Abstract: A New features are extracted and compared to
improve the prediction of protein-protein interactions. The basic idea
is to select and use the best set of features from the Tensor matrices
that are produced by the frequency vectors of the protein sequences.
Three set of features are compared, the first set is based on the
indices that are the most common in the interacting proteins, the
second set is based on the indices that tend to be common in the
interacting and non-interacting proteins, and the third set is
constructed by using random indices. Moreover, three encoding
strategies are compared; that are based on the amino asides polarity,
structure, and chemical properties. The experimental results indicate
that the highest accuracy can be obtained by using random indices
with chemical properties encoding strategy and support vector
machine.
Abstract: Forty-five dairy cows were used to compare the
enzyme activity of alkaline phosphatase (ALP), lactate
dehydrogenase (LDH), α -amylase in the cervical mucus of cows
during spontaneous and induced estrus using progestagen or PGF2 α
and to determine whether these enzymes affect the fertility in cows
with induced estrus, at the time of Al. The animals were assigned to 3
groups (no treatment, a Crestar® for 12 days, a double im injection of
PGF2 α). The cows were artificially inseminated (AI). Cervical
mucus samples were collected from all cows 3 to 5 min before the
AI. The results are summarized as follows: ALP and α -amylase
activity for spontaneous estrus were similar to those for induced
estrus (P>0.05) . LDH activity levels during spontaneous and PGF2 α
induced estrus was significantly lower (P < 0.001) than that in
progestagene induced estrus groups. While no difference was found
between the first and the third groups. Our result showed a significant
difference in LDH activity levels between cows conceived with 2 or
more AI and those conceived with 1 AI. The result of this study
showed that the enzyme activity in cervical mucus is helpful for
detection of ovulation and time of AI.
Abstract: This paper investigates the performance of a speech
recognizer in an interactive voice response system for various coded
speech signals, coded by using a vector quantization technique namely
Multi Switched Split Vector Quantization Technique. The process of
recognizing the coded output can be used in Voice banking application.
The recognition technique used for the recognition of the coded speech
signals is the Hidden Markov Model technique. The spectral distortion
performance, computational complexity, and memory requirements of
Multi Switched Split Vector Quantization Technique and the
performance of the speech recognizer at various bit rates have been
computed. From results it is found that the speech recognizer is
showing better performance at 24 bits/frame and it is found that the
percentage of recognition is being varied from 100% to 93.33% for
various bit rates.
Abstract: Let p be a prime number, Fpbe a finite field and let Qpdenote the set of quadratic residues in Fp. In the first section we givesome notations and preliminaries from elliptic curves. In the secondsection, we consider some properties of rational points on ellipticcurves Ep,b: y2= x3+ b2 over Fp, where b ∈ F*p. Recall that theorder of Ep,bover Fpis p + 1 if p ≡ 5(mod 6). We generalize thisresult to any field Fnp for an integer n≥ 2. Further we obtain someresults concerning the sum Σ[x]Ep,b(Fp) and Σ[y]Ep,b(Fp), thesum of x- and y- coordinates of all points (x, y) on Ep,b, and alsothe the sum Σ(x,0)Ep,b(Fp), the sum of points (x, 0) on Ep,b.
Abstract: This report shows the performance of composite
biodegradable film from chitosan, starch and sawdust fiber. The main
objectives of this research are to fabricate and characterize composite
biodegradable film in terms of morphology and physical properties.
The film was prepared by casting method. Sawdust fiber was used as
reinforcing agent and starch as polymer matrix in the casting
solution. The morphology of the film was characterized using atomic
force microscope (AFM). The result showed that the film has
smooth structure. Chemical composition of the film was investigated
using Fourier transform infrared (FTIR) where the result revealed
present of starch in the film. The thermal properties were
characterized using thermal gravimetric analyzer (TGA) and
differential scanning calorimetric (DSC) where the results showed
that the film has small difference in melting and degradation
temperature.
Abstract: In the meantime, there were lots of hardware solutions like products or urban facilities for crime prevention in the public design area. Meanwhile, people have growing interest in public design so by making a village; community design in public design is getting active by the society. The system for crime prevention is actively done by the citizens who created the community. Regarding the social situation, in this project, we saw it as a kind of community design practices and researched about 'how does community design influence Crime prevention?' The purpose of this study is to propose the community design as a way of preventing the crime in the city. First, we found out about the definition, elements and methods of community design by reviewing the theory. And then, this study analyzed the case that was enforced in Seoul and organize the elements and methods of community design. This study can be refer to Public Design based on civil participation and make the community design area contribute to expand the way of solving social problems.
Abstract: Data mining (DM) is the process of finding and extracting frequent patterns that can describe the data, or predict unknown or future values. These goals are achieved by using various learning algorithms. Each algorithm may produce a mining result completely different from the others. Some algorithms may find millions of patterns. It is thus the difficult job for data analysts to select appropriate models and interpret the discovered knowledge. In this paper, we describe a framework of an intelligent and complete data mining system called SUT-Miner. Our system is comprised of a full complement of major DM algorithms, pre-DM and post-DM functionalities. It is the post-DM packages that ease the DM deployment for business intelligence applications.
Abstract: Biomass is becoming a large renewable resource for
power generation; it is involved in higher frequency in
environmentally clean processes, and even it is used for biofuels
preparation. On the other hand, hydrogen – other energy source – can
be produced in a variety of methods including gasification of
biomass. In this study, the production of hydrogen by gasification of
biomass waste is examined. This work explores the production of a
gaseous mixture with high power potential from Amazonas´ specie
known as copoazu, using a counter-flow fixed-bed bioreactor.
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: In this paper, we observe that developed countries are generally equipped with innovation capabilities and produce major chunk of the world-s knowledge and technology. The contribution of developing countries, on the other hand, is insignificant, and most of them far behind the global technological front. More specifically, we empirically observe that the developing world neither contributes substantially to the world-s scientific publications nor to the R&D activities. They also have lesser “absorptive capacity" and “technological capability", and their “innovation systems" are plagued with many problems. Finally, we argue that these countries can break the shackles and improve their innovation capabilities by pursuing genuine innovation policies on long-term basis with honesty and commitment.
Abstract: Understanding proteins functions is a major goal in
the post-genomic era. Proteins usually work in context of other
proteins and rarely function alone. Therefore, it is highly relevant to
study the interaction partners of a protein in order to understand its
function. Machine learning techniques have been widely applied to
predict protein-protein interactions. Kernel functions play an
important role for a successful machine learning technique. Choosing
the appropriate kernel function can lead to a better accuracy in a
binary classifier such as the support vector machines. In this paper,
we describe a Bayesian kernel for the support vector machine to
predict protein-protein interactions. The use of Bayesian kernel can
improve the classifier performance by incorporating the probability
characteristic of the available experimental protein-protein
interactions data that were compiled from different sources. In
addition, the probabilistic output from the Bayesian kernel can assist
biologists to conduct more research on the highly predicted
interactions. The results show that the accuracy of the classifier has
been improved using the Bayesian kernel compared to the standard
SVM kernels. These results imply that protein-protein interaction can
be predicted using Bayesian kernel with better accuracy compared to
the standard SVM kernels.
Abstract: State-based testing is frequently used in software testing. Test data generation is one of the key issues in software testing. A properly generated test suite may not only locate the errors in a software system, but also help in reducing the high cost associated with software testing. It is often desired that test data in the form of test sequences within a test suite can be automatically generated to achieve required test coverage. This paper proposes an Ant Colony Optimization approach to test data generation for the state-based software testing.
Abstract: Regulatory relationships of 686 intronic miRNA and 784 intergenic miRNAs with mRNAs of 51 intronic miRNA coding genes were established. Interaction features of studied miRNAs with 5'UTR, CDS and 3'UTR of mRNA of each gene were revealed. Functional regions of mRNA were shown to be significantly heterogenous according to the number of binding sites of miRNA and to the location density of these sites.
Abstract: Graphene-metal contact resistance limits the performance of graphene-based electrical devices. In this work, we have fabricated both graphene field-effect transistors (GFET) and transfer length measurement (TLM) test devices with titanium contacts. The purpose of this work is to compare the contact resistances that can be numerically extracted from the GFETs and measured from the TLM structures. We also provide a brief review of the work done in the field to solve the contact resistance problem.
Abstract: Using a texture database, a statistical estimation of
spring-back was conducted in this study on the basis of statistical
analysis. Both spring-back in bending deformation and experimental
data related to the crystal orientation show significant dispersion.
Therefore, a probabilistic statistical approach was established for the
proper quantification of these values. Correlation was examined
among the parameters F(x) of spring-back, F(x) of the buildup fraction
to three orientations after 92° bending, and F(x) at an as-received part
on the basis of the three-parameter Weibull distribution. Consequent
spring-back estimation using a texture database yielded excellent
estimates compared with experimental values.
Abstract: Wheeled Mobile Robots (WMRs) are built with their
Wheels- drive machine, Motors. Depend on their desire design of
WMR, Technicians made used of DC Motors for motion control. In
this paper, the author would like to analyze how to choose DC motor
to be balance with their applications of especially for WMR.
Specification of DC Motor that can be used with desire WMR is to
be determined by using MATLAB Simulink model. Therefore, this
paper is mainly focus on software application of MATLAB and
Control Technology. As the driving system of DC motor, a
Peripheral Interface Controller (PIC) based control system is
designed including the assembly software technology and H-bridge
control circuit. This Driving system is used to drive two DC gear
motors which are used to control the motion of WMR. In this
analyzing process, the author mainly focus the drive system on
driving two DC gear motors that will control with Differential Drive
technique to the Wheeled Mobile Robot . For the design analysis of
Motor Driving System, PIC16F84A is used and five inputs of sensors
detected data are tested with five ON/OFF switches. The outputs of
PIC are the commands to drive two DC gear motors, inputs of Hbridge
circuit .In this paper, Control techniques of PIC
microcontroller and H-bridge circuit, Mechanism assignments of
WMR are combined and analyzed by mainly focusing with the
“Modeling and Simulink of DC Motor using MATLAB".
Abstract: System identification is the process of creating
models of dynamic process from input- output signals. The aim of
system identification can be identified as “ to find a model with
adjustable parameters and then to adjust them so that the predicted
output matches the measured output". This paper presents a method
of modeling and simulating with system identification to achieve the
maximum fitness for transformation function. First by using
optimized KLM equivalent circuit for PVDF piezoelectric transducer
and assuming different inputs including: sinuside, step and sum of
sinusides, get the outputs, then by using system identification
toolbox in MATLAB, we estimate the transformation function from
inputs and outputs resulted in last program. Then compare the fitness
of transformation function resulted from using ARX,OE(Output-
Error) and BJ(Box-Jenkins) models in system identification toolbox
and primary transformation function form KLM equivalent circuit.
Abstract: The paper shows that in the analysis of a queuing system with fixed-size batch arrivals, there emerges a set of polynomials which are a generalization of Chebyshev polynomials of the second kind. The paper uses these polynomials in assessing the transient behaviour of the overflow (equivalently call blocking) probability in the system. A key figure to note is the proportion of the overflow (or blocking) probability resident in the transient component, which is shown in the results to be more significant at the beginning of the transient and naturally decays to zero in the limit of large t. The results also show that the significance of transients is more pronounced in cases of lighter loads, but lasts longer for heavier loads.
Abstract: One of the most common practices for strengthening
the reinforced concrete structures is the application of FRP (Fiber
Reinforce Plastic) sheets to increase the flexural and shear strengths
of the member. The elastic modulus of FRP is considerably higher
than that of concrete. This will result in debonding between the FRP
sheets and concrete surface. With conventional surface preparation of
concrete, the ultimate capacity of the FRP sheets can hardly be
achieved. New methods for preparation of the bonding surface have
shown improvements in reducing the premature debonding of FRP
sheets from concrete surface. The present experimental study focuses
on the application of grooving method to postpone debonding of the
FRP sheets attached to the side faces of concrete beams for shear
strengthening. Comparison has also been made with conventional
surface preparation method. This study clearly shows the efficiency
of grooving method compared to surface preparation method, in
preventing the debonding phenomenon and in increasing the load
carrying capacity of FRP.
Abstract: In recent years, the research in wireless sensor
network has increased steadily, and many studies were focusing on
reducing energy consumption of sensor nodes to extend their lifetimes.
In this paper, the issue of energy consumption is investigated and two
adaptive mechanisms are proposed to extend the network lifetime.
This study uses high-energy-first scheme to determine cluster heads
for data transmission. Thus, energy consumption in each cluster is
balanced and network lifetime can be extended. In addition, this study
uses cluster merging and dynamic routing mechanisms to further
reduce energy consumption during data transmission. The simulation
results show that the proposed method can effectively extend the
lifetime of wireless sensor network, and it is suitable for different base
station locations.