Tomographic Image Reconstruction of Fan-Beam Projections with Equidistant Detectors using Partially Connected Neural Networks

We present a neural network approach for tomographic imaging problem using interpolation methods and fan-beam projections. This approach uses a partially connected neural network especially assembled for solving tomographic\ud reconstruction with no need of training. We extended the calculations to perform reconstruction with interpolation and to allow tomography of fan-beam geometry. The main goal is to aggregate speed while maintaining or improving the quality of the tomographic reconstruction process

Instrumentos de queda livre para medição de parâmetros oceanográficos

This work deals with the development of free falling oceanographic instruments. The stability and constant speed during the fall are guaranteed by the action of rotary wings attached to a cilindric body. Signals from the sensors are brought aboard by electrical cable where they feed graphic or magnetic recorders. One can get profiles from the different parameters versus time which represents depth due to the constant falling speed. Among the principal characteristics of these instruments are the high rate of data acquisition, low cost, ease of handling and the possible use of single or multiple sensors. The development of the free falling body is presented followed by the adaptation of temperature, spectral irradiance and transmittance sensors to this body.Apresenta o desenvolvimento de instrumentos oceanográficos funcionando em princípio de queda livre. A queda livre estável e à velocidade constante é obtida pela ação de asas rotativas presas a um corpo cilíndrico que aloja os sensores e a parte eletrônica. Os sinais são trazidos para bordo por cabo elétrico onde alimentam registrador gráfico ou magnético obtendo-se assim perfis dos diversos parâmetros versus tempo, que, devido à queda à velocidade constante, representa a profundidade. Entre as principais características dessa família de instrumentos, estão a rapidez na aquisição de dados e facilidade de manuseio, a possibilidade de utilização de pequenas e grandes embarcações, o uso de sensores individuais ou múltiplos e o baixo custo. Apresenta-se o desenvolvimento de um corpo em queda livre e a incorporação de sensores para medição de temperatura, irradiância espectral e transmitância

Thumbs up, thumbs down:non-verbal human-robot interaction through real-time EMG classification via inductive and supervised transductive transfer learning

In this study, we present a transfer learning method for gesture classification via an inductive and supervised transductive approach with an electromyographic dataset gathered via the Myo armband. A ternary gesture classification problem is presented by states of ’thumbs up’, ’thumbs down’, and ’relax’ in order to communicate in the affirmative or negative in a non-verbal fashion to a machine. Of the nine statistical learning paradigms benchmarked over 10-fold cross validation (with three methods of feature selection), an ensemble of Random Forest and Support Vector Machine through voting achieves the best score of 91.74% with a rule-based feature selection method. When new subjects are considered, this machine learning approach fails to generalise new data, and thus the processes of Inductive and Supervised Transductive Transfer Learning are introduced with a short calibration exercise (15 s). Failure of generalisation shows that 5 s of data per-class is the strongest for classification (versus one through seven seconds) with only an accuracy of 55%, but when a short 5 s per class calibration task is introduced via the suggested transfer method, a Random Forest can then classify unseen data from the calibrated subject at an accuracy of around 97%, outperforming the 83% accuracy boasted by the proprietary Myo system. Finally, a preliminary application is presented through social interaction with a humanoid Pepper robot, where the use of our approach and a most-common-class metaclassifier achieves 100% accuracy for all trials of a ‘20 Questions’ game

An Elephant in the Room: Using Sampling for Detecting Heavy-Hitters in Programmable Switches

The ability to detect elephant flows in the forwarding device itself, i.e., a switch, facilitates the deployment of new advanced applications such as load-balancing, per-flow QoS management, etc. Sketches and Space Saving summarization techniques are used for elephant flow detection. However, their memory and computing requirements force the cooperation of an external controller device, due to the scarce resources of current programmable switches. To overcome this limitation, we adapt Sketch and Space Saving elephant flow detection techniques to operate with instant notification and sampled traffic. We evaluate the performance of the resulting techniques with three real traffic traces. The use of sampling allows the identification of a large share of the total traffic corresponding to the elephant flows with a low memory footprint and a reduction of the computing requirements in two orders of magnitude compared to unsampled versions. In turn, we observe a slight increase in the number of false positives and the number of flow notifications.The work of Alberto García-Martínez and Marcelo Bagnulo was supported by the TRUE5G Project ('Evolución hacia redes y servicios auto-gestionados para el 5G del futuro') by the Spanish National Research Agency under Grant PID2019-108713RB-C52/AEI/10.13039/501100011033

Bartolomeu: An SDN rebalancing system across multiple interdomain paths

Bartolomeu is a solution to enable stub networks to perform adaptive egress traffic load balancing across multiple interdomain routes by spreading the traffic across available paths according to a passive measurement of their performance. It defines a BGP-SDN architecture that increases the number of BGP routes that can be used by stub networks. Bartolomeu measures the available capacity of each path to any destination prefix, and allocates to each path a number of large flows that is proportional to its capacity. This strategy reduces the mean sojourn time, i.e., mean time to flow completion, compared to state-of-the-art traffic balancing techniques as ECMP. We develop a mathematical model to compute this time and compare with ECMP and single path (fast path) selection. An analysis of the traffic traces of two content providers was performed to ensure that our solution is deployable. An experiment with traffic exchange over the Internet is used to show that Bartolomeu can provide gains with real interfering traffic. A discrete-event simulator fed with the traces captured is used to asses Bartolomeu's gains with prefixes with different number of flows, and flows with different sizes and arrival time. We observe in this experiment that Bartolomeu can reduce the sojourn time, compared to ECMP, by half when path rates differ in a factor of 3, or to a sixth when path rates differ in a factor of 10. We compute the maximum number of per-flow entries and the maximum entry change request rate to show that the resources required fit in with the specifications of the current generation of SDN switches.The work of Pedro Rodrigues Torres-Jr. was partially supported by the Fundación Carolina, program Mobilidad SEGIB 2019. The work of Alberto García-Martínez was supported by the 5G-TRANSFORMER project, H2020-761536. The work of and Marcelo Bagnulo was supported in part by the 5G-TRANSFORMER project, and by the Spanish Ministry of Economy and Competitiveness under 5GCity project, TEC2016-76795-C6-3-R

Carotid Intern Aneurysms

Cerebral aneurysms (CA) are acquired lesions, affecting 5–10% of the population, being about three times more common in women than in men. The absolute majority of CA is asymptomatic. However, in symptomatic cases, cerebral aneurysms present without about 80% of cases with severe intracranial hemorrhage, with mortality up to 50% and severe morbidity of up to 80%. At this point, the carotid siphon is particularly important because it is the blood gateway to the anterior cerebral circulation, being the most sinuous portion of the internal carotid artery, and because it houses about 30% of the intracranial aneurysm. The constant interactions of blood flow with carotid siphon curvatures are apparently intrinsically related to the epidemiology of these lesions in the various locations of the intracranial circulation and their presentation form. It is well established that a greater anterior knee angle has a significant independent relation with intracranial aneurysms located after carotid siphon, larger aneurysms, and greater risk of rupture. These findings may be associated with the hemodynamic interactions of blood flow and the curvature of carotid siphon. Little is known about the anatomical changes in carotid siphon and, consequently, the repercussions of the hemodynamic changes that the neurosurgical interventions mechanisms could entail. Devices such as intracranial stents, detachable coils, and even clips of aneurysms can modify the morphology of carotid siphon, and the knowledge of these consequences could be used to obtain better therapeutic results. In the last 10 years, a new device for the treatment of intracranial aneurysms has been presenting promising results, flow diverters stents (FDS), and its use to treat aneurysms in carotid siphon appears to cause morphological changes characterized by increased anterior and posterior angles. Specifically, the anterior angle increase was associated with better angiographic results. Aneurysms of the extracranial carotid artery (ECAA) are rare and little is known about its natural history. The etiology is diverse and most ECAA are asymptomatic, but they may progress to a pulsatile mass, cranial nerve compression, or cause a stroke. ECAA treatment is still controversial and a better insight into natural history and risk of complications of the different treatments is needed in order to get the consensus

TWICE Dataset: Digital Twin of Test Scenarios in a Controlled Environment

Ensuring the safe and reliable operation of autonomous vehicles under adverse weather remains a significant challenge. To address this, we have developed a comprehensive dataset composed of sensor data acquired in a real test track and reproduced in the laboratory for the same test scenarios. The provided dataset includes camera, radar, LiDAR, inertial measurement unit (IMU), and GPS data recorded under adverse weather conditions (rainy, night-time, and snowy conditions). We recorded test scenarios using objects of interest such as car, cyclist, truck and pedestrian -- some of which are inspired by EURONCAP (European New Car Assessment Programme). The sensor data generated in the laboratory is acquired by the execution of simulation-based tests in hardware-in-the-loop environment with the digital twin of each real test scenario. The dataset contains more than 2 hours of recording, which totals more than 280GB of data. Therefore, it is a valuable resource for researchers in the field of autonomous vehicles to test and improve their algorithms in adverse weather conditions, as well as explore the simulation-to-reality gap. The dataset is available for download at: https://twicedataset.github.io/site/Comment: 8 pages, 13 figures, submitted to IEEE Sensors Journa

Alterations in the stomatognathic system due to amyotrophic lateral sclerosis

Objectives: To compare the molar bite force, electromyographic activity, chewing efficiency and thickness of the masseter and temporalis muscles in individuals with amyotrophic lateral sclerosis (ALS) and healthy individuals. Material and Methods: Thirty individuals enrolled in the study were divided into the study group (with ALS, n=15) and control group (healthy individuals, n=15). Data regarding molar bite force (right and left), electromyographic activity (mandibular rest, right and left laterality, protrusion, and maximum voluntary contraction), chewing efficiency (habitual and non-habitual), and masticatory muscle thickness (rest and maximum voluntary contraction) were tabulated and subjected to statistical analysis (Student’s t-test, p≤0.05). Results: Comparisons between the groups demonstrated a statistically significant increase in the electromyographic activity of the right masseter (p=0.03) and left masseter (p=0.03) muscles during mandibular rest; left masseter (p=0.00), right temporalis (p=0.00), and left temporalis (p=0.03) muscles during protrusion; and right masseter (p=0.00), left masseter (p=0.00), and left temporalis (p=0.00) muscles during left laterality, in individuals with ALS as compared with healthy individuals. A statistically significant decrease was observed in the habitual chewing efficiency of the right masseter (p=0.00) and right temporalis (p=0.04) muscles in individuals with ALS. No statistically significant difference between the groups was found the masticatory muscle thickness and maximal molar bite force. Conclusions: ALS may lead to modifications in the activities of the stomatognathic system, including muscular hyperactivity and reduction in chewing efficiency; however, no change has been observed in the masticatory muscle thickness and molar bite force

Development of a plasma activated multifunctional polyester fabric using zinc oxide nanoparticles and citronella oil microcapsules

There is a high demand for the development of textiles possessing multifunctional properties for outdoor, protective and health care applications. The coating of polyester (PES) textiles with metal nanoparticles and essential oils may act in a synergistic mode to obtain materials with improved antimicrobial and UV-protection properties. However, the lack of functional groups onto PES structure makes the adhesion of particles a difficult task. In this work, PES fabric was activated by dielectric barrier discharge (DBD) plasma treatment, and functionalized with zinc oxide nanoparticles (ZnO NPs) and poly (methyl methacrylate) (PMMA)-citronella microcapsules by dip-coating