Abstract: This study links up the theories of social psychology,
economics and sport management to assess the impact of sport
participation on subjective well-being (SWB) and use a simple statistic
method to estimate the relative monetary value that sport participation
derives SWB for Taiwan-s college students. By constructing proper
measurements on sport participation and SWB respectively, a
structural equation model (SEM) is developed to perform a
confirmatory factory analysis, and the causal relationship between
sport participation and SWB as well as the effect of the demographic
variables on these two concepts are also discussed.
Abstract: This paper is aimed at describing a delay-based endto-
end (e2e) congestion control algorithm, called Very FAST TCP
(VFAST), which is an enhanced version of FAST TCP. The main
idea behind this enhancement is to smoothly estimate the Round-Trip
Time (RTT) based on a nonlinear filter, which eliminates throughput
and queue oscillation when RTT fluctuates. In this context, an evaluation
of the suggested scheme through simulation is introduced, by
comparing our VFAST prototype with FAST in terms of throughput,
queue behavior, fairness, stability, RTT and adaptivity to changes in
network. The achieved simulation results indicate that the suggested
protocol offer better performance than FAST TCP in terms of RTT
estimation and throughput.
Abstract: The paper deals with determination of electromagnetic
and temperature field distribution of induction heating system used
for pipe brazing. The problem is considered as coupled – time
harmonic electromagnetic and transient thermal field. It has been
solved using finite element method. The detailed maps of
electromagnetic and thermal field distribution have been obtained.
The good understanding of the processes in the considered system
ensures possibilities for control, management and increasing the
efficiency of the welding process.
Abstract: Cloud Computing is an approach that provides computation and storage services on-demand to clients over the network, independent of device and location. In the last few years, cloud computing became a trend in information technology with many companies that transfer their business processes and applications in the cloud. Cloud computing with service oriented architecture has contributed to rapid development of Geographic Information Systems. Open Geospatial Consortium with its standards provides the interfaces for hosted spatial data and GIS functionality to integrated GIS applications. Furthermore, with the enormous processing power, clouds provide efficient environment for data intensive applications that can be performed efficiently, with higher precision, and greater reliability. This paper presents our work on the geospatial data services within the cloud computing environment and its technology. A cloud computing environment with the strengths and weaknesses of the geographic information system will be introduced. The OGC standards that solve our application interoperability are highlighted. Finally, we outline our system architecture with utilities for requesting and invoking our developed data intensive applications as a web service.
Abstract: Developing techniques for mobile robot navigation constitutes one of the major trends in the current
research on mobile robotics. This paper develops a local
model network (LMN) for mobile robot navigation. The
LMN represents the mobile robot by a set of locally valid
submodels that are Multi-Layer Perceptrons (MLPs).
Training these submodels employs Back Propagation (BP) algorithm. The paper proposes the fuzzy C-means (FCM) in this scheme to divide the input space to sub regions, and then a submodel (MLP) is identified to represent a particular
region. The submodels then are combined in a unified
structure. In run time phase, Radial Basis Functions (RBFs) are employed as windows for the activated submodels. This
proposed structure overcomes the problem of changing operating regions of mobile robots. Read data are used in all experiments. Results for mobile robot navigation using the
proposed LMN reflect the soundness of the proposed
scheme.
Abstract: The evaluation of unit cell neutronic parameters and
lifetime for some innovant reactors without on sit-refuling will be
held in this work. the behavior of some small and medium reactors
without on site refueling with triso and cermet fuel. For the FBNR
long life except we propose to change the enrichment of the Cermet
MFE to 9%. For the AFPR reactor we can see that the use of the
Cermet MFE can extend the life of this reactor but to maintain the
same life period for AFPR-SC we most use burnup poison to have the
same slope for Kinf (Burnup). PFPWR50 cell behaves almost in
same way using both fuels Cermet and TRISO. So we can conclude
that PFPWR50 reactor, with CERMET Fuel, is kept among the long
cycle reactors and with the new configuration we avoid subcriticality
at the beginning of cycle. The evaluation of unit cell neutronic
parameters reveals a good agreement with the goal of BWR-PB
concept. It is found out that the Triso fuel assembly lifetime can be
extended for a reasonably long period without being refueled,
approximately up to 48GWd/t burnup. Using coated particles fuels
with the Cermet composition can be more extended the fuel assembly
life time, approximately 52 GWd/t.
Abstract: In this paper, a model of self-organizing spiking neural networks is introduced and applied to mobile robot environment representation and path planning problem. A network of spike-response-model neurons with a recurrent architecture is used to create robot-s internal representation from surrounding environment. The overall activity of network simulates a self-organizing system with unsupervised learning. A modified A* algorithm is used to find the best path using this internal representation between starting and goal points. This method can be used with good performance for both known and unknown environments.
Abstract: Project selection problems on management
information system (MIS) are often considered a multi-criteria
decision-making (MCDM) for a solving method. These problems
contain two aspects, such as interdependencies among criteria and
candidate projects and qualitative and quantitative factors of projects.
However, most existing methods reported in literature consider these
aspects separately even though these two aspects are simultaneously
incorporated. For this reason, we proposed a hybrid method using
analytic network process (ANP) and fuzzy logic in order to represent
both aspects. We then propose a goal programming model to conduct
an optimization for the project selection problems interpreted by a
hybrid concept. Finally, a numerical example is conducted as
verification purposes.
Abstract: The accelerated growth in aircraft industries desire
effectual schemes, programs, innovative designs of advanced systems
to accomplishing the augmenting need for home-free air
transportation. In this paper, a contemporary conceptual design of an
airplane has been proposed without landing gear systems in order to
reducing accidents, time consumption, and to eliminating drawbacks
by using superconducting levitation phenomenon. This invention of
an airplane with superconductive material coating, on the solar plexus
region assist to reduce weight by approximately 4% of the total takeoff
weight, and cost effective. Moreover, we conjectured that
superconductor landing system reduces ground friction, mission fuel,
total drag, take-off and landing distance.
Abstract: In today-s information age, numbers of organizations
are still arguing on capitalizing the values of Information Technology
(IT) and Knowledge Management (KM) to which individuals can
benefit from and effective communication among the individuals can
be established. IT exists in enabling positive improvement for
communication among knowledge workers (k-workers) with a
number of social network technology domains at workplace. The
acceptance of digital discourse in sharing of knowledge and
facilitating the knowledge and information flows at most of the
organizations indeed impose the culture of knowledge sharing in
Digital Social Networks (DSN). Therefore, this study examines
whether the k-workers with IT background would confer an effect on
the three knowledge characteristics -- conceptual, contextual, and
operational. Derived from these three knowledge characteristics, five
potential factors will be examined on the effects of knowledge
exchange via e-mail domain as the chosen query. It is expected, that
the results could provide such a parameter in exploring how DSN
contributes in supporting the k-workers- virtues, performance and
qualities as well as revealing the mutual point between IT and KM.
Abstract: Over last two decades, due to hostilities of environment
over the internet the concerns about confidentiality of information
have increased at phenomenal rate. Therefore to safeguard the information
from attacks, number of data/information hiding methods have
evolved mostly in spatial and transformation domain.In spatial domain
data hiding techniques,the information is embedded directly on
the image plane itself. In transform domain data hiding techniques the
image is first changed from spatial domain to some other domain and
then the secret information is embedded so that the secret information
remains more secure from any attack. Information hiding algorithms
in time domain or spatial domain have high capacity and relatively
lower robustness. In contrast, the algorithms in transform domain,
such as DCT, DWT have certain robustness against some multimedia
processing.In this work the authors propose a novel steganographic
method for hiding information in the transform domain of the gray
scale image.The proposed approach works by converting the gray
level image in transform domain using discrete integer wavelet
technique through lifting scheme.This approach performs a 2-D
lifting wavelet decomposition through Haar lifted wavelet of the cover
image and computes the approximation coefficients matrix CA and
detail coefficients matrices CH, CV, and CD.Next step is to apply the
PMM technique in those coefficients to form the stego image. The
aim of this paper is to propose a high-capacity image steganography
technique that uses pixel mapping method in integer wavelet domain
with acceptable levels of imperceptibility and distortion in the cover
image and high level of overall security. This solution is independent
of the nature of the data to be hidden and produces a stego image
with minimum degradation.
Abstract: ZnO nanocrystals with mean diameter size 14 nm
have been prepared by precipitation method, and examined as
photocatalyst for the UV-induced degradation of insecticide diazinon
as deputy of organic pollutant in aqueous solution. The effects of
various parameters, such as illumination time, the amount of
photocatalyst, initial pH values and initial concentration of
insecticide on the photocatalytic degradation diazinon were
investigated to find desired conditions. In this case, the desired
parameters were also tested for the treatment of real water containing
the insecticide. Photodegradation efficiency of diazinon was
compared between commercial and prepared ZnO nanocrystals. The
results indicated that UV/ZnO process applying prepared
nanocrystalline ZnO offered electrical energy efficiency and
quantum yield better than commercial ZnO. The present study, on the
base of Langmuir-Hinshelwood mechanism, illustrated a pseudo
first-order kinetic model with rate constant of surface reaction equal
to 0.209 mg l-1 min-1 and adsorption equilibrium constant of 0.124 l
mg-1.
Abstract: A new approach for protection of power transformer is
presented using a time-frequency transform known as Wavelet transform.
Different operating conditions such as inrush, Normal, load,
External fault and internal fault current are sampled and processed
to obtain wavelet coefficients. Different Operating conditions provide
variation in wavelet coefficients. Features like energy and Standard
deviation are calculated using Parsevals theorem. These features
are used as inputs to PNN (Probabilistic neural network) for fault
classification. The proposed algorithm provides more accurate results
even in the presence of noise inputs and accurately identifies inrush
and fault currents. Overall classification accuracy of the proposed
method is found to be 96.45%. Simulation of the fault (with and
without noise) was done using MATLAB AND SIMULINK software
taking 2 cycles of data window (40 m sec) containing 800 samples.
The algorithm was evaluated by using 10 % Gaussian white noise.
Abstract: To meet the demands of wireless sensor networks
(WSNs) where data are usually aggregated at a single source prior to
transmitting to any distant user, there is a need to establish a tree
structure inside any given event region. In this paper , a novel
technique to create one such tree is proposed .This tree preserves the
energy and maximizes the lifetime of event sources while they are
constantly transmitting for data aggregation. The term Decentralized
Lifetime Maximizing Tree (DLMT) is used to denote this tree.
DLMT features in nodes with higher energy tend to be chosen as data
aggregating parents so that the time to detect the first broken tree link
can be extended and less energy is involved in tree maintenance. By
constructing the tree in such a way, the protocol is able to reduce the
frequency of tree reconstruction, minimize the amount of data loss
,minimize the delay during data collection and preserves the energy.
Abstract: Telemedicine is brought to life by contemporary changes of our world and summarizes the entire range of services that are at the crossroad of traditional healthcare and information technology. It is believed that eHealth can help in solving critical issues of rising costs, care for ageing and housebound population, staff shortage. It is a feasible tool to provide routine as well as specialized health service as it has the potential to improve both the access to and the standard of care. eHealth is no more an optional choice. It has already made quite a way but it still remains a fantastic challenge for the future requiring cooperation and coordination at all possible levels. The strategic objectives of this paper are: 1. To start with an attempt to clarify the mass of terms used nowadays; 2. To answer the question “Who needs eHealth"; 3. To focus on the necessity of bridging telemedicine and medical (health) informatics as well as on the dual relationship between them; as well as 4. To underline the need of networking in understanding, developing and implementing eHealth.
Abstract: In this paper a novel approach for generalized image
retrieval based on semantic contents is presented. A combination of
three feature extraction methods namely color, texture, and edge
histogram descriptor. There is a provision to add new features in
future for better retrieval efficiency. Any combination of these
methods, which is more appropriate for the application, can be used
for retrieval. This is provided through User Interface (UI) in the
form of relevance feedback. The image properties analyzed in this
work are by using computer vision and image processing algorithms.
For color the histogram of images are computed, for texture cooccurrence
matrix based entropy, energy, etc, are calculated and for
edge density it is Edge Histogram Descriptor (EHD) that is found.
For retrieval of images, a novel idea is developed based on greedy
strategy to reduce the computational complexity. The entire system
was developed using AForge.Imaging (an open source product),
MATLAB .NET Builder, C#, and Oracle 10g. The system was tested
with Coral Image database containing 1000 natural images and
achieved better results.
Abstract: This paper describes a practical approach to design
and develop a hybrid learning with acceleration feedback control
(HLC) scheme for input tracking and end-point vibration suppression
of flexible manipulator systems. Initially, a collocated proportionalderivative
(PD) control scheme using hub-angle and hub-velocity
feedback is developed for control of rigid-body motion of the system.
This is then extended to incorporate a further hybrid control scheme
of the collocated PD control and iterative learning control with
acceleration feedback using genetic algorithms (GAs) to optimize the
learning parameters. Experimental results of the response of the
manipulator with the control schemes are presented in the time and
frequency domains. The performance of the HLC is assessed in terms
of input tracking, level of vibration reduction at resonance modes and
robustness with various payloads.
Abstract: To overcome the product overload of Internet
shoppers, we introduce a semantic recommendation procedure which
is more efficient when applied to Internet shopping malls. The
suggested procedure recommends the semantic products to the
customers and is originally based on Web usage mining, product
classification, association rule mining, and frequently purchasing.
We applied the procedure to the data set of MovieLens Company for
performance evaluation, and some experimental results are provided.
The experimental results have shown superior performance in
terms of coverage and precision.
Abstract: Facial recognition and expression analysis is rapidly
becoming an area of intense interest in computer science and humancomputer
interaction design communities. The most expressive way
humans display emotions is through facial expressions. In this paper
skin and non-skin pixels were separated. Face regions were extracted
from the detected skin regions. Facial expressions are analyzed from
facial images by applying Gabor wavelet transform (GWT) and
Discrete Cosine Transform (DCT) on face images. Radial Basis
Function (RBF) Network is used to identify the person and to classify
the facial expressions. Our method reliably works even with faces,
which carry heavy expressions.
Abstract: The aim of this paper is to rank the impact of Object
Oriented(OO) metrics in fault prediction modeling using Artificial
Neural Networks(ANNs). Past studies on empirical validation of
object oriented metrics as fault predictors using ANNs have focused
on the predictive quality of neural networks versus standard
statistical techniques. In this empirical study we turn our attention to
the capability of ANNs in ranking the impact of these explanatory
metrics on fault proneness. In ANNs data analysis approach, there is
no clear method of ranking the impact of individual metrics. Five
ANN based techniques are studied which rank object oriented
metrics in predicting fault proneness of classes. These techniques are
i) overall connection weights method ii) Garson-s method iii) The
partial derivatives methods iv) The Input Perturb method v) the
classical stepwise methods. We develop and evaluate different
prediction models based on the ranking of the metrics by the
individual techniques. The models based on overall connection
weights and partial derivatives methods have been found to be most
accurate.