Abstract: The aim of this paper is to propose a dynamic integrated approach, based on modularity concept and on the business ecosystem approach, that exploit different eBusiness services for SMEs under an open business network platform. The adoption of this approach enables firms to collaborate locally for delivering the best product/service to the customers as well as globally by accessing international markets, interrelate directly with the customers, create relationships and collaborate with worldwide actors. The paper will be structured as following: We will start by offering an overview of the state of the art of eBusiness platforms among SME of food and tourism firms and then we discuss the main drawbacks that characterize them. The digital business ecosystem approach and the modularity concept will be described as the theoretical ground in which our proposed integrated model is rooted. Finally, the proposed model along with a discussion of the main value creation potentialities it might create for SMEs will be presented.
Abstract: Several researchers have proposed methods about
combination of Genetic Algorithm (GA) and Fuzzy Logic (the use of
GA to obtain fuzzy rules and application of fuzzy logic in
optimization of GA). In this paper, we suggest a new method in
which fuzzy decision making is used to improve the performance of
genetic algorithm. In the suggested method, we determine the alleles
that enhance the fitness of chromosomes and try to insert them to the
next generation.
In this algorithm we try to present an innovative vaccination in the
process of reproduction in genetic algorithm, with considering the
trade off between exploration and exploitation.
Abstract: Depressurization and pressurization streams in
industrial systems constitute a work exchange network (WEN). In this
paper, a novel graphical approach for targeting energy conservation
potential of a WEN is proposed. Through constructing the composite
work curves in the pressure-work diagram and assuming all of the
mechanical energy of the depressurization streams is recovered by
expanders, the maximum work target of a WEN can be determined via
the proposed targeting steps. A WEN in an ammonia production
process is used as a case study to illustrate the applicability of the
proposed graphical approach.
Abstract: In this paper we consider a nonlinear feedback
control called augmented automatic choosing control (AACC)
using the automatic choosing functions of gradient optimization
type for nonlinear systems. Constant terms which arise from sectionwise
linearization of a given nonlinear system are treated as
coefficients of a stable zero dynamics. Parameters included in the
control are suboptimally selected by minimizing the Hamiltonian
with the aid of the genetic algorithm. This approach is applied to
a field excitation control problem of power system to demonstrate
the splendidness of the AACC. Simulation results show that the
new controller can improve performance remarkably well.
Abstract: In the current decade, wireless sensor networks are
emerging as a peculiar multi-disciplinary research area. By this
way, energy efficiency is one of the fundamental research themes
in the design of Medium Access Control (MAC) protocols for
wireless sensor networks. Thus, in order to optimize the energy
consumption in these networks, a variety of MAC protocols are
available in the literature. These schemes were commonly evaluated
under simple network density and a few results are published on
their robustness in realistic network-s size. We, in this paper, provide
an analytical study aiming to highlight the energy waste sources in
wireless sensor networks. Then, we experiment three energy efficient
hybrid CSMA/CA based MAC protocols optimized for wireless
sensor networks: Sensor-MAC (SMAC), Time-out MAC (TMAC)
and Traffic aware Energy Efficient MAC (TEEM). We investigate
these protocols with different network densities in order to discuss
the end-to-end performances of these schemes (i.e. in terms of energy
efficiency, delay and throughput). Through Network Simulator (NS-
2) implementations, we explore the behaviors of these protocols with
respect to the network density. In fact, this study may help the multihops
sensor networks designers to design or select the MAC layer
which matches better their applications aims.
Abstract: Banyan networks are really attractive for serving as
the optical switching architectures due to their unique properties of
small depth and absolute signal loss uniformity. The fact has been
established that the limitations of blocking nature and the nonavailability
of proper connections due to non-rearrangeable property
can be easily ruled out using electro-optic MZI switches as basic
switching elements. Combination of the horizontal expansion and
vertical stacking of optical banyan networks is an appropriate scheme
for constructing non-blocking banyan-based optical switching
networks. The interconnected banyan switching fabrics (IBSF) have
been considered and analyzed to best serve the purpose of optical
switching with electro-optic MZI basic elements. The cross/bar state
interchange for the switches has been facilitated by appropriate
voltage switching or the by the switching of operating wavelength.
The paper is dedicated to the modification of the basic switching
element being used as well as the architecture of the switching
network.
Abstract: The most common forensic activity is searching a hard
disk for string of data. Nowadays, investigators and analysts are
increasingly experiencing large, even terabyte sized data sets when
conducting digital investigations. Therefore consecutive searching can
take weeks to complete successfully. There are two primary search
methods: index-based search and bitwise search. Index-based
searching is very fast after the initial indexing but initial indexing
takes a long time. In this paper, we discuss a high speed bitwise search
model for large-scale digital forensic investigations. We used pattern
matching board, which is generally used for network security, to
search for string and complex regular expressions. Our results indicate
that in many cases, the use of pattern matching board can substantially
increase the performance of digital forensic search tools.
Abstract: The success of an electronic system in a System-on- Chip is highly dependent on the efficiency of its interconnection network, which is constructed from routers and channels (the routers move data across the channels between nodes). Since neither classical bus based nor point to point architectures can provide scalable solutions and satisfy the tight power and performance requirements of future applications, the Network-on-Chip (NoC) approach has recently been proposed as a promising solution. Indeed, in contrast to the traditional solutions, the NoC approach can provide large bandwidth with moderate area overhead. The selected topology of the components interconnects plays prime rule in the performance of NoC architecture as well as routing and switching techniques that can be used. In this paper, we present two generic NoC architectures that can be customized to the specific communication needs of an application in order to reduce the area with minimal degradation of the latency of the system. An experimental study is performed to compare these structures with basic NoC topologies represented by 2D mesh, Butterfly-Fat Tree (BFT) and SPIN. It is shown that Cluster mesh (CMesh) and MinRoot schemes achieves significant improvements in network latency and energy consumption with only negligible area overhead and complexity over existing architectures. In fact, in the case of basic NoC topologies, CMesh and MinRoot schemes provides substantial savings in area as well, because they requires fewer routers. The simulation results show that CMesh and MinRoot networks outperforms MESH, BFT and SPIN in main performance metrics.
Abstract: Internet addiction has become a critical problem on
adolescents in Taiwan, and its negative effects on various dimensions
of adolescent development caught the attention of educational and
psychological experts. This study examined the correlation between
cognitive (locus of control) and emotion (emotion venting strategies)
factors on internet addiction of adolescents in Taiwan. Using the
Compulsive Internet Use (CIU) and the Emotion Venting Strategy
scales, a survey was conducted and 215 effective samples (students
ranging from12 to14 years old) returned. Quantitative analysis
methods such as descriptive statistics, t-test, ANOVA, Pearson
correlations and multiple regression were adopted. The results were as
follows: 1. Severity of Internet addiction has significant gender
differences; boys were at a higher risk than girls in becoming addicted
to the Internet. 2. Emotion venting, locus of control and internet
addiction have been shown to be positive correlated with one another.
3. Setting the locus of control as the control variable, emotion venting
strategy has positive and significant contribution to internet addiction.
The results of this study suggest that coaching deconstructive emotion
strategies and cognitive believes are encouraged to integrate with
actual field work.
Abstract: The back-propagation algorithm calculates the weight
changes of an artificial neural network, and a two-term algorithm
with a dynamically optimal learning rate and a momentum factor
is commonly used. Recently the addition of an extra term, called a
proportional factor (PF), to the two-term BP algorithm was proposed.
The third term increases the speed of the BP algorithm. However,
the PF term also reduces the convergence of the BP algorithm, and
optimization approaches for evaluating the learning parameters are
required to facilitate the application of the three terms BP algorithm.
This paper considers the optimization of the new back-propagation
algorithm by using derivative information. A family of approaches
exploiting the derivatives with respect to the learning rate, momentum
factor and proportional factor is presented. These autonomously
compute the derivatives in the weight space, by using information
gathered from the forward and backward procedures. The three-term
BP algorithm and the optimization approaches are evaluated using
the benchmark XOR problem.
Abstract: A simple network model is developed in OPNET to
study the performance of the Wi-Fi protocol. The model is simulated
in OPNET and performance factors such as load, throughput and delay
are analysed from the model. Four applications such as oracle, http, ftp
and voice are applied over the Wireless LAN network to determine the
throughput. The voice application utilises a considerable amount of
bandwidth of up to 5Mbps, as a result the 802.11g standard of the
Wi-Fi protocol was chosen which can support a data rate of up to
54Mbps. Results indicate that when the load in the Wi-Fi network is
increased the queuing delay on the point-to-point links in the Wi-Fi
network significantly reduces until it is comparable to that of WiMAX.
In conclusion, the queuing delay of the Wi-Fi protocol for the network
model simulated was about 0.00001secs comparable to WiMAX
network values.
Abstract: Verapamil has been shown to inhibit fentanyl uptake in vitro and is a potent P-glycoprotein inhibitor. Tissue partitioning of loperamide, a commercially available opioid, is closely controlled by the P-gp efflux transporter. The following studies were designed to evaluate the effect of opioids on verapamil partitioning in the lung and brain, in vivo. Opioid (fentanyl or loperamide) was administered by intravenous infusion to Sprague Dawley rats alone or in combination with verapamil and plasma, with lung and brain tissues were collected at 1, 5, 6, 8, 10 and 60 minutes. Drug dispositions were modeled by recirculatory pharmacokinetic models. Fentanyl slightly increased the verapamil lung (PL) partition coefficient yet decreased the brain (PB) partition coefficient. Furthermore, loperamide significantly increased PLand PB. Fentanyl reduced the verapamil volume of distribution (V1) and verapamil elimination clearance (ClE). Fentanyl decreased verapamil brain partitioning, yet increased verapamil lung partitioning. Also, loperamide increased lung and brain partitioning in vivo. These results suggest that verapamil and fentanyl may be substrates of an unidentified inward transporter in brain tissue and confirm that verapamil and loperamide are substrates of the efflux transporter P-gp.
Abstract: In this paper we describes the authentication for DHCP
(Dynamic Host Configuration Protocol) message which provides the
efficient key management and reduces the danger replay attack without
an additional packet for a replay attack. And the authentication for
DHCP message supports mutual authentication and provides both
entity authentication and message authentication. We applied the
authentication for DHCP message to the home network environments
and tested through a home gateway.
Abstract: Quantum cryptography offers a way of key agreement,
which is unbreakable by any external adversary. Authentication is
of crucial importance, as perfect secrecy is worthless if the identity
of the addressee cannot be ensured before sending important information.
Message authentication has been studied thoroughly, but no
approach seems to be able to explicitly counter meet-in-the-middle
impersonation attacks. The goal of this paper is the development of
an authentication scheme being resistant against active adversaries
controlling the communication channel. The scheme is built on top
of a key-establishment protocol and is unconditionally secure if built
upon quantum cryptographic key exchange. In general, the security
is the same as for the key-agreement protocol lying underneath.
Abstract: An adaptive fuzzy PID controller with gain scheduling is proposed in this paper. The structure of the proposed gain scheduled fuzzy PID (GS_FPID) controller consists of both fuzzy PI-like controller and fuzzy PD-like controller. Both of fuzzy PI-like and PD-like controllers are weighted through adaptive gain scheduling, which are also determined by fuzzy logic inference. A modified genetic algorithm called accumulated genetic algorithm is designed to learn the parameters of fuzzy inference system. In order to learn the number of fuzzy rules required for the TSK model, the fuzzy rules are learned in an accumulated way. In other words, the parameters learned in the previous rules are accumulated and updated along with the parameters in the current rule. It will be shown that the proposed GS_FPID controllers learned by the accumulated GA perform well for not only the regular linear systems but also the higher order and time-delayed systems.
Abstract: Currently, most of distance learning courses can only
deliver standard material to students. Students receive course content
passively which leads to the neglect of the goal of education – “to suit
the teaching to the ability of students". Providing appropriate course
content according to students- ability is the main goal of this paper.
Except offering a series of conventional learning services, abundant
information available, and instant message delivery, a complete online
learning environment should be able to distinguish between students-
ability and provide learning courses that best suit their ability.
However, if a distance learning site contains well-designed course
content and design but fails to provide adaptive courses, students will
gradually loss their interests and confidence in learning and result in
ineffective learning or discontinued learning. In this paper, an
intelligent tutoring system is proposed and it consists of several
modules working cooperatively in order to build an adaptive learning
environment for distance education. The operation of the system is
based on the result of Self-Organizing Map (SOM) to divide students
into different groups according to their learning ability and learning
interests and then provide them with suitable course content.
Accordingly, the problem of information overload and internet traffic
problem can be solved because the amount of traffic accessing the
same content is reduced.
Abstract: The effect of magnetic field on germination
characteristics of two wheat Seeds has been studied under laboratory
conditions. Seeds were magnetically exposed to magnetic field
strengths, 125 or 250mT for different periods of time. Mean
germination time and the time required to obtain 10, 25, 50, 75 and
90%of seeds to germinate were calculated. The germination time for
each treatment were in general, higher than corresponding control
values, in the other word in treated seeds time required for mean seed
germination time increased nearly 3 hours in compared non treated
control seeds. T10 for doses D5, D6, D11 and D12 significantly higher
than the control values for both cultivars. Mean germination time
(MGT) in both cultivars significantly increased when the time of
seed exposed at magnetic field treatments increased , about 3 and 2
hour respectively for Omid and BCR cultivars.
Abstract: Motion detection is a basic operation in the selection of significant segments of the video signals. For an effective Human Computer Intelligent Interaction, the computer needs to recognize the motion and track the moving object. Here an efficient neural network system is proposed for motion detection from the static background. This method mainly consists of four parts like Frame Separation, Rough Motion Detection, Network Formation and Training, Object Tracking. This paper can be used to verify real time detections in such a way that it can be used in defense applications, bio-medical applications and robotics. This can also be used for obtaining detection information related to the size, location and direction of motion of moving objects for assessment purposes. The time taken for video tracking by this Neural Network is only few seconds.
Abstract: In this paper, an intelligent algorithm for optimal
document archiving is presented. It is kown that electronic archives
are very important for information system management. Minimizing
the size of the stored data in electronic archive is a main issue to
reduce the physical storage area. Here, the effect of different types of
Arabic fonts on electronic archives size is discussed. Simulation
results show that PDF is the best file format for storage of the Arabic
documents in electronic archive. Furthermore, fast information
detection in a given PDF file is introduced. Such approach uses fast
neural networks (FNNs) implemented in the frequency domain. The
operation of these networks relies on performing cross correlation in
the frequency domain rather than spatial one. It is proved
mathematically and practically that the number of computation steps
required for the presented FNNs is less than that needed by
conventional neural networks (CNNs). Simulation results using
MATLAB confirm the theoretical computations.
Abstract: Reachability graph (RG) generation suffers from the
problem of exponential space and time complexity. To alleviate the
more critical problem of time complexity, this paper presents the new
approach for RG generation for the Petri net (PN) models of parallel
processes. Independent RGs for each parallel process in the PN
structure are generated in parallel and cross-product of these RGs
turns into the exhaustive state space from which the RG of given
parallel system is determined. The complexity analysis of the
presented algorithm illuminates significant decrease in the time
complexity cost of RG generation. The proposed technique is
applicable to parallel programs having multiple threads with the
synchronization problem.