In mining projects, all uncertainties associated with a project must be considered to determine the feasibility study. Grade uncertainty is one of the major components of technical uncertainty that affects the variability of the project. Geostatistical simulation, as a reliable approach, is the most widely used method to quantify risk analysis to overcome the drawbacks of the estimation methods...

PURPOSE To develop a fully automated algorithm (AP) to perform a volumetric measure of the optic disc using conventional stereoscopic optic nerve head (ONH) photographs, and to compare algorithm-produced parameters with manual photogrammetry (MP), scanning laser ophthalmoscope (SLO) and optical coherence tomography (OCT) measurements. METHODS One hundred twenty-two stereoscopic optic disc pho...

Inspired by the evolution process of human intelligence and the social learning theory, a new swarm intelligence algorithm paradigm named the social learning optimization (SLO) algorithm is proposed. SLO consists of three co-evolution spaces: the bottom is the micro-space, where genetic evolution occurs; the middle layer is the learning space, where individuals enhance their intelligence throug...

Adaptive optics scanning laser ophthalmoscopy (AO-SLO) has recently been used to achieve exquisite subcellular resolution imaging of the mouse retina. Wavefront sensing-based AO typically restricts the field of view to a few degrees of visual angle. As a consequence the relationship between AO-SLO data and larger scale retinal structures and cellular patterns can be difficult to assess. The ret...

This paper presents a novel biologically inspired metaheuristic algorithm called seven-spot ladybird optimization (SLO). The SLO is inspired by recent discoveries on the foraging behavior of a seven-spot ladybird. In this paper, the performance of the SLO is compared with that of the genetic algorithm, particle swarm optimization, and artificial bee colony algorithms by using five numerical ben...

in this paper, we study the generalized bin covering problem. for this problem an exact algorithm is introduced which can nd optimal solution for small scale instances. to nd a solution near optimal for large scale instances, a heuristic algorithm has been proposed. by computational experiments, the eciency of the heuristic algorithm is assessed.

This paper presents a new method to quickly extract geodesic paths on images and 3D meshes. We use a heuristic to drive the front propagation procedure of the classical Fast Marching. This results in a modification of the Fast Marching algorithm that is similar to the A∗ algorithm used in artificial intelligence. In order to find very quickly geodesic paths between any given pair of points, two...

this paper presents a new meta-heuristic solution to find the efficient frontier using the mean-variance approach. portfolio optimization problem is a quadratic programming model and, changes to np-hard if the number of assets and constraints has increased, and it cannot be solved using common mathematical methods in a reasonable time. therefore, a heuristic or meta-heuristic algorithm should b...

Streptococcus dysgalactiae subsp. equisimilis (SDSE) has emerged as an important cause of severe skin and soft tissue infections, but little is known of the pathogenic mechanisms underlying tissue pathology. Patient samples and a collection of invasive and non-invasive group G SDSE strains (n = 69) were analyzed with respect to virulence factor expression and cytotoxic or inflammatory effects o...

one of the most important and valuable goal of software development life cycle is software cost estimation or sce. during the recent years, sce has attracted the attention of researchers due to huge amount of software project requests. there have been proposed so many models using heuristic and meta-heuristic algorithms to do machine learning process for sce. cocomo81 is one of the most popular...