Representing and applying knowledge for argumentation in a social context

The concept of argumentation in AI is based almost exclusively on the use of formal, abstract representations. Despite their appealing computational properties, these abstractions become increasingly divorced from their real world counterparts, and, crucially, lose the ability to express the rich gamut of natural argument forms required for creating effective text. In this paper, the demands that socially situated argumentation places on knowledge representation are explored, and the various problems with existing formalisations are discussed. Insights from argumentation theory and social psychology are then adduced as key contributions to a notion of social context which is both computationally tractable and suitably expressive for handling the complexities of argumentation found in natural language.     

Automatic ARIMA time series modeling for adaptive I/O prefetching

Inadequate I/O performance remains a major challenge in using high-end computing systems effectively. To address this problem, we present TsModeler, an automatic time series modeling and prediction framework for adaptive I/O prefetching that uses ARIMA time series models to predict the temporal patterns of I/O requests. These online pattern analysis techniques and cutoff indicators for autocorrelation patterns enable multistep online predictions suitable for multiblock prefetching. This work also combines time series predictions with spatial Markov model predictions to determine when, what, and how many blocks to prefetch. Experimental results show reductions in execution time compared to the standard Linux file system across various hardware configurations.     

Solution of a Well-Field Design Problem with Implicit Filtering

Problems involving the management of groundwater resources occur routinely, and management decisions based upon optimization approaches offer the potential to save substantial amounts of money. However, this class of application is notoriously difficult to solve due to non-convex objective functions with multiple local minima and both nonlinear models and nonlinear constraints. We solve a subset of community test problems from this application field using MODFLOW, a standard groundwater flow model, and IFFCO, an implicit filtering algorithm that was designed to solve problems similar to those of focus in this work. While sampling methods have received only scant attention in the groundwater optimization literature, we show encouraging results that suggest they are deserving of more widespread consideration for this class of problems. In keeping with our objectives for the community problems, we have packaged the approaches used in this work to facilitate additional work on these problems by others and the application of implicit filtering to other problems in this field. We provide the data for our formulation and solution on the web.     

The effects of fuel variability on the electrical performance and durability of a solid oxide fuel cell operating on biohythane

Biohythane is typically composed of 60/30/10 vol% CH₄/CO₂/H₂ and can be produced via two-stage anaerobic digestion of renewable and low carbon biomass with much greater efficiency compared with CH₄/CO₂ biogas. This work investigates the effects of fuel variability on the electrical performance and fuel processing of a commercially available anode supported solid oxide fuel cell (SOFC) operating on biohythane mixtures at 750 °C. Cell electrical performance was characterised using current-voltage curves and electrochemical impedance spectroscopy. Fuel processing was characterised using quadrupole mass spectroscopy. It is shown that when H₂/CO₂ is blended with CH₄ to make biohythane, the SOFC efficiency is significantly increased, high SOFC durability is achieved, and there are considerable savings in CH₄ consumption. Enhanced electrical performance was due to the additional presence of H₂ and promotion of CH₄ dry reforming, the reverse Boudouard and reverse water-gas shift reactions. These processes alleviated carbon deposition and promoted electrochemical oxidation of H₂ as the primary power production pathway. Substituting 50 vol% CH₄ with 25/75 vol% H₂/CO₂ was shown to increase cell power output by 81.6% at 0.8 V compared with pure CH₄. This corresponded to a 3.4-fold increase in the overall energy conversion efficiency and a 72% decrease in CH₄ consumption. A 260 h durability test demonstrated very high cell durability when operating on a typical 60/30/10 vol% CH₄/CO₂/H₂ biohythane mixture under high fuel utilisation due to inhibition of carbon deposition. Overall, this work suggests that decarbonising gas grids by substituting natural gas with renewably produced H₂/CO₂ mixtures (rather than pure H₂ derived from fossil fuels), and utilising in SOFC technology, gives considerable gains in energy conversion efficiency and carbon emissions savings.     

Removing peanut allergens by tannic acid

Tannic acid (TA) forms insoluble complexes with proteins. The aims here were to remove major peanut allergens as insoluble TA complexes and determine if they would dissociate and release the allergens at pH 2 and 8 (gut pH). Release of the allergens in the gut could lead to absorption and consequently an allergic reaction. TA (0.25, 0.5, 1, and 2 mg/ml) was added to a peanut butter extract (5 mg/ml; pH 7.2), stirred, and centrifuged. The precipitates were then suspended in buffer at pH 2, centrifuged, re-suspended at pH 8, and centrifuged. Supernatants from each step were analysed by SDS–PAGE, ELISA, and Western blots. The effect of NaCl (1 M) on complexes was also determined. Results showed that complexes formed at a TA concentration >0.5 mg/ml did not release major peanut allergens at pH 2 and 8, regardless of 1 M NaCl being present or not. IgE binding of the extracts was reduced substantially, especially at a TA concentration of 1–2 mg/ml. Animal or clinical studies are still needed before TA can find an application in the development of low-allergen peanut products/beverages or the removal of peanut allergens due to accidental ingestion.     

Closed‐Loop Transmit Diversity Techniques for Small Wireless Terminals and Their Performance Assessment in a Flat Fading Channel

Closed‐loop transmit diversity is considered an important technique for improving the link budget in the third generation and future wireless communication standards. This paper proposes several transmit diversity algorithms suitable for small wireless terminals and presents performance assessment in terms of average signal‐to‐noise ratio (SNR) and outage improvement, convergence, and complexity of operations. The algorithms presented herein are verified using data from measured indoor channels with variable antenna spacing and the results explained using measured radiation patterns for a two‐element array. It is shown that for a two‐element array, the best among the proposed techniques provides SNR improvement of about 3 dB in a tightly spaced array (inter‐element spacing of 0.1 wavelength at 2 GHz) typical of small wireless devices. Additionally, these techniques are shown to perform significantly better than a single antenna device in an indoor channel considering realistic values of latency and propagation errors.     

A sub-space method to detect multiple wireless microphone signals in TV band white space

The main hurdle in the realization of dynamic spectrum access systems from the physical layer perspective is the reliable sensing of low power licensed users. One such scenario shows up in the unlicensed use of the TV bands where the TV band devices are required to sense extremely low power wireless microphones (WMs). The lack of technical standards among various wireless manufacturers and the resemblance of certain WM signals to narrow-band interference signals, such as spurious emissions, further aggravate the problem. Due to these uncertainties, it is extremely difficult to abstract the features of WM signals and hence develop robust sensing algorithms. To partly counter these challenges, we develop a two-stage sub-space algorithm that detects multiple narrow-band analog frequency-modulated signals generated by WMs. The performance of the algorithm is verified by using the real WM signals experimentally captured under low SNR conditions. The problem of differentiating between the WM and other narrow-band signals is left as future work.     

Impact Sensitivity Reduction Via Exo-Electron Control

Many materials, upon fracturing, emit electrons (exo-electrons) by a process called fracto-emission. For a substance or mixture that can deflagrate or detonate upon impact or friction, these exo-electrons may contribute to the initiation of deflagration or detonation. Some materials, such as p-type semiconductors, can absorb exo-electrons and, as used as additives, can reduce the impact or friction sensitivity of propellants or explosives. It was found that the addition of 1% p-type silicon powder did decrease the impact sensitivity of a propellant consisting of ammonium perchlorate in a polybutadiene matrix, but did not reduce the impact sensitivity of powdered cyclotetramethylenetetranitramine (HMX), cyclotrimethylenetrinitramine (RDX), and pentaerythritol trinitrate (PETN).     

Impact failure of poly(methyl methacrylate)

Damage development during instrumented falling weight impact (IFWIM) testing of poly(methyl methacrylate) (PMMA) is recorded using short pulse photography. The first visible damage is cracking on application of the peak force. Finite element analysis predicts the deformation and state of stress throughout the specimen until the first point of failure is reached. A variation in the specimen geometry produces a significant change in initial failure energy, while the maximum tensile stress is approximately constant. The proposed failure criterion is the attainment of a critical time-dependent value of tensile stress. © 1992 John Wiley & Sons, Inc.