Abstract: Remarkable changes, like the progress in the ability to understand others' minds, can be identified in several socio-cognitive dimensions between age four and seven. Recently, the parenting attitudes have been considerate as one of the potential extrinsic modifiers of these important developmental aspects. The aim of present study is to explore the relationship among authoritarian parenting attitudes and individual differences in Theory of Mind performance. The study included ninety-two Costarrican preschoolers. Six False-belief tasks, an Advanced Theory of Mind test and the Parenting Attitudes Inventory were used. The results demonstrate that participants with high and low Authoritarian Parenting Received differ in their performance on First and Second Order False-belief tasks, but not in Advanced Theory of Mind tasks. Theoretical considerations about possible explanations regarding these results are discussed and methodological limitations are considered to shed light over future directions.
Abstract: In this paper, a novel associative memory model will be proposed and applied to memory retrievals based on the conventional continuous time model. The conventional model presents memory capacity is very low and retrieval process easily converges to an equilibrium state which is very different from the stored patterns. Genetic Algorithms is well-known with the capability of global optimal search escaping local optimum on progress to reach a global optimum. Based on the well-known idea of Genetic Algorithms, this work proposes a heuristic rule to make a mutation when the state of the network is trapped in a spurious memory. The proposal heuristic associative memory show the stored capacity does not depend on the number of stored patterns and the retrieval ability is up to ~ 1.
Abstract: Permanent magnet synchronous machines are known
as a good candidate for hybrid electric vehicles due to their unique
merits. However they have two major drawbacks i.e. high cost and
small speed range. In this paper an optimal design of a permanent
magnet machine is presented. A reduction of permanent magnet
material for a constant torque and an extension in speed and torque
ranges are chosen as the optimization aims. For this purpose the
analytical model of the permanent magnet synchronous machine is
derived and the appropriate design algorithm is devised. The genetic
algorithm is then employed to optimize some machine specifications.
Finally the finite element method is used to validate the designed
machine.
Abstract: The kinetics of palm oil catalytic cracking over
aluminum containing mesoporous silica Al-MCM-41 (5% Al) was
investigated in a batch autoclave reactor at the temperatures range of
573 – 673 K. The catalyst was prepared by using sol-gel technique
and has been characterized by nitrogen adsorption and x-ray
diffraction methods. Surface area of 1276 m2/g with average pore
diameter of 2.54 nm and pore volume of 0.811 cm3/g was obtained.
The experimental catalytic cracking runs were conducted using 50 g
of oil and 1 g of catalyst. The reaction pressure was recorded at
different time intervals and the data were analyzed using Levenberg-
Marquardt (LM) algorithm using polymath software. The results
show that the reaction order was found to be -1.5 and activation
energy of 3200 J/gmol.
Abstract: The forest fires in Thailand are annual occurrence which is the cause of air pollutions. This study intended to estimate the emission from forest fire during 2005-2009 using MODerateresolution Imaging Spectro-radiometer (MODIS) sensor aboard the Terra and Aqua satellites, experimental data, and statistical data. The forest fire emission is estimated using equation established by Seiler and Crutzen in 1982. The spatial and temporal variation of forest fire emission is analyzed and displayed in the form of grid density map. From the satellite data analysis suggested between 2005 and 2009, the number of fire hotspots occurred 86,877 fire hotspots with a significant highest (more than 80% of fire hotspots) in the deciduous forest. The peak period of the forest fire is in January to May. The estimation on the emissions from forest fires during 2005 to 2009 indicated that the amount of CO, CO2, CH4, and N2O was about 3,133,845 tons, 47,610.337 tons, 204,905 tons, and 6,027 tons, respectively, or about 6,171,264 tons of CO2eq. They also emitted 256,132 tons of PM10. The year 2007 was found to be the year when the emissions were the largest. Annually, March is the period that has the maximum amount of forest fire emissions. The areas with high density of forest fire emission were the forests situated in the northern, the western, and the upper northeastern parts of the country.
Abstract: In recent years various types of electric vehicles
has gained again increasing attention as an environmentally
benign technology in transport. Especially for urban areas with
high local pollution this Zero-emission technology (at the point
of use) is considered to provide proper solutions. Yet, the bad
economics and the limited driving ranges are still major barriers
for a broader market penetration of battery electric vehicles
(BEV) and of fuel cell vehicles (FCV). The major result of our
analyses is that the most important precondition for a further
dissemination of BEV in urban areas are emission-free zones.
This is an instrument which allows the promotion of BEV
without providing excessive subsidies. In addition, it is
important to note that the full benefits of EV can only be
harvested if the electricity used is produced from renewable
energy sources. That is to say, it has to be ensured that the use of
BEV in urban areas is clearly linked to a green electricity
purchase model. And moreover, the introduction of a CO2-
emission-based tax system would support this requirement.
Abstract: Thermo-chemical treatment (TCT) such as pyrolysis
is getting recognized as a valid route for (i) materials and valuable
products and petrochemicals recovery; (ii) waste recycling; and (iii)
elemental characterization. Pyrolysis is also receiving renewed
attention for its operational, economical and environmental
advantages. In this study, samples of polyethylene terephthalate
(PET) and polystyrene (PS) were pyrolysed in a microthermobalance
reactor (using a thermogravimetric-TGA setup). Both
polymers were prepared and conditioned prior to experimentation.
The main objective was to determine the kinetic parameters of the
depolymerization reactions that occur within the thermal degradation
process. Overall kinetic rate constants (ko) and activation energies
(Eo) were determined using the general kinetics theory (GKT)
method previously used by a number of authors. Fitted correlations
were found and validated using the GKT, errors were within ± 5%.
This study represents a fundamental step to pave the way towards the
development of scaling relationship for the investigation of larger
scale reactors relevant to industry.
Abstract: Spectrum is a scarce commodity, and considering the spectrum scarcity faced by the wireless-based service providers led to high congestion levels. Technical inefficiencies from pooled, since all networks share a common pool of channels, exhausting the available channels will force networks to block the services. Researchers found that cognitive radio (CR) technology may resolve the spectrum scarcity. A CR is a self-configuring entity in a wireless networking that senses its environment, tracks changes, and frequently exchanges information with their networks. However, CRN facing challenges and condition become worst while tracks changes i.e. reallocation of another under-utilized channels while primary network user arrives. In this paper, channels or resource reallocation technique based on DNA-inspired computing algorithm for CRN has been proposed.
Abstract: Network-Centric Air Defense Missile Systems
(NCADMS) represents the superior development of the air defense
missile systems and has been regarded as one of the major research
issues in military domain at present. Due to lack of knowledge and
experience on NCADMS, modeling and simulation becomes an effective
approach to perform operational analysis, compared with
those equation based ones. However, the complex dynamic interactions
among entities and flexible architectures of NCADMS put forward
new requirements and challenges to the simulation framework
and models. ABS (Agent-Based Simulations) explicitly addresses
modeling behaviors of heterogeneous individuals. Agents have capability
to sense and understand things, make decisions, and act on the
environment. They can also cooperate with others dynamically to
perform the tasks assigned to them. ABS proves an effective approach
to explore the new operational characteristics emerging in
NCADMS. In this paper, based on the analysis of network-centric
architecture and new cooperative engagement strategies for
NCADMS, an agent-based simulation framework by expanding the
simulation framework in the so-called System Effectiveness Analysis
Simulation (SEAS) was designed. The simulation framework specifies
components, relationships and interactions between them, the
structure and behavior rules of an agent in NCADMS. Based on scenario
simulations, information and decision superiority and operational
advantages in NCADMS were analyzed; meanwhile some
suggestions were provided for its future development.
Abstract: To realize the vision of ubiquitous computing, it is
important to develop a context-aware infrastructure which can help
ubiquitous agents, services, and devices become aware of their
contexts because such computational entities need to adapt themselves
to changing situations. A context-aware infrastructure manages the
context model representing contextual information and provides
appropriate information. In this paper, we introduce Context-Aware
Middleware for URC System (hereafter CAMUS) as a context-aware
infrastructure for a network-based intelligent robot system and discuss
the ontology-based context modeling and reasoning approach which is
used in that infrastructure.
Abstract: The purpose of Grid computing is to utilize
computational power of idle resources which are distributed in
different areas. Given the grid dynamism and its decentralize
resources, there is a need for an efficient scheduler for scheduling
applications. Since task scheduling includes in the NP-hard problems
various researches have focused on invented algorithms especially
the genetic ones. But since genetic is an inherent algorithm which
searches the problem space globally and does not have the efficiency
required for local searching, therefore, its combination with local
searching algorithms can compensate for this shortcomings. The aim
of this paper is to combine the genetic algorithm and GELS (GAGELS)
as a method to solve scheduling problem by which
simultaneously pay attention to two factors of time and number of
missed tasks. Results show that the proposed algorithm can decrease
makespan while minimizing the number of missed tasks compared
with the traditional methods.
Abstract: A fuzzy classifier using multiple ellipsoids approximating decision regions for classification is to be designed in this paper. An algorithm called Gustafson-Kessel algorithm (GKA) with an adaptive distance norm based on covariance matrices of prototype data points is adopted to learn the ellipsoids. GKA is able toadapt the distance norm to the underlying distribution of the prototypedata points except that the sizes of ellipsoids need to be determined a priori. To overcome GKA's inability to determine appropriate size ofellipsoid, the genetic algorithm (GA) is applied to learn the size ofellipsoid. With GA combined with GKA, it will be shown in this paper that the proposed method outperforms the benchmark algorithms as well as algorithms in the field.
Abstract: This paper introduces application of multi degree of freedom fuzzy(MDOFF) controller in permanent magnet (PM)drive system. The drive system model is developed for FO control. Simulation of the system is carried out to predict the performance at NL and under load,. The results indicate that application of MDOFF controller is effective for sensorless PM drive system.
Abstract: Fuzzy logic system (FLS) is used in this study to
predict the tractive performance in terms of traction force, and
motion resistance for an intelligent air cushion track vehicle while it
operates in the swamp peat. The system is effective to control the
intelligent air –cushion system with measuring the vehicle traction
force (TF), motion resistance (MR), cushion clearance height (CH)
and cushion pressure (CP). Ultrasonic displacement sensor, pull-in
solenoid electromagnetic switch, pressure control sensor, micro
controller, and battery pH sensor are incorporated with the Fuzzy
logic system to investigate experimentally the TF, MR, CH, and CP.
In this study, a comparison for tractive performance of an intelligent
air cushion track vehicle has been performed with the results obtained
from the predicted values of FLS and experimental actual values. The
mean relative error of actual and predicted values from the FLS
model on traction force, and total motion resistance are found as 5.58
%, and 6.78 % respectively. For all parameters, the relative error of
predicted values are found to be less than the acceptable limits. The
goodness of fit of the prediction values from the FLS model on TF,
and MR are found as 0.90, and 0.98 respectively.
Abstract: A frequency grouping approach for multi-channel
instantaneous blind source separation (I-BSS) of convolutive
mixtures is proposed for a lower net residual inter-symbol
interference (ISI) and inter-channel interference (ICI) than the
conventional short-time Fourier transform (STFT) approach. Starting
in the time domain, STFTs are taken with overlapping windows to
convert the convolutive mixing problem into frequency domain
instantaneous mixing. Mixture samples at the same frequency but
from different STFT windows are grouped together forming unique
frequency groups.
The individual frequency group vectors are input to the I-BSS
algorithm of choice, from which the output samples are dispersed
back to their respective STFT windows. After applying the inverse
STFT, the resulting time domain signals are used to construct the
complete source estimates via the weighted overlap-add method
(WOLA). The proposed algorithm is tested for source deconvolution
given two mixtures, and simulated along with the STFT approach to
illustrate its superiority for fairly motionless sources.
Abstract: A novel concept to balance and tradeoff between
make-to-stock and make-to-order has been hybrid MTS/MTO production context. One of the most important decisions involved in
the hybrid MTS/MTO environment is determining whether a product
is manufactured to stock, to order, or hybrid MTS/MTO strategy. In this paper, a model based on analytic network process is developed to tackle the addressed decision. Since the regarded decision deals with
the uncertainty and ambiguity of data as well as experts- and
managers- linguistic judgments, the proposed model is equipped with
fuzzy sets theory. An important attribute of the model is its generality due to diverse decision factors which are elicited from the
literature and developed by the authors. Finally, the model is validated by applying to a real case study to reveal how the proposed
model can actually be implemented.
Abstract: Hypernetworks are a generalized graph structure
representing higher-order interactions between variables. We present a
method for self-organizing hypernetworks to learn an associative
memory of sentences and to recall the sentences from this memory.
This learning method is inspired by the “mental chemistry" model of
cognition and the “molecular self-assembly" technology in
biochemistry. Simulation experiments are performed on a corpus of
natural-language dialogues of approximately 300K sentences
collected from TV drama captions. We report on the sentence
completion performance as a function of the order of word-interaction
and the size of the learning corpus, and discuss the plausibility of this
architecture as a cognitive model of language learning and memory.
Abstract: A spanning tree of a connected graph is a tree which
consists the set of vertices and some or perhaps all of the edges from
the connected graph. In this paper, a model for spanning tree
transformation of connected graphs into single-row networks, namely
Spanning Tree of Connected Graph Modeling (STCGM) will be
introduced. Path-Growing Tree-Forming algorithm applied with
Vertex-Prioritized is contained in the model to produce the spanning
tree from the connected graph. Paths are produced by Path-Growing
and they are combined into a spanning tree by Tree-Forming. The
spanning tree that is produced from the connected graph is then
transformed into single-row network using Tree Sequence Modeling
(TSM). Finally, the single-row routing problem is solved using a
method called Enhanced Simulated Annealing for Single-Row
Routing (ESSR).
Abstract: Among all geo-hydrological relationships, rainfallrunoff
relationship is of utmost importance in any hydrological
investigation and water resource planning. Spatial variation, lag time
involved in obtaining areal estimates for the basin as a whole can
affect the parameterization in design stage as well as in planning
stage. In conventional hydrological processing of data, spatial aspect
is either ignored or interpolated at sub-basin level. Temporal
variation when analysed for different stages can provide clues for its
spatial effectiveness. The interplay of space-time variation at pixel
level can provide better understanding of basin parameters.
Sustenance of design structures for different return periods and their
spatial auto-correlations should be studied at different geographical
scales for better management and planning of water resources.
In order to understand the relative effect of spatio-temporal
variation in hydrological data network, a detailed geo-hydrological
analysis of Betwa river catchment falling in Lower Yamuna Basin is
presented in this paper. Moreover, the exact estimates about the
availability of water in the Betwa river catchment, especially in the
wake of recent Betwa-Ken linkage project, need thorough scientific
investigation for better planning. Therefore, an attempt in this
direction is made here to analyse the existing hydrological and
meteorological data with the help of SPSS, GIS and MS-EXCEL
software. A comparison of spatial and temporal correlations at subcatchment
level in case of upper Betwa reaches has been made to
demonstrate the representativeness of rain gauges. First, flows at
different locations are used to derive correlation and regression
coefficients. Then, long-term normal water yield estimates based on
pixel-wise regression coefficients of rainfall-runoff relationship have
been mapped. The areal values obtained from these maps can
definitely improve upon estimates based on point-based
extrapolations or areal interpolations.
Abstract: Location-based services (LBS) exploit the known
location of a user to provide services dependent on their geographic
context and personalized needs [1].
The development and arrival of broadband mobile data networks
supported with mobile terminals equipped with new location
technologies like GPS have finally created opportunities for
implementation of LBS applications. But, from the other side,
collecting location information data in general raises privacy
concerns.
This paper presents results from two surveys of LBS acceptance in
Croatia. The first survey was administered on 181 students, and the
second extended survey involved pattern of 180 Croatian citizens.
We developed questionnaire which consists of descriptions of 15
different applications with scale which measures perceptions and
attitudes of users towards these applications.
We report the results to identify potential commercial applications
for LBS in B2C segment. Our findings suggest that some types of
applications like emergency&safety services and navigation have
significantly higher rate of acceptance than other types.