Abstract: Gastric ulceration is a discontinuity in gastric mucosa, usually occurs due to imbalance between the gastric mucosal protective factors, that is called gastric mucosal barrier, and the aggressive factors, to which the mucosa is exposed. This study was carried out on sixty male Sprague-Dowely rats (12- 16 weeks old) allocated into two groups. The first control group and the second Gastric lesion group which induced by oral administration of a single daily dose of aspirin at a dose of 300 mg/kg body weight for 7 consecutive-days (6% aspirin solution will be prepared and each rat will be given 5 ml of that solution/kg body weight). Blood is collected 1, 2 and 3 weeks after induction of gastric ulceration. Significant increase in serum copper, nitric oxide, and prostaglandin E2 all over the period of experiment. Significant decrease in erythrocyte superoxide dismutase (t-SOD) activities, serum (calcium, phosphorus, glucose and insulin) levels. Non-significant changes in serum sodium and potassium levels are obtained.
Abstract: An attempt has been made to investigate the
machinability of zirconia toughened alumina (ZTA) inserts while
turning AISI 4340 steel. The insert was prepared by powder
metallurgy process route and the machining experiments were
performed based on Response Surface Methodology (RSM) design
called Central Composite Design (CCD). The mathematical model of
flank wear, cutting force and surface roughness have been developed
using second order regression analysis. The adequacy of model has
been carried out based on Analysis of variance (ANOVA) techniques.
It can be concluded that cutting speed and feed rate are the two most
influential factor for flank wear and cutting force prediction. For
surface roughness determination, the cutting speed & depth of cut
both have significant contribution. Key parameters effect on each
response has also been presented in graphical contours for choosing
the operating parameter preciously. 83% desirability level has been
achieved using this optimized condition.
Abstract: This paper presents a solution for the behavioural
animation of autonomous virtual agent navigation in virtual environments.
We focus on using Dempster-Shafer-s Theory of Evidence
in developing visual sensor for virtual agent. The role of the visual
sensor is to capture the information about the virtual environment
or identifie which part of an obstacle can be seen from the position
of the virtual agent. This information is require for vitual agent to
coordinate navigation in virtual environment. The virual agent uses
fuzzy controller as a navigation system and Fuzzy α - level for
the action selection method. The result clearly demonstrates the path
produced is reasonably smooth even though there is some sharp turn
and also still not diverted too far from the potential shortest path.
This had indicated the benefit of our method, where more reliable
and accurate paths produced during navigation task.
Abstract: It is important to remove manganese from water
because of its effects on human and the environment. Human
activities are one of the biggest contributors for excessive manganese
concentration in the environment. The proposed method to remove
manganese in aqueous solution by using adsorption as in carbon
nanotubes (CNT) at different parameters: The parameters are CNT
dosage, pH, agitation speed and contact time. Different pHs are pH
6.0, pH 6.5, pH 7.0, pH 7.5 and pH 8.0, CNT dosages are 5mg,
6.25mg, 7.5mg, 8.75mg or 10mg, contact time are 10 min, 32.5 min,
55 min, 87.5 min and 120 min while the agitation speeds are 100rpm,
150rpm, 200rpm, 250rpm and 300rpm. The parameters chosen for
experiments are based on experimental design done by using Central
Composite Design, Design Expert 6.0 with 4 parameters, 5 levels and
2 replications. Based on the results, condition set at pH 7.0, agitation
speed of 300 rpm, 7.5mg and contact time 55 minutes gives the
highest removal with 75.5%. From ANOVA analysis in Design
Expert 6.0, the residual concentration will be very much affected by
pH and CNT dosage. Initial manganese concentration is 1.2mg/L
while the lowest residual concentration achieved is 0.294mg/L,
which almost satisfy DOE Malaysia Standard B requirement.
Therefore, further experiments must be done to remove manganese
from model water to the required standard (0.2 mg/L) with the initial
concentration set to 0.294 mg/L.
Abstract: In this paper, SFQ (Start Time Fair Queuing)
algorithm is analyzed when this is applied in computer networks to
know what kind of behavior the traffic in the net has when different
data sources are managed by the scheduler. Using the NS2 software
the computer networks were simulated to be able to get the graphs
showing the performance of the scheduler. Different traffic sources
were introduced in the scripts, trying to establish the real scenario.
Finally the results were that depending on the data source, the traffic
can be affected in different levels, when Constant Bite Rate is
applied, the scheduler ensures a constant level of data sent and
received, but the truth is that in the real life it is impossible to ensure
a level that resists the changes in work load.
Abstract: Feature selection plays an important role in applications with high dimensional data. The assessment of the stability of feature selection/ranking algorithms becomes an important issue when the dataset is small and the aim is to gain insight into the underlying process by analyzing the most relevant features. In this work, we propose a graphical approach that enables to analyze the similarity between feature ranking techniques as well as their individual stability. Moreover, it works with whatever stability metric (Canberra distance, Spearman's rank correlation coefficient, Kuncheva's stability index,...). We illustrate this visualization technique evaluating the stability of several feature selection techniques on a spectral binary dataset. Experimental results with a neural-based classifier show that stability and ranking quality may not be linked together and both issues have to be studied jointly in order to offer answers to the domain experts.
Abstract: Laser Doppler flowmetry is a modern method of noninvasive
microcirculation investigation. The aim of our study was to
use this method in the examination of patients with secondary
lymphedema of the lower extremities and obliterating atherosclerosis
of lower extremities. In the analysis of the amplitude-frequency
spectrum of secondary lymphedema patients we have identified
remarkable changes. To describe the changes we used a special
amplitude rate. In both of patients groups this rate was significally
(p
Abstract: With increasing number of wireless devices like
laptops, Wi-Fi Web Cams, network extenders, etc., a new kind of
problems appeared, mostly related to poor Wi-Fi throughput or
communication problems. In this paper an investigation on wireless
networks and it-s saturation in Vilnius City and its surrounding is
presented, covering the main problems of wireless saturation and
network load during day. Also an investigation on wireless channel
selection and noise levels were made, showing the impact of
neighbor AP to signal and noise levels and how it changes during the
day.
Abstract: Technology transfer is a common method for
companies to acquire new technology and presents both challenges
and substantial benefits. In some cases especially in developing
countries, the mere possession of technology does not guarantee a
competitive advantage if the appropriate infrastructure is not in place.
In this paper, we identify the localization factors needed to provide a
better understanding of the conditions necessary for localization in
order to benefit from future technology developments. Our
theoretical and empirical analyses allow us to identify several factors
in the technology transfer process that affect localization and provide
leverage in enhancing capabilities and absorptive capacity.The
impact factors are categorized within different groups of government,
firms, institutes and market, and are verified through the empirical
survey of a technology transfer experience. Moreover, statistical
analysis has allowed a deeper understanding of the importance of
each factor and has enabled each group to prioritize their
organizational policies to effectively localize their technology.
Abstract: Ice cover County has a significant impact on rivers as it affects with the ice melting capacity which results in flooding, restrict navigation, modify the ecosystem and microclimate. River ices are made up of different ice types with varying ice thickness, so surveillance of river ice plays an important role. River ice types are captured using infrared imaging camera which captures the images even during the night times. In this paper the river ice infrared texture images are analysed using first-order statistical methods and secondorder statistical methods. The second order statistical methods considered are spatial gray level dependence method, gray level run length method and gray level difference method. The performance of the feature extraction methods are evaluated by using Probabilistic Neural Network classifier and it is found that the first-order statistical method and second-order statistical method yields low accuracy. So the features extracted from the first-order statistical method and second-order statistical method are combined and it is observed that the result of these combined features (First order statistical method + gray level run length method) provides higher accuracy when compared with the features from the first-order statistical method and second-order statistical method alone.
Abstract: Prior research evidenced that unimodal biometric
systems have several tradeoffs like noisy data, intra-class variations,
restricted degrees of freedom, non-universality, spoof attacks, and
unacceptable error rates. In order for the biometric system to be more
secure and to provide high performance accuracy, more than one
form of biometrics are required. Hence, the need arise for multimodal
biometrics using combinations of different biometric modalities. This
paper introduces a multimodal biometric system (MMBS) based on
fusion of whole dorsal hand geometry and fingerprints that acquires
right and left (Rt/Lt) near-infra-red (NIR) dorsal hand geometry (HG)
shape and (Rt/Lt) index and ring fingerprints (FP). Database of 100
volunteers were acquired using the designed prototype. The acquired
images were found to have good quality for all features and patterns
extraction to all modalities. HG features based on the hand shape
anatomical landmarks were extracted. Robust and fast algorithms for
FP minutia points feature extraction and matching were used. Feature
vectors that belong to similar biometric traits were fused using
feature fusion methodologies. Scores obtained from different
biometric trait matchers were fused using the Min-Max
transformation-based score fusion technique. Final normalized scores
were merged using the sum of scores method to obtain a single
decision about the personal identity based on multiple independent
sources. High individuality of the fused traits and user acceptability
of the designed system along with its experimental high performance
biometric measures showed that this MMBS can be considered for
med-high security levels biometric identification purposes.
Abstract: Flash memory has become an important storage device
in many embedded systems because of its high performance, low
power consumption and shock resistance. Multi-level cell (MLC) is
developed as an effective solution for reducing the cost and increasing
the storage density in recent years. However, most of flash file system
cannot handle the error correction sufficiently. To correct more errors
for MLC, we implement Reed-Solomon (RS) code to YAFFS, what is
widely used for flash-based file system. RS code has longer computing
time but the correcting ability is much higher than that of Hamming
code.
Abstract: Purpose: To develop a method for automatic segmentation of adipose and muscular tissue in thighs from magnetic resonance images. Materials and methods: Thirty obese women were scanned on a Siemens Impact Expert 1T resonance machine. 1500 images were finally used in the tests. The developed segmentation method is a recursive and multilevel process that makes use of several concepts such as shaped histograms, adaptative thresholding and connectivity. The segmentation process was implemented in Matlab and operates without the need of any user interaction. The whole set of images were segmented with the developed method. An expert radiologist segmented the same set of images following a manual procedure with the aid of the SliceOmatic software (Tomovision). These constituted our 'goal standard'. Results: The number of coincidental pixels of the automatic and manual segmentation procedures was measured. The average results were above 90 % of success in most of the images. Conclusions: The proposed approach allows effective automatic segmentation of MRIs from thighs, comparable to expert manual performance.
Abstract: Bay leaves have been shown to improve insulin
function in vitro but the effects on people have not been determined.
The objective of this study was to determine if bay leaves may be
important in the prevention and/or alleviation of type 1 diabetes.
Methods: Fifty five people with type 1 diabetes were divided into
two groups, 45 given capsules containing 3 g of bay leaves per day
for 30 days and 10 given a placebo capsules. Results All the patients
consumed bay leaves shows reduced serum glucose with significant
decreases 27% after 30 d. Total cholesterol decreased, 21 %, after 30
days with larger decreases in low density lipoprotein (LDL) 24%.
High density lipoprotein (HDL) increased 20% and Triglycerides
also decreased 26%. There were no significant changes in the
placebo group. Conclusion, this study demonstrates that consumption
of bay leaves, 3 g/d for 30 days, decreases risk factors for diabetes
and cardiovascular diseases and suggests that bay leaves may be
beneficial for people with type 1 diabetes.
Abstract: We introduce an extended resource leveling model that abstracts real life projects that consider specific work ranges for each resource. Contrary to traditional resource leveling problems this model considers scarce resources and multiple objectives: the minimization of the project makespan and the leveling of each resource usage over time. We formulate this model as a multiobjective optimization problem and we propose a multiobjective genetic algorithm-based solver to optimize it. This solver consists in a two-stage process: a main stage where we obtain non-dominated solutions for all the objectives, and a postprocessing stage where we seek to specifically improve the resource leveling of these solutions. We propose an intelligent encoding for the solver that allows including domain specific knowledge in the solving mechanism. The chosen encoding proves to be effective to solve leveling problems with scarce resources and multiple objectives. The outcome of the proposed solvers represent optimized trade-offs (alternatives) that can be later evaluated by a decision maker, this multi-solution approach represents an advantage over the traditional single solution approach. We compare the proposed solver with state-of-art resource leveling methods and we report competitive and performing results.
Abstract: In recent years, the relevance feedback technology is regarded in content-based image retrieval. This paper suggests a neural networks feedback algorithm based on the radial basis function, coming to extract the semantic character of image. The results of experiment indicated that the performance of this relevance feedback is better than the feedback algorithm based on Single-RBF.
Abstract: In this paper, we study on finite projective Hjelmslev planes M(Zq) coordinatized by Hjelmslev ring Zq (where prime power q = pk). We obtain finite hyperbolic Klingenberg planes from these planes under certain conditions. Also, we give a combinatorical result on M(Zq), related by deleting a line from lines in same neighbour.
Abstract: The goal of speech parameterization is to extract the relevant information about what is being spoken from the audio signal. In speech recognition systems Mel-Frequency Cepstral Coefficients (MFCC) and Relative Spectral Mel-Frequency Cepstral Coefficients (RASTA-MFCC) are the two main techniques used. It will be shown in this paper that it presents some modifications to the original MFCC method. In our work the effectiveness of proposed changes to MFCC called Modified Function Cepstral Coefficients (MODFCC) were tested and compared against the original MFCC and RASTA-MFCC features. The prosodic features such as jitter and shimmer are added to baseline spectral features. The above-mentioned techniques were tested with impulsive signals under various noisy conditions within AURORA databases.
Abstract: This work was conducted to improve the level of
resistant starch (RS) in a rice noodle using unripe banana flour and to
investigate the effect of substitution of unripe banana flour for rice
flour on the physical properties of rice noodle. In order to prepare
rice noodles, the unripe banana flour were replaced the rice flour
with different degrees of substitutions including 0, 20, 40, 60, 80, and
100%. The results indicated that substitution of unripe banana flour
was significantly affected the viscosity properties of noodle flour,
color, cooking loss, RS and total starch content of noodle. It was
found that the noodle prepared from 100% unripe banana indicated
the greatest changes on the viscosity properties and color profiles. It
also showed the highest values of cooking loss (2.53%), tensile
strength (129.03%), and RS content (13.15%).
Abstract: This paper examines economic and Information and Communication Technology (ICT) development influence on recently increasing Internet purchases by individuals for European Union member states. After a growing trend for Internet purchases in EU27 was noticed, all possible regression analysis was applied using nine independent variables in 2011. Finally, two linear regression models were studied in detail. Conducted simple linear regression analysis confirmed the research hypothesis that the Internet purchases in analyzed EU countries is positively correlated with statistically significant variable Gross Domestic Product per capita (GDPpc). Also, analyzed multiple linear regression model with four regressors, showing ICT development level, indicates that ICT development is crucial for explaining the Internet purchases by individuals, confirming the research hypothesis.