Non-deterministic exponential time has two-prover interactive protocols

We determine the exact power of two-prover interactive proof systems introduced by Ben-Or, Goldwasser, Kilian, and Wigderson (1988). In this system, two all-powerful noncommunicating provers convince a randomizing polynomial time verifier in polynomial time that the inputx belongs to the languageL. We show that the class of languages having tow-prover interactive proof systems is nondeterministic exponential time.We also show that to prove membership in languages inEXP, the honest provers need the power ofEXP only.The first part of the proof of the main result extends recent techniques of polynomial extrapolation used in the single prover case by Lund, Fortnow, Karloff, Nisan, and Shamir.The second part is averification scheme for multilinearity of a function in several variables held by an oracle and can be viewed as an independent result onprogram verification. Its proof rests on combinatorial techniques employing a simple isoperimetric inequality for certain graphs:     

ON THE USE OF BUFFER INVENTORIES TO MINIMIZE COSTS WITH AN UNRELIABLE MACHINE

In this paper, we discuss the problem of quality control with an unreliable machine which produces defects at a rate of Λ₀, per unit when in-control and a rate of Lambda; ₁, when out-of-control (where Λ₁ Λ ₀). Every h time periods, we sample n units, count the number of defects, and (using a process based on a Shewart c-chart) test the hypothesis that the machine is in control by comparing the total number of defects to an upper control limit (UCL). More important, we introduce the concept that a buffer inventory which immediately follows the unreliable machine may reduce expected total costs. This buffer serves to delay the movement of items from the unreliable machine to the next stage of the production process. In this way, we can isolate and repair most defective items before they are embedded in a product downstream or sold to customers where repair is more costly. To search for the optimal control policy, we find bounds for n, h, and UCL; given values for these variables, we show how the optimal buffer size can be determined directly. Numerical results illustrate the magnitude of potential savings.     

Catalytic combustion over platinum group catalysts: fuel-lean versus fuel-rich operation

Performance data are presented for methane oxidation on alumina-supported Pd, Pt, and Rh catalysts under both fuel-rich and fuel-lean conditions. Catalyst activity was measured in a micro-scale isothermal reactor at temperatures between 300 and 800 °C. Non-isothermal (near adiabatic) temperature and reaction data were obtained in a full-length (non-differential) sub-scale reactor operating at high pressure (0.9 MPa) and constant inlet temperature, simulating actual reactor operation in catalytic combustion applications.

Under fuel-lean conditions, Pd catalyst was the most active, although deactivation occurred above 650 °C, with reactivation upon cooling. Rh catalyst also deactivated above 750 °C, but did not reactivate. Pt catalyst was active above 600 °C. Fuel-lean reaction products were CO₂ and H₂O for all three catalysts.

The same catalysts tested under fuel-rich conditions demonstrated much higher activity. In addition, a ‘lightoff’ temperature was found (between 450 and 600 °C), where a stepwise increase in reaction rate was observed. Following ‘lightoff’ partial oxidation products (CO, H₂) appeared in the mixture, and their concentration increased with increasing temperature. All three catalysts exhibited this behavior.

High-pressure (0.9 MPa) sub-scale reactor and combustor data are shown, demonstrating the benefits of fuel-rich operation over the catalyst for ultra-low emissions combustion.     

Quantifying the genericness of trademarks using natural language processing: an introduction with suggested metrics

If a trademark (“mark”) becomes a generic term, it may be cancelled under trademark law, a process known as genericide. Typically, in genericide cases, consumer surveys are brought into evidence to establish a mark’s semantic status as generic or distinctive. Some drawbacks of surveys are cost, delay, small sample size, lack of reproducibility, and observer bias. Today, however, much discourse involving marks is online. As a potential complement to consumer surveys, therefore, we explore an artificial intelligence approach based chiefly on word embeddings: mathematical models of meaning based on distributional semantics that can be trained on texts selected for jurisdictional and temporal relevance. After identifying two main factors in mark genericness, we first offer a simple screening metric based on the ngram frequency of uncapitalized variants of a mark. We then add two word embedding metrics: one addressing contextual similarity of uncapitalized variants, and one comparing the neighborhood density of marks and known generic terms in a category. For clarity and validation, we illustrate our metrics with examples of genericized, somewhat generic, and distinctive marks such as, respectively, DUMPSTER, DOBRO, and ROLEX.

     

The privileged sensing framework: A principled approach to improved human-autonomy integration

ABSTRACT

A primary goal for human-autonomy integration (HAI) is to balance the strengths of human and autonomy in order to achieve performance objectives more efficiently and robustly than either the human or autonomous agents would independently. This paper proposes the Privileged Sensing Framework (PSF) as a novel approach to HAI. This approach is based on the concept of dynamically ‘privileging’ information during the process of integration by dynamically bestowing special rights based on the characteristics of each individual agent, the task context, and the performance goals. The proposed framework is tested through a series of simulation experiments that provide a clear demonstration of increased accuracy and throughput of human-autonomy performance. These proof-of-concept simulations provide initial evidence of the utility of the PSF. Continued development of this approach has the potential to revolutionise capabilities of multi-agent cooperative teams across a broad range of applications.     

Gaming Prediction Markets: Equilibrium Strategies with a Market Maker

We study the equilibrium behavior of informed traders interacting with market scoring rule (MSR) market makers. One attractive feature of MSR is that it is myopically incentive compatible: it is optimal for traders to report their true beliefs about the likelihood of an event outcome provided that they ignore the impact of their reports on the profit they might garner from future trades. In this paper, we analyze non-myopic strategies and examine what information structures lead to truthful betting by traders. Specifically, we analyze the behavior of risk-neutral traders with incomplete information playing in a dynamic game. We consider finite-stage and infinite-stage game models. For each model, we study the logarithmic market scoring rule (LMSR) with two different information structures: conditionally independent signals and (unconditionally) independent signals. In the finite-stage model, when signals of traders are independent conditional on the state of the world, truthful betting is a Perfect Bayesian Equilibrium (PBE). Moreover, it is the unique Weak Perfect Bayesian Equilibrium (WPBE) of the game. In contrast, when signals of traders are unconditionally independent, truthful betting is not a WPBE. In the infinite-stage model with unconditionally independent signals, there does not exist an equilibrium in which all information is revealed in a finite amount of time. We propose a simple discounted market scoring rule that reduces the opportunity for bluffing strategies. We show that in any WPBE for the infinite-stage market with discounting, the market price converges to the fully-revealing price, and the rate of convergence can be bounded in terms of the discounting parameter. When signals are conditionally independent, truthful betting is the unique WPBE for the infinite-stage market with and without discounting.     

Extracting Kolmogorov complexity with applications to dimension zero-one laws

We apply results on extracting randomness from independent sources to “extract” Kolmogorov complexity. For any α,?>0, given a string x with K(x)>α|x|, we show how to use a constant number of advice bits to efficiently compute another string y, |y|=Ω(|x|), with K(y)>(1-?)|y|. This result holds for both unbounded and space-bounded Kolmogorov complexity.We use the extraction procedure for space-bounded complexity to establish zero-one laws for the strong dimensions of complexity classes within ESPACE. The unbounded extraction procedure yields a zero-one law for the constructive strong dimensions of Turing degrees.     

Micro-engineered first wall tungsten armor for high average power laser fusion energy systems

The high average power laser program is developing an inertial fusion energy demonstration power reactor with a solid first wall chamber. The first wall (FW) will be subject to high energy density radiation and high doses of high energy helium implantation. Tungsten has been identified as the candidate material for a FW armor. The fundamental concern is long term thermo-mechanical survivability of the armor against the effects of high temperature pulsed operation and exfoliation due to the retention of implanted helium. Even if a solid tungsten armor coating would survive the high temperature cyclic operation with minimal failure, the high helium implantation and retention would result in unacceptable material loss rates. Micro-engineered materials, such as castellated structures, plasma sprayed nano-porous coatings and refractory foams are suggested as a first wall armor material to address these fundamental concerns. A micro-engineered FW armor would have to be designed with specific geometric features that tolerate high cyclic heating loads and recycle most of the implanted helium without any significant failure. Micro-engineered materials are briefly reviewed. In particular, plasma-sprayed nano-porous tungsten and tungsten foams are assessed for their potential to accommodate inertial fusion specific loads. Tests show that nano-porous plasma spray coatings can be manufactured with high permeability to helium gas, while retaining relatively high thermal conductivities. Tungsten foams where shown to be able to overcome thermo-mechanical loads by cell rotation and deformation. Helium implantation tests have shown, that pulsed implantation and heating releases significant levels of implanted helium. Helium implantation and release from tungsten was modeled using an expanded kinetic rate theory, to include the effects of pulsed implantations and thermal cycles. Although, significant challenges remain micro-engineered materials are shown to constitute potential candidate FW armor materials.