Search results for "Computational Theory and Mathematics"
showing 10 items of 565 documents
Molecular signatures of silencing suppression degeneracy from a complex RNA virus
2021
As genomic architectures become more complex, they begin to accumulate degenerate and redundant elements. However, analyses of the molecular mechanisms underlying these genetic architecture features remain scarce, especially in compact but sufficiently complex genomes. In the present study, we followed a proteomic approach together with a computational network analysis to reveal molecular signatures of protein function degeneracy from a plant virus (as virus-host protein-protein interactions). We employed affinity purification coupled to mass spectrometry to detect several host factors interacting with two proteins of Citrus tristeza virus (p20 and p25) that are known to function as RNA sil…
Plankton Tracker: A novel integrated system to investigate the dynamic sinking behavior in phytoplankton
2020
Abstract Phytoplankton sinking is an important property that can determine community composition, affecting nutrient and light absorption in the photic zone, and influencing biogeochemical cycling via material loss to the deep ocean. To date, the difficulty in exploring the sinking processes is partly due to methodological limitations in measuring phytoplankton sinking rate. However, in the last decade, works have illustrated various methods based on some non-invasive and low perturbing approaches (laser scanner, video-microscopy, fluorescence spectroscopy). In this study, we review the methods for sinking rate estimation and describe the Plankton Tracker, a novel integrated system to inves…
Identifying small pelagic Mediterranean fish schools from acoustic and environmental data using optimized artificial neural networks
2019
Abstract The Common Fisheries Policy of the European Union aims to exploit fish stocks at a level of Maximum Sustainable Yield by 2020 at the latest. At the Mediterranean level, the General Fisheries Commission for the Mediterranean (GFCM) has highlighted the importance of reversing the observed declining trend of fish stocks. In this complex context, it is important to obtain reliable biomass estimates to support scientifically sound advice for sustainable management of marine resources. This paper presents a machine learning methodology for the classification of pelagic species schools from acoustic and environmental data. In particular, the methodology was tuned for the recognition of an…
Natural Selection Fails to Optimize Mutation Rates for Long-Term Adaptation on Rugged Fitness Landscapes
2008
The rate of mutation is central to evolution. Mutations are required for adaptation, yet most mutations with phenotypic effects are deleterious. As a consequence, the mutation rate that maximizes adaptation will be some intermediate value. Here, we used digital organisms to investigate the ability of natural selection to adjust and optimize mutation rates. We assessed the optimal mutation rate by empirically determining what mutation rate produced the highest rate of adaptation. Then, we allowed mutation rates to evolve, and we evaluated the proximity to the optimum. Although we chose conditions favorable for mutation rate optimization, the evolved rates were invariably far below the optimu…
Exploring the development of scientific research on Marine Protected Areas: From conservation to global ocean sustainability
2021
Abstract Marine Protected Areas (MPAs) are playing a central role in the achievement of ocean sustainability and, since 2000, their global coverage has increased over ten times. The success of MPAs, and therefore the delivery of their potential outcomes for human well-being and global sustainability, requires multi-disciplinary, holistic, and comprehensive approaches for its achievement. In this study, the global scientific literature on MPAs was quantitatively reviewed through bibliometrics approaches, investigating patterns and trends in its development over time. In particular, bibliometric network and citation burst analyses of keywords were performed using VOSviewer and CiteSpace softw…
Rings for Privacy: an Architecture for Large Scale Privacy-Preserving Data Mining
2021
This article proposes a new architecture for privacy-preserving data mining based on Multi Party Computation (MPC) and secure sums. While traditional MPC approaches rely on a small number of aggregation peers replacing a centralized trusted entity, the current study puts forth a distributed solution that involves all data sources in the aggregation process, with the help of a single server for storing intermediate results. A large-scale scenario is examined and the possibility that data become inaccessible during the aggregation process is considered, a possibility that traditional schemes often neglect. Here, it is explicitly examined, as it might be provoked by intermittent network connec…
FeatherCNN: Fast Inference Computation with TensorGEMM on ARM Architectures
2020
Deep Learning is ubiquitous in a wide field of applications ranging from research to industry. In comparison to time-consuming iterative training of convolutional neural networks (CNNs), inference is a relatively lightweight operation making it amenable to execution on mobile devices. Nevertheless, lower latency and higher computation efficiency are crucial to allow for complex models and prolonged battery life. Addressing the aforementioned challenges, we propose FeatherCNN – a fast inference library for ARM CPUs – targeting the performance ceiling of mobile devices. FeatherCNN employs three key techniques: 1) A highly efficient TensorGEMM (generalized matrix multiplication) routine is app…
Usability and acceptability assessment of an empathic virtual agent to prevent major depression
2016
In Human-Computer Interaction, the adaptation of the content and the way of how this content is communicated to the users in interactive sessions is a critical issue to promote the acceptability and usability of any computational system. We present a user-adapted interactive platform to identify and provide an early intervention for symptoms of depression and suicide. In particular, we describe the work performed to assess users' system acceptability and usability. An empathic Virtual Agent is the main interface with the user, and it has been designed to generate the appropriate dialogues and emotions during the interactions according to the detected user's specific needs. This personalizat…
Homography based egomotion estimation with a common direction
2017
International audience; In this paper, we explore the different minimal solutions for egomotion estimation of a camera based on homography knowing the gravity vector between calibrated images. These solutions depend on the prior knowledge about the reference plane used by the homography. We then demonstrate that the number of matched points can vary from two to three and that a direct closed-form solution or a Gröbner basis based solution can be derived according to this plane. Many experimental results on synthetic and real sequences in indoor and outdoor environments show the efficiency and the robustness of our approach compared to standard methods.
An Ontology to Support Semantic Management of FMEA Knowledge
2016
<p>Risk mitigation has always been a special concern for organization’s strategic management. Various tools and techniques have been developed to manage risk in an effective way. Failure Mode and Effects Analysis (FMEA) is one of the tools used for effective assessment of risk. It analyzes all potential failure modes, their causes, and effects on a product or process. Moreover it recommends actions to mitigate failures in order to enhance product reliability. Organizations spend their resources and domain experts make their efforts to complete this analysis. It further helps organizations identify the expected risks and plan strategies in advance to tackle them. But unfortunately the …