Abstract: Orthogonal Frequency Division Multiplexing
(OFDM) is an efficient method of data transmission for high speed
communication systems. However, the main drawback of OFDM
systems is that, it suffers from the problem of high Peak-to-Average
Power Ratio (PAPR) which causes inefficient use of the High Power
Amplifier and could limit transmission efficiency. OFDM consist of
large number of independent subcarriers, as a result of which the
amplitude of such a signal can have high peak values. In this paper,
we propose an effective reduction scheme that combines DCT and
SLM techniques. The scheme is composed of the DCT followed by
the SLM using the Riemann matrix to obtain phase sequences for the
SLM technique. The simulation results show PAPR can be greatly
reduced by applying the proposed scheme. In comparison with
OFDM, while OFDM had high values of PAPR –about 10.4dB our
proposed method achieved about 4.7dB reduction of the PAPR with
low complexities computation. This approach also avoids
randomness in phase sequence selection, which makes it simpler to
decode at the receiver. As an added benefit, the matrices can be
generated at the receiver end to obtain the data signal and hence it is
not required to transmit side information (SI).
Abstract: Fixed-bed slow pyrolysis experiments of rice husk
have been conducted to determine the effect of pyrolysis
temperature, heating rate, particle size and reactor length on the
pyrolysis product yields. Pyrolysis experiments were performed at
pyrolysis temperature between 400 and 600°C with a constant
heating rate of 60°C/min and particle sizes of 0.60-1.18 mm. The
optimum process conditions for maximum liquid yield from the rice
husk pyrolysis in a fixed bed reactor were also identified. The highest
liquid yield was obtained at a pyrolysis temperature of 500°C,
particle size of
1.18-1.80 mm, with a heating rate of 60°C/min in a 300 mm length
reactor. The obtained yield of, liquid, gas and solid were found be in
the range of 22.57-31.78 %, 27.75-42.26 % and 34.17-42.52 % (all
weight basics) respectively at different pyrolysis conditions. The
results indicate that the effects of pyrolysis temperature and particle
size on the pyrolysis yield are more significant than that of heating
rate and reactor length. The functional groups and chemical
compositions present in the liquid obtained at optimum conditions
were identified by Fourier Transform-Infrared (FT-IR) spectroscopy
and Gas Chromatography/ Mass Spectroscopy (GC/MS) analysis
respectively.
Abstract: Steel corrosion in concrete is considered as a main
engineering problems for many countries and lots of expenses has been paid for their repair and maintenance annually. This problem
may occur in all engineering structures whether in coastal and offshore or other areas. Hence, concrete structures should be able to
withstand corrosion factors existing in water or soil. Reinforcing
steel corrosion enhancement can be measured by use of concrete
electrical resistance; and maintaining high electric resistivity in concrete is necessary for steel corrosion prevention. Lots of studies
devoted to different aspects of the subjects worldwide. In this paper, an evaluation of the effects of W/C ratio, cementitious materials, and
percent increase in silica fume were investigated on electric resistivity of high strength concrete. To do that, sixteen mix design
with one aggregate grading was planned. Five of them had varying amount of W/C ratio and other eleven mixes was prepared with
constant W/C ratio but different amount of cementitious materials.
Silica fume and super plasticizer were used with different proportions
in all specimens. Specimens were tested after moist curing for 28 days. A total of 80 cube specimens (50 mm) were tested for concrete
electrical resistance. Results show that concrete electric resistivity can be increased with increasing amount of cementitious materials
and silica fume.
Abstract: Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the kmeans algorithm. Solutions obtained from this technique depend on the initialization of cluster centers and the final solution converges to local minima. In order to overcome K-means algorithm shortcomings, this paper proposes a hybrid evolutionary algorithm based on the combination of PSO, SA and K-means algorithms, called PSO-SA-K, which can find better cluster partition. The performance is evaluated through several benchmark data sets. The simulation results show that the proposed algorithm outperforms previous approaches, such as PSO, SA and K-means for partitional clustering problem.
Abstract: In this paper, we propose a method to extract the road
signs. Firstly, the grabbed image is converted into the HSV color space
to detect the road signs. Secondly, the morphological operations are
used to reduce noise. Finally, extract the road sign using the geometric
property. The feature extraction of road sign is done by using the color
information. The proposed method has been tested for the real
situations. From the experimental results, it is seen that the proposed
method can extract the road sign features effectively.
Abstract: This work concerns the topological optimization
problem for determining the optimal petroleum refinery
configuration. We are interested in further investigating and
hopefully advancing the existing optimization approaches and
strategies employing logic propositions to conceptual process
synthesis problems. In particular, we seek to contribute to this
increasingly exciting area of chemical process modeling by
addressing the following potentially important issues: (a) how the
formulation of design specifications in a mixed-logical-and-integer
optimization model can be employed in a synthesis problem to enrich
the problem representation by incorporating past design experience,
engineering knowledge, and heuristics; and (b) how structural
specifications on the interconnectivity relationships by space (states)
and by function (tasks) in a superstructure should be properly
formulated within a mixed-integer linear programming (MILP)
model. The proposed modeling technique is illustrated on a case
study involving the alternative processing routes of naphtha, in which
significant improvement in the solution quality is obtained.
Abstract: Determination of nano particle size is substantial since
the nano particle size exerts a significant effect on various properties
of nano materials. Accordingly, proposing non-destructive, accurate
and rapid techniques for this aim is of high interest. There are some
conventional techniques to investigate the morphology and grain size
of nano particles such as scanning electron microscopy (SEM),
atomic force microscopy (AFM) and X-ray diffractometry (XRD).
Vibrational spectroscopy is utilized to characterize different
compounds and applied for evaluation of the average particle size
based on relationship between particle size and near infrared spectra
[1,4] , but it has never been applied in quantitative morphological
analysis of nano materials. So far, the potential application of nearinfrared
(NIR) spectroscopy with its ability in rapid analysis of
powdered materials with minimal sample preparation, has been
suggested for particle size determination of powdered
pharmaceuticals. The relationship between particle size and diffuse
reflectance (DR) spectra in near infrared region has been applied to
introduce a method for estimation of particle size. Back propagation
artificial neural network (BP-ANN) as a nonlinear model was applied
to estimate average particle size based on near infrared diffuse
reflectance spectra. Thirty five different nano TiO2 samples with
different particle size were analyzed by DR-FTNIR spectrometry and
the obtained data were processed by BP- ANN.
Abstract: The Japanese integrative approach to social systems
can be observed in supply chain management as well as in the
relationship between public and private sectors. Both the Lean
Production System and the Developmental State Model are
characterized by efforts towards the achievement of mutual goals,
resulting in initiatives for capacity building which emphasize the
system level. In Brazil, although organizations undertake efforts to
build capabilities at the individual and organizational levels, the
system level is being neglected. Fieldwork data confirmed the findings
of other studies in terms of the lack of integration in supply chain
management in the Brazilian automobile industry. Moreover, due to
the absence of an active role of the Brazilian state in its relationship
with the private sector, automakers are not fully exploiting the
opportunities in the domestic and regional markets. For promoting a
higher level of economic growth as well as to increase the degree of
spill-over of technologies and techniques, a more integrative approach
is needed.
Abstract: The Major Depressive Disorder has been a burden of
medical expense in Taiwan as well as the situation around the world.
Major Depressive Disorder can be defined into different categories by
previous human activities. According to machine learning, we can
classify emotion in correct textual language in advance. It can help
medical diagnosis to recognize the variance in Major Depressive
Disorder automatically. Association language incremental is the
characteristic and relationship that can discovery words in sentence.
There is an overlapping-category problem for classification. In this
paper, we would like to improve the performance in classification in
principle of no overlapping-category problems. We present an
approach that to discovery words in sentence and it can find in high
frequency in the same time and can-t overlap in each category, called
Association Language Features by its Category (ALFC).
Experimental results show that ALFC distinguish well in Major
Depressive Disorder and have better performance. We also compare
the approach with baseline and mutual information that use single
words alone or correlation measure.
Abstract: In order to optimize annual IT spending and to reduce
the complexity of an entire system architecture, SOA trials have been
started. It is common knowledge that to design an SOA system we
have to adopt the top-down approach, but in reality silo systems are
being made, so these companies cannot reuse newly designed services,
and cannot enjoy SOA-s economic benefits. To prevent this situation,
we designed a generic SOA development process referred to as the
architecture of “mass customization."
To define the generic detail development processes, we did a case
study on an imaginary company. Through the case study, we could
define the practical development processes and found this could vastly
reduce updating development costs.
Abstract: A DEA model can generally evaluate the performance
using multiple inputs and outputs for the same period. However, it is
hard to avoid the production lead time phenomenon some times, such
as long-term project or marketing activity. A couple of models have
been suggested to capture this time lag issue in the context of DEA.
This paper develops a dual-MPO model to deal with time lag effect in
evaluating efficiency. A numerical example is also given to show that
the proposed model can be used to get efficiency and reference set of
inefficient DMUs and to obtain projected target value of input
attributes for inefficient DMUs to be efficient.
Abstract: Data from 1731 Gentile di Puglia lambs, sired by 65 rams over a 5-year period were analyzed by a mixed model to estimate the variance components for heritability. The considered growth traits were: birth weight (BW), weight at 30 days of age (W30) and average daily gain from birth to 30 days of age (DG). Year of birth, sex of lamb, type of birth (single or twin), dam age at lambing and farm were significant sources of variation for all the considered growth traits. The average lamb weights were 3.85±0.16 kg at birth, 9.57±0.91 kg at 30 days of age and the average daily gain was 191±14 g. Estimates of heritability were 0.33±0.05, 0.41±0.06 and 0.16±0.05 respectively for the same traits. These values suggest there is a good opportunity to improve Gentile di Puglia lambs by selecting animals for growth traits.
Abstract: We developed a non-contact method for the in-situ
monitoring of the thermal forming of glass and Si foils to optimize
the manufacture of mirrors for high-resolution space x-ray
telescopes. Their construction requires precise and light-weight
segmented optics with angular resolution better than 5 arcsec. We
used 75x25 mm Desag D263 glass foils 0.75 mm thick and 0.6 mm
thick Si foils. The glass foils were shaped by free slumping on a
frame at viscosities in the range of 109.3-1012 dPa·s, the Si foils by
forced slumping above 1000°C. Using a Nikon D80 digital camera,
we took snapshots of a foil-s shape every 5 min during its isothermal
heat treatment. The obtained results we can use for computer
simulations. By comparing the measured and simulated data, we can
more precisely define material properties of the foils and optimize
the forming technology.
Abstract: A new strain of Type A influenza virus can cause the
transmission of H1N1 virus. This virus can spread between the
people by coughing and sneezing. Because the people are always
movement, so this virus can be easily spread. In this study, we
construct the dynamical network model of H1N1 virus by separating
the human into five groups; susceptible, exposed, infectious,
quarantine and recovered groups. The movement of people between
houses (local level) is considered. The behaviors of solutions to our
dynamical model are shown for the different parameters.
Abstract: The effect of the rotational speed and axial torque on
the diagnostics of tapered rolling element bearing defects was
investigated. The accelerometer was mounted on the bearing housing
and connected to Sound and Vibration Analyzer (SVAN 958) and
was used to measure the accelerations from the bearing housing. The
data obtained from the bearing was processed to detect damage of the
bearing using statistical tools and the results were subsequently
analyzed to see if bearing damage had been captured. From this study
it can be seen that damage is more evident when the bearing is
loaded. Also, at the incipient stage of damage the crest factor and
kurtosis values are high but as time progresses the crest factors and
kurtosis values decrease whereas the peak and RMS values are low at
the incipient stage but increase with damage.
Abstract: In this paper an alternative visualisation approach of
the wake behind different vehicle body shapes with simplified and
fully-detailed underbody has been proposed and analysed. This
allows for a more clear distinction among the different wake regions.
This visualisation is based on a transformation of the cartesian
coordinates of a chosen wake plane to polar coordinates, using as
filter velocities lower than the freestream. This transformation
produces a polar wake plot that enables the division and
quantification of the wake in a number of sections. In this paper,
local drag has been used to visualise the drag contribution of the flow
by the different sections. Visually, a balanced wake can be observed
by the concentric behaviour of the polar plots. Alternatively,
integration of the local drag of each degree section as a ratio of the
total local drag yields a quantifiable approach of the wake uniformity,
where different sections contribute equally to the local drag, with the
exception of the wheels.
Abstract: How to effectively allocate system resource to process
the Client request by Gateway servers is a challenging problem. In
this paper, we propose an improved scheme for autonomous
performance of Gateway servers under highly dynamic traffic loads.
We devise a methodology to calculate Queue Length and Waiting
Time utilizing Gateway Server information to reduce response time
variance in presence of bursty traffic. The most widespread
contemplation is performance, because Gateway Servers must offer
cost-effective and high-availability services in the elongated period,
thus they have to be scaled to meet the expected load. Performance
measurements can be the base for performance modeling and
prediction. With the help of performance models, the performance
metrics (like buffer estimation, waiting time) can be determined at
the development process. This paper describes the possible queue
models those can be applied in the estimation of queue length to
estimate the final value of the memory size. Both simulation and
experimental studies using synthesized workloads and analysis of
real-world Gateway Servers demonstrate the effectiveness of the
proposed system.
Abstract: In Supply Chain Management (SCM), strengthening partnerships with suppliers is a significant factor for enhancing competitiveness. Hence, firms increasingly emphasize supplier evaluation processes. Supplier evaluation systems are basically developed in terms of criteria such as quality, cost, delivery, and flexibility. Because there are many variables to be analyzed, this process becomes hard to execute and needs expertise. On this account, this study aims to develop an expert system on supplier evaluation process by designing Artificial Neural Network (ANN) that is supported with Data Envelopment Analysis (DEA). The methods are applied on the data of 24 suppliers, which have longterm relationships with a medium sized company from German Iron and Steel Industry. The data of suppliers consists of variables such as material quality (MQ), discount of amount (DOA), discount of cash (DOC), payment term (PT), delivery time (DT) and annual revenue (AR). Meanwhile, the efficiency that is generated by using DEA is added to the supplier evaluation system in order to use them as system outputs.
Abstract: Direct conversion of methane to methanol by partial oxidation in a thermal reactor has a poor yield of about 2% which is less than the expected economical yield of about 10%. Conventional thermal catalytic reactors have been proposed to be superseded by plasma reactors as a promising approach, due to strength of the electrical energy which can break C-H bonds of methane. Among the plasma techniques, non-thermal dielectric barrier discharge (DBD) plasma chemical process is one of the most future promising technologies in synthesizing methanol. The purpose of this paper is presenting a brief review of CH4 oxidation with O2 in DBD plasma reactors based on the recent investigations. For this reason, the effect of various parameters of reactor configuration, feed ratio, applied voltage, residence time (gas flow rate), type of applied catalyst, pressure and reactor wall temperature on methane conversion and methanol selectivity are discussed.
Abstract: A number of routing algorithms based on learning
automata technique have been proposed for communication
networks. How ever, there has been little work on the effects of
variation of graph scarcity on the performance of these algorithms. In
this paper, a comprehensive study is launched to investigate the
performance of LASPA, the first learning automata based solution to
the dynamic shortest path routing, across different graph structures
with varying scarcities. The sensitivity of three main performance
parameters of the algorithm, being average number of processed
nodes, scanned edges and average time per update, to variation in
graph scarcity is reported. Simulation results indicate that the LASPA
algorithm can adapt well to the scarcity variation in graph structure
and gives much better outputs than the existing dynamic and fixed
algorithms in terms of performance criteria.