A 74-year-old man with a history of a chondroid lesion of the larynx noted an enlarging neck mass. Axial CT showed a large expansile lesion arising from the left thyroid cartilage. Multiple rings and arcs with relatively intact cortex indicated a chondroid lesion. Irregularity of the anterolateral margin abutted a prominent soft-tissue component. The specimen obtained from fine needle aspiratio...

The purpose of this study is to use the same diagnostic-quality verification and planning CTs to validate planning margin account for residual interfractional variations with image-guided soft tissue alignment of the prostate. For nine pros-tate cancer patients treated with IMRT to 78 Gy in 39 fractions, daily verification CT-on-rails images of the first seven and last seven fractions (n = 126)...

Purpose: We investigated the margin recipes with different alignment techniques in the image-guided intensity-modulated radiotherapy (IMRT) of whole pelvis prostate cancer patients. Materials and Methods: Forty-eight computed tomography (CT) scans of eight prostate cancer patients were investigated. Each patient had an initial planning CT scan and 5 consecutive serial CT scans during the course...

For short-term wind power prediction, a soft margin multiple kernel learning (MKL) method is proposed. In order to improve the predictive effect of MKL for power, slack variable introduced into each base solve objective function. Two kinds methods based on hinge loss function and square can be obtained when functions are selected. The improved demonstrate good robustness avoid disadvantage hard...

This paper investigates the asymptotic behavior of soft-margin and hard-margin support vector machine (SVM) classifiers for simultaneously high-dimensional numerous data (large n large p with n/p→ δ) drawn from a Gaussian mixture distribution. Sharp predictions classification error rate SVM are provided, as well limits such important parameters margin bias. As further outcome, analysis allows i...

the concept of soft sets, introduced by molodtsov [20] is a mathematicaltool for dealing with uncertainties, that is free from the difficultiesthat have troubled the traditional theoretical approaches. in this paper, weapply the notion of the soft sets of molodtsov to the theory of hilbert algebras.the notion of soft hilbert (abysmal and deductive) algebras, soft subalgebras,soft abysms and sof...

When lesions in soft tissue reach the gingival margin, they can produce aesthetic defects during its permanence and after its removal. Periodontal plastic surgery allows the correction of the gingival contour using different techniques. This paper is a case report of a peripheral ossifying fibroma removal in the interproximal area of teeth 21 and 22 in addition to root coverage of the affected ...

Maximal margin classifiers are a core technology in modern machine learning. They have strong theoretical justifications and have shown empirical successes. We provide an alternative justification for maximal margin hyperplane classifiers by relating them to Bayes optimal classifiers that use Parzen windows estimations with Gaussian kernels. For any value of the smoothing parameter (the width o...