The following paper, "Cross-border digital public services in the European Union: a systematic literature review" (International Journal of Electronic Governance 16(1) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following paper, "How to sample in necessary condition analysis (NCA)" (European Journal of International Management 23(1) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Bringing together virtual reality (VR) and artificial intelligence (AI) could lead to significant advancements in the field of interior design, according to research in the International Journal of Information and Communication Technology. Such a technological merger could be used to improve the design experience, tailor designs through simulated indoor environments, and give us better architectural outcomes. Such an approach would not remove our reliance on specialist designers and architects, but could lead to new approaches and opportunities.
According to Nan Yin of the Jilin University of Architecture and Technology in Changchun, Jilin, China, user-friendly design software, particularly from industry leaders like Autodesk in the USA and Kusile in China, has helped lower the overall workload for designers. Such software has allowed professionals to engage in interior design in different ways and even opened up the possibility of design to amateur designers. These tools have commonly used 3D reconstruction and virtual environments to offer an intuitive design experience.
Yin suggests that geometric and mathematical optimization strategies are now needed to address the complexity of building interior design. He suggests that in the use of hybrid recommendation modes and convolutional neural networks (CNNs) it should be possible to allow professional standards to be maintained while allowing for user preferences. Such a system has great potential for interior design, the research suggests.
The work focuses on the scientific application of geometric forms in interior design, particularly in terms of furniture selection and placement, with the emphasis on space functionality and user experience. The study offers insights into how different geometric forms affect the way in which we can move around a space and how it can be broken up into different areas, or zones, with different purposes.
Yin has used collaborative filtering (CF) methods and CNNs to develop intelligent interior design schemes. The research thus offers a theoretical basis for the use of geometric forms in design. The use of CNNs specifically allows texture analysis for comparing design elements.
Yin, N. (2024) ‘The application of geometric form in architectural interior environment design’, Int. J. Information and Communication Technology, Vol. 24, No. 5, pp.95–105
The following paper, "A societal shift to the right or the political mobilisation of a shrinking minority? Explaining rise and radicalisation of the AfD in Germany" (International Journal of Public Policy 17(3) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
During the COVID-19 pandemic, facemasks became almost ubiquitous and still are in some environments. There is a need for face recognition to be able to “see behind the mask” for security and safety. Research in the International Journal of Computational Vision and Robotics discusses the potential of new software that might be trained on a large database of photographs of individuals in different poses and holding different facial expressions, where a simulated mask has been superimposed on the image, to allow facial recognition to work despite the mask you use.
Freha Mezzoudj and Chahreddine Medjahed of the Department of Computer Science at the University Hassiba Benbouali of Chlef in Algeria, have developed a comprehensive database of masked faces, termed FEI-SM. The training set contained images of 2000 unmasked faces and 18000 “masked” faces with different types of face covering, surgical masks and consumer-type masks. The database might now be used to test biometric identification of masked individuals.
Facial recognition as a form of biometric identification is now widely used in security systems. It can be used to open one’s smartphone, for instance, or be used to allow access to a building only for accredited individuals. It can also be used by the police and other authorities to identify individuals in a given, putatively illegal, setting.
The team explains that “deep learning” a subset of artificial intelligence technology is a powerful approach to image recognition that usually stumbles when faced with a masked individual. The team has used several convolutional neural network systems – deep learning tools – based on three ResNet and two DarkNet models (ResNet18, ResNet50, ResNet101, DarkNet19, and DarkNet53) to see how successful they might be in the biometric identification of masked and unmasked faces from their database. They found that ResNet18 is the most accurate and fastest in their tests.
Mezzoudj, F. and Medjahed, C. (2024) ‘Efficient masked face identification biometric systems based on ResNet and DarkNet convolutional neural networks’, Int. J. Computational Vision and Robotics, Vol. 14, No. 3, pp.284–303.
The following paper, "Characteristics of industrial service ecosystem practices for industrial renewal" (International Journal of Services Technology and Management 29(1) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
International Journal of Biometrics 16(3/4) 2024
The accurate validation of signed documents is important to ensuring personal privacy and digital safety and security. Offline handwritten signature recognition is now widely used in sectors like banking, healthcare, and legal proceedings. However, there remains a security risk in that a handwritten signature might easily be forged by a malicious third party. There is an urgent need in many sectors to improve the current recognition techniques so that they can identify faked autographs.
Research from China published in the International Journal of Biometrics has introduced a new approach to offline handwritten signature recognition based on Generative Adversarial Networks (GANs). This approach allows variable features such as a measure of the pen pressure and tilt angle to be used for signature recognition. Xiaoguang Jiang of the Department of Culture and Arts at Yongcheng Vocational College explains that by integrating GANs to enhance accuracy it is possible to generate realistic virtual signatures that alongside training classifiers from authentic written signatures and so improve the accuracy of the classifier.
Jianh has used a Deep Convolutional GAN (DCGAN) model and demonstrated 95 percent accuracy in tests, which is much greater than the accuracy possible with earlier models. Accurate signature recognition is critical for identity verification processes in finance, law, healthcare, and other areas. The same techniques might also be applied more esoterically to signature verification in the art world, for instance, or the digitization of historical documents to ensure authenticity and provenance.
Jiang, X. (2024) ‘Offline handwritten signature recognition based on generative adversarial networks’, Int. J. Biometrics, Vol. 16, Nos. 3/4, pp.236–255.
The following paper, "Subcarrier power control for URLLC communication system via multi-agent deep reinforcement learning in IoT network" (International Journal of Communication Networks and Distributed Systems 30(3) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Research in the International Journal of Biometrics introduces a new method for assessing a practitioner’s precision in martial arts training. The method focuses on quickly identifying errors in the athlete’s movements and allowing their trainer to more precisely guide them to correct form. The system has been developed with a particular focus on Wushu, a collection of Chinese martial arts styles known for their complexity and precision.
Zhiqiang Li of the Department of Police Sports Teaching and Research at Jilin Police College in Changchun, China, explains how the system used advanced algorithms, including the optical flow method and shot adaptive K-means clustering. These are used to extract “key frames” from video and to then analyse texture features of the martial artist’s movements. The analysis can attain a high accuracy rate of 96.58% in detecting incorrect movements. The minimal recognition error is 1.9%, Li adds. Critically, the method is very efficient, giving the trainer or student a positive recognition within just 11 seconds or so.
The approach could be very useful in martial arts training, allowing coaches to identify errors in real-time and offer on the spot advice and guidance to their students, even if an error was difficult to spot in the class or there were ambiguity in judging it. The method could thus enhance training effectiveness and, given that incorrect actions are often associated with injury, it could also reduce the number of physical problems faced by students. The high precision will benefit the students in developing their technical proficiency but also make their participation in martial arts safer. The system will also benefit to the overall aesthetic appeal of a martial arts performances.
One might imagine that the system could be extended for refereeing purposes where there is ambiguity in judging a move or action as allowed or illegal in the particular marshal art. It would also be quite easy to imagine that such a system would be as controversial as the likes of the digital line judges used in international tennis and the video assistant referee (VAR) used in (association) football.
Li, Z. (2024) ‘A method for recognising wrong actions of martial arts athletes based on keyframe extraction’, Int. J. Biometrics, Vol. 16, Nos. 3/4, pp.256–271.
International Journal of Environmental Technology and Management 27(3) 2024
Journal for International Business and Entrepreneurship Development 15(4) 2023
Industry faces many problems in the current economic, sociopolitical, and environmental context. The idea of industrial renewal has thus come to the fore as an approach that might allow us to address those different challenges sitting with the new approach to understanding, known as service ecosystems.
Writing in the International Journal of Services Technology and Management, a team from Finland explains how service ecosystems might play an important part in speeding up industrial renewal. However, they add that there are many aspects of the complex social dynamics that drive these ecosystems, which must be understood before we can move ahead and which have previously been overlooked in some research.
Maaria Nuutinen, Katri Valkokari, and Maarit Halttunen of the VTT Technical Research Centre of Finland Ltd, and Katariina Palomäki of Sitowise Ltd, have taken a new look at service ecosystem research. They focused on the practical aspects of industrial service ecosystems in order to help explain what they need to encompass in order to facilitate industrial renewal.
Industrial renewal refers to the process of revitalizing or rejuvenating a given industrial sector. It generally involves implementing strategies and initiatives to modernize, upgrade, or transform existing practices to allow them to adapt to changing markets, to adopt technological advancements, to take into account environmental considerations, and to face up to global competition.
The team has identified three main characteristics in service ecosystem practice that will be useful in guiding future work: accomplishment, attractiveness, and actionability. Accomplishment refers to the ongoing process of creating value within the service ecosystem by bringing together technology, data, and skills. Attractiveness pertains to the ability of the ecosystem to draw in and retain talented people in the sector. Actionability emphasizes how effective the service ecosystem is in reaching useful goals as well as helping in the process of industrial renewal.
By offering a new perspective for research in this area, the team also provides useful insights for policymakers, businesses, and others involved in a range of industrial sectors. These insights should help us to use the concept of service ecosystems to tackle global problems by accelerating industrial renewal.
Nuutinen, M., Valkokari, K., Halttunen, M. and Palomäki, K. (2024) ‘Characteristics of industrial service ecosystem practices for industrial renewal’, Int. J. Services Technology and Management, Vol. 29, No. 1, pp.76–96.
The following paper, "Process window development of DED-LB/M process with coaxial wire for stainless steel AISI 316L" (International Journal of Experimental Design and Process Optimisation 7(3) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
A review in the International Journal of Grid and Utility Computing has investigated ways in which the increasing problem of duplicate data in computer storage systems might be addressed. Solutions to this problem could improve storage efficiency, system performance, and reduce the overall demand on resources.
Amdewar Godavari and Chapram Sudhakar of the department of Computer Science and Engineering at the National Institute of Technology Warangal in Warangal, Telangana, India explain how the advent of the Internet of Things (IoT) and the emergence of big data in science, engineering, medical, and many other areas has led to a massive increase in computer storage demand.
Some researchers have suggested that by 2025, the amount of stored data will amount to around 175 zettabytes (175 trillion terabytes). Other research has provided estimates of duplication in this data and suggests that around three-quarters, 75 percent, is wholly redundant. This redundancy leads to inefficient storage utilization and decreased performance in storage systems. Identifying the duplicate content that might be removed from a system is not a simple matter.
To address this challenge, the researchers point out that there are two general approaches. The first is data compression, which will compare files and crush file sizes based in the identification of duplicates. Full-on data deduplication, however, can compute a unique “hash value” for much larger blocks of data, compares those hashes to find blocks containing identical data and so flag them for removal as appropriate. This latter approach could be used to reduce the amount of down-time or latency that would otherwise impinge on performance and access.
The team suggests that various chunking algorithms and machine learning-based techniques might be used to identify redundant blocks of data. Their tests show that variable-sized chunking offers better deduplication ratios compared to fixed-sized chunking, although this approach is slower. The algorithmic approach, however, could allow redundancy categorization to use machine learning to improve efficiency still further.
Godavari, A. and Sudhakar, C. (2024) ‘A survey on deduplication systems’, Int. J. Grid and Utility Computing, Vol. 15, No. 2, pp.143–159.
International Journal of Exergy 43(4) 2024
Research in the International Journal of Environment and Waste Management has looked at how used diapers (baby nappies or adult napkins) and sanitary wear might be efficiently composted using cow dung a readily available by-product of cattle farming the world over.
Namasivayam Vasudevan, Greeshma Odukkathil, and Gomathi Ravi of the Centre for Environmental Studies at Anna University in Chennai, Tamilnadu, India, explain how absorbent hygiene products (AHPs) including diapers and sanitary wear are now ubiquitous in the developing and developed world having broadly displaced the washable and reusable alternatives. As such, they represent a growing waste disposal problem.
AHPs are generally not biodegradable unless somehow pre-processed nor easily recyclable, not least because of the waste they carry with them. They generally accumulate on rubbish dumps and in landfill in regions where such waste is not burnt. More than 250 tonnes of such waste enters the waste stream in Chennai alone each year, the team writes.
The team has looked at cow dung and effective microbes that might be able to break down used diapers and sanitary pads. They tested the putative composting process over a sixty-day period, recording chemical and physical changes in pH, moisture content, carbon-to-nitrogen ratio, and nutrient levels.
The team suggests that their results are somewhat promising. The compost derived from AHPs exhibited favourable characteristics, including a neutral pH, optimal moisture content, and suitable nutrient levels. There was, in addition, a significant drop in overall volume and mass, ranging from 70% to 85% during composting. This latter point suggests that the composted AHPs would if ultimately destined for landfill at least take up less volume in the site if processed in this way first. The chemical changes induced by composting would not necessarily make them useful as soil conditioner in other similar applications, but at least the processed materials would be somewhat less polluting. However, with further optimisation, it may well be possible to process used AHPs into a usable compost for an overall more ecologically conscious approach to their disposal.
Vasudevan, N., Odukkathil, G. and Ravi, G. (2024) ‘Effectiveness of cow dung and effective microorganisms on composting of napkins and diapers‘, Int. J. Environment and Waste Management, Vol. 33, No. 4, pp.511-523.
