Abstract: The main aim of this study was to examine whether
people understand indicative conditionals on the basis of syntactic
factors or on the basis of subjective conditional probability. The
second aim was to investigate whether the conditional probability of
q given p depends on the antecedent and consequent sizes or derives
from inductive processes leading to establish a link of plausible cooccurrence
between events semantically or experientially associated.
These competing hypotheses have been tested through a 3 x 2 x 2 x 2
mixed design involving the manipulation of four variables: type of
instructions (“Consider the following statement to be true", “Read the
following statement" and condition with no conditional statement);
antecedent size (high/low); consequent size (high/low); statement
probability (high/low). The first variable was between-subjects, the
others were within-subjects. The inferences investigated were Modus
Ponens and Modus Tollens. Ninety undergraduates of the Second
University of Naples, without any prior knowledge of logic or
conditional reasoning, participated in this study.
Results suggest that people understand conditionals in a syntactic
way rather than in a probabilistic way, even though the perception of
the conditional probability of q given p is at least partially involved in
the conditionals- comprehension. They also showed that, in presence
of a conditional syllogism, inferences are not affected by the
antecedent or consequent sizes. From a theoretical point of view these
findings suggest that it would be inappropriate to abandon the idea
that conditionals are naturally understood in a syntactic way for the
idea that they are understood in a probabilistic way.
Abstract: Bridges are one of the main components of
transportation networks. They should be functional before and after
earthquake for emergency services. Therefore we need to assess
seismic performance of bridges under different seismic loadings.
Fragility curve is one of the popular tools in seismic evaluations. The
fragility curves are conditional probability statements, which give the
probability of a bridge reaching or exceeding a particular damage
level for a given intensity level. In this study, the seismic
performance of a two-span simply supported concrete bridge is
assessed. Due to usual lack of empirical data, the analytical fragility
curve was developed by results of the dynamic analysis of bridge
subjected to the different time histories in near-fault area.
Abstract: In large Internet backbones, Service Providers
typically have to explicitly manage the traffic flows in order to
optimize the use of network resources. This process is often referred
to as Traffic Engineering (TE). Common objectives of traffic
engineering include balance traffic distribution across the network
and avoiding congestion hot spots. Raj P H and SVK Raja designed
the Bayesian network approach to identify congestion hors pots in
MPLS. In this approach for every node in the network the
Conditional Probability Distribution (CPD) is specified. Based on
the CPD the congestion hot spots are identified. Then the traffic can
be distributed so that no link in the network is either over utilized or
under utilized. Although the Bayesian network approach has been
implemented in operational networks, it has a number of well known
scaling issues.
This paper proposes a new approach, which we call the Pragati
(means Progress) Node Popularity (PNP) approach to identify the
congestion hot spots with the network topology alone. In the new
Pragati Node Popularity approach, IP routing runs natively over the
physical topology rather than depending on the CPD of each node as
in Bayesian network. We first illustrate our approach with a simple
network, then present a formal analysis of the Pragati Node
Popularity approach. Our PNP approach shows that for any given
network of Bayesian approach, it exactly identifies the same result
with minimum efforts. We further extend the result to a more
generic one: for any network topology and even though the network
is loopy. A theoretical insight of our result is that the optimal routing
is always shortest path routing with respect to some considerations of
hot spots in the networks.
Abstract: Seemingly simple probabilities in the m-player game bingo have never been calculated. These probabilities include expected game length and the expected number of winners on a given turn. The difficulty in probabilistic analysis lies in the subtle interdependence among the m-many bingo game cards in play. In this paper, the game i got it!, a bingo variant, is considered. This variation provides enough weakening of the inter-player dependence to allow probabilistic analysis not possible for traditional bingo. The probability of winning in exactly k turns is calculated for a one-player game. Given a game of m-many players, the expected game length and tie probability are calculated. With these calculations, the game-s interesting payout scheme is considered.