Abstract: The most common cause of power transformer failures
is mechanical defect brought about by excessive vibration, which is
formed by the combination of multiples of a frequency of 120 Hz. In
this paper, the types of mechanical exciting forces applied to the
power transformer were classified, and the mechanical damage
mechanism of the power transformer was identified using the
vibration transfer route to the machine or structure. The general
effects of 120 Hz-vibration on the enclosure, bushing, Buchholz
relay, pressure release valve and tap changer of the transformer were
also examined.
Abstract: Information society is an absolutely new public formation at which the infrastructure and the social relations correspond to the socialized essence of «information genotype» mankind. Information society is a natural social environment which allows the person to open completely the information nature, to use intelligence for joint creation with other people of new information on the basis of knowledge earlier saved up by previous generations.
Abstract: Most agricultural crops cultivated in Brazil are highly
nutrient demanding. Brazilian soils are generally acidic with low base
saturation and available nutrients. Demand for fertilizer application
has increased because the national agricultural sector expansion. To
improve productivity without environmental impact, there is the need
for the utilization of novel procedures and techniques to optimize
fertilizer application. This includes the digital soil mapping and GIS
application applied to mapping in different scales. This paper is
based on research, realized during 2005 to 2010 by Brazilian
Corporation for Agricultural Research (EMBRAPA) and its partners.
The purpose was to map soil fertility in national and regional scales.
A soil profile data set in national scale (1:5,000,000) was constructed
from the soil archives of Embrapa Soils, Rio de Janeiro and in the
regional scale (1:250,000) from COMIGO Cooperative soil data set,
Rio Verde, Brazil. The mapping was doing using ArcGIS 9.1 tools
from ESRI.
Abstract: This study examined the effects of 8-week Pilates training program on limits of stability (LOS) and abdominal muscle strength in young dancers. Twenty-four female volunteered and randomly assigned as experimental group (EG) or control group (CG). All subjects received the same dance lessons but the EG underwent an extra Pilates mat exercises for 40 minutes, three times a week, for 8 weeks. LOS was evaluated by the Biodex Balance System and the abdominal strength was measured by 30/60 seconds sit-ups test. One factor ANCOVA was used to examine the differences between groups after training. The results showed that the overall LOS scores at levels 2/8 and the 30/60 seconds sit-ups for the EG group pre- and post-training were changed from 22/38 % to 31/51 % and 20/33 times to 24/42 times, respectively. The study demonstrated that 8-week Pilates training can improve the LOS performance and abdominal strength in young dancers.
Abstract: The comparative analysis of different taxonomic
groups of microorganisms isolated from dark chernozem soils under
different agricultures (alfalfa, melilot, sainfoin, soybean, rapeseed) at
Almaty region of Kazakhstan was conducted. It was shown that the
greatest number of micromycetes was typical to the soil planted with
alfalfa and canola. Species diversity of micromycetes markedly
decreases as it approaches the surface of the root, so that the species
composition in the rhizosphere is much more uniform than in the
virgin soil. Promising strains of microscopic fungi and yeast with
plant growth-promoting activity to agricultures were selected. Among
the selected fungi there are representatives of Penicillium bilaiae,
Trichoderma koningii, Fusarium equiseti, Aspergillus ustus. The
highest rates of growth and development of seedlings of plants
observed under the influence of yeasts Aureobasidium pullulans,
Rhodotorula mucilaginosa, Metschnikovia pulcherrima. Using
molecular - genetic techniques confirmation of the identification
results of selected micromycetes was conducted.
Abstract: This paper proposes a new technique based on nonlinear Minmax Detector Based (MDB) filter for image restoration. The aim of image enhancement is to reconstruct the true image from the corrupted image. The process of image acquisition frequently leads to degradation and the quality of the digitized image becomes inferior to the original image. Image degradation can be due to the addition of different types of noise in the original image. Image noise can be modeled of many types and impulse noise is one of them. Impulse noise generates pixels with gray value not consistent with their local neighborhood. It appears as a sprinkle of both light and dark or only light spots in the image. Filtering is a technique for enhancing the image. Linear filter is the filtering in which the value of an output pixel is a linear combination of neighborhood values, which can produce blur in the image. Thus a variety of smoothing techniques have been developed that are non linear. Median filter is the one of the most popular non-linear filter. When considering a small neighborhood it is highly efficient but for large window and in case of high noise it gives rise to more blurring to image. The Centre Weighted Mean (CWM) filter has got a better average performance over the median filter. However the original pixel corrupted and noise reduction is substantial under high noise condition. Hence this technique has also blurring affect on the image. To illustrate the superiority of the proposed approach, the proposed new scheme has been simulated along with the standard ones and various restored performance measures have been compared.
Abstract: This paper presents a technique for diagnosis of the abdominal aorta aneurysm in magnetic resonance imaging (MRI) images. First, our technique is designed to segment the aorta image in MRI images. This is a required step to determine the volume of aorta image which is the important step for diagnosis of the abdominal aorta aneurysm. Our proposed technique can detect the volume of aorta in MRI images using a new external energy for snakes model. The new external energy for snakes model is calculated from Law-s texture. The new external energy can increase the capture range of snakes model efficiently more than the old external energy of snakes models. Second, our technique is designed to diagnose the abdominal aorta aneurysm by Bayesian classifier which is classification models based on statistical theory. The feature for data classification of abdominal aorta aneurysm was derived from the contour of aorta images which was a result from segmenting of our snakes model, i.e., area, perimeter and compactness. We also compare the proposed technique with the traditional snakes model. In our experiment results, 30 images are trained, 20 images are tested and compared with expert opinion. The experimental results show that our technique is able to provide more accurate results than 95%.
Abstract: An on chip low drop out voltage regulator that
employs elegant compensation scheme is presented in this paper. The
novelty in this design is that the device parasitic capacitances are
exploited for compensation at different loads. The proposed LDO is
designed to provide a constant voltage of 1.2V and is implemented in
UMC 180 nano meter CMOS technology. The voltage regulator
presented improves stability even at lighter loads and enhances line
and load regulation.
Abstract: Generalized Center String (GCS) problem are
generalized from Common Approximate Substring problem
and Common substring problems. GCS are known to be
NP-hard allowing the problems lies in the explosion of
potential candidates. Finding longest center string without
concerning the sequence that may not contain any motifs is
not known in advance in any particular biological gene
process. GCS solved by frequent pattern-mining techniques
and known to be fixed parameter tractable based on the
fixed input sequence length and symbol set size. Efficient
method known as Bpriori algorithms can solve GCS with
reasonable time/space complexities. Bpriori 2 and Bpriori
3-2 algorithm are been proposed of any length and any
positions of all their instances in input sequences. In this
paper, we reduced the time/space complexity of Bpriori
algorithm by Constrained Based Frequent Pattern mining
(CBFP) technique which integrates the idea of Constraint
Based Mining and FP-tree mining. CBFP mining technique
solves the GCS problem works for all center string of any
length, but also for the positions of all their mutated copies
of input sequence. CBFP mining technique construct TRIE
like with FP tree to represent the mutated copies of center
string of any length, along with constraints to restraint
growth of the consensus tree. The complexity analysis for
Constrained Based FP mining technique and Bpriori
algorithm is done based on the worst case and average case
approach. Algorithm's correctness compared with the
Bpriori algorithm using artificial data is shown.
Abstract: Broccoli has been widely recognized as a wealthy
vegetable which contains multiple nutrients with potent anti-cancer
properties. Lamb’s lettuce has been used as food for many centuries
but only recently became commercially available and literature is
therefore exiguous concerning these vegetables. The aim of this work
was to evaluate the influence of the extraction conditions on the yield
of phenolic compounds and the corresponding antioxidant capacity of
broccoli and lamb’s lettuce. The results indicate that lamb’s lettuce,
compared to broccoli, contains simultaneously a large amount of total
polyphenols as well as high antioxidant activity. It is clearly
demonstrated that extraction solvent significantly influences the
antioxidant activity. Methanol is the solvent that can globally
maximize the antioxidant extraction yield. The results presented
herein prove lamb’s lettuce as a very interesting source of
polyphenols, and thus a potential health-promoting food.
Abstract: A virtualized and virtual approach is presented on
academically preparing students to successfully engage at a strategic
perspective to understand those concerns and measures that are both
structured and not structured in the area of cyber security and
information assurance. The Master of Science in Cyber Security and
Information Assurance (MSCSIA) is a professional degree for those
who endeavor through technical and managerial measures to ensure
the security, confidentiality, integrity, authenticity, control,
availability and utility of the world-s computing and information
systems infrastructure. The National University Cyber Security and
Information Assurance program is offered as a Master-s degree. The
emphasis of the MSCSIA program uniquely includes hands-on
academic instruction using virtual computers. This past year, 2011,
the NU facility has become fully operational using system
architecture to provide a Virtual Education Laboratory (VEL)
accessible to both onsite and online students. The first student cohort
completed their MSCSIA training this past March 2, 2012 after
fulfilling 12 courses, for a total of 54 units of college credits. The
rapid pace scheduling of one course per month is immensely
challenging, perpetually changing, and virtually multifaceted. This
paper analyses these descriptive terms in consideration of those
globalization penetration breaches as present in today-s world of
cyber security. In addition, we present current NU practices to
mitigate risks.
Abstract: The field of polymeric biomaterials is very important
from the socio-economical viewpoint. Synthetic carbohydrate
polymers are being increasingly investigated as biodegradable,
biocompatible and biorenewable materials. The aim of this study was
to synthesize and characterize some derivatives based on D-mannose.
D-mannose was chemically modified to obtain 1-O-allyl-2,3:5,6-di-
O-isopropylidene-D-mannofuranose and 1-O-(2-,3--epoxy-propyl)-
2,3:5,6-di-O-isopropylidene-D-mannofuranose.
The chemical structure of the resulting compounds was
characterized by FT-IR and NMR spectroscopy, and by HPLC-MS.
Abstract: With the proliferation of the mobile device
technologies, mobile learning can be used to complement and
improve traditional learning problems. Both students and teachers
need a proper and handy system to monitor and keep track the
performance of the students. This paper presents an implementation
of M-learning for primary school in Malaysia by using an open
source technology. It focuses on learning mathematics using
handheld devices for primary schools- students aged 11 and 12 years
old. Main users for this system include students, teachers and the
administrator. This application suggests a new mobile learning
environment with mobile graph for tracking the students- progress
and performance. The purpose of this system is not to replace
traditional classroom but to complement the learning process. In a
testing conducted, students who used this system performed better in
their examination.
Abstract: To determine if the murine insulinoma, β-TC-6, is a
suitable substitute for primary pancreatic β-cells in the study of β-
cell functional heterogeneity, we used three distinct functional assays
to ascertain the cell line-s response to glucose or a glucose analog.
These assays include: (i) a 2-NBDG uptake assay; (ii) a calcium
influx assay, and; (iii) a quinacrine secretion assay. We show that a
population of β-TC-6 cells endocytoses the glucose analog, 2-
NBDG, at different rates, has non-uniform intracellular calcium ion
concentrations and releases quinacrine at different rates when
challenged with glucose. We also measured the Km for β-TC-6
glucose uptake to be 46.9 mM and the Vm to be 8.36 x 10-5
mmole/million cells/min. These data suggest that β-TC-6 might be
used as an alternative to primary pancreatic β-cells for the study of
glucose-dependent β-cell functional heterogeneity.
Abstract: Signature represents an individual characteristic of a
person which can be used for his / her validation. For such application
proper modeling is essential. Here we propose an offline signature
recognition and verification scheme which is based on extraction of
several features including one hybrid set from the input signature
and compare them with the already trained forms. Feature points
are classified using statistical parameters like mean and variance.
The scanned signature is normalized in slant using a very simple
algorithm with an intention to make the system robust which is
found to be very helpful. The slant correction is further aided by the
use of an Artificial Neural Network (ANN). The suggested scheme
discriminates between originals and forged signatures from simple
and random forgeries. The primary objective is to reduce the two
crucial parameters-False Acceptance Rate (FAR) and False Rejection
Rate (FRR) with lesser training time with an intension to make the
system dynamic using a cluster of ANNs forming a multiple classifier
system.
Abstract: The paper proposes and validates a new method of solving instances of the vehicle routing problem (VRP). The approach is based on a multiple agent system paradigm. The paper contains the VRP formulation, an overview of the multiple agent environment used and a description of the proposed implementation. The approach is validated experimentally. The experiment plan and the discussion of experiment results follow.
Abstract: The purposes of this research are 1) to study English language learning strategies used by the fourth-year students majoring in English and Business English, 2) to study the English language learning strategies which have an affect on English learning achievement, and 3) to compare the English language learning strategies used by the students majoring in English and Business English. The population and sampling comprise of 139 university students of the Suan Sunandha Rajabhat University. Research instruments are language learning strategies questionnaire which was constructed by the researcher and improved on by three experts and the transcripts that show the results of English learning achievement. The questionnaire includes 1) Language Practice Strategy 2)Memory Strategy 3) Communication Strategy 4)Making an Intelligent Guess or Compensation Strategy 5) Self-discipline in Learning Management Strategy 6) Affective Strategy 7)Self-Monitoring Strategy 8) Self-studySkill Strategy. Statistics used in the study are mean, standard deviation, T-test and One Way ANOVA, Pearson product moment correlation coefficient and Regression Analysis. The results of the findings reveal that the English language learning strategies most frequently used by the students are affective strategy, making an intelligent guess or compensation strategy, self-studyskill strategy and self-monitoring strategy respectively. The aspect of making an intelligent guess or compensation strategy had the most significant affect on English learning achievement. It is found that the English language learning strategies mostly used by the Business English major students and moderately used by the English major students. Their language practice strategies uses were significantly different at the 0.05 level and their communication strategies uses were significantly different at the 0.01 level. In addition, it is found that the poor students and the fair ones most frequently used affective strategy while the good ones most frequently used making an intelligent guess or compensation strategy. KeywordsEnglish language, language learning strategies, English learning achievement, and students majoring in English, Business English. Pranee Pathomchaiwat is an Assistant Professor in Business English Program, Suan Sunandha Rajabhat University, Bangkok, Thailand (e-mail: [email protected]).
Abstract: In this paper, we study the multi-scenario knapsack problem, a variant of the well-known NP-Hard single knapsack problem. We investigate the use of an adaptive algorithm for solving heuristically the problem. The used method combines two complementary phases: a size reduction phase and a dynamic 2- opt procedure one. First, the reduction phase applies a polynomial reduction strategy; that is used for reducing the size problem. Second, the adaptive search procedure is applied in order to attain a feasible solution Finally, the performances of two versions of the proposed algorithm are evaluated on a set of randomly generated instances.
Abstract: One promising way to achieve low temperature
combustion regime is the use of a large amount of cooled EGR. In
this paper, the effect of injection timing on low temperature
combustion process and emissions were investigated via three
dimensional computational fluid dynamics (CFD) procedures in a DI
diesel engine using high EGR rates. The results show when
increasing EGR from low levels to levels corresponding to reduced
temperature combustion, soot emission after first increasing, is
decreased beyond 40% EGR and get the lowest value at 58% EGR
rate. Soot and NOx emissions are simultaneously decreased at
advanced injection timing before 20.5 ºCA BTDC in conjunction
with 58% cooled EGR rate in compared to baseline case.
Abstract: Thermoacoustic instabilities in combustors have
remained a topic of investigation for over a few decades due to the
challenges it posses to the operation of low emission gas turbines.
For combustors burning liquid fuel, understanding the cause-andeffect
relationship between spray combustion dynamics and
thermoacoustic oscillations is imperative for the successful
development of any control methodology for its mitigation. The
paper presents some very unique operating characteristics of a
kerosene-fueled diffusion type combustor undergoing limit-cycle
oscillations. Combustor stability limits were mapped using three
different-sized injectors. The results show that combustor instability
depends on the characteristics of the fuel spray. A simple analytic
analysis is also reported in support of a plausible explanation for the
unique combustor behavior. The study indicates that high amplitude
acoustic pressure in the combustor may cause secondary breakdown
of fuel droplets resulting in premixed pre-vaporized type burning of
the diffusion type combustor.