Search

Researchers at the University of Padova in Italy have developed an Internet of Things (IoT) system that monitors the heart rate of an opera singer in real time and provides feedback. The system also adds effects to manipulate the sounds emitted by the singer's body during a self-healing practice. The system was designed in collaboration with an opera singer who suffered from a carotid aneurysm, and it allows the singer to rest and alternate between demanding and less demanding singing techniques during a performance. The research found that the system had a positive effect on the singer's practice and could have potential applications in different performative scenarios. [Extracted from the article]

Researchers from the University of Science & Technology Oran Mohamed Boudiaf in Algeria have developed a bio-inspired spiking network model based on Hodgkin-Huxley neurons for human motion perception. The model mimics the mechanisms of direction selectivity found in the primary visual cortex and effectively replicates the directional selectivity operation of the visual cortex when presented with time-varying images. The model's motion maps can be used for action recognition in input videos and show competitive performance in motion segmentation tasks. This research has been peer-reviewed and published in Cognitive Neurodynamics. [Extracted from the article]

A researcher from Universita degli Studi di Milano has published a new study on computer security, specifically focusing on ensuring cybersecurity for industrial networks. The study highlights the vulnerability of industrial control systems (ICSs) to security risks due to the increased adoption of the Internet Protocol (IP). The researcher proposes a protocol called ArpON, which effectively prevents ARP cache poisoning attempts in real time, without incurring high operational costs or requiring hardware features or cryptography functionality. Simulation results demonstrate the effectiveness of ArpON in avoiding ARP poisoning with minimal communication overhead. The full research article is available for free online. [Extracted from the article]

A study conducted in Wenzhou, People's Republic of China, proposes the use of an explainable deep neural network called XAIRL to segment foot infrared imaging datasets. The study compares the results of XAIRL with other algorithms and finds that XAIRL performs the best in terms of accuracy, precision, recall, F1 score, intersection over union, Dice similarity coefficient, boundary displacement error, Hausdorff distance, and receiver operating characteristic. The researchers suggest that these machine learning-based algorithms can be used to analyze foot temperature and pressure distribution, which can help customize shoes for individual wearers and reduce the risk of foot injuries, especially for those with high blood pressure. [Extracted from the article]

A recent report from the University of Sfax discusses the challenges of security in wireless body sensor networks (WBSNs) and the Internet of Medical Things (IoMT) in healthcare technology. The report proposes a solution called the Enhanced Random Forest Classifier with K-Means Clustering (ERF-KMC) algorithm, which combines the accuracy of the enhanced random forest classifier with the clustering capabilities of K-means. This algorithm enhances security in IoMT networks by detecting and categorizing attack messages, specifically distinguishing between man-in-the-middle (MITM) and distributed denial of service (DDoS) attacks. The ERF-KMC algorithm also improves network performance metrics and contributes to the reliability and security of IoMT systems. [Extracted from the article]

Researchers from the Institute of Computer Science in Iasi, Romania, have conducted experiments on iris image classification using texture features and SURF (Speeded Up Robust Features) keypoints. They developed a method called DENOL, which generates a fixed number of SURF keypoints for each image by adapting the Hessian threshold parameter. The experiments used two well-known datasets, UBIRIS and UPOL, and the results were comparable to those obtained using Masek implementation of Daugman's method. For more information, readers can refer to the research article published in Memoirs of the Scientific Sections of the Romanian Academy. [Extracted from the article]