Abstract: Diagnostic and detection of the arterial stiffness is
very important; which gives indication of the associated increased risk of cardiovascular diseases. To make a cheap and easy method for general screening technique to avoid the future cardiovascular
complexes , due to the rising of the arterial stiffness ; a proposed algorithm depending on photoplethysmogram to be used. The
photoplethysmograph signals would be processed in MATLAB. The
signal will be filtered, baseline wandering removed, peaks and
valleys detected and normalization of the signals should be achieved
.The area under the catacrotic phase of the photoplethysmogram
pulse curve is calculated using trapezoidal algorithm ; then will used
in cooperation with other parameters such as age, height, blood
pressure in neural network for arterial stiffness detection. The Neural
network were implemented with sensitivity of 80%, accuracy 85%
and specificity of 90% were got from the patients data. It is
concluded that neural network can detect the arterial STIFFNESS
depending on risk factor parameters.
Abstract: Land with low pH soil spread widely in Indonesia
can be used for soybean (Glycine max) cultivation, however the
production is low. The use of acid tolerant soybean and acidaluminium
tolerant nitrogen-fixing bacteria formula was an
alternative way to increase soybean productivity on acid soils.
Bradyrhizobium japonicum is one of the nitrogen fixing bacteria
which can symbiose with soybean plants through root nodule
formation. Most of the nitrogen source required by soybean plants
can be provided by this symbiosis. This research was conducted to
study the influence of acid-aluminium tolerant B. japonicum strain
BJ 11 formula using peat as carrier on growth of Tanggamus and
Anjasmoro cultivar soybean planted on acid soil fields (pH 5.0-
5.5). The results showed that the inoculant was able to increase the
growth and production of soybean which were grown on fields acid
soil at Sukadana (Lampung) and Tanah Laut (South Kalimantan),
Indonesia.
Abstract: The dynamic speckle or biospeckle is an interference
phenomenon generated at the reflection of a coherent light by an
active surface or even by a particulate or living body surface. The
above mentioned phenomenon gave scientific support to a method
named biospeckle which has been employed to study seed viability,
biological activity, tissue senescence, tissue water content, fruit
bruising, etc. Since the above mentioned method is not invasive and
yields numerical values, it can be considered for possible automation
associated to several processes, including selection and sorting.
Based on these preliminary considerations, this research work
proposed to study the interaction of a laser beam with vegetative
samples by measuring the incident light intensity and the transmitted
light beam intensity at several vegetative slabs of varying thickness.
Tests were carried on fifteen slices of apple tissue divided into three
thickness groups, i.e., 4 mm, 5 mm, 18 mm and 22 mm. A diode laser
beam of 10mW and 632 nm wavelength and a Samsung digital
camera were employed to carry the tests. Outgoing images were
analyzed by comparing the gray gradient of a fixed image column of
each image to obtain a laser penetration scale into the tissue,
according to the slice thickness.
Abstract: The myoelectric signal (MES) is one of the Biosignals
utilized in helping humans to control equipments. Recent approaches
in MES classification to control prosthetic devices employing pattern
recognition techniques revealed two problems, first, the classification
performance of the system starts degrading when the number of
motion classes to be classified increases, second, in order to solve the
first problem, additional complicated methods were utilized which
increase the computational cost of a multifunction myoelectric
control system. In an effort to solve these problems and to achieve a
feasible design for real time implementation with high overall
accuracy, this paper presents a new method for feature extraction in
MES recognition systems. The method works by extracting features
using Wavelet Packet Transform (WPT) applied on the MES from
multiple channels, and then employs Fuzzy c-means (FCM)
algorithm to generate a measure that judges on features suitability for
classification. Finally, Principle Component Analysis (PCA) is
utilized to reduce the size of the data before computing the
classification accuracy with a multilayer perceptron neural network.
The proposed system produces powerful classification results (99%
accuracy) by using only a small portion of the original feature set.
Abstract: Nano-MgO was successfully deposited on titania using deposition-precipitation method. The catalyst produced was characterised using FTIR, XRD, BET and XRF and its activity was tested on the transesterification reaction of soybean oil to biodiesel. The catalyst activity improved when the reaction temperature was increasedfrom 150 and 225 OC. It was also observed that increasing the reaction time above 1h had no significant benefit on conversion. The stability fixed MgO on TiO2 was investigated using XRF and ICP-OES. It was observed that MgO loss during the reaction was between 0.5-2.3 percent and that there was no correlation between the reaction temperature and the MgO loss.
Abstract: The determination of sugars in foods is very
significant. Their relation in fact, can affect the chemical and
sensorial quality of the matrix (e.g., sweetness, pH, total acidity,
microbial stability, global acceptability) and can provide information
on food to optimize several selected technological processes. Three
stages of ripeness (green, yellow and red) of tomatoes (Lycopersicon
Esculentum cv. Elegance) at different harvest dates were evaluated.
Fruit from all harvests were exposed to different of ozone doses
(0.25, 0.50 and 1 mg O3/g tomatoes) and clean air for 5 day at 15
°C±2 and 90-95 % relative humidity. Then, fruits were submitted for
extraction and analysis after a day from the finish of exposure of each
stage. The concentrations of the glucose and fructose increased in the
tomatoes which were subjected to ozone treatments.
Abstract: In this paper, a generalized derivatives operator n
λ,βf
introduced by the authors will be discussed. Some subordination and
superordination results involving this operator for certain normalized
analytic functions in the open unit disk will be investigated. Our
results extend corresponding previously known results.
Abstract: This study1 holds for the formation of international financial crisis and political factors for economic crisis in Turkey, are evaluated in chronological order. The international arena and relevant studies conducted in Turkey work in the literature are assessed. The main purpose of the study is to hold the linkage between the crises and political stability in Turkey in details, and to examine the position of Turkey in this regard. The introduction part follows the literature survey on the models explaining causes and results of the crises, the second part of the study. In the third part, the formations of the world financial crises are studied. The fourth part, financial crisis in Turkey in 1994, 2000, 2001 and 2008 are reviewed and their political reasons are analyzed. In the last part of the study the results and recommendations are held. Political administrations have laid the grounds for an economic crisis in Turkey. In this study, the emergence of an economic crisis in Turkey and the developments after the crisis are chronologically examined and an explanation is offered as to the cause and effect relationship between the political administration and economic equilibrium in the country. Economic crises can be characterized as follows: high prices of consumables, high interest rates, current account deficits, budget deficits, structural defects in government finance, rising inflation and fixed currency applications, rising government debt, declining savings rates and increased dependency on foreign capital stock. Entering into the conditions of crisis during a time when the exchange value of the country-s national currency was rising, speculative finance movements and shrinking of foreign currency reserves happened due to expectations for devaluation and because of foreign investors- resistance to financing national debt, and a financial risk occurs. During the February 2001 crisis and immediately following, devaluation and reduction of value occurred in Turkey-s stock market. While changing over to the system of floating exchange rates in the midst of this crisis, the effects of the crisis on the real economy are discussed in this study. Administered politics include financial reforms, such as the rearrangement of banking systems. These reforms followed with the provision of foreign financial support. There have been winners and losers in the imbalance of income distribution, which has recently become more evident in Turkey-s fragile economy.
Abstract: In this paper, we propose a new class of Volterra series based filters for image enhancement and restoration. Generally the linear filters reduce the noise and cause blurring at the edges. Some nonlinear filters based on median operator or rank operator deal with only impulse noise and fail to cancel the most common Gaussian distributed noise. A class of second order Volterra filters is proposed to optimize the trade-off between noise removal and edge preservation. In this paper, we consider both the Gaussian and mixed Gaussian-impulse noise to test the robustness of the filter. Image enhancement and restoration results using the proposed Volterra filter are found to be superior to those obtained with standard linear and nonlinear filters.
Abstract: Continuous pyrolysis of Cogongrass by control
temperature in the novel pyrolysis reactor were conducted at three
difference temperatures 400, 450 and 500°C. Preliminary calculate of
the product yields founded the liquid yield of Cogongrass was
highest of 41.45 %, at 500 oC. Indicated that the liquid yield from
Cogongrass had good received yields because it gave over 40 % and
its produced more liquid than that solid and gas. The compounds
detected in bio-oil from Cogongrass showed the functional group,
especially; Phenol, Phenol, 2,5-dimethyl, Phenol, 3-methyl, 2-
methyl-1,3-oxathiofane, Benzene,1-ethyl-4-methoxy, 2-Cyclopenten-
1-one,2,3-dimethyl, 2- Cyclopenten-1- one, 3-Methyl.
Abstract: This paper describes a simulation model for analyzing artificial emotion injected to design the game characters. Most of the game storyboard is interactive in nature and the virtual characters of the game are equipped with an individual personality and dynamic emotion value which is similar to real life emotion and behavior. The uncertainty in real expression, mood and behavior is also exhibited in game paradigm and this is focused in the present paper through a fuzzy logic based agent and storyboard. Subsequently, a pheromone distribution or labeling is presented mimicking the behavior of social insects.
Abstract: This paper presents Qmulus- a Cloud Based GPS
Model. Qmulus is designed to compute the best possible route which
would lead the driver to the specified destination in the shortest time
while taking into account real-time constraints. Intelligence
incorporated to Qmulus-s design makes it capable of generating and
assigning priorities to a list of optimal routes through customizable
dynamic updates. The goal of this design is to minimize travel and
cost overheads, maintain reliability and consistency, and implement
scalability and flexibility. The model proposed focuses on
reducing the bridge between a Client Application and a Cloud
service so as to render seamless operations. Qmulus-s system
model is closely integrated and its concept has the potential to be
extended into several other integrated applications making it capable
of adapting to different media and resources.
Abstract: Nowadays, driving support systems, such as car
navigation systems, are getting common, and they support drivers in
several aspects. It is important for driving support systems to detect
status of driver's consciousness. Particularly, detecting driver's
drowsiness could prevent drivers from collisions caused by drowsy
driving. In this paper, we discuss the various artificial detection
methods for detecting driver's drowsiness processing technique. This
system is based on facial images analysis for warning the driver of
drowsiness or in attention to prevent traffic accidents.
Abstract: In this paper we are to find the optimum
multiwavelet for compression of electrocardiogram (ECG)
signals. At present, it is not well known which multiwavelet is
the best choice for optimum compression of ECG. In this
work, we examine different multiwavelets on 24 sets of ECG
data with entirely different characteristics, selected from MITBIH
database. For assessing the functionality of the different
multiwavelets in compressing ECG signals, in addition to
known factors such as Compression Ratio (CR), Percent Root
Difference (PRD), Distortion (D), Root Mean Square Error
(RMSE) in compression literature, we also employed the
Cross Correlation (CC) criterion for studying the
morphological relations between the reconstructed and the
original ECG signal and Signal to reconstruction Noise Ratio
(SNR). The simulation results show that the cardbal2 by the
means of identity (Id) prefiltering method to be the best
effective transformation.
Abstract: The electroencephalograph (EEG) signal is one of the most widely signal used in the bioinformatics field due to its rich information about human tasks. In this work EEG waves classification is achieved using the Discrete Wavelet Transform DWT with Fast Fourier Transform (FFT) by adopting the normalized EEG data. The DWT is used as a classifier of the EEG wave's frequencies, while FFT is implemented to visualize the EEG waves in multi-resolution of DWT. Several real EEG data sets (real EEG data for both normal and abnormal persons) have been tested and the results improve the validity of the proposed technique.
Abstract: The objective of this research was to study the career
success and the satisfaction of female executives working for schools
in Bangkok, Thailand. This paper drew upon the survey data
collected from 68 female executives. The survey conducted in on
Bangkok schools. The statistics utilized in this paper included
percentage, mean, standard deviation as well as t-test. The findings
revealed that the majority of samples had more than 30 years of
experience, held a master degree, and had an average income of less
than 40,000 baht. The majority of respondents worked not more than
50 hours per week. In addition, the mean score revealed career
development was ranked as their number one career satisfaction and
having a job related to education was ranked as their number one job
satisfaction. Also, the mean score of all categories of satisfaction was
4.61 with standard deviation of 1.677 which indicated that female
executive level of satisfaction was high. In terms of the subjectivity
career success, the hypothesis testing’s result disclosed that female
executives with different married status had a difference in their job
satisfaction which was significant at the 0.05 confidence level.
Abstract: Cooperative visual modeling is more and more
necessary in our complicated world. A collaborative environment
which supports interactive operation and communication is required
to increase work efficiency. We present a collaborative visual
modeling framework which collaborative platform could be built on.
On this platform, cooperation and communication is available for
designers from different regions. This framework, which is different
from other collaborative frameworks, contains a uniform message
format, a message handling mechanism and other functions such as
message pretreatment and Role-Communication-Token Access
Control (RCTAC). We also show our implementation of this
framework called Orchestra Designer, which support BPLE
workflow modeling cooperatively online.
Abstract: In this paper we present a full performance analysis of an energy conserving routing protocol in mobile ad hoc network, named ER-AODV (Energy Reverse Ad-hoc On-demand Distance Vector routing). ER-AODV is a reactive routing protocol based on a policy which combines two mechanisms used in the basic AODV protocol. AODV and most of the on demand ad hoc routing protocols use single route reply along reverse path. Rapid change of topology causes that the route reply could not arrive to the source node, i.e. after a source node sends several route request messages, the node obtains a reply message, and this increases in power consumption. To avoid these problems, we propose a mechanism which tries multiple route replies. The second mechanism proposes a new adaptive approach which seeks to incorporate the metric "residual energy " in the process route selection, Indeed the residual energy of mobile nodes were considered when making routing decisions. The results of simulation show that protocol ER-AODV answers a better energy conservation.
Abstract: Order reduction of linear-time invariant systems employing two methods; one using the advantages of Routh approximation and other by an evolutionary technique is presented in this paper. In Routh approximation method the denominator of the reduced order model is obtained using Routh approximation while the numerator of the reduced order model is determined using the indirect approach of retaining the time moments and/or Markov parameters of original system. By this method the reduced order model guarantees stability if the original high order model is stable. In the second method Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical examples.
Abstract: In this paper, a second order autoregressive (AR)
model is proposed to discriminate alcoholics using single trial
gamma band Visual Evoked Potential (VEP) signals using 3 different
classifiers: Simplified Fuzzy ARTMAP (SFA) neural network (NN),
Multilayer-perceptron-backpropagation (MLP-BP) NN and Linear
Discriminant (LD). Electroencephalogram (EEG) signals were
recorded from alcoholic and control subjects during the presentation
of visuals from Snodgrass and Vanderwart picture set. Single trial
VEP signals were extracted from EEG signals using Elliptic filtering
in the gamma band spectral range. A second order AR model was
used as gamma band VEP exhibits pseudo-periodic behaviour and
second order AR is optimal to represent this behaviour. This
circumvents the requirement of having to use some criteria to choose
the correct order. The averaged discrimination errors of 2.6%, 2.8%
and 11.9% were given by LD, MLP-BP and SFA classifiers. The
high LD discrimination results show the validity of the proposed
method to discriminate between alcoholic subjects.