Abstract: This paper presents an optimization technique to economic load dispatch (ELD) problems with considering the daily load patterns and generator constraints using a particle swarm optimization (PSO). The objective is to minimize the fuel cost. The optimization problem is subject to system constraints consisting of power balance and generation output of each units. The application of a constriction factor into PSO is a useful strategy to ensure convergence of the particle swarm algorithm. The proposed method is able to determine, the output power generation for all of the power generation units, so that the total constraint cost function is minimized. The performance of the developed methodology is demonstrated by case studies in test system of fifteen-generation units. The results show that the proposed algorithm scan give the minimum total cost of generation while satisfying all the constraints and benefiting greatly from saving in power loss reduction
Abstract: Traditional multivariate control charts assume that measurement from manufacturing processes follows a multivariate normal distribution. However, this assumption may not hold or may be difficult to verify because not all the measurement from manufacturing processes are normal distributed in practice. This study develops a new multivariate control chart for monitoring the processes with non-normal data. We propose a mechanism based on integrating the one-class classification method and the adaptive technique. The adaptive technique is used to improve the sensitivity to small shift on one-class classification in statistical process control. In addition, this design provides an easy way to allocate the value of type I error so it is easier to be implemented. Finally, the simulation study and the real data from industry are used to demonstrate the effectiveness of the propose control charts.
Abstract: Infrared communication in the wavelength band 780-
950 nm is very suitable for short-range point-to-point communications.
It is a good choice for vehicle-to-vehicle communication in several
intelligent-transportation-system (ITS) applications such as cooperative
driving, collision warning, and pileup-crash prevention. In this
paper, with the aid of a physical model established in our previous
works, we explore the communication area of an infrared intervehicle
communication system utilizing a typical low-cost cormmercial lightemitting
diodes (LEDs) as the emitter and planar p-i-n photodiodes
as the receiver. The radiation pattern of the emitter fabricated by
aforementioned LEDs and the receiving pattern of the receiver are
approximated by a linear combination of cosinen functions. This
approximation helps us analyze the system performance easily. Both
multilane straight-road conditions and curved-road conditions with
various radius of curvature are taken into account. The condition of
a small car communicating with a big truck, i.e., there is a vertical
mounting height difference between the emitter and the receiver, is
also considered. Our results show that the performance of the system
meets the requirement of aforementioned ITS applications in terms
of the communication area.
Abstract: In this paper, we introduce a new method for elliptical
object identification. The proposed method adopts a hybrid scheme
which consists of Eigen values of covariance matrices, Circular
Hough transform and Bresenham-s raster scan algorithms. In this
approach we use the fact that the large Eigen values and small Eigen
values of covariance matrices are associated with the major and minor
axial lengths of the ellipse. The centre location of the ellipse can be
identified using circular Hough transform (CHT). Sparse matrix
technique is used to perform CHT. Since sparse matrices squeeze zero
elements and contain a small number of nonzero elements they
provide an advantage of matrix storage space and computational time.
Neighborhood suppression scheme is used to find the valid Hough
peaks. The accurate position of circumference pixels is identified
using raster scan algorithm which uses the geometrical symmetry
property. This method does not require the evaluation of tangents or
curvature of edge contours, which are generally very sensitive to
noise working conditions. The proposed method has the advantages of
small storage, high speed and accuracy in identifying the feature. The
new method has been tested on both synthetic and real images.
Several experiments have been conducted on various images with
considerable background noise to reveal the efficacy and robustness.
Experimental results about the accuracy of the proposed method,
comparisons with Hough transform and its variants and other
tangential based methods are reported.
Abstract: This paper proposes a simple model of economic geography within the Dixit-Stiglitz-Iceberg framework that may be used to analyze migration patterns among three cities. The cost–benefit tradeoffs affecting incentives for three types of migration, including echelon migration, are discussed. This paper develops a tractable, heterogeneous-agent, general equilibrium model, where agents share constant human capital, and explores the relationship between the benefits of echelon migration and gross human capital. Using Chinese numerical solutions, we study the manifestation of echelon migration and how it responds to changes in transportation cost and elasticity of substitution. Numerical results demonstrate that (i) there are positive relationships between a migration-s benefit-and-wage ratio, (ii) there are positive relationships between gross human capital ratios and wage ratios as to origin and destination, and (iii) we identify 13 varieties of human capital convergence among cities. In particular, this model predicts population shock resulting from the processes of migration choice and echelon migration.
Abstract: In this paper, based on the coupled-mode and carrier rate equations, derivation of a dynamic model and numerically analysis of a MQW chirped DFB-SOA all-optical flip-flop is done precisely. We have analyzed the effects of strains of QW and MQW and cross phase modulation (XPM) on the dynamic response, and rise and fall times of the DFB-SOA all optical flip flop. We have shown that strained MQW active region in under an optimized condition into a DFB-SOA with chirped grating can improve the switching ON speed limitation in such a of the device, significantly while the fall time is increased. The values of the rise times for such an all optical flip-flop, are obtained in an optimized condition, areas tr=255ps.
Abstract: A Rotary Disc Contactor with inner diameter of
9.1cm and maximum operating height of 40cm has been used to
investigate break up phenomenon. Water-Toluene, Water as
continuous phase and Toluene as dispersed phase, was selected as
chemical system in the experiments. The mentioned chemical system
has high interfacial tension so it was possible to form big drops
which permit accurate investigation on break up phenomenon as well
as the first and second critical rotor speeds.
In this study, Break up phenomenon has been studied as a function
of mother drop size, rotor speed and continuous phase height. Further
more; the effects of mother drop size and continuous phase height on
the first and second critical rotor speeds were investigated. Finally,
two modified correlations were proposed to estimate the first and
second critical speeds.
Abstract: To improve HSE standards, oil and gas industries are
interested in using remotely controlled and autonomous robots instead
of human workers on offshore platforms. In addition to earlier reason
this strategy would increase potential revenue, efficient usage of
work experts and even would allow operations in more remote areas.
This article is the presentation of a custom climbing robot, called
Walloid, designed for offshore platform topside automation. This 4
arms climbing robot with grippers is an ongoing project at University
of Oslo.
Abstract: The dome with ribs and rings, which covers the
ROMEXPO pavilion from Bucharest, was designed after the collapse
of the single layer reticulated dome. In this paper, it was made the
checking of the structure, under the dynamic loads with three
recorded accelerograms calibrated according to Romanian seismic
design code P100-1/2006. Under the action the dynamic loadings, it
was made a time-history analysis to determine the zones where the
plastic hinges appear, at what accelerations and their position on the
structure. The studied dome is formed by 32 spatial semi arches and
three rings: one circular ring located at the top of the dome and
another two rings, design as trusses, the first near the supports and the
second as an intermediate rings above the skylights. Above the
skylights up to the top, the dome is tight together with purlins and
bracings.
Abstract: In this paper, the modelling and design of artificial neural network architecture for load forecasting purposes is investigated. The primary pre-requisite for power system planning is to arrive at realistic estimates of future demand of power, which is known as Load Forecasting. Short Term Load Forecasting (STLF) helps in determining the economic, reliable and secure operating strategies for power system. The dependence of load on several factors makes the load forecasting a very challenging job. An over estimation of the load may cause premature investment and unnecessary blocking of the capital where as under estimation of load may result in shortage of equipment and circuits. It is always better to plan the system for the load slightly higher than expected one so that no exigency may arise. In this paper, a load-forecasting model is proposed using a multilayer neural network with an appropriately modified back propagation learning algorithm. Once the neural network model is designed and trained, it can forecast the load of the power system 24 hours ahead on daily basis and can also forecast the cumulative load on daily basis. The real load data that is used for the Artificial Neural Network training was taken from LDC, Gujarat Electricity Board, Jambuva, Gujarat, India. The results show that the load forecasting of the ANN model follows the actual load pattern more accurately throughout the forecasted period.
Abstract: A geothermal power plant multiple simulator for
operators training is presented. The simulator is designed to be
installed in a wireless local area network and has a capacity to train
one to six operators simultaneously, each one with an independent
simulation session. The sessions must be supervised only by one
instructor. The main parts of this multiple simulator are: instructor
and operator-s stations. On the instructor station, the instructor
controls the simulation sessions, establishes training exercises and
supervises each power plant operator in individual way. This station
is hosted in a Main Personal Computer (NS) and its main functions
are: to set initial conditions, snapshots, malfunctions or faults,
monitoring trends, and process and soft-panel diagrams. On the other
hand the operators carry out their actions over the power plant
simulated on the operator-s stations; each one is also hosted in a PC.
The main software of instructor and operator-s stations are executed
on the same NS and displayed in PCs through graphical Interactive
Process Diagrams (IDP). The geothermal multiple simulator has been
installed in the Geothermal Simulation Training Center (GSTC) of
the Comisi├│n Federal de Electricidad, (Federal Commission of
Electricity, CFE), Mexico, and is being utilized as a part of the
training courses for geothermal power plant operators.
Abstract: The evaluation of non-conventional water resources
on seed germination and seedling growth performance at early
growth stages is still in progress especially in forage crops. This
study was designed to test the effect of four types of water qualities
(treated wastewater (TWW), industrial water (IW), grey water (GW),
and Distilled water (DW)) on germination and early seedling vigor of
Leucaena leucocephala. The results showed that the germination
was not significantly affected by the different water qualities. Seed
germination reached maximum after 17, 14, 14, and 21 days under
GW, IW, TWW, and DW treatments, respectively. The highest mean
of shoot length was scored under the GW treatment. And, the highest
mean of root length was scored under DW which was not significant
from GW treatment. The means of shoot fresh was the highest under
the TWW. The means of root fresh weight was not significantly
different from each other's under different treatments. The growth
performance was in progress with no mortality during 21 days of
growth. Thus, the best non-conventional water qualities alternatives
based on the cleanness, nutrients, and toxicity are the GW, TWW and
IW, respectively.
Abstract: Communication is an important factor and a prop in
directing corporate activities efficiently, in ensuring the flow of
knowledge which is necessary for the continuity of the institution, in
creating a common language in the institution, in transferring
corporate culture and ultimately in corporate success. The idea of
transmitting the knowledge among the workers in a healthy manner
has revived knowledge communication. Knowledge communication
can be defined as the act of mutual creation and communication of
intuitions, assessments, experiences and capabilities, as long as
maintained effectively, can provide advantages such as corporate
continuity, access to corporate objectives and making true
administrative decisions. Although the benefits of the knowledge
communication to corporations are known, and the necessary worth
and care is given, some hardships may arise which makes it difficult
or even block it. In this article, difficulties that prevent knowledge
communication will be discussed and solutions will be proposed.
Abstract: In pattern recognition applications the low level
segmentation and the high level object recognition are generally
considered as two separate steps. The paper presents a method that
bridges the gap between the low and the high level object
recognition. It is based on a Bayesian network representation and
network propagation algorithm. At the low level it uses hierarchical
structure of quadratic spline wavelet image bases. The method is
demonstrated for a simple circuit diagram component identification
problem.
Abstract: The state of melt viscosity in injection process is significantly influenced by the setting parameters due to that the shear rate of injection process is higher than other processes. How to determine plastic melt viscosity during injection process is important to understand the influence of setting parameters on the melt viscosity. An apparatus named as pressure sensor bushing (PSB) module that is used to evaluate the melt viscosity during injection process is developed in this work. The formulations to coupling melt viscosity with fill time and injection pressure are derived and then the melt viscosity is determined. A test mold is prepared to evaluate the accuracy on viscosity calculations between the PSB module and the conventional approaches. The influence of melt viscosity on the tensile strength of molded part is proposed to study the consistency of injection quality.
Abstract: Major social changes in the last century had significant impact on the Kazakh literature. Participants of the World War II, writers and poets imprisoned during the war, formed the Kazakh literature in emigration within the framework of 'Turkistan Legion'. This was a topic which remained closed until Kazakhstan gained its independence, though even after the independence, there were few research works done about the literature in emigration. The article studies the formation of the Kazakh literature in emigration, its prominent figures, its artistic heritage, and notes of emigration in works of poets and writers.
Abstract: This study considers the problem of determining
operation and maintenance schedules for a containership equipped
with components during its sailing according to a pre-determined
navigation schedule. The operation schedule, which specifies work
time of each component, determines the due-date of each maintenance
activity, and the maintenance schedule specifies the actual start
time of each maintenance activity. The main constraints are component
requirements, workforce availability, working time limitation,
and inter-maintenance time. To represent the problem mathematically,
a mixed integer programming model is developed. Then,
due to the problem complexity, we suggest a heuristic for the objective
of minimizing the sum of earliness and tardiness between the
due-date and the starting time of each maintenance activity. Computational
experiments were done on various test instances and the
results are reported.
Abstract: When the profile information of an existing road is
missing or not up-to-date and the parameters of the vertical
alignment are needed for engineering analysis, the engineer has to recreate
the geometric design features of the road alignment using
collected profile data. The profile data may be collected using
traditional surveying methods, global positioning systems, or digital
imagery. This paper develops a method that estimates the parameters
of the geometric features that best characterize the existing vertical
alignments in terms of tangents and the expressions of the curve, that
may be symmetrical, asymmetrical, reverse, and complex vertical
curves. The method is implemented using an Excel-based
optimization method that minimizes the differences between the
observed profile and the profiles estimated from the equations of the
vertical curve. The method uses a 'wireframe' representation of the
profile that makes the proposed method applicable to all types of
vertical curves. A secondary contribution of this paper is to introduce
the properties of the equal-arc asymmetrical curve that has been
recently developed in the highway geometric design field.
Abstract: In this paper in consideration of each available
techniques deficiencies for speech recognition, an advanced method
is presented that-s able to classify speech signals with the high
accuracy (98%) at the minimum time. In the presented method, first,
the recorded signal is preprocessed that this section includes
denoising with Mels Frequency Cepstral Analysis and feature
extraction using discrete wavelet transform (DWT) coefficients; Then
these features are fed to Multilayer Perceptron (MLP) network for
classification. Finally, after training of neural network effective
features are selected with UTA algorithm.
Abstract: The goal of this work is to improve the efficiency and the reliability of the automatic artifact rejection, in particular from the Electroencephalographic (EEG) recordings. Artifact rejection is a key topic in signal processing. The artifacts are unwelcome signals that may occur during the signal acquisition and that may alter the analysis of the signals themselves. A technique for the automatic artifact rejection, based on the Independent Component Analysis (ICA) for the artifact extraction and on some high order statistics such as kurtosis and Shannon-s entropy, was proposed some years ago in literature. In this paper we enhance this technique introducing the Renyi-s entropy. The performance of our method was tested exploiting the Independent Component scalp maps and it was compared to the performance of the method in literature and it showed to outperform it.