Abstract: Protein 3D structure prediction has always been an
important research area in bioinformatics. In particular, the
prediction of secondary structure has been a well-studied research
topic. Despite the recent breakthrough of combining multiple
sequence alignment information and artificial intelligence algorithms
to predict protein secondary structure, the Q3 accuracy of various
computational prediction algorithms rarely has exceeded 75%. In a
previous paper [1], this research team presented a rule-based method
called RT-RICO (Relaxed Threshold Rule Induction from Coverings)
to predict protein secondary structure. The average Q3 accuracy on
the sample datasets using RT-RICO was 80.3%, an improvement
over comparable computational methods. Although this demonstrated
that RT-RICO might be a promising approach for predicting
secondary structure, the algorithm-s computational complexity and
program running time limited its use. Herein a parallelized
implementation of a slightly modified RT-RICO approach is
presented. This new version of the algorithm facilitated the testing of
a much larger dataset of 396 protein domains [2]. Parallelized RTRICO
achieved a Q3 score of 74.6%, which is higher than the
consensus prediction accuracy of 72.9% that was achieved for the
same test dataset by a combination of four secondary structure
prediction methods [2].
Abstract: Leo Breimans Random Forests (RF) is a recent
development in tree based classifiers and quickly proven to be one of
the most important algorithms in the machine learning literature. It
has shown robust and improved results of classifications on standard
data sets. Ensemble learning algorithms such as AdaBoost and
Bagging have been in active research and shown improvements in
classification results for several benchmarking data sets with mainly
decision trees as their base classifiers. In this paper we experiment to
apply these Meta learning techniques to the random forests. We
experiment the working of the ensembles of random forests on the
standard data sets available in UCI data sets. We compare the
original random forest algorithm with their ensemble counterparts
and discuss the results.
Abstract: The dominant judgment for earthquake damaged reinforced concrete (RC) structures is to rebuild them with the new ones. Consequently, this paper estimates if there is chance to repair earthquake RC beams and obtain economical contribution to modern day society. Therefore, the totally damaged (damaged in shear under cyclic load) reinforced concrete (RC) beams repaired and strengthened by externally bonded carbon fibre reinforced polymer (CFRP) strips in this study. Four specimens, apart from the reference beam, were separated into two distinct groups. Two experimental beams in the first group primarily tested up to failure then appropriately repaired and strengthened with CFRP strips. Two undamaged specimens from the second group were not repaired but strengthened by the identical strengthening scheme as the first group for comparison. This study studies whether earthquake damaged RC beams that have been repaired and strengthened will validate similar strength and behavior to equally strengthened, undamaged RC beams. Accordingly, a strength correspondence according to strengthened specimens was acquired for the repaired and strengthened specimens. Test results confirmed that repair and strengthening, which were estimated in the experimental program, were effective for the specimens with the cracking patterns considered in the experimental program.
Abstract: We report a lithography-free approach to fabricate the
biomimetics, quasi-beehive Si nanostructures (QBSNs), on
Si-substrates. The self-assembled SiGe nanoislands via the strain
induced surface roughening (Asaro-Tiller-Grinfeld instability) during
in-situ annealing play a key role as patterned sacrifice regions for
subsequent reactive ion etching (RIE) process performed for
fabricating quasi-beehive nanostructures on Si-substrates. As the
measurements of field emission, the bare QBSNs show poor field
emission performance, resulted from the existence of the native oxide
layer which forms an insurmountable barrier for electron emission. In
order to dramatically improve the field emission characteristics, the
platinum nanopillars (Pt-NPs) were deposited on QBSNs to form
Pt-NPs/QBSNs heterostructures. The turn-on field of Pt-NPs/QBSNs
is as low as 2.29 V/μm (corresponding current density of 1 μA/cm2),
and the field enhancement factor (β-value) is significantly increased to
6067. More importantly, the uniform and continuous electrons excite
light emission, due to the surrounding filed emitters from
Pt-NPs/QBSNs, can be easily obtained. This approach does not require
an expensive photolithographic process and possesses great potential
for applications.
Abstract: Research into the problem of classification of sonar signals has been taken up as a challenging task for the neural networks. This paper investigates the design of an optimal classifier using a Multi layer Perceptron Neural Network (MLP NN) and Support Vector Machines (SVM). Results obtained using sonar data sets suggest that SVM classifier perform well in comparison with well-known MLP NN classifier. An average classification accuracy of 91.974% is achieved with SVM classifier and 90.3609% with MLP NN classifier, on the test instances. The area under the Receiver Operating Characteristics (ROC) curve for the proposed SVM classifier on test data set is found as 0.981183, which is very close to unity and this clearly confirms the excellent quality of the proposed classifier. The SVM classifier employed in this paper is implemented using kernel Adatron algorithm is seen to be robust and relatively insensitive to the parameter initialization in comparison to MLP NN.
Abstract: Reliable information about tool temperature
distribution is of central importance in metal cutting. In this study,
tool-chip interface temperature was determined in cutting of ST37
steel workpiece by applying HSS as the cutting tool in dry turning.
Two different approaches were implemented for temperature
measuring: an embedded thermocouple (RTD) in to the cutting tool
and infrared (IR) camera. Comparisons are made between
experimental data and results of MSC.SuperForm and FLUENT
software.
An investigation of heat generation in cutting tool was performed
by varying cutting parameters at the stable cutting tool geometry and
results were saved in a computer; then the diagrams of tool
temperature vs. various cutting parameters were obtained. The
experimental results reveal that the main factors of the increasing
cutting temperature are cutting speed (V ), feed rate ( S ) and depth
of cut ( h ), respectively. It was also determined that simultaneously
change in cutting speed and feed rate has the maximum effect on
increasing cutting temperature.
Abstract: This paper presents a novel approach to finding a
priori interesting regions in mammograms. In order to delineate those
regions of interest (ROI-s) in mammograms, which appear to be
prominent, a topographic representation called the iso-level contour
map consisting of iso-level contours at multiple intensity levels and
region segmentation based-thresholding have been proposed. The
simulation results indicate that the computed boundary gives the
detection rate of 99.5% accuracy.
Abstract: The experimental study of position control of a light
weight and small size robotic finger during non-contact motion is
presented in this paper. The finger possesses fingertip pinching and
self adaptive grasping capabilities, and is made of a seven bar linkage
mechanism with a slider in the middle phalanx. The control system is
tested under the Proportional Integral Derivative (PID) control
algorithm and Recursive Least Square (RLS) based Feedback Error
Learning (FEL) control scheme to overcome the uncertainties present
in the plant. The experiments conducted in Matlab Simulink and xPC
Target environments show that the overall control strategy is efficient
in controlling the finger movement.
Abstract: Nowadays, several techniques such as; Fuzzy
Inference System (FIS) and Neural Network (NN) are employed for
developing of the predictive models to estimate parameters of water
quality. The main objective of this study is to compare between the
predictive ability of the Adaptive Neuro-Fuzzy Inference System
(ANFIS) model and Artificial Neural Network (ANN) model to
estimate the Biochemical Oxygen Demand (BOD) on data from 11
sampling sites of Saen Saep canal in Bangkok, Thailand. The data is
obtained from the Department of Drainage and Sewerage, Bangkok
Metropolitan Administration, during 2004-2011. The five parameters
of water quality namely Dissolved Oxygen (DO), Chemical Oxygen
Demand (COD), Ammonia Nitrogen (NH3N), Nitrate Nitrogen
(NO3N), and Total Coliform bacteria (T-coliform) are used as the
input of the models. These water quality indices affect the
biochemical oxygen demand. The experimental results indicate that
the ANN model provides a higher correlation coefficient (R=0.73)
and a lower root mean square error (RMSE=4.53) than the
corresponding ANFIS model.
Abstract: The changes in quality properties and nutritional
components in two fermented mugworts (Artemisia capillaries
Thumberg, Artemisiaeasiaticae Nakai) were characterized followed
by the rapid pattern analysis of volatile flavor compounds by Electric
Nose based on SAW(Surface Acoustic Wave) sensor in GC system.
There were remarkable decreases in the pH and small changes in the
total soluble solids after fermentation. The L (lightness) and b
(yellowness) values in Hunter's color system were shown to be
decreased, whilst the a (redness) value was increased by fermentation.
The HPLC analysis demonstrated that total amino acids were
increased in quantity and the essential amino acids were contained
higher in A. asiaticaeNakai than in A. capillaries Thumberg. While
the total polyphenol contents were not affected by fermentation, the
total sugar contents were dramatically decreased. Scopoletinwere
highly abundant in A. capillarisThumberg, however, it was not
detected in A. asiaticaeNakai. Volatile flavor compounds by Electric
Nose showed that the intensity of several peaks were increased much
and seven additional flavor peaks were newly produced after
fermentation. The flavor differences of two mugworts were clearly
distinguished from the image patterns of VaporPrintTM which indicate
that the fermentation enables the two mugworts to have subtle flavor
differences.
Abstract: The paper is concerned with developing stochastic delay mechanisms for efficient multicast protocols and for smooth mobile handover processes which are capable of preserving a given Quality of Service (QoS). In both applications the participating entities (receiver nodes or subscribers) sample a stochastic timer and generate load after a random delay. In this way, the load on the networking resources is evenly distributed which helps to maintain QoS communication. The optimal timer distributions have been sought in different p.d.f. families (e.g. exponential, power law and radial basis function) and the optimal parameter have been found in a recursive manner. Detailed simulations have demonstrated the improvement in performance both in the case of multicast and mobile handover applications.
Abstract: The main goal of the present work is to decrease the
computational burden for optimum design of steel frames with
frequency constraints using a new type of neural networks called
Wavelet Neural Network. It is contested to train a suitable neural
network for frequency approximation work as the analysis program.
The combination of wavelet theory and Neural Networks (NN)
has lead to the development of wavelet neural networks.
Wavelet neural networks are feed-forward networks using
wavelet as activation function. Wavelets are mathematical
functions within suitable inner parameters, which help them to
approximate arbitrary functions. WNN was used to predict the
frequency of the structures. In WNN a RAtional function with
Second order Poles (RASP) wavelet was used as a transfer
function. It is shown that the convergence speed was faster
than other neural networks. Also comparisons of WNN with
the embedded Artificial Neural Network (ANN) and with
approximate techniques and also with analytical solutions are
available in the literature.
Abstract: The response surface methodology (RSM) is a
collection of mathematical and statistical techniques useful in the
modeling and analysis of problems in which the dependent variable
receives the influence of several independent variables, in order to
determine which are the conditions under which should operate these
variables to optimize a production process. The RSM estimated a
regression model of first order, and sets the search direction using the
method of maximum / minimum slope up / down MMS U/D.
However, this method selects the step size intuitively, which can
affect the efficiency of the RSM. This paper assesses how the step
size affects the efficiency of this methodology. The numerical
examples are carried out through Monte Carlo experiments,
evaluating three response variables: efficiency gain function, the
optimum distance and the number of iterations. The results in the
simulation experiments showed that in response variables efficiency
and gain function at the optimum distance were not affected by the
step size, while the number of iterations is found that the efficiency if
it is affected by the size of the step and function type of test used.
Abstract: In first stage of each microwave receiver there is Low
Noise Amplifier (LNA) circuit, and this stage has important rule in
quality factor of the receiver. The design of a LNA in Radio
Frequency (RF) circuit requires the trade-off many importance
characteristics such as gain, Noise Figure (NF), stability, power
consumption and complexity. This situation Forces desingners to
make choices in the desing of RF circuits. In this paper the aim is to
design and simulate a single stage LNA circuit with high gain and
low noise using MESFET for frequency range of 5 GHz to 6 GHz.
The desing simulation process is down using Advance Design
System (ADS). A single stage LNA has successfully designed with
15.83 dB forward gain and 1.26 dB noise figure in frequency of 5.3
GHz. Also the designed LNA should be working stably In a
frequency range of 5 GHz to 6 GHz.
Abstract: The Non-Rotating Adjustable Stabilizer / Directional
Solution (NAS/DS) is the imitation of a mechanical process or an
object by a directional drilling operation that causes a respond
mathematically and graphically to data and decision to choose the
best conditions compared to the previous mode.
The NAS/DS Auto Guide rotary steerable tool is undergoing final
field trials. The point-the-bit tool can use any bit, work at any
rotating speed, work with any MWD/LWD system, and there is no
pressure drop through the tool. It is a fully closed-loop system that
automatically maintains a specified curvature rate.
The Non–Rotating Adjustable stabilizer (NAS) can be controls
curvature rate by exactly positioning and run with the optimum bit,
use the most effective weight (WOB) and rotary speed (RPM) and
apply all of the available hydraulic energy to the bit. The directional
simulator allowed to specify the size of the curvature rate
performance errors of the NAS tool and the magnitude of the random
errors in the survey measurements called the Directional Solution
(DS).
The combination of these technologies (NAS/DS) will provide
smoother bore holes, reduced drilling time, reduced drilling cost and
incredible targeting precision. This simulator controls curvature rate
by precisely adjusting the radial extension of stabilizer blades on a
near bit Non-Rotating Stabilizer and control process corrects for the
secondary effects caused by formation characteristics, bit and tool
wear, and manufacturing tolerances.
Abstract: In this paper we present a soft timing phase estimation (STPE) method for wireless mobile receivers operating in low signal to noise ratios (SNRs). Discrete Polyphase Matched (DPM) filters, a Log-maximum a posterior probability (MAP) and/or a Soft-output Viterbi algorithm (SOVA) are combined to derive a new timing recovery (TR) scheme. We apply this scheme to wireless cellular communication system model that comprises of a raised cosine filter (RCF), a bit-interleaved turbo-coded multi-level modulation (BITMM) scheme and the channel is assumed to be memory-less. Furthermore, no clock signals are transmitted to the receiver contrary to the classical data aided (DA) models. This new model ensures that both the bandwidth and power of the communication system is conserved. However, the computational complexity of ideal turbo synchronization is increased by 50%. Several simulation tests on bit error rate (BER) and block error rate (BLER) versus low SNR reveal that the proposed iterative soft timing recovery (ISTR) scheme outperforms the conventional schemes.
Abstract: A heuristic conceptual model for to develop the
Reliability Centered Maintenance (RCM), especially in preventive
strategy, has been explored during this paper. In most real cases
which complicity of system obligates high degree of reliability, this
model proposes a more appropriate reliability function between life
time distribution based and another which is based on relevant
Extreme Value (EV) distribution. A statistical and mathematical
approach is used to estimate and verify these two distribution
functions. Then best one is chosen just among them, whichever is
more reliable. A numeric Industrial case study will be reviewed to
represent the concepts of this paper, more clearly.
Abstract: The advances in wireless communication have opened unlimited horizons but there are some challenges as well. The Nature derived air medium between MS (Mobile Station) and BS (Base Station) is beyond human control and produces channel impairment. The impact of the natural conditions at the air medium is the biggest issue in wireless communication. Natural conditions make reliability more cumbersome; here reliability refers to the efficient recovery of the lost or erroneous data. The SR-ARQ (Selective Repeat-Automatic Repeat Request) protocol is a de facto standard for any wireless technology at the air interface with its standard reliability features. Our focus in this research is on the reliability of the control or feedback signal of the SR-ARQ protocol. The proposed mechanism, RSR-ARQ (Reliable SR-ARQ) is an enhancement of the SR-ARQ protocol that has ensured the reliability of the control signals through channel impairment sensitive mechanism. We have modeled the system under two-state discrete time Markov Channel. The simulation results demonstrate the better recovery of the lost or erroneous data that will increase the overall system performance.
Abstract: A general purpose viscous flow solver Ansys CFX
was used to solve the unsteady three-dimensional (3D) Reynolds
Averaged Navier-Stokes Equation (RANSE) for simulating a 3D
numerical viscous wave tank. A flap-type wave generator was
incorporated in the computational domain to generate the desired
incident waves. Authors have made effort to study the physical
behaviors of Flap type wave maker with governing parameters.
Dependency of the water fill depth, Time period of oscillations and
amplitude of oscillations of flap were studied. Effort has been made
to establish relations between parameters. A validation study was
also carried out against CFD methodology with wave maker theory.
It has been observed that CFD results are in good agreement with
theoretical results. Beaches of different slopes were introduced to
damp the wave, so that it should not cause any reflection from
boundary. As a conclusion this methodology can simulate the
experimental wave-maker for regular wave generation for different
wave length and amplitudes.
Abstract: Drying characteristics of rough rice (variety of lenjan) with an initial moisture content of 25% dry basis (db) was studied in a hot air dryer assisted by infrared heating. Three arrival air temperatures (30, 40 and 500C) and four infrared radiation intensities (0, 0.2 , 0.4 and 0.6 W/cm2) and three arrival air speeds (0.1, 0.15 and 0.2 m.s-1) were studied. Bending strength of brown rice kernel, percentage of cracked kernels and time of drying were measured and evaluated. The results showed that increasing the drying arrival air temperature and radiation intensity of infrared resulted decrease in drying time. High bending strength and low percentage of cracked kernel was obtained when paddy was dried by hot air assisted infrared dryer. Between this factors and their interactive effect were a significant difference (p