Abstract: Loop detectors report traffic characteristics in real
time. They are at the core of traffic control process. Intuitively,
one would expect that as density of detection increases, so would
the quality of estimates derived from detector data. However, as
detector deployment increases, the associated operating and
maintenance cost increases. Thus, traffic agencies often need to
decide where to add new detectors and which detectors should
continue receiving maintenance, given their resource constraints.
This paper evaluates the effect of detector spacing on freeway
travel time estimation. A freeway section (Interstate-15) in Salt
Lake City metropolitan region is examined. The research reveals
that travel time accuracy does not necessarily deteriorate with
increased detector spacing. Rather, the actual location of detectors
has far greater influence on the quality of travel time estimates.
The study presents an innovative computational approach that
delivers optimal detector locations through a process that relies on
Genetic Algorithm formulation.
Abstract: The problem of manipulator control is a highly
complex problem of controlling a system which is multi-input, multioutput,
non-linear and time variant. In this paper some adaptive
fuzzy, and a new hybrid fuzzy control algorithm have been
comparatively evaluated through simulations, for manipulator
control. The adaptive fuzzy controllers consist of self-organizing,
self-tuning, and coarse/fine adaptive fuzzy schemes. These
controllers are tested for different trajectories and for varying
manipulator parameters through simulations. Various performance
indices like the RMS error, steady state error and maximum error are
used for comparison. It is observed that the self-organizing fuzzy
controller gives the best performance. The proposed hybrid fuzzy
plus integral error controller also performs remarkably well, given its
simple structure.
Abstract: In production of medicinal plants, seed germination is
very important problem. The treated seeds (control, hydro priming
and ZnSO4) of Cumin (Cuminum cyminum L.) were evaluated at
germination and seedling growth for tolerance to salt (NaCl and
Na2SO4) conditions at the same water potentials of 0.0, -0.3, -0.6, -
0.9 and -1.2MPa. Electrical conductivity (EC) values of the NaCl
solutions were 0.0, 6.5, 12.7, 18.4 and 23.5 dSm-1, respectively. The
objective of the study was to determine factors responsible for
germination and early seedling growth due to salt toxicity or osmotic
effect and to optimize the best priming treatment for these stress
conditions. Results revealed that germination delayed in both
solutions, having variable germination with different priming
treatments. Germination, shoot and weight, root and shoot length
were higher but mean germination time and abnormal germination
percentage were lower in NaCl than Na2SO4 at the same water
potential. The root / shoot weight and R/S length increased with
increase in osmotic potential in both NaCl and Na2SO4 solutions.
NaCl had less inhibitor effect on seedling growth than the
germination. It was concluded that inhibition of germination at the
same water potential of NaCl and Na2SO4 resulted from salt toxicity
rather than osmotic effect. Hydro priming increased germination and
seedling growth under salt stress. This protocol has practical
importance and could be recommended to farmers to achieve higher
germination and uniform emergence under field conditions.
Abstract: Wireless sensor networks include small nodes which
have sensing ability; calculation and connection extend themselves
everywhere soon. Such networks have source limitation on
connection, calculation and energy consumption. So, since the nodes
have limited energy in sensor networks, the optimized energy
consumption in these networks is of more importance and has created
many challenges. The previous works have shown that by organizing
the network nodes in a number of clusters, the energy consumption
could be reduced considerably. So the lifetime of the network would
be increased. In this paper, we used the Queen-bee algorithm to
create energy efficient clusters in wireless sensor networks. The
Queen-bee (QB) is similar to nature in that the queen-bee plays a
major role in reproduction process. The QB is simulated with J-sim
simulator. The results of the simulation showed that the clustering by
the QB algorithm decreases the energy consumption with regard to
the other existing algorithms and increases the lifetime of the
network.
Abstract: This paper addresses modeling and optimization of process parameters in powder mixed electrical discharge machining (PMEDM). The process output characteristics include metal removal rate (MRR) and electrode wear rate (EWR). Grain size of Aluminum powder (S), concentration of the powder (C), discharge current (I) pulse on time (T) are chosen as control variables to study the process performance. The experimental results are used to develop the regression models based on second order polynomial equations for the different process characteristics. Then, a genetic algorithm (GA) has been employed to determine optimal process parameters for any desired output values of machining characteristics.
Abstract: Due to their high power-to-weight ratio and low cost,
pneumatic actuators are attractive for robotics and automation
applications; however, achieving fast and accurate control of their
position have been known as a complex control problem. A
methodology for obtaining high position accuracy with a linear
pneumatic actuator is presented. During experimentation with a
number of PID classical control approaches over many operations of
the pneumatic system, the need for frequent manual re-tuning of the
controller could not be eliminated. The reason for this problem is
thermal and energy losses inside the cylinder body due to the
complex friction forces developed by the piston displacements.
Although PD controllers performed very well over short periods, it
was necessary in our research project to introduce some form of
automatic gain-scheduling to achieve good long-term performance.
We chose a fuzzy logic system to do this, which proved to be an
easily designed and robust approach. Since the PD approach showed
very good behaviour in terms of position accuracy and settling time,
it was incorporated into a modified form of the 1st order Tagaki-
Sugeno fuzzy method to build an overall controller. This fuzzy gainscheduler
uses an input variable which automatically changes the PD
gain values of the controller according to the frequency of repeated
system operations. Performance of the new controller was
significantly improved and the need for manual re-tuning was
eliminated without a decrease in performance. The performance of
the controller operating with the above method is going to be tested
through a high-speed web network (GRID) for research purposes.
Abstract: Utilization of bagasse ash for silica sources is one of
the most common application for agricultural wastes and valuable
biomass byproducts in sugar milling. The high percentage silica
content from bagasse ash was used as silica source for sodium
silicate solution. Different heating temperature, time and acid
treatment were studies for silica extraction. The silica was
characterized using various techniques including X-ray fluorescence,
X-ray diffraction, Scanning electron microscopy, and Fourier
Transform Infrared Spectroscopy method,. The synthesis conditions
were optimized to obtain the bagasse ash with the maximum silica
content. The silica content of 91.57 percent was achieved from
heating of bagasse ash at 600°C for 3 hours under oxygen feeding
and HCl treatment. The result can be used as value added for bagasse
ash utilization and minimize the environmental impact of disposal
problems.
Abstract: In this paper we present a new approach to detecting a
flaw in T.O.F.D (Time Of Flight Diffraction) type ultrasonic image
based on texture features. Texture is one of the most important
features used in recognizing patterns in an image. The paper
describes texture features based on 2D Gabor functions, i.e.,
Gaussian shaped band-pass filters, with dyadic treatment of the radial
spatial frequency range and multiple orientations, which represent an
appropriate choice for tasks requiring simultaneous measurement in
both space and frequency domains. The most relevant features are
used as input data on a Fuzzy c-mean clustering classifier. The
classes that exist are only two: 'defects' or 'no defects'. The proposed
approach is tested on the T.O.F.D image achieved at the laboratory
and on the industrial field.
Abstract: The new semi-experimental method for simulation of
the turbine flow meters rotation in the transitional flow has been
developed. The method is based on the experimentally established
exponential low of changing of dimensionless relative turbine gas
meter rotation frequency and meter inertia time constant. For
experimental evaluation of the meter time constant special facility
has been developed. The facility ensures instant switching of turbine
meter under test from one channel to the other channel with different
flow rate and measuring the meter response. The developed method
can be used for evaluation and predication of the turbine meters
response and dynamic error in the transitional flow with any arbitrary
law of flow rate changing. The examples of the method application
are presented.
Abstract: In the paper a detailed analysis of the dynamic
response of a cooling tower shell to mining tremors originated from
two main regions of mining activity in Poland (Upper Silesian Coal
Basin and Legnica-Glogow Copper District) was presented. The
representative time histories registered in the both regions were used
as ground motion data in calculations of the dynamic response of the
structure. It was proved that the dynamic response of the shell is
strongly dependent not only on the level of vibration amplitudes but
on the dominant frequency range of the mining shock typical for the
mining region as well. Also a vertical component of vibrations
occurred to have considerable influence on the total dynamic
response of the shell. Finally, it turned out that non-uniformity of
kinematic excitation resulting from spatial variety of ground motion
plays a significant role in dynamic analysis of large-dimensional
shells under mining shocks.
Abstract: Real-time embedded systems should benefit from
component-based software engineering to handle complexity and
deal with dependability. In these systems, applications should not
only be logically correct but also behave within time windows.
However, in the current component based software engineering
approaches, a few of component models handles time properties in
a manner that allows efficient analysis and checking at the
architectural level. In this paper, we present a meta-model for
component-based software description that integrates timing
issues. To achieve a complete functional model of software
components, our meta-model focuses on four functional aspects:
interface, static behavior, dynamic behavior, and interaction
protocol. With each aspect we have explicitly associated a time
model. Such a time model can be used to check a component-s
design against certain properties and to compute the timing
properties of component assemblies.
Abstract: One of the most used assumptions in logic programming
and deductive databases is the so-called Closed World Assumption
(CWA), according to which the atoms that cannot be inferred
from the programs are considered to be false (i.e. a pessimistic
assumption). One of the most successful semantics of conventional
logic programs based on the CWA is the well-founded semantics.
However, the CWA is not applicable in all circumstances when
information is handled. That is, the well-founded semantics, if
conventionally defined, would behave inadequately in different cases.
The solution we adopt in this paper is to extend the well-founded
semantics in order for it to be based also on other assumptions. The
basis of (default) negative information in the well-founded semantics
is given by the so-called unfounded sets. We extend this concept
by considering optimistic, pessimistic, skeptical and paraconsistent
assumptions, used to complete missing information from a program.
Our semantics, called extended well-founded semantics, expresses
also imperfect information considered to be missing/incomplete,
uncertain and/or inconsistent, by using bilattices as multivalued
logics. We provide a method of computing the extended well-founded
semantics and show that Kripke-Kleene semantics is captured by
considering a skeptical assumption. We show also that the complexity
of the computation of our semantics is polynomial time.
Abstract: In this paper, the problem of estimating the optimal
radio capacity of a single-cell spread spectrum (SS) multiple-inputmultiple-
output (MIMO) system operating in a Rayleigh fading environment
is examined. The optimisation between the radio capacity
and the theoretically achievable average channel capacity (in the
sense of information theory) per user of a MIMO single-cell SS system
operating in a Rayleigh fading environment is presented. Then,
the spectral efficiency is estimated in terms of the achievable average
channel capacity per user, during the operation over a broadcast
time-varying link, and leads to a simple novel-closed form expression
for the optimal radio capacity value based on the maximization
of the achieved spectral efficiency. Numerical results are presented to
illustrate the proposed analysis.
Abstract: Because today-s media centric students have adopted
digital as their native form of communication, teachers are having
increasingly difficult time motivating reluctant readers to read and
write. Our research has shown these text-averse individuals can learn
to understand the importance of reading and writing if the instruction
is based on digital narratives. While these students are naturally
attracted to story, they are better at consuming them than creating
them. Therefore, any intervention that utilizes story as its basis needs
to include instruction on the elements of story making. This paper
presents a series of digitally-based tools to identify potential
weaknesses of visually impaired visual learners and to help motivate
these and other media-centric students to select and complete books
that are assigned to them
Abstract: Using entropy weight and TOPSIS method, a
comprehensive evaluation is done on the development level of
Chinese regional service industry in this paper. Firstly, based on
existing research results, an evaluation index system is constructed
from the scale of development, the industrial structure and the
economic benefits. An evaluation model is then built up based on
entropy weight and TOPSIS, and an empirical analysis is conducted on
the development level of service industries in 31 Chinese provinces
during 2006 and 2009 from the two dimensions or time series and
cross section, which provides new idea for assessing regional service
industry. Furthermore, the 31 provinces are classified into four
categories based on the evaluation results, and deep analysis is carried
out on the evaluation results.
Abstract: Advances in computing applications in recent years
have prompted the demand for more flexible scheduling models for
QoS demand. Moreover, in practical applications, partly violated
temporal constraints can be tolerated if the violation meets certain
distribution. So we need extend the traditional Liu and Lanland model
to adapt to these circumstances. There are two extensions, which are
the (m, k)-firm model and Window-Constrained model. This paper
researches on weakly hard real-time constraints and their combination
to support QoS. The fact that a practical application can tolerate some
violations of temporal constraint under certain distribution is
employed to support adaptive QoS on the open real-time system. The
experiment results show these approaches are effective compared to
traditional scheduling algorithms.
Abstract: This paper proposes a new method for image searches and image indexing in databases with a color temperature histogram. The color temperature histogram can be used for performance improvement of content–based image retrieval by using a combination of color temperature and histogram. The color temperature histogram can be represented by a range of 46 colors. That is more than the color histogram and the dominant color temperature. Moreover, with our method the colors that have the same color temperature can be separated while the dominant color temperature can not. The results showed that the color temperature histogram retrieved an accurate image more often than the dominant color temperature method or color histogram method. This also took less time so the color temperature can be used for indexing and searching for images.
Abstract: The customary practice of identifying industrial sickness is a set traditional techniques which rely upon a range of manual monitoring and compilation of financial records. It makes the process tedious, time consuming and often are susceptible to manipulation. Therefore, certain readily available tools are required which can deal with such uncertain situations arising out of industrial sickness. It is more significant for a country like India where the fruits of development are rarely equally distributed. In this paper, we propose an approach based on Artificial Neural Network (ANN) to deal with industrial sickness with specific focus on a few such units taken from a less developed north-east (NE) Indian state like Assam. The proposed system provides decision regarding industrial sickness using eight different parameters which are directly related to the stages of sickness of such units. The mechanism primarily uses certain signals and symptoms of industrial health to decide upon the state of a unit. Specifically, we formulate an ANN based block with data obtained from a few selected units of Assam so that required decisions related to industrial health could be taken. The system thus formulated could become an important part of planning and development. It can also contribute towards computerization of decision support systems related to industrial health and help in better management.
Abstract: A two-dimensional moving mesh algorithm is developed to simulate the general motion of two rotating bodies with relative translational motion. The grid includes a background grid and two sets of grids around the moving bodies. With this grid arrangement rotational and translational motions of two bodies are handled separately, with no complications. Inter-grid boundaries are determined based on their distances from two bodies. In this method, the overset concept is applied to hybrid grid, and flow variables are interpolated using a simple stencil. To evaluate this moving mesh algorithm unsteady Euler flow is solved for different cases using dual-time method of Jameson. Numerical results show excellent agreement with experimental data and other numerical results. To demonstrate the capability of present algorithm for accurate solution of flow fields around moving bodies, some benchmark problems have been defined in this paper.
Abstract: In this paper, a class of recurrent neural networks (RNNs) with variable delays are studied on almost periodic time scales, some sufficient conditions are established for the existence and global exponential stability of the almost periodic solution. These results have important leading significance in designs and applications of RNNs. Finally, two examples and numerical simulations are presented to illustrate the feasibility and effectiveness of the results.