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: 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: 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: Link reliability and transmitted power are two important design constraints in wireless network design. Error control coding (ECC) is a classic approach used to increase link reliability and to lower the required transmitted power. It provides coding gain, resulting in transmitter energy savings at the cost of added decoder power consumption. But the choice of ECC is very critical in the case of wireless sensor network (WSN). Since the WSNs are energy constraint in nature, both the BER and power consumption has to be taken into count. This paper develops a step by step approach in finding suitable error control codes for WSNs. Several simulations are taken considering different error control codes and the result shows that the RS(31,21) fits both in BER and power consumption criteria.
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: 17α-ethynylestradiol (EE2) is a synthetic estrogen
used as a key ingredient in an oral contraceptives pill. EE2 is an
endocrine disrupting compound, high in estrogenic potency.
Although EE2 exhibits low degree of biodegradability with common
microorganisms in wastewater treatment plants (WWTPs), this
compound can be biotransformed by ammonia-oxidizing bacteria
(AOB) via a co-metabolism mechanism in WWTPs. This study
aimed to investigate the effect of real wastewater on
biotransformation of EE2 by AOB. A preliminary experiment on the
effect of nitrite and pH levels on abiotic transformation of EE2
suggested that the abiotic transformation occurred at only pH
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: 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: 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.
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: 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: This study examines the possibility to apply the theory of multidimensional accounting (momentum accounting) in a Brazilian Navy-s Services Provider Military Organization (Organização Militar Prestadora de Serviços - OMPS). In general, the core of the said theory is the fact that Accounting does not recognize the inertia of transactions occurring in an entity, and that occur repeatedly in some cases, regardless of the implementation of new actions by its managers. The study evaluates the possibility of greater use of information recorded in the financial statements of the unit of analysis, within the strategic decisions of the organization. As a research strategy, we adopted the case study. The results infer that it is possible to use the theory in the context of a multidimensional OMPS, promoting useful information for decision-making and thereby contributing to the strengthening of the necessary alignment of its administration with the current desires of the Brazilian society.
Abstract: High quality requirements analysis is one of the most
crucial activities to ensure the success of a software project, so that
requirements verification for software system becomes more and more
important in Requirements Engineering (RE) and it is one of the most
helpful strategies for improving the quality of software system.
Related works show that requirement elicitation and analysis can be
facilitated by ontological approaches and semantic web technologies.
In this paper, we proposed a hybrid method which aims to verify
requirements with structural and formal semantics to detect
interactions. The proposed method is twofold: one is for modeling
requirements with the semantic web language OWL, to construct a
semantic context; the other is a set of interaction detection rules which
are derived from scenario-based analysis and represented with
semantic web rule language (SWRL). SWRL based rules are working
with rule engines like Jess to reason in semantic context for
requirements thus to detect interactions. The benefits of the proposed
method lie in three aspects: the method (i) provides systematic steps
for modeling requirements with an ontological approach, (ii) offers
synergy of requirements elicitation and domain engineering for
knowledge sharing, and (3)the proposed rules can systematically assist
in requirements interaction detection.
Abstract: We study dynamic instability in high-rise steel moment
resisting frames (SMRFs) subjected to synthetic long-period ground
motions caused by hypothetical huge subduction earthquakes. Since
long duration as well as long dominant periods is a characteristic of
long-period ground motions, interstory drifts may enter the negative
postyield stiffness range many times when high-rise buildings are
subjected to long-period ground motions. Through the case studies of
9 high-rise SMRFs designed in accordance with the Japanese design
practice in 1980s, we demonstrate that drifting, or accumulation of
interstory drifts in one direction, occurs at the lower stories of the
SMRFs, if their natural periods are close to the dominant periods of the
long-period ground motions. The drifting led to residual interstory
drift ratio over 0.01, or to collapse if the design base shear was small.
Abstract: Groundwater has become the most dependable source
of fresh water for agriculture, domestic and industrial uses in the past
few decades. This wide use of groundwater if left uncontrolled and
unseen will lead to overexploitation causing sea water intrusion in the
coastal areas and illegal water marketing. Several Policies and Acts
have been enacted to regulate and manage the use of this valuable
resource. In spite of this the over extraction of groundwater beyond
the recharging capacity of aquifers and depletion in the quality of
groundwater is continuing. The current study aims at reviewing the
Acts and Policies existing in the State of Tamil Nadu and in the
National level regarding groundwater regulation and management.
Further an analysis is made on the rights associated with the usage of
groundwater resources and the gaps in these policies have been
analyzed. Some suggestions are made to reform the existing
groundwater policies for better management and regulation of the
resource.
Abstract: The thermal, epithermal and fast fluxes were
calculated for three irradiation channels at Egypt Second Research
Reactor (ETRR-2) using CITVAP code. The validity of the
calculations was verified by experimental measurements. There are
some deviations between measurements and calculations. This is due
to approximations in the calculation models used, homogenization of
regions, condensation of energy groups and uncertainty in nuclear
data used. Neutron flux data for the three irradiation channels are
now available. This would enable predicting the irradiation
conditions needed for future radioisotope production.
Abstract: The hypercube Qn is one of the most well-known
and popular interconnection networks and the k-ary n-cube Qk
n is
an enlarged family from Qn that keeps many pleasing properties
from hypercubes. In this article, we study the panpositionable
hamiltonicity of Qk
n for k ≥ 3 and n ≥ 2. Let x, y of V (Qk
n)
be two arbitrary vertices and C be a hamiltonian cycle of Qk
n.
We use dC(x, y) to denote the distance between x and y on the
hamiltonian cycle C. Define l as an integer satisfying d(x, y) ≤ l ≤ 1
2 |V (Qk
n)|. We prove the followings:
• When k = 3 and n ≥ 2, there exists a hamiltonian cycle C
of Qk
n such that dC(x, y) = l.
• When k ≥ 5 is odd and n ≥ 2, we request that l /∈ S
where S is a set of specific integers. Then there exists a
hamiltonian cycle C of Qk
n such that dC(x, y) = l.
• When k ≥ 4 is even and n ≥ 2, we request l-d(x, y) to be
even. Then there exists a hamiltonian cycle C of Qk
n such
that dC(x, y) = l.
The result is optimal since the restrictions on l is due to the
structure of Qk
n by definition.
Abstract: In this study we investigate silica nanoparticle (SiO2- NP) effects on the structure and phase properties of supported lipid monolayers and bilayers, coupling surface pressure measurements, fluorescence microscopy and atomic force microscopy. SiO2-NPs typically in size range of 10nm to 100 nm in diameter are tested. Our results suggest first that lipid molecules organization depends to their nature. Secondly, lipid molecules in the vinicity of big aggregates nanoparticles organize in liquid condensed phase whereas small aggregates are localized in both fluid liquid-expanded (LE) and liquid-condenced (LC). We demonstrated also by atomic force microscopy that by measuring friction forces it is possible to get information as if nanoparticle aggregates are recovered or not by lipid monolayers and bilayers.
Abstract: The group mutual exclusion (GME) problem is a
variant of the mutual exclusion problem. In the present paper a
token-based group mutual exclusion algorithm, capable of handling
transient faults, is proposed. The algorithm uses the concept of
dynamic request sets. A time out mechanism is used to detect the
token loss; also, a distributed scheme is used to regenerate the token.
The worst case message complexity of the algorithm is n+1. The
maximum concurrency and forum switch complexity of the
algorithm are n and min (n, m) respectively, where n is the number of
processes and m is the number of groups. The algorithm also satisfies
another desirable property called smooth admission. The scheme can
also be adapted to handle the extended group mutual exclusion
problem.