42459861
Vq-Based Gray Watermark Embedding Scheme With Genetic Index Assignment
A digital watermarking scheme based on vector quantisation (VQ) for gray watermark is proposed. It begins with the procedure of encoding the gray watermark, and embeds the encoded indices into the cover image in VQ domain then. To improve the performance of the watermarking scheme, a genetic index assignment (GIA) procedure, which modifies the signal of the watermark to suit the signal of the cover image, is proposed. The proposed gray watermark embedding scheme is easy to implement, requires no original cover image to be presented during extraction, expands the size of the used watermark, and provides better watermarked results. Experimental results will show the novelty and effectiveness of it.
38537152
A Digital Image Watermarking Method Based on Labeled Bisecting Clustering Algorithm
172381
Robust VQ-based digital watermarking for memoryless binary symmetric channel
Vector quantization (VQ) has been distinguished for its high compression rate in lossy data compression applications. And VQ-based watermarking plays a newly developed branch in digital watermarking research fields. In this paper, we propose optimized schemes for VQ-based image watermarking. We overcome the VQ index assignment problem with genetic algorithm, which is suitable for transmitting the watermarked image over noisy channels. We obtain better robustness of the watermarking algorithm against the effects caused by channel noise in our simulations after inspecting the results from several test images. In addition, to compare with existing schemes in literature, the watermarked image quality in our scheme has approximately the same quality, with better performance in robustness, to the schemes proposed by other researchers. This also proves the effectiveness of our proposed schemes in VQ-based image watermarking for copyright protection.
19822286
A Multi-user Based Watermarking System with Two-Security-Level Keys
This paper presents a new watermarking scheme to reduce the detection error probability through removal of local mean values of an original signal. It will be analytically proven that the removal process plays role in reducing the interference between an original signal and a watermark to be embedded. This is simply based on the orthogonality of the DC signal and the AC signal. As a result, the process improves the ability of the right detection. The proposed method is analytically and empirically evaluated with no attack as well as JPEG compression attacks.
45038628
Fast clustering algorithms for vector quantization
Abstract Some fast clustering algorithms for vector quantization (VQ) based on the LBG recursive algorithm are presented and compared. Experimental results in comparison to the conventional vector-quantization (VQ) clustering algorithm with speech data demonstrate that the best approach will save more than 99% in the number of multiplications, as well as considerable saving in the number of additions. The increase in the number of comparisons is moderate. An improve absolute error inequality (AEI) criterion for Euclidean distortion measure is also proposed and utilized in the VQ clustering algorithm.
13091217
A Parallel Particle Swarm Optimization Algorithm with Communication Strategies
Particle swarm optimization (PSO) is an alternative population-based evolutionary computation technique. It has been shown to be capable of optimizing hard mathematical problems in continuous or binary space. We present here a parallel version of the particle swarm optimization (PPSO) algorithm together with three communication strategies which can be used according to the independence of the data. The first strategy is designed for solution parameters that are independent or are only loosely correlated, such as the Rosenbrock and Rastrigrin functions. The second communication strategy can be applied to parameters that are more strongly correlated such as the Griewank function. In cases where the properties of the parameters are unknown, a third hybrid communication strategy can be used. Experimental results demonstrate the usefulness of the proposed PPSO algorithm.
40563613
Mixed binary integer programming formulations for the reentrant job shop scheduling problem
This paper describes the development of mixed binary integer programming (BIP) formulations for the reentrant job shop scheduling problem. Based on an earlier classical job shop model developed by Manne and improved by Liao and You, this paper presents two extended BIP optimization formulations for the problem under consideration. In order to improve the solution speed of the BIP formulations, two layer division procedures are developed and incorporated in the corresponding models. Results of computational experiments, in which an average performance of these formulations is investigated, are also reported.
18411364
Uncertainty and RuleML Rulebases: A Preliminary Report
Uncertainty, like imprecision and vagueness, has gained considerable attention the last decade. To this extend we present a preliminary report on extending the Rule Markup Language (RuleML) with fuzzy set theory, in order to be able to represent and handle vague knowledge. We also provide semantics for the case of fuzzy FOL RuleML.
768133
Performance analysis of TCP-friendly AIMD algorithms for multimedia applications
In this paper, the performance of TCP-friendly generic AIMD (Additive Increase and Multiplicative Decrease) algorithms for Web-based playback and multirate multimedia applications is investigated. The necessary and sufficient TCP-friendly condition is derived, and the effectiveness and responsiveness of AIMD are studied. Due to practical implications, a Dynamic TCP-friendly AIMD (DTAIMD) algorithm is proposed. Extensive simulation results are given to verify the derived necessary and sufficient condition, and to demonstrate the performance of the proposed DTAIMD algorithm.
42756636
Requirements for a Semantic Web Rule Language
The need for integrating rules within the Semantic Web framework was clear since the early developments. However, up to the last few years, the research community focused its efforts on the design of the so called Ontology Layer. Nowadays, this layer is fairly mature in the form of Description Logics based languages [1, 6] such as the OWL Web Ontology Language [2], which is now a W3C recommendation. In this paper, we argue for three characteristics that a Semantic Web rule langauge should have.
16470845
Dynamic server selection using fuzzy inference in content distribution networks
To accommodate the exponential growth of Web traffic, Content Distribution Networks (CDN) have been designed and deployed to distribute content to different cache servers, and to transparently and dynamically redirect user requests to the cache servers according to the latest network and server status. Server selection therefore is vital and crucial to both the functionality and performance of any CDN systems. An appropriate server should be selected by taking estimated user location, measured round-trip time, and advertised server load into account. However, it is unlikely to obtain accurate and timely inputs of these parameters in practice, so that the effectiveness and efficiency of CDN cannot be fully achieved by traditional means. In this paper, a novel CDN server selection scheme using fuzzy inference is proposed. The scheme selects appropriate servers based on partial round-trip time measurements and historical server load information, and it can be implemented generically wherever the decision is made. It is shown that the fuzzy inference-based scheme is inherently capable of handling multiple decision inputs efficiently, tolerable to measurement noise and errors, and able to deal with network dynamics. Simulation results demonstrate that, compared with other server selection schemes, the proposed scheme can achieve higher resource utilization, provide better user-perceived Quality of Service (QoS), and efficiently deal with network dynamics.