Abstract: The main aim of this study is to identify the most
influential variables that cause defects on the items produced by a
casting company located in Turkey. To this end, one of the items
produced by the company with high defective percentage rates is
selected. Two approaches-the regression analysis and decision treesare
used to model the relationship between process parameters and
defect types. Although logistic regression models failed, decision tree
model gives meaningful results. Based on these results, it can be
claimed that the decision tree approach is a promising technique for
determining the most important process variables.
Abstract: Software maintenance and mainly software
comprehension pose the largest costs in the software lifecycle. In
order to assess the cost of software comprehension, various
complexity measures have been proposed in the literature. This paper
proposes new cognitive-spatial complexity measures, which combine
the impact of spatial as well as architectural aspect of the software to
compute the software complexity. The spatial aspect of the software
complexity is taken into account using the lexical distances (in
number of lines of code) between different program elements and the
architectural aspect of the software complexity is taken into
consideration using the cognitive weights of control structures
present in control flow of the program. The proposed measures are
evaluated using standard axiomatic frameworks and then, the
proposed measures are compared with the corresponding existing
cognitive complexity measures as well as the spatial complexity
measures for object-oriented software. This study establishes that the
proposed measures are better indicators of the cognitive effort
required for software comprehension than the other existing
complexity measures for object-oriented software.
Abstract: This paper aims to select the optimal location and
setting parameters of TCSC (Thyristor Controlled Series
Compensator) controller using Particle Swarm Optimization (PSO)
and Genetic Algorithm (GA) to mitigate small signal oscillations in a
multimachine power system. Though Power System Stabilizers
(PSSs) are prime choice in this issue, installation of FACTS device
has been suggested here in order to achieve appreciable damping of
system oscillations. However, performance of any FACTS devices
highly depends upon its parameters and suitable location in the
power network. In this paper PSO as well as GA based techniques are
used separately and compared their performances to investigate this
problem. The results of small signal stability analysis have been
represented employing eigenvalue as well as time domain response in
face of two common power system disturbances e.g., varying load
and transmission line outage. It has been revealed that the PSO based
TCSC controller is more effective than GA based controller even
during critical loading condition.
Abstract: At the previous study of new metal gasket, contact
width and contact stress were important design parameter for
optimizing metal gasket performance. However, the range of contact
stress had not been investigated thoroughly. In this study, we
conducted a gasket design optimization based on an elastic and plastic
contact stress analysis considering forming effect using FEM. The
gasket model was simulated by using two simulation stages which is
forming and tightening simulation. The optimum design based on an
elastic and plastic contact stress was founded. Final evaluation was
determined by helium leak quantity to check leakage performance of
both type of gaskets. The helium leak test shows that a gasket based
on the plastic contact stress design better than based on elastic stress
design.
Abstract: Employing a recently introduced unified adaptive filter
theory, we show how the performance of a large number of important
adaptive filter algorithms can be predicted within a general framework
in nonstationary environment. This approach is based on energy conservation
arguments and does not need to assume a Gaussian or white
distribution for the regressors. This general performance analysis can
be used to evaluate the mean square performance of the Least Mean
Square (LMS) algorithm, its normalized version (NLMS), the family
of Affine Projection Algorithms (APA), the Recursive Least Squares
(RLS), the Data-Reusing LMS (DR-LMS), its normalized version
(NDR-LMS), the Block Least Mean Squares (BLMS), the Block
Normalized LMS (BNLMS), the Transform Domain Adaptive Filters
(TDAF) and the Subband Adaptive Filters (SAF) in nonstationary
environment. Also, we establish the general expressions for the
steady-state excess mean square in this environment for all these
adaptive algorithms. Finally, we demonstrate through simulations that
these results are useful in predicting the adaptive filter performance.
Abstract: A mobile Ad-hoc network consists of wireless nodes
communicating without the need for a centralized administration. A
user can move anytime in an ad hoc scenario and, as a result, such a
network needs to have routing protocols which can adopt
dynamically changing topology. To accomplish this, a number of ad
hoc routing protocols have been proposed and implemented, which
include DSR, OLSR and AODV. This paper presents a study on the
QoS parameters for MANET application traffics in large-scale
scenarios with 50 and 120 nodes. The application traffics analyzed in
this study is File Transfer Protocol (FTP). In large scale networks
(120 nodes) OLSR shows better performance and in smaller scale
networks (50 nodes)AODV shows less packet drop rate and OLSR
shows better throughput.
Abstract: Global Positioning System (GPS) technology is widely used today in the areas of geodesy and topography as well as in aeronautics mainly for military purposes. Due to the military usage of GPS, full access and use of this technology is being denied to the civilian user who must then work with a less accurate version. In this paper we focus on the estimation of the receiver coordinates ( X, Y, Z ) and its clock bias ( δtr ) of a fixed point based on pseudorange measurements of a single GPS receiver. Utilizing the instantaneous coordinates of just 4 satellites and their clock offsets, by taking into account the atmospheric delays, we are able to derive a set of pseudorange equations. The estimation of the four unknowns ( X, Y, Z , δtr ) is achieved by introducing an extended Kalman filter that processes, off-line, all the data collected from the receiver. Higher performance of position accuracy is attained by appropriate tuning of the filter noise parameters and by including other forms of biases.
Abstract: Sleep stage scoring is the process of classifying the
stage of the sleep in which the subject is in. Sleep is classified into
two states based on the constellation of physiological parameters.
The two states are the non-rapid eye movement (NREM) and the
rapid eye movement (REM). The NREM sleep is also classified into
four stages (1-4). These states and the state wakefulness are
distinguished from each other based on the brain activity. In this
work, a classification method for automated sleep stage scoring
based on a single EEG recording using wavelet packet decomposition
was implemented. Thirty two ploysomnographic recording from the
MIT-BIH database were used for training and validation of the
proposed method. A single EEG recording was extracted and
smoothed using Savitzky-Golay filter. Wavelet packets
decomposition up to the fourth level based on 20th order Daubechies
filter was used to extract features from the EEG signal. A features
vector of 54 features was formed. It was reduced to a size of 25 using
the gain ratio method and fed into a classifier of regression trees. The
regression trees were trained using 67% of the records available. The
records for training were selected based on cross validation of the
records. The remaining of the records was used for testing the
classifier. The overall correct rate of the proposed method was found
to be around 75%, which is acceptable compared to the techniques in
the literature.
Abstract: In power systems, protective relays must filter their
inputs to remove undesirable quantities and retain signal quantities of
interest. This job must be performed accurate and fast. A new
method for filtering the undesirable components such as DC and
harmonic components associated with the fundamental system
signals. The method is s based on a dynamic filtering algorithm. The
filtering algorithm has many advantages over some other classical
methods. It can be used as dynamic on-line filter without the need of
parameters readjusting as in the case of classic filters. The proposed
filter is tested using different signals. Effects of number of samples
and sampling window size are discussed. Results obtained are
presented and discussed to show the algorithm capabilities.
Abstract: An alternative iterative computational procedure is
proposed for internal normal ball loads calculation in statically
loaded single-row, angular-contact ball bearings, subjected to a
known thrust load, which is applied in the inner ring at the geometric
bearing center line. An accurate method for curvature radii at
contacts with inner and outer raceways in the direction of the motion
is used. Numerical aspects of the iterative procedure are discussed.
Numerical examples results for a 218 angular-contact ball bearing
have been compared with those from the literature. Twenty figures
are presented showing the geometrical features, the behavior of the
convergence variables and the following parameters as functions of
the thrust load: normal ball loads, contact angle, distance between
curvature centers, and normal ball and axial deflections.
Abstract: This experiment was conducted to investigate the
effect of dietary supplementation of different levels of black seed
(Nigella sativa L.) on the performance and immune response of broiler chicks. A total 240 day-old broiler chicks were used and
randomly allotted equally into six experimental groups designated as 1, 2, 3, 4, 5 and 6 having black seed at the rate of 0, 2, 4, 6, 8 and
10 g /kg diet respectively. The study was lasted for 42 days. Average body weight, weight gain, relative growth rate, feed
conversion, antibody titer against Newcastle disease, phagocytic activity and phagocytic index, some blood parameters(GOT, GPT,
Glucose, Cholesterol, Triglyceride, Total protein, Albumen, WBCs,
RBCs, Hb and PCV), dressing percentage, weight of different body
organs, abdominal fat weight, were determined. It was found that, N. Sativa significantly improved final body weight, total body gain
and feed conversion ratio of groups 2 and 3 when compared with the control group. Higher levels of N. Sativa did not improve
growth performance of the chicks. Non significant differences were
observed for antibody titer against Newcastle virus, WBCs count,
serum GOT, glucose level, dressing %, relative liver, spleen, heart and head percentages. Lymphoid organs (Bursa and Thymus)
improved significantly with increasing N. Sativa level in all supplemented groups. Serum cholesterol, triglyceride and visible fat
% significantly decreased with Nigella sativa supplementation while
serum GPT level significantly increased with nigella sativa
supplementation.
Abstract: Problem solving has traditionally been one of the principal research areas for artificial intelligence. Yet, although artificial intelligence reasoning techniques have been employed in several product support systems, the benefit of integrating product support, knowledge engineering, and problem solving, is still unclear. This paper studies the synergy of these areas and proposes a knowledge engineering framework that integrates product support systems and artificial intelligence techniques. The framework includes four spaces; the data, problem, hypothesis, and solution ones. The data space incorporates the knowledge needed for structured reasoning to take place, the problem space contains representations of problems, and the hypothesis space utilizes a multimodal reasoning approach to produce appropriate solutions in the form of virtual documents. The solution space is used as the gateway between the system and the user. The proposed framework enables the development of product support systems in terms of smaller, more manageable steps while the combination of different reasoning techniques provides a way to overcome the lack of documentation resources.
Abstract: Business Process Modeling (BPM) is the first and
most important step in business process management lifecycle. Graph
based formalism and rule based formalism are the two most
predominant formalisms on which process modeling languages are
developed. BPM technology continues to face challenges in coping
with dynamic business environments where requirements and goals
are constantly changing at the execution time. Graph based
formalisms incur problems to react to dynamic changes in Business
Process (BP) at the runtime instances. In this research, an adaptive
and flexible framework based on the integration between Object
Oriented diagramming technique and Petri Net modeling language is
proposed in order to support change management techniques for
BPM and increase the representation capability for Object Oriented
modeling for the dynamic changes in the runtime instances. The
proposed framework is applied in a higher education environment to
achieve flexible, updatable and dynamic BP.
Abstract: Wavelet neural networks (WNNs) have emerged as a vital alternative to the vastly studied multilayer perceptrons (MLPs) since its first implementation. In this paper, we applied various clustering algorithms, namely, K-means (KM), Fuzzy C-means (FCM), symmetry-based K-means (SBKM), symmetry-based Fuzzy C-means (SBFCM) and modified point symmetry-based K-means (MPKM) clustering algorithms in choosing the translation parameter of a WNN. These modified WNNs are further applied to the heterogeneous cancer classification using benchmark microarray data and were compared against the conventional WNN with random initialization method. Experimental results showed that a WNN classifier with the MPKM algorithm is more precise than the conventional WNN as well as the WNNs with other clustering algorithms.
Abstract: The Euler-s equation of motion is extended to include
the viscosity stress tensor leading to the formulation of Navier–
Stokes type equation. The latter is linearized and applied to
investigate the rotational motion or vorticity in a viscous fluid.
Relations for the velocity of viscous waves and attenuation parameter
are obtained in terms of viscosity (μ) and the density (¤ü) of the fluid.
μ and ¤ü are measured experimentally as a function of temperature for
two different samples of light and heavy crude oil. These data
facilitated to determine the activation energy, velocity of viscous
wave and the attenuation parameter. Shear wave velocity in heavy oil
is found to be much larger than the light oil, whereas the attenuation
parameter in heavy oil is quite low in comparison to light one. The
activation energy of heavy oil is three times larger than light oil.
Abstract: The analytical solutions for geodesic acoustic
eigenmodes in tokamak plasmas with circular concentric magnetic
surfaces are found. In the frame of ideal magnetohydrodynamics the
dispersion relation taking into account the toroidal coupling between
electrostatic perturbations and electromagnetic perturbations with
poloidal mode number |m| = 2 is derived. In the absence of such
a coupling the dispersion relation gives the standard continuous
spectrum of geodesic acoustic modes. The analysis of the existence
of global eigenmodes for plasma equilibria with both off-axis
and on-axis maximum of the local geodesic acoustic frequency is
performed.
Abstract: In order to derive important parameters concerning
mobile subscriber MS with ongoing calls in Low Earth Orbit Mobile
Satellite Systems LEO MSSs, a positioning system had to be
integrated into MSS in order to localize mobile subscribers MSs and
track them during the connection. Such integration is regarded as a
complex implementation.
We propose in this paper a novel method based on advantages of
mobility model of Low Earth Orbit Mobile Satellite System LEO
MSS called Evaluation Parameters Method EPM which allows for
such systems the evaluation of different information concerning a
MS with a call in progress even if its location is unknown.
Abstract: The process parameters, temperature, pH and
substrate concentration, were optimized for the production of
gentamicin using Micromonouspora echinospora. Experiments were
carried out according to central composite design in response surface
method. The optimum conditions for the maximum production of
gentamicin were found to be: temperature – 31.7oC, pH – 6.8 and
substrate concentration – 3%. At these optimized conditions the
production of gentamicin was found to be – 1040 mg/L. The R2 value
of 0.9465 indicates a good fitness of the model.
Abstract: This paper reports a new approach on identifying the
individuality of persons by using parametric classification of multiple
mental thoughts. In the approach, electroencephalogram (EEG)
signals were recorded when the subjects were thinking of one or
more (up to five) mental thoughts. Autoregressive features were
computed from these EEG signals and classified by Linear
Discriminant classifier. The results here indicate that near perfect
identification of 400 test EEG patterns from four subjects was
possible, thereby opening up a new avenue in biometrics.
Abstract: The Model for Knowledge Base of Computational Objects
(KBCO model) has been successfully applied to represent the
knowledge of human like Plane Geometry, Physical, Calculus. However,
the original model cannot easyly apply in inorganic chemistry
field because of the knowledge specific problems. So, the aim of
this article is to introduce how we extend the Computional Object
(Com-Object) in KBCO model, kinds of fact, problems model, and
inference algorithms to develop a program for solving problems
in inorganic chemistry. Our purpose is to develop the application
that can help students in their study inorganic chemistry at schools.
This application was built successful by using Maple, C# and WPF
technology. It can solve automatically problems and give human
readable solution agree with those writting by students and teachers.