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: Permanent magnet synchronous machines are known
as a good candidate for hybrid electric vehicles due to their unique
merits. However they have two major drawbacks i.e. high cost and
small speed range. In this paper an optimal design of a permanent
magnet machine is presented. A reduction of permanent magnet
material for a constant torque and an extension in speed and torque
ranges are chosen as the optimization aims. For this purpose the
analytical model of the permanent magnet synchronous machine is
derived and the appropriate design algorithm is devised. The genetic
algorithm is then employed to optimize some machine specifications.
Finally the finite element method is used to validate the designed
machine.
Abstract: The paper discusses a 3D numerical solution of the inverse boundary problem for a continuous casting process of alloy. The main goal of the analysis presented within the paper was to estimate heat fluxes along the external surface of the ingot. The verified information on these fluxes was crucial for a good design of a mould, effective cooling system and generally the whole caster. In the study an enthalpy-porosity technique implemented in Fluent package was used for modeling the solidification process. In this method, the phase change interface was determined on the basis of the liquid fraction approach. In inverse procedure the sensitivity analysis was applied for retrieving boundary conditions. A comparison of the measured and retrieved values showed a high accuracy of the computations. Additionally, the influence of the accuracy of measurements on the estimated heat fluxes was also investigated.
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 phase diagrams and compositions of coexisting
phases have been determined for aqueous two-phase systems
containing poly(propylene glycol) with average molecular weight of
425 and sodium citrate at various pH of 3.93, 4.44, 4.6, 4.97, 5.1,
8.22. The effect of pH on the salting-out effect of poly (propylene
glycol) by sodium citrate has been studied. It was found that, an
increasing in pH caused the expansion of two-phase region.
Increasing pH also increases the concentration of PPG in the PPGrich
phase, while the salt-rich phase will be somewhat mole diluted.
Abstract: Spectrum is a scarce commodity, and considering the spectrum scarcity faced by the wireless-based service providers led to high congestion levels. Technical inefficiencies from pooled, since all networks share a common pool of channels, exhausting the available channels will force networks to block the services. Researchers found that cognitive radio (CR) technology may resolve the spectrum scarcity. A CR is a self-configuring entity in a wireless networking that senses its environment, tracks changes, and frequently exchanges information with their networks. However, CRN facing challenges and condition become worst while tracks changes i.e. reallocation of another under-utilized channels while primary network user arrives. In this paper, channels or resource reallocation technique based on DNA-inspired computing algorithm for CRN has been proposed.
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: This paper presents an algorithm to estimate the parameters of two closely spaced sinusoids, providing a frequency resolution that is more than 800 times greater than that obtained by using the Discrete Fourier Transform (DFT). The strategy uses a highly optimized grid search approach to accurately estimate frequency, amplitude and phase of both sinusoids, keeping at the same time the computational effort at reasonable levels. The proposed method has three main characteristics: 1) a high frequency resolution; 2) frequency, amplitude and phase are all estimated at once using one single package; 3) it does not rely on any statistical assumption or constraint. Potential applications to this strategy include the difficult task of resolving coincident partials of instruments in musical signals.
Abstract: Synthetic Aperture Radar (SAR) is an imaging radar form by taking full advantage of the relative movement of the antenna with respect to the target. Through the simultaneous processing of the radar reflections over the movement of the antenna via the Range Doppler Algorithm (RDA), the superior resolution of a theoretical wider antenna, termed synthetic aperture, is obtained. Therefore, SAR can achieve high resolution two dimensional imagery of the ground surface. In addition, two filtering steps in range and azimuth direction provide accurate enough result. This paper develops a simulation in which realistic SAR images can be generated. Also, the effect of velocity errors in the resulting image has also been investigated. Taking some velocity errors into account, the simulation results on the image resolution would be presented. Most of the times, algorithms need to be adjusted for particular datasets, or particular applications.
Abstract: Model-checking tools such as Symbolic Model Verifier
(SMV) and NuSMV are available for checking hardware designs.
These tools can automatically check the formal legitimacy of a
design. However, NuSMV is too low level for describing a complete
hardware design. It is therefore necessary to translate the system
definition, as designed in a language such as Verilog or VHDL, into
a language such as NuSMV for validation. In this paper, we present
a meta hardware description language, Melasy, that contains a code
generator for existing hardware description languages (HDLs) and
languages for model checking that solve this problem.
Abstract: This paper is concerned with the numerical minimization
of energy functionals in BV (
) (the space of bounded variation
functions) involving total variation for gray-scale 1-dimensional inpainting
problem. Applications are shown by finite element method
and discontinuous Galerkin method for total variation minimization.
We include the numerical examples which show the different recovery
image by these two methods.
Abstract: The automatic discrimination of seismic signals is an important practical goal for the earth-science observatories due to the large amount of information that they receive continuously. An essential discrimination task is to allocate the incoming signal to a group associated with the kind of physical phenomena producing it. In this paper, we present new techniques for seismic signals classification: local, regional and global discrimination. These techniques were tested on seismic signals from the data base of the National Geophysical Institute of the Centre National pour la Recherche Scientifique et Technique (Morocco) by using the Moroccan software for seismic signals analysis.
Abstract: The purpose of Grid computing is to utilize
computational power of idle resources which are distributed in
different areas. Given the grid dynamism and its decentralize
resources, there is a need for an efficient scheduler for scheduling
applications. Since task scheduling includes in the NP-hard problems
various researches have focused on invented algorithms especially
the genetic ones. But since genetic is an inherent algorithm which
searches the problem space globally and does not have the efficiency
required for local searching, therefore, its combination with local
searching algorithms can compensate for this shortcomings. The aim
of this paper is to combine the genetic algorithm and GELS (GAGELS)
as a method to solve scheduling problem by which
simultaneously pay attention to two factors of time and number of
missed tasks. Results show that the proposed algorithm can decrease
makespan while minimizing the number of missed tasks compared
with the traditional methods.
Abstract: A fuzzy classifier using multiple ellipsoids approximating decision regions for classification is to be designed in this paper. An algorithm called Gustafson-Kessel algorithm (GKA) with an adaptive distance norm based on covariance matrices of prototype data points is adopted to learn the ellipsoids. GKA is able toadapt the distance norm to the underlying distribution of the prototypedata points except that the sizes of ellipsoids need to be determined a priori. To overcome GKA's inability to determine appropriate size ofellipsoid, the genetic algorithm (GA) is applied to learn the size ofellipsoid. With GA combined with GKA, it will be shown in this paper that the proposed method outperforms the benchmark algorithms as well as algorithms in the field.
Abstract: This paper introduces application of multi degree of freedom fuzzy(MDOFF) controller in permanent magnet (PM)drive system. The drive system model is developed for FO control. Simulation of the system is carried out to predict the performance at NL and under load,. The results indicate that application of MDOFF controller is effective for sensorless PM drive system.
Abstract: This paper describes the challenges on the requirements engineering for developing an enterprise applications in higher
education environment. The development activities include software implementation, maintenance, and enhancement and support for online
transaction processing and overnight batch processing.
Generally, an enterprise application for higher education environment
may include Student Information System (SIS), HR/Payroll system,
Financial Systems etc. By the way, there are so many challenges in
requirement engineering phases in order to provide two distinctive
services that are production processing support and systems
development.
Abstract: Fuzzy linear programming is an application of fuzzy set theory in linear decision making problems and most of these problems are related to linear programming with fuzzy variables. A convenient method for solving these problems is based on using of auxiliary problem. In this paper a new method for solving fuzzy variable linear programming problems directly using linear ranking functions is proposed. This method uses simplex tableau which is used for solving linear programming problems in crisp environment before.
Abstract: The Informational Infrastructures of small and medium-sized manufacturing enterprises are relatively poor, there are serious shortages of capitals which can be invested in informatization construction, computer hardware and software resources, and human resources. To address the informatization issue in small and medium-sized manufacturing enterprises, and enable them to the application of advanced management thinking and enhance their competitiveness, the paper establish a manufacturing-oriented small and medium-sized enterprises informatization platform based on the ASP business intelligence technology, which effectively improves the scientificity of enterprises decision and management informatization.