Issues’21 - Issues in Education

In the scope of the INW21, an international scientific joint event organized by Politécnico do Porto – Escola Superior de Educação (International Relations Office) and inED – Centre for Research and Innovation in Education, teachers, researchers and staff working in the field of Education joined together to share, discuss, reflect on and develop their ideas on topics related to Networking in Education. This meeting offered good opportunities for intercultural exchange and both personal and academic development. Therefore, professionals who attended the INW21 Conference / International Week had the chance to get in touch with high quality presentations which portray the rich research projects that we, educational practitioners, have been undertaking. Therefore, in order to make record of these presentations, a call for chapters has been promoted. In this way, issuEs 21 – Issues in Education, an e-Book, has been born.This publication is funded by National Funds through the FCT - Fundação para a Ciência e a Tecnologia, I.P., under the scope of the project UIDB/ 05198/2020 (Centre for Research and Innovation in Education, inED).info:eu-repo/semantics/publishedVersio

Preface of the "Symposium on dynamical systems applied to robotics"

[Excerpt] Robotics has been evolving in last years, considering the different fields that can be tackled. This is an important and diversified domain, which is normally solved using bio-inspired or model-based approaches. In this symposia, we focus on the use of the dynamical systems theory to address any related problems in the robotics domain. Dynamical systems exhibit some properties which makes them well suited to real-time robotic applications, such as movement generation for legged; modular and wheeled platforms; balance control; grasping; reaching, etc. [...](undefined

A brainstem-like modulation approach for gait transition in a quadruped robot

The ability to traverse a wide variety of terrains while walking is basically a requirement for performing useful tasks in our human centric world. In this article, we propose a bio-inspired robotic controller able to generate locomotion and to easily switch between different type of gaits. In order to improve the robot stability and response while locomoting, we adjust both the duty factor and the interlimb phase relationships, according to the velocities. We extend previous work, by applying nonlinear oscillators to generate the rhythmic locomotor movements for a quadruped robot, similarly to the biological counterparts. The generated trajectories are modulated by a drive signal, that modifies the oscillator frequency, amplitude and the coupling parameters among the oscillators, proportionally to the drive signal strength. By increasing the drive signal, locomotion can be elicited and velocity increased while switching to the appropriate gaits. This drive signal can be specified according to sensory information or set a priori. The implementation of the central pattern generator network and the activity modulation layer is shown in simulation and in an AIBO robot

Towards precise recognition of pollen bearing bees by convolutional neural networks

Automatic recognition of pollen bearing bees can provide important information both for pollination monitoring and for assessing the health and strength of bee colonies, with the consequent impact on people's lives, due to the role of bees in the pollination of many plant species. In this paper, we analyse some of the Convolutional Neural Networks (CNN) methods for detection of pollen bearing bees in images obtained at hive entrance. In order to show the in uence of colour we preprocessed the dataset images. Studying the results of nine state-of-the-art CNNs, we provide a baseline for pollen bearing bees recognition based in deep learning. For some CNNs the best results were achieved with the original images. However, our experiments showed evidence that DarkNet53 and VGG16 have superior performance against the other CNNs tested, with unsharp masking preprocessed images, achieving accuracy results of 99:1% and 98:6%, respectively.info:eu-repo/semantics/publishedVersio

The role of the corticomotorneurons in pathogenesis of amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a progressive, degenerative disease of the motor system clinically defined by the presence of upper and lower motor neuron (LMN) signs. The site of onset of pathophysiology within the motor system in ALS remains unresolved and this thesis examines the role of the corticomotor neuron in the pathogenesis of ALS. The diagnostic utility of the split-hand sign in ALS involving preferential wasting of the ‘thenar’ group of intrinsic hand muscles namely the abductor pollicis brevis (APB) and first dorsal interosseous (FDI) was established by recording the split-hand index (SI) which was noted to reliably differentiate ALS from mimic neuromuscular disorders. The cortical and axonal excitability characteristics of the ‘thenar’ muscles namely the APB and FDI was compared with the hypothenar abductor digiti minimi (ADM) with threshold tracking transcranial magnetic stimulation (TMS) studies revealing cortical hyperexcitability to be a feature of ALS pronounced over the ‘thenar’ muscles while axonal hyperexcitability while a feature of ALS, did not selectively affect the prominently wasted ‘thenar’ muscles. Cortical hyperexcitability was also noted to precede the development of lower motor neuron dysfunction in a clinically and neurophysiologically normal APB muscle. The selective vulnerability of muscles in ALS was further defined by the split hand plus sign with a greater degree of cortical hyperexcitability over the preferentially wasted APB muscle in ALS patients when compared with a similarly innervated and relatively preserved flexor pollicis longus (FPL) muscle. In summary, corticomotorneuronal hyperexcitability as a marker of corticomotorneuronal dysfunction predominates over the muscles which are preferentially wasted in ALS and precedes evidence of lower motor neuron loss. The findings presented in this thesis support the primacy of the corticomotor neuron in the pathogenesis of the split hand phenomenon and suggest a mechanism for the pathogenesis of ALS

Impact of discrete corrections in a modular approach for trajectory generation in quadruped robots

Online generation of trajectories in robots is a very complex task that involves the combination of different types of movements, i.e., distinct motor primitives. The later are used to model complex behaviors in robots, such as locomotion in irregular terrain and obstacle avoidance. In this paper, we consider two motor primitives: rhythmic and discrete. We study the effect on the robots’ gaits of superimposing the two motor primitives, considering two distinct types of coupling. Additionally, we simulate two scenarios, where the discrete primitive is inserted in all of the four limbs, or is inserted in ipsilateral pairs of limbs. Numerical results show that amplitude and frequency of the periodic solutions, corresponding to the gaits trot and pace, are almost constant for diffusive and synaptic couplings.CP was supported by Research funded by the European Regional Development Fund through the programme COMPETE and by the Portuguese Government through the FCT Fundacao para a Ciencia e a Tecnologia under the project PEst-C/MAT/UI0144/2011. This work was also funded by FEDER Funding supported by the Operational Program Competitive Factors COMPETE and National Funding supported by the FCT - Portuguese Science Foundation through project PTDC/EEACRO/100655/2008

A new CPG model for the generation of modular trajectories for hexapod robots

Legged robots are often used in a large variety of tasks, in different environments. Nevertheless, due to the large number of degrees-of-freedom to be controlled, online generation of trajectories in these robots is very complex. In this paper, we consider a modular approach to online generation of trajectories, based on biological concepts, namely Central Pattern Generators (CPGs). We introduce a new CPG model for hexapod robots’ rhythms, based in the work of Golubitsky et al (1998). Each neuron/oscillator in the CPG consists of two modules/primitives: rhythmic and discrete. We study the effect on the robots’ gaits of superimposing the two motor primitives, considering two distinct types of coupling.We conclude, from the simulation results, that the amplitude and frequency of periodic solutions, identified with hexapods’ tripod and metachronal gaits, remain constant for the two couplings, after insertion of the discrete part.CP was supported by Research funded by the European Regional Development Fund through the programme COMPETE and by the Portuguese Government through the FCT Fundacao para a Ciencia e a Tecnologia under the project PEst-C/MAT/UI0144/2011. This work was also funded by FEDER Funding supported by the Operational Program Competitive Factors COMPETE and National Funding supported by the FCT - Portuguese Science Foundation through project PTDC/EEACRO/100655/2008

A modular approach for trajectory generation in biped robots

Robot locomotion has been a major research issue in the last decades. In particular, humanoid robotics has had a major breakthrough. The motivation for this study is that bipedal locomotion is superior to wheeled approaches on real terrain and situations where robots accompany or replace humans. Some examples are, on the development of human assisting device, such as prosthetics, orthotics, and devices for rehabilitation, rescue of wounded troops, help at the office, help as maidens, accompany and assist elderly people, amongst others. Generating trajectories online for these robots is a hard process, that includes different types of movements, i.e., distinct motor primitives. In this paper, we consider two motor primitives: rhythmic and discrete.We study the effect on a bipeds robots’ gaits of inserting the discrete part as an offset of the rhythmic primitive, in synaptic and diffusive couplings. Numerical results show that amplitude and frequency of the periodic solution, corresponding to the gait run are almost constant in all cases studied here.(undefined

An Efficient Monte Carlo-based Probabilistic Time-Dependent Routing Calculation Targeting a Server-Side Car Navigation System

Incorporating speed probability distribution to the computation of the route planning in car navigation systems guarantees more accurate and precise responses. In this paper, we propose a novel approach for dynamically selecting the number of samples used for the Monte Carlo simulation to solve the Probabilistic Time-Dependent Routing (PTDR) problem, thus improving the computation efficiency. The proposed method is used to determine in a proactive manner the number of simulations to be done to extract the travel-time estimation for each specific request while respecting an error threshold as output quality level. The methodology requires a reduced effort on the application development side. We adopted an aspect-oriented programming language (LARA) together with a flexible dynamic autotuning library (mARGOt) respectively to instrument the code and to take tuning decisions on the number of samples improving the execution efficiency. Experimental results demonstrate that the proposed adaptive approach saves a large fraction of simulations (between 36% and 81%) with respect to a static approach while considering different traffic situations, paths and error requirements. Given the negligible runtime overhead of the proposed approach, it results in an execution-time speedup between 1.5x and 5.1x. This speedup is reflected at infrastructure-level in terms of a reduction of around 36% of the computing resources needed to support the whole navigation pipeline