The Study on the Wireless Power Transfer System for Mobile Robots
A wireless power transfer system can attribute to the
fields in robot, aviation and space in which lightening the weight of
device and improving the movement play an important role. A
wireless power transfer system was investigated to overcome the
inconvenience of using power cable. Especially a wireless power
transfer technology is important element for mobile robots. We
proposed the wireless power transfer system of the half-bridge
resonant converter with the frequency tracking and optimized
power transfer control unit. And the possibility of the application
and development system was verified through the experiment with
Wireless Power Transmission (WPT), resonancefrequency, protection circuit. LED.
Improvements in Edge Detection Based on Mathematical Morphology and Wavelet Transform using Fuzzy Rules
In this paper, an improved edge detection algorithm
based on fuzzy combination of mathematical morphology and
wavelet transform is proposed. The combined method is proposed to
overcome the limitation of wavelet based edge detection and
mathematical morphology based edge detection in noisy images.
Experimental results show superiority of the proposed method, as
compared to the traditional Prewitt, wavelet based and morphology
based edge detection methods. The proposed method is an effective
edge detection method for noisy image and keeps clear and
Edge detection, Wavelet transform, Mathematical
morphology, Fuzzy logic.
Face Recognition with PCA and KPCA using Elman Neural Network and SVM
In this paper, in order to categorize ORL database face
pictures, principle Component Analysis (PCA) and Kernel Principal
Component Analysis (KPCA) methods by using Elman neural
network and Support Vector Machine (SVM) categorization methods
are used. Elman network as a recurrent neural network is proposed
for modeling storage systems and also it is used for reviewing the
effect of using PCA numbers on system categorization precision rate
and database pictures categorization time. Categorization stages are
conducted with various components numbers and the obtained results
of both Elman neural network categorization and support vector
machine are compared. In optimum manner 97.41% recognition
accuracy is obtained.
Face recognition, Principal Component Analysis,
Kernel Principal Component Analysis, Neural network, Support
Artificial Intelligent (AI) Based Cascade Multi-Level Inverter for Smart Nano Grid
As wind, solar and other clean and green energy
sources gain popularity worldwide, engineers are seeking ways to
make renewable energy systems more affordable and to integrate
them with existing ac power grids. In the present paper an attempt
has been made for integrating the PV arrays to the smart nano grid
using an artificial intelligent (AI) based solar powered cascade multilevel
inverter. The AI based controller switching scheme has been
used for improving the power quality by reducing the Total Harmonic
Distortion (THD) of the multi-level inverter output voltage.
Artificial Intelligent (AI), Solar Powered Multi-level Inverter, Smart nano grid, Total Harmonic Distortion (THD).
Effective Keyword and Similarity Thresholds for the Discovery of Themes from the User Web Access Patterns
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.
Data mining, knowledge discovery, clustering, dataanalysis, Web log analysis, theme based searching.
Colorectal Cancer Screening by a CEACAM-6 Immunosensor
The biomarker for colorectal cancer (CRC) is CEACAM-6 antigen (C6AG). Therefore, this study aims to develop a novel, simple and low-cost CEACAM-6 antigen immumosensor (C6AG-IMS), based on electrical impedance measurement, for precise determination of C6AG. A low-cost screen-printed graphite electrode was constructed and used as the sensor, with CEACAM-6 antibody (C6AB) immobilized on it. The procedures of sensor fabrication and antibody immobilization are simple and low-cost. Measurement of the electrical impedance at a definite frequency ranges (0.43 – 1.26 MHz) showed that the C6AG-IMS has an excellent linear (r2>0.9) response range (8.125 – 65 pg/mL), covering the normal physiological and pathological ranges of blood C6AG levels. Also, the C6AG-IMS has excellent reliability and validity, with the intraclass correlation coefficient being 0.97. In conclusion, a novel, simple, low-cost and reliable C6AG-IMS was designed and developed, being able to accurately determine blood C6AG levels in the range of pathological and normal physiological regions. The C6AG-IMS can provide a point-of-care and immediate screening results to the user at home.
Colorectal Cancer, Immunosensor, Electrical Impedance, CEACAM-6, Measurement, Point-of-Care
Mining and Visual Management of XML-Based Image Collections
This article describes Uruk, the virtual museum of
Iraq that we developed for visual exploration and retrieval of image
collections. The system largely exploits the loosely-structured
hierarchy of XML documents that provides a useful representation
method to store semi-structured or unstructured data, which does not
easily fit into existing database. The system offers users the
capability to mine and manage the XML-based image collections
through a web-based Graphical User Interface (GUI). Typically, at an
interactive session with the system, the user can browse a visual
structural summary of the XML database in order to select interesting
elements. Using this intermediate result, queries combining structure
and textual references can be composed and presented to the system.
After query evaluation, the full set of answers is presented in a visual
and structured way.
Data-centric XML, graphical user interfaces,
information retrieval, case-based reasoning, fuzzy sets
Determination of Adequate Fuzzy Inequalities for their Usage in Fuzzy Query Languages
Although the usefulness of fuzzy databases has been
pointed out in several works, they are not fully developed in numerous
domains. A task that is mostly disregarded and which is the topic
of this paper is the determination of suitable inequalities for fuzzy
sets in fuzzy query languages. This paper examines which kinds
of fuzzy inequalities exist at all. Afterwards, different procedures
are presented that appear theoretically appropriate. By being applied
to various examples, their strengths and weaknesses are revealed.
Furthermore, an algorithm for an efficient computation of the selected
fuzzy inequality is shown.
Fuzzy Databases, Fuzzy Inequalities, Fuzzy QueryLanguages, Fuzzy Ranking.
Preparation Influences of Breed, sex and Sodium Butyrate Supplementation on the Performance, Carcass Traits and Mortality of Fattening Rabbits
Twenty four New Zealand white rabbits (12 does and
12 bucks) and twenty four Flanders (12 does and 12 bucks) rabbits,
allotted into two feeding regime (6 for each breed, 3 males and 3
females) first one fed commercial ration and second one fed
commercial diet plus sodium butyrate (300 g/ton). The obtained
results showed that at end of 8th week experimental period New
Zealand white rabbits were heavier body weight than Flanders rabbits
(1934.55+39.05 vs. 1802.5+30.99 g); significantly high body weight
gain during experimental period especially during 8th week
(136.1+3.5 vs. 126.8+1.8 g/week); better feed conversion ratio during
all weeks of experiment from first week (3.07+0.16 vs. 3.12+0.10)
till the 8th week of experiment (5.54+0.16 vs. 5.76+0.07) with
significantly high dressing percentages (0.54+0.01 vs. 0.52+0.01).
Also all carcass cuts were significantly high in New Zealand white
rabbits than Flanders. Females rabbits (at the same age) were lower
body weight than males from start of experiment (941.1+39.8
vs.972.1+33.5 g) till the end of experiment (1833.64+37.69 vs.
1903.41+36.93 g); gained less during all weeks of experiment except
during 8th week (132.1+2.3 vs. 130.9+3.4 g/week), with lower
dressing percentage (0.52+0.01 vs. 0.53+0.01) and lighter carcass
cuts than males, however, they had better feed conversion ratio
during 1st week, 7th week and 8th week of experiment. Addition of
300g sodium butyrate/ton of rabbit increased the body weight of
rabbits at the end of experimental period (1882.71+26.45 vs.
1851.5+49.82 g); improve body weight gain at 3rd, 4th, 5th, 6th and
7th week of experiment and significantly improve feed conversion
ratio during all weeks of the experiment from 1st week (2.85+0.07
vs. 3.30+0.15) till the 8th week of the experiment (5.51+0.12 vs.
5.77+0.12). Also the dressing percentage was higher in Sodium
butyrate fed groups than control one (0.53+0.01 vs. 0.52+0.01) and
the most important results of feeding sodium butyrate is the reducing
of the mortality percentage in rabbits during 8 week experiment to
zero percentage as compared with 16% in control group.
rabbit, productive performance, carcass quality,
Intelligent Multi-Agent Middleware for Ubiquitous Home Networking Environments
The next stage of the home networking environment is
supposed to be ubiquitous, where each piece of material is equipped
with an RFID (Radio Frequency Identification) tag. To fully support
the ubiquitous environment, home networking middleware should be
able to recommend home services based on a user-s interests and
efficiently manage information on service usage profiles for the users.
Therefore, USN (Ubiquitous Sensor Network) technology, which
recognizes and manages a appliance-s state-information (location,
capabilities, and so on) by connecting RFID tags is considered. The
Intelligent Multi-Agent Middleware (IMAM) architecture was
proposed to intelligently manage the mobile RFID-based home
networking and to automatically supply information about home
services that match a user-s interests. Evaluation results for
personalization services for IMAM using Bayesian-Net and Decision
Trees are presented.
Intelligent Agents, Home Network, Mobile RFID,Intelligent Middleware.
Secondary School Students- Perceptions about Biological Issues in South Korea
The purpose of present paper was to investigate
perceptions of Korean secondary school students about social issues
related to biological sciences. Twenty issues were selected based on
topics of articles in the newspaper from 2005 to 2010. The issues were
categorized into biotechnology, health-disease and environment
domains. Subjects were 541 high school students (male 253 and
female 288). On the survey, students were asked to answer on 5-point
Lickert scales how they thought of the effect of biological phenomena
or events related to biological issues on the individual life and the
society. They perceived that the biological issues would be more
effectible on the society than on the individual life. Female students
had a little more perceptions than males.
biological issue, biological sciences, perception,
A Study on the Secure ebXML Transaction Models
ebXML (Electronic Business using eXtensible
Markup Language) is an e-business standard, sponsored by
UN/CEFACT and OASIS, which enables enterprises to exchange
business messages, conduct trading relationships, communicate
data in common terms and define and register business
processes. While there is tremendous e-business value in the
ebXML, security remains an unsolved problem and one of the
largest barriers to adoption. XML security technologies emerging
recently have extensibility and flexibility suitable for security
implementation such as encryption, digital signature, access
control and authentication.
In this paper, we propose ebXML business transaction models
that allow trading partners to securely exchange XML based
business transactions by employing XML security technologies.
We show how each XML security technology meets the ebXML
standard by constructing the test software and validating messages
between the trading partners.
Electronic commerce, e-business standard, ebXML,XML security, secure business transaction.
A Simple Adaptive Algorithm for Norm-Constrained Optimization
In this paper we propose a simple adaptive algorithm
iteratively solving the unit-norm constrained optimization problem.
Instead of conventional parameter norm based normalization,
the proposed algorithm incorporates scalar normalization which is
computationally much simpler. The analysis of stationary point is
presented to show that the proposed algorithm indeed solves the
constrained optimization problem. The simulation results illustrate
that the proposed algorithm performs as good as conventional ones
while being computationally simpler.
constrained optimization, unit-norm, LMS, principle
Intuitive Robot Control Using Surface EMG and Accelerometer Signals
This paper proposes a method of remotely controlling robots with arm gestures using surface electromyography (EMG) and accelerometer sensors attached to the operator’s wrists. The EMG and accelerometer sensors receive signals from the arm gestures of the operator and infer the corresponding movements to execute the command to control the robot. The movements of the robot include moving forward and backward and turning left and right. The accuracy is over 99% and movements can be controlled in real time.
EMG, accelerometer, K-nn, entropy.
Vision Based Hand Gesture Recognition Using Generative and Discriminative Stochastic Models
Many approaches to pattern recognition are founded on probability theory, and can be broadly characterized as either generative
or discriminative according to whether or not the distribution of the image features. Generative and discriminative models have
very different characteristics, as well as complementary strengths and weaknesses. In this paper, we study these models to recognize the patterns of alphabet characters (A-Z) and numbers (0-9). To handle isolated pattern, generative model as Hidden Markov Model (HMM) and discriminative models like Conditional Random Field (CRF), Hidden Conditional Random Field (HCRF) and Latent-Dynamic Conditional Random Field (LDCRF) with different number of window size are applied on extracted pattern features. The gesture recognition rate is improved initially as the window size increase, but degrades as window size increase further. Experimental results show that the LDCRF is the best in terms of results than CRF, HCRF and HMM at window size equal 4. Additionally, our results show that; an overall recognition rates are 91.52%, 95.28%, 96.94% and 98.05% for CRF,
HCRF, HMM and LDCRF respectively.
Statistical Pattern Recognition, Generative Model, Discriminative Model, Human Computer Interaction.
Spark Breakdown Voltage and Surface Degradation of Multiwalled Carbon Nanotube Electrode Surfaces
Silicon substrates coated with multiwalled carbon nanotubes (MWCNTs) were experimentally investigated to determine spark breakdown voltages relative to uncoated surfaces, the degree of surface degradation associated with the spark discharge, and techniques to minimize the surface degradation. The results may be applicable to instruments or processes that use MWCNT as a means of increasing local electric field strength and where spark breakdown is a possibility that might affect the devices’ performance or longevity. MWCNTs were shown to reduce the breakdown voltage of a 1mm gap in air by 30-50%. The relative decrease in breakdown voltage was maintained over gap distances of 0.5 to 2mm and gauge pressures of 0 to 4 bar. Degradation of the MWCNT coated surfaces was observed. Several techniques to improve durability were investigated. These included: chromium and gold-palladium coatings, tube annealing, and embedding clusters of MWCNT in a ceramic matrix.
Ionization sensor, spark, nanotubes, electrode, breakdown.
A Novel Method for Non-Invasive Diagnosis of Hepatitis C Virus Using Electromagnetic Signal Detection: A Multicenter International Study
A simple, rapid and non-invasive electromagnetic sensor (C-FAST device) was- patented; for diagnosis of HCV RNA. Aim: To test the validity of the device compared to standard HCV PCR. Subjects and Methods: The first phase was done as pilot in Egypt on 79 participants; the second phase was done in five centers: one center from Egypt, two centers from Pakistan and two centers from India (800, 92 and 113 subjects respectively). The third phase was done nationally as multicenter study on (1600) participants for ensuring its representativeness. Results: When compared to PCR technique, C-FAST device revealed sensitivity 95% to 100%, specificity 95.5% to 100%, PPV 89.5% to 100%, NPV 95% to 100% and positive likelihood ratios 21.8% to 38.5%. Conclusion: It is practical evidence that HCV nucleotides emit electromagnetic signals that can be used for its identification. As compared to PCR, C-FAST is an accurate, valid and non-invasive device.
C-FAST- a valid and reliable device, Distant cellular interaction, Electromagnetic signal detection, Non-invasive diagnosis of HCV.
Inhibitory Effects of Ambrosia trifida L. on the Development of Root Hairs and Protein Patterns of Radicles
Ambrosia trifida L. is designated as invasive alien
species by the Act on the Conservation and Use of Biodiversity by the
Ministry of Environment, Korea. The purpose of present paper was to
investigate the inhibitory effects of aqueous extracts of A.trifida on the
development of root hairs of Triticum aestivum L., and Allium
tuberosum Rottler ex Spreng and the electrophoretic protein patterns of
their radicles. The development of root hairs was inhibited by
increasing of aqueous extract concentrations. Through SDS-PAGE,
the electrophoretic protein bands of extracted proteins from their
radicles were appeared in controls, but protein bands of specific
molecular weight disappeared or weakened in treatments. In
conclusion, inhibitory effects of A. trifida made two receptor species
changed morphologically, and at the molecular level in early growth
Ambrosia trifida L., invasive alien species, inhibitory
effect, root hair, electrophoretic protein, radicle.
Secondary Science Teachers’ Views about Purposes of Practical Works in School Science
The purpose of this paper was to examine views of
secondary school science teachers about purposes to use practical
works in school science. The instrument to survey consisted eighteen
items, which were categorized into four components as follows:
‘Scientific inquiry’, ‘Scientific knowledge’, ‘Science-related attitude’,
and ‘STS (science-technology-society)’. Subjects were 152 secondary
school science teachers (male 70 and female 82; middle school 50 and
high school 102), who are teaching in 42 schools of 8 provinces. On
the survey, science teachers were asked to answer on 5-point Lickert
scale (from 1 to 5) how they thought of using practical works on
purposes with domains of science objectives in school. They had
positive views about using practical works for improving scientific
inquiry process skills, science-related attitudes, and perceptions about
STS literacy, and acquiring scientific knowledge. They would have the
most willingness of using practical works for ‘Scientific Inquiry’
among domains of science objectives in school.
Secondary school, science teacher, practical work,
scientific inquiry, scientific knowledge, science-related attitude, STS.
Impact of Harmonic Resonance and V-THD in Sohar Industrial Port–C Substation
This paper presents an analysis study on the impacts
of the changes of the capacitor banks, the loss of a transformer, and
the installation of distributed generation on the voltage total harmonic
distortion and harmonic resonance. The study is applied in a real
system in Oman, Sohar Industrial Port–C Substation Network.
Frequency scan method and Fourier series analysis method are used
with the help of EDSA software. Moreover, the results are compared
with limits specified by national Oman distribution code.
Power quality, capacitor bank, voltage total
harmonics distortion, harmonic resonance, frequency scan.
Replicating Brain’s Resting State Functional Connectivity Network Using a Multi-Factor Hub-Based Model
The brain’s functional connectivity while temporally non-stationary does express consistency at a macro spatial level. The study of stable resting state connectivity patterns hence provides opportunities for identification of diseases if such stability is severely perturbed. A mathematical model replicating the brain’s spatial connections will be useful for understanding brain’s representative geometry and complements the empirical model where it falls short. Empirical computations tend to involve large matrices and become infeasible with fine parcellation. However, the proposed analytical model has no such computational problems. To improve replicability, 92 subject data are obtained from two open sources. The proposed methodology, inspired by financial theory, uses multivariate regression to find relationships of every cortical region of interest (ROI) with some pre-identified hubs. These hubs acted as representatives for the entire cortical surface. A variance-covariance framework of all ROIs is then built based on these relationships to link up all the ROIs. The result is a high level of match between model and empirical correlations in the range of 0.59 to 0.66 after adjusting for sample size; an increase of almost forty percent. More significantly, the model framework provides an intuitive way to delineate between systemic drivers and idiosyncratic noise while reducing dimensions by more than 30 folds, hence, providing a way to conduct attribution analysis. Due to its analytical nature and simple structure, the model is useful as a standalone toolkit for network dependency analysis or as a module for other mathematical models.
Functional magnetic resonance imaging, multivariate regression, network hubs, resting state functional connectivity.
Effect of the Cross-Sectional Geometry on Heat Transfer and Particle Motion of Circulating Fluidized Bed Riser for CO2 Capture
Effect of the cross-sectional geometry on heat transfer and particle motion of circulating fluidized bed riser for CO2 capture was investigated. Numerical simulation using Eulerian-eulerian method with kinetic theory of granular flow was adopted to analyze gas-solid flow consisting in circulating fluidized bed riser. Circular, square, and rectangular cross-sectional geometry cases of the same area were carried out. Rectangular cross-sectional geometries were analyzed having aspect ratios of 1: 2, 1: 4, 1: 8, and 1:16. The cross-sectional geometry significantly influenced the particle motion and heat transfer. The downward flow pattern of solid particles near the wall was changed. The gas-solid mixing degree of the riser with the rectangular cross section of the high aspect ratio was the lowest. There were differences in bed-to-wall heat transfer coefficient according to rectangular geometry with different aspect ratios.
Bed geometry, computational fluid dynamics, circulating fluidized bed riser, heat transfer.