Abstract: A novel application of neural network approach to
fault classification and fault location of Medium voltage cables is
demonstrated in this paper. Different faults on a protected cable
should be classified and located correctly. This paper presents the use
of neural networks as a pattern classifier algorithm to perform these
tasks. The proposed scheme is insensitive to variation of different
parameters such as fault type, fault resistance, and fault inception
angle. Studies show that the proposed technique is able to offer high
accuracy in both of the fault classification and fault location tasks.
Abstract: The problem of N cracks interaction in an isotropic
elastic solid is decomposed into a subproblem of a homogeneous solid
without crack and N subproblems with each having a single crack
subjected to unknown tractions on the two crack faces. The unknown
tractions, namely pseudo tractions on each crack are expanded into
polynomials with unknown coefficients, which have to be determined
by the consistency condition, i.e. by the equivalence of the original
multiple cracks interaction problem and the superposition of the N+1
subproblems. In this paper, Kachanov-s approach of average tractions
is extended into the method of moments to approximately impose the
consistence condition. Hence Kachanov-s method can be viewed as
the zero-order method of moments. Numerical results of the stress
intensity factors are presented for interactions of two collinear cracks,
three collinear cracks, two parallel cracks, and three parallel cracks.
As the order of moment increases, the accuracy of the method of
moments improves.
Abstract: Studies in economics domain tried to reveal the correlation between stock markets. Since the globalization era, interdependence between stock markets becomes more obvious. The Dynamic Interaction Network (DIN) algorithm, which was inspired by a Gene Regulatory Network (GRN) extraction method in the bioinformatics field, is applied to reveal important and complex dynamic relationship between stock markets. We use the data of the stock market indices from eight countries around the world in this study. Our results conclude that DIN is able to reveal and model patterns of dynamic interaction from the observed variables (i.e. stock market indices). Furthermore, it is also found that the extracted network models can be utilized to predict movement of the stock market indices with a considerably good accuracy.
Abstract: The medical data statistical analysis often requires the
using of some special techniques, because of the particularities of
these data. The principal components analysis and the data clustering
are two statistical methods for data mining very useful in the medical
field, the first one as a method to decrease the number of studied
parameters, and the second one as a method to analyze the
connections between diagnosis and the data about the patient-s
condition. In this paper we investigate the implications obtained from
a specific data analysis technique: the data clustering preceded by a
selection of the most relevant parameters, made using the principal
components analysis. Our assumption was that, using the principal
components analysis before data clustering - in order to select and to
classify only the most relevant parameters – the accuracy of
clustering is improved, but the practical results showed the opposite
fact: the clustering accuracy decreases, with a percentage
approximately equal with the percentage of information loss reported
by the principal components analysis.
Abstract: Researches on the general rules of temperature field
changing and their effects on the bridge in construction are necessary.
This paper investigated the rules of temperature field changing and its
effects on bridge using onsite measurement and computational
analysis. Guanyinsha Bridge was used as a case study in this research.
The temperature field was simulated in analyses. The effects of certain
boundary conditions such as sun radiance, wind speed, and model
parameters such as heat factor and specific heat on temperature field
are investigated. Recommended values for these parameters are
proposed. The simulated temperature field matches the measured
observations with high accuracy. At the same time, the stresses and
deflections of the bridge computed with the simulated temperature
field matches measured values too. As a conclusion, the temperature
effect analysis of reinforced concrete box girder can be conducted
directly based on the reliable weather data of the concerned area.
Abstract: A trustworthy voting process in democratic is
important that each vote is recorded with accuracy and impartiality.
The accuracy and impartiality are tallied in high rate with biometric
system. One of the sign is a fingerprint. Fingerprint recognition is
still a challenging problem, because of the distortions among the
different impression of the same finger. Because of the trustworthy of
biometric voting technologies, it may give a great effect on numbers
of voter-s participation and outcomes of the democratic process.
Hence in this study, the authors are interested in designing and
analyzing the Electronic Voting System and the participation of the
users. The system is based on the fingerprint minutiae with the
addition of person ID number. This is in order to enhance the
accuracy and speed of the voting process. The new design is analyzed
by conducting pilot election among a class of students for selecting
their representative.
Abstract: Evapotranspiration (ET) is a major component of the hydrologic cycle and its accurate estimation is essential for hydrological studies. In past, various estimation methods have been developed for different climatological data, and the accuracy of these methods varies with climatic conditions. Reference crop evapotranspiration (ET0) is a key variable in procedures established for estimating evapotranspiration rates of agricultural crops. Values of ET0 are used with crop coefficients for many aspects of irrigation and water resources planning and management. Numerous methods are used for estimating ET0. As per internationally accepted procedures outlined in the United Nations Food and Agriculture Organization-s Irrigation and Drainage Paper No. 56(FAO-56), use of Penman-Monteith equation is recommended for computing ET0 from ground based climatological observations. In the present study, seven methods have been selected for performance evaluation. User friendly software has been developed using programming language visual basic. The visual basic has ability to create graphical environment using less coding. For given data availability the developed software estimates reference evapotranspiration for any given area and period for which data is available. The accuracy of the software has been checked by the examples given in FAO-56.The developed software is a user friendly tool for estimating ET0 under different data availability and climatic conditions.
Abstract: In this paper, we propose a method for detecting
circular shapes with subpixel accuracy. First, the geometric properties
of circles have been used to find the diameters as well as the
circumference pixels. The center and radius are then estimated by the
circumference pixels. Both synthetic and real images have been tested
by the proposed method. The experimental results show that the new
method is efficient.
Abstract: A new approach to predict the 3D structures of proteins by combining the knowledge-based method and Molecular Dynamics Simulation is presented on the chicken villin headpiece subdomain (HP-36). Comparative modeling is employed as the knowledge-based method to predict the core region (Ala9-Asn28) of the protein while the remaining residues are built as extended regions (Met1-Lys8; Leu29-Phe36) which then further refined using Molecular Dynamics Simulation for 120 ns. Since the core region is built based on a high sequence identity to the template (65%) resulting in RMSD of 1.39 Å from the native, it is believed that this well-developed core region can act as a 'nucleation center' for subsequent rapid downhill folding. Results also demonstrate that the formation of the non-native contact which tends to hamper folding rate can be avoided. The best 3D model that exhibits most of the native characteristics is identified using clustering method which then further ranked based on the conformational free energies. It is found that the backbone RMSD of the best model compared to the NMR-MDavg is 1.01 Å and 3.53 Å, for the core region and the complete protein, respectively. In addition to this, the conformational free energy of the best model is lower by 5.85 kcal/mol as compared to the NMR-MDavg. This structure prediction protocol is shown to be effective in predicting the 3D structure of small globular protein with a considerable accuracy in much shorter time compared to the conventional Molecular Dynamics simulation alone.
Abstract: A high-linearity and high-speed current-mode sampleand-
hold circuit is designed and simulated using a 0.25μm CMOS
technology. This circuit design is based on low voltage and it utilizes
a fully differential circuit. Due to the use of only two switches the
switch related noise has been reduced. Signal - dependent -error is
completely eliminated by a new zero voltage switching technique.
The circuit has a linearity error equal to ±0.05μa, i.e. 12-bit
accuracy with a ±160 μa differential output - input signal frequency
of 5MHZ, and sampling frequency of 100 MHZ. Third
harmonic is equal to –78dB.
Abstract: Recently, the Spherical Motion Models (SMM-s) have been introduced [1]. These new models have been developed for 3D local landmark-base Autonomous Navigation (AN). This paper is revealing new arguments and experimental results to support the SMM-s characteristics. The accuracy and the robustness in performing a specific task are the main concerns of the new investigations. To analyze their performances of the SMM-s, the most powerful tools of estimation theory, the extended Kalman filter (EKF) and unscented Kalman filter (UKF), which give the best estimations in noisy environments, have been employed. The Monte Carlo validation implementations used to test the stability and robustness of the models have been employed as well.
Abstract: A new reverse phase-high performance liquid chromatography (RP-HPLC) method with fluorescent detector (FLD) was developed and optimized for Norfloxacin determination in human plasma. Mobile phase specifications, extraction method and excitation and emission wavelengths were varied for optimization. HPLC system contained a reverse phase C18 (5 μm, 4.6 mm×150 mm) column with FLD operated at excitation 330 nm and emission 440 nm. The optimized mobile phase consisted of 14% acetonitrile in buffer solution. The aqueous phase was prepared by mixing 2g of citric acid, 2g sodium acetate and 1 ml of triethylamine in 1 L of Milli-Q water was run at a flow rate of 1.2 mL/min. The standard curve was linear for the range tested (0.156–20 μg/mL) and the coefficient of determination was 0.9978. Aceclofenac sodium was used as internal standard. A detection limit of 0.078 μg/mL was achieved. Run time was set at 10 minutes because retention time of norfloxacin was 0.99 min. which shows the rapidness of this method of analysis. The present assay showed good accuracy, precision and sensitivity for Norfloxacin determination in human plasma with a new internal standard and can be applied pharmacokinetic evaluation of Norfloxacin tablets after oral administration in human.
Abstract: this paper presents an auto-regressive network called the Auto-Regressive Multi-Context Recurrent Neural Network (ARMCRN), which forecasts the daily peak load for two large power plant systems. The auto-regressive network is a combination of both recurrent and non-recurrent networks. Weather component variables are the key elements in forecasting because any change in these variables affects the demand of energy load. So the AR-MCRN is used to learn the relationship between past, previous, and future exogenous and endogenous variables. Experimental results show that using the change in weather components and the change that occurred in past load as inputs to the AR-MCRN, rather than the basic weather parameters and past load itself as inputs to the same network, produce higher accuracy of predicted load. Experimental results also show that using exogenous and endogenous variables as inputs is better than using only the exogenous variables as inputs to the network.
Abstract: one of the significant factors for improving the
accuracy of Land Surface Temperature (LST) retrieval is the correct
understanding of the directional anisotropy for thermal radiance. In
this paper, the multiple scattering effect between heterogeneous
non-isothermal surfaces is described rigorously according to the
concept of configuration factor, based on which a directional thermal
radiance model is built, and the directional radiant character for urban
canopy is analyzed. The model is applied to a simple urban canopy
with row structure to simulate the change of Directional Brightness
Temperature (DBT). The results show that the DBT is aggrandized
because of the multiple scattering effects, whereas the change range of
DBT is smoothed. The temperature difference, spatial distribution,
emissivity of the components can all lead to the change of DBT. The
“hot spot" phenomenon occurs when the proportion of high
temperature component in the vision field came to a head. On the other
hand, the “cool spot" phenomena occur when low temperature
proportion came to the head. The “spot" effect disappears only when
the proportion of every component keeps invariability. The model
built in this paper can be used for the study of directional effect on
emissivity, the LST retrieval over urban areas and the adjacency effect
of thermal remote sensing pixels.
Abstract: This paper describes the development of a fully
automated measurement software for antenna radiation pattern
measurements in a Compact Antenna Test Range (CATR). The
CATR has a frequency range from 2-40 GHz and the measurement
hardware includes a Network Analyzer for transmitting and
Receiving the microwave signal and a Positioner controller to control
the motion of the Styrofoam column. The measurement process
includes Calibration of CATR with a Standard Gain Horn (SGH)
antenna followed by Gain versus angle measurement of the Antenna
under test (AUT). The software is designed to control a variety of
microwave transmitter / receiver and two axis Positioner controllers
through the standard General Purpose interface bus (GPIB) interface.
Addition of new Network Analyzers is supported through a slight
modification of hardware control module. Time-domain gating is
implemented to remove the unwanted signals and get the isolated
response of AUT. The gated response of the AUT is compared with
the calibration data in the frequency domain to obtain the desired
results. The data acquisition and processing is implemented in
Agilent VEE and Matlab. A variety of experimental measurements
with SGH antennas were performed to validate the accuracy of
software. A comparison of results with existing commercial
softwares is presented and the measured results are found to be
within .2 dBm.
Abstract: Bioinformatics methods for predicting the T cell
coreceptor usage from the array of membrane protein of HIV-1 are
investigated. In this study, we aim to propose an effective prediction
method for dealing with the three-class classification problem of
CXCR4 (X4), CCR5 (R5) and CCR5/CXCR4 (R5X4). We made
efforts in investigating the coreceptor prediction problem as follows: 1)
proposing a feature set of informative physicochemical properties
which is cooperated with SVM to achieve high prediction test
accuracy of 81.48%, compared with the existing method with
accuracy of 70.00%; 2) establishing a large up-to-date data set by
increasing the size from 159 to 1225 sequences to verify the proposed
prediction method where the mean test accuracy is 88.59%, and 3)
analyzing the set of 14 informative physicochemical properties to
further understand the characteristics of HIV-1coreceptors.
Abstract: This paper presents design, analysis and comparison of the different rotor type permanent magnet machines. The presented machines are designed as having same geometrical dimensions and same materials for comparison. The main machine parameters of interior and exterior rotor type machines including eddy current effect, torque-speed characteristics and magnetic analysis are investigated using MAXWELL program. With this program, the components of the permanent magnet machines can be calculated with high accuracy. Six types of Permanent machines are compared with respect to their topology, size, magnetic field, air gap flux, voltage, torque, loss and efficiency. The analysis results demonstrate the effectiveness of the proposed machines design methodology. We believe that, this study will be a helpful resource in terms of examination and comparison of the basic structure and magnetic features of the PM (Permanent magnet) machines which have different rotor structure.
Abstract: The length of a given rational B'ezier curve is
efficiently estimated. Since a rational B'ezier function is nonlinear,
it is usually impossible to evaluate its length exactly. The
length is approximated by using subdivision and the accuracy
of the approximation n is investigated. In order to improve
the efficiency, adaptivity is used with some length estimator.
A rigorous theoretical analysis of the rate of convergence of
n to is given. The required number of subdivisions to
attain a prescribed accuracy is also analyzed. An application
to CAD parametrization is briefly described. Numerical results
are reported to supplement the theory.
Abstract: In this paper, an optimal design of linear phase digital
high pass finite impulse response (FIR) filter using Particle Swarm
Optimization with Constriction Factor and Inertia Weight Approach
(PSO-CFIWA) has been presented. In the design process, the filter
length, pass band and stop band frequencies, feasible pass band and
stop band ripple sizes are specified. FIR filter design is a multi-modal
optimization problem. The conventional gradient based optimization
techniques are not efficient for digital filter design. Given the filter
specifications to be realized, the PSO-CFIWA algorithm generates a
set of optimal filter coefficients and tries to meet the ideal frequency
response characteristic. In this paper, for the given problem, the
designs of the optimal FIR high pass filters of different orders have
been performed. The simulation results have been compared to those
obtained by the well accepted algorithms such as Parks and
McClellan algorithm (PM), genetic algorithm (GA). The results
justify that the proposed optimal filter design approach using PSOCFIWA
outperforms PM and GA, not only in the accuracy of the
designed filter but also in the convergence speed and solution
quality.
Abstract: Deep Brain Stimulation or DBS is a surgical treatment for Parkinson-s Disease with three stimulation parameters: frequency, pulse width, and voltage. The parameters should be selected appropriately to achieve effective treatment. This selection now, performs clinically. The aim of this research is to study chaotic behavior of recorded tremor of patients under DBS in order to present a computational method to recognize stimulation optimum voltage. We obtained some chaotic features of tremor signal, and discovered embedding space of it has an attractor, and its largest Lyapunov exponent is positive, which show tremor signal has chaotic behavior, also we found out, in optimal voltage, entropy and embedding space variance of tremor signal have minimum values in comparison with other voltages. These differences can help neurologists recognize optimal voltage numerically, which leads to reduce patients' role and discomfort in optimizing stimulation parameters and to do treatment with high accuracy.