Abstract: This paper presents an approach which is based on the
use of supervised feed forward neural network, namely multilayer
perceptron (MLP) neural network and finite element method (FEM)
to solve the inverse problem of parameters identification. The
approach is used to identify unknown parameters of ferromagnetic
materials. The methodology used in this study consists in the
simulation of a large number of parameters in a material under test,
using the finite element method (FEM). Both variations in relative
magnetic permeability and electrical conductivity of the material
under test are considered. Then, the obtained results are used to
generate a set of vectors for the training of MLP neural network.
Finally, the obtained neural network is used to evaluate a group of
new materials, simulated by the FEM, but not belonging to the
original dataset. Noisy data, added to the probe measurements is used
to enhance the robustness of the method. The reached results
demonstrate the efficiency of the proposed approach, and encourage
future works on this subject.
Abstract: Management Systems are powerful tools for businesses
to manage quality , environmental and occupational health and safety
requirements . where once these systems were considered as stand
alone control mechanisms , industry is now opting to increase the
efficiency of these documented systems through a more integrated
approach . System integration offers a significant step forward, where
there are similarities between system components , reducing
duplication and adminstration costs and increasing efficiency .
At first , this paper reviews integrated management system structure
and its benefits. The second part of this paper focuses on the one
example implementation of such a system at Imam Khomeini
Hospital and in final part of the paper will be discuss outcomes of
that proccess .
Abstract: Today, transport and logistic systems are often tightly
integrated in the production. Lean production and just-in-time delivering create multiple constraints that have to be fulfilled. As transport networks often have evolved over time they are very
expensive to change. This paper describes a discrete-event-simulation
system which simulates transportation models using real time
resource routing and collision avoidance. It allows for the
specification of own control algorithms and validation of new
strategies. The simulation is integrated into a virtual reality (VR)
environment and can be displayed in 3-D to show the progress.
Simulation elements can be selected through VR metaphors. All data
gathered during the simulation can be presented as a detailed summary afterwards. The included cost-benefit calculation can help to optimize the financial outcome. The operation of this approach is shown by the example of a timber harvest simulation.
Abstract: The objective of this research is to develop the
performance indicators (PIs) in operational level for the Pre-hospital Emergency Medical Service (EMS) system employing in Thailand. This research started with ascertaining the current pre-hospital care
system. The team analyzed the strategies of Narerthorn, a government unit under the ministry of public health, and the existing PIs of the pre-hospital care. Afterwards, the current National Strategic Plan of EMS development (2008-2012) of the Emergency
Medical Institute of Thailand (EMIT) was considered using strategic
analysis to developed Strategy Map (SM) and identified the Success
Factors (SFs). The analysis results from strategy map and SFs were used to develop the Performance Indicators (PIs). To verify the set of
PIs, the team has interviewed with the relevant practitioners for the possibilities to implement the PIs. To this paper, it was to ascertain
that all the developed PIs support the objectives of the strategic plan. Nevertheless, the results showed that the operational level PIs suited
only with the first dimension of National Strategic Plan
(infrastructure and information technology development). Besides,
the SF was the infrastructure development (to contribute the EMS system to people throughout with standard and efficiency both in normally and disaster conditions). Finally, twenty-nine indicators
were developed from the analysis results of SM and SFs.
Abstract: Conventionally the selection of parameters depends
intensely on the operator-s experience or conservative technological
data provided by the EDM equipment manufacturers that assign
inconsistent machining performance. The parameter settings given by
the manufacturers are only relevant with common steel grades. A
single parameter change influences the process in a complex way.
Hence, the present research proposes artificial neural network (ANN)
models for the prediction of surface roughness on first commenced
Ti-15-3 alloy in electrical discharge machining (EDM) process. The
proposed models use peak current, pulse on time, pulse off time and
servo voltage as input parameters. Multilayer perceptron (MLP) with
three hidden layer feedforward networks are applied. An assessment
is carried out with the models of distinct hidden layer. Training of the
models is performed with data from an extensive series of
experiments utilizing copper electrode as positive polarity. The
predictions based on the above developed models have been verified
with another set of experiments and are found to be in good
agreement with the experimental results. Beside this they can be
exercised as precious tools for the process planning for EDM.
Abstract: In this paper a new robust and efficient algorithm to automatic text extraction from colored book and journal cover sheets is proposed. First, we perform wavelet transform. Next for edge detecting from detail wavelet coefficient, we use dynamic threshold. By blurring approximate coefficients with alternative heuristic thresholding, achieve effective edge,. Afterward, with ROI technique get binary image. Finally text boxes would be extracted with new projection profile.
Abstract: In this paper we proposed multistage adaptive
ARQ/HARQ/HARQ scheme. This method combines pure ARQ
(Automatic Repeat reQuest) mode in low channel bit error rate and
hybrid ARQ method using two different Reed-Solomon codes in
middle and high error rate conditions. It follows, that our scheme has
three stages. The main goal is to increase number of states in adaptive
HARQ methods and be able to achieve maximum throughput for
every channel bit error rate. We will prove the proposal by
calculation and then with simulations in land mobile satellite channel
environment. Optimization of scheme system parameters is described
in order to maximize the throughput in the whole defined Signal-to-
Noise Ratio (SNR) range in selected channel environment.
Abstract: This paper describes the design of a real-time audiorange
digital oscilloscope and its implementation in 90nm CMOS
FPGA platform. The design consists of sample and hold circuits,
A/D conversion, audio and video processing, on-chip RAM, clock
generation and control logic. The design of internal blocks and
modules in 90nm devices in an FPGA is elaborated. Also the key
features and their implementation algorithms are presented.
Finally, the timing waveforms and simulation results are put
forward.
Abstract: The main objective of this study is to test the
relationship between numbers of variables representing the firm
characteristics (market-related variables) and the extent of voluntary
disclosure levels (forward-looking disclosure) in the annual reports of
Egyptian firms listed on the Egyptian Stock Exchange. The results
show that audit firm size is significantly positively correlated (in all
the three years) with the level of forward-looking disclosure.
However, industry type variable (which divided to: industries,
cement, construction, petrochemicals and services), is found being
insignificantly association with the level of forward-looking
information disclosed in the annual reports for all the three years.
Abstract: The study deals with the modelling of the gas flow during heliox therapy. A special model has been developed to study the effect of the helium upon the gas flow in the airways during the spontaneous breathing. Lower density of helium compared with air decreases the Reynolds number and it allows improving the flow during the spontaneous breathing. In the cases, where the flow becomes turbulent while the patient inspires air the flow is still laminar when the patient inspires heliox. The use of heliox decreases the work of breathing and improves ventilation. It allows in some cases to prevent the intubation of the patients.
Abstract: Software reliability, defined as the probability of a
software system or application functioning without failure or errors
over a defined period of time, has been an important area of research
for over three decades. Several research efforts aimed at developing
models to improve reliability are currently underway. One of the
most popular approaches to software reliability adopted by some of
these research efforts involves the use of operational profiles to
predict how software applications will be used. Operational profiles
are a quantification of usage patterns for a software application. The
research presented in this paper investigates an innovative multiagent
framework for automatic creation and management of
operational profiles for generic distributed systems after their release
into the market. The architecture of the proposed Operational Profile
MAS (Multi-Agent System) is presented along with detailed
descriptions of the various models arrived at following the analysis
and design phases of the proposed system. The operational profile in
this paper is extended to comprise seven different profiles. Further,
the criticality of operations is defined using a new composed metrics
in order to organize the testing process as well as to decrease the time
and cost involved in this process. A prototype implementation of the
proposed MAS is included as proof-of-concept and the framework is
considered as a step towards making distributed systems intelligent
and self-managing.
Abstract: Physiological control of a left ventricle assist device (LVAD) is generally a complicated task due to diverse operating environments and patient variability. In this work, a tracking control algorithm based on sliding mode and feed forward control for a class of discrete-time single input single output (SISO) nonlinear uncertain systems is presented. The controller was developed to track the reference trajectory to a set operating point without inducing suction in the ventricle. The controller regulates the estimated mean pulsatile flow Qp and mean pulsatility index of pump rotational speed PIω that was generated from a model of the assist device. We recall the principle of the sliding mode control theory then we combine the feed-forward control design with the sliding mode control technique to follow the reference trajectory. The uncertainty is replaced by its upper and lower boundary. The controller was tested in a computer simulation covering two scenarios (preload and ventricular contractility). The simulation results prove the effectiveness and the robustness of the proposed controller
Abstract: Although lots of research work has been done for
human pose recognition, the view-point of cameras is still critical
problem of overall recognition system. In this paper, view-point
insensitive human pose recognition is proposed. The aims of the
proposed system are view-point insensitivity and real-time processing.
Recognition system consists of feature extraction module, neural
network and real-time feed forward calculation. First, histogram-based
method is used to extract feature from silhouette image and it is
suitable for represent the shape of human pose. To reduce the
dimension of feature vector, Principle Component Analysis(PCA) is
used. Second, real-time processing is implemented by using Compute
Unified Device Architecture(CUDA) and this architecture improves
the speed of feed-forward calculation of neural network. We
demonstrate the effectiveness of our approach with experiments on
real environment.
Abstract: Tool wear and surface roughness prediction plays a
significant role in machining industry for proper planning and control
of machining parameters and optimization of cutting conditions. This
paper deals with developing an artificial neural network (ANN)
model as a function of cutting parameters in turning steel under
minimum quantity lubrication (MQL). A feed-forward
backpropagation network with twenty five hidden neurons has been
selected as the optimum network. The co-efficient of determination
(R2) between model predictions and experimental values are 0.9915,
0.9906, 0.9761 and 0.9627 in terms of VB, VM, VS and Ra
respectively. The results imply that the model can be used easily to
forecast tool wear and surface roughness in response to cutting
parameters.
Abstract: This paper presents a method to estimate load profile
in a multiple power flow solutions for every minutes in 24 hours per
day. A method to calculate multiple solutions of non linear profile is
introduced. The Power System Simulation/Engineering (PSS®E) and
python has been used to solve the load power flow. The result of this
power flow solutions has been used to estimate the load profiles for
each load at buses using Independent Component Analysis (ICA)
without any knowledge of parameter and network topology of the
systems. The proposed algorithm is tested with IEEE 69 test bus
system represents for distribution part and the method of ICA has
been programmed in MATLAB R2012b version. Simulation results
and errors of estimations are discussed in this paper.
Abstract: This paper introduces an intelligent system, which can be applied in the monitoring of vehicle speed using a single camera. The ability of motion tracking is extremely useful in many automation problems and the solution to this problem will open up many future applications. One of the most common problems in our daily life is the speed detection of vehicles on a highway. In this paper, a novel technique is developed to track multiple moving objects with their speeds being estimated using a sequence of video frames. Field test has been conducted to capture real-life data and the processed results were presented. Multiple object problems and noisy in data are also considered. Implementing this system in real-time is straightforward. The proposal can accurately evaluate the position and the orientation of moving objects in real-time. The transformations and calibration between the 2D image and the actual road are also considered.
Abstract: Road rage is an increasingly prevalent expression of
aggression in our society. Its dangers are apparent and understanding
its causes may shed light on preventative measures. This study
involved a fifteen-minute survey administered to 147 undergraduate
students at a North Eastern suburban university. The survey
consisted of a demographics section, questions regarding financial
investment in respondents- vehicles, experience driving, habits of
driving, experiences witnessing role models driving, and an
evaluation of road rage behavior using the Driving Vengeance
Questionnaire. The study found no significant differences in driving
aggression between respondents who were financially invested in
their vehicle compared to those who were not, or between
respondents who drove in heavy traffic hours compared to those who
did not, suggesting internal factors correlate with aggressive driving
habits. The study also found significant differences in driving
aggression between males versus females, those with more points on
their license versus fewer points, and those who witnessed parents
driving aggressively very often versus rarely or never. Additional
studies can investigate how witnessing parents driving aggressively
is related to future driving behaviors.
Abstract: In many sensor network applications, sensor nodes are deployed in open environments, and hence are vulnerable to physical attacks, potentially compromising the node's cryptographic keys. False sensing report can be injected through compromised nodes, which can lead to not only false alarms but also the depletion of limited energy resource in battery powered networks. Ye et al. proposed a statistical en-route filtering scheme (SEF) to detect such false reports during the forwarding process. In this scheme, the choice of a security threshold value is important since it trades off detection power and overhead. In this paper, we propose a fuzzy logic for determining a security threshold value in the SEF based sensor networks. The fuzzy logic determines a security threshold by considering the number of partitions in a global key pool, the number of compromised partitions, and the energy level of nodes. The fuzzy based threshold value can conserve energy, while it provides sufficient detection power.
Abstract: The essence of the 21st century is knowledge economy. Knowledge has become the key resource of economic growth and social development. Construction industry is no exception. Because of the characteristic of complexity, project manager can't depend only on information management. The only way to improve the level of construction project management is to set up a kind of effective knowledge accumulation mechanism. This paper first introduced the IFC standard and the concept of ontology. Then put forward the construction method of the architectural engineering domain ontology based on IFC. And finally build up the concepts, properties and the relationship between the concepts of the ontology. The deficiency of this paper is also pointed out.
Abstract: These days we face with so many advertisements in
magazines, those mentioned coaching is pragmatic specialties which
help people make change in their lives. Up to know Specialty coaches
are not necessarily therapists, consultants or psychologist, thus they
may not know psychological theories. The International Coach
Federation identifies "facilitating learning and results" as one of its
four core coach competencies, without understanding learning
theories coaching practice hangs in theoretical abyss. Thus the aim of
this article is investigating learning theories within coaching process.
Therefore, I reviewed some cognitive and behavioral learning
theories and analyzed their contribution with coaching process which
has been introduced in mentor coaches and ICF certified coaches'
papers and books. The result demonstrated that coaching profession
is strongly grounded in learning theories, and it will be strengthened
by the validation of theories and evidence-based research as we move
forward. Thus, it needs more research in order to applying effective
theoretical frameworks.