Abstract: This paper describes the development of an electronic
instrument that looks like a flute, which is able to sense the basic musical notes being executed by a specific user. The principal function of the instrument is to teach how to play a flute. This device
will generate a significant academic impact, in a field of virtual reality interactive that combine art and technology. With this example is expected to contribute in research and implementation of teaching devices around the world.
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: The use of power system stabilizers (PSSs) to damp
power system swing mode of oscillations is practical important. Our
purpose is to retune the power system stabilizer (PSS1A) parameters
in Unitrol D produced by ABB– was installed in 1995in Benghazi
North Power Plants (BNPPs) at General Electricity Company of
Libya (GECOL). The optimal values of the power system stabilizer
(PSS1A) parameters are determined off-line by a particle swarm
optimization technique (PSO). The objective is to damp the local and
inter-area modes of oscillations that occur following power system
disturbances. The retuned power system stabilizer (PSS1A) can cope
with large disturbance at different operating points and has enhanced
power system stability.
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: Chaos and fractals are novel fields of physics and mathematics showing up a new way of universe viewpoint and creating many ideas to solve several present problems. In this paper, a novel algorithm based on the chaotic sequence generator with the highest ability to adapt and reach the global optima is proposed. The adaptive ability of proposal algorithm is flexible in 2 steps. The first one is a breadth-first search and the second one is a depth-first search. The proposal algorithm is examined by 2 functions, the Camel function and the Schaffer function. Furthermore, the proposal algorithm is applied to optimize training Multilayer Neural Networks.
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: 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: The temporal nature of negative selection is an under exploited area. In a negative selection system, newly generated antibodies go through a maturing phase, and the survivors of the phase then wait to be activated by the incoming antigens after certain number of matches. These without having enough matches will age and die, while these with enough matches (i.e., being activated) will become active detectors. A currently active detector may also age and die if it cannot find any match in a pre-defined (lengthy) period of time. Therefore, what matters in a negative selection system is the dynamics of the involved parties in the current time window, not the whole time duration, which may be up to eternity. This property has the potential to define the uniqueness of negative selection in comparison with the other approaches. On the other hand, a negative selection system is only trained with “normal" data samples. It has to learn and discover unknown “abnormal" data patterns on the fly by itself. Consequently, it is more appreciate to utilize negation selection as a system for pattern discovery and recognition rather than just pattern recognition. In this paper, we study the potential of using negative selection in discovering unknown temporal patterns.
Abstract: Dredged sediment (DS) was utilized as source of
silt-clay and organic matter in artificially prepared eelgrass substrates with mountain sand (MS) as the sand media. Addition of DS showed
improved growth of eelgrass in the mixed substrates. Increase in added
DS up to 15% silt-clay showed increased shoot growth but additional
DS in 20% silt-clay mixture didn-t result to further increase in eelgrass
growth. Improved root establishment were also found for plants in pots
with added DS as shown by the increased resistance to uprooting, increased number of rhizome nodes and longer roots. Results demonstrated that addition of DS may be beneficial to eelgrass up to a
certain extent only and too much of it might be harmful to eelgrass plants.
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: 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: Magnetic Nanoparticles (MNPs) have great potential
to overcome many of the shortcomings of the present diagnostic and
therapeutic approaches used in cancer diagnosis and treatment. This
Literature review discusses the use of Magnetic Nanoparticles
focusing mainly on Iron oxide based MNPs in cancer imaging using
MRI.
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.
Abstract: This paper discusses the designing of knowledge
integration of clinical information extracted from distributed medical
ontologies in order to ameliorate a machine learning-based multilabel
coding assignment system. The proposed approach is
implemented using a decision tree technique of the machine learning
on the university hospital data for patients with Coronary Heart
Disease (CHD). The preliminary results obtained show a satisfactory
finding that the use of medical ontologies improves the overall
system performance.
Abstract: Fungal infections are becoming more common and the
range of susceptible individuals has expanded. While Candida
albicans remains the most common infective species, other Candida
spp. are becoming increasingly significant. In a range of large-scale
studies of candidaemia between 1999 and 2006, about 52% of 9717
cases involved C. albicans, about 30% involved either C. glabrata or
C. parapsilosis and less than 15% involved C. tropicalis, C. krusei or
C. guilliermondii. However, the probability of mortality within 30
days of infection with a particular species was at least 40% for C.
tropicalis, C. albicans, C. glabrata and C. krusei and only 22% for
C. parapsilopsis. Clinical isolates of Candida spp. grew at rates
ranging from 1.65 h-1 to 4.9 h-1. Three species (C. krusei, C. albicans
and C. glabrata) had relatively high growth rates (μm > 4 h-1), C.
tropicalis and C. dubliniensis grew moderately quickly (Ôëê 3 h-1) and
C. parapsilosis and C. guilliermondii grew slowly (< 2 h-1). Based
on these data, the log of the odds of mortality within 30 days of
diagnosis was linearly related to μm. From this the underlying
probability of mortality is 0.13 (95% CI: 0.10-0.17) and it increases
by about 0.09 ± 0.02 for each unit increase in μm. Given that the
overall crude mortality is about 0.36, the growth of Candida spp.
approximately doubles the rate, consistent with the results of larger
case-matched studies of candidaemia.
Abstract: Finding effective ways of improving university quality assurance requires, as well, a retraining of the staff. This article illustrates an Online Programme of Excellence Model (OPEM), based on the European quality assurance model, for improving participants- formative programme standards. The results of applying this OPEM indicate the necessity of quality policies that support the evaluators- competencies to improve formative programmes. The study concludes by outlining how faculty and agency staff can use OPEM for the internal and external quality assurance of formative programmes.
Abstract: There are several approaches for handling multiclass classification. Aside from one-against-one (OAO) and one-against-all (OAA), hierarchical classification technique is also commonly used. A binary classification tree is a hierarchical classification structure that breaks down a k-class problem into binary sub-problems, each solved by a binary classifier. In each node, a set of classes is divided into two subsets. A good class partition should be able to group similar classes together. Many algorithms measure similarity in term of distance between class centroids. Classes are grouped together by a clustering algorithm when distances between their centroids are small. In this paper, we present a binary classification tree with tuned observation-based clustering (BCT-TOB) that finds a class partition by performing clustering on observations instead of class centroids. A merging step is introduced to merge any insignificant class split. The experiment shows that performance of BCT-TOB is comparable to other algorithms.
Abstract: Information sharing and exchange, rather than
information processing, is what characterizes information
technology in the 21st century. Ontologies, as shared common
understanding, gain increasing attention, as they appear as the
most promising solution to enable information sharing both at
a semantic level and in a machine-processable way. Domain
Ontology-based modeling has been exploited to provide
shareability and information exchange among diversified,
heterogeneous applications of enterprises.
Contextual ontologies are “an explicit specification of
contextual conceptualization". That is: ontology is
characterized by concepts that have multiple representations
and they may exist in several contexts. Hence, contextual
ontologies are a set of concepts and relationships, which are
seen from different perspectives. Contextualization is to allow
for ontologies to be partitioned according to their contexts.
The need for contextual ontologies in enterprise modeling
has become crucial due to the nature of today's competitive
market. Information resources in enterprise is distributed and
diversified and is in need to be shared and communicated
locally through the intranet and globally though the internet.
This paper discusses the roles that ontologies play in an
enterprise modeling, and how ontologies assist in building a
conceptual model in order to provide communicative and
interoperable information systems. The issue of enterprise
modeling based on contextual domain ontology is also
investigated, and a framework is proposed for an enterprise
model that consists of various applications.
Abstract: Recent theorizations on the cognitive process of moral
judgment have focused on the role of intuitions and emotions, marking
a departure from previous emphasis on conscious, step-by-step
reasoning. My study investigated how being in a disgusted mood state
affects moral judgment.
Participants were induced to enter a disgusted mood state through
listening to disgusting sounds and reading disgusting descriptions.
Results shows that they, when compared to control who have not been
induced to feel disgust, are more likely to endorse actions that are
emotionally aversive but maximizes utilitarian return
The result is analyzed using the 'emotion-as-information' approach
to decision making. The result is consistent with the view that
emotions play an important role in determining moral judgment.
Abstract: This study was carried out in Ankara, the capital city of Turkey, in order to determine how people living in the slums of Ankara benefit from educational equality. Within the scope of the research, interviews were made with 64 families whose children have been getting education from the primary schools of these parts and the data of the study was collected by the researcher. The results of the research demonstrate that the children getting education in the slums of Ankara can not experience educational equality and justice. The results of this study show that the opportunities of the schools in the slums of Ankara are very limited, so the individuals in these districts can not equally benefit from the education. The families are aware of the problem they are faced with. KeywordsDiscrimination, inequality, primary education, slums of Turkey.