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  • Research published in the International Journal of Computational Vision and Robotics, points to several approaches that might be used to up-convert Super SloMo video files with deep learning offering improvements in final quality. The methods described offer a way to convert a video with a lower number of frames per second to be converted to one with a higher number of frames per second.

    Minseop Kim and Haechul Choi of the Hanbat National University in Daejeon, Republic of Korea explain how a training data set can be used to gain optimal results with Super SloMo boosting signal-to-noise ratio significantly. Super SloMo is a deep learning-based frame rate up-conversion (FRUC) method proposed by graphics hardware company NVIDIA. The current team's approach works with this and can preclude flickering effects when displaying video that does not match the quality of the display itself by creating frames between frames using the techniques of artificial intelligence. This allows a more natural up-conversion to be carried out whereas earlier approaches can successfully reduce flicker but look unnatural. The new approach avoids the negative impact that can be seen when a bad motion vector is used to add frames.

    The team trained the system with thousands of videos showing various moving objects of different sizes. The large objects dataset contained more than 50000 images of basketball, soccer, volleyball, marathons, and vehicles. The dataset with small moving objects contained more than 50000 images of golf, badminton, table tennis, and tennis. A similar-sized dataset of both large and small objects was also used.

    "The results of training by object size shows that the performance was improved in terms of peak signal-to-noise ratio (PSNR) and the mean of the structural similarity index (MSSIM) in most cases when the training set and the validation set had similar properties," the team reports. Specifically, "The experimental results show that the two proposed methods improved the peak signal-to-noise ratio and the mean of the structural similarity index by 0.11 dB and 0.033% with the specialised training set and by 0.37 dB and 0.077% via adjusting the reconstruction and warping loss parameters, respectively," the team writes.

    Kim, M. and Choi, H. (2021) 'A high-quality frame rate up-conversion technique for Super SloMo', Int. J. Computational Vision and Robotics, Vol. 11, No. 5, pp.512–525.
    DOI: 10.1504/IJCVR.2021.117583

  • Research published in the International Journal of Internet Marketing and Advertising has looked at how cultural differences affect behaviour on social media. Myron Guftométros and João Guerreiro Instituto Universitário de Lisboa, in Lisbon, Portugal, focused on what is perhaps the most well-known and well-populated online social network, Facebook. They used an organic approach to assimilate data from 6750 posts from 225 different Facebook brand pages across fifteen different countries.

    The team categorized the engagement metrics such as the number of likes, shares and comments and the various versions of "likes" such as love, wow, and funny that can be used to tag an update. They then used Hofstede's cultural dimensions to analyse the data. The team found several interesting differences that could be explained by Hofstede's dimensions. For instance, countries that are considered low in individualism and/or high in power distance, share posts more than commenting on them. They also found that the use of the "funny" or "wow" emoticon responses instead of a standard "like" also related to higher scores on individualism.

    Despite the reach of Facebook and other social media systems, globalisation and interconnectedness, people still retain and favour their own cultural values in different regions and across different groups within those regions. However, ongoing studies are still needed to discern whether the effects of globalisation are blurring cultural distinctions or not particularly in update and commenting activity on social media. The authors write that their work appears to be the first published based on real-world organically gathered data in the form of engagement metrics to analyse cultural differences.

    The next step will be to look at cultural differences surrounding smaller, local companies, and also to extend the analysis of metrics to other applications, such as the microblogging site Twitter and the photo- and video-oriented Instagram. The researchers also find that their study poses several more questions that future research might answer: Does "loving" a post instead of "liking" it mean that there is a stronger brand relationship? Also, they ask, does responding with the "funny" or "wow" emoticon mean that customers are more engaged and interested in the posts? Of course, the bigger question is to learn whether these fleeting online sentiments actually reveal anything at all about a user or customer's actual feelings towards a given brand.

    Guftométros, M. and Guerreiro, J. (2021) 'The effects of cultural differences on social media behaviour', Int. J. Internet Marketing and Advertising, Vol. 15, No. 4, pp.412–428.
    DOI: 10.1504/IJIMA.2021.117561

  • In response to the COVID-19 pandemic governments, corporations and private companies, as well as not-for-profit organisations have tried to support public health in many different ways. A new report in the International Journal of Indian Culture and Business Management, has looked at what strategies appear to have worked in coping with this disease.

    Amina Omrane of the ECSTRA Research Center at IHEC Carthage, University of Sfax, in Tunisia and Sudin Bag of Vidyasagar University in West Bengal, India, found that digital tools and technologies coupled with specific cultural responses have helped us face the pandemic in many ways. Their detailed findings point to how corporate management, government and state officials, as well as entrepreneurs, might learn from the current crisis how best to cope with the ongoing problems it brings as well as how we might successfully cope with a similar crisis in the future.

    In late 2019, human health, security, and safety took a turn for the worse with the emergence of a novel and potentially lethal airborne coronavirus dubbed SARS-CoV-2, which causes a disease labeled COVID-19, as we all know. In March 2020, the World Health Organisation declared a global pandemic, which has proven to be the worst for many decades in terms of people affected and the number of deaths around the world that it has wrought.

    There have been many different responses to the disease in different parts of the world, such as telecommuting mandates, lockdowns, and border controls, some more successful in some places than others. At the time of writing, we now have several vaccines available to some parts of the world population. There has also been significant blowback from those concerned with the societal and economic impact as opposed to the direct public health effects. Irrespective of the politic of such discussions, the pandemic has wreaked havoc in most parts of the world affecting everyone in one way or another. At the time of writing, the WHO reports that more than 4.6 million people have died of this disease.

    There is now a pressing need to move forward with research in the biomedical, social, and business sciences to help us cope with the current ongoing problems we face and to ready ourselves for a future pandemic even before this one is over.

    Omrane, A. and Bag, S. (2021) 'Which strategies are appropriate for the fight against the worldwide coronavirus crisis?', Int. J. Indian Culture and Business Management, Vol. 23, No. 4, pp.416–430.
    DOI: 10.1504/IJICBM.2021.117476

  • The downside to solar power is that it's not always sunny and so grid operators have to compensate for energy drops by bringing alternative generation sources online. New research in the International Journal of Powertrains, looks at how short-term forecast of sunshine using satellite images could offer one tool to help power companies maintain a steady supply.

    A. Shobana Devi of the Sathyabama Institute of Science and Technology, in Chennai, India and colleagues explain how solar irradiance forecasting currently represents a major challenge to companies hoping to integrate solar energy resources into the existing structures of energy supply. Fundamentally, it is the vagaries of changing cloud cover that compromise the power output of solar panels. However, it might be possible to compensate for the problem if there were a way to predict cloud movements within a fifteen to ninety-minute window throughout the day.

    The team has developed an approach using the long short-term memory (LSTM) technique and tested it against known satellite imagery and the power output of a 250-megawatt solar plant to show that the predictions can be sufficiently accurate to allow grid operators to balance power output from solar and other sources. Their tests demonstrate that this approach is more accurate than other methods when tested against cloud cover data accumulated over a seven-month period. Statistical regression models allow them to assess the efficacy of the various models tested.

    "The results of experiments verify and affirm that over current techniques, our suggested algorithms can considerably enhance the precision of cloud monitoring and solar energy estimation," the team writes. They add that "This predictive solar power data in the smart grid can be used efficiently for grid operation (load tracking) and energy management system."

    Devi, A.S., Maragatham, G., Boopathi, K. and Prabu, M.R. (2021) 'Short-term solar power forecasting using satellite images', Int. J. Powertrains, Vol. 10, No. 2, pp.125–142.
    DOI: 10.1504/IJPT.2021.117457

  • Machine learning might be able to predict which employees within an organisation are readying themselves to leave the company for whatever reason. Research published in the International Journal of Data Science, explains how employee turnover costs organisations billions of dollars annually. Finding ways to improve employee retention might be guided effectively if there were a way to spot the trends in employee intentions ahead of their making any decision to move to a new position within another organisation, for example.

    Owen Hall of the Graziadio School of Business at Pepperdine University in Malibu, California, USA, points out that, as one might expect, engagement, job satisfaction, experience, and compensation are four of the most obvious factors that point to an employee's decision to leave when any combination of those factors fails to align with that person's aspirations and expectations with regard to their career and prospects.

    Employee retention is a perennial issue for those working in human resource management. This has become even more acute during the COVID-19 where normal life and work practices have been changed beyond recognition in many areas of employment. Increased competition, more customer demands, and intensified recruiting and onboarding challenges, have never been of greater concern, it might be said.

    Within HR, the understanding of employee turnover has generally been done in retrospect, perhaps long after specific employees have already moved on. A proactive stance is needed, which is where Hall suggests machine learning might be able to assist. "Machine learning can be used to both identify employees that are planning to leave and design specific implementation amelioration strategies," writes Hall.

    Machine learning can do this with much less bias than might be experienced with human assessment of the situation as it unfolds in terms of employee intentions. Of course, engaging senior leadership is then required to mitigate against the loss of experienced and useful employees to opportunities elsewhere. Hall explains that "The results of a machine learning analysis featuring extreme gradient boost trees and neural nets of a representative employee database yielded classification accuracy levels on the order of 90%."

    Hall, O.P. (2021) 'Managing employee turnover: machine learning to the rescue', Int. J. Data Science, Vol. 6, No. 1, pp.57–82.
    DOI: 10.1504/IJDS.2021.117472

  • In the wake of the COVID-19 pandemic, we must not squander the clean energy gains that were made through reduced human activity and economic downturn during the periods of lockdown and beyond. That is the message from recent research published in the International Journal of Global Warming.

    Fatemeh Nadi of the Department of Agricultural Machinery Mechanics at the Islamic Azad University, in Azadshahr, Iran, and Mustafa Özilgen of the Department of Food Engineering at Yeditepe University, in Istanbul, Turkey, explain how during the ongoing pandemic, prices across the energy sector were pushed down by reduced demand.

    As such, there may well have been a shortfall in investment into renewable energy projects in the short term during the current period and after the pandemic, they add. That said, at the time of writing this Research Highlight, there is already growing signs that point to price hikes across the energy sector as nations relieve restrictions and endeavour to unlock their economies once more.

    The team has looked at one particular energy-intensive sector in Iran – bakeries. The Iranian baked goods industry is among the most energy-intensive in that sector across the globe with bread production amounting to an annual 15 million tonnes.

    The team has developed three different scenarios that could lead to a 45% reduction in energy consumption across bakeries, a rate that amounts to well over 100 megajoules per tonne of produce per annum. Their approaches involving adopting wind power and biogas use in baking and in the growing of wheat and flour milling before that. They also suggest a potential greening of the sector amounting to a 70% reduction in carbon dioxide emissions. They add that waste products and waste bread might be fed back into the production cycle for bioethanol for making requisite transportation greener too.

    To conclude, the team writes how "Sustainability of the baking industry may be improved substantially through implementing three different scenarios: improving the flour production process from farm to factory, replacing fossil fuels with their renewable counterparts, and producing ethanol from the leftover bread." They add that "Such an improvement may be a major attempt toward protecting the clean energy gains of the pre-pandemic era."

    Nadi, F. and Özilgen, M. (2021) 'Effects of COVID-19 on energy savings and emission reduction: a case study', Int. J. Global Warming, Vol. 25, No. 1, pp.38–57.
    DOI: 10.1504/IJGW.2021.117432

  • The transportation of hazardous materials through densely populated areas, such as cities, is a necessary part of modern life, but comes with risks of spills and leaks, explosions, environmental issues, and public health concerns. New research in the International Journal of Simulation and Process Modelling, has used a transportation management simulation to look at problems that might arise in moving hazardous materials within a city when traffic congestion is common.

    Luiz Antonio Reis, Sergio Luiz Pereira, Eduardo Mario Dias, and Maria Lídia Rebello Pinho Dias Scoton of the Polytechnic School of the University of São Paulo in Brazil explain how their simulation can be used to reduce risk and find optimal routes for the transport of hazardous materials. By suggesting ways that traffic might be better managed overall in a city, they also demonstrated how to improve city life. The advanced simulation system makes a huge contribution to reducing traffic jams and their consequences on fuel consumption and greenhouse gas emissions, the team writes.

    The team points out that Brazil's National Transport Confederation says that road transport is responsible for 61% of cargo transportation, and practically all of the dangerous cargo transportation in the country's urban areas. "Thus, the greater the control and standardisation of operating procedures for this type of transport, the better and safer it will be for society," the team writes.

    As city infrastructure and control mature and we can begin to talk about "smart" cities, there is a pressing need to address the issues of real-world logistics and transportation which can succumb to the whims of real-world traffic and drivers and the incidents and accidents that plague them. To make use of the output from their simulation there is thus a need for greater control and traffic awareness and management in the urban environment.

    Obviously, registered vehicles with hazardous cargos will be tracked continuously, but private and even commercial traffic will not other than through the closed-circuit television network and monitoring present on many roads and perhaps drone or helicopter surveillance of traffic congestion as it arises. As such, there need to be stronger connections formed between different stakeholder departments who might then share timely information and using the team's model be able to respond quickly to help avoid congestion issues and potential accidents involving, primarily, the hazardous cargos, but also the wider traffic base in a city.

    Reis, L.A., Pereira, S.L., Dias, E.M. and Scoton, M.L.R.P.D. (2021) 'Traffic jam prediction using hazardous material transportation management simulation', Int. J. Simulation and Process Modelling, Vol. 16, No. 3, pp.256–269.
    DOI: 10.1504/IJSPM.2021.117336

  • Smart cities will not be truly smart until they have sustainable transport systems. New work published in the International Journal of Shipping and Transport Logistics has used fuzzy logic to look at the options.

    Chenghua Wang of the School of Public Affairs at Chongqing University, in Chongqing, China, and colleagues Oscar Sanjuán Martínez and Rubén González Crespo of the School of Engineering and Technology at the Universidad Internacional de La Rioja in Spain, suggest that current expansion of transportation is having an increasingly detrimental effect on environment at the local and global levels as well as reducing the quality of life for many people. They suggest that governments and those running our cities must invest in clean, safe, efficient, economic, and sustainable transport networks to address this growing problem. This is even more pressing given the demands of the citizens living and working in technologically rich cities, which we might refer to as smart cities.

    The problem facing policy makers, planners, and stakeholders in transportation is how to define what is meant by sustainable transport and how to select the appropriate systems to fulfill the demands of such a system.

    The current team has introduced what they refer to as an improved hybrid fuzzy logic system (IHFLS) for the generation of aggregate values for the sustainable evaluation of hybrid fuzzy logic to allow the decisions to be made more effectively. In the first step, they define the sustainability evaluation criteria for transport. In step two, experts provide language ratings against selected criteria for potential alternatives. Finally, the IHFLS generates aggregate results for the evaluation of sustainability and the choice of the best alternatives. The approach allows the social, economic, and environmental considerations, to be balanced equitably, viably, and in a way that stakeholders can bear. Optimally, all of these criteria will mesh together to enable a sustainable solution to be found for a given city.

    Wang, C., Sanjuán Martínez, O. and González Crespo, R. (2021) 'Improved hybrid fuzzy logic system for evaluating sustainable transportation systems in smart cities', Int. J. Shipping and Transport Logistics, Vol. 13, No. 5, pp.554–568.
    DOI: 10.1504/IJSTL.2021.117295

  • Video evidence is commonly used to prove what happened during an event. However, with the emergence and rapid development of CGI (computer-generated images), deep fakes, and video manipulation, there is a pressing need for tools to detect forgeries that would otherwise undermine the value of video evidence.

    A review in the International Journal of Electronic Security and Digital Forensics has taken a look at the state-of-the-art in video forgery detection with a particular focus on how those tools might be used to ensure evidence in a criminal investigation has not been compromised or is not a forgery. Punam Sunil Raskar and Sanjeevani Kiran Shah of Savitribai Phule Pune University, in Pune, Maharashtra, India, explain how they have categorised forgery detection tools into four distinct domains within digital forensics.

    The first domain involves those tools that can help those investigating so-called "copy move attacks" (CMA). In a CMA, part of an image is cloned (selected, copied, and pasted) on to another area of the image, still or moving. It may be used to render invisible something that is incriminating or identifying in the image. A CMA might also be used to duplicate a part of an image in a suggestive manner for nefarious purposes. The second domain represents tools that can scrutinise a video and detecting tampering based on motion estimation techniques. The third area uses the principle of optical flow to identify problems with a moving object in a video suggestive of something having been faked. The fourth section looks at the specific issues that arise in extracting information from a compressed video.

    It is the latter area of research on compressed video evidence that is yet to mature fully although the researchers suggest that their review points to numerous routes that might be taken in developing all of the areas of digital forensics for video evidence.

    Raskar, P.S. and Shah, S.K. (2021) 'Methods for forgery detection in digital forensics', Int. J. Electronic Security and Digital Forensics, Vol. 13, No. 5, pp.528–547.
    DOI: 10.1504/IJESDF.2021.117310

  • The social media network, Twitter, has been at the heart of many a public debate not least the national and international response to the COVID-19 pandemic. New research from the USA published in the International Journal of Business and Systems Research, has examined public opinion on "lockdowns" and "reopening for the economy" during the first summer of the pandemic as revealed by more than a million unique Twitter updates about COVID-19.

    Sina Shokoohyar and Julianne Dang of Saint Joseph's University in Philadelphia, Pennsylvania, and Hossein Rikhtehgar Berenji of Pacific University in Forest Grove, Oregon, classified 1.3 million Twitter updates, whimsically known to users of the microblogging website and application as "tweets". Their classification divided updates into three camps. The first, were in favour of removing lockdown restrictions to allow the US economy to "reopen". The second category had those updates aligned with continuing lockdown restrictions for the sake of public health. The third category were neutral tweets offering facts rather than opinion.

    Rather than using logistic regression, decision tree, random forest, neutral network or multinomial naïve Bayes, the team turned to a gradient boosting classifier algorithm, which they demonstrate had an accuracy of 88% and so outperformed those other classifiers in their research.

    The fundamental conclusion from the analysis is that there were significantly more tweets in favour of reopening the economy rather than persisting with lockdown measures, such as ongoing educational and business closures and stay-at-home orders and that this opinion became increasingly prominent as time passed during the early stages of the pandemic lockdowns. The team suggests that the perceived and real socioeconomic impact of lockdowns on stock markets, gross domestic product (GDP), unemployment rates, and rates of household consumption were drivers for the offered opinions of many Twitter users.

    Of course, lockdowns led to an increase in social media activity and so this in itself partly underpins the increase in tweets offering an opinion on lockdown, public health, and the socioeconomic impact of COVID-19.

    "Perhaps one of the most surprising side effects of the outbreak is the increase in US residents' engagement in expressing their opinion on social media," the team writes. "People from all walks of life are suddenly reading statistical analyses and epidemiology charts and sharing them as if they were popular music videos or comedy memes," the researchers add.

    There are implications for policymakers of this study, the team suggests. Twitter and other social media can be used to extract public opinion quite widely and so reveal how public attitudes to any given policy or regulation might change in an emergency situation such as a global pandemic.

    The team adds that "Analysing these tweets can shorten the time to observe the consequences of the pandemic, and can facilitate faster response by policymakers." Whether or not policymakers should be chasing public opinion in a crisis of this sort is perhaps a different matter when there are direct implications for public health to be weighed against long-term implications for the economy and ultimately its effects on public wellbeing and public health.

    Shokoohyar, S., Rikhtehgar Berenji, H. and Dang, J. (2021) 'Exploring the heated debate over reopening for economy or continuing lockdown for public health safety concerns about COVID-19 in Twitter', Int. J. Business and Systems Research, Vol. 15, No. 5, pp.650–672.
    DOI: 10.1504/IJBSR.2021.117316


New Editor for International Journal of Sustainable Agricultural Management and Informatics

Associate Prof. Jason Papathanasiou from the University of Macedonia in Greece has been appointed to take over editorship of the International Journal of Sustainable Agricultural Management and Informatics.

New Editor for International Journal of Product Sound Quality

Associate Prof. Jinyang Xu from Shanghai Jiao Tong University in China has been appointed to take over editorship of the International Journal of Product Sound Quality.

New Editor for International Journal of Internet Manufacturing and Services

Prof. Mitsuo Gen from the Fuzzy Logic Systems Institute in Japan has been appointed to take over editorship of the International Journal of Internet Manufacturing and Services.

International Conference on Advanced Vehicle Powertrains (ICAVP2021) a Success

The International Conference on Advanced Vehicle Powertrains (ICAVP), a biennial event since 2017, was initiated by the International Journal of Powertrains. ICAVP2021 took place over 3-4 September (hosted by Beihang University in Beijing, China), and the two-day conference was truly a success. More than 200 online and offline experts and scholars from China, the United States, Germany, the United Kingdom, Australia and other countries participated to discuss "dual carbon goals". Furthermore, the development status and future trends of cutting-edge technologies such as advanced motive power systems, electric propulsion systems and new energy vehicle technologies were also discussed.

The hybrid conference offered both in-person and global online attendance to address the pandemic situation. It was also broadcast globally via the internet for its prospective audience. 73 experts attended in person, over 143 attended online, and over 186,000 viewers viewed its free broadcasts.

The following broadcast links from ICAVP2021 will be available online for one year.

The Main Venue Link

3 September Room A

3 September Room B

4 September Room B

4 September Room A (including Closing)

ICAVP2021 had five invited keynotes, ten invited technical reports from ten automotive companies, and 29 technical presentations from 32 accepted full papers. One BPA and two Student BPAs were awarded. The conference programme is available here.

Please refer to the above links for more detail information.

Improved Clarivate Citation Reports and Impact Factors for Inderscience Journals

Inderscience's Editorial Office is pleased to announce that 2021's Journal Citation Reports from Clarivate Analytics have revealed advances in impact factors for many Inderscience journals, including the European Journal of Industrial Engineering, European Journal of International Management, International Journal of Bio-Inspired Computation, International Journal of Exergy, International Journal of Global Warming, International Journal of Mobile Communications, International Journal of Oil, Gas and Coal Technology, International Journal of Shipping and Transport Logistics, International Journal of Surface Science and Engineering, International Journal of Technology Management, International Journal of Web and Grid Services, and Progress in Computational Fluid Dynamics.

The Editorial Office would like to congratulate and thank all editors, board members, authors and reviewers involved, and is pleased to see their endeavours rewarded in these latest Citation Reports.