Formal Analysis of Multiparty Contract Signing

We analyze the multiparty contract-signing protocols of Garay and MacKenzie (GM) and of Baum and Waidner (BW). We use a finite-state tool, Mocha, which allows specification of protocol properties in a branching-time temporal logic with game semantics. While our analysis does not reveal any errors in the BW protocol, in the GM protocol we discover serious problems with fairness for four signers and an oversight regarding abuse-freeness for three signers. We propose a complete revision of the GM subprotocols in order to restore fairness.     

Data structures for symbolic multi-valued model-checking

Multi-valued logics provide an interesting alternative to classical boolean logic for modeling and reasoning about systems. Such logics can be used for reasoning about partially-specified systems, effectively encode vacuity detection and query-checking problems, help in detecting inconsistencies, and many others.In our earlier work, we identified a useful family of multi-valued logics: those specified over finite distributive lattices where negation preserves involution, i.e., for every element a of the logic. Such structures are called quasi-boolean algebras, and model-checking over these not only extends the domain of applicability of automated reasoning to new problems, but can also speed up solutions to some classical verification problems.Symbolic model-checking over quasi-boolean algebras can be cast in terms of operations over multi-valued sets: sets whose membership functions are multi-valued. In this paper, we propose and empirically evaluate several choices for implementing multi-valued sets with decision diagrams. In particular, we describe two major approaches: (1) representing the multi-valued membership function canonically, using MDDs or ADDs; (2) representing multi-valued sets as a collection of classical sets, using a vector of either MBTDDs or BDDs. The naive implementation of (2) includes having a classical set for each value of the algebra. We exploit a result of lattice theory to reduce the number of such sets that need to be represented.The major contribution of this paper is the evaluation of the different implementations of multi-valued sets, done via a series of experiments and using several case studies.

Augmenting interaction and cognition using agent architectures and technology inspired by psychology and social worlds

Intelligent agents can play a pivotal role in providing both software systems and augmented interfaces, to individual users from all walks of life, to utilise the Internet 24 h a day, 7 days a week (24×7), including interaction with other users, over both wireless and broadband infrastructures. However, traditional approaches to user modelling are not adequate for this purpose, as they mainly account for a generic, approximate, idealised user. New user models are therefore required to be adaptable for each individual and flexible enough to represent the diversity of all users using information technology. Such models should be able to cover all aspects of an individual’s life—those aspects of most interest to the individual user themselves. This paper describes a novel intelligent agent architecture and methodology both called ShadowBoard, based on a complex user model drawn from analytical psychology. An equally novel software tool, called the DigitalFriend based on ShadowBoard, is also introduced. This paper illustrates how aspects of user cognition can be outsourced, using, for example, an internationalised book price quoting agent. The Locales Framework from Computer Supported Co-operative Work is then used to understand the problematic aspects of interaction involved in complex social spaces, identifying specific needs for technology intervention in such social spaces, and to understand how interactions amongst mobile users with different abilities might be technically assisted in such spaces. In this context, the single user-centred multi-agent technology demonstrated in the DigitalFriend is adapted to a multi-user system dubbed ShadowPlaces. The aim of ShadowPlaces is to outsource some of the interaction necessary, for a group of mobile individuals with different abilities to interact cooperatively and effectively in a social world, supported by wireless networks and backed by broadband Internet services. An overview of the user model, the architecture and methodology (ShadowBoard) and the resulting software tool (the DigitalFriend) is presented, and progress on ShadowPlaces—the multi-user version—is outlined.

Predicting change for individual psychotherapy clients on the basis of their nearest neighbors.

This study extended client-focused research by using the nearest neighbor (NN) approach, a client-specific sampling and prediction strategy derived from research on alpine avalanches. Psychotherapy clients (N = 203) seen in routine practice settings in the United Kingdom completed a battery of intake measures and then completed symptom intensity ratings before each session. Forecasts of each client's rate of change and session-by-session variability were computed on the basis of that client's NNs (n = 10-50 in different comparisons). Alternative forecasts used linear or log-linear slopes and were compared with an alternative prediction strategy. Results showed that the NN approach was superior to the alternative model in predicting rate of change, though the advantage was less clear for predicting variability. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation

The Moderate Resolution Imaging Radiometer (MODIS) is the primary instrument in the NASA Earth Observing System for monitoring the seasonality of global terrestrial vegetation. Estimates of 8-day mean daily gross primary production (GPP) at the 1 km spatial resolution are now operationally produced by the MODIS Land Science Team for the global terrestrial surface using a production efficiency approach. In this study, the 2001 MODIS GPP product was compared with scaled GPP estimates (25 km²) based on ground measurements at two forested sites. The ground-based GPP scaling approach relied on a carbon cycle process model run in a spatially distributed mode. Land cover classification and maximum annual leaf area index, as derived from Landsat ETM+ imagery, were used in model initiation. The model was driven by daily meteorological observations from an eddy covariance flux tower situated at the center of each site. Model simulated GPPs were corroborated with daily GPP estimates from the flux tower. At the hardwood forest site, the MODIS GPP phenology started earlier than was indicated by the scaled GPP, and the summertime GPP from MODIS was generally lower than the scaled GPP values. The fall-off in production at the end of the growing season was similar to the validation data. At the boreal forest site, the GPP phenologies generally agreed because both responded to the strong signal associated with minimum temperature. The midsummer MODIS GPP there was generally higher than the ground-based GPP. The differences between the MODIS GPP products and the ground-based GPPs were driven by differences in the timing of FPAR and the magnitude of light use efficiency as well as by differences in other inputs to the MODIS GPP algorithm—daily incident PAR, minimum temperature, and vapor pressure deficit. Ground-based scaling of GPP has the potential to improve the parameterization of light use efficiency in satellite-based GPP monitoring algorithms.     

Violet

Violet is an easy-to-use theorem prover based on locking resolution, with integrated equality extensions that use term rewriting and Knuth–Bendix completion. Violet participated in the CADE-13 ATP System Competition.     

Boundary cell-based acceleration for volume ray casting

Several effective acceleration techniques for volume rendering offer efficient means to skip over empty space, providing significant speedup without affecting image quality. The effectiveness of such an approach depends on its ability to accurately estimate the object boundary inside a volume with minimal computational overhead. We propose a novel boundary cell-based acceleration technique for ray casting which skips over empty space by accurately calculating the intersection distance for each ray. Very short distance estimation time is achieved by exploiting a projection template to calculate the parallel-projection values of each boundary cell and the coherency of adjacent cells. Since no hardware acceleration is used, the projection procedure can also be efficiently parallelized. Experimental results are provided to demonstrate the performance of our new algorithm.     

The Managerial Implications of Real-Time New Product Development in Financial Services

A review of the various models of New Product Development (NPD) process shows that although different approaches have been proposed, they are in fact all variants on a linear theme: some may include feedback loops, but they all essentially advocate that certain steps precede, or are preceded by, others. An inevitable consequence on the Internet/World Wide Web (WWW or Web) is that such models are no longer applicable. Based on the lessons learned from the development of a new financial service offered via the Internet, we show how such assumptions of linearity need no longer be a constraint. In addition, innovativeness is not related to firm size. But the fact that the Web allows for the real-time development of new financial services based on on-going feedback from potential and current customers raises a new set of managerial issues that have to be tackled. The objective of this paper is to use the context of the recent launch of an innovative financial service product via the Web to explore the managerial changes that are starting to affect the banking industry.     

Goal-driven automation of a deep space communications station: a case study in knowledge engineering for plan generation and execution

Abstract: This paper describes the application of Artificial Intelligence techniques for plan generation, plan execution, and plan monitoring to automate a Deep Space Communication Station. This automation allows a communication station to respond to a set of tracking goals by appropriately reconfiguring the communications hardware and software to provide the requested communications services. In particular this paper describes: (1) the overall automation architecture, (2) the plan generation and execution monitoring AI technologies used and implemented software components, and (3) the knowledge engineering process and effort required for automation. This automation was demonstrated in February 1995, at the DSS13 Antenna Station in Goldstone, CA on a series of Voyager tracks and the technologies demonstrated are being transferred to the operational Deep Space Network stations.     

Placebo Psychotherapies and Nonconscious Learning in the Placebo Effect: Reply to Kirsch (2004).

In this reply, the authors explore several issues raised by I. Kirsch (2004; see record 2004-11156-008) concerning their original article (S. Stewart-Williams & J. Podd, 2004; see record 2004-11156-007), which dealt with the roles of expectancy and classical conditioning in the placebo effect. The only notable disagreement concerns a definitional issue, namely, Stewart-Williams and Podd's claim that the placebo concept can be extended to inert psychotherapies. The authors defend this claim against the criticisms Kirsch raised. In addition, they comment on the suggestion that nonconscious learning processes play only a small role in human placebo effects, arguing that there are theoretical reasons to expect these processes to be more important than has previously been recognized. (PsycINFO Database Record (c) 2010 APA, all rights reserved)