Abstract: This research focuses on the effect of weight
percentage variation and size variation of MgFeSi added,
gating system design and reaction chamber design on inmold
process. By using inmold process, well-known problem of
fading is avoided because the liquid iron reacts with
magnesium in the mold and not, as usual, in the ladle. During
the pouring operation, liquid metal passes through the
chamber containing the magnesium, where the reaction of the
metal with magnesium proceeds in the absence of atmospheric
oxygen [1].In this paper, the results of microstructural
characteristic of ductile iron on this parameters are mentioned.
The mechanisms of the inmold process are also described [2].
The data obtained from this research will assist in producing
the vehicle parts and other machinery parts for different
industrial zones and government industries and in transferring
the technology to all industrial zones in Myanmar. Therefore,
the inmold technology offers many advantages over traditional
treatment methods both from a technical and environmental,
as well as an economical point of view. The main objective of
this research is to produce ductile iron castings in all industrial
sectors in Myanmar more easily with lower costs. It will also
assist the sharing of knowledge and experience related to the
ductile iron production.
Abstract: This paper proposes an efficient learning method for the layered neural networks based on the selection of training data and input characteristics of an output layer unit. Comparing to recent neural networks; pulse neural networks, quantum neuro computation, etc, the multilayer network is widely used due to its simple structure. When learning objects are complicated, the problems, such as unsuccessful learning or a significant time required in learning, remain unsolved. Focusing on the input data during the learning stage, we undertook an experiment to identify the data that makes large errors and interferes with the learning process. Our method devides the learning process into several stages. In general, input characteristics to an output layer unit show oscillation during learning process for complicated problems. The multi-stage learning method proposes by the authors for the function approximation problems of classifying learning data in a phased manner, focusing on their learnabilities prior to learning in the multi layered neural network, and demonstrates validity of the multi-stage learning method. Specifically, this paper verifies by computer experiments that both of learning accuracy and learning time are improved of the BP method as a learning rule of the multi-stage learning method. In learning, oscillatory phenomena of a learning curve serve an important role in learning performance. The authors also discuss the occurrence mechanisms of oscillatory phenomena in learning. Furthermore, the authors discuss the reasons that errors of some data remain large value even after learning, observing behaviors during learning.
Abstract: A 1.2 V, 0.61 mA bias current, low noise amplifier
(LNA) suitable for low-power applications in the 2.4 GHz band is
presented. Circuit has been implemented, laid out and simulated using
a UMC 130 nm RF-CMOS process. The amplifier provides a 13.3 dB
power gain a noise figure NF< 2.28 dB and a 1-dB compression point
of -15.69 dBm, while dissipating 0.74 mW. Such performance make
this design suitable for wireless sensor networks applications such as
ZigBee.
Abstract: Knowledge about the magnetic quantities in a magnetic circuit is always of great interest. On the one hand, this information is needed for the simulation of a transformer. On the other hand, parameter studies are more reliable, if the magnetic quantities are derived from a well established model. One possibility to model the 3-phase transformer is by using a magnetic equivalent circuit (MEC). Though this is a well known system, it is often not an easy task to set up such a model for a large number of lumped elements which additionally includes the nonlinear characteristic of the magnetic material. Here we show the setup of a solver for a MEC and the results of the calculation in comparison to measurements taken. The equations of the MEC are based on a rearranged system of the nodal analysis. Thus it is possible to achieve a minimum number of equations, and a clear and simple structure. Hence, it is uncomplicated in its handling and it supports the iteration process. Additional helpful tasks are implemented within the solver to enhance the performance. The electric circuit is described by an electric equivalent circuit (EEC). Our results for the 3-phase transformer demonstrate the computational efficiency of the solver, and show the benefit of the application of a MEC.
Abstract: Mostly the systems are dealing with time varying
signals. The Power efficiency can be achieved by adapting the system
activity according to the input signal variations. In this context
an adaptive rate filtering technique, based on the level crossing sampling
is devised. It adapts the sampling frequency and the filter order
by following the input signal local variations. Thus, it correlates the
processing activity with the signal variations. Interpolation is required
in the proposed technique. A drastic reduction in the interpolation
error is achieved by employing the symmetry during the interpolation
process. Processing error of the proposed technique is
calculated. The computational complexity of the proposed filtering
technique is deduced and compared to the classical one. Results
promise a significant gain of the computational efficiency and hence
of the power consumption.
Abstract: In Lebanon, public construction projects are awarded
to the contractor submitting the lowest bid price based on a
competitive bidding process. The contractor has to make a strategic
decision in choosing the appropriate bid price that will offer a
satisfactory profit with a greater probability to win. A simulation
model for bid price decision making based on the lowest bid price
evaluation is developed. The model, built using Crystal Ball decisionengineering
software, considers two main factors affecting the
bidding process: the number of qualified bidders and the size of the
project. The validity of the model is tested on twelve separate
projects. The study also shows how to use the model to conduct risk
analysis and help any specific contractor to decide on his bid price
with associated certainty level in a scientific method.
Abstract: This paper examines the use of mechanical aerator for
oxidation-ditch process. The rotor, which controls the aeration, is the
main component of the aeration process. Therefore, the objective of
this study is to find out the variations in overall oxygen transfer
coefficient (KLa) and aeration efficiency (AE) for different
configurations of aerator by varying the parameters viz. speed of
aerator, depth of immersion, blade tip angles so as to yield higher
values of KLa and AE. Six different configurations of aerator were
developed and fabricated in the laboratory and were tested for abovementioned
parameters. The curved blade rotor (CBR) emerged as a
potential aerator with blade tip angle of 47°.
The mathematical models are developed for predicting the
behaviour of CBR w.r.t kLa and power. In laboratory studies, the
optimum value of KLa and AE were observed to be 10.33 h-1 and
2.269 kg O2/ kWh.
Abstract: With the aim of improving nutritional profile and antioxidant capacity of gluten-free cookies, blueberry pomace, by-product of juice production, was processed into a new food ingredient by drying and grinding and used for a gluten-free cookie formulation. Since the quality of a baked product is highly influenced by the baking conditions, the objective of this work was to optimize the baking time and thickness of dough pieces, by applying Response Surface Methodology (RSM) in order to obtain the best technological quality of the cookies. The experiments were carried out according to a Central Composite Design (CCD) by selecting the dough thickness and baking time as independent variables, while hardness, color parameters (L*, a* and b* values), water activity, diameter and short/long ratio were response variables. According to the results of RSM analysis, the baking time of 13.74min and dough thickness of 4.08mm was found to be the optimal for the baking temperature of 170°C. As similar optimal parameters were obtained by previously conducted experiment based on sensory analysis, response surface methodology (RSM) can be considered as a suitable approach to optimize the baking process.
Abstract: The results from experimental research of deformation
by upsetting and die forging of lead specimens wit controlled impact
are presented. Laboratory setup for conducting the investigations,
which uses cold rocket engine operated with compressed air, is
described. The results show that when using controlled impact is
achieving greater plastic deformation and consumes less impact
energy than at ordinary impact deformation process.
Abstract: Speckled images arise when coherent microwave,
optical, and acoustic imaging techniques are used to image an object, surface or scene. Examples of coherent imaging systems include synthetic aperture radar, laser imaging systems, imaging sonar
systems, and medical ultrasound systems. Speckle noise is a form of object or target induced noise that results when the surface of the object is Rayleigh rough compared to the wavelength of the illuminating radiation. Detection and estimation in images corrupted
by speckle noise is complicated by the nature of the noise and is not
as straightforward as detection and estimation in additive noise. In
this work, we derive stochastic models for speckle noise, with an emphasis on speckle as it arises in medical ultrasound images. The
motivation for this work is the problem of segmentation and tissue classification using ultrasound imaging. Modeling of speckle in this
context involves partially developed speckle model where an underlying Poisson point process modulates a Gram-Charlier series
of Laguerre weighted exponential functions, resulting in a doubly
stochastic filtered Poisson point process. The statistical distribution of partially developed speckle is derived in a closed canonical form.
It is observed that as the mean number of scatterers in a resolution cell is increased, the probability density function approaches an
exponential distribution. This is consistent with fully developed speckle noise as demonstrated by the Central Limit theorem.
Abstract: Response Surface Methodology (RSM) is a powerful
and efficient mathematical approach widely applied in the
optimization of cultivation process. Cellulase enzyme production by
Trichoderma reesei RutC30 using agricultural waste rice straw and
banana fiber as carbon source were investigated. In this work,
sequential optimization strategy based statistical design was
employed to enhance the production of cellulase enzyme through
submerged cultivation. A fractional factorial design (26-2) was applied
to elucidate the process parameters that significantly affect cellulase
production. Temperature, Substrate concentration, Inducer
concentration, pH, inoculum age and agitation speed were identified
as important process parameters effecting cellulase enzyme synthesis.
The concentration of lignocelluloses and lactose (inducer) in the
cultivation medium were found to be most significant factors. The
steepest ascent method was used to locate the optimal domain and a
Central Composite Design (CCD) was used to estimate the quadratic
response surface from which the factor levels for maximum
production of cellulase were determined.
Abstract: This paper proposes method of diagnosing ball screw
preload loss through the Hilbert-Huang Transform （HHT） and
Multiscale entropy （MSE） process. The proposed method can
diagnose ball screw preload loss through vibration signals when the
machine tool is in operation. Maximum dynamic preload of 2 %, 4 %,
and 6 % ball screws were predesigned, manufactured, and tested
experimentally. Signal patterns are discussed and revealed using
Empirical Mode Decomposition（EMD）with the Hilbert Spectrum.
Different preload features are extracted and discriminated using HHT.
The irregularity development of a ball screw with preload loss is
determined and abstracted using MSE based on complexity
perception. Experiment results show that the proposed method can
predict the status of ball screw preload loss. Smart sensing for the
health of the ball screw is also possible based on a comparative
evaluation of MSE by the signal processing and pattern matching of
EMD/HHT. This diagnosis method realizes the purposes of prognostic
effectiveness on knowing the preload loss and utilizing convenience.
Abstract: Starting from the basic pillars of the supportability
analysis this paper queries its characteristics in LCI (Life Cycle
Integration) environment. The research methodology contents a
review of modern logistics engineering literature with the objective to
collect and synthesize the knowledge relating to standards of
supportability design in e-logistics environment. The results show
that LCI framework has properties which are in fully compatibility
with the requirement of simultaneous logistics support and productservice
bundle design. The proposed approach is a contribution to the
more comprehensive and efficient supportability design process.
Also, contributions are reflected through a greater consistency of
collected data, automated creation of reports suitable for different
analysis, as well as the possibility of their customization according
with customer needs. In addition to this, convenience of this approach
is its practical use in real time. In a broader sense, LCI allows
integration of enterprises on a worldwide basis facilitating electronic
business.
Abstract: Environmental decision making, particularly about
hazardous waste management, is inherently exposed to a high
potential conflict, principally because of the trade-off between sociopolitical,
environmental, health and economic factors. The need to
plan complex contexts has led to an increasing request for decision
analytic techniques as support for the decision process. In this work,
alternative systems of asbestos-containing waste management
(ACW) in Puglia (Southern Italy) were explored by a multi-criteria
decision analysis. In particular, through Analytic Hierarchy Process
five alternatives management have been compared and ranked
according to their performance and efficiency, taking into account
environmental, health and socio-economic aspects. A separated
valuation has been performed for different temporal scale. For short
period results showed a narrow deviation between the disposal
alternatives “mono-material landfill in public quarry" and “dedicate
cells in existing landfill", with the best performance of the first one.
While for long period “treatment plant to eliminate hazard from
asbestos-containing waste" was prevalent, although high energy
demand required to achieve the change of crystalline structure. A
comparison with results from a participative approach in valuation
process might be considered as future development of method
application to ACW management.
Abstract: Intelligent schools are those which use IT devices and
technologies as media software, hardware and networks to improve
learning process. On the other hand Strategic management is a field
that deals with the major intended and emergent initiatives taken by
general managers on behalf of owners, involving utilization of resources, to enhance the performance of firms in their external environments. Here, we present a model Strategic Management System that has been applied on some schools and have made strict
improvement.
Abstract: This paper proposes a neural network weights and
topology optimization using genetic evolution and the
backpropagation training algorithm. The proposed crossover and
mutation operators aims to adapt the networks architectures and
weights during the evolution process. Through a specific inheritance
procedure, the weights are transmitted from the parents to their
offsprings, which allows re-exploitation of the already trained
networks and hence the acceleration of the global convergence of the
algorithm. In the preprocessing phase, a new feature extraction
method is proposed based on Legendre moments with the Maximum
entropy principle MEP as a selection criterion. This allows a global
search space reduction in the design of the networks. The proposed
method has been applied and tested on the well known MNIST
database of handwritten digits.
Abstract: Student-s movements have been going increasing in
last decades. International students can have different psychological
and sociological problems in their adaptation process. Depression is
one of the most important problems in this procedure. This research
purposed to reveal level of foreign students- depression, kinds of
interpersonal communication networks (host/ethnic interpersonal
communication) and media usage (host/ethnic media usage).
Additionally study aimed to display the relationship between
depression and communication (host/ethnic interpersonal
communication and host/ethnic media usage) among foreign
university students. A field research was performed among 283
foreign university students who have been attending 8 different
universities in Turkey. A purposeful sampling technique was used in
this research cause of data collect facilities. Results indicated that
58.3% of foreign students- depression stage was “intermediate" while
33.2% of foreign students- depression level was “low". Add to this,
host interpersonal communication behaviors and Turkish web sites
usages were negatively and significantly correlated with depression.
Abstract: The chatter is one of the major limitations of the productivity in the ball end milling process. It affects the surface roughness, the dimensional accuracy and the tool life. The aim of this research is to propose the new system to detect the chatter during the ball end milling process by using the wavelet transform. The proposed method is implemented on the 5-axis CNC machining center and the new three parameters are introduced from three dynamic cutting forces, which are calculated by taking the ratio of the average variances of dynamic cutting forces to the absolute variances of themselves. It had been proved that the chatter can be easier to detect during the in-process cutting by using the new parameters which are proposed in this research. The experimentally obtained results showed that the wavelet transform can provide the reliable results to detect the chatter under various cutting conditions.
Abstract: There is inadequate information on the practice of
female genital mutilation (FGM) in the UK, and there are often
myths and perceptions within communities that influence the
effectiveness of prevention programmes. This means it is difficult to
address the trends and changes in the practice in the UK.
To this end, FORWARD undertook novel and innovative research
using the Participatory Ethnographic and Evaluative Research
(PEER) method to explore the views of women from Eritrea, Sudan,
Somalia and Ethiopia that live in London and Bristol (two UK cities).
Women-s views, taken from PEER interviews, reflected reasons for
continued practice of FGM: marriageability, the harnessing and
control of female sexuality, and upholding traditions from their
countries of origin. It was also clear that the main supporters of the
practice were believed to be older women within families and
communities.
Women described the impact FGM was having on their lives as
isolating. And although it was clearly considered a private and
personal matter, they developed a real sense of connection with their
peers within the research process.
The women were overwhelmingly positive about combating the
practice, although they believed it would probably take a while
before it ends completely. They also made concrete
recommendations on how to improve support services for women
affected by FGM: Training for professionals (particularly in
healthcare), increased engagement with, and outreach to,
communities, culturally appropriate materials and information made
available and accessible to communities, and more consequent
implementation of legislation.
Finally, the women asked for more empathy and understanding,
particularly from health professionals. Rather than presenting FGM
as a completely alien and inconceivable practice, it may help for
those looking into these women-s lives and working with them to
understand the social and economic context in which the practice
takes place.
Abstract: As a vital activity for companies, new product
development (NPD) is also a very risky process due to the high
uncertainty degree encountered at every development stage and the
inevitable dependence on how previous steps are successfully
accomplished. Hence, there is an apparent need to evaluate new
product initiatives systematically and make accurate decisions under
uncertainty. Another major concern is the time pressure to launch a
significant number of new products to preserve and increase the
competitive power of the company. In this work, we propose an
integrated decision-making framework based on neural networks and
fuzzy logic to make appropriate decisions and accelerate the
evaluation process. We are especially interested in the two initial
stages where new product ideas are selected (go/no go decision) and
the implementation order of the corresponding projects are
determined. We show that this two-staged intelligent approach allows
practitioners to roughly and quickly separate good and bad product
ideas by making use of previous experiences, and then, analyze a
more shortened list rigorously.