Advanced Materials Research Vols. 255-260

Abstract: In order to generate complex chaotic attractors, a six-dimensional chaotic system is designed, which contains six parameters and each equation contains a nonlinear product term. When its parameters satisfy certain conditions, the system is chaotic. By Matlab numerical simulation, chaotic attractor and relevant Lyapunov exponents spectrum can be obtained, which validates that the system is chaotic. And, time domain waveform and power spectrum are shown. Finally, the implementation circuit of this system is designed, and circuit simulation can be done by using Multisim. Circuit simulation result is identical to system simulation completely. The circuit has a practical significance in secrecy communication and correlative fields.

Abstract: In this research, a force-sensing keypad was constructed by adding the pressure sensors with the individual keys on the standard keypad. The sensors permit the dynamic measurement of applied force and key-press timings. It can provide an advantage of more detailed information about key-press force. Details of the experimental setup used are given, and the results from initial tests are reported. The results shows the force-space-time method for user identification based on force-sensing keypad is valid.

Abstract: Traditional relevance feedback technique could help improve retrieval performance. It usually utilize the most frequent terms in the relevant documents to enrich the user’s initial query. We re-examine this method and find that many expansion terms identified in traditional approaches are indeed unrelated to the query and harmful to the retrieval. This paper introduces a Support Vector Machines Based method to improve the retrieval results. Firstly, the classifier is trained on the feedback documents. Then, we can utilize this classifier to classify the rest of the documents and move relevant documents to the front of irrelevant documents. This new approach avoids modifying the initial query, so it’s a new direction for the relevance feedback techniques. Our Experiments on TREC dataset demonstrate that retrieval effectiveness can be improved more than 24.37% when our proposed approach is used.

Abstract: Preprocessing model counting instances can reduce their size considerably and decrease the solving time. In this paper we present a preprocessing algorithm Preprocess, which combines many advanced techniques, such as the unit propagation, and the hyper-binary resolution. In particular, it also combines (1) clause elimination by subsumption, and (2) variable elimination by equivalence reasoning. It has proved that these excellent technologies not only reduce the size of the model counting formulae, but also improve the ability of the model counters to solve model counting problems.

Abstract: This paper proposes an adaptive Canny operator edge detection algorithm. The proposed method can automatically set the threshold value according to the different image gray-scale gradient histogram adaptively and improve the performance in the detail edge detection and good localization. Experiments show that this method produces better edge detection results performance than the Otsu method. Besides our method, Roberts operator, Prewitt operator, Sobel operator, Log operator and Canny operator based on Otsu algorithm are also tested for comparisons.

Abstract: With the fast developing portable digital audio player, the copyright protection of music faces a severe challenge. Audio watermarking is an efficient approach to solve this problem. In order to improve the performance of real-time processing, a new real-time audio watermarking based on fast MCLT is presented. Algorithms, which use of quantitative method, can be realized watermark blind detection. The experiment results show that the algorithm, which is utilized in the copyright protection, meet the timely processing requirements. Embedded of watermark audio have obviously robustness and transparency compared to the traditional methods. Furthermore, it can against MP3 compression attacks efficiently.

Abstract: Fingerprint enhancement is an essential preprocessing step and it is crucial for the efficiency of fingerprint recognition algorithm. We present an enhancement algorithm based on fast discrete curvelet transform (FDCT). First, implement positive transform on input image, namely decompose the image into coarse scales and fine scales coefficients. Then make use of a directional filter and a soft threshold function to enhance image and reduce noise respectively. Finally, implement inverse transform, and reconstruct the enhanced image. Experiments are carried out on FVC2004 databases. For bad quality fingerprints, the results indicate that the proposed algorithm has better enhancement and de-noising effect than traditional methods, and need less time.

Abstract: Commonly, an upstream member in a supply chain provides productions or resources for many downstream members. When the sum of retailers order quantities is beyond suppliers' inventories, suppliers might apply order allocation mechanism to solve the difficulty. The allocation mechanism is not considered in most of previous studies on the bullwhip effect. This paper develops the supply chain simulation software based browser/server technology, which can build tree-shape supply chain structure considering allocation mechanism. Two experiments are designed and implemented in order to isolate the effect of different order allocation mechanisms on bullwhip effect. The studies show that BWV differs from allocation mechanisms. For three types of supply chain members, the change tendencies of BWV with two allocation mechanism are similar. The paper also demonstrates that distributors have effect more obviously on bullwhip effect than other two roles with different allocation mechanism.

Abstract: This paper introduces an image retrieval model based on dimensionality reduction. The proposed model is divided into two main techniques, the first one is concerned with the feature extraction from image database, and the second one is performing a dimensionality reduction. In the first technique, the color histogram and Color Texture Moment are used to extract the color and texture features, respectively. In the second technique, Local Fisher Discriminant Analysis (LFDA) which is a supervised linear dimensionality reduction algorithm is used to performing dimensionality. LFDA combines the ideas of Fisher Discriminant Analysis (FDA) and Locality Preserving Projection (LPP). LFDA can preserve both manifold of data and discriminant information. Experiments demonstrate that the proposed image retrieval scheme based on dimensionality reduction can achieve satisfactory results.

Abstract: In Cognitive Wireless Sensor Network (C-WSN), spectrum utilization and energy-efficiency are both significant items for the whole network. Interference between Primary User (PU) sensor and Secondary User (SU) sensor should be eliminated in order to realize spectrum sharing. In this paper, mathematical model of multi-carrier power allocation in cognitive OFDM is constructed. Multi-carrier power allocation based on rate adaptive criterion is proposed under the constraints of SUs’ power control. An efficient subcarrier power allocation algorithm based on adaptive water-filling is proposed. The improved algorithm could directly determine the sub-carriers that do not require additional power injection by rough estimation of water levels. Computational complexity of proposed algorithm could reduce rapidly. Meanwhile, theoretical derivation and numerical results both indicate that, with the proposed power allocation algorithm, SU’s spectral efficiency is superior to other traditional water-filling schemes, and the algorithm also has some adaptive features for practical implementation in C-WSN.