Abstract: Cloud computing is becoming more and more matured over the last few years and consequently the demands for better cloud services is increasing rapidly. One of the research topics to improve cloud services is the desktop computing in virtualized environment. This paper aims at the development of an adaptive virtual desktop service in cloud computing platform based on our previous research on the virtualization technology. We implement cloud virtual desktop and application software streaming technology that make it possible for providing Virtual Desktop as a Service (VDaaS). Given the development of remote desktop virtualization, it allows shifting the user’s desktop from the traditional PC environment to the cloud-enabled environment, which is stored on a remote virtual machine rather than locally. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. Users no longer need to burden the platform maintenances and drastically reduces the overall cost of hardware and software licenses. Moreover, this flexible remote desktop service represents the next significant step to the mobile workplace, and it lets users access their desktop environments from virtually anywhere.
Abstract: The electromagnetic spectrum is a natural resource
and hence well-organized usage of the limited natural resources is the
necessities for better communication. The present static frequency
allocation schemes cannot accommodate demands of the rapidly
increasing number of higher data rate services. Therefore, dynamic
usage of the spectrum must be distinguished from the static usage to
increase the availability of frequency spectrum. Cognitive radio is not
a single piece of apparatus but it is a technology that can incorporate
components spread across a network. It offers great promise for
improving system efficiency, spectrum utilization, more effective
applications, reduction in interference and reduced complexity of
usage for users. Cognitive radio is aware of its environmental,
internal state, and location, and autonomously adjusts its operations
to achieve designed objectives. It first senses its spectral environment
over a wide frequency band, and then adapts the parameters to
maximize spectrum efficiency with high performance. This paper
only focuses on the analysis of Bit-Error-Rate in cognitive radio by
using Particle Swarm Optimization Algorithm. It is theoretically as
well as practically analyzed and interpreted in the sense of
advantages and drawbacks and how BER affects the efficiency and
performance of the communication system.
Abstract: One challenging direction of mobile commerce (mcommerce)
that is getting a great deal of attention globally is mobile
financing. The smart-phone and PDA users all around the world are
facing difficulties to become accustomed and trust in m-commerce.
The main rationale can be the slow variation and lack of trust in
mobile payment systems. Mobile payment systems that are in use
need to be more effective and efficient. This paper proposes: the
interface design is not the only factor affecting the m-commerce
adoption and lack of trust; in fact it is the combined effect of
interface usability and trustworthy mobile payment systems, because
it-s the money that the user has to spend at the end of the day, which
the user requires to get transferred securely. The purpose of this
research is to identify the problems regarding the trust and adaption
of m-commerce applications by mobile users and to provide the best
possible solution with respect to human computer interaction (HCI)
principles.
Abstract: Well-being has been given special emphasis in quality
of life. It involves living a meaningful, life satisfaction, stability and
happiness in life. Well-being also concerns the satisfaction of
physical, psychological, social needs and demands of an individual.
The purpose of this study was to validate three-factor measurement
model of well-being using structural equation modeling (SEM). The
conceptions of well-being measured such dimensions as physical,
psychological and social well-being. This study was done based on a
total sample of 650 adolescents from east-coast of peninsular
Malaysia. The Well-Being Scales which was adapted from [1] was
used in this study. The items were hypothesized a priori to have nonzero
loadings on all dimensions in the model. The findings of the
SEM demonstrated that it is a good fitting model which the proposed
model fits the driving theory; (x2df = 1.268; GFI = .994; CFI = .998;
TLI= .996; p = .255; RMSEA = .021). Composite reliability (CR)
was .93 and average variance extracted (AVE) was 58%. The model
in this study fits with the sample of data and well-being is important
to bring sustainable development to the mainstream.
Abstract: A variable structure model reference adaptive control
(VS-MRAC) strategy for active steering assistance of a two wheel
steering car is proposed. An ideal steering system with fixed
properties and moving on an ideal road is used as the reference
model, and the active steering assistance system is forced to attain
the same behavior as the reference model. The proposed system can
treat the nonlinear relationships between the side slip angles and
lateral forces on tire, and the uncertainties on friction of the road
surface, whose compensation are very important under critical
situations. Simulation results show improvements on yaw rate and
side slip.
Abstract: Age at first marriage is a basic temporal term that is
culturally constructed for marriage relationship between an adult
male and an adult female intended to have sex, to reproduce and to
adapt to environment from one generation to another around the
world. Cross-cultural evidences suggest that age at first marriage for
both male and female not only varies across the cultures, but also
varies among the subcultures of the same society. The purpose of the
study was to compare age at first marriage for husband and wife
including age differences between them between Muslim and Santal
communities in rural Bangladesh. For this we hypothesized that (1)
there were significant differences in age at first marriage and age
interval between husband and wife between Muslim and Santal
communities in rural Bangladesh. In so doing, 288 couples (145 pairs
of couples for Muslim and 143 pairs of couples for Santal) were
selected by cluster random sampling from the Kalna village situated
in the Tanore Upazila of Rajshahi district, Bangladesh, whose
current mean age range was 36.59 years for husband and 28.85 years
for wife for the Muslim and 31.74 years for husband and 25.21 years
for wife for the Santal respectively. The results of Independent
Sample t test showed that mean age at first marriage for the Muslim
samples was 23.05 years for husbands and 15.11 years for wives,
while mean age at first marriage for the Santal samples was 20.71
years for husbands and 14.34 years for wives respectively that were
significantly different at p0.05) among the selected husbands
and wives between the two communities. This study recommends
that further cross-cultural researches should be done on the causeeffect
relationships between socio-cultural factors and age at
marriage between the two communities in Bangladesh.
Abstract: Extensive information is required within a R&D environment,
and a considerable amount of time and efforts are being
spent on finding the necessary information. An adaptive information
providing system would be beneficial to the environment, and a
conceptual model of the resources, people and context is mandatory
for developing such applications. In this paper, an information model
on various contexts and resources is proposed which provides the
possibility of effective applications for use in adaptive information
systems within a R&D project and meeting environment.
Abstract: Common acceptable cuisine usually discussed in the
multicultural/ethnic nation as it represents the process of sharing it
among the ethnic groups. The common acceptable cuisine is also
considered as a precursor in the process of constructing the national
food identity within ethnic groups in the multicultural countries. The
adaptation of certain ethnic cuisines through its types of food,
methods of cooking, ingredients and eating decorum by ethnic groups
is believed creating or enhancing the process of formation on
common acceptable cuisines in a multicultural country. Malaysia as
the multicultural country without doubt is continuing to experience
cross-culturing processes among the ethnic groups including cuisine.
This study empirically investigates the adaptation level of Malay,
Chinese and Indian chefs on each other ethnic cuisine attributes
toward the formation on common acceptable cuisines and national
food identity.
Abstract: The frequency contents of the non-stationary
signals vary with time. For proper characterization of such
signals, a smart time-frequency representation is necessary.
Classically, the STFT (short-time Fourier transform) is
employed for this purpose. Its limitation is the fixed timefrequency
resolution. To overcome this drawback an enhanced
STFT version is devised. It is based on the signal driven
sampling scheme, which is named as the cross-level sampling.
It can adapt the sampling frequency and the window function
(length plus shape) by following the input signal local
variations. This adaptation results into the proposed technique
appealing features, which are the adaptive time-frequency
resolution and the computational efficiency.
Abstract: An adaptive software reliability prediction model
using evolutionary connectionist approach based on Recurrent Radial
Basis Function architecture is proposed. Based on the currently
available software failure time data, Fuzzy Min-Max algorithm is
used to globally optimize the number of the k Gaussian nodes. The
corresponding optimized neural network architecture is iteratively
and dynamically reconfigured in real-time as new actual failure time
data arrives. The performance of our proposed approach has been
tested using sixteen real-time software failure data. Numerical results
show that our proposed approach is robust across different software
projects, and has a better performance with respect to next-steppredictability
compared to existing neural network model for failure
time prediction.
Abstract: Employing a recently introduced unified adaptive filter
theory, we show how the performance of a large number of important
adaptive filter algorithms can be predicted within a general framework
in nonstationary environment. This approach is based on energy conservation
arguments and does not need to assume a Gaussian or white
distribution for the regressors. This general performance analysis can
be used to evaluate the mean square performance of the Least Mean
Square (LMS) algorithm, its normalized version (NLMS), the family
of Affine Projection Algorithms (APA), the Recursive Least Squares
(RLS), the Data-Reusing LMS (DR-LMS), its normalized version
(NDR-LMS), the Block Least Mean Squares (BLMS), the Block
Normalized LMS (BNLMS), the Transform Domain Adaptive Filters
(TDAF) and the Subband Adaptive Filters (SAF) in nonstationary
environment. Also, we establish the general expressions for the
steady-state excess mean square in this environment for all these
adaptive algorithms. Finally, we demonstrate through simulations that
these results are useful in predicting the adaptive filter performance.
Abstract: The use of the mechanical simulation (in particular the finite element analysis) requires the management of assumptions in order to analyse a real complex system. In finite element analysis (FEA), two modeling steps require assumptions to be able to carry out the computations and to obtain some results: the building of the physical model and the building of the simulation model. The simplification assumptions made on the analysed system in these two steps can generate two kinds of errors: the physical modeling errors (mathematical model, domain simplifications, materials properties, boundary conditions and loads) and the mesh discretization errors. This paper proposes a mesh adaptive method based on the use of an h-adaptive scheme in combination with an error estimator in order to choose the mesh of the simulation model. This method allows us to choose the mesh of the simulation model in order to control the cost and the quality of the finite element analysis.
Abstract: Business Process Modeling (BPM) is the first and
most important step in business process management lifecycle. Graph
based formalism and rule based formalism are the two most
predominant formalisms on which process modeling languages are
developed. BPM technology continues to face challenges in coping
with dynamic business environments where requirements and goals
are constantly changing at the execution time. Graph based
formalisms incur problems to react to dynamic changes in Business
Process (BP) at the runtime instances. In this research, an adaptive
and flexible framework based on the integration between Object
Oriented diagramming technique and Petri Net modeling language is
proposed in order to support change management techniques for
BPM and increase the representation capability for Object Oriented
modeling for the dynamic changes in the runtime instances. The
proposed framework is applied in a higher education environment to
achieve flexible, updatable and dynamic BP.
Abstract: Avoiding learning failures in mathematics e-learning environments caused by emotional problems in students with autism has become an important topic for combining of special education with information and communications technology. This study presents an adaptive emotional adjustment model in mathematics e-learning for students with autism, emphasizing the lack of emotional perception in mathematics e-learning systems. In addition, an emotion classification for students with autism was developed by inducing emotions in mathematical learning environments to record changes in the physiological signals and facial expressions of students. Using these methods, 58 emotional features were obtained. These features were then processed using one-way ANOVA and information gain (IG). After reducing the feature dimension, methods of support vector machines (SVM), k-nearest neighbors (KNN), and classification and regression trees (CART) were used to classify four emotional categories: baseline, happy, angry, and anxious. After testing and comparisons, in a situation without feature selection, the accuracy rate of the SVM classification can reach as high as 79.3-%. After using IG to reduce the feature dimension, with only 28 features remaining, SVM still has a classification accuracy of 78.2-%. The results of this research could enhance the effectiveness of eLearning in special education.
Abstract: Robustness is one of the primary performance criteria for an Intelligent Video Surveillance (IVS) system. One of the key factors in enhancing the robustness of dynamic video analysis is,providing accurate and reliable means for shadow detection. If left undetected, shadow pixels may result in incorrect object tracking and classification, as it tends to distort localization and measurement information. Most of the algorithms proposed in literature are computationally expensive; some to the extent of equalling computational requirement of motion detection. In this paper, the homogeneity property of shadows is explored in a novel way for shadow detection. An adaptive division image (which highlights homogeneity property of shadows) analysis followed by a relatively simpler projection histogram analysis for penumbra suppression is the key novelty in our approach.
Abstract: The advances in multimedia and networking technologies
have created opportunities for Internet pirates, who can easily
copy multimedia contents and illegally distribute them on the Internet,
thus violating the legal rights of content owners. This paper describes
how a simple and well-known watermarking procedure based on a
spread spectrum method and a watermark recovery by correlation can
be improved to effectively and adaptively protect MPEG-2 videos
distributed on the Internet. In fact, the procedure, in its simplest
form, is vulnerable to a variety of attacks. However, its security
and robustness have been increased, and its behavior has been
made adaptive with respect to the video terminals used to open
the videos and the network transactions carried out to deliver them
to buyers. In fact, such an adaptive behavior enables the proposed
procedure to efficiently embed watermarks, and this characteristic
makes the procedure well suited to be exploited in web contexts,
where watermarks usually generated from fingerprinting codes have
to be inserted into the distributed videos “on the fly", i.e. during the
purchase web transactions.
Abstract: In this paper by using the port-controlled Hamiltonian
(PCH) systems theory, a full-order nonlinear controlled model is first
developed. Then a nonlinear passivity-based robust adaptive control
(PBRAC) of switched reluctance motor in the presence of external
disturbances for the purpose of torque ripple reduction and
characteristic improvement is presented. The proposed controller
design is separated into the inner loop and the outer loop controller.
In the inner loop, passivity-based control is employed by using
energy shaping techniques to produce the proper switching function.
The outer loop control is employed by robust adaptive controller to
determine the appropriate Torque command. It can also overcome the
inherent nonlinear characteristics of the system and make the whole
system robust to uncertainties and bounded disturbances. A 4KW 8/6
SRM with experimental characteristics that takes magnetic saturation
into account is modeled, simulation results show that the proposed
scheme has good performance and practical application prospects.
Abstract: In this paper, we present a method named Signal Level
Matrix (SLM) which can improve the accuracy and stability of active
RFID indoor positioning system. Considering the accuracy and cost,
we use uniform distribution mode to set up and separate the
overlapped signal covering areas, in order to achieve preliminary
location setting. Then, based on the proposed SLM concept and the
characteristic of the signal strength value that attenuates as the
distance increases, this system cross-examines the distribution of
adjacent signals to locate the users more accurately. The experimental
results indicate that the adaptive positioning method proposed in this
paper could improve the accuracy and stability of the positioning
system effectively and satisfyingly.
Abstract: The recent growth of using multimedia transmission
over wireless communication systems, have challenges to protect the
data from lost due to wireless channel effect. Images are corrupted
due to the noise and fading when transmitted over wireless channel,
in wireless channel the image is transmitted block by block, Due to
severe fading, entire image blocks can be damaged. The aim of this
paper comes out from need to enhance the digital images at the
wireless receiver side. Proposed Boundary Interpolation (BI)
Algorithm using wavelet, have been adapted here used to
reconstruction the lost block in the image at the receiver depend on
the correlation between the lost block and its neighbors. New
Proposed technique by using Boundary Interpolation (BI) Algorithm
using wavelet with Pixel interleaver has been implemented. Pixel
interleaver work on distribute the pixel to new pixel position of
original image before transmitting the image. The block lost through
wireless channel is only effects individual pixel. The lost pixels at the
receiver side can be recovered by using Boundary Interpolation (BI)
Algorithm using wavelet. The results showed that the New proposed
algorithm boundary interpolation (BI) using wavelet with pixel
interleaver is better in term of MSE and PSNR.
Abstract: A Variable Structure Model Reference Adaptive Controller using state variables is proposed for a class of multi input-multi output systems. Adaptation law is of variable structure type and switching functions is designed based on stability requirements. Global exponential stability is proved based on Lyapunov criterion. Transient behavior is analyzed using sliding mode control and shows perfect model following at a finite time.