Abstract: Cholera is a disease that is predominately common in
developing countries due to poor sanitation and overcrowding
population. In this paper, a deterministic model for the dynamics of
cholera is developed and control measures such as health educational
message, therapeutic treatment, and vaccination are incorporated in
the model. The effective reproduction number is computed in terms
of the model parameters. The existence and stability of the
equilibrium states, disease free and endemic equilibrium states are
established and showed to be locally and globally asymptotically
stable when R0 < 1 and R0 > 1 respectively. The existence of
backward bifurcation of the model is investigated. Furthermore,
numerical simulation of the model developed is carried out to show
the impact of the control measures and the result indicates that
combined control measures will help to reduce the spread of cholera
in the population.
Abstract: This article presents an alternative collapse capacity
intensity measure in the three elements form which is influenced by
the spectral ordinates at periods longer than that of the first mode
period at near and far source sites. A parameter, denoted by β, is
defined by which the spectral ordinate effects, up to the effective
period (2T1), on the intensity measure are taken into account. The
methodology permits to meet the hazard-levelled target extreme
event in the probabilistic and deterministic forms. A MATLAB code
is developed involving OpenSees to calculate the collapse capacities
of the 8 archetype RC structures having 2 to 20 stories for regression
process. The incremental dynamic analysis (IDA) method is used to
calculate the structure’s collapse values accounting for the element
stiffness and strength deterioration. The general near field set
presented by FEMA is used in a series of performing nonlinear
analyses. 8 linear relationships are developed for the 8structutres
leading to the correlation coefficient up to 0.93. A collapse capacity
near field prediction equation is developed taking into account the
results of regression processes obtained from the 8 structures. The
proposed prediction equation is validated against a set of actual near
field records leading to a good agreement. Implementation of the
proposed equation to the four archetype RC structures demonstrated
different collapse capacities at near field site compared to those of
FEMA. The reasons of differences are believed to be due to
accounting for the spectral shape effects.
Abstract: In recent decades, probabilistic constrained optimal
control problems have attracted much attention in many research
fields. Although probabilistic constraints are generally intractable
in an optimization problem, several tractable methods haven been
proposed to handle probabilistic constraints. In most methods,
probabilistic constraints are reduced to deterministic constraints
that are tractable in an optimization problem. However, there is a
gap between the transformed deterministic constraints in case of
known and unknown probability distribution. This paper examines
the conservativeness of probabilistic constrained optimization method
for unknown probability distribution. The objective of this paper is
to provide a quantitative assessment of the conservatism for tractable
constraints in probabilistic constrained optimization with unknown
probability distribution.
Abstract: This paper presents a methodology for probabilistic
assessment of bearing capacity and prediction of failure mechanism
of masonry vaults at the ultimate state with consideration of the
natural variability of Young’s modulus of stones. First, the
computation model is explained. The failure mode corresponds to the
four-hinge mechanism. Based on this consideration, the study of a
vault composed of 16 segments is presented. The Young’s modulus of
the segments is considered as random variable defined by a mean
value and a coefficient of variation. A relationship linking the vault
bearing capacity to the voussoirs modulus variation is proposed. The
most probable failure mechanisms, in addition to that observed in the
deterministic case, are identified for each variability level as well as
their probability of occurrence. The results show that the mechanism
observed in the deterministic case has decreasing probability of
occurrence in terms of variability, while the number of other
mechanisms and their probability of occurrence increases with the
coefficient of variation of Young’s modulus. This means that if a
significant change in the Young’s modulus of the segments is proven,
taking it into account in computations becomes mandatory, both for
determining the vault bearing capacity and for predicting its failure
mechanism.
Abstract: This paper presents a state-of-the-art survey of the
operations research models developed for internal audit planning.
Two alternative approaches have been followed in the literature for
audit planning: (1) identifying the optimal audit frequency; and (2)
determining the optimal audit resource allocation. The first approach
identifies the elapsed time between two successive audits, which can
be presented as the optimal number of audits in a given planning
horizon, or the optimal number of transactions after which an audit
should be performed. It also includes the optimal audit schedule. The
second approach determines the optimal allocation of audit frequency
among all auditable units in the firm. In our review, we discuss both
the deterministic and probabilistic models developed for audit
planning. In addition, game theory models are reviewed to find the
optimal auditing strategy based on the interactions between the
auditors and the clients.
Abstract: Quality of Service (QoS) attributes as part of the
service description is an important factor for service attribute. It is not
easy to exactly quantify the weight of each QoS conditions since
human judgments based on their preference causes vagueness. As
web services selection requires optimization, evolutionary computing
based on heuristics to select an optimal solution is adopted. In this
work, the evolutionary computing technique Particle Swarm
Optimization (PSO) is used for selecting a suitable web services
based on the user’s weightage of each QoS values by optimizing the
QoS weight vector and thereby finding the best weight vectors for
best services that is being selected. Finally the results are compared
and analyzed using static inertia weight and deterministic inertia
weight of PSO.
Abstract: One of the crucial parameters of digital cryptographic
systems is the selection of the keys used and their distribution. The
randomness of the keys has a strong impact on the system’s security
strength being difficult to be predicted, guessed, reproduced, or
discovered by a cryptanalyst. Therefore, adequate key randomness
generation is still sought for the benefit of stronger cryptosystems.
This paper suggests an algorithm designed to generate and test
pseudo random number sequences intended for cryptographic
applications. This algorithm is based on mathematically manipulating
a publically agreed upon information between sender and receiver
over a public channel. This information is used as a seed for
performing some mathematical functions in order to generate a
sequence of pseudorandom numbers that will be used for
encryption/decryption purposes. This manipulation involves
permutations and substitutions that fulfill Shannon’s principle of
“confusion and diffusion”. ASCII code characters were utilized in the
generation process instead of using bit strings initially, which adds
more flexibility in testing different seed values. Finally, the obtained
results would indicate sound difficulty of guessing keys by attackers.
Abstract: We proposed a Hyperbolic Gompertz Growth Model
(HGGM), which was developed by introducing a shape parameter
(allometric). This was achieved by convoluting hyperbolic sine
function on the intrinsic rate of growth in the classical gompertz
growth equation. The resulting integral solution obtained
deterministically was reprogrammed into a statistical model and used
in modeling the height and diameter of Pines (Pinus caribaea). Its
ability in model prediction was compared with the classical gompertz
growth model, an approach which mimicked the natural variability of
height/diameter increment with respect to age and therefore provides
a more realistic height/diameter predictions using goodness of fit
tests and model selection criteria. The Kolmogorov Smirnov test and
Shapiro-Wilk test was also used to test the compliance of the error
term to normality assumptions while the independence of the error
term was confirmed using the runs test. The mean function of top
height/Dbh over age using the two models under study predicted
closely the observed values of top height/Dbh in the hyperbolic
gompertz growth models better than the source model (classical
gompertz growth model) while the results of R2, Adj. R2, MSE and
AIC confirmed the predictive power of the Hyperbolic Gompertz
growth models over its source model.
Abstract: The check-in area of airport terminal is one of the
busiest sections at airports at certain periods. The passengers are
subjected to queues and delays during the check-in process. These
delays and queues are due to constraints in the capacity of service
facilities. In this project, the airport terminal is decomposed into
several check-in areas. The airport check-in scheduling problem
requires both a deterministic (integer programming) and stochastic
(simulation) approach. Integer programming formulations are
provided to minimize the total number of counters in each check-in
area under the realistic constraint that counters for one and the same
flight should be adjacent and the desired number of counters
remaining in each area should be fixed during check-in operations.
By using simulation, the airport system can be modeled to study the
effects of various parameters such as number of passengers on a
flight and check-in counter opening and closing time.
Abstract: Stochastic User Equilibrium (SUE) model is a widely
used traffic assignment model in transportation planning, which is
regarded more advanced than Deterministic User Equilibrium (DUE)
model. However, a problem exists that the performance of the SUE
model depends on its error term parameter. The objective of this
paper is to propose a systematic method of determining the
appropriate error term parameter value for the SUE model. First, the
significance of the parameter is explored through a numerical
example. Second, the parameter calibration method is developed
based on the Logit-based route choice model. The calibration process
is realized through multiple nonlinear regression, using sequential
quadratic programming combined with least square method. Finally,
case analysis is conducted to demonstrate the application of the
calibration process and validate the better performance of the SUE
model calibrated by the proposed method compared to the SUE
models under other parameter values and the DUE model.
Abstract: reliability-based methodology for the assessment
and evaluation of reinforced concrete (R/C) structural elements of
concrete structures is presented herein. The results of the reliability
analysis and assessment for R/C structural elements were verified by
the results obtained through deterministic methods. The outcomes of
the reliability-based analysis were compared against currently
adopted safety limits that are incorporated in the reliability indices
β’s, according to international standards and codes. The methodology
is based on probabilistic analysis using reliability concepts and
statistics of the main random variables that are relevant to the subject
matter, and for which they are to be used in the performance-function
equation(s) associated with the structural elements under study.
These methodology techniques can result in reliability index β, which
is commonly known as the reliability index or reliability measure
value that can be utilized to assess and evaluate the safety, human
risk, and functionality of the structural component. Also, these
methods can result in revised partial safety factor values for certain
target reliability indices that can be used for the purpose of
redesigning the R/C elements of the building and in which they could
assist in considering some other remedial actions to improve the
safety and functionality of the member.
Abstract: This paper aims at introducing finite automata theory,
the different ways to describe regular languages and create a program
to implement the subset construction algorithms to convert
nondeterministic finite automata (NFA) to deterministic finite
automata (DFA). This program is written in c++ programming
language. The program reads FA 5tuples from text file and then
classifies it into either DFA or NFA. For DFA, the program will read
the string w and decide whether it is acceptable or not. If accepted, the
program will save the tracking path and point it out. On the other hand,
when the automation is NFA, the program will change the Automation
to DFA so that it is easy to track and it can decide whether the w exists
in the regular language or not.
Abstract: The expanded Invasive Weed Optimization algorithm (exIWO) is an optimization metaheuristic modelled on the original IWO version created by the researchers from the University of Tehran. The authors of the present paper have extended the exIWO algorithm introducing a set of both deterministic and non-deterministic strategies of individuals’ selection. The goal of the project was to evaluate the exIWO by testing its usefulness for solving some test instances of the traveling salesman problem (TSP) taken from the TSPLIB collection which allows comparing the experimental results with optimal values.
Abstract: The optimization of biological systems, which is a branch of metabolic engineering, has generated a lot of industrial and academic interest for a long time. In the last decade, metabolic engineering approaches based on mathematical optimizations have been used extensively for the analysis and manipulation of metabolic networks. In practical optimization of metabolic reaction networks, designers have to manage the nature of uncertainty resulting from qualitative characters of metabolic reactions, e.g., the possibility of enzyme effects. A deterministic approach does not give an adequate representation for metabolic reaction networks with uncertain characters. Fuzzy optimization formulations can be applied to cope with this problem. A fuzzy multi-objective optimization problem can be introduced for finding the optimal engineering interventions on metabolic network systems considering the resilience phenomenon and cell viability constraints. The accuracy of optimization results depends heavily on the development of essential kinetic models of metabolic networks. Kinetic models can quantitatively capture the experimentally observed regulation data of metabolic systems and are often used to find the optimal manipulation of external inputs. To address the issues of optimizing the regulatory structure of metabolic networks, it is necessary to consider qualitative effects, e.g., the resilience phenomena and cell viability constraints. Combining the qualitative and quantitative descriptions for metabolic networks makes it possible to design a viable strain and accurately predict the maximum possible flux rates of desired products. Considering the resilience phenomena in metabolic networks can improve the predictions of gene intervention and maximum synthesis rates in metabolic engineering. Two case studies will present in the conference to illustrate the phenomena.
Abstract: We present a deterministic model which describes
the dynamics of tuberculosis in Algerian population where the
vaccination program with BCG is in place since 1969 and where
the WHO recommendations regarding the DOTS (directly-observed
treatment, short course) strategy are in application. The impact
of an intervention program, targeting recently infected people
among all close contacts of active cases and their treatment to
prevent endogenous reactivation, on the incidence of tuberculosis,
is investigated. We showed that a widespread treatment of latently
infected individuals for some years is recommended to shift from
higher to lower equilibrium state and thereafter relaxation is
recommended.
Abstract: In this paper we study mathematically the eigenvalue
problem for stochastic elliptic partial differential equation of Wick
type. Using the Wick-product and the Wiener-Itô chaos expansion,
the stochastic eigenvalue problem is reformulated as a system of an
eigenvalue problem for a deterministic partial differential equation
and elliptic partial differential equations by using the Fredholm
alternative. To reduce the computational complexity of this system,
we shall use a decomposition method using the Wiener-Itô chaos
expansion. Once the approximation of the solution is performed using
the finite element method for example, the statistics of the numerical
solution can be easily evaluated.
Abstract: A scheme integrated with deterministic–stochastic subspace system identification and the method of damage localization vector is proposed in this study for damage detection of structures based on seismic response data. A series of shaking table tests using a five-storey steel frame has been conducted in National Center for Research on Earthquake Engineering (NCREE), Taiwan. Damage condition is simulated by reducing the cross-sectional area of some of the columns at the bottom. Both single and combinations of multiple damage conditions at various locations have been considered. In the system identification analysis, either full or partial observation conditions have been taken into account. It has been shown that the damaged stories can be identified from global responses of the structure to earthquakes if sufficiently observed. In addition to detecting damage(s) with respect to the intact structure, identification of new or extended damages of the as-damaged (ill-conditioned) counterpart has also been studied. The proposed scheme proves to be effective.
Abstract: This paper proposes an improved Maximum Power Point Tracking of PhotoVoltaic system using Deterministic Partical Swarm Optimization technique. This method has the ability to track the maximum power under varying environmental conditions i.e. partial shading conditions. The advantage of this method, particles moves in the restricted value of velocity to achieve the maximum power. SEPIC converter is employed to boost up the voltage of PV system. To estimate the value of the proposed method, MATLAB simulation carried out under partial shading condition.
Abstract: Transit route Network Design Problem (TrNDP) is the most important component in Transit planning, in which the overall cost of the public transportation system highly depends on it. The main purpose of this study is to develop a novel solution methodology for the TrNDP, which goes beyond pervious traditional sophisticated approaches. The novelty of the solution methodology, adopted in this paper, stands on the deterministic operators which are tackled to construct bus routes. The deterministic manner of the TrNDP solution relies on using linear and integer mathematical formulations that can be solved exactly with their standard solvers. The solution methodology has been tested through Mandl’s benchmark network problem. The test results showed that the methodology developed in this research is able to improve the given network solution in terms of number of constructed routes, direct transit service coverage, transfer directness and solution reliability. Although the set of routes resulted from the methodology would stand alone as a final efficient solution for TrNDP, it could be used as an initial solution for meta-heuristic procedures to approach global optimal. Based on the presented methodology, a more robust network optimization tool would be produced for public transportation planning purposes.
Abstract: Globalization is putting enormous pressure on the business organizations specially manufacturing one to rethink the supply chain in innovative manners. Inventory consumes major portion of total sale revenue. Effective and efficient inventory management plays a vital role for the successful functioning of any organization. Selection of inventory policy is one of the important purchasing activities. This paper focuses on selection and ranking of alternative inventory policies. A deterministic quantitative model based on Distance Based Approach (DBA) method has been developed for evaluation and ranking of inventory policies. We have employed this concept first time for this type of the selection problem. Four inventory policies economic order quantity (EOQ), just in time (JIT), vendor managed inventory (VMI) and monthly policy are considered. Improper selection could affect a company’s competitiveness in terms of the productivity of its facilities and quality of its products. The ranking of inventory policies is a multi-criteria problem. There is a need to first identify the selection criteria and then processes the information with reference to relative importance of attributes for comparison. Criteria values for each inventory policy can be obtained either analytically or by using a simulation technique or they are linguistic subjective judgments defined by fuzzy sets, like, for example, the values of criteria. A methodology is developed and applied to rank the inventory policies.