Thiago de Castro Martins

Simulated annealing with adaptive neighborhood: A case study in off-line robot path planning

Simulated annealing (SA) is an optimization technique that can process cost functions with degrees of nonlinearities, discontinuities and stochasticity. It can process arbitrary boundary conditions and constraints imposed on these cost functions. The SA technique is applied to the problem of robot path planning. Three situations are considered here: the path is represented as a polyline; as a Bezier curve; and as a spline interpolated curve. In the proposed SA algorithm, the sensitivity of each continuous parameter is evaluated at each iteration increasing the number of accepted solutions. The sensitivity of each parameter is associated to its probability distribution in the definition of the next candidate.

Image Reconstruction Using Interval Simulated Annealing in Electrical Impedance Tomography

Electrical impedance tomography (EIT) is an imaging technique that attempts to reconstruct the impedance distribution inside an object from the impedance between electrodes placed on the object surface. The EIT reconstruction problem can be approached as a nonlinear nonconvex optimization problem in which one tries to maximize the matching between a simulated impedance problem and the observed data. This nonlinear optimization problem is often ill-posed, and not very suited to methods that evaluate derivatives of the objective function. It may be approached by simulated annealing (SA), but at a large computational cost due to the expensive evaluation process of the objective function, which involves a full simulation of the impedance problem at each iteration. A variation of SA is proposed in which the objective function is evaluated only partially, while ensuring boundaries on the behavior of the modified algorithm.

A Rickettsia parkeri-like agent infecting Amblyomma calcaratum nymphs from wild birds in Mato Grosso do Sul, Brazil

In total, 142 birds, mostly passerines, belonging to 42 species were examined for the presence of ticks in 3 locations in Mato Grosso do Sul Brazil during 2006. Seven birds (5%) were infested with 4 nymphs of Amblyomma calcaratum (Ramphocelus carbo, 3 infested/12 examined) and 5 larvae of Amblyomma sp. (Furnarius rufus, 2/5; Turdus leucomelas, 1/6; and Paroaria capitata, 1/8). All 4 nymphs of A. calcaratum tested by polymerase chain reaction targeting rickettsial genes gltA and ompA and by amplicon sequencing were found to be infected with a Rickettsia sp. strain NOD, a Rickettsia parkeri-like agent. A. calcaratum infected with a rickettsial bacterium was found for the first time.

An algorithm for the strip packing problem using collision free region and exact fitting placement

The irregular shape packing problem is approached. The container has a fixed width and an open dimension to be minimized. The proposed algorithm constructively creates the solution using an ordered list of items and a placement heuristic. Simulated annealing is the adopted metaheuristic to solve the optimization problem. A two-level algorithm is used to minimize the open dimension of the container. To ensure feasible layouts, the concept of collision free region is used. A collision free region represents all possible translations for an item to be placed and may be degenerated. For a moving item, the proposed placement heuristic detects the presence of exact fits (when the item is fully constrained by its surroundings) and exact slides (when the item position is constrained in all but one direction). The relevance of these positions is analyzed and a new placement heuristic is proposed. Computational comparisons on benchmark problems show that the proposed algorithm generated highly competitive solutions. Moreover, our algorithm updated some best known results.

SIMULATED ANNEALING APPLIED TO THE ROTATIONAL POLYGON PACKING

Abstract This work deals with the problem of minimize the waste of space that occurs on a placement of a set of bi-dimensional polygons inside a bi-dimensional container. This problem is approached with an heuristic based on Simulated Annealing, which is inspired on the physic-chemical process that take place during the recrystallization of a metal. Traditional “external penalization” techniques are avoided through the application of the Minkowski sum algorithm, that represents collision-free areas for the set of polygons. That gives to the proposed process a more universal character, as external penalization are based on empiric parameters of great influence on the optimization performance. The proposed process is suited for non-convex polygons and containers, and can be easily adapted for related problems, such as container size minimization.

Pre-hatching embryo-dependent and -independent programming of endometrial function in cattle

The bovine pre-implantation embryo secretes bioactive molecules from early development stages, but effects on endometrial function are reported to start only after elongation. Here, we interrogated spatially defined regions of the endometrium transcriptome for responses to a day 7 embryo in vivo. We hypothesize that exposure to an embryo changes the abundance of specific transcripts in the cranial region of the pregnant uterine horn. Endometrium was collected from the uterotubal junction (UTJ), anterior (IA), medial (IM) and posterior (IP) regions of the uterine horn ipsilateral to the CL 7 days after estrus from sham-inseminated (Con) or artificially inseminated, confirmed pregnant (Preg) cows. Abundance of 86 transcripts was evaluated by qPCR using a microfluidic platform. Abundance of 12 transcripts was modulated in the Preg endometrium, including classical interferon-stimulated genes (ISG15, MX1, MX2 and OAS1Y), prostaglandin biosynthesis genes (PTGES, HPGD and AKR1C4), water channel (AQP4) and a solute transporter (SLC1A4) and this was in the UTJ and IA mainly. Additionally, for 71 transcripts, abundance varied according to region of the reproductive tract. Regulation included downregulation of genes associated with proliferation (IGF1, IGF2, IGF1R and IGF2R) and extracellular matrix remodeling (MMP14, MMP19 and MMP2) and upregulation of anti-adhesive genes (MUC1) in the cranial regions of uterine horn. Physical proximity to the embryo provides paracrine regulation of endometrial function. Embryo-independent regulation of the endometrial transcriptome may support subsequent stages of embryo development, such as elongation and implantation. We speculate that successful early embryo-dependent and -independent programming fine-tune endometrial functions that are important for maintenance of pregnancy in cattle.

Electrical impedance tomography reconstruction through Simulated Annealing with incomplete evaluation of the objective function

The EIT reconstruction problem is approached as an optimization problem where the difference between a simulated impedance domain and the observed one is minimized. This optimization problem is often solved by Simulated Annealing (SA), but at a large computational cost due to the expensive evaluation process of the objective function. We propose here, a variation of SA applied to EIT where the objective function is evaluated only partially, while ensuring upper boundaries on the deviation on the behavior of the modified SA. The reconstruction method is evaluated with simulated and experimental data.

Converting CSG models into meshed B-Rep models using euler operators and propagation based marching cubes

The purpose of this work is to define a new algorithm for converting a CSG representation into a B-Rep representation. Usually this conversion is done determining the union, intersection or difference from two B-Rep represented solids. Due to the lack of explicit representation of surface boundaries, CSG models must be converted into B-Rep solid models when a description based on polygonal mesh is required. A potential solution is to convert a CSG model into a voxel based volume representation and then construct a B-Rep solid model. This method is called CSG voxelization, conceptually it is a set membership classification problem with respect to the CSG object for all sampling points in a volume space. Marching cubes algorithms create a simple mesh that is enough for visualization purposes. However, when engineering processes are involved, a solid model is necessary. A solid ensures that all triangles in the mesh are consistently oriented and define a closed surface. It is proposed in this work an algorithm for converting CSG models into triangulated solid models through propagation based marching cubes algorithm. Three main new concepts are used in the algorithm: open boundary, B-Rep/CSG Voxelization mapping and constructive triangulation of active cells. The triangles supplied by the marching cubes algorithm need not be coherently oriented; the algorithm itself finds the correct orientation for the supplied triangles. The proposed algorithm restricts the exploration to the space occupied by the solids boundary. Differently from normal marching cubes algorithms that explore the complete sampled space. Keywords : solid model, marching cubes algorithm, triangular meshes

Rotational Placement using Simulated Annealing and Collision Free Region

Abstract The packing problem, which considers how to arrange items on a container without overlaps, can increase the utility rate of the sheet stock. This paper investigates the irregular shape rotational packing problem. In this work the Simulated Annealing (SA) is combined with deterministic heuristics (larger first (LF), bottom left (BL) and translations only (Tr)). The problem is represented as an ordered list of items to be packed, and the items are placed touching already placed items or container. The items are placed on the vertices of the collision free region (CFR). The CRF is determined by a robust implementation of non manifold Boolean operations. Several results comparing the SA with deterministic heuristics are presented.

Rotational placement of irregular polygons over containers with fixed dimensions using simulated annealing and no-fit polygons

This work deals with the problem of minimizing the waste of space that occurs on a rotational placement of a set of irregular bi-dimensional small items inside a bi-dimensional large object. This problem is approached with an heuristic based on simulated annealing. Traditional “external penalization” techniques are avoided through the application of the no-fit polygon, that determinates the collision-free region for each small item before its placement. The simulated annealing controls: the rotation applied ch non-placed small item, a limited depth binary search is performed to find a scale factor that when applied to the small item, would allow it to be fitted in the large object. Three possibilities to define the sequence on which the small items are placed are studied: larger-first, random permutation and weight sorted. The proposed algorithm is suited for non-convex small items and large objects.