Convex Perimeter Research Articles

Graphite Compactness Degree and Nodularity of High-Si Ductile Iron Produced via Permanent Mold versus Sand Mold Casting

In recent years, high-Si ductile cast irons (3–6% Si) have begun to be used more and more in the automotive and maritime industries, but also in wind energy technology and mechanical engineering. Si-alloyed ferrite has high strength, hardness and oxidation and corrosion resistance, but it has low ductility, toughness and thermal conductivity, with graphite as an important influencing factor. In this study, 4.5% Si uninoculated ductile iron solidified in thin wall castings (up to 15 mm section size) via a permanent (metal) mold versus a sand mold, was evaluated. Solidification in a metal mold led to small size, higher graphite particles (less dependent on the section size). The graphite particles’ real perimeter was 3–5% higher than the convex perimeter, while the values of these parameters were 41–43% higher in the sand mold. Increasing the casting section size led to an increased graphite perimeter, with it being much higher for sand mold. The graphite particles’ shape factors, involving the maximum and minimum size, were at a lower level for metal mold solidification, while by involving the difference between Pr and Pc, is higher for the metal mold. The shape factor, including the graphite area and maximum size, had higher values in the metal mold, sustaining a higher compactness degree of graphite particles and a higher nodularity regarding metal mold solidification (75.5% versus 67.4%). The higher was due to the graphite compactness degree level (shape factor increasing from 0.50 up to 0.80), while the lower was due to the graphite nodularity for both the metal mold (39.1% versus 88.5%) and the sand mold (32.3% versus 83.1%). The difference between the metal mold and sand mold as the average graphite nodularity increased favored the metal mold.

Extremal convex polygons inscribed in a given convex polygon

A convex polygon Q is inscribed in a convex polygon P if every side of P contains at least one vertex of Q. We present algorithms for finding a minimum area and a minimum perimeter convex polygon inscribed in any given convex n-gon in O(n) and O(n3) time, respectively. We also investigate other variants of this problem.

Weightage of Mature Leaf in Eucalyptus Clones in Characterization and Variability Assessment for DUS Testing (Distinct, Uniform and Stable) using MuInvariant Analysis

The studies were undertaken to develop DUS testing guidelines of selected 25 Eucalyptus clones from commonly available 82 clones from Institute of Forest Genetics and Tree Breeding (IFGTB). The results revealed that all individual clones showed considerable variation in qualitative, pseudo-qualitative and quantitative characteristic traits (17 morpho-metric traits) of Mature leaves and were grouped into different categories. The traits like leaf shape, base shape, apex shape, margin, symmetry, petiole length, lamina area, length, breadth, perimeter, convex perimeter, curve length, curve width, roundness, aspect ratio, convex area and full ratio were identified as grouping traits. The weightage of the quantitative traits were proven by Multi-variant analysis. In Canonical Discriminant analysis, three significant discriminant functions, which had Eigen value >1 and this 3 values accounted for a cumulative variation of 76.2%. In Principal Component Analysis, two significant principal components (PCs) extracted had Eigen value >1 and out of 12 this two values accounted for a cumulative variation of 89.47%. In Eucalyptus clones the dendrogram drawn depicted three distinct clusters based on the similarity using Pearson correlation coefficient method. The dendrogram drawn depicted three distinct clusters based on the euclidean distances grouped them by dissimilarity using agglomerative hierarchical clustering technique (Ward’s method).

Effects of a solid lipid curcumin particle formulation on chronic activation of microglia and astroglia in the GFAP-IL6 mouse model

Chronic glial activation is characterized by increased numbers of activated glial cells, secreting free radicals and cytotoxic cytokines, subsequently causing neuronal damage. In order to investigate the anti-inflammatory activity of Longvida® Optimised Curcumin (LC), we fed 500 ppm of LC to 2-month-old wild type and GFAP-IL6 mice for 6 months. LC feeding led to a significant reduction in the number of Iba-1+ microglia by 26% in the hippocampus and by 48% in the cerebellum, GFAP+ astrocytes by 30%, and TSPO+ cells by 24% in the hippocampus and by 31% in the cerebellum of the GFAP-IL6 mice. The morphology of the cells was assessed and LC significantly decreased the dendritic length of microglia and the convex area, convex perimeter, dendritic length, nodes and number of processes of astrocytes in the hippocampus while decreasing the soma area and perimeter in the cerebellum, in LC-fed GFAP-IL6 mice. In addition, LC feeding increased pre- and postsynaptic protein levels and improved balance measured by Rotarod. Together, these data suggest that LC is able to attenuate the inflammatory pathology and ameliorate neurodegeneration and motor deficits in GFAP-IL6 mice. For patients with neuro-inflammatory disorders, LC might potentially reverse the detrimental effects of chronic glial activation.

Thermophysical properties of camelina (Camelina sativa (L.) Crantz) seeds fertilized with nitrogen

AbstractThe aim of this study was to evaluate the effect of nitrogen fertilization (0, 40, 80, 120, 160 kg N ha−1) on changes in selected physical, thermal, and geometric parameters of camelina seeds. Samples 0 kg N ha−1 and 40 kg N ha−1 formed a homogenous group with lower values of 1,000 seed weight and differed significantly from the second homogeneous group of samples 80, 120, and 160 kg N ha−1 with higher 1,000 seed weight. Nitrogen fertilization did not exert a significant effect on bulk density, true density, or porosity. Fertilization had no significant effect on the thermal properties of camelina seeds. Based on all linear dimensions and shape factors, samples 0 and 40 kg N ha−1 formed one homogenous group and were significantly different from the remaining samples. Samples 0 and 40 kg N ha−1 were characterized by the lowest values of linear dimensions, including length, width, surface area, profile specific perimeter, and convex perimeter, the lowest values of selected shape factors, including diameter range, standard deviation of all radii, Blair‐Bliss coefficient, and Danielsson coefficient, as well as the highest values of the radius ratio and roundness.Practical ApplicationsNitrogen fertilization strongly influences the properties of camelina seeds. Camelina seeds subjected to 120 kg N ha−1 were characterized by the highest dimensions, such as: length, width, surface area, and high values of 1,000 seed weight and they may be most desirable to be used in practice.

Geometric Analysis of Estimability of Target Object Shape Using Location-Unknown Distance Sensors

We geometrically analyze the problem of estimating parameters related to the shape and size of a 2-D target object on the plane by using randomly distributed distance sensors whose locations are unknown. Based on the analysis using geometric probability, we discuss the estimability of these parameters: which parameters we can estimate and what conditions are required to estimate them. For a convex target object, its size and perimeter length can be estimated, and other parameters cannot be estimated. For a general polygon target object, convexity, in addition to its size and perimeter length, can be estimated. Parameters related to a concave vertex can be estimated when some conditions are satisfied. We also propose a method for estimating the convexity of a target object and the perimeter length of the target object.

Morphological Feature Extraction of Jabon’s Leaf Seedling Pathogen using Microscopic Image

This research aims to analyze morphological techniques for feature extraction of Jabon’s leaf seedling pathogen using digital microscopic image. The kinds of the pathogen were Curvularia sp., Colletotrichum sp., and Fusarium sp.. Pathogens or causes of disease were identified manually based on macroscopic and microscopic observation of morphological characters. Morphological characters describe the characteristics of shape, color and size of a pathogen structure. We focused on shape feature by using the morphological techniques to feature extraction. The morphology features extraction used were area, perimeter, convex area, convex perimeter, compactness, solidity, convexity, and roundness. The methodologies were acquisition, preprocessing, features extraction and data analysis for derivative features. With features extraction, we got the pattern that described each pathogen for pathogen identification. From the experimental result showed that compactness and roundness feature were able to differentiate each pathogen due to that the characteristics of each pathogen class were separated.

New results on stabbing segments with a polygon

We consider a natural variation of the concept of stabbing a set of segments with a simple polygon: a segment s is stabbed by a simple polygon P if at least one endpoint of s is contained in P, and a segment set S is stabbed by P if P stabs every element of S. Given a segment set S, we study the problem of finding a simple polygon P stabbing S in a way that some measure of P (such as area or perimeter) is optimized. We show that if the elements of S are pairwise disjoint, the problem can be solved in polynomial time. In particular, this solves an open problem posed by Löffler and van Kreveld [Algorithmica 56(2), 236–269 (2010)] [16] about finding a maximum perimeter convex hull for a set of imprecise points modeled as line segments. Our algorithm can also be extended to work for a more general problem, in which instead of segments, the set S consists of a collection of point sets with pairwise disjoint convex hulls. We also prove that for general segments our stabbing problem is NP-hard.

Blind Separation of Dependent Sources With a Bounded Component Analysis Deflationary Algorithm

The problem of blind source separation of complex-valued sources from a linear mixture is addressed. We propose a deflationary algorithm for the sequential recovery of a set of communication signals, where each source is extracted by performing a Bounded Component Analysis of the linear mixture. The contribution of each recovered source to the observations is removed by minimizing its convex perimeter, without using second-order statistics. This implies to run a gradient descent algorithm several times. In order to accelerate the convergence, we have derived a fast step size that exploits the second-order information of the cost function by means of the augmented Hessian matrix. Computer simulations show that the proposed method is able to blindly separate even dependent sources, as long as they satisfy the BCA separability conditions. Also, the speed of convergence of this novel step size is compared with other classical approaches.

Artificial neural network in diagnosis of lobular carcinoma of breast in fine‐needle aspiration cytology

In this study, we applied artificial neural network (ANN) for the diagnosis of lobular carcinoma in fine-needle aspiration cytology (FNAC) material. We selected a total of 64 cases of histology proven breast lesions consisting of 20 fibroadenomas, 28 infiltrating ductal carcinomas (IDC), and 16 infiltrating lobular carcinomas (ILC). Detailed cytomorphological features were studied on representative Haematoxylin-Eosin (H&E) and May-Grunwald Giemsa stained slides. Image morphometric analysis was performed on Haematoxylin-Eosin stained smears to study nuclear area, diameter, perimeter, roundness, convex area, and convex perimeter. Both the qualitative cytological features and objective morphometric data were collected and a total of 18 variables were studied. Back propagation ANN was designed and this data were used as input values. ANN network was designed as 34-17-3. There were a total of 34 first layers neurons, 17 hidden neurons and three output neurons. The total cases were randomly divided automatically by the program into three groups: training set (40), validation set (8), and test set (16). After the successful training, the program was able to differentiate all the benign and lobular carcinoma cases and majority of the ductal carcinoma cases. In test set, the ANN program successfully classified all the cases of benign, and ILC cases and six of seven IDC cases. A suitably designed ANN may be able to diagnose the lobular carcinoma of breast on FNAC material. ANN is an efficient software program with immense potential.

Morphometric analysis of llama (Lama glama) sperm head

Llama production in Argentina has increased, as the international interest in breeding this type of animals has grown in the last years. Considering the great polymorphism that llama spermatozoa present at evaluation using light microscopy, the aim of this study was to objectively evaluate llama sperm head morphometry using digital morphometric analysis. Five ejaculates from each of eight males were obtained to evaluate morphometric parameters of 8000 sperm heads stained with Tinción 15(®). The following average results were obtained for each parameter: size parameters: area 20.09 μm(2), length 6.60 μm, width 4.14 μm, equivalent circle diameter 5.06 μm, curve length 5.79 μm and curve width 3.48 μm; boundary parameters: perimeter 18.54 μm and convex perimeter 17.34 μm; and shape parameters: roundness 1.28 and elongation 1.59. Morphometric parameters of sperm head were compared between ejaculates of the same male and between males. Significant differences between ejaculates of the same male were found for all parameters evaluated (P < 0.01). Significant differences between males were found for all morphometric parameters (P < 0.01) except for curve length, curve width and perimeter. The differences detected would indicate that there is not a single morphometric pattern for Lama glama sperm head, because parameter values cannot be standardised.

Contribution of nuclear morphometric features to differentiation of atypical complex type endometrial hyperplasia and low grade endometrial carcinoma

Objective: The differentiation of atypical complex type endometrial hyperplasia (ACEH) and low grade endometrial carcinoma (EC) may be problematic in endometrial biopsy materials. Desmoplasia and stromal invasion are diagnostic for EC but they are not always demonstrated in endometrial biopsies. In this study, we investigated the contribution of nuclear morphometry to distinction of ACEH and low grade EC. Methods: Ten low grade EC and eight ACEH cases retrieved from the archives of the Department of Pathology. For each case at least 100 nuclei (totally 1000 for both groups) were selected using hematoxylen-eosine stained sections and evaluated by a computer assisted system. Measured nuclear morphometric features were nuclear area, nuclear perimeter, circular form factor, diameter equivalent circle, minimum feret, maximum feret, area convex hull, perimeter convex hull. Results: There was no significant differences between these two groups for circular form factor (P=0.871). But all other morphometric features were statistically significant (P<0.05). Conclusion: Our findings suggest that nuclear morphometric features may be used as an ancillary diagnostic tool in addition to conventional histopathological findings in borderline lesion. These findings should be confirmed with expanded case series.

Bounded Component Analysis of Linear Mixtures: A Criterion of Minimum Convex Perimeter

This study presents a blind and geometric technique which pursues the linear decomposition of the observations in bounded component signals. The bounded component analysis of the observations relies on the hypotheses of compactness and Cartesian decomposition of the convex support of the vector of component signals, and in the invertibility of the mixture. Assumptions, which in absence of noise, are able to guarantee the identifiability of the mixture and separability of the components, up to permutation, scaling, and phase ambiguities. Under these conditions, the convex perimeter of the normalized linear combination of the observations is shown to be a global contrast function whose minima correspond with the extraction of bounded components of the observations. Practical extraction and separation algorithms based on the minimization of this criterion are given. The experimental results with communications signals serve to illustrate the good performance of the proposed method in high SNR scenarios, even for a small number of samples.

309 MORPHOMETRICAL ANALYSIS OF THE LAMA GLAMA SPERM HEAD

During the last decades, the interest in breeding South American Camelids has increased, not only as companion animals but also for their high- quality fiber. Although several studies have been carried out on artificial insemination in Lama glama, this technique has not been widely applied in reproductive programs, principally due to the difficulty in collecting raw semen from males and the lack of knowledge about freezing/thawing techniques and semen characteristics. The aim of the present study was to objectively characterize llama sperm morphometry by a computer-assisted system, thereby increasing the knowledge on male llama physiology, leading to further developement of reproductive biotechnologies such as artificial insemination. Five semen samples were obtained by electroejaculation from each of 8 males, 6- to 10-year-old llamas of proven fertility. Smears were prepared from each sample and stained with Tinción 15® (Biopur S.R.L., Rosario, Argentina) and observed at x 1000 magnification. Images of sperm heads were captured by a Leica DC180 camera (Leica Microsystems Co., Wetzlar, Germany), obtaining 200 images from each sample. Binary images were obtained and area, length, width, equivalent circle diameter, curve length, curve width, perimeter, convex perimeter, roundness, and elongation were measured using QWin Plus (Leica Microsystems Co.). A total of 8005 sperm heads were measured. Descriptive statistics of the complete population was performed, with the following results obtained (mean ± SD): area (μm2) 20.09 ± 0.6, length (μm) 6.6 ± 0.3, width (μm) 4.14 ± 0.1, equivalent diameter ((μm) 5.06 ± 0.1, curve length (μm) 5.8 ± 0.3, curve width (μm) 3.48 ± 0.3, perimeter (μm) 18.54 ± 0.1, convex perimeter (μm) 17.34 ± 0.3, roundness 1.28 ± 0.04, and elongation 1.6 ± 0.01. Coefficients of variation were between 0.47 and 8.72%. A design considering the male as a fixed factor and the ejaculate as a nested factor was used for the purpose of identifying differences in morphometry between ejaculates of the same male and/or between males. Normality was tested using the Kolmogorov test. Significant differences between ejaculates of some males were found for curve length, curve width, perimeter, roundness, and elongation (P &lt; 0.05). There were no intra-male differences for sperm head area, length, width, equivalent circle diameter, and convex perimeter. Of the parameters, there were significant differences between males for sperm area, length, equivalent circle diameter, and convex perimeter (P &lt; 0.05). The differences found in sperm morphometry confirm the great polymorphism observed when subjectively evaluating llama semen morphology and make the establishment of a single pattern of normal llama sperm morphometry impossible.

Application of ANOVA to image analysis results of talc particles produced by different milling

This study presents statistical evaluation of the shape parameters for different mill products of talc mineral using Clemex image analysis system. The aim of this study was to determine whether the image parameters of the three different mill products were statistically different from each other or not. Image analysis of talc particles ground by laboratory size ball, rod and autogenous mills was performed with a Nikon SMZ 800 stereoscopic zoom microscope and a Clemex PE image analysis system. A total of 446 particles were measured by image analysis for these three different mill products. The shape data such as area, perimeter, convex perimeter, sphericity and roughness were compared by applying one way ANOVA (analysis of variance) method followed by post hoc Tukey's test using the software SPSS (Statistical Package for Social Science) with a .05 significance level. Multiple comparison tests revealed that, the difference between the image data group for different mill products are significant with a 95% confidence level. Finally, autogenous mill products had the highest sphericity and the smoothness among the ball and rod mill products due to its abrasion effect on talc mineral studied. On the other hand, the roughest and most elongated particles of talc mineral studied were obtained by rod milling.

Imaging and Soft Computing for Online Trash Identification in Cotton

A general framework for automating ginning process using computer-vision-based approach for online trash identification and removal is presented in this study. It involves trash identification using imaging and consequently trash classification and estimation using soft computing techniques of artificial neural network. A computer programme was developed to automate image capture, analysis and computing processes generating overall statistics of trash content in cotton lint. Measurement of trash features such as area, perimeter, convex perimeter, ferret meandiameter, ferret elongation, elongation, length and compactness yielded higher values in stick trash type as comparedto leaf objects. There was not much difference in breadth and roughness of these trash types. Designed back propagation classifier system correctly distinguished 60% trash types with 80-99% confidence measure (CM), 25% data with CM 40-80%, 10% data with CM 20-40% and 5% data left undefined or wrongly identified with CM less than 10%. Information on trash types present in cotton can be used to appropriately configure cleaning and ginning machineries. Overall benefit is increased bale value and energy savings that add to monetary gain. It also assists in online assigning of classer grade to processed bales

Image processing and geometric parameters extracted from sliced image of porous biomaterial

To perform comprehensive modeling for intraflow field and transport processes in a biomaterial, a detailed probing technique is needed for profiling its interior. In our 2004 advanced Powder Technology paper, 10 commonly adopted techniques were compared for their capability to probe the interior structure of sludge floc. However, morphological information extracted from sliced images depends on how the image was thresholded. As a continuation work of our 2004 Advanced Powder Technology paper, this work surveyed several frequently encountered problems when applying the histogram-based and bolb feature-based methods for the bilevel thresholding of the sliced images of flocs. A combined scheme using Otsu's method to obtain the porosity and the maximum convex perimeter method to probe the shapes and spatial distribution of the pores was discussed. Some geometric parameters were adopted to describe the interior structure of flocs. The probable misuse of the Sierpinski fractal dimension, due to the numerous pores and solid grains being simultaneously removed from floc image when its resolution was subsequently reduced, was highlighted.

Intra-layer flow in fouling layer on membranes

The structure of fouling layer determines the pressure drop across the fouling layer. Three-dimensional distributions of nucleic acids, proteins, α- d-glucopyranose polysaccharides, β- d-glucopyranose polysaccharides and lipids in the biofouling layer that is formed on a mixed cellulose ester membrane were determined using a six-fold staining protocol combined with confocal laser scanning microscopy (CLSM). Based on the three-dimensional volumetric grid model of the fouling layer structure observed from the series of CLSM images, the intra-layer flow field during filtration was simulated using commercial software. The effective permeability of the fouling layer was estimated to be 2.65 × 10 −12 m 2, which determines the upper estimate on the permeability of the fouling layer. The pores were categorized according to their diameters, using the maximum convex perimeter approach, and then the effects of the blocking pores on the permeability of the fouling layer were investigated. Blocking the large pores that accounted for 15% of the porosity reduced the mean permeability by 58%.

Bilevel thresholding of sliced image of sludge floc.

This work examined the feasibility of employing various thresholding algorithms to determining the optimal bilevel thresholding value for estimating the geometric parameters of sludge flocs from the microtome sliced images and from the confocal laser scanning microscope images. Morphological information extracted from images depends on the bilevel thresholding value. According to the evaluation on the luminescence-inverted images and fractal curves (quadric Koch curve and Sierpinski carpet), Otsu's method yields more stable performance than other histogram-based algorithms and is chosen to obtain the porosity. The maximum convex perimeter method, however, can probe the shapes and spatial distribution of the pores among the biomass granules in real sludge flocs. A combined algorithm is recommended for probing the sludge floc structure.

Applications of image analysis in the characterization of Streptomyces olindensis in submerged culture

The morphology of Streptomyces olindensis (producer of retamycin, an antitumor antibiotic) grown in submerged culture was assessed by image analysis. The morphology was differentiated into four classes: pellets, clumps (or entangled filaments), branched and unbranched free filaments. Four morphological parameters were initially considered (area, convex area, perimeter, and convex perimeter) but only two parameters (perimeter and convex perimeter) were chosen to automatically classify the cells into the four morphological classes, using histogram analysis. Each morphological class was evaluated during growth carried out in liquid media in fermenter or shaker. It was found that pellets and clumps dominated in early growth stages in fermenter (due to the inoculum coming from a shaker cultivation) and that during cultivation, the breakage of pellets and clumps caused an increase in the percentage of free filaments. The criteria of morphological classification by image analysis proposed were useful to quantify the percentage of each morphological class during fermentations and may help to establish correlations between antibiotic production and microorganism morphology.