Abstract: This paper focuses on a technique for identifying the geological boundary of the ground strata in front of a tunnel excavation site using the first order adjoint method based on the optimal control theory. The geological boundary is defined as the boundary which is different layers of elastic modulus. At tunnel excavations, it is important to presume the ground situation ahead of the cutting face beforehand. Excavating into weak strata or fault fracture zones may cause extension of the construction work and human suffering. A theory for determining the geological boundary of the ground in a numerical manner is investigated, employing excavating blasts and its vibration waves as the observation references. According to the optimal control theory, the performance function described by the square sum of the residuals between computed and observed velocities is minimized. The boundary layer is determined by minimizing the performance function. The elastic analysis governed by the Navier equation is carried out, assuming the ground as an elastic body with linear viscous damping. To identify the boundary, the gradient of the performance function with respect to the geological boundary can be calculated using the adjoint equation. The weighed gradient method is effectively applied to the minimization algorithm. To solve the governing and adjoint equations, the Galerkin finite element method and the average acceleration method are employed for the spatial and temporal discretizations, respectively. Based on the method presented in this paper, the different boundary of three strata can be identified. For the numerical studies, the Suemune tunnel excavation site is employed. At first, the blasting force is identified in order to perform the accuracy improvement of analysis. We identify the geological boundary after the estimation of blasting force. With this identification procedure, the numerical analysis results which almost correspond with the observation data were provided.
Abstract: It is known that the heart interacts with and adapts to its venous and arterial loading conditions. Various experimental studies and modeling approaches have been developed to investigate the underlying mechanisms. This paper presents a model of the left ventricle derived based on nonlinear stress-length myocardial characteristics integrated over truncated ellipsoidal geometry, and second-order dynamic mechanism for the excitation-contraction coupling system. The results of the model presented here describe the effects of the viscoelastic damping element of the electromechanical coupling system on the hemodynamic response. Different heart rates are considered to study the pacing effects on the performance of the left-ventricle against constant preload and afterload conditions under various damping conditions. The results indicate that the pacing process of the left ventricle has to take into account, among other things, the viscoelastic damping conditions of the myofilament excitation-contraction process. The effects of left ventricular dimensions on the hemdynamic response have been examined. These effects are found to be different at different viscoelastic and pacing conditions.
Abstract: This study presents the numerical simulation of
optimum pin-fin heat sink with air impinging cooling by using
Taguchi method. 9 L ( 4 3 ) orthogonal array is selected as a plan for
the four design-parameters with three levels. The governing
equations are discretized by using the
control-volume-based-finite-difference method with a power-law
scheme on the non-uniform staggered grid. We solved the coupling of
the velocity and the pressure terms of momentum equations using
SIMPLEC algorithm. We employ the k −ε two-equations
turbulence model to describe the turbulent behavior. The parameters
studied include fin height H (35mm-45mm), inter-fin spacing a , b ,
and c (2 mm-6.4 mm), and Reynolds number ( Re = 10000- 25000).
The objective of this study is to examine the effects of the fin
spacings and fin height on the thermal resistance and to find the
optimum group by using the Taguchi method. We found that the fin
spacings from the center to the edge of the heat sink gradually
extended, and the longer the fin’s height the better the results. The
optimum group is 3 1 2 3 H a b c . In addition, the effects of parameters are
ranked by importance as a , H , c , and b .
Abstract: In the present article, a new class of solutions of
Einstein field equations is investigated for a spherically symmetric
space-time when the source of gravitation is a perfect fluid. All the
solutions have been derived by making some suitable arrangements
in the field equations. The solutions so obtained have been seen to
describe Schwarzschild interior solutions. Most of the solutions are
subjected to the reality conditions. As far as the authors are aware the
solutions are new.
Abstract: In this paper, we propose an improved 3D star skeleton
technique, which is a suitable skeletonization for human posture representation
and reflects the 3D information of human posture.
Moreover, the proposed technique is simple and then can be performed
in real-time. The existing skeleton construction techniques, such as
distance transformation, Voronoi diagram, and thinning, focus on the
precision of skeleton information. Therefore, those techniques are not
applicable to real-time posture recognition since they are computationally
expensive and highly susceptible to noise of boundary. Although
a 2D star skeleton was proposed to complement these problems,
it also has some limitations to describe the 3D information of the
posture. To represent human posture effectively, the constructed skeleton
should consider the 3D information of posture. The proposed 3D
star skeleton contains 3D data of human, and focuses on human action
and posture recognition. Our 3D star skeleton uses the 8 projection
maps which have 2D silhouette information and depth data of human
surface. And the extremal points can be extracted as the features of 3D
star skeleton, without searching whole boundary of object. Therefore,
on execution time, our 3D star skeleton is faster than the “greedy" 3D
star skeleton using the whole boundary points on the surface. Moreover,
our method can offer more accurate skeleton of posture than the
existing star skeleton since the 3D data for the object is concerned.
Additionally, we make a codebook, a collection of representative 3D
star skeletons about 7 postures, to recognize what posture of constructed
skeleton is.
Abstract: In a recent year usage of VoIP subscription has increased tremendously as compare to Public Switching Telephone System(PSTN). A VoIP subscriber would like to know the exact tariffs of the calls made using VoIP. As the usage increases, the rate of fraud is also increases, causing users complain about excess billing. This in turn hampers the growth of VoIP .This paper describe the common frauds and attack on VoIP based system and make an attempt to solve the billing attack by creating secured channel between caller and callee.
Abstract: Sensory input plays an important role to human
posture control system to initiate strategy in order to counterpart any
unbalance condition and thus, prevent fall. In previous study, joint
stiffness was observed able to describe certain issues regarding to
movement performance. But, correlation between balance ability and
joint stiffness is still remains unknown. In this study, joint stiffening
strategy at ankle and hip were observed under different sensory
manipulations and its correlation with conventional clinical test
(Functional Reach Test) for balance ability was investigated. In order
to create unstable condition, two different surface perturbations (tilt
up-tilt (TT) down and forward-backward (FB)) at four different
frequencies (0.2, 0.4, 0.6 and 0.8 Hz) were introduced. Furthermore,
four different sensory manipulation conditions (include vision and
vestibular system) were applied to the subject and they were asked to
maintain their position as possible. The results suggested that joint
stiffness were high during difficult balance situation. Less balance
people generated high average joint stiffness compared to balance
people. Besides, adaptation of posture control system under repetitive
external perturbation also suggested less during sensory limited
condition. Overall, analysis of joint stiffening response possible to
predict unbalance situation faced by human
Abstract: All the available algorithms for blind estimation namely constant modulus algorithm (CMA), Decision-Directed Algorithm (DDA/DFE) suffer from the problem of convergence to local minima. Also, if the channel drifts considerably, any DDA looses track of the channel. So, their usage is limited in varying channel conditions. The primary limitation in such cases is the requirement of certain overhead bits in the transmit framework which leads to wasteful use of the bandwidth. Also such arrangements fail to use channel state information (CSI) which is an important aid in improving the quality of reception. In this work, the main objective is to reduce the overhead imposed by the pilot symbols, which in effect reduces the system throughput. Also we formulate an arrangement based on certain dynamic Artificial Neural Network (ANN) topologies which not only contributes towards the lowering of the overhead but also facilitates the use of the CSI. A 2×2 Multiple Input Multiple Output (MIMO) system is simulated and the performance variation with different channel estimation schemes are evaluated. A new semi blind approach based on dynamic ANN is proposed for channel tracking in varying channel conditions and the performance is compared with perfectly known CSI and least square (LS) based estimation.
Abstract: Transmission and distribution lines are vital links between the generating unit and consumers. They are exposed to atmosphere, hence chances of occurrence of fault in transmission line is very high which has to be immediately taken care of in order to minimize damage caused by it. In this paper Discrete wavelet transform of voltage signals at the two ends of transmission lines have been analyzed. The transient energy of the detail information of level five is calculated for different fault conditions. It is observed that the variation of transient energy of healthy and faulted line can give important information which can be very useful in classifying and locating the fault.
Abstract: This research work is concerned with the eigenvalue problem for the integral operators which are obtained by linearization of a nonlocal evolution equation. The purpose of section II.A is to describe the nature of the problem and the objective of the project. The problem is related to the “stable solution" of the evolution equation which is the so-called “instanton" that describe the interface between two stable phases. The analysis of the instanton and its asymptotic behavior are described in section II.C by imposing the Green function and making use of a probability kernel. As a result , a classical Theorem which is important for an instanton is proved. Section III devoted to a study of the integral operators related to interface dynamics which concern the analysis of the Cauchy problem for the evolution equation with initial data close to different phases and different regions of space.
Abstract: In this work, Experimental tie-line results and
solubility (binodal) curves were obtained for the ternary systems
(water + acetic acid + methyl isobutyl ketone (MIBK)), (water +
lactic acid+ methyl isobutyl ketone) at T = 294.15K and atmospheric
pressure. The consistency of the values of the experimental tie-lines
was determined through the Othmer-Tobias and Hands correlations.
For the extraction effectiveness of solvents, the distribution and
selectivity curves were plotted. In addition, these experimental tieline
data were also correlated with NRTL model. The interaction
parameters for the NRTL model were retrieved from the obtained
experimental results by means of a combination of the homotopy
method and the genetic algorithms.
Abstract: The paper attempts to elucidate the columnar structure
of the cortex by answering the following questions. (1) Why the
cortical neurons with similar interests tend to be vertically arrayed
forming what is known as cortical columns? (2) How to describe the
cortex as a whole in concise mathematical terms? (3) How to design
efficient digital models of the cortex?
Abstract: Designing a simulated system and training it to optimize its tasks in simulated environment helps the designers to avoid problems that may appear when designing the system directly in real world. These problems are: time consuming, high cost, high errors percentage and low efficiency and accuracy of the system. The proposed system will investigate and improve the efficiency and accuracy of a simulated robot to choose correct behavior to perform its task. In this paper, machine learning, which uses genetic algorithm, is adopted. This type of machine learning is called genetic-based machine learning in which a distributed classifier system is used to improve the efficiency and accuracy of the robot. Consequently, it helps the robot to achieve optimal action.
Abstract: This paper aims at a new challenge of customer
satisfaction on mobile customer relationship management. In this
paper presents a conceptualization of mCRM on its unique
characteristics of customer satisfaction. Also, this paper develops an
empirical framework in conception of customer satisfaction in
mCRM. A single-case study is applied as the methodology. In order to
gain an overall view of the empirical case, this paper accesses to
invisible and important information of company in this investigation.
Interview is the key data source form the main informants of the
company through which the issues are identified and the proposed
framework is built. It supports the development of customer
satisfaction in mCRM; links this theoretical framework into practice;
and provides the direction for future research. Therefore, this paper is
very useful for the industries as it helps them to understand how
customer satisfaction changes the mCRM structure and increase the
business competitive advantage. Finally, this paper provides a
contribution in practice by linking a theoretical framework in
conception of customer satisfaction in mCRM for companies to a
practical real case.
Abstract: The scientific achievements coming from molecular
biology depend greatly on the capability of computational
applications to analyze the laboratorial results. A comprehensive
analysis of an experiment requires typically the simultaneous study
of the obtained dataset with data that is available in several distinct
public databases. Nevertheless, developing a centralized access to
these distributed databases rises up a set of challenges such as: what
is the best integration strategy, how to solve nomenclature clashes,
how to solve database overlapping data and how to deal with huge
datasets. In this paper we present GeNS, a system that uses a simple and yet innovative approach to address several biological data integration issues. Compared with existing systems, the main
advantages of GeNS are related to its maintenance simplicity and to its coverage and scalability, in terms of number of supported
databases and data types. To support our claims we present the current use of GeNS in two concrete applications. GeNS currently contains more than 140 million of biological relations and it can be
publicly downloaded or remotely access through SOAP web services.
Abstract: The research on two-wheeled inverted pendulum (TWIP) mobile robots or commonly known as balancing robots have gained momentum over the last decade in a number of robotic laboratories around the world. This paper describes the hardware design of such a robot. The objective of the design is to develop a TWIP mobile robot as well as MATLAB interfacing configuration to be used as flexible platform comprises of embedded unstable linear plant intended for research and teaching purposes. Issues such as selection of actuators and sensors, signal processing units, MATLAB Real Time Workshop coding, modeling and control scheme will be addressed and discussed. The system is then tested using a wellknown state feedback controller to verify its functionality.
Abstract: The present study is aim to prepare and evaluate the selfnanoemulsifying drug delivery (SNEDDS) system of a poorly water soluble drug valsartan in order to achieve a better dissolution rate which would further help in enhancing oral bioavailability. The present research work describes a SNEDDS of valsartan using labrafil M 1944 CS, Tween 80 and Transcutol HP. The pseudoternary phase diagrams with presence and absence of drug were plotted to check for the emulsification range and also to evaluate the effect of valsartan on the emulsification behavior of the phases. The mixtures consisting of oil (labrafil M 1944 CS) with surfactant (tween 80), co-surfactant (Transcutol HP) were found to be optimum formulations. Prepared formulations were evaluated for its particle size distribution, nanoemulsifying properties, robustness to dilution, self emulsication time, turbidity measurement, drug content and invitro dissolution. The optimized formulations are further evaluated for heating cooling cycle, centrifugation studies, freeze thaw cycling, particle size distribution and zeta potential were carried out to confirm the stability of the formed SNEDDS formulations. The prepared formulation revealed t a significant improvement in terms of the drug solubility as compared with marketed tablet and pure drug.
Abstract: The project describes the modeling of various
architectures mechatronics specifically morphologies of robots in an educational environment. Each structure developed by students of
pre-school, primary and secondary was created using the concept of
reverse engineering in a constructivist environment, to later be integrated in educational software that promotes the teaching of
educational Robotics in a virtual and economic environment.
Abstract: An unsupervised classification algorithm is derived
by modeling observed data as a mixture of several mutually
exclusive classes that are each described by linear combinations of
independent non-Gaussian densities. The algorithm estimates the
data density in each class by using parametric nonlinear functions
that fit to the non-Gaussian structure of the data. This improves
classification accuracy compared with standard Gaussian mixture
models. When applied to textures, the algorithm can learn basis
functions for images that capture the statistically significant structure
intrinsic in the images. We apply this technique to the problem of
unsupervised texture classification and segmentation.
Abstract: In this paper, we present a new method for
incorporating global shift invariance in support vector machines.
Unlike other approaches which incorporate a feature extraction stage,
we first scale the image and then classify it by using the modified
support vector machines classifier. Shift invariance is achieved by
replacing dot products between patterns used by the SVM classifier
with the maximum cross-correlation value between them. Unlike the
normal approach, in which the patterns are treated as vectors, in our
approach the patterns are treated as matrices (or images). Crosscorrelation
is computed by using computationally efficient
techniques such as the fast Fourier transform. The method has been
tested on the ORL face database. The tests indicate that this method
can improve the recognition rate of an SVM classifier.