A linked data-driven & service-oriented architecture for sharing educational resources

The two fundamental aims of managing educational resources are to enable resources to be reusable and interoperable and to enable Web-scale sharing of resources across learning communities. Currently, a variety of approaches have been proposed to expose and manage educational resources and their metadata on the Web. These are usually based on heterogeneous metadata standards and schemas, such as IEEE LOM or ADL SCORM, and diverse repository interfaces such as OAI-PMH or SQI. Also, there is still a lack of usage of controlled vocabularies and available data sets that could replace the widespread use of unstructured text for describing resources. On the other hand, the Linked Data approach has proven that it offers a set of successful principles that have the potential to alleviate the aforementioned issues. In this paper, we introduce an architecture and prototype which is fundamentally based on (a) Linked Data principles and (b) Service-orientation to resolve the integration issues for sharing educational resources

New records and noteworthy data of plants, algae and fungi in SE Europe and adjacent regions, 11

This paper presents new records and noteworthy data on the following taxa in SE Europe and adjacent regions: red algae Sheathia confusa, parasitic fungus Anthracoidea caryophylleae, mycorrhizal fugus Hydnellum caeruleum, bryoparasitic fungus Octospora erzbergeri, liverwort Cephaloziella baumgartneri, mosses Hamatocaulis vernicosus, Streblotrichum convolutum var. commutatum and Ulota crispula, monocots Ophrys bertolonii subsp. bertolonii, Ophrys scolopax subsp. cornuta and Spiranthes spiralis and dicots Androsace hedraeantha, Hieracium mrazii, Ramonda nathaliae and Triglochin palustris are given within SE Europe and adjacent region

Semantic annotation and linking of medical educational resources

Educational content is often shared among different educators and is enriched, adapted and in general repurposed so that it can be re-used in different contexts. This paper presents the MetaMorphosis+ environment for publishing, sharing and repurposing educational content in medical education. The environment meshes the paradigms of social Web and semantic Web to publish richly annotated educational resources that are further semantically enriched and exposed in the Linked Open Data cloud. The goal is to enable more relevant searching and retrieval of medical educational resources, as well as linking to other related resources in the medical domain, including scientific publications and clinical data

Assessment of Asteroid Classification Using Deep Convolutional Neural Networks

Near-Earth Asteroids represent potential threats to human life because their trajectories may bring them in the proximity of the Earth. Monitoring these objects could help predict future impact events, but such efforts are hindered by the large numbers of objects that pass in the Earth’s vicinity. Additionally, there is also the problem of distinguishing asteroids from other objects in the night sky, which implies sifting through large sets of telescope image data. Within this context, we believe that employing machine learning techniques could greatly improve the detection process by sorting out the most likely asteroid candidates to be reviewed by human experts. At the moment, the use of machine learning techniques is still limited in the field of astronomy and the main goal of the present paper is to study the effectiveness of deep convolutional neural networks for the classification of astronomical objects, asteroids in this particular case, by comparing some of the well-known deep convolutional neural networks, including InceptionV3, Xception, InceptionResNetV2 and ResNet152V2. We applied transfer learning and fine-tuning on these pre-existing deep convolutional networks, and from the results that we obtained, the potential of using deep convolutional neural networks in the process of asteroid classification can be seen. The InceptionV3 model has the best results in the asteroid class, meaning that by using it, we lose the least number of valid asteroids

Spatial data processing tools and applications for Black Sea catchment region

The enviroGRIDS project has developed and provides through the BSC-OS portal a set of tools, applications and platforms concerning with the processing of huge spatial data for the Black Sea catchment region. The presentation highlights the main issues of interoperability between Geospatial and Grid infrastructures, and between different platforms supporting the Earth Science oriented tools and applications. The BSC-OS portal provides end user applications for spatial data management, hydrological model calibration, environmental scenario development and execution, workflow based satellite image processing, data reporting and scenarios visualization, and development of Earth Science oriented training materials

Software Platform Interoperability Throughout EnviroGRIDS Portal

The Black Sea Catchment area is well known for subjects such as ecologically unsustainable development or inadequate resource management. The EnviroGRIDS project addresses these issues by using emerging information technologies. The enviroGRIDS Web Portal allows the users to access the geospatial functionality given by Web infrastructure, and to high power computation resources given by Grid infrastructure. The Black Sea Catchment Observation System portal provides a single point of access to the enviroGRIDS applications and tools. Both the vertical and horizontal interoperability are available between the platforms and applications throughout the portal. The horizontal interoperability is accomplished through services, meaning the applications are working together by the exposed services. The vertical interoperability is supported by the communication between the layers of end user applications, Web infrastructure, and Grid infrastructure. The basic solution of interoperability is accomplished by services, messages, and data. The paper highlights the solutions developed by the Black Sea Catchment Observation System portal to support various types of interoperability between the modules of geospatial data management, hydrological model calibration and running, satellite image processing, spatial data visualization, and virtual training center

New records and noteworthy data of plants, algae and fungi in SE Europe and adjacent regions, 3

This paper presents new records and noteworthy data on the following taxa in SE Europe and adjacent regions: parasitic fungus Antherospora hortensis, saprotrophic fungi Loweomyces fractipes and Pholiota henningsii, stonewort Chara canescens, mosses Grimmia caespiticia and Rhodobryum ontariense, fern Woodsia alpina, monocots Aegilops triuncialis, Epipactis purpurata, Galanthus elwesii and Typha shuttleworthii and dicot Umbilicus luteus