Abstract
This study presents and applies noninvasive subject specific validation of human whole-body (WB) center of mass (COM) kinematic from 3D anthropometric multibody model using dynamic data from ground reaction forces during impulse phase at standard maximum vertical jump (MVJ) with long countermovement (CM) on countermovement jump (CMJ) and short CM on drop jump (DJ) for comparison with MVJ without CM on squat jump (SJ), assessing lower limb CM contribution and muscle stretch-shortening cycle (SSC) at WB COM vertical impulse. A small group of n = 6 sports and physical education degree students with (21.5 ± 1.4) years old, without previous injuries, specific sport abilities or train were weighed (76.7 ± 9.3) kg and their height measured (1.79 ± 0.06) m. Adhesive reflective marks were attached at main upper and lower limb joints. Each subject performed a total of 3 trial at each MVJ, CMJ, DJ and SJ. During trial tests kinematics of anatomical points were registered with two JVC GR-VL9800 digital video cameras at 100 Hz and ground reaction forces with AMTI platform model BP2416-4000 CE operating at 1000 Hz. WB COM kinematics was determined using calibrated SIMI motion tracking of joint reflective marks and Dempster model selecting vertical WB COM displacement ?zk according to higher amplitude and research interest on MVJ WB COM movement for CM and SSC assessment. Dynamic of WB COM vertical displacement ?zd was determined from double time integration of COM vertical acceleration. Comparison of kinematic ?zk and dynamic ?zd was statistically tested on average and variance at each MVJ type, ?zk with ?zd and on root mean square-error (RMSE) during impulse phase. Results present similar variability of ?zk and ?zd at each MVJ p > 0.05, with mean values discriminating CMJ different means p < 0.05 from DJ and SJ with equal means p > 0.05, pointing dynamic data as suitable for validation of WB COM movement from 3D anthropometric image as well as for detection of different RMSE at each type of MVJ, its influence on assessment of CM and SSC and improve accuracy on kinematic, dynamic measurements and models. © Springer Nature Switzerland AG 2019.

Abstract
This study has the objective of select the best service at image processing and recognition, running in the cloud, and best suited for usage in systems to aid and improve the daily lives of blind people. To accomplish this purpose, a set of candidate services was built, including Microsoft Cognitive Services and Google Cloud Vision. A test mobile app was developed to automatically take pictures, which are sent to the online cloud services for processing. The results and the functionalities were evaluated with the aim to measure their accuracy and relevance. The following variables were registered: relative accuracy, represented by the ratio of the number of accurate results vs. the number of results shown; confidence degree, representing the service accuracy (when provided by the service); and relevance, identifying situations that can be useful in the daily lives of the blind people. The results have shown that these two services, Microsoft Cognitive Services and Google Cloud Vision, provided good accuracy and significance, in supporting systems to help blind people in their daily tasks. It was chosen some functionalities in two APIs of services running in the cloud like face identification, image description, objects, and text recognition. © BEIESP.

Abstract
Renewable energy resources are integrated into microgrid through power converters. During abnormal situations like PV intermittency and load variations, the controller plays the most key role. In this paper, a combined control method is proposed and it consists of model predictive control (MPC) and sliding mode control (SMC) for power converters. The voltage source inverter (VSI) is controlled by using MPC, while the DC-DC boost converter is controlled by using SMC. Discrete state space model of interlinking inverter, LC-filter and load is used to predict the future trend of load voltage for each of the eight switching states. On the other hand, the detailed SMC model for boost converter is analyzed for fast convergence rate with finite-time convergence and chattering free signals. A comparison between the proposed control method and the control method based on PID is presented to illustrate the superiority of the proposed method. The performance of the proposed control strategy is verified by the simulation results. The controller performance is analyzed under different scenarios including fluctuating generation and variable loads. Unlike conventional PID controllers, the proposed strategy is simple and robust with a fast-dynamic response.

Abstract
In this paper we describe a comparative classification of Pneumonia using Convolution Neural Network. The database used was the dataset Labeled Optical Coherence Tomography (OCT) and Chest X-Ray Images for Classification made available by (Kermany, 2018) with a total of 5863 images, with 2 classes: normal and pneumonia. To evaluate the generalization capacity of the models, cross-validation of k-fold was used. The classification models proved to be efficient compared to the work of (Kermany et al., 2018) which obtained 92.8 % and the present work had an average accuracy of 95.30 %.

Abstract
The wavelength sensitivity and spectral resolution of Mach-Zehnder fiber interferometers obtained through a combination of two identical uncoated and titanium dioxide (TiO2) coated long period fiber gratings (LPFGs) is presented and compared with single LPFGs-based refractometric sensors. A set of LPFGs were fabricated in single mode fiber with the resonance band having an amplitude of 3 dB in order to split in half the optical power between the core and the specific cladding modes. The separation between the pair of LPFG written in the fiber was varied between 1 and 3 cm and the thickness of the TiO2 coating around the fiber ranged from 20 to 40 nm. A wavelength shift sensitivity of 216 nm/refractive index units (RIU) was achieved for the device with 3 cm and a 30-nm thick TiO2 coating, which presented a spectral resolution of 1.1 x 10(-4 )Rill Despite the lower wavelength shift sensitivity of 142 nm/RIU, attained for a 2-cm long device and 30-nm thick TiO2 coating, a spectral resolution of 1.8 x 10(-5) RIU was measured, which is one order of magnitude lower than a single LPFG.

Abstract
A multiplicity of innovative applications has been developed based on the mobile crowdsourcing (MCS) paradigm. One group of applications addresses the creation of accessibility maps in large cities. In this context, a conceptual model of a system for the detection and the timely notification of the existence of temporary obstacles and other dangers in the urban environment is proposed in "Pervasive Crowd Mapping for Dynamic Environments". This concept (PCM4DE) encompasses, among other technologies, the use of crowdsourcing. The system will be particularly useful to people with disabilities and elderly people. An exploratory literature review showed that data quality and the motivation strategies fur participating in the systems based on MCS remain two of the key challenges to the effectiveness of those systems. This paper aims to contribute to the implementation of the PCM4DE concept by proposing the development of a mechanism that should improve the data quality through motivation forms which will enable a positive personal user experience, i.e., an experience which meets the participant's objectives, needs and preferences.