The enormous amount of data generated by sensors and other data sources in modern grid management systems requires new infrastructures, such as IoT (Internet of Things) and Big Data architectures. This, in combination with Data Mining techniques, allows the management and processing of all these heterogeneous massive data in order to discover new insights that can help to reduce the energy consumption of the building. In this paper, we describe a developed methodology for an Internet of Things (IoT) system based on a robust big data architecture.
View Article and Find Full Text PDFBackground: Body composition, currently evaluated by computed tomography scan, is related to poor evolution and severity of Crohn's disease (CD). Few MRI studies have been performed, yet it is the most commonly used imaging modality for the surveillance of the disease.
Aim: Evaluate the feasibility of MRI body composition measurement and compare the variation according to the activity of the disease.
Obstructive congenital anomalies of the kidney and urinary tract have a high risk of kidney failure if not surgically corrected. Dynamic renal scintigraphy is the gold standard technique to evaluate drainage curves and split renal function (SRF). To compare functional magnetic resonance (MR) urography with dynamic renal scintigraphy in measuring volumetric SRF and in the classification of drainage curves in patients with congenital anomalies of the kidney and urinary tract.
View Article and Find Full Text PDFObjectives: Assessment of perianal fistulas is important to guide management of Crohn's disease (CD). Our objectives were to analyze the feasibility of magnetization transfer (MT) imaging to assess fistulas and to evaluate its contribution in assessing disease activity.
Methods: During 15 months, all patients referred for perianal fistulas in CD underwent 3T-MRI including diffusion, T2/T1-weighted gadolinium-enhanced sequences and MT sequences (one with an off-resonance saturation pulse of 800 and one with 1200 Hz).