Abstract: In this paper, a new descent-projection method with a
new search direction for monotone structured variational inequalities
is proposed. The method is simple, which needs only projections
and some function evaluations, so its computational load is very tiny.
Under mild conditions on the problem-s data, the method is proved to
converges globally. Some preliminary computational results are also
reported to illustrate the efficiency of the method.
Abstract: The practical implementation of audio-video coupled speech recognition systems is mainly limited by the hardware complexity to integrate two radically different information capturing devices with good temporal synchronisation. In this paper, we propose a solution based on a smart CMOS image sensor in order to simplify the hardware integration difficulties. By using on-chip image processing, this smart sensor can calculate in real time the X/Y projections of the captured image. This on-chip projection reduces considerably the volume of the output data. This data-volume reduction permits a transmission of the condensed visual information via the same audio channel by using a stereophonic input available on most of the standard computation devices such as PC, PDA and mobile phones. A prototype called VMIKE (Visio-Microphone) has been designed and realised by using standard 0.35um CMOS technology. A preliminary experiment gives encouraged results. Its efficiency will be further investigated in a large variety of applications such as biometrics, speech recognition in noisy environments, and vocal control for military or disabled persons, etc.
Abstract: In this work a new offline signature recognition system
based on Radon Transform, Fractal Dimension (FD) and Support Vector Machine (SVM) is presented. In the first step, projections of
original signatures along four specified directions have been performed using radon transform. Then, FDs of four obtained
vectors are calculated to construct a feature vector for each
signature. These vectors are then fed into SVM classifier for recognition of signatures. In order to evaluate the effectiveness of
the system several experiments are carried out. Offline signature
database from signature verification competition (SVC) 2004 is used
during all of the tests. Experimental result indicates that the proposed method achieved high accuracy rate in signature recognition.
Abstract: Most CT reconstruction system x-ray computed
tomography (CT) is a well established visualization technique in
medicine and nondestructive testing. However, since CT scanning
requires sampling of radiographic projections from different viewing
angles, common CT systems with mechanically moving parts are too
slow for dynamic imaging, for instance of multiphase flows or live
animals. A large number of X-ray projections are needed to
reconstruct CT images, so the collection and calculation of the
projection data consume too much time and harmful for patient. For
the purpose of solving the problem, in this study, we proposed a
method for tomographic reconstruction of a sample from a limited
number of x-ray projections by using linear interpolation method. In
simulation, we presented reconstruction from an experimental x-ray
CT scan of a Aluminum phantom that follows to two steps: X-ray
projections will be interpolated using linear interpolation method and
using it for CT reconstruction based upon Ordered Subsets
Expectation Maximization (OSEM) method.
Abstract: Sport is one of the sectors in which the largest
technical projections regarding the functions of textiles can be found.
He is a large consumer of high performance composite materials and
new fibers. It is one of the sectors where the innovation is the most
important when the greatest numbers of spectacular developments are
aimed at increasing performance. In medicine, textile innovation is
used and contributes in the amelioration of different materials such as
dressing, orthosis, bandages, etc. The hygienic textiles in non-woven
materials record a strong growth. The objective of this study is to
show the different advances of development we obtained in the both
ways (sport and medicine). Polyamide fibers where developed
tacking into account the specification of the high level athlete’s
performance like swimming and triathlon (Olympic Games, Brazil
2016). The first textile utilization was for skiing (Olympic Games,
Sotchi 2014). The different textiles technologies where adapted for
medicine.
Abstract: Internal controls of accounting are an essential
business function for a growth-oriented organization, and include the
elements of risk assessment, information communications and even
employees' roles and responsibilities. Internal controls of accounting
systems are designed to protect a company from fraud, abuse and
inaccurate data recording and help organizations keep track of
essential financial activities. Internal controls of accounting provide a
streamlined solution for organizing all accounting procedures and
ensuring that the accounting cycle is completed consistently and
successfully. Implementing a formal Accounting Procedures Manual
for the organization allows the financial department to facilitate
several processes and maintain rigorous standards. Internal controls
also allow organizations to keep detailed records, manage and
organize important financial transactions and set a high standard for
the organization's financial management structure and protocols. A
well-implemented system also reduces the risk of accounting errors
and abuse. A well-implemented controls system allows a company's
financial managers to regulate and streamline all functions of the
accounting department. Internal controls of accounting can be set up
for every area to track deposits, monitor check handling, keep track
of creditor accounts, and even assess budgets and financial statements
on an ongoing basis. Setting up an effective accounting system to
monitor accounting reports, analyze records and protect sensitive
financial information also can help a company set clear goals and
make accurate projections. Creating efficient accounting processes
allows an organization to set specific policies and protocols on
accounting procedures, and reach its financial objectives on a regular
basis. Internal accounting controls can help keep track of such areas
as cash-receipt recording, payroll management, appropriate recording
of grants and gifts, cash disbursements by authorized personnel, and
the recording of assets. These systems also can take into account any
government regulations and requirements for financial reporting.
Abstract: In this paper we present a technique to speed up
ICA based on the idea of reducing the dimensionality of the data
set preserving the quality of the results. In particular we refer to
FastICA algorithm which uses the Kurtosis as statistical property
to be maximized. By performing a particular Johnson-Lindenstrauss
like projection of the data set, we find the minimum dimensionality
reduction rate ¤ü, defined as the ratio between the size k of the reduced
space and the original one d, which guarantees a narrow confidence
interval of such estimator with high confidence level. The derived
dimensionality reduction rate depends on a system control parameter
β easily computed a priori on the basis of the observations only.
Extensive simulations have been done on different sets of real world
signals. They show that actually the dimensionality reduction is very
high, it preserves the quality of the decomposition and impressively
speeds up FastICA. On the other hand, a set of signals, on which the
estimated reduction rate is greater than 1, exhibits bad decomposition
results if reduced, thus validating the reliability of the parameter β.
We are confident that our method will lead to a better approach to
real time applications.
Abstract: The complex hybrid and nonlinear nature of many processes that are met in practice causes problems with both structure modelling and parameter identification; therefore, obtaining a model that is suitable for MPC is often a difficult task. The basic idea of this paper is to present an identification method for a piecewise affine (PWA) model based on a fuzzy clustering algorithm. First we introduce the PWA model. Next, we tackle the identification method. We treat the fuzzy clustering algorithm, deal with the projections of the fuzzy clusters into the input space of the PWA model and explain the estimation of the parameters of the PWA model by means of a modified least-squares method. Furthermore, we verify the usability of the proposed identification approach on a hybrid nonlinear batch reactor example. The result suggest that the batch reactor can be efficiently identified and thus formulated as a PWA model, which can eventually be used for model predictive control purposes.