Abstract: The rapid expansion of the web is causing the
constant growth of information, leading to several problems such as
increased difficulty of extracting potentially useful knowledge. Web
content mining confronts this problem gathering explicit information
from different web sites for its access and knowledge discovery.
Query interfaces of web databases share common building blocks.
After extracting information with parsing approach, we use a new
data mining algorithm to match a large number of schemas in
databases at a time. Using this algorithm increases the speed of
information matching. In addition, instead of simple 1:1 matching,
they do complex (m:n) matching between query interfaces. In this
paper we present a novel correlation mining algorithm that matches
correlated attributes with smaller cost. This algorithm uses Jaccard
measure to distinguish positive and negative correlated attributes.
After that, system matches the user query with different query
interfaces in special domain and finally chooses the nearest query
interface with user query to answer to it.
Abstract: This paper presents a general trainable framework
for fast and robust upright human face and non-human object
detection and verification in static images. To enhance the
performance of the detection process, the technique we develop is
based on the combination of fast neural network (FNN) and
classical neural network (CNN). In FNN, a useful correlation is
exploited to sustain high level of detection accuracy between input
image and the weight of the hidden neurons. This is to enable the
use of Fourier transform that significantly speed up the time
detection. The combination of CNN is responsible to verify the
face region. A bootstrap algorithm is used to collect non human
object, which adds the false detection to the training process of the
human and non-human object. Experimental results on test images
with both simple and complex background demonstrate that the
proposed method has obtained high detection rate and low false
positive rate in detecting both human face and non-human object.
Abstract: Resource discovery is one of the chief services of a grid. A new approach to discover the provenances in grid through learning automata has been propounded in this article. The objective of the aforementioned resource-discovery service is to select the resource based upon the user-s applications and the mercantile yardsticks that is to say opting for an originator which can accomplish the user-s tasks in the most economic manner. This novel service is submitted in two phases. We proffered an applicationbased categorization by means of an intelligent nerve-prone plexus. The user in question sets his or her application as the input vector of the nerve-prone nexus. The output vector of the aforesaid network limns the appropriateness of any one of the resource for the presented executive procedure. The most scrimping option out of those put forward in the previous stage which can be coped with to fulfill the task in question is picked out. Te resource choice is carried out by means of the presented algorithm based upon the learning automata.
Abstract: A logic model for analyzing complex systems- stability
is very useful to many areas of sciences. In the real world, we are
enlightened from some natural phenomena such as “biosphere", “food
chain", “ecological balance" etc. By research and practice, and taking
advantage of the orthogonality and symmetry defined by the theory of
multilateral matrices, we put forward a logic analysis model of
stability of complex systems with three relations, and prove it by
means of mathematics. This logic model is usually successful in
analyzing stability of a complex system. The structure of the logic
model is not only clear and simple, but also can be easily used to
research and solve many stability problems of complex systems. As an
application, some examples are given.
Abstract: In the present work, an attempt has been made to
understand the feasibility of using UHF technique for identification
of any corona discharges/ arcing in insulating material due to water
droplets. The sensors of broadband type are useful for identification
of such discharges. It is realised that arcing initiated by liquid droplet
radiates UHF signals in the entire bandwidth up to 2 GHz. The
frequency content of the UHF signal generated due to corona/arcing
is not much varied in epoxy nanocomposites with different weight
percentage of clay content. The exfoliated/intercalated properties
were analysed through TEM studies. It is realized that corona
initiated discharges are of intermittent process. The hydrophobicity
of the material characterized through contact angle measurement. It
is realized that low Wt % of nanoclay content in epoxy resin reduces
the surface carbonization due to arcing/corona discharges. The results
of the study with gamma irradiated specimen indicates that contact
angle, discharge inception time and evaporation time of the liquid are
much lower than the virgin epoxy nanocomposite material.
Abstract: Large full frequency band gaps of surface and bulk
acoustic waves in two-dimensional phononic band structures with
hollow cylinders are addressed in this paper. It is well-known that
absolute frequency band gaps are difficultly obtained in a band
structure consisted of low-acoustic-impedance cylinders in
high-acoustic-impedance host materials such as PMMA/Ni band
structures. Phononic band structures with hollow cylinders are
analyzed and discussed to obtain large full frequency band gaps not
only for bulk modes but also for surface modes. The tendency of
absolute frequency band gaps of surface and bulk acoustic waves is
also addressed by changing the inner radius of hollow cylinders in this
paper. The technique and this kind of band structure are useful for
tuning the frequency band gaps and the design of acoustic waveguides.
Abstract: Cluster analysis divides data into groups that are
meaningful, useful, or both. Analysis of biological data is creating a
new generation of epidemiologic, prognostic, diagnostic and
treatment modalities. Clustering of protein sequences is one of the
current research topics in the field of computer science. Linear
relation is valuable in rule discovery for a given data, such as if value
X goes up 1, value Y will go down 3", etc. The classical linear
regression models the linear relation of two sequences perfectly.
However, if we need to cluster a large repository of protein sequences
into groups where sequences have strong linear relationship with
each other, it is prohibitively expensive to compare sequences one by
one. In this paper, we propose a new technique named General
Regression Model Technique Clustering Algorithm (GRMTCA) to
benignly handle the problem of linear sequences clustering. GRMT
gives a measure, GR*, to tell the degree of linearity of multiple
sequences without having to compare each pair of them.
Abstract: This paper presents the development of a software
application for Off-line robot task programming and simulation. Such
application is designed to assist in robot task planning and to direct
manipulator motion on sensor based programmed motion. The
concept of the designed programming application is to use the power
of the knowledge base for task accumulation. In support of the
programming means, an interactive graphical simulation for
manipulator kinematics was also developed and integrated into the
application as the complimentary factor to the robot programming
media. The simulation provides the designer with useful,
inexpensive, off-line tools for retain and testing robotics work cells
and automated assembly lines for various industrial applications.
Abstract: Full adders are important components in applications
such as digital signal processors (DSP) architectures and
microprocessors. In addition to its main task, which is adding two
numbers, it participates in many other useful operations such as
subtraction, multiplication, division,, address calculation,..etc. In
most of these systems the adder lies in the critical path that
determines the overall speed of the system. So enhancing the
performance of the 1-bit full adder cell (the building block of the
adder) is a significant goal.Demands for the low power VLSI have
been pushing the development of aggressive design methodologies to
reduce the power consumption drastically. To meet the growing
demand, we propose a new low power adder cell by sacrificing the
MOS Transistor count that reduces the serious threshold loss
problem, considerably increases the speed and decreases the power
when compared to the static energy recovery full (SERF) adder. So a
new improved 14T CMOS l-bit full adder cell is presented in this
paper. Results show 50% improvement in threshold loss problem,
45% improvement in speed and considerable power consumption
over the SERF adder and other different types of adders with
comparable performance.
Abstract: Despite the availability of natural disaster related time series data for last 110 years, there is no forecasting tool available to humanitarian relief organizations to determine forecasts for emergency logistics planning. This study develops a forecasting tool based on identifying probability distributions. The estimates of the parameters are used to calculate natural disaster forecasts. Further, the determination of aggregate forecasts leads to efficient pre-disaster planning. Based on the research findings, the relief agencies can optimize the various resources allocation in emergency logistics planning.
Abstract: In this work we present some matrix operators named
circulant operators and their action on square matrices. This study on
square matrices provides new insights into the structure of the space
of square matrices. Moreover it can be useful in various fields as in
agents networking on Grid or large-scale distributed self-organizing
grid systems.
Abstract: This paper presents a solution for ceramic cutting tools availability in interrupted machining. Experiments were performed on a special fixture – the interrupted cut simulator. This fixture was constructed at our Department of Machining and Assembly within the scope of a project by the Czech Science Foundation. The goals of the tests were to contribute to the wider usage of these cutting materials in machining, especially in interrupted machining. Through the centuries, producers of ceramic cutting tools have taken big steps forward. Namely, increasing durability in maintaining high levels of strength and hardness lends an advantage. Some producers of these materials advise cutting inserts for interrupted machining at the present time [1, 2].
Abstract: In order to accommodate various multimedia
services, next generation wireless networks are characterized
by very high transmission bit rates. Thus, in such systems and
networks, the received signal is not only limited by noise but -
especially with increasing symbols rate often more
significantly by the intersymbol interference (ISI) caused by
the time dispersive radio channels such as those are used in
this work. This paper deals with the study of the performance
of detector for high bit rate transmission on some worst case
models of frequency selective fading channels for outdoor
mobile radio environments. This paper deals with a number of
different wireless channels with different power profiles and
different number of resolvable paths. All the radio channels
generated in this paper are for outdoor vehicular environments
with Doppler spread of 100 Hz. A carrier frequency of 1800
MHz is used and all the channels used in this work are such
that they are useful for next generation wireless systems.
Schemes for mitigation of ISI with adaptive equalizers of
different types have been investigated and their performances
have been investigated in terms of BER measured as a function
of SNR.
Abstract: Previous researches found that conventional WBL is effective for meaningful learner, because rote learner learn by repeating without thinking or trying to understand. It is impossible to have full benefit from conventional WBL. Understanding of rote learner-s intention and what influences it becomes important. Poorly designed user interface will discourage rote learner-s cultivation and intention to use WBL. Thus, user interface design is an important factor especially when WBL is used as comprehensive replacement of conventional teaching. This research proposes the influencing factors that can enhance learner-s intention to use the system. The enhanced TAM is used for evaluating the proposed factors. The research result points out that factors influencing rote learner-s intention are Perceived Usefulness of Homepage Content Structure, Perceived User Friendly Interface, Perceived Hedonic Component, and Perceived (homepage) Visual Attractiveness.
Abstract: As the latest advancement and trend in IT field, Green
& Smart IT has attracted more and more attentions from researchers.
This study focuses on the development of assessing tools which can be
used for evaluating Green & Smart IT level within an organization. In
order to achieve meaningful results, a comprehensive review of
relevant literature was performed in advance, then, Delphi survey and
other processes were also employed to develop the assessment tools
for Green & Smart IT level. Two rounds of Delphi questionnaire
survey were conducted with 20 IT experts in public sector. The results
reveal that the top five weighted KPIs to evaluate maturity of Green &
Smart IT were: (1) electronic execution of business process; (2)
shutdown of unused IT devices; (3) virtualization of severs; (4)
automation of constant temperature and humidity; and (5) introduction
of smart-work system. Finally, these tools were applied to case study
of a public research institute in Korea. The findings presented in this
study provide organizations with useful implications for the
introduction and promotion of Green & Smart IT in the future
Abstract: This paper aims to fabricated high quality anodic
aluminum oxide (AAO) film by anodization method. AAO pore size,
pore density, and film thickness can be controlled in 10~500 nm,
108~1011 pore．cm-2, and 1~100 μm. AAO volume and surface area can
be computed based on structural parameters such as thickness, pore
size, pore density, and sample size. Base on the thetorical calculation,
AAO has 100 μm thickness with 15 nm, 60 nm, and 500 nm pore
diameters AAO surface areas are 1225.2 cm2, 3204.4 cm2, and 549.7
cm2, respectively. The large unit surface area which is useful for
adsorption application. When AAO adsorbed pH indictor of
bromphenol blue presented a sensitive pH detection of solution
change. This testing method can further be used for the precise
measurement of biotechnology, convenience measurement of
industrial engineering.
Abstract: A business case is a proposal for an investment
initiative to satisfy business and functional requirements. The
business case provides the foundation for tactical decision making
and technology risk management. It helps to clarify how the
organization will use its resources in the best way by providing
justification for investment of resources. This paper describes how
simulation was used for business case benefits and return on
investment for the procurement of 8 production machines. With
investment costs of about 4.7 million dollars and annual operating
costs of about 1.3 million, we needed to determine if the machines
would provide enough cost savings and cost avoidance. We
constructed a model of the existing factory environment consisting of
8 machines and subsequently, we conducted average day simulations
with light and heavy volumes to facilitate planning decisions
required to be documented and substantiated in the business case.
Abstract: In this paper we compare the accuracy of data mining
methods to classifying students in order to predicting student-s class
grade. These predictions are more useful for identifying weak
students and assisting management to take remedial measures at early
stages to produce excellent graduate that will graduate at least with
second class upper. Firstly we examine single classifiers accuracy on
our data set and choose the best one and then ensembles it with a
weak classifier to produce simple voting method. We present results
show that combining different classifiers outperformed other single
classifiers for predicting student performance.
Abstract: This study retrospectively investigated the significance of whole body CT (WCT) for patients with sepsis. A medical chart review was retrospectively performed for all patients with systemic inflammatory response syndrome that were treated initially between April 2011 and March 2012. The subjects were divided into a WCT group that underwent WCT on arrival and a control group. Results of this study suggested that WCT for sepsis was useful for elderly patients whose chief complaint or physiological findings could not suggest the anatomical site of infection, to determine the infectious focus and indications/method for surgery, to diagnose the basic diseases associated with opportunistic infections and to evaluate complicated diseases
Abstract: The goal of this paper is to segment the countries
based on the value of export from Iran during 14 years ending at 2005. To measure the dissimilarity among export baskets of different countries, we define Dissimilarity Export Basket (DEB) function and
use this distance function in K-means algorithm. The DEB function
is defined based on the concepts of the association rules and the
value of export group-commodities. In this paper, clustering quality
function and clusters intraclass inertia are defined to, respectively,
calculate the optimum number of clusters and to compare the
functionality of DEB versus Euclidean distance. We have also study
the effects of importance weight in DEB function to improve
clustering quality. Lastly when segmentation is completed, a
designated RFM model is used to analyze the relative profitability of
each cluster.