On the capacity of information processing systems

We propose and analyze a family of information processing systems, where a finite set of experts or servers are employed to extract information about a stream of incoming jobs. Each job is associated with a hidden label drawn from some prior distribution. An inspection by an expert produces a noisy outcome that depends both on the job's hidden label and the type of the expert, and occupies the expert for a finite time duration. A decision maker's task is to dynamically assign inspections so that the resulting outcomes can be used to accurately recover the labels of all jobs, while keeping the system stable. Among our chief motivations are applications in crowd-sourcing, diagnostics, and experiment designs, where one wishes to efficiently learn the nature of a large number of items, using a finite pool of computational resources or human agents. We focus on the capacity of such an information processing system. Given a level of accuracy guarantee, we ask how many experts are needed in order to stabilize the system, and through what inspection architecture. Our main result provides an adaptive inspection policy that is asymptotically optimal in the following sense: the ratio between the required number of experts under our policy and the theoretical optimal converges to one, as the probability of error in label recovery tends to zero

Implementation of a Hardware/Software Platform for Real-Timedata-Intensive Applications in Hazardous Environments

Real-Time Technology and Applications Symposium. Brookline, MA, USA, 10-12 Oct. 1996In real-time data-intensive applications, the simultaneous achievement of the required performance and determinism is a difficult issue to address, mainly due to the time needed to perform I/O operations, which is more significant than the CPU processing time. Additional features need to be considered if these applications are intended to perform in hostile environments. In this paper, we address the implementation of a hardware/software platform designed to acquire, transfer, process and store massive amounts of information at sustained rates of several MBytes/sec, capable of supporting real-time applications with stringent throughput requirements under hazardous environmental conditions. A real-world system devoted to the inspection of nuclear power plants is presented as an illustrative examplePublicad

Airport Noise Regulation, Airline Service Quality, and Social Welfare

This paper explores the impact of airport noise regulation on airline service quality and airfares. It also characterizes the socially optimal stringency of noise limits, taking both noise damage and the various costs borne by airlines and their passengers into account. The analysis also investigates the effect of noise taxes, as well as the optimal level level of such taxes. Along with the companion paper by Girvin (2006a), this work represents the first complete theoretical investigation into the economics of airport noise regulation using a model where the interests of the key relevant stakeholders are captured.Airport noise; Flight frequency: Airfares

Multidisciplinary systems optimization by linear decomposition

In a typical design process major decisions are made sequentially. An illustrated example is given for an aircraft design in which the aerodynamic shape is usually decided first, then the airframe is sized for strength and so forth. An analogous sequence could be laid out for any other major industrial product, for instance, a ship. The loops in the discipline boxes symbolize iterative design improvements carried out within the confines of a single engineering discipline, or subsystem. The loops spanning several boxes depict multidisciplinary design improvement iterations. Omitted for graphical simplicity is parallelism of the disciplinary subtasks. The parallelism is important in order to develop a broad workfront necessary to shorten the design time. If all the intradisciplinary and interdisciplinary iterations were carried out to convergence, the process could yield a numerically optimal design. However, it usually stops short of that because of time and money limitations. This is especially true for the interdisciplinary iterations

Airport Noise Regulation, Airline Service Quality, and Social Welfare

This paper explores the impact of airport noise regulation on airline service quality and airfares. It also characterizes the socially optimal stringency of noise limits, taking both noise damage and the various costs borne by airlines and their passengers into account. The analysis also investigates the effect of noise taxes, as well as the optimal level of such taxes. Along with the companion paper by Girvin (2006a), this work represents the first complete theoretical investigation into the economics of airport noise regulation using a model where the interests of the key relevant stakeholders are captured.airport, airport noise, airport noise regulation, airline, airline service quality, noise taxes, transportation

Active sequential hypothesis testing

Consider a decision maker who is responsible to dynamically collect observations so as to enhance his information about an underlying phenomena of interest in a speedy manner while accounting for the penalty of wrong declaration. Due to the sequential nature of the problem, the decision maker relies on his current information state to adaptively select the most ``informative'' sensing action among the available ones. In this paper, using results in dynamic programming, lower bounds for the optimal total cost are established. The lower bounds characterize the fundamental limits on the maximum achievable information acquisition rate and the optimal reliability. Moreover, upper bounds are obtained via an analysis of two heuristic policies for dynamic selection of actions. It is shown that the first proposed heuristic achieves asymptotic optimality, where the notion of asymptotic optimality, due to Chernoff, implies that the relative difference between the total cost achieved by the proposed policy and the optimal total cost approaches zero as the penalty of wrong declaration (hence the number of collected samples) increases. The second heuristic is shown to achieve asymptotic optimality only in a limited setting such as the problem of a noisy dynamic search. However, by considering the dependency on the number of hypotheses, under a technical condition, this second heuristic is shown to achieve a nonzero information acquisition rate, establishing a lower bound for the maximum achievable rate and error exponent. In the case of a noisy dynamic search with size-independent noise, the obtained nonzero rate and error exponent are shown to be maximum.Comment: Published in at http://dx.doi.org/10.1214/13-AOS1144 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

How Concurrent Engineering Reconfigures Process Engineering Activity - The Case of the Chemical Industry

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In silico evolution of diauxic growth

The glucose effect is a well known phenomenon whereby cells, when presented with two different nutrients, show a diauxic growth pattern, i.e. an episode of exponential growth followed by a lag phase of reduced growth followed by a second phase of exponential growth. Diauxic growth is usually thought of as a an adaptation to maximise biomass production in an environment offering two or more carbon sources. While diauxic growth has been studied widely both experimentally and theoretically, the hypothesis that diauxic growth is a strategy to increase overall growth has remained an unconfirmed conjecture. Here, we present a minimal mathematical model of a bacterial nutrient uptake system and metabolism. We subject this model to artificial evolution to test under which conditions diauxic growth evolves. As a result, we find that, indeed, sequential uptake of nutrients emerges if there is competition for nutrients and the metabolism/uptake system is capacity limited. However, we also find that diauxic growth is a secondary effect of this system and that the speed-up of nutrient uptake is a much larger effect. Notably, this speed-up of nutrient uptake coincides with an overall reduction of efficiency. Our two main conclusions are: (i) Cells competing for the same nutrients evolve rapid but inefficient growth dynamics. (ii) In the deterministic models we use here no substantial lag-phase evolves. This suggests that the lag-phase is a consequence of stochastic gene expression