Abstract: The aim of this study is to emphasize the opportunities in space design under the aspect of HCI as performance areas. HCI is a multidisciplinary approach that could be identified in many different areas. The aesthetical reflections of HCI by virtual reality in space design are the high-tech solutions of the new innovations as computational facilities by artistic features. The method of this paper is to identify the subject in 3 main parts. In the first part a general approach and definition of interactivity on the basis of space design; in the second part the concept of multimedia interactive theater by some chosen samples from the world and interactive design aspects; in the third part the samples from Turkey will be identified by stage designing principles. In the results it could be declared that the multimedia database is the virtual approach of theatre stage designing regarding interactive means by computational facilities according to aesthetical aspects. HCI is mostly identified in theatre stages as computational intelligence under the affect of interactivity.
Abstract: The Carrier Frequency Offset (CFO) due to timevarying
fading channel is the main cause of the loss of orthogonality
among OFDM subcarriers which is linked to inter-carrier interference
(ICI). Hence, it is necessary to precisely estimate and compensate the
CFO. Especially for mobile broadband communications, CFO and
channel gain also have to be estimated and tracked to maintain the
system performance. Thus, synchronization pilots are embedded in
every OFDM symbol to track the variations. In this paper, we present
the pilot scheme for both channel and CFO estimation where channel
estimation process can be carried out with only one OFDM symbol.
Additional, the proposed pilot scheme also provides better
performance in CFO estimation comparing with the conventional
orthogonal pilot scheme due to the increasing of signal-tointerference
ratio.
Abstract: School leadership is commonly considered to have a
significant influence on school effectiveness and improvement.
Effective school leaders are expected to successfully introduce and
support change and innovation at the school unit. Despite an
abundance of studies on educational leadership, very few studies
have provided evidence on the link between leadership models, and
specific educational and school outcomes. This is true of a popular
contemporary approach to leadership, namely, distributed leadership.
The paper provides an overview of research findings on the effect of
distributed leadership on educational outcomes. The theoretical basis
for this approach to leadership is presented, with reference to
methodological and research limitations. The paper discusses
research findings and draws their implications for educational
research on school leadership.
Abstract: The solvated electron is self-trapped (polaron) owing
to strong interaction with the quantum polarization field. If the
electron and quantum field are strongly coupled then the collective
localized state of the field and quasi-particle is formed. In such a
formation the electron motion is rather intricate. On the one hand the
electron oscillated within a rather deep polarization potential well
and undergoes the optical transitions, and on the other, it moves
together with the center of inertia of the system and participates in
the thermal random walk. The problem is to separate these motions
correctly, rigorously taking into account the conservation laws. This
can be conveniently done using Bogolyubov-Tyablikov method of
canonical transformation to the collective coordinates. This
transformation removes the translational degeneracy and allows one
to develop the successive approximation algorithm for the energy and
wave function while simultaneously fulfilling the law of conservation
of total momentum of the system. The resulting equations determine
the electron transitions and depend explicitly on the translational
velocity of the quasi-particle as whole. The frequency of optical
transition is calculated for the solvated electron in ammonia, and an
estimate is made for the thermal-induced spectral bandwidth.
Abstract: This paper presents one of the best applications of wireless sensor network for campus Monitoring. With the help of PIR sensor, temperature sensor and humidity sensor, effective utilization of energy resources has been implemented in one of rooms of Sharda University, Greater Noida, India. The RISC microcontroller is used here for analysis of output of sensors and providing proper control using ZigBee protocol. This wireless sensor module presents a tremendous power saving method for any campus
Abstract: Electric vehicles are considered as technology which
can significantly reduce the problems related to road transport such
as increasing GHG emissions, air pollutions and energy import
dependency.
The core objective of this paper is to analyze the current energetic,
ecological and economic characteristics of different types of electric
vehicles.
The major conclusions of this analysis are: The high investments
cost are the major barrier for broad market breakthrough of battery
electric vehicles and fuel cell vehicles. For battery electric vehicles
also the limited driving range states a key obstacle. The analyzed
hybrids could in principle serve as a bridging technology. However,
due to their tank-to-wheel emissions they cannot state a proper
solution for urban areas.
Finally, the most important perception is that also battery electric
vehicles and fuel cell vehicles are environmentally benign solution if
the primary fuel source is renewable.
Abstract: In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.
Abstract: Conception is the primordial part in the realization of
a computer system. Several tools have been used to help inventors to
describe their software. These tools knew a big success in the
relational databases domain since they permit to generate SQL script
modeling the database from an Entity/Association model. However,
with the evolution of the computer domain, the relational databases
proved their limits and object-relational model became used more
and more. Tools of present conception don't support all new concepts
introduced by this model and the syntax of the SQL3 language. We
propose in this paper a tool of help to the conception and
implementation of object-relational databases called «NAVIGTOOLS"
that allows the user to generate script modeling its database
in SQL3 language. This tool bases itself on the Entity/Association
and navigational model for modeling the object-relational databases.
Abstract: In many data mining applications, it is a priori known
that the target function should satisfy certain constraints imposed
by, for example, economic theory or a human-decision maker. In this
paper we consider partially monotone prediction problems, where the
target variable depends monotonically on some of the input variables
but not on all. We propose a novel method to construct prediction
models, where monotone dependences with respect to some of
the input variables are preserved by virtue of construction. Our
method belongs to the class of mixture models. The basic idea is to
convolute monotone neural networks with weight (kernel) functions
to make predictions. By using simulation and real case studies,
we demonstrate the application of our method. To obtain sound
assessment for the performance of our approach, we use standard
neural networks with weight decay and partially monotone linear
models as benchmark methods for comparison. The results show that
our approach outperforms partially monotone linear models in terms
of accuracy. Furthermore, the incorporation of partial monotonicity
constraints not only leads to models that are in accordance with the
decision maker's expertise, but also reduces considerably the model
variance in comparison to standard neural networks with weight
decay.
Abstract: The application of Neural Network for disease
diagnosis has made great progress and is widely used by physicians.
An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which
was the great motivation towards our study. In our work, tachycardia
features obtained are used for the training and testing of a Neural
Network. In this study we are using Fuzzy Probabilistic Neural
Networks as an automatic technique for ECG signal analysis. As
every real signal recorded by the equipment can have different
artifacts, we needed to do some preprocessing steps before feeding it
to our system. Wavelet transform is used for extracting the
morphological parameters of the ECG signal. The outcome of the
approach for the variety of arrhythmias shows the represented
approach is superior than prior presented algorithms with an average
accuracy of about %95 for more than 7 tachy arrhythmias.
Abstract: The H.264/AVC standard is a highly efficient video
codec providing high-quality videos at low bit-rates. As employing
advanced techniques, the computational complexity has been
increased. The complexity brings about the major problem in the
implementation of a real-time encoder and decoder. Parallelism is the
one of approaches which can be implemented by multi-core system.
We analyze macroblock-level parallelism which ensures the same bit
rate with high concurrency of processors. In order to reduce the
encoding time, dynamic data partition based on macroblock region is
proposed. The data partition has the advantages in load balancing and
data communication overhead. Using the data partition, the encoder
obtains more than 3.59x speed-up on a four-processor system. This
work can be applied to other multimedia processing applications.
Abstract: This paper describes a study of geometrically
nonlinear free vibration of thin circular functionally graded (CFGP)
plates resting on Winkler elastic foundations. The material properties
of the functionally graded composites examined here are assumed to
be graded smoothly and continuously through the direction of the
plate thickness according to a power law and are estimated using the
rule of mixture. The theoretical model is based on the classical Plate
theory and the Von-Kármán geometrical nonlinearity assumptions.
An homogenization procedure (HP) is developed to reduce the
problem considered here to that of isotropic homogeneous circular
plates resting on Winkler foundation. Hamilton-s principle is applied
and a multimode approach is derived to calculate the fundamental
nonlinear frequency parameters which are found to be in a good
agreement with the published results. On the other hand, the
influence of the foundation parameters on the nonlinear fundamental
frequency has also been analysed.
Abstract: Emerging Bio-engineering fields such as Brain
Computer Interfaces, neuroprothesis devices and modeling and
simulation of neural networks have led to increased research activity
in algorithms for the detection, isolation and classification of Action
Potentials (AP) from noisy data trains. Current techniques in the field
of 'unsupervised no-prior knowledge' biosignal processing include
energy operators, wavelet detection and adaptive thresholding. These
tend to bias towards larger AP waveforms, AP may be missed due to
deviations in spike shape and frequency and correlated noise
spectrums can cause false detection. Also, such algorithms tend to
suffer from large computational expense.
A new signal detection technique based upon the ideas of phasespace
diagrams and trajectories is proposed based upon the use of a
delayed copy of the AP to highlight discontinuities relative to
background noise. This idea has been used to create algorithms that
are computationally inexpensive and address the above problems.
Distinct AP have been picked out and manually classified from
real physiological data recorded from a cockroach. To facilitate
testing of the new technique, an Auto Regressive Moving Average
(ARMA) noise model has been constructed bases upon background
noise of the recordings. Along with the AP classification means this
model enables generation of realistic neuronal data sets at arbitrary
signal to noise ratio (SNR).
Abstract: A two dimensional three segments coupled pendulum system that mathematically models human arm configuration was developed along with constructing and solving the equations of motions for this model using the energy (work) based approach of Lagrange. The equations of motion of the model were solved iteratively both as an initial value problem and as a two point boundary value problem. In the initial value problem solutions, both the initial system configuration (segment angles) and initial system velocity (segment angular velocities) were used as inputs, whereas, in the two point boundary value problem solutions initial and final configurations and time were used as inputs to solve for the trajectory of motion. The results suggest that the model solutions are sensitive to small changes in the dynamic forces applied to the system as well as to the initial and boundary conditions used. To overcome the system sensitivity a new approach is suggested.
Abstract: This paper presents the applications of computational intelligence techniques to economic load dispatch problems. The fuel cost equation of a thermal plant is generally expressed as continuous quadratic equation. In real situations the fuel cost equations can be discontinuous. In view of the above, both continuous and discontinuous fuel cost equations are considered in the present paper. First, genetic algorithm optimization technique is applied to a 6- generator 26-bus test system having continuous fuel cost equations. Results are compared to conventional quadratic programming method to show the superiority of the proposed computational intelligence technique. Further, a 10-generator system each with three fuel options distributed in three areas is considered and particle swarm optimization algorithm is employed to minimize the cost of generation. To show the superiority of the proposed approach, the results are compared with other published methods.
Abstract: In order to define a new model of Tunisian foot
sizes and for building the most comfortable shoes, Tunisian
industrialists must be able to offer for their customers products able
to put on and adjust the majority of the target population concerned.
Moreover, the use of models of shoes, mainly from others
country, causes a mismatch between the foot and comfort of the
Tunisian shoes.
But every foot is unique; these models become uncomfortable for
the Tunisian foot. We have a set of measures produced from a
3D scan of the feet of a diverse population (women, men ...) and we
try to analyze this data to define a model of foot specific to the
Tunisian footwear design.
In this paper we propose tow new approaches to modeling a new
foot sizes model. We used, indeed, the neural networks, and specially
the Kohonen network.
Next, we combine neural networks with the concept of half-foot
size to improve the models already found. Finally, it was necessary to
compare the results obtained by applying each approach and we
decide what-s the best approach that give us the most model of foot
improving more comfortable shoes.
Abstract: A theory for optimal filtering of infinite sets of random
signals is presented. There are several new distinctive features of the
proposed approach. First, a single optimal filter for processing any
signal from a given infinite signal set is provided. Second, the filter is
presented in the special form of a sum with p terms where each term
is represented as a combination of three operations. Each operation
is a special stage of the filtering aimed at facilitating the associated
numerical work. Third, an iterative scheme is implemented into the
filter structure to provide an improvement in the filter performance at
each step of the scheme. The final step of the scheme concerns signal
compression and decompression. This step is based on the solution of
a new rank-constrained matrix approximation problem. The solution
to the matrix problem is described in this paper. A rigorous error
analysis is given for the new filter.
Abstract: Synchronization is a difficult problem in CDMA
satellite communications. Due to the influence of additive noise and
fading in the mobile channel, it is not easy to keep up with the
attenuation and offset. This paper considers a recently proposed
approach to solve the problem of synchronization chaotic Chen
system in CDMA satellite communication in the presence of constant
attenuation and offset. An analytic algorithm that provides closed
form channel and carrier offset estimates is presented. The principle
of this approach is based on adding a compensation block before the
receiver to compensate the distortion of the imperfect channel by
using genetic algorithm.
The resultants presented, show that the receiver is able to recover
rapidly the synchronization with the transmitter.
Abstract: Eco-driving allows the driver to optimize his/her behaviour in order to achieve several types of benefits: reducing pollution emissions, increasing road safety, and fuel saving. One of the main rules for adopting eco-driving is to anticipate the traffic events by avoiding strong acceleration or braking and maintaining a steady speed when possible. Therefore, drivers have to comply with speed limits and time headway. The present study explored the role of three types of motivation and social norms in predicting French drivers- intentions to comply with speed limits and time headway as eco-driving practices as well as examine the variations according to gender and age. 1234 drivers with ages between 18 and 75 years old filled in a questionnaire which was presented as part of an online survey aiming to better understand the drivers- road habits. It included items assessing: a) behavioural intentions to comply with speed limits and time headway according to three types of motivation: reducing pollution emissions, increasing road safety, and fuel saving, b) subjective and descriptive social norms regarding the intention to comply with speed limits and time headway, and c) sociodemographical variables. Drivers expressed their intention to frequently comply with speed limits and time headway in the following 6 months; however, they showed more intention to comply with speed limits as compared to time headway regardless of the type of motivation. The subjective injunctive norms were significantly more important in predicting drivers- intentions to comply with speed limits and time headway as compared to the descriptive norms. In addition, the most frequently reported type of motivation for complying with speed limits and time headway was increasing road safety followed by fuel saving and reducing pollution emissions, hence underlining a low motivation to practice eco-driving. Practical implications of the results are discussed.
Abstract: Modern manufacturing facilities are large scale,
highly complex, and operate with large number of variables under
closed loop control. Early and accurate fault detection and diagnosis
for these plants can minimise down time, increase the safety of plant
operations, and reduce manufacturing costs. Fault detection and
isolation is more complex particularly in the case of the faulty analog
control systems. Analog control systems are not equipped with
monitoring function where the process parameters are continually
visualised. In this situation, It is very difficult to find the relationship
between the fault importance and its consequences on the product
failure. We consider in this paper an approach to fault detection and
analysis of its effect on the production quality using an adaptive
centring and scaling in the pickling process in cold rolling. The fault
appeared on one of the power unit driving a rotary machine, this
machine can not track a reference speed given by another machine.
The length of metal loop is then in continuous oscillation, this affects
the product quality. Using a computerised data acquisition system,
the main machine parameters have been monitored. The fault has
been detected and isolated on basis of analysis of monitored data.
Normal and faulty situation have been obtained by an artificial neural
network (ANN) model which is implemented to simulate the normal
and faulty status of rotary machine. Correlation between the product
quality defined by an index and the residual is used to quality
classification.