This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that

spider veins are clusters of Ectatic venules & are common finding on the lower limbs generally believed to be caused by multiple factors, including genetic predisposition, hormonal factors, gravity, occupation, pregnancy, becoming increasingly apparent with age, and trauma. Therapeutic options include sclerotherapy, surgical procedures, and treatment with different laser systems.

 Objectives: The purpose of the study was to evaluate the efficacy and safety of long pulsed (Nd:YAG) laser emitting at 1064nm in the treatment of spider veins.

Patients, Materials and Methods: This prospective study was done in the laser medicine research clinics of the Institute of las

The study aims to identify the level of cognitive beliefs, as well as to identify the level of self-organized learning strategies among intermediate school students. The study also aims to identify the differences in the level of self-organized learning strategies among intermediate school students in term of gender, branch (scientific, literary). In order to achieve the research objectives, the researcher designed a scale to measure the cognitive beliefs. As for the scale of self-organized learning strategies, the researcher adopted a scale of (Pintrich et al. 1991), which was translated by (Izzat Abdelhamid, 1999) , For self-organized learning strategies, the sample consisted of (400) students from the research population, whic

An efficient modification and a novel technique combining the homotopy concept with  Adomian decomposition method (ADM) to obtain an accurate analytical solution for Riccati matrix delay differential equation (RMDDE) is introduced  in this paper  . Both methods are very efficient and effective. The whole integral part of ADM is used instead of the integral part of homotopy technique. The major feature in current technique gives us a large convergence region of iterative approximate solutions .The results acquired by this technique give better approximations for a larger region as well as previously. Finally, the results conducted via suggesting an efficient and easy technique, and may be addressed to other non-linear problems.

Smart thinking requires a continuous flexible systeroatic  teaching in order that the lecturer can reach at easily, The Successful individuals in smart thin king are the most knowledgably with  it, where the cognitive (intuitive- systematic) style has common bases with another cognitive styles in many traits, and these two concepts are the core of theorization of the rost important cognitive styles. The present study aims to measure the Smart thinking among university lecturers according to sex variable and recognize the statistically differences significance in the level of cognitive (intuitive- systematic) style among the university lecturers according to sex variable and recognize the correlation between smart thinki

            The development of a new, cheap, efficient, and ecofriendly adsorbents has become an important demand for the treatment of waste water, so nano silica is considered a good choice. A sample of nanosilica (NS) was prepared from sodium silicate as precursor and the nonionic surfactant Tween 20 as a template. The prepared sample was characterized using various characterization techniques such as FT-IR, AFM, SEM and EDX analysis. The spectrum of FTIR confirms the presence of silica in the sample, while SEM analysis of sample shows nanostructures with pore ranging (2-100nm).The adsorptive properties of this sample were studied by removing Congo red dye (CR) from aqueous solution. Batch experimental methods were carried o

Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff

Due to the vast using of digital images and the fast evolution in computer science and especially the using of images in the social network.This lead to focus on securing these images and protect it against attackers, many techniques are proposed to achieve this goal. In this paper we proposed a new chaotic method to enhance AES (Advanced Encryption Standards) by eliminating Mix-Columns transformation to reduce time consuming and using palmprint biometric and Lorenz chaotic system to enhance authentication and security of the image, by using chaotic system that adds more sensitivity to the encryption system and authentication for the system.

Medical image segmentation is one of the most actively studied fields in the past few decades, as the development of modern imaging modalities such as magnetic resonance imaging (MRI) and computed tomography (CT), physicians and technicians nowadays have to process the increasing number and size of medical images. Therefore, efficient and accurate computational segmentation algorithms become necessary to extract the desired information from these large data sets. Moreover, sophisticated segmentation algorithms can help the physicians delineate better the anatomical structures presented in the input images, enhance the accuracy of medical diagnosis and facilitate the best treatment planning. Many of the proposed algorithms could perform w