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: Optimization is often a critical issue for most system
design problems. Evolutionary Algorithms are population-based,
stochastic search techniques, widely used as efficient global
optimizers. However, finding optimal solution to complex high
dimensional, multimodal problems often require highly
computationally expensive function evaluations and hence are
practically prohibitive. The Dynamic Approximate Fitness based
Hybrid EA (DAFHEA) model presented in our earlier work [14]
reduced computation time by controlled use of meta-models to
partially replace the actual function evaluation by approximate
function evaluation. However, the underlying assumption in
DAFHEA is that the training samples for the meta-model are
generated from a single uniform model. Situations like model
formation involving variable input dimensions and noisy data
certainly can not be covered by this assumption. In this paper we
present an enhanced version of DAFHEA that incorporates a
multiple-model based learning approach for the SVM approximator.
DAFHEA-II (the enhanced version of the DAFHEA framework) also
overcomes the high computational expense involved with additional
clustering requirements of the original DAFHEA framework. The
proposed framework has been tested on several benchmark functions
and the empirical results illustrate the advantages of the proposed
technique.
Abstract: This paper studies ruin probabilities in two discrete-time
risk models with premiums, claims and rates of interest modelled by
three autoregressive moving average processes. Generalized Lundberg
inequalities for ruin probabilities are derived by using recursive
technique. A numerical example is given to illustrate the applications
of these probability inequalities.
Abstract: The removal efficiency of 4-chlorophenol with
different advanced oxidation processes have been studied. Oxidation
experiments were carried out using two 4-chlorophenol
concentrations: 100 mg L-1 and 250 mg L-1 and UV generated from a
KrCl excilamp with (molar ratio H2O2: 4-chlorophenol = 25:1) and
without H2O2, and, with Fenton process (molar ratio H2O2:4-
chlorophenol of 25:1 and Fe2+ concentration of 5 mg L-1).
The results show that there is no significant difference in the 4-
chlorophenol conversion when using one of the three assayed
methods. However, significant concentrations of the photoproductos
still remained in the media when the chosen treatment involves UV
without hydrogen peroxide. Fenton process removed all the
intermediate photoproducts except for the hydroquinone and the
1,2,4-trihydroxybenzene. In the case of UV and hydrogen peroxide
all the intermediate photoproducts are removed.
Microbial bioassays were carried out utilising the naturally
luminescent bacterium Vibrio fischeri and a genetically modified
Pseudomonas putida isolated from a waste treatment plant receiving
phenolic waste. The results using V. fischeri show that with samples
after degradation, only the UV treatment showed toxicity (IC50 =38)
whereas with H2O2 and Fenton reactions the samples exhibited no
toxicity after treatment in the range of concentrations studied. Using
the Pseudomonas putida biosensor no toxicity could be detected for
all the samples following treatment due to the higher tolerance of the
organism to phenol concentrations encountered.
Abstract: This study aims at investigating factors in research
and development (R&D) growth and exploring the role of R&D
management in enhancing social innovation and productivity
improvement in Iran-s industrial sector. It basically explores the
common types of R&D activities and the industries which benefited
the most from active R&D units in Iran. The researchers generated
qualitative analyses obtained from primary and secondary data.
The primary data have been retrieved through interviews with five
key players (Managing Director, Internal Manager, General Manager,
Executive Manager, and Project Manager) in the industrial sector.
The secondary data acquired from an investigation on Mazandaran, a
province of northern Iran. The findings highlight Iran-s focuses of R
& D on cost reduction and upgrading productivity. Industries that
have benefited the most from active R&D units are metallic,
machinery and equipment design, and automotive.
We rank order the primary effects of R&D on productivity
improvement as follows, industry improvement, economic growth,
using professional human resources, generating productivity and
creativity culture, creating a competitive and innovative environment,
and increasing people-s knowledge.
Generally, low budget dedication and insufficient supply of highly
skilled scientists and engineers are two important obstacles for R&D
in Iran. Whereas, R&D has resulted in improvement in Iranian
society, transfer of contemporary knowledge into the international
market is still lacking.
Abstract: As a part of the development of a numerical method of
close capture exhausts systems for machining devices, a test rig
recreating a situation similar to a grinding operation, but in a
perfectly controlled environment, is used. The properties of the
obtained spray of solid particles are initially characterized using
particle tracking velocimetry (PTV), in order to obtain input and
validation parameters for numerical simulations. The dispersion of a
tracer gas (SF6) emitted simultaneously with the particle jet is then
studied experimentally, as the dispersion of such a gas is
representative of that of finer particles, whose aerodynamic response
time is negligible. Finally, complete modeling of the test rig is
achieved to allow comparison with experimental results and thus to
progress towards validation of the models used to describe a twophase
flow generated by machining operation.
Abstract: Functional Magnetic Resonance Imaging(fMRI) is a
noninvasive imaging technique that measures the hemodynamic
response related to neural activity in the human brain. Event-related
functional magnetic resonance imaging (efMRI) is a form of
functional Magnetic Resonance Imaging (fMRI) in which a series of
fMRI images are time-locked to a stimulus presentation and averaged
together over many trials. Again an event related potential (ERP) is a
measured brain response that is directly the result of a thought or
perception. Here the neuronal response of human visual cortex in
normal healthy patients have been studied. The patients were asked
to perform a visual three choice reaction task; from the relative
response of each patient corresponding neuronal activity in visual
cortex was imaged. The average number of neurons in the adult
human primary visual cortex, in each hemisphere has been estimated
at around 140 million. Statistical analysis of this experiment was
done with SPM5(Statistical Parametric Mapping version 5) software.
The result shows a robust design of imaging the neuronal activity of
human visual cortex.
Abstract: The main aim of this work is to develop a model of hydrogen sulfide (H2S) separation from natural gas by using membrane separation technology. The model is developed by incorporating three diffusion mechanisms which are Knudsen, viscous and surface diffusion towards membrane selectivity and permeability. The findings from the simulation result shows that the permeability of the gas is dependent toward the pore size of the membrane, operating pressure, operating temperature as well as feed composition. The permeability of methane has the highest value for Poly (1-trimethylsilyl-1-propyne ) PTMSP membrane at pore size of 0.1nm and decreasing toward a minimum peak at pore range 1 to 1.5 nm as pore size increased before it increase again for pore size is greater than 1.5 nm. On the other hand, the permeability of hydrogen sulfide is found to increase almost proportionally with the increase of membrane pore size. Generally, the increase of pressure will increase the permeability of gas since more driving force is provided to the system while increasing of temperature would decrease the permeability due to the surface diffusion drop off effect. A corroboration of the simulation result also showed a good agreement with the experimental data.
Abstract: Our research aims at helping the tutor on line to
evaluate the student-s cognitive processes. The student is a learner in
French as a Second Language who studies an on-line socio-cognitive
scenario in written communication. In our method, these cognitive
processes are defined. For that, the language abilities and learning
tasks are associated to cognitive operation. Moreover, the found
cognitive processes are named with specific terms. The result was to
create an instrumental pattern to question the learner about the
cognitive processes used to build an item of written comprehension.
Our research follows the principles of the third historical generation
of studies on the cognitive activity of the text comprehension. The
strength of our instrumental pattern stands in the precision and the
logical articulation of the questions to the learner. However, the
learner-s answers can still be subjective but the precision of the
instrument restricts it.
Abstract: For relatively small particles of aluminum (5%) is observed to
corrode before passivation occurs at moderate temperatures (>50oC)
in de-ionized water within one hour. Physical contact with alumina
powder results in a significant increase in both the rate of corrosion
and the extent of corrosion before passivation. Whereas the resulting
release of hydrogen gas could be of commercial interest for portable
hydrogen supply systems, the fundamental aspects of Al corrosion
acceleration in presence of dispersed alumina particles are equally
important. This paper investigates the effects of various amounts of
alumina on the corrosion rate of aluminum powders in water and the
effect of multiple additions of aluminum into a single reactor.
Abstract: Osteoarthritis (OA) is the most prevalent and far common debilitating form of arthritis which can be defined as a degenerative condition affecting synovial joint. Patients suffering from osteoarthritis often complain of dull ache pain on movement.
Physical agents can fight the painful process when correctly indicated and used such as heat or cold therapy Aim. This study was carried out to: Compare the effect of cold, warm and contrast therapy on controlling knee osteoarthritis associated problems. Setting: The study was carried out in orthopedic outpatient clinics of Menoufia University and teaching Hospitals, Egypt. Sample: A convenient sample of 60 adult patients with unilateral knee osteoarthritis. Tools: three tools were utilized to collect the data. Tool I : An interviewing questionnaire. It comprised of three parts covering sociodemographic data, medical data and adverse effects of the treatment protocol. Tool II : Knee Injury and Osteoarthritis Outcome Score (KOOS) It consists of five main parts. Tool II1 : 0-10 Numeric pain rating scale. Results: reveled that the total knee symptoms score was decreased from moderate symptoms pre intervention to mild symptoms after warm and contrast method of therapy, but the contrast therapy had significant effect in reducing the knee symptoms and pain than the other symptoms. Conclusions: all of the three
methods of therapy resulted in improvement in all knee symptoms and pain but the most appropriate protocol of treatment to relive symptoms and pain was contrast therapy.
Abstract: Economic dispatch problem is an optimization problem where objective function is highly non linear, non-convex, non-differentiable and may have multiple local minima. Therefore, classical optimization methods may not converge or get trapped to any local minima. This paper presents a comparative study of four different evolutionary algorithms i.e. genetic algorithm, bacteria foraging optimization, ant colony optimization and particle swarm optimization for solving the economic dispatch problem. All the methods are tested on IEEE 30 bus test system. Simulation results are presented to show the comparative performance of these methods.
Abstract: In this paper, a new algorithm for generating codebook is proposed for vector quantization (VQ) in image coding. The significant features of the training image vectors are extracted by using the proposed Orthogonal Polynomials based transformation. We propose to generate the codebook by partitioning these feature vectors into a binary tree. Each feature vector at a non-terminal node of the binary tree is directed to one of the two descendants by comparing a single feature associated with that node to a threshold. The binary tree codebook is used for encoding and decoding the feature vectors. In the decoding process the feature vectors are subjected to inverse transformation with the help of basis functions of the proposed Orthogonal Polynomials based transformation to get back the approximated input image training vectors. The results of the proposed coding are compared with the VQ using Discrete Cosine Transform (DCT) and Pairwise Nearest Neighbor (PNN) algorithm. The new algorithm results in a considerable reduction in computation time and provides better reconstructed picture quality.
Abstract: Optimization plays an important role in most real
world applications that support decision makers to take the right
decision regarding the strategic directions and operations of the
system they manage. Solutions for traffic management and traffic
congestion problems are considered major problems that most
decision making authorities for cities around the world are looking
for. This review paper gives a full description of the traffic problem
as part of the transportation planning process and present a view as a
framework of urban transportation system analysis where the core of
the system is a transportation network equilibrium model that is
based on optimization techniques and that can also be used for
evaluating an alternative solution or a combination of alternative
solutions for the traffic congestion. Different transportation network
equilibrium models are reviewed from the sequential approach to the
multiclass combining trip generation, trip distribution, modal split,
trip assignment and departure time model. A GIS-Based intelligent
decision support system framework for urban transportation system
analysis is suggested for implementation where the selection of
optimized alternative solutions, single or packages, will be based on
an intelligent agent rather than human being which would lead to
reduction in time, cost and the elimination of the difficulty, by
human being, for finding the best solution to the traffic congestion
problem.
Abstract: Sustainable development is highly dependent on the
implementation of environmental education programs, which has as
its ultimate goal to produce environmentally literate citizens that
undertake environmentally friendly actions. Efforts on environmental
education along past years are now perceived on the increase of
citizens awareness on European countries and, particularly, in
Portugal. However, we still have a lack of information on the
prevalence of specific behaviors that contributes to sustainability,
influenced by a new attitude toward the environment. The
determination of pro-environmental behaviors prevalence in higher
education students is an important approach to understand to which
extend the next leading generation is, in practice, committed with the
goals of sustainable development. Therefore, present study evaluates
the prevalence of a specific set of behaviors (water savings, energy
savings, environmental criteria on shopping, and mobility) on the
University of Madeira students and discusses their commitment with
sustainable development.
Abstract: This paper presents a model for the evaluation of
energy performance and aerodynamic forces acting on a small
straight-bladed Darrieus-type vertical axis wind turbine depending on
blade geometrical section. It consists of an analytical code coupled to
a solid modeling software, capable of generating the desired blade
geometry based on the desired blade design geometric parameters.
Such module is then linked to a finite volume commercial CFD code
for the calculation of rotor performance by integration of the
aerodynamic forces along the perimeter of each blade for a full period
of revolution.After describing and validating the computational
model with experimental data, the results of numerical simulations
are proposed on the bases of two candidate airfoil sections, that is a
classical symmetrical NACA 0021 blade profile and the recently
developed DU 06-W-200 non-symmetric and laminar blade
profile.Through a full CFD campaign of analysis, the effects of blade
geometrical section on angle of attack are first investigated and then
the overall rotor torque and power are analyzed as a function of blade
azimuthal position, achieving a numerical quantification of the
influence of airfoil geometry on overall rotor performance.
Abstract: This paper aims to develop a model that assists the
international retailer in selecting the country that maximizes the
degree of fit between the retailer-s goals and the country
characteristics in his initial internationalization move. A two-stage
multi criteria decision model is designed integrating the Analytic
Hierarchy Process (AHP) and Goal Programming. Ethical, cultural,
geographic and economic proximity are identified as the relevant
constructs of the internationalization decision. The constructs are
further structured into sub-factors within analytic hierarchy. The
model helps the retailer to integrate, rank and weigh a number of
hard and soft factors and prioritize the countries accordingly. The
model has been implemented on a Turkish luxury goods retailer who
was planning to internationalize. Actual entry of the specific retailer
in the selected country is a support for the model. Implementation on
a single retailer limits the generalizability of the results; however, the
emphasis of the paper is on construct identification and model
development. The paper enriches the existing literature by proposing
a hybrid multi objective decision model which introduces new soft
dimensions i.e. perceived distance, ethical proximity, humane
orientation to the decision process and facilitates effective decision
making.
Abstract: In recent past, the Unified Modeling Language (UML) has become the de facto industry standard for object-oriented modeling of the software systems. The syntax and semantics rich UML has encouraged industry to develop several supporting tools including those capable of generating deployable product (code) from the UML models. As a consequence, ensuring the correctness of the model/design has become challenging and extremely important task. In this paper, we present an approach for automatic verification of protocol model/design. As a case study, Session Initiation Protocol (SIP) design is verified for the property, “the CALLER will not converse with the CALLEE before the connection is established between them ". The SIP is modeled using UML statechart diagrams and the desired properties are expressed in temporal logic. Our prototype verifier “UML-SMV" is used to carry out the verification. We subjected an erroneous SIP model to the UML-SMV, the verifier could successfully detect the error (in 76.26ms) and generate the error trace.
Abstract: This research attempts to study the feasibility of
augmenting an augmented reality (AR) image card on a Quick
Response (QR) code. The authors have developed a new visual tag,
which contains a QR code and an augmented AR image card. The new
visual tag has features of reading both of the revealed data of the QR
code and the instant data from the AR image card. Furthermore, a
handheld communicating device is used to read and decode the new
visual tag, and then the concealed data of the new visual tag can be
revealed and read through its visual display. In general, the QR code is
designed to store the corresponding data or, as a key, to access the
corresponding data from the server through internet. Those reveled
data from the QR code are represented in text. Normally, the AR
image card is designed to store the corresponding data in
3-Dimensional or animation/video forms. By using QR code's
property of high fault tolerant rate, the new visual tag can access those
two different types of data by using a handheld communicating device.
The new visual tag has an advantage of carrying much more data than
independent QR code or AR image card. The major findings of this
research are: 1) the most efficient area for the designed augmented AR
card augmenting on the QR code is 9% coverage area out of the total
new visual tag-s area, and 2) the best location for the augmented AR
image card augmenting on the QR code is located in the bottom-right
corner of the new visual tag.
Abstract: Prior research has not effectively investigated how the
profitability of Chinese branches affect FDIs in China [1, 2], so this
study for the first time incorporates realistic earnings information
to systematically investigate effects of innovation, imitation, and
profit factors of FDI diffusions from Taiwan to China. Our nonlinear
least square (NLS) model, which incorporates earnings factors,
forms a nonlinear ordinary differential equation (ODE) in numerical
simulation programs. The model parameters are obtained through
a genetic algorithms (GA) technique and then optimized with the
collected data for the best accuracy. Particularly, Taiwanese regulatory
FDI restrictions are also considered in our modified model to meet
the realistic conditions. To validate the model-s effectiveness, this
investigation compares the prediction accuracy of modified model
with the conventional diffusion model, which does not take account
of the profitability factors.
The results clearly demonstrate the internal influence to be positive,
as early FDI adopters- consistent praises of FDI attract potential firms
to make the same move. The former erects a behavior model for the
latter to imitate their foreign investment decision. Particularly, the
results of modified diffusion models show that the earnings from
Chinese branches are positively related to the internal influence. In
general, the imitating tendency of potential consumers is substantially
hindered by the losses in the Chinese branches, and these firms would
invest less into China. The FDI inflow extension depends on earnings
of Chinese branches, and companies will adjust their FDI strategies
based on the returns. Since this research has proved that earning is
an influential factor on FDI dynamics, our revised model explicitly
performs superior in prediction ability than conventional diffusion
model.