International Working Group on Assurance Cases (for Security)

Critical systems are aptly named - from electric power to water and gas to the telephone system and the Internet, they're all critical to some aspect of our daily lives. We're a networked society and as such, it's important to both know whether critical systems are trustworthy and be able to communicate, review, and debate the level of trust achieved in them. In the safety domain, explicit safety cases are increasingly required by law, regulations, and standards. In this article, we outline what a small, international group of experts, spanning various disciplines in safety, security, reliability, and critical infrastructure, been doing with the International Working Group on Assurance Cases (for Security), what we hope to achieve, and where we go next.     

The Effect of Moisture Content in Epoxy Film Adhesives on their Performance. II. T-Peel and 105°C Lap Shear Strength

The benefits of adhesively bonded structures are well known. However, the most significant factor limiting the extensive application of metal bonding in primary aerospace structures is the prevailing lack of confidence in its long term durability under hostile environmental conditions.^1,2     

Single-Phase Permanent-Magnet Motor Analysis

A unified theoretical approach is presented for the calculation of the performance of the single-phase capacitor-start permanent-magnet (PM) ac line-start motor. The earlier work of Chang and of Finch and Lawrenson on capacitor reluctance motors is extended. As far as possible, a common set of reference frame transformations for steady-state, transient, and asynchronous performance is also provided, permitting the use of all the theory developed for the analysis of the balanced polyphase PM motor. A new approximate technique is given for estimating the average asynchronous torque/speed curve from computed acceleration curves.     

A new approach to model reference adaptive control

In classical model reference adaptive control, the goal is to design a controller to make the closed-loop system act like a prespecified reference model in the face of significant plant uncertainty. Typically, the controller consists of an identifier (or tuner) which is used to adjust the parameters of a linear time-invariant (LTI) compensator, and under suitable assumptions on the plant model uncertainty it is proven that asymptotic matching is achieved. However, the controller is typically highly nonlinear, and the closed loop system can exhibit undesirable behavior, such as large transients or a large control signal, especially if the initial parameter estimates are poor. Furthermore, its ability to tolerate time-varying parameters is typically limited. Here, we propose an alternative approach. Rather than estimating the plant or compensator parameters, instead we estimate what the control signal would be if the plant parameters and plant state were known and the "ideal LTI compensator" were applied. We end up with a linear periodic controller. Our assumptions are reasonably natural extensions of the classical ones to the time-varying setting; we allow rapid parameter variations, although we add a compactness requirement. We prove that we can obtain arbitrarily good tracking, explore the benefits and limitations of the approach, and provide a simulation study.     

A distributed adverse drug reaction detection system using intelligent agents with a fuzzy recognition‐primed decision model

Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is highly desirable. Nevertheless, current postmarketing surveillance methods largely rely on spontaneous reports that suffer from serious underreporting, latency, and inconsistent reporting. Thus these methods are not ideal for rapidly identifying rare ADRs. The multiagent systems paradigm is an emerging and effective approach to tackling distributed problems, especially when data sources and knowledge are geographically located in different places and coordination and collaboration are necessary for decision making. In this article, we propose an active, multiagent framework for early detection of ADRs by utilizing electronic patient data distributed across many different sources and locations. In this framework, intelligent agents assist a team of experts based on the well‐known human decision‐making model called Recognition‐Primed Decision (RPD). We generalize the RPD model to a fuzzy RPD model and utilize fuzzy logic technology to not only represent, interpret, and compute imprecise and subjective cues that are commonly encountered in the ADR problem but also to retrieve prior experiences by evaluating the extent of matching between the current situation and a past experience. We describe our preliminary multiagent system design and illustrate its potential benefits for assisting expert teams in early detection of previously unknown ADRs. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 827–845, 2007.     

Catalytic effects during cellulose liquefaction

Cellulose can be totally liquefied by heating to 350 °C in the presence of an aqueous phenolic solvent containing a catalyst. The main products are light aromatic hydrocarbons, benzofurans, heavier aromatic hydrocarbons such as substituted indanes and tetralin, and xanthenes. The variation of product distribution with catalyst was examined and it was found that in aqueous phenol, xanthene formation was enhanced by acidity. By substituting guaiacol for phenol, it was determined that most benzofuran formation involved the phenol solvent molecules, although a small proportion did not. This benzofuran may have arises from phenol generated from cellulose, the incorporation of phenol in the products being enhanced through a cage effect.