Application of an iterative method and an evolutionary algorithm in fuzzy optimization

This work develops two approaches based on the fuzzy set theory to solve a class of fuzzy mathematical optimization problems with uncertainties in the objective function and in the set of constraints. The first approach is an adaptation of an iterative method that obtains cut levels and later maximizes the membership function of fuzzy decision making using the bound search method. The second one is a metaheuristic approach that adapts a standard genetic algorithm to use fuzzy numbers. Both approaches use a decision criterion called satisfaction level that reaches the best solution in the uncertain environment. Selected examples from the literature are presented to compare and to validate the efficiency of the methods addressed, emphasizing the fuzzy optimization problem in some import-export companies in the south of Spain. © 2012 Brazilian Operations Research Society.

A genetic algorithm for crop rotation

In the last few years, crop rotation has gained attention due to its economic, environmental and social importance which explains why it can be highly beneficial for farmers. This paper presents a mathematical model for the Crop Rotation Problem (CRP) that was adapted from literature for this highly complex combinatorial problem. The CRP is devised to find a vegetable planting program that takes into account green fertilization restrictions, the set-aside period, planting restrictions for neighboring lots and for crop sequencing, demand constraints, while, at the same time, maximizing the profitability of the planted area. The main aim of this study is to develop a genetic algorithm and test it in a real context. The genetic algorithm involves a constructive heuristic to build the initial population and the operators of crossover, mutation, migration and elitism. The computational experiment was performed for a medium dimension real planting area with 16 lots, considering 29 crops of 10 different botanical families and a two-year planting rotation. Results showed that the algorithm determined feasible solutions in a reasonable computational time, thus proving its efficacy for dealing with this practical application.

Semiautomatic dental recognition using a graph-based segmentation algorithm and teeth shapes features

Dental recognition is very important for forensic human identification, mainly regarding the mass disasters, which have frequently happened due to tsunamis, airplanes crashes, etc. Algorithms for automatic, precise, and robust teeth segmentation from radiograph images are crucial for dental recognition. In this work we propose the use of a graph-based algorithm to extract the teeth contours from panoramic dental radiographs that are used as dental features. In order to assess our proposal, we have carried out experiments using a database of 1126 tooth images, obtained from 40 panoramic dental radiograph images from 20 individuals. The results of the graph-based algorithm was qualitatively assessed by a human expert who reported excellent scores. For dental recognition we propose the use of the teeth shapes as biometric features, by the means of BAS (Bean Angle Statistics) and Shape Context descriptors. The BAS descriptors showed, on the same database, a better performance (EER 14%) than the Shape Context (EER 20%). © 2012 IEEE.

Controlling traffic jams on urban roads modeled in Coloured Petri net using Genetic Algorithm

This paper presents an application to traffic lights control in congested urban traffic, in real time, taking as input the position and route of the vehicles in the involved areas. This data is obtained from the communication between vehicles and infrastructure (V2I). Due to the great complexity of the possible combination of traffic lights and the short time to get a response, Genetic Algorithm was used to optimize this control. According to test results, the application can reduce the number of vehicles in congested areas, even with the entry of vehicles that previously were not being considered in these roads, such as parked vehicles. © 2012 IEEE.

Causes of resistant hypertension detected by a standardized algorithm

Resistant hypertension (RH) is characterized by blood pressure above 140 × 90 mm Hg, despite the use, in appropriate doses, of three antihypertensive drug classes, including a diuretic, or the need of four classes to control blood pressure. Resistant hypertension patients are under a greater risk of presenting secondary causes of hypertension and may be benefited by therapeutical approach for this diagnosis. However, the RH is currently little studied, and more knowledge of this clinical condition is necessary. In addition, few studies had evaluated this issue in emergent countries. Therefore, we proposed the analysis of specific causes of RH by using a standardized protocol in Brazilian patients diagnosed in a center for the evaluation and treatment of hypertension. The management of these patients was conducted with the application of a preformulated protocol which aimed at the identification of the causes of resistant hypertension in each patient through management standardization. The data obtained suggest that among patients with resistant hypertension there is a higher prevalence of secondary hypertension, than that observed in general hypertensive ones and a higher prevalence of sleep apnea as well. But there are a predominance of obesity, noncompliance with diet, and frequent use of hypertensive drugs. These latter factors are likely approachable at primary level health care, since that detailed anamneses directed to the causes of resistant hypertension are applied. © 2012 Livia Beatriz Santos Limonta et al.

Structure, histochemistry and ultrastructure of the male reproductive accessory glands in the neotropical flat-faced fruit-eating bat Artibeus planirostris (Chiroptera: Phyllostomidae)

Chiroptera, the second largest mammalian order, presents different reproductive strategies and unique reproductive features. However, there are few reports regarding male reproductive accessory glands (RAGs) in Chiroptera. Thus, the aim of the present study was to characterise the RAGs of the exclusively neotropical bat Artibeus planirostris (Chiroptera: Phyllostomidae) macroscopically, microscopically and ultrastructurally. The RAGs were composed of a prostatic complex with two regions (ventral and dorsal) and paraurethral and bulbourethral glands, but no seminal vesicles. The ventral region had an undefined epithelium, with secretory and basal cells, and its secretions were periodic acid-Schiff (PAS) positive. The dorsal region received both deferens ducts, had a columnar pseudostratified epithelium with secretory and basal cells. There were two types of secretions from the dorsal region: one that was basophilic and another that was mixed PAS positive and PAS negative. The paraurethral glands were dispersed in the connective tissue of the urethra, whereas the bulbourethral glands were located in the penile root. Histological and ultrastructural data confirmed the prostatic nature of the ventral and dorsal regions and the holocrine nature of the ventral region, with the latter finding never having been described previously for the prostate gland. Our findings demonstrate the wide discrepancy of RAGs between A. planirostris and other mammals in terms of their composition, structure and morphology. © CSIRO 2013.

A hybrid multi-population genetic algorithm applied to solve the multi-level capacitated lot sizing problem with backlogging

The present paper proposes a new hybrid multi-population genetic algorithm (HMPGA) as an approach to solve the multi-level capacitated lot sizing problem with backlogging. This method combines a multi-population based metaheuristic using fix-and-optimize heuristic and mathematical programming techniques. A total of four test sets from the MULTILSB (Multi-Item Lot-Sizing with Backlogging) library are solved and the results are compared with those reached by two other methods recently published. The results have shown that HMPGA had a better performance for most of the test sets solved, specially when longer computing time is given. © 2012 Elsevier Ltd.

A heuristic algorithm based on multi-assignment procedures for nurse scheduling

This paper tackles a Nurse Scheduling Problem which consists of generating work schedules for a set of nurses while considering their shift preferences and other requirements. The objective is to maximize the satisfaction of nurses' preferences and minimize the violation of soft constraints. This paper presents a new deterministic heuristic algorithm, called MAPA (multi-assignment problem-based algorithm), which is based on successive resolutions of the assignment problem. The algorithm has two phases: a constructive phase and an improvement phase. The constructive phase builds a full schedule by solving successive assignment problems, one for each day in the planning period. The improvement phase uses a couple of procedures that re-solve assignment problems to produce a better schedule. Given the deterministic nature of this algorithm, the same schedule is obtained each time that the algorithm is applied to the same problem instance. The performance of MAPA is benchmarked against published results for almost 250,000 instances from the NSPLib dataset. In most cases, particularly on large instances of the problem, the results produced by MAPA are better when compared to best-known solutions from the literature. The experiments reported here also show that the MAPA algorithm finds more feasible solutions compared with other algorithms in the literature, which suggest that this proposed approach is effective and robust. © 2013 Springer Science+Business Media New York.

The Vampirome: Transcriptome and proteome analysis of the principal and accessory submaxillary glands of the vampire bat Desmodus rotundus, a vector of human rabies

Vampire bats are notorious for being the sole mammals that strictly feed on fresh blood for their survival. While their saliva has been historically associated with anticoagulants, only one antihemostatic (plasminogen activator) has been molecularly and functionally characterized. Here, RNAs from both principal and accessory submaxillary (submandibular) salivary glands of Desmodus rotundus were extracted, and ~. 200. million reads were sequenced by Illumina. The principal gland was enriched with plasminogen activators with fibrinolytic properties, members of lipocalin and secretoglobin families, which bind prohemostatic prostaglandins, and endonucleases, which cleave neutrophil-derived procoagulant NETs. Anticoagulant (tissue factor pathway inhibitor, TFPI), vasodilators (PACAP and C-natriuretic peptide), and metalloproteases (ADAMTS-1) were also abundantly expressed. Members of the TSG-6 (anti-inflammatory), antigen 5/CRISP, and CCL28-like (antimicrobial) protein families were also sequenced. Apyrases (which remove platelet agonist ADP), phosphatases (which degrade procoagulant polyphosphates), and sphingomyelinase were found at lower transcriptional levels. Accessory glands were enriched with antimicrobials (lysozyme, defensin, lactotransferrin) and protease inhibitors (TIL-domain, cystatin, Kazal). Mucins, heme-oxygenase, and IgG chains were present in both glands. Proteome analysis by nano LC-MS/MS confirmed that several transcripts are expressed in the glands. The database presented herein is accessible online at http://exon.niaid.nih.gov/transcriptome/D_rotundus/Supplemental-web.xlsx. These results reveal that bat saliva emerges as a novel source of modulators of vascular biology. Biological significance: Vampire bat saliva emerges as a novel source of antihemostatics which modulate several aspects of vascular biology. © 2013.

Study of the ℤ3 symmetry in QCD at finite temperature and chemical potential using a worm algorithm

Traditional Monte Carlo simulations of QCD in the presence of a baryon chemical potential are plagued by the complex phase problem and new numerical approaches are necessary for studying the phase diagram of the theory. In this work we consider a ℤ3 Polyakov loop model for the deconfining phase transition in QCD and discuss how a flux representation of the model in terms of dimer and monomer variable solves the complex action problem. We present results of numerical simulations using a worm algorithm for the specific heat and two-point correlation function of Polyakov loops. Evidences of a first order deconfinement phase transition are discussed. © 2013 American Institute of Physics.

Annual reproductive cycle of males of the flat-faced fruit-eating bat, Artibeus planirostris (Chiroptera: Phyllostomidae)

Artibeus planirostris is an endemic species of Phyllostomid bat from the Neotropical region. Some studies have indicated that it exhibits seasonal bimodal polyestry; however, others postulate that it may be able to produce young at any time during the year. Thus, the aim of this study was to evaluate the annual variations in testicular and epididymal parameters of this species in southeast Brazil and try to understand how the reproduction of this species is regulated in this environment. Sixty mature male specimens, collected between June 2009 and May 2010, were submitted to morphometric and immunohistochemical analysis. Our study showed that A. planirostris presented a continuously active pattern of spermatogenesis throughout the year, presenting spermatozoa inside its cauda epididymis in all months, but with two pronounced peaks of spermatogenic production, one in September and other in February. We propose that the males developed these two peaks in order to produce sufficient sperm for the reproduction in a harem system and to synchronize with the female reproductive cycle, which had a bimodal polyestric pattern. Control of this variation is directly linked to the expression of the androgen receptor (AR) in Sertoli cells and to serum testosterone levels, which appear to synchronize to establish these two peaks. In the months preceding the two peaks, the testis have a higher expression of the AR, which possibly stimulates the increase in PCNA, and drives a gradual increase in the testicular parameters. Taken together the results suggest that if sperm storage happens in this species, it is of short duration. © 2013 Elsevier Inc.

Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging

The present paper solves the multi-level capacitated lot sizing problem with backlogging (MLCLSPB) combining a genetic algorithm with the solution of mixed-integer programming models and the improvement heuristic fix and optimize. This approach is evaluated over sets of benchmark instances and compared to methods from literature. Computational results indicate competitive results applying the proposed method when compared with other literature approaches. © 2013 IEEE.

Local data fusion algorithm for fire detection through mobile robot

Multisensor data fusion is a technique that combines the readings of multiple sensors to detect some phenomenon. Data fusion applications are numerous and they can be used in smart buildings, environment monitoring, industry and defense applications. The main goal of multisensor data fusion is to minimize false alarms and maximize the probability of detection based on the detection of multiple sensors. In this paper a local data fusion algorithm based on luminosity, temperature and flame for fire detection is presented. The data fusion approach was embedded in a low cost mobile robot. The prototype test validation has indicated that our approach can detect fire occurrence. Moreover, the low cost project allow the development of robots that could be discarded in their fire detection missions. © 2013 IEEE.

BCS: A Binary Cuckoo Search algorithm for feature selection

Feature selection has been actively pursued in the last years, since to find the most discriminative set of features can enhance the recognition rates and also to make feature extraction faster. In this paper, the propose a new feature selection called Binary Cuckoo Search, which is based on the behavior of cuckoo birds. The experiments were carried out in the context of theft detection in power distribution systems in two datasets obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others nature-inspired optimization techniques. © 2013 IEEE.

A hybrid image restoration algorithm based on Projections onto Convex Sets and Harmony Search

Image restoration is a research field that attempts to recover a blurred and noisy image. Since it can be modeled as a linear system, we propose in this paper to use the meta-heuristics optimization algorithm Harmony Search (HS) to find out near-optimal solutions in a Projections Onto Convex Sets-based formulation to solve this problem. The experiments using HS and four of its variants have shown that we can obtain near-optimal and faster restored images than other evolutionary optimization approach. © 2013 IEEE.