Abstract: This paper presents a new problem solving approach
that is able to generate optimal policy solution for finite-state
stochastic sequential decision-making problems with high data
efficiency. The proposed algorithm iteratively builds and improves
an approximate Markov Decision Process (MDP) model along with
cost-to-go value approximates by generating finite length trajectories
through the state-space. The approach creates a synergy between an
approximate evolving model and approximate cost-to-go values to
produce a sequence of improving policies finally converging to the
optimal policy through an intelligent and structured search of the
policy space. The approach modifies the policy update step of the
policy iteration so as to result in a speedy and stable convergence to
the optimal policy. We apply the algorithm to a non-holonomic
mobile robot control problem and compare its performance with
other Reinforcement Learning (RL) approaches, e.g., a) Q-learning,
b) Watkins Q(λ), c) SARSA(λ).
Abstract: Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows drawing conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stageby- stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.
Abstract: Isobaric vapor-liquid equilibrium measurements are reported for the binary mixtures of n-Butylamine and Triethylamine with Cumene at 97.3 kPa. The measurements have been performed using a vapor recirculating type (modified Othmer's) equilibrium still. The binary mixture of n-Butylamine + Cumene shows positive deviation from ideality. Triethylamine + Cumene mixture shows negligible deviation from ideality. None of the systems form an azeotrope. The activity coefficients have been calculated taking into consideration the vapor phase nonideality. The data satisfy the thermodynamic consistency test of Herington. The activity coefficients have been satisfactorily correlated by means of the Margules, NRTL, and Black equations. The activity coefficient values obtained by the UNIFAC model are also reported.
Abstract: Sedimentation process resulting from soil erosion in
the water basin especially in arid and semi-arid where poor
vegetation cover in the slope of the mountains upstream could
contribute to sediment formation. The consequence of sedimentation
not only makes considerable change in the morphology of the river
and the hydraulic characteristics but would also have a major
challenge for the operation and maintenance of the canal network
which depend on water flow to meet the stakeholder-s requirements.
For this reason mathematical modeling can be used to simulate the
effective factors on scouring, sediment transport and their settling
along the waterways. This is particularly important behind the
reservoirs which enable the operators to estimate the useful life of
these hydraulic structures. The aim of this paper is to simulate the
sedimentation and erosion in the eastern and western water intake
structures of the Dez Diversion weir using GSTARS-3 software. This
is done to estimate the sedimentation and investigate the ways in
which to optimize the process and minimize the operational
problems. Results indicated that the at the furthest point upstream of
the diversion weir, the coarser sediment grains tended to settle. The
reason for this is the construction of the phantom bridge and the
outstanding rocks just upstream of the structure. The construction of
these along the river course has reduced the momentum energy
require to push the sediment loads and make it possible for them to
settle wherever the river regime allows it. Results further indicated a
trend for the sediment size in such a way that as the focus of study
shifts downstream the size of grains get smaller and vice versa. It
was also found that the finding of the GSTARS-3 had a close
proximity with the sets of the observed data. This suggests that the
software is a powerful analytical tool which can be applied in the
river engineering project with a minimum of costs and relatively
accurate results.
Abstract: Oxidative stress and overwhelming free radicals
associated with diabetes mellitus are likely to be linked with
development of certain complication such as retinopathy,
nephropathy and neuropathy. Treatment of diabetic subjects with
antioxidant may be of advantage in attenuating these complications.
Olive leaf (Oleaeuropaea), has been endowed with many beneficial
and health promoting properties mostly linked to its antioxidant
activity. This study aimed to evaluate the significance of
supplementation of Olive leaves extract (OLE) in reducing oxidative
stress, hyperglycemia and hyperlipidemia in Sterptozotocin (STZ)-
induced diabetic rats. After induction of diabetes, a significant rise in
plasma glucose, lipid profiles except High density lipoproteincholestrol
(HDLc), malondialdehyde (MDA) and significant decrease
of plasma insulin, HDLc and Plasma reduced glutathione GSH as
well as alteration in enzymatic antioxidants was observed in all
diabetic animals. During treatment of diabetic rats with 0.5g/kg body
weight of Olive leaves extract (OLE) the levels of plasma (MDA)
,(GSH), insulin, lipid profiles along with blood glucose and
erythrocyte enzymatic antioxidant enzymes were significantly
restored to establish values that were not different from normal
control rats. Untreated diabetic rats on the other hand demonstrated
persistent alterations in the oxidative stress marker (MDA), blood
glucose, insulin, lipid profiles and the antioxidant parameters. These
results demonstrate that OLE may be of advantage in inhibiting
hyperglycemia, hyperlipidemia and oxidative stress induced by
diabetes and suggest that administration of OLE may be helpful in
the prevention or at least reduced of diabetic complications
associated with oxidative stress.
Abstract: A continuum model is presented to study vdW
interaction on buckling analysis of multi-walled walled carbon
nanotube. In previous studies, only the vdW interaction between
adjacent two layers was considered and the vdW interaction between
the other two layers was neglected. The results show that the vdW
interaction cofficients are dependent on the change of interlayer
spacing and the radii of tubes. With increase of radii the vdW
coefficients approach a constant value. The numerical results show
that the effect of vdW interaction on the critical strain for a doublewalled
CNT is negligible when the radius is large enough for the
both the cases of before and after buckling.
Abstract: The quality of short term load forecasting can improve the efficiency of planning and operation of electric utilities. Artificial Neural Networks (ANNs) are employed for nonlinear short term load forecasting owing to their powerful nonlinear mapping capabilities. At present, there is no systematic methodology for optimal design and training of an artificial neural network. One has often to resort to the trial and error approach. This paper describes the process of developing three layer feed-forward large neural networks for short-term load forecasting and then presents a heuristic search algorithm for performing an important task of this process, i.e. optimal networks structure design. Particle Swarm Optimization (PSO) is used to develop the optimum large neural network structure and connecting weights for one-day ahead electric load forecasting problem. PSO is a novel random optimization method based on swarm intelligence, which has more powerful ability of global optimization. Employing PSO algorithms on the design and training of ANNs allows the ANN architecture and parameters to be easily optimized. The proposed method is applied to STLF of the local utility. Data are clustered due to the differences in their characteristics. Special days are extracted from the normal training sets and handled separately. In this way, a solution is provided for all load types, including working days and weekends and special days. The experimental results show that the proposed method optimized by PSO can quicken the learning speed of the network and improve the forecasting precision compared with the conventional Back Propagation (BP) method. Moreover, it is not only simple to calculate, but also practical and effective. Also, it provides a greater degree of accuracy in many cases and gives lower percent errors all the time for STLF problem compared to BP method. Thus, it can be applied to automatically design an optimal load forecaster based on historical data.
Abstract: Gastric ulceration is a discontinuity in gastric mucosa, usually occurs due to imbalance between the gastric mucosal protective factors, that is called gastric mucosal barrier, and the aggressive factors, to which the mucosa is exposed. This study was carried out on sixty male Sprague-Dowely rats (12- 16 weeks old) allocated into two groups. The first control group and the second Gastric lesion group which induced by oral administration of a single daily dose of aspirin at a dose of 300 mg/kg body weight for 7 consecutive-days (6% aspirin solution will be prepared and each rat will be given 5 ml of that solution/kg body weight). Blood is collected 1, 2 and 3 weeks after induction of gastric ulceration. Significant increase in serum copper, nitric oxide, and prostaglandin E2 all over the period of experiment. Significant decrease in erythrocyte superoxide dismutase (t-SOD) activities, serum (calcium, phosphorus, glucose and insulin) levels. Non-significant changes in serum sodium and potassium levels are obtained.
Abstract: Since the advent of the information era, the Internet has
brought various positive effects in everyday life. Nevertheless,
recently, problems and side-effects have been noted. Internet
witch-trials and spread of pornography are only a few of these
problems.In this study, problems and causes of malicious replies on
internet boards were analyzed, using the key ideas of game theory. The
study provides a mathematical model for the internet reply game to
devise three possible plans that could efficiently counteract malicious
replies. Furthermore, seven specific measures that comply with one of
the three plans were proposed and evaluated according to the
importance and utility of each measure using the orthogonal array
survey and SPSS conjoint analysis.The conclusion was that the most
effective measure would be forbidding unsigned user access to
malicious replies. Also notable was that some analytically proposed
measures, when implemented, could backfire and encourage malicious
replies.
Abstract: This article summarizes ways to verify neutron
fluence for neutron transmutation doping of silicon with phosphorus
on the LVR-15 reactor. Neutron fluence is determined using
activation detectors placed along the crystal in a strip or encapsulated
in a rod holder. Holders are placed at the centre of a water-filled
capsule or in an aluminum or silicon ingot that simulates a real single
crystal. If the diameter of the crystal is significantly less than the
capsule diameter and water from the primary circuit enters the free
space in the capsule, neutron interaction in the water changes neutron
fluence, affecting axial irradiation homogeneity. The effect of
moving the capsule vertically in the channel relative to maximum
neutron fluence in the reactor core was also measured. Even a small
shift of the capsule-s centre causes great irradiation inhomogeneity.
This effect was measured using activation detectors, and was also
confirmed by MCNP calculation.
Abstract: With a surge of stream processing applications novel
techniques are required for generation and analysis of association
rules in streams. The traditional rule mining solutions cannot handle
streams because they generally require multiple passes over the data
and do not guarantee the results in a predictable, small time. Though
researchers have been proposing algorithms for generation of rules
from streams, there has not been much focus on their analysis.
We propose Association rule profiling, a user centric process for
analyzing association rules and attaching suitable profiles to them
depending on their changing frequency behavior over a previous
snapshot of time in a data stream.
Association rule profiles provide insights into the changing nature
of associations and can be used to characterize the associations. We
discuss importance of characteristics such as predictability of
linkages present in the data and propose metric to quantify it. We
also show how association rule profiles can aid in generation of user
specific, more understandable and actionable rules.
The framework is implemented as SUPAR: System for Usercentric
Profiling of Association Rules in streaming data. The
proposed system offers following capabilities:
i) Continuous monitoring of frequency of streaming item-sets
and detection of significant changes therein for association rule
profiling.
ii) Computation of metrics for quantifying predictability of
associations present in the data.
iii) User-centric control of the characterization process: user
can control the framework through a) constraint specification and b)
non-interesting rule elimination.
Abstract: IEEE 802.16 is a new wireless technology standard, it
has some advantages, including wider coverage, higher bandwidth,
and QoS support. As the new wireless technology for last mile
solution, there are designed two models in IEEE 802.16 standard. One
is PMP (point to multipoint) and the other is Mesh. In this paper we
only focus on IEEE 802.16 Mesh model. According to the IEEE
802.16 standard description, Mesh model has two scheduling modes,
centralized and distributed. Considering the pros and cons of the two
scheduling, we present the combined scheduling QoS framework that
the BS (Base Station) controls time frame scheduling and selects the
shortest path from source to destination directly. On the other hand, we
propose the Expedited Queue mechanism to cut down the transmission
time. The EQ mechanism can reduce a lot of end-to-end delay in our
QoS framework. Simulation study has shown that the average delay is
smaller than contrasts. Furthermore, our proposed scheme can also
achieve higher performance.
Abstract: Discretization of spatial derivatives is an important
issue in meshfree methods especially when the derivative terms
contain non-linear coefficients. In this paper, various methods used
for discretization of second-order spatial derivatives are investigated
in the context of Smoothed Particle Hydrodynamics. Three popular
forms (i.e. "double summation", "second-order kernel derivation",
and "difference scheme") are studied using one-dimensional unsteady
heat conduction equation. To assess these schemes, transient response
to a step function initial condition is considered. Due to parabolic
nature of the heat equation, one can expect smooth and monotone
solutions. It is shown, however in this paper, that regardless of
the type of kernel function used and the size of smoothing radius,
the double summation discretization form leads to non-physical
oscillations which persist in the solution. Also, results show that when
a second-order kernel derivative is used, a high-order kernel function
shall be employed in such a way that the distance of inflection
point from origin in the kernel function be less than the nearest
particle distance. Otherwise, solutions may exhibit oscillations near
discontinuities unlike the "difference scheme" which unconditionally
produces monotone results.
Abstract: An attempt has been made to investigate the
machinability of zirconia toughened alumina (ZTA) inserts while
turning AISI 4340 steel. The insert was prepared by powder
metallurgy process route and the machining experiments were
performed based on Response Surface Methodology (RSM) design
called Central Composite Design (CCD). The mathematical model of
flank wear, cutting force and surface roughness have been developed
using second order regression analysis. The adequacy of model has
been carried out based on Analysis of variance (ANOVA) techniques.
It can be concluded that cutting speed and feed rate are the two most
influential factor for flank wear and cutting force prediction. For
surface roughness determination, the cutting speed & depth of cut
both have significant contribution. Key parameters effect on each
response has also been presented in graphical contours for choosing
the operating parameter preciously. 83% desirability level has been
achieved using this optimized condition.
Abstract: In this paper, the periodic surveillance scheme has
been proposed for any convex region using mobile wireless sensor
nodes. A sensor network typically consists of fixed number of
sensor nodes which report the measurements of sensed data such as
temperature, pressure, humidity, etc., of its immediate proximity
(the area within its sensing range). For the purpose of sensing an
area of interest, there are adequate number of fixed sensor
nodes required to cover the entire region of interest. It implies
that the number of fixed sensor nodes required to cover a given
area will depend on the sensing range of the sensor as well as
deployment strategies employed. It is assumed that the sensors to
be mobile within the region of surveillance, can be mounted on
moving bodies like robots or vehicle. Therefore, in our
scheme, the surveillance time period determines the number of
sensor nodes required to be deployed in the region of interest.
The proposed scheme comprises of three algorithms namely:
Hexagonalization, Clustering, and Scheduling, The first algorithm
partitions the coverage area into fixed sized hexagons that
approximate the sensing range (cell) of individual sensor node.
The clustering algorithm groups the cells into clusters, each of
which will be covered by a single sensor node. The later
determines a schedule for each sensor to serve its respective cluster.
Each sensor node traverses all the cells belonging to the cluster
assigned to it by oscillating between the first and the last cell for
the duration of its life time. Simulation results show that our
scheme provides full coverage within a given period of time using
few sensors with minimum movement, less power consumption,
and relatively less infrastructure cost.
Abstract: One main drawback of intrusion detection system is the
inability of detecting new attacks which do not have known
signatures. In this paper we discuss an intrusion detection method
that proposes independent component analysis (ICA) based feature
selection heuristics and using rough fuzzy for clustering data. ICA is
to separate these independent components (ICs) from the monitored
variables. Rough set has to decrease the amount of data and get rid of
redundancy and Fuzzy methods allow objects to belong to several
clusters simultaneously, with different degrees of membership. Our
approach allows us to recognize not only known attacks but also to
detect activity that may be the result of a new, unknown attack. The
experimental results on Knowledge Discovery and Data Mining-
(KDDCup 1999) dataset.
Abstract: Design and implementation of a novel B-ACOSD CFAR algorithm is presented in this paper. It is proposed for detecting radar target in log-normal distribution environment. The BACOSD detector is capable to detect automatically the number interference target in the reference cells and detect the real target by an adaptive threshold. The detector is implemented as a System on Chip on FPGA Altera Stratix II using parallelism and pipelining technique. For a reference window of length 16 cells, the experimental results showed that the processor works properly with a processing speed up to 115.13MHz and processing time0.29 ┬Ás, thus meets real-time requirement for a typical radar system.
Abstract: In this paper, we propose an improvement of pattern
growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use sufficient data structure for Seq-Tree
framework and separator database to reduce the execution time and
memory usage. Thus, with I-PrefixSpan there is no in-memory database stored after index set is constructed. The experimental result
shows that using Java 2, this method improves the speed of PrefixSpan up to almost two orders of magnitude as well as the memory usage to more than one order of magnitude.
Abstract: This paper presents a solution for the behavioural
animation of autonomous virtual agent navigation in virtual environments.
We focus on using Dempster-Shafer-s Theory of Evidence
in developing visual sensor for virtual agent. The role of the visual
sensor is to capture the information about the virtual environment
or identifie which part of an obstacle can be seen from the position
of the virtual agent. This information is require for vitual agent to
coordinate navigation in virtual environment. The virual agent uses
fuzzy controller as a navigation system and Fuzzy α - level for
the action selection method. The result clearly demonstrates the path
produced is reasonably smooth even though there is some sharp turn
and also still not diverted too far from the potential shortest path.
This had indicated the benefit of our method, where more reliable
and accurate paths produced during navigation task.
Abstract: the aim of that work is to study the proton transfer
phenomenon which takes place in the elastic scattering of 12C on 11B
at energies near the coulomb barrier. This reaction was studied at four
different energies 16, 18, 22, 24 MeV. The experimental data of the
angular distribution at these energies were compared to the
calculation prediction using the optical potential codes such as
ECIS88 and SPIVAL. For the raising in the cross section at backward
angles due to the transfer process we could use Distorted Wave Born
Approximation (DWUCK5). Our analysis showed that SPIVAL code
with l-dependent imaginary potential could be used effectively.