Segmentation of defects in textile fabric with robust texture representation and total variation

2020 ◽  
Vol 32 (6) ◽  
pp. 813-823
Author(s):  
Jian Zhou ◽  
Jianli Liu
Keyword(s):  
Total Variation ◽  
Dictionary Learning ◽  
Inspection System ◽  
Content Type ◽  
Robust Representation ◽  
Textile Fabrics ◽  
Human Eyes ◽  
Textile Fabric ◽  
Critical Process ◽  
Selection Of

PurposeVisual quality control on raw textile fabrics is a vital process in weaving factories to ensure their exterior quality (visual defects or imperfection) satisfying customer requirements. Commonly, this critical process is manually conducted by human inspectors, which can hardly provide a fast and reliable inspection results due to fatigue and subjective errors. To meet modern production needs, it is highly demanded to develop an automated defect inspection system by replacing human eyes with computer vision.Design/methodology/approachAs a structural texture, fabric textures can be effectively represented by a linearly summation of basic elements (dictionary). To create a robust representation of a fabric texture in an unsupervised manner, a smooth constraint is imposed on dictionary learning model. Such representation is robust to defects when using it to recover a defective image. Thus an abnormal map (likelihood of defective regions) can be computed by measuring similarity between recovered version and itself. Finally, the total variation (TV) based model is built to segment defects on the abnormal map.FindingsDifferent from traditional dictionary learning method, a smooth constraint is introduced in dictionary learning that not only able to create a robust representation for fabric textures but also avoid the selection of dictionary size. In addition, a TV based model is designed according to defects' characteristics. The experimental results demonstrate that (1) the dictionary with smooth constraint can generate a more robust representation of fabric textures compared to traditional dictionary; (2) the TV based model can achieve a robust and good segmentation result.Originality/valueThe major originality of the proposed method are: (1) Dictionary size can be set as a constant instead of selecting it empirically; (2) The total variation based model is built, which can enhance less salient defects, improving segmentation performance significantly.

Estimation of fabric opacity by scanner

Sensor Review ◽  
2014 ◽  
Vol 34 (4) ◽  
pp. 404-409
Author(s):  
Abbas Hajipour ◽  
Ali Shams Nateri ◽  
Alireza Sadr Momtaz
Keyword(s):  
Textile Industry ◽  
Polynomial Regression ◽  
Low Cost ◽  
Color Space ◽  
Simple Method ◽  
Content Type ◽  
Textile Fabrics ◽  
Order Polynomial ◽  
Textile Fabric ◽  
Fourth Order Polynomial

Purpose – This study aimed to use a scanner as a low-cost method for measuring the opacity of textile fabric. Textile fabrics must have specific ranges of opacity according to their uses for shirting, curtaining, etc. In this way, opacity is an important property in the textile industry. Conventionally, textile opacity is estimated using a spectrophotometer, which is an expensive method. Design/methodology/approach – In this study a scanner was used as a low-cost method for measuring the opacity of textile fabric. The opacity was estimated by using red, green and blue (RGB) parameters of images of fabric against white and black background. Findings – The accuracy of opacity estimation was improved by converting RGB into several color spaces. The best opacity estimation was obtained by using the XYZ color space. In addition, using a regression method, the best estimation was obtained by using a fourth-order polynomial regression with the LSLM color space. Originality/value – The opacity of fabric has been measured by spectrophotometer, but in this study, the opacity of fabric was measured by scanner as a low cost device and also with novel and simple method. This method achieved acceptable accuracy for opacity estimation. The obtained result is comparable with spectrophotometer results.

Flexible biosensor using inkjet printing of silver nanoparticles

Sensor Review ◽  
2014 ◽  
Vol 34 (4) ◽  
pp. 360-366 ◽  
Author(s):  
Zahra Abadi ◽  
Vahid Mottaghitalab ◽  
Mansour Bidoki ◽  
Ali Benvidi
Keyword(s):  
Silver Nanoparticles ◽  
Inkjet Printing ◽  
Design Methodology ◽  
Electrochemical Sensors ◽  
Flexible Substrate ◽  
Paper Substrate ◽  
Content Type ◽  
Textile Fabrics ◽  
Textile Fabric

Purpose – The purpose of this paper is to present a sophisticated methodology for inkjet printing of silver nanoparticles (AgNPs) in the range of 80-200 nm on different flexible substrate. AgNPs was chemically deposited by ejection of silver nitrate and ascorbic acid solutions onto different substrates such as paper and textile fabrics. The fabricated pattern was used to employ as electrode for electrochemical sensors. Design/methodology/approach – The morphology of deposited AgNPs was characterized by means of scanning electron microscopy. Moreover, conductivity and electrochemical behavior were identified, respectively, using four probe and cyclic voltammetry techniques. Acquired image shows a well-defined shape and size for the deposited AgNP. Findings – The conductivity of the paper substrate after printing process reached 5.54 × 105 S/m. This printed electrode shows a sharp electrochemical response for early determination of glucose. The proposed electrode provides a new alternative to develop electrochemical sensors using AgNPs chemically deposited on paper and textile fabric surfaces.

PROMETHEE-based ranking of project managers based on the five personality traits

Kybernetes ◽  
2019 ◽  
Vol 49 (4) ◽  
pp. 1083-1102
Author(s):  
Georgios N. Aretoulis ◽  
Jason Papathanasiou ◽  
Fani Antoniou
Keyword(s):  
Personality Traits ◽  
Questionnaire Survey ◽  
Multicriteria Decision Making ◽  
Project Managers ◽  
Preference Ranking ◽  
Infrastructure Projects ◽  
Public Infrastructure ◽  
Content Type ◽  
The One ◽  
Selection Of

Purpose This paper aims to rank and identify the most efficient project managers (PMs) based on personality traits, using Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE) methodology. Design/methodology/approach The proposed methodology relies on the five personality traits. These were used as the selection criteria. A questionnaire survey among 82 experienced engineers was used to estimate the required weights per personality trait. A second two-part questionnaire survey aimed at recording the PMs profile and assess the performance of personality traits per PM. PMs with the most years of experience are selected to be ranked through Visual PROMETHEE. Findings The findings suggest that a competent PM is the one that scores low on the “Neuroticism” trait and high especially on the “Conscientiousness” trait. Research limitations/implications The research applied a psychometric test specifically designed for Greek people. Furthermore, the proposed methodology is based on the personality characteristics to rank the PMs and does not consider the technical skills. Furthermore, the type of project is not considered in the process of ranking PMs. Practical implications The findings could contribute in the selection of the best PM that maximizes the project team’s performance. Social implications Improved project team communication and collaboration leading to improved project performance through better communication and collaboration. This is an additional benefit for the society, especially in the delivery of public infrastructure projects. A lot of public infrastructure projects deviate largely as far as cost and schedule is concerned and this is an additional burden for public and society. Proper project management through efficient PMs would save people’s money and time. Originality/value Identification of the best PMbased on a combination of multicriteria decision-making and psychometric tests, which focus on personality traits.

Does knowing overcome wanting? The impact of consumer knowledge and materialism upon credit card selection with young consumers

2015 ◽  
Vol 16 (1) ◽  
pp. 50-70 ◽  
Author(s):  
Jakob Cakarnis ◽  
Steve Peter D'Alessandro
Keyword(s):  
Comparative Study ◽  
Survey Research ◽  
Credit Card ◽  
Design Methodology ◽  
Credit Cards ◽  
Consumer Knowledge ◽  
Content Type ◽  
Young Professionals ◽  
The Impact ◽  
Selection Of

Purpose – This paper investigates the determinants of credit card use and misuse by student and young professionals. Critical to the research is the impact of materialism and knowledge on selection of the appropriate credit card. Design/methodology/approach – This study uses survey research and partial least squares to investigate credit card behaviors of students versus young professionals. Findings – In a comparative study of young professionals and students, it was found that consumer knowledge, as expected, leads to better consumer selection of credit cards. Materialism was also found to increase the motivation for more optimal consumer outcomes. For more experienced consumers, such as young professionals, it was found that despite them being more knowledgeable, they were more likely to select a credit card based on impulse. Originality/value – This paper examines how materialism may in fact encourage some consumers to make better decisions because they are more motivated to develop better knowledge. It also shows how better credit card selection may inhibit impulse purchasing.

Reflections on the theme issue outcomes

2016 ◽  
Vol 8 (4) ◽  
pp. 504-510
Author(s):  
Gunjan M. Sanjeev ◽  
Richard Teare
Keyword(s):  
Customer Service ◽  
Hospitality Industry ◽  
Theme Issue ◽  
Policy Makers ◽  
Content Type ◽  
Starting Point ◽  
Cost Competitiveness ◽  
Hotel Sector ◽  
Practical Implications ◽  
Selection Of

Purpose The paper aims to profile the theme issue of Worldwide Hospitality and Tourism Themes titled “How is the need for innovation being addressed by the Indian hospitality industry?” with reference to the experiences of the theme editor, contributors from the industry and academia and the theme issue outcomes. Design/methodology/approach The paper uses structured questions to enable the theme editor to reflect on the rationale for their theme issue question, the starting-point, the selection of the writing team and material and the editorial process. Findings It highlights recent innovations that have taken place in the Indian hospitality industry especially in the areas of customer service, cost competitiveness, culinary management, revenue management and technology. Practical implications As hotel sector investment in India intensifies, this theme issue will be of interest to hoteliers, policy makers, analysts and others interested in the role that innovation can play in helping to facilitate differentiation between competing hotel products and services. Originality/value There is limited literature available on industry innovations in the Indian context. All the papers in this theme issue were written after several cycles of interaction between academics and practitioners and so they incorporate real–time, relevant and contemporary data.

Using rational and emotional appeals in online advertisements for Muslim customers

2014 ◽  
Vol 5 (1) ◽  
pp. 97-124 ◽  
Author(s):  
Mehdi Behboudi ◽  
Hossein Vazifehdoust ◽  
Kobra Najafi ◽  
Mina Najafi
Keyword(s):  
Latent Variables ◽  
Online Advertising ◽  
Product Involvement ◽  
Content Type ◽  
Factors Affecting ◽  
Advertising Appeals ◽  
Emotional Appeals ◽  
Advertising Strategies ◽  
Larger Sample ◽  
Selection Of

Purpose – The purpose of this study is to verify the factors affecting the use of emotional and rational appeals in online advertising among Muslim customers in Iran. Design/methodology/approach – By reviewing the literature of advertising appeals and developing a comprehensive theoretical model, the effect of rational and emotional appeals on online advertising was examined. Expert questionnaire was administered to verify the validity of collected features. The Student's t-test was utilized to analyze the data collected from 271 participants. Findings – Five latent variables, namely user type, product involvement, e-lifestyle, advertising strategies, and internet motives were examined to explain factors affecting online advertising appeals among Muslim customers in Iran. It was found that “advertising strategies” and “user type” are the most effective factors influencing Muslims customers in developing an online advertising campaign. Research limitations/implications – The sample of this study was Iranian experts and it is necessary to conduct a survey with a larger sample size. Originality/value – This study provides insights into factors affecting the selection of emotional and rational appeals in Muslims countries. Moreover, it reports the primary columns of online advertising appeals.

Preventive maintenance scheduling using analysis of variance-based ant lion optimizer

2018 ◽  
Vol 15 (2) ◽  
pp. 254-272 ◽  
Author(s):  
Umamaheswari Elango ◽  
Ganesan Sivarajan ◽  
Abirami Manoharan ◽  
Subramanian Srikrishna
Keyword(s):  
Analysis Of Variance ◽  
Heuristic Algorithm ◽  
Heuristic Algorithms ◽  
Statistical Tests ◽  
Population Based ◽  
Maintenance Scheduling ◽  
Content Type ◽  
Ant Lion Optimizer ◽  
Ant Lion ◽  
Selection Of

Purpose Generator maintenance scheduling (GMS) is an essential task for electric power utilities as the periodical maintenance activity enhances the lifetime and also ensures the reliable and continuous operation of generating units. Though numerous meta-heuristic algorithms have been reported for the GMS solution, enhancing the existing techniques or developing new optimization procedure is still an interesting research task. The meta-heuristic algorithms are population based and the selection of their algorithmic parameters influences the quality of the solution. This paper aims to propose statistical tests guided meta-heuristic algorithm for solving the GMS problems. Design/methodology/approach The intricacy characteristics of the GMS problem in power systems necessitate an efficient and robust optimization tool. Though several meta-heuristic algorithms have been applied to solve the chosen power system operational problem, tuning of their control parameters is a protracting process. To prevail over the previously mentioned drawback, the modern meta-heuristic algorithm, namely, ant lion optimizer (ALO), is chosen as the optimization tool for solving the GMS problem. Findings The meta-heuristic algorithms are population based and require proper selection of algorithmic parameters. In this work, the ANOVA (analysis of variance) tool is proposed for selecting the most feasible decisive parameters in algorithm domain, and the statistical tests-based validation of solution quality is described. The parametric and non-parametric statistical tests are also performed to validate the selection of ALO against the various competing algorithms. The numerical and statistical results confirm that ALO is a promising tool for solving the GMS problems. Originality/value As a first attempt, ALO is applied to solve the GMS problem. Moreover, the ANOVA-based parameter selection is proposed and the statistical tests such as Wilcoxon signed rank and one-way ANOVA are conducted to validate the applicability of the intended optimization tool. The contribution of the paper can be summarized in two folds: the ANOVA-based ALO for GMS applications and statistical tests-based performance evaluation of intended algorithm.

scholarly journals New Recombinant Mycobacterium bovis BCG Expression Vectors: Improving Genetic Control over Mycobacterial Promoters

2016 ◽  
Vol 82 (8) ◽  
pp. 2240-2246 ◽  
Author(s):  
Alex I. Kanno ◽  
Cibelly Goulart ◽  
Henrique K. Rofatto ◽  
Sergio C. Oliveira ◽  
Luciana C. C. Leite ◽  
...  
Keyword(s):  
Mycobacterium Bovis ◽  
Fluorescent Protein ◽  
Vaccine Development ◽  
Expression Vectors ◽  
Content Type ◽  
Expression Levels ◽  
Wide Range ◽  
Mycobacteriophage L5 ◽  
Green Fluorescent ◽  
Selection Of

ABSTRACTThe expression of many antigens, stimulatory molecules, or even metabolic pathways in mycobacteria such asMycobacterium bovisBCG orM. smegmatiswas made possible through the development of shuttle vectors, and several recombinant vaccines have been constructed. However, gene expression in any of these systems relied mostly on the selection of natural promoters expected to provide the required level of expression by trial and error. To establish a systematic selection of promoters with a range of strengths, we generated a library of mutagenized promoters through error-prone PCR of the strong PL5promoter, originally from mycobacteriophage L5. These promoters were cloned upstream of the enhanced green fluorescent protein reporter gene, and recombinantM. smegmatisbacteria exhibiting a wide range of fluorescence levels were identified. A set of promoters was selected and identified as having high (pJK-F8), intermediate (pJK-B7, pJK-E6, pJK-D6), or low (pJK-C1) promoter strengths in bothM. smegmatisandM. bovisBCG. The sequencing of the promoter region demonstrated that it was extensively modified (6 to 11%) in all of the plasmids selected. To test the functionality of the system, two different expression vectors were demonstrated to allow corresponding expression levels of theSchistosoma mansoniantigen Sm29 in BCG. The approach used here can be used to adjust expression levels for synthetic and/or systems biology studies or for vaccine development to maximize the immune response.

Design and topological optimization of rear pressure bulkhead for a typical aircraft

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Marshal Thakran ◽  
Meenakshi ◽  
Jitender Sharma ◽  
Charles Gilbert Martin
Keyword(s):  
Numerical Analysis ◽  
Significant Influence ◽  
Design Methodology ◽  
Structural Integrity ◽  
Topological Optimization ◽  
Content Type ◽  
Iterative Design ◽  
Practical Implications ◽  
Insight Into ◽  
Selection Of

Purpose The purpose of this paper is to evaluate the model of a rear pressure bulkhead with different design optimizations to meet the pressurized cabin requirements of an aircraft. Design/methodology/approach This paper presents the results of the static analysis of a dome-shaped rear pressure bulkhead model designed in Catia-v5. Numerical analysis of model meshed in hyper-mesh and solved using Opti-Struct for iterative design optimizations. Findings All the iterative models are analyzed at 9 Psi. Rear pressure bulkhead designed with L-section stringer shows better results than the model optimized with T-section stringer for the same thickness. The model optimized with L-shaped stinger also reduces the weight of the bulkhead without affecting the structural integrity. Practical implications It has been concluded in this paper that the selection of specific shapes of the stringers shows a significant influence on weight reduction. Originality/value This paper provides a topical, technical insight into the design and development of a rear pressure bulkhead. It also outlines the future development of dome-shaped rear pressure bulkhead.

Artificial intelligence-based automatic visual inspection system for built heritage

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lukman E. Mansuri ◽  
D.A. Patel
Keyword(s):  
Artificial Intelligence ◽  
Visual Inspection ◽  
Image Data ◽  
Inspection System ◽  
Data Set ◽  
Web Based ◽  
Content Type ◽  
Built Heritage ◽  
Automatic Visual Inspection ◽  
Inspection Systems

PurposeHeritage is the latent part of a sustainable built environment. Conservation and preservation of heritage is one of the United Nations' (UN) sustainable development goals. Many social and natural factors seriously threaten heritage structures by deteriorating and damaging the original. Therefore, regular visual inspection of heritage structures is necessary for their conservation and preservation. Conventional inspection practice relies on manual inspection, which takes more time and human resources. The inspection system seeks an innovative approach that should be cheaper, faster, safer and less prone to human error than manual inspection. Therefore, this study aims to develop an automatic system of visual inspection for the built heritage.Design/methodology/approachThe artificial intelligence-based automatic defect detection system is developed using the faster R-CNN (faster region-based convolutional neural network) model of object detection to build an automatic visual inspection system. From the English and Dutch cemeteries of Surat (India), images of heritage structures were captured by digital camera to prepare the image data set. This image data set was used for training, validation and testing to develop the automatic defect detection model. While validating this model, its optimum detection accuracy is recorded as 91.58% to detect three types of defects: “spalling,” “exposed bricks” and “cracks.”FindingsThis study develops the model of automatic web-based visual inspection systems for the heritage structures using the faster R-CNN. Then it demonstrates detection of defects of spalling, exposed bricks and cracks existing in the heritage structures. Comparison of conventional (manual) and developed automatic inspection systems reveals that the developed automatic system requires less time and staff. Therefore, the routine inspection can be faster, cheaper, safer and more accurate than the conventional inspection method.Practical implicationsThe study presented here can improve inspecting the built heritages by reducing inspection time and cost, eliminating chances of human errors and accidents and having accurate and consistent information. This study attempts to ensure the sustainability of the built heritage.Originality/valueFor ensuring the sustainability of built heritage, this study presents the artificial intelligence-based methodology for the development of an automatic visual inspection system. The automatic web-based visual inspection system for the built heritage has not been reported in previous studies so far.

Sign in / Sign up

Export Citation Format

Share Document