Abstract: Applying a rigorous process to optimize the elements
of a supply-chain network resulted in reduction of the waiting time
for a service provider and customer. Different sources of downtime
of hydraulic pressure controller/calibrator (HPC) were causing
interruptions in the operations. The process examined all the issues to
drive greater efficiencies. The issues included inherent design issues
with HPC pump, contamination of the HPC with impurities, and the
lead time required for annual calibration in the USA.
HPC is used for mandatory testing/verification of formation
tester/pressure measurement/logging-while drilling tools by oilfield
service providers, including Halliburton.
After market study andanalysis, it was concluded that the current
HPC model is best suited in the oilfield industry. To use theexisting
HPC model effectively, design andcontamination issues were
addressed through design and process improvements. An optimum
network is proposed after comparing different supply-chain models
for calibration lead-time reduction.
Abstract: The paper presents a one-dimensional transient
mathematical model of compressible non-isothermal multicomponent
fluid mixture flow in a pipe. The set of the mass,
momentum and enthalpy conservation equations for gas phase is
solved in the model. Thermo-physical properties of multi-component
gas mixture are calculated by solving the Equation of State (EOS)
model. The Soave-Redlich-Kwong (SRK-EOS) model is chosen. Gas
mixture viscosity is calculated on the basis of the Lee-Gonzales-
Eakin (LGE) correlation. Numerical analysis of rapid gas
decompression process in rich and base natural gases is made on the
basis of the proposed mathematical model. The model is successfully
validated on the experimental data [1]. The proposed mathematical
model shows a very good agreement with the experimental data [1] in
a wide range of pressure values and predicts the decompression in
rich and base gas mixtures much better than analytical and
mathematical models, which are available from the open source
literature.
Abstract: The ideal sinc filter, ignoring the noise statistics, is often
applied for generating an arbitrary sample of a bandlimited signal by
using the uniformly sampled data. In this article, an optimal interpolator is proposed; it reaches a minimum mean square error (MMSE)
at its output in the presence of noise. The resulting interpolator is
thus a Wiener filter, and both the optimal infinite impulse response
(IIR) and finite impulse response (FIR) filters are presented. The
mean square errors (MSE-s) for the interpolator of different length
impulse responses are obtained by computer simulations; it shows that
the MSE-s of the proposed interpolators with a reasonable length are
improved about 0.4 dB under flat power spectra in noisy environment with signal-to-noise power ratio (SNR) equal 10 dB. As expected,
the results also demonstrate the improvements for the MSE-s with various fractional delays of the optimal interpolator against the ideal
sinc filter under a fixed length impulse response.
Abstract: In the recent past, there has been an increasing interest
in applying evolutionary methods to Knowledge Discovery in
Databases (KDD) and a number of successful applications of Genetic
Algorithms (GA) and Genetic Programming (GP) to KDD have been
demonstrated. The most predominant representation of the
discovered knowledge is the standard Production Rules (PRs) in the
form If P Then D. The PRs, however, are unable to handle
exceptions and do not exhibit variable precision. The Censored
Production Rules (CPRs), an extension of PRs, were proposed by
Michalski & Winston that exhibit variable precision and supports an
efficient mechanism for handling exceptions. A CPR is an
augmented production rule of the form:
If P Then D Unless C, where C (Censor) is an exception to the rule.
Such rules are employed in situations, in which the conditional
statement 'If P Then D' holds frequently and the assertion C holds
rarely. By using a rule of this type we are free to ignore the exception
conditions, when the resources needed to establish its presence are
tight or there is simply no information available as to whether it
holds or not. Thus, the 'If P Then D' part of the CPR expresses
important information, while the Unless C part acts only as a switch
and changes the polarity of D to ~D.
This paper presents a classification algorithm based on evolutionary
approach that discovers comprehensible rules with exceptions in the
form of CPRs.
The proposed approach has flexible chromosome encoding, where
each chromosome corresponds to a CPR. Appropriate genetic
operators are suggested and a fitness function is proposed that
incorporates the basic constraints on CPRs. Experimental results are
presented to demonstrate the performance of the proposed algorithm.
Abstract: Open Agent System platform based on High Level
Architecture is firstly proposed to support the application involving
heterogeneous agents. The basic idea is to develop different wrappers
for different agent systems, which are wrapped as federates to join a
federation. The platform is based on High Level Architecture and the
advantages for this open standard are naturally inherited, such as
system interoperability and reuse. Especially, the federal architecture
allows different federates to be heterogeneous so as to support the
integration of different agent systems. Furthermore, both implicit
communication and explicit communication between agents can be
supported. Then, as the wrapper RTI_JADE an example, the
components are discussed. Finally, the performance of RTI_JADE is
analyzed. The results show that RTI_JADE works very efficiently.
Abstract: In this paper we address a multi-objective scheduling problem for unrelated parallel machines. In unrelated parallel systems, the processing cost/time of a given job on different machines may vary. The objective of scheduling is to simultaneously determine the job-machine assignment and job sequencing on each machine. In such a way the total cost of the schedule is minimized. The cost function consists of three components, namely; machining cost, earliness/tardiness penalties and makespan related cost. Such scheduling problem is combinatorial in nature. Therefore, a Simulated Annealing approach is employed to provide good solutions within reasonable computational times. Computational results show that the proposed approach can efficiently solve such complicated problems.
Abstract: The protection issues in distribution systems with open and closed-loop are studied, and a generalized protection setting scheme based on the traditional over current protection theories is proposed to meet the new requirements. The setting method is expected to be easier realized using computer program, so that the on-line adaptive setting for coordination in distribution system can be implemented. An automatic setting program is created and several cases are taken into practice. The setting results are verified by the coordination curves of the protective devices which are plotted using MATLAB.
Abstract: Active vibration control is an important problem in
structures. The objective of active vibration control is to reduce the vibrations of a system by automatic modification of the system-s
structural response. In this paper, the modeling and design of a fast
output sampling feedback controller for a smart flexible beam system embedded with shear sensors and actuators for SISO system using
Timoshenko beam theory is proposed. FEM theory, Timoshenko beam theory and the state space techniques are used to model the
aluminum cantilever beam. For the SISO case, the beam is divided into 5 finite elements and the control actuator is placed at finite
element position 1, whereas the sensor is varied from position 2 to 5, i.e., from the nearby fixed end to the free end. Controllers are
designed using FOS method and the performance of the designed FOS controller is evaluated for vibration control for 4 SISO models
of the same plant. The effect of placing the sensor at different locations on the beam is observed and the performance of the
controller is evaluated for vibration control. Some of the limitations of the Euler-Bernoulli theory such as the neglection of shear and
axial displacement are being considered here, thus giving rise to an accurate beam model. Embedded shear sensors and actuators have
been considered in this paper instead of the surface mounted sensors
and actuators for vibration suppression because of lot of advantages. In controlling the vibration modes, the first three dominant modes of
vibration of the system are considered.
Abstract: The perfect operation of common Active Filters is depended on accuracy of identification system distortion. Also, using a suitable method in current injection and reactive power compensation, leads to increased filter performance. Due to this fact, this paper presents a method based on predictive current control theory in shunt active filter applications. The harmonics of the load current is identified by using o–d–q reference frame on load current and eliminating the DC part of d–q components. Then, the rest of these components deliver to predictive current controller as a Threephase reference current by using Park inverse transformation. System is modeled in discreet time domain. The proposed method has been tested using MATLAB model for a nonlinear load (with Total Harmonic Distortion=20%). The simulation results indicate that the proposed filter leads to flowing a sinusoidal current (THD=0.15%) through the source. In addition, the results show that the filter tracks the reference current accurately.
Abstract: Earthmoving operations are a major part of many
construction projects. Because of the complexity and fast-changing
environment of such operations, the planning and estimating are
crucial on both planning and operational levels. This paper presents
the framework ofa microscopic discrete-event simulation system for
modeling earthmoving operations and conducting productivity
estimations on an operational level.A prototype has been developed
to demonstrate the applicability of the proposed framework, and this
simulation system is presented via a case study based on an actual
earthmoving project. The case study shows that the proposed
simulation model is capable of evaluating alternative operating
strategies and resource utilization at a very detailed level.
Abstract: Heart disease (HD) is a major cause of morbidity and mortality in the modern society. Medical diagnosis is an important but complicated task that should be performed accurately and efficiently and its automation would be very useful. All doctors are unfortunately not equally skilled in every sub specialty and they are in many places a scarce resource. A system for automated medical diagnosis would enhance medical care and reduce costs. In this paper, a new approach based on coactive neuro-fuzzy inference system (CANFIS) was presented for prediction of heart disease. The proposed CANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach which is then integrated with genetic algorithm to diagnose the presence of the disease. The performances of the CANFIS model were evaluated in terms of training performances and classification accuracies and the results showed that the proposed CANFIS model has great potential in predicting the heart disease.
Abstract: Image restoration involves elimination of noise. Filtering techniques were adopted so far to restore images since last five decades. In this paper, we consider the problem of image restoration degraded by a blur function and corrupted by random noise. A method for reducing additive noise in images by explicit analysis of local image statistics is introduced and compared to other noise reduction methods. The proposed method, which makes use of an a priori noise model, has been evaluated on various types of images. Bayesian based algorithms and technique of image processing have been described and substantiated with experimentation using MATLAB.
Abstract: The objective this study was to characterize and
develop anthropomorphic liver phantoms in tomography hepatic
procedures for quality control and improvement professionals in
nuclear medicine. For the conformation of the anthropomorphic
phantom was used in plaster and acrylic. We constructed three
phantoms representing processes with liver cirrhosis. The phantoms
were filled with 99mTc diluted with water to obtain the scintigraphic
images. Tomography images were analyzed anterior and posterior
phantom representing a body with a greater degree cirrhotic. It was
noted that the phantoms allow the acquisition of images similar to
real liver with cirrhosis. Simulations of hemangiomas may contribute
to continued professional education of nuclear medicine, on the
question of image acquisition, allowing of the study parameters such
of the matrix, energy window and count statistics.
Abstract: Shot boundary detection is a fundamental step for the organization of large video data. In this paper, we propose a new method for video gradual shots detection and classification, using advantages of fractal analysis and AIS-based classifier. Proposed features are “vertical intercept" and “fractal dimension" of each frame of videos which are computed using Fourier transform coefficients. We also used a classifier based on Clonal Selection Algorithm. We have carried out our solution and assessed it according to the TRECVID2006 benchmark dataset.
Abstract: Many factors affect the success of Machine Learning
(ML) on a given task. The representation and quality of the instance
data is first and foremost. If there is much irrelevant and redundant
information present or noisy and unreliable data, then knowledge
discovery during the training phase is more difficult. It is well known
that data preparation and filtering steps take considerable amount of
processing time in ML problems. Data pre-processing includes data
cleaning, normalization, transformation, feature extraction and
selection, etc. The product of data pre-processing is the final training
set. It would be nice if a single sequence of data pre-processing
algorithms had the best performance for each data set but this is not
happened. Thus, we present the most well know algorithms for each
step of data pre-processing so that one achieves the best performance
for their data set.
Abstract: Classes on creativity, innovation, and entrepreneurship
are becoming quite popular at universities throughout the world.
However, it is not easy for business students to get involved to
innovative activities, especially patent application. The present study
investigated how to enhance business students- intention to participate
in innovative activities and which incentives universities should
consider. A 22-item research scale was used, and confirmatory factor
analysis was conducted to verify its reliability and validity. Multiple
regression and discriminant analyses were also conducted. The results
demonstrate the effect of growth-need strength on innovative behavior
and indicate that the theory of planned behavior can explain and
predict business students- intention to participate in innovative
activities. Additionally, the results suggest that applying our proposed
model in practice would effectively strengthen business students-
intentions to engage in innovative activities.
Abstract: This article proposes modeling, simulation and
kinematic and workspace analysis of a spatial cable suspended robot
as incompletely Restrained Positioning Mechanism (IRPM). These
types of robots have six cables equal to the number of degrees of
freedom. After modeling, the kinds of workspace are defined then an
statically reachable combined workspace for different geometric
structures of fixed and moving platform is obtained. This workspace
is defined as the situations of reference point of the moving platform
(center of mass) which under external forces such as weight and with
ignorance of inertial effects, the moving platform should be in static
equilibrium under conditions that length of all cables must not be
exceeded from the maximum value and all of cables must be at
tension (they must have non-negative tension forces). Then the effect
of various parameters such as the size of moving platform, the size of
fixed platform, geometric configuration of robots, magnitude of
applied forces and moments to moving platform on workspace of
these robots with different geometric configuration are investigated.
Obtained results should be effective in employing these robots under
different conditions of applied wrench for increasing the workspace
volume.
Abstract: Wireless Sensor Network (WSN) comprises of sensor
nodes which are designed to sense the environment, transmit sensed
data back to the base station via multi-hop routing to reconstruct
physical phenomena. Since physical phenomena exists significant
overlaps between temporal redundancy and spatial redundancy, it is
necessary to use Redundancy Suppression Algorithms (RSA) for sensor
node to lower energy consumption by reducing the transmission
of redundancy. A conventional algorithm of RSAs is threshold-based
RSA, which sets threshold to suppress redundant data. Although
many temporal and spatial RSAs are proposed, temporal-spatial RSA
are seldom to be proposed because it is difficult to determine when
to utilize temporal or spatial RSAs. In this paper, we proposed a
novel temporal-spatial redundancy suppression algorithm, Codebookbase
Redundancy Suppression Mechanism (CRSM). CRSM adopts
vector quantization to generate a codebook, which is easily used to
implement temporal-spatial RSA. CRSM not only achieves power
saving and reliability for WSN, but also provides the predictability
of network lifetime. Simulation result shows that the network lifetime
of CRSM outperforms at least 23% of that of other RSAs.
Abstract: This paper addresses a stock-cutting problem with rotation of items and without the guillotine cutting constraint. In order to solve the large-scale problem effectively and efficiently, we propose a simple but fast heuristic algorithm. It is shown that this heuristic outperforms the latest published algorithms for large-scale problem instances.
Abstract: In this paper, a design methodology to implement low-power and high-speed 2nd order recursive digital Infinite Impulse Response (IIR) filter has been proposed. Since IIR filters suffer from a large number of constant multiplications, the proposed method replaces the constant multiplications by using addition/subtraction and shift operations. The proposed new 6T adder cell is used as the Carry-Save Adder (CSA) to implement addition/subtraction operations in the design of recursive section IIR filter to reduce the propagation delay. Furthermore, high-level algorithms designed for the optimization of the number of CSA blocks are used to reduce the complexity of the IIR filter. The DSCH3 tool is used to generate the schematic of the proposed 6T CSA based shift-adds architecture design and it is analyzed by using Microwind CAD tool to synthesize low-complexity and high-speed IIR filters. The proposed design outperforms in terms of power, propagation delay, area and throughput when compared with MUX-12T, MCIT-7T based CSA adder filter design. It is observed from the experimental results that the proposed 6T based design method can find better IIR filter designs in terms of power and delay than those obtained by using efficient general multipliers.