Abstract: Many contemporary telemedical applications rely on
regular consultations over the phone or video conferencing which
consumes valuable resources such as the time of the doctors. Some
applications or treatments allow automated diagnostics on the patient
side which only notifies the doctors in case a significant worsening
of patient’s condition is measured.
Such programs can save valuable resources but an important
implementation issue is how to ensure effective and cheap diagnostics
on the patient side. First, specific diagnostic devices on patient side
are expensive and second, they need to be user-˜friendly to encourage
patient’s cooperation and reduce errors in usage which may cause
noise in diagnostic data.
This article proposes the use of modern smartphones and various
build-in or attachable sensors as universal diagnostic devices applicable
in a wider range of telemedical programs and demonstrates their
application on a case-study – a program for schizophrenic relapse
prevention.
Abstract: The emergence of the Internet has brewed the
revolution of information storage and retrieval. As most of the
data in the web is unstructured, and contains a mix of text,
video, audio etc, there is a need to mine information to cater to
the specific needs of the users without loss of important
hidden information. Thus developing user friendly and
automated tools for providing relevant information quickly
becomes a major challenge in web mining research. Most of
the existing web mining algorithms have concentrated on
finding frequent patterns while neglecting the less frequent
ones that are likely to contain outlying data such as noise,
irrelevant and redundant data. This paper mainly focuses on
Signed approach and full word matching on the organized
domain dictionary for mining web content outliers. This
Signed approach gives the relevant web documents as well as
outlying web documents. As the dictionary is organized based
on the number of characters in a word, searching and retrieval
of documents takes less time and less space.
Abstract: This paper deals with econometric analysis of real
retail trade turnover. It is a part of an extensive scientific research
about modern trends in Croatian national economy. At the end of the
period of transition economy, Croatia confronts with challenges and
problems of high consumption society. In such environment as
crucial economic variables: real retail trade turnover, average
monthly real wages and household loans are chosen for consequence
analysis. For the purpose of complete procedure of multiple
econometric analysis data base adjustment has been provided.
Namely, it has been necessary to deflate original national statistics
data of retail trade turnover using consumer price indices, as well as
provide process of seasonally adjustment of its contemporary
behavior. In model establishment it has been necessary to involve the
overcoming procedure for the autocorrelation and colinearity
problems. Moreover, for case of time-series shift a specific
appropriate econometric instrument has been applied. It would be
emphasize that the whole methodology procedure is based on the real
Croatian national economy time-series.
Abstract: Ceramics comprise the largest proportion of Korea-s cultural heritage currently preserved (Cited from “The Beauty of Old Ceramics of Korea" written by Yoon Yong-iee). Thus, this researcher conducted this investigation in an attempt to gain insight into Korea-s past culture and the lost period of the colonial period and the Korean War by looking into the ceramics. Korea, China and Japan are part of the similar cultural bloc within the East Asian region. Their porcelains manifest distinctive characteristics by each nation along with similarities. Thus, this research seeks to find the distinctive characteristics of the Korean porcelain by conducting comparative analysis of the similarities and distinctive characteristics. These distinctive characteristics are manifested effectively in the colors of the porcelains following the materials that can be obtained in Korea, China and Japan and production method. Likewise, this research seeks to identify the characteristics of the Korean porcelains- colors based on the comparative analysis of the porcelain colors. The reasons that porcelains were selected were because they are the most well preserved cultural remains in Korea and since they have both similarities and distinctive characteristics due to the cultural interchanges among Korea, China and Japan, which facilitates comparative study. The research targets include Korea, China and Japan-s porcelains. By comparing the colors of the porcelains from Korea, China and Japan that have their distinctive characteristics, this research seeks to identify Korea-specific porcelain colors. These colors derive from the materials that can be obtained only in Korea, and they are affected by the ideologies that governed at the time. This research is meaningful in the sense that this identifies the colors that embraces the Korean culture and provides important data by leveraging the study of the characteristics of the Korea-specific porcelains.
Abstract: The purpose of this study was to find out the
effectiveness of neurological impress method and repeated reading
technique on reading fluency of children with learning disabilities.
Thirty primary four pupils in three public primary schools
participated in the study. There were two experimental groups and a
control. This research employed a 3 by 2 factorial matrix and the
participants were taught for one session. Two hypotheses were
formulated to guide the research. T-test was used to analyse the data
gathered, and data analysis revealed that pupils exposed to the two
treatment strategies had improvement in their reading fluency. It was
recommended that the two strategies used in the study can be used to
intervene in reading fluency problems in children with learning
disabilities.
Abstract: The performance results of the athletes competed in
the 1988-2008 Olympic Games were analyzed (n = 166). The data
were obtained from the IAAF official protocols. In the principal
component analysis, the first three principal components explained
70% of the total variance. In the 1st principal component (with
43.1% of total variance explained) the largest factor loadings were
for 100m (0.89), 400m (0.81), 110m hurdle run (0.76), and long jump
(–0.72). This factor can be interpreted as the 'sprinting performance'.
The loadings on the 2nd factor (15.3% of the total variance)
presented a counter-intuitive throwing-jumping combination: the
highest loadings were for throwing events (javelin throwing 0.76;
shot put 0.74; and discus throwing 0.73) and also for jumping events
(high jump 0.62; pole vaulting 0.58). On the 3rd factor (11.6% of
total variance), the largest loading was for 1500 m running (0.88); all
other loadings were below 0.4.
Abstract: This paper employs a the variable returns to scale DEA
model to take account of risky assets and estimate the operating
efficiencies for the 21 domestic listed securities firms during the
period 2005-2009. Evidence is found that on average the brokerage
securities firms- operating efficiencies are better than integrated
securities firms. Evidence is also found that the technical inefficiency
from inappropriate management constitutes the main source of the
operating inefficiency for both types of securities firms. Moreover, the
scale economies prevail in brokerage and integrated securities firms,
in other words, which exhibit the characteristic of increasing returns to
scale.
Abstract: In this paper 2D Simulation of catalytic Fixed Bed Reactor in Fischer-Tropsch Synthesis of GTL technology has been performed utilizing computational fluid dynamics (CFD). Synthesis gas (a mixture of carbon monoxide and hydrogen) has been used as feedstock. The reactor was modeled and the model equations were solved employing finite volume method. The model was validated against the experimental data reported in literature. The comparison showed a good agreement between simulation results and the experimental data. In addition, the model was applied to predict the concentration contours of the reactants and products along the length of reactor.
Abstract: A vast array of biological materials, especially algae have received increasing attention for heavy metal removal. Algae have been proven to be cheaper, more effective for the removal of metallic elements in aqueous solutions. A fresh water algal strain was isolated from Zoo Lake, Johannesburg, South Africa and identified as Desmodesmus sp. This paper investigates the efficacy of Desmodesmus sp.in removing heavy metals contaminating the Wonderfonteinspruit Catchment Area (WCA) water bodies. The biosorption data fitted the pseudo-second order and Langmuir isotherm models. The Langmuir maximum uptakes gave the sequence: Mn2+>Ni2+>Fe2+. The best results for kinetic study was obtained in concentration 120 ppm for Fe3+ and Mn2+, whilst for Ni2+ was at 20 ppm, which is about the same concentrations found in contaminated water in the WCA (Fe3+115 ppm, Mn2+ 121 ppm and Ni2+ 26.5 ppm).
Abstract: Biclustering is a very useful data mining technique for
identifying patterns where different genes are co-related based on a
subset of conditions in gene expression analysis. Association rules
mining is an efficient approach to achieve biclustering as in
BIMODULE algorithm but it is sensitive to the value given to its
input parameters and the discretization procedure used in the
preprocessing step, also when noise is present, classical association
rules miners discover multiple small fragments of the true bicluster,
but miss the true bicluster itself. This paper formally presents a
generalized noise tolerant bicluster model, termed as μBicluster. An
iterative algorithm termed as BIDENS based on the proposed model
is introduced that can discover a set of k possibly overlapping
biclusters simultaneously. Our model uses a more flexible method to
partition the dimensions to preserve meaningful and significant
biclusters. The proposed algorithm allows discovering biclusters that
hard to be discovered by BIMODULE. Experimental study on yeast,
human gene expression data and several artificial datasets shows that
our algorithm offers substantial improvements over several
previously proposed biclustering algorithms.
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: In order to achieve better road utilization and traffic
efficiency, there is an urgent need for a travel information delivery
mechanism to assist the drivers in making better decisions in the
emerging intelligent transportation system applications. In this paper,
we propose a relayed multicast scheme under heterogeneous networks
for this purpose. In the proposed system, travel information consisting
of summarized traffic conditions, important events, real-time traffic
videos, and local information service contents is formed into layers
and multicasted through an integration of WiMAX infrastructure and
Vehicular Ad hoc Networks (VANET). By the support of adaptive
modulation and coding in WiMAX, the radio resources can be
optimally allocated when performing multicast so as to dynamically
adjust the number of data layers received by the users. In addition to
multicast supported by WiMAX, a knowledge propagation and
information relay scheme by VANET is designed. The experimental
results validate the feasibility and effectiveness of the proposed
scheme.
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: 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: We suggest a novel method to incorporate longterm
redundancy (LTR) in signal time domain compression
methods. The proposition is based on block-sorting and curve
simplification. The proposition is illustrated on the ECG
signal as a post-processor for the FAN method. Test
applications on the new so-obtained FAN+ method using the
MIT-BIH database show substantial improvement of the
compression ratio-distortion behavior for a higher quality
reconstructed signal.
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: The current research paper is an implementation of
Eigen Faces and Karhunen-Loeve Algorithm for face recognition.
The designed program works in a manner where a unique
identification number is given to each face under trial. These faces
are kept in a database from where any particular face can be matched
and found out of the available test faces. The Karhunen –Loeve
Algorithm has been implemented to find out the appropriate right
face (with same features) with respect to given input image as test
data image having unique identification number. The procedure
involves usage of Eigen faces for the recognition of faces.
Abstract: In this paper, an ultrasonic technique is proposed to
predict oil content in a fresh palm fruit. This is accomplished by
measuring the attenuation based on ultrasonic transmission mode.
Several palm fruit samples with known oil content by Soxhlet
extraction (ISO9001:2008) were tested with our ultrasonic
measurement. Amplitude attenuation data results for all palm samples
were collected. The Feedforward Neural Networks (FNNs) are
applied to predict the oil content for the samples. The Root Mean
Square Error (RMSE) and Mean Absolute Error (MAE) of the FNN
model for predicting oil content percentage are 7.6186 and 5.2287
with the correlation coefficient (R) of 0.9193.
Abstract: Noise causes significant sensibility changes on a human. This study investigated the effect of five different noises on electroencephalogram (EEG) and subjective evaluation. Six human subjects were exposed to classic piano, ocean wave, alarm in army, ambulance, mosquito noise and EEG data were collected during the experimental session. Alpha band activity in the mosquito noise was smaller than that in the classic piano. Alpha band activity decreased 43.4 ± 8.2 % in the mosquito noise. On the other hand, Beta band activity in the mosquito noise was greater than that in the classic piano. Beta band activity increased 60.1 ± 10.7 % in the mosquito noise. The advances from this study may aid the product design process with human sensibility engineering. This result may provide useful information in designing a human-oriented product to avoid the stress.