查看更多>>摘要：There are generally zero drift, sensitivity drift and nonlinear error in silicon piezoresistive pressure sensors due to the inherent characteristics of semiconduc-tor materials. It is necessary to compensate and correct the errors produced so as to meet the requirements of measurement accuracy. In order to further improve the compensation precision, based on the research of various basic software compensation methods, a surface fitting compensation algorithm based on least square method is designed, and the software is implemented on the Visual Basic platform. The experimental results show that the zero drift, sensitivity drift and nonlinear error is effectively eliminated, and the output precision of the sensor is greatly improved.
查看更多>>摘要：How to classify incredible messages has attracted great attention from academic and industry nowadays. The recent work mainly focuses on one type of incredible messages (a.k.a rumors or fake news) and achieves some success to detect them. The existing problem is that incredible messages have different types on social media, and rumors or fake news cannot represent all incredible messages. Based on this, in the paper, we divide messages on social media into five types based on three dimensions of information evaluation metrics. And a novel method is proposed based on deep learning for classifying the five types of incredible messages on social media. More specifically, we use attention mechanism to obtain deep text semantic features and strengthen emotional semantics features, meanwhile, construct universal meta-data as auxiliary features, concatenating them for incredible messages classification. A series of experiments on two representative real-world datasets demonstrate that the proposed method outperforms the state-of-the-art methods.
查看更多>>摘要：The development of algorithms to solve Many-objective optimization problems (MaOPs) has attracted significant research interest in recent years. Solving various types of Pareto front (PF) is a daunting challenge for evolutionary algorithm. A Research mode based evolutionary algorithm (RMEA) is proposed for many-objective optimization. The archive in the RMEA is used to store non-dominated solutions that can reflect the shape of the PF to guide the reference vector adaptation. Information concerning the population is collected, once the number of non-dominated solutions reaches its limit after many generations without exceeding a given thresh-old, RMEA introduces a research mode that generates more reference vectors to search through the solutions. The proposed algorithm showed competitive performance with four state-of-the-art evolutionary algorithms in a large number of experiments.
查看更多>>摘要：Characteristics of long-running applica-tions in cloud and big data environment are various and significantly influence the performance of cache systems. The gap between existing cache systems and the increasing performance requirements motivates us to propose the Application-oriented cache allocation and prefetching method (ACAP) to improve data access performance. An application-oriented cache allocation approach is designed based on hit count growth rates for a higher overall hit rate. Two application-oriented sequential prefetching approaches are proposed to improve the hit rate and prefetching accuracy by learning average read sizes of long-running applications. Based on correlation of data accesses, a parallelized correlated-directed prefetching approach is proposed to further increase the hit rate. Above approaches are intergrated to obtain the maximized hit rate and prefetching accuracy. Experimental results on 12 public real system traces show that ACAP achieves 14.03％ (up to 33.82％) higher prefetching accuracy and 2.01％ (up to 7.54％) higher hit rate compared with the best combination of baselines.
查看更多>>摘要：Duffing oscillator is one of the classic nonlinear system that can generate chaotic motion. Given the sensitivity to regular signals but immunity to noise of its chaotic attractor, the Duffing oscillator can be used for weak signal detection. Our recent study on other attractors of Duffing oscillator showed that the state transition of its steady attractor not only has the two major advantages of the chaotic attractor, but also has a specific advantage, that is, it has no transitional zone. In the nearby area of the steady attractor, noise may even cause stochastic resonance, which significantly increases the output signal-to-noise ratio. For the first time, we present a measure function for the state transition of the steady attractor of Duffing oscillator and then proposed a novel estimation method for weak sinusoidal signal buried in strong noise. Simulations were conducted to show the efficiency of the proposed method, and results indicate that the proposed method can achieve estimation of amplitude and frequency for sinusoidal signal. Moreover, the proposed method has a higher estimation accuracy and a stronger anti-noise performance than the classical spectrum and maximum likelihood estimation method.
查看更多>>摘要：This paper proposed Quaternion locality preserving projection (QLPP) for multi-feature multi-modal biometric recognition. Multi-features fill the real part or the three imaginary parts of quaternion to constitute the quaternion fusion features. In quaternion division ring, QLPP extracts the local information and finds essential manifold structure of the quaternion fusion features. Deferent from Quaternion principal component analysis (QPCA) and Quaternion fisher discriminant analysis (QFDA), QLPP takes advantage of the optimal linear approximations to find the nonlinear manifold structures. Two experiments are designed: one fuses four features from two biometric modalities, and the other fuses three features from three biometric modalities. The experimental results show the proposed algorithm achieves much better performance than the unimodal biometric algorithms, the traditional feature level fusion methods(weighted sum rule and series rule) and two quaternion representation methods(QPCA and QFDA).
查看更多>>摘要：To facilitate the search of rapidly growing biomedical knowledge in literature, we developed a Biomedical entity-relationship search tool (BERST). It is also a biomedical knowledge integration framework, which presently contains six popular databases represented in terms of a network of concepts and relations extracted from these knowledge sources. Users search the integrated knowledge network by entering keywords, and BERST returns a sub-network matching and representing the keywords and their relationships. The resulting graph can be navigated interactively allowing users to explore specific paths between any two nodes representing potentially interesting relationships between them. A graphical UI was developed to provide a more intuitive and overall view of the information being searched and studied. BERST framework can be naturally expanded to integrate other biomedical knowledge sources. BERST is implemented as a Java web application.
查看更多>>摘要：Ultrasound computed tomography (USCT) is considered to have great potential for breast cancer screening. Compared with ray-based methods, Waveform inversion (WI) methods obtain high spatial resolution images because they consider higher-order diffraction effects. For the WI method, considering more properties of the medium in a forward model can estimate more accurate images. However, longer reconstruction time is required. Therefore, to reduce the reconstruction time, three hypotheses are set in this work to develop the medium under different conditions. We compare the reconstructed images using the four forward models to analyze the effects of the various considered medium properties, which include the sound speed, density of the medium, acoustic absorption and dispersion. To reduce the difficulty of hardware manufacturing, a square border ultrasonic transducer array is adopted in the USCT data acquisition system. Penalized least-squares optimization problems are constructed to obtain numerical solutions of the sound speed and bulk modulus distributions. The reconstruction of the bulk modulus makes the reconstructed sound speed images more accurate. Computer simulations are conducted to compare reconstructed images using the four forward models under different noise conditions. A numerical breast phantom is used to evaluate the performance. The results suggest that for breast imaging, the forward model (which only considers the heterogeneous sound speed) is a compromise option between image accuracy and computational time.
查看更多>>摘要：Depression is a neurophysiological disorder with recurrent dysregulations of self-mental states. Multi-scale Approximate entropy (ApEn) and Sample entropy (SampEn) are employed to characterize nonlinear com-plexity of Magnetoencephalography (MEG) of depressive patients in our contribution. SampEn shares similarities with ApEn while has better distinctions between the MEGs of depression patients and normal people. Test results prove that nonlinear complexity of the depressive MEG is lower than that of the normal subjects, indicating weaker response of depression patients to emotional stimuli, and the optimum discriminations between the depressive and healthy people lie in frontal lobe of brain which is related to emotional regulation. Our findings provide valuable information about depression, highlight the loss of nonlinear complexity in MEG of depressive patient and can be used as clinical diagnostic aids.
查看更多>>摘要：If the glowworm individual has no memory during its movement, and the decision of next direction is limited to its current position. It is precisely these reasons mentioned above that make the basic Glowworm Swarm Optimization easy to trap into the local optimum. In order to solve the problem, this paper suggests a Shuffled mutation glowworm swarm optimization(SMGSO), which combines the thought of Shuffled Frog Leaping with Glowworm Swarm Optimization. Making use of a grouping idea of Shuffled Mutation, the glowworm swarm is divided into several subgroups. The location updating of each individual is not only influenced by the brightest node in neighbour scope, but also by the brightest one in their local subgroup, meanwhile the locations of those isolated nodes are updated by the difference mutation of the global optimum and local optimal. In group shuffling stage, an orthogonal strategy can guide the whole population to generate their offspring. The performance of this proposed approach is examined by well-known 10 benchmark functions, and its obtained results are compared with what other variants hold. The experimental analysis show that the Shuffled mutation glowworm swarm optimization is effective and outperforms other variants in terms of solving multi-modal function optimization problems, and the proposed approach can improve the positioning accuracy of the centroid localization.
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