Alagheband, Mahdi R. Mashatan, Atefeh
Published in
The Journal of Supercomputing
The Internet of Things (IoT) is increasingly becoming widespread in different areas such as healthcare, transportation, and manufacturing. IoT networks comprise many diverse entities, including smart small devices for capturing sensitive information, which may be attainable targets for malicious parties. Thus security and privacy are of utmost impo...
Fang, Zheng Ye, Bichao Yuan, Bingan Wang, Tingjun Zhong, Shuo Li, Shunren Zheng, Jianyi
Published in
The Journal of Supercomputing
Computer Tomography (CT) is a complicated imaging system, requiring highly geometric positioning. We found a special artifact caused by detection plane tilted around z-axis. In short scan cone-beam reconstruction, this kind of geometric deviation result in half circle shaped fuzzy around highlighted particles in reconstructed slices. This artifact ...
Fu, Junchen Qi, Zhaohui
Published in
The Journal of Supercomputing
E-commerce platforms usually train their recommender system models to achieve personalized recommendations based on user behavior data. User behavior can be categorized into implicit and explicit feedback. Explicit feedback data have been well studied. However, the implicit feedback data still have many issues, such as the multiple types of behavio...
Binbusayyis, Adel Alaskar, Haya Vaiyapuri, Thavavel Dinesh, M.
Published in
The Journal of Supercomputing
Internet of Medical Things (IoMT) is network of interconnected medical devices (smart watches, pace makers, prosthetics, glucometer, etc.), software applications, and health systems and services. IoMT has successfully addressed many old healthcare problems. But it comes with its drawbacks essentially with patient’s information privacy and security ...
Kumar, Vinod Mahmoud, Mahmoud Shuker Alkhayyat, Ahmed Srinivas, Jangirala Ahmad, Musheer Kumari, Adesh
Published in
The Journal of Supercomputing
With the fast growth of technologies like cloud computing, big data, the Internet of Things, artificial intelligence, and cyber-physical systems, the demand for data security and privacy in communication networks is growing by the day. Patient and doctor connect securely through the Internet utilizing the Internet of medical devices in cloud-health...
Nayak, Janmenjoy Meher, Saroj K. Souri, Alireza Naik, Bighnaraj Vimal, S.
Published in
The Journal of Supercomputing
The Internet of Medical Things (IoMT) is a bionetwork of allied medical devices, sensors, wearable biosensor devices, etc. It is gradually reforming the healthcare industry by leveraging its capabilities to improve personalized healthcare services by enabling seamless communication of medical data. IoMT facilitates prompt emergency responses and pr...
Tripathi, Dipty Biswas, Amit Tripathi, Anil Kumar Singh, Lalit Kumar Chaturvedi, Amrita
Published in
The Journal of Supercomputing
In this work, we propose a multi-tier architectural model to separate functionality and security concerns for distributed cyber-physical systems. On the line of distributed computing, such systems require the identification of leaders for distribution of work, aggregation of results, etc. Further, we propose a fault-tolerant leader election algorit...
Li, Xiaowen Lu, Ran Liu, Peiyu Zhu, Zhenfang
Published in
The Journal of Supercomputing
Aspect-level sentiment classification has been widely used by researchers as a fine-grained sentiment classification task to predict the sentiment polarity of specific aspect words in a given sentence. Previous studies have shown relatively good experimental results using graph convolutional networks, so more and more approaches are beginning to ex...
Mittal, Payal Sharma, Akashdeep Singh, Raman Sangaiah, Arun Kumar
Published in
The Journal of Supercomputing
This paper compares the classification performance of machine learning classifiers vs. deep learning-based handcrafted models and various pretrained deep networks. The proposed study performs a comprehensive analysis of object classification techniques implemented on low-altitude UAV datasets using various machine and deep learning models. Multiple...
Wang, Yun Huang, Lu Yee, Austin Lin
Published in
The Journal of Supercomputing
This study was carried out with the aim of exploring the full-convolution Siamese network (SiamFC) in the application of neonatal facial video image tracking, achieving accurate recognition of neonatal pain and helping doctors evaluate neonatal emotions in an automatic manner. The current technology shows low accuracy on facial image recognition of...