Abstract: The synthesis of CuFe2O4 spinel powders by an
optimized combustion-like process followed by calcination is
described herein. The samples were characterized using X-ray
diffraction (XRD), differential thermal analysis (TG/DTA), scanning
electron microscopy (SEM), dilatometry and 4-probe DC methods.
Different glycine to nitrate (G/N) ratios of 1 (fuel-deficient), 1.48
(stoichiometric) and 2 (fuel-rich) were employed. Calcining the asprepared
powders at 800 and 1000°C for 5 hours showed that the G/N
ratio of 2 results in the formation of the desired copper spinel single
phase at both calcination temperatures. For G/N=1, formation of
CuFe2O4 takes place in three steps. First, iron and copper nitrates
decompose to iron oxide and pure copper. Then, copper transforms to
copper oxide and finally, copper and iron oxides react with each other
to form a copper ferrite spinel phase. The electrical conductivity and
the coefficient of thermal expansion of the sintered pelletized
samples were 2 S.cm-1 (800°C) and 11×10-6 °C-1 (25-800°C),
respectively.
Abstract: This study compares the intensity of game load among
player positions and between the 1st and the 2nd half of the games.
Two guards, three forwards, and three centers (female basketball
players) participated in this study. The heart rate (HR) and its
development were monitored during two competitive games.
Statistically insignificant differences in the intensity of game load
were recorded between guards, forwards, and centers below and
above 85% of the maximal heart rate (HRmax) and in the mean HR as
% of HRmax (87.81±3.79%, 87.02±4.37%, and 88.76±3.54%,
respectively). Moreover, when the 1st and the 2nd half of the games
were compared in the mean HR (87.89±4.18% vs. 88.14±3.63% of
HRmax), no statistical significance was recorded. This information can
be useful for coaching staff, to manage and to precisely plan the
training process.
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: 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: In present global scenario, aluminum alloys are
coining the attention of many innovators as competing structural
materials for automotive and space applications. Comparing to other
challenging alloys, especially, 7xxx series aluminum alloys have
been studied seriously because of benefits such as moderate strength;
better deforming characteristics and affordable cost. It is expected
that substitution of aluminum alloys for steels will result in great
improvements in energy economy, durability and recyclability.
However, it is necessary to improve the strength and the formability
levels at low temperatures in aluminum alloys for still better
applications. Aluminum–Zinc–Magnesium with or without other
wetting agent denoted as 7XXX series alloys are medium strength
heat treatable alloys. In addition to Zn, Mg as major alloying
additions, Cu, Mn and Si are the other solute elements which
contribute for the improvement in mechanical properties by suitable
heat treatment process. Subjecting to suitable treatments like age
hardening or cold deformation assisted heat treatments; known as low
temperature thermomechanical treatments (LTMT) the challenging
properties might be incorporated. T6 is the age hardening or
precipitation hardening process with artificial aging cycle whereas T8
comprises of LTMT treatment aged artificially with X% cold
deformation. When the cold deformation is provided after solution
treatment, there is increase in hardness related properties such as
wear resistance, yield and ultimate strength, toughness with the
expense of ductility. During precipitation hardening both hardness
and strength of the samples are increasing. The hardness value may
further improve when room temperature deformation is positively
supported with age hardening known as thermomechanical treatment.
It is intended to perform heat treatment and evaluate hardness, tensile
strength, wear resistance and distribution pattern of reinforcement in
the matrix. 2 to 2.5 and 3 to 3.5 times increase in hardness is reported
in age hardening and LTMT treatments respectively as compared to
as-cast composite. There was better distribution of reinforcements in
the matrix, nearly two fold increase in strength levels and up to 5
times increase in wear resistance are also observed in the present
study.
Abstract: In this paper a novel color image compression
technique for efficient storage and delivery of data is proposed. The
proposed compression technique started by RGB to YCbCr color
transformation process. Secondly, the canny edge detection method is
used to classify the blocks into the edge and non-edge blocks. Each
color component Y, Cb, and Cr compressed by discrete cosine
transform (DCT) process, quantizing and coding step by step using
adaptive arithmetic coding. Our technique is concerned with the
compression ratio, bits per pixel and peak signal to noise ratio, and
produce better results than JPEG and more recent published schemes
(like CBDCT-CABS and MHC). The provided experimental results
illustrate the proposed technique that is efficient and feasible in terms
of compression ratio, bits per pixel and peak signal to noise ratio.
Abstract: Brownfields are one of the most important problems
that must be solved by today's cities. The topic of this article is
description of developing a comprehensive transformation of postindustrial
area of the former iron factory national cultural heritage
lower Vítkovice. City of Ostrava used to be industrial superpower of
the Czechoslovak Republic, especially in the area of coal mining and
iron production, after declining industrial production and mining in
the 80s left many unused areas of former factories generally
brownfields and backfields. Since the late 90s we are observing how
the city officials or private entities seeking to remedy this situation.
Regeneration of brownfields is a very expensive and long-term
process. The area is now rebuilt for tourists and residents of the city
in the entertainment, cultural, and social center. It was necessary do
the reconstruction of the industrial monuments. Equally important
was the construction of new buildings, which helped reusing of the
entire complex. This is a unique example of transformation of
technical monuments and completion of necessary new objects, so
that the area could start working again and reintegrate back into the
urban system.
Abstract: Si ion implantation was widely used to synthesize
specimens of SiO2 containing supersaturated Si and subsequent high
temperature annealing induces the formation of embedded
luminescent Si nanocrystals. In this work, the potentialities of excimer
UV-light (172 nm, 7.2 eV) irradiation and rapid thermal annealing
(RTA) to enhance the photoluminescence and to achieve low
temperature formation of Si nanocrystals have been investigated. The
Si ions were introduced at acceleration energy of 180 keV to fluence of
7.5 x 1016 ions/cm2. The implanted samples were subsequently
irradiated with an excimer-UV lamp. After the process, the samples
were rapidly thermal annealed before furnace annealing (FA).
Photoluminescence spectra were measured at various stages at the
process. We found that the luminescence intensity is strongly
enhanced with excimer-UV irradiation and RTA. Moreover, effective
visible photoluminescence is found to be observed even after FA at
900 oC, only for specimens treated with excimer-UV lamp and RTA.
We also prepared specimens of Si nanocrystals embedded in a SiO2 by
reactive pulsed laser deposition (PLD) in an oxygen atmosphere. We
will make clear the similarities and differences with the way of
preparation.
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: This paper presents Carrier Sense Multiple Access
(CSMA) communication models based on SoC design methodology.
Such a model can be used to support the modeling of the complex
wireless communication systems. Therefore, the use of such
communication model is an important technique in the construction
of high-performance communication. SystemC has been chosen
because it provides a homogeneous design flow for complex designs
(i.e. SoC and IP-based design). We use a swarm system to validate
CSMA designed model and to show how advantages of incorporating
communication early in the design process. The wireless
communication created through the modeling of CSMA protocol that
can be used to achieve communication between all the agents and to
coordinate access to the shared medium (channel).
Abstract: Continuous upflow filters can combine the nutrient
(nitrogen and phosphate) and suspended solid removal in one unit
process. The contaminant removal could be achieved chemically or
biologically; in both processes the filter removal efficiency depends
on the interaction between the packed filter media and the influent. In
this paper a residence time distribution (RTD) study was carried out
to understand and compare the transfer behaviour of contaminants
through a selected filter media packed in a laboratory-scale
continuous up flow filter; the selected filter media are limestone and
white dolomite. The experimental work was conducted by injecting a
tracer (red drain dye tracer –RDD) into the filtration system and then
measuring the tracer concentration at the outflow as a function of
time; the tracer injection was applied at hydraulic loading rates
(HLRs) (3.8 to 15.2 m h-1). The results were analysed according to
the cumulative distribution function F(t) to estimate the residence
time of the tracer molecules inside the filter media. The mean
residence time (MRT) and variance σ2 are two moments of RTD that
were calculated to compare the RTD characteristics of limestone with
white dolomite. The results showed that the exit-age distribution of
the tracer looks better at HLRs (3.8 to 7.6 m h-1) and (3.8 m h-1) for
limestone and white dolomite respectively. At these HLRs the
cumulative distribution function F(t) revealed that the residence time
of the tracer inside the limestone was longer than in the white
dolomite; whereas all the tracer took 8 minutes to leave the white
dolomite at 3.8 m h-1. On the other hand, the same amount of the
tracer took 10 minutes to leave the limestone at the same HLR. In
conclusion, the determination of the optimal level of hydraulic
loading rate, which achieved the better influent distribution over the
filtration system, helps to identify the applicability of the material as
filter media. Further work will be applied to examine the efficiency
of the limestone and white dolomite for phosphate removal by
pumping a phosphate solution into the filter at HLRs (3.8 to 7.6 m h-1).
Abstract: In this paper a new model for center of motion
creating is proposed. This new method uses cables. So, it is very
useful in robots because it is light and has easy assembling process.
In the robots which need to be in touch with some things this method
is so useful. It will be described in the following. The accuracy of the
idea is proved by two experiments. This system could be used in the
robots which need a fixed point in the contact with some things and
make a circular motion.
Abstract: In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.
Abstract: Academicians at the Arab Open University have
always voiced their concern about the efficacy of the blended
learning process. Based on 75% independent study and 25% face-toface
tutorial, it poses the challenge of the predisposition to
adjustment. Being used to the psychology of traditional educational
systems, AOU students cannot be easily weaned from being spoonfed.
Hence they lack the motivation to plunge into self-study. For
better involvement of AOU students into the learning practices, it is
imperative to diagnose the factors that impede or increase their
motivation. This is conducted through an empirical study grounded
upon observations and tested hypothesis and aimed at monitoring and
optimizing the students’ learning outcome. Recommendations of the
research will follow the findings.
Abstract: Model transformation, as a pivotal aspect of Modeldriven
engineering, attracts more and more attentions both from
researchers and practitioners. Many domains (enterprise engineering,
software engineering, knowledge engineering, etc.) use model
transformation principles and practices to serve to their domain
specific problems; furthermore, model transformation could also be
used to fulfill the gap between different domains: by sharing and
exchanging knowledge. Since model transformation has been widely
used, there comes new requirement on it: effectively and efficiently
define the transformation process and reduce manual effort that
involved in. This paper presents an automatic model transformation
methodology based on semantic and syntactic comparisons, and
focuses particularly on granularity issue that existed in transformation
process. Comparing to the traditional model transformation
methodologies, this methodology serves to a general purpose: crossdomain
methodology. Semantic and syntactic checking
measurements are combined into a refined transformation process,
which solves the granularity issue. Moreover, semantic and syntactic
comparisons are supported by software tool; manual effort is replaced
in this way.
Abstract: This paper presents an approach for the classification of
an unstructured format description for identification of file formats.
The main contribution of this work is the employment of data mining
techniques to support file format selection with just the unstructured
text description that comprises the most important format features for
a particular organisation. Subsequently, the file format indentification
method employs file format classifier and associated configurations to
support digital preservation experts with an estimation of required file
format. Our goal is to make use of a format specification knowledge
base aggregated from a different Web sources in order to select file
format for a particular institution. Using the naive Bayes method,
the decision support system recommends to an expert, the file format
for his institution. The proposed methods facilitate the selection of
file format and the quality of a digital preservation process. The
presented approach is meant to facilitate decision making for the
preservation of digital content in libraries and archives using domain
expert knowledge and specifications of file formats. To facilitate
decision-making, the aggregated information about the file formats is
presented as a file format vocabulary that comprises most common
terms that are characteristic for all researched formats. The goal is to
suggest a particular file format based on this vocabulary for analysis
by an expert. The sample file format calculation and the calculation
results including probabilities are presented in the evaluation section.
Abstract: Submerged arc welding is a very complex process. It
is a very efficient and high performance welding process. In this
present study an attempt have been done to reduce the welding
distortion by increased amount of oxide flux through TiO2 in
submerged arc welding process. Care has been taken to avoid the
excessiveness of the adding agent for attainment of significant
results. Data Envelopment Analysis (DEA) based BAT algorithm is
used for the parametric optimization purpose in which DEA is used
to convert multi response parameters into a single response
parameter. The present study also helps to know the effectiveness of
the addition of TiO2 in active flux during submerged arc welding
process.
Abstract: There is not much effective guideline on development of design parameters selection on spring back for advanced high strength steel sheet metal in U-channel process during cold forming process. This paper presents the development of predictive model for spring back in U-channel process on advanced high strength steel sheet employing Response Surface Methodology (RSM). The experimental was performed on dual phase steel sheet, DP590 in Uchannel forming process while design of experiment (DoE) approach was used to investigates the effects of four factors namely blank holder force (BHF), clearance (C) and punch travel (Tp) and rolling direction (R) were used as input parameters using two level values by applying Full Factorial design (24 ). From a statistical analysis of variant (ANOVA), result showed that blank holder force (BHF), clearance (C) and punch travel (Tp) displayed significant effect on spring back of flange angle (β2 ) and wall opening angle (β1 ), while rolling direction (R) factor is insignificant. The significant parameters are optimized in order to reduce the spring back behavior using Central Composite Design (CCD) in RSM and the optimum parameters were determined. A regression model for spring back was developed. The effect of individual parameters and their response was also evaluated. The results obtained from optimum model are in agreement with the experimental values.
Abstract: The system for analyzing and eliciting public
grievances serves its main purpose to receive and process all sorts of
complaints from the public and respond to users. Due to the more
number of complaint data becomes big data which is difficult to store
and process. The proposed system uses HDFS to store the big data
and uses MapReduce to process the big data. The concept of cache
was applied in the system to provide immediate response and timely
action using big data analytics. Cache enabled big data increases the
response time of the system. The unstructured data provided by the
users are efficiently handled through map reduce algorithm. The
processing of complaints takes place in the order of the hierarchy of
the authority. The drawbacks of the traditional database system used
in the existing system are set forth by our system by using Cache
enabled Hadoop Distributed File System. MapReduce framework
codes have the possible to leak the sensitive data through
computation process. We propose a system that add noise to the
output of the reduce phase to avoid signaling the presence of
sensitive data. If the complaints are not processed in the ample time,
then automatically it is forwarded to the higher authority. Hence it
ensures assurance in processing. A copy of the filed complaint is sent
as a digitally signed PDF document to the user mail id which serves
as a proof. The system report serves to be an essential data while
making important decisions based on legislation.
Abstract: In this paper, a new concept of closed-loop design for a
product is presented. The closed-loop design model is developed by
integrating forward design and reverse design. Based on this new
concept, a closed-loop design model for sustainable manufacturing by
integrated evaluation of forward design, reverse design, and green
manufacturing using a fuzzy analytic network process is developed. In
the design stage of a product, with a given product requirement and
objective, there can be different ways to design the detailed
components and specifications. Therefore, there can be different
design cases to achieve the same product requirement and objective.
Subsequently, in the design evaluation stage, it is required to analyze
and evaluate the different design cases. The purpose of this research is
to develop a model for evaluating the design cases by integrated
evaluating the criteria in forward design, reverse design, and green
manufacturing. A fuzzy analytic network process method is presented
for integrated evaluation of the criteria in the three models. The
comparison matrices for evaluating the criteria in the three groups are
established. The total relational values among the three groups
represent the total relational effects. In applications, a super matrix
model is created and the total relational values can be used to evaluate
the design cases for decision-making to select the final design case. An
example product is demonstrated in this presentation. It shows that the
model is useful for integrated evaluation of forward design, reverse
design, and green manufacturing to achieve a closed-loop design for
sustainable manufacturing objective.