Abstract: This paper addresses the design of predictive
networked controller with adaptation of a communication delay. The
networked control system contains random delays from sensor to
controller and from controller to actuator. The proposed predictive
controller includes an adaptation loop which decreases the influence
of communication delay on the control performance. Also, the
predictive controller contains a filter which improves the robustness
of the control system. The performance of the proposed adaptive
predictive controller is demonstrated by simulation results in
comparison with PI controller and predictive controller with constant
delay.
Abstract: Facial expression analysis plays a significant role for
human computer interaction. Automatic analysis of human facial
expression is still a challenging problem with many applications. In
this paper, we propose neuro-fuzzy based automatic facial expression
recognition system to recognize the human facial expressions like
happy, fear, sad, angry, disgust and surprise. Initially facial image is
segmented into three regions from which the uniform Local Binary
Pattern (LBP) texture features distributions are extracted and
represented as a histogram descriptor. The facial expressions are
recognized using Multiple Adaptive Neuro Fuzzy Inference System
(MANFIS). The proposed system designed and tested with JAFFE
face database. The proposed model reports 94.29% of classification
accuracy.
Abstract: This paper proposes a neural network weights and
topology optimization using genetic evolution and the
backpropagation training algorithm. The proposed crossover and
mutation operators aims to adapt the networks architectures and
weights during the evolution process. Through a specific inheritance
procedure, the weights are transmitted from the parents to their
offsprings, which allows re-exploitation of the already trained
networks and hence the acceleration of the global convergence of the
algorithm. In the preprocessing phase, a new feature extraction
method is proposed based on Legendre moments with the Maximum
entropy principle MEP as a selection criterion. This allows a global
search space reduction in the design of the networks. The proposed
method has been applied and tested on the well known MNIST
database of handwritten digits.
Abstract: Based on the one-bit-matching principle and by turning the de-mixing matrix into an orthogonal matrix via certain normalization, Ma et al proposed a one-bit-matching learning algorithm on the Stiefel manifold for independent component analysis [8]. But this algorithm is not adaptive. In this paper, an algorithm which can extract kurtosis and its sign of each independent source component directly from observation data is firstly introduced.With the algorithm , the one-bit-matching learning algorithm is revised, so that it can make the blind separation on the Stiefel manifold implemented completely in the adaptive mode in the framework of natural gradient.
Abstract: In this paper a combination approach of two heuristic-based algorithms: genetic algorithm and tabu search is proposed. It has been developed to obtain the least cost based on the split-pipe design of looped water distribution network. The proposed combination algorithm has been applied to solve the three well-known water distribution networks taken from the literature. The development of the combination of these two heuristic-based algorithms for optimization is aimed at enhancing their strengths and compensating their weaknesses. Tabu search is rather systematic and deterministic that uses adaptive memory in search process, while genetic algorithm is probabilistic and stochastic optimization technique in which the solution space is explored by generating candidate solutions. Split-pipe design may not be realistic in practice but in optimization purpose, optimal solutions are always achieved with split-pipe design. The solutions obtained in this study have proved that the least cost solutions obtained from the split-pipe design are always better than those obtained from the single pipe design. The results obtained from the combination approach show its ability and effectiveness to solve combinatorial optimization problems. The solutions obtained are very satisfactory and high quality in which the solutions of two networks are found to be the lowest-cost solutions yet presented in the literature. The concept of combination approach proposed in this study is expected to contribute some useful benefits in diverse problems.
Abstract: Pretreatment is an essential step in the conversion of
lignocellulosic biomass to fermentable sugar that used for biobutanol
production. Among pretreatment processes, microwave is considered
to improve pretreatment efficiency due to its high heating efficiency,
easy operation, and easily to combine with chemical reaction. The
main objectives of this work are to investigate the feasibility of
microwave pretreatment to enhance enzymatic hydrolysis of
corncobs and to determine the optimal conditions using response
surface methodology. Corncobs were pretreated via two-stage
pretreatment in dilute sodium hydroxide (2 %) followed by dilute
sulfuric acid 1 %. Pretreated corncobs were subjected to enzymatic
hydrolysis to produce reducing sugar. Statistical experimental design
was used to optimize pretreatment parameters including temperature,
residence time and solid-to-liquid ratio to achieve the highest amount
of glucose. The results revealed that solid-to-liquid ratio and
temperature had a significant effect on the amount of glucose.
Abstract: Student-s movements have been going increasing in
last decades. International students can have different psychological
and sociological problems in their adaptation process. Depression is
one of the most important problems in this procedure. This research
purposed to reveal level of foreign students- depression, kinds of
interpersonal communication networks (host/ethnic interpersonal
communication) and media usage (host/ethnic media usage).
Additionally study aimed to display the relationship between
depression and communication (host/ethnic interpersonal
communication and host/ethnic media usage) among foreign
university students. A field research was performed among 283
foreign university students who have been attending 8 different
universities in Turkey. A purposeful sampling technique was used in
this research cause of data collect facilities. Results indicated that
58.3% of foreign students- depression stage was “intermediate" while
33.2% of foreign students- depression level was “low". Add to this,
host interpersonal communication behaviors and Turkish web sites
usages were negatively and significantly correlated with depression.
Abstract: This study was a part of the three-year longitudinal
research on setting up an math learning model for the disadvantaged
students in Taiwan. A target 2nd grade class with 10 regular students
and 6 disadvantaged students at a disadvantaged area in Taipei
participated in this study. Two units of a market basal math textbook
concerning fractions, three-dimensional figures, weight and capacity
were adapted to enhance their math learning motivations, confidences
and effects. The findings were (1) curriculum adaptation was effective
on enhancing students- learning motivations, confidences and effects;
(2) story-type problems and illustrations decreased difficulties on
understanding math language for students from new immigrant
families and students with special needs; (3) “concrete –
semiconcrete – abstract" teaching strategies and hands-on activities
were essential to raise students learning interests and effects; and (4)
curriculum adaptation knowledge and skills needed to be included in
the pre- and in-service teacher training programs.
Abstract: The 4G front-end transceiver needs a high
performance which can be obtained mainly with an optimal
architecture and a multi-band Local Oscillator. In this study, we
proposed and presented a new architecture of multi-band frequency
synthesizer based on an Inverse Sine Phase Detector Phase Locked
Loop (ISPD PLL) without any filters and any controlled gain block
and associated with adapted multi band LC tuned VCO using a
several numeric controlled capacitive branches but not binary
weighted. The proposed architecture, based on 0.35μm CMOS
process technology, supporting Multi-band GSM/DCS/DECT/
UMTS/WiMax application and gives a good performances: a phase
noise @1MHz -127dBc and a Factor Of Merit (FOM) @ 1MHz -
186dB and a wide band frequency range (from 0.83GHz to 3.5GHz),
that make the proposed architecture amenable for monolithic
integration and 4G multi-band application.
Abstract: In this paper an alternative analysis in the time
domain is described and the results of the interpolation process are
presented by means of functions that are based on the rule of
conditional mathematical expectation and the covariance function. A
comparison between the interpolation error caused by low order
filters and the classic sinc(t) truncated function is also presented.
When fewer samples are used, low-order filters have less error. If the
number of samples increases, the sinc(t) type functions are a better
alternative. Generally speaking there is an optimal filter for each
input signal which depends on the filter length and covariance
function of the signal. A novel scheme of work for adaptive
interpolation filters is also presented.
Abstract: In this paper, we consider the analysis of the
acquisition process for a hybrid double-dwell system with antenna
diversity for DS-CDMA (direct sequence-code division multiple
access) using an adaptive threshold. Acquisition systems with a fixed
threshold value are unable to adapt to fast varying mobile
communications environments and may result in a high false alarm
rate, and/or low detection probability. Therefore, we propose an
adaptively varying threshold scheme through the use of a cellaveraging
constant false alarm rate (CA-CFAR) algorithm, which is
well known in the field of radar detection. We derive exact
expressions for the probabilities of detection and false alarm in
Rayleigh fading channels. The mean acquisition time of the system
under consideration is also derived. The performance of the system is
analyzed and compared to that of a hybrid single dwell system.
Abstract: The main objective of this paper is to provide an efficient tool for delineating brain tumors in three-dimensional magnetic resonance images. To achieve this goal, we use basically a level-sets approach to delineating three-dimensional brain tumors. Then we introduce a compression plan of 3D brain structures based for the meshes simplification, adapted for time to the specific needs of the telemedicine and to the capacities restricted by network communication. We present here the main stages of our system, and preliminary results which are very encouraging for clinical practice.
Abstract: Since its independence in 1962, Algeria has struggled
to establish an educational system tailored to the needs of the
population it may address. Considering the historical connection with
France, Algeria has always looked at the French language as a
cultural imperative until late in the seventies. After the Arabization
policy of 1971 and the socioeconomic changes taking place
worldwide, the use of English as a communicating vehicle started to
gain more space within globalized Algeria. Consequently, disparities
in the use of French started to fade away at the cross-roads leaving
more space to the teaching of English as a second foreign language.
Moreover, the introduction of the Bologna Process and the
European Credit Transfer System in Higher Education has
necessitated some innovations in the design and development of new
curricula adapted to the socioeconomic market. In this paper, I will
try to highlight the important historical dimensions Algeria has taken
towards the implementation of an English language methodology and
to the status it acquired from second foreign language, to first foreign
language to “the language of knowledge and sciences". I will also
propose new pedagogical perspectives for a better treatment of the
English language in order to encourage independent and autonomous
learning.
Abstract: The approach based on the wavelet transform has
been widely used for image denoising due to its multi-resolution
nature, its ability to produce high levels of noise reduction and the
low level of distortion introduced. However, by removing noise, high
frequency components belonging to edges are also removed, which
leads to blurring the signal features. This paper proposes a new
method of image noise reduction based on local variance and edge
analysis. The analysis is performed by dividing an image into 32 x 32
pixel blocks, and transforming the data into wavelet domain. Fast
lifting wavelet spatial-frequency decomposition and reconstruction is
developed with the advantages of being computationally efficient and
boundary effects minimized. The adaptive thresholding by local
variance estimation and edge strength measurement can effectively
reduce image noise while preserve the features of the original image
corresponding to the boundaries of the objects. Experimental results
demonstrate that the method performs well for images contaminated
by natural and artificial noise, and is suitable to be adapted for
different class of images and type of noises. The proposed algorithm
provides a potential solution with parallel computation for real time
or embedded system application.
Abstract: Outlier detection in streaming data is very challenging because streaming data cannot be scanned multiple times and also new concepts may keep evolving. Irrelevant attributes can be termed as noisy attributes and such attributes further magnify the challenge of working with data streams. In this paper, we propose an unsupervised outlier detection scheme for streaming data. This scheme is based on clustering as clustering is an unsupervised data mining task and it does not require labeled data, both density based and partitioning clustering are combined for outlier detection. In this scheme partitioning clustering is also used to assign weights to attributes depending upon their respective relevance and weights are adaptive. Weighted attributes are helpful to reduce or remove the effect of noisy attributes. Keeping in view the challenges of streaming data, the proposed scheme is incremental and adaptive to concept evolution. Experimental results on synthetic and real world data sets show that our proposed approach outperforms other existing approach (CORM) in terms of outlier detection rate, false alarm rate, and increasing percentages of outliers.
Abstract: In this paper a new Joint Adaptive Block Matching
Search (JABMS) algorithm is proposed to generate motion vector
and search a best match macro block by classifying the motion vector
movement based on prediction error. Diamond Search (DS)
algorithm generates high estimation accuracy when motion vector is
small and Adaptive Rood Pattern Search (ARPS) algorithm can
handle large motion vector but is not very accurate. The proposed
JABMS algorithm which is capable of considering both small and
large motions gives improved estimation accuracy and the
computational cost is reduced by 15.2 times compared with
Exhaustive Search (ES) algorithm and is 1.3 times less compared
with Diamond search algorithm.
Abstract: This paper introduces an adaptive control scheme to synchronize two identical Chua's systems. Introductory part of the paper is presented in the first part of the paper and then in the second part, a new theorem is proposed based on which an adaptive control scheme is developed to synchronize two identical modified Chua's circuit. Finally, numerical simulations are included to verify the effectiveness of the proposed control method.
Abstract: In this paper, we proposed the robust mobile object
detection method for light effect in the night street image block based
updating reference background model using block state analysis.
Experiment image is acquired sequence color video from steady
camera. When suddenly appeared artificial illumination, reference
background model update this information such as street light, sign
light. Generally natural illumination is change by temporal, but
artificial illumination is suddenly appearance. So in this paper for
exactly detect artificial illumination have 2 state process. First process
is compare difference between current image and reference
background by block based, it can know changed blocks. Second
process is difference between current image-s edge map and reference
background image-s edge map, it possible to estimate illumination at
any block. This information is possible to exactly detect object,
artificial illumination and it was generating reference background
more clearly. Block is classified by block-state analysis. Block-state
has a 4 state (i.e. transient, stationary, background, artificial
illumination). Fig. 1 is show characteristic of block-state respectively
[1]. Experimental results show that the presented approach works well
in the presence of illumination variance.
Abstract: After Apple's first introduction its smart phone, iPhone
in the end of 2009 in Korea, the number of Korean smarphone users
had been rapidly increasing so that the half of Korean population
became smart phone users as of February, 2012. Currently, smart
phones are positioned as a major digital media with powerful
influences in Korea. And, now, Koreans are leaning new information,
enjoying games and communicating other people every time and
everywhere. As smart phone devices' performances increased, the
number of usable services became more while adequate GUI
developments are required to implement various functions with smart
phones. The strategy to provide similar experiences on smart phones
through familiar features based on employment of existing media's
functions mostly contributed to smart phones' popularization in
connection with smart phone devices' iconic GUIs.
The spread of Smart phone increased mobile web accesses.
Therefore, the attempts to implement PC's web in the smart phone's
web are continuously made. The mobile web GUI provides familiar
experiences to users through designs adequately utilizing the smart
phone's GUIs. As the number of users familiarized to smart phones
and mobile web GUIs, opposite to reversed remediation from many
parts of PCs, PCs are starting to adapt smart phone GUIs.
This study defines this phenomenon as the reversed remediation,
and reviews the reversed remediation cases of Smart phone GUI'
characteristics of PCs. For this purpose, the established study issues
are as under:
· what is the reversed remediation?
· what are the smart phone GUI's characteristics?
· what kind of interrelationship exist s between the smart phone and
PC's web site?
It is meaningful in the forecast of the future GUI's change by
understanding of characteristics in the paradigm changes of PC and
smart phone's GUI designs. This also will be helpful to establish
strategies for digital devices' development and design.
Abstract: This paper presents the development of an active
vibration control using direct adaptive controller to suppress the
vibration of a flexible beam system. The controller is realized based
on linear parametric form. Differential evolution optimisation
algorithm is used to optimize the controller using single objective
function by minimizing the mean square error of the observed
vibration signal. Furthermore, an alternative approach is developed to
systematically search for the best controller model structure together
with it parameter values. The performance of the control scheme is
presented and analysed in both time and frequency domain.
Simulation results demonstrate that the proposed scheme is able to
suppress the unwanted vibration effectively.