Abstract. Support Vector Machines (SVMs) are a popular data classification method with many diverse applications. The SVMs performance depends on choice a suitable kernel function for a given problem. Using an appropriate kernel; the data are transform into a space with higher dimension in which they are separable by an hyperplane. A major challenges of SVMs are how to select an appropriate kernel and how to find near optimal values of its parameters. Usually a single kernel is used by most studies, but the real world applications may required a combination of multiple kernels. In this paper, a new method called, weighted powered kernels for data classification is proposed. The proposed method combined three kernels to produce a new combined kernel (WPK). The method used Scatter Search approach to find near optimal values of weights, alphas and kernels parameters which associated with each kernel. To evaluate the performance of the proposed method, 11 benchmark are used. Experiments and comparisons prove that the method given acceptable outcomes and has a competitive performance relative to a single kernel and some other published methods

Abstract.In this paper, a new classification approach combining support vector machine with scatter search approach for hepatitis disease diagnosis is presented, called 3SVM. The scatter search approach is used to find near optimal values of SVM parameters and its kernel parameters. The hepatitis dataset is obtained from UCI. Experimental results and comparisons prove that the 3SVM gives better outcomes and has a competitive performance relative to other published methods found in literature, where the average accuracy rate obtained is 98.75%.

Abstract.In this paper, a new classification approach combining support vector machine with scatter search approach for hepatitis disease diagnosis is presented, called 3SVM. The scatter search approach is used to find near optimal values of SVM parameters and its kernel parameters. The hepatitis dataset is obtained from UCI. Experimental results and comparisons prove that the 3SVM gives better outcomes and has a competitive performance relative to other published methods found in literature, where the average accuracy rate obtained is 98.75%.

Abstract.In this paper, a new classification approach combining support vector machine with scatter search approach for hepatitis disease diagnosis is presented, called 3SVM. The scatter search approach is used to find near optimal values of SVM parameters and its kernel parameters. The hepatitis dataset is obtained from UCI. Experimental results and comparisons prove that the 3SVM gives better outcomes and has a competitive performance relative to other published methods found in literature, where the average accuracy rate obtained is 98.75%.

Abstract. The one dimensional (1D) barcode was developed as a package label that could be swiftly and accurately read by a laser scanner. It has become ubiquitous, with symbologies such as UPC used to label approximately 99% of all packaged goods in the US [1]. The two-dimensional (2D) barcode has improved the information encoded capacity, and it also has enriched the applications of barcode technique. Recently, there are researches dealing with watermark technique on barcode to prevent it from counterfeited or prepensely tampered. The existent methods still have to limit the size of embedded watermark in a relatively small portion. Furthermore, it also needs to utilize original watermark or other auxiliary verification mechanism to achieve the barcode verification. In this paper, we propose a novel watermarking barcode reading enhancement method. The proposed method can fight most of reading challenges of watermarking barcode. Experiments with challenging barcode images show substantial improvement over other state-of-the-art algorithms.

Abstract. The one dimensional (1D) barcode was developed as a package label that could be swiftly and accurately read by a laser scanner. It has become ubiquitous, with symbologies such as UPC used to label approximately 99% of all packaged goods in the US [1]. The two-dimensional (2D) barcode has improved the information encoded capacity, and it also has enriched the applications of barcode technique. Recently, there are researches dealing with watermark technique on barcode to prevent it from counterfeited or prepensely tampered. The existent methods still have to limit the size of embedded watermark in a relatively small portion. Furthermore, it also needs to utilize original watermark or other auxiliary verification mechanism to achieve the barcode verification. In this paper, we propose a novel watermarking barcode reading enhancement method. The proposed method can fight most of reading challenges of watermarking barcode. Experiments with challenging barcode images show substantial improvement over other state-of-the-art algorithms.

Abstract. The one dimensional (1D) barcode was developed as a package label that could be swiftly and accurately read by a laser scanner. It has become ubiquitous, with symbologies such as UPC used to label approximately 99% of all packaged goods in the US [1]. The two-dimensional (2D) barcode has improved the information encoded capacity, and it also has enriched the applications of barcode technique. Recently, there are researches dealing with watermark technique on barcode to prevent it from counterfeited or prepensely tampered. The existent methods still have to limit the size of embedded watermark in a relatively small portion. Furthermore, it also needs to utilize original watermark or other auxiliary verification mechanism to achieve the barcode verification. In this paper, we propose a novel watermarking barcode reading enhancement method. The proposed method can fight most of reading challenges of watermarking barcode. Experiments with challenging barcode images show substantial improvement over other state-of-the-art algorithms.

Abstract. Video Frame quality and statistical undetectability are two key issues related to steganography techniques. In this paper, we propose a novel flash video file (.flv file extension) information-embedding scheme in which the embedded information is reconstructed without knowing the original host flash video file. The proposed method presents high rate of information embedding and is robust to lossless and lossy compression. The characteristic of the proposed scheme is to use a weak point in the header information of flash video file to assist compression process. Experimental results have indicated that the method is robust against lossless and lossy compression.

Abstract. Video Frame quality and statistical undetectability are two key issues related to steganography techniques. In this paper, we propose a novel flash video file (.flv file extension) information-embedding scheme in which the embedded information is reconstructed without knowing the original host flash video file. The proposed method presents high rate of information embedding and is robust to lossless and lossy compression. The characteristic of the proposed scheme is to use a weak point in the header information of flash video file to assist compression process. Experimental results have indicated that the method is robust against lossless and lossy compression.

Abstract. Video Frame quality and statistical undetectability are two key issues related to steganography techniques. In this paper, we propose a novel flash video file (.flv file extension) information-embedding scheme in which the embedded information is reconstructed without knowing the original host flash video file. The proposed method presents high rate of information embedding and is robust to lossless and lossy compression. The characteristic of the proposed scheme is to use a weak point in the header information of flash video file to assist compression process. Experimental results have indicated that the method is robust against lossless and lossy compression.