Abstract: Geographical routing protocol requires node physical
location information to make forwarding decision. Geographical
routing uses location service or position service to obtain the position
of a node. The geographical information is a geographic coordinates
or can be obtained through reference points on some fixed coordinate
system. Link can be formed between two nodes. Link lifetime plays a
crucial role in MANET. Link lifetime represent how long the link is
stable without any failure between the nodes. Link failure may occur
due to mobility and because of link failure energy of nodes can be
drained. Thus this paper proposes survey about link lifetime
prediction using geographical information.
Abstract: Tannase (tannin acyl hydrolase, E.C.3.1.1.20) is an
important hydrolysable enzyme with innumerable applications and
industrial potential. In the present study, a kinetic model has been
developed for the batch fermentation used for the production of
tannase by A.flavus MTCC 3783. Maximum tannase activity of
143.30 U/ml was obtained at 96 hours under optimum operating
conditions at 35oC, an initial pH of 5.5 and with an inducer tannic
acid concentration of 3% (w/v) for a fermentation period of 120
hours. The biomass concentration reaches a maximum of 6.62 g/l at
96 hours and further there was no increase in biomass concentration
till the end of the fermentation. Various unstructured kinetic models
were analyzed to simulate the experimental values of microbial
growth, tannase activity and substrate concentration. The Logistic
model for microbial growth , Luedeking - Piret model for production
of tannase and Substrate utilization kinetic model for utilization of
substrate were capable of predicting the fermentation profile with
high coefficient of determination (R2) values of 0.980, 0.942 and
0.983 respectively. The results indicated that the unstructured models
were able to describe the fermentation kinetics more effectively.
Abstract: Drying is a phenomenon that accompanies the
hardening of hydraulic materials. This study is concerned the
modelling of drying shrinkage of the hydraulic materials and the
prediction of the rate of spontaneous deformations of hydraulic
materials during hardening. The model developed takes consideration
of the main factors affecting drying shrinkage. There was agreement
between drying shrinkage predicted by the developed model and
experimental results. In last we show that developed model describe
the evolution of the drying shrinkage of high performances concretes
correctly.
Abstract: This paper presents the design process of a high
performance 3-phase 3.7 kW 2-pole line start permanent magnet
synchronous motor for pumping system. A method was proposed to
study the starting torque characteristics considering line start with
high inertia load. A d-q model including cage was built to study the
synchronization capability. Time-stepping finite element method
analysis was utilized to accurately predict the dynamic and transient
performance, efficiency, starting current, speed curve and etc.
Considering the load torque of pumps during starting stage, the rotor
bar was designed with minimum demagnetization of permanent
magnet caused by huge starting current.
Abstract: Particle size distribution, the most important
characteristics of aerosols, is obtained through electrical
characterization techniques. The dynamics of charged nanoparticles
under the influence of electric field in Electrical Mobility
Spectrometer (EMS) reveals the size distribution of these particles.
The accuracy of this measurement is influenced by flow conditions,
geometry, electric field and particle charging process, therefore by
the transfer function (transfer matrix) of the instrument. In this work,
a wire-cylinder corona charger was designed and the combined fielddiffusion
charging process of injected poly-disperse aerosol particles
was numerically simulated as a prerequisite for the study of a
multichannel EMS. The result, a cloud of particles with no uniform
charge distribution, was introduced to the EMS. The flow pattern and
electric field in the EMS were simulated using Computational Fluid
Dynamics (CFD) to obtain particle trajectories in the device and
therefore to calculate the reported signal by each electrometer.
According to the output signals (resulted from bombardment of
particles and transferring their charges as currents), we proposed a
modification to the size of detecting rings (which are connected to
electrometers) in order to evaluate particle size distributions more
accurately. Based on the capability of the system to transfer
information contents about size distribution of the injected particles,
we proposed a benchmark for the assessment of optimality of the
design. This method applies the concept of Von Neumann entropy
and borrows the definition of entropy from information theory
(Shannon entropy) to measure optimality. Entropy, according to the
Shannon entropy, is the ''average amount of information contained in
an event, sample or character extracted from a data stream''.
Evaluating the responses (signals) which were obtained via various
configurations of detecting rings, the best configuration which gave
the best predictions about the size distributions of injected particles,
was the modified configuration. It was also the one that had the
maximum amount of entropy. A reasonable consistency was also
observed between the accuracy of the predictions and the entropy
content of each configuration. In this method, entropy is extracted
from the transfer matrix of the instrument for each configuration.
Ultimately, various clouds of particles were introduced to the
simulations and predicted size distributions were compared to the
exact size distributions.
Abstract: Spacer grid assembly supporting the nuclear fuel rods
is an important concern in the design of structural components of a
Pressurized Water Reactor (PWR). The spacer grid is composed by
springs and dimples which are formed from a strip sheet by means of
blanking and stamping processes. In this paper, the blanking process
and tooling parameters are evaluated by means of a 2D plane-strain
finite element model in order to evaluate the punch load and quality
of the sheared edges of Inconel 718 strips used for nuclear spacer
grids. A 3D finite element model is also proposed to predict the
tooling loads resulting from the stamping process of a preformed
Inconel 718 strip and to analyse the residual stress effects upon the
spring and dimple design geometries of a nuclear spacer grid.
Abstract: The design of Reverse logistics Network has attracted
growing attention with the stringent pressures from both
environmental awareness and business sustainability. Reverse
logistical activities include return, remanufacture, disassemble and
dispose of products can be quite complex to manage. In addition,
demand can be difficult to predict, and decision making is one of the
challenges task in such network. This complexity has amplified the
need to develop an integrated architecture for product return as an
enterprise system. The main purpose of this paper is to design Multi
Agent System (MAS) architecture using the Prometheus
methodology to efficiently manage reverse logistics processes. The
proposed MAS architecture includes five types of agents: Gate
keeping Agent, Collection Agent, Sorting Agent, Processing Agent
and Disposal Agent which act respectively during the five steps of
reverse logistics Network.
Abstract: Voting algorithms are extensively used to make
decisions in fault tolerant systems where each redundant module
gives inconsistent outputs. Popular voting algorithms include
majority voting, weighted voting, and inexact majority voters. Each
of these techniques suffers from scenarios where agreements do not
exist for the given voter inputs. This has been successfully overcome
in literature using fuzzy theory. Our previous work concentrated on a
neuro-fuzzy algorithm where training using the neuro system
substantially improved the prediction result of the voting system.
Weight training of Neural Network is sub-optimal. This study
proposes to optimize the weights of the Neural Network using
Artificial Bee Colony algorithm. Experimental results show the
proposed system improves the decision making of the voting
algorithms.
Abstract: Based on application requirements, nodes are static or
mobile in Wireless Sensor Networks (WSNs). Mobility poses
challenges in protocol design, especially at the link layer requiring
mobility adaptation algorithms to localize mobile nodes and predict
link quality to be established with them. This study implements
XMAC and Berkeley Media Access Control (BMAC) routing
protocols to evaluate performance under WSN’s static and mobility
conditions. This paper gives a comparative study of mobility-aware
MAC protocols. Routing protocol performance, based on Average
End to End Delay, Average Packet Delivery Ratio, Average Number
of hops, and Jitter is evaluated.
Abstract: Experiential marketing is one of the marketing
approaches that offer an exceptional framework to integrate elements
of experience and entertainment in a product or service. Experiential
marketing is defined as a memorable experience that goes deeply into
the customer’s mind. Besides that, customer satisfaction is defined as
an emotional response to the experiences provided by and associated
with particular products or services purchased. Thus, experiential
marketing activities can affect the level of customer satisfaction and
loyalty. In this context, the research aims to explore the relationship
among experiential marketing, customer satisfaction and customer
loyalty among the cosmetic products customers in Konya. The partial
least squares (PLS) method is used to analyze the survey data.
Findings of the present study revealed that experiential marketing has
been a significant predictor of customer satisfaction and customer
loyalty, and also experiential marketing has a significantly positive
effect on customer satisfaction and customer loyalty.
Abstract: In recent years, fire accidents have been steadily
increased and the amount of property damage caused by the accidents
has gradually raised. Damaging building structure, fire incidents bring
about not only such property damage but also strength degradation and
member deformation. As a result, the building structure undermines its
structural ability. Examining the degradation and the deformation is
very important because reusing the building is more economical than
reconstruction. Therefore, engineers need to investigate the strength
degradation and member deformation well, and make sure that they
apply right rehabilitation methods. This study aims at evaluating
deformation characteristics of fire damaged and rehabilitated normal
strength concrete beams through both experiments and finite element
analyses. For the experiments, control beams, fire damaged beams and
rehabilitated beams are tested to examine deformation characteristics.
Ten test beam specimens with compressive strength of 21MPa are
fabricated and main test variables are selected as cover thickness of
40mm and 50mm and fire exposure time of 1 hour or 2 hours. After
heating, fire damaged beams are air-recurred for 2 months and
rehabilitated beams are repaired with polymeric cement mortar after
being removed the fire damaged concrete cover. All beam specimens
are tested under four points loading. FE analyses are executed to
investigate the effects of main parameters applied to experimental
study. Test results show that both maximum load and stiffness of the
rehabilitated beams are higher than those of the fire damaged beams.
In addition, predicted structural behaviors from the analyses also show
good rehabilitation effect and the predicted load-deflection curves are
similar to the experimental results. For the further, the proposed
analytical method can be used to predict deformation characteristics of
fire damaged and rehabilitated concrete beams without suffering from
time and cost consuming of experimental process.
Abstract: Human beings have the ability to make logical
decisions. Although human decision - making is often optimal, it is
insufficient when huge amount of data is to be classified. Medical
dataset is a vital ingredient used in predicting patient’s health
condition. In other to have the best prediction, there calls for most
suitable machine learning algorithms. This work compared the
performance of Artificial Neural Network (ANN) and Decision Tree
Algorithms (DTA) as regards to some performance metrics using
diabetes data. WEKA software was used for the implementation of
the algorithms. Multilayer Perceptron (MLP) and Radial Basis
Function (RBF) were the two algorithms used for ANN, while
RegTree and LADTree algorithms were the DTA models used. From
the results obtained, DTA performed better than ANN. The Root
Mean Squared Error (RMSE) of MLP is 0.3913 that of RBF is
0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206
respectively.
Abstract: DNA Barcode provides good sources of needed
information to classify living species. The classification problem has
to be supported with reliable methods and algorithms. To analyze
species regions or entire genomes, it becomes necessary to use the
similarity sequence methods. A large set of sequences can be
simultaneously compared using Multiple Sequence Alignment which
is known to be NP-complete. However, all the used methods are still
computationally very expensive and require significant computational
infrastructure. Our goal is to build predictive models that are highly
accurate and interpretable. In fact, our method permits to avoid the
complex problem of form and structure in different classes of
organisms. The empirical data and their classification performances
are compared with other methods. Evenly, in this study, we present
our system which is consisted of three phases. The first one, is called
transformation, is composed of three sub steps; Electron-Ion
Interaction Pseudopotential (EIIP) for the codification of DNA
Barcodes, Fourier Transform and Power Spectrum Signal Processing.
Moreover, the second phase step is an approximation; it is
empowered by the use of Multi Library Wavelet Neural Networks
(MLWNN). Finally, the third one, is called the classification of DNA
Barcodes, is realized by applying the algorithm of hierarchical
classification.
Abstract: This study utilizes a frequency domain approach over
the period of 1996 to 2013 to examine the causal relationship between
governance and economic growth in ten Asian countries, which have
different levels of democracy; classified as “Free”, “Partly Free”, and
“Not Free” countries. The empirical results show that there is no
Granger causality running from governance to economic growth in
“Not Free” countries and “Partly Free” countries with the exception of
Singapore. As for “Free” countries such as South Korea and Taiwan,
there is a one-way causality running from governance to economic
growth. The findings of this study indicate that policy makers in South
Korea, Taiwan, and Singapore could use governance index to improve
their predictions of the future economic growth.
Abstract: Numerical investigations were conducted to study the
influence of flexural reinforcement ratio on the diagonal cracking
strength and ultimate shear strength of reinforced concrete (RC)
beams without stirrups. Three-dimensional nonlinear finite element
analyses (FEAs) of the beams with flexural reinforcement ratios
ranging from 0.58% to 2.20% subjected to a mid-span concentrated
load were carried out. It is observed that the load-deflection and loadstrain
curves obtained from the numerical analyses agree with those
obtained from the experiments. It is concluded that flexural
reinforcement ratio has a significant effect on the shear strength and
deflection capacity of RC beams without stirrups. The predictions of
diagonal cracking strength and ultimate shear strength of beams
obtained by using the equations defined by a number of codes and
researchers are compared with each other and with the experimental
values.
Abstract: Accurate forecasting of fresh produce demand is one
the challenges faced by Small Medium Enterprise (SME)
wholesalers. This paper is an attempt to understand the cause for the
high level of variability such as weather, holidays etc., in demand of
SME wholesalers. Therefore, understanding the significance of
unidentified factors may improve the forecasting accuracy. This
paper presents the current literature on the factors used to predict
demand and the existing forecasting techniques of short shelf life
products. It then investigates a variety of internal and external
possible factors, some of which is not used by other researchers in the
demand prediction process. The results presented in this paper are
further analysed using a number of techniques to minimize noise in
the data. For the analysis past sales data (January 2009 to May 2014)
from a UK based SME wholesaler is used and the results presented
are limited to product ‘Milk’ focused on café’s in derby. The
correlation analysis is done to check the dependencies of variability
factor on the actual demand. Further PCA analysis is done to
understand the significance of factors identified using correlation.
The PCA results suggest that the cloud cover, weather summary and
temperature are the most significant factors that can be used in
forecasting the demand. The correlation of the above three factors
increased relative to monthly and becomes more stable compared to
the weekly and daily demand.
Abstract: It is necessary to predict a fatigue crack propagation
life for estimation of structural integrity. Because of an uncertainty
and a randomness of a structural behavior, it is also required to
analyze stochastic characteristics of the fatigue crack propagation life
at a specified fatigue crack size. The essential purpose of this study is to find the effect of load ratio
on probability distribution of the fatigue crack propagation life at a
specified grown crack size and to confirm the good probability
distribution in magnesium alloys under various fatigue load ratio
conditions. To investigate a stochastic crack growth behavior, fatigue
crack propagation experiments are performed in laboratory air under
several conditions of fatigue load ratio using AZ31. By Anderson-Darling test, a goodness-of-fit test for probability
distribution of the fatigue crack propagation life is performed. The
effect of load ratio on variability of fatigue crack propagation life is
also investigated.
Abstract: In Electric Power Steering (EPS), spoke type
Brushless AC (BLAC) motors offer distinct advantages over other
electric motor types in terms torque smoothness, reliability and
efficiency. This paper deals with the shape optimization of spoke
type BLAC motor, in order to reduce cogging torque. This paper
examines 3 steps skewing rotor angle, optimizing rotor core edge and
rotor overlap length for reducing cogging torque in spoke type BLAC
motor. The methods were applied to existing machine designs and
their performance was calculated using finite- element analysis
(FEA). Prototypes of the machine designs were constructed and
experimental results obtained. It is shown that the FEA predicted the
cogging torque to be nearly reduce using those methods.
Abstract: This study investigates the effects of the lead angle
and chip thickness variation on surface roughness during the
machining of compacted graphite iron using ceramic cutting tools
under dry cutting conditions. Analytical models were developed for
predicting the surface roughness values of the specimens after the
face milling process. Experimental data was collected and imported
to the artificial neural network model. A multilayer perceptron model
was used with the back propagation algorithm employing the input
parameters of lead angle, cutting speed and feed rate in connection
with chip thickness. Furthermore, analysis of variance was employed
to determine the effects of the cutting parameters on surface
roughness. Artificial neural network and regression analysis were
used to predict surface roughness. The values thus predicted were
compared with the collected experimental data, and the
corresponding percentage error was computed. Analysis results
revealed that the lead angle is the dominant factor affecting surface
roughness. Experimental results indicated an improvement in the
surface roughness value with decreasing lead angle value from 88° to
45°.
Abstract: Based on Business and Consumer Survey (BCS) data,
the European Commission (EC) regularly publishes the monthly
Economic Sentiment Indicator (ESI) for each EU member state. ESI
is conceptualized as a leading indicator, aimed ad tracking the overall
economic activity. In calculating ESI, the EC employs arbitrarily
chosen weights on 15 BCS response balances. This paper raises the
predictive quality of ESI by applying nonlinear programming to find
such weights that maximize the correlation coefficient of ESI and
year-on-year GDP growth. The obtained results show that the highest
weights are assigned to the response balances of industrial sector
questions, followed by questions from the retail trade sector. This
comes as no surprise since the existing literature shows that the
industrial production is a plausible proxy for the overall Croatian
economic activity and since Croatian GDP is largely influenced by
the aggregate personal consumption.