Abstract: This paper discusses the undesirable charge transfer
through the parasitic capacitances of the input transistors in a
multi-inputs voltage sense amplifier. Its intrinsic rail-to-rail voltage
transitions at the output nodes inevitably disturb the input sides
through the capacitive coupling between the outputs and inputs. Then,
it can possible degrade the stabilities of the reference voltage levels.
Moreover, it becomes more serious in multi-channel systems by
altering them for other channels, and so degrades the linearity of the
overall systems. In order to alleviate the internal node voltage
transition, the internal node stabilization techniques are proposed. It
achieves 45% and 40% improvements for node stabilization and input
referred disturbance, respectively.
Abstract: The web’s increased popularity has included a huge
amount of information, due to which automated web page
classification systems are essential to improve search engines’
performance. Web pages have many features like HTML or XML
tags, hyperlinks, URLs and text contents which can be considered
during an automated classification process. It is known that Webpage
classification is enhanced by hyperlinks as it reflects Web page
linkages. The aim of this study is to reduce the number of features to
be used to improve the accuracy of the classification of web pages. In
this paper, a novel feature selection method using an improved
Particle Swarm Optimization (PSO) using principle of evolution is
proposed. The extracted features were tested on the WebKB dataset
using a parallel Neural Network to reduce the computational cost.
Abstract: Human motion capture has become one of the major
area of interest in the field of computer vision. Some of the major
application areas that have been rapidly evolving include the
advanced human interfaces, virtual reality and security/surveillance
systems. This study provides a brief overview of the techniques and
applications used for the markerless human motion capture, which
deals with analyzing the human motion in the form of mathematical
formulations. The major contribution of this research is that it
classifies the computer vision based techniques of human motion
capture based on the taxonomy, and then breaks its down into four
systematically different categories of tracking, initialization, pose
estimation and recognition. The detailed descriptions and the
relationships descriptions are given for the techniques of tracking and
pose estimation. The subcategories of each process are further
described. Various hypotheses have been used by the researchers in
this domain are surveyed and the evolution of these techniques have
been explained. It has been concluded in the survey that most
researchers have focused on using the mathematical body models for
the markerless motion capture.
Abstract: With increasingly more mobile health applications
appearing due to the popularity of smartphones, the possibility arises
that these data can be used to improve the medical diagnostic process,
as well as the overall quality of healthcare, while at the same time
lowering costs. However, as of yet there have been no reports of a
successful combination of patient-generated data from smartphones
with data from clinical routine. In this paper we describe how these
two types of data can be combined in a secure way without
modification to hospital information systems, and how they can
together be used in a medical expert system for automatic nutritional
classification and triage.
Abstract: In this paper, an analysis of some model order
reduction techniques is presented. A new hybrid algorithm for model
order reduction of linear time invariant systems is compared with the
conventional techniques namely Balanced Truncation, Hankel Norm
reduction and Dominant Pole Algorithm (DPA). The proposed hybrid
algorithm is known as Clustering Dominant Pole Algorithm (CDPA),
is able to compute the full set of dominant poles and its cluster center
efficiently. The dominant poles of a transfer function are specific
eigenvalues of the state space matrix of the corresponding dynamical
system. The effectiveness of this novel technique is shown through
the simulation results.
Abstract: Collection of storm water runoff and forcing it into the
groundwater is the need of the hour to sustain the ground water table.
However, the runoff entraps various types of sediments and other
floating objects whose removal are essential to avoid pollution of
ground water and blocking of pores of aquifer. However, it requires
regular cleaning and maintenance due to problem of clogging. To
evaluate the performance of filter system consisting of coarse sand
(CS), gravel (G) and pebble (P) layers, a laboratory experiment was
conducted in a rectangular column. The effect of variable thickness
of CS, G and P layers of the filtration unit of the recharge shaft on the
recharge rate and the sediment concentration of effluent water were
evaluated.
Medium sand (MS) of three particle sizes, viz. 0.150–0.300 mm
(T1), 0.300–0.425 mm (T2) and 0.425–0.600 mm of thickness 25 cm,
30 cm and 35 cm respectively in the top layer of the filter system and
having seven influent sediment concentrations of 250–3,000 mg/l
were used for experimental study. The performance was evaluated in
terms of recharge rates and clogging time. The results indicated that
100 % suspended solids were entrapped in the upper 10 cm layer of
MS, the recharge rates declined sharply for influent concentrations of
more than 1,000 mg/l. All treatments with higher thickness of MS
media indicated recharge rate slightly more than that of all treatment
with lower thickness of MS media respectively. The performance of
storm water infiltration systems was highly dependent on the
formation of a clogging layer at the filter. An empirical relationship
has been derived between recharge rates, inflow sediment load, size
of MS and thickness of MS with using MLR.
Abstract: This paper presents an efficient fusion algorithm for
iris images to generate stable feature for recognition in unconstrained
environment. Recently, iris recognition systems are focused on real
scenarios in our daily life without the subject’s cooperation. Under
large variation in the environment, the objective of this paper is to
combine information from multiple images of the same iris. The
result of image fusion is a new image which is more stable for further
iris recognition than each original noise iris image. A wavelet-based
approach for multi-resolution image fusion is applied in the fusion
process. The detection of the iris image is based on Adaboost
algorithm and then local binary pattern (LBP) histogram is then
applied to texture classification with the weighting scheme.
Experiment showed that the generated features from the proposed
fusion algorithm can improve the performance for verification system
through iris recognition.
Abstract: Load modeling is one of the central functions in
power systems operations. Electricity cannot be stored, which means
that for electric utility, the estimate of the future demand is necessary
in managing the production and purchasing in an economically
reasonable way. A majority of the recently reported approaches are
based on neural network. The attraction of the methods lies in the
assumption that neural networks are able to learn properties of the
load. However, the development of the methods is not finished, and
the lack of comparative results on different model variations is a
problem. This paper presents a new approach in order to predict the
Tunisia daily peak load. The proposed method employs a
computational intelligence scheme based on the Fuzzy neural
network (FNN) and support vector regression (SVR). Experimental
results obtained indicate that our proposed FNN-SVR technique gives
significantly good prediction accuracy compared to some classical
techniques.
Abstract: Graphical User Interface (GUI) is essential to
programming, as is any other characteristic or feature, due to the fact
that GUI components provide the fundamental interaction between
the user and the program. Thus, we must give more interest to GUI
during building and development of systems. Also, we must give a
greater attention to the user who is the basic corner in the dealing
with the GUI. This paper introduces an approach for designing GUI
from one of the models of business workflows which describe the
workflow behavior of a system, specifically through Activity
Diagrams (AD).
Abstract: As the use of geothermal energy grows internationally
more effort is required to monitor and protect areas with rare and
important geothermal surface features. A number of approaches are
presented for developing and calibrating numerical geothermal
reservoir models that are capable of accurately representing
geothermal surface features. The approaches are discussed in the
context of cases studies of the Rotorua geothermal system and the
Orakei-korako geothermal system, both of which contain important
surface features. The results show that models are able to match the
available field data accurately and hence can be used as valuable
tools for predicting the future response of the systems to changes in
use.
Abstract: Random epistemologies and hash tables have garnered
minimal interest from both security experts and experts in the last
several years. In fact, few information theorists would disagree with
the evaluation of expert systems. In our research, we discover how
flip-flop gates can be applied to the study of superpages. Though
such a hypothesis at first glance seems perverse, it is derived from
known results.
Abstract: The 3D body movement signals captured during
human-human conversation include clues not only to the content of
people’s communication but also to their culture and personality.
This paper is concerned with automatic extraction of this information
from body movement signals. For the purpose of this research, we
collected a novel corpus from 27 subjects, arranged them into groups
according to their culture. We arranged each group into pairs and
each pair communicated with each other about different topics.
A state-of-art recognition system is applied to the problems of
person, culture, and topic recognition. We borrowed modeling,
classification, and normalization techniques from speech recognition.
We used Gaussian Mixture Modeling (GMM) as the main technique
for building our three systems, obtaining 77.78%, 55.47%, and
39.06% from the person, culture, and topic recognition systems
respectively. In addition, we combined the above GMM systems with
Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and
40.63% accuracy for person, culture, and topic recognition
respectively.
Although direct comparison among these three recognition
systems is difficult, it seems that our person recognition system
performs best for both GMM and GMM-SVM, suggesting that intersubject
differences (i.e. subject’s personality traits) are a major
source of variation. When removing these traits from culture and
topic recognition systems using the Nuisance Attribute Projection
(NAP) and the Intersession Variability Compensation (ISVC)
techniques, we obtained 73.44% and 46.09% accuracy from culture
and topic recognition systems respectively.
Abstract: Diffusion stills have been effective in water
desalination. The present work represents a model of the distillation
process by using vertical single-effect diffusion stills. A semianalytical
model has been developed to model the process. A
software computer code using Engineering Equation Solver EES
software has been developed to solve the equations of the developed
model. An experimental setup has been constructed, and used for the
validation of the model. The model is also validated against former
literature results. The results obtained from the present experimental
test rig, and the data from the literature, have been compared with the
results of the code to find its best range of validity. In addition, a
parametric analysis of the system has been developed using the
model to determine the effect of operating conditions on the system's
performance. The dominant parameters that affect the productivity of
the still are the hot plate temperature that ranges from (55- 90°C) and
feed flow rate in range of (0.00694-0.0211 kg/m2-s).
Abstract: A knowledge-based expert system with the acronym
RASPE is developed as an application tool to help decision makers in
construction companies make informed decisions about managing
risks in pipeline construction projects. Choosing to use expert
systems from all available artificial intelligence techniques is due to
the fact that an expert system is more suited to representing a
domain’s knowledge and the reasoning behind domain-specific
decisions. The knowledge-based expert system can capture the
knowledge in the form of conditional rules which represent various
project scenarios and potential risk mitigation/response actions. The
built knowledge in RASPE is utilized through the underlying
inference engine that allows the firing of rules relevant to a project
scenario into consideration. Paper provides an overview of the
knowledge acquisition process and goes about describing the
knowledge structure which is divided up into four major modules.
The paper shows one module in full detail for illustration purposes
and concludes with insightful remarks.
Abstract: Teachers can play a huge role in encouraging students
to use computers and can affect students’ attitudes towards
computers. So understanding teachers’ beliefs and their use of
computers is an important way to create effective motivational
systems for teachers to use computers in the classroom in an effective
way. A qualitative study (6 focus group) was carried out among
Saudi High school teachers, both male and female, to examine their
attitudes towards computers and to find out their computer skills and
usage. The study showed a gender differences in that females were
less likely to attend computer workshops, females also had less
computer skills, and they have more negative attitudes towards
computers than males. Also the study found that low computer skills
in the classroom made students unlikely to have the lessons presented
using computers. Furthermore, the study found some factors that
effected teachers’ attitudes towards computers. These factors were
computer experience and confidence as much having skills and good
experience in computer use, the role and importance of computers
had become in their life and in teaching as well.
Abstract: Iran has several potential for using renewable
energies, so use them could significantly contribute to energy supply.
The purpose of this paper is to identify the potential of the country
and select the appropriate DG technologies with consideration the
potential and primary energy resources in the regions. In this context,
hybrid energy systems proportionate with the potential of different
regions will be determined based on technical, economic, and
environmental aspect. In the following the proposed structure will be
optimized in terms of size and cost. DG technologies used in this
project include photovoltaic system, wind turbine, diesel generator
and battery bank. The HOMER software is applied for choosing the
appropriate structure and the optimization of system sizing. The
results have been analyzed in terms of technical and economic. The
performance and the cost of each project demonstrate the appropriate
structure of hybrid energy system in that region.
Abstract: The present paper summarizes the analysis of the
request for consultation of information and data on industrial
emissions made publicly available on the web site of the Ministry of
Environment, Land and Sea on integrated pollution prevention and
control from large industrial installations, the so called “AIA Portal”.
As a matter of fact, a huge amount of information on national
industrial plants is already available on internet, although it is usually
proposed as textual documentation or images.
Thus, it is not possible to access all the relevant information
through interoperability systems and also to retrieval relevant
information for decision making purposes as well as rising of
awareness on environmental issue.
Moreover, since in Italy the number of institutional and private
subjects involved in the management of the public information on
industrial emissions is substantial, the access to the information is
provided on internet web sites according to different criteria; thus, at
present it is not structurally homogeneous and comparable.
To overcome the mentioned difficulties in the case of the
Coordinating Committee for the implementation of the Agreement
for the industrial area in Taranto and Statte, operating before the
IPPC permit granting procedures of the relevant installation located
in the area, a big effort was devoted to elaborate and to validate data
and information on characterization of soil, ground water aquifer and
coastal sea at disposal of different subjects to derive a global
perspective for decision making purposes. Thus, the present paper
also focuses on main outcomes matured during such experience.
Abstract: In this paper we describe one critical research
program within a complex, ongoing multi-year project (2010 to 2014
inclusive) with the overall goal to improve the learning outcomes for
first year undergraduate commerce/business students within an
Information Systems (IS) subject with very large enrolment. The
single research program described in this paper is the analysis of
student attitudes and decision making in relation to the availability of
formative assessment feedback via Web-based real time conferencing
and document exchange software (Adobe Connect). The formative
assessment feedback between teaching staff and students is in respect
of an authentic problem-based, team-completed assignment. The
analysis of student attitudes and decision making is investigated via
both qualitative (firstly) and quantitative (secondly) application of the
Theory of Planned Behavior (TPB) with a two statistically-significant
and separate trial samples of the enrolled students. The initial
qualitative TPB investigation revealed that perceived self-efficacy,
improved time-management, and lecturer-student relationship
building were the major factors in shaping an overall favorable
student attitude to online feedback, whilst some students expressed
valid concerns with perceived control limitations identified within the
online feedback protocols. The subsequent quantitative TPB
investigation then confirmed that attitude towards usage, subjective
norms surrounding usage, and perceived behavioral control of usage
were all significant in shaping student intention to use the online
feedback protocol, with these three variables explaining 63 percent of
the variance in the behavioral intention to use the online feedback
protocol. The identification in this research of perceived behavioral
control as a significant determinant in student usage of a specific
technology component within a virtual learning environment (VLE)
suggests that VLEs could now be viewed not as a single, atomic
entity, but as a spectrum of technology offerings ranging from the
mature and simple (e.g., email, Web downloads) to the cutting-edge
and challenging (e.g., Web conferencing and real-time document
exchange). That is, that all VLEs should not be considered the same.
The results of this research suggest that tertiary students have the
technological sophistication to assess a VLE in this more selective
manner.
Abstract: Different tools and technologies were implemented
for Crisis Response and Management (CRM) which is generally
using available network infrastructure for information exchange.
Depending on type of disaster or crisis, network infrastructure could
be affected and it could not be able to provide reliable connectivity.
Thus any tool or technology that depends on the connectivity could
not be able to fulfill its functionalities. As a solution, a new message
exchange framework has been developed. Framework provides
offline/online information exchange platform for CRM Information
Systems (CRMIS) and it uses XML compression and packet
prioritization algorithms and is based on open source web
technologies. By introducing offline capabilities to the web
technologies, framework will be able to perform message exchange
on unreliable networks. The experiments done on the simulation
environment provide promising results on low bandwidth networks
(56kbps and 28.8 kbps) with up to 50% packet loss and the solution is
to successfully transfer all the information on these low quality
networks where the traditional 2 and 3 tier applications failed.
Abstract: Managing and improving efficiency in the current
highly competitive global automotive industry demands that those
companies adopt leaner and more flexible systems. During the past
20 years the domestic automotive industry in North America has been
focusing on establishing new management strategies in order to meet
market demands. The lean management process also known as
Toyota Manufacturing Process (TPS) or lean manufacturing
encompasses tools and techniques that were established in order to
provide the best quality product with the fastest lead time at the
lowest cost. The following paper presents a study that focused on
improving labor efficiency at one of the Big Three (Ford, GM,
Chrysler LLC) domestic automotive facility in North America. The
objective of the study was to utilize several lean management tools in
order to optimize the efficiency and utilization levels at the “Pre-
Marriage” chassis area in a truck manufacturing and assembly
facility. Utilizing three different lean tools (i.e. Standardization of
work, 7 Wastes, and 5S) this research was able to improve efficiency
by 51%, utilization by 246%, and reduce operations by 14%. The
return on investment calculated based on the improvements made
was 284%.