Search results for "methodologies"
showing 10 items of 2106 documents
Detecting RNA modifications in the epitranscriptome: predict and validate
2017
RNA modifications are emerging players in the field of post-transcriptional regulation of gene expression, and are attracting a comparable degree of research interest to DNA and histone modifications in the field of epigenetics. We now know of more than 150 RNA modifications and the true potential of a few of these is currently emerging as the consequence of a leap in detection technology, principally associated with high-throughput sequencing. This Review outlines the major developments in this field through a structured discussion of detection principles, lays out advantages and drawbacks of new high-throughput methods and presents conventional biophysical identification of modifications …
Ethics of Artificial Intelligence : Research Challenges and Potential Solutions
2020
Artificial Intelligence (AI) is a rapidly emerging paradigm with many applications in healthcare, industries, and smart cities. However, this rise of global interest in AI has fueled a renewed interest from the public sector and global policymakers. As AI networks (e.g., chatbots, automation systems, and helping agents) are paving their way as interactive household items, a critically important research issue is understanding the ethical impact of these autonomous agents. What is the explanation of the AI decision-making process? What are the legal, societal, and moral consequences of these decisions and actions? Should these AI systems be allowed to make decisions for human beings and to w…
Data Mining Algorithms for Knowledge Extraction
2020
In this paper, we study the methods, techniques, and algorithms used in data mining, and from the studied algorithms, we emphasized the clustering algorithms, more precisely on the K-means algorithm. This algorithm was first studied using the Euclidean distance, then modifying the distance between the clusters using the distances Mahalanobis and Canberra. After implementing the algorithms in C/C++, we compared the clustering of the three algorithms, after which we modified them and studied the distance between the clusters.
noRANSAC for fundamental matrix estimation
2011
The estimation of the fundamental matrix from a set of corresponding points is a relevant topic in epipolar stereo geometry [10]. Due to the high amount of outliers between the matches, RANSAC-based approaches [7, 13, 29] have been used to obtain the fundamental matrix. In this paper two new contributes are presented: a new normalized epipolar error measure which takes into account the shape of the features used as matches [17] and a new strategy to compare fundamental matrices. The proposed error measure gives good results and it does not depend on the image scale. Moreover, the new evaluation strategy describes a valid tool to compare diffe rent RANSAC-based methods because it does not re…
On thermoeconomics of energy systems at variable load conditions: integrated optimization of plant design and operation
2007
Abstract Thermoeconomics has been assuming a growing role among the disciplines oriented to the analysis of energy systems, its different methodologies allowing solution of problems in the fields of cost accounting, plant design optimisation and diagnostic of malfunctions. However, the thermoeconomic methodologies as such are particularly appropriate to analyse large industrial systems at steady or quasi-steady operation, but they can be hardly applied to small to medium scale units operating in unsteady conditions to cover a variable energy demand. In this paper, the fundamentals of thermoeconomics for systems operated at variable load are discussed, examining the cost formation process an…
Search for new phenomena in final states with large jet multiplicities and missing transverse momentum at s√=8 TeV proton-proton collisions using the…
2013
A search is presented for new particles decaying to large numbers (7 or more) of jets, with missing transverse momentum and no isolated electrons or muons. This analysis uses 20.3 fb[superscript −1] of pp collision data at s√ = 8 TeV collected by the ATLAS experiment at the Large Hadron Collider. The sensitivity of the search is enhanced by considering the number of b-tagged jets and the scalar sum of masses of large-radius jets in an event. No evidence is found for physics beyond the Standard Model. The results are interpreted in the context of various simplified supersymmetry-inspired models where gluinos are pair produced, as well as an mSUGRA/CMSSM model.
Infrared image processing and its application to forest fire surveillance
2007
This paper describes an scheme for automatic forest surveillance. A complete system for forest fire detection is firstly presented although we focus on infrared image processing. The proposed scheme based on infrared image processing performs early detection of any fire threat. With the aim of determining the presence or absence of fire, the proposed algorithms performs the fusion of different detectors which exploit different expected characteristics of a real fire, like persistence and increase. Theoretical results and practical simulations are presented to corroborate the control of the system related with probability of false alarm (PFA). Probability of detection (PD) dependence on sign…
Automatic image representation for content-based access to personal photo album
2007
The proposed work exploits methods and techniques for automatic characterization of images for content-based access to personal photo libraries. Several techniques, even if not reliable enough to address the general problem of content-based image retrieval, have been proven quite robust in a limited domain such as the one of personal photo album. In particular, starting from the observation that most personal photos depict a usually small number of people in a relatively small number of different contexts (e.g. Beach, Public Garden, Indoor, Nature, Snow, City, etc...) we propose the use of automatic techniques borrowed from the fields of computer vision and pattern recognition to index imag…
A multiagent system approach for image segmentation using genetic algorithms and extremal optimization heuristics
2006
We propose a new distributed image segmentation algorithm structured as a multiagent system composed of a set of segmentation agents and a coordinator agent. Starting from its own initial image, each segmentation agent performs the iterated conditional modes method, known as ICM, in applications based on Markov random fields, to obtain a sub-optimal segmented image. The coordinator agent diversifies the initial images using the genetic crossover and mutation operators along with the extremal optimization local search. This combination increases the efficiency of our algorithm and ensures its convergence to an optimal segmentation as it is shown through some experimental results.
RootsGLOH2: embedding RootSIFT 'square rooting' in sGLOH2
2020
This study introduces an extension of the shifting gradient local orientation histogram doubled (sGLOH2) local image descriptor inspired by RootSIFT ‘square rooting’ as a way to indirectly alter the matching distance used to compare the descriptor vectors. The extended descriptor, named RootsGLOH2, achieved the best results in terms of matching accuracy and robustness among the latest state-of-the-art non-deep descriptors in recent evaluation contests dealing with both planar and non-planar scenes. RootsGLOH2 also achieves a matching accuracy very close to that obtained by the best deep descriptors to date. Beside confirming that ‘square rooting’ has beneficial effects on sGLOH2 as it happe…