Abstract: According to development of communications and
web-based technologies in recent years, e-Learning has became very
important for everyone and is seen as one of most dynamic teaching
methods.
Grid computing is a pattern for increasing of computing power
and storage capacity of a system and is based on hardware and
software resources in a network with common purpose. In this article
we study grid architecture and describe its different layers. In this
way, we will analyze grid layered architecture. Then we will
introduce a new suitable architecture for e-Learning which is based
on grid network, and for this reason we call it Grid Learning
Architecture. Various sections and layers of suggested architecture
will be analyzed; especially grid middleware layer that has key role.
This layer is heart of grid learning architecture and, in fact,
regardless of this layer, e-Learning based on grid architecture will
not be feasible.
Abstract: In the present study, a numerical analysis is carried
out to investigate unsteady MHD (magneto-hydrodynamic) flow and
heat transfer of a non-Newtonian second grade viscoelastic fluid
over an oscillatory stretching sheet. The flow is induced due to an
infinite elastic sheet which is stretched oscillatory (back and forth) in
its own plane. Effect of viscous dissipation and joule heating are
taken into account. The non-linear differential equations governing
the problem are transformed into system of non-dimensional
differential equations using similarity transformations. A newly
developed meshfree numerical technique Element free Galerkin
method (EFGM) is employed to solve the coupled non linear
differential equations. The results illustrating the effect of various
parameters like viscoelastic parameter, Hartman number, relative
frequency amplitude of the oscillatory sheet to the stretching rate and
Eckert number on velocity and temperature field are reported in
terms of graphs and tables. The present model finds its application in
polymer extrusion, drawing of plastic films and wires, glass, fiber
and paper production etc.
Abstract: In order to explore the relationship of promotion activities, destination attribute and destination image of Vietnam and find possible solutions, this study uses decision system analysis (DSA) method to develop flowcharts based on three rounds of expert interviews. The interviews were conducted with the experts who were confirmed to directly participate or influence on the decision making that drives the promotion of Vietnam tourism process. This study identifies three models and describes specific decisions on promotion activities, destination attributes and destination images. This study finally derives a general model for promoting the Tourism Industrial Service Network (TISN) in Vietnam. This study finds that the coordination with all sectors and industries of tourism to facilitate favorable condition and improving destination attributes in linking with the efficient promotion activities is highly recommended in order to make visitors satisfied and improve the destination image.
Abstract: The talks about technological convergence had been
around for almost twenty years. Today Internet made it possible. And
this is not only technical evolution. The way it changed our lives
reflected in variety of applications, services and technologies used in
day-to-day life. Such benefits imposed even more requirements on
heterogeneous and unreliable IP networks.
Current paper outlines QoS management system developed in the
NetQoS [1] project. It describes an overall architecture of
management system for heterogeneous networks and proposes
automated multi-layer QoS management. Paper focuses on the
structure of the most crucial modules of the system that enable
autonomous and multi-layer provisioning and dynamic adaptation.
Abstract: Medical Decision Support Systems (MDSSs) are sophisticated, intelligent systems that can provide inference due to lack of information and uncertainty. In such systems, to model the uncertainty various soft computing methods such as Bayesian networks, rough sets, artificial neural networks, fuzzy logic, inductive logic programming and genetic algorithms and hybrid methods that formed from the combination of the few mentioned methods are used. In this study, symptom-disease relationships are presented by a framework which is modeled with a formal concept analysis and theory, as diseases, objects and attributes of symptoms. After a concept lattice is formed, Bayes theorem can be used to determine the relationships between attributes and objects. A discernibility relation that forms the base of the rough sets can be applied to attribute data sets in order to reduce attributes and decrease the complexity of computation.
Abstract: In this paper we consider the problem of distributed adaptive estimation in wireless sensor networks for two different observation noise conditions. In the first case, we assume that there are some sensors with high observation noise variance (noisy sensors) in the network. In the second case, different variance for observation noise is assumed among the sensors which is more close to real scenario. In both cases, an initial estimate of each sensor-s observation noise is obtained. For the first case, we show that when there are such sensors in the network, the performance of conventional distributed adaptive estimation algorithms such as incremental distributed least mean square (IDLMS) algorithm drastically decreases. In addition, detecting and ignoring these sensors leads to a better performance in a sense of estimation. In the next step, we propose a simple algorithm to detect theses noisy sensors and modify the IDLMS algorithm to deal with noisy sensors. For the second case, we propose a new algorithm in which the step-size parameter is adjusted for each sensor according to its observation noise variance. As the simulation results show, the proposed methods outperforms the IDLMS algorithm in the same condition.
Abstract: The load flow study in a power system constitutes a study of paramount importance. The study reveals the electrical performance and power flows (real and reactive) for specified condition when the system is operating under steady state. This paper gives an overview of different techniques used for load flow study under different specified conditions.
Abstract: In line with changes of consumers modern lifestyle has call for the advertising strategy to change. This research is to find out how game with telepresence and product experience embedded in the computer game to affect users- intention to purchase. Game content developers are urging to consider of placing product message as part of game design strategy that can influence the game player-s intention to purchase. Experiment was carried out on two hundred and fifty undergraduate students who volunteered to participate in the Internet game playing activities. A factor analysis and correlation analysis was performed on items designed to measure telepresence, attitudes toward telepresence, and game player intention to purchase the product advertise in the game that respondents experienced. The results indicated that telepresence consist of interactive experience and product experience. The study also found that product experience is positively related to the game players- intention to purchase. The significance of product experience implies the usefulness of an interactive advertising in the game playing to attract players- intention to purchase the advertised product placed in the creative game design.
Abstract: Virtual Reality Modelling Language (VRML) is description language, which belongs to a field Window on World virtual reality system. The file, which is in VRML format, can be interpreted by VRML explorer in three-dimensional scene. VRML was created with aim to represent virtual reality on Internet easier. Development of 3D graphic is connected with Silicon Graphic Corporation. VRML 2.0 is the file format for describing interactive 3D scenes and objects. It can be used in collaboration with www, can be used for 3D complex representations creating of scenes, products or VR applications VRML 2.0 enables represent static and animated objects too. Interesting application of VRML is in area of manufacturing systems presentation.
Abstract: The nature of wireless ad hoc and sensor networks
make them very attractive to attackers. One of the most popular and
serious attacks in wireless ad hoc networks is wormhole attack and
most proposed protocols to defend against this attack used
positioning devices, synchronized clocks, or directional antennas.
This paper analyzes the nature of wormhole attack and existing
methods of defending mechanism and then proposes round trip time
(RTT) and neighbor numbers based wormhole detection mechanism.
The consideration of proposed mechanism is the RTT between two
successive nodes and those nodes- neighbor number which is needed
to compare those values of other successive nodes. The identification
of wormhole attacks is based on the two faces. The first consideration
is that the transmission time between two wormhole attack affected
nodes is considerable higher than that between two normal neighbor
nodes. The second detection mechanism is based on the fact that by
introducing new links into the network, the adversary increases the
number of neighbors of the nodes within its radius. This system does
not require any specific hardware, has good performance and little
overhead and also does not consume extra energy. The proposed
system is designed in ad hoc on-demand distance vector (AODV)
routing protocol and analysis and simulations of the proposed system
are performed in network simulator (ns-2).
Abstract: The increasing number of senior population gradually
causes to demand the use of information and communication
technology for their satisfactory lives. This paper presents the
development of an integrated TV based system which offers an
opportunity to provide value added services to a large number of
elderly citizens, and thus helps improve their quality of life. The
design philosophy underlying this paper is to fulfill both technological
and human aspects. The balance between these two dimensions has
been currently stressed as a crucial element for the design of usable
systems in real use, particularly to the elderly who have physical and
mental decline. As the first step to achieve it, we have identified
human and social factors that affect the elder-s quality of life by a
literature review, and based on them, build four fundamental services:
information, healthcare, learning and social network services.
Secondly, the system architecture, employed technologies and the
elderly-friendly system design considerations are presented. This
reflects technological and human perspectives in terms of the system
design. Finally, we describe some scenarios that illustrate the
potentiality of the proposed system to improve elderly people-s quality
of life.
Abstract: In this paper multi-objective genetic algorithms are
employed for Pareto approach optimization of ideal Turboshaft
engines. In the multi-objective optimization a number of conflicting
objective functions are to be optimized simultaneously. The
important objective functions that have been considered for
optimization are specific thrust (F/m& 0), specific fuel consumption
( P S ), output shaft power 0 (& /&) shaft W m and overall efficiency( ) O
η .
These objectives are usually conflicting with each other. The design
variables consist of thermodynamic parameters (compressor pressure
ratio, turbine temperature ratio and Mach number).
At the first stage single objective optimization has been
investigated and the method of NSGA-II has been used for multiobjective
optimization. Optimization procedures are performed for
two and four objective functions and the results are compared for
ideal Turboshaft engine. In order to investigate the optimal
thermodynamic behavior of two objectives, different set, each
including two objectives of output parameters, are considered
individually. For each set Pareto front are depicted. The sets of
selected decision variables based on this Pareto front, will cause the
best possible combination of corresponding objective functions.
There is no superiority for the points on the Pareto front figure,
but they are superior to any other point. In the case of four objective
optimization the results are given in tables.
Abstract: Despite many success stories of manufacturing safety, many organizations are still reluctant, perceiving it as cost increasing and time consuming. The clear contributor may be due to the use of lagging indicators rather than leading indicator measures. The study therefore proposes a combinatorial model for determining the best safety strategy. A combination theory and cost benefit analysis was employed to develop a monetary saving / loss function in terms value of preventions and cost of prevention strategy. Documentations, interviews and structured questionnaire were employed to collect information on Before-And-After safety programme records from a Tobacco company between periods of 1993-2001(for pre-safety) and 2002-2008 (safety period) for the model application. Three combinatorial alternatives A, B, C were obtained resulting into 4, 6 and 4 strategies respectively with PPE and Training being predominant. A total of 728 accidents were recorded for a 9 year period of pre-safety programme and 163 accidents were recorded for 7 years period of safety programme. Six preventions activities (alternative B) yielded the best results. However, all the years of operation experienced except year 2004. The study provides a leading resources for planning successful safety programme
Abstract: In response to address different development challenges, Tanzania is striving to achieve its fourth attribute of the National Development Vision, i.e. to have a well educated and learned society by the year 2025. One of the most cost effective methods that can reach a large part of the society in a short time is to integrate ICT in education through e-learning initiatives. However, elearning initiatives are challenged by limited or lack of connectivity to majority of secondary schools, especially those in rural and remote areas. This paper has explores the possibility for rural secondary school to access online e-Learning resources from a centralized e- Learning Management System (e-LMS). The scope of this paper is limited to schools that have computers irrespective of internet connectivity, resulting in two categories schools; those with internet access and those without. Different connectivity configurations have been proposed according to the ICT infrastructure status of the respective schools. However, majority of rural secondary schools in Tanzania have neither computers nor internet connection. Therefore this is a challenge to be addressed for the disadvantaged schools to benefit from e-Learning initiatives.
Abstract: Planning capacities when regenerating complex investment goods involves particular challenges in that the planning is subject to a large degree of uncertainty regarding load information. Using information fusion – by applying Bayesian Networks – a method is being developed for forecasting the anticipated expenditures (human labor, tool and machinery utilization, time etc.) for regenerating a good. The generated forecasts then later serve as a tool for planning capacities and ensure a greater stability in the planning processes.
Abstract: The new programming technologies allow for the
creation of components which can be automatically or manually
assembled to reach a new experience in knowledge understanding
and mastering or in getting skills for a specific knowledge area. The
project proposes an interactive framework that permits the creation,
combination and utilization of components that are specific to
mathematical training in high schools.
The main framework-s objectives are:
• authoring lessons by the teacher or the students; all they need
are simple operating skills for Equation Editor (or something
similar, or Latex); the rest are just drag & drop operations,
inserting data into a grid, or navigating through menus
• allowing sonorous presentations of mathematical texts and
solving hints (easier understood by the students)
• offering graphical representations of a mathematical function
edited in Equation
• storing of learning objects in a database
• storing of predefined lessons (efficient for expressions and
commands, the rest being calculations; allows a high
compression)
• viewing and/or modifying predefined lessons, according to the
curricula
The whole thing is focused on a mathematical expressions minicompiler,
storing the code that will be later used for different
purposes (tables, graphics, and optimisations).
Programming technologies used. A Visual C# .NET
implementation is proposed. New and innovative digital learning
objects for mathematics will be developed; they are capable to
interpret, contextualize and react depending on the architecture
where they are assembled.
Abstract: The stem cells have ability to differentiated
themselves through mitotic cell division and various range of
specialized cell types. Cellular differentiation is a way by which few
specialized cell develops into more specialized.This paper studies the
fundamental problem of computational schema for an artificial neural
network based on chemical, physical and biological variables of
state. By doing this type of study system could be model for a viable
propagation of various economically important stem cells
differentiation. This paper proposes various differentiation outcomes
of artificial neural network into variety of potential specialized cells
on implementing MATLAB version 2009. A feed-forward back
propagation kind of network was created to input vector (five input
elements) with single hidden layer and one output unit in output
layer. The efficiency of neural network was done by the assessment
of results achieved from this study with that of experimental data
input and chosen target data. The propose solution for the efficiency
of artificial neural network assessed by the comparatative analysis of
“Mean Square Error" at zero epochs. There are different variables of
data in order to test the targeted results.
Abstract: Optical Bursts Switching (OBS) is a relatively new
optical switching paradigm. Contention and burst loss in OBS
networks are major concerns. To resolve contentions, an interesting
alternative to discarding the entire data burst is to partially drop the
burst. Partial burst dropping is based on burst segmentation concept
that its implementation is constrained by some technical challenges,
besides the complexity added to the algorithms and protocols on both
edge and core nodes. In this paper, the burst segmentation concept is
investigated, and an implementation scheme is proposed and
evaluated. An appropriate dropping policy that effectively manages
the size of the segmented data bursts is presented. The dropping
policy is further supported by a new control packet format that
provides constant transmission overhead.
Abstract: This study has investigated a vehicle Lumped
Parameter Model (LPM) in frontal crash. There are several ways for
determining spring and damper characteristics and type of problem
shall be considered as system identification. This study use Genetic
Algorithm (GA) procedure, being an effective procedure in case of
optimization issues, for optimizing errors, between target data
(experimental data) and calculated results (being obtained by
analytical solving). In this study analyzed model in 5-DOF then
compared our results with 5-DOF serial model. Finally, the response
of model due to external excitement is investigated.
Abstract: Reverse engineering of full-genomic interaction networks based on compendia of expression data has been successfully applied for a number of model organisms. This study adapts these approaches for an important non-model organism: The major human fungal pathogen Candida albicans. During the infection process, the pathogen can adapt to a wide range of environmental niches and reversibly changes its growth form. Given the importance of these processes, it is important to know how they are regulated. This study presents a reverse engineering strategy able to infer fullgenomic interaction networks for C. albicans based on a linear regression, utilizing the sparseness criterion (LASSO). To overcome the limited amount of expression data and small number of known interactions, we utilize different prior-knowledge sources guiding the network inference to a knowledge driven solution. Since, no database of known interactions for C. albicans exists, we use a textmining system which utilizes full-text research papers to identify known regulatory interactions. By comparing with these known regulatory interactions, we find an optimal value for global modelling parameters weighting the influence of the sparseness criterion and the prior-knowledge. Furthermore, we show that soft integration of prior-knowledge additionally improves the performance. Finally, we compare the performance of our approach to state of the art network inference approaches.