Abstract: The research investigates the “impact of VLE on mathematical concepts acquisition of the special education needs (SENs) students at KS4 secondary education sector" in England. The overall aim of the study is to establish possible areas of difficulties to approach for above or below knowledge standard requirements for KS4 students in the acquisition and validation of basic mathematical concepts. A teaching period, in which virtual learning environment (Fronter) was used to emphasise different mathematical perception and symbolic representation was carried out and task based survey conducted to 20 special education needs students [14 actually took part]. The result shows that students were able to process information and consider images, objects and numbers within the VLE at early stages of acquisition process. They were also able to carry out perceptual tasks but with limiting process of different quotient, thus they need teacher-s guidance to connect them to symbolic representations and sometimes coach them through. The pilot study further indicates that VLE curriculum approaches for students were minutely aligned with mathematics teaching which does not emphasise the integration of VLE into the existing curriculum and current teaching practice. There was also poor alignment of vision regarding the use of VLE in realisation of the objectives of teaching mathematics by the management. On the part of teacher training, not much was done to develop teacher-s skills in the technical and pedagogical aspects of VLE that is in-use at the school. The classroom observation confirmed teaching practice will find a reliance on VLE as an enhancer of mathematical skills, providing interaction and personalisation of learning to SEN students.
Abstract: Wavelet transforms is a very powerful tools for image compression. One of its advantage is the provision of both spatial and frequency localization of image energy. However, wavelet transform coefficients are defined by both a magnitude and sign. While algorithms exist for efficiently coding the magnitude of the transform coefficients, they are not efficient for the coding of their sign. It is generally assumed that there is no compression gain to be obtained from the coding of the sign. Only recently have some authors begun to investigate the sign of wavelet coefficients in image coding. Some authors have assumed that the sign information bit of wavelet coefficients may be encoded with the estimated probability of 0.5; the same assumption concerns the refinement information bit. In this paper, we propose a new method for Separate Sign Coding (SSC) of wavelet image coefficients. The sign and the magnitude of wavelet image coefficients are examined to obtain their online probabilities. We use the scalar quantization in which the information of the wavelet coefficient to belong to the lower or to the upper sub-interval in the uncertainly interval is also examined. We show that the sign information and the refinement information may be encoded by the probability of approximately 0.5 only after about five bit planes. Two maps are separately entropy encoded: the sign map and the magnitude map. The refinement information of the wavelet coefficient to belong to the lower or to the upper sub-interval in the uncertainly interval is also entropy encoded. An algorithm is developed and simulations are performed on three standard images in grey scale: Lena, Barbara and Cameraman. Five scales are performed using the biorthogonal wavelet transform 9/7 filter bank. The obtained results are compared to JPEG2000 standard in terms of peak signal to noise ration (PSNR) for the three images and in terms of subjective quality (visual quality). It is shown that the proposed method outperforms the JPEG2000. The proposed method is also compared to other codec in the literature. It is shown that the proposed method is very successful and shows its performance in term of PSNR.
Abstract: Identity verification of authentic persons by their multiview faces is a real valued problem in machine vision. Multiview faces are having difficulties due to non-linear representation in the feature space. This paper illustrates the usability of the generalization of LDA in the form of canonical covariate for face recognition to multiview faces. In the proposed work, the Gabor filter bank is used to extract facial features that characterized by spatial frequency, spatial locality and orientation. Gabor face representation captures substantial amount of variations of the face instances that often occurs due to illumination, pose and facial expression changes. Convolution of Gabor filter bank to face images of rotated profile views produce Gabor faces with high dimensional features vectors. Canonical covariate is then used to Gabor faces to reduce the high dimensional feature spaces into low dimensional subspaces. Finally, support vector machines are trained with canonical sub-spaces that contain reduced set of features and perform recognition task. The proposed system is evaluated with UMIST face database. The experiment results demonstrate the efficiency and robustness of the proposed system with high recognition rates.
Abstract: With the explosive growth of information sources available on the World Wide Web, it has become increasingly difficult to identify the relevant pieces of information, since web pages are often cluttered with irrelevant content like advertisements, navigation-panels, copyright notices etc., surrounding the main content of the web page. Hence, tools for the mining of data regions, data records and data items need to be developed in order to provide value-added services. Currently available automatic techniques to mine data regions from web pages are still unsatisfactory because of their poor performance and tag-dependence. In this paper a novel method to extract data items from the web pages automatically is proposed. It comprises of two steps: (1) Identification and Extraction of the data regions based on visual clues information. (2) Identification of data records and extraction of data items from a data region. For step1, a novel and more effective method is proposed based on visual clues, which finds the data regions formed by all types of tags using visual clues. For step2 a more effective method namely, Extraction of Data Items from web Pages (EDIP), is adopted to mine data items. The EDIP technique is a list-based approach in which the list is a linear data structure. The proposed technique is able to mine the non-contiguous data records and can correctly identify data regions, irrespective of the type of tag in which it is bound. Our experimental results show that the proposed technique performs better than the existing techniques.
Abstract: Because of increasing demands for security in today-s
society and also due to paying much more attention to machine
vision, biometric researches, pattern recognition and data retrieval in
color images, face detection has got more application. In this article
we present a scientific approach for modeling human skin color, and
also offer an algorithm that tries to detect faces within color images
by combination of skin features and determined threshold in the
model. Proposed model is based on statistical data in different color
spaces. Offered algorithm, using some specified color threshold, first,
divides image pixels into two groups: skin pixel group and non-skin
pixel group and then based on some geometric features of face
decides which area belongs to face.
Two main results that we received from this research are as follow:
first, proposed model can be applied easily on different databases and
color spaces to establish proper threshold. Second, our algorithm can
adapt itself with runtime condition and its results demonstrate
desirable progress in comparison with similar cases.
Abstract: Internet infrastructures in most places of the world
have been supported by the advancement of optical fiber technology,
most notably wavelength division multiplexing (WDM) system.
Optical technology by means of WDM system has revolutionized
long distance data transport and has resulted in high data capacity,
cost reductions, extremely low bit error rate, and operational
simplification of the overall Internet infrastructure. This paper
analyses and compares the system impairments, which occur at data
transmission rates of 2.5Gb/s and 10 Gb/s per wavelength channel in
our proposed optical WDM system for Internet infrastructure in
Tanzania. The results show that the data transmission rate of 2.5 Gb/s
has minimum system impairments compared with a rate of 10 Gb/s
per wavelength channel, and achieves a sufficient system
performance to provide a good Internet access service.
Abstract: The sanitary sewerage connection rate becomes an
important indicator of advanced cities. Following the construction of
sanitary sewerages, the maintenance and management systems are
required for keeping pipelines and facilities functioning well. These
maintenance tasks often require sewer workers to enter the manholes
and the pipelines, which are confined spaces short of natural
ventilation and full of hazardous substances. Working in sewers could
be easily exposed to a risk of adverse health effects. This paper
proposes the use of Bayesian belief networks (BBN) as a higher level
of noncarcinogenic health risk assessment of sewer workers. On the
basis of the epidemiological studies, the actual hospital attendance
records and expert experiences, the BBN is capable of capturing the
probabilistic relationships between the hazardous substances in sewers
and their adverse health effects, and accordingly inferring the
morbidity and mortality of the adverse health effects. The provision of
the morbidity and mortality rates of the related diseases is more
informative and can alleviate the drawbacks of conventional methods.
Abstract: SDMA (Space-Division Multiple Access) is a MIMO
(Multiple-Input and Multiple-Output) based wireless communication
network architecture which has the potential to significantly increase
the spectral efficiency and the system performance. The maximum
likelihood (ML) detection provides the optimal performance, but its
complexity increases exponentially with the constellation size of
modulation and number of users. The QR decomposition (QRD)
MUD can be a substitute to ML detection due its low complexity and
near optimal performance. The minimum mean-squared-error
(MMSE) multiuser detection (MUD) minimises the mean square
error (MSE), which may not give guarantee that the BER of the
system is also minimum. But the minimum bit error rate (MBER)
MUD performs better than the classic MMSE MUD in term of
minimum probability of error by directly minimising the BER cost
function. Also the MBER MUD is able to support more users than
the number of receiving antennas, whereas the rest of MUDs fail in
this scenario. In this paper the performance of various MUD
techniques is verified for the correlated MIMO channel models based
on IEEE 802.16n standard.
Abstract: The adaptive power control of Code Division Multiple
Access (CDMA) communications using Remote Radio Head
(RRH) between multiple Unmanned Aerial Vehicles (UAVs) with
a link-budget based Signal-to-Interference Ratio (SIR) estimate is
applied to four inner loop power control algorithms. It is concluded
that Base Station (BS) can calculate not only UAV distance using
linearity between speed and Consecutive Transmit-Power-Control
Ratio (CTR) of Adaptive Step-size Closed Loop Power Control (ASCLPC),
Consecutive TPC Ratio Step-size Closed Loop Power Control
(CS-CLPC), Fixed Step-size Power Control (FSPC), but also UAV
position with Received Signal Strength Indicator (RSSI) ratio of
RRHs.
Abstract: Omni directional mobile robots have been popularly
employed in several applications especially in soccer player robots
considered in Robocup competitions. However, Omni directional
navigation system, Omni-vision system and solenoid kicking
mechanism in such mobile robots have not ever been combined. This
situation brings the idea of a robot with no head direction into
existence, a comprehensive Omni directional mobile robot. Such a
robot can respond more quickly and it would be capable for more
sophisticated behaviors with multi-sensor data fusion algorithm for
global localization base on the data fusion. This paper has tried to
focus on the research improvements in the mechanical, electrical and
software design of the robots of team ADRO Iran. The main
improvements are the world model, the new strategy framework,
mechanical structure, Omni-vision sensor for object detection, robot
path planning, active ball handling mechanism and the new kicker
design, , and other subjects related to mobile robot
Abstract: In this paper, we propose a robust face relighting
technique by using spherical space properties. The proposed method
is done for reducing the illumination effects on face recognition.
Given a single 2D face image, we relight the face object by
extracting the nine spherical harmonic bases and the face spherical
illumination coefficients. First, an internal training illumination
database is generated by computing face albedo and face normal
from 2D images under different lighting conditions. Based on the
generated database, we analyze the target face pixels and compare
them with the training bootstrap by using pre-generated tiles. In this
work, practical real time processing speed and small image size were
considered when designing the framework. In contrast to other works,
our technique requires no 3D face models for the training process
and takes a single 2D image as an input. Experimental results on
publicly available databases show that the proposed technique works
well under severe lighting conditions with significant improvements
on the face recognition rates.
Abstract: The objective of this research was to study the themes
of alcoholic beverage advertisements in Thailand after the enactment
of the 2008 Alcoholic Beverage Control Act. Data was collected
through textual analysis of 35 television and cinema advertisements
for alcoholic beverage products broadcast in Thailand. Nine themes
were identified, seven of which were themes that had previously been
used before the new law (i.e. power, competition, friendship,
Thainess, success, romance and safety) and two of which were new
themes (volunteerism and conservation) that were introduced as a
form of adaptation and negotiation in response to the new law.
Abstract: Imprecision is a long-standing problem in CAD design
and high accuracy image-based reconstruction applications. The visual
hull which is the closed silhouette equivalent shape of the objects
of interest is an important concept in image-based reconstruction.
We extend the domain-theoretic framework, which is a robust and
imprecision capturing geometric model, to analyze the imprecision in
the output shape when the input vertices are given with imprecision.
Under this framework, we show an efficient algorithm to generate the
2D partial visual hull which represents the exact information of the
visual hull with only basic imprecision assumptions. We also show
how the visual hull from polyhedra problem can be efficiently solved
in the context of imprecise input.
Abstract: The main objective of this study was to determine if a
minimal increase in road light level (luminance) could lead to
improved driving performance among older adults. Older, middleaged
and younger adults were tested in a driving simulator following
vision and cognitive screening. Comparisons were made for the
performance of simulated night driving under two road light
conditions (0.6 and 2.5 cd/m2). At each light level, the effects of self
reported night driving avoidance were examined along with the
vision/cognitive performance. It was found that increasing road light
level from 0.6 cd/m2 to 2.5 cd/m2 resulted in improved recognition of
signage on straight highway segments. The improvement depends on
different driver-related factors such as vision and cognitive abilities,
and confidence. On curved road sections, the results showed that
driver-s performance worsened. It is concluded that while increasing
road lighting may be helpful to older adults especially for sign
recognition, it may also result in increased driving confidence and
thus reduced attention in some driving situations.
Abstract: In this paper, we present an improved fast and robust
search algorithm for copy detection using histogram-based features for
short MPEG video clips from large video database. There are two
types of histogram features used to generate more robust features. The
first one is based on the adjacent pixel intensity difference quantization
(APIDQ) algorithm, which had been reliably applied to human face
recognition previously. An APIDQ histogram is utilized as the feature
vector of the frame image. Another one is ordinal histogram feature
which is robust to color distortion. Furthermore, by Combining with a
temporal division method, the spatial and temporal features of the
video sequence are integrated to realize fast and robust video search
for copy detection. Experimental results show the proposed algorithm
can detect the similar video clip more accurately and robust than
conventional fast video search algorithm.
Abstract: A complex valued neural network is a neural network, which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in image and vision processing. In Neural networks, radial basis functions are often used for interpolation in multidimensional space. A Radial Basis function is a function, which has built into it a distance criterion with respect to a centre. Radial basis functions have often been applied in the area of neural networks where they may be used as a replacement for the sigmoid hidden layer transfer characteristic in multi-layer perceptron. This paper aims to present exhaustive results of using RBF units in a complex-valued neural network model that uses the back-propagation algorithm (called 'Complex-BP') for learning. Our experiments results demonstrate the effectiveness of a Radial basis function in a complex valued neural network in image recognition over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error on a neural network model with RBF units. Some inherent properties of this complex back propagation algorithm are also studied and discussed.
Abstract: In this paper, we propose an improved fast search
algorithm using combined histogram features and temporal division
method for short MPEG video clips from large video database. There
are two types of histogram features used to generate more robust
features. The first one is based on the adjacent pixel intensity
difference quantization (APIDQ) algorithm, which had been reliably
applied to human face recognition previously. An APIDQ histogram is
utilized as the feature vector of the frame image. Another one is
ordinal feature which is robust to color distortion. Combined with
active search [4], a temporal pruning algorithm, fast and robust video
search can be realized. The proposed search algorithm has been
evaluated by 6 hours of video to search for given 200 MPEG video
clips which each length is 30 seconds. Experimental results show the
proposed algorithm can detect the similar video clip in merely 120ms,
and Equal Error Rate (ERR) of 1% is achieved, which is more
accurately and robust than conventional fast video search algorithm.
Abstract: Subdivision surfaces were applied to the entire
meshes in order to produce smooth surfaces refinement from coarse
mesh. Several schemes had been introduced in this area to provide a
set of rules to converge smooth surfaces. However, to compute and
render all the vertices are really inconvenient in terms of memory
consumption and runtime during the subdivision process. It will lead
to a heavy computational load especially at a higher level of
subdivision. Adaptive subdivision is a method that subdivides only at
certain areas of the meshes while the rest were maintained less
polygons. Although adaptive subdivision occurs at the selected areas,
the quality of produced surfaces which is their smoothness can be
preserved similar as well as regular subdivision. Nevertheless,
adaptive subdivision process burdened from two causes; calculations
need to be done to define areas that are required to be subdivided and
to remove cracks created from the subdivision depth difference
between the selected and unselected areas. Unfortunately, the result
of adaptive subdivision when it reaches to the higher level of
subdivision, it still brings the problem with memory consumption.
This research brings to iterative process of adaptive subdivision to
improve the previous adaptive method that will reduce memory
consumption applied on triangular mesh. The result of this iterative
process was acceptable better in memory and appearance in order to
produce fewer polygons while it preserves smooth surfaces.
Abstract: An algorithm for estimating the disparity of objects of
interest is proposed. This algorithm uses image shifting and
overlapping area to estimate the disparity value; thereby depth of the
objects of interest can be obtained. The algorithm is able to perform
at different levels of accuracy. However, as the accuracy increases
the processing speed decreases. The algorithm is tested with static
stereo images and sequence of stereo images. The experimental
results are presented in this paper.
Abstract: In this paper we propose an enhanced equalization technique for multi-carrier code division multiple access (MC-CDMA). This method is based on the control of Equal Gain Combining (EGC) technique. Indeed, we introduce a new level changer to the EGC equalizer in order to adapt the equalization parameters to the channel coefficients. The optimal equalization level is, first, determined by channel training. The new approach reduces drastically the mutliuser interferences caused by interferes, without increasing the noise power. To compare the performances of the proposed equalizer, the theoretical analysis and numerical performances are given.