Exploring adaptation & self-adaptation in autonomic computing systems

This panel paper sets out to discuss what self-adaptation means, and to explore the extent to which current autonomic systems exhibit truly self-adaptive behaviour. Many of the currently cited examples are clearly adaptive, but debate remains as to what extent they are simply following prescribed adaptation rules within preset bounds, and to what extent they have the ability to truly learn new behaviour. Is there a standard test that can be applied to differentiate? Is adaptive behaviour sufficient anyway? Other autonomic computing issues are also discussed

An Intersection Management Protocol for Mixed Autonomous and Legacy Vehicles

3rd Doctoral Congress in Engineering will be held at FEUP on the 27th to 28th of June, 2019An important element in urban traffic management is the Intersection Management (IM) that deals with traffic lights signaling (either real or virtual). Intersections are vulnerable to traffic congestion and accidents. Therefore, this paper investigates a synchronous intersection management protocol for mixed autonomous and humandriven vehicles in the context of decentralized traffic management.info:eu-repo/semantics/publishedVersio

Bioinspired Implementation and Assessment of a Remote-Controlled Robot

This research was funded by the Universidad de Las Americas, Direccion General de Investigacion.Daily activities are characterized by an increasing interaction with smart machines that present a certain level of autonomy. However, the intelligence of such electronic devices is not always transparent for the end user. This study is aimed at assessing the quality of the remote control of a mobile robot whether the artefact exhibits a human-like behavior or not. The bioinspired behavior implemented in the robot is the well-described two-thirds power law. The performance of participants who teleoperate the semiautonomous vehicle implementing the biological law is compared to a manual and nonbiological mode of control. The results show that the time required to complete the path and the number of collisions with obstacles are significantly lower in the biological condition than in the two other conditions. Also, the highest percentage of occurrences of curvilinear or smooth trajectories are obtained when the steering is assisted by an integration of the power law in the robot's way of working. This advanced analysis of the performance based on the naturalness of the movement kinematics provides a refined evaluation of the quality of the Human-Machine Interaction (HMI). This finding is consistent with the hypothesis of a relationship between the power law and jerk minimization. In addition, the outcome of this study supports the theory of a CNS origin of the power law. The discussion addresses the implications of the anthropocentric approach to enhance the HMI.publishersversionpublishe

Influence of magnesium on excitability of neurons of different levels of their organization

AbstractThe article indicates that the hyper-excitability of neurons is associated with ionic imbalance of cell membranes, in which a number of trace elements are involved. The energy component of these processes is associated with the presence of magnesium (Mg) as a universal supplier of the latter. Mg supports the functioning of NMDA receptors, which does not allow the excitotoxic effects of glutamate, which triggers the mechanisms of Ca entry into the neuron and its death, to manifest itself. Mg stimulates the main excitatory neurotransmitter acetylcholine, regulates the release of serotonin, glycine, dopamine, thereby normalizing the extrapyramidal system, the spinal stem structures, and the final executive motor apparatus. Participates in the energy support of adaptation processes, the activation of central regulatory mechanisms, control the excess of catecholamines and corticosteroids, other hormones and mediators involved in stress reactions

Determination of cognitive workload variation in driving from ECG derived respiratory signal and heart rate

2nd International Neuroergonomics Conference, PHILADELPHIE, ETATS-UNIS, 27-/06/2018 - 29/06/2018Research works on operator monitoring underline the benefit of taking into consideration several signal modalities to improve accuracy for an objective mental state diagnosis. Heart rate (HR) is one of the most utilized systemic measures to assess cognitive workload (CW), whereas respiration parameters are hardly utilized. This study aims at verifying the contribution of analyzing respiratory signals to extract features to evaluate driver's activity and CW variations in driving with regard to cardiac activity. Eighteen subjects participated in the study. The participants carried out two different cognitive tasks requiring different CW demands, a single task as well as a competing cognitive task realized while driving in a simulator. Our results confirm that both HR and breathing rate (BR) increase in driving and are sensitive to CW. However, HR and BR are differently modulated by the CW variations in driving. Specifically, BR is suitable to evidence a variation of CW when driving is not required. On the other hand, spectral features characterizing respiratory signal could be also used similarly to HR variability indices to detect high CW episodes. These results hint the use of respiration to monitor the driver mental state in autonomic vehicles in order to predict the available cognitive resources if the user has to take over the vehicle

Implementation of Gas Detection System using Unmanned Moving Vehicle

Abstract: Unmanned moving vehicles are nowadays largely used in environment monitoring system. In order to identify the leakage of gas in a housing area or an industry or in an agricultural area, it can be easily monitored and detected by the sensors that are embedded on a moving vehicle. A remote controlled vehicle is used in the proposed system. With help of camera attached to this the area where hazardous gas leakage can be identified. In case of emergency like fire explosion in some other area the vehicle can be manually moved to that location. The information about the gas leakage is transferred through ZIGBEE. GPS is used to trace the location where leakage has happened. The leakage of harmful gas in agricultural area, housing area and industrial area can be detected more accurately

Logistics 4.0: Challenges, Opportunities and Threats

Climate change, the main accelerator of which has been consumerism and the industry driving it, soon will force companies to make changes that will intensify their activities in the natural environment. The Covid-19 pandemic, Due to their specificity, has disrupted global supply chains on an unprecedented scale. In addition, the progress of the analysis supported by the assumptions and tools of Industry 4.0 (I4.0) opens unlimited development opportunities. These changes also have a significant impact on Logistics, making the concept of Logistics 4.0 (L4.0) increasingly popular. The scope of defining L4.0 varies from the use of individual I4.0 tools to the presentation of complex models. This paper presents a literature review using the STAR method on the L4.0 concept to identify the scope of its determinants and possible perspectives for the development of logistics in the context of I4.0 and the challenges mentioned

Respiration and Heart Rate Modulation Due to Competing Cognitive Tasks While Driving

Research works on operator monitoring underline the benefit of taking into consideration several signal modalities to improve accuracy for an objective mental state diagnosis. Heart rate (HR) is one of the most utilized systemic measures to assess cognitive workload (CW), whereas, respiration parameters are hardly utilized. This study aims at verifying the contribution of analyzing respiratory signals to extract features to evaluate driver’s activity and CW variations in driving. Eighteen subjects participated in the study. The participants carried out two different cognitive tasks requiring different CW demands, a single task as well as a competing cognitive task realized while driving in a simulator. Our results confirm that both HR and breathing rate (BR) increase in driving and are sensitive to CW. However, HR and BR are differently modulated by the CW variations in driving. Specifically, HR is affected by both driving activity and CW, whereas, BR is suitable to evidence a variation of CW only when driving is not required. On the other hand, spectral features characterizing respiratory signal could be also used similarly to HR variability indices to detect high CW episodes. These results hint the use of respiration as an alternative to HR to monitor the driver mental state in autonomic vehicles in order to predict the available cognitive resources if the user has to take over the vehicle