the authors divide wavelet into two parts: low frequency area and high frequency area; in different areas different methods are used. They apply grey theory in wavelet coefficient selection. The new algorithm gives a new method of wavelet coefficient selection, solves the nonzero coefficients sort, and achieves a good image denoising result while reducing the phenomenon of “Gibbs.”

The results show that the method proposed in this paper can distinguish between the information of image and noise accurately and also reduce the Gibbs artifacts. From the comparisons, the model proposed preserves the important information of the image very well and shows very good performance.

The proposed image denoising model introducing grey relation analysis in the wavelet coefficients selecting and modifying is original. The proposed model provides a viable tool to engineers for processing the image.

The purpose of this paper is to develop a deeper understanding of the new service development (NSD) research field. It addresses its scientific production, social and intellectual structures, and maturity.

This study uses a bibliometric-based literature review. Quantitative and qualitative analyses are performed on a sample of 277 NSD articles (published from 1984 to 2014). These articles are organized into four periods to improve the analyses from an evolutionary perspective: Early Writings (1984-1995), Advancing of Literature (1996-2001), Progressive Literature (2002-2008), and Recent Works (2009-2014).

The scientific production in the NSD field has grown significantly over these four periods, and the entry of new authors has extended the social structure. However, collaboration networks seem disconnected from one another. Nonetheless, the intellectual structure has shown great progress, making NSD an independent area of research and discovery from the new product development domain, with its own foundations and expansions into new topics. Although the NSD research field has not yet reached maturity, it is consistently moving toward it.

This study delivers a multiperspective view of research on NSD using a mixed quantitative and qualitative approach. It provides new insights into the discussion of the field’s maturity and can be used as a roadmap for academics and practitioners who would like to understand the state of existing knowledge and are looking for research opportunities.

The purpose of this paper is to highlight the biological activities of low-calorie natural sweetener, i.e. monk fruit (Siraitia grosvenorii), which are associated with its bioactive constituents.

Recent investigations focused on biochemical characterization and nutraceutical potential of monk fruit (traditional Chinese perennial vine) have been critically reviewed. Also, the safety and influence of monk fruit on organoleptic characteristics of prepared food products have been documented.

Biochemistry of monk fruit revealed that mogrosides are the principal compounds responsible for the high-intensity sweetness in the monk fruit. The fruit induces several biological activities including anti-oxidative effect, hypoglycemic response, anti-allergic properties, anti-carcinogenic and anti-tissue damage activities. Attributing to great potential as a bio-functional sweetener in food products, monk fruit extract has been approved as Generally Regarded as Safe.

This paper highlights the biological potential of monk fruit opening the doors to future investigations for its utilization in products of commercial importance including food and pharmaceutical preparations.