Ranking of rubber vulcanizates used as seals based on effect of accelerated aging

Technical properties such as hardness, tensile strength, ultimate elongation, and rebound resilience are popular in quality control, but the trend in these properties shows a generalized picture of the structure–property relations. Test specimens were aged in hot air by systematically varying the time and temperature from 24 to 96 h at 70 to 100°C. For an effective comparison the observed values were plotted as a function of time, temperature, and formulations. The data thus obtained were correlated with shelf‐aging in particular cases, and it was observed that aging at 100°C for 24 h could be used for such formulations. A “sulfur donor” system cured nitrile‐butadiene rubber (NBR) vulcanizate and an ethylene‐propylene‐diene (EPDM) vulcanizate showed the best retention of properties. Although the SEM micrograph of the NBR was in agreement with this observation, the EPDM was not. © 2000 John Wiley & Sons, Inc. J Appl Polym Sci 78: 2500–2510, 2000     

A Logical Formulation of Probabilistic Spatial Databases

There are numerous applications where there: is uncertainty over space and time. Examples of such uncertainty arise in vehicle tracking systems where we are not always sure where a vehicle is now (or may be in the future), and cell and satellite phone applications where we are not sure exactly where a phone may be, and so on. In this paper, we propose the concept of a Spatial Probabilistic Temporal (SPOT) database that contains statements of the form "Object O is in spatial region R at some time / with some probability in the interval [L, U]." We define the syntax and a declarative semantics for SPOT databases based on a mix of logic and linear programming, as well as query algebra. We show alternative implementations of some of these query algebra operators when the SPOT database has a disjoint/less property. Though the declarative semantics of SPOT databases is rooted in linear programming, we have found very efficient algorithms that do not use linear programming methods. We report on experiments we have conducted that show that the system scales to large numbers of SPOT atoms, as well as to fairly fine temporal and spatial granularity.     

Improving Performance of Heterogeneous Agents

Agents provide services not only to humans users but also to agents in one or more multiagent systems. When agents are confronted with multiple tasks to perform (or requests to satisfy), the agent can reduce load on itself by attempting to take advantage of commonalities between the tasks that need to be performed. In this paper, we develop a logical theory by which such “heavily loaded” agents can merge commonalities amongst such tasks. In our framework, agents can be built on top of legacy codebases. We propose a logical formalism called invariants using which agent developers may specify known commonalities between tasks – after this, we propose a sound and complete mechanism to derive all possible derived commonalities. An obvious A ^*-based algorithm may be used to merge a set of tasks in a way that minimised expected execution cost. Unfortunately the execution time of this algorithm is prohibitive, even when only 10 tasks need to be merged, thus making it unusable in practice. We develop heuristic algorithms for this problem that take much less time to execute and produce almost as good ways of merging tasks.     

A Petri net model for reasoning in the presence of inconsistency

Petri nets provide a promising framework for executing queries to logic programs. Petri net models for query processing in logic programming were initially developed by T. Murata and D. Zhang (IEEE Trans. Software Eng., vol.14, no.4, p.481-97, 1988). It is shown how this framework can be extended to be applicable to reasoning in the presence of inconsistency. This yields a Petri net model of programs that be inconsistent in classical logic. This is interesting because large expert systems may often contain inconsistent information. The Petri net method proposed suggests a robust way of preventing inconsistency from infecting a system and rendering it useless     

Focused most probable world computations in probabilistic logic programs

The “Most Probable World” (MPW) problem in probabilistic logic programming (PLPs) is that of finding a possible world with the highest probability. Past work has shown that this problem is computationally intractable and involves solving exponentially many linear programs, each of which is of exponential size. In this paper, we study what happens when the user focuses his interest on a set of atoms in such a PLP. We show that we can significantly reduce the number of worlds to be considered by defining a “reduced” linear program whose solution is in one-one correspondence with the exact solution to the MPW problem. However, the problem is still intractable. We develop a Monte Carlo sampling approach that enables us to build a quick approximation of the reduced linear program that allows us to estimate (inexactly) the solution to the MPW problem. We show experimentally that our approach works well in practice, scaling well to problems where the exact solution is intractable to compute.     

Optimal models of disjunctive logic programs: semantics, complexity, and computation

Almost all semantics for logic programs with negation identify a set, SEM(P), of models of program P, as the intended semantics of P, and any model M in this class is considered a possible meaning of P with regard to the semantics the user has in mind. Thus, for example, in the case of stable models [M. Gelfond et al., (1988)], choice models [D. Sacca et al., (1990)], answer sets [M. Gelfond et al., (1991)], etc., different possible models correspond to different ways of "completing" the incomplete information in the logic program. However, different end-users may have different ideas on which of these different models in SEM(P) is a reasonable one from their point of view. For instance, given SEM(P), user U/sub 1/ may prefer model M/sub 1//spl isin/SEM(P) to model M/sub 2//spl isin/SEM(P) based on some evaluation criterion that she has. We develop a logic program semantics based on optimal models. This semantics does not add yet another semantics to the logic programming arena - it takes as input an existing semantics SEM(P) and a user-specified objective function Obj, and yields a new semantics Opt(P)_/spl sube/ SEM(P) that realizes the objective function within the framework of preferred models identified already by SEM(P). Thus, the user who may or may not know anything about logic programming has considerable flexibility in making the system reflect her own objectives by building "on top" of existing semantics known to the system. In addition to the declarative semantics, we provide a complete complexity analysis and algorithms to compute optimal models under varied conditions when SEM(P) is the stable model semantics, the minimal models semantics, and the all-models semantics.     

Presentation planning for distributed VoD systems

A distributed video-on-demand (VoD) system is one where a collection of video data is located at dispersed sites across a computer network. In a single site environment, a local video server retrieves video data from its local storage device. However, in distributed VoD systems, when a customer requests a movie from the local server, the server may need to interact with other servers located across the network. In this paper, we present different types of presentation plans that a local server can construct in order to satisfy a customer request. Informally speaking, a presentation plan is a temporally synchronized sequence of steps that the local server must perform in order to present the requested movie to the customer. This involves obtaining commitments from other video servers, obtaining commitments from the network service provider, as well as making commitments of local resources, while keeping within the limitations of available bandwidth, available buffer, and customer data consumption rates. Furthermore, in order to evaluate the quality of a presentation plan, we introduce two measures of optimality for presentation plans: minimizing wait time for a customer and minimizing access bandwidth which, informally speaking, specifies how much network/disk bandwidth is used. We develop algorithms to compute three different optimal presentation plans that work at a block level, or at a segment level, or with a hybrid mix of the two, and compare their performance through simulation experiments. We have also mathematically proven effects of increased buffer or bandwidth and data replications for presentation plans which had previously been verified experimentally in the literature.