Abstract: One of the most important aspects expected from ERP systems is to integrate various operations existing in administrative, financial, commercial, human resources, and production departments of the consumer organization. Also, it is often needed to integrate the new ERP system with the organization legacy systems when implementing the ERP package in the organization. Without relying on an appropriate software architecture to realize the required integration, ERP implementation processes become error prone and time consuming; in some cases, the ERP implementation may even encounters serious risks. In this paper, we propose a new architecture that is based on the agent oriented vision and supplies the integration expected from ERP systems using several independent but cooperator agents. Besides integration which is the main issue of this paper, the presented architecture will address some aspects of intelligence and learning capabilities existing in ERP systems
Abstract: The daily growing use of agents in software environments, because of many reasons such as independence and intelligence is not a secret anymore. One of such environments in which there is a prominent job for the agents would be emarketplaces in which a user is able to give those agents the responsibility of buying and selling, instead of searching the emarketplace himself. Making up a framework which has sufficient attention to the required roles and their relations, is the first step of achieving such e-markets. In this paper, we suggest a framework in order to establish such e-markets and we will continue investigating the roles such as seller or buyer and the relations in JADE environment in details.
Abstract: Four design alternatives for lateral force-resisting
systems of tall buildings in Dubai, UAE are presented. Quantitative
comparisons between the different designs are also made. This paper
is intended to provide different feasible lateral systems to be used in
Dubai in light of the available seismic hazard studies of the UAE.
The different lateral systems are chosen in conformance with the
International Building Code (IBC). Moreover, the expected behavior
of each system is highlighted and light is shed on some of the cost
implications associated with lateral system selection.
Abstract: Fourty one strains of ESBL producing P.aeruginosa
which were previously isolated from burn patients in Kerman
University general hospital, Iran were subjected to PCR, RFLP and
sequencing in order to determine the type of extended spectrum β-
lactamases (ESBL), the restriction digestion pattern and possibility of
mutation among detected genes. DNA extraction was carried out by
phenol chloroform method. PCR for detection of bla genes was
performed using specific primer for each gene. Restriction Fragment
Length Polymorphism (RFLP) for ESBL genes was carried out using
EcoRI, NheI, PVUII, EcoRV, DdeI, and PstI restriction enzymes. The
PCR products were subjected to direct sequencing of both the strands
for identification of the ESBL genes.The blaCTX-M, blaVEB-1, blaPER-1,
blaGES-1, blaOXA-1, blaOXA-4 and blaOXA-10 genes were detected in the
(n=1) 2.43%, (n=41)100%, (n=28) 68.3%, (n=10) 24.4%, (n=29)
70.7%, (n=7)17.1% and (n=38) 92.7% of the ESBL producing isolates
respectively. The RFLP analysis showed that each ESBL gene has
identical pattern of digestion among the isolated strains. Sequencing
of the ESBL genes confirmed the genuinety of PCR products and
revealed no mutation in the restriction sites of the above genes. From
results of the present investigation it can be concluded that blaVEB-1
and blaCTX-M were the most and the least frequently isolated ESBL
genes among the P.aeruginosa strains isolated from burn patients. The
RFLP and sequencing analysis revealed that same clone of the bla
genes were indeed existed among the antibiotic resistant strains.
Abstract: Modeling and simulation of fixed bed three-phase
catalytic reactors are considered for wet air catalytic oxidation of
phenol to perform a comparative numerical analysis between tricklebed
and packed-bubble column reactors. The modeling involves
material balances both for the catalyst particle as well as for different
fluid phases. Catalyst deactivation is also considered in a transient
reactor model to investigate the effects of various parameters
including reactor temperature on catalyst deactivation. The
simulation results indicated that packed-bubble columns were
slightly superior in performance than trickle beds. It was also found
that reaction temperature was the most effective parameter in catalyst
deactivation.
Abstract: Considering non-ideal behavior of fluids and its effects on hydrodynamic and mass transfer in multiphase flow is very essential. Simulations were performed that takes into account the effects of mass transfer and mixture non-ideality on hydrodynamics reported by Irani et al. In this paper, by assuming the density of phases to be constant and Raullt-s law instead of using EOS and fugacity coefficient definition, respectively for both the liquid and gas phases, the importance of non-ideality effects on mass transfer and hydrodynamic behavior was studied. The results for a system of octane/propane (T=323 K, P =445 kpa) also indicated that the assumption of constant density in simulation had major role to diverse from experimental data. Furthermore, comparison between obtained results and the previous report indicated significant differences between experimental data and simulation results with more ideal assumptions.
Abstract: With the exponential progress of technological
development comes a strong sense that events are moving too quickly
for our schools and that teachers may be losing control of them in the
process. This paper examines the impact of e-learning and e-teaching
in universities, from both the student and teacher perspective. In
particular, it is shown that e-teachers should focus not only on the
technical capacities and functions of IT materials and activities, but
must attempt to more fully understand how their e-learners perceive
the learning environment. From the e-learner perspective, this paper
indicates that simply having IT tools available does not automatically
translate into all students becoming effective learners. More
evidence-based evaluative research is needed to allow e-learning and
e-teaching to reach full potential.
Abstract: One of the determinants of a firm-s prosperity is the
customers- perceived service quality and satisfaction. While service
quality is wide in scope, and consists of various dimensions, there
may be differences in the relative importance of these dimensions in
affecting customers- overall satisfaction of service quality.
Identifying the relative rank of different dimensions of service quality
is very important in that it can help managers to find out which
service dimensions have a greater effect on customers- overall
satisfaction. Such an insight will consequently lead to more effective
resource allocation which will finally end in higher levels of
customer satisfaction. This issue –despite its criticality- has not
received enough attention so far. Therefore, using a sample of 240
bank customers in Iran, an artificial neural network is developed to
address this gap in the literature. As customers- evaluation of service
quality is a subjective process, artificial neural networks –as a brain
metaphor- may appear to have a potentiality to model such a
complicated process. Proposing a neural network which is able to
predict the customers- overall satisfaction of service quality with a
promising level of accuracy is the first contribution of this study. In
addition, prioritizing the service quality dimensions in affecting
customers- overall satisfaction –by using sensitivity analysis of
neural network- is the second important finding of this paper.
Abstract: Integration of system process information obtained
through an image processing system with an evolving knowledge
database to improve the accuracy and predictability of wear particle
analysis is the main focus of the paper. The objective is to automate
intelligently the analysis process of wear particle using classification
via self organizing maps. This is achieved using relationship
measurements among corresponding attributes of various
measurements for wear particle. Finally, visualization technique is
proposed that helps the viewer in understanding and utilizing these
relationships that enable accurate diagnostics.
Abstract: Integration of system process information obtained
through an image processing system with an evolving knowledge
database to improve the accuracy and predictability of wear debris
analysis is the main focus of the paper. The objective is to automate
intelligently the analysis process of wear particle using classification
via self-organizing maps. This is achieved using relationship
measurements among corresponding attributes of various
measurements for wear debris. Finally, visualization technique is
proposed that helps the viewer in understanding and utilizing these
relationships that enable accurate diagnostics.
Abstract: An original DEA model is to evaluate each DMU
optimistically, but the interval DEA Model proposed in this paper
has been formulated to obtain an efficiency interval consisting of
Evaluations from both the optimistic and the pessimistic view points.
DMUs are improved so that their lower bounds become so large as to
attain the maximum Value one. The points obtained by this method
are called ideal points. Ideal PPS is calculated by ideal of efficiency
DMUs. The purpose of this paper is to rank DMUs by this ideal PPS.
Finally we extend the efficiency interval of a DMU under variable
RTS technology.