ROI-Based On-Board Compression for Hyperspectral Remote Sensing Images on GPU.

In recent years, hyperspectral sensors for Earth remote sensing have become very popular. Such systems are able to provide the user with images having both spectral and spatial information. The current hyperspectral spaceborne sensors are able to capture large areas with increased spatial and spectral resolution. For this reason, the volume of acquired data needs to be reduced on board in order to avoid a low orbital duty cycle due to limited storage space. Recently, literature has focused the attention on efficient ways for on-board data compression. This topic is a challenging task due to the difficult environment (outer space) and due to the limited time, power and computing resources. Often, the hardware properties of Graphic Processing Units (GPU) have been adopted to reduce the processing time using parallel computing. The current work proposes a framework for on-board operation on a GPU, using NVIDIA's CUDA (Compute Unified Device Architecture) architecture. The algorithm aims at performing on-board compression using the target's related strategy. In detail, the main operations are: the automatic recognition of land cover types or detection of events in near real time in regions of interest (this is a user related choice) with an unsupervised classifier; the compression of specific regions with space-variant different bit rates including Principal Component Analysis (PCA), wavelet and arithmetic coding; and data volume management to the Ground Station. Experiments are provided using a real dataset taken from an AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) airborne sensor in a harbor area.

Recent Advances and Future Directions in Syncope Management: A Comprehensive Narrative Review.

Syncope is a highly prevalent clinical condition characterized by a rapid, complete, and brief loss of consciousness, followed by full recovery caused by cerebral hypoperfusion. This symptom carries significance, as its potential underlying causes may involve the heart, blood pressure, or brain, leading to a spectrum of consequences, from sudden death to compromised quality of life. Various factors contribute to syncope, and adhering to a precise diagnostic pathway can enhance diagnostic accuracy and treatment effectiveness. A standardized initial assessment, risk stratification, and appropriate test identification facilitate determining the underlying cause in the majority of cases. New technologies, including artificial intelligence and smart devices, may have the potential to reshape syncope management into a proactive, personalized, and data-centric model, ultimately enhancing patient outcomes and quality of life. This review addresses key aspects of syncope management, including pathogenesis, current diagnostic testing options, treatments, and considerations in the geriatric population.