Abstract: We present a novel construction of 16-QAM codewords of length n = 2k . The number of constructed codewords is 162×[4k-1×k-k+1] . When these constructed codewords are utilized as a code in OFDM systems, their peak-to-mean envelope power ratios (PMEPR) are bounded above by 3.6 . The principle of our scheme is illustrated with a four subcarrier example.
Abstract: In order to maximize efficiency of an information management platform and to assist in decision making, the collection, storage and analysis of performance-relevant data has become of fundamental importance. This paper addresses the merits and drawbacks provided by the OLAP paradigm for efficiently navigating large volumes of performance measurement data hierarchically. The system managers or database administrators navigate through adequately (re)structured measurement data aiming to detect performance bottlenecks, identify causes for performance problems or assessing the impact of configuration changes on the system and its representative metrics. Of particular importance is finding the root cause of an imminent problem, threatening availability and performance of an information system. Leveraging OLAP techniques, in contrast to traditional static reporting, this is supposed to be accomplished within moderate amount of time and little processing complexity. It is shown how OLAP techniques can help improve understandability and manageability of measurement data and, hence, improve the whole Performance Analysis process.
Abstract: Currently is characterized production engineering
together with the integration of industrial automation and robotics
such very quick view of to manufacture the products. The production
range is continuously changing, expanding and producers have to be
flexible in this regard. It means that need to offer production
possibilities, which can respond to the quick change. Engineering
product development is focused on supporting CAD software, such
systems are mainly used for product design. That manufacturers are
competitive, it should be kept procured machines made available
capable of responding to output flexibility. In response to that
problem is the development of flexible manufacturing systems,
consisting of various automated systems. The integration of flexible
manufacturing systems and subunits together with product design and
of engineering is a possible solution for this issue. Integration is
possible through the implementation of CIM systems. Such a solution
and finding a hyphen between CAD and procurement system ICIM
3000 from Festo Co. is engaged in the research project and this
contribution. This can be designed the products in CAD systems and
watch the manufacturing process from order to shipping by the
development of methods and processes of integration, This can be
modeled in CAD systems products and watch the manufacturing
process from order to shipping to develop methods and processes of
integration, which will improve support for product design
parameters by monitoring of the production process, by creating of
programs for production using the CAD and therefore accelerates the
a total of process from design to implementation.
Abstract: This paper presents the doping profile measurement
and characterization technique for the pocket implanted nano scale
n-MOSFET. Scanning capacitance microscopy and atomic force
microscopy have been used to image the extent of lateral dopant
diffusion in MOS structures. The data are capacitance vs. voltage
measurements made on a nano scale device. The technique is nondestructive
when imaging uncleaved samples. Experimental data from
the published literature are presented here on actual, cleaved device
structures which clearly indicate the two-dimensional dopant profile
in terms of a spatially varying modulated capacitance signal. Firstorder
deconvolution indicates the technique has much promise for
the quantitative characterization of lateral dopant profiles. The pocket
profile is modeled assuming the linear pocket profiles at the source
and drain edges. From the model, the effective doping concentration
is found to use in modeling and simulation results of the various
parameters of the pocket implanted nano scale n-MOSFET. The
potential of the technique to characterize important device related
phenomena on a local scale is also discussed.
Abstract: This paper presents a new adaptive DMC controller
that improves the controller performance in case of plant-model
mismatch. The new controller monitors the plant measured output,
compares it with the model output and calculates weights applied to
the controller move. Simulations show that the new controller can
help improve control performance and avoid instability in case of
severe model mismatches.
Abstract: In the present study, the incorporation of graphene
into blends of acrylonitrile-butadiene-styrene terpolymer with
polypropylene (ABS/PP) was investigated focusing on the
improvement of their thermomechanical characteristics and the effect
on their rheological behavior. The blends were prepared by melt
mixing in a twin-screw extruder and were characterized by measuring
the MFI as well as by performing DSC, TGA and mechanical tests.
The addition of graphene to ABS/PP blends tends to increase their
melt viscosity, due to the confinement of polymer chains motion.
Also, graphene causes an increment of the crystallization temperature
(Tc), especially in blends with higher PP content, because of the
reduction of surface energy of PP nucleation, which is a consequence
of the attachment of PP chains to the surface of graphene through the
intermolecular CH-π interaction. Moreover, the above nanofiller
improves the thermal stability of PP and increases the residue of
thermal degradation at all the investigated compositions of blends,
due to the thermal isolation effect and the mass transport barrier
effect. Regarding the mechanical properties, the addition of graphene
improves the elastic modulus, because of its intrinsic mechanical
characteristics and its rigidity, and this effect is particularly strong in
the case of pure PP.
Abstract: This paper presents an integrated model that
automatically measures the change of rivers, damage area of bridge
surroundings, and change of vegetation. The proposed model is on the
basis of a neurofuzzy mechanism enhanced by SOM optimization
algorithm, and also includes three functions to deal with river imagery.
High resolution imagery from FORMOSAT-2 satellite taken before
and after the invasion period is adopted. By randomly selecting a
bridge out of 129 destroyed bridges, the recognition results show that
the average width has increased 66%. The ruined segment of the
bridge is located exactly at the most scour region. The vegetation
coverage has also reduced to nearly 90% of the original. The results
yielded from the proposed model demonstrate a pinpoint accuracy rate
at 99.94%. This study brings up a successful tool not only for
large-scale damage assessment but for precise measurement to
disasters.
Abstract: The interaction of tunneling or mining with
groundwater has become a very relevant problem not only due to the
need to guarantee the safety of workers and to assure the efficiency of
the tunnel drainage systems, but also to safeguard water resources
from impoverishment and pollution risk. Therefore it is very
important to forecast the drainage processes (i.e., the evaluation of
drained discharge and drawdown caused by the excavation). The aim
of this study was to know better the system and to quantify the flow
drained from the Fontane mines, located in Val Germanasca (Turin,
Italy). This allowed to understand the hydrogeological local changes
in time. The work has therefore been structured as follows: the
reconstruction of the conceptual model with the geological,
hydrogeological and geological-structural study; the calculation of
the tunnel inflows (through the use of structural methods) and the
comparison with the measured flow rates; the water balance at the
basin scale. In this way it was possible to understand what are the
relationships between rainfall, groundwater level variations and the
effect of the presence of tunnels as a means of draining water.
Subsequently, it the effects produced by the excavation of the mining
tunnels was quantified, through numerical modeling. In particular,
the modeling made it possible to observe the drawdown variation as a
function of number, excavation depth and different mines linings.
Abstract: This paper presents a new method for estimating the mean curve of impulse voltage waveforms that are recorded during impulse tests. In practice, these waveforms are distorted by noise, oscillations and overshoot. The problem is formulated as an estimation problem. Estimation of the current signal parameters is achieved using a fast and accurate technique. The method is based on discrete dynamic filtering algorithm (DDF). The main advantage of the proposed technique is its ability in producing the estimates in a very short time and at a very high degree of accuracy. The algorithm uses sets of digital samples of the recorded impulse waveform. The proposed technique has been tested using simulated data of practical waveforms. Effects of number of samples and data window size are studied. Results are reported and discussed.
Abstract: Human genome is not only the evolutionary
summation of all advantageous events, but also houses lesions of
deleterious foot prints. A single gene mutation sometimes may
express multiple consequences in numerous tissues and a linear
relationship of the genotype and the phenotype may often be obscure.
ß Thalassemia minor, a transfusion independent mild anaemia,
coupled with environment among other factors may articulate into
phenotypic pleotropy with Hypocholesterolemia, Vitamin D
deficiency, Tissue hypoxia, Hyper-parathyroidism and Psychological
alterations. Occurrence of Pancreatic insufficiency, resultant
steatorrhoea, Vitamin-D (25-OH) deficiency (13.86 ngm/ml) with
Hypocholesterolemia (85mg/dl) in a 30 years old male ß Thal-minor
patient (Hemoglobin 11mg/dl with Fetal Hemoglobin 2.10%, Hb A2
4.60% and Hb Adult 84.80% and altered Hemogram) with increased
Para thyroid hormone (62 pg/ml) & moderate Serum Ca+2
(9.5mg/ml) indicate towards a cascade of phenotypic pleotropy
where the ß Thalassemia mutation ,be it in the 5’ cap site of the
mRNA , differential splicing etc in heterozygous state is effecting
several metabolic pathways. Compensatory extramedulary
hematopoiesis may not coped up well with the stressful life style of
the young individual and increased erythropoietic stress with high
demand for cholesterol for RBC membrane synthesis may have
resulted in Hypocholesterolemia.Oxidative stress and tissue hypoxia
may have caused the pancreatic insufficiency, leading to Vitamin D
deficiency. This may in turn have caused the secondary
hyperparathyroidism to sustain serum Calcium level. Irritability and
stress intolerance of the patient was a cumulative effect of the vicious
cycle of metabolic compromises. From these findings we propose
that the metabolic deficiencies in the ß Thalassemia mutations may
be considered as the phenotypic display of the pleotropy to explain
the genetic epidemiology.
According to the recommendations from the NIH Workshop on
Gene-Environment Interplay in Common Complex Diseases: Forging
an Integrative Model, study design of observations should be
informed by gene-environment hypotheses and results of a study
(genetic diseases) should be published to inform future hypotheses.
Variety of approaches is needed to capture data on all possible
aspects, each of which is likely to contribute to the etiology of
disease. Speakers also agreed that there is a need for development of
new statistical methods and measurement tools to appraise
information that may be missed out by conventional method where
large sample size is needed to segregate considerable effect.
A meta analytic cohort study in future may bring about significant
insight on to the title comment.
Abstract: In wireless communication system, a Decision Feedback Equalizer (DFE) to cancel the intersymbol interference (ISI) is required. In this paper, an exact convergence analysis of the (DFE) adapted by the Least Mean Square (LMS) algorithm during the training phase is derived by taking into account the finite alphabet context of data transmission. This allows us to determine the shortest training sequence that allows to reach a given Mean Square Error (MSE). With the intention of avoiding the problem of ill-convergence, the paper proposes an initialization strategy for the blind decision directed (DD) algorithm. This then yields a semi-blind DFE with high speed and good convergence.
Abstract: A robot simulator was developed to measure and
investigate the performance of a robot navigation system based on
the relative position of the robot with respect to random obstacles in
any two dimensional environment. The presented simulator focuses
on investigating the ability of a fuzzy-neural system for object
avoidance. A navigation algorithm is proposed and used to allow
random navigation of a robot among obstacles when the robot faces
an obstacle in the environment. The main features of this simulator
can be used for evaluating the performance of any system that can
provide the position of the robot with respect to obstacles in the
environment. This allows a robot developer to investigate and
analyze the performance of a robot without implementing the
physical robot.
Abstract: This paper presents the prediction of kidney
dysfunction using different neural network (NN) approaches. Self
organization Maps (SOM), Probabilistic Neural Network (PNN) and
Multi Layer Perceptron Neural Network (MLPNN) trained with Back
Propagation Algorithm (BPA) are used in this study. Six hundred and
sixty three sets of analytical laboratory tests have been collected from
one of the private clinical laboratories in Baghdad. For each subject,
Serum urea and Serum creatinin levels have been analyzed and tested
by using clinical laboratory measurements. The collected urea and
cretinine levels are then used as inputs to the three NN models in
which the training process is done by different neural approaches.
SOM which is a class of unsupervised network whereas PNN and
BPNN are considered as class of supervised networks. These
networks are used as a classifier to predict whether kidney is normal
or it will have a dysfunction. The accuracy of prediction, sensitivity
and specificity were found for each type of the proposed networks
.We conclude that PNN gives faster and more accurate prediction of
kidney dysfunction and it works as promising tool for predicting of
routine kidney dysfunction from the clinical laboratory data.
Abstract: A company CSR commitment, as stated in its Social
Report is, actually, perceived by its stakeholders?And in what
measure? Moreover, are stakeholders satisfied with the company
CSR efforts? Indeed, business returns from Corporate Social
Responsibility (CSR) practices, such as company reputation and
customer loyalty, depend heavily on how stakeholders perceive the
company social conduct. In this paper, we propose a methodology to
assess a company CSR commitment based on Global Reporting
Initiative (GRI) indicators, Content Analysis and a CSR positioning
matrix. We evaluate three aspects of CSR: the company commitment
disclosed through its Social Report; the company commitment
perceived by its stakeholders; the CSR commitment that stakeholders
require to the company. The positioning of the company under study
in the CSR matrix is based on the comparison among the three
commitment aspects (disclosed, perceived, required) and it allows
assessment and development of CSR strategies.
Abstract: the data quality is a kind of complex and unstructured concept, which is concerned by information systems managers. The reason of this attention is the high amount of Expenses for maintenance and cleaning of the inefficient data. Such a data more than its expenses of lack of quality, cause wrong statistics, analysis and decisions in organizations. Therefor the managers intend to improve the quality of their information systems' data. One of the basic subjects of quality improvement is the evaluation of the amount of it. In this paper, we present a precautionary method, which with its application the data of information systems would have a better quality. Our method would cover different dimensions of data quality; therefor it has necessary integrity. The presented method has tested on three dimensions of accuracy, value-added and believability and the results confirm the improvement and integrity of this method.
Abstract: Color image segmentation can be considered as a
cluster procedure in feature space. k-means and its adaptive
version, i.e. competitive learning approach are powerful tools
for data clustering. But k-means and competitive learning suffer
from several drawbacks such as dead-unit problem and need to
pre-specify number of cluster. In this paper, we will explore to
use competitive and cooperative learning approach to perform
color image segmentation. In competitive and cooperative
learning approach, seed points not only compete each other, but
also the winner will dynamically select several nearest
competitors to form a cooperative team to adapt to the input
together, finally it can automatically select the correct number
of cluster and avoid the dead-units problem. Experimental
results show that CCL can obtain better segmentation result.
Abstract: Solution to unsteady Navier-Stokes equation by Splitting method in physical orthogonal algebraic curvilinear coordinate system, also termed 'Non-linear grid system' is presented. The linear terms in Navier-Stokes equation are solved by Crank- Nicholson method while the non-linear term is solved by the second order Adams-Bashforth method. This work is meant to bring together the advantage of Splitting method as pressure-velocity solver of higher efficiency with the advantage of consuming Non-linear grid system which produce more accurate results in relatively equal number of grid points as compared to Cartesian grid. The validation of Splitting method as a solution of Navier-Stokes equation in Nonlinear grid system is done by comparison with the benchmark results for lid driven cavity flow by Ghia and some case studies including Backward Facing Step Flow Problem.
Abstract: Through a proper analysis of residual strain and stress
distributions obtained at the surface of high speed milled specimens
of AA 6082–T6 aluminium alloy, the performance of an improved
indentation method is evaluated. This method integrates a special
device of indentation to a universal measuring machine. The
mentioned device allows introducing elongated indents allowing to
diminish the absolute error of measurement. It must be noted that the
present method offers the great advantage of avoiding both the
specific equipment and highly qualified personnel, and their inherent
high costs. In this work, the cutting tool geometry and high speed
parameters are selected to introduce reduced plastic damage.
Through the variation of the depth of cut, the stability of the shapes
adopted by the residual strain and stress distributions is evaluated.
The results show that the strain and stress distributions remain
unchanged, compressive and small. Moreover, these distributions
reveal a similar asymmetry when the gradients corresponding to
conventional and climb cutting zones are compared.
Abstract: In this paper, we study the application of Extreme
Learning Machine (ELM) algorithm for single layered feedforward
neural networks to non-linear chaotic time series problems. In this
algorithm the input weights and the hidden layer bias are randomly
chosen. The ELM formulation leads to solving a system of linear
equations in terms of the unknown weights connecting the hidden
layer to the output layer. The solution of this general system of
linear equations will be obtained using Moore-Penrose generalized
pseudo inverse. For the study of the application of the method we
consider the time series generated by the Mackey Glass delay
differential equation with different time delays, Santa Fe A and
UCR heart beat rate ECG time series. For the choice of sigmoid,
sin and hardlim activation functions the optimal values for the
memory order and the number of hidden neurons which give the
best prediction performance in terms of root mean square error are
determined. It is observed that the results obtained are in close
agreement with the exact solution of the problems considered
which clearly shows that ELM is a very promising alternative
method for time series prediction.
Abstract: Yogurt is a coagulated milk product obtained from
the lactic acid fermentation by the action of Lactobacillus
bulgaricus and Streptococcus thermophilus. The additions of fruits
into milk may enhance the taste and the therapeutical values of milk
products. However fruits also may change the fermentation
behaviour. In this present study, the changes in physicochemical, the
peptide concentration, total phenolics content and the antioxidant
potential of yogurt upon the addition of Hylocereus polyrhizus and
Hylocereus undatus (white and red dragon fruit) were investigated.
Fruits enriched yogurt (10%, 20%, 30% w/w) were prepared and the
pH, TTA, syneresis measurement, peptide concentration, total
phenolics content and DPPH antioxidant inhibition percentage were
determined. Milk fermentation rate was enhanced in red dragon fruit
yogurt for all doses (-0.3606 - -0.4126 pH/h) while only white
dragon fruit yogurt with 20% and 30% (w/w) composition showed
increment in fermentation rate (-0.3471 - -0.3609 pH/h) compared to
plain yogurt (-0.3369pH/h). All dragon fruit enriched yogurts
generally showed lower pH readings (pH 3.95 - 4.03) compared to
plain yogurt (pH 4.05). Both fruit yogurts showed a higher lactic
acid percentage (1.14-1.23%) compared to plain yogurt (1.08%).
Significantly higher syneresis percentage (57.19 - 70.32%)
compared to plain yogurt (52.93%) were seen in all fruit enriched
yogurts. The antioxidant activity of plain yogurt (19.16%) was
enhanced by the presence of white and red dragon fruit (24.97-
45.74%). All fruit enriched yogurt showed an increment in total
phenolic content (36.44 - 64.43mg/ml) compared to plain yogurt
(20.25mg/ml). However, the addition of white and red dragon fruit
did not enhance the proteolysis of milk during fermentation.
Therefore, it could be concluded that the addition of white and red
dragon fruit into yogurt enhanced the milk fermentation rate, lactic
acid content, syneresis percentage, antioxidant activity, and total
phenolics content in yogurt.