is simple, it can be applied for handling MOSFET circuits analytically and can predict the circuit behavior in the submicro-meter region. Using the model, closed-form expressions are derived for the delay, the short-circuit power, and the transition voltage of CMOS invert-ers. The resultant delay expression

that this latter behavior is important from a modeling perspective, as almost all of our TCP traces contained more time-out events than fast retransmit events. Our measurements demonstrate that our model is able to more accurately predict TCP send rate and is accurate over a wider range of loss rates. We also

Abstract. Sequences of events describing the behavior and actions of users or systems can be collected in several domains. An episode is a collection of events that occur relatively close to each other in a given partial order. We consider the problem of discovering frequently occurring episodes

Abstract Participants' eye movements were recorded as they inspected a semi-realistic visual scene showing a boy, a cake, and various distractor objects. Whilst viewing this scene, they heard sentences such as`the boy will move the cake' or`the boy will eat the cake'. The cake

-value and lazy evaluation), references and assignment, nondeterminism, first-class continuations, and program tracing. The underlying mechanism of our system is monad transformers, a simple form of abstraction for introducing a wide range of computational behaviors, such as state, I/O, continuations

on responses to distant-future events than near-future events. This article explores the implications of construal level theory for temporal changes in evaluation, prediction, and choice. The authors suggest that construal level underlies a broad range of evaluative and behavioral consequences of psychological

ABSTRACT: This paper aims to predict consumer acceptance of e-commerce by proposing a set of key drivers for engaging consumers in on-line transactions. The primary constructs for capturing consumer acceptance of e-commerce are intention to transact and on-line transaction behavior. Following

manual labeling. We show how to detect abnormal behaviors (e.g. taking a wrong bus) by concurrently tracking his activities with a trained and a prior model. Experiments show that our model is able to accurately predict the goals of a person and to recognize situations in which the user performs unknown

Abstract—With climate change as prototype example, this paper analyzes the implications of structural uncertainty for the economics of lowprobability, high-impact catastrophes. Even when updated by Bayesian learning, uncertain structural parameters induce a critical “tail fattening” of posterior-predictive

ABSTRACT Modelling strategies for predicting the potential impacts of climate change on the natural distribution of species have often focused on the characterization of a species' bioclimate envelope. A number of recent critiques have questioned the validity of this approach by pointing