A novel architecture for the field of industrial automation is described, goals which are: 1) computation optimal production plans; 2) automated usage optimized 3) flexibility and reusability at development maintenance; 4) seamless transition from current practice to approach introduced herein. The consists three main components: a set OPC unified (UA) servers, are used model information device level; services organized into two layers (basic complex services), act as link between first...

In recent years, powered by state-of-the-art achievements in a broad range of areas, machine learning has received considerable attention from the healthcare sector. Despite their ability to provide solutions within personalized medicine, strict regulations on confidentiality patient health information have many cases hindered adoption deep learning-based clinical workflows. To allow for processing sensitive without disclosing underlying data, we propose solution based fully homomorphic...

We introduce a patient-specific model for coronary circulation, by combining anatomical, hemodynamic and functional information from medical images other clinical observations. The main components of the coupled are: lumped heart model, reduced-order hemodynamics in arterial vessel tree (both healthy stenosed), physiological microvascular bed. anatomy is extracted Coronary Computed Tomography Angiography (CTA) images, followed an estimation impedance distal network. For blood flow...

We introduce a Computational Fluid Dynamics (CFD) based method for performing patient-specific coronary hemodynamic computations under two conditions: at rest and during drug-induced hyperemia. The proposed is on novel estimation procedure determining the boundary conditions from non-invasively acquired patient data rest. A multi-variable feedback control framework ensures that computed mean arterial pressure flow distribution matches estimated values an individual state. hyperemia are...

Data privacy is a major concern when accessing and processing sensitive medical data. A promising approach among privacy-preserving techniques homomorphic encryption (HE), which allows for computations to be performed on encrypted Currently, HE still faces practical limitations related high computational complexity, noise accumulation, sole applicability the at bit or small integer values level. We propose herein an encoding method that enables typical schemes operate real-valued numbers of...

Following the reports of breakthrough performances, machine learning based applications have become very popular in medical field. However, with recent increase concerns related to data privacy, and publication specific regulations (e.g. GDPR), development and, thus, exploitation deep clinical decision making processes, has been rendered impossible many cases. Herein, we describe evaluate an approach that employs Fully Homo-morphic Encryption for allowing computations be performed on...

Among all the sub-sections in a typical radiology report, Clinical Indications, Findings, and Impression often reflect important details about health status of patient. The information included is also covered Findings. While Findings can be deduced by inspecting image, Indications require additional context. cognitive task interpreting medical images remains most critical time-consuming step workflow. Instead generating an end-to-end this paper, we focus on from automated interpretation...

Deep learning (DL)-based algorithms have demonstrated remarkable results in potentially improving the performance and efficiency of healthcare applications. Since data typically needs to leave facility for performing model training inference, e.g., a cloud based solution, privacy concerns been raised. As result, demand privacy-preserving techniques that enable DL inference on secured has significantly grown. We propose an image obfuscation algorithm combines variational autoencoder (VAE)...

We propose a numerical implementation based on Graphics Processing Unit (GPU) for the acceleration of execution time Lattice Boltzmann Method (LBM). The study focuses application LBM patient-specific blood flow computations, and hence, to obtain higher accuracy, double precision computations are employed. specific operations grouped into two kernels, whereas only one them uses information from neighboring nodes. Since regularly 1/5 or less nodes represent fluid nodes, an indirect addressing...

Stencil based algorithms are used intensively in scientific computations. Graphics Processing Units (GPU) implementations of stencil computations speed-up the execution significantly compared to conventional CPU only systems. In this paper we focus on double precision computations, which required for meeting high accuracy requirements, inherent Starting from two baseline (using dimensional and three thread block structures respectively), employ different optimization techniques lead seven...

The paper describes an optimized GPU based approach for stencil algorithms. simulations have been performed a two dimensional steady state heat conduction problem, which has solved through the red black point successive over relaxation method. Two kernels developed and their performance greatly improved coalesced memory accesses special shared approaches. described in does not only represent step forward problem but also any other algorithm performs numerical solution of partial differential...

Abstract Although having been the subject of intense research over years, cardiac function quantification from MRI is still not a fully automatic process in clinical practice. This partly due to shortage training data covering all relevant cardiovascular disease phenotypes. We propose synthetically generate short axis CINE using generative adversarial model expand available sets that consist predominantly healthy subjects include more cases with reduced ejection fraction. introduce deep...

The industrial environment has gone through the fourth revolution, also called “Industry 4.0”, where main aspect is digitalization. Each device employed in an process connected to a network Internet of things (IIOT). With IIOT manufacturers being capable tracking every device, it become easier prevent or quickly solve failures. Specifically, large amount available data allowed use artificial intelligence (AI) algorithms improve applications many ways (e.g., failure detection, optimization,...

We propose a hierarchical parameter estimation framework for performing patient-specific hemodynamic computations in arterial models, which use structured tree boundary conditions. A calibration problem is formulated at each stage of the framework, seeks fixed point solution nonlinear system equations. Common properties, like resistance and compliance, are estimated first order to match objectives given by clinical measurements pressure and/or flow rate. The second estimates parameters trees...

This paper presents the synthesis of a SCADA (supervisory control and data acquisition) system, named Pollution Guard, designed to collect process atmospheric pollution measured in several strategic points region. Guard makes use GPRS (general packet radio service) communication infrastructure from mobile provider that covers very large area, practically air being collected every place country. In comparison other similar systems, new functionalities provided by are SMS (short messaging...

SUMMARY One‐dimensional blood flow models have been used extensively for computing pressure and waveforms in the human arterial circulation. We propose an improved numerical implementation based on a graphics processing unit (GPU) acceleration of execution time one‐dimensional model. A novel parallel hybrid CPU–GPU algorithm with compact copy operations (PHCGCC) GPU only (PGO) are developed, which compared against previously introduced PHCG versions, single‐threaded CPU multi‐threaded...

This paper addresses the issue of modelling concurrent systems whose structure is subject to changes by using an extension Petri nets formalism. Within this scope, we introduce concept reconfigurable finite capacity and apply it a flexible manufacturing system model. Besides providing designer facile means expressing dynamic character system, formalism also simplifies In second part present compare net model equivalent for such evaluate these models PetriNetExec, software library supporting...

Information retrieval is a technique used in search engines, advertisement placement and cognitive databases. With increasing amounts of data stringent response time requirements, improving the underlying implementation document becomes critical. To this end, we consider Bloom filter, simple randomized structure that answers membership queries with no false negative customizable positive probability. Mainly, focus on speed-up algorithm by using Graphics Processing Units (GPU) based...

We introduce a model-based approach for the non-invasive estimation of patient specific, left ventricular PV loops. A lumped parameter circulation model is used, composed pulmonary venous circulation, atrium, ventricle and systemic circulation. fully automated framework introduced personalization, two sequential steps: first, series parameters are computed directly, and, next, automatic optimization-based calibration method employed to iteratively estimate values remaining parameters. The...

Motivated by state-of-the-art performances across a wide variety of areas, over the last few years Machine Learning has drawn significant amount attention from healthcare domain. Despite their potential in enabling person-alized medicine applications, adoption Deep based solutions clinical workflows been hindered many cases strict regulations concerning privacy patient health data. We propose solution that relies on Fully Homomorphic Encryption, particularly MORE scheme, as mechanism for...

The paper demonstrates the use of nonresistive secondary control an induction motor to improve efficiency, power factor and torque. A mathematical algorithm is presented predict requirements in terms capacitance. required capacitance implemented by a novel electronic switching technique that effectively increases value used capacitor. This overcomes high-capacitance demand provides feasible solution. Experimental verification results obtained from small drive.

The single/two phase induction motor startup is usually done by connecting the auxiliary winding of to mains; provide phase-shift supply voltage with respect mains voltage, a series capacitor, also called split capacitor connected named winding. In steady state operation switched-off or run-capacitor reduce currents through To optimize efficiency drive both at and in steady-state various structures have been proposed presented literature. A simple structure use an electronically switched...