International Journal of Grid and Utility Computing (9 papers in press)

Regular Issues

• Recommendation system based on space-time user similarity
  by Wei Luo, Zhihao Peng, Ansheng Deng 
  Abstract: With the advent of 5G, the way people get information and the means of information transmission have become more and more important. As the main platform of information transmission, social media not only brings convenience to people's lives, but also generates huge amounts of redundant information because of the speed of information updating. In order to meet the personalised needs of users and enable users to find interesting information in a large volume of data, recommendation systems emerged as the times require. Recommendation systems, as an important tool to help users to filter internet information, play an extremely important role in both academia and industry. The traditional recommendation system assumes that all users are independent. In this paper, in order to improve the prediction accuracy, a recommendation system based on space-time user similarity is proposed. The experimental results on Sina Weibo dataset show that, compared with the traditional collaborative filtering recommendation system based on user similarity, the proposed method has better performance in precision, recall and F-measure evaluation value.
  Keywords: time-based user similarity; space-based user similarity; recommendation system; user preference; collaborative filtering.
  
  
• Joint end-to-end recognition deep network and data augmentation for industrial mould number recognition  
  by RuiMing Li, ChaoJun Dong, JiaCong Chen, YiKui Zhai 
  Abstract: With the booming manufacturing industry, the significance of mould management is increasing. At present, manual management is gradually eliminated owing to need for a large amount of labour, while the effect of a radiofrequency identification (RFID) system is not ideal, which is limited by the characteristics of the metal, such as rust and erosion. Fortunately, the rise of convolutional neural networks (CNNs) brings down to the solution of mould management from the perspective of images that management by identifying the digital number on the mould. Yet there is no trace of a public database for mould recognition, and there is no special recognition method in this field. To address this problem, this paper first presents a novel data set aiming to support the CNN training. The images in the database are collected in the real scene and finely manually labelled, which can train an effective recognition model and generalise to the actual scenario. Besides, we combined the mainstream text spotter and the data augmentation specifically designed for the real world, and found that it has a considerable effect on mould recognition.
  Keywords: mould recognition database; text spotter; mould recognition; data augmentation.
  
  
• Assessment of a cuckoo search-based intelligent system for mesh routers placement optimisation in WMNs considering various distributions of mesh clients  
  by Shinji Sakamoto 
  Abstract: Wireless Mesh Networks (WMNs) have many advantages. However, they have several issues related to wireless communication. An effective approach to deal with these problems is the optimization of mesh routers placement in WMNs, but this is an NP-hard problem. Thus, heuristic and intelligent algorithms are needed. In the previous work, we developed an intelligent simulation system based on Cuckoo Search (CS) (WMN-CS), which is a meta-heuristic algorithm. In this work, we evaluate the WMN-CS performance for various distributions of mesh clients: Uniform, Normal, Exponential, Weibull and Chi-square distributions. The simulation results show that for Normal distribution the WMN-CS system can find suitable locations of mesh routers for about 30 phases. The Uniform distribution has the lowest performance compared to the other distributions. Also, Exponential andWeibull distributions converge slower than Chi-square distribution. However, Exponential distribution converges faster than Weibull distribution.
  Keywords: wireless mesh networks; node placement problem; cuckoo search; client distributions.
  DOI: 10.1504/IJGUC.2024.10068275
   
  
• Analysis of cybersecurity attacks and solution approaches  
  by Ali Yılmaz, Resul Das 
  Abstract: Numerous cybersecurity vulnerabilities have emerged as a result of the quickly changing digital environment, posing serious risks to people, corporations, and governments alike The article "An analysis cybersecurity attacks and solution approaches" delves into the subtleties of this contemporary conflict zone and offers a thorough analysis of the many assault vectors, techniques, and their far-reaching effects This article examines the full spectrum of online hazards, from well-known enemies such as malware, phishing, and denial-of-service attacks to more sophisticated and sneaky threats such as advanced persistent threats (APT) It explores the methods and strategies employed by cybercriminals, offering light on their always-changing approaches This article also sheds light on preventive measures and problem-solving techniques created to combat these risks Provides an overview of a wide range of cybersecurity techniques and tools, including artificial intelligence, intrusion detection systems, encryption, and multifactor authentication Individuals and organizations can protect their digital domains from the onslaught of cyberattacks by being aware of the threats and having the necessary tools and knowledge. With a clearer grasp of the cyberthreat landscape and the various solutions to reduce these risks, readers should be better equipped to use the internet safely as a result of this thorough analysis.
  Keywords: information security; cybersecurity; malware; network security; attacks; cyberthreats.
  DOI: 10.1504/IJGUC.2024.10068492
   
  
• A two-stage intrusion detection framework in IoT using random forest for binary and multi-class classification  
  by Arash Salehpour, Pejman Hosseinioun, MohammadAli Balafar 
  Abstract: The proliferation of IoT devices due to cyber threats, which have become increasingly sophisticated, requires a strong security framework. This paper proposed a new framework for Intrusion Detection System-IoT-IDs using a Random Forest classifier to first classify the attack into binary features and prepare a new dataset that would enable multiclass classification. It achieved an overall accuracy of 0.98 on the comprehensive UNSW-NB15 dataset, with very good performance in detecting 'Generic' attacks, having almost perfect precision, recall, and F1-score. it also presented cases of 'Analysis' and 'Backdoor' types of attacks, where further improvements should be done. All these models have been analyzed to find the pros and cons in IoT settings. The Random Forests, XGBoost and MLP. Further studies based on the research could be done on multiplying models with improved features, intrusion detection in real time, and more strong AI techniques. This paper focuses on addressing challenges with imbalanced classes and scalability concerns using data privacy preservation methods for improving the performance of IDS.
  Keywords: IDS; intrusion detection system; IoT; internet of things; ensemble learning; UNSWNB15; cybersecurity; hybrid models.
  DOI: 10.1504/IJGUC.2024.10071203
   
  
• Implementation and evaluation of a gesture-based virtual reality system for dementia prevention  
  by Kaisei Komoto, Naho Kuriya, Tomoyuki Ishida 
  Abstract: Japan is a super-aging society with the number of patients with dementia rising annually underscoring the crucial need for dementia prevention. Among various preventive methods, a method known as cognicise is gaining popularity. The term “cognicise” combines the words “cognition” and “exercise.” Towards dementia prevention, we developed a gesture-based virtual reality (VR) system that utilizes a depth camera and a stereo hand-tracking camera. The depth camera captures the player’s real-space walking movements and synchronizes them with a virtual avatar’s actions in the VR world. Additionally, the stereo hand-tracking camera recognizes the player’s hand gestures for playing the popular game rock-paper-scissors with a computer-generated virtual avatar. This system allows players to gamify their experience by engaging in rock-paper-scissors while walking through an immersive VR world. Although the system received high ratings across multiple evaluation criteria, specific issues were identified regarding the operability of the walk-through function.
  Keywords: dementia prevention; cognicise; virtual reality; gesture recognition.
  DOI: 10.1504/IJGUC.2025.10077271
   
  
• Application of improved PBFT based on double layer structure in enterprise supply chain information management  
  by Jiangna Liu, Yuxia Song, Congwei Zhang, Fei Guo 
  Abstract: In liquor enterprises, the traditional supply chain system information is centrally managed, which carries high risks. Therefore, it is necessary to upgrade the management methods. To improve the security of supply chain management in liquor enterprises, this study proposes to optimise the Practical Byzantine Fault Tolerance using a double layer structure and apply it to the supply chain management system. The optimisation process first divides the network nodes into multiple layers and then communicates based on the hierarchical nodes to achieve the effect of optimising communication complexity and improving security. Finally, the optimisation algorithm is applied to performance analysis in enterprise supply chain management. The experimental results showed that the improved Byzantine-fault Tolerance using a double layer structure could not only achieve a throughput of 2872 Tps when the number of nodes was 90 but also achieve a minimum latency of 0.43 s. Applying this algorithm to the system could achieve a maximum malicious node tolerance of 3374, and the application satisfaction score of different system modules could reach over 80 points. Therefore, the improved algorithm constructed in this study has excellent information management performance in the supply chain of liquor enterprises.
  Keywords: double layer structure; practical Byzantine fault tolerance; supply chain; blockchain technology; information management.
  DOI: 10.1504/IJGUC.2025.10077558
   
  
• A soldering motion analysis system for monitoring whole body of workers during soldering operation: evaluation for different scenarios  
  by Tetsuya Oda 
  Abstract: Soldering is one of the industrial techniques required in electronic device manufacturing plants to solder electric circuits which affects product quality. However, there are some danger situations or accidents during soldering for people with Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD) and Motor Disability (MD). In this paper, we propose a soldering motion analysis system to estimate the movement of a worker during soldering operation while seated in a chair. We considered three scenarios the safety movement, the general dangerous movement and the dangerous movement caused by characteristics of a person with disabilities during soldering. The performance evaluation shows that the proposed system is capable to recognize the body movements images by RGB-D camera. Also, the proposed system can assist beginners and persons with disabilities for safe soldering operations.
  Keywords: soldering; motion analysis; people with developmental disabilities; movements of soldering.
  
  

Special Issue on: Cloud and Fog Computing for Corporate Entrepreneurship in the Digital Era

• Study on the economic consequences of enterprise financial sharing model  
  by Yu Yang, Zecheng Yin 
  Abstract: Using enterprise system ideas to examine the business process requirements of firms, the Financial Enterprise Model (FEM) is a demanding program. This major integrates finance, accounting, and other critical business processes. Conventional financial face difficulties due to low economic inclusion, restricted access to capital, lack of data, poor R&D expenditures, underdeveloped distribution channels, and so on. This paper mentions making, consuming, and redistributing goods through collaborative platform networks. These three instances highlight how ICTs (Information and Communication Technologies) can be exploited as a new source of company innovation. The sharing economy model can help social companies solve their market problems since social value can be embedded into their sharing economy cycles. As part of the ICT-based sharing economy, new business models for social entrepreneurship can be developed by employing creative and proactive platforms. Unlike most public organizations, double-bottom-line organizations can create social and economic advantages. There are implications for developing and propagating societal values based on these findings.
  Keywords: finance; economy; enterprise; ICT; social advantage.