Abstract: Bandwidth allocation in wired network is less complex
and to allocate bandwidth in wireless networks is complex and
challenging, due to the mobility of source end system.This paper
proposes a new approach to bandwidth allocation to higher and lower
priority mobile nodes.In our proposal bandwidth allocation to new
mobile node is based on bandwidth utilization of existing mobile
nodes.The first section of the paper focuses on introduction to
bandwidth allocation in wireless networks and presents the existing
solutions available for allocation of bandwidth. The second section
proposes the new solution for the bandwidth allocation to higher and
lower priority nodes. Finally this paper ends with the analytical
evaluation of the proposed solution.
Abstract: This paper concerns a formal model to help the
simulation of agent societies where institutional roles and
institutional links can be specified operationally. That is, this paper
concerns institutional roles that can be specified in terms of a minimal behavioral capability that an agent should have in order to
enact that role and, thus, to perform the set of institutional functions that role is responsible for. Correspondingly, the paper concerns
institutional links that can be specified in terms of a minimal
interactional capability that two agents should have in order to, while
enacting the two institutional roles that are linked by that institutional
link, perform for each other the institutional functions supported by
that institutional link. The paper proposes a cognitive architecture
approach to institutional roles and institutional links, that is, an approach in which a institutional role is seen as an abstract cognitive
architecture that should be implemented by any concrete agent (or set of concrete agents) that enacts the institutional role, and in which
institutional links are seen as interactions between the two abstract
cognitive agents that model the two linked institutional roles. We
introduce a cognitive architecture for such purpose, called the
Institutional BCC (IBCC) model, which lifts Yoav Shoham-s BCC
(Beliefs-Capabilities-Commitments) agent architecture to social
contexts. We show how the resulting model can be taken as a means
for a cognitive architecture account of institutional roles and
institutional links of agent societies. Finally, we present an example
of a generic scheme for certain fragments of the social organization
of agent societies, where institutional roles and institutional links are
given in terms of the model.
Abstract: Estimating the lifetime distribution of computer networks in which nodes and links exist in time and are bound for failure is very useful in various applications. This problem is known to be NP-hard. In this paper we present efficient combinatorial approaches to Monte Carlo estimation of network lifetime distribution. We also present some simulation results.
Abstract: Optical Character Recognition (OCR) is a very old and of great interest in pattern recognition field. In this paper we introduce a very powerful approach to recognize Persian text. We have used morphological operators, especially Hit/Miss operator to descript each sub-word and by using a template matching approach we have tried to classify generated description. We used just one font in two different sizes to verify our approach. We achieved a very good rate, up to 99.9%.
Abstract: Zeolite A and MCM-41 have extensive applications in basic science, petrochemical science, energy conservation/storage, medicine, chemical sensor, air purification, environmentally benign composite structure and waste remediation. However, the use of zeolite A and MCM-41 in these areas, especially environmental remediation, are restricted due to prohibitive production cost. Efficient recycling of and resource recovery from coal fly ash has been a major topic of current international research interest, aimed at achieving sustainable development of human society from the viewpoints of energy, economy, and environmental strategy. This project reported an original, novel, green and fast methods to produce nano-porous zeolite A and MCM-41 materials from coal fly ash. For zeolite A, this novel production method allows a reduction by half of the total production time while maintaining a high degree of crystallinity of zeolite A which exists in a narrower particle size distribution. For MCM-41, this remarkably green approach, being an environmentally friendly process and reducing generation of toxic waste, can produce pure and long-range ordered MCM-41 materials from coal fly ash. This approach took 24 h at 25 oC to produce 9 g of MCM-41 materials from 30 g of the coal fly ash, which is the shortest time and lowest reaction temperature required to produce pure and ordered MCM-41 materials (having the largest internal surface area) compared to the values reported in the literature. Performance evaluation of the produced zeolite A and MCM-41 materials in wastewater treatment and air pollution control were reported. The residual fly ash was also converted to zeolite Na-P1 which showed good performance in removal of multi-metal ions in wastewater. In wastewater treatment, compared to commercial-grade zeolite A, adsorbents produced from coal fly ash were effective in removing multi heavy metal ions in water and could be an alternative material for treatment of wastewater. In methane emission abatement, the zeolite A (produced from coal fly ash) achieved similar methane removal efficiency compared to the zeolite A prepared from pure chemicals. This report provides the guidance for production of zeolite A and MCM-41 from coal fly ash by a cost-effective approach which opens potential applications of these materials in environmental industry. Finally, environmental and economic aspects of production of zeolite A and MCM-41 from coal fly ash were discussed.
Abstract: A systematic way to derive the conserved quantities for the axisymmetric liquid jet, free jet and wall jet using conservation laws is presented. The flow in axisymmetric jets is governed by Prandtl-s momentum boundary layer equation and the continuity equation. The multiplier approach is used to construct a basis of conserved vectors for the system of two partial differential equations for the two velocity components. The basis consists of two conserved vectors. By integrating the corresponding conservation laws across the jet and imposing the boundary conditions, conserved quantities are derived for the axisymmetric liquid and free jet. The multiplier approach applied to the third-order partial differential equation for the stream function yields two local conserved vectors one of which is a non-local conserved vector for the system. One of the conserved vectors gives the conserved quantity for the axisymmetric free jet but the conserved quantity for the wall jet is not obtained from the second conserved vector. The conserved quantity for the axisymmetric wall jet is derived from a non-local conserved vector of the third-order partial differential equation for the stream function. This non-local conserved vector for the third-order partial differential equation for the stream function is obtained by using the stream function as multiplier.
Abstract: This paper presented a MATLAB-based system named Smart Access Network Testing, Analyzing and Database (SANTAD), purposely for in-service transmission surveillance and self restoration against fiber fault in fiber-to-the-home (FTTH) access network. The developed program will be installed with optical line terminal (OLT) at central office (CO) to monitor the status and detect any fiber fault that occurs in FTTH downwardly from CO towards residential customer locations. SANTAD is interfaced with optical time domain reflectometer (OTDR) to accumulate every network testing result to be displayed on a single computer screen for further analysis. This program will identify and present the parameters of each optical fiber line such as the line's status either in working or nonworking condition, magnitude of decreasing at each point, failure location, and other details as shown in the OTDR's screen. The failure status will be delivered to field engineers for promptly actions, meanwhile the failure line will be diverted to protection line to ensure the traffic flow continuously. This approach has a bright prospect to improve the survivability and reliability as well as increase the efficiency and monitoring capabilities in FTTH.
Abstract: Currently WWW is the first solution for scholars in
finding information. But, analyzing and interpreting this volume of
information will lead to researchers overload in pursuing their
research.
Trend detection in scientific publication retrieval systems helps
scholars to find relevant, new and popular special areas by
visualizing the trend of input topic.
However, there are few researches on trend detection in scientific
corpora while their proposed models do not appear to be suitable.
Previous works lack of an appropriate representation scheme for
research topics.
This paper describes a method that combines Semantic Web and
ontology to support advance search functions such as trend detection
in the context of scholarly Semantic Web system (SSWeb).
Abstract: In this paper, we propose to study the synthesis of the
vertical dipole antenna over imperfect ground. The synthesis
implementation-s method for this type of antenna permits to
approach the appropriated radiance-s diagram. The used approach is
based on neural network. Our main contribution in this paper is the
extension of a synthesis model of this vertical dipole antenna over
imperfect ground.
Abstract: This paper focuses on creating a component model of information system under uncertainty. The paper identifies problem in current approach of component modeling and proposes fuzzy tool, which will work with vague customer requirements and propose components of the resulting component model. The proposed tool is verified on specific information system and results are shown in paper. After finding suitable sub-components of the resulting component model, the component model is visualised by tool.
Abstract: Basel III (or the Third Basel Accord) is a global
regulatory standard on bank capital adequacy, stress testing and
market liquidity risk agreed upon by the members of the Basel
Committee on Banking Supervision in 2010-2011, and scheduled to
be introduced from 2013 until 2018. Basel III is a comprehensive set
of reform measures. These measures aim to; (1) improve the banking
sector-s ability to absorb shocks arising from financial and economic
stress, whatever the source, (2) improve risk management and
governance, (3) strengthen banks- transparency and disclosures.
Similarly the reform target; (1) bank level or micro-prudential,
regulation, which will help raise the resilience of individual banking
institutions to periods of stress. (2) Macro-prudential regulations,
system wide risk that can build up across the banking sector as well
as the pro-cyclical implication of these risks over time. These two
approaches to supervision are complementary as greater resilience at
the individual bank level reduces the risk system wide shocks.
Macroeconomic impact of Basel III; OECD estimates that the
medium-term impact of Basel III implementation on GDP growth is
in the range -0,05 percent to -0,15 percent per year. On the other hand
economic output is mainly affected by an increase in bank lending
spreads as banks pass a rise in banking funding costs, due to higher
capital requirements, to their customers. Consequently the estimated
effects on GDP growth assume no active response from monetary
policy. Basel III impact on economic output could be offset by a
reduction (or delayed increase) in monetary policy rates by about 30
to 80 basis points. The aim of this paper is to create a framework
based on the recent regulations in order to prevent financial crises.
Thus the need to overcome the global financial crisis will contribute
to financial crises that may occur in the future periods. In the first
part of the paper, the effects of the global crisis on the banking
system examine the concept of financial regulations. In the second
part; especially in the financial regulations and Basel III are analyzed.
The last section in this paper explored the possible consequences of
the macroeconomic impacts of Basel III.
Abstract: Tacit knowledge has been one of the most discussed
and contradictory concepts in the field of knowledge management
since the mid 1990s. The concept is used relatively vaguely to refer
to any type of information that is difficult to articulate, which has led
to discussions about the original meaning of the concept (adopted
from Polanyi-s philosophy) and the nature of tacit knowing. It is
proposed that the subject should be approached from the perspective
of cognitive science in order to connect tacit knowledge to
empirically studied cognitive phenomena. Some of the most
important examples of tacit knowing presented by Polanyi are
analyzed in order to trace the cognitive mechanisms of tacit knowing
and to promote better understanding of the nature of tacit knowledge.
The cognitive approach to Polanyi-s theory reveals that the
tacit/explicit typology of knowledge often presented in the
knowledge management literature is not only artificial but totally
opposite approach compared to Polanyi-s thinking.
Abstract: Comparison of two approaches for the simulation of
the dynamic behaviour of a permanent magnet linear actuator is
presented. These are full coupled model, where the electromagnetic
field, electric circuit and mechanical motion problems are solved
simultaneously, and decoupled model, where first a set of static
magnetic filed analysis is carried out and then the electric circuit and
mechanical motion equations are solved employing bi-cubic spline
approximations of the field analysis results. The results show that the
proposed decoupled model is of satisfactory accuracy and gives more
flexibility when the actuator response is required to be estimated for
different external conditions, e.g. external circuit parameters or
mechanical loads.
Abstract: Multi-energy systems will enhance the system
reliability and power quality. This paper presents an integrated
approach for the design and operation of distributed energy resources
(DER) systems, based on energy hub modeling. A multi-objective
optimization model is developed by considering an integrated view of
electricity and natural gas network to analyze the optimal design and
operating condition of DER systems, by considering two conflicting
objectives, namely, minimization of total cost and the minimization
of environmental impact which is assessed in terms of CO2
emissions. The mathematical model considers energy demands of the
site, local climate data, and utility tariff structure, as well as technical
and financial characteristics of the candidate DER technologies. To
provide energy demands, energy systems including photovoltaic, and
co-generation systems, boiler, central power grid are considered. As
an illustrative example, a hotel in Iran demonstrates potential
applications of the proposed method. The results prove that
increasing the satisfaction degree of environmental objective leads to
increased total cost.
Abstract: We present a novel scheme to evaluate sinusoidal functions with low complexity and high precision using cubic spline interpolation. To this end, two different approaches are proposed to find the interpolating polynomial of sin(x) within the range [- π , π]. The first one deals with only a single data point while the other with two to keep the realization cost as low as possible. An approximation error optimization technique for cubic spline interpolation is introduced next and is shown to increase the interpolator accuracy without increasing complexity of the associated hardware. The architectures for the proposed approaches are also developed, which exhibit flexibility of implementation with low power requirement.
Abstract: Embedded systems need to respect stringent real
time constraints. Various hardware components included in such
systems such as cache memories exhibit variability and therefore
affect execution time. Indeed, a cache memory access from an
embedded microprocessor might result in a cache hit where the
data is available or a cache miss and the data need to be fetched
with an additional delay from an external memory. It is therefore
highly desirable to predict future memory accesses during
execution in order to appropriately prefetch data without incurring
delays. In this paper, we evaluate the potential of several artificial
neural networks for the prediction of instruction memory
addresses. Neural network have the potential to tackle the nonlinear
behavior observed in memory accesses during program
execution and their demonstrated numerous hardware
implementation emphasize this choice over traditional forecasting
techniques for their inclusion in embedded systems. However,
embedded applications execute millions of instructions and
therefore millions of addresses to be predicted. This very
challenging problem of neural network based prediction of large
time series is approached in this paper by evaluating various neural
network architectures based on the recurrent neural network
paradigm with pre-processing based on the Self Organizing Map
(SOM) classification technique.
Abstract: Flexible Job Shop Problem (FJSP) is an extension of
classical Job Shop Problem (JSP). The FJSP extends the routing
flexibility of the JSP, i.e assigning machine to an operation. Thus it
makes it more difficult than the JSP. In this study, Cooperative Coevolutionary
Genetic Algorithm (CCGA) is presented to solve the
FJSP. Makespan (time needed to complete all jobs) is used as the
performance evaluation for CCGA. In order to test performance and
efficiency of our CCGA the benchmark problems are solved.
Computational result shows that the proposed CCGA is comparable
with other approaches.
Abstract: This paper presents an application of level sets for the segmentation of abdominal and thoracic aortic aneurysms in CTA
datasets. An important challenge in reliably detecting aortic is the
need to overcome problems associated with intensity
inhomogeneities. Level sets are part of an important class of methods
that utilize partial differential equations (PDEs) and have been extensively applied in image segmentation. A kernel function in the
level set formulation aids the suppression of noise in the extracted
regions of interest and then guides the motion of the evolving contour
for the detection of weak boundaries. The speed of curve evolution
has been significantly improved with a resulting decrease in segmentation time compared with previous implementations of level
sets, and are shown to be more effective than other approaches in
coping with intensity inhomogeneities. We have applied the Courant
Friedrichs Levy (CFL) condition as stability criterion for our algorithm.
Abstract: Content-based music retrieval generally involves analyzing, searching and retrieving music based on low or high level features of a song which normally used to represent artists, songs or music genre. Identifying them would normally involve feature extraction and classification tasks. Theoretically the greater features analyzed, the better the classification accuracy can be achieved but with longer execution time. Technique to select significant features is important as it will reduce dimensions of feature used in classification and contributes to the accuracy. Artificial Immune System (AIS) approach will be investigated and applied in the classification task. Bio-inspired audio content-based retrieval framework (B-ACRF) is proposed at the end of this paper where it embraces issues that need further consideration in music retrieval performances.
Abstract: Partitioning is a critical area of VLSI CAD. In order to build complex digital logic circuits its often essential to sub-divide multi -million transistor design into manageable Pieces. This paper looks at the various partitioning techniques aspects of VLSI CAD, targeted at various applications. We proposed an evolutionary time-series model and a statistical glitch prediction system using a neural network with selection of global feature by making use of clustering method model, for partitioning a circuit. For evolutionary time-series model, we made use of genetic, memetic & neuro-memetic techniques. Our work focused in use of clustering methods - K-means & EM methodology. A comparative study is provided for all techniques to solve the problem of circuit partitioning pertaining to VLSI design. The performance of all approaches is compared using benchmark data provided by MCNC standard cell placement benchmark net lists. Analysis of the investigational results proved that the Neuro-memetic model achieves greater performance then other model in recognizing sub-circuits with minimum amount of interconnections between them.