37096144
Operation Propagation in Real-Time Group Editors
Operation propagation refers to the mechanisms and policies used in group editors for the participants to notify each other of their individual editing activities. The timing and granularity of propagation depend on different requirements, such as network bandwidth, session scale, the computational power of the involved sites and the preferences of each user. In this article, we draw on some common design principles in two group editors we have implemented.
17075751
A collaboration specification language
COCA (Collaborative Objects Coordination Architecture) was proposed as a novel means to model and support collaborations over the Internet. Our approach separates coordination policies from user interfaces and the policies are specified in a logic-based language. Over the past year, both the collaboration model and the specification language have been substantially refined and evaluated through our experience in building real-life collaboration systems. This paper presents the design of the specification language and illustrates the main ideas with a few simple design examples. Semantics, implementation, runtime support, and applications are also covered but not as the focus of this paper.
34229141
Spatio-Temporal Association Mining for Un-sampled Sites
In this paper, we investigate interpolation methods that are suitable for discovering spatio-temporal association rules for unsampled points with an initial focus on drought risk management. For drought risk management, raw weather data is collected, converted to various indices, and then mined for association rules. To generate association rules for unsampled sites, interpolation methods can be applied at any stage of this data mining process. We develop and integrate three interpolation models into our association rule mining algorithm. The performance of these three models is experimentally evaluated comparing interpolated association rules with rules discovered from actual raw data.
6720899
Mode selection and mode-dependency modeling for power-aware embedded systems
Among the techniques for system-level power management, it is not currently possible to guarantee timing constraints and have a comprehensive system model supporting multiple components at the same time. We propose a new method for modeling and selecting the power modes for the optimal system-power management of embedded systems under timing and power constraints. First, we not only model the modes and the transitions overhead at the component level, but we also capture the application-imposed relationships among the components by introducing a mode dependency graph at the system level. Second, we propose a mode selection technique, which determines when and how to change mode in these components such that the whole system can meet all power and timing constraints. Our constraint-driven approach is a critical feature for exploring power/performance tradeoffs in power-aware embedded systems. We demonstrate the application of our techniques to a low-power sensor and an autonomous rover.
207726898
Quick response policy with Bayesian information updates
Abstract In this paper we investigate the quick response (QR) policy with different Bayesian models. Under QR policy, a retailer can collect market information from the sales of a pre-seasonal product whose demand is closely related to a seasonal product’s demand. This information is then used to update the distribution for the seasonal product’s demand by a Bayesian approach. We study two information update models: one with the revision of an unknown mean, and the other with the revision of both an unknown mean and an unknown variance. The impacts of the information updates under both models are compared and discussed. We also identify the features of the pre-seasonal product which can bring more significant profit improvement. We conclude that an effective QR policy depends on a precise information update model as well as a selection of an appropriate pre-seasonal product as the observation target.
4669631
A new hierarchical control scheme for a class of cyclically repeated discrete-event systems
We extend the hierarchical control method in (Li et al., 2004) to a more generic setting which involves cyclically repeated processes. A hierarchical architecture is presented to facilitate control synthesis. Specifically, a conservative max-plus model for cyclically repeated processes is introduced on the upper level which provides an optimal online plan list. An enhanced min-plus algebra based scheme on the lower level not only handles unexpected events but, more importantly, addresses cooperation issues between sub-plants and different cycles. A rail traffic example is given to demonstrate the effectiveness of the proposed approach.
16976457
Fuzzy linear programming technique for multiattribute group decision making in fuzzy environments
The aim of this paper is to develop a linear programming technique for multidimensional analysis of preferences in multiattribute group decision making under fuzzy environments. Fuzziness is inherent in decision data and group decision making processes, and linguistic variables are well suited to assessing an alternative on qualitative attributes using fuzzy ratings. A crisp decision matrix can be converted into a fuzzy decision matrix once the decision makers' fuzzy ratings have been extracted. In this paper, we first define group consistency and inconsistency indices based on preferences to alternatives given by decision makers and construct a linear programming decision model based on the distance of each alternative to a fuzzy positive ideal solution which is unknown. Then the fuzzy positive ideal solution and the weights of attributes are estimated using the new decision model based on the group consistency and inconsistency indices. Finally, the distance of each alternative to the fuzzy positive ideal solution is calculated to determine the ranking order of all alternatives. A numerical example is examined to demonstrate the implementation process of the technique.