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: 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: Examining existing experimental results for shallow
rigid foundations subjected to vertical centric load (N), accompanied
or not with a bending moment (M), two main non-linear mechanisms
governing the cyclic response of the soil-foundation system can be
distinguished: foundation uplift and soil yielding. A soil-foundation
failure limit, is defined as a domain of resistance in the two
dimensional (2D) load space (N, M) inside of which lie all the
admissible combinations of loads; these latter correspond to a pure
elastic, non-linear elastic or plastic behavior of the soil-foundation
system, while the points lying on the failure limit correspond to a
combination of loads leading to a failure of the soil-foundation
system. In this study, the proposed resistance domain is constructed
analytically based on mechanics. Original elastic limit, uplift
initiation limit and iso-uplift limits are constructed inside this
domain. These limits give a prediction of the mechanisms activated
for each combination of loads applied to the foundation. A
comparison of the proposed failure limit with experimental tests
existing in the literature shows interesting results. Also, the
developed uplift initiation limit and iso-uplift curves are confronted
with others already proposed in the literature and widely used due to
the absence of other alternatives, and remarkable differences are
noted, showing evident errors in the past proposals and relevant
accuracy for those given in the present work.
Abstract: In-memory database systems are becoming popular
due to the availability and affordability of sufficiently large RAM and
processors in modern high-end servers with the capacity to manage
large in-memory database transactions. While fast and reliable inmemory
systems are still being developed to overcome cache misses,
CPU/IO bottlenecks and distributed transaction costs, disk-based data
stores still serve as the primary persistence. In addition, with the
recent growth in multi-tenancy cloud applications and associated
security concerns, many organisations consider the trade-offs and
continue to require fast and reliable transaction processing of diskbased
database systems as an available choice. For these
organizations, the only way of increasing throughput is by improving
the performance of disk-based concurrency control. This warrants a
hybrid database system with the ability to selectively apply an
enhanced disk-based data management within the context of inmemory
systems that would help improve overall throughput.
The general view is that in-memory systems substantially
outperform disk-based systems. We question this assumption and
examine how a modified variation of access invariance that we call
enhanced memory access, (EMA) can be used to allow very high
levels of concurrency in the pre-fetching of data in disk-based
systems. We demonstrate how this prefetching in disk-based systems
can yield close to in-memory performance, which paves the way for
improved hybrid database systems. This paper proposes a novel EMA
technique and presents a comparative study between disk-based EMA
systems and in-memory systems running on hardware configurations
of equivalent power in terms of the number of processors and their
speeds. The results of the experiments conducted clearly substantiate
that when used in conjunction with all concurrency control
mechanisms, EMA can increase the throughput of disk-based systems
to levels quite close to those achieved by in-memory system. The
promising results of this work show that enhanced disk-based
systems facilitate in improving hybrid data management within the
broader context of in-memory systems.
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: An efficient and green method for oxidation of thiols
to the corresponding disulfides is reported using ionic liquid
[HSO3N(C2H4OSO3H)3] in the presence of free nano-Fe2O3 at 60°C.
Ionic liquid is selective oxidant for S-S Coupling variety aliphatic
and aromatic of thiols to corresponding disulfide in the presence of
free nano-Fe2O3 as recoverable catalyst. Reaction has been performed
in methanol as an inexpensive solvent. This reaction is clean and easy
work-up with no side reaction.
Abstract: The purpose of this study is to examine the possible
link between employee and customer satisfaction. The service
provided by employees, help to build a good relationship with
customers and can help at increasing their loyalty. Published data for
job satisfaction and indicators of customer services of banks were
gathered from relevant published works which included data from
five different countries. The scores of customers and employees
satisfaction of the different published works were transformed and
normalized to the scale of 1 to 100. The data were analyzed and a
regression analysis of the two parameters was used to describe the
link between employee’s satisfaction and customer’s satisfaction.
Assuming that employee satisfaction has a significant influence on
customer’s service and the resulting customer satisfaction, the
reviewed data indicate that employee’s satisfaction contributes
significantly on the level of customer satisfaction in the Banking
sector. There was a significant correlation between the two
parameters (Pearson correlation R2=0.52 P
Abstract: Wet scrubbers have found widespread use in cleaning
contaminated gas streams because of their ability to remove
particulates and based on the applications of scrubbing of marine
engine exhaust gases by spraying sea-water. In order to examine the
flow characteristics inside the scrubber, the model is designated with
flow properties of hot air and water sprayer. The flow dynamics of
evaporation of hot air by the injection of water droplets is the key
factor considered in this paper. The flow behavior inside the scrubber
was investigated from the previous works and to sum up the
evaporation rate with respect to the concentration of water droplets are
predicted to bring out the competent modelling. The numerical
analysis using CFD facilitates in understanding the problem better and
empathies the behavior of the model over its entire operating envelope.
Abstract: Web-based Cognitive Writing Instruction (WeCWI)’s
contribution towards language development can be divided into
linguistic and non-linguistic perspectives. In linguistic perspective,
WeCWI focuses on the literacy and language discoveries, while the
cognitive and psychological discoveries are the hubs in non-linguistic
perspective. In linguistic perspective, WeCWI draws attention to free
reading and enterprises, which are supported by the language
acquisition theories. Besides, the adoption of process genre approach
as a hybrid guided writing approach fosters literacy development.
Literacy and language developments are interconnected in the
communication process; hence, WeCWI encourages meaningful
discussion based on the interactionist theory that involves input,
negotiation, output, and interactional feedback. Rooted in the elearning
interaction-based model, WeCWI promotes online
discussion via synchronous and asynchronous communications,
which allows interactions happened among the learners, instructor,
and digital content. In non-linguistic perspective, WeCWI highlights
on the contribution of reading, discussion, and writing towards
cognitive development. Based on the inquiry models, learners’
critical thinking is fostered during information exploration process
through interaction and questioning. Lastly, to lower writing anxiety,
WeCWI develops the instructional tool with supportive features to
facilitate the writing process. To bring a positive user experience to
the learner, WeCWI aims to create the instructional tool with
different interface designs based on two different types of perceptual
learning style.
Abstract: There is decagram of strategic decisions of operations
and production/service management (POSM) within operational
research (OR) which must collate, namely: design, inventory, quality,
location, process and capacity, layout, scheduling, maintain ace, and
supply chain. This paper presents an architectural configuration
conceptual framework of a decagram of sets decisions in a form of
mathematical complete graph and abelian graph.
Mathematically, a complete graph is undirected (UDG), and
directed (DG) a relationship where every pair of vertices is
connected, collated, confluent, and holomorphic.
There has not been any study conducted which, however,
prioritizes the holomorphic sets which of POMS within OR field of
study. The study utilizes OR structured technique known as The
Analytic Hierarchy Process (AHP) analysis for organizing, sorting
and prioritizing(ranking) the sets within the decagram of POMS
according to their attribution (propensity), and provides an analysis
how the prioritization has real-world application within the 21st
century.
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: Nowadays, the successful implementation of ICTs is
vital for almost any kind of organization. Good governance and ICT
management are essential for delivering value, managing
technological risks, managing resources and performance
measurement. In addition, outsourcing is a strategic IT service
solution which complements IT services provided internally in
organizations. This paper proposes the measurement tools of a new
holistic maturity model based on standards ISO/IEC 20000 and
ISO/IEC 38500, and the frameworks and best practices of ITIL and
COBIT, with a specific focus on IT outsourcing. These measurement
tools allow independent validation and practical application in the
field of higher education, using a questionnaire, metrics tables, and
continuous improvement plan tables as part of the measurement
process. Guidelines and standards are proposed in the model for
facilitating adaptation to universities and achieving excellence in the
outsourcing of IT services.
Abstract: Starting in 2020, an EU-wide CO2-limitation of
95 g/km is scheduled for the average of an OEMs passenger car fleet.
Taking that into consideration additional improvement measures of
the Diesel cycle are necessary in order to reduce fuel consumption
and emissions while boosting, or at the least, keeping performance
values at the same time.
The present article deals with the possibilities of an optimized
air/water charge air cooler, also called iCAC (indirect Charge Air
Cooler) for a Diesel passenger car amongst extreme-boundary
conditions. In this context, the precise objective was to show the
impact of improved intercooling with reference to the engine working
process (fuel consumption and NOx-emissions). Several extremeboundaries
- e.g. varying ambient temperatures or mountainous
routes - that will become very important in the near future regarding
RDE (Real Driving emissions) were subject of the investigation.
With the introduction of RDE in 2017 (EU6c measure), the
controversial NEDC (New European Driving Cycle) will belong to
the past and the OEMs will have to avoid harmful emissions in any
conceivable real life situation.
This is certainly going to lead to optimization-measurements at the
powertrain, which again is going to make the implementation of
iCACs, presently solely used for the premium class, more and more
attractive for compact class cars. The investigations showed a benefit
in FC between 1 and 3% for the iCAC in real world conditions.
Abstract: Currently, thorium fuel has been especially noticed
because of its proliferation resistance than long half-life alpha emitter
minor actinides, breeding capability in fast and thermal neutron flux
and mono-isotopic naturally abundant. In recent years, efficiency of
minor actinide burning up in PWRs has been investigated. Hence, a
minor actinide-contained thorium based fuel matrix can confront both
proliferation resistance and nuclear waste depletion aims. In the
present work, minor actinide depletion rate in a CANDU-type nuclear
core modeled using MCNP code has been investigated. The obtained
effects of minor actinide load as mixture of thorium fuel matrix on
the core neutronics has been studied with comparing presence and
non-presence of minor actinide component in the fuel matrix.
Depletion rate of minor actinides in the MA-contained fuel has been
calculated using different power loads. According to the obtained
computational data, minor actinide loading in the modeled core
results in more negative reactivity coefficients. The MA-contained
fuel achieves less radial peaking factor in the modeled core. The
obtained computational results showed 140 kg of 464 kg initial load
of minor actinide has been depleted in during a 6-year burn up in 10
MW power.
Abstract: Factors affecting construction unit cost vary
depending on a country’s political, economic, social and
technological inclinations. Factors affecting construction costs have
been studied from various perspectives. Analysis of cost factors
requires an appreciation of a country’s practices. Identified cost
factors provide an indication of a country’s construction economic
strata. The purpose of this paper is to identify the essential factors
that affect unit cost estimation and their breakdown using artificial
neural networks. Twenty five (25) identified cost factors in road
construction were subjected to a questionnaire survey and employing
SPSS factor analysis the factors were reduced to eight. The 8 factors
were analysed using neural network (NN) to determine the
proportionate breakdown of the cost factors in a given construction
unit rate. NN predicted that political environment accounted 44% of
the unit rate followed by contractor capacity at 22% and financial
delays, project feasibility and overhead & profit each at 11%. Project
location, material availability and corruption perception index had
minimal impact on the unit cost from the training data provided.
Quantified cost factors can be incorporated in unit cost estimation
models (UCEM) to produce more accurate estimates. This can create
improvements in the cost estimation of infrastructure projects and
establish a benchmark standard to assist the process of alignment of
work practises and training of new staff, permitting the on-going
development of best practises in cost estimation to become more
effective.
Abstract: Artificial Neural Network (ANN) can be trained using
back propagation (BP). It is the most widely used algorithm for
supervised learning with multi-layered feed-forward networks.
Efficient learning by the BP algorithm is required for many practical
applications. The BP algorithm calculates the weight changes of
artificial neural networks, and a common approach is to use a twoterm
algorithm consisting of a learning rate (LR) and a momentum
factor (MF). The major drawbacks of the two-term BP learning
algorithm are the problems of local minima and slow convergence
speeds, which limit the scope for real-time applications. Recently the
addition of an extra term, called a proportional factor (PF), to the
two-term BP algorithm was proposed. The third increases the speed
of the BP algorithm. However, the PF term also reduces the
convergence of the BP algorithm, and criteria for evaluating
convergence are required to facilitate the application of the three
terms BP algorithm. Although these two seem to be closely related,
as described later, we summarize various improvements to overcome
the drawbacks. Here we compare the different methods of
convergence of the new three-term BP algorithm.
Abstract: Developing young people’s employability is a key
policy issue for ensuring their successful transition to the labour
market and their access to career oriented employment. The youths of
today irrespective of their gender need to acquire the knowledge,
skills and attitudes that will enable them to create or find jobs as well
as cope with unpredictable labour market changes throughout their
working lives. In a study carried out to determine the influence of
gender on job-competencies requirements of chemical-based
industries and undergraduate-competencies acquisition by chemists
working in the industries, all chemistry graduates working in twenty
(20) chemical-based industries that were randomly selected from six
sectors of chemical-based industries in Lagos and Ogun States of
Nigeria were administered with Job-competencies required and
undergraduate-competencies acquired assessment questionnaire. The
data were analysed using means and independent sample t-test. The
findings revealed that the population of female chemists working in
chemical-based industries is low compared with the number of male
chemists; furthermore, job-competencies requirements are found not
to be gender biased while there is no significant difference in
undergraduate-competencies acquisition of male and female
chemists. This suggests that females should be given the same
opportunity of employment in chemical-based industries as their male
counterparts. The study also revealed the level of acquisition of
undergraduate competencies as related to the needs of chemicalbased
industries.