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  • Taiwan is one of the most important suppliers of electrical and electronic products in the world; as such it is itself also an important consumer of those products. This means that the amount of electronic waste, e-waste, generated from information technology (IT) products, home electrical appliances and lighting, is increasing rapidly there.

    Writing in the International Journal of Environment and Waste Management, Wen-Tien Tsai of the Graduate Institute of Bioresources, at National Pingtung University of Science and Technology, in Pingtung, Taiwan, explains how he has investigated the regulatory promotion of e-waste recycling in Taiwan. He found that although the annual quantity of e-waste recycling through the implementing agencies seemed to increase more than tenfold from 7,321 tons in 2001 to 74,421 tons in 2015, there is evidence that the recycling market in Taiwan has matured in recent years partly because of the country's ageing population and slow economic growth. Tsai also highlights the case of fluorescent lighting tubes and how mercury can be successfully recovered from these at end-of-life.

    He points out how the waste composition is still shifting as new products emerge in the realm of personalised medicine, electric vehicles, IT products, novel consumer electronics products, and an increased diversity of food products and home electrical appliances.

    We must address these novel waste streams and find ways to recycle such goods, especially those that contain toxic materials, including mercury. Tsai adds that the improper management and disposal of waste or discarded items could lead to significant environmental harm and harm to human health. In addition, there is a need to retrieve from such goods rare elements that are of limited supply such as precious metals and mineral elements.

    Tsai, W-T. (2019) 'Current practice and policy for transforming e-waste into urban mining: case study in Taiwan', Int. J. Environment and Waste Management, Vol. 23, No. 1, pp.1-15.
    DOI: 10.1504/IJEWM.2019.096540

  • With every news story, the concepts of data mining healthcare information move higher still up the research and policy agenda in this area. Clinical information and genetic data contained within electronic health records (EHRs) represents a major source of useful information for biomedical research but accessing it in a useful way can be difficult.

    Writing in the International Journal of Intelligent Engineering Informatics, Hassan Mahmoud and Enas Abbas of Benha University and Ibrahim Fathy Ain Shams University, in Egypt, discuss the need for innovative and effective methods for representing this huge amount of data. They point out that there are data mining techniques as well as ontology-based techniques that can play a major role in detecting syndromes in patients efficiently and accurately. A syndrome is defined as a set of concomitant medical symptoms and indicators associated with a given disease or disorder.

    The team has reviewed the state of the art and also focused on reviewing the well-known data mining techniques such as decision trees (J48), Naïve Bayes, multi-layer perceptron (MLP), and random forest (RF) techniques and compared how well they each perform in the classification of a particular syndrome, heart disease.

    The team concludes that in experiments with a public data set, the RF classifier provides the best performance in terms of accuracy. In the future, they suggest that data mining will benefit healthcare and medicine significant for building a system able to detect a specific syndrome.

    Mahmoud, H., Abbas, E. and Fathy, I. (2018) 'Data mining and ontology-based techniques in healthcare management', Int. J. Intelligent Engineering Informatics, Vol. 6, No. 6, pp.509–526.
    DOI: 10.1504/IJIEI.2018.096549

  • Face recognition is becoming an increasingly common feature of biometric verification systems. Now, a team from India has used a multi-class support vector machine to extend the way in which such systems work to take into account a person's age. Jayant Jagtap of Symbiosis International (Deemed) University in Pune, and Manesh Kokare of the Shri Guru Gobind Singhji Institute of Engineering and Technology, in Nanded, India, explain that human age classification has remained an important barrier to the next generation of face recognition technology but could be a useful additional parameter in security and other contexts.

    The team's novel two stage age classification framework based on appearance and facial skin ageing features using a multi-class support vector machine (M-SVM) can classify, the team suggests, classify images of faces into one of seven age groups. Fundamentally, the system examines characteristics of the image coincident with facial skin textural and wrinkles and is accurate 94.45% of the time. It works well despite factors such as genetics, gender, health, life-time weather conditions, working and living environment tobacco and alcohol use. Indeed, accuracy is more than 98% in the first step wherein adult and non-adult faces are distinguished.

    "The proposed framework of age classification gives better performance than existing age classification systems," the team reports. They add that future research will look to improve accuracy still further for use in real-time applications. This will be done through the development of an algorithm for extracting facial skin ageing features and through the design of an efficient age classifier, the team concludes.

    Jagtap, J. and Kokare, M. (2019) 'Human age classification using appearance and facial skin ageing features with multi-class support vector machine', Int. J. Biometrics, Vol. 11, No. 1, pp.22-34.
    DOI: 10.1504/IJBM.2019.096559

  • Sentiment analysis is an increasingly important part of data mining, especially in the age of social media and social networking where there is endless opinion and commentary that could be of use to a wide range of stakeholders in commerce, other businesses, and even politics.

    Now, an innovative and efficient method of sentiment analysis of comments on the microblogging platform, Twitter, is reported in the International Journal of Data Mining, Modelling and Management by a team from India. Hima Suresh of the School of Computer Sciences, at Mahatma Gandhi University, in Kottayam, Kerala and Gladston Raj. S of the Department of Computer Science, Government College, also in Kerala explain how sentiment analysis centres on analysing attitudes and opinions revealed in a data set and pertaining to a particular topic of interest. The analysis exploits machine learning approaches, lexicon-based approaches and hybrid approaches that splice both of the former.

    "An efficient approach for predicting sentiments would allow us to bring out opinions from the web contents and to predict online public choices," the team suggests. They have now demonstrated a novel approach to sentiment analysis surrounding the discussion of a commercial brand on Twitter using data collected over a fourteen-month period. Their method has an unrivalled accuracy for gleaning the true opinion almost 87% of the time in their tests using a specific smart phone model as the target brand being studied. They suggest that accuracy could be improved still further by incorporating a wider lexicon that included Twitter slang, for instance.

    Suresh, H. and Raj. S, G. (2019) 'An innovative and efficient method for Twitter sentiment analysis', Int. J. Data Mining, Modelling and Management, Vol. 11, No. 1, pp.1-18.
    DOI: 10.1504/IJDMMM.2019.096543

  • Online behavioural targeting and device fingerprinting could be used to combat credit card fraud according to a team from Botswana International University of Science and Technology, in Palapye, Botswana. Writing in the International Journal of Electronic Security and Digital Forensics, Motlhaleemang Moalosi, Hlomani Hlomani, and Othusitse Phefo explain how there are numerous existing credit card fraud detection techniques employed by card issuers and other stakeholders. Nevertheless, billions of dollars are lost each year to fraudsters.

    The team has now combined behaviour and fingerprinting technology to boost the efficiency and efficacy of the fusion approach using Dempster-Shafer theory and Bayesian learning for fraud detection. The approach can spot odd behaviour that is not characteristic of the legitimate user of a given credit card and so detect fraudulent activity on the account. The approach discussed in the paper is at present a theoretical treatise, the next step will be to simulate actual behaviour using synthetic data sets and then apply to a real-world scenario for testing its efficacy. So far efficacy has been demonstrated with data from devices that have already been used in known fraudulent activity.

    The team suggests that their approach goes well beyond simply tweaking existing fraud-detection algorithms and could offer what they say is a ground-breaking approach that performs far better than trial and error approaches and reduces the number of false positives.

    Moalosi, M., Hlomani, H. and Phefo, O.S.D. (2019) 'Combating credit card fraud with online behavioural targeting and device fingerprinting', Int. J. Electronic Security and Digital Forensics, Vol. 11, No. 1, pp.46-69.
    DOI: 10.1504/IJESDF.2019.096527

  • Throughout human history, certain professions have been commonly peripatetic – the wandering minstrel perhaps a case in point. Musical entertainers who travelled the lands performing for the peasants in return for food and drink and a bed for the night. The modern "minstrel", more frequently known as a pop star might still travel the world, although the remunerative rewards are often grander than a couple of pints and a bunk-up…but not always.

    Researchers in Germany have investigated the ambivalent imaginings that perpetually touring musicians have when contemplating their home and their sense of belong. Writing in the International Journal of Tourism Anthropology, Anna Lisa Ramella of the University of Siegen has looked at touring musicians who spend much of their time "on the road". She has determined that the conventional notions of immobility and mobility are not to be framed as home and away for such people. Instead, they can be more realistically conceptualised as familiar and alien, depending on the individual and their particular circumstances. "The very blurring of the boundaries of movement and stasis enables a shifting of perspectives in which 'home' and 'tour' may be experienced as either a source of stability or transience," she says.

    The findings may well be obvious to the musicians themselves, particularly when one considers the 20th-century songbook and the folk, blues, and rock traditions that tell tales of life on the endless road and finding no place like home. Musicians have always been travellers that "need to do the road" and from ancient times to today, that urge to travel has been driven by culture and economic necessity.

    Of course, throughout the latter years of the 20th Century, the notion of musicians touring to promote their recorded offerings became commonplace. Now in the age of streaming, digital downloads, and file sharing, the money to be made from recordings has dwindled for many musicians and touring and merchandise has become the revenue-generating vehicle rather than the marketing manoeuvres.

    Ramella, A.L. (2018) 'Deciphering movement and stasis: touring musicians and their ambivalent imaginings of home and belonging', Int. J. Tourism Anthropology, Vol. 6, No. 4, pp.323-339.
    DOI: 10.1504/IJTA.2018.096361

  • The library continues to play a critical role in academic life, as one would hope! However, in today's connected world, there is pressure to update the conventional paradigms and an urgency for librarians to embrace online social media for the benefit of their users. Writing in International Journal of Electronic Customer Relationship Management, Melissa Clark and Scott Bacon of Coastal Carolina University, in Conway, South Carolina, USA, point out that the library is not only the repository of information sources for students but represents a hub that connects those students to the university.

    The team has now investigated student perception of the role of the modern university library and whether or not following the social media account, or accounts, of their university library improves this perception or otherwise. Fundamentally, they found that "following the library on social media is positively related to a student's perception of their relationship quality with the university; students interested in multiple library services are likely to report the perception of a higher quality relationship with the university.".

    One might consider that today's young students are almost all "digital natives" and use multiple social media platforms regularly and very much on a daily basis. Concomitant with that is the notion that education must be marketed in the modern environment in a way that it perhaps was not in the past: "By tapping into this channel, higher education marketers have a viable outlet that could be used to build a long-lasting relationship with their audience," the team reports.

    The team adds that "Engagement on university social networks is cyclical by nature, as students enter the university, build networks and then graduate." They point out that there is natural attrition and so the university library's social media content strategy must be constantly tweaked to seek out the "freshers", the new students at the beginning of each academic year and to find ways to serve them better while they study and maybe even after they graduate, especially as alumni are often the greatest marketers for an academic institution.

    Clark, M.N. and Bacon, S.D. (2018) 'Utilising social media to improve relationship quality: the case of the university library', Int. J. Electronic Customer Relationship Management, Vol. 11, No. 4, pp.384-410.
    DOI: 10.1504/IJECRM.2018.096247

  • Non-contrast computed tomography (NCCT) is a low-cost medical imaging technology that is used widely in investigating damage to a patient's brain caused by ischaemic stroke. However, writing in the International Journal of Image Mining, researchers from Algeria explain that it is not without limitations. As such, they are developing an algorithm that can automatically detect ischaemic areas of the brain from CT images within hours of the onset of symptoms using a comparison of the two brain hemispheres.

    Yahiaoui Amina Fatima Zahra and Bessaid Abdelhafid of the Department of Biomedical Engineering, at the University of Tlemcen, explain how subtle changes in ischaemia are difficult to visualise and to extract and although there are techniques that allow radiologists to "score" the damage and to make diagnostic decisions regarding thrombolytic treatment there is always room for improvement. Moreover, commonly only patients with a high baseline score benefit from endovascular revascularisation therapy. This could change if there were a better way to assess the CT images quickly.

    The team reports that their algorithm has five steps: pre-processing, segmentation of regions of interest, elimination of old infarcts and cerebrospinal fluid (CSF) space, feature extraction and ASPECTS scoring. They have tested it on 25 patients and found it to be effective in comparison with methods previously reported in the scientific literature and it shows high sensitivity at almost 91%.

    Zahra, Y.A.F. and Abdelhafid, B. (2018) 'A promising method for early detection of ischemic stroke area on brain CT images', Int. J. Image Mining, Vol. 3, No. 2, pp.139-151.
    DOI: 10.1504/IJIM.2018.096298

  • Consumers have the opportunity to express their views about the products and services they use in ways that were simply not technologically possible a decade ago. Social media and social networks allow them to opine wildly to fellow users and also directly and in public to the companies that provide those products and services.

    Of course, with any system involving subjectivity and more critically, money, there is likely to be gaming of that system on both sides. An unscrupulous company may attempt to spam the system and improve its ratings artificially. Conversely, an individual or pressure group with a particular grudge might wish to sabotage that company's ranking.

    Writing in the International Journal of Web Based Communities, Meesala Shobha Rani and S. Sumathy of the School of Computer Science and Engineering, at Vellore Institute of Technology, in Vellore, India, have looked to nature for inspiration to find the best way to root out opinion spam. They have reviewed algorithms that use the notions of "a moth to a flame", "grey wolf hunting", or "flower pollination by insects". Their review looks at how well different approaches are able to detect fake opinions on social media. The same approaches might also be useful in spotting fake political opinion and even fake news.

    Customers depend on e-commerce sites to save them shopping time and they require accurate and honest reviews on those sites to help them in their decision making, the team reports. However, spammers, often in exchange for payment can post a fake opinion, good or bad and so degrade the quality of the reviews. In their assessment of the different approaches, the team found that "grey wolf" is the more effective and might well be adopted by organizations and companies hoping to detect and delete fake opinion on their systems.

    Rani, M.S. and Sumathy, S. (2018) 'Online social networking services and spam detection approaches in opinion mining - a review', Int. J. Web Based Communities, Vol. 14, No. 4, pp.353-378.
    DOI: 10.1504/IJWBC.2018.096245

  • The work-life balance and juggling family can lead to emotional turmoil for those who find themselves unable to resolve the conflicting demands of work and family. A research team in India has now looked surveyed 346 employees from 93 organisations in order to ascertain whether "emotional dissonance" caused by work-family conflicts correlates with a person's intention to quit their employment.

    Subhash Kundu and Nidhi Gaba of the Haryana School of Business, at Guru Jambheshwar University of Science and Technology, in Hisar, Haryana, India, explain how they used multiple regression analysis on the data to test their hypothesis. Writing in the International Journal of Business and Globalisation, they describe how the analysis shows that the conflict between work and family life has a positive and statistically significant influence on a person's intention to quit. Critically, they showed that emotional dissonance is a key mediating factor in this regard.

    Longer working hours, more rigid targets, mobile computing, and other factors and the change in the structure of families from single earners to dual-career couples as well as increased pressure from urbanization and longer-lived older family members are putting many people under new kinds of pressure and stress. There is even specifically on those in employment not only to perform well in their jobs but also to be successful in terms of a family too. But work demands and family demands are very different and pull people in two different directions commonly leading to conflict and what psychologists might refer to as emotional dissonance that a lay person might simply perceive as stress.

    New insights into how emotional dissonance arises because of this almost ubiquitous work-family conflict could help policymakers and managers cope better with a changing world and to help retain a happy and less conflicted workforce.

    Kundu, S.C. and Gaba, N. (2018) 'Work-family conflict and intention to quit: the mediating role of emotional dissonance', Int. J. Business and Globalisation, Vol. 21, No. 4, pp.464–483.
    DOI: 10.1504/IJBG.2018.095764

News

New Editor for International Journal of Intelligent Systems Technologies and Applications

Prof. Tao Wu from Shanghai Jiaotong University School of Medicine in China has been appointed to take over editorship of the International Journal of Intelligent Systems Technologies and Applications.

New Editor for International Journal of Earthquake and Impact Engineering

Dr. Erol Kalkan from the United States Geological Survey has been appointed to take over editorship of the International Journal of Earthquake and Impact Engineering.

Rotating Editorship for International Journal of Multinational Corporation Strategy

Associate Prof. Joseph Amankwah-Amoah from the University of Kent in the UK has been appointed to take on a rotating editorship of the International Journal of Multinational Corporation Strategy, and will be Editor in Chief of the journal for the duration of 2019.

New Editor for International Journal of Knowledge-Based Development

Prof. Francisco Javier Carrillo from the World Capital Institute in Mexico has been appointed to take over editorship of the International Journal of Knowledge-Based Development.