Abstract: Search for a tertiary substructure that geometrically
matches the 3D pattern of the binding site of a well-studied protein provides a solution to predict protein functions. In our previous work,
a web server has been built to predict protein-ligand binding sites
based on automatically extracted templates. However, a drawback of such templates is that the web server was prone to resulting in many
false positive matches. In this study, we present a sequence-order constraint to reduce the false positive matches of using automatically
extracted templates to predict protein-ligand binding sites. The binding site predictor comprises i) an automatically constructed template library and ii) a local structure alignment algorithm for
querying the library. The sequence-order constraint is employed to
identify the inconsistency between the local regions of the query protein and the templates. Experimental results reveal that the sequence-order constraint can largely reduce the false positive matches and is effective for template-based binding site prediction.
Abstract: Hexapod Machine Tool (HMT) is a parallel robot
mostly based on Stewart platform. Identification of kinematic
parameters of HMT is an important step of calibration procedure. In
this paper an algorithm is presented for identifying the kinematic
parameters of HMT using inverse kinematics error model. Based on
this algorithm, the calibration procedure is simulated. Measurement
configurations with maximum observability are decided as the first
step of this algorithm for a robust calibration. The errors occurring in
various configurations are illustrated graphically. It has been shown
that the boundaries of the workspace should be searched for the
maximum observability of errors. The importance of using
configurations with sufficient observability in calibrating hexapod
machine tools is verified by trial calibration with two different
groups of randomly selected configurations. One group is selected to
have sufficient observability and the other is in disregard of the
observability criterion. Simulation results confirm the validity of the
proposed identification algorithm.
Abstract: Sensory nerves in the foot play an important part in the diagnosis of various neuropathydisorders, especially in diabetes mellitus.However, a detailed description of the anatomical distribution of the nerves is currently lacking. A computationalmodel of the afferent nerves inthe foot may bea useful tool for the study of diabetic neuropathy. In this study, we present the development of an anatomically-based model of various major sensory nerves of the sole and dorsal sidesof the foot. In addition, we presentan algorithm for generating synthetic somatosensory nerve networks in the big-toe region of a right foot model. The algorithm was based on a modified version of the Monte Carlo algorithm, with the capability of being able to vary the intra-epidermal nerve fiber density in differentregionsof the foot model. Preliminary results from the combinedmodel show the realistic anatomical structure of the major nerves as well as the smaller somatosensory nerves of the foot. The model may now be developed to investigate the functional outcomes of structural neuropathyindiabetic patients.
Abstract: Wireless sensor networks (WSN) consists of many sensor nodes that are placed on unattended environments such as military sites in order to collect important information. Implementing a secure protocol that can prevent forwarding forged data and modifying content of aggregated data and has low delay and overhead of communication, computing and storage is very important. This paper presents a new protocol for concealed data aggregation (CDA). In this protocol, the network is divided to virtual cells, nodes within each cell produce a shared key to send and receive of concealed data with each other. Considering to data aggregation in each cell is locally and implementing a secure authentication mechanism, data aggregation delay is very low and producing false data in the network by malicious nodes is not possible. To evaluate the performance of our proposed protocol, we have presented computational models that show the performance and low overhead in our protocol.
Abstract: Conception is the primordial part in the realization of
a computer system. Several tools have been used to help inventors to
describe their software. These tools knew a big success in the
relational databases domain since they permit to generate SQL script
modeling the database from an Entity/Association model. However,
with the evolution of the computer domain, the relational databases
proved their limits and object-relational model became used more
and more. Tools of present conception don't support all new concepts
introduced by this model and the syntax of the SQL3 language. We
propose in this paper a tool of help to the conception and
implementation of object-relational databases called «NAVIGTOOLS"
that allows the user to generate script modeling its database
in SQL3 language. This tool bases itself on the Entity/Association
and navigational model for modeling the object-relational databases.
Abstract: In many data mining applications, it is a priori known
that the target function should satisfy certain constraints imposed
by, for example, economic theory or a human-decision maker. In this
paper we consider partially monotone prediction problems, where the
target variable depends monotonically on some of the input variables
but not on all. We propose a novel method to construct prediction
models, where monotone dependences with respect to some of
the input variables are preserved by virtue of construction. Our
method belongs to the class of mixture models. The basic idea is to
convolute monotone neural networks with weight (kernel) functions
to make predictions. By using simulation and real case studies,
we demonstrate the application of our method. To obtain sound
assessment for the performance of our approach, we use standard
neural networks with weight decay and partially monotone linear
models as benchmark methods for comparison. The results show that
our approach outperforms partially monotone linear models in terms
of accuracy. Furthermore, the incorporation of partial monotonicity
constraints not only leads to models that are in accordance with the
decision maker's expertise, but also reduces considerably the model
variance in comparison to standard neural networks with weight
decay.
Abstract: Image processing for capsule endoscopy requires large
memory and it takes hours for diagnosis since operation time is
normally more than 8 hours. A real-time analysis algorithm of capsule
images can be clinically very useful. It can differentiate abnormal
tissue from health structure and provide with correlation information
among the images. Bleeding is our interest in this regard and we
propose a method of detecting frames with potential bleeding in
real-time. Our detection algorithm is based on statistical analysis and
the shapes of bleeding spots. We tested our algorithm with 30 cases of
capsule endoscopy in the digestive track. Results were excellent where
a sensitivity of 99% and a specificity of 97% were achieved in
detecting the image frames with bleeding spots.
Abstract: Imperfect knowledge cannot be avoided all the time. Imperfections may have several forms; uncertainties, imprecision and incompleteness. When we look to classification of methods for the management of imperfect knowledge we see fuzzy set-based techniques. The choice of a method to process data is linked to the choice of knowledge representation, which can be numerical, symbolic, logical or semantic and it depends on the nature of the problem to be solved for example decision support, which will be mentioned in our study. Fuzzy Logic is used for its ability to manage imprecise knowledge, but it can take advantage of the ability of neural networks to learn coefficients or functions. Such an association of methods is typical of so-called soft computing. In this study a new method was used for the management of imprecision for collected knowledge which related to economic analysis of construction industry in Turkey. Because of sudden changes occurring in economic factors decrease competition strength of construction companies. The better evaluation of these changes in economical factors in view of construction industry will made positive influence on company-s decisions which are dealing construction.
Abstract: This paper describes a study of geometrically
nonlinear free vibration of thin circular functionally graded (CFGP)
plates resting on Winkler elastic foundations. The material properties
of the functionally graded composites examined here are assumed to
be graded smoothly and continuously through the direction of the
plate thickness according to a power law and are estimated using the
rule of mixture. The theoretical model is based on the classical Plate
theory and the Von-Kármán geometrical nonlinearity assumptions.
An homogenization procedure (HP) is developed to reduce the
problem considered here to that of isotropic homogeneous circular
plates resting on Winkler foundation. Hamilton-s principle is applied
and a multimode approach is derived to calculate the fundamental
nonlinear frequency parameters which are found to be in a good
agreement with the published results. On the other hand, the
influence of the foundation parameters on the nonlinear fundamental
frequency has also been analysed.
Abstract: This paper presents the concept and realisation of an
e-learning tool that provides predefined or automatically generated
exercises concerning logistics cost accounting. Students may practise
where and whenever they like to via the Internet. Their solutions are
marked automatically by the tool while considering consecutive
faults and without any intervention of lecturers.
Abstract: Earlier studies in kinship networks have primarily
focused on observing the social relationships existing between family
relatives. In this study, we pre-identified hubs in the network to
investigate if they could play a catalyst role in the transfer of physical
information. We conducted a case study of a ceremony performed in
one of the families of a small Hindu community – the Uttar Rarhi
Kayasthas. Individuals (n = 168) who resided in 11 geographically
dispersed regions were contacted through our hub-based
representation. We found that using this representation, over 98% of
the individuals were successfully contacted within the stipulated
period. The network also demonstrated a small-world property, with
an average geodesic distance of 3.56.
Abstract: A two dimensional three segments coupled pendulum system that mathematically models human arm configuration was developed along with constructing and solving the equations of motions for this model using the energy (work) based approach of Lagrange. The equations of motion of the model were solved iteratively both as an initial value problem and as a two point boundary value problem. In the initial value problem solutions, both the initial system configuration (segment angles) and initial system velocity (segment angular velocities) were used as inputs, whereas, in the two point boundary value problem solutions initial and final configurations and time were used as inputs to solve for the trajectory of motion. The results suggest that the model solutions are sensitive to small changes in the dynamic forces applied to the system as well as to the initial and boundary conditions used. To overcome the system sensitivity a new approach is suggested.
Abstract: As is known, one of the priority directions of research
works of natural sciences is introduction of applied section of
contemporary mathematics as approximate and numerical methods to
solving integral equation into practice. We fare with the solving of
integral equation while studying many phenomena of nature to whose
numerically solving by the methods of quadrature are mainly applied.
Taking into account some deficiency of methods of quadrature for
finding the solution of integral equation some sciences suggested of
the multistep methods with constant coefficients. Unlike these papers,
here we consider application of hybrid methods to the numerical
solution of Volterra integral equation. The efficiency of the suggested
method is proved and a concrete method with accuracy order p = 4
is constructed. This method in more precise than the corresponding
known methods.
Abstract: In this paper, delay-dependent stability analysis for
neutral type neural networks with uncertain paramters and
time-varying delay is studied. By constructing new
Lyapunov-Krasovskii functional and dividing the delay interval into
multiple segments, a novel sufficient condition is established to
guarantee the globally asymptotically stability of the considered
system. Finally, a numerical example is provided to illustrate the
usefulness of the proposed main results.
Abstract: In switch mode power inverters, small sized inverters
can be obtained by increasing the switching frequency. Switching
frequency increment causes high driver losses. Also, high dt
di
and
dt
dv
produced by the switching action creates high Electromagnetic
Interference (EMI) and Radio Frequency Interference (RFI). In this
paper, a series half bridge series resonant inverter circuit is simulated
and evaluated practically to demonstrate the turn-on and turn-off
conditions during zero or close to zero voltage switching. Also, the
reverse recovery current effects of the body diode of the MOSFETs
were investigated by operating above and below resonant frequency.
Abstract: Social networking is one of the most successful and popular tools to emerge from the Web 2.0 era. However, the increased interconnectivity and access to peoples- personal lives and information has created a plethora of opportunities for the nefarious side of human nature to manifest. This paper categorizes and describes the major types of anti-social behavior and criminal activity that can arise through undisciplined use and/or misuse of social media. We specifically address identity theft, misrepresentation of information posted, cyber bullying, children and social networking, and social networking in the work place. Recommendations are provided for how to reduce the risk of being the victim of a crime or engaging in embarrassing behavior that could irrevocably harm one-s reputation either professionally or personally. We also discuss what responsibilities social networking companies have to protect their users and also what law enforcement and policy makers can do to help alleviate the problems.
Abstract: Longitudinal data typically have the characteristics of
changes over time, nonlinear growth patterns, between-subjects
variability, and the within errors exhibiting heteroscedasticity and
dependence. The data exploration is more complicated than that of
cross-sectional data. The purpose of this paper is to organize/integrate
of various visual-graphical techniques to explore longitudinal data.
From the application of the proposed methods, investigators can
answer the research questions include characterizing or describing the
growth patterns at both group and individual level, identifying the time
points where important changes occur and unusual subjects, selecting
suitable statistical models, and suggesting possible within-error
variance.
Abstract: Bus networks design is an important problem in
public transportation. The main step to this design, is determining the
number of required terminals and their locations. This is an especial
type of facility location problem, a large scale combinatorial
optimization problem that requires a long time to be solved.
The genetic algorithm (GA) is a search and optimization technique
which works based on evolutionary principle of natural
chromosomes. Specifically, the evolution of chromosomes due to the
action of crossover, mutation and natural selection of chromosomes
based on Darwin's survival-of-the-fittest principle, are all artificially
simulated to constitute a robust search and optimization procedure.
In this paper, we first state the problem as a mixed integer
programming (MIP) problem. Then we design a new crossover and
mutation for bus terminal location problem (BTLP). We tested the
different parameters of genetic algorithm (for a sample problem) and
obtained the optimal parameters for solving BTLP with numerical try
and error.
Abstract: One of the key research issues in wireless sensor networks (WSNs) is how to efficiently deploy sensors to cover an area. In this paper, we present a Fishnet Based Dispatch Scheme (FiBDS) with energy aware mobility and interest based sensing angle. We propose two algorithms, one is FiBDS centralized algorithm and another is FiBDS distributed algorithm. The centralized algorithm is designed specifically for the non-time critical applications, commonly known as non real-time applications while the distributed algorithm is designed specifically for the time critical applications, commonly known as real-time applications. The proposed dispatch scheme works in a phase-selection manner. In this in each phase a specific constraint is dealt with according to the specified priority and then moved onto the next phase and at the end of each only the best suited nodes for the phase are chosen. Simulation results are presented to verify their effectiveness.
Abstract: In this paper, an extended study is performed on the
effect of different factors on the quality of vector data based on a
previous study. In the noise factor, one kind of noise that appears in
document images namely Gaussian noise is studied while the previous
study involved only salt-and-pepper noise. High and low levels of
noise are studied. For the noise cleaning methods, algorithms that were
not covered in the previous study are used namely Median filters and
its variants. For the vectorization factor, one of the best available
commercial raster to vector software namely VPstudio is used to
convert raster images into vector format. The performance of line
detection will be judged based on objective performance evaluation
method. The output of the performance evaluation is then analyzed
statistically to highlight the factors that affect vector quality.