Pragmatic Maxims and Presumptions in Legal Interpretation

The fields of linguistic pragmatics and legal interpretation are deeply interrelated. The purpose of this paper is to show how pragmatics and the developments in argumentation theory can contribute to the debate on legal interpretation. The relation between the pragmatic maxims and the presumptions underlying the legal canons are brought to light, unveiling the principles that underlie the types of argument usually used to justify a construction. The Gricean maxims and the arguments of legal interpretation are regarded as presumptions subject to default used to justify an interpretation. This approach can allow one to trace the different legal interpretive arguments back to their basic underlying presumptions, so that they can be compared, ordered, and assessed according to their defeasibility conditions. This approach allows one to understand the difference between various types of interpretive canons, and their strength in justifying an interpretation

Minimum energy transmission scheduling subject to deadline constraints

We consider the problem of transmission scheduling of data over a wireless fading channel with hard deadline constraints. Our system consists of N users, each with a fixed amount of data that must be served by a common deadline. Given that, for each user, the channel fade state determines the throughput per unit of energy expended, our objective is to minimize the overall expected energy consumption while satisfying the deadline constraint. We consider both a linear and a strictly convex rate-power curve and obtain optimal solutions, based on dynamic programming (DP), and tractable approximate heuristics in both cases. For the special non-fading channel case with convex rate-power curve, an optimal solution is obtained based on the Shortest Path formulation. In the case of a linear rate-power curve, our DP solution has a nice “threshold ” form; while for the convex rate-power curve we are able to obtain a heuristic algorithm with comparable performance with that of the optimal scheduling scheme. 1

Minimum energy transmission scheduling subject to deadline constraints

We consider the problem of transmission scheduling of data over a wireless fading channel with hard deadline constraints. Our system consists of N users, each with a fixed amount of data that must be served by a common deadline. Given that, for each user, the channel fade state determines the throughput per unit of energy expended, our objective is to minimize the overall expected energy consumption while satisfying the deadline constraint. We consider both a linear and a strictly convex rate-power curve and obtain optimal solutions, based on dynamic programming (DP), and tractable approximate heuristics in both cases. For the special non-fading channel case with convex ratepower curve, an optimal solution is obtained based on the Shortest Path formulation. In the case of a linear rate-power curve, our DP solution has a nice “threshold” form; while for the convex rate-power curve we are able to obtain a heuristic algorithm with comparable performance with that of the optimal scheduling scheme.

Energy efficient transmission scheduling over mars proximity links

Abstract—We consider the scheduling of transmissions from an energy limited Mars lander to a Mars orbiter. Typically, the channel quality of the Mars proximity links is time-varying due to orbital dynamics, multi-path effects and the antenna positioning on the lander. Since the channel state determines the throughput obtained per unit of energy transmitted, it is desirable to select when, and at what data rate, to transmit based on channel conditions. In this paper we consider the dual problem of maximizing the throughput of a lander that has a limited amount of energy to be used for transmission; and minimizing the energy consumption used for transmission of data subject to delay constraints. In [1], [3] it was shown, using techniques from Dynamic Programming, that energy efficiency can be significantly improved through an adaptive rate and power allocation scheme. We apply the policies developed in [1] and [3] to the Mars proximity link and compare them with scheduling algorithms presently in use for proximity links. Our simulations, using channel measurement data obtained from NASA’s 2001 Mars Odyssey orbiter and the Mars Exploration Rover (MER) project, show over an order of magnitude increase in throughput and decrease in energy consumption through the use of the Dynamic Programming based rate and power adaptation scheme. I