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81 
On the KratkyPorod model for semiflexible polymers in an external force fieldKilanowski, Philip D. 01 September 2010 (has links)
No description available.

82 
An analytic approach to overland flow as influenced by stochastic surface impressed forces /Merva, George E. January 1967 (has links)
No description available.

83 
Interaction of policy and stochastic effects in an Air Force reparable item process : a model of aircraft engine aging and removal over time /Jones, Eugene Etheridge January 1978 (has links)
No description available.

84 
Theory and applications of intervalaverage sampling /Krausman, Dennis January 1978 (has links)
No description available.

85 
On the existence of random fields compatible with given systems of conditional probabilitiesHamilton, Malcolm D. January 1974 (has links)
No description available.

86 
Local behaviour of solutions of stochastic integral equationsAnderson, William J. January 1969 (has links)
No description available.

87 
Branching Processes in Random EnvironmentsAdam, Jeanne January 1986 (has links)
No description available.

88 
Some stochastic problems in reliability and inventoryHargreaves, Carol Anne 04 1900 (has links)
An attempt is made in this thesis to study some stochastic models of both reliability and
inventory systems with reference to the following aspects:
(i) the confidence limits with the introduction of commoncause failures.
(ii) the Erlangian repair time distributions.
(iii) the product interactions and demand interactions.
(iv) the products are perishable.
This thesis contains six chapters.
Chaper 1 is introductory in nature and gives a review of the literature and the techniques
used in the analysis of reliability systems.
Chapter 2 is a study of component commoncause failure systems. Such failures may
greatly reduce the reliability indices. Two models of such systems (series and parallel)
have been studied in this chapter. The expressions such as, reliability, availability and
expected number of repairs have been obtained. The confidence limits for the steady
state availability of these two systems have also been obtained. A numerical example
illustrates the results.
A 100 (1  a) % confidence limit for the steady state availability of a two unit hot and
warm standby system has been studied, when the failure of an online unit is constant and
the repair time of a failed unit is Erlangian.
The general introduction of various inventory systems and the techniques used in the
analysis of such systems have been explained in chapter 4.
Chapter 5 provides two models of two component continuous review inventory systems.
Here we assume that demand occurs according to a poisson process and that a demand
can be satisfied only if both the components are available in inventory. Backorders
are not permitted. The two components are bought from outside suppliers and are
replenished according to (s, S) policy. In model 1 we assume that the leadtime of
the components follow an exponential distribution. By identifying the inventory level
as a Markov process, a system of differencedifferential equations at any time and the
steadystate for the state of inventory level are obtained. Tn model 2 we assume that the
leadtime distribution of one product is arbitrary and the other is exponential. Identifying
the underlying process as a semiregenerative process we find the stationary distribution
of the inventory level. For both these models, we find out the performance measures such
as the mean stationary rate of the number of lost demands, the demands satisfied and the
reorders made. Numerical examples for the two models are also considered.
Chaper 6 is devoted to the study of a two perishable product inventory model in which
the products are substitutable. The perishable rates of product 1 and product 2 are two
different constants. Demand for product 1 and product 2 follow two independent Poisson
processes. For replenishment of product 1 (s, S) ordering policy is followed and the
associated leadtime is arbitrary. Replenishment of product 2 is instantaneous. A demand
for product 1 which occurs during its stockout period can be substituted by product 2 with
some probability. Expressions are derived for the stationary distribution of the inventor}'
level by identifying the underlying stochastic process as a semiregenerative process. An
expression for the expected profit rate is obtained. A numerical illustration is provided
and an optimal reordering level maximising the profit rate is also studied.
To sum up, this thesis is an effort to improve the state the of art of (i) complex reliability
systems and their estimation study (ii) muitiproduct inventory systems. The salient
features of the thesis are:
(i) Analysis of a twocomponent reliability system with commoncause failures.
(ii) Estimation study of a complex system in which the repair time for both hot standby
and warm standby systems are assumed to be Eriangian.
(iii) A multiproduct continuous review inventory system with product interaction, with a
(s, S) policy.
(iv) Introduction of the concept of substitutability for products.
(v) Derivation of expressions for various statistical measures.
(vi) Effective use of the regeneration point technique in deriving various measures for both
reliability and inventory systems.
(vii) Illustration of the various results by extensive numerical work.
(vii) Consideration of relevant optimization problems. / Mathematical Sciences / PhD (Statistics)

89 
The stochastic multicellular repressilatorFryett, Matthew January 2014 (has links)
The discovery of genetic regulatory networks was an important advancement in science. Not only do they help understand how organisms behave but the development of synthetic genetic networks has aided in other fields of science and industry. Many genetic networks have been modelled deterministically by using differential equations to provide an insight into the network's behaviour. However, within a biological environment, a certain degree of intrinsic noise should be expected and the robustness of these networks should be tested. Creating and analysing a genetic network in a biological environment can be a time consuming task so applying stochastic methods, such as the Gillespie Algorithm, to a computer model will provide an important, initial insight into the behaviour of the system. One interesting genetic network is the coupled repressilator due to its relatively simplistic design and the broad, multistable dynamics it offers. The inhomogeneous solutions that it can yield are particularly interesting as they may help explain certain biological phenomena, and may be used as a tool to assist with further research into genetic networks. In this thesis, the Gillespie Algorithm will be applied to the coupled repressilator so that its robustness can be tested. Biologically feasible modifications will be made to the system to produce much more stable and predictable dynamics so that the broad range of solutions can exist within a noisy environment. The methods developed will take into account previously made assumptions and potential errors in biological data so that they can be applied to other genetic system. One further objective in this thesis is to explore computational limitations that may occur when modelling large, stochastic networks. Issues such as rounding errors and dealing with very small and very large numbers were encountered and methods to circumvent these without sacrificing computational runtime will be developed and applied.

90 
Invariant limiting shape distributions for some sequential rectangularmodels陳冠全, Chen, Koonchuen. January 1998 (has links)
published_or_final_version / Statistics and Actuarial Science / Doctoral / Doctor of Philosophy

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