Sampled-data fuzzy controller for continuous nonlinear systems

The sampled-data fuzzy control of nonlinear systems is presented. The consequents of the fuzzy controller rules are linear sampled-data sub-controllers. As a result, the fuzzy controller is a weighted sum of some linear sampled-data sub-controllers that can be implemented by a microcontroller or a digital computer to lower the implementation cost. Consequently, a hybrid fuzzy controller consisting of continuous-time grades of memberships and discrete-time sub-controller is obtained. The system stability of the fuzzy control system is investigated on the basis of Lyapunov-based approach. The sampling activity introduces discontinuity to complicate the system dynamics and make the stability analysis difficult. The proposed fuzzy controller exhibits a favourable property to alleviate the conservativeness of the stability analysis. Furthermore, linear matrix inequality-based performance conditions are derived to guarantee the system performance of the fuzzy control system. An application example is given to illustrate the merits of the proposed approac

Tests of Seasonal and Non-Seasonal Serial Correlation

This paper considers tests for seasonal and non-seasonal serial correlation in time series and in the errors of regression models. The problem of testing for white noise against multiplicative seasonal ARMA(l,l)-ARMA(l,l) alternatives is investigated. This testing problem is non-standard due to nuisance parameters that appear under the alternative but not under the null hypothesis. The likelihood ratio (LR), sup Lagrange multiplier (LM), and exponential average LM and LR tests are considered and are shown to be asymptotically admissible for multiplicative seasonal ARMA(l,l)-ARMA(l,l) alternatives. In addition, they are shown to be consistent against all (weakly stationary strong mixing) non-white noise alternatives. Simulation results compare the tests to several tests in the literature. The exponential average test, Exp-LR infinity , is found to be the best test overall. It performs substantially better than the Box-Pierce, Durbin-Watson, and Wallis tests

Parametric Analysis of Energy Absorption in Micro-particle Photophoresis in Absorbing Gaseous Media

The study deals with photophoresis of a spherical micro-particle suspended in absorbing gaseous media. Photophoretic motion of the particle stems from the asymmetric distribution of absorbed energy within the particle. By evaluating the so-called heat source function at various conditions, the study focuses on the effects of governing parameters on the energy distribution within the particle and their potential influences to the photophoresis. The results reveal that the increase in either particle size or absorptivity enhances the energy intensity on the illuminated (leading) side and tends to generate positive photophoresis. For a particle of low absorptivity, the energy distribution is dominated by particle refraction. Enhancing particle refractivity, the energy tends to be focused onto a certain spot area on the shaded (trailing) side and leads to a tendency of negative photophoresis. Increasing medium absorptivity significantly degrades the level of energy absorbed by the particle and in turn weakens the driving force of the particle photophoresis.Defence Science Journal, 2010, 60(3), pp.233-237, DOI:http://dx.doi.org/10.14429/dsj.60.34

Quantum State Reconstruction of Many Body System Based on Complete Set of Quantum Correlations Reduced by Symmetry

We propose and study a universal approach for the reconstruction of quantum states of many body systems from symmetry analysis. The concept of minimal complete set of quantum correlation functions (MCSQCF) is introduced to describe the state reconstruction. As an experimentally feasible physical object, the MCSQCF is mathematically defined through the minimal complete subspace of observables determined by the symmetry of quantum states under consideration. An example with broken symmetry is analyzed in detail to illustrate the idea.Comment: 10 pages, n figures, Revte

ACHIKO-D350: A dataset for early AMD detection and drusen segmentation

Age related macular degeneration is the third leading cause of global blindness. Its prevalence is increasing in these years for the coming of ”aging population”. Early detection and grading can prevent it from becoming severe and protect vision. Drusen is an important indicator for AMD. Thus automatic drusen detection and segmentation has attracted much research attention in the past years. However, a barrier handicapping the research of drusen segmentation is the lack of a public dataset and test platform. To address this issue, in this paper, we publish a dataset, named ACHIKO-D350, with manually marked drusen boundary. ACHIKO-D350 includes 254 healthy fundus images and 96 fundus images with drusen. The images with drusen cover a wide range of types, including images with sparsely distributed drusen or clumped drusen, images of poor quality, and both well macular centered images and mis-centered images. ACHIKO-D350 will be used for performance evaluation of drusen segmentation methods. It will facilitate an objective evaluation and comparison

Topological Phase Transition and Electrically Tunable Diamagnetism in Silicene

Silicene is a monolayer of silicon atoms forming a honeycomb lattice. The lattice is actually made of two sublattices with a tiny separation. Silicene is a topological insulator, which is characterized by a full insulating gap in the bulk and helical gapless edges. It undergoes a phase transition from a topological insulator to a band insulator by applying external electric field. Analyzing the spin Chern number based on the effective Dirac theory, we find their origin to be a pseudospin meron in the momentum space. The peudospin degree of freedom arises from the two-sublattice structure. Our analysis makes clear the mechanism how a phase transition occurs from a topological insulator to a band insulator under increasing electric field. We propose a method to determine the critical electric field with the aid of diamagnetism of silicene. Diamagnetism is tunable by the external electric field, and exhibits a singular behaviour at the critical electric field. Our result is important also from the viewpoint of cross correlation between electric field and magnetism. Our finding will be important for future electro-magnetic correlated devices.Comment: 4 pages,5 figure

Establishment of Prognostic Models for Astrocytic and Oligodendroglial Brain Tumors with Standardized Quantification of Marker Gene Expression and Clinical Variables

Background Prognosis models established using multiple molecular markers in cancer along with clinical variables should enable prediction of natural disease progression and residual risk faced by patients. In this study, multivariate Cox proportional hazards analyses were done based on overall survival (OS) of 100 glioblastoma multiformes (GBMs, 92 events), 49 anaplastic astrocytomas (AAs, 33 events), 45 gliomas with oligodendroglial features, including anaplastic oligodendroglioma (AO, 13 events) and oligodendraglioma (O, 9 events). The modeling included two clinical variables (patient age and recurrence at the time of sample collection) and the expression variables of 13 genes selected based on their proven biological and/or prognosis functions in gliomas ( ABCG2, BMI1, MELK, MSI1, PROM1, CDK4, EGFR, MMP2, VEGFA, PAX6, PTEN, RPS9, and IGFBP2 ). Gene expression data was a log-transformed ratio of marker and reference ( ACTB ) mRNA levels quantified using absolute real-time qRT-PCR. Results Age is positively associated with overall grade (4 for GBM, 3 for AA, 2_1 for AO_O), but lacks significant prognostic value in each grade. Recurrence is an unfavorable prognostic factor for AA, but lacks significant prognostic values for GBM and AO_O. Univariate models revealed opposing prognostic effects of ABCG2, MELK, BMI1, PROM1, IGFBP2, PAX6, RPS9 , and MSI1 expressions for astrocytic (GBM and AA) and oligodendroglial tumors (AO_O). Multivariate models revealed independent prognostic values for the expressions of MSI1 (unfavorable) in GBM, CDK4 (unfavorable) and MMP2 (favorable) in AA, while IGFBP2 and MELK (unfavorable) in AO_O. With all 13 genes and 2 clinical variables, the model R 2 was 14.2% ( P = 0.358) for GBM, 45.2% ( P = 0.029) for AA, and 62.2% ( P = 0.008) for AO_O. Conclusion The study signifies the challenge in establishing a significant prognosis model for GBM. Our success in establishing prognosis models for AA and AO_O was largely based on identification of a set of genes with independent prognostic values and application of standardized gene expression quantification to allow formation of a large cohort in analysis

Optimal Energy Dissipation in Sliding Friction Simulations

Non-equilibrium molecular dynamics simulations, of crucial importance in sliding friction, are hampered by arbitrariness and uncertainties in the removal of the frictionally generated Joule heat. Building upon general pre-existing formulation, we implement a fully microscopic dissipation approach which, based on a parameter-free, non-Markovian, stochastic dynamics, absorbs Joule heat equivalently to a semi-infinite solid and harmonic substrate. As a test case, we investigate the stick-slip friction of a slider over a two-dimensional Lennard-Jones solid, comparing our virtually exact frictional results with approximate ones from commonly adopted dissipation schemes. Remarkably, the exact results can be closely reproduced by a standard Langevin dissipation scheme, once its parameters are determined according to a general and self-standing variational procedure