Abstract: The controllable electrical loss which consists of the
copper loss and iron loss can be minimized by the optimal control of
the armature current vector. The control algorithm of current vector
minimizing the electrical loss is proposed and the optimal current
vector can be decided according to the operating speed and the load
conditions. The proposed control algorithm is applied to the
experimental PM motor drive system and this paper presents a
modern approach of speed control for permanent magnet
synchronous motor (PMSM) applied for Electric Vehicle using a
nonlinear control. The regulation algorithms are based on the
feedback linearization technique. The direct component of the current
is controlled to be zero which insures the maximum torque operation.
The near unity power factor operation is also achieved. More over,
among EV-s motor electric propulsion features, the energy efficiency
is a basic characteristic that is influenced by vehicle dynamics and
system architecture. For this reason, the EV dynamics are taken into
account.
Abstract: This paper discusses a method for improving accuracy
of fuzzy-rule-based classifiers using particle swarm optimization
(PSO). Two different fuzzy classifiers are considered and optimized.
The first classifier is based on Mamdani fuzzy inference system
(M_PSO fuzzy classifier). The second classifier is based on Takagi-
Sugeno fuzzy inference system (TS_PSO fuzzy classifier). The
parameters of the proposed fuzzy classifiers including premise
(antecedent) parameters, consequent parameters and structure of
fuzzy rules are optimized using PSO. Experimental results show that
higher classification accuracy can be obtained with a lower number
of fuzzy rules by using the proposed PSO fuzzy classifiers. The
performances of M_PSO and TS_PSO fuzzy classifiers are compared
to other fuzzy based classifiers
Abstract: In this paper, a new robust audio fingerprinting
algorithm in MP3 compressed domain is proposed with high
robustness to time scale modification (TSM). Instead of simply
employing short-term information of the MP3 stream, the new
algorithm extracts the long-term features in MP3 compressed domain
by using the modulation frequency analysis. Our experiment has
demonstrated that the proposed method can achieve a hit rate of
above 95% in audio retrieval and resist the attack of 20% TSM. It has
lower bit error rate (BER) performance compared to the other
algorithms. The proposed algorithm can also be used in other
compressed domains, such as AAC.
Abstract: Traditional object segmentation methods are time consuming and computationally difficult. In this paper, onedimensional object detection along the secant lines is applied. Statistical features of texture images are computed for the recognition process. Example matrices of these features and formulae for calculation of similarities between two feature patterns are expressed. And experiments are also carried out using these features.
Abstract: Firms have invested heavily in knowledge
management (KM) with the aim to build a knowledge capability and
use it to achieve a competitive advantage. Research has shown,
however, that not all knowledge management projects succeed. Some
studies report that about 84% of knowledge management projects
fail. This paper has integrated studies on the impediments to
knowledge management into a theoretical framework. Based on this
framework, five cases documenting failed KM initiatives were
analysed. The analysis gave us a clear picture about why certain KM
projects fail. The high failure rate of KM can be explained by the
gaps that exist between users and management in terms of KM
perceptions and objectives
Abstract: This paper presented the technique of robot control by event-related potentials (ERPs) of brain waves. Based on the proposed technique, severe physical disabilities can free browse outside world. A specific component of ERPs, N2P3, was found and used to control the movement of robot and the view of camera on the designed brain-computer interface (BCI). Users only required watching the stimuli of attended button on the BCI, the evoked potentials of brain waves of the target button, N2P3, had the greatest amplitude among all control buttons. An experimental scene had been constructed that the robot required walking to a specific position and move the view of camera to see the instruction of the mission, and then completed the task. Twelve volunteers participated in this experiment, and experimental results showed that the correct rate of BCI control achieved 80% and the average of execution time was 353 seconds for completing the mission. Four main contributions included in this research: (1) find an efficient component of ERPs, N2P3, for BCI control, (2) embed robot's viewpoint image into user interface for robot control, (3) design an experimental scene and conduct the experiment, and (4) evaluate the performance of the proposed system for assessing the practicability.
Abstract: Gesture recognition is a challenging task for extracting
meaningful gesture from continuous hand motion. In this paper, we propose an automatic system that recognizes isolated gesture,
in addition meaningful gesture from continuous hand motion for Arabic numbers from 0 to 9 in real-time based on Hidden Markov Models (HMM). In order to handle isolated gesture, HMM using
Ergodic, Left-Right (LR) and Left-Right Banded (LRB) topologies is applied over the discrete vector feature that is extracted from stereo
color image sequences. These topologies are considered to different
number of states ranging from 3 to 10. A new system is developed to recognize the meaningful gesture based on zero-codeword detection
with static velocity motion for continuous gesture. Therefore, the
LRB topology in conjunction with Baum-Welch (BW) algorithm for
training and forward algorithm with Viterbi path for testing presents the best performance. Experimental results show that the proposed system can successfully recognize isolated and meaningful gesture and achieve average rate recognition 98.6% and 94.29% respectively.
Abstract: This paper proposes a visual cryptography by random
grids scheme with identifiable shares. The method encodes an image
O in two shares that exhibits the following features: (1) each generated
share has the same scale as O, (2) any share singly has noise-like
appearance that reveals no secret information on O, (3) the secrets can
be revealed by superimposing the two shares, (4) folding a share up
can disclose some identification patterns, and (5) both of the secret
information and the designated identification patterns are recognized
by naked eye without any computation. The property to show up
identification patterns on folded shares establishes a simple and
friendly interface for users to manage the numerous shares created by
VC schemes.
Abstract: The aim of the study is to determine the effects of
perceived organizational support on organizational identification. In
accordance with this purpose was applied on 131 family physicians in
Konya. The data obtained by means of the survey method were
analyzed. According to the results of correlation analysis, while
positive relationship between perceived organizational support,
organizational identification and supervisor support was revealed.
Also, with the scope of the research, relationships between these
variables and certain demographic variables were detected.
According to difference analysis results of the research, significant
differences between organizational identification and gender variable
were determined. However, significant differences were not
determined between demographic variables and perceived
organizational support.
Abstract: The objective of this paper is to design a model of human vital sign prediction for decreasing prediction error by using two states mapping based time series neural network BP (back-propagation) model. Normally, lot of industries has been applying the neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has a residual error between real value and prediction output. Therefore, we designed two states of neural network model for compensation of residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We found that most of simulations cases were satisfied by the two states mapping based time series prediction model compared to normal BP. In particular, small sample size of times series were more accurate than the standard MLP model. We expect that this algorithm can be available to sudden death prevention and monitoring AGENT system in a ubiquitous homecare environment.
Abstract: The research focuses on the effects of polyphenols
extracted from Sambucus nigra fruit, using an experimental arterial
hypertension pattern, as well as their influence on the oxidative
stress. The results reveal the normalization of the reduced glutathion
concentration, as well as a considerable reduction in the
malondialdehide serum concentration by the polyphenolic protection.
The rat blood pressure values were recorded using a CODATM
system, which uses a non-invasive blood pressure measuring method.
All the measured blood pressure components revealed a biostatistically
significant (p
Abstract: In this paper, we propose a novel adaptive
spatiotemporal filter that utilizes image sequences in order to remove
noise. The consecutive frames include: current, previous and next
noisy frames. The filter proposed in this paper is based upon the
weighted averaging pixels intensity and noise variance in image
sequences. It utilizes the Appropriate Number of Consecutive Frames
(ANCF) based on the noisy pixels intensity among the frames. The
number of consecutive frames is adaptively calculated for each
region in image and its value may change from one region to another
region depending on the pixels intensity within the region. The
weights are determined by a well-defined mathematical criterion,
which is adaptive to the feature of spatiotemporal pixels of the
consecutive frames. It is experimentally shown that the proposed
filter can preserve image structures and edges under motion while
suppressing noise, and thus can be effectively used in image
sequences filtering. In addition, the AWA filter using ANCF is
particularly well suited for filtering sequences that contain segments
with abruptly changing scene content due to, for example, rapid
zooming and changes in the view of the camera.
Abstract: Operational risk has become one of the most discussed topics in the financial industry in the recent years. The reasons for this attention can be attributed to higher investments in information systems and technology, the increasing wave of mergers and acquisitions and emergence of new financial instruments. In addition, the New Basel Capital Accord (known as Basel II) demands a capital requirement for operational risk and further motivates financial institutions to more precisely measure and manage this type of risk. The aim of this paper is to shed light on main characteristics of operational risk management and common applied methods: scenario analysis, key risk indicators, risk control self assessment and loss distribution approach.
Abstract: Rural areas of Tanzania are still disadvantaged in terms of diffusion of IP-based services; this is due to lack of Information and Communication Technology (ICT) infrastructures, especially lack of connectivity. One of the limitations for connectivity problems in rural areas of Tanzania is the high cost to establish infrastructures for IP-based services [1-2]. However the cost of connectivity varies from one technology to the other and at the same time, the cost is also different from one operator (service provider) to another within the country. This paper presents development of software system to calculate cost of connectivity to rural areas of Tanzania. The system is developed to make an easy access of connectivity cost from different technologies and different operators. The development of the calculator follows the V-model software development lifecycle. The calculator is used to evaluate the economic viability of different technologies considered as being potential candidates to provide rural connectivity. In this paper, the evaluation is based on the techno-economic analysis approach.
Abstract: As the electrical power industry is restructured, the electrical power exchange is becoming extended. One of the key information used to determine how much power can be transferred through the network is known as available transfer capability (ATC). To calculate ATC, traditional deterministic approach is based on the severest case, but the approach has the complexity of procedure. Therefore, novel approach for ATC calculation is proposed using cost-optimization method in this paper, and is compared with well-being method and risk-benefit method. This paper proposes the optimal transfer capability of HVDC system between mainland and a separated island in Korea through these three methods. These methods will consider production cost, wheeling charge through HVDC system and outage cost with one depth (N-1 contingency)
Abstract: From year to year, the incidence of different diseases is increasing in humans, and the cause is inadequate intake of dietary fibre, vitamins, and minerals. One of the possibilities to take care of your health preventively is including in the diet products with increased dietary fibre, vitamin, and mineral content.Jerusalem artichoke powder (JAP) made from Jerusalem artichoke (Helianthus tuberosus L) roots is a valuable product. By adding it to pastry goods, we can obtain a fibre-rich food that could be healthier and an excellent alternative to the classical pastry products of this kind.Experiments were carried out at the Faculty of Food Technology of Latvia University of Agriculture (LLU). Results of experiments showed that addition of Jerusalem artichoke powder has significant impact on all the studied pastry products nutritional value (p
Abstract: Cooperative learning has been defined as learners working together as a team to solve a problem to complete a task or to accomplish a common goal, which emphasizes the importance of interactions among members to promote the whole learning performance. With the popularity of society networks, cooperative learning is no longer limited to traditional classroom teaching activities. Since society networks facilitate to organize online learners, to establish common shared visions, and to advance learning interaction, the online community and online learning community have triggered the establishment of web-based societies. Numerous research literatures have indicated that the collaborative learning community is a critical issue to enhance learning performance. Hence, this paper proposes a learning community recommendation approach to facilitate that a learner joins the appropriate learning communities, which is based on k-nearest neighbor (kNN) classification. To demonstrate the viability of the proposed approach, the proposed approach is implemented for 117 students to recommend learning communities. The experimental results indicate that the proposed approach can effectively recommend appropriate learning communities for learners.
Abstract: The essential oil of M. × piperita L. was formulated
into a topical gel. The prepared gel was characterized for its pH,
viscosity, spreadiblity, consistency and extrudiblity, while its stability
was evaluated under different temperature conditions. The prepared
M. × piperita oil gel was clear and transparent. The pH value of
developed gel was 6.6, while its viscosity was 1200 cP. Spreadability
and consistency of the M. × piperita oil gel was 10.7 g.cm/sec and 7
mm, respectively. The prepared gel showed good extrudiblity. During
the stability studies, no significant change in pH and viscosity as a
function of time for gel was observed, indicating stability of prepared
formulation. The gel developed in this study is expected to forward
the usage of M. × piperita essential towards commercial application.
Abstract: Inthis paper, design and fabrication of vertical
micromirror for optical switching applications of single mode optical
fibers are proposed. The structure of micromirror will be created
from negative photoresist (SU-8) on X-ray lithography using X-ray
from synchrotron light source. The properties of X-ray from
synchrotron light source are high-energy electrons which can
construct materials that have a high aspect ratio. In addition, the
technique of gold coating of reflective material has been used for
change direction of light between two pairs of optical fibers. At a
wavelength of 1310 nm with minimum average loss of 5.305 dB is
obtained.
Abstract: Autoregressive Moving average (ARMA) is a parametric based method of signal representation. It is suitable for problems in which the signal can be modeled by explicit known source functions with a few adjustable parameters. Various methods have been suggested for the coefficients determination among which are Prony, Pade, Autocorrelation, Covariance and most recently, the use of Artificial Neural Network technique. In this paper, the method of using Artificial Neural network (ANN) technique is compared with some known and widely acceptable techniques. The comparisons is entirely based on the value of the coefficients obtained. Result obtained shows that the use of ANN also gives accurate in computing the coefficients of an ARMA system.