Abstract: Three-phase induction machines are today a standard
for industrial electrical drives. Cost, reliability, robustness and maintenance free operation are among the reasons these machines are
replacing dc drive systems. The development of power electronics
and signal processing systems has eliminated one of the greatest
disadvantages of such ac systems, which is the issue of control. With
modern techniques of field oriented vector control, the task of
variable speed control of induction machines is no longer a
disadvantage. The need to increase system performance, particularly
when facing limits on the power ratings of power supplies and
semiconductors, motivates the use of phase number other than three,
In this paper a novel scheme of connecting two, three phase
induction motors in parallel fed by two inverters; viz. VSI and CSI
and their vector control is presented.
Abstract: In this paper, we propose APO, a new packet scheduling
scheme with Quality of Service (QoS) support for hybrid of
real and non-real time services in HSDPA networks. The APO
scheduling algorithm is based on the effective channel anticipation
model. In contrast to the traditional schemes, the proposed method is
implemented based on a cyclic non-work-conserving discipline.
Simulation results indicated that proposed scheme has good
capability to maximize the channel usage efficiency in compared to
another exist scheduling methods. Simulation results demonstrate the
effectiveness of the proposed algorithm.
Abstract: Efficient and safe plant operation can only be
achieved if the operators are able to monitor all key process
parameters. Instrumentation is used to measure many process
variables, like temperatures, pressures, flow rates, compositions or
other product properties. Therefore Performance monitoring is a
suitable tool for operators. In this paper, we integrate rigorous
simulation model, data reconciliation and parameter estimation to
monitor process equipments and determine key performance
indicator (KPI) of them. The applied method here has been
implemented in two case studies.
Abstract: Anodizing is an electrochemical process that converts the metal surface into a decorative, durable, corrosion-resistant, anodic oxide finish. Aluminum is ideally suited to anodizing, although other nonferrous metals, such as magnesium and titanium, also can be anodized. The anodic oxide structure originates from the aluminum substrate and is composed entirely of aluminum oxide. This aluminum oxide is not applied to the surface like paint or plating, but is fully integrated with the underlying aluminum substrate, so cannot chip or peel. It has a highly ordered, porous structure that allows for secondary processes such as coloring and sealing. In this experimental paper, we focus on a reliable method for fabricating nanoporous alumina with high regularity. Starting from study of nanostructure materials synthesize methods. After that, porous alumina fabricate in the laboratory by anodization of aluminum oxide. Hard anodization processes are employed to fabricate the nanoporous alumina using 0.3M oxalic acid and 90, 120 and 140 anodized voltages. The nanoporous templates were characterized by SEM and FFT. The nanoporous templates using 140 voltages have high ordered. The pore formation, influence of the experimental conditions on the pore formation, the structural characteristics of the pore and the oxide chemical reactions involved in the pore growth are discuss.
Abstract: Solution of some practical problems is reduced to the
solution of the integro-differential equations. But for the numerical
solution of such equations basically quadrature methods or its
combination with multistep or one-step methods are used. The
quadrature methods basically is applied to calculation of the integral
participating in right hand side of integro-differential equations. As
this integral is of Volterra type, it is obvious that at replacement with
its integrated sum the upper limit of the sum depends on a current
point in which values of the integral are defined. Thus we receive the
integrated sum with variable boundary, to work with is hardly.
Therefore multistep method with the constant coefficients, which is
free from noted lack and gives the way for finding it-s coefficients is
present.
Abstract: A cross sectional study design and standard
microbiological procedures were used to determine the prevalence
and antimicrobial susceptibility patterns of Escherichia coli,
Salmonella enterica serovar typhimurium and Vibrio cholerae O1
isolated from water and two fish species Rastrineobola argentea and
Oreochromis niloticus collected from fish landing beaches and
markets in the Lake Victoria Basin of western Kenya. Out of 162
samples analyzed, 133 (82.1%) were contaminated, with S.
typhimurium as the most prevalent (49.6%), followed by E. coli
(46.6%), and lastly V. cholerae (2.8%). All the bacteria isolates were
sensitive to ciprofloxacin. E. coli isolates were resistant to ampicillin,
tetracycline, cotrimoxazole, chloramphenical and gentamicin while
S. typhimurium isolates exhibited resistance to ampicillin,
tetracycline, and cotrimoxazole. The V. cholerae O1 isolates were
resistant to tetracycline and ampicillin. The high prevalence of drug
resistant enteric bacteria in water and fish from the study region
needs public health intervention from the local government.
Abstract: The purpose of this paper is to explore the relationship
between the customers- issues in company corporate governance and
the financial performance. At the beginning theoretical background
consisting stakeholder theory and corporate governance is presented.
On this theoretical background, the empirical research is built,
collecting data of 60 Czech joint stock companies- boards
considering their relationships with customers. Correlation analysis
and multivariate regression analysis were employed to test the sample
on two hypotheses. The weak positive correlation between
stakeholder approach and the company size was identified. But both
hypotheses were not supported, because there was no significant
relation of independent variables to financial performance.
Abstract: Construction project control attempts to obtain real-time information and effectively enhance dynamic control and management via information sharing and analysis among project participants to eliminate construction conflicts and project delays. However, survey results for Taiwan indicate that construction commercial project management software is not widely accepted for subcontractors and suppliers. To solve the project communications problems among participants, this study presents a novel system called the Construction Dynamic Teams Communication Management (Con-DTCM) system for small-to-medium sized subcontractors and suppliers in Taiwanese Construction industry, and demonstrates that the Con-DTCM system responds to the most recent project information efficiently and enhances management of project teams (general contractor, suppliers and subcontractors) through web-based environment. Web-based technology effectively enhances information sharing during construction project management, and generates cost savings via the Internet. The main unique characteristic of the proposed Con-DTCM system is extremely user friendly and easily design compared with current commercial project management applications. The Con-DTCM system is applied to a case study of construction of a building project in Taiwan to confirm the proposed methodology and demonstrate the effectiveness of information sharing during the construction phase. The advantages of the Con-DTCM system are in improving project control and management efficiency for general contractors, and in providing dynamic project tracking and management, which enables subcontractors and suppliers to acquire the most recent project-related information. Furthermore, this study presents and implements a generic system architecture.
Abstract: Most integrated inertial navigation systems (INS) and
global positioning systems (GPS) have been implemented using the
Kalman filtering technique with its drawbacks related to the need for
predefined INS error model and observability of at least four
satellites. Most recently, a method using a hybrid-adaptive network
based fuzzy inference system (ANFIS) has been proposed which is
trained during the availability of GPS signal to map the error
between the GPS and the INS. Then it will be used to predict the
error of the INS position components during GPS signal blockage.
This paper introduces a genetic optimization algorithm that is used to
update the ANFIS parameters with respect to the INS/GPS error
function used as the objective function to be minimized. The results
demonstrate the advantages of the genetically optimized ANFIS for
INS/GPS integration in comparison with conventional ANFIS
specially in the cases of satellites- outages. Coping with this problem
plays an important role in assessment of the fusion approach in land
navigation.
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: The studies concerned an effect of six variants of ion
exchange substrate (nutrient carriers with a different potential impact
on pH of soil solution) on vegetation of orchard grass during two
different periods (42 and 84 days). In the pot experiment plants were
grown on sand (model of degraded soil) and six mixtures of sand and
2% (v/v) additions of particular variants of ion exchange substrate
(with pH ranged from 5.5 to 8.0). The study results showed that the
addition of the substrate at pH=6.5 caused the highest increase in
plant yield after shorter vegetation period whereas the addition of the
substrate at pH=5.5 increased dry stem and root biomass of orchard
grass after longer vegetation period. Thus, the ion exchange substrate
at pH=6.5 can be recommended for restoration of exhausted soils
when shorter vegetation period is planned; the ion exchange substrate
at pH=5.5 can be used for the same purpose when longer periods of
vegetative growth are considered.
Abstract: Automated discovery of Rule is, due to its applicability, one of the most fundamental and important method in KDD. It has been an active research area in the recent past. Hierarchical representation allows us to easily manage the complexity of knowledge, to view the knowledge at different levels of details, and to focus our attention on the interesting aspects only. One of such efficient and easy to understand systems is Hierarchical Production rule (HPRs) system. A HPR, a standard production rule augmented with generality and specificity information, is of the following form: Decision If < condition> Generality Specificity . HPRs systems are capable of handling taxonomical structures inherent in the knowledge about the real world. This paper focuses on the issue of mining Quantified rules with crisp hierarchical structure using Genetic Programming (GP) approach to knowledge discovery. The post-processing scheme presented in this work uses Quantified production rules as initial individuals of GP and discovers hierarchical structure. In proposed approach rules are quantified by using Dempster Shafer theory. Suitable genetic operators are proposed for the suggested encoding. Based on the Subsumption Matrix(SM), an appropriate fitness function is suggested. Finally, Quantified Hierarchical Production Rules (HPRs) are generated from the discovered hierarchy, using Dempster Shafer theory. Experimental results are presented to demonstrate the performance of the proposed algorithm.
Abstract: The main issue of interest here is whether individuals
who differ in arithmetical reasoning ability and levels of imagery ability display different brain activity during the conduct of mental
arithmetical reasoning tasks. This was a case study of four
participants who represented four extreme combinations of Maths –Imagery abilities: ie., low-low, high-high, high-low, low-high respectively. As the Ps performed a series of 60 arithmetical reasoning tasks, 128-channel EEG recordings were taken and the
pre-response interval subsequently analysed using EGI GeosourceTM
software. The P who was high in both imagery and maths ability
showed peak activity prior to response in BA7 (superior parietal cortex) but other Ps did not show peak activity in this region. The
results are considered in terms of the diverse routes that may be employed by individuals during the conduct of arithmetical reasoning
tasks and the possible implications of this for mathematics education.
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: Random and natural textures classification is still
one of the biggest challenges in the field of image processing and
pattern recognition. In this paper, texture feature extraction using
Slant Hadamard Transform was studied and compared to other
signal processing-based texture classification schemes. A
parametric SHT was also introduced and employed for natural
textures feature extraction. We showed that a subtly modified
parametric SHT can outperform ordinary Walsh-Hadamard
transform and discrete cosine transform. Experiments were carried
out on a subset of Vistex random natural texture images using a
kNN classifier.
Abstract: Using the quantum hydrodynamic (QHD) model for quantum plasma at finite temperature the modulational instability of electron plasma waves is investigated by deriving a nonlinear Schrodinger equation. It was found that the electron degeneracy parameter significantly affects the linear and nonlinear properties of electron plasma waves in quantum plasma.
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: 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.