Abstract: In the last few decades, many southeast-Asia women
migrate to Taiwan by marriage, and it usually takes several years for
them to acquire Taiwanese citizenship. This study investigates the
relationship between their citizenship acquisition and whether they
develop Taiwanese identities, and how does it affect their ethnical
identity towards their original ethnics. Furthermore, the present study
also explores that whether citizenship acquisition help the immigrant
women to explore the host society further and make commitment to it,
or the identification towards mainstream Taiwanese society is only
symbolic and superficial? One hundred and ninety-two immigrant
women were measured using Multigroup Ethnic Identity
Measure-Revised and a global 10-point ethnic identity question.
Correlation tests, t-test, and hierarchical regression were performed to
answer the above questions. The results revealed that citizenship
acquisition does help immigrant women to identify with Taiwanese
society, but it does not affect how they identify with their own ethnics.
Furthermore, the results also indicated that acquiring citizenship
would not help these immigrant women become involved in deeper
cultural exploration of Taiwan nor would it encourage them to make
commitments to the host society.
Abstract: In this study a ternary system containing sodium
chloride as solute, water as primary solvent and ethanol as the
antisolvent was considered to investigate the application of artificial
neural network (ANN) in prediction of sodium solubility in the
mixture of water as the solvent and ethanol as the antisolvent. The
system was previously studied using by Extended UNIQUAC model
by the authors of this study. The comparison between the results of
the two models shows an excellent agreement between them
(R2=0.99), and also approves the capability of ANN to predict the
thermodynamic behavior of ternary electrolyte systems which are
difficult to model.
Abstract: To date, one of the few comprehensive indicators for
the measurement of food security is the Global Food Security Index
(GFSI). This index is a dynamic quantitative and qualitative
benchmarking model, constructed from 28 unique indicators, that
measures drivers of food security across both developing and
developed countries. Whereas the GFSI has been calculated across a
set of 109 countries, in this paper we aim to present and compare, for
the Middle East and North Africa (MENA), 1) the Food Security
Index scores achieved and 2) the data available on affordability,
availability, and quality of food. The data for this work was taken
from the latest available report published by the creators of the GFSI,
which in turn used information from national and international
statistical sources. MENA countries rank from place 17/109 (Israel,
although with resent political turmoil this is likely to have changed)
to place 91/109 (Yemen) with household expenditure spent in food
ranging from 15.5% (Israel) to 60% (Egypt). Lower spending on food
as a share of household consumption in most countries and better
food safety net programs in the MENA have contributed to a notable
increase in food affordability. The region has also, however,
experienced a decline in food availability, owing to more limited
food supplies and higher volatility of agricultural production. In
terms of food quality and safety the MENA has the top ranking
country (Israel). The most frequent challenges faced by the countries
of the MENA include public expenditure on agricultural research and
development as well as volatility of agricultural production. Food
security is a complex phenomenon that interacts with many other
indicators of a country’s wellbeing; in the MENA it is slowly but
markedly improving.
Abstract: A Distributed Denial of Service (DDoS) attack is a
major threat to cyber security. It originates from the network layer or
the application layer of compromised/attacker systems which are
connected to the network. The impact of this attack ranges from the
simple inconvenience to use a particular service to causing major
failures at the targeted server. When there is heavy traffic flow to a
target server, it is necessary to classify the legitimate access and
attacks. In this paper, a novel method is proposed to detect DDoS
attacks from the traces of traffic flow. An access matrix is created
from the traces. As the access matrix is multi dimensional, Principle
Component Analysis (PCA) is used to reduce the attributes used for
detection. Two classifiers Naive Bayes and K-Nearest neighborhood
are used to classify the traffic as normal or abnormal. The
performance of the classifier with PCA selected attributes and actual
attributes of access matrix is compared by the detection rate and
False Positive Rate (FPR).
Abstract: Vertical Handover(VHO) among different
communication technologies ensuring uninterruption and service
continuity is one of the most important performance parameter in
Heterogenous networks environment. In an integrated Universal
Mobile Telecommunicatin System(UMTS) and Wireless Local
Area Network(WLAN), WLAN is given an inherent priority over
UMTS because of its high data rates with low cost. Therefore
mobile users want to be associated with WLAN maximum of the
time while roaming, to enjoy best possible services with low cost.
That encourages reduction of number of VHO. In this work the
reduction of number of VHO with respect to varying number of
WLAN Access Points(APs) in an integrated UMTS and WLAN
network is investigated through simulation to provide best possible
cost effective service to the users. The simulation has been carried
out for an area (7800 × 9006)m2 where COST-231 Hata model
and 3GPP (TR 101 112 V 3.1.0) specified models are used for
WLAN and UMTS path loss models respectively. The handover
decision is triggered based on the received signal level as compared
to the fade margin. Fade margin gives a probabilistic measure of
the reliability of the communication link. A relationship between
number of WLAN APs and the number of VHO is also established
in this work.
Abstract: Given the dynamic nature of the higher education
landscape, induction programmes for new academics has become the
norm nowadays to support academics negotiate these rough terrain.
This study investigates an induction programme for new academics
in a higher education institution to establish what difference it has
made to participants. The findings revealed that the benefits ranged
from creating safe spaces for collaboration and networking to
fostering reflective practice and contributing to the scholarship of
teaching and learning. The study also revealed that some of the
intentions of the programme may not have been achieved, for
example transformative learning. This led to questioning whether this
intention is an appropriate one given the short duration of the
programme and the long, drawn out process of transformation. It may
be concluded that the academic induction programme in this study
serves to sow the seeds for transformative learning through fostering
critically reflective practice. Recommendations for further study
could include long term impact of the programme on student learning
and success, these being the core business of higher education. It is
also recommended that in addition to an induction programme, the
university invests in a mentoring programme for new staff and extend
the support for academics in order to sustain critical reflection and
which may contribute to transformative educational practice.
Abstract: Wireless mesh networking is rapidly gaining in
popularity with a variety of users: from municipalities to enterprises,
from telecom service providers to public safety and military
organizations. This increasing popularity is based on two basic facts:
ease of deployment and increase in network capacity expressed in
bandwidth per footage; WMNs do not rely on any fixed
infrastructure. Many efforts have been used to maximizing
throughput of the network in a multi-channel multi-radio wireless
mesh network. Current approaches are purely based on either static or
dynamic channel allocation approaches. In this paper, we use a
hybrid multichannel multi radio wireless mesh networking
architecture, where static and dynamic interfaces are built in the
nodes. Dynamic Adaptive Channel Allocation protocol (DACA), it
considers optimization for both throughput and delay in the channel
allocation. The assignment of the channel has been allocated to be codependent
with the routing problem in the wireless mesh network and
that should be based on passage flow on every link. Temporal and
spatial relationship rises to re compute the channel assignment every
time when the pattern changes in mesh network, channel assignment
algorithms assign channels in network. In this paper a computing
path which captures the available path bandwidth is the proposed
information and the proficient routing protocol based on the new path
which provides both static and dynamic links. The consistency
property guarantees that each node makes an appropriate packet
forwarding decision and balancing the control usage of the network,
so that a data packet will traverse through the right path.
Abstract: In this paper a new algorithm to generate random
simple polygons from a given set of points in a two dimensional
plane is designed. The proposed algorithm uses a genetic algorithm to
generate polygons with few vertices. A new merge algorithm is
presented which converts any two polygons into a simple polygon.
This algorithm at first changes two polygons into a polygonal chain
and then the polygonal chain is converted into a simple polygon. The
process of converting a polygonal chain into a simple polygon is
based on the removal of intersecting edges. The experiments results
show that the proposed algorithm has the ability to generate a great
number of different simple polygons and has better performance in
comparison to celebrated algorithms such as space partitioning and
steady growth.
Abstract: The main aim of a communication system is to
achieve maximum performance. In Cognitive Radio any user or
transceiver has ability to sense best suitable channel, while channel is
not in use. It means an unlicensed user can share the spectrum of a
licensed user without any interference. Though, the spectrum sensing
consumes a large amount of energy and it can reduce by applying
various artificial intelligent methods for determining proper spectrum
holes. It also increases the efficiency of Cognitive Radio Network
(CRN). In this survey paper we discuss the use of different learning
models and implementation of Artificial Neural Network (ANN) to
increase the learning and decision making capacity of CRN without
affecting bandwidth, cost and signal rate.
Abstract: Spam is any unwanted electronic message or material
in any form posted too many people. As the world is growing as
global world, social networking sites play an important role in
making world global providing people from different parts of the
world a platform to meet and express their views. Among different
social networking sites Facebook become the leading one. With
increase in usage different users start abusive use of Facebook by
posting or creating ways to post spam. This paper highlights the
potential spam types nowadays Facebook users’ faces. This paper
also provide the reason how user become victim to spam attack. A
methodology is proposed in the end discusses how to handle different
types of spam.
Abstract: In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.
Abstract: Given a graph G. A cycle of G is a sequence of
vertices of G such that the first and the last vertices are the same.
A hamiltonian cycle of G is a cycle containing all vertices of G.
The graph G is k-ordered (resp. k-ordered hamiltonian) if for any
sequence of k distinct vertices of G, there exists a cycle (resp.
hamiltonian cycle) in G containing these k vertices in the specified
order. Obviously, any cycle in a graph is 1-ordered, 2-ordered and 3-
ordered. Thus the study of any graph being k-ordered (resp. k-ordered
hamiltonian) always starts with k = 4. Most studies about this topic
work on graphs with no real applications. To our knowledge, the
chordal ring families were the first one utilized as the underlying
topology in interconnection networks and shown to be 4-ordered.
Furthermore, based on our computer experimental results, it was
conjectured that some of them are 4-ordered hamiltonian. In this
paper, we intend to give some possible directions in proving the
conjecture.
Abstract: In this study, we propose a novel technique for acoustic
echo suppression (AES) during speech recognition under barge-in
conditions. Conventional AES methods based on spectral subtraction
apply fixed weights to the estimated echo path transfer function
(EPTF) at the current signal segment and to the EPTF estimated until
the previous time interval. However, the effects of echo path changes
should be considered for eliminating the undesired echoes. We
describe a new approach that adaptively updates weight parameters in
response to abrupt changes in the acoustic environment due to
background noises or double-talk. Furthermore, we devised a voice
activity detector and an initial time-delay estimator for barge-in speech
recognition in communication networks. The initial time delay is
estimated using log-spectral distance measure, as well as
cross-correlation coefficients. The experimental results show that the
developed techniques can be successfully applied in barge-in speech
recognition systems.
Abstract: Cost of governance in Nigeria has become a challenge
to development and concern to practitioners and scholars alike in the
field of business and social science research. In the 2010 national
budget of NGN4.6 trillion or USD28.75billion for instance, only a
pantry sum of NGN1.8trillion or USD11.15billion was earmarked for
capital expenditure. Similarly, in 2013, out of a total national budget
of NGN4.92trillion or USD30.75billion, only the sum of
NGN1.50trllion or USD9.38billion was voted for capital expenditure.
Therefore, based on the data sourced from the Nigerian Office of
Statistics, Central bank of Nigeria Statistical Bulletin as well as from
the United Nations Development Programme, this study examined
the causes of high cost of governance in Nigeria. It found out that the
high cost of governance in the country is in the interest of the ruling
class, arising from their unethical behaviour – corrupt practices and
the poor management of public resources. As a result, the study
recommends the need to intensify the war against corruption and
mismanagement of public resources by government officials as
possible solution to overcome the high cost of governance in Nigeria.
This could be achieved by strengthening the constitutional powers of
the various anti-corruption agencies in the area of arrest, investigation
and prosecution of offenders without the interference of the executive
arm of government either at the local, state or federal level.
Abstract: Validity, integrity, and impacts of the IT systems of
the US federal courts have been studied as part of the Human Rights
Alert-NGO (HRA) submission for the 2015 Universal Periodic
Review (UPR) of human rights in the United States by the Human
Rights Council (HRC) of the United Nations (UN). The current
report includes overview of IT system analysis, data-mining and case
studies. System analysis and data-mining show: Development and
implementation with no lawful authority, servers of unverified
identity, invalidity in implementation of electronic signatures,
authentication instruments and procedures, authorities and
permissions; discrimination in access against the public and
unrepresented (pro se) parties and in favor of attorneys; widespread
publication of invalid judicial records and dockets, leading to their
false representation and false enforcement. A series of case studies
documents the impacts on individuals' human rights, on banking
regulation, and on international matters. Significance is discussed in
the context of various media and expert reports, which opine
unprecedented corruption of the US justice system today, and which
question, whether the US Constitution was in fact suspended. Similar
findings were previously reported in IT systems of the State of
California and the State of Israel, which were incorporated, subject to
professional HRC staff review, into the UN UPR reports (2010 and
2013). Solutions are proposed, based on the principles of publicity of
the law and the separation of power: Reliance on US IT and legal
experts under accountability to the legislative branch, enhancing
transparency, ongoing vigilance by human rights and internet
activists. IT experts should assume more prominent civic duties in the
safeguard of civil society in our era.
Abstract: In this study, the performance analyses of the twenty
five Coal-Fired Power Plants (CFPPs) used for electricity generation
are carried out through various Data Envelopment Analysis (DEA)
models. Three efficiency indices are defined and pursued. During the
calculation of the operational performance, energy and non-energy
variables are used as input, and net electricity produced is used as
desired output (Model-1). CO2 emitted to the environment is used as
the undesired output (Model-2) in the computation of the pure
environmental performance while in Model-3 CO2 emissions is
considered as detrimental input in the calculation of operational and
environmental performance. Empirical results show that most of the
plants are operating in increasing returns to scale region and Mettur
plant is efficient one with regards to energy use and environment.
The result also indicates that the undesirable output effect is
insignificant in the research sample. The present study will provide
clues to plant operators towards raising the operational and
environmental performance of CFPPs.
Abstract: The Roma (Gypsies) is a transnational minority with a
high degree of consanguineous marriages. Similar to other
genetically isolated founder populations, the Roma harbor a number
of unique or rare genetic disorders. This paper discusses about a rare
form of Charcot-Marie-Tooth disease – type 4G (CMT4G), also
called Hereditary Motor and Sensory Neuropathy type Russe, an
autosomal recessive disease caused by mutation private to Roma
characterized by abnormally increased density of non-myelinated
axons. CMT4G was originally found in Bulgarian Roma and in 2009
two putative causative mutations in the HK1 gene were identified.
Since then, several cases were reported in Roma families mainly
from Bulgaria and Spain. Here we present a Slovak Roma family in
which CMT4G was diagnosed on the basis of clinical examination
and genetic testing. This case is a further proof of the role of the HK1
gene in pathogenesis of the disease. It confirms that mutation in the
HK1 gene is a common cause of autosomal recessive CMT disease in
Roma and should be considered as a common part of a diagnostic
procedure.
Abstract: One of the major difficulties introduced with wind
power penetration is the inherent uncertainty in production originating
from uncertain wind conditions. This uncertainty impacts many
different aspects of power system operation, especially the balancing
power requirements. For this reason, in power system development
planing, it is necessary to evaluate the potential uncertainty in future
wind power generation. For this purpose, simulation models are
required, reproducing the performance of wind power forecasts.
This paper presents a wind power forecast error simulation models
which are based on the stochastic process simulation. Proposed
models capture the most important statistical parameters recognized
in wind power forecast error time series. Furthermore, two distinct
models are presented based on data availability. First model uses
wind speed measurements on potential or existing wind power plant
locations, while the seconds model uses statistical distribution of wind
speeds.
Abstract: This paper describes a novel application of Fiber
Braggs Grating (FBG) sensors in the assessment of human postural
stability and balance on an unstable platform. In this work, FBG
sensor Stability Analyzing Device (FBGSAD) is developed for
measurement of plantar strain to assess the postural stability of
subjects on unstable platforms during different stances in eyes open
and eyes closed conditions on a rocker board. The studies are
validated by comparing the Centre of Gravity (CG) variations
measured on the lumbar vertebra of subjects using a commercial
accelerometer. The results obtained from the developed FBGSAD
depict qualitative similarities with the data recorded by commercial
accelerometer. The advantage of the FBGSAD is that it measures
simultaneously plantar strain distribution and postural stability of the
subject along with its inherent benefits like non-requirement of
energizing voltage to the sensor, electromagnetic immunity and
simple design which suits its applicability in biomechanical
applications. The developed FBGSAD can serve as a tool/yardstick to
mitigate space motion sickness, identify individuals who are
susceptible to falls and to qualify subjects for balance and stability,
which are important factors in the selection of certain unique
professionals such as aircraft pilots, astronauts, cosmonauts etc.
Abstract: We have developed a new computer program in
Fortran 90, in order to obtain numerical solutions of a system
of Relativistic Magnetohydrodynamics partial differential equations
with predetermined gravitation (GRMHD), capable of simulating
the formation of relativistic jets from the accretion disk of matter
up to his ejection. Initially we carried out a study on numerical
methods of unidimensional Finite Volume, namely Lax-Friedrichs,
Lax-Wendroff, Nessyahu-Tadmor method and Godunov methods
dependent on Riemann problems, applied to equations Euler in
order to verify their main features and make comparisons among
those methods. It was then implemented the method of Finite
Volume Centered of Nessyahu-Tadmor, a numerical schemes that
has a formulation free and without dimensional separation of
Riemann problem solvers, even in two or more spatial dimensions,
at this point, already applied in equations GRMHD. Finally, the
Nessyahu-Tadmor method was possible to obtain stable numerical
solutions - without spurious oscillations or excessive dissipation -
from the magnetized accretion disk process in rotation with respect
to a central black hole (BH) Schwarzschild and immersed in a
magnetosphere, for the ejection of matter in the form of jet over a
distance of fourteen times the radius of the BH, a record in terms
of astrophysical simulation of this kind. Also in our simulations,
we managed to get substructures jets. A great advantage obtained
was that, with the our code, we got simulate GRMHD equations in
a simple personal computer.