Abstract: This paper represents an investigation on how exploiting multiple transmit antennas by OFDM based wireless LAN subscribers can mitigate physical layer error rate. Then by comparing the Wireless LANs that utilize spatial diversity techniques with the conventional ones it will reveal how PHY and TCP throughputs behaviors are ameliorated. In the next step it will assess the same issues based on a cellular context operation which is mainly introduced as an innovated solution that beside a multi cell operation scenario benefits spatio-temporal signaling schemes as well. Presented simulations will shed light on the improved performance of the wide range and high quality wireless LAN services provided by the proposed approach.
Abstract: This paper focuses on operational risk measurement
techniques and on economic capital estimation methods. A data
sample of operational losses provided by an anonymous Central
European bank is analyzed using several approaches. Loss
Distribution Approach and scenario analysis method are considered.
Custom plausible loss events defined in a particular scenario are
merged with the original data sample and their impact on capital
estimates and on the financial institution is evaluated. Two main
questions are assessed – What is the most appropriate statistical
method to measure and model operational loss data distribution? and
What is the impact of hypothetical plausible events on the financial
institution? The g&h distribution was evaluated to be the most
suitable one for operational risk modeling. The method based on the
combination of historical loss events modeling and scenario analysis
provides reasonable capital estimates and allows for the measurement
of the impact of extreme events on banking operations.
Abstract: This work provides a practical method for the
development of rural road networks in rural areas of developing
countries. The proposed methodology enables to determine
obligatory points in the rural road network maximizing the number of
settlements that have access to basic services within a given
maximum distance. The proposed methodology is simple and
practical, hence, highly applicable to real-world scenarios, as
demonstrated in the definition of the road network for the rural areas
of Nepal.
Abstract: WiMAX is defined as Worldwide Interoperability for
Microwave Access by the WiMAX Forum, formed in June 2001 to
promote conformance and interoperability of the IEEE 802.16
standard, officially known as WirelessMAN. The attractive features
of WiMAX technology are very high throughput and Broadband
Wireless Access over a long distance. A detailed simulation
environment is demonstrated with the UGS, nrtPS and ertPS service
classes for throughput, delay and packet delivery ratio for a mixed
environment of fixed and mobile WiMAX. A simple mobility aspect
is considered for the mobile WiMAX and the PMP mode of
transmission is considered in TDD mode. The Network Simulator 2
(NS-2) is the tool which is used to simulate the WiMAX network
scenario. A simple Priority Scheduler and Weighted Round Robin
Schedulers are the WiMAX schedulers used in the research work
Abstract: The present disposal routes of sewage sludge represent a critical environmental issue in Egypt. Recently, there has been an increasing concern about sewage sludge management due to the environmental risks, which resulted from the fast expansion of wastewater treatment plants without equal attention in dealing with the produced sludge. This paper discusses the current situation of sewage sludge management in Egypt presenting a brief overview of the existing wastewater treatment plants, sludge production and characteristics as well as options of beneficial use and potential demand of sewage sludge under Egyptian conditions. The characteristics of sewage sludge are discussed considering the results of own sampling and analysis as well as previous studies. Furthermore, alternative treatment scenarios for sewage sludge, which have been recently developed in Egypt, are discussed and perspectives for a sustainable agricultural use are outlined.
Abstract: Overhead conveyor systems are in use in many installations around the world, meeting the widest range of applications possible. Overhead conveyor systems are particularly preferred in automotive industry but also at post offices. Overhead conveyor systems must always be integrated with a logistical process by finding the best way for a cheaper material flow in order to guarantee precise and fast workflows. With their help, any transport can take place without wasting ground and space, without excessive company capacity, lost or damaged products, erroneous delivery, endless travels and without wasting time. Ultra-light overhead conveyor systems are rope-based conveying systems with individually driven vehicles. The vehicles can move automatically on the rope and this can be realized by energy and signals. Crossings are realized by switches. Ultra-light overhead conveyor systems provide optimal material flow, which produces profit and saves time. This article introduces two new ultra-light overhead conveyor designs in logistics and explains their components. According to the explanation of the components, scenarios are created by means of their technical characteristics. The scenarios are visualized with the help of CAD software. After that, assumptions are made for application area. According to these assumptions scenarios are visualized. These scenarios help logistics companies achieve lower development costs as well as quicker market maturity.
Abstract: In this paper presents the mathematical model of
hydrothermal processes in thermal power plant with different wind
direction scenarios in the water reservoir, which is solved by the
Navier - Stokes and temperature equations for an incompressible
fluid in a stratified medium. Numerical algorithm based on the
method of splitting by physical parameters. Three dimensional
Poisson equation is solved with Fourier method by combination of
tridiagonal matrix method (Thomas algorithm).
Abstract: This paper describes the authorization system
architecture for Pervasive Grid environment. It discusses the
characteristics of classical authorization system and requirements of
the authorization system in pervasive grid environment as well.
Based on our analysis of current systems and taking into account the
main requirements of such pervasive environment, we propose new
authorization system architecture as an extension of the existing grid
authorization mechanisms. This architecture not only supports user
attributes but also context attributes which act as a key concept for
context-awareness thought. The architecture allows authorization of
users dynamically when there are changes in the pervasive grid
environment. For this, we opt for hybrid authorization method that
integrates push and pull mechanisms to combine the existing grid
authorization attributes with dynamic context assertions. We will
investigate the proposed architecture using a real testing environment
that includes heterogeneous pervasive grid infrastructures mapped
over multiple virtual organizations. Various scenarios are described
in the last section of the article to strengthen the proposed mechanism
with different facilities for the authorization procedure.
Abstract: This paper describes the architectural design
considerations for building a new class of application, a Personal
Knowledge Integrator and a particular example a Knowledge Theatre.
It then supports this description by describing a scenario of a child
acquiring knowledge and how this process could be augmented by
the proposed architecture and design of a Knowledge Theatre. David
Merrill-s first “principles of instruction" are kept in focus to provide
a background to view the learning potential.
Abstract: The necessity of ever-increasing use of distributed
data in computer networks is obvious for all. One technique that is
performed on the distributed data for increasing of efficiency and
reliablity is data rplication. In this paper, after introducing this
technique and its advantages, we will examine some dynamic data
replication. We will examine their characteristies for some overus
scenario and the we will propose some suggestion for their
improvement.
Abstract: In this paper, a Bayesian Network (BN) based system
is presented for providing clinical decision support to healthcare
practitioners in rural or remote areas of India for young infants or
children up to the age of 5 years. The government is unable to
appoint child specialists in rural areas because of inadequate number
of available pediatricians. It leads to a high Infant Mortality Rate
(IMR). In such a scenario, Intelligent Pediatric System provides a
realistic solution. The prototype of an intelligent system has been
developed that involves a knowledge component called an Intelligent
Pediatric Assistant (IPA); and User Agents (UA) along with their
Graphical User Interfaces (GUI). The GUI of UA provides the
interface to the healthcare practitioner for submitting sign-symptoms
and displaying the expert opinion as suggested by IPA. Depending
upon the observations, the IPA decides the diagnosis and the
treatment plan. The UA and IPA form client-server architecture for
knowledge sharing.
Abstract: This paper considers a scheduling problem in flexible
flow shops environment with the aim of minimizing two important
criteria including makespan and cumulative tardiness of jobs. Since
the proposed problem is known as an Np-hard problem in literature,
we have to develop a meta-heuristic to solve it. We considered
general structure of Genetic Algorithm (GA) and developed a new
version of that based on Data Envelopment Analysis (DEA). Two
objective functions assumed as two different inputs for each Decision
Making Unit (DMU). In this paper we focused on efficiency score of
DMUs and efficient frontier concept in DEA technique. After
introducing the method we defined two different scenarios with
considering two types of mutation operator. Also we provided an
experimental design with some computational results to show the
performance of algorithm. The results show that the algorithm
implements in a reasonable time.
Abstract: In this article, the design of a Supply Chain Network
(SCN) consisting of several suppliers, production plants, distribution
centers and retailers, is considered. Demands of retailers are
considered stochastic parameters, so we generate amounts of data via
simulation to extract a few demand scenarios. Then a mixed integer
two-stage programming model is developed to optimize
simultaneously two objectives: (1) minimization the fixed and
variable cost, (2) maximization the service level. A weighting method
is utilized to solve this two objective problem and a numerical
example is made to show the performance of the model.
Abstract: Mobile robots are used in a large field of scenarios,
like exploring contaminated areas, repairing oil rigs under water,
finding survivors in collapsed buildings, etc. Currently, there is no
unified intuitive user interface (UI) to control such complex mobile
robots. As a consequence, some scenarios are done without the
exploitation of experience and intuition of human teleoperators.
A novel framework has been developed to embed a flexible and
modular UI into a complete 3-D virtual reality simulation system.
This new approach wants to access maximum benefits of human
operators. Sensor information received from the robot is prepared for
an intuitive visualization. Virtual reality metaphors support the
operator in his decisions. These metaphors are integrated into a real
time stereo video stream. This approach is not restricted to any
specific type of mobile robot and allows for the operation of different
robot types with a consistent concept and user interface.
Abstract: This paper introduces a mixed integer programming model to find the optimum development plan for port Anzali. The model minimizes total system costs taking into account both port infrastructure costs and shipping costs. Due to the multipurpose function of the port, the model consists of 1020 decision variables and 2490 constraints. Results of the model determine the optimum number of berths that should be constructed in each period and for each type of cargo. In addition to, the results of sensitivity analysis on port operation quantity provide useful information for managers to choose the best scenario for port planning with the lowest investment risks. Despite all limitations-due to data availability-the model offers a straightforward decision tools to port planners aspiring to achieve optimum port planning steps.
Abstract: A multilayer self organizing neural neural network
(MLSONN) architecture for binary object extraction, guided by a beta
activation function and characterized by backpropagation of errors
estimated from the linear indices of fuzziness of the network output
states, is discussed. Since the MLSONN architecture is designed to
operate in a single point fixed/uniform thresholding scenario, it does
not take into cognizance the heterogeneity of image information in
the extraction process. The performance of the MLSONN architecture
with representative values of the threshold parameters of the beta
activation function employed is also studied. A three layer bidirectional
self organizing neural network (BDSONN) architecture
comprising fully connected neurons, for the extraction of objects from
a noisy background and capable of incorporating the underlying image
context heterogeneity through variable and adaptive thresholding,
is proposed in this article. The input layer of the network architecture
represents the fuzzy membership information of the image scene to
be extracted. The second layer (the intermediate layer) and the final
layer (the output layer) of the network architecture deal with the self
supervised object extraction task by bi-directional propagation of the
network states. Each layer except the output layer is connected to the
next layer following a neighborhood based topology. The output layer
neurons are in turn, connected to the intermediate layer following
similar topology, thus forming a counter-propagating architecture
with the intermediate layer. The novelty of the proposed architecture
is that the assignment/updating of the inter-layer connection weights
are done using the relative fuzzy membership values at the constituent
neurons in the different network layers. Another interesting feature
of the network lies in the fact that the processing capabilities of
the intermediate and the output layer neurons are guided by a beta
activation function, which uses image context sensitive adaptive
thresholding arising out of the fuzzy cardinality estimates of the
different network neighborhood fuzzy subsets, rather than resorting to
fixed and single point thresholding. An application of the proposed
architecture for object extraction is demonstrated using a synthetic
and a real life image. The extraction efficiency of the proposed
network architecture is evaluated by a proposed system transfer index
characteristic of the network.
Abstract: Ambient Intelligence (AmI) environments bring
significant potential to exploit sophisticated computer technology in
everyday life. In particular, the educational domain could be
significantly enhanced through AmI, as personalized and adapted
learning could be transformed from paper concepts and prototypes to
real-life scenarios. In this paper, an integrated framework is
presented, named ClassMATE, supporting ubiquitous computing and
communication in a school classroom. The main objective of
ClassMATE is to enable pervasive interaction and context aware
education in the technologically augmented classroom of the future.
Abstract: Climate change has profound consequences for the agriculture of south-eastern Australia and its climate-induced water shortage in the Murray-Darling Basin. Post Keynesian Economics (PKE) macro-dynamics, along with Kaleckian investment and growth theory, are used to develop an ecological-economic system dynamics model of this complex nonlinear river basin system. The Murray- Darling Basin Simulation Model (MDB-SM) uses the principles of PKE to incorporate the fundamental uncertainty of economic behaviors of farmers regarding the investments they make and the climate change they face, particularly as regards water ecosystem services. MDB-SM provides a framework for macroeconomic policies, especially for long-term fiscal policy and for policy directed at the sustainability of agricultural water, as measured by socio-economic well-being considerations, which include sustainable consumption and investment in the river basin. The model can also reproduce other ecological and economic aspects and, for certain parameters and initial values, exhibit endogenous business cycles and ecological sustainability with realistic characteristics. Most importantly, MDBSM provides a platform for the analysis of alternative economic policy scenarios. These results reveal the importance of understanding water ecosystem adaptation under climate change by integrating a PKE macroeconomic analytical framework with the system dynamics modelling approach. Once parameterised and supplied with historical initial values, MDB-SM should prove to be a practical tool to provide alternative long-term policy simulations of agricultural water and socio-economic well-being.
Abstract: In this paper, we propose improved versions of DVHop
algorithm as QDV-Hop algorithm and UDV-Hop algorithm for
better localization without the need for additional range measurement
hardware. The proposed algorithm focuses on third step of DV-Hop,
first error terms from estimated distances between unknown node and
anchor nodes is separated and then minimized. In the QDV-Hop
algorithm, quadratic programming is used to minimize the error to
obtain better localization. However, quadratic programming requires
a special optimization tool box that increases computational
complexity. On the other hand, UDV-Hop algorithm achieves
localization accuracy similar to that of QDV-Hop by solving
unconstrained optimization problem that results in solving a system
of linear equations without much increase in computational
complexity. Simulation results show that the performance of our
proposed schemes (QDV-Hop and UDV-Hop) is superior to DV-Hop
and DV-Hop based algorithms in all considered scenarios.
Abstract: The Address Resolution Protocol (ARP) is used by
computers to map logical addresses (IP) to physical addresses
(MAC). However ARP is an all trusting protocol and is stateless
which makes it vulnerable to many ARP cache poisoning attacks
such as Man-in-the-Middle (MITM) and Denial of service (DoS)
attacks. These flaws result in security breaches thus weakening the
appeal of the computer for exchange of sensitive data. In this paper
we describe ARP, outline several possible ARP cache poisoning
attacks and give the detailed of some attack scenarios in network
having both wired and wireless hosts. We have analyzed each of
proposed solutions, identify their strengths and limitations. Finally
get that no solution offers a feasible solution. Hence, this paper
presents an efficient and secure version of ARP that is able to cope
up with all these types of attacks and is also a feasible solution. It is a
stateful protocol, by storing the information of the Request frame in
the ARP cache, to reduce the chances of various types of attacks in
ARP. It is more efficient and secure by broadcasting ARP Reply
frame in the network and storing related entries in the ARP cache
each time when communication take place.