Abstract: Groundlessness of application probability-statistic methods are especially shown at an early stage of the aviation GTE technical condition diagnosing, when the volume of the information has property of the fuzzy, limitations, uncertainty and efficiency of application of new technology Soft computing at these diagnosing stages by using the fuzzy logic and neural networks methods. It is made training with high accuracy of multiple linear and nonlinear models (the regression equations) received on the statistical fuzzy data basis. At the information sufficiency it is offered to use recurrent algorithm of aviation GTE technical condition identification on measurements of input and output parameters of the multiple linear and nonlinear generalized models at presence of noise measured (the new recursive least squares method (LSM)). As application of the given technique the estimation of the new operating aviation engine D30KU-154 technical condition at height H=10600 m was made.
Abstract: The quantitative determination of several trace
elements (Cr, As, Se, Cd, Hg, Pb) existing as inorganic impurities in
some oriental herb-products such as Lingzhi Mushroom capsules,
Philamin powder, etc using ICP-MS has been studied. Various
instrumental parameters such as power, gas flow rate, sample depth, as
well as the concentration of nitric acid and thick background due to
high concentration of possible interferences on the determination of
these above-mentioned elements was investigated and the optimum
working conditions of the sample measurement on ICP-MS
(Agilent-7500a) were reported. Appropriate isotope internal standards
were also used to improve the accuracy of mercury determination.
Optimal parameters for sampling digestion were also investigated. The
recovery of analytical procedure was examined by using a Certified
Reference Material (IAEA-CRM 359). The recommended procedure
was then applied for the quantitative determination of Cr, As, Se, Cd,
Hg, Pb in Lingzhi Mushroom capsule, and Philamine powder samples.
The reproducibility of sample measurement (average value between
94 and 102%) and the uncertainty of analytical data (less than 20%)
are acceptable.
Abstract: Petri Net (PN) has proven to be effective graphical, mathematical, simulation, and control tool for Discrete Event Systems (DES). But, with the growth in the complexity of modern industrial, and communication systems, PN found themselves inadequate to address the problems of uncertainty, and imprecision in data. This gave rise to amalgamation of Fuzzy logic with Petri nets and a new tool emerged with the name of Fuzzy Petri Nets (FPN). Although there had been a lot of research done on FPN and a number of their applications have been anticipated, but their basic types and structure are still ambiguous. Therefore, in this research, an effort is made to categorize FPN according to their structure and algorithms Further, literature review of the applications of FPN in the light of their classifications has been done.
Abstract: This paper examines the influence of communication
form on employee uncertainty during mergers and acquisitions
(M&As). Specifically, the author uses narrative theory to analyze
how narrative organizational communication affects the three
components of uncertainty – decreased predictive, explanatory, and
descriptive ability. It is hypothesized that employees whose
organizations use narrative M&A communication will have greater
predictive, explanatory, and descriptive abilities than employees of
organizations using non-narrative M&A communication. This paper
contributes to the stream of research examining uncertainty during
mergers and acquisitions and argues that narratives are an effective
means of managing uncertainty in the mergers and acquisitions
context.
Abstract: This paper presents an approach based on the
adoption of a distributed cognition framework and a non parametric
multicriteria evaluation methodology (DEA) designed specifically to
compare e-commerce websites from the consumer/user viewpoint. In
particular, the framework considers a website relative efficiency as a
measure of its quality and usability. A website is modelled as a black
box capable to provide the consumer/user with a set of
functionalities. When the consumer/user interacts with the website to
perform a task, he/she is involved in a cognitive activity, sustaining a
cognitive cost to search, interpret and process information, and
experiencing a sense of satisfaction. The degree of ambiguity and
uncertainty he/she perceives and the needed search time determine
the effort size – and, henceforth, the cognitive cost amount – he/she
has to sustain to perform his/her task. On the contrary, task
performing and result achievement induce a sense of gratification,
satisfaction and usefulness. In total, 9 variables are measured,
classified in a set of 3 website macro-dimensions (user experience,
site navigability and structure). The framework is implemented to
compare 40 websites of businesses performing electronic commerce
in the information technology market. A questionnaire to collect
subjective judgements for the websites in the sample was purposely
designed and administered to 85 university students enrolled in
computer science and information systems engineering
undergraduate courses.
Abstract: Probabilistic measures of uncertainty have been
obtained as functions of time and birth and death rates in a queuing
process. The variation of different entropy measures has been studied
in steady and non-steady processes of queuing theory.
Abstract: This paper argues that increased uncertainty, in certain
situations, may actually encourage investment. Since earlier studies
mostly base their arguments on the assumption of geometric Brownian
motion, the study extends the assumption to alternative stochastic
processes, such as mixed diffusion-jump, mean-reverting process, and
jump amplitude process. A general approach of Monte Carlo
simulation is developed to derive optimal investment trigger for the
situation that the closed-form solution could not be readily obtained
under the assumption of alternative process. The main finding is that
the overall effect of uncertainty on investment is interpreted by the
probability of investing, and the relationship appears to be an invested
U-shaped curve between uncertainty and investment. The implication
is that uncertainty does not always discourage investment even under
several sources of uncertainty. Furthermore, high-risk projects are not
always dominated by low-risk projects because the high-risk projects
may have a positive realization effect on encouraging investment.
Abstract: In inspection and workpiece localization, sampling point data is an important issue. Since the devices for sampling only sample discrete points, not the completely surface, sampling size and location of the points will be taken into consideration. In this paper a method is presented for determining the sampled points size and location for achieving efficient sampling. Firstly, uncertainty analysis of the localization parameters is investigated. A localization uncertainty model is developed to predict the uncertainty of the localization process. Using this model the minimum size of the sampled points is predicted. Secondly, based on the algebra theory an eigenvalue-optimal optimization is proposed. Then a freeform surface is used in the simulation. The proposed optimization is implemented. The simulation result shows its effectivity.
Abstract: Molodstov-s soft sets theory was originally proposed
as general mathematical tool for dealing with uncertainty problems. The matrix form has been introduced in soft set and some of its
properties have been discussed. However, the formulation of soft
matrix in group decision making problem only with equal importance
weights of criteria, which does not show the true opinion of decision maker on each criteria. The aim of this paper is to propose a method
for solving group decision making problem incorporating the importance of criteria by using soft matrices in a more objective manner. The weight of each criterion is calculated by using the Analytic Hierarchy Process (AHP) method. An example of house
selection process is given to illustrate the effectiveness of the proposed method.
Abstract: Inventory decisional environment of short life-cycle
products is full of uncertainties arising from randomness and
fuzziness of input parameters like customer demand requiring
modeling under hybrid uncertainty. Prior inventory models
incorporating fuzzy demand have unfortunately ignored stochastic
variation of demand. This paper determines an unambiguous optimal
order quantity from a set of n fuzzy observations in a newsvendor
inventory setting in presence of fuzzy random variable demand
capturing both fuzzy perception and randomness of customer
demand. The stress of this paper is in providing solution procedure
that attains optimality in two steps with demand information
availability in linguistic phrases leading to fuzziness along with
stochastic variation. The first step of solution procedure identifies
and prefers one best fuzzy opinion out of all expert opinions and the
second step determines optimal order quantity from the selected
event that maximizes profit. The model and solution procedure is
illustrated with a numerical example.
Abstract: There is a growing body of evidence to support the
proposition of product take back for remanufacturing particularly
within the context of Extended Producer Responsibility (EPR).
Remanufacturing however presents challenges unlike that of
traditional manufacturing environments due to its high levels of
uncertainty which may further distract organizations from
considering its potential benefits. This paper presents a novel
modeling approach for evaluating the uncertainty of part failures
within the remanufacturing process and its impact on economic and
environmental performance measures. This paper presents both the
theoretical modeling approach and an example of its use in
application.
Abstract: In a wind power generator using doubly fed induction
generator (DFIG), the three-phase pulse width modulation (PWM)
voltage source converter (VSC) is used as grid side converter (GSC)
and rotor side converter (RSC). The standard linear control laws
proposed for GSC provides not only instablity against comparatively
large-signal disturbances, but also the problem of stability due to
uncertainty of load and variations in parameters. In this paper, a
nonlinear controller is designed for grid side converter (GSC) of a
DFIG for wind power application. The nonlinear controller is
designed based on the input-output feedback linearization control
method. The resulting closed-loop system ensures a sufficient
stability region, make robust to variations in circuit parameters and
also exhibits good transient response. Computer simulations and
experimental results are presented to confirm the effectiveness of the
proposed control strategy.
Abstract: In this paper is shown that the probability-statistic methods application, especially at the early stage of the aviation gas turbine engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence is considered the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods. Training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. Thus for GTE technical condition more adequate model making are analysed dynamics of skewness and kurtosis coefficients' changes. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows to draw conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. For checking of models adequacy is considered the Fuzzy Multiple Correlation Coefficient of Fuzzy Multiple Regression. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-bystage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine temperature condition was made.
Abstract: This paper reviews recent studies and particularly the
effects of Climate Change in the North Tropical Atlantic by studying
atmospheric conditions that prevailed in 2005 ; Coral Bleaching
HotSpot and Hurricane Katrina. In the aim to better understand and
estimate the impact of the physical phenomenon, i.e. Thermal
Oceanic HotSpot (TOHS), isotopic studies of δ18O and δ13C on
marine animals from Guadeloupe (French Caribbean Island) were
carried out. Recorded measures show Sea Surface Temperature (SST)
up to 35°C in August which is much higher than data recorded by
NOAA satellites 32°C. After having reviewed the process that led to
the creation of Hurricane Katrina which hit New Orleans in August
29, 2005, it will be shown that the climatic conditions in the
Caribbean from August to October 2005 have influenced Katrina
evolution. This TOHS is a combined effect of various phenomenon
which represent an additional factor to estimate future climate
changes.
Abstract: Public sector corruption has long-term and damaging
effects that are deep and broad. Addressing corruption relies on
understanding the drivers that precipitate acts of corruption and
developing educational programs that target areas of vulnerability.
This paper provides an innovative approach to explore the nature of
corruption by drawing on the perceptions and ideas of a group of
public servants who have been part of a corruption investigation. The
paper examines these reflections through the ideas of Pierre Bourdieu
and Alfred Schutz to point to some of the steps that can lead to
corrupt activity. The paper demonstrates that phenomenological
inquiry is useful in the exploration of corruption and, as a theoretical
framework, it highlights that corruption emerges through a
combination of conflict, doubt and uncertainty. The paper calls for
anti-corruption education programs to be attentive to way in which
these conditions can influence the steps into corruption.
Abstract: The prediction of long-term deformations of concrete and reinforced concrete structures has been a field of extensive research and several different creep models have been developed so far. Most of the models were developed for constant concrete stresses, thus, in case of varying stresses a specific superposition principle or time-integration, respectively, is necessary. Nowadays, when modeling concrete creep the engineering focus is rather on the application of sophisticated time-integration methods than choosing the more appropriate creep model. For this reason, this paper presents a method to quantify the uncertainties of creep prediction originating from the selection of creep models or from the time-integration methods. By adapting variance based global sensitivity analysis, a methodology is developed to quantify the influence of creep model selection or choice of time-integration method. Applying the developed method, general recommendations how to model creep behavior for varying stresses are given.
Abstract: Characterization of radio communication signals aims
at automatic recognition of different characteristics of radio signals in
order to detect their modulation type, the central frequency, and the
level. Our purpose is to apply techniques used in image processing in
order to extract pertinent characteristics. To the single analysis, we
add several rules for checking the consistency of hypotheses using
fuzzy logic. This allows taking into account ambiguity and
uncertainty that may remain after the extraction of individual
characteristics. The aim is to improve the process of radio
communications characterization.
Abstract: Supplier selection is a multi criteria decision-making process that comprises tangible and intangible factors. The majority of previous supplier selection techniques do not consider strategic perspective. Besides, uncertainty is one of the most important obstacles in supplier selection. For the first, time in this paper, the idea of the algorithm " Knapsack " is used to select suppliers Moreover, an attempt has to be made to take the advantage of a simple numerical method for solving model .This is an innovation to resolve any ambiguity in choosing suppliers. This model has been tried in the suppliers selected in a competitive environment and according to all desired standards of quality and quantity to show the efficiency of the model, an industry sample has been uses.
Abstract: The Proton Exchange Membrane Fuel Cell (PEMFC)
control system has an important effect on operation of cell.
Traditional controllers couldn-t lead to acceptable responses because
of time- change, long- hysteresis, uncertainty, strong- coupling and
nonlinear characteristics of PEMFCs, so an intelligent or adaptive
controller is needed. In this paper a neural network predictive
controller have been designed to control the voltage of at the
presence of fluctuations of temperature. The results of
implementation of this designed NN Predictive controller on a
dynamic electrochemical model of a small size 5 KW, PEM fuel cell
have been simulated by MATLAB/SIMULINK.
Abstract: Physiological control of a left ventricle assist device (LVAD) is generally a complicated task due to diverse operating environments and patient variability. In this work, a tracking control algorithm based on sliding mode and feed forward control for a class of discrete-time single input single output (SISO) nonlinear uncertain systems is presented. The controller was developed to track the reference trajectory to a set operating point without inducing suction in the ventricle. The controller regulates the estimated mean pulsatile flow Qp and mean pulsatility index of pump rotational speed PIω that was generated from a model of the assist device. We recall the principle of the sliding mode control theory then we combine the feed-forward control design with the sliding mode control technique to follow the reference trajectory. The uncertainty is replaced by its upper and lower boundary. The controller was tested in a computer simulation covering two scenarios (preload and ventricular contractility). The simulation results prove the effectiveness and the robustness of the proposed controller