A principal problem of any internet user is the increasing number of spam, which became a great problem today. Therefore, spam filtering has become a research fo-cus that attracts the attention of several security researchers and practitioners. Spam filtering can be viewed as a two-class classification problem. To this end, this paper proposes a spam filtering approach based on Possibilistic c-Means (PCM) algorithm and weighted distance coined as (WFCM) that can efficiently distinguish between spam and legitimate email messages. The objective of the formulated fuzzy problem is to construct two fuzzy clusters: spam and email clusters. The weight assignment is set by information gain algorithm. Experimental results on spam based benchmark dataset reveal that proper setting of feature-weight can improve the performance of the proposed spam filtering approach. Furthermore, the proposed spam filtering ap-proach performance is better than PCM and Naïve Bayes filtering technique.
Background Bilateral cleft lip deformity is much more difficult to correct than unilateral cleft lip deformity. The complexity of the deformity and the sensitive relationships between the arrangement of the muscles and the characteristics of the external lip necessitate a comprehensive preoperative plan for management. The purpose of this study was to evaluate the repair of bilateral cleft lip using the Byrd modification of the traditional Millard and Manchester methods. A key component of this repair technique is focused on reconstruction of the central tubercle.
Methods Fourteen patients with mean age of 5.7 months presented with bilateral cleft lip deformity and were operated on using a mod
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Civil environment in nursing education enhances achieving learning outcomes. Addressing incivility can be crucial to improve academic achievements. The purpose of this study was examining the psychometric properties of the Arabic version of the Incivility in Nursing Education-Revised scale regarding nursing faculty.
This cross-sectional study conducted in five Arab countries using a convenience sampling st
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Researchers have identified and defined β- approach normed space if some conditions are satisfied. In this work, we show that every approach normed space is a normed space.However, the converse is not necessarily true by giving an example. In addition, we define β – normed Banach space, and some examples are given. We also solve some problems. We discuss a finite β-dimensional app-normed space is β-complete and consequent Banach app- space. We explain that every approach normed space is a metric space, but the converse is not true by giving an example. We define β-complete and give some examples and propositions. If we have two normed vector spaces, then we get two properties that are equivalent. We also explain that
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The aim of this paper is to prove a theorem on the Riesz means of expansions with respect to Riesz bases, which extends the previous results of [1] and [2] on the Schrödinger operator and the ordinary differential operator of 4-th order to the operator of order 2m by using the eigen functions of the ordinary differential operator. Some Symbols that used in the paper: the uniform norm. <,> the inner product in L2. G the set of all boundary elements of G. ˆ u the dual function of u.
The aim of this paper is prove a theorem on the Riesz mean of expansions with respect to Riesz bases, which extends the previous results of Loi and Tahir on the Schrodinger operator to the operator of 4-th order.
In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between every
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In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between ev
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In this paper an improved weighted 0-1 knapsack method (WKM) is proposed to optimize the resource allocation process when the sum of items' weight exceeds the knapsack total capacity .The improved method depends on a modified weight for each item to ensure the allocation of the required resources for all the involved items. The results of the improved WKM are compared to the traditional 0-1 Knapsack Problem (KP). The proposed method dominates on the other one in term of the total optimal solution value of the knapsack .
The main work of this paper is devoted to a new technique of constructing approximated solutions for linear delay differential equations using the basis functions power series functions with the aid of Weighted residual methods (collocations method, Galerkin’s method and least square method).
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