Abstract: Tip vortex cavitation is one of well known patterns of
cavitation phenomenon which occurs in axial pumps. This pattern of
cavitation occurs due to pressure difference between the pressure and
suction sides of blades of an axial pump. Since the pressure in the
pressure side of the blade is higher than the pressure in its suction
side, thus a very small portion of liquid flow flows back from
pressure side to the suction side. This fact is cause of tip vortex
cavitation and gap cavitation that may occur in axial pumps. In this
paper the results of our experimental investigation about movement
of tip vortex cavitation along blade edge due to reduction of pump
flow rate in an axial pump is reported. Results show that reduction of
pump flow rate in conjunction with increasing of outlet pressure
causes movement of tip vortex cavitation along blade edge towards
the blade tip. Results also show that by approaching tip vortex
cavitation to the blade tip, vortex tip pattern of cavitation replaces
with a cavitation phenomenon on the blade tip. Furthermore by
further reduction of pump flow rate and increasing of outlet pressure,
an unstable cavitation phenomenon occurs between each blade
leading edge and the next blade trailing edge.
Abstract: Three service providers in competition, try to optimize
their quality of service / content level and their service access
price. But, they have to deal with uncertainty on the consumers-
preferences. To reduce their uncertainty, they have the opportunity
to buy information and to build alliances. We determine the Shapley
value which is a fair way to allocate the grand coalition-s revenue
between the service providers. Then, we identify the values of β
(consumers- sensitivity coefficient to the quality of service / contents)
for which allocating the grand coalition-s revenue using the Shapley
value guarantees the system stability. For other values of β, we prove
that it is possible for the regulator to impose a per-period interest rate
maximizing the market coverage under equal allocation rules.
Abstract: This article presents a computationally tractable probabilistic model for the relation between the complex wavelet coefficients of two images of the same scene. The two images are acquisitioned at distinct moments of times, or from distinct viewpoints, or by distinct sensors. By means of the introduced probabilistic model, we argue that the similarity between the two images is controlled not by the values of the wavelet coefficients, which can be altered by many factors, but by the nature of the wavelet coefficients, that we model with the help of hidden state variables. We integrate this probabilistic framework in the construction of a new image registration algorithm. This algorithm has sub-pixel accuracy and is robust to noise and to other variations like local illumination changes. We present the performance of our algorithm on various image types.
Abstract: Interior brick-infill partitions are usually considered as
non-structural components, and only their weight is accounted for in
practical structural design. In this study, the brick-infill panels are
simulated by compression struts to clarify their effect on the
progressive collapse potential of an earthquake-resistant RC building.
Three-dimensional finite element models are constructed for the RC
building subjected to sudden column loss. Linear static analyses are
conducted to investigate the variation of demand-to-capacity ratio
(DCR) of beam-end moment and the axial force variation of the beams
adjacent to the removed column. Study results indicate that the
brick-infill effect depends on their location with respect to the
removed column. As they are filled in a structural bay with a shorter
span adjacent to the column-removed line, more significant reduction
of DCR may be achieved. However, under certain conditions, the
brick infill may increase the axial tension of the two-span beam
bridging the removed column.
Abstract: Nowadays there is a growing interest in biofuel production in most countries because of the increasing concerns about hydrocarbon fuel shortage and global climate changes, also for enhancing agricultural economy and producing local needs for transportation fuel. Ethanol can be produced from biomass by the hydrolysis and sugar fermentation processes. In this study ethanol was produced without using expensive commercial enzymes from sugarcane bagasse. Alkali pretreatment was used to prepare biomass before enzymatic hydrolysis. The comparison between NaOH, KOH and Ca(OH)2 shows NaOH is more effective on bagasse. The required enzymes for biomass hydrolysis were produced from sugarcane solid state fermentation via two fungi: Trichoderma longibrachiatum and Aspergillus niger. The results show that the produced enzyme solution via A. niger has functioned better than T. longibrachiatum. Ethanol was produced by simultaneous saccharification and fermentation (SSF) with crude enzyme solution from T. longibrachiatum and Saccharomyces cerevisiae yeast. To evaluate this procedure, SSF of pretreated bagasse was also done using Celluclast 1.5L by Novozymes. The yield of ethanol production by commercial enzyme and produced enzyme solution via T. longibrachiatum was 81% and 50% respectively.
Abstract: Feature selection has recently been the subject of intensive research in data mining, specially for datasets with a large number of attributes. Recent work has shown that feature selection can have a positive effect on the performance of machine learning algorithms. The success of many learning algorithms in their attempts to construct models of data, hinges on the reliable identification of a small set of highly predictive attributes. The inclusion of irrelevant, redundant and noisy attributes in the model building process phase can result in poor predictive performance and increased computation. In this paper, a novel feature search procedure that utilizes the Ant Colony Optimization (ACO) is presented. The ACO is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It looks for optimal solutions by considering both local heuristics and previous knowledge. When applied to two different classification problems, the proposed algorithm achieved very promising results.
Abstract: The visualization of geographic information on mobile devices has become popular as the widespread use of mobile Internet. The mobility of these devices brings about much convenience to people-s life. By the add-on location-based services of the devices, people can have an access to timely information relevant to their tasks. However, visual analysis of geographic data on mobile devices presents several challenges due to the small display and restricted computing resources. These limitations on the screen size and resources may impair the usability aspects of the visualization applications. In this paper, a variable-scale visualization method is proposed to handle the challenge of small mobile display. By merging multiple scales of information into a single image, the viewer is able to focus on the interesting region, while having a good grasp of the surrounding context. This is essentially visualizing the map through a fisheye lens. However, the fisheye lens induces undesirable geometric distortion in the peripheral, which renders the information meaningless. The proposed solution is to apply map generalization that removes excessive information around the peripheral and an automatic smoothing process to correct the distortion while keeping the local topology consistent. The proposed method is applied on both artificial and real geographical data for evaluation.
Abstract: A generalized Dirichlet to Neumann map is
one of the main aspects characterizing a recently introduced
method for analyzing linear elliptic PDEs, through which it
became possible to couple known and unknown components
of the solution on the boundary of the domain without
solving on its interior. For its numerical solution, a well conditioned
quadratically convergent sine-Collocation method
was developed, which yielded a linear system of equations
with the diagonal blocks of its associated coefficient matrix
being point diagonal. This structural property, among others,
initiated interest for the employment of iterative methods for
its solution. In this work we present a conclusive numerical
study for the behavior of classical (Jacobi and Gauss-Seidel)
and Krylov subspace (GMRES and Bi-CGSTAB) iterative
methods when they are applied for the solution of the Dirichlet
to Neumann map associated with the Laplace-s equation
on regular polygons with the same boundary conditions on
all edges.
Abstract: AAM (active appearance model) has been successfully
applied to face and facial feature localization. However, its performance is sensitive to initial parameter values. In this paper, we propose a two-stage AAM for robust face alignment, which first fits an
inner face-AAM model to the inner facial feature points of the face and then localizes the whole face and facial features by optimizing the
whole face-AAM model parameters. Experiments show that the proposed face alignment method using two-stage AAM is more reliable to the background and the head pose than the standard
AAM-based face alignment method.
Abstract: In online context, the design and implementation of
effective remote laboratories environment is highly challenging on
account of hardware and software needs. This paper presents the
remote laboratory software framework modified from ilab shared
architecture (ISA). The ISA is a framework which enables students to
remotely acccess and control experimental hardware using internet
infrastructure. The need for remote laboratories came after
experiencing problems imposed by traditional laboratories. Among
them are: the high cost of laboratory equipment, scarcity of space,
scarcity of technical personnel along with the restricted university
budget creates a significant bottleneck on building required
laboratory experiments. The solution to these problems is to build
web-accessible laboratories. Remote laboratories allow students and
educators to interact with real laboratory equipment located
anywhere in the world at anytime. Recently, many universities and
other educational institutions especially in third world countries rely
on simulations because they do not afford the experimental
equipment they require to their students. Remote laboratories enable
users to get real data from real-time hand-on experiments. To
implement many remote laboratories, the system architecture should
be flexible, understandable and easy to implement, so that different
laboratories with different hardware can be deployed easily. The
modifications were made to enable developers to add more
equipment in ISA framework and to attract the new developers to
develop many online laboratories.
Abstract: Due to its geographical location, Iran is considered one of the earthquake-prone areas where the best way to decrease earthquake effects is supposed to be strengthening the buildings. Even though, one idea suggests that the use of adobe in constructing buildings be prohibited for its weak function especially in earthquake-prone areas, however, regarding ecological considerations, sustainability and other local skills, another idea pays special attention to adobe as one of the construction technologies which is popular among people. From the architectural and technological point of view, as strong sustainable building construction materials, compressed adobe construction materials make most of the construction in urban or rural areas ranging from small to big industrial buildings used to replace common earth blocks in traditional systems and strengthen traditional adobe buildings especially against earthquake. Mentioning efficient construction using compressed adobe system as a reliable replacement for traditional soil construction materials , this article focuses on the experiences of India in the fields of sustainable development of compressed adobe systems in the form of system in which the compressed soil is combined with cement, load bearing building with brick/solid concrete block system, brick system using rat trap bond, metal system with adobe infill and finally emphasizes on the use of these systems in the earthquake-struck city of Bam in Iran.
Abstract: The hidden-point bar method is useful in many
surveying applications. The method involves determining the
coordinates of a hidden point as a function of horizontal and vertical
angles measured to three fixed points on the bar. Using these
measurements, the procedure involves calculating the slant angles,
the distances from the station to the fixed points, the coordinates of
the fixed points, and then the coordinates of the hidden point. The
propagation of the measurement errors in this complex process has
not been fully investigated in the literature. This paper evaluates the
effect of the bar geometry on the position accuracy of the hidden
point which depends on the measurement errors of the horizontal and
vertical angles. The results are used to establish some guidelines
regarding the inclination angle of the bar and the location of the
observed points that provide the best accuracy.
Abstract: This paper proposes a bi-objective model for the
facility location problem under a congestion system. The idea of the
model is motivated by applications of locating servers in bank
automated teller machines (ATMS), communication networks, and so
on. This model can be specifically considered for situations in which
fixed service facilities are congested by stochastic demand within
queueing framework. We formulate this model with two perspectives
simultaneously: (i) customers and (ii) service provider. The
objectives of the model are to minimize (i) the total expected
travelling and waiting time and (ii) the average facility idle-time.
This model represents a mixed-integer nonlinear programming
problem which belongs to the class of NP-hard problems. In addition,
to solve the model, two metaheuristic algorithms including nondominated
sorting genetic algorithms (NSGA-II) and non-dominated
ranking genetic algorithms (NRGA) are proposed. Besides, to
evaluate the performance of the two algorithms some numerical
examples are produced and analyzed with some metrics to determine
which algorithm works better.
Abstract: In this paper, we propose a new hybrid learning model for stock market indices prediction by adding a passive congregation term to the standard hybrid model comprising Particle Swarm Optimization (PSO) with Genetic Algorithm (GA) operators in training Neural Networks (NN). This new passive congregation term is based on the cooperation between different particles in determining new positions rather than depending on the particles selfish thinking without considering other particles positions, thus it enables PSO to perform both the local and global search instead of only doing the local search. Experiment study carried out on the most famous European stock market indices in both long term and short term prediction shows significantly the influence of the passive congregation term in improving the prediction accuracy compared to standard hybrid model.
Abstract: High level and high velocity flood flows are
potentially harmful to bridge piers as evidenced in many toppled
piers, and among them the single-column piers were considered as
the most vulnerable. The flood flow characteristic parameters
including drag coefficient, scouring and vortex shedding are built into
a pier-flood interaction model to investigate structural safety against
flood hazards considering the effects of local scouring, hydrodynamic
forces, and vortex induced resonance vibrations. By extracting the
pier-flood simulation results embedded in a neural networks code,
two cases of pier toppling occurred in typhoon days were reexamined:
(1) a bridge overcome by flash flood near a mountain side;
(2) a bridge washed off in flood across a wide channel near the
estuary. The modeling procedures and simulations are capable of
identifying the probable causes for the tumbled bridge piers during
heavy floods, which include the excessive pier bending moments and
resonance in structural vibrations.
Abstract: The conventional GA combined with a local search
algorithm, such as the 2-OPT, forms a hybrid genetic algorithm(HGA)
for the traveling salesman problem (TSP). However, the geometric
properties which are problem specific knowledge can be used to
improve the search process of the HGA. Some tour segments (edges)
of TSPs are fine while some maybe too long to appear in a short tour.
This knowledge could constrain GAs to work out with fine tour
segments without considering long tour segments as often.
Consequently, a new algorithm is proposed, called intelligent-OPT
hybrid genetic algorithm (IOHGA), to improve the GA and the 2-OPT
algorithm in order to reduce the search time for the optimal solution.
Based on the geometric properties, all the tour segments are assigned
2-level priorities to distinguish between good and bad genes. A
simulation study was conducted to evaluate the performance of the
IOHGA. The experimental results indicate that in general the IOHGA
could obtain near-optimal solutions with less time and better accuracy
than the hybrid genetic algorithm with simulated annealing algorithm
(HGA(SA)).
Abstract: Electronic voting (E-voting) using an internet has been
recently performed in some nations and regions. There is no spatial
restriction which a voter directly has to visit the polling place, but an
e-voting using an internet has to go together the computer in which the
internet connection is possible. Also, this voting requires an access
code for the e-voting through the beforehand report of a voter. To
minimize these disadvantages, we propose a method in which a voter,
who has the wireless certificate issued in advance, uses its own cellular
phone for an e-voting without the special registration for a vote. Our
proposal allows a voter to cast his vote in a simple and convenient way
without the limit of time and location, thereby increasing the voting
rate, and also ensuring confidentiality and anonymity.
Abstract: This paper presents a Neural Network (NN) identification of icing parameters in an A340 aircraft and a reconfiguration technique to keep the A/C performance close to the performance prior to icing. Five aircraft parameters are assumed to be considerably affected by icing. The off-line training for identifying the clear and iced dynamics is based on the Levenberg-Marquard Backpropagation algorithm. The icing parameters are located in the system matrix. The physical locations of the icing are assumed at the right and left wings. The reconfiguration is based on the technique known as the control mixer approach or pseudo inverse technique. This technique generates the new control input vector such that the A/C dynamics is not much affected by icing. In the simulations, the longitudinal and lateral dynamics of an Airbus A340 aircraft model are considered, and the stability derivatives affected by icing are identified. The simulation results show the successful NN identification of the icing parameters and the reconfigured flight dynamics having the similar performance before the icing. In other words, the destabilizing icing affect is compensated.
Abstract: This paper discusses a new model of Islamic code of
ethics for directors. Several corporate scandals and local (example
Transmile and Megan Media) and overseas corporate (example
Parmalat and Enron) collapses show that the current corporate
governance and regulatory reform are unable to prevent these events
from recurring. Arguably, the code of ethics for directors is under
research and the current code of ethics only concentrates on binding
the work of the employee of the organization as a whole, without
specifically putting direct attention to the directors, the group of
people responsible for the performance of the company. This study
used a semi-structured interview survey of well-known Islamic
scholars such as the Mufti to develop the model. It is expected that
the outcome of the research is a comprehensive model of code of
ethics based on the Islamic principles that can be applied and used by
the company to construct a code of ethics for their directors.
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.