Abstract: Dichotomization of the outcome by a single cut-off point is an important part of various medical studies. Usually the relationship between the resulted dichotomized dependent variable and explanatory variables is analyzed with linear regression, probit regression or logistic regression. However, in many real-life situations, a certain cut-off point dividing the outcome into two groups is unknown and can be specified only approximately, i.e. surrounded by some (small) uncertainty. It means that in order to have any practical meaning the regression model must be robust to this uncertainty. In this paper, we show that neither the beta in the linear regression model, nor its significance level is robust to the small variations in the dichotomization cut-off point. As an alternative robust approach to the problem of uncertain medical categories, we propose to use the linear regression model with the fuzzy membership function as a dependent variable. This fuzzy membership function denotes to what degree the value of the underlying (continuous) outcome falls below or above the dichotomization cut-off point. In the paper, we demonstrate that the linear regression model of the fuzzy dependent variable can be insensitive against the uncertainty in the cut-off point location. In the paper we present the modeling results from the real study of low hemoglobin levels in infants. We systematically test the robustness of the binomial regression model and the linear regression model with the fuzzy dependent variable by changing the boundary for the category Anemia and show that the behavior of the latter model persists over a quite wide interval.
Abstract: A stack with a small critical temperature gradient is
desirable for a standing wave thermoacoustic engine to obtain a low
onset temperature difference (the minimum temperature difference to
start engine-s self-oscillation). The viscous and heat relaxation loss in
the stack determines the critical temperature gradient. In this work, a
dimensionless critical temperature gradient factor is obtained based
on the linear thermoacoustic theory. It is indicated that the
impedance determines the proportion between the viscous loss, heat
relaxation losses and the power production from the heat energy. It
reveals the effects of the channel dimensions, geometrical
configuration and the local acoustic impedance on the critical
temperature gradient in stacks. The numerical analysis shows that
there exists a possible optimum combination of these parameters
which leads to the lowest critical temperature gradient. Furthermore,
several different geometries have been tested and compared
numerically.
Abstract: Coal fly ash (CFA) generated by coal-based thermal
power plants is mainly composed of some oxides having high
crystallinity, like quartz and mullite. In this study, the effect of CFA
crystallinity toward lead adsorption capacity was investigated. To get
solid with various crystallinity, the solution of sodium hydroxide
(NaOH) of 1-7 M was used to treat CFA at various temperature and
reflux time. Furthermore, to evaluate the effect of NaOH-treated CFA
with respect to adsorption capacity, the treated CFA were examine as
adsorbent for removing lead in the solution. The result shows that
using NaOH to treat CFA causes crystallinity of quartz and mullite
decrease. At higher NaOH concentration (>3M), in addition the
damage of quartz and mullite crystallinity is followed by crystal
formation called hydroxysodalite. The lower crystalllinity, the higher
adsorption capacity.
Abstract: Multi criteria decision making (MCDM) methods like analytic hierarchy process, ELECTRE and multi-attribute utility theory are critically studied. They have irregularities in terms of the reliability of ranking of the best alternatives. The Routing Decision Support (RDS) algorithm is trying to improve some of their deficiencies. This paper gives a mathematical verification that the RDS algorithm conforms to the test criteria for an effective MCDM method when a linear preference function is considered.
Abstract: At a time of growing market turbulence and a strong
shifts towards increasingly complex risk models and more stringent audit requirements, it is more critical than ever to maintain the highest quality of financial and credit information. IFC implemented
an approach that helps increase data integrity and quality significantly. This approach is called “Screening". Screening is based on linking information from different sources to identify potential
inconsistencies in key financial and credit data. That, in turn, can help
to ease the trials of portfolio supervision, and improve overall company global reporting and assessment systems. IFC experience
showed that when used regularly, Screening led to improved information.
Abstract: This paper has introduced a slope photogrammetric mapping using unmanned aerial vehicle. There are two units of UAV has been used in this study; namely; fixed wing and multi-rotor. Both UAVs were used to capture images at the study area. A consumer digital camera was mounted vertically at the bottom of UAV and captured the images at an altitude. The objectives of this study are to obtain three dimensional coordinates of slope area and to determine the accuracy of photogrammetric product produced from both UAVs. Several control points and checkpoints were established Real Time Kinematic Global Positioning System (RTK-GPS) in the study area. All acquired images from both UAVs went through all photogrammetric processes such as interior orientation, exterior orientation, aerial triangulation and bundle adjustment using photogrammetric software. Two primary results were produced in this study; namely; digital elevation model and digital orthophoto. Based on results, UAV system can be used to mapping slope area especially for limited budget and time constraints project.
Abstract: Sensor Network are emerging as a new tool for
important application in diverse fields like military surveillance,
habitat monitoring, weather, home electrical appliances and others.
Technically, sensor network nodes are limited in respect to energy
supply, computational capacity and communication bandwidth. In
order to prolong the lifetime of the sensor nodes, designing efficient
routing protocol is very critical. In this paper, we illustrate the
existing routing protocol for wireless sensor network using data
centric approach and present performance analysis of these protocols.
The paper focuses in the performance analysis of specific protocol
namely Directed Diffusion and SPIN. This analysis reveals that the
energy usage is important features which need to be taken into
consideration while designing routing protocol for wireless sensor
network.
Abstract: Real world Speaker Identification (SI) application
differs from ideal or laboratory conditions causing perturbations that
leads to a mismatch between the training and testing environment
and degrade the performance drastically. Many strategies have been
adopted to cope with acoustical degradation; wavelet based Bayesian
marginal model is one of them. But Bayesian marginal models
cannot model the inter-scale statistical dependencies of different
wavelet scales. Simple nonlinear estimators for wavelet based
denoising assume that the wavelet coefficients in different scales are
independent in nature. However wavelet coefficients have significant
inter-scale dependency. This paper enhances this inter-scale
dependency property by a Circularly Symmetric Probability Density
Function (CS-PDF) related to the family of Spherically Invariant
Random Processes (SIRPs) in Log Gabor Wavelet (LGW) domain
and corresponding joint shrinkage estimator is derived by Maximum
a Posteriori (MAP) estimator. A framework is proposed based on
these to denoise speech signal for automatic speaker identification
problems. The robustness of the proposed framework is tested for
Text Independent Speaker Identification application on 100 speakers
of POLYCOST and 100 speakers of YOHO speech database in three
different noise environments. Experimental results show that the
proposed estimator yields a higher improvement in identification
accuracy compared to other estimators on popular Gaussian Mixture
Model (GMM) based speaker model and Mel-Frequency Cepstral
Coefficient (MFCC) features.
Abstract: When an assignable cause(s) manifests itself to a multivariate process and the process shifts to an out-of-control condition, a root-cause analysis should be initiated by quality engineers to identify and eliminate the assignable cause(s) affected the process. A root-cause analysis in a multivariate process is more complex compared to a univariate process. In the case of a process involved several correlated variables an effective root-cause analysis can be only experienced when it is possible to identify the required knowledge including the out-of-control condition, the change point, and the variable(s) responsible to the out-of-control condition, all simultaneously. Although literature addresses different schemes to monitor multivariate processes, one can find few scientific reports focused on all the required knowledge. To the best of the author’s knowledge this is the first time that a multi task model based on artificial neural network (ANN) is reported to monitor all the required knowledge at the same time for a multivariate process with more than two correlated quality characteristics. The performance of the proposed scheme is evaluated numerically when different step shifts affect the mean vector. Average run length is used to investigate the performance of the proposed multi task model. The simulated results indicate the multi task scheme performs all the required knowledge effectively.
Abstract: In this paper, a novel corner detection method is
presented to stably extract geometrically important corners.
Intensity-based corner detectors such as the Harris corner can detect
corners in noisy environments but has inaccurate corner position and
misses the corners of obtuse angles. Edge-based corner detectors such
as Curvature Scale Space can detect structural corners but show
unstable corner detection due to incomplete edge detection in noisy
environments. The proposed image-based direct curvature estimation
can overcome limitations in both inaccurate structural corner detection
of the Harris corner detector (intensity-based) and the unstable corner
detection of Curvature Scale Space caused by incomplete edge
detection. Various experimental results validate the robustness of the
proposed method.
Abstract: Relevant agricultural information disseminator
(extension agent) ratio of 1:3500 farm families which become a
menace to agricultural production capacity in developing countries
necessitate this study. Out of 4 zones in the state, 24 extension agents
in each zone, 4 extension agents using cell phones and 120 farmers
using cell phone and 120 other farmers not using cell phone were
purposively selected to give 240 farmers that participated in the
research. Data were collected using interview guide and analysized
using frequency, percentage and t-test.. Frequency of contact with
agricultural information centers revealed that cell phone user farmers
had greater means score of X 41.43 contact as against the low mean
X19.32 contact recorded by farmers receiving agricultural
information from extension agents not using cell phone and their
production was statistically significant at P < 0.05. Usage of cell
phone increase extension agent contact and increase farmers-
production capacity.
Abstract: In this paper, the techniques for estimating the
residual stress in high velocity oxy fuel thermal spray coatings have
been discussed and compared. The development trend and the last
investigation have been studied. It is seemed that the there is not
effective study on the effect of the peening action in HVOF
analytically and numerically.
Abstract: Optimal design of structure has a main role in reduction of material usage which leads to deduction in the final cost of construction projects. Evolutionary approaches are found to be more successful techniques for solving size and shape structural optimization problem since it uses a stochastic random search instead of a gradient search. By reviewing the recent literature works the problem found was the optimization of weight. A new meta-heuristic algorithm called as Cuckoo Search (CS) Algorithm has used for the optimization of the total weight of the truss structures. This paper has used set of 10 bars and 25 bars trusses for the testing purpose. The main objective of this work is to reduce the number of iterations, weight and the total time consumption. In order to demonstrate the effectiveness of the present method, minimum weight design of truss structures is performed and the results of the CS are compared with other algorithms.
Abstract: The main objective of this paper is to estimate the cost of road traffic accidents in Egypt. The Human Capital (HC) approach, specifically the Gross-Loss-of-Output methodology, is adopted for estimation. Moreover, cost values obtained by previous national literature are updated using the inflation rates. The results indicate an estimated cost of road traffic accidents in Egypt of approximately 10 billion Egyptian Pounds (about $US 1.8 billion) for the year 2008. In addition, it is expected that this cost will rise in 2009 to 11.8 billion Egyptian Pounds (about $US 2.1 billion).
Abstract: SIP (Session Initiation Protocol), using HTML based
call control messaging which is quite simple and efficient, is being
replaced for VoIP networks recently. As for authentication and
authorization purposes there are many approaches and considerations
for securing SIP to eliminate forgery on the integrity of SIP
messages. On the other hand Elliptic Curve Cryptography has
significant advantages like smaller key sizes, faster computations on
behalf of other Public Key Cryptography (PKC) systems that obtain
data transmission more secure and efficient. In this work a new
approach is proposed for secure SIP authentication by using a public
key exchange mechanism using ECC. Total execution times and
memory requirements of proposed scheme have been improved in
comparison with non-elliptic approaches by adopting elliptic-based
key exchange mechanism.
Abstract: Modern retailers such as hypermarket/supermarket
need to be more customer-oriented in order to survive in today-s
competitive business world. As a result, the investigation of
determinant factors of store loyalty becomes important issue for
modern retailing players. This study suggests that consumers- store
loyalty in the modern retailing market (hypermarkets and
supermarkets) is influenced by environmental factors (such as store
image, store personnel). Using a model of stimulus-organismresponse
(S-O-R), this research examines S-R relationship of store
loyalty. S-O-R framework is derived from the existence literature and
tested empirically based on Indonesian consumers- experience. The
stimuli for this study are store image, store personnel, satisfaction
and culture factors. Affect, or the consumers- liking to modern
retailing stores, mediates the chosen environmental factors on
consumer-s store loyalty. The findings showed that store image, store
satisfaction and culture have significant positive relationship to store
loyalty via affect.
Abstract: The effect of moisture content and loading rate on
mechanical strength of 12 brown rice grain varieties was determined.
The results showed that the rupture force of brown rice grain
decreased by increasing the moisture content and loading rate. The
highest rupture force values was obtained at the moisture content of
8% (w.b.) and loading rate of 10 mm/min; while the lowest rupture
force corresponded to the moisture content of 14% (w.b.) and loading
rate of 15 mm/min. The 12 varieties were divided into three groups,
namely local short grain varieties, local long grain varieties and
improved long grain varieties. It was observed that the rupture
strength of the three groups were statistically different from each
other (P
Abstract: Structural representation and technology mapping of
a Boolean function is an important problem in the design of nonregenerative
digital logic circuits (also called combinational logic
circuits). Library aware function manipulation offers a solution to
this problem. Compact multi-level representation of binary networks,
based on simple circuit structures, such as AND-Inverter Graphs
(AIG) [1] [5], NAND Graphs, OR-Inverter Graphs (OIG), AND-OR
Graphs (AOG), AND-OR-Inverter Graphs (AOIG), AND-XORInverter
Graphs, Reduced Boolean Circuits [8] does exist in
literature. In this work, we discuss a novel and efficient graph
realization for combinational logic circuits, represented using a
NAND-NOR-Inverter Graph (NNIG), which is composed of only
two-input NAND (NAND2), NOR (NOR2) and inverter (INV) cells.
The networks are constructed on the basis of irredundant disjunctive
and conjunctive normal forms, after factoring, comprising terms with
minimum support. Construction of a NNIG for a non-regenerative
function in normal form would be straightforward, whereas for the
complementary phase, it would be developed by considering a virtual
instance of the function. However, the choice of best NNIG for a
given function would be based upon literal count, cell count and
DAG node count of the implementation at the technology
independent stage. In case of a tie, the final decision would be made
after extracting the physical design parameters.
We have considered AIG representation for reduced disjunctive
normal form and the best of OIG/AOG/AOIG for the minimized
conjunctive normal forms. This is necessitated due to the nature of
certain functions, such as Achilles- heel functions. NNIGs are found
to exhibit 3.97% lesser node count compared to AIGs and
OIG/AOG/AOIGs; consume 23.74% and 10.79% lesser library cells
than AIGs and OIG/AOG/AOIGs for the various samples considered.
We compare the power efficiency and delay improvement achieved
by optimal NNIGs over minimal AIGs and OIG/AOG/AOIGs for
various case studies. In comparison with functionally equivalent,
irredundant and compact AIGs, NNIGs report mean savings in power
and delay of 43.71% and 25.85% respectively, after technology
mapping with a 0.35 micron TSMC CMOS process. For a
comparison with OIG/AOG/AOIGs, NNIGs demonstrate average
savings in power and delay by 47.51% and 24.83%. With respect to
device count needed for implementation with static CMOS logic
style, NNIGs utilize 37.85% and 33.95% lesser transistors than their
AIG and OIG/AOG/AOIG counterparts.
Abstract: In many applications, it is a priori known that the
target function should satisfy certain constraints imposed by, for
example, economic theory or a human-decision maker. Here we
consider partially monotone problems, where the target variable
depends monotonically on some of the predictor variables but not all.
We propose an approach to build partially monotone models based
on the convolution of monotone neural networks and kernel
functions. The results from simulations and a real case study on
house pricing show that our approach has significantly better
performance than partially monotone linear models. Furthermore, the
incorporation of partial monotonicity constraints not only leads to
models that are in accordance with the decision maker's expertise,
but also reduces considerably the model variance in comparison to
standard neural networks with weight decay.
Abstract: Ten simply supported grossly underreinforced
tapered concrete beams of full size were tested upto complete
collapse under flexural effect .Out of 10 beams, 5 beams were
nonfibrous and the remaining beams contained fibres. The beams
had a variation in the tapered angle as 2°, 4°, 6°, 8° and 10°. The
concrete mix, conventional steel and the type of fibre used were
held constant. Flat corrugated steel fibres were utilized as
secondary reinforcement. The strength and stability parameters
were measured. It is established that the fibrous tapered beams can
be used economically in earthquake prone areas.