Optimal opportunistic maintenance model of multi-unit systems

An opportunistic maintenance model is presented for a continuously deteriorating series system with economical de-pendence. The system consists of two kinds of units, which are respectively subjected to the deterioration failure described by Gamma process and the random failure described by Poisson process. A two-level opportunistic policy defined by three decision parameters is proposed to coordinate the different maintenance actions and minimize the long-run maintenance cost rate of the system. A computable expression of the average cost rate is established by using the renewal property of the stochastic process of the maintained system state. The optimal values of three deci- sion parameters are derived by an iteration approach based on the characteristic of Gamma process. The behavior of the proposed policy is illustrated through a numerical experiment. Comparative study with the widely used corrective maintenance policy demonstrates the advantage of the proposed opportunistic maintenance method in significantly reducing the maintenance cost. Simultane- ously, the applicable area of this opportunistic model is discussed by the sensitivity analysis of the set-up cost and random failure rate.

AB081.Multi-unit ocular biometric system based on corneal shapes

Background:Our goal is to build a multi-unit ocular biometric system based on the fusion of left and right corneal shapes for identity authentication.Methods:Ocular biometrics such as iris,periocular,retina,sclera and eye movement have become established biometric traits,primarily due to extensive efforts made by the biometrics community in the field of iris recognition.In this work,we propose an ocular biometric trait based on the 3D shape of the cornea to improve biometric authentication.We show how the fusion of the left and right corneas can be used as a biometric trait for person recognition.First,we started by realizing our own cornea database by using a Pentacam Topographer(Oculus)which contains 288 corneal topographies of both eyes captured from 36 different people of different ages.For each eye,data acquisition was done during two different sessionsto establish the repeatability of the measurements over time.The time interval between the two sessions was equal or greater than one month.In each session;8 acquisitions(4 left eyes end 4 right eyes)were taken.Then,features were extracted by modeling the shape of the left and right corneas with a Zernike polynomial expansion.The fusion of the left and right shapes of cornea was performed at the matching score level using the weighted-sum rule.Results:For each individual,we had eight feature vectors(eight measures in two sessions)of size 36(Zernike polynomial coefficients)from their corneal topographies.The experimental results on our cornea database constructed for this study showed encouraging performance of the proposed ocular biometric system with Equal Error Rate decreasing to 1.38%with the weighted-sum rule compared to the analysis of the left(4.5%)or right(3.7%)cornea alone.Conclusions:The objective of this work was to investigate corneal topographyas an accurate biometric modality using shape discriminating features.Our idea was to propose an ocular multi-unit system based on the fusion of the left and right corneal shapes.The corneal feature extraction was done by Zernike polynomial decomposition.Multi-unit cornea fusion was performed at the matching score level to generate a unique score.This allowed a significative decrease of the EER to 1.38%.

AB062. Cortical state contribution to neuronal response variability

Background:Visual cortex neurons often respond to stimuli very differently on repeated trials.This trial-by-trial variability is known to be correlated among nearby neurons.Our long-term goal is to quantitatively estimate neuronal response variability,using multi-channel local field potential(LFP)data from single trials.Methods:Acute experiments were performed with anesthetized(Remifentanil,Propofol,nitrous oxide)and paralyzed(Gallamine Triethiodide)cats.Computer-controlled visual stimuli were displayed on a gamma-corrected CRT monitor.For the principal experiment,two kinds of visual stimuli were used:drifting sine-wave gratings,and a uniform mean-luminance gray screen.These two stimuli were each delivered monocularly for 100 sec in a random order,for 10 trials.Multi-unit activity(MUA)and LFP signals were extracted from broadband raw data acquired from Area 17 and 18 using A1X32 linear arrays(NeuroNexus)and the OpenEphys recording system.LFP signal processing was performed using Chronux,an open-source MATLAB toolbox.Current source density(CSD)analysis was performed on responses to briefly flashed full-field stimuli using the MATLAB toolbox,CSDplotter.The common response variability(global noise)of MUA was estimated using the model proposed by Scholvinck et al.[2015].Results:On different trials,a given neuron responded with different firing to the same visual stimuli.Within one trial,a neuron’s firing rate also fluctuated across successive cycles of a drifting grating.When the animal was given extra anesthesia,neurons fired in a desynchronized pattern;with lighter levels of anesthesia,neuronal firing because more synchronized.By examining the cross-correlations of LFP signals recorded from different cortical layers,we found LFP signals could be divided to two groups:those recorded in layer IV and above,and those from layers V and VI.Within each group,LFP signals recorded by different channels are highly correlated.These two groups were observed in lighter and deeper anesthetized animals,also in sine-wave and uniform gray stimulus conditions.We also investigated correlations between LFP signals and global noise.Power in the LFP beta band was highly correlated with global noise,when animals were in deeper anesthesia.Conclusions:Brain states contribute to variations in neuronal responses.Raw LFP correlation results suggest that we should analyze LFP data according to their laminar organization.Correlation of low-frequency LFP under deeper anesthesia with global noise gives us some insight to predict noise from single-trial data,and we hope to extend this analysis to lighter anesthesia in the future.

Optimal Maintenance Modeling for Systems with Multiple Non-Identical Units Using Extended DSSP Method

In the optimal maintenance modeling, all possible maintenance activities and their corresponding probabilities play a key role in modeling. For a system with multiple non-identical units, its maintenance requirements are very complicated, and it is time-consuming, even omission may occur when enumerating them with various combinations of units and even with different maintenance actions for them. Deterioration state space partition (DSSP) method is an efficient approach to analyze all possible maintenance requirements at each maintenance decision point and deduce their corresponding probabilities for maintenance modeling of multi-unit systems. In this paper, an extended DSSP method is developed for systems with multiple non-identical units considering opportunistic, preventive and corrective maintenance activities for each unit. In this method, different maintenance types are distinguished in each maintenance requirement. A new representation of the possible maintenance requirements and their corresponding probabilities is derived according to the partition results based on the joint probability density function of the maintained system deterioration state. Furthermore, focusing on a two-unit system with a non-periodical inspected condition-based opportunistic preventive-maintenance strategy;a long-term average cost model is established using the proposed method to determine its optimal maintenance parameters jointly, in which “hard failure” and non-negligible maintenance time are considered. Numerical experiments indicate that the extended DSSP method is valid for opportunistic maintenance modeling of multi-unit systems.

TMAHS:a truthful multi-unit double auction framework for heterogeneous spectrum in secondary market

Auction was widely used to tackle spectrum allocation and sharing in the secondary market under the condition of spectrum scarcity. In real communication system, such as broadband communication, the utilization of spectrum resource is various because of different requirements and complex application scenarios. So, these schemes cannot be directly applied to the above wireless communication system. To solve this problem, a new model where sellers/buyers can sell/buy multi-unit for heterogeneous spectrum was proposed and a truthful multi-unit double auction framework was designed for heterogeneous spectrum trading. A valuation function is first applied to represent the buyer's true valuation of the sub-band and reflect the buyer's satisfaction degree and a novel concept termed ‘virtual player' was introduced. Then the buyer group was constructed based on the conflict graph to reuse the same spectrum among interference-free buyers in both spatial and temporal domains. The winner determination strategy and algorithm of clearing price were designed elaborately. According to the theoretical analysis, the scheme can satisfy three critical economic properties: truthfulness, individual rationality, and budget balance. Finally, simulation results show that the proposed scheme can achieve better user satisfaction, auction efficiency and spectrum reuse rate for the real communication system. The proposed auction framework is practical and effective.

Chicken retinal ganglion cells response characteristics:multi-channel electrode recording study

The first stage of visual processing occurs in the retina, the function of which is to process the raw information obtained from the outside world. In the present study, the electrical activities of a group of retinal ganglion cells were recorded from a small functioning piece of retina, using multi-electrode array (MEA), and the action potentials were detected by applying nonlinear algorithm. By analyzing the ensemble retinal ganglion output characteristics, it is revealed that both firing rates and correlated activity between adjacent neurons in the retina contribute to visual information encoding.

Privacy-Preserving Strategyproof Auction Mechanisms for Resource Allocation

In recent years, auction theory has been extensively studied and many state-of-the-art solutions have been proposed aiming at allocating scarce resources. However, most of these studies assume that the auctioneer is always trustworthy in the sealed-bid auctions, which is not always true in a more realistic scenario. Besides the privacy-preserving issue, the performance guarantee of social efficiency maximization is also crucial for auction mechanism design. In this paper, we study the auction mechanisms that consider the above two aspects. We discuss two multi-unit auction models： the identical multiple-items auction and the distinct multiple-items auction.Since the problem of determining a multi-unit auction mechanism that can maximize its social efficiency is NPhard, we design a series of nearly optimal multi-unit auction mechanisms for the proposed models. We prove that the proposed auction mechanisms are strategyproof. Moreover, we also prove that the privacy of bid value from each bidder can be preserved in the auction mechanisms. To the best of our knowledge, this is the first work on the strategyproof multi-unit auction mechanisms that simultaneously consider privacy preservation and social efficiency maximization. The extensive simulations show that the proposed mechanisms have low computation and communication overheads.