Search results for "Algorithms"
showing 10 items of 1716 documents
Metaheuristic procedures for the lexicographic bottleneck assembly line balancing problem
2015
The goal of this work is to develop an improved procedure for the solution of the lexicographic bottleneck variant of the assembly line balancing problem (LB-ALBP). The objective of the LB-ALBP is to minimize the workload of the most heavily loaded workstation, followed by the workload of the second most heavily loaded workstation and so on. This problem-recently introduced to the literature (Pastor, 2011)-has practical relevance to manufacturing facilities. We design, implement and fine-tune GRASP, tabu search (TS) and scatter search (SS) heuristics for the LB-ALBP and show that our procedures are able to obtain solutions of a quality that outperforms previous approaches. We rely on both s…
Additively manufactured textiles and parametric modelling by generative algorithms in orthopaedic applications
2020
Purpose The purpose of this paper is to implement a new process aimed at the design and production of orthopaedic devices fully manufacturable by additive manufacturing (AM). In this context, the use of generative algorithms for parametric modelling of additively manufactured textiles (AMTs) also has been investigated, and new modelling solutions have been proposed. Design/methodology/approach A new method for the design of customised elbow orthoses has been implemented. In particular, to better customise the elbow orthosis, a generative algorithm for parametric modelling and creation of a flexible structure, typical of an AMT, has been developed. Findings To test the developed modelling a…
Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?
2020
Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem. Several different solvers can be applied to the resulting linear problem. In this paper, a thorough comparison of possible and recently proposed, especially randomized, algorithms is carried out for this problem with a representative set of regression datasets. In addition, we compare MLM with shallow and deep feedforward neural network models and study the effects of the number of observations and the number of features with a special dat…
A Novel Border Identification Algorithm Based on an “Anti-Bayesian” Paradigm
2013
Published version of a chapter in the book: Computer Analysis of Images and Patterns. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-40261-6_23 Border Identification (BI) algorithms, a subset of Prototype Reduction Schemes (PRS) aim to reduce the number of training vectors so that the reduced set (the border set) contains only those patterns which lie near the border of the classes, and have sufficient information to perform a meaningful classification. However, one can see that the true border patterns (“near” border) are not able to perform the task independently as they are not able to always distinguish the testing samples. Thus, researchers have worked on thi…
Gray code for derangements
2004
AbstractWe give a Gray code and constant average time generating algorithm for derangements, i.e., permutations with no fixed points. In our Gray code, each derangement is transformed into its successor either via one or two transpositions or a rotation of three elements. We generalize these results to permutations with number of fixed points bounded between two constants.
Engineering of a DNA Polymerase for Direct m6A Sequencing
2017
Methods for the detection of RNA modifications are of fundamental importance for advancing epitranscriptomics. N6-methyladenosine (m6A) is the most abundant RNA modification in mammalian mRNA and is involved in the regulation of gene expression. Current detection techniques are laborious and rely on antibody-based enrichment of m6A-containing RNA prior to sequencing, since m6A modifications are generally "erased" during reverse transcription (RT). To overcome the drawbacks associated with indirect detection, we aimed to generate novel DNA polymerase variants for direct m6A sequencing. Therefore, we developed a screen to evolve an RT-active KlenTaq DNA polymerase variant that sets a mark for…
Group analysis of ongoing EEG data based on fast double-coupled nonnegative tensor decomposition
2019
Abstract Background Ongoing EEG data are recorded as mixtures of stimulus-elicited EEG, spontaneous EEG and noises, which require advanced signal processing techniques for separation and analysis. Existing methods cannot simultaneously consider common and individual characteristics among/within subjects when extracting stimulus-elicited brain activities from ongoing EEG elicited by 512-s long modern tango music. New method Aiming to discover the commonly music-elicited brain activities among subjects, we provide a comprehensive framework based on fast double-coupled nonnegative tensor decomposition (FDC-NTD) algorithm. The proposed algorithm with a generalized model is capable of simultaneo…
Application of guidelines for the management of nonalcoholic fatty liver disease in three prospective cohorts of HIV-monoinfected patients
2020
Objectives: Current guidelines recommend use of a diagnostic algorithm to assess disease severity in cases of suspected nonalcoholic fatty liver disease (NAFLD). We applied this algorithm to HIV-monoinfected patients. Methods: We analysed three prospective screening programmes for NAFLD carried out in the following cohorts: the Liver Disease in HIV (LIVEHIV) cohort in Montreal, the Modena HIV Metabolic Clinic (MHMC) cohort and the Liver Pathologies in HIV in Palermo (LHivPa) cohort. In the LIVEHIV and LHivPa cohorts, NAFLD was diagnosed if the controlled attenuation parameter (CAP) was ≥ 248 dB/m; in the MHMC cohort, it was diagnosed if the liver/spleen Hounsfield unit (HU) ratio on abdomin…
Novel noninvasive embryo selection algorithm combining time-lapse morphokinetics and oxidative status of the spent embryo culture medium.
2019
Objective To develop a noninvasive embryo selection algorithm consisting of time-lapse morphokinetics and the oxidative status of the spent embryo culture medium determined using the Thermochemiluminescence (TCL) Analyzer. Design Retrospective cohort. Setting Not applicable. Patient(s) From women participating in the oocyte donation program, data from 505 samples of spent embryo culture media samples from 292 intracytoplasmic sperm injection cycles. Intervention(s) None. Main Outcome Measure(s) Morphokinetic parameters assessed during incubation in the time-lapse system Embryoscope. Oxidative parameters (H1sm, H2sm, and H3sm) from the spent culture medium on day 5 of incubation measured usi…
Effects of Study Population, Labeling and Training on Glaucoma Detection Using Deep Learning Algorithms
2020
Author(s): Christopher, Mark; Nakahara, Kenichi; Bowd, Christopher; Proudfoot, James A; Belghith, Akram; Goldbaum, Michael H; Rezapour, Jasmin; Weinreb, Robert N; Fazio, Massimo A; Girkin, Christopher A; Liebmann, Jeffrey M; De Moraes, Gustavo; Murata, Hiroshi; Tokumo, Kana; Shibata, Naoto; Fujino, Yuri; Matsuura, Masato; Kiuchi, Yoshiaki; Tanito, Masaki; Asaoka, Ryo; Zangwill, Linda M | Abstract: PurposeTo compare performance of independently developed deep learning algorithms for detecting glaucoma from fundus photographs and to evaluate strategies for incorporating new data into models.MethodsTwo fundus photograph datasets from the Diagnostic Innovations in Glaucoma Study/African Descent…