Two Novel Hydroperoxylated Lycopodium Alkaloids from Huperzia serrata

Two novel hydroperoxylated Lycopodium alkaloids, 11alpha-hydroperoxyphlegmariurine B (1) and 7-hydroperoxyphlegmariurine B (2), along with a known compound, phlegmanurine B (3), were isolated from the total alkaloid fraction of the Chinese medicinal herb Huperzia serrata (Thunb.) Trev. Their structures and relative configurations were elucidated on the basis of spectroscopic analyses.

The MAP/PH(PH/PH)/1 Discrete-time Queuing System with Repairable Server

In this paper, we discuss a discrete time repairable queuing system with Markovian arrival process, where lifetime of server, service time and repair time of server are all discrete phase type random variables. Using the theory of matrix geometric solution, we give the steady state distribution of queue length and waiting time. In addition, the stable availability of the system is also provided.

广州地铁十三号线南岗站B口正式开通

十三号线南岗站B口已完成验收工作,于9月11日正式开门迎客。此前南岗站已于2017年12月28日开通试运营,但该站B口因受征地拆迁影响未能与车站同步投入运营服务。据了解,南岗站已开通的C口位于黄埔东路东南侧,D口及E口位于黄埔东路西北侧。

Quality prediction of batch process using the global-local discriminant analysis based Gaussian process regression model

The conventional single model strategy may be ill- suited due to the multiplicity of operation phases and system uncertainty. A novel global-local discriminant analysis （GLDA） based Gaussian process regression （GPR） approach is developed for the quality prediction of nonlinear and multiphase batch processes. After the collected data is preprocessed through batchwise unfolding, the hidden Markov model （HMM） is applied to identify different operation phases. A GLDA algorithm is also presented to extract the appropriate process variables highly correlated with the quality variables, decreasing the complexity of modeling. Besides, the multiple local GPR models are built in the reduced- dimensional space for all the identified operation phases. Furthermore, the HMM-based state estimation is used to classify each measurement sample of a test batch into a corresponding phase with the maximal likelihood estimation. Therefore, the local GPR model with respect to specific phase is selected for online prediction. The effectiveness of the proposed prediction approach is demonstrated through the multiphase penicillin fermentation process. The comparison results show that the proposed GLDA-GPR approach is superior to the regular GPR model and the GPR based on HMM （HMM-GPR） model.

Degradation Process of Coated Tinplate by Phase Space Reconstruction Theory

The degradation process of organosol coated tinplate in beverage was investigated by electrochemical noise (EN) technique combined with morphology characterization.EN data were analyzed using phase space reconstruction theory.With the correlation dimensions obtained from the phase space reconstruction,the chaotic behavior of EN was quantitatively evaluated.The results show that both electrochemical potential noise (EPN) and electrochemical current noise (ECN) have chaotic properties.The correlation dimensions of EPN increase with corrosion extent,while those of ECN seem nearly unchanged.The increased correlation dimensions of EPN during the degradation process are associated with the increased susceptibility to local corrosion.

On approximating multifractal traffic burstiness with Markov modulated Poisson processes

We investigate the approximating capability of Markov modulated Poisson processes (MMPP) for modeling multifractal Internet traffic. The choice of MMPP is motivated by its ability to capture the variability and correlation in moderate time scales while being analytically tractable. Important statistics of traffic burstiness are described and a customized moment-based fitting procedure of MMPP to traffic traces is presented. Our methodology of doing this is to examine whether the MMPP can be used to predict the performance of a queue to which MMPP sample paths and measured traffic traces are fed for comparison respectively, in addition to the goodness-of-fit test of MMPP. Numerical results and simulations show that the fitted MMPP can approximate multifractal traffic quite well, i.e. accurately predict the queueing performance.

An Optimized Vertical Handoff Algorithm Based on Markov Process in Vehicle Heterogeneous Network

In order to solve the problem the existing vertical handoff algorithms of vehicle heterogeneous wireless network do not consider the diversification of network's status, an optimized vertical handoff algorithm based on markov process is proposed and discussed in this paper. This algorithm takes into account that the status transformation of available network will affect the quality of service(Qo S) of vehicle terminal's communication service. Firstly, Markov process is used to predict the transformation of wireless network's status after the decision via transition probability. Then the weights of evaluating parameters will be determined by fuzzy logic method. Finally, by comparing the total incomes of each wireless network, including handoff decision incomes, handoff execution incomes and communication service incomes after handoff, the optimal network to handoff will be selected. Simulation results show that: the algorithm proposed, compared to the existing algorithm, is able to receive a higher level of load balancing and effectively improves the average blocking rate, packet loss rate and ping-pang effect.

On Kendall's Conjecture for an Extended Birth-death Q-processes with Instantaneous State and Catastrophes

A new structure with the special property that instantaneous state and catas-trophes is imposed to ordinary birth-death processes is considered. Kendall's conjecture forthe processes is proved to be right.

A new analytical algorithm for computing probability distribution of project completion time

An analytical algorithm was presented for the exact computation of the probability distribution of the project completion time in stochastic networks,where the activity durations are mutually independent and continuously distributed random variables. Firstly,stochastic activity networks were modeled as continuous-time Markov process with a single absorbing state by the well-know method of supplementary variables and the time changed from the initial state to absorbing state is equal to the project completion time.Then,the Markov process was regarded as a special case of Markov skeleton process.By taking advantage of the backward equations of Markov skeleton processes,a backward algorithm was proposed to compute the probability distribution of the project completion time.Finally,a numerical example was solved to demonstrate the performance of the proposed methodology.The results show that the proposed algorithm is capable of computing the exact distribution function of the project completion time,and the expectation and variance are obtained.

Active Contours and Mumford-Shah Segmentation Based on Level Sets

This paper is to detect regions (objects) boundaries, also to isolate and extract individual components from a medical image. This can be done using an active contours to detect regions in a given image, based on techniques of curve evolution, Mumford Shah functional for segmentation and level sets. The paper classified the images into different intensity regions based on Markov random field, then detected regions whose boundaries are not necessarily defined by gradient by minimizing an energy of Mumford Shah functional for segmentation which can be seen as a particular case of the minimal partition problem. In the level set formulation, the problem becomes a mean curvature flow like evolving the active contour, which will stop on the desired boundary. The stopping term does not depend on the gradient of the image, as in the classical active contour and the initial curve of level set can be anywhere in the image, and interior contours are automatically detected. The final image segmentation is one closed boundary per actual region in the image.

A Novel Dynamic Decision Model in 2-player Symmetric Repeated Games

Considering the dynamic character of repeated games and Markov process, this paper presented a novel dynamic decision model for symmetric repeated games. In this model, players＇ actions were mapped to a Markov decision process with payoffs, and the Boltzmann distribution was intousluced. Our dynamic model is different from others＇ , we used this dynamic model to study the iterated prisoner＇ s dilemma, and the results show that this decision model can successfully be used in symmetric repeated games and has an ability of adaptive learning.

Efficient Temporal Difference Learning with Adaptive λ

Aim To find a more efficient learning method based on temporal difference learning for delayed reinforcement learning tasks. Methods A kind of Q learning algorithm based on truncated TD( λ ) with adaptive schemes of λ value selection addressed to absorbing Markov decision processes was presented and implemented on computers. Results and Conclusion Simulations on the shortest path searching problems show that using adaptive λ in the Q learning based on TTD( λ ) can speed up its convergence.

Optimization of the CBSMAP Queueing Model

The present paper is devoted to the research of controlled queueing models at control of CBSMAP （Controlled Batch Semi-Markov Arrival Process）. The control is based on the theory of controlled semi-markov processes for system optimization. The control is carried out using a type of the next batch and moments of batch arrivals.

Survivability modeling and analysis on 3D mobile ad-hoc networks

Most existing work on survivability in mobile ad-hoc networks(MANETs) focuses on two dimensional(2D) networks.However,many real applications run in three dimensional(3D) networks,e.g.,climate and ocean monitoring,and air defense systems.The impact on network survivability due to node behaviors was presented,and a quantitative analysis method on survivability was developed in 3D MANETs by modeling node behaviors and analyzing 3D network connectivity.Node behaviors were modeled by using a semi-Markov process.The node minimum degree of 3D MANETs was discussed.An effective approach to derive the survivability of k-connected networks was proposed through analyzing the connectivity of 3D MANETs caused by node misbehaviors,based on the model of node isolation.The quantitative analysis of node misbehaviors on the survivability in 3D MANETs is obtained through mathematical description,and the effectiveness and rationality of the proposed approach are verified through numerical analysis.The analytical results show that the effect from black and gray attack on network survivability is much severer than other misbehaviors.

Bed Load Transport Rates during Scouring and Armoring Processes

Dambreak-induced bed scouring may undermine the foundation of bridge piers and other structures,and that destruction can pose a serious threat.Consequently,this paper aims at exploring the mechanisms of scouring and armoring.Firstly,the incipient velocity for nonuniform sediment particles was studied,and a formula was derived based on the angle of repose of nonuniform sediment.The results showed that the mechanism of incipient motion for sand and fine gravel differed from that for coarse gravel and cobbles.Also,comparison between experimental and field data shows that the results from the proposed formula agree well with those observed for all conditions.Secondly,a birth-death,immigration-emigration Markov process was developed to describe the bed load transport rate associated with scouring and armoring.The comparison between experimental data and computed results shows that our model can predict the bed load transport rate,although there may be some limitations,the chief of which is that there are many variables in the model to be determined through experiment.This makes its application in river engineering inconvenient.

Evolutionary Game Dynamics in a Fitness-Dependent Wright-Fisher Process with Noise

Evolutionary game dynamics in finite size populations can be described by a fitness-dependent Wright- Fisher process. We consider symmetric 2×2 games in a well-mixed population. In our model, two parameters to describe the level of player＇s rationality and noise intensity in environment are introduced. In contrast with the fixation probability method that used in a noiseless case, the introducing of the noise intensity parameter makes the process an ergodic Markov process and based on the limit distribution of the process, we can analysis the evolutionary stable strategy （ESS） of the games. We illustrate the effects of the two parameters on the ESS of games using the Prisoner＇s dilemma games （PDG） and the snowdrift games （SG）. We also compare the ESS of our model with that of the replicator dynamics in infinite size populations. The results are determined by simulation experiments.

The Stability of Logistic Model with Random Impulse

This paper is devoted to studying the stability of Logistic model with random impulse by using the theory of Markov skeleton processes and a convenient condition for Logistic model with random impulse to be stable is given.

A Brief Analysis on BMW＇S Automatic Transmission Problems and Treatment

the article analyses the principles AT work, and a detailed analysis of BMW＇s automatic transmission failures, and maintenance process.Maintenance of other automatic transmission provides a certain degree of significance.

Separation Processes of Granular Materials by Sizes at the Sieve Classifiers

A mathematical model of the kinetics of thin-layer separation of granular materials by size stacked sieve classifiers based on the theory of Markov processes is constructed. The probability of screening in a cell in the shape and size of the holes and particle sieve material shared with the influence of the relative speed of their movement was determined. Residues on whole meal with sieves were identified by a kinetic model and numerical calculations, the efficacy of separation.