Search results for "Mining"
showing 10 items of 1730 documents
Application of non-invasive technologies in dry-cured ham: An overview
2019
Background: Dry-cured ham is one of the most valued food products by Mediterranean consumers. In this sense, the appropriate development of its different production stages is essential to ensure the quality requirements. For this reason, non-invasive technologies have gained popularity and have been reported as useful not only to ensure the food safety of different products, but also to monitor fundamental stages in the production process, such as the salting stage, to analyze the content of different compounds without sample losses, and to correct possible defects in the final product. Scope and approach: This work has been focused on summarizing the studies that describe and have successf…
Contribution of virtual reality to functional rehabilitation
2010
Virtual reality has grown immensely. Practical applications for the use of this technology encompass many fields in both engineering science and human science. In the field of medicine, one of the newest fields to benefit from the advances in VR technology, virtual reality has become a major new therapeutic tool not only in medicine and surgery but also for the treatment of psychological disorders and rehabilitation for impaired person. Our research presented in this thesis aims at developing utilities to aid in functional rehabilitation using virtual reality technology. The main research question of our work concerns the effect of virtual metaphors in learning and training human gestures f…
Response to "Trust, but verify".
2020
Application of the group method of data handling (GMDH) approach for landslide susceptibility zonation using readily available spatial covariates
2022
Abstract Landslide susceptibility (LS) mapping is an essential tool for landslide risk assessment. This study aimed to provide a new approach with better performance for landslide mapping and adopting readily available variables. In addition, it investigates the capability of a state-of-the-art model developed using the group method of data handling (GMDH) to spatially model LS. Furthermore, hybridized models of GMDH were developed using different metaheuristic algorithms. The study area was the Bonghwa region of South Korea, for which an accurate landslide inventory dataset is available. We considered a total of 13 spatial covariates (altitude, slope, aspect, topographic wetness index, val…
Ultimate Order Statistics-Based Prototype Reduction Schemes
2013
Published version of a chapter in the book: AI 2013: Advances in Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-319-03680-9_42 The objective of Prototype Reduction Schemes (PRSs) and Border Identification (BI) algorithms is to reduce the number of training vectors, while simultaneously attempting to guarantee that the classifier built on the reduced design set performs as well, or nearly as well, as the classifier built on the original design set. In this paper, we shall push the limit on the field of PRSs to see if we can obtain a classification accuracy comparable to the optimal, by condensing the information in the data set into a single tr…
Putting the user into the active learning loop : Towards realistic but efficient photointerpretation
2012
In recent years, several studies have been published about the smart definition of training set using active learning algorithms. However, none of these works consider the contradiction between the active learning methods, which rank the pixels according to their uncertainty, and the confidence of the user in labeling, which is related both to the homogeneity of the pixel context and to the knowledge of the user of the scene. In this paper, we propose a two-steps procedure based on a filtering scheme to learn the confidence of the user in labeling. This way, candidate training pixels are ranked according both to their uncertainty and to the chances of being labeled correctly by the user. In…
Intelligent Sampling for Vegetation Nitrogen Mapping Based on Hybrid Machine Learning Algorithms
2021
Upcoming satellite imaging spectroscopy missions will deliver spatiotemporal explicit data streams to be exploited for mapping vegetation properties, such as nitrogen (N) content. Within retrieval workflows for real-time mapping over agricultural regions, such crop-specific information products need to be derived precisely and rapidly. To allow fast processing, intelligent sampling schemes for training databases should be incorporated to establish efficient machine learning (ML) models. In this study, we implemented active learning (AL) heuristics using kernel ridge regression (KRR) to minimize and optimize a training database for variational heteroscedastic Gaussian processes regression (V…
Activation and methotrexate-mediated suppression of the TNF alpha promoter in T cells and macrophages.
1998
The Wilms' tumor suppressor gene (wt1) product regulates Dax-1 gene expression during gonadal differentiation.
1999
Gonadal differentiation is dependent upon a molecular cascade responsible for ovarian or testicular development from the bipotential gonadal ridge. Genetic analysis has implicated a number of gene products essential for this process, which include Sry, WT1, SF-1, and DAX-1. We have sought to better define the role of WT1 in this process by identifying downstream targets of WT1 during normal gonadal development. We have noticed that in the developing murine gonadal ridge, wt1 expression precedes expression of Dax-1, a nuclear receptor gene. We document here that the spatial distribution profiles of both proteins in the developing gonad overlap. We also demonstrate that WT1 can activate the D…