Abstract: The current tools for real time management of sewer
systems are based on two software tools: the software of weather
forecast and the software of hydraulic simulation. The use of the first
ones is an important cause of imprecision and uncertainty, the use of
the second requires temporal important steps of decision because of
their need in times of calculation. This way of proceeding fact that
the obtained results are generally different from those waited. The major idea of this project is to change the basic paradigm by
approaching the problem by the "automatic" face rather than by that
"hydrology". The objective is to make possible the realization of a
large number of simulations at very short times (a few seconds)
allowing to take place weather forecasts by using directly the real
time meditative pluviometric data. The aim is to reach a system
where the decision-making is realized from reliable data and where
the correction of the error is permanent. A first model of control laws was realized and tested with different
return-period rainfalls. The gains obtained in rejecting volume vary
from 19 to 100 %. The development of a new algorithm was then
used to optimize calculation time and thus to overcome the
subsequent combinatorial problem in our first approach. Finally, this
new algorithm was tested with 16- year-rainfall series. The obtained
gains are 40 % of total volume rejected to the natural environment
and of 65 % in the number of discharges.
Abstract: Anammox is a novel and promising technology that has changed the traditional concept of biological nitrogen removal. The process facilitates direct oxidation of ammonical nitrogen under anaerobic conditions with nitrite as an electron acceptor without addition of external carbon sources. The present study investigated the feasibility of Anammox Hybrid Reactor (AHR) combining the dual advantages of suspended and attached growth media for biodegradation of ammonical nitrogen in wastewater. Experimental unit consisted of 4 nos. of 5L capacity AHR inoculated with mixed seed culture containing anoxic and activated sludge (1:1). The process was established by feeding the reactors with synthetic wastewater containing NH4-H and NO2-N in the ratio 1:1 at HRT (hydraulic retention time) of 1 day. The reactors were gradually acclimated to higher ammonium concentration till it attained pseudo steady state removal at a total nitrogen concentration of 1200 mg/l. During this period, the performance of the AHR was monitored at twelve different HRTs varying from 0.25-3.0 d with increasing NLR from 0.4 to 4.8 kg N/m3d. AHR demonstrated significantly higher nitrogen removal (95.1%) at optimal HRT of 1 day. Filter media in AHR contributed an additional 27.2% ammonium removal in addition to 72% reduction in the sludge washout rate. This may be attributed to the functional mechanism of filter media which acts as a mechanical sieve and reduces the sludge washout rate many folds. This enhances the biomass retention capacity of the reactor by 25%, which is the key parameter for successful operation of high rate bioreactors. The effluent nitrate concentration, which is one of the bottlenecks of anammox process was also minimised significantly (42.3-52.3 mg/L). Process kinetics was evaluated using first order and Grau-second order models. The first-order substrate removal rate constant was found as 13.0 d-1. Model validation revealed that Grau second order model was more precise and predicted effluent nitrogen concentration with least error (1.84±10%). A new mathematical model based on mass balance was developed to predict N2 gas in AHR. The mass balance model derived from total nitrogen dictated significantly higher correlation (R2=0.986) and predicted N2 gas with least error of precision (0.12±8.49%). SEM study of biomass indicated the presence of heterogeneous population of cocci and rod shaped bacteria of average diameter varying from 1.2-1.5 mm. Owing to enhanced NRE coupled with meagre production of effluent nitrate and its ability to retain high biomass, AHR proved to be the most competitive reactor configuration for dealing with nitrogen laden wastewater.
Abstract: This study presents three different approaches to
estimate bubble point pressures for the binary system of CO2 and
ethyl palmitate fatty acid ethyl ester. The first method involves the
Peng-Robinson (PR) Equation of State (EoS) with the conventional
mixing rule of Van der Waals. The second approach involves the PR
EOS together with the Wong Sandler (WS) mixing rule, coupled with
the UNIQUAC GE model. In order to model the bubble point
pressures with this approach, the volume and area parameter for ethyl
palmitate were estimated by the Hansen group contribution method.
The last method involved the Peng-Robinson, combined with the
Wong-Sandler method, but using NRTL as the GE model. Results
using the Van der Waals mixing rule clearly indicated that this
method has the largest errors among all three methods, with errors in
the range of 3.96-6.22%. The PR-WS-UNIQUAC method exhibited
small errors, with average absolute deviations between 0.95 to 1.97
percent. The PR-WS-NRTL method led to the least errors, where
average absolute deviations ranged between 0.65-1.7%.
Abstract: In this paper, we present a new segmentation approach
for focal liver lesions in contrast enhanced ultrasound imaging. This
approach, based on a two-cluster Fuzzy C-Means methodology,
considers type-II fuzzy sets to handle uncertainty due to the image
modality (presence of speckle noise, low contrast, etc.), and to
calculate the optimum inter-cluster threshold. Fine boundaries are
detected by a local recursive merging of ambiguous pixels. The
method has been tested on a representative database. Compared to
both Otsu and type-I Fuzzy C-Means techniques, the proposed
method significantly reduces the segmentation errors.
Abstract: An approach was evaluated for the retrieval of soil
moisture of bare soil surface using bistatic scatterometer data in the
angular range of 200 to 700 at VV- and HH- polarization. The
microwave data was acquired by specially designed X-band (10
GHz) bistatic scatterometer. The linear regression analysis was done
between scattering coefficients and soil moisture content to select the
suitable incidence angle for retrieval of soil moisture content. The 250
incidence angle was found more suitable. The support vector
regression analysis was used to approximate the function described
by the input output relationship between the scattering coefficient and
corresponding measured values of the soil moisture content. The
performance of support vector regression algorithm was evaluated by
comparing the observed and the estimated soil moisture content by
statistical performance indices %Bias, root mean squared error
(RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias,
root mean squared error (RMSE) and Nash-Sutcliffe Efficiency
(NSE) were found 2.9451, 1.0986 and 0.9214 respectively at HHpolarization.
At VV- polarization, the values of %Bias, root mean
squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were
found 3.6186, 0.9373 and 0.9428 respectively.
Abstract: Localization of nodes is one of the key issues of
Wireless Sensor Network (WSN) that gained a wide attention in
recent years. The existing localization techniques can be generally
categorized into two types: range-based and range-free. Compared
with rang-based schemes, the range-free schemes are more costeffective,
because no additional ranging devices are needed. As a
result, we focus our research on the range-free schemes. In this paper
we study three types of range-free location algorithms to compare the
localization error and energy consumption of each one. Centroid
algorithm requires a normal node has at least three neighbor anchors,
while DV-hop algorithm doesn’t have this requirement. The third
studied algorithm is the amorphous algorithm similar to DV-Hop
algorithm, and the idea is to calculate the hop distance between two
nodes instead of the linear distance between them. The simulation
results show that the localization accuracy of the amorphous
algorithm is higher than that of other algorithms and the energy
consumption does not increase too much.
Abstract: This paper presents a power control for a Doubly Fed
Induction Generator (DFIG) using in Wind Energy Conversion
System (WECS) connected to the grid. The proposed control strategy
employs two nonlinear controllers, Backstipping (BSC) and slidingmode
controller (SMC) scheme to directly calculate the required
rotor control voltage so as to eliminate the instantaneous errors of
active and reactive powers. In this paper the advantages of BSC and
SMC are presented, the performance and robustness of this two
controller’s strategy are compared between them. First, we present a
model of wind turbine and DFIG machine, then a synthesis of the
controllers and their application in the DFIG power control.
Simulation results on a 1.5MW grid-connected DFIG system are
provided by MATLAB/Simulink.
Abstract: Most of the existing video streaming protocols
provide video services without considering security aspects in
decentralized mobile ad-hoc networks. The security policies adapted
to the currently existing non-streaming protocols, do not comply with
the live video streaming protocols resulting in considerable
vulnerability, high bandwidth consumption and unreliability which
cause severe security threats, low bandwidth and error prone
transmission respectively in video streaming applications. Therefore
a synergized methodology is required to reduce vulnerability and
bandwidth consumption, and enhance reliability in the video
streaming applications in MANET. To ensure the security measures
with reduced bandwidth consumption and improve reliability of the
video streaming applications, a Secure Low-bandwidth Video
Streaming through Reliable Multipath Propagation (SLVRMP)
protocol architecture has been proposed by incorporating the two
algorithms namely Secure Low-bandwidth Video Streaming
Algorithm and Reliable Secure Multipath Propagation Algorithm
using Layered Video Coding in non-overlapping zone routing
network topology. The performances of the proposed system are
compared to those of the other existing secure multipath protocols
Sec-MR, SPREAD using NS 2.34 and the simulation results show
that the performances of the proposed system get considerably
improved.
Abstract: The output error of the globoidal cam mechanism can
be considered as a relevant indicator of mechanism performance,
because it determines kinematic and dynamical behavior of
mechanical transmission. Based on the differential geometry and the
rigid body transformations, the mathematical model of surface
geometry of the globoidal cam is established. Then we present the
analytical expression of the output error (including the transmission
error and the displacement error along the output axis) by considering
different manufacture and assembly errors. The effects of the center
distance error, the perpendicular error between input and output axes
and the rotational angle error of the globoidal cam on the output error
are systematically analyzed. A globoidal cam mechanism which is
widely used in automatic tool changer of CNC machines is applied for
illustration. Our results show that the perpendicular error and the
rotational angle error have little effects on the transmission error but
have great effects on the displacement error along the output axis. This
study plays an important role in the design, manufacture and assembly
of the globoidal cam mechanism.
Abstract: Live video streaming is one of the most widely used
service among end users, yet it is a big challenge for the network
operators in terms of quality. The only way to provide excellent
Quality of Experience (QoE) to the end users is continuous
monitoring of live video streaming. For this purpose, there are several
objective algorithms available that monitor the quality of the video in
a live stream. Subjective tests play a very important role in fine
tuning the results of objective algorithms. As human perception is
considered to be the most reliable source for assessing the quality of a
video stream subjective tests are conducted in order to develop more
reliable objective algorithms. Temporal impairments in a live video
stream can have a negative impact on the end users. In this paper we
have conducted subjective evaluation tests on a set of video
sequences containing temporal impairment known as frame freezing.
Frame Freezing is considered as a transmission error as well as a
hardware error which can result in loss of video frames on the
reception side of a transmission system. In our subjective tests, we
have performed tests on videos that contain a single freezing event
and also for videos that contain multiple freezing events. We have
recorded our subjective test results for all the videos in order to give a
comparison on the available No Reference (NR) objective
algorithms. Finally, we have shown the performance of no reference
algorithms used for objective evaluation of videos and suggested the
algorithm that works better. The outcome of this study shows the
importance of QoE and its effect on human perception. The results
for the subjective evaluation can serve the purpose for validating
objective algorithms.
Abstract: Multiple User Interference (MUI) considers the
primary problem in Optical Code-Division Multiple Access
(OCDMA), which resulting from the overlapping among the users. In
this article we aim to mitigate this problem by studying an
interference cancellation scheme called successive interference
cancellation (SIC) scheme. This scheme will be tested on two
different detection schemes, spectral amplitude coding (SAC) and
direct detection systems (DS), using partial modified prime (PMP) as
the signature codes. It was found that SIC scheme based on both SAC
and DS methods had a potential to suppress the intensity noise, that is
to say it can mitigate MUI noise. Furthermore, SIC/DS scheme
showed much lower bit error rate (BER) performance relative to
SIC/SAC scheme for different magnitude of effective power. Hence,
many more users can be supported by SIC/DS receiver system.
Abstract: Sound processing is one the subjects that newly
attracts a lot of researchers. It is efficient and usually less expensive
than other methods. In this paper the flow generated sound is used to
estimate the flow speed of free flows. Many sound samples are
gathered. After analyzing the data, a parameter named wave power is
chosen. For all samples the wave power is calculated and averaged
for each flow speed. A curve is fitted to the averaged data and a
correlation between the wave power and flow speed is found. Test
data are used to validate the method and errors for all test data were
under 10 percent. The speed of the flow can be estimated by
calculating the wave power of the flow generated sound and using the
proposed correlation.
Abstract: Human beings have the ability to make logical
decisions. Although human decision - making is often optimal, it is
insufficient when huge amount of data is to be classified. Medical
dataset is a vital ingredient used in predicting patient’s health
condition. In other to have the best prediction, there calls for most
suitable machine learning algorithms. This work compared the
performance of Artificial Neural Network (ANN) and Decision Tree
Algorithms (DTA) as regards to some performance metrics using
diabetes data. WEKA software was used for the implementation of
the algorithms. Multilayer Perceptron (MLP) and Radial Basis
Function (RBF) were the two algorithms used for ANN, while
RegTree and LADTree algorithms were the DTA models used. From
the results obtained, DTA performed better than ANN. The Root
Mean Squared Error (RMSE) of MLP is 0.3913 that of RBF is
0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206
respectively.
Abstract: In the cooperative transmission scheme, both the
cellular system and broadcasting system are composed. Two cellular
base stations (CBSs) communicating with a user in the cell edge use
cooperative transmission scheme in the conventional scheme. In the
case that the distance between two CBSs and the user is distant, the
conventional scheme does not guarantee the quality of the
communication because the channel condition is bad. Therefore, if the
distance between CBSs and a user is distant, the performance of the
conventional scheme is decreased. Also, the bad channel condition has
bad effects on the performance. The proposed scheme uses two relays
to communicate well with CBSs when the channel condition between
CBSs and the user is poor. Using the relay in the high attenuation
environment can obtain both advantages of the high bit error rate
(BER) and throughput performance.
Abstract: EEG correlates of mathematical and trait anxiety level
were studied in 52 healthy Russian-speakers during execution of
error-recognition tasks with lexical, arithmetic and algebraic
conditions. Event-related spectral perturbations were used as a
measure of brain activity. The ERSP plots revealed alpha/beta
desynchronizations within a 500-3000 ms interval after task onset
and slow-wave synchronization within an interval of 150-350 ms.
Amplitudes of these intervals reflected the accuracy of error
recognition, and were differently associated with the three conditions.
The correlates of anxiety were found in theta (4-8 Hz) and beta2 (16-
20 Hz) frequency bands. In theta band the effects of mathematical
anxiety were stronger expressed in lexical, than in arithmetic and
algebraic condition. The mathematical anxiety effects in theta band
were associated with differences between anterior and posterior
cortical areas, whereas the effects of trait anxiety were associated
with inter-hemispherical differences. In beta1 and beta2 bands effects
of trait and mathematical anxiety were directed oppositely. The trait
anxiety was associated with increase of amplitude of
desynchronization, whereas the mathematical anxiety was associated
with decrease of this amplitude. The effect of mathematical anxiety
in beta2 band was insignificant for lexical condition but was the
strongest in algebraic condition. EEG correlates of anxiety in theta
band could be interpreted as indexes of task emotionality, whereas
the reaction in beta2 band is related to tension of intellectual
resources.
Abstract: In this paper, improved performance scheme for
joint transmission (JT) is proposed in downlink (DL) coordinated
multi-point (CoMP) in case of the constraint transmission power.
This scheme is that a serving transmission point (TP) requests the
JT to an inter-TP and it selects a precoding technique according
to the channel state information (CSI) from user equipment (UE).
The simulation results show that the bit error rate (BER) and the
throughput performances of the proposed scheme provide the high
spectral efficiency and the reliable data at the cell edge.
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: In recent years, multi-antenna techniques are being considered as a potential solution to increase the flow of future wireless communication systems. The objective of this article is to study the emission and reception system MIMO (Multiple Input Multiple Output), and present the different reception decoding techniques. First we will present the least complex technical, linear receivers such as the zero forcing equalizer (ZF) and minimum mean squared error (MMSE). Then a nonlinear technique called ordered successive cancellation of interferences (OSIC) and the optimal detector based on the maximum likelihood criterion (ML), finally, we simulate the associated decoding algorithms for MIMO system such as ZF, MMSE, OSIC and ML, thus a comparison of performance of these algorithms in MIMO context.
Abstract: In the present study, response surface methodology has been used to optimize turn-assisted deep cold rolling process of AISI 4140 steel. A regression model is developed to predict surface hardness and surface roughness using response surface methodology and central composite design. In the development of predictive model, deep cold rolling force, ball diameter, initial roughness of the workpiece, and number of tool passes are considered as model variables. The rolling force and the ball diameter are the significant factors on the surface hardness and ball diameter and numbers of tool passes are found to be significant for surface roughness. The predicted surface hardness and surface roughness values and the subsequent verification experiments under the optimal operating conditions confirmed the validity of the predicted model. The absolute average error between the experimental and predicted values at the optimal combination of parameter settings for surface hardness and surface roughness is calculated as 0.16% and 1.58% respectively. Using the optimal processing parameters, the surface hardness is improved from 225 to 306 HV, which resulted in an increase in the near surface hardness by about 36% and the surface roughness is improved from 4.84µm to 0.252 µm, which resulted in decrease in the surface roughness by about 95%. The depth of compression is found to be more than 300µm from the microstructure analysis and this is in correlation with the results obtained from the microhardness measurements. Taylor hobson talysurf tester, micro vickers hardness tester, optical microscopy and X-ray diffractometer are used to characterize the modified surface layer.
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.