Abstract: The aim of the study was to investigate phytochemical
properties, antimicrobial activity and cytotoxicity of Aloe vera. The
phytochemical screening of the extracts of leaves of A. vera revealed
the presence of bioactive compounds such as alkaloids, tannins,
flavonoids phenolic compounds, and etc. with absence of cyanogenic
glycosides. Three different solvents such as methanol, ethanol and
Di-Methyl sulfoxide were used to screen the antimicrobial activity of
A. vera leaves against four human clinical pathogens by agar well
diffusion method. The maximum antibacterial activities were
observed in methanol extract followed by ethanol and Di-Methyl
sulfoxide. It was also found that remarkable antibacterial activities
with methanolic and ethanolic extracts of A. vera compared with the
standard antibiotic, tetracycline that was not active against E. coli
and S. boydii and supported the view that A. vera is a potent
antimicrobial agent compared with the conventional antibiotic.
Moreover, the brine shrimps (Artemia salina) toxicity test exhibited
LC50 value was 569.52 ppm. The resulting data indicated that the A.
vera plant have less toxic effects on brine shrimp. Hence, it is
signified that Aloe vera plant extract is safe to be used as an
antimicrobial agent.
Abstract: This paper introduces an automatic voice classification
system for the diagnosis of individual constitution based on Sasang
Constitutional Medicine (SCM) in Traditional Korean Medicine
(TKM). For the developing of this algorithm, we used the voices of
309 female speakers and extracted a total of 134 speech features from
the voice data consisting of 5 sustained vowels and one sentence. The
classification system, based on a rule-based algorithm that is derived
from a non parametric statistical method, presents 3 types of decisions:
reserved, positive and negative decisions. In conclusion, 71.5% of the
voice data were diagnosed by this system, of which 47.7% were
correct positive decisions and 69.7% were correct negative decisions.
Abstract: Two algorithms are proposed to reduce the storage requirements for mammogram images. The input image goes through a shrinking process that converts the 16-bit images to 8-bits by using pixel-depth conversion algorithm followed by enhancement process. The performance of the algorithms is evaluated objectively and subjectively. A 50% reduction in size is obtained with no loss of significant data at the breast region.
Abstract: Recommender systems are usually regarded as an
important marketing tool in the e-commerce. They use important
information about users to facilitate accurate recommendation. The
information includes user context such as location, time and interest
for personalization of mobile users. We can easily collect information
about location and time because mobile devices communicate with the
base station of the service provider. However, information about user
interest can-t be easily collected because user interest can not be
captured automatically without user-s approval process. User interest
usually represented as a need. In this study, we classify needs into two
types according to prior research. This study investigates the
usefulness of data mining techniques for classifying user need type for
recommendation systems. We employ several data mining techniques
including artificial neural networks, decision trees, case-based
reasoning, and multivariate discriminant analysis. Experimental
results show that CHAID algorithm outperforms other models for
classifying user need type. This study performs McNemar test to
examine the statistical significance of the differences of classification
results. The results of McNemar test also show that CHAID performs
better than the other models with statistical significance.
Abstract: Two-dimensional (2D) bar codes were designed to
carry significantly more data with higher information density and
robustness than its 1D counterpart. Thanks to the popular
combination of cameras and mobile phones, it will naturally bring
great commercial value to use the camera phone for 2D bar code
reading. This paper addresses the problem of specific 2D bar code
design for mobile phones and introduces a low-level encoding
method of matrix codes. At the same time, we propose an efficient
scheme for 2D bar codes decoding, of which the effort is put on
solutions of the difficulties introduced by low image quality that is
very common in bar code images taken by a phone camera.
Abstract: As the new industrial revolution advances in the
nanotechnology have been followed with interest throughout the
world and also in Turkey. Media has an important role in conveying
these advances to public, rising public awareness and creating
attitudes related to nanotechnology. As well as representing how a
subject is treated, media frames determine how public think about
this subject. In literature definite frames related to nanoscience and
nanotechnology such as process, regulation, conflict and risks were
mentioned in studies focusing different countries. So how
nanotechnology news is treated by which frames and in which news
categories in Turkey as a one of developing countries? In this study
examining different variables about nanotechnology that affect
public attitudes such as category, frame, story tone, source in Turkish
media via framing analysis developed in agenda setting studies was
aimed. In the analysis data between 2005 and 2009 obtained from the
first five national newspapers with wide circulation in Turkey will be
used. In this study the direction of the media about nanotechnology,
in which frames nanotechnologic advances brought to agenda were
reported as news, and sectoral, legal, economic and social scenes
reflected by these frames to public related to nanotechnology in
Turkey were planned.
Abstract: The incessant discomfort for Voluntary Counselling and Testing (VCT) exhibited by students in some tertiary institutions in Kano State, Nigeria is capable of causing Psychological Resistance as well as jeopardizing the purpose of HIV intervention. This study investigated the Prevalence of Psychological Resistance to VCT of HIV/AIDS among students of tertiary institutions in the state. Two null hypotheses were postulated and tested. Cross- Sectional Survey Design was employed in which 1512 sample was selected from a student population of 104,841 following Stratified Random Sampling technique. A self-developed 20-item scale whose reliability coefficient is 0.83 was used for data collection. Data analyzed via Chi-square and t-test reveals a prevalence of 38% with males (Mean=0.34; SD=0.475) constituting 60% and females (Mean=0.45; SD=0.498) 40%. Also, the calculated chi-square and ttest were not significant at 0.05 as such the null hypotheses were upheld. Recommendation offered suggests the use of reinforcement and social support for students who patronize HIV/AIDS counselling.
Abstract: In this paper a novel algorithm is proposed that integrates the process of fuzzy hierarchy generation and rule discovery for automated discovery of Production Rules with Fuzzy Hierarchy (PRFH) in large databases.A concept of frequency matrix (Freq) introduced to summarize large database that helps in minimizing the number of database accesses, identification and removal of irrelevant attribute values and weak classes during the fuzzy hierarchy generation.Experimental results have established the effectiveness of the proposed algorithm.
Abstract: Existing experiences indicate that one of the most
prominent reasons that some ERP implementations fail is related to
selecting an improper ERP package. Among those important factors
resulting in inappropriate ERP selections, one is to ignore preliminary
activities that should be done before the evaluation of ERP packages.
Another factor yielding these unsuitable selections is that usually
organizations employ prolonged and costly selection processes in
such extent that sometimes the process would never be finalized
or sometimes the evaluation team might perform many key final
activities in an incomplete or inaccurate way due to exhaustion, lack
of interest or out-of-date data. In this paper, a systematic approach
that recommends some activities to be done before and after the
main selection phase is introduced for choosing an ERP package. On
the other hand, the proposed approach has utilized some ideas that
accelerates the selection process at the same time that reduces the
probability of an erroneous final selection.
Abstract: Clustering techniques have been used by many intelligent software agents to group similar access patterns of the Web users into high level themes which express users intentions and interests. However, such techniques have been mostly focusing on one salient feature of the Web document visited by the user, namely the extracted keywords. The major aim of these techniques is to come up with an optimal threshold for the number of keywords needed to produce more focused themes. In this paper we focus on both keyword and similarity thresholds to generate themes with concentrated themes, and hence build a more sound model of the user behavior. The purpose of this paper is two fold: use distance based clustering methods to recognize overall themes from the Proxy log file, and suggest an efficient cut off levels for the keyword and similarity thresholds which tend to produce more optimal clusters with better focus and efficient size.
Abstract: With constraints on data availability and for study of power system stability it is adequate to model the synchronous generator with field circuit and one equivalent damper on q-axis known as the model 1.1. This paper presents a systematic procedure for modelling and simulation of a single-machine infinite-bus power system installed with a thyristor controlled series compensator (TCSC) where the synchronous generator is represented by model 1.1, so that impact of TCSC on power system stability can be more reasonably evaluated. The model of the example power system is developed using MATLAB/SIMULINK which can be can be used for teaching the power system stability phenomena, and also for research works especially to develop generator controllers using advanced technologies. Further, the parameters of the TCSC controller are optimized using genetic algorithm. The non-linear simulation results are presented to validate the effectiveness of the proposed approach.
Abstract: Existing work in temporal logic on representing the
execution of infinitely many transactions, uses linear-time temporal
logic (LTL) and only models two-step transactions. In this paper,
we use the comparatively efficient branching-time computational tree
logic CTL and extend the transaction model to a class of multistep
transactions, by introducing distinguished propositional variables
to represent the read and write steps of n multi-step transactions
accessing m data items infinitely many times. We prove that the
well known correspondence between acyclicity of conflict graphs
and serializability for finite schedules, extends to infinite schedules.
Furthermore, in the case of transactions accessing the same set of
data items in (possibly) different orders, serializability corresponds
to the absence of cycles of length two. This result is used to give an
efficient encoding of the serializability condition into CTL.
Abstract: The batch nature limits the standard kernel principal component analysis (KPCA) methods in numerous applications, especially for dynamic or large-scale data. In this paper, an efficient adaptive approach is presented for online extraction of the kernel principal components (KPC). The contribution of this paper may be divided into two parts. First, kernel covariance matrix is correctly updated to adapt to the changing characteristics of data. Second, KPC are recursively formulated to overcome the batch nature of standard KPCA.This formulation is derived from the recursive eigen-decomposition of kernel covariance matrix and indicates the KPC variation caused by the new data. The proposed method not only alleviates sub-optimality of the KPCA method for non-stationary data, but also maintains constant update speed and memory usage as the data-size increases. Experiments for simulation data and real applications demonstrate that our approach yields improvements in terms of both computational speed and approximation accuracy.
Abstract: Thailand-s health system is challenged by the rising
number of patients and decreasing ratio of medical
practitioners/patients, especially in rural areas. This may tempt
inexperienced GPs to rush through the process of anamnesis with the
risk of incorrect diagnosis. Patients have to travel far to the hospital
and wait for a long time presenting their case. Many patients try to
cure themselves with traditional Thai medicine. Many countries are
making use of the Internet for medical information gathering,
distribution and storage. Telemedicine applications are a relatively
new field of study in Thailand; the infrastructure of ICT had
hampered widespread use of the Internet for using medical
information. With recent improvements made health and technology
professionals can work out novel applications and systems to help
advance telemedicine for the benefit of the people. Here we explore
the use of telemedicine for people with health problems in rural areas
in Thailand and present a Telemedicine Diagnosis System for Rural
Thailand (TEDIST) for diagnosing certain conditions that people
with Internet access can use to establish contact with Community
Health Centers, e.g. by mobile phone. The system uses a Web-based
input method for individual patients- symptoms, which are taken by
an expert system for the analysis of conditions and appropriate
diseases. The analysis harnesses a knowledge base and a backward
chaining component to find out, which health professionals should be
presented with the case. Doctors have the opportunity to exchange
emails or chat with the patients they are responsible for or other
specialists. Patients- data are then stored in a Personal Health Record.
Abstract: This paper presents a method to detect multiple cracks
based on frequency information. When a structure is subjected to
dynamic or static loads, cracks may develop and the modal
frequencies of the cracked structure may change. To detect cracks in a
structure, we construct a high precision wavelet finite element (EF)
model of a certain structure using the B-spline wavelet on the interval
(BSWI). Cracks can be modeled by rotational springs and added to the
FE model. The crack detection database will be obtained by solving
that model. Then the crack locations and depths can be determined
based on the frequency information from the database. The
performance of the proposed method has been numerically verified by
a rotor example.
Abstract: Variations in the growth rate constant of the Listeria
monocytogenes bacterial species were determined at 37°C in
irradiated environments and compared to the situation of a nonirradiated
environment. The bacteria cells, contained in a suspension
made of a nutrient solution of Brain Heart Infusion, were made to
grow at different frequency (2.30e2.60 GHz) and power (0e400
mW) values, in a plug flow reactor positioned in the irradiated
environment. Then the reacting suspension was made to pass into a
cylindrical cuvette where its optical density was read every 2.5
minutes at a wavelength of 600 nm. The obtained experimental data
of optical density vs. time allowed the bacterial growth rate constant
to be derived; this was found to be slightly influenced by microwave
power, but not by microwave frequency; in particular, a minimum
value was found for powers in the 50e150 mW field.
Abstract: POS (also been called DGPS/IMU) technique can obtain the Exterior Orientation Elements of aerial photo, so the triangulation and DLG production using POS can save large numbers of ground control points (GCP), and this will improve the produce efficiency of DLG and reduce the cost of collecting GCP. This paper mainly research on POS technique in production of 1:10 000 scale DLG on GCP distribution. We designed 23 kinds of ground control points distribution schemes, using integrated sensor direction method to do the triangulation experiments, based on the results of triangulation, we produce a map with the scale of 1:10 000 and test its accuracy. This paper put forward appropriate GCP distributing schemes by experiments and research above, and made preparations for the application of POS technique on photogrammetry 4D data production.
Abstract: A number of studies highlighted problems related to
ERP systems, yet, most of these studies focus on the problems during
the project and implementation stages but not during the postimplementation
use process. Problems encountered in the process of
using ERP would hinder the effective exploitation and the extended
and continued use of ERP systems and their value to organisations.
This paper investigates the different types of problems users
(operational, supervisory and managerial) faced in using ERP and
how 'feral system' is used as the coping mechanism. The paper
adopts a qualitative method and uses data collected from two cases
and 26 interviews, to inductively develop a casual network model of
ERP usage problem and its coping mechanism. This model classified
post ERP usage problems as data quality, system quality, interface
and infrastructure. The model is also categorised the different coping
mechanism through use of 'feral system' inclusive of feral
information system, feral data and feral use of technology.
Abstract: Computing and maintaining network structures for efficient
data aggregation incurs high overhead for dynamic events
where the set of nodes sensing an event changes with time. Moreover,
structured approaches are sensitive to the waiting time that is used
by nodes to wait for packets from their children before forwarding
the packet to the sink. An optimal routing and data aggregation
scheme for wireless sensor networks is proposed in this paper. We
propose Tree on DAG (ToD), a semistructured approach that uses
Dynamic Forwarding on an implicitly constructed structure composed
of multiple shortest path trees to support network scalability. The key
principle behind ToD is that adjacent nodes in a graph will have
low stretch in one of these trees in ToD, thus resulting in early
aggregation of packets. Based on simulations on a 2,000-node Mica2-
based network, we conclude that efficient aggregation in large-scale
networks can be achieved by our semistructured approach.
Abstract: This research examines possible effects of climatic
change focusing on global warming and its impacts on world
agricultural product markets, by using a world food model developed
to consider climate changes. GDP and population for each scenario
were constructed by IPCC and climate data for each scenario was
reported by the Hadley Center and are used in this research to consider
results in different contexts. Production and consumption of primary
agriculture crops of the world for each socio-economic scenario are
obtained and investigated by using the modified world food model.
Simulation results show that crop production in some countries or
regions will have different trends depending on the context. These
alternative contexts depend on the rate of GDP growth, population,
temperature, and rainfall. Results suggest that the development of
environment friendly technologies lead to more consumption of food
in many developing countries. Relationships among environmental
policy, clean energy development, and poverty elimination warrant
further investigation.