A new logic for verification of security policies is proposed. The logic, HyperLTL, extends linear-time temporal logic (LTL) with connectives for explicit and simultaneous quantification over multiple execution paths, thereby enabling HyperLTL to express information-flow security policies that LTL cannot. A model-checking algorithm for a fragment of HyperLTL is given, and the algorithm is imple...

The development of predictive models in healthcare settings has been growing; one such area is the prediction of patient arrivals to the Emergency Department (ED). The general premise behind these works is that such models may be used to help manage an ED which consistently faces high congestion. In this work, we propose a class of proactive policies which utilizes future information of potenti...

In this paper we first describe the stochastic optimal control algorithm called ((OPTCON)). The algorithm minimizes an intertemporal objective loss function subject to a nonlinear dynamic system in order to achieve optimal value of control (or instrument) variables. Second as an application, we implemented the algorithm by the statistical programming system ((GAUSS)) to determine the optimal fi...

In the current global market, organizations use many promotional tools to increase their sales. One such tool is sales teams’ initiatives or promotional policies, i.e., free gifts, discounts, packaging, etc. This phenomenon motivates the retailer/or buyer to order a large inventory lot so as to take full benefit of promotional policies. In view of this the present paper considers a two-warehous...

Processor scheduling policies can be broadly divided into space-sharing and time-sharing policies. Space-sharing policies partition system processors and each partition is allocated exclusively to a job. In time-sharing policies, processors are temporally shared by jobs (e.g., in a round robin fashion). Space-sharing policies can be either static (processor allocation remains constant during th...

Multiobjective reinforcement learning algorithms extend reinforcement learning techniques to problems with multiple conflicting objectives. This paper discusses the advantages gained from applying stochastic policies to multiobjective tasks and examines a particular form of stochastic policy known as a mixture policy. Two methods are proposed for deriving mixture policies for episodic multiobje...

Certificate policies play a central role in public key infrastructures, since they are the basis for the evaluation of trust in binding between a key and a subject in a public key certificate. The absence of common ways of formally specifying details of policies is a source of difficulty in the operation of global public key infrastructures. In this paper, the problem of the formalisation of ce...

Gang scheduling is a job scheduling policy for parallel computers that combines elements of space-sharing and time-sharing. In this paper, we analyze the performance of gang scheduling policies that allow the remapping of an executing job to a new set of processors. Most previously proposed gang-scheduling policies do not allow such job remapping under the assumption that it is prohibitively ex...

| We develop a formal framework of MAC policies in multilevel relational databases. We identify the important components of MAC policies and their desirable properties. The framework provides a basis for systematically specifying MAC policies and characterizing their potential mismatches. Based on the framework, we compare and unify the MAC policies and policy components that are proposed in th...

In large-scale grid systems, plenty of applications are constrained by soft or hard deadline requirement. However, it is difficult to guarantee the deadline requirements of these applications because of the dynamical nature of distributed systems. In this paper, a novel approach is proposed to evaluate the deadline-guarantee of co-allocation schemes that obtained from conventional co-allocation...