Framework design for competitive marketing mechanism in Iraqi social media

Several organizations in Iraq manufacture similar commodities in this aggressive social trading. The objective of these organizations is diffusing information about their commodities publicly for popularity of the commodities in social media. More returns result in popular commodities and vice versa. The development of a framework incorporating two organizations engaging to broaden the information to the large media has been undertaken. The organizations first identified their initial seed points concurrently and then data was scattered as per the Independent Cascade Model (ICM). The major objective of the organizations is the identification of seed points for the diffusion of data to several points in social media. Significant is also how fast data diffusion can be done. Data effect will arise from either none, one or more nodes in a social interconnection. Evaluation is also accomplished on the number of fraction parts in various sections are affected by the different rates of data diffusion. The simulation result for suggested framework presented better outcomes result for random network 1 and random network 2 comparing with regular network. This framework is used a Hotellingframwork of competition.

Particle System-Based Multi-Hierarchy Dynamic Visualization of Ocean Current Data

In three-dimensional (3D) digital Earth environment, there are many problems when using the existing methods to express the ocean current, such as uneven distribution of seed points, density leap in scale change and messy visualization. In this paper, a new dynamic visualization method of multi-hierarchy flow field based on particle system is proposed; Specifically, three typical spherical uniform algorithms are studied and compared, and the streamline becoming denser from the equator to the poles on globe is eliminated by placing seed points using Marsaglia polar method as the most efficient. In addition, a viewport-adaptive adjustment algorithm is proposed, which realizes that the density of particles is always suitable to any viewing distance during continuous zooming. To solve the visual representation deficiency, we design a new dynamic pattern to enhance the expression and perception of current, which makes up for the shortcoming of the arrow glyph and streamline methods. Finally, a prototype of GPU parallel and viewport coherence is achieved, whose feasibility and effectiveness are verified by a series of experiments. The results show that our method can not only represent ocean current data clearly and efficiently, but also has outstanding uniformity and hierarchy effect.

Altered Functional Connectivity of the Nucleus Accumbens Network Between Deficit and Non-deficit Schizophrenia

Deficit schizophrenia (DS), which is marked by stable negative symptoms, is regarded as a homogeneous subgroup of schizophrenia. While DS patients have structurally altered nucleus accumbens (NAcc) compared to non-deficit schizophrenia (NDS) patients and healthy individuals, the investigation of NAcc functional connectivity (FC) with negative symptoms and neurocognition could provide insights into the pathophysiology of schizophrenia. 58 DS, 93 NDS, and 113 healthy controls (HCs) underwent resting-state functional magnetic resonance (rsfMRI). The right and left NAcc were respectively used as seed points to construct the functional NAcc network in whole-brain FC analysis. ANCOVA compared the differences in NAcc network FC and partial correlation analysis explored the relationships between altered FC of NAcc, negative symptoms and neurocognition. Compared to HCs, both DS and NDS patients showed decreased FC between the left NAcc (LNAcc) and bilateral middle cingulate gyrus, and between the right NAcc (RNAcc) and right middle frontal gyrus (RMFG), as well as increased FC between bilateral NAcc and bilateral lingual gyrus. Moreover, the FC between the LNAcc and bilateral calcarine gyrus (CAL) was lower in the DS group compared to NDS patients. Correlation analysis indicated that FC value of LNAcc-CAL was negatively correlated to negative symptoms. Furthermore, aberrant FC values within the NAcc network were correlated with severity of clinical symptoms and neurocognitive impairments in DS and NDS patients. This study demonstrated abnormal patterns of FC in the NAcc network between DS and NDS. The presence of altered LNAcc-CAL FC might be involved in the pathogenesis of negative symptoms in schizophrenia.

Voronoi Entropy vs. Continuous Measure of Symmetry of the Penrose Tiling: Part I. Analysis of the Voronoi Diagrams

A continuous measure of symmetry and the Voronoi entropy of 2D patterns representing Voronoi diagrams emerging from the Penrose tiling were calculated. A given Penrose tiling gives rise to a diversity of the Voronoi diagrams when the centers, vertices, and the centers of the edges of the Penrose rhombs are taken as the seed points (or nuclei). Voronoi diagrams keep the initial symmetry group of the Penrose tiling. We demonstrate that the continuous symmetry measure and the Voronoi entropy of the studied sets of points, generated by the Penrose tiling, do not necessarily correlate. Voronoi diagrams emerging from the centers of the edges of the Penrose rhombs, considered nuclei, deny the hypothesis that the continuous measure of symmetry and the Voronoi entropy are always correlated. The Voronoi entropy of this kind of tiling built of asymmetric convex quadrangles equals zero, whereas the continuous measure of symmetry of this pattern is high. Voronoi diagrams generate new types of Penrose tiling, which are different from the classical Penrose tessellation.

Detection of Sickle Cell Anemia Through Contour Evidence Extraction and Estimation

Diagnosis of sickle cell anemia by manual visual inspection through microscope is time consuming and causes human errors. Observational errors occur mostly due to overlapping of cells in blood smear image. Here, an automatic segmentation approach is introduced which isolates sickle cells from all other cells within a blood sample. The proposed system is an approach to find the elliptically shaped sickle cells through geometric feature extraction and contour based segmentation to isolate sickle cells. This technique is a method of isolating sickle cells from other cells within blood sample using cell morphology. A combined approach of extraction of seed points, contour extraction and estimation of contours is used for separation of sickle cells from red blood cells. The methods used for the extraction of seed points are by Ultimate Erosion for Convex Sets and Fast Radial Symmetry transform. The contour evidence is extracted by associating edges of the cells to the seed points. The overlapping and clustered cells in image are identified using ellipse fitting method for contour estimation. Using the seed points and the contour extraction, the edges of the cells are estimated. The lines joining the shape of cells are drawn through estimation of shape of contour. This eliminates cells other than elliptical shaped cells. The proposed system can successfully isolate sickle cells from healthy blood cells within the blood smear image. This automated system has a better accuracy and faster computation speed compared to the existing methods for the detection of sickle cells. This identification methodology helps the health professionals for faster diagnosis.

Altered Functional Connectivity in the Resting State Neostriatum After Complete Sleep Deprivation: Impairment of Motor Control and Regulatory Network

Sleep loss not only compromises individual physiological functions but also induces a psychocognitive decline and even impairs the motor control and regulatory network. In this study, we analyzed whole-brain functional connectivity changes in the putamen and caudate nucleus as seed points in the neostriatum after 36 h of complete sleep deprivation in 30 healthy adult men by resting state functional magnetic resonance imaging to investigate the physiological mechanisms involved in impaired motor control and regulatory network in individuals in the sleep-deprived state. The functional connectivity between the putamen and the bilateral precentral, postcentral, superior temporal, and middle temporal gyrus, and the left caudate nucleus and the postcentral and inferior temporal gyrus were significantly reduced after 36 h of total sleep deprivation. This may contribute to impaired motor perception, fine motor control, and speech motor control in individuals. It may also provide some evidence for neurophysiological changes in the brain in the sleep-deprived state and shed new light on the study of the neostriatum in the basal ganglia.

Droplets Image Segmentation Method Based on Machine learning and Watershed

Watershed algorithm is used widely in segmentation of droplet overlapped spots on water-sensitive test paper. However, the phenomenon of over-segmentation, however, is often caused by noise and subtle changes of gray levels in images. To further improve segmentation accuracy of watershed algorithm, this paper proposes a cyclic iterative watershed segmentation algorithm. Through statistical analysis and logistic regression, machine learning models were classified to extract overlapping droplets on test papers. Loop iterative processing of seed points segments overlapping droplets with appropriate thresholds. Compared with fixed threshold watershed segmentation, this method has higher precision and efficiency for spray droplet evaluation in pesticide application.

On symmetry breaking of dual polyhedra of non-crystallographic group H 3

The study of the polyhedra described in this paper is relevant to the icosahedral symmetry in the assembly of various spherical molecules, biomolecules and viruses. A symmetry-breaking mechanism is applied to the family of polytopes {\cal V}_{H_{3}}(\lambda) constructed for each type of dominant point λ. Here a polytope {\cal V}_{H_{3}}(\lambda) is considered as a dual of a {\cal D}_{H_{3}}(\lambda) polytope obtained from the action of the Coxeter group H 3 on a single point \lambda\in{\bb R}^{3}. The H 3 symmetry is reduced to the symmetry of its two-dimensional subgroups H 2, A 1 × A 1 and A 2 that are used to examine the geometric structure of {\cal V}_{H_{3}}(\lambda) polytopes. The latter is presented as a stack of parallel circular/polygonal orbits known as the `pancake' structure of a polytope. Inserting more orbits into an orbit decomposition results in the extension of the {\cal V}_{H_{3}}(\lambda) structure into various nanotubes. Moreover, since a {\cal V}_{H_{3}}(\lambda) polytope may contain the orbits obtained by the action of H 3 on the seed points (a, 0, 0), (0, b, 0) and (0, 0, c) within its structure, the stellations of flat-faced {\cal V}_{H_{3}}(\lambda) polytopes are constructed whenever the radii of such orbits are appropriately scaled. Finally, since the fullerene C20 has the dodecahedral structure of {\cal V}_{H_{3}}(a,0,0), the construction of the smallest fullerenes C24, C26, C28, C30 together with the nanotubes C20+6N , C20+10N is presented.

A semi-automatic seed point-based method for separation of individual vertebrae in 3D surface meshes: a proof of principle study

Purpose The purpose of this paper is to present and validate a new semi-automated 3D surface mesh segmentation approach that optimizes the laborious individual human vertebrae separation in the spinal virtual surgical planning workflow and make a direct accuracy and segmentation time comparison with current standard segmentation method. Methods The proposed semi-automatic method uses the 3D bone surface derived from CT image data for seed point-based 3D mesh partitioning. The accuracy of the proposed method was evaluated on a representative patient dataset. In addition, the influence of the number of used seed points was studied. The investigators analyzed whether there was a reduction in segmentation time when compared to manual segmentation. Surface-to-surface accuracy measurements were applied to assess the concordance with the manual segmentation. Results The results demonstrated a statically significant reduction in segmentation time, while maintaining a high accuracy compared to the manual segmentation. A considerably smaller error was found when increasing the number of seed points. Anatomical regions that include articulating areas tend to show the highest errors, while the posterior laminar surface yielded an almost negligible error. Conclusion A novel seed point initiated surface based segmentation method for the laborious individual human vertebrae separation was presented. This proof-of-principle study demonstrated the accuracy of the proposed method on a clinical CT image dataset and its feasibility for spinal virtual surgical planning applications.

Automated Mapping of Transportation Embankments in Fine-Resolution LiDAR DEMs

Fine-resolution LiDAR DEMs can represent surface features such as road and railway embankments with high fidelity. However, transportation embankments are problematic for several environmental modelling applications, and particularly hydrological modelling. Currently, there are no automated techniques for the identification and removal of embankments from LiDAR DEMs. This paper presents a novel algorithm for identifying embankments in LiDAR DEMs. The algorithm utilizes repositioned transportation network cells as seed points in a region-growing operation. The embankment region grows based on derived morphometric parameters, including road surface width, embankment width, embankment height, and absolute slope. The technique was tested on eight LiDAR DEMs representing subsections of four watersheds in southwestern Ontario, Canada, ranging in size from 16 million cells to 134 million cells. The algorithm achieved a recall greater than or equal to 90% for seven of the eight DEMs, while achieving a Pearson’s phi correlation coefficient greater than 80% for five of the eight DEMs. Therefore, the method has moderate to high accuracy for identifying embankments. The processing times associated with applying the technique to the eight study site DEMs ranged from 1.4 s to 20.3 s, which demonstrates the practicality of using the embankment mapping tool in applications with data set sizes commonly encountered in practice.