An efficient and security dynamic identity based authentication protocol for multi-server architecture using smart cards

Generally, if a user wants to use numerous different network services, he/she must register himself/herself to every service providing server. It is extremely hard for users to remember these different identities and passwords. In order to resolve this problem, various multi-server authentication protocols have been proposed. Recently, Sood et al. analyzed Hsiang and Shih's multi-server authentication protocol and proposed an improved dynamic identity based authentication protocol for multi-server architecture. They claimed that their protocol provides user's anonymity, mutual authentication, the session key agreement and can resist several kinds of attacks. However, through careful analysis, we find that Sood et al.'s protocol is still vulnerable to leak-of-verifier attack, stolen smart card attack and impersonation attack. Besides, since there is no way for the control server CS to know the real identity of the user, the authentication and session key agreement phase of Sood et al.'s protocol is incorrect. We propose an efficient and security dynamic identity based authentication protocol for multi-server architecture that removes the aforementioned weaknesses. The proposed protocol is extremely suitable for use in distributed multi-server architecture since it provides user's anonymity, mutual authentication, efficient, and security.     

Dynamical coherence patterns in neural field model at criticality

Phase synchronization is a mechanism that plays a crucial role in information processing in the brain, and coherence is one of the factors used to evaluate the pairwise degree of phase synchronization. Coherence is also an important measure for examining brain functions because it implies communication and cooperation among neurons. In this work, we study the coherence patterns of spontaneous activity in a neural field model at criticality where a second-order phase transition occurs with special properties that differentiate it from other regions. The results are summarized as follows. First, in high-frequency bands, the system outside the critical region is unable to communicate efficiently via phase synchronization. Second, the dynamical coherence patterns at the criticality show switching between high and low coherence states. Finally, we found that in a very brief period, there is high broadband coherence between some pairs of spatial points. This phenomenon can be observed only in the critical region.     

Observer‐based Reliable Control for Discrete Time Systems: An Average Dwell Time Approach

This paper deals with the problem of reliable control for discrete time systems with actuator failures. The actuator is assumed to fail occasionally and can recover over a time interval. During the time of suffering failures, the considered closed‐loop system is assumed unstable. Using an average dwell time method and under the condition that the activation time ratio between the system without actuator failures and the system with actuator failures is not less than a specified constant, an observer‐based feedback controller is developed in terms of linear matrix inequalities such that the resulting closed‐loop system is exponentially stable. An example is included to demonstrate the effectiveness of the proposed approach.     

Asynchronous decentralized event-triggered control

In this paper we propose an approach to the implementation of controllers with decentralized strategies triggering controller updates. We consider set-ups with a central node in charge of the computation of the control commands, and a set of not co-located sensors providing measurements to the controller node. The solution we propose does not require measurements from the sensors to be synchronized in time. The sensors in our proposal provide measurements in an aperiodic way triggered by local conditions. Furthermore, in the proposed implementation (most of) the communication between nodes requires only the exchange of one bit of information (per controller update), which could aid in reducing transmission delays and as a secondary effect result in fewer transmissions being triggered.     

Maximum principle for mean-field jump–diffusion stochastic delay differential equations and its application to finance

This paper investigates a stochastic optimal control problem with delay and of mean-field type, where the controlled state process is governed by a mean-field jump–diffusion stochastic delay differential equation. Two sufficient maximum principles and one necessary maximum principle are established for the underlying system. As an application, a bicriteria mean–variance portfolio selection problem with delay is studied to demonstrate the effectiveness and potential of the proposed techniques. Under certain conditions, explicit expressions are provided for the efficient portfolio and the efficient frontier, which are as elegant as those in the classical mean–variance problem without delays.     

Alcohol consumption detection through behavioural analysis using intelligent systems

We describe in this paper a new methodology for blood alcohol content (BAC) estimation of a subject. Rather than using external devices to determine the BAC value of a subject, we perform a behaviour analysis of this subject using intelligent systems. We monitor the user’s actions in an ordinary task and label those data to various measured BAC values. The obtained data-set is then used to train learning systems to detect alcoholic consumption and perform BAC estimation. We obtain good results on a mono-user base, and lower results with multiple users. We improve the results by combining multiple classifiers and regression algorithms.     

ARD算法收敛性分析

对交替行对角化（ARD）算法收敛性进行分析.基于收敛性分析,给出了一些关于如何选取初始矩阵的策略,提出了算法终止的新准则.通过3个数值例子来说明所提出的分析策略的有效性.     

Estimation and forecasting with logarithmic autoregressive conditional duration models: A comparative study with an application

This paper presents a semi-parametric method of parameter estimation for the class of logarithmic ACD (Log-ACD) models using the theory of estimating functions (EF). A number of theoretical results related to the corresponding EF estimators are derived. A simulation study is conducted to compare the performance of the proposed EF estimates with corresponding ML (maximum likelihood) and QML (quasi maximum likelihood) estimates. It is argued that the EF estimates are relatively easier to evaluate and have sampling properties comparable with those of ML and QML methods. Furthermore, the suggested EF estimates can be obtained without any knowledge of the distribution of errors is known. We apply all these suggested methodology for a real financial duration dataset. Our results show that Log-ACD (1, 1) fits the data well giving relatively smaller variation in forecast errors than in Linear ACD (1, 1) regardless of the method of estimation. In addition, the Diebold–Mariano (DM) and superior predictive ability (SPA) tests have been applied to confirm the performance of the suggested methodology. It is shown that the new method is slightly better than traditional methods in practice in terms of computation; however, there is no significant difference in forecasting ability for all models and methods.     

Lower Bounds for Eigenvalues of Elliptic Operators: By Nonconforming Finite Element Methods

The paper is to introduce a new systematic method that can produce lower bounds for eigenvalues. The main idea is to use nonconforming finite element methods. The conclusion is that if local approximation properties of nonconforming finite element spaces are better than total errors (sums of global approximation errors and consistency errors) of nonconforming finite element methods, corresponding methods will produce lower bounds for eigenvalues. More precisely, under three conditions on continuity and approximation properties of nonconforming finite element spaces we analyze abstract error estimates of approximate eigenvalues and eigenfunctions. Subsequently, we propose one more condition and prove that it is sufficient to guarantee nonconforming finite element methods to produce lower bounds for eigenvalues of symmetric elliptic operators. We show that this condition hold for most low-order nonconforming finite elements in literature. In addition, this condition provides a guidance to modify known nonconforming elements in literature and to propose new nonconforming elements. In fact, we enrich locally the Crouzeix-Raviart element such that the new element satisfies the condition; we also propose a new nonconforming element for second order elliptic operators and prove that it will yield lower bounds for eigenvalues. Finally, we prove the saturation condition for most nonconforming elements.