Search results for "Computer Science Applications"
showing 10 items of 3993 documents
Atlas-Based Evaluation of Hemodynamic in Ascending Thoracic Aortic Aneurysms
2021
Atlas-based analyses of patients with cardiovascular diseases have recently been explored to understand the mechanistic link between shape and pathophysiology. The construction of probabilistic atlases is based on statistical shape modeling (SSM) to assess key anatomic features for a given patient population. Such an approach is relevant to study the complex nature of the ascending thoracic aortic aneurysm (ATAA) as characterized by different patterns of aortic shapes and valve phenotypes. This study was carried out to develop an SSM of the dilated aorta with both bicuspid aortic valve (BAV) and tricuspid aortic valve (TAV), and then assess the computational hemodynamic of virtual models ob…
Assessing the Electrochemical Performance of Different Nanostructured CeO2 Samples as Anodes for Lithium-Ion Batteries
2021
In this work, six samples of CeO2 are successfully prepared by diverse synthesis routes leading to different microstructures regarding both morphology and particle size. The structural and microstructural characteristics presented by the samples and their influence on the electrochemical response of the prepared anodes are analyzed. In particular, the Ce-CMK3 sample, synthesized from a mesoporous carbon obtained through a CMK3 silica template, displays an enhanced electrochemical response. Thus, capacity values of ~220 mA h g−1 are obtained at a current rate of 0.155 A g−1 after 50 cycles and an excellent cyclability at intermediate current densities. On the other hand, it is observed that …
Analysis of Upper Limbs Target-Reaching Movement and Muscle Co-Activation in Patients with First Time Stroke for Rehabilitation Progress Monitoring
2022
In this paper, the authors analysed changes occurring during the rehabilitation processes in patients after early stroke based on analysis of their upper limbs’ target-reaching movement and muscle co-activation. Ischemic stroke often results in reduced mobility of the upper extremities and frequently is a cause for long-term disability. The ever-developing technology of 3D movement analysis and miniaturisation of equipment for testing the bioelectrical activity of muscles can help to assess the progress of rehabilitation. The aim of this study was to examine the use of analysis of target-reaching movement indicators and muscle co-activation for diagnosing the rehabilitation process in post-…
Towards an Assembly Support System with Dynamic Bayesian Network
2022
Due to the new technological advancements and the adoption of Industry 4.0 concepts, the manufacturing industry is now, more than ever, in a continuous transformation. This work analyzes the possibility of using dynamic Bayesian networks to predict the next assembly steps within an assembly assistance training system. The goal is to develop a support system to assist the human workers in their manufacturing activities. The evaluations were performed on a dataset collected from an experiment involving students. The experimental results show that dynamic Bayesian networks are appropriate for such a purpose, since their prediction accuracy was among the highest on new patterns. Our dynamic Bay…
On Unsupervised Methods for Medical Image Segmentation: Investigating Classic Approaches in Breast Cancer DCE-MRI
2021
Unsupervised segmentation techniques, which do not require labeled data for training and can be more easily integrated into the clinical routine, represent a valid solution especially from a clinical feasibility perspective. Indeed, large-scale annotated datasets are not always available, undermining their immediate implementation and use in the clinic. Breast cancer is the most common cause of cancer death in women worldwide. In this study, breast lesion delineation in Dynamic Contrast Enhanced MRI (DCE-MRI) series was addressed by means of four popular unsupervised segmentation approaches: Split-and-Merge combined with Region Growing (SMRG), k-means, Fuzzy C-Means (FCM), and spatial FCM (…
Anodic Alumina Membranes: From Electrochemical Growth to Use as Template for Fabrication of Nanostructured Electrodes
2022
The great success of anodic alumina membranes is due to their morphological features coupled to both thermal and chemical stability. The electrochemical fabrication allows accurate control of the porous structure: in fact, the membrane morphological characteristics (pore length, pore diameter and cell density) can be controlled by adjusting the anodizing parameters (bath, temperature, voltage and time). This article deals with both the fabrication and use of anodic alumina membranes. In particular, we will show the specific role of the addition of aluminum ions to phosphoric acid-based anodizing solution in modifying the morphology of anodic alumina membranes. Anodic alumina membranes were …
A Methodology for Exploiting Smart Prosumers’ Flexibility in a Bottom-Up Aggregation Process
2022
The electrical power system is evolving in a way that requires new measures for ensuring its secure and reliable operation. Demand-side aggregation represents one of the more interesting ways to provide ancillary services by the coordinated management of a multitude of different distributed resources. In this framework, aggregators play the main role in ensuring the effectiveness of the coordinated action of the distributed resources, usually becoming mediators in the relation between distribution system operators and smart prosumers. The research project DEMAND recently introduced a new concept in demand-side aggregation by proposing a scheme without a central aggregator where prosumers ca…
Simple Lossless Inductive Snubbers-Assisted Series Load Resonant Inverter Operating under ZCS-PDM Scheme for High-Frequency Induction Heating Fixed R…
2022
This paper presents a high-frequency pulse-density-modulated (PDM) soft-switching series load resonant inverter for use in induction heating (IH) fixed roller applications, which is used in copy and printing machines. The proposed simple high-frequency resonant inverter uses an asymmetrical pulse pattern PDM control scheme to achieve complete zero-current soft-switching commutations over a wide output range of input power regulation. Additionally, when the printer toner requires operation in very light load conditions, this causes difficulty in achieving zero-voltage or zero-current soft-switching operations in the IH high-frequency resonant inverters with pulse frequency modulation or puls…
Application of Hydrogen Peroxide to Improve the Microbiological Stability of Food Ice Produced in Industrial Facilities
2022
This work was aimed to produce an “active” food ice to preserve its microbiological safety over time. With this in mind, ice cubes were processed with the addition of H2O2 to water before freezing. Four food ice productions were performed at the industrial level: one control trial without the addition of H2O2 (0OX) and three experimental trials obtained by adding 4, 8, and 12 mg/L of H2O2 (4OX, 8OX, and 12OX), respectively. After production, all food ice trials were artificially contaminated with 102 CFU/100 mL of water-borne pathogenic bacteria (Escherichia coli ATCC 25922, Enteroccus faecalis ATCC 29212, and Pseudomonas aeruginosa ATCC 27853) inoculated individually. Thawed ice samples we…
Development of a Novel Object Detection System Based on Synthetic Data Generated from Unreal Game Engine
2022
This paper presents a novel approach to training a real-world object detection system based on synthetic data utilizing state-of-the-art technologies. Training an object detection system can be challenging and time-consuming as machine learning requires substantial volumes of training data with associated metadata. Synthetic data can solve this by providing unlimited desired training data with automatic generation. However, the main challenge is creating a balanced dataset that closes the reality gap and generalizes well when deployed in the real world. A state-of-the-art game engine, Unreal Engine 4, was used to approach the challenge of generating a photorealistic dataset for deep learnin…