Abstract: Kepsut-Dursunbey volcanic field (KDVF) is located
in NW Turkey and contains various products of the post-collisional
Neogene magmatic activity. Two distinct volcanic suites have been
recognized; the Kepsut volcanic suite (KVS) and the Dursunbey
volcanic suite (DVS). The KVS includes basaltic trachyandesitebasaltic
andesite-andesite lavas and associated pyroclastic rocks. The
DVS consists of dacite-rhyodacite lavas and extensive pumice-ash
fall and flow deposits. Petrographical features (i.e. existence of
xenocrysts, glomerocrysts, and mixing-compatible textures) and
mineral chemistry of phenocryst assemblages of both suites provide
evidence for magma mixing/AFC. Calculated crystallization
pressures and temperatures give values of 5.7–7.0 kbar and 927–982
°C for the KVS and 3.7–5.3 kbar and 783-787°C for the DVS,
indicating separate magma reservoirs and crystallization in magma
chambers at deep and mid crustal levels, respectively. These
observations support the establishment and evolution of KDVF
magma system promoted by episodic basaltic inputs which may
generate and mix with crustal melts.
Abstract: Catalytic converters are used for minimizing the release of pollutants to the atmosphere. It is during the warm-up period that hydrocarbons are seen to be released in appreciable quantities from these converters. In this paper the conversion of a fast oxidizing hydrocarbon propylene is analysed using two numerical methods. The quasi steady state method assumes the accumulation terms to be negligible in the gas phase mass and energy balance equations, however this term is present in the solid phase energy balance. The unsteady state model accounts for the accumulation term to be present in the gas phase mass and energy balance and in the solid phase energy balance. The results derived from the two models for gas concentration, gas temperature and solid temperature are compared.
Abstract: The p53 tumor suppressor gene plays two important
roles in genomic stability: blocking cell proliferation after DNA
damage until it has been repaired, and starting apoptosis if the
damage is too critical. Codon 72 exon4 polymorphism (Arg72Pro) of
the P53 gene has been implicated in cancer risk. Various studies have
been done to investigate the status of p53 at codon 72 for arginine
(Arg) and proline (Pro) alleles in different populations and also the
association of this codon 72 polymorphism with various tumors. Our
objective was to investigate the possible association between P53
Arg72Pro polymorphism and susceptibility to colorectal cancer
among Isfahan and Chaharmahal Va Bakhtiari (a part of south west
of Iran) population. We investigated the status of p53 at codon 72 for
Arg/Arg, Arg/Pro and Pro/Pro allele polymorphisms in blood
samples from 145 colorectal cancer patients and 140 controls by
Nested-PCR of p53 exon 4 and digestion with BstUI restriction
enzyme and the DNA fragments were then resolved by
electrophoresis in 2% agarose gel. The Pro allele was 279 bp, while
the Arg allele was restricted into two fragments of 160 and 119 bp.
Among the 145 colorectal cancer cases 49 cases (33.79%) were
homozygous for the Arg72 allele (Arg/Arg), 18 cases (12.41%) were
homozygous for the Pro72 allele (Pro/Pro) and 78 cases (53.8%)
found in heterozygous (Arg/Pro).
In conclusion, it can be said that p53Arg/Arg genotype may be
correlated with possible increased risk of this kind of cancers in south
west of Iran.
Abstract: This paper provides an in-depth study of Wireless
Sensor Network (WSN) application to monitor and control the
swiftlet habitat. A set of system design is designed and developed
that includes the hardware design of the nodes, Graphical User
Interface (GUI) software, sensor network, and interconnectivity for
remote data access and management. System architecture is proposed
to address the requirements for habitat monitoring. Such applicationdriven
design provides and identify important areas of further work
in data sampling, communications and networking. For this
monitoring system, a sensor node (MTS400), IRIS and Micaz radio
transceivers, and a USB interfaced gateway base station of Crossbow
(Xbow) Technology WSN are employed. The GUI of this monitoring
system is written using a Laboratory Virtual Instrumentation
Engineering Workbench (LabVIEW) along with Xbow Technology
drivers provided by National Instrument. As a result, this monitoring
system is capable of collecting data and presents it in both tables and
waveform charts for further analysis. This system is also able to send
notification message by email provided Internet connectivity is
available whenever changes on habitat at remote sites (swiftlet farms)
occur. Other functions that have been implemented in this system
are the database system for record and management purposes; remote
access through the internet using LogMeIn software. Finally, this
research draws a conclusion that a WSN for monitoring swiftlet
habitat can be effectively used to monitor and manage swiftlet
farming industry in Sarawak.
Abstract: Non-viral gene carriers composed of biodegradable
polymers or lipids have been considered as a safer alternative for gene
carriers over viral vectors. We have developed multi-functional
nano-micelles for both drug and gene delivery application.
Polyethyleneimine (PEI) was modified by grafting stearic acid (SA)
and formulated to polymeric micelles (PEI-SA) with positive surface
charge for gene and drug delivery. Our results showed that PEI-SA
micelles provided high siRNA binding efficiency. In addition, siRNA
delivered by PEI-SA carriers also demonstrated significantly high
cellular uptake even in the presence of serum proteins. The
post-transcriptional gene silencing efficiency was greatly improved by
the polyplex formulated by 10k PEI-SA/siRNA. The amphiphilic
structure of PEI-SA micelles provided advantages for multifunctional
tasks; where the hydrophilic shell modified with cationic charges can
electrostatically interact with DNA or siRNA, and the hydrophobic
core can serve as payloads for hydrophobic drugs, making it a
promising multifunctional vehicle for both genetic and chemotherapy
application.
Abstract: In the recent past Learning Classifier Systems have
been successfully used for data mining. Learning Classifier System
(LCS) is basically a machine learning technique which combines
evolutionary computing, reinforcement learning, supervised or
unsupervised learning and heuristics to produce adaptive systems. A
LCS learns by interacting with an environment from which it
receives feedback in the form of numerical reward. Learning is
achieved by trying to maximize the amount of reward received. All
LCSs models more or less, comprise four main components; a finite
population of condition–action rules, called classifiers; the
performance component, which governs the interaction with the
environment; the credit assignment component, which distributes the
reward received from the environment to the classifiers accountable
for the rewards obtained; the discovery component, which is
responsible for discovering better rules and improving existing ones
through a genetic algorithm. The concatenate of the production rules
in the LCS form the genotype, and therefore the GA should operate
on a population of classifier systems. This approach is known as the
'Pittsburgh' Classifier Systems. Other LCS that perform their GA at
the rule level within a population are known as 'Mitchigan' Classifier
Systems. The most predominant representation of the discovered
knowledge is the standard production rules (PRs) in the form of IF P
THEN D. The PRs, however, are unable to handle exceptions and do
not exhibit variable precision. The Censored Production Rules
(CPRs), an extension of PRs, were proposed by Michalski and
Winston that exhibit variable precision and supports an efficient
mechanism for handling exceptions. A CPR is an augmented
production rule of the form: IF P THEN D UNLESS C, where
Censor C is an exception to the rule. Such rules are employed in
situations, in which conditional statement IF P THEN D holds
frequently and the assertion C holds rarely. By using a rule of this
type we are free to ignore the exception conditions, when the
resources needed to establish its presence are tight or there is simply
no information available as to whether it holds or not. Thus, the IF P
THEN D part of CPR expresses important information, while the
UNLESS C part acts only as a switch and changes the polarity of D
to ~D. In this paper Pittsburgh style LCSs approach is used for
automated discovery of CPRs. An appropriate encoding scheme is
suggested to represent a chromosome consisting of fixed size set of
CPRs. Suitable genetic operators are designed for the set of CPRs
and individual CPRs and also appropriate fitness function is proposed
that incorporates basic constraints on CPR. Experimental results are
presented to demonstrate the performance of the proposed learning
classifier system.
Abstract: In this paper, a new time-delay estimation
technique based on the cross IB-energy operator [5] is
introduced. This quadratic energy detector measures how
much a signal is present in another one. The location of the
peak of the energy operator, corresponding to the maximum of
interaction between the two signals, is the estimate of the
delay. The method is a fully data-driven approach. The
discrete version of the continuous-time form of the cross IBenergy
operator, for its implementation, is presented. The
effectiveness of the proposed method is demonstrated on real
underwater acoustic signals arriving from targets and the
results compared to the cross-correlation method.
Abstract: This paper presents the results of the experimental
tests of the cooling performance of a 12,000-Btu/h modified air
conditioner (referred to as M-AC) that use the ground as a heat sink
of a condenser. In the tests, cooling capacity of M-AC with an
optimal length of a condensing coil as well as life expectancy of
copper coil buried underground were investigated. The lengths of
copper coil fabricated and used as condenser coil of M-AC were set
at 67, 50, 40 and 30 m whereas that of a 12,000-Btu/h conventional
split-type air conditioner (referred to as C-AC) was about 22 m. The
results showed that the ground can absorb heat rejected from a
condenser of M-AC. The coefficient of performance (COP) of C-AC
was about 2.5 whereas those of M-AC were found to be higher. It
was found that the values of COP of M-AC with condensing coils of
67, 50 and 40 m long were about 6.9, 5.5 and 3.3, respectively, while
that of 30-m-long one was found to be about 2.1. The electrical
consumptions of M-AC were found lower than that of C-AC in the
range of 11.5 – 15.5%. Additionally, life expectancy of underground
condensing coil of M-AC was found to be over 7 years.
Abstract: Human identification at a distance has recently gained
growing interest from computer vision researchers. Gait recognition
aims essentially to address this problem by identifying people based
on the way they walk [1]. Gait recognition has 3 steps. The first step
is preprocessing, the second step is feature extraction and the third
one is classification. This paper focuses on the classification step that
is essential to increase the CCR (Correct Classification Rate).
Multilayer Perceptron (MLP) is used in this work. Neural Networks
imitate the human brain to perform intelligent tasks [3].They can
represent complicated relationships between input and output and
acquire knowledge about these relationships directly from the data
[2]. In this paper we apply MLP NN for 11 views in our database and
compare the CCR values for these views. Experiments are performed
with the NLPR databases, and the effectiveness of the proposed
method for gait recognition is demonstrated.
Abstract: A Comparison and evaluation of the different
condition monitoring (CM) techniques was applied experimentally
on RC e.g. Dynamic cylinder pressure and crankshaft Instantaneous
Angular Speed (IAS), for the detection and diagnosis of valve faults
in a two - stage reciprocating compressor for a programme of
condition monitoring which can successfully detect and diagnose a
fault in machine. Leakage in the valve plate was introduced
experimentally into a two-stage reciprocating compressor. The effect
of the faults on compressor performance was monitored and the
differences with the normal, healthy performance noted as a fault
signature been used for the detection and diagnosis of faults.
The paper concludes with what is considered to be a unique
approach to condition monitoring. First, each of the two most useful
techniques is used to produce a Truth Table which details the
circumstances in which each method can be used to detect and
diagnose a fault. The two Truth Tables are then combined into a
single Decision Table to provide a unique and reliable method of
detection and diagnosis of each of the individual faults introduced
into the compressor. This gives accurate diagnosis of compressor
faults.
Abstract: The paper deals with the estimation of amplitude and phase of an analogue multi-harmonic band-limited signal from irregularly spaced sampling values. To this end, assuming the signal fundamental frequency is known in advance (i.e., estimated at an independent stage), a complexity-reduced algorithm for signal reconstruction in time domain is proposed. The reduction in complexity is achieved owing to completely new analytical and summarized expressions that enable a quick estimation at a low numerical error. The proposed algorithm for the calculation of the unknown parameters requires O((2M+1)2) flops, while the straightforward solution of the obtained equations takes O((2M+1)3) flops (M is the number of the harmonic components). It is applied in signal reconstruction, spectral estimation, system identification, as well as in other important signal processing problems. The proposed method of processing can be used for precise RMS measurements (for power and energy) of a periodic signal based on the presented signal reconstruction. The paper investigates the errors related to the signal parameter estimation, and there is a computer simulation that demonstrates the accuracy of these algorithms.
Abstract: Let R be a ring and n a fixed positive integer, we
investigate the properties of n-strongly Gorenstein projective, injective
and flat modules. Using the homological theory , we prove that
the tensor product of an n-strongly Gorenstein projective (flat) right
R -module and projective (flat) left R-module is also n-strongly
Gorenstein projective (flat). Let R be a coherent ring ,we prove that
the character module of an n -strongly Gorenstein flat left R -module
is an n-strongly Gorenstein injective right R -module . At last, let
R be a commutative ring and S a multiplicatively closed set of R ,
we establish the relation between n -strongly Gorenstein projective
(injective , flat ) R -modules and n-strongly Gorenstein projective
(injective , flat ) S−1R-modules. All conclusions in this paper is
helpful for the research of Gorenstein dimensions in future.
Abstract: Three alumina-supported Pt-Sn catalysts have been
prepared by means of co-impregnation and characterized by XRD and
N2 adsorption. The influence of catalyst composition and reaction
conditions on the conversion and selectivity were investigated in the
hydrogenation of acetic acid in an isothermal integral fixed bed
reactor. The experiments were performed on the temperature interval
468-548 K, liquid hourly space velocity (LHSV) of 0.3-0.7h-1,
pressures between 1.0 and 5.0Mpa. A good compromise of
0.75%Pt-1.5%Sn can act as an optimized acetic acid hydrogenation
catalyst, and the conversion and selectivity can be tuned through the
variation of reaction conditions.
Abstract: In the past few years there is a change in the view of high performance applications and parallel computing. Initially such applications were targeted towards dedicated parallel machines. Recently trend is changing towards building meta-applications composed of several modules that exploit heterogeneous platforms and employ hybrid forms of parallelism. The aim of this paper is to propose a model of virtual parallel computing. Virtual parallel computing system provides a flexible object oriented software framework that makes it easy for programmers to write various parallel applications.
Abstract: The technology usages of high speed Internet leads to
establish and start new era of online education. With the
advancement of the information technology and communication
systems new opportunities have been created. This leads universities
to have various online education channels to meet the demand of
different learners- needs. One of these channels is M-learning, which
can be used to improve the online education environment. With using
such mobile technology in learning both students and instructors can
easily access educational courses anytime from anywhere. The paper
first presents literature about mobile learning and to what extent this
approach can be utilized to enhance the overall learning system. It
provides a comparison between mobile learning and traditional elearning
showing the wide array of benefits of the new generation of
technology. The possible challenges and potential advantages of Mlearning
in the online education system are also discussed.
Abstract: Experimental investigations were carried out in the
Manchester Tidal flow Facility (MTF) to study the flow patterns in
the region around and adjacent to a hypothetical headland in tidal
(oscillatory) ambient flow. The Planar laser-induced fluorescence
(PLIF) technique was used for visualization, with fluorescent dye
released at specific points around the headland perimeter and in its
adjacent recirculation zone. The flow patterns can be generalized into
the acceleration, stable flow and deceleration stages for each halfcycle,
with small variations according to location, which are more
distinct for low Keulegan-Carpenter number (KC) cases. Flow
patterns in the mixing region are unstable and complex, especially in
the recirculation zone. The flow patterns are in agreement with
previous visualizations, and support previous results in steady
ambient flow. It is suggested that the headland lee could be a viable
location for siting of pollutant outfalls.
Abstract: The purpose of this paper is to solve the problem of protecting aerial lines from high impedance faults (HIFs) in distribution systems. This investigation successfully applies 3I0 zero sequence current to solve HIF problems. The feature extraction system based on discrete wavelet transform (DWT) and the feature identification technique found on statistical confidence are then applied to discriminate effectively between the HIFs and the switch operations. Based on continuous wavelet transform (CWT) pattern recognition of HIFs is proposed, also. Staged fault testing results demonstrate that the proposed wavelet based algorithm is feasible performance well.
Abstract: This paper presents the modeling results of an
innovative system for the temperature control in the interior
compartment of a stationary automobile facing the solar energy from
the sun. A very thin layer of PCM inside a pouch placed in the
ceiling of the car in which the heating energy is absorbed and release
with melting and solidification of phase change materials. As a result
the temperature of the car interior is maintained in the comfort
condition. The amount of required PCM has been calculated to be
about 755 g. The PCM-temperature controlling system is simple and
has a potential to be implemented as a practical solution to prevent
undesirable heating of the automobile-s cabin.
Abstract: In recent years, scanning probe atomic force
microscopy SPM AFM has gained acceptance over a wide spectrum
of research and science applications. Most fields focuses on physical,
chemical, biological while less attention is devoted to manufacturing
and machining aspects. The purpose of the current study is to assess
the possible implementation of the SPM AFM features and its
NanoScope software in general machining applications with special
attention to the tribological aspects of cutting tool. The surface
morphology of coated and uncoated as-received carbide inserts is
examined, analyzed, and characterized through the determination of
the appropriate scanning setting, the suitable data type imaging
techniques and the most representative data analysis parameters
using the MultiMode SPM AFM in contact mode. The NanoScope
operating software is used to capture realtime three data types
images: “Height", “Deflection" and “Friction". Three scan sizes are
independently performed: 2, 6, and 12 μm with a 2.5 μm vertical
range (Z). Offline mode analysis includes the determination of three
functional topographical parameters: surface “Roughness", power
spectral density “PSD" and “Section". The 12 μm scan size in
association with “Height" imaging is found efficient to capture every
tiny features and tribological aspects of the examined surface. Also,
“Friction" analysis is found to produce a comprehensive explanation
about the lateral characteristics of the scanned surface. Configuration
of many surface defects and drawbacks has been precisely detected
and analyzed.
Abstract: Trust management and Reputation models are
becoming integral part of Internet based applications such as CSCW,
E-commerce and Grid Computing. Also the trust dimension is a
significant social structure and key to social relations within a
collaborative community. Collaborative Decision Making (CDM) is
a difficult task in the context of distributed environment (information
across different geographical locations) and multidisciplinary
decisions are involved such as Virtual Organization (VO). To aid
team decision making in VO, Decision Support System and social
network analysis approaches are integrated. In such situations social
learning helps an organization in terms of relationship, team
formation, partner selection etc. In this paper we focus on trust
learning. Trust learning is an important activity in terms of
information exchange, negotiation, collaboration and trust
assessment for cooperation among virtual team members. In this
paper we have proposed a reinforcement learning which enhances the
trust decision making capability of interacting agents during
collaboration in problem solving activity. Trust computational model
with learning that we present is adapted for best alternate selection of
new project in the organization. We verify our model in a multi-agent
simulation where the agents in the community learn to identify
trustworthy members, inconsistent behavior and conflicting behavior
of agents.