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The intelligent identification of stains can quickly and accurately identify stains. At present, stains are identified subjectively by appearance, color, taste, feel, location, etc. Color is an important factor in identifying stains. K/S value is used to analyze the color of textile fabric, and it has additivity. The purpose of the study is to explore its application in stain recognition is of great significance to intelligent washing.

A certain method used to stain the textile, then the K/S value of the textile before and after the stain was analyzed and tested by the color difference instrument. The K/S curve of the stain was calculated by the addition of K/S, and then the stain was identified and distinguished.

The K/S value of the textile stained with stains could be deducted by the K/S value of the color difference meter. After deducting the base cloth, the K/S curve of the same stain is basically the same. Then the stain can be identified and analyzed.

The K/S value can be used for stain analysis, but it needs to be analyzed and tested in the laboratory.

This study provides a simple method for stains identification.

In addition to common methods of stain identification, such as appearance, color, feel, smell, location, stain removal materials, breaking the substrate, IR, etc., K/S value can be used for stain analysis. Identifying stains and washing them in a targeted way to achieve a better washing effect could provide certain technical support for the development of smart washing and smart home appliances.

This paper aims to quantify atmospheric corrosion by image analyses. The corrosion extent, form and distribution of corrosion product on Q235B and T91 steels exposed to a Zhoushan marine atmosphere over one year are characterized by image analysis.

Image analysis of corrosion images were achieved using the gray value, wavelet analysis and fuzzy Kolmogorov–Sinai (K–S) entropy.

As corrosion becomes extensive, the gray value of corrosion images decreases, and the energy value of nine subimages after wavelength decomposition decreases. Fuzzy K–S entropy increases as localized corrosion propagates but decreases as uniform corrosion spreads.

The methods proposed in this work open a new way for fast corrosion evaluation of metallic materials exposed to atmospheric conditions.

The purpose of this study is to optimize single-bath dyeing process of wool and silk blend, to achieve uniform colour strength for both the fibre after the dyeing process. Due to different absorption characteristics of wool and silk, two-stage dyeing is preferred in the industry. If the fibres are dyed together, the wool fibre becomes darker and the silk fibre becomes lighter after the dyeing process. Solid dyeing effect can be achieved using a single-bath dyeing process.

The dye-acceptor sites in the wool fibre are first blocked using one commercial syntan Mesitol HWS. Then, the syntan-treated wool and silk fibres (80:20 blend ratios) are dyed with Telon Navy AMF dyes in the presence of sodium sulphate. To explore the influence of Syntan, sodium sulphate and the experimental conditions on the dyeing process and to optimize the process, central composite design (CCD) of four factors and three levels was tested.

The design process is optimized using four independent variables: Mesitol HWS concentration, sodium sulphate concentration, pH of dyebath and temperature of dyeing. Three levels of Mesitol HWS concentration (5, 10 and 15 per cent), sodium sulphate concentration (10, 20 and 30 per cent), pH (2.5, 4 and 5.5) and temperature of dyeing (70, 80 and 900°C) were selected for this study. These variables are optimized using response surface regression equation of the ratio of K/S wool and K/S silk. The predicted equation matched well with the experimental data.

This paper proposes the use of one-bath dyeing process of wool and silk blend fabric to reduce the dyeing time, process step and to save water.

The purpose of this paper is to explore a new eco-friendly green textile dyeing. Natural plant Buddleja officinalis is traditionally used as yellow pigment addition in rice. It is worth developing its application and dyeing performance in cotton fabric.

Buddleja officinalis dried flower was extracted with ethanol aqueous. The extraction conditions including ethanol concentration, material to liquor ratio, extract time and temperature were optimized. Then cotton fabrics were dyed with Buddleja officinalis extraction under conventional and ultrasonic conditions. The effects of dyeing time, bath ratio, pH value of dyeing bath, dyeing temperature and mordants on K/S values were studied and the resulting color strength obtained by conventional and ultrasonic dyeing were compared. The ultraviolet (UV) transmittance of Buddleja officinalis dyed cotton fabric was also evaluated.

The color strength of the fabric dyed with Buddleja officinalis under ultrasonic conditions was higher than that under conventional conditions. Alum, Fe and Cu as simultaneous mordants improved the K/S value of the dyed cotton fabrics. Both washing fastness and rubbing fastness were fairly good in all Buddleja officinalis dyed cotton fabrics, washing fastness = 3–4 and rubbing fastness = 4. What’s more, the dyed cotton fabrics showed lower transmittance values as compared to undyed cotton fabrics and indicated potential UV protection capability.

Buddleja officinalis can be a new natural dye source for the ultrasonic dyeing of cotton fabric.

It is for the first time that Buddleja officinalis is used as a natural dye in cotton fabric dyeing with less water and the dyeing using ultrasound has been found to have an obvious improvement in the color strength and color-fastness.

The purpose of this paper is to know whether the authors’ productivity pattern of library and information science (LIS) open access journals adheres to Lotka’s inverse square law of scientific productivity. Since the law was introduced, it has been tested in various fields of knowledge, and results have varied. This study has closely followed Lotka’s inverse square law in the field of LIS open access journals to find a factual result and set a baseline for future studies on author productivity of LIS open access journals.

The publication data of selected ten LIS open access journals pertain to authorship, citations were downloaded from the Scopus database and analysed using bibliometric indicators like authorship pattern, collaborative index (CI), degree of collaboration (DC), collaborative coefficient (CC) and citation counts. This study has applied Lotka’s inverse square law to assess authors’ productivity pattern of LIS open access journals and further Kolmogorov-Smirnov (K-S) goodness-of-fit test applied for testing of observed and expected author productivity data.

Inferences were drawn for the set objectives on authorship pattern, collaboration trend and authors’ productivity pattern of LIS open access journals covered in this study. The single authorship pattern is dominant in LIS open access journals covered in this study. The CI, DC and CC are found to be 1.95, 0.47 and 0.29, respectively. The expected values as per Lotka’s law (n = −2) significantly vary from the observed values as per the chi-square test and K-S goodness-of-fit test. Hence, this study does not adhere to Lotka’s inverse square law of scientific productivity.

Researchers may find an idea about the authors’ productivity patterns of LIS open access journals. This study has used the K-S goodness-of-fit test and the chi-square test to validate the authors’ productivity data. The inferences found out from this study will be a baseline for future research on author productivity of LIS open access journals.

This study is significant from the viewpoint of the growing research on open access journals in the field of LIS and to identify the authorship pattern, collaboration trend and author productivity pattern of such journals.

The health and environmental hazards associated with synthetic dyes have led to a revival of natural dyes that are non-toxic, environmentally benign and coupled with various functions. The study aims to investigate and develop the potentiality of a popular herb called Chromolaena odorata (C. odorata) as a sustainable and stable dyestuff in textiles.

Natural colorant extracted from C. odorata leaves is used to dye the worsted fabric, which is one of the premier end-use of wool in fashion, via the padding method associated with pre-, simultaneous and post-mordanting with chitosan, tannic acid and copper sulfate pentahydrate. The effects of extraction, dyeing and mordanting processes on fabric’s color strength K/S and color difference ΔE_CMC are investigated via International Commission on Illumination’s L*a*b* color space, Fourier transform infrared spectroscopy, scanning electron microscope, color fastness to washing, rubbing, perspiration and light.

The results obtained indicate extraction with ethanol 90% with a solid/liquid ratio of 1:5 within 1 h, and coloration with a liquor ratio of 1:5 (pH 5) within 2 h under padding pressure of 0.3 MPa are the most effective for coloring worsted fabric.

The C. odorata’s application as a highly effective dyestuff possessing good colorimetric effectiveness has expanded this herb's economic potential, contributing partly to economic growth and adding value to wool in global supply chain.

C. odorata dyestuff has prevailed over other natural colorants because of its impressive color fastness against washing, rubbing, perspiration and especially color stability for pH change.

The paper aims to investigate the feasibility of developing natural dyes from the barks of Araucaria columnaris and leaves of Macaranga peltata, Averrhoa bilimbi. The paper also deals with the application of natural dyes in textile coloration.

Dye extraction was carried out using the aqueous method. The dyeability of the aqueous extract was assessed on cotton, silk and polyester yarns using different mordants (alum, acetic acid, CuSO₄, lemon juice) and without mordant. UV–Visible spectral analysis and pH of different natural dyes were determined. Percent absorption, K/S values, CIELab values and fastness properties of the selected dyed yarns were also assessed.

The percentage values for dye exhaustion differed with various mordants. The K/S values were found to be influenced by the addition of mordants. Different hues were obtained with the usage of different mordants. Fastness results exhibited good to very good grades.

The effective application of aqueous method of dye extraction in the study avoids solvent toxicity. The current results proved that the dyeing could be achieved at room temperature for different yarns (cotton, silk, polyester). At present, no report exists in the literature of research work on the extraction of natural dyes from the leaves of M. peltata, A. bilimbi and their dyeing potential on cotton, silk and polyester.

The present work offers new environment-friendly dye as well as simple dyeing method. Barks and leaves are promising sources of dye. Enormous availability of barks and leaves avoids the exploitation of the plant parts for the extraction of natural dyes.

The important feature of this study was the effective dyeing of natural and synthetic fibers at room temperature. The novel sources of natural dyes would contribute significantly to the existing knowledge of dyeing, and the natural dyes reduce the environmental impact of synthetic dyes.

In today’s digital era, data pertaining to scientific research have attracted considerable attention of researchers. Data of scientific publications can be modeled in the form of networks such as citation networks, co-citation networks, collaboration networks, and others. Identification and ranking of important nodes in such networks is useful in many applications, such as finding most influential papers, most productive researchers, pattern of citation, and many more. The paper aims to discuss this issue.

A number of methods are available in literature for node ranking, and K-shell decomposition is one such method. This method categorizes nodes in different groups based on their topological position. The shell number of a node provides useful insights about the node’s importance in the network. It has been found that shells produced by the K-shell method need to be further refined to quantify the influence of the nodes aptly. In this work, a method has been developed, which ranks nodes by taking the core(s) as the origin and second-order neighborhood of a node as its immediate sphere of influence.

It is found that the performance of the proposed technique is either comparable or better than other methods in terms of correctness and accuracy. In case of assigning different ranks to nodes, the performance of the proposed technique is far more superior to existing methods. The proposed method can be used to rank authors, research articles, and fields of research.

The proposed method ranks nodes by their global position in a network as well as their local sphere of information. It leads to better quantification of a node’s impact. This method is found to be better in terms of accuracy and correctness. In case of assigning different ranks to nodes, the performance of the proposed technique is far more superior to existing methods.

The purpose of this paper is to propose a system with the highest discriminatory power by selecting an indicator system based on the K–S test according to the unique circumstances of small enterprises.

The proposed method relies on calculating the K–S test statistical magnitude of D iteratively to reach a system with the maximum discriminatory power.

The empirical results, demonstrated using 3,045 small businesses from a Chinese bank, show that credit rating system should focus on the indicator system’s discriminatory power rather than a single indicator’s discriminatory power, because the interaction between indicators affects the discriminatory power of the system.

The proposed method creates a credit rating system with the highest discriminatory power, rather than its indicators, which is a more reasonable and novel approach to credit rating.

The approach is unique because the final system will have high discriminatory power and has excellent potential for decision support. The authors believe that this contribution is theoretically and practically relevant because credit rating for small business is especially difficult and complicated.

Porosity is one of the most important properties of the textile substrate. It can influence the comfort of a garment by affecting its breathability and thermal conductivity. During the process of dyeing, the dye liquor comes in contact with the substrate; the absorption of the dye liquor into the substrate will be dependent on its porosity. The concept of porosity between the yarns of fabric is a common phenomenon; however, the porosity between the fibres in the yarn can also influence the dyeing behaviour of the fabric.

In this research, ring and rotor yarns of 25/s and 30/s counts are considered as textile substrates. The porosity of yarns was determined theoretically and experimentally using the image analysis method.

It was found that theoretical porosity is independent of the yarn manufacturing method. In addition, 30/s yarn was more porous as compared with 25/s yarn having a higher pore area. Rotor yarns had higher porosity, dye fixation and K/S as compared with ring yarns. Dyeing behaviour was also dependent on the count of yarn. Specifically, 30/s yarns have higher dye fixation as compared with 25/s yarns. However, 25/s yarns were dyed with deeper shades showing higher K/S values. Also, 25/s yarns are coarser than 30/s yarns having higher diameters and cross-sectional area, thus resulting in deeper shades and higher K/S values.

This novel technique is based on the comparative study of the porosity of various types of yarns using the image analysis technique. This investigation shows that the porosity between the fibres in the yarn can also influence the dyeing behaviour of the yarn.