Abstract Digital Watermarking (DWM) is a recent technology used to strengthen the security of many applications in different fields. It is a signal which is permanently visible or invisible embedded into digital data called digital cover medium. Content security is one of the fields that are tightly related to digital watermarking. It is usually relevant to the ability of detecting changes... Digital Watermarking (DWM) is a recent technology used to strengthen the security of many applications in different fields. It is a signal which is permanently visible or invisible embedded into digital data called digital cover medium. Content security is one of the fields that are tightly related to digital watermarking. It is usually relevant to the ability of detecting changes in multimedia content, especially in images. However, it remains to examine how applications allow different kinds of users to authenticate e-content and conform its originality, and where the conflicts might be found between the application features and the content authentication. This paper aims to introduce an analytical review for digital watermarking used for authentication in different domains covering state-of-the-art concepts, applications, classifications, and design issues. In this paper, we introduce a new classification for digital watermarking techniques and extract the most important design issues of these techniques depending on our reading in a wide range of digital watermarking literatures. Our new classification for digital watermarking techniques can be considered a contribution of this paper. A recent domain utilizes this technique is eLearning system which is a recent tool that produces a new era of education. It allows student/ teacher to learn/teach anywhere at any time. One of the important issues in eLearning environment is content security. The capability to detect changes in eLearning contents has become crucial for many applications in online environment. Thus, we finally present a case study of using digital watermarking techniques for content authentication in eLearning environment taking into account the aspects of our new classification and the design issues extracted for digital watermarking techniques. Read More Read Less

Abstract Protein folding prediction is a fundamental problem in biology. The spatial structure (Conformation) of the protein is the manipulation key of its biochemical and cellular functions. The protein tends to fold on itself. However, a protein cannot fold in any way: it must reach a lowest level of energy. Determining the conformation of the protein in this state of lowest... Protein folding prediction is a fundamental problem in biology. The spatial structure (Conformation) of the protein is the manipulation key of its biochemical and cellular functions. The protein tends to fold on itself. However, a protein cannot fold in any way: it must reach a lowest level of energy. Determining the conformation of the protein in this state of lowest energy is known as the protein folding problem. This can be modeled as an optimization problem. Even under the simplified models, the problem is NP-complete [1] [2] [3]. Thus, there is no polynomial time algorithm to resolve this problem. In this paper, a biologically inspired algorithm for protein spatial structure prediction is proposed; it uses the honey-bee colony reproduction processes. Read More Read Less

Abstract In this paper, a fast and efficient gender classification system based on facial features is proposed to classify the gender. Facial feature extraction is one of the most important and attempted problems in computer vision. It is a necessary step in face recognition, facial image compression. There are many methods have been proposed in the literature for the facial features... In this paper, a fast and efficient gender classification system based on facial features is proposed to classify the gender. Facial feature extraction is one of the most important and attempted problems in computer vision. It is a necessary step in face recognition, facial image compression. There are many methods have been proposed in the literature for the facial features and gender classification. However, all of them have still disadvantage such as not complete reflection about face structure, face texture. This technique applies to both face alignment and recognition and significantly improves three aspects. First, we introduce shape description for face model. Second, the feature extraction phase, two geometric features are evaluated as the ratios of the distances between eyes, noses, and mouths. Finally, we classified the gender based on the association of two methods: geometric feature based method and Independent Component Analysis (PCA) method for improving the efficiency of facial feature extraction stage. The algorithm has also been tested in practice with a webcam, giving (near) real-time performance and good extraction results Read More Read Less