Search results for " algorithm"
showing 10 items of 2538 documents
The positioning system of the ANTARES Neutrino Telescope
2012
The ANTARES neutrino telescope, located 40km off the coast of Toulon in the Mediterranean Sea at a mooring depth of about 2475m, consists of twelve detection lines equipped typically with 25 storeys. Every storey carries three optical modules that detect Cherenkov light induced by charged secondary particles (typically muons) coming from neutrino interactions. As these lines are flexible structures fixed to the sea bed and held taut by a buoy, sea currents cause the lines to move and the storeys to rotate. The knowledge of the position of the optical modules with a precision better than 10cm is essential for a good reconstruction of particle tracks. In this paper the ANTARES positioning sys…
Bluetooth Base Station Minimal Deployment for High Definition Positioning
2005
This paper discusses our approach to the problem of arranging a Bluetooth based positioning system capable of providing people coordinates in a given area with an accuracy as high as possible. Our strategy focuses on optimizing the disposition of a minimal number of available Bluetooth base stations in a subset of locations which are the only ones permitted by site characteristics and constraints. We used a genetic algorithm to this purpose and a layout chromosome whose best evolution suggested us how to deploy a minimal set of Bluetooth base stations. As a case study, we discuss our experiments and results which deal with a late middle age castle in Sicily where we carried out many trials.
Active contour algorithm with discriminant analysis for delineating tumors in positron emission tomography.
2019
Abstract In the context of cancer delineation using positron emission tomography datasets, we present an innovative approach which purpose is to tackle the real-time, three-dimensional segmentation task in a full, or at least nearly full automatized way. The approach comprises a preliminary initialization phase where the user highlights a region of interest around the cancer on just one slice of the tomographic dataset. The algorithm takes care of identifying an optimal and user-independent region of interest around the anomalous tissue and located on the slice containing the highest standardized uptake value so to start the successive segmentation task. The three-dimensional volume is then…
A probabilistic framework for automatic prostate segmentation with a statistical model of shape and appearance
2011
International audience; Prostate volume estimation from segmented prostate contours in Trans Rectal Ultrasound (TRUS) images aids in diagnosis and treatment of prostate diseases, including prostate cancer. However, accurate, computationally efficient and automatic segmentation of the prostate in TRUS images is a challenging task owing to low Signal-To-Noise-Ratio (SNR), speckle noise, micro-calcifications and heterogeneous intensity distribution inside the prostate region. In this paper, we propose a probabilistic framework for propagation of a parametric model derived from Principal Component Analysis (PCA) of prior shape and posterior probability values to achieve the prostate segmentatio…
A distributed minimum losses optimal power flow for islanded microgrids
2017
Abstract In this work, the minimum losses optimal power dispatch problem for islanded microgrids with distributed energy resources (DER) is solved by means of a distributed heuristic approach. Optimal power management is performed almost in real time, with a predefined schedule, i.e. every 5 min, and the solution is applied to generators when the current operating solution violates voltage or current constraints or when the current configuration produces too large power losses. The operating point of both inverter-interfaced generation units as well as rotating production systems can be modified simply using local information. The latter are voltage measurements and power injections or load…
A predictive function optimization algorithm for multi-spectral skin lesion assessment
2015
The newly introduced Kubelka-Munk Genetic Algorithm (KMGA) is a promising technique used in the assessment of skin lesions. Unfortunately, this method is computationally expensive due to its function inverting process. In the work of this paper, we design a Predictive Function Optimization Algorithm in order to improve the efficiency of KMGA by speeding up its convergence rate. Using this approach, a High-Convergence-Rate KMGA (HCR-KMGA) is implemented onto multi-core processors and FPGA devices respectively. Furthermore, the implementations are optimized using parallel computing techniques. Intensive experiments demonstrate that HCR-KMGA can effectively accelerate KMGA method, while improv…
Next generation diagnostic algorithm in non-small cell lung cancer predictive molecular pathology: The KWAY Italian multicenter cost evaluation study
2022
Abstract Aims The KWAY project aims to investigate the economic sustainability of the up-front NGS technologies adoption in the analysis of clinically relevant molecular alterations in NSCLC patients. Methods The diagnostic workflow and the related sustained costs of five Italian referral centers were assessed in four different evolving scenarios were analyzed. For each scenario, two alternative testing strategies were evaluated: the Maximized Standard strategy and the Maximized NGS strategy. Results For each center, the robustness of obtained results was verified through a deterministic sensitivity analysis, observing the variation of total costs based on a variation of ±20 % of the input …
Effects of a French remedial program on pupils’ educational outcomes
2018
International audience; Few studies have examined the French “Networks for Specialized Assistance to Pupils in Difficulty” (Rased). In this article, we evaluate the impact of receiving Rased services in the first year of primary schooling on academic success. Using data from a national panel study, we find inconsistency in student selection within Rased. Using matching methods, our results reveal that pupils who benefited from the program school have a higher probability of grade repetition and obtain significantly lower scores on the third grade national assessment, particularly in mathematics, compared to pupils with similar characteristics who did not take part in the program. This impac…
A probabilistic rainfall model to estimate the leading-edge lifetime of wind turbine blade coating system
2021
Rain-induced leading-edge erosion of wind turbine blades is associated with high repair and maintenance costs. For efficient operation and maintenance, erosion models are required that provide estimates of blade coating lifetime at a real scale. In this study, a statistical rainfall model is established that describes probabilistic distributions of rain parameters that are critical for site-specific leading-edge erosion assessment. A new droplet size distribution (DSD) is determined based on two years’ onshore rainfall data of an inland site in the Netherlands and the obtained DSD is compared with those from the literature. Joint probability distribution functions of rain intensities and dr…
Rapid screening of the LDL receptor point mutation FH-Genoa/Palermo
1999
The LDL-receptor gene point mutation FH-Genoa/Palermo is the most frequent mutation responsible for Familial Hypercholesterolemia in Sicily. The mutation does not introduce or abolish any useful restriction site. We establish a GeneComb™-based strategy to identify this mutation in a population of Sicilian unrelated clinically diagnosed FH probands. The method was very sensitive and specific; 12 out of 90 (13.3%) unrelated FH probands were found to carry the FH-Genoa/Palermo mutation. According to these results, the FH-Genoa/Palermo is the more frequent LDL-receptor gene mutation among the Sicilian FH patients. Moreover FH-Genoa/Palermo is the mutation cluster to date more represented in Sou…