44484805
Parallel Ant Colony Systems
In this paper a Parallel Ant Colony System (PACS) is developed. Three communication methods for updating the pheromone level between groups in PACS are proposed and work on the traveling salesman problem using our system is presented. Experimental results based on three well-known traveling salesman data sets demonstrate the proposed PACS is superior to the existing Ant Colony System (ACS) and Ant System (AS) with similar or better running times.
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.
38537152
A Digital Image Watermarking Method Based on Labeled Bisecting 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.
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.
6653256
Domain-constrained semi-supervised mining of tracking models in sensor networks
Accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. Specifically, the localization problem is to determine the location of a client device accurately given the radio signal strength values received at the client device from multiple beacon sensors or access points. Conventional data mining and machine learning methods can be applied to solve this problem. However, all of them require large amounts of labeled training data, which can be quite expensive. In this paper, we propose a probabilistic semi supervised learning approach to reduce the calibration effort and increase the tracking accuracy. Our method is based on semi-supervised conditional random fields which can enhance the learned model from a small set of training data with abundant unlabeled data effectively. To make our method more efficient, we exploit a Generalized EM algorithm coupled with domain constraints. We validate our method through extensive experiments in a real sensor network using Crossbow MICA2 sensors. The results demonstrate the advantages of methods compared to other state-of-the-art object-tracking algorithms.
206616426
VideoCube: A Novel Tool for Video Mining and Classification
We propose a new tool to classify a video clip into one of n given classes (e.g., "news", "commercials", etc). The first novelty of our approach is a method to automatically derive a "vocabulary" from each class of video clips, using the powerful method of "Independent Component Analysis" (ICA). Second, the method is unified in that it works with both video and audio information, and gives vocabulary describing not only the still images, but also motion and the audio part. Further-more, this vocabulary is natural in that it is closely related to human perceptual processing. More specifically, every class of video clips gives a list of "basis functions", which can compress its members very well. Once we represent video clips in "vocabularies", we can do classification and pattern discovery. For the classification of a video clip, we propose using compression: we test which of the "vocabularies" can compress the video clip best, and we assign it to the corresponding class.For data mining, we inspect the basis functions of each video genre class and identify genre characteristics such as fast motions/transitions, more harmonic audio, etc. In experiments on real data of 62 news and 43 commercial clips, our method achieved overall accuracy of ? 81%.
911431
Isometric-path numbers of block graphs
An isometric path between two vertices in a graph G is a shortest path joining them. The isometric-path number of G, denoted by ip(G), is the minimum number of isometric paths required to cover all vertices of G. In this paper, we determine exact values of isometric-path numbers of block graphs. We also give a linear-time algorithm for finding the corresponding paths.
6313972
Analysis and evaluation of expiration-based hierarchical caching systems
This paper investigates some fundamental properties and performance issues of the expiration-based caching systems. We focus on the hierarchical caching systems based on the time-to-live (TTL) expiration mechanism, and present a basic model for such systems. By analyzing the intrinsic timing behavior in this model, we derive some important performance metrics from the perspectives of caching systems and end users, respectively. We use network simulation results to further substantiate the efficacy of our analysis. Our results show some basic properties and trade-offs for a hierarchical caching system based on the weak consistency mechanism.
1155416
Co-Localization from Labeled and Unlabeled Data Using Graph Laplacian
This paper addresses the problem of recovering the locations of both mobile devices and access points from radio signals, a problem which we call colocalization, by exploiting both labeled and unlabeled data from mobile devices and access points. We first propose a solution using Latent Semantic Indexing to construct the relative locations of the mobile devices and access points when their absolute locations are unknown. We then propose a semi-supervised learning algorithm based on manifold to obtain the absolute locations of the devices. Both solutions are finally combined together in terms of graph Laplacian. Extensive experiments are conducted in wireless local-area networks, wireless sensor networks and radio frequency identification networks. The experimental results showthat we can achieve high accuracy with much less calibration effort as compared to several previous systems.