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    Advanced Methods to Extract Value from Scientific Datasets
    (Springer, 2019) Perju, Lucian; Nicolaescu, Marius-Dorian; Pop, Forin; Dobre, Ciprian; Maiduc, Sanda
    In these days the scientific community is times bigger comparing with the previous centuries. The need of powerful tools to aggregate and analyse the information about articles, books and other publications becomes greater with each published paper. In this paper we describe a solution for understanding and leveraging this data. The platform integrates the following requirements: data aggregation, data analysis (visualizations, dashboards, graphs), complex and simple searches, and support for data export. The platform brings value to its users due to various reasons such as quick identification of relevant data and in depth analysis on the provided input. Another key feature is the granularity, application being easily configurable for rigorous use cases: just one author, a group of authors or an entire scientific field.
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    My cloudy time machine: a scalable microservice-based platform for data processing in cloud-edge systems: a proof of concept for the ROBIN-cloud project
    (ACM, 2019) Neatu, Darius-Florentin; Stochitoiu, Radu Dumitru; Postoaca, Andrei-Vlad; Filip, Ion-Dorinel; Pop, Florin
    As Cloud computing is a very well developed domain, many companies tend to move their entire activity in Cloud. At the same time, there is a tendency to move some of the data processing from Cloud to Edge as close as possible to the end devices. One main advantage of this approach is minimizing the latency in communication between the end devices and Cloud. Better usage of on premise devices is also a good achievement of the Edge offload. In this paper, we propose an architecture for applications that are connected to ROBIN-Cloud or to a general Cloud. We present how we have encapsulated Python-based microservices in Docker containers. We provide an implementation for the My Cloudy Time Machine application - GIGEL (Guided Intelligent GEared Legend), a nearby autonomous assistive robot. We use this prototype to evaluate the scalability of the proposed architecture. We also present results that show how to gain high performance by tuning a container-based embedded system.
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    The 4-Steiner Root Problem
    (2019) Ducoffe, Guillaume
    The k th-power of a graph G is obtained by adding an edge between every two distinct vertices at a distance ≤ k in G. We call G a k-Steiner power if it is an induced subgraph of the k th-power of some tree T. In particular, G is a k-leaf power if all vertices in V (G) are leaf-nodes of T. Our main contribution is a polynomial-time recognition algorithm of 4-Steiner powers, thereby extending the decade-year-old results of (Lin, Kearney and Jiang, ISAAC’00) for k = 1, 2 and (Chang and Ko, WG’07) for k = 3. As a byproduct, we give the first known polynomial-time recognition algorithm for 6-leaf powers. Our work combines several new algorithmic ideas that help us overcome the previous limitations on the usual dynamic programming approach for these problems.
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    Integrated Consumer Technologies for Older Adults' Quality of Life Improvement: the vINCI Project
    (IEEE, 2019) Spinsante, Susanna; Strazza, Annachiara; Dobre, Ciprian; Băjenaru, Lidia; Mavromoustakis, Constandinos; Batalla, Jordi Mongay; Krawiec, Piotr; Georgescu, George; Molan, Gregor; Gonzalez-Velez, Horacio; Herghelegiu, Anna Marie; Prada, Gabriel Ioan; Draghici, Rozeta
    A low physical activity is one of the most important lifestyle risk factors for many chronic conditions in the older age. To tackle this issue, the consequences of which have relevant impact on the sustainability of national welfare in many developed countries, consumer technologies may be leveraged to offer easy-to-use tools enabling older adults to optimize their health-related quality of life, and promote an active and healthy longevity. This paper describes a technical platform named vINCI, obtained by the integration of consumer technologies with Assisted Living solutions and services, where multiple wearable devices work together to create an aggregated solution able to capture the various facets of events leading to the decrease in the perceived health-related quality of life, as typically associated with old age. Supporting the feedback of specialized medical evaluations, the vINCI technology enables elderly not only to self-evaluate their physical activity level, but also to change their behaviors and lifestyle in the long-term.
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    A new application of Orthogonal Range Searching for computing Giant Graph Diameters
    (2019) Ducoffe, Guillaume
    A well-known problem for which it is difficult to improve the textbook algorithm is computing the graph diameter. We present two versions of a simple algorithm (one being Monte Carlo and the other deterministic) that for every fixed h and unweighted undirected graph G with n vertices and m edges, either correctly concludes that diam(G) < hn or outputs diam(G), in time O(m + n^{1+o(1)}). The algorithm combines a simple randomized strategy for this problem (Damaschke, IWOCA'16) with a popular framework for computing graph distances that is based on range trees (Cabello and Knauer, Computational Geometry'09). We also prove that under the Strong Exponential Time Hypothesis (SETH), we cannot compute the diameter of a given n-vertex graph in truly subquadratic time, even if the diameter is an Θ(n/ log n).