Abstract: In this work, a special case of the image superresolution
problem where the only type of motion is global
translational motion and the blurs are shift-invariant is investigated.
The necessary conditions for exact reconstruction of the original
image by using finite impulse-response reconstruction filters are
developed. Given that the conditions are satisfied, a method for exact
super-resolution is presented and some simulation results are shown.
Abstract: Oilsands bitumen is an extremely important source of
energy for North America. However, due to the presence of large
molecules such as asphaltenes, the density and viscosity of the
bitumen recovered from these sands are much higher than those of
conventional crude oil. As a result the extracted bitumen has to be
diluted with expensive solvents, or thermochemically upgraded in
large, capital-intensive conventional upgrading facilities prior to
pipeline transport. This study demonstrates that globally abundant
natural zeolites such as clinoptilolite from Saint Clouds, New Mexico
and Ca-chabazite from Bowie, Arizona can be used as very effective
reagents for cracking and visbreaking of oilsands bitumen. Natural
zeolite cracked oilsands bitumen products are highly recoverable (up
to ~ 83%) using light hydrocarbons such as pentane, which indicates
substantial conversion of heavier fractions to lighter components.
The resultant liquid products are much less viscous, and have lighter
product distribution compared to those produced from pure thermal
treatment. These natural minerals impart similar effect on industrially
extracted Athabasca bitumen.
Abstract: Ever increasing capacities of contemporary storage devices
inspire the vision to accumulate (personal) information without
the need of deleting old data over a long time-span. Hence the target
of SemanticLIFE project is to create a Personal Information Management
system for a human lifetime data. One of the most important
characteristics of the system is its dedication to retrieve information
in a very efficient way. By adopting user demands regarding the
reduction of ambiguities, our approach aims at a user-oriented and
yet powerful enough system with a satisfactory query performance.
We introduce the query system of SemanticLIFE, the Virtual Query
System, which uses emerging Semantic Web technologies to fulfill
users- requirements.
Abstract: In this paper, the effect of receive and/or transmit
antenna spacing on the performance (BER vs. SNR) of multipleantenna
systems is determined by using an RCS (Radar Cross
Section) channel model. In this physical model, the scatterers
existing in the propagation environment are modeled by their RCS so
that the correlation of the receive signal complex amplitudes, i.e.,
both magnitude and phase, can be estimated. The proposed RCS
channel model is then compared with classical models.
Abstract: In IETF RFC 2002, Mobile-IP was developed to
enable Laptobs to maintain Internet connectivity while moving
between subnets. However, the packet loss that comes from
switching subnets arises because network connectivity is lost while
the mobile host registers with the foreign agent and this encounters
large end-to-end packet delays. The criterion to initiate a simple and
fast full-duplex connection between the home agent and foreign
agent, to reduce the roaming duration, is a very important issue to be
considered by a work in this paper. State-transition Petri-Nets of the
modeling scenario-based CIA: communication inter-agents procedure
as an extension to the basic Mobile-IP registration process was
designed and manipulated to describe the system in discrete events.
The heuristic of configuration file during practical Setup session for
registration parameters, on Cisco platform Router-1760 using IOS
12.3 (15)T and TFTP server S/W is created. Finally, stand-alone
performance simulations from Simulink Matlab, within each subnet
and also between subnets, are illustrated for reporting better end-toend
packet delays. Results verified the effectiveness of our Mathcad
analytical manipulation and experimental implementation. It showed
lower values of end-to-end packet delay for Mobile-IP using CIA
procedure-based early registration. Furthermore, it reported packets
flow between subnets to improve losses between subnets.
Abstract: For lack of the visualization of the ultrasonic detection
method of partial discharge (PD), the ultrasonic detection technology
combined with the X-ray visual detection method (UXV) is proposed.
The method can conduct qualitative analysis accurately and conduct
reliable positioning diagnosis to the internal insulation defects of
GIS, and while it could make up the blindness of the X-ray visual
detection method and improve the detection rate. In this paper, an
experimental model of GIS is used as the trial platform, a variety of
insulation defects are set inside the GIS cavity. With the proposed
method, the ultrasonic method is used to conduct the preliminary
detection, and then the X-ray visual detection is used to locate and
diagnose precisely. Therefore, the proposed UXV technology is
feasible and practical.
Abstract: Artificial Intelligence based gaming is an interesting topic in the state-of-art technology. This paper presents an automation of a tradition Omani game, called Al-Hawalees. Its related issues are resolved and implemented using artificial intelligence approach. An AI approach called mini-max procedure is incorporated to make a diverse budges of the on-line gaming. If number of moves increase, time complexity will be increased in terms of propositionally. In order to tackle the time and space complexities, we have employed a back propagation neural network (BPNN) to train in off-line to make a decision for resources required to fulfill the automation of the game. We have utilized Leverberg- Marquardt training in order to get the rapid response during the gaming. A set of optimal moves is determined by the on-line back propagation training fashioned with alpha-beta pruning. The results and analyses reveal that the proposed scheme will be easily incorporated in the on-line scenario with one player against the system.
Abstract: The presented work is motivated by a French law
regarding nuclear waste management. A new conceptual Accelerator
Driven System (ADS) designed for the Minor Actinides (MA)
transmutation has been assessed by numerical simulation. The
MUltiple Spallation Target (MUST) ADS combines high thermal power (up to 1.4 GWth) and high specific power. A 30 mA and 1
GeV proton beam is divided into three secondary beams transmitted on three liquid lead-bismuth spallation targets. Neutron and thermalhydraulic
simulations have been performed with the code MURE, based on the Monte-Carlo transport code MCNPX. A methodology has been developed to define characteristic of the MUST ADS concept according to a specific transmutation scenario. The reference
scenario is based on a MA flux (neptunium, americium and curium)
providing from European Fast Reactor (EPR) and a plutonium multireprocessing
strategy is accounted for. The MUST ADS reference
concept is a sodium cooled fast reactor. The MA fuel at equilibrium is mixed with MgO inert matrix to limit the core reactivity and
improve the fuel thermal conductivity. The fuel is irradiated over five
years. Five years of cooling and two years for the fuel fabrication are
taken into account. The MUST ADS reference concept burns about 50% of the initial MA inventory during a complete cycle. In term of
mass, up to 570 kg/year are transmuted in one concept. The methodology to design the MUST ADS and to calculate fuel
composition at equilibrium is precisely described in the paper. A detailed fuel evolution analysis is performed and the reference scenario is compared to a scenario where only americium transmutation is performed.
Abstract: At present, it is very common to find renewable
energy resources, especially wind power, connected to distribution
systems. The impact of this wind power on voltage distribution levels
has been addressed in the literature. The majority of this works deals
with the determination of the maximum active and reactive power
that is possible to be connected on a system load bus, until the
voltage at that bus reaches the voltage collapse point. It is done by the
traditional methods of PV curves reported in many references.
Theoretical expression of maximum power limited by voltage
stability transfer through a grid is formulated using an exact
representation of distribution line with ABCD parameters. The
expression is used to plot PV curves at various power factors of a
radial system. Limited values of reactive power can be obtained. This
paper presents a method to study the relationship between the active
power and voltage (PV) at the load bus to identify the voltage
stability limit. It is a foundation to build a permitted working
operation region in complying with the voltage stability limit at the
point of common coupling (PCC) connected wind farm.
Abstract: Multi-Radio Multi-Channel Wireless Mesh Networks (MRMC-WMNs) operate at the backbone to access and route high volumes of traffic simultaneously. Such roles demand high network capacity, and long “online" time at the expense of accelerated transmission energy depletion and poor connectivity. This is the problem of transmission power control. Numerous power control methods for wireless networks are in literature. However, contributions towards MRMC configurations still face many challenges worth considering. In this paper, an energy-efficient power selection protocol called PMMUP is suggested at the Link-Layer. This protocol first divides the MRMC-WMN into a set of unified channel graphs (UCGs). A UCG consists of multiple radios interconnected to each other via a common wireless channel. In each UCG, a stochastic linear quadratic cost function is formulated. Each user minimizes this cost function consisting of trade-off between the size of unification states and the control action. Unification state variables come from independent UCGs and higher layers of the protocol stack. The PMMUP coordinates power optimizations at the network interface cards (NICs) of wireless mesh routers. The proposed PMMUP based algorithm converges fast analytically with a linear rate. Performance evaluations through simulations confirm the efficacy of the proposed dynamic power control.
Abstract: Careful design and selection of daylighting systems can greatly help in reducing not only artificial lighting use, but also decrease cooling energy consumption and, therefore, potential for downsizing air-conditioning systems. This paper aims to evaluate the energy performance of two types of top-light daylighting systems due to the integration of daylight together with artificial lighting in an existing examinaton hall in University Kebangsaan Malaysia, based on a hot and humid climate. Computer simulation models have been created for building case study (base case) and the two types of toplight daylighting designs for building energy performance evaluation using the VisualDOE 4.0 building energy simulation program. The finding revealed that daylighting through top-light systems is a very beneficial design strategy in reducing annual lighting energy consumption and the overall total annual energy consumption.
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: 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: 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.