SustainGraph
SustainGraph is a open-source Knowledge Graph (KG) that considers in a holistic way the tracking of the progress towards the Sustainable Development Goals (SDG). It monitors SDG targets and the evolution of indicators at national and regional levels, along with their relationship with specified policies and the implementation of case studies across Europe. SustainGraph is considered as the basis for the systemic representation of knowledge related to the SDGs, enabling the collection and homogeneous representation of data along with their semantics and overcoming data management barriers (e.g., existence of multiple data silos, absence of semantic alignment of data coming from different disciplines). In addition to tracking the evolution towards the achievement of the targets posed in the SDGs, one of the main objectives of SustainGraph is to enable the development of participatory modeling and analysis processes (e.g., socio-environmental models), taking advantage of the semantic alignment of the represented terms and the knowledge produced through the analysis of the information that is made available. SustainGraph is developed within the framework of the ARSINOE H2020 project.
License: Eclipse Public License 2.0
GitLab repository: https://gitlab.com/netmode/sustaingraph
k8s-RL-autoscaler
k8s RL autoscaler is an open-source software project that offers autoscaling mechanisms for serverless applications that are powered by Reinforcement Learning (RL) techniques. A set of RL environments and agents have been implemented (based on Q-learning, DynaQ+ and Deep Q-learning algorithms) for driving autoscaling mechanisms, able to autonomously manage dynamic workloads with Quality of Service (QoS) guarantees, while opting for efficient usage of resources. The produced environments and agents are evaluated in real and simulated environments, taking advantage of the Kubeless open-source serverless platform. A simulation environment has been also developed to support extensive training of RL agents to overcome time-related limitations of real environments. The k8s-RL-autoscaler has been extended towards a multi-agent setting for managing autoscaling mechanisms within an application graph, based on the application of Multi-agent Reinforcement Learning (MARL) techniques. The extended version is called as k8s-marl-autoscaler.
License: Apache License 2.0
GitLab repository (for single-agent setting): https://gitlab.com/netmode/k8s-rl-autoscaler
GitLab repository (for multi-agent setting): https://gitlab.com/netmode/k8s-marl-autoscaler
SeLCont
SeLCont (Synchronized eLearning Content) was developed at the Network Management & Optimal Design (NETMODE) laboratory of the National Technical University of Athens (NTUA). It is an easy to use toolkit with minimal post-processing effort and no special installation requirements from lecture rooms. The final outcome is dynamically adjusted to any user browser (laptop, desktop, tablet, smart phone) running Windows, Android and iOS. It centers on WordPress CMS, with adjustable HTML5 Web pages of lecture material (ppt’s with or without annotations, PDF’s, Internet screens etc.), synchronized with video-audio, stored in YouTube (or any video provider) and reproduced via the popular JWPlayer.
License: GNU GPLv3
GitHub repository: https://github.com/netmode/selcont
EmoSociograms
EmoSociograms is an open-source tool that supports sociometric and emotional intelligence assessment processes based on the EmoSocio open-access Emotional Intelligence (EI) model. You can create your group, select and activate questionnaires from a list of emotional intelligence and social interaction assessment measures, run evaluation campaigns and continuously track the evolution of social and emotional competencies’ of your group through interactive visualisations. EmoSociograms is currently under application and evaluation in groups of students in primary and secondary schools within the framework of the EduCardia Erasmus+ project.
License: GNU GPLv3
Link: https://emosociograms.com/
GitLab repository: https://gitlab.com/netmode/emosociograms