Routing Algorithm Based on Area Division Management of Node in Wireless Sensor Networks

In order to reduce the communication overhead among sensor nodes, a routing algorithm is proposed based on zoning management nodes. The algorithm defines the calculation method of the network partition radius after nodes deployment, and divides monitored area according to the radius meanwhile layouts one management node in each partition. Then nodes’ communication cost is calculated based on the distance among nodes as well as nodes’ energy, and finishes the selection of routing nodes based on the cost. Finally, using the Matlab simulation environment, the parameters impacting the optimal partition radius are discussed, and the proposed routing algorithm is compared with existing algorithms. Theoretical analysis and experimental results show that the proposed algorithm is more balanced on nodes energy consumption. The algorithm reduces network traffic overhead while extends the lifetime of the network

Identifying speculative bubbles with an in finite hidden Markov model

This paper proposes an infinite hidden Markov model (iHMM) to detect, date stamp,and estimate speculative bubbles. Three features make this new approach attractive to practitioners. First, the iHMM is capable of capturing the nonlinear dynamics of different types of bubble behaviors as it allows an infinite number of regimes. Second, the implementation of this procedure is straightforward as the detection, dating, and estimation of bubbles are done simultaneously in a coherent Bayesian framework. Third, the iHMM, by assuming hierarchical structures, is parsimonious and superior in out-of-sample forecast. Two empirical applications are presented: one to the Argentinian money base, exchange rate, and consumer price from January 1983 to November 1989; and the other to the U.S. oil price from April 1983 to December 2010. We find prominent results, which have not been discovered by the existing finite hidden Markov model. Model comparison shows that the iHMM is strongly supported by the predictive likelihood

Nonfragile Robust Finite-Time L

The nonfragile robust finite-time L2-L∞ control problem for a class of nonlinear uncertain systems with uncertainties and time-delays is considered. The nonlinear parameters are considered to satisfy the Lipschitz conditions and the exogenous disturbances are unknown but energy bounded. By using the Lyapunov function approach, the sufficient condition for the existence of nonfragile robust finite-time L2-L∞ controller is given in terms of linear matrix inequalities (LMIs). The finite-time controller is designed such that the resulting closed-loop system is finite-time bounded for all admissible uncertainties and satisfies the given L2-L∞ control index. Simulation results illustrate the validity of the proposed approach

Identifying speculative bubbles with an in finite hidden Markov model

This paper proposes an infinite hidden Markov model (iHMM) to detect, date stamp,and estimate speculative bubbles. Three features make this new approach attractive to practitioners. First, the iHMM is capable of capturing the nonlinear dynamics of different types of bubble behaviors as it allows an infinite number of regimes. Second, the implementation of this procedure is straightforward as the detection, dating, and estimation of bubbles are done simultaneously in a coherent Bayesian framework. Third, the iHMM, by assuming hierarchical structures, is parsimonious and superior in out-of-sample forecast. Two empirical applications are presented: one to the Argentinian money base, exchange rate, and consumer price from January 1983 to November 1989; and the other to the U.S. oil price from April 1983 to December 2010. We find prominent results, which have not been discovered by the existing finite hidden Markov model. Model comparison shows that the iHMM is strongly supported by the predictive likelihood

Numerical simulation of pore-scale flow in chemical flooding process

AbstractChemical flooding is one of the effective technologies to increase oil recovery of petroleum reservoirs after water flooding. Above the scale of representative elementary volume (REV), phenomenological modeling and numerical simulations of chemical flooding have been reported in literatures, but the studies alike are rarely conducted at the pore-scale, at which the effects of physicochemical hydrodynamics are hardly resolved either by experimental observations or by traditional continuum-based simulations. In this paper, dissipative particle dynamics (DPD), one of mesoscopic fluid particle methods, is introduced to simulate the pore-scale flow in chemical flooding processes. The theoretical background, mathematical formulation and numerical approach of DPD are presented. The plane Poiseuille flow is used to illustrate the accuracy of the DPD simulation, and then the processes of polymer flooding through an oil-wet throat and a water-wet throat are studies, respectively. The selected parameters of those simulations are given in details. These preliminary results show the potential of this novel method for modeling the physicochemical hydrodynamics at the pore scale in the area of chemical enhanced oil recovery

Functional evaluation of Asp76, 84, 102 and 150 in human arsenic(III) methyltransferase (hAS3MT) interacting with S-adenosylmethionine

AbstractWe prepared eight mutants (D76P, D76N, D84P, D84N, D102P, D102N, D150P and D150N) to investigate the functions of residues Asp76, 84, 102 and 150 in human arsenic(III) methyltransferase (hAS3MT) interacting with the S-adenosylmethionine (SAM)-binding. The affinity of all the mutants for SAM were weakened. All the mutants except for D150N completely lost their methylation activities. Residues Asp76, 84, 102 and 150 greatly influenced hAS3MT catalytic activity via affecting SAM-binding or methyl transfer. Asp76 and 84 were located in the SAM-binding pocket, and Asp102 significantly affected SAM-binding via forming hydrogen bonds with SAM

Surface decoration of multi-walled carbon nanotubes modified carbon paste electrode with CuO nanoparticles for electrocatalytic oxidation of nitrite

625-632In this paper, CuO nanoparticles have been electrodeposited onto the film of multiwalled carbon nanotubes (MWCNTs) modified carbon paste electrode (MWCPE), which fabricated a sensitive nano-copper oxide coated multi-walled carbon nanotubes modified carbon paste electrode (CuOnano/MWCPE) to detect nitrite. Scanning electron microscope (SEM) image have indicated that copper oxide nanoparticles desposited on MWCPE are homogeneous. The CuOnano/MWCPE has been used to detect nitrite by square wave voltammetry and cyclic voltammetry techniques. The sensor has exhibited outstanding performance for the electrocatalysis of nitrite. Electrocatalytic oxidation of nitrite at the surface of CuOnano/MWCPE has been remarkably improved compared to the unmodified CPE and the MWCPE. Under optimum conditions, the oxidation current is linear with the concentration of nitrite ion in the range of 5 μM – 1000 μM. The detection limit has evaluated to be 1.25 μM (S/N = 3). The sensor has been successfully used to determine nitrite in water samples with excellent recoveries

Spectral correction method based on improved flat-top convoluted window for parameter estimation of power harmonic

Točna procjena harmonijskog parametra je važan zadatak u obradi signala elektroenergetskog sustava. Predlaže se nova vrsta flat-top prozora koja se generira vlastitim konvolucijama brzo padajućeg flat-top prozora (FDMS-FT) u domenu vremena. Proučavaju se značajke bočnog i glavnog režnja novog prozora. Nadalje, kako bi se poboljšala glatkoća glavnog režnja novog prozora, optimiziraju se koeficijenti matičnog prozora. Predstavlja se izmjenjivi algoritam ispravke razlike faze duljine prozora baziran na novom prozoru kako bi se procijenio strujni harmonični parametar. Kako bi se provjerila učinkovitost i točnost prikazane metode, provedeno je nekoliko računalnih simulacija i praktičnih eksperimenata s višefrekvencijskim strujnim signalima. Rezultati pokazuju da predložena metoda može učinkovito smanjiti opseg računanja i daje visok parametar točnosti procjene harmonijske snage.Accurate estimation of harmonic parameter is an important task in signal processing of power system. A new class of flat-top windows is proposed, which is generated by self-convolutions of the fast-decaying minimum-sidelobe flat-top (FDMS-FT) window in the time-domain. The mainlobe and sidelobe features of the new window are studied. In addition, to improve the flatness of mainlobe of the new window, the coefficients of its parent window are optimized. A window-length changeable discrete phase difference correction algorithm based on the new window is presented to estimate power harmonic parameter. In order to inspect the efficiency and accuracy of the presented method, several computer simulations and practical experiments were conducted with power multi-frequency signals. Results show that the proposed method can reduce the computation load efficiently and gives a high parameter estimation accuracy of power harmonic