Abstract: WIMAX relay station mesh network has been approved by IEEE 802.16j as a standard to provide a highly data rate transmission, the RS was implemented to extend the coverage zone of the BS, for instance the MSs previously were out of the coverage of the BS they become in the coverage of the RS, therefore these MSs can have Admission control from the BS through the RS. This paper describe a problem in the mesh network Relay station, for instance the problem of how to serve the mobile stations (MSs) which are out of the Relay station coverage. This paper also proposed a solution for mobile stations out of the coverage of the WIMAX Relay stations mesh Network. Therefore Ad-hoc network defined as a solution by using its admission control schema and apply it on the mobiles inside and outside the Relay station coverage.
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: 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: Falling has been one of the major concerns and threats
to the independence of the elderly in their daily lives. With the
worldwide significant growth of the aging population, it is essential
to have a promising solution of fall detection which is able to operate
at high accuracy in real-time and supports large scale implementation
using multiple cameras. Field Programmable Gate Array (FPGA) is a
highly promising tool to be used as a hardware accelerator in many
emerging embedded vision based system. Thus, it is the main
objective of this paper to present an FPGA-based solution of visual
based fall detection to meet stringent real-time requirements with
high accuracy. The hardware architecture of visual based fall
detection which utilizes the pixel locality to reduce memory accesses
is proposed. By exploiting the parallel and pipeline architecture of
FPGA, our hardware implementation of visual based fall detection
using FGPA is able to achieve a performance of 60fps for a series of
video analytical functions at VGA resolutions (640x480). The results
of this work show that FPGA has great potentials and impacts in
enabling large scale vision system in the future healthcare industry
due to its flexibility and scalability.
Abstract: Jordan exerts many efforts to nurture their academically gifted students in special schools since 2001. During
the past nine years of launching these schools, their learning and excellence environments were believed to be distinguished compared
to public schools. This study investigated the environments of gifted
students compared with other non-gifted, using a survey instrument
that measures the dimensions of family, peers, teachers, school- support, society, and resources –dimensions rooted deeply in supporting gifted education, learning, and achievement. A total
number of 109 were selected from excellence schools for
academically gifted students, and 119 non-gifted students were selected from public schools. Around 8.3% of the non-gifted students
reported that they “Never" received any support from their surrounding environments, 14.9% reported “Seldom" support, 23.7% reported “ Often" support, 26.0% reported “Frequent" support, and
32.8% reported “Very frequent" support. Where the gifted students reported more “Never" support than the non-gifted did with 11.3%,
“Seldom" support with 15.4%, “Often" support with 26.6%,
“Frequent" support with 29.0%, and reported “Very frequent" support less than the non-gifted students with 23.6%. Unexpectedly,
statistical differences were found between the two groups favoring
non-gifted students in perception of their surrounding environments
in specific dimensions, namely, school- support, teachers, and society. No statistical differences were found in the other dimensions
of the survey, namely, family, peers, and resources. As the
differences were found in teachers, school- support, and society, the
nurturing environments for the excellence schools need to be revised to adopt more creative teaching styles, rich school atmosphere and
infrastructures, interactive guiding for the students and their parents, promoting for the excellence environments, and re-build successful
identification models. Thus, families, schools, and society should
increase their cooperation, communication, and awareness of the
gifted supportive environments. However, more studies to investigate
other aspects of promoting academic giftedness and excellence are recommended.
Abstract: An Optimal Power Flow based on Improved Particle
Swarm Optimization (OPF-IPSO) with Generator Capability Curve
Constraint is used by NN-OPF as a reference to get pattern of
generator scheduling. There are three stages in Designing NN-OPF.
The first stage is design of OPF-IPSO with generator capability curve
constraint. The second stage is clustering load to specific range and
calculating its index. The third stage is training NN-OPF using
constructive back propagation method. In training process total load
and load index used as input, and pattern of generator scheduling
used as output. Data used in this paper is power system of Java-Bali.
Software used in this simulation is MATLAB.
Abstract: This paper presents nonlinear elastic dynamic analysis
of 3-D semi-rigid steel frames including geometric and connection
nonlinearities. The geometric nonlinearity is considered by using
stability functions and updating geometric stiffness matrix. The
nonlinear behavior of the steel beam-to-column connection is
considered by using a zero-length independent connection element
comprising of six translational and rotational springs. The nonlinear
dynamic equilibrium equations are solved by the Newmark numerical
integration method. The nonlinear time-history analysis results are
compared with those of previous studies and commercial SAP2000
software to verify the accuracy and efficiency of the proposed
procedure.
Abstract: In this paper, a mathematical model of human immunodeficiency
virus (HIV) is utilized and an optimization problem is
proposed, with the final goal of implementing an optimal 900-day
structured treatment interruption (STI) protocol. Two type of commonly
used drugs in highly active antiretroviral therapy (HAART),
reverse transcriptase inhibitors (RTI) and protease inhibitors (PI), are
considered. In order to solving the proposed optimization problem an
adaptive memetic algorithm with population management (AMAPM)
is proposed. The AMAPM uses a distance measure to control the
diversity of population in genotype space and thus preventing the
stagnation and premature convergence. Moreover, the AMAPM uses
diversity parameter in phenotype space to dynamically set the population
size and the number of crossovers during the search process.
Three crossover operators diversify the population, simultaneously.
The progresses of crossover operators are utilized to set the number
of each crossover per generation. In order to escaping the local optima
and introducing the new search directions toward the global optima,
two local searchers assist the evolutionary process. In contrast to
traditional memetic algorithms, the activation of these local searchers
is not random and depends on both the diversity parameters in
genotype space and phenotype space. The capability of AMAPM in
finding optimal solutions compared with three popular metaheurestics
is introduced.
Abstract: Developing a stable early warning system (EWS)
model that is capable to give an accurate prediction is a challenging
task. This paper introduces k-nearest neighbour (k-NN) method
which never been applied in predicting currency crisis before with the
aim of increasing the prediction accuracy. The proposed k-NN
performance depends on the choice of a distance that is used where in
our analysis; we take the Euclidean distance and the Manhattan as a
consideration. For the comparison, we employ three other methods
which are logistic regression analysis (logit), back-propagation neural
network (NN) and sequential minimal optimization (SMO). The
analysis using datasets from 8 countries and 13 macro-economic
indicators for each country shows that the proposed k-NN method
with k = 4 and Manhattan distance performs better than the other
methods.
Abstract: Space-time block code(STBC) has been studied to get
full diversity and full rate in multiple input multiple output(MIMO)
system. Achieving full rate is difficult in cooperative communications
due to the each user consumes the time slots for transmitting
information in cooperation phase. So combining MIMO systems
with cooperative communications has been researched for full diversity
and full rate. In orthogonal frequency division multiple access
(OFDMA) system, it is an alternative way that each user shares their
allocated subchannels instead of using the MIMO system to improve
the transmission rate. In this paper, a Decode-and-forward (DF)
based cooperative communication scheme is proposed. The proposed
scheme has improved transmission rate and reliability in multi-path
fading channel of the OFDMA up-link condition by modified STBC
structure and subchannel sharing.
Abstract: A supervisory scheme is proposed that implements Stepwise Safe Switching Logic. The functionality of the supervisory scheme is organized in the following eight functional units: Step- Wise Safe Switching unit, Common controllers design unit, Experimentation unit, Simulation unit, Identification unit, Trajectory cruise unit, Operating points unit and Expert system unit. The supervisory scheme orchestrates both the off-line preparative actions, as well as the on-line actions that implement the Stepwise Safe Switching Logic. The proposed scheme is a generic tool, that may be easily applied for a variety of industrial control processes and may be implemented as an automation software system, with the use of a high level programming environment, like Matlab.
Abstract: In this paper, the influencing parameters of a novel
purely mechanical wireless in-mould injection moulding sensor
were investigated. The sensor is capable of detecting the melt
front at predefined locations inside the mould. The sensor comprises
a movable pin which acts as the sensor element generating
structure-borne sound triggered by the passing melt front. Due to
the sensor design, melt pressure is the driving force. For pressure
level measurement during pin movement a pressure transducer
located at the same position as the movable pin. By deriving
a mathematical model for the mechanical movement, dominant
process parameters could be investigated towards their impact
on the melt front detection characteristic. It was found that the
sensor is not affected by the investigated parameters enabling it
for reliable melt front detection. In addition, it could be proved
that the novel sensor is in comparable range to conventional melt
front detection sensors.
Abstract: In this study, a minimal submaximal element of LIT(X) (the lattice of all intuitionistic topologies for X, ordered by inclusion) is determined. Afterwards, a new contractive property, intuitionistic mega-connectedness, is defined. We show that the submaximality and mega-connectedness are not complementary intuitionistic topological invariants by identifying those members of LIT(X) which are intuitionistic mega-connected.
Abstract: This research aims to create a model for analysis of student motivation behavior on e-Learning based on association rule mining techniques in case of the Information Technology for Communication and Learning Course at Suan Sunandha Rajabhat University. The model was created under association rules, one of the data mining techniques with minimum confidence. The results showed that the student motivation behavior model by using association rule technique can indicate the important variables that influence the student motivation behavior on e-Learning.
Abstract: Today's business environment requires that companies have access to highly relevant information in a matter of seconds.
Modern Business Intelligence tools rely on data structured mostly in traditional dimensional database schemas, typically represented by
star schemas. Dimensional modeling is already recognized as a
leading industry standard in the field of data warehousing although
several drawbacks and pitfalls were reported. This paper focuses on
the analysis of another data warehouse modeling technique - the
anchor modeling, and its characteristics in context with the standardized dimensional modeling technique from a query performance perspective. The results of the analysis show
information about performance of queries executed on database
schemas structured according to principles of each database modeling
technique.
Abstract: This paper presents a method of model selection and
identification of Hammerstein systems by hybridization of the genetic
algorithm (GA) and particle swarm optimization (PSO). An unknown
nonlinear static part to be estimated is approximately represented
by an automatic choosing function (ACF) model. The weighting
parameters of the ACF and the system parameters of the linear
dynamic part are estimated by the linear least-squares method. On
the other hand, the adjusting parameters of the ACF model structure
are properly selected by the hybrid algorithm of the GA and PSO,
where the Akaike information criterion is utilized as the evaluation
value function. Simulation results are shown to demonstrate the
effectiveness of the proposed hybrid algorithm.
Abstract: Water is the key of national development. Wherever a spring has been dried out or a river has changed its course, the area-s people have migrated and have been scattered and the area-s civilization has lost its brilliance. Today, air pollution, global warming and ozone layer damage are as the problems of countries, but certainly in the next decade the shortage and pollution of waters will be important issues of the world. The polluted waters are more dangerous in when they are used in agriculture. Because they infect plants and these plants are used in human and livestock consumption in food chain. With the increasing population growth and after that, the increase need to facilities and raw materials, human beings has started to do haste actions and wanted or unwanted destroyed his life basin. They try to overuse and capture his environment extremely, instead of having futurism approach in sustainable use of nature. This process includes Zayanderood recession, and caused its pollution after the transition from industrial and urban areas. Zayandehrood River in Isfahan is a vital artery of a living ecosystem. Now is the location of disposal waste water of many cities, villages and existing industries. The central area of the province is an important industrial place, and its environmental situation has reached a critical stage. Not only a large number of pollution-generating industries are active in the city limits, but outside of the city and adjacent districts Zayandehrood River, heavy industries like steel, Mobarakeh Steel and other tens great units pollute wild life. This article tries to study contaminant sources of Zayanderood and their severity, and determine and discuss the share of each of these resources by major industrial centers located in areas. At the end, we represent suitable strategy.
Abstract: This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of Pulping of Sugar Maple problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified problem where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.
Abstract: One part of the total employee’s reward is apart from basic wages or salary, employee’s benefits and intangible remuneration also so called contingent (variable) pay. Contingent pay is connected to performance, contribution, cap competency or skills of individual employees, and to team’s or company-wide performance or to combination of few of the mentioned possibilities. Sometimes among the contingent pay is also incorporated the remuneration based on length of employment, when the financial reward is not connected to performance or skills, but to length of continuous employment either on one working position or in one level of remuneration scale. Main aim of this article is to define, based on available information, contingent pay, describe individual forms, its advantages and disadvantages and possibilities to utilization in practice; but also bring information not only about its extent and level of utilization of contingent pay by companies in one of the Czech Republic’s regions, but also mention their practical experience with this type of remuneration.