Abstract: Research has suggested that implicit learning tasks
may rely on episodic processing to generate above chance
performance on the standard classification tasks. The current
research examines the invariant features task (McGeorge and Burton,
1990) and argues that such episodic processing is indeed important.
The results of the experiment suggest that both rejection and
similarity strategies are used by participants in this task to
simultaneously reject unfamiliar items and to accept (falsely) familiar
items. Primarily these decisions are based on the presence of low or
high frequency goal based features of the stimuli presented in the
incidental learning phase. It is proposed that a goal based analysis of
the incidental learning task provides a simple step in understanding
which features of the episodic processing are most important for
explaining the match between incidental, implicit learning and test
performance.
Abstract: In this work, the results of mixing study by a jet mixer in a tank have been investigated in the laboratory scale. The tank dimensions are H/D=1 and the jet entrance have been considered in
the center of upper surface of tank. RNG-k-ε model is used as the
turbulent model for the prediction of the pattern of turbulent flow
inside the tank. For this purpose, a tank with volume of 110 liter is
simulated and it has been divided into 410,000 tetrahedral control
cells for performing the calculations. The grids at the vicinity of the
nozzle and suction pare are finer to get more accurate results. The
experimental results showed that in a vertical jet, the lowest mixing
time takes place at 35 degree. In addition, mixing time decreased by
increasing the Reynolds number. Furthermore, the CFD simulation
predicted the items as well a flow patterns precisely that validates the
experiments.
Abstract: Now-a-days, numbers of simulation software are
being used all over the world to solve Computational Fluid
Dynamics (CFD) related problems. In this present study, a
commercial CFD simulation software namely STAR-CCM+ is
applied to analyze the airflow characteristics inside a 2.5" hard
disk drive. Each step of the software is described adequately to
obtain the output and the data are verified with the theories to
justify the robustness of the simulation outcome. This study
gives an insight about the accuracy level of the CFD
simulation software to compute CFD related problems
although it largely depends upon the computer speed. Also
this study will open avenues for further research.
Abstract: As there are also graph methods of circuit analysis in
addition to algebraic methods, it is, in theory, clearly possible to
carry out an analysis of a whole switched circuit in two-phase
switching exclusively by the graph method as well. This article deals
with two methods of full-graph solving of switched circuits: by
transformation graphs and by two-graphs. It deals with the circuit
switched capacitors and the switched current, too. All methods are
presented in an equally detailed steps to be able to compare.
Abstract: The human knee joint has a three dimensional
geometry with multiple body articulations that produce complex
mechanical responses under loads that occur in everyday life and
sports activities. To produce the necessary joint compliance and
stability for optimal daily function various menisci and ligaments are
present while muscle forces are used to this effect. Therefore,
knowledge of the complex mechanical interactions of these load
bearing structures is necessary when treatment of relevant diseases is
evaluated and assisting devices are designed.
Numerical tools such as finite element analysis are suitable for
modeling such joints in order to understand their physics. They have
been used in the current study to develop an accurate human knee
joint and model its mechanical behavior. To evaluate the efficacy of
this articulated model, static load cases were used for comparison
purposes with previous experimentally verified modeling works
drawn from literature.
Abstract: This paper systematically investigates the timedependent
health outcomes for office staff during computer work
using the developed mathematical model. The model describes timedependent
health outcomes in multiple body regions associated with
computer usage. The association is explicitly presented with a doseresponse
relationship which is parametrized by body region
parameters. Using the developed model we perform extensive
investigations of the health outcomes statically and dynamically. We
compare the risk body regions and provide various severity rankings
of the discomfort rate changes with respect to computer-related
workload dynamically for the study population. Application of the
developed model reveals a wide range of findings. Such broad
spectrum of investigations in a single report literature is lacking.
Based upon the model analysis, it is discovered that the highest
average severity level of the discomfort exists in neck, shoulder, eyes,
shoulder joint/upper arm, upper back, low back and head etc. The
biggest weekly changes of discomfort rates are in eyes, neck, head,
shoulder, shoulder joint/upper arm and upper back etc. The fastest
discomfort rate is found in neck, followed by shoulder, eyes, head,
shoulder joint/upper arm and upper back etc. Most of our findings are
consistent with the literature, which demonstrates that the developed
model and results are applicable and valuable and can be utilized to
assess correlation between the amount of computer-related workload
and health risk.
Abstract: Prediction of highly non linear behavior of suspended
sediment flow in rivers has prime importance in the field of water
resources engineering. In this study the predictive performance of
two Artificial Neural Networks (ANNs) namely, the Radial Basis
Function (RBF) Network and the Multi Layer Feed Forward (MLFF)
Network have been compared. Time series data of daily suspended
sediment discharge and water discharge at Pari River was used for
training and testing the networks. A number of statistical parameters
i.e. root mean square error (RMSE), mean absolute error (MAE),
coefficient of efficiency (CE) and coefficient of determination (R2)
were used for performance evaluation of the models. Both the models
produced satisfactory results and showed a good agreement between
the predicted and observed data. The RBF network model provided
slightly better results than the MLFF network model in predicting
suspended sediment discharge.
Abstract: The present study is concerned with the free
convective two dimensional flow and heat transfer, within the
framework of Boussinesq approximation, in anisotropic fluid filled
porous rectangular enclosure subjected to end-to-end temperature
difference have been investigated using Lattice Boltzmann method
fornon-Darcy flow model. Effects of the moving lid direction (top,
bottom, left, and right wall moving in the negative and positive x&ydirections),
number of moving walls (one or two opposite walls), the
sliding wall velocity, and four different constant temperatures
opposite walls cases (two surfaces are being insulated and the
twoother surfaces areimposed to be at constant hot and cold
temperature)have been conducted. The results obtained are discussed
in terms of the Nusselt number, vectors, contours, and isotherms.
Abstract: Deep Brain Stimulation or DBS is the second solution
for Parkinson's Disease. Its three parameters are: frequency, pulse
width and voltage. They must be optimized to achieve successful
treatment. Nowadays it is done clinically by neurologists and there is
not certain numerical method to detect them. The aim of this research
is to introduce simulation and modeling of Parkinson's Disease
treatment as a computational procedure to select optimum voltage.
We recorded finger tremor signals of some Parkinsonian patients
under DBS treatment at constant frequency and pulse width but
variable voltages; then, we adapted a new model to fit these data. The
optimum voltages obtained by data fitting results were the same as
neurologists- commented voltages, which means modeling can be
used as an engineering method to select optimum stimulation
voltages.
Abstract: Software security testing is an important means to ensure software security and trustiness. This paper first mainly discusses the definition and classification of software security testing, and investigates methods and tools of software security testing widely. Then it analyzes and concludes the advantages and disadvantages of various methods and the scope of application, presents a taxonomy of security testing tools. Finally, the paper points out future focus and development directions of software security testing technology.
Abstract: An on-demand routing protocol for wireless ad hoc
networks is one that searches for and attempts to discover a route to
some destination node only when a sending node originates a data
packet addressed to that node. In order to avoid the need for such a
route discovery to be performed before each data packet is sent, such
routing protocols must cache routes previously discovered. This
paper presents an analysis of the effect of intelligent caching in a non
clustered network, using on-demand routing protocols in wireless ad
hoc networks. The analysis carried out is based on the Dynamic
Source Routing protocol (DSR), which operates entirely on-demand.
DSR uses the cache in every node to save the paths that are learnt
during route discovery procedure. In this implementation, caching
these paths only at intermediate nodes and using the paths from these
caches when required is tried. This technique helps in storing more
number of routes that are learnt without erasing the entries in the
cache, to store a new route that is learnt.
The simulation results on DSR have shown that this technique
drastically increases the available memory for caching the routes
discovered without affecting the performance of the DSR routing
protocol in any way, except for a small increase in end to end delay.
Abstract: The development of information and communication
technology, the increased use of the internet, as well as the effects of
the recession within the last years, have lead to the increased use of
cloud computing based solutions, also called on-demand solutions.
These solutions offer a large number of benefits to organizations as
well as challenges and risks, mainly determined by data visualization
in different geographic locations on the internet. As far as the specific
risks of cloud environment are concerned, data security is still
considered a peak barrier in adopting cloud computing. The present
study offers an approach upon ensuring the security of cloud data,
oriented towards the whole data life cycle. The final part of the study
focuses on the assessment of data security in the cloud, this
representing the bases in determining the potential losses and the
premise for subsequent improvements and continuous learning.
Abstract: Insulation used in transformer is mostly oil pressboard insulation. Insulation failure is one of the major causes of catastrophic failure of transformers. It is established that partial discharges (PD) cause insulation degradation and premature failure of insulation. Online monitoring of PDs can reduce the risk of catastrophic failure of transformers. There are different techniques of partial discharge measurement like, electrical, optical, acoustic, opto-acoustic and ultra high frequency (UHF). Being non invasive and non interference prone, acoustic emission technique is advantageous for online PD measurement. Acoustic detection of p.d. is based on the retrieval and analysis of mechanical or pressure signals produced by partial discharges. Partial discharges are classified according to the origin of discharges. Their effects on insulation deterioration are different for different types. This paper reports experimental results and analysis for classification of partial discharges using acoustic emission signal of laboratory simulated partial discharges in oil pressboard insulation system using three different electrode systems. Acoustic emission signal produced by PD are detected by sensors mounted on the experimental tank surface, stored on an oscilloscope and fed to computer for further analysis. The measured AE signals are analyzed using discrete wavelet transform analysis and wavelet packet analysis. Energy distribution in different frequency bands of discrete wavelet decomposed signal and wavelet packet decomposed signal is calculated. These analyses show a distinct feature useful for PD classification. Wavelet packet analysis can sort out any misclassification arising out of DWT in most cases.
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: A comparative study on the feasibility of producing instant high fibre plantain flour for diabetic fufu by blending soy residence with different plantain (Musa spp) varieties (Horn, false Horn and French), all sieved at 60 mesh, mixed in ratio of 60:40 was analyzed for their passing properties using standard analytical method. Results show that VIIIS60 had the highest peak viscosity (303.75 RVU), Trough value (182.08 RVU), final viscosity (284.50 RVU), and lowest in breakdown viscosity (79.58 RVU), set back value (88.17 RVU), peak time (4.36min), pasting temperature (81.18°C) and differed significantly (p
Abstract: Cardiac pulse-related artifacts in the EEG recorded
simultaneously with fMRI are complex and highly variable. Their
effective removal is an unsolved problem. Our aim is to develop an
adaptive removal algorithm based on the matching pursuit (MP)
technique and to compare it to established methods using a visual
evoked potential (VEP). We recorded the VEP inside the static
magnetic field of an MR scanner (with artifacts) as well as in an
electrically shielded room (artifact free). The MP-based artifact
removal outperformed average artifact subtraction (AAS) and
optimal basis set removal (OBS) in terms of restoring the EEG field
map topography of the VEP. Subsequently, a dipole model was fitted
to the VEP under each condition using a realistic boundary element
head model. The source location of the VEP recorded inside the MR
scanner was closest to that of the artifact free VEP after cleaning
with the MP-based algorithm as well as with AAS. While none of the
tested algorithms offered complete removal, MP showed promising
results due to its ability to adapt to variations of latency, frequency
and amplitude of individual artifact occurrences while still utilizing a
common template.
Abstract: This paper presents an optimized algorithm for robot localization which increases the correctness and accuracy of the estimating position of mobile robot to more than 150% of the past methods [1] in the uncertain and noisy environment. In this method the odometry and vision sensors are combined by an adapted well-known discrete kalman filter [2]. This technique also decreased the computation process of the algorithm by DKF simple implementation. The experimental trial of the algorithm is performed on the robocup middle size soccer robot; the system can be used in more general environments.
Abstract: The paper focuses on the implementation phase of the
strategy of the European Union and the national strategy of the
Czech Republic to promote academic and research staff with the
potential to produce results that provide innovation useful for
economic growth. It deals with the use of financial resources of the
Operational Program Education for Competitiveness at the
University of West Bohemia in Pilsen. The author presents an
example of two strategic projects in the field of human resources –
Excellence in Human Resources as a Source of Competitiveness and
New Excellence of Human Resources. The subject of this paper is the
potential contribution of newly recruited postdoctoral within these
projects for the University of West Bohemia in Pilsen and its internal
environment.
Abstract: The textile industry produces highly coloured
effluents containing polar and non-polar compounds. The textile mill
run by the Assam Polyester Co-operative Society Limited (APOL) is
situated at Rangia, about 55 km from Guwahati (26011' N, 91047' E)
in the northern bank of the river Brahmaputra, Assam (India). This
unit was commissioned in June 1988 and started commercial
production in November 1988. The installed capacity of the weaving
unit was 8000 m/day and that of the processing unit was 20,000
m/day. The mill has its own dyeing unit with a capacity of 1500-2000
kg/day. The western side of the mill consists of vast agricultural land
and the far northern and southern side of the mill has scattered human
population. The eastern side of the mill has a major road for
thoroughfare. The mill releases its effluents into the agricultural land
in the western side of the mill. The present study was undertaken to
assess the impact of the textile mill on surface soil quality in and
around the mill with particular reference to Cr, Mn, Ni and Zn.
Surface soil samples, collected along different directions at 200, 500
and 1000 m were digested and the metals were estimated with
Atomic Absorption Spectrophotometer. The metals were found in the
range of: Cr 50.9 – 105.0 mg kg-1, Mn 19.2- 78.6 mg kg-1, Ni 41.9 –
50.6 mg kg-1 and Zn 187.8 – 1095.8 mg kg-1. The study reveals
enrichment of Cr, Mn, Ni and Zn in the soil near the textile mill.
Abstract: Security risk models have been successful in estimating the likelihood of attack for simple security threats. However, modeling complex system and their security risk is even a challenge. Many methods have been proposed to face this problem. Often difficult to manipulate, and not enough all-embracing they are not as famous as they should with administrators and deciders. We propose in this paper a new tool to model big systems on purpose. The software, takes into account attack threats and security strength.