The recognition and retrieval of identical videos by combing through entire video files requires a great deal of time and memory space. Therefore, most current video-matching methods analyze only a part of each video’s image frame information. All these methods, however, share the critical problem of erroneously categorizing identical videos as different if they have merely been altered in resolution or converted with a different codec. This paper deals instead with an identical-video-retrieval method using the low-peak feature of audio data. The low-peak feature remains relatively stable even with changes in bit-rate or codec. The proposed method showed a search success rate of 93.7% in a video matching experiment. This approach could provide a technique for recognizing identical content on video file share sites.

Single-channel separation (SCS) is a challenging scenario where the objective is to segregate speaker signals from their mixture with high accuracy. In this research a novel framework called subband perceptually weighted transformation (SPWT) is developed to offer a perceptually relevant feature to replace the commonly used magnitude of the short-time Fourier transform (STFT). The main objectives of the proposed SPWT are to lower the spectral distortion (SD) and to improve the ideal separation quality. The performance of the SPWT is compared to those obtained using mixmax and Wiener filter methods. A comprehensive statistical analysis is conducted to compare the SPWT quantization performance as well as the ideal separation quality with other features of log-spectrum and magnitude spectrum. Our evaluations show that the SPWT provides lower SD values and a more compact distribution of SD, leading to more acceptable subjective separation quality as evaluated using the mean opinion score.

In cognitive radio systems, the design of spectrum sensing has to face the challenges of radio sensitivity and wide-band frequency agility. It is difficult for a single cognitive user to achieve timely and accurate wide-band spectrum sensing because of hardware limitations. However, cooperation among cognitive users may provide a way to do so. In this paper, we consider such a cooperative wide-band spectrum sensing problem with each of the cognitive users able to imperfectly sense only a small portion of spectrum at a time. The goal is to maximize the average throughput of the cognitive network, given the primary network’s collision probability thresholds in each spectrum sub-band. The solution answers the essential questions: to what extent should each cognitive user cooperate with others and which part of the spectrum should the user choose to sense? An exhaustive search is used to find the optimal solution and a heuristic cooperative sensing algorithm is proposed to simplify the computational complexity. Inspired by this optimization problem, two practical cooperative sensing strategies are then presented for the centralized and distributed cognitive network respectively. Simulation results are given to demonstrate the promising performance of our proposed algorithm and strategies.

One major goal of mesh parameterization is to minimize the conformal distortion. Measured boundary parameterizations focus on lowering the distortion by setting the boundary free with the help of distance from a center vertex to all the boundary vertices. Hence these parameterizations strongly depend on the determination of the center vertex. In this paper, we introduce two methods to determine the center vertex automatically. Both of them can be used as necessary supplements to the existing measured boundary methods to minimize the common artifacts as a result of the obscure choice of the center vertex. In addition, we propose a simple and fast measured boundary parameterization method based on the Poisson’s equation. Our new approach generates less conformal distortion than the fixed boundary methods. It also generates more regular domain boundaries than other measured boundary methods. Moreover, it offers a good tradeoff between computation costs and conformal distortion compared with the fast and robust angle based flattening (ABF++).

Light emitting diode (LED) indicators used on automobile meters are essential for safe driving and few errors can be tolerated. The current manual inspection approach can achieve only 95% accuracy rate in weeding out errors occurring in the production process. It is imperative to improve the accuracy of the inspection process to better achieve the goal of safe driving. This paper proposes an automatic inspection method for LED indicators for use on automobile meters. Firstly, red-green-blue (RGB) color images of LED indicators are acquired and converted into R, G, and B intensity images. A seeded region growing (SRG) algorithm, which selects seeds automatically based on Otsu’s method, is then used to extract the LED indicator regions. Finally, a region matching process based on the seed and three area parameters of each region is applied to inspect the LED indicators one by one to locate any errors. Experiments on standard automobile meters showed that the inspection accuracy rate of this method was up to 99.52% and the inspection speed was faster compared with the manual method. Thus, the new method shows good prospects for practical application.

As e-commerce applications and the underlying public key infrastructure have become more popular over time, many digital mechanisms emulating traditional business activities have been developed and deployed. To build a full-fledged secure digital world, secure implementations of more commercial activity primitives are required. In this paper, we present a secure proxy signature scheme and its threshold version based on the homomorphic Paillier cryptosystem, which can be used in many e-commerce applications such as e-voting, e-bidding/auction, and privacy-preserving data mining. These two schemes are existentially unforgeable against chosen-message attacks and chosen-warrant attacks in the random oracle model. Although it is based on factoring, the threshold Paillier proxy scheme operates without requiring any trusted dealer or combiner. Thus, these two schemes are practical for integration in modularized secure multi-party protocols.

In this paper, we determine the delay-dependent conditions of global asymptotic stability for a class of multi-dimensional nonlinear time-delay systems with application to computer communication networks. A nonlinear delayed model is considered for a rate-based congestion control system of a heterogeneous network with arbitrary topology and time-varying delays. We propose a Lyapunov-based method to obtain a sufficient condition under which global asymptotic stability of the equilibrium is guaranteed. The main contribution of the paper lies in considering time variations of delays in a heterogeneous network which may be applicable in actual networks. Moreover, we obtain conditions for Internet-style networks with multi-source multi-link topology. We first prove the stability for a class of nonlinear time-delay systems. Then, we apply the results to a Kelly’s rate-based approximation of the congestion control system.