Application of artificial intelligence techniques in textile wastewater decolorisation fields : A systematic and citation network analysis review / Senbiao Liu in COLORATION TECHNOLOGY, Vol. 138, N° 2 (04/2022)  

[article]  inCOLORATION TECHNOLOGY > Vol. 138, N° 2 (04/2022) . - p. 117-136 Titre : Application of artificial intelligence techniques in textile wastewater decolorisation fields : A systematic and citation network analysis review Type de document : texte imprimé Auteurs : Senbiao Liu, Auteur ; Chris K. Y. Lo, Auteur ; Chi-Wai Kan, Auteur Année de publication : 2022 Article en page(s) : p. 117-136 Note générale : Bibliogr. Langues : Anglais (eng) Catégories : Comptage Décoloration Eaux usées -- Décontamination Eaux usées -- Epuration Intelligence artificielle Publications scientifiques Réseaux neuronaux (informatique) Index. décimale : 667.3 Teinture et impression des tissus Résumé : This study reviewed 155 journal articles to examine how artificial intelligence techniques are being applied in textile coloration and related fields. Distribution of the reviewed articles was assessed in terms of the type of journals, year of publication, methods, and research background. Based on the citation network analysis method, an objective approach, CitNetExplorer and VOSviewer are used to identify the clusters. It is found that artificial intelligence techniques are mainly three-layer artificial neural networks with different designs, which are mainly used in textile wastewater decolorisation fields, including wastewater treatment and colour fading, such as colour prediction and real-time monitoring of textile wastewater, dye removal efficiency, and dye degradation. Finally, the future research direction and limitations of this article are put forward. Note de contenu : - METHODOLOGY - DESCRIPTIVE STATISTICS : Distribution of articles by journal - Distribution of articles by year of publication - Distribution of articles by region - Distribution of methodologies used in textile coloration-related fields - Research fields while using artificial intelligence techniques - CLASSIFICATION OF RESEARCH DOMAINS - MAIN PATH ANALYSIS OF THE MAJOR RESEARCH DOMAINS - FUTURE DEVELOPMENT - LIMITATIONS DOI : https://doi.org/10.1111/cote.12589 En ligne : https://onlinelibrary.wiley.com/doi/epdf/10.1111/cote.12589 Format de la ressource électronique : Pdf Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=37843 [article]

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Counting craters / Julian Rixrath in EUROPEAN COATINGS JOURNAL (ECJ), (01-02/2023)  

[article]  inEUROPEAN COATINGS JOURNAL (ECJ) > (01-02/2023) . - p. 38-43 Titre : Counting craters : A digital assistant for quantifying coating defects Type de document : texte imprimé Auteurs : Julian Rixrath, Auteur ; Philipp Isken, Auteur Année de publication : 2023 Article en page(s) : p. 38-43 Note générale : Bibliogr. Langues : Anglais (eng) Catégories : Analyse numérique Antimousse Comptage Cratère (défaut) Revêtements -- Analyse:Peinture -- Analyse Revêtements -- Défauts:Peinture -- Défauts Index. décimale : 667.9 Revêtements et enduits Résumé : Routine laboratory work is often time-consuming and can limit the scope for innovation. Such work includes analysing and evaluating coated samples for the purpose of selecting ideal formulations. A digital assistant for complex evaluations would increase the efficiency of these tasks and enable coating defects to be quantified objectively. Note de contenu : - Sustainability driving innovation - Manual evaluations are subjective - Computer quantification of defects takes seconds - Practical example : defoaming of architectural coatings - Eliminating foam effectively : striking the right balance - Digital detection - Comparison of detection results with manual evaluation - An everyday laboratory example - Computer vision boosts efficiency - Digitisation and sustainability go hand in hand En ligne : https://drive.google.com/file/d/1YI59J-BhoSO2vGTZBRMywROMKvSDwOZl/view?usp=drive [...] Format de la ressource électronique : Pdf Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=38737 [article]

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Determination of number of threads per unit length of textile woven fabrics - DIN EN 1049-2 / Deutsches Institut für Normung (Berlin, Germany) / Berlin [Germany] : Deutsches Institut für Normung (DIN) (1994)

Accompagne Textiles. Woven fabrics - Construction - Methods of analysis - Part 2 : Determination of number of threads per unit length - International Standard ISO 7211/2 / International Organization for Standardization (Genève, Suisse) / Geneve [Switzerland] : International Organization for Standardization (ISO) (1984) Titre : Determination of number of threads per unit length of textile woven fabrics - DIN EN 1049-2 Type de document : texte imprimé Auteurs : Deutsches Institut für Normung (Berlin, Germany), Auteur Editeur : Berlin [Germany] : Deutsches Institut für Normung (DIN) Année de publication : 1994 Importance : 8 p. Présentation : ill. Format : 30 cm Prix : 67,50 E Note générale : ISO 7211-2 : 1984, modified Langues : Anglais (eng) Langues originales : Allemand (ger) Catégories : Comptage Essais (technologie) Fil Textiles et tissus -- Normes Tissés Index. décimale : 677 Textiles Résumé : This part of ISO 7211 specifies three methods for the determination of the number of threads per centimetre in woven fabrics. Any of the three methods may be used, the choice depending on the character of the fabric. However, in cas of dispute method 1 is recommended. Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=30036

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Development and qualification of a machine learning algorithm for automated hair counting in INTERNATIONAL JOURNAL OF COSMETIC SCIENCE, Vol. 43, N° S1 (11/2021)  

[article]  inINTERNATIONAL JOURNAL OF COSMETIC SCIENCE > Vol. 43, N° S1 (11/2021) . - p. 34-41 Titre : Development and qualification of a machine learning algorithm for automated hair counting Type de document : document électronique Année de publication : 2021 Article en page(s) : p. 34-41 Note générale : Bibliogr. Langues : Anglais (eng) Catégories : Cheveux -- Comptage Cheveux -- Croissance Cheveux -- Soins et hygiène Comptage Imagerie (technique) Statistique Index. décimale : 668.5 Parfums et cosmétiques Résumé : - Objective : Determining the amount of hair on the scalp has always been an important metric of patient satisfaction for hair growth and hair retention technologies. While simple in concept, this measurement is a difficult, resource intensive task for the dermatologist and the research scientist. Specifically, counting and measuring hair in phototrichogram images is very time consuming and labour intensive. Due to cost, often only a fraction of available images is manually analysed. There is a need for an automated method that can significantly increase speed and throughput while reducing the cost of counting and measuring hair in phototrichogram images. - Methods : Recent advances in machine learning and deep convolutional neural networks (deep learning) have led to a revolution in the analysis of image, video, speech, text and other sensor data. Image diagnostics have seen remarkable improvements with completely automated methods outperforming both human experts and human-engineered analysis methods. Deep learning methods can also provide speed and cost benefits. To enable use of a deep learning, we created a data set of 288 manually annotated phototrichogram images with marked location and length of each hair (the training dataset). We designed a custom neural network architecture and custom image processing algorithms to best utilize the available training data and to maximize performance for hair counting and length measurement. The performance of the algorithm was qualified by comparing hair count and length measurements to an independent ground truth method, the semi-manual Canfield's Hair Metrix method. - Results : Leveraging deep neural networks, we have developed capability to apply machine learning to reduce the time needed to acquire data from phototrichograms of patients’ scalp from months to seconds. Our algorithm enables fast and fully automated hair counting and length measurement. The algorithm shows high agreement with human manually assisted analysis (ground truth). - Conclusions : We have trained and deployed an algorithm utilizing this technology and have demonstrated the reproducibility, accuracy and speed of this algorithm that, once deployed, requires little to no recurring cost or manual intervention for its operation. The method allows fast analysis of large number of images, reducing study cost and significantly reducing study analysis time. Note de contenu : - Study design and statistical analysis - Imaging area preparation - Image capture - Dataset selection - Creation of training labels & training approach - Automated hair detection method - Image capture for treatment benefit confirmation - Qualification / acceptance criteria - Table 1 : Confirmation of ability to detect treatment benefits for hair count En ligne : https://drive.google.com/file/d/1ffvEGbZIZECRgmeLo4cRVukZvv4ruIBF/view?usp=shari [...] Format de la ressource électronique : Pdf Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=36878 [article]

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Development of quantitative estimation of hair follicle patterns for leather surface by point pattern analysis / Satoru Dohshi in JOURNAL OF THE SOCIETY OF LEATHER TECHNOLOGISTS & CHEMISTS (JSLTC), Vol. 97, N° 1 (01-02/2013)  

[article]  inJOURNAL OF THE SOCIETY OF LEATHER TECHNOLOGISTS & CHEMISTS (JSLTC) > Vol. 97, N° 1 (01-02/2013) . - p. 1-4 Titre : Development of quantitative estimation of hair follicle patterns for leather surface by point pattern analysis Type de document : texte imprimé Auteurs : Satoru Dohshi, Auteur ; Akira Okumura, Auteur ; Hisayoshi Shiozaki, Auteur Année de publication : 2013 Article en page(s) : p. 1-4 Note générale : Bibliogr. Langues : Anglais (eng) Catégories : Comptage Cuirs et peaux -- Analyse Cuirs et peaux de chèvres Follicule pileux Index. décimale : 675 Technologie du cuir et de la fourrure Résumé : The quantitative estimation of hair follicle patterns for a leather surface was investigated by point pattern analysis for use a possible method for correct identification of leather materials. The L-function was used as a point pattern analysis. In the case of goatskins, the L-function correctly indicated the distribution patterns of guard hair follicles. Moreover, it was found that the density of hair follicles and the microscope magnification affect could be estimated quantitatively by point pattern analysis with optimum conditions. This result suggested that leather materials could be identified objectively by this method. Note de contenu : - EXPERIMENTAL PROCEDURE : Leather sample - Observation by microscope - Point pattern analysis - RESULTS AND DISCUSSION : L-function for goatskin - Effect of individual differences - Effect of the microscope observation method - Effect of the microscope magnification En ligne : https://drive.google.com/file/d/12W4HD1IXnSkY3_vxFFt3W5L-o0vYmCR9/view?usp=drive [...] Format de la ressource électronique : Pdf Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=17446 [article]

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Plastiques renforcés de verre textile. Détermination de la teneur en vide. Méthodes par perte au feu, par désintégration mécanique et par comptage statistique - Norme NF EN ISO 7822 / Association Française de Normalisation (Paris) / Saint-Denis La Plaine : Association Française de Normalisation (AFNOR) (1999)

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Quantitative estimation of hair follicle patterns for leather surface using K-function (L-fonction) Method (i): influence of individual and location differences for goatskins on estimation of L-function / Satoru Dohshi in JOURNAL OF THE SOCIETY OF LEATHER TECHNOLOGISTS & CHEMISTS (JSLTC), Vol. 97, N° 4 (07-08/2013)  

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Quantitative estimation of hair follicte patterns for leather surface using K-function (L-function) method (2) : Influence of individual and location differences for sheepskins on estimation of L-function / Satoru Dohshi in JOURNAL OF THE SOCIETY OF LEATHER TECHNOLOGISTS & CHEMISTS (JSLTC), Vol. 97, N° 5 (09-10/2013)  

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Textiles. Determination of twist in yarns - Direct counting method - Norme NF EN ISO 2061 / Association Française de Normalisation (Paris) / Saint-Denis La Plaine : Association Française de Normalisation (AFNOR) (2015)

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Textiles. Knitted fabrics : Determination of number of stitches per unit length and unit area - Norme NF EN14971 / Association Française de Normalisation (Paris) / Saint-Denis La Plaine : Association Française de Normalisation (AFNOR) (2006)

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Textiles. Woven fabrics - Construction - Methods of analysis - Part 2 : Determination of number of threads per unit length - International Standard ISO 7211/2 / International Organization for Standardization (Genève, Suisse) / Geneve [Switzerland] : International Organization for Standardization (ISO) (1984)

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