Abstract: Determination of wellbore problems during a
production/injection process might be evaluated thorough
temperature log analysis. Other applications of this kind of log
analysis may also include evaluation of fluid distribution analysis
along the wellbore and identification of anomalies encountered
during production/injection process. While the accuracy of such
prediction is paramount, the common method of determination of a
wellbore temperature log includes use of steady-state energy balance
equations, which hardly describe the real conditions as observed in
typical oil and gas flowing wells during production operation; and
thus increase level of uncertainties. In this study, a practical method
has been proposed through development of a simplified semianalytical
model to apply for predicting temperature profile along the
wellbore. The developed model includes an overall heat transfer
coefficient accounting all modes of heat transferring mechanism,
which has been focused on the prediction of a temperature profile as
a function of depth for the injection/production wells. The model has
been validated with the results obtained from numerical simulation.
Abstract: Opportunistic network is a kind of Delay Tolerant Networks (DTN) where the nodes in this network come into contact with each other opportunistically and communicate wirelessly and, an end-to-end path between source and destination may have never existed, and disconnection and reconnection is common in the network. In such a network, because of the nature of opportunistic network, perhaps there is no a complete path from source to destination for most of the time and even if there is a path; the path can be very unstable and may change or break quickly. Therefore, routing is one of the main challenges in this environment and, in order to make communication possible in an opportunistic network, the intermediate nodes have to play important role in the opportunistic routing protocols. In this paper we proposed an Adaptive Fuzzy Routing in opportunistic network (AFRON). This protocol is using the simple parameters as input parameters to find the path to the destination node. Using Message Transmission Count, Message Size and Time To Live parameters as input fuzzy to increase delivery ratio and decrease the buffer consumption in the all nodes of network.
Abstract: Recognizing behavioral patterns of financial markets
is essential for traders. Japanese candlestick chart is a common tool to
visualize and analyze such patterns in an economic time series. Since
the world was introduced to Japanese candlestick charting, traders
saw how combining this tool with intelligent technical approaches
creates a powerful formula for the savvy investors.
This paper propose a generalization to box counting method of
Grassberger-Procaccia, which is based on computing the correlation
dimension of Japanese candlesticks instead commonly used 'close'
points. The results of this method applied on several foreign
exchange rates vs. IRR (Iranian Rial). Satisfactorily show lower
chaotic dimension of Japanese candlesticks series than regular
Grassberger-Procaccia method applied merely on close points of
these same candles. This means there is some valuable information
inside candlesticks.
Abstract: This paper proposes a way to track persons by making use of multiple non-overlapping cameras. Tracking persons on multiple non-overlapping cameras enables data communication among cameras through the network connection between a camera and a computer, while at the same time transferring human feature data captured by a camera to another camera that is connected via the network. To track persons with a camera and send the tracking data to another camera, the proposed system uses a hierarchical human model that comprises a head, a torso, and legs. The feature data of the person being modeled are transferred to the server, after which the server sends the feature data of the human model to the cameras connected over the network. This enables a camera that captures a person's movement entering its vision to keep tracking the recognized person with the use of the feature data transferred from the server.
Abstract: This paper presents an effective method for detecting vehicles in front of the camera-assisted car during nighttime driving. The proposed method detects vehicles based on detecting vehicle headlights and taillights using techniques of image segmentation and clustering. First, to effectively extract spotlight of interest, a segmentation process based on automatic multi-level threshold method is applied on the road-scene images. Second, to spatial clustering vehicle of detecting lamps, a grouping process based on light tracking and locating vehicle lighting patterns. For simulation, we are implemented through Da-vinci 7437 DSP board with near infrared mono-camera and tested it in the urban and rural roads. Through the test, classification performances are above 97% of true positive rate evaluated on real-time environment. Our method also has good performance in the case of clear, fog and rain weather.
Abstract: In competitive electricity markets all over the world, an adoption of suitable transmission pricing model is a problem as transmission segment still operates as a monopoly. Transmission pricing is an important tool to promote investment for various transmission services in order to provide economic, secure and reliable electricity to bulk and retail customers. The nodal pricing based on SRMC (Short Run Marginal Cost) is found extremely useful by researchers for sending correct economic signals. The marginal prices must be determined as a part of solution to optimization problem i.e. to maximize the social welfare. The need to maximize the social welfare subject to number of system operational constraints is a major challenge from computation and societal point of views. The purpose of this paper is to present a nodal transmission pricing model based on SRMC by developing new mathematical expressions of real and reactive power marginal prices using GA-Fuzzy based optimal power flow framework. The impacts of selecting different social welfare functions on power marginal prices are analyzed and verified with results reported in literature. Network revenues for two different power systems are determined using expressions derived for real and reactive power marginal prices in this paper.
Abstract: Support Vector Machine (SVM) is a statistical
learning tool that was initially developed by Vapnik in 1979 and later
developed to a more complex concept of structural risk minimization
(SRM). SVM is playing an increasing role in applications to
detection problems in various engineering problems, notably in
statistical signal processing, pattern recognition, image analysis, and
communication systems. In this paper, SVM was applied to the
detection of SAR (synthetic aperture radar) images in the presence of
partially developed speckle noise. The simulation was done for single
look and multi-look speckle models to give a complete overlook and
insight to the new proposed model of the SVM-based detector. The
structure of the SVM was derived and applied to real SAR images
and its performance in terms of the mean square error (MSE) metric
was calculated. We showed that the SVM-detected SAR images have
a very low MSE and are of good quality. The quality of the
processed speckled images improved for the multi-look model.
Furthermore, the contrast of the SVM detected images was higher
than that of the original non-noisy images, indicating that the SVM
approach increased the distance between the pixel reflectivity levels
(the detection hypotheses) in the original images.
Abstract: According to investigating impact of complexity of
stereoscopic frame pairs on stereoscopic video coding and
transmission, a new rate control algorithm is presented. The proposed
rate control algorithm is performed on three levels: stereoscopic group
of pictures (SGOP) level, stereoscopic frame (SFrame) level and
frame level. A temporal-spatial frame complexity model is firstly
established, in the bits allocation stage, the frame complexity, position
significance and reference property between the left and right frames
are taken into account. Meanwhile, the target buffer is set according to
the frame complexity. Experimental results show that the proposed
method can efficiently control the bitrates, and it outperforms the fixed
quantization parameter method from the rate distortion perspective,
and average PSNR gain between rate-distortion curves (BDPSNR) is
0.21dB.
Abstract: In this paper, we propose a fixed formatting method of PPX(Pretty Printer for XML). PPX is a query language for XML database which has extensive formatting capability that produces HTML as the result of a query. The fixed formatting method is to completely specify the combination of variables and layout specification operators within the layout expression of the GENERATE clause of PPX. In the experiment, a quick comparison shows that PPX requires far less description compared to XSLT or XQuery programs doing the same tasks.
Abstract: IEEE 802.15.4a impulse radio-time hopping ultra wide
band (IR-TH UWB) physical layer, due to small duty cycle and very
short pulse widths is robust against multipath propagation. However,
scattering and reflections with the large number of obstacles in indoor
channel environments, give rise to dense multipath fading. It imposes
serious problem to optimum Rake receiver architectures, for which
very large number of fingers are needed. Presence of strong noise
also affects the reception of fine pulses having extremely low power
spectral density. A robust SRake receiver for IEEE 802.15.4a IRTH
UWB in dense multipath and additive white Gaussian noise
(AWGN) is proposed to efficiently recover the weak signals with
much reduced complexity. It adaptively increases the signal to noise
(SNR) by decreasing noise through a recursive least square (RLS)
algorithm. For simulation, dense multipath environment of IEEE
802.15.4a industrial non line of sight (NLOS) is employed. The power
delay profile (PDF) and the cumulative distribution function (CDF)
for the respective channel environment are found. Moreover, the error
performance of the proposed architecture is evaluated in comparison
with conventional SRake and AWGN correlation receivers. The
simulation results indicate a substantial performance improvement
with very less number of Rake fingers.
Abstract: Online Communities are an example of sociallyaware,
self-organising, complex adaptive computing systems.
The multi-agent systems (MAS) paradigm coordinated by
self-organisation mechanisms has been used as an effective
way for the simulation and modeling of such systems. In this
paper, we propose a model for simulating an online health
community using a situated multi-agent system approach,
governed by the co-evolution of the social and spatial
organisations of the agents.
Abstract: In the last few years, the Semantic Web gained scientific acceptance as a means of relationships identification in knowledge base, widely known by semantic association. Query about complex relationships between entities is a strong requirement for many applications in analytical domains. In bioinformatics for example, it is critical to extract exchanges between proteins. Currently, the widely known result of such queries is to provide paths between connected entities from data graph. However, they do not always give good results while facing the user need by the best association or a set of limited best association, because they only consider all existing paths but ignore the path evaluation. In this paper, we present an approach for supporting association discovery queries. Our proposal includes (i) a query language PmSPRQL which provides a multiparadigm query expressions for association extraction and (ii) some quantification measures making easy the process of association ranking. The originality of our proposal is demonstrated by a performance evaluation of our approach on real world datasets.
Abstract: Various solar energy technologies exist and they have
different application techniques in the generation of electrical power.
The widespread use of photovoltaic (PV) modules in such
technologies has been limited by relatively high costs and low
efficiencies. The efficiency of PV panels decreases as the operating
temperatures increase. This is due to the affect of solar intensity and
ambient temperature. In this work, Computational Fluid Dynamics
(CFD) was used to model the heat transfer from a standard PV panel
and thus determine the rate of dissipation of heat. To accurately
model the specific climatic conditions of the United Arab Emirates
(UAE), a case study of a new build green building in Dubai was
used. A finned heat pipe arrangement is proposed and analyzed to
determine the improved heat dissipation and thus improved
performance efficiency of the PV panel. A prototype of the
arrangement is built for experimental testing to validate the CFD
modeling and proof of concept.
Abstract: This research presents a system for post processing of
data that takes mined flat rules as input and discovers crisp as well as
fuzzy hierarchical structures using Learning Classifier System
approach. Learning Classifier System (LCS) is basically a machine
learning technique that combines evolutionary computing,
reinforcement learning, supervised or unsupervised learning and
heuristics to produce adaptive systems. A LCS learns by interacting
with an environment from which it receives feedback in the form of
numerical reward. Learning is achieved by trying to maximize the
amount of reward received. Crisp description for a concept usually
cannot represent human knowledge completely and practically. In the
proposed Learning Classifier System initial population is constructed
as a random collection of HPR–trees (related production rules) and
crisp / fuzzy hierarchies are evolved. A fuzzy subsumption relation is
suggested for the proposed system and based on Subsumption Matrix
(SM), a suitable fitness function is proposed. Suitable genetic
operators are proposed for the chosen chromosome representation
method. For implementing reinforcement a suitable reward and
punishment scheme is also proposed. Experimental results are
presented to demonstrate the performance of the proposed system.
Abstract: This study aims to investigate how much both son and
daughter trust their father and what are the underlying reasons they
trust their father. The results revealed five main reasons why
Malaysian adolescents trust their father. Those reasons are related to
the role of father, father-child relationship, father-s characteristics,
father-s nurturing nature and father-s attitude and behavior. A total of
1022 students (males = 241, females = 781) from one of public
university in Sabah, Malaysia participated in the study. The
participants completed open-ended questionnaires developed by Kim
(2008), asking how much the adolescents trust their father, and the
reasons why they trust their father. The data was analysed by using
the indigenous psychology method proposed by [1] Findings of this
study revealed the pattern of trust towards father for both Malaysian
male and female adolescents. The results contributed new
information about Malaysian adolescents- trust towards their father
form the indigenous context. The implications of finding will be
discussed.
Abstract: The counter flow solar air heaters, with four
transverse fins and wire mesh layers are constructed and investigated
experimentally for thermal efficiency at a geographic location of
Cyprus in the city of Famagusta. The absorber plate is replaced by
sixteen steel wire mesh layers, 0.18 x 0.18cm in cross section
opening and a 0.02cm in diameter. The wire mesh layers arranged in
three groups, first and second include 6 layers, while the third include
4 layers. All layers fixed in the duct parallel to the glazing and each
group separated from the others by wood frame thickness of 0.5cm to
reduce the pressure drop. The transverse fins arranged in a way to
force the air to flow through the bed like eight letter path with flow
depth 3cm. The proposed design has increased the heat transfer rate,
but on other hand causes a high pressure drop. The obtained results
show that, for air mass flow rate range between 0.011-0.036kg/s, the
thermal efficiency increases with increasing the air mass flow. The
maximum efficiency obtained is 65.6% for the mass flow rate of
0.036kg/s. Moreover, the temperature difference between the outlet
flow and the ambient temperature, ΔT, reduces as the air mass flow
rate increase. The maximum difference between the outlet and
ambient temperature obtained was 43°C for double pass for minimum
mass flow rate of 0.011kg/s. Comparison with a conventional solar
air heater collector shows a significantly development in the thermal
efficiency.
Abstract: In manufacturing industries, development of measurement leads to increase the number of monitoring variables and eventually the importance of multivariate control comes to the fore. Statistical process control (SPC) is one of the most widely used as multivariate control chart. Nevertheless, SPC is restricted to apply in processes because its assumption of data as following specific distribution. Unfortunately, process data are composed by the mixture of several processes and it is hard to estimate as one certain distribution. To alternative conventional SPC, therefore, nonparametric control chart come into the picture because of the strength of nonparametric control chart, the absence of parameter estimation. SVDD based control chart is one of the nonparametric control charts having the advantage of flexible control boundary. However,basic concept of SVDD has been an oversight to the important of data characteristic, density distribution. Therefore, we proposed DW-SVDD (Density Weighted SVDD) to cover up the weakness of conventional SVDD. DW-SVDD makes a new attempt to consider dense of data as introducing the notion of density Weight. We extend as control chart using new proposed SVDD and a simulation study of various distributional data is conducted to demonstrate the improvement of performance.
Abstract: The fault current levels through the electric devices
have a significant impact on failure probability. New fault current
results in exceeding the rated capacity of circuit breaker and switching
equipments and changes operation characteristic of overcurrent relay.
In order to solve these problems, SFCL (Superconducting Fault
Current Limiter) has rising as one of new alternatives so as to improve
these problems. A fault current reduction differs depending on
installed location. Therefore, a location of SFCL is very important.
Also, SFCL decreases the fault current, and it prevents surrounding
protective devices to be exposed to fault current, it then will bring a
change of reliability. In this paper, we propose method which
determines the optimal location when SFCL is installed in power
system. In addition, the reliability about the power system which
SFCL was installed is evaluated. The efficiency and effectiveness of
this method are also shown by numerical examples and the reliability
indices are evaluated in this study at each load points. These results
show a reliability change of a system when SFCL was installed.
Abstract: Recordings from recent earthquakes have provided evidence that ground motions in the near field of a rupturing fault differ from ordinary ground motions, as they can contain a large energy, or “directivity" pulse. This pulse can cause considerable damage during an earthquake, especially to structures with natural periods close to those of the pulse. Failures of modern engineered structures observed within the near-fault region in recent earthquakes have revealed the vulnerability of existing RC buildings against pulse-type ground motions. This may be due to the fact that these modern structures had been designed primarily using the design spectra of available standards, which have been developed using stochastic processes with relatively long duration that characterizes more distant ground motions. Many recently designed and constructed buildings may therefore require strengthening in order to perform well when subjected to near-fault ground motions. Fiber Reinforced Polymers are considered to be a viable alternative, due to their relatively easy and quick installation, low life cycle costs and zero maintenance requirements. The objective of this paper is to investigate the adequacy of Artificial Neural Networks (ANN) to determine the three dimensional dynamic response of FRP strengthened RC buildings under the near-fault ground motions. For this purpose, one ANN model is proposed to estimate the base shear force, base bending moments and roof displacement of buildings in two directions. A training set of 168 and a validation set of 21 buildings are produced from FEA analysis results of the dynamic response of RC buildings under the near-fault earthquakes. It is demonstrated that the neural network based approach is highly successful in determining the response.
Abstract: The changing economic climate has made global
manufacturing a growing reality over the last decade, forcing
companies from east and west and all over the world to
collaborate beyond geographic boundaries in the design,
manufacture and assemble of products. The ISO10303 and
ISO14649 Standards (STEP and STEP-NC) have been
developed to introduce interoperability into manufacturing
enterprises so as to meet the challenge of responding to
production on demand. This paper describes and illustrates a
STEP compliant CAD/CAPP/CAM System for the manufacture
of rotational parts on CNC turning centers. The information
models to support the proposed system together with the data
models defined in the ISO14649 standard used to create the NC
programs are also described. A structured view of a STEP
compliant CAD/CAPP/CAM system framework supporting the
next generation of intelligent CNC controllers for turn/mill
component manufacture is provided. Finally a proposed
computational environment for a STEP-NC compliant system
for turning operations (SCSTO) is described. SCSTO is the
experimental part of the research supported by the specification
of information models and constructed using a structured
methodology and object-oriented methods. SCSTO was
developed to generate a Part 21 file based on machining
features to support the interactive generation of process plans
utilizing feature extraction. A case study component has been
developed to prove the concept for using the milling and turning
parts of ISO14649 to provide a turn-mill CAD/CAPP/CAM
environment.