Abstract: This paper proposes a new technique for improving
the efficiency of software testing, which is based on a conventional
attempt to reduce test cases that have to be tested for any given
software. The approach utilizes the advantage of Regression Testing
where fewer test cases would lessen time consumption of the testing
as a whole. The technique also offers a means to perform test case
generation automatically. Compared to one of the techniques in the
literature where the tester has no option but to perform the test case
generation manually, the proposed technique provides a better
option. As for the test cases reduction, the technique uses simple
algebraic conditions to assign fixed values to variables (Maximum,
minimum and constant variables). By doing this, the variables values
would be limited within a definite range, resulting in fewer numbers
of possible test cases to process. The technique can also be used in
program loops and arrays.
Abstract: In this paper, an image adaptive, invisible digital
watermarking algorithm with Orthogonal Polynomials based
Transformation (OPT) is proposed, for copyright protection of digital
images. The proposed algorithm utilizes a visual model to determine
the watermarking strength necessary to invisibly embed the
watermark in the mid frequency AC coefficients of the cover image,
chosen with a secret key. The visual model is designed to generate a
Just Noticeable Distortion mask (JND) by analyzing the low level
image characteristics such as textures, edges and luminance of the
cover image in the orthogonal polynomials based transformation
domain. Since the secret key is required for both embedding and
extraction of watermark, it is not possible for an unauthorized user to
extract the embedded watermark. The proposed scheme is robust to
common image processing distortions like filtering, JPEG
compression and additive noise. Experimental results show that the
quality of OPT domain watermarked images is better than its DCT
counterpart.
Abstract: In this paper a hybrid technique of Genetic Algorithm
and Simulated Annealing (HGASA) is applied for Fractal Image
Compression (FIC). With the help of this hybrid evolutionary
algorithm effort is made to reduce the search complexity of matching
between range block and domain block. The concept of Simulated
Annealing (SA) is incorporated into Genetic Algorithm (GA) in order
to avoid pre-mature convergence of the strings. One of the image
compression techniques in the spatial domain is Fractal Image
Compression but the main drawback of FIC is that it involves more
computational time due to global search. In order to improve the
computational time along with acceptable quality of the decoded
image, HGASA technique has been proposed. Experimental results
show that the proposed HGASA is a better method than GA in terms
of PSNR for Fractal image Compression.
Abstract: Heterogeneous catalysis is vital for a number of
chemical, refinery and pollution control processes. The use of
catalyst pellets of hollow cylindrical shape provide several distinct
advantages over other common shapes, and can therefore help to
enhance conversion levels in reactors. A better utilization of the
catalytic material is probably most notable of these features due to
the absence of the pellet core, which helps to significantly lower the
effect of the internal transport resistance. This is reflected in the
enhancement of the effectiveness factor. For the case of the first order
irreversible kinetics, a substantial increase in the effectiveness factor
can be obtained by varying shape parameters. Important shape
parameters of a finite hollow cylinder are the ratio of the inside to the
outside radii (κ) and the height to the diameter ratio (γ). A high value
of κ the generally helps to enhance the effectiveness factor. On the
other hand, lower values of the effectiveness factors are obtained
when the dimension of the height and the diameter are comparable.
Thus, the departure of parameter γ from the unity favors higher
effectiveness factor. Since a higher effectiveness factor is a measure
of a greater utilization of the catalytic material, higher conversion
levels can be achieved using the hollow cylindrical pellets possessing
optimized shape parameters.
Abstract: In this study, three subtypes of influenza A viruses (pH1N1, H5N1 and H3N2) which naturally infected human were analyzed by bioinformatic approaches to find candidate human cellular miRNAs targeting viral genomes. There were 76 miRNAs targeting influenza A viruses. Among these candidates, 70 miRNAs were subtypes specifically targeting each subtype of influenza A virus including 21 miRNAs targeted subtype H1N1, 27 miRNAs targeted subtype H5N1 and 22 miRNAs targeted subtype H3N2. The remaining 6 miRNAs target on multiple subtypes of influenza A viruses. Uniquely, hsa-miR-3145 is the only one candidate miRNA targeting PB1 gene of all three subtypes. Obviously, most of the candidate miRNAs are targeting on polymerase complex genes (PB2, PB1 and PA) of influenza A viruses. This study predicted potential human miRNAs targeting on different subtypes of influenza A viruses which might be useful for inhibition of viral replication and for better understanding of the interaction between virus and host cell.
Abstract: We introduce a new interactive 3D simulator of ocular motion and expressions suitable for: (1) character animation applications to game design, film production, HCI (Human Computer Interface), conversational animated agents, and virtual reality; (2) medical applications (ophthalmic neurological and muscular pathologies: research and education); and (3) real time simulation of unconscious cognitive and emotional responses (for use, e.g., in psychological research). Using state-of-the-art computer animation technology we have modeled and rigged a physiologically accurate 3D model of the eyes, eyelids, and eyebrow regions and we have 'optimized' it for use with an interactive and web deliverable platform. In addition, we have realized a prototype device for realtime control of eye motions and expressions, including unconsciously produced expressions, for application as in (1), (2), and (3) above. The 3D simulator of eye motion and ocular expression is, to our knowledge, the most advanced/realistic available so far for applications in character animation and medical pedagogy.
Abstract: We investigate the sufficient condition under which each positive b-weakly compact operator is Dunford-Pettis. We also investigate the necessary condition on which each positive b-weakly compact operator is Dunford-Pettis. Necessary condition on which each positive b-weakly compact operator is weakly compact is also considered. We give the operator that is semi-compact, but it is not bweakly. We present a necessary and sufficient condition under which each positive semi-compact operator is b-weakly compact.
Abstract: Thousands of masters athletes participate
quadrennially in the World Masters Games (WMG), yet this cohort
of athletes remains proportionately under-investigated. Due to a
growing global obesity pandemic in context of benefits of physical
activity across the lifespan, the BMI trends for this unique population
was of particular interest. The nexus between health, physical
activity and aging is complex and has raised much interest in recent
times due to the realization that a multifaceted approach is necessary
in order to counteract the obesity pandemic. By investigating age
based trends within a population adhering to competitive sport at
older ages, further insight might be gleaned to assist in understanding
one of many factors influencing this relationship.BMI was derived
using data gathered on a total of 6,071 masters athletes (51.9% male,
48.1% female) aged 25 to 91 years ( =51.5, s =±9.7), competing at
the Sydney World Masters Games (2009). Using linear and loess
regression it was demonstrated that the usual tendency for prevalence
of higher BMI increasing with age was reversed in the sample. This
trend in reversal was repeated for both male and female only sub-sets
of the sample participants, indicating the possibility of improved
prevalence of BMI with increasing age for both the sample as a
whole and these individual sub-groups.This evidence of improved
classification in one index of health (reduced BMI) for masters
athletes (when compared to the general population) implies there are
either improved levels of this index of health with aging due to
adherence to sport or possibly the reduced BMI is advantageous and
contributes to this cohort adhering (or being attracted) to masters
sport at older ages.
Abstract: This paper describes the development of an
autonomous robot for painting the interior walls of buildings. The
robot consists of a painting arm with an end effector roller that scans
the walls vertically and a mobile platform to give horizontal feed to
paint the whole area of the wall. The painting arm has a planar twolink
mechanism with two joints. Joints are driven from a stepping
motor through a ball screw-nut mechanism. Four ultrasonic sensors
are attached to the mobile platform and used to maintain a certain
distance from the facing wall and to avoid collision with side walls.
When settled on adjusted distance from the wall, the controller starts
the painting process autonomously. Simplicity, relatively low weight
and short painting time were considered in our design. Different
modules constituting the robot have been separately tested then
integrated. Experiments have shown successfulness of the robot in its
intended tasks.
Abstract: Two different superhydrophobic surfaces were
elaborated and their oil repellency behavior was evaluated using
several liquid with different surface tension. A silicone rubber/SiO2
nanocomposite coated (A) on aluminum substrate by “spin-coating"
and the sample B was an anodized aluminum surface covered by
Teflon-like coating. A high static contact angle about ∼162° was
measured for two prepared surfaces on which the water droplet rolloff.
Scanning electron microscopy (SEM) showed the presence of
micro/nanostructures for both sample A and B similar to that of lotus
leaf.
However the sample A presented significantly different behaviour
of wettability against the low surface tension liquid. Sample A has
been wetted totally by oil (dodecan) droplet while sample B showed
oleophobic behaviour. Oleophobic property of Teflon like coating
can be contributed to the presence of CF2 and CF3 functional group
which was shown by XPS analysis.
Abstract: This paper tries to study the effect of geosynthetic inclusion on the improvement of the load-settlement characters of two layered soil. In addition, the effect of geogrid and geotextile in reduction of the required thickness of subbase layer in unpaved roads is studied. Considering the vast application of bearing ratio tests in road construction projects, this test is used in present investigation. Bearing ratio tests were performed on two layered soil including a granular soil layer at the top (as the subbase layer) and a weak clayey soil placed at the bottom (as the subgrade layer). These tests were performed for different conditions including unreinforced and reinforced by geogrid and geotextile and three thicknesses for top layer soil (subbase layer). In the reinforced condition the reinforcing element was placed on the interface of the top granular layer and the beneath clayey layer to study the separation effect of geosynthetics. In all tests the soils (both granular and clayey soil layers) were compacted according to optimum water content. At the end, the diagrams were plotted and were compared with each other. Furthermore, a comparison between geogrids and geotextiles behaviors on two layer soil is done in this paper. The results show an increase in compression strength of reinforced specimen in comparison with unreinforced soil sample. The effect of geosynthetic inclusion reduces by increasing the subbase thickness. In addition it was found that geogrids have more desirable behavior rather than geotextiles due to interlocking with the subbase layer aggregates.
Abstract: Wetting characteristics of reactive (Sn–0.7Cu solder)
and non– reactive (castor oil) wetting of liquids on Cu and Ag plated
Al substrates have been investigated. Solder spreading exhibited
capillary, gravity and viscous regimes. Oils did not exhibit noticeable
spreading regimes. Solder alloy showed better wettability on Ag
coated Al substrate compared to Cu plating. In the case of castor oil,
Cu coated Al substrate exhibited good wettability as compared to Ag
coated Al substrates. The difference in wettability during reactive
wetting of solder and non–reactive wetting of oils is attributed to the
change in the surface energies of Al substrates brought about by the
formation of intermetallic compounds (IMCs).
Abstract: Large volumes of fingerprints are collected and stored
every day in a wide range of applications, including forensics, access
control etc. It is evident from the database of Federal Bureau of
Investigation (FBI) which contains more than 70 million finger
prints. Compression of this database is very important because of this
high Volume. The performance of existing image coding standards
generally degrades at low bit-rates because of the underlying block
based Discrete Cosine Transform (DCT) scheme. Over the past
decade, the success of wavelets in solving many different problems
has contributed to its unprecedented popularity. Due to
implementation constraints scalar wavelets do not posses all the
properties which are needed for better performance in compression.
New class of wavelets called 'Multiwavelets' which posses more
than one scaling filters overcomes this problem. The objective of this
paper is to develop an efficient compression scheme and to obtain
better quality and higher compression ratio through multiwavelet
transform and embedded coding of multiwavelet coefficients through
Set Partitioning In Hierarchical Trees algorithm (SPIHT) algorithm.
A comparison of the best known multiwavelets is made to the best
known scalar wavelets. Both quantitative and qualitative measures of
performance are examined for Fingerprints.
Abstract: This research paper deals with the implementation of face recognition using neural network (recognition classifier) on low-resolution images. The proposed system contains two parts, preprocessing and face classification. The preprocessing part converts original images into blurry image using average filter and equalizes the histogram of those image (lighting normalization). The bi-cubic interpolation function is applied onto equalized image to get resized image. The resized image is actually low-resolution image providing faster processing for training and testing. The preprocessed image becomes the input to neural network classifier, which uses back-propagation algorithm to recognize the familiar faces. The crux of proposed algorithm is its beauty to use single neural network as classifier, which produces straightforward approach towards face recognition. The single neural network consists of three layers with Log sigmoid, Hyperbolic tangent sigmoid and Linear transfer function respectively. The training function, which is incorporated in our work, is Gradient descent with momentum (adaptive learning rate) back propagation. The proposed algorithm was trained on ORL (Olivetti Research Laboratory) database with 5 training images. The empirical results provide the accuracy of 94.50%, 93.00% and 90.25% for 20, 30 and 40 subjects respectively, with time delay of 0.0934 sec per image.
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: Interactions among proteins are the basis of various
life events. So, it is important to recognize and research protein
interaction sites. A control set that contains 149 protein molecules
were used here. Then 10 features were extracted and 4 sample sets
that contained 9 sliding windows were made according to features.
These 4 sample sets were calculated by Radial Basis Functional neutral
networks which were optimized by Particle Swarm Optimization
respectively. Then 4 groups of results were obtained. Finally, these 4
groups of results were integrated by decision fusion (DF) and Genetic
Algorithm based Selected Ensemble (GASEN). A better accuracy was
got by DF and GASEN. So, the integrated methods were proved to
be effective.
Abstract: With the globalized production and logistics
environment, the need for reducing the product development interval
and lead time, having a faster response to orders, conforming to quality
standards, fair tracking, and boosting information exchanging
activities with customers and partners, and coping with changes in the
management environment, manufacturers are in dire need of an
information management system in their manufacturing environments.
There are lots of information systems that have been designed to
manage the condition or operation of equipment in the field but
existing systems have a decentralized architecture, which is not
unified. Also, these systems cannot effectively handle the status data
extraction process upon encountering a problem related to protocols or
changes in the equipment or the setting. In this regard, this paper will
introduce a system for processing and saving the status info of
production equipment, which uses standard representation formats, to
enable flexible responses to and support for variables in the field
equipment. This system can be used for a variety of manufacturing and
equipment settings and is capable of interacting with higher-tier
systems such as MES.
Abstract: End milling process is one of the common metal
cutting operations used for machining parts in manufacturing
industry. It is usually performed at the final stage in manufacturing a
product and surface roughness of the produced job plays an
important role. In general, the surface roughness affects wear
resistance, ductility, tensile, fatigue strength, etc., for machined parts
and cannot be neglected in design. In the present work an
experimental investigation of end milling of aluminium alloy with
carbide tool is carried out and the effect of different cutting
parameters on the response are studied with three-dimensional
surface plots. An artificial neural network (ANN) is used to establish
the relationship between the surface roughness and the input cutting
parameters (i.e., spindle speed, feed, and depth of cut). The Matlab
ANN toolbox works on feed forward back propagation algorithm is
used for modeling purpose. 3-12-1 network structure having
minimum average prediction error found as best network architecture
for predicting surface roughness value. The network predicts surface
roughness for unseen data and found that the result/prediction is
better. For desired surface finish of the component to be produced
there are many different combination of cutting parameters are
available. The optimum cutting parameter for obtaining desired
surface finish, to maximize tool life is predicted. The methodology is
demonstrated, number of problems are solved and algorithm is coded
in Matlab®.
Abstract: This study examined the role of driving experience in hazard perception and categorization using traffic scene pictures. Specifically, young-inexperienced, moderately experienced and very experienced (taxi) drivers observed traffic scene pictures while connected to an eye tracking system and were asked to rate the level of hazardousness of each picture and to mention the three most prominent hazards in it. Target pictures included nine, nearly identical, pairs of pictures where one picture in each pair included an actual hazard as an additional element. Altogether, 22 areas of interest (AOIs) were predefined and included 13 potential hazards and 9 actual hazards. Data analysis included both verbal reports and eye scanning patterns of these AOIs. Generally, both experienced and taxi drivers noted a relatively larger number of potential hazards than young inexperienced drivers Thus, by relating to less salient potential hazards, experienced drivers have demonstrated a better situation model of the traffic environment.
Abstract: The Artificial immune systems algorithms are Meta
heuristic optimization method, which are used for clustering and
pattern recognition applications are abundantly. These algorithms in
multimodal optimization problems are more efficient than genetic
algorithms. A major drawback in these algorithms is their slow
convergence to global optimum and their weak stability can be
considered in various running of these algorithms. In this paper,
improved Artificial Immune System Algorithm is introduced for the
first time to overcome its problems of artificial immune system. That
use of the small size of a local search around the memory antibodies
is used for improving the algorithm efficiently. The credibility of the
proposed approach is evaluated by simulations, and it is shown that
the proposed approach achieves better results can be achieved
compared to the standard artificial immune system algorithms