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: This research aims at development of the Multiple
Intelligences Measurement of Elementary Students. The structural
accuracy test and normality establishment are based on the Multiple
Intelligences Theory of Gardner. This theory consists of eight aspects
namely linguistics, logic and mathematics, visual-spatial relations,
body and movement, music, human relations, self-realization/selfunderstanding
and nature. The sample used in this research consists
of elementary school students (aged between 5-11 years). The size of
the sample group was determined by Yamane Table. The group has
2,504 students. Multistage Sampling was used. Basic statistical
analysis and construct validity testing were done using confirmatory
factor analysis. The research can be summarized as follows; 1.
Multiple Intelligences Measurement consisting of 120 items is
content-accurate. Internal consistent reliability according to the
method of Kuder-Richardson of the whole Multiple Intelligences
Measurement equals .91. The difficulty of the measurement test is
between .39-.83. Discrimination is between .21-.85. 2). The Multiple
Intelligences Measurement has construct validity in a good range,
that is 8 components and all 120 test items have statistical
significance level at .01. Chi-square value equals 4357.7; p=.00 at the
degree of freedom of 244 and Goodness of Fit Index equals 1.00.
Adjusted Goodness of Fit Index equals .92. Comparative Fit Index
(CFI) equals .68. Root Mean Squared Residual (RMR) equals 0.064
and Root Mean Square Error of Approximation equals 0.82. 3). The
normality of the Multiple Intelligences Measurement is categorized
into 3 levels. Those with high intelligence are those with percentiles
of more than 78. Those with moderate/medium intelligence are those
with percentiles between 24 and 77.9. Those with low intelligence
are those with percentiles from 23.9 downwards.
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: A new fuzzy filter is presented for noise reduction of
images corrupted with additive noise. The filter consists of two
stages. In the first stage, all the pixels of image are processed for
determining noisy pixels. For this, a fuzzy rule based system
associates a degree to each pixel. The degree of a pixel is a real
number in the range [0,1], which denotes a probability that the pixel
is not considered as a noisy pixel. In the second stage, another fuzzy
rule based system is employed. It uses the output of the previous
fuzzy system to perform fuzzy smoothing by weighting the
contributions of neighboring pixel values. Experimental results are
obtained to show the feasibility of the proposed filter. These results
are also compared to other filters by numerical measure and visual
inspection.
Abstract: Early detection of lung cancer through chest radiography is a widely used method due to its relatively affordable cost. In this paper, an approach to improve lung nodule visualization on chest radiographs is presented. The approach makes use of linear phase high-frequency emphasis filter for digital filtering and
histogram equalization for contrast enhancement to achieve improvements. Results obtained indicate that a filtered image can
reveal sharper edges and provide more details. Also, contrast enhancement offers a way to further enhance the global (or local) visualization by equalizing the histogram of the pixel values within
the whole image (or a region of interest). The work aims to improve lung nodule visualization of chest radiographs to aid detection of lung cancer which is currently the leading cause of cancer deaths worldwide.
Abstract: In this study Vitaton (an organic supplement which
contains fermentative β-carotene) and synthetic astaxanthin
(CAROPHYLL® Pink) were evaluated as pro-growth factors in
Rainbow trout diet. An 8 week feeding trial was conducted to
determine the effects of Vitaton versus astaxanthin on rearing factors,
survival rate and visual flesh color of Rainbow trout
(Oncorhnchynchus mykiss) with initial weight of 196±5. Four
practical diets were formulated to contain 50 and 80 (ppm) of β-
carotene and astaxanthin and also a control diet was prepared without
any pigment. Each diet was fed to triplicate groups of fish rearing in
fresh water. Fish were fed twice daily. The water temperature
fluctuated from 12 to 15 (C˚) and also dissolved oxygen content was
between 7 to 7.5 (mg/lit) during the experimental period. At the end
of the experiment, growth and food utilization parameters and
survival rate were unaffected by dietary treatments (p>0.05). Also,
there was no significant difference between carcass yield within
treatments (p>0.05). No significant difference recognized between
visual flesh color (SalmoFan score) of fish fed Vitaton-containing
diets. On the contrary, feeding on diets containing 50 and 80 (ppm)
of astaxanthin, increased SalmoFan score (flesh astaxanthin
concentration) from
Abstract: In this paper, we present a novel technique called Self-Learning Expert System (SLES). Unlike Expert System, where there is a need for an expert to impart experiences and knowledge to create the knowledge base, this technique tries to acquire the experience and knowledge automatically. To display this technique at work, a simulation of a mobile robot navigating through an environment with obstacles is employed using visual basic. The mobile robot will move through this area without colliding with any obstacle and save the path that it took. If the mobile robot has to go through a similar environment again, then it will apply this experience to help it move through quicker without having to check for collision.
Abstract: Nowadays scientific data is inevitably digital and
stored in a wide variety of formats in heterogeneous systems.
Scientists need to access an integrated view of remote or local
heterogeneous data sources with advanced data accessing, analyzing,
and visualization tools. This research suggests the use of Service
Oriented Architecture (SOA) to integrate biological data from
different data sources. This work shows SOA will solve the problems
that facing integration process and if the biologist scientists can
access the biological data in easier way. There are several methods to
implement SOA but web service is the most popular method. The
Microsoft .Net Framework used to implement proposed architecture.
Abstract: Supply Chain Management (SCM) is the integration
between manufacturer, transporter and customer in order to form one
seamless chain that allows smooth flow of raw materials, information
and products throughout the entire network that help in minimizing
all related efforts and costs. The main objective of this paper is to
develop a model that can accept a specified number of spare-parts
within the supply chain, simulating its inventory operations
throughout all stages in order to minimize the inventory holding
costs, base-stock, safety-stock, and to find the optimum quantity of
inventory levels, thereby suggesting a way forward to adapt some
factors of Just-In-Time to minimizing the inventory costs throughout
the entire supply chain. The model has been developed using Micro-
Soft Excel & Visual Basic in order to study inventory allocations in
any network of the supply chain. The application and reproducibility
of this model were tested by comparing the actual system that was
implemented in the case study with the results of the developed
model. The findings showed that the total inventory costs of the
developed model are about 50% less than the actual costs of the
inventory items within the case study.
Abstract: Protection and proper management of archaeological heritage are an essential process of studying and interpreting the generations present and future. Protecting the archaeological heritage is based upon multidiscipline professional collaboration. This study aims to gather data by different sources (Photogrammetry and Geographic Information System (GIS)) integrated for the purpose of documenting one the of significant archeological sites (Ahl-Alkahf, Jordan). 3D modeling deals with the actual image of the features, shapes and texture to represent reality as realistically as possible by using texture. The 3D coordinates that result of the photogrammetric adjustment procedures are used to create 3D-models of the study area. Adding Textures to the 3D-models surfaces gives a 'real world' appearance to the displayed models. GIS system combined all data, including boundary maps, indicating the location of archeological sites, transportation layer, digital elevation model and orthoimages. For realistic representation of the study area, 3D - GIS model prepared, where efficient generation, management and visualization of such special data can be achieved.
Abstract: Traditional higher-education classrooms allow lecturers to observe students- behaviours and responses to a particular pedagogy during learning in a way that can influence changes to the pedagogical approach. Within current e-learning systems it is difficult to perform continuous analysis of the cohort-s behavioural tendency, making real-time pedagogical decisions difficult. This paper presents a Virtual Learning Process Environment (VLPE) based on the Business Process Management (BPM) conceptual framework. Within the VLPE, course designers can model various education pedagogies in the form of learning process workflows using an intuitive flow diagram interface. These diagrams are used to visually track the learning progresses of a cohort of students. This helps assess the effectiveness of the chosen pedagogy, providing the information required to improve course design. A case scenario of a cohort of students is presented and quantitative statistical analysis of their learning process performance is gathered and displayed in realtime using dashboards.
Abstract: The design of a pattern classifier includes an attempt
to select, among a set of possible features, a minimum subset of
weakly correlated features that better discriminate the pattern classes.
This is usually a difficult task in practice, normally requiring the
application of heuristic knowledge about the specific problem
domain. The selection and quality of the features representing each
pattern have a considerable bearing on the success of subsequent
pattern classification. Feature extraction is the process of deriving
new features from the original features in order to reduce the cost of
feature measurement, increase classifier efficiency, and allow higher
classification accuracy. Many current feature extraction techniques
involve linear transformations of the original pattern vectors to new
vectors of lower dimensionality. While this is useful for data
visualization and increasing classification efficiency, it does not
necessarily reduce the number of features that must be measured
since each new feature may be a linear combination of all of the
features in the original pattern vector. In this paper a new approach is
presented to feature extraction in which feature selection, feature
extraction, and classifier training are performed simultaneously using
a genetic algorithm. In this approach each feature value is first
normalized by a linear equation, then scaled by the associated weight
prior to training, testing, and classification. A knn classifier is used to
evaluate each set of feature weights. The genetic algorithm optimizes
a vector of feature weights, which are used to scale the individual
features in the original pattern vectors in either a linear or a nonlinear
fashion. By this approach, the number of features used in classifying
can be finely reduced.
Abstract: Experiments have been performed to investigate the radiation effects on mixed convection heat transfer for thermally developing airflow in vertical ducts with two differentially heated isothermal walls and two adiabatic walls. The investigation covers the Reynolds number Re = 800 to Re = 2900, heat flux varied from 256 W/m2 to 863 W/m2, hot wall temperature ranges from 27°C to 100 °C, aspect ratios 1 & 0.5 and the emissivity of internal walls are 0.05 and 0.85. In the present study, combined flow visualization was conducted to observe the flow patterns. The effect of surface temperature along the walls was studied to investigate the local Nusselt number variation within the duct. The result shows that flow condition and radiation significantly affect the total Nusselt number and tends to reduce the buoyancy condition.
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: On-line (near infrared) spectroscopy is widely used to support the operation of complex process systems. Information extracted from spectral database can be used to estimate unmeasured product properties and monitor the operation of the process. These techniques are based on looking for similar spectra by nearest neighborhood algorithms and distance based searching methods. Search for nearest neighbors in the spectral space is an NP-hard problem, the computational complexity increases by the number of points in the discrete spectrum and the number of samples in the database. To reduce the calculation time some kind of indexing could be used. The main idea presented in this paper is to combine indexing and visualization techniques to reduce the computational requirement of estimation algorithms by providing a two dimensional indexing that can also be used to visualize the structure of the spectral database. This 2D visualization of spectral database does not only support application of distance and similarity based techniques but enables the utilization of advanced clustering and prediction algorithms based on the Delaunay tessellation of the mapped spectral space. This means the prediction has not to use the high dimension space but can be based on the mapped space too. The results illustrate that the proposed method is able to segment (cluster) spectral databases and detect outliers that are not suitable for instance based learning algorithms.
Abstract: In recent years, there has been an increasing interest in using daylight to save energy in buildings. In tropical regions, daylighting is always an energy saver. On the other hand, daylight provides visual comfort. According to standards, it shows that many criteria should be taken into consideration in order to have daylight utilization and visual comfort. The current standard in Malaysia, MS 1525 does not provide sufficient guideline. Hence, more research is needed on daylight performance. If architects do not consider daylight design, it not only causes inconvenience in working spaces but also causes more energy consumption as well as environmental pollution. This research had surveyed daylight performance in 5 selected office buildings from different area of Malaysian through experimental method. Several parameters of daylight quality such as daylight factor, surface luminance and surface luminance ratio were measured in different rooms in each building. The result of this research demonstrated that most of the buildings were not designed for daylight utilization. Therefore, it is very important that architects follow the daylight design recommendation to reduce consumption of electric power for artificial lighting while the sufficient quality of daylight is available.
Abstract: An experimental investigation was performed on pulp
liquid flow in straight ducts with a square cross section. Fully
developed steady flow was visualized and the fiber concentration was
obtained using a light-section method developed by the author et al.
The obtained results reveal quantitatively, in a definite form, the
distribution of the fiber concentration. From the results and
measurements of pressure loss, it is found that the flow characteristics
of pulp liquid in ducts can be classified into five patterns. The
relationships among the distributions of mean and fluctuation of fiber
concentration, the pressure loss and the flow velocity are discussed,
and then the features for each pattern are extracted. The degree of
nonuniformity of the fiber concentration, which is indicated by the
standard deviation of its distribution, is decreased from 0.3 to 0.05
with an increase in the velocity of the tested pulp liquid from 0.4 to
0.8%.
Abstract: In this paper, we consider the problem of tracking
multiple maneuvering targets using switching multiple target motion
models. With this paper, we aim to contribute in solving the problem
of model-based body motion estimation by using data coming from
visual sensors. The Interacting Multiple Model (IMM) algorithm is
specially designed to track accurately targets whose state and/or
measurement (assumed to be linear) models changes during motion
transition. However, when these models are nonlinear, the IMM
algorithm must be modified in order to guarantee an accurate track.
In this paper we propose to avoid the Extended Kalman filter because
of its limitations and substitute it with the Unscented Kalman filter
which seems to be more efficient especially according to the
simulation results obtained with the nonlinear IMM algorithm (IMMUKF).
To resolve the problem of data association, the JPDA
approach is combined with the IMM-UKF algorithm, the derived
algorithm is noted JPDA-IMM-UKF.
Abstract: This paper proposes an alternative control mechanism
for an interactive Pan/Tilt/Zoom (PTZ) camera control system.
Instead of using a mouse or a joystick, the proposed mechanism
utilizes a Nintendo Wii remote and infrared (IR) sensor bar. The Wii
remote has buttons that allows the user to control the movement of a
PTZ camera through Bluetooth connectivity. In addition, the Wii
remote has a built-in motion sensor that allows the user to give
control signals to the PTZ camera through pitch and roll movement.
A stationary IR sensor bar, placed at some distance away opposite the
Wii remote, enables the detection of yaw movement. In addition, the
Wii remote-s built-in IR camera has the ability to detect its spatial
position, and thus generates a control signal when the user moves the
Wii remote. Some experiments are carried out and their performances
are compared with an industry-standard PTZ joystick.
Abstract: Noise contamination in a magnetic resonance (MR)
image could occur during acquisition, storage, and transmission in
which effective filtering is required to avoid repeating the MR
procedure. In this paper, an iterative asymmetrical triangle fuzzy
filter with moving average center (ATMAVi filter) is used to reduce
different levels of salt and pepper noise in a brain MR image. Besides
visual inspection on filtered images, the mean squared error (MSE) is
used as an objective measurement. When compared with the median
filter, simulation results indicate that the ATMAVi filter is effective
especially for filtering a higher level noise (such as noise density =
0.45) using a smaller window size (such as 3x3) when operated
iteratively or using a larger window size (such as 5x5) when operated
non-iteratively.