Abstract: This study is concerned with the investigation of the
suitability of several empirical and semi-empirical drying models
available in the literature to define drying behavior of viscose yarn
bobbins. For this purpose, firstly, experimental drying behaviour of
viscose bobbins was determined on an experimental dryer setup
which was designed and manufactured based on hot-air bobbin
dryers used in textile industry. Afterwards, drying models considered
were fitted to the experimentally obtained moisture ratios. Drying
parameters were drying temperature and bobbin diameter. The fit
was performed by selecting the values for constants in the models in
such a way that these values make the sum of the squared differences
between the experimental and the model results for moisture ratio
minimum. Suitability of fitting was specified as comparing the
correlation coefficient, standard error and mean square deviation.
The results show that the most appropriate model in describing the
drying curves of viscose bobbins is the Page model.
Abstract: The impact of noise upon live quality has become an
important aspect to make both urban and environmental policythroughout
Europe and in Turkey. Concern over the quality of urban
environments, including noise levels and declining quality of green
space, is over the past decade with increasing emphasis on designing
livable and sustainable communities. According to the World Health
Organization, noise pollution is the third most hazardous
environmental type of pollution which proceeded by only air (gas
emission) and water pollution. The research carried out in two
phases, the first stage of the research noise and plant types providing
the suction of noise was evaluated through literature study and at the
second stage, definite types (Juniperus horizontalis L., Spirea
vanhouetti Briot., Cotoneaster dammerii C.K., Berberis thunbergii
D.C., Pyracantha coccinea M. etc.) were selected for the city of
Konya. Trials were conducted on the highway of Konya. The biggest
value of noise reduction was 6.3 dB(A), 4.9 dB(A), 6.2 dB(A) value
with compared to the control which includes the group that formed
by the bushes at the distance of 7m, 11m, 20m from the source and
5m, 9m, 20m of plant width, respectively. In this paper, definitions
regarding to noise and its sources were made and the precautions
were taken against to noise that mentioned earlier with the adverse
effects of noise. Plantation design approaches and suggestions
concerning to the diversity to be used, which are peculiar to roadside,
were developed to discuss the role and the function of plant material
to reduce the noise of the traffic.
Abstract: In this study, the Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm are used to classify to effective diagnosis Parkinsons disease(PD).It-s a challenging problem for medical community.Typically characterized by tremor, PD occurs due to the loss of dopamine in the brains thalamic region that results in involuntary or oscillatory movement in the body. A feature selection algorithm along with biomedical test values to diagnose Parkinson disease.Clinical diagnosis is done mostly by doctor-s expertise and experience.But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests for diagnosis.In many cases,not all the tests contribute towards effective diagnosis of a disease.Our work is to classify the presence of Parkinson disease with reduced number of attributes.Original,22 attributes are involved in classify.We use Information Gain to determine the attributes which reduced the number of attributes which is need to be taken from patients.The Artificial neural networks is used to classify the diagnosis of patients.Twenty-Two attributes are reduced to sixteen attributes.The accuracy is in training data set is 82.051% and in the validation data set is 83.333%.
Abstract: Innovation is being view from four areas of
innovation, product, service, technology, and marketing. Whereas
customer loyalty is composed of customer expectation, perceived
quality, perceived value, corporate image, customer satisfaction,
customer trust/confidence, customer commitment, customer
complaint, and customer loyalty. This study aimed to investigate the
influence of innovation factors to customer loyalty to GSM in the
telecom companies where use of products and services. Structural
Equation Modeling (SEM) using to analyze innovation factors. It was
found the factor of innovation have significant influence on customer
loyalty.
Abstract: This paper considers the development of a two-point
predictor-corrector block method for solving delay differential
equations. The formulae are represented in divided difference form
and the algorithm is implemented in variable stepsize variable order
technique. The block method produces two new values at a single
integration step. Numerical results are compared with existing
methods and it is evident that the block method performs very well.
Stability regions of the block method are also investigated.
Abstract: This study examined the effects of eight weeks of
whole-body vibration training (WBVT) on vertical and decuple jump
performance in handball athletes. Sixteen collegiate Level I handball
athletes volunteered for this study. They were divided equally as
control group and experimental group (EG). During the period of the
study, all athletes underwent the same handball specific training, but
the EG received additional WBVT (amplitude: 2 mm, frequency: 20 -
40 Hz) three time per week for eight consecutive weeks. The vertical
jump performance was evaluated according to the maximum height of
squat jump (SJ) and countermovement jump (CMJ). Single factor
ANCOVA was used to examine the differences in each parameter
between the groups after training with the pretest values as a covariate.
The statistic significance was set at p < .05. After 8 weeks WBVT, the
EG had significantly improved the maximal height of SJ (40.92 ± 2.96
cm vs. 48.40 ± 4.70 cm, F = 5.14, p < .05) and the maximal height
CMJ (47.25 ± 7.48 cm vs. 52.20 ± 6.25 cm, F = 5.31, p < .05). 8 weeks
of additional WBVT could improve the vertical and decuple jump
performance in handball athletes. Enhanced motor unit
synchronization and firing rates, facilitated muscular contraction
stretch-shortening cycle, and improved lower extremity
neuromuscular coordination could account for these enhancements.
Abstract: It is observed that the Weighted least-square (WLS)
technique, including the modifications, results in equiripple error
curve. The resultant error as a percent of the ideal value is highly
non-uniformly distributed over the range of frequencies for which the
differentiator is designed. The present paper proposes a modification
to the technique so that the optimization procedure results in lower
maximum relative error compared to the ideal values. Simulation
results for first order as well as higher order differentiators are given
to illustrate the excellent performance of the proposed method.
Abstract: Residue Number System (RNS) is a modular representation and is proved to be an instrumental tool in many digital signal processing (DSP) applications which require high-speed computations. RNS is an integer and non weighted number system; it can support parallel, carry-free, high-speed and low power arithmetic. A very interesting correspondence exists between the concepts of Multiple Valued Logic (MVL) and Residue Number Arithmetic. If the number of levels used to represent MVL signals is chosen to be consistent with the moduli which create the finite rings in the RNS, MVL becomes a very natural representation for the RNS. There are two concerns related to the application of this Number System: reaching the most possible speed and the largest dynamic range. There is a conflict when one wants to resolve both these problem. That is augmenting the dynamic range results in reducing the speed in the same time. For achieving the most performance a method is considere named “One-Hot Residue Number System" in this implementation the propagation is only equal to one transistor delay. The problem with this method is the huge increase in the number of transistors they are increased in order m2 . In real application this is practically impossible. In this paper combining the Multiple Valued Logic and One-Hot Residue Number System we represent a new method to resolve both of these two problems. In this paper we represent a novel design of an OHRNS-based adder circuit. This circuit is useable for Multiple Valued Logic moduli, in comparison to other RNS design; this circuit has considerably improved the number of transistors and power consumption.
Abstract: This paper will discuss about an active power generator scheduling method in order to increase the limit level of steady state systems. Some power generator optimization methods such as Langrange, PLN (Indonesian electricity company) Operation, and the proposed Z-Thevenin-based method will be studied and compared in respect of their steady state aspects. A method proposed in this paper is built upon the thevenin equivalent impedance values between each load respected to each generator. The steady state stability index obtained with the REI DIMO method. This research will review the 500kV-Jawa-Bali interconnection system. The simulation results show that the proposed method has the highest limit level of steady state stability compared to other optimization techniques such as Lagrange, and PLN operation. Thus, the proposed method can be used to create the steady state stability limit of the system especially in the peak load condition.
Abstract: As the majority of faults are found in a few of its
modules so there is a need to investigate the modules that are
affected severely as compared to other modules and proper
maintenance need to be done in time especially for the critical
applications. As, Neural networks, which have been already applied
in software engineering applications to build reliability growth
models predict the gross change or reusability metrics. Neural
networks are non-linear sophisticated modeling techniques that are
able to model complex functions. Neural network techniques are
used when exact nature of input and outputs is not known. A key
feature is that they learn the relationship between input and output
through training. In this present work, various Neural Network Based
techniques are explored and comparative analysis is performed for
the prediction of level of need of maintenance by predicting level
severity of faults present in NASA-s public domain defect dataset.
The comparison of different algorithms is made on the basis of Mean
Absolute Error, Root Mean Square Error and Accuracy Values. It is
concluded that Generalized Regression Networks is the best
algorithm for classification of the software components into different
level of severity of impact of the faults. The algorithm can be used to
develop model that can be used for identifying modules that are
heavily affected by the faults.
Abstract: Due to the high percentage of induction motors in industrial market, there exist a large opportunity for energy savings. Replacement of working induction motors with more efficient ones can be an important resource for energy savings. A calculation of energy savings and payback periods, as a result of such a replacement, based on nameplate motor efficiency or manufacture-s data can lead to large errors [1]. Efficiency of induction motors (IMs) can be extracted using some procedures that use the no-load test results. In the cases that we must estimate the efficiency on-line, some of these procedures can-t be efficient. In some cases the efficiency estimates using the rating values of the motor, but these procedures can have errors due to the different working condition of the motor. In this paper the efficiency of an IM estimated by using the genetic algorithm. The results are compared with the measured values of the torque and power. The results show smaller errors for this procedure compared with the conventional classical procedures, hence the cost of the equipments is reduced and on-line estimation of the efficiency can be made.
Abstract: In this research, CaO-ZnO catalysts (with various
Ca:Zn atomic ratios of 1:5, 1:3, 1:1, and 3:1) prepared by incipientwetness
impregnation (IWI) and co-precipitation (CP) methods were
used as a catalyst in the transesterification of palm oil with methanol
for biodiesel production. The catalysts were characterized by several
techniques, including BET method, CO2-TPD, and Hemmett
Indicator. The effects of precursor concentration, and calcination
temperature on the catalytic performance were studied under reaction
conditions of a 15:1 methanol to oil molar ratio, 6 wt% catalyst,
reaction temperature of 60°C, and reaction time of 8 h. At Ca:Zn
atomic ratio of 1:3 gave the highest FAME value owing to a basic
properties and surface area of the prepared catalyst.
Abstract: Dual phase steels (DPS)s have a microstructure
consisting of a hard second phase called Martensite in the soft Ferrite
matrix. In recent years, there has been interest in dual-phase steels,
because the application of these materials has made significant usage;
particularly in the automotive sector Composite microstructure of
(DPS)s exhibit interesting characteristic mechanical properties such
as continuous yielding, low yield stress to tensile strength
ratios(YS/UTS), and relatively high formability; which offer
advantages compared with conventional high strength low alloy
steels(HSLAS). The research dealt with the characterization of
damage in (DPS)s. In this study by review the mechanisms of failure
due to volume fraction of martensite second phase; a new method is
introduced to identifying the mechanisms of failure in the various
phases of these types of steels. In this method the acoustic emission
(AE) technique was used to detect damage progression. These failure
mechanisms consist of Ferrite-Martensite interface decohesion and/or
martensite phase fracture. For this aim, dual phase steels with
different volume fraction of martensite second phase has provided by
various heat treatment methods on a low carbon steel (0.1% C), and
then AE monitoring is used during tensile test of these DPSs. From
AE measurements and an energy ratio curve elaborated from the
value of AE energy (it was obtained as the ratio between the strain
energy to the acoustic energy), that allows detecting important
events, corresponding to the sudden drops. These AE signals events
associated with various failure mechanisms are classified for ferrite
and (DPS)s with various amount of Vm and different martensite
morphology. It is found that AE energy increase with increasing Vm.
This increasing of AE energy is because of more contribution of
martensite fracture in the failure of samples with higher Vm. Final
results show a good relationship between the AE signals and the
mechanisms of failure.
Abstract: The dental composites are preferably used as filling
materials due to their esthetic appearances. Nevertheless one of the
major problems, during the application of the dental composites, is
shape change named as “polymerisation shrinkage" affecting clinical
success of the dental restoration while photo-polymerisation.
Polymerisation shrinkage of composites arises basically from the
formation of a polymer due to the monomer transformation which
composes of an organic matrix phase. It was sought, throughout this
study, to detect and evaluate the structural polymerisation shrinkage
of prepared dental composites in order to optimize the effects of
various fillers included in hydroxyapatite (HA)-reinforced dental
composites and hence to find a means to modify the properties of
these dental composites prepared with defined parameters. As a
result, the shrinkage values of the experimental dental composites
were decreased by increasing the filler content of composites and the
composition of different fillers used had effect on the shrinkage of
the prepared composite systems.
Abstract: Traffic Density provides an indication of the level of
service being provided to the road users. Hence, there is a need to
study the traffic flow characteristics with specific reference to
density in detail. When the length and speed of the vehicles in a
traffic stream vary significantly, the concept of occupancy, rather
than density, is more appropriate to describe traffic concentration.
When the concept of occupancy is applied to heterogeneous traffic
condition, it is necessary to consider the area of the road space and
the area of the vehicles as the bases. Hence, a new concept named,
'area-occupancy' is proposed here. It has been found that the
estimated area-occupancy gives consistent values irrespective of
change in traffic composition.
Abstract: Dorsal hand vein pattern is an emerging biometric which is attracting the attention of researchers, of late. Research is being carried out on existing techniques in the hope of improving them or finding more efficient ones. In this work, Principle Component Analysis (PCA) , which is a successful method, originally applied on face biometric is being modified using Cholesky decomposition and Lanczos algorithm to extract the dorsal hand vein features. This modified technique decreases the number of computation and hence decreases the processing time. The eigenveins were successfully computed and projected onto the vein space. The system was tested on a database of 200 images and using a threshold value of 0.9 to obtain the False Acceptance Rate (FAR) and False Rejection Rate (FRR). This modified algorithm is desirable when developing biometric security system since it significantly decreases the matching time.
Abstract: The modeling of inelastic behavior of plastic materials requires measurements providing information on material response to different multiaxial loading conditions. Different triaxiality conditions and values of Lode parameters have to be
covered for complex description of the material plastic behavior.
Samples geometries providing material plastic behavoiur over the range of interest are proposed with the use of FEM analysis. Round samples with 3 different notches and smooth surface are used
together with butterfly type of samples tested at angle ranging for 0 to
90°. Identification of ductile damage parameters is carried out on
the basis of obtained experimental data for austenitic stainless steel.
The obtained material plastic damage parameters are subsequently applied to FEM simulation of notched CT normally samples used for
fracture mechanics testing and results from the simulation are
compared with real tests.
Abstract: As known, the guard wires of overhead high voltage
are usually grounded through the grounding systems of support and
of the terminal stations. They do affect the zero sequence impedance
value of the line, Z0, which is generally, calculated assuming that the
wires guard are at ground potential. In this way it is not considered
the effect of the resistances of earth of supports and stations. In this
work is formed a formula for the calculation of Z0 which takes
account of said resistances. Is also proposed a method of calculating
the impedance zero sequence overhead lines in which, in various
sections or spans, the guard wires are connected to the supports, or
isolated from them, or are absent. Parametric analysis is given for
lines 220 kV and 400 kV, which shows the extent of the errors made
with traditional methods of calculation.
Abstract: Modeling of a manufacturing system enables one to
identify the effects of key design parameters on the system performance and as a result to make correct decision. This paper
proposes a manufacturing system modeling approach using a spreadsheet model based on queuing network theory, in which a
static capacity planning model and stochastic queuing model are integrated. The model was used to improve the existing system utilization in relation to product design. The model incorporates few
parameters such as utilization, cycle time, throughput, and batch size.
The study also showed that the validity of developed model is good enough to apply and the maximum value of relative error is 10%, far
below the limit value 32%. Therefore, the model developed in this
study is a valuable alternative model in evaluating a manufacturing system
Abstract: In this paper, we present a novel objective nonreference performance assessment algorithm for image fusion. It takes into account local measurements to estimate how well the important information in the source images is represented by the fused image. The metric is based on the Universal Image Quality Index and uses the similarity between blocks of pixels in the input images and the fused image as the weighting factors for the metrics. Experimental results confirm that the values of the proposed metrics correlate well with the subjective quality of the fused images, giving a significant improvement over standard measures based on mean squared error and mutual information.