D.A. Karras, S.A. Karkanis and B.G. Mertzios
This paper suggests a novel methodology for building robust information processing systems based on wavelets and artificial neural networks (ANN) to be applied either in…
Abstract
This paper suggests a novel methodology for building robust information processing systems based on wavelets and artificial neural networks (ANN) to be applied either in decision‐making tasks based on image information or in signal prediction and modeling tasks. The efficiency of such systems is increased when they simultaneously use input information in its original and wavelet transformed form, invoking ANN technology to fuse the two different types of input. A quality control decision‐making system as well as a signal prediction system have been developed to illustrate the validity of our approach. The first one offers a solution to the problem of defect recognition for quality control systems. The second application improves the quality of time series prediction and signal modeling in the domain of NMR. The accuracy obtained shows that the proposed methodology deserves the attention of designers of effective information processing systems.
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Chris Atkinson, Tillal Eldabi, Ray J. Paul and Athanasia Pouloudi
This paper looks at a number of approaches to health informatics that support decision‐making relevant to the integrated development and management of information systems with…
Abstract
This paper looks at a number of approaches to health informatics that support decision‐making relevant to the integrated development and management of information systems with clinical and managerial practices in healthcare. Its main aim is to explore three such approaches for integrated development, the soft information systems and technologies methodology, participative simulation modelling and stakeholder analysis. A description of the health informatics research and development environment in the UK is given as necessary background to the paper. Organisational and social aspects are examined through these approaches including information and clinical process development, telemedicine, ethical issues of drug use and management, health policies and information management and strategies, tele‐education and modelling structures. In the conclusion the synergies between the three approaches are discussed and some principles are extracted for future research and development in integrated approaches to health informatics research.
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Francisco J. Veredas, Héctor Mesa and Laura Morente
Pressure ulcer is a clinical pathology of localized damage to the skin and underlying tissue caused by pressure, shear, and friction. Diagnosis, treatment and care of pressure…
Abstract
Purpose
Pressure ulcer is a clinical pathology of localized damage to the skin and underlying tissue caused by pressure, shear, and friction. Diagnosis, treatment and care of pressure ulcers involve high costs for sanitary systems. Accurate wound evaluation is a critical task to optimize the efficacy of treatments and health‐care. Clinicians evaluate the pressure ulcers by visual inspection of the damaged tissues, which is an imprecise manner of assessing the wound state. Current computer vision approaches do not offer a global solution to this particular problem. The purpose of this paper is to use a hybrid learning approach based on neural and Bayesian networks to design a computational system to automatic tissue identification in wound images.
Design/methodology/approach
A mean shift procedure and a region‐growing strategy are implemented for effective region segmentation. Color and texture features are extracted from these segmented regions. A set of k multi‐layer perceptrons is trained with inputs consisting of color and texture patterns, and outputs consisting of categorical tissue classes determined by clinical experts. This training procedure is driven by a k‐fold cross‐validation method. Finally, a Bayesian committee machine is formed by training a Bayesian network to combine the classifications of the k neural networks (NNs).
Findings
The authors outcomes show high efficiency rates from a two‐stage cascade approach to tissue identification. Giving a non‐homogeneous distribution of pattern classes, this hybrid approach has shown an additional advantage of increasing the classification efficiency when classifying patterns with relative low frequencies.
Practical implications
The methodology and results presented in this paper could have important implications to the field of clinical pressure ulcer evaluation and diagnosis.
Originality/value
The novelty associated with this work is the use of a hybrid approach consisting of NNs and Bayesian classifiers which are combined to increase the performance of a pattern recognition task applied to the real clinical problem of tissue detection under non‐controlled illumination conditions.
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Manuel Ferreira, Cristina Santos and Joao Monteiro
The purpose of this paper is to propose a set of techniques, in the domain of texture analysis, dedicated to the classification of industrial textures. One of the main purposes…
Abstract
Purpose
The purpose of this paper is to propose a set of techniques, in the domain of texture analysis, dedicated to the classification of industrial textures. One of the main purposes was to deal with a high diversity of textures, including structural and highly random patterns.
Design/methodology/approach
The global system includes a texture segmentation phase and a classification phase. The approach for image texture segmentation is based on features extracted from wavelets transform, fuzzy spectrum and interaction maps. The classification architecture uses a fuzzy grammar inference system.
Findings
The classifier uses the aggregation of features from the several segmentation techniques, resulting in high flexibility concerning the diversity of industrial textures. The resulted system allows on‐line learning of new textures. This approach avoids the need for a global re‐learning of the all textures each time a new texture is presented to the system.
Practical implications
These achievements demonstrate the practical value of the system, as it can be applied to different industrial sectors for quality control operations.
Originality/value
The global approach was integrated in a cork vision system, leading to an industrial prototype that has already been tested. Similarly, it was tested in a textile machine, for a specific fabric inspection, and gave results that corroborate the diversity of possible applications. The segmentation procedure reveals good performance that is indicated by high classification rates, revealing good perspectives for full industrialization.
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Education institutions persist by transforming leadership skills to manage their knowledge resources efficiently as well as enhance the lecturer’s teaching and learning innovation…
Abstract
Purpose
Education institutions persist by transforming leadership skills to manage their knowledge resources efficiently as well as enhance the lecturer’s teaching and learning innovation capabilities. Therefore, the purpose of this study is to investigate whether knowledge management plays a role of mediator between transformational leadership and teaching and learning innovation in teacher education.
Design/methodology/approach
A cross-sectional survey design was used to collect the primary data from 359 teacher educators across Malaysia. Self-administered questionnaires were distributed to all the samples, and the collected data was analysed using structural equation modelling approach.
Findings
The data analysis indicated that knowledge management did not play the role of a mediator in this study because the direct effect of transformational leadership on teaching and learning innovation was stronger than the indirect effect of transformational leadership through knowledge management.
Practical implications
From the aspect of implications on the practice, it was suggested that all lecturers and head of departments attend clinical training and workshops on knowledge management to further understand the knowledge management processes that could enhance the quality of teaching in teacher education institutes.
Originality/value
This study is perhaps the first study to investigate the role of knowledge management as a mediator between transformational leadership and teaching and learning innovation in teacher education.
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Md Anwar Hossain, Sifat Kibria Srijan, Kazi Rashed Rinaz, Siyam Quddus Khan and Ahmed Jalal Uddin
This study aims to analyze the spinning consistency index (SCI) and its impact on yarn quality. It focuses on the relationship between SCI and the final properties of 30 Ne carded…
Abstract
Purpose
This study aims to analyze the spinning consistency index (SCI) and its impact on yarn quality. It focuses on the relationship between SCI and the final properties of 30 Ne carded hosiery yarn. By evaluating key quality parameters, the research seeks to determine how SCI can serve as a predictive tool for optimizing yarn production.
Design/methodology/approach
The study involved producing 30 Ne carded hosiery yarn and rigorously testing its properties using the Uster Evenness Tester-5. Various quality parameters, including neps content, mass irregularity, yarn imperfections and tensile behavior, were evaluated at each processing stage.
Findings
The findings reveal that Type 1 yarn demonstrated a count strength product value approximately 15% higher than the other two types. In addition, it exhibited a CVm% that was 18% lower, highlighting reduced mass variation and enhanced uniformity. Regarding imperfections, Type 1 yarn showed a 25% reduction compared to the other two types, reflecting improved fiber spinnability and overall yarn performance.
Originality/value
This research thoroughly examines SCI’s role in yarn production, highlighting its predictive value for optimizing yarn quality. The study offers valuable insights for textile manufacturers seeking to enhance the efficiency and effectiveness of their spinning processes, ultimately contributing to the development of higher-quality textile products.
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Dimitrios Karkanis and Myrsini Fotopoulou
The purpose of this paper is to identify trade integration and structure effects on bilateral trade between China and its partners, focusing on Chinese merchandise imports during…
Abstract
Purpose
The purpose of this paper is to identify trade integration and structure effects on bilateral trade between China and its partners, focusing on Chinese merchandise imports during the period 1995–2018.
Design/methodology/approach
The methodological approach applied here uses the augmented gravity model to investigate the factors lying behind import intensity, by use of the ordinary least squares (OLS) and Poisson pseudo maximum likelihood (PPML) estimators.
Findings
The findings provide evidence of complementarity between the Chinese demand and the world commodity markets. Free trade agreements between China and third countries seem to gradually lose significance, as the Chinese economy consolidates in world trade. Higher product diversification in export structures of China’s trading partners can become advantageous for facilitating market penetration. Diversification of energy resources, the steady, high demand for infrastructure equipment and more sophisticated consumer products constantly determine the structure of Chinese merchandise imports originating mainly and increasingly from countries with direct access to the Pacific Ocean.
Originality/value
The analytical breakdown of Chinese imports, presented in this paper, adds value to the existing literature with regard to trade structure analysis for China, paving the way for similar research for other developing countries as well.
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Abdelmounaim Lahrech, Anass Faribi, Husam-Aldin N. Al-Malkawi and Kevin Sylwester
The purpose of this paper is to examine the impact of the global financial crisis (GFC) on Morocco’s export performance employing a gravity model framework.
Abstract
Purpose
The purpose of this paper is to examine the impact of the global financial crisis (GFC) on Morocco’s export performance employing a gravity model framework.
Design/methodology/approach
The authors investigate trade flows between Morocco and its 18 major trading partners from 2001 to 2015. The authors employ a trade gravity model using a first-order Taylor approximation of multilateral resistance terms and estimate by OLS and PPML.
Findings
Morocco’s export performance was affected by the GFC. The authors find evidence that the fall in aggregate demand from Morocco’s trading partners, particularly in Europe, led to a fall in its exports. The authors also find that Morocco’s exports are positively correlated with the market size of its partner but negatively associated with distance.
Originality/value
This study contributes to the literature in two distinct ways. First, it examines variables affecting export performance in one of the emerging markets in the Middle East and North Africa region. Second, it assesses empirically whether there is a relationship between the GFC and the decline in Moroccan exports. The study also provides a number of important implications for policy makers and academics.
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Igor Gomes Vidigal, Mariana Pereira de Melo, Adriano Francisco Siqueira, Domingos Sávio Giordani, Érica Leonor Romão, Eduardo Ferro dos Santos and Ana Lucia Gabas Ferreira
This study aims to describe a bibliometric analysis of recent articles addressing the applications of e- noses with particular emphasis on those dealing with fuel-related…
Abstract
Purpose
This study aims to describe a bibliometric analysis of recent articles addressing the applications of e- noses with particular emphasis on those dealing with fuel-related products. Documents covering the general area of e-nose research and published between 1975 and 2021 were retrieved from the Web of Science database, and peer-reviewed articles were selected and appraised according to specific descriptors and criteria.
Design/methodology/approach
Analyses were performed by mapping the knowledge domain using the software tools VOSviewer and RStudio. It was possible to identify the countries, research organizations, authors and disciplines that were most prolific in the area, together with the most cited articles and the most frequent keywords. A total of 3,921 articles published in peer-reviewed journals were initially retrieved but only 47 (1.19%) described fuel-related e-nose applications with original articles published in indexed journals. However, this number was reduced to 38 (0.96%) articles strictly related to the target subject.
Findings
Rigorous appraisal of these documents yielded 22 articles that could be classified into two groups, those aimed at predicting the values of key parameters and those dealing with the discrimination of samples. Most of these 22 selected articles (68.2%) were published between 2017 and 2021, but little evidence was apparent of international collaboration between researchers and institutions currently working on this topic. The strategy of switching energy systems away from fossil fuels towards low-carbon renewable technologies that has been adopted by many countries will generate substantial research opportunities in the prediction, discrimination and quantification of volatiles in biofuels using e-nose.
Research limitations/implications
It is important to highlight that the greatest difficulty in using the e-nose is the interpretation of the data generated by the equipment; most studies have so far used the maximum value of the electrical resistance signal of each e-nose sensor as the only data provided by this sensor; however, from 2019 onwards, some works began to consider the entire electrical resistance curve as a data source, extracting more information from it.
Originality/value
This study opens a new and promising way for the effective use of e-nose as a fuel analysis instrument, as low-cost sensors can be developed for use with the new data analysis methodology, enabling the production of portable, cheaper and more reliable equipment.
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In this second part of a paper examining the problem of nursing shortages in the health profession in Canada, the author draws on nursing reports from three provinces, Ontario…
Abstract
In this second part of a paper examining the problem of nursing shortages in the health profession in Canada, the author draws on nursing reports from three provinces, Ontario, British Columbia, and Alberta, to identify how professional associations are dealing with the nursing shortage. Although education is seen as a major key to the nursing dilemma, the author notes that Canadian nurses are already exceedingly well educated. Neither more education nor public relation campaigns have been able to overcome the systemic problems facing the nursing profession today. If there is a solution, it lies in a more integrative approach, where structural issues, value issues, and even legal issues related to statute can be addressed. The author believes that the issue of nursing shortages cannot be resolved without a substantial degree of empowerment and autonomy for the profession.