Abstract: Bioprocesses are appreciated as difficult to control because their dynamic behavior is highly nonlinear and time varying, in particular, when they are operating in fed batch mode. The research objective of this study was to develop an appropriate control method for a complex bioprocess and to implement it on a laboratory plant. Hence, an intelligent control structure has been designed in order to produce biomass and to maximize the specific growth rate.
Abstract: The paper describes a knowledge based system for
analysis of microscopic wear particles. Wear particles contained in
lubricating oil carry important information concerning machine
condition, in particular the state of wear. Experts (Tribologists) in the
field extract this information to monitor the operation of the machine
and ensure safety, efficiency, quality, productivity, and economy of
operation. This procedure is not always objective and it can also be
expensive. The aim is to classify these particles according to their
morphological attributes of size, shape, edge detail, thickness ratio,
color, and texture, and by using this classification thereby predict
wear failure modes in engines and other machinery. The attribute
knowledge links human expertise to the devised Knowledge Based
Wear Particle Analysis System (KBWPAS). The system provides an
automated and systematic approach to wear particle identification
which is linked directly to wear processes and modes that occur in
machinery. This brings consistency in wear judgment prediction
which leads to standardization and also less dependence on
Tribologists.
Abstract: Deep Brain Stimulation or DBS is a surgical treatment for Parkinson-s Disease with three stimulation parameters: frequency, pulse width, and voltage. The parameters should be selected appropriately to achieve effective treatment. This selection now, performs clinically. The aim of this research is to study chaotic behavior of recorded tremor of patients under DBS in order to present a computational method to recognize stimulation optimum voltage. We obtained some chaotic features of tremor signal, and discovered embedding space of it has an attractor, and its largest Lyapunov exponent is positive, which show tremor signal has chaotic behavior, also we found out, in optimal voltage, entropy and embedding space variance of tremor signal have minimum values in comparison with other voltages. These differences can help neurologists recognize optimal voltage numerically, which leads to reduce patients' role and discomfort in optimizing stimulation parameters and to do treatment with high accuracy.
Abstract: Wireless sensor network can be applied to both abominable
and military environments. A primary goal in the design of
wireless sensor networks is lifetime maximization, constrained by
the energy capacity of batteries. One well-known method to reduce
energy consumption in such networks is data aggregation. Providing
efcient data aggregation while preserving data privacy is a challenging
problem in wireless sensor networks research. In this paper,
we present privacy-preserving data aggregation scheme for additive
aggregation functions. The Cluster-based Private Data Aggregation
(CPDA)leverages clustering protocol and algebraic properties of
polynomials. It has the advantage of incurring less communication
overhead. The goal of our work is to bridge the gap between
collaborative data collection by wireless sensor networks and data
privacy. We present simulation results of our schemes and compare
their performance to a typical data aggregation scheme TAG, where
no data privacy protection is provided. Results show the efficacy and
efficiency of our schemes.
Abstract: In neural networks, when new patterns are learned by a network, the new information radically interferes with previously stored patterns. This drawback is called catastrophic forgetting or catastrophic interference. In this paper, we propose a biologically inspired neural network model which overcomes this problem. The proposed model consists of two distinct networks: one is a Hopfield type of chaotic associative memory and the other is a multilayer neural network. We consider that these networks correspond to the hippocampus and the neocortex of the brain, respectively. Information given is firstly stored in the hippocampal network with fast learning algorithm. Then the stored information is recalled by chaotic behavior of each neuron in the hippocampal network. Finally, it is consolidated in the neocortical network by using pseudopatterns. Computer simulation results show that the proposed model has much better ability to avoid catastrophic forgetting in comparison with conventional models.
Abstract: A lot of research has been done in the past decade in the field of audio content analysis for extracting various information from audio signal. One such significant information is the "perceived mood" or the "emotions" related to a music or audio clip. This information is extremely useful in applications like creating or adapting the play-list based on the mood of the listener. This information could also be helpful in better classification of the music database. In this paper we have presented a method to classify music not just based on the meta-data of the audio clip but also include the "mood" factor to help improve the music classification. We propose an automated and efficient way of classifying music samples based on the mood detection from the audio data. We in particular try to classify the music based on mood for Indian bollywood music. The proposed method tries to address the following problem statement: Genre information (usually part of the audio meta-data) alone does not help in better music classification. For example the acoustic version of the song "nothing else matters by Metallica" can be classified as melody music and thereby a person in relaxing or chill out mood might want to listen to this track. But more often than not this track is associated with metal / heavy rock genre and if a listener classified his play-list based on the genre information alone for his current mood, the user shall miss out on listening to this track. Currently methods exist to detect mood in western or similar kind of music. Our paper tries to solve the issue for Indian bollywood music from an Indian cultural context
Abstract: The expectation of network performance from the
early days of ARPANET until now has been changed significantly.
Every day, new advancement in technological infrastructure opens
the doors for better quality of service and accordingly level of
perceived quality of network services have been increased over the
time. Nowadays for many applications, late information has no value
or even may result in financial or catastrophic loss, on the other hand,
demands for some level of guarantee in providing and maintaining
quality of service are ever increasing. Based on this history, having a
QoS aware routing system which is able to provide today's required
level of quality of service in the networks and effectively adapt to the
future needs, seems as a key requirement for future Internet. In this
work we have extended the traditional AntNet routing system to
support QoS with multiple metrics such as bandwidth and delay
which is named Q-Net. This novel scalable QoS routing system aims
to provide different types of services in the network simultaneously.
Each type of service can be provided for a period of time in the
network and network nodes do not need to have any previous
knowledge about it. When a type of quality of service is requested,
Q-Net will allocate required resources for the service and will
guarantee QoS requirement of the service, based on target objectives.
Abstract: The virulent debates that have dogged research on,
and the diffusion of, a wide range of technologies indicate a growing
loss of confidence in what we might call, the techno-scientific
endeavour to reshape the world. Utopian images of a world rendered
ever more amenable to human desires are now closely shadowed by
just as compelling dystopian visions of monstrosity and disaster that
are nevertheless constructed from the same cultural material. The
paper uses the case of the debates over developments in reproductive
technology to offer some observations on the ways in which such
technologies routinely become enmirred in cultural ambivalence.
Abstract: Virtual environments are a hot topic in academia and more importantly in courses offered via distance education. Today-s gaming generation view virtual worlds as strong social and interactive mediums for communicating and socializing. And while institutions of higher education are challenged with increasing enrollment while balancing budget cuts, offering effective courses via distance education become a valid option. Educators can utilize virtual worlds to offer students an enhanced learning environment which has the power to alleviate feelings of isolation through the promotion of communication, interaction, collaboration, teamwork, feedback, engagement and constructivists learning activities. This paper focuses on the use of virtual environments to facilitate interaction in distance education courses so as to produce positive learning outcomes for students. Furthermore, the instructional strategies were reviewed and discussed for use in virtual worlds to enhance learning within a social context.
Abstract: Exposure to ambient air pollution has been linked to a
number of health outcomes, starting from modest transient changes in
the respiratory tract and impaired pulmonary function, continuing to
restrict activity/reduce performance and to the increase emergency
rooms visits, hospital admissions or mortality. The increase of
allergenic symptoms has been associated with air contaminants such
as ozone, particulate matter, fungal spores and pollen.
Considering the potential relevance of crossed effects of nonbiological
pollutants and airborne pollens and fungal spores on
allergy worsening, the aim of this work was to evaluate the influence
of non-biological pollutants (O3 and PM10) and meteorological
parameters on the concentrations of pollen and fungal spores using
multiple linear regressions.
The data considered in this study were collected in Oporto which
is the second largest Portuguese city, located in the North. Daily
mean of O3, PM10, pollen and fungal spore concentrations,
temperature, relative humidity, precipitation, wind velocity, pollen
and fungal spore concentrations, for 2003, 2004 and 2005 were
considered. Results showed that the 90th percentile of the adjusted
coefficient of determination, P90 (R2aj), of the multiple regressions
varied from 0.613 to 0.916 for pollen and from 0.275 to 0.512 for
fungal spores. O3 and PM10 showed to have some influence on the
biological pollutants. Among the meteorological parameters
analysed, temperature was the one that most influenced the pollen
and fungal spores airborne concentrations. Relative humidity also
showed to have some influence on the fungal spore dispersion.
Nevertheless, the models for each pollen and fungal spore were
different depending on the analysed period, which means that the
correlations identified as statistically significant can not be, even so,
consistent enough.
Abstract: In this paper we present a GP-based method for automatically evolve projections, so that data can be more easily classified in the projected spaces. At the same time, our approach can reduce dimensionality by constructing more relevant attributes. Fitness of each projection measures how easy is to classify the dataset after applying the projection. This is quickly computed by a Simple Linear Perceptron. We have tested our approach in three domains. The experiments show that it obtains good results, compared to other Machine Learning approaches, while reducing dimensionality in many cases.
Abstract: This research was to study on background and social
and cultural context of Kamchanoad community for sustainable
tourism management. All data was collected through in-depth
interview with village headmen, community committees, teacher,
monks, Kamchanoad forest field officers and respected senior citizen
above 60 years old in the community who have lived there for more
than 40 years. Altogether there were 30 participants for this research.
After analyzing the data, content from interview and discussion,
Kamchanoad has both high land and low land in the region as well as
swamps that are very capable of freshwater animals’ conservation.
Kamchanoad is also good for agriculture and animal farming. 80% of
Kamchanoad’s land are forest, freshwater and rice farms.
Kamchanoad was officially set up as community in 1994 as “Baan
Nonmuang”. Inhabitants in Kamchanoad make a living by farming
based on sufficiency economy. They have rice farm, eucalyptus farm,
cassava farm and rubber tree farm. Local people in Kamchanoad still
believe in the myth of Srisutto Naga. They are still religious and love
to preserve their traditional way of life. In order to understand how to
create successful tourism business in Kamchanoad, we have to study
closely on local culture and traditions. Outstanding event in
Kamchanoad is the worship of Grand Srisutto, which is on the fullmoon
day of 6th month or Visakhabucha Day. Other big events are
also celebration at the end of Buddhist lent, Naga firework, New
Year celebration, Boon Mahachart, Songkran, Buddhist Lent, Boon
Katin and Loy Kratong. Buddhism is the main religion in
Kamchanoad. The promotion of tourism in Kamchanoad is expected
to help spreading more income for this region. More infrastructures
will be provided for local people as well as funding for youth support
and people activities.
Abstract: In analyzing large scale nonlinear dynamical systems,
it is often desirable to treat the overall system as a collection of
interconnected subsystems. Solutions properties of the large scale
system are then deduced from the solution properties of the
individual subsystems and the nature of the interconnections. In this
paper a new approach is proposed for the stability analysis of large
scale systems, which is based upon the concept of vector Lyapunov
functions and the decomposition methods. The present results make
use of graph theoretic decomposition techniques in which the overall
system is partitioned into a hierarchy of strongly connected
components. We show then, that under very reasonable assumptions,
the overall system is stable once the strongly connected subsystems
are stables. Finally an example is given to illustrate the constructive
methodology proposed.
Abstract: This paper presents an efficient approach to feeder
reconfiguration for power loss reduction and voltage profile
imprvement in unbalanced radial distribution systems (URDS). In
this paper Genetic Algorithm (GA) is used to obtain solution for
reconfiguration of radial distribution systems to minimize the losses.
A forward and backward algorithm is used to calculate load flows in
unbalanced distribution systems. By simulating the survival of the
fittest among the strings, the optimum string is searched by
randomized information exchange between strings by performing
crossover and mutation. Results have shown that proposed algorithm
has advantages over previous algorithms The proposed method is
effectively tested on 19 node and 25 node unbalanced radial
distribution systems.
Abstract: In this paper, we proposed an invention of an
accessory into a communication device that will help humans to be
connected universally. Generally, this device will be made up of
crystal and will combine many technologies that will enable the user
to run various applications and software anywhere and everywhere.
Bringing up the concept of from being user friendly, we had used the
crystal as the main material of the device that will trap the
surrounding lights to produce projection of its screen. This leads to a
lesser energy consumption and allows smaller sized battery to be
used, making the device less bulky. Additionally, we proposed the
usage of micro batteries as our energy source. Thus, researches
regarding crystal were made along with explanations in details of
specification and function of the technology used in the device.
Finally, we had also drawn several views of the invention from
different sides to be visualized.
Abstract: Accurate modeling of high speed RLC interconnects
has become a necessity to address signal integrity issues in current
VLSI design. To accurately model a dispersive system of interconnects
at higher frequencies; a full-wave analysis is required.
However, conventional circuit simulation of interconnects with full
wave models is extremely CPU expensive. We present an algorithm
for reducing large VLSI circuits to much smaller ones with similar
input-output behavior. A key feature of our method, called Frequency
Shift Technique, is that it is capable of reducing linear time-varying
systems. This enables it to capture frequency-translation and sampling
behavior, important in communication subsystems such as mixers,
RF components and switched-capacitor filters. Reduction is obtained
by projecting the original system described by linear differential
equations into a lower dimension. Experiments have been carried out
using Cadence Design Simulator cwhich indicates that the proposed
technique achieves more % reduction with less CPU time than the
other model order reduction techniques existing in literature. We
also present applications to RF circuit subsystems, obtaining size
reductions and evaluation speedups of orders of magnitude with
insignificant loss of accuracy.
Abstract: Microbial-induced calcite precipitation (MICP) is a
relatively green and sustainable soil improvement technique. It
utilizes biochemical process that exists naturally in soil to improve
engineering properties of soils. The calcite precipitation process is
uplifted by the mean of injecting higher concentration of urease
positive bacteria and reagents into the soil. The main objective of this
paper is to provide an overview of the factors affecting the MICP in
soil. Several factors were identified including nutrients, bacteria type,
geometric compatibility of bacteria, bacteria cell concentration,
fixation and distribution of bacteria in soil, temperature, reagents
concentration, pH, and injection method. These factors were found to
be essential for promoting successful MICP soil treatment.
Furthermore, a preliminary laboratory test was carried out to
investigate the potential application of the technique in improving the
shear strength and impermeability of a residual soil specimen. The
results showed that both shear strength and impermeability of
residual soil improved significantly upon MICP treatment. The
improvement increased with increasing soil density.
Abstract: This study is concerned with pH solution detection
using 2 × 4 flexible sensor array based on a plastic polyethylene
terephthalate (PET) substrate that is coated a conductive layer and a
ruthenium dioxide (RuO2) sensitive membrane with the technologies
of screen-printing and RF sputtering. For data analysis, we also
prepared a dynamic measurement system for acquiring the response
voltage and analyzing the characteristics of the working electrodes
(WEs), such as sensitivity and linearity. In this condition, an array
measurement system was designed to acquire the original signal from
sensor array, and it is based on the method of digital signal processing
(DSP). The DSP modifies the unstable acquisition data to a direct
current (DC) output using the technique of digital filter. Hence, this
sensor array can obtain a satisfactory yield, 62.5%, through the design
measurement and analysis system in our laboratory.
Abstract: Strategic alliances generally mean the cooperation or
collaboration between firms which pursue for a synergy that each
member hopes the benefits from the alliances would be much more
than those from individual efforts. Past researches provide us
sufficient theories and considerations for alliance forming in liner
shipping market. This research reviews important academic journals
for the past decade regarding to the most important reasons to form the
alliances. We would explain the motive of alliances and details of
shipping cooperation in literature review.
The paper also empirically investigates the key service quality
requirements improved through alliances by using quality function
deployment (QFD). Moreover, the research investigates famous
shipping reports, shipping consultant websites and most recent
shipping publications to find out the executive-s viewpoint of several
leading carriers among top 20 to assess current shipping strategic
alliance on Asia/Europe route. These comments provide meaningful
managerial reasons to consider alliance formations and search if there
is any gap between the theories and industrial practice. Analysis of the
empirical investigation and top management-s perspective on current
market situation will contribute us some meaningful managerial
suggestions to evaluate these theories applied to current strategic
alliances.
Abstract: Adaptive e-learning today gives the student a central
role in his own learning process. It allows learners to try things out,
participate in courses like never before, and get more out of learning
than before. In this paper, an adaptive e-learning model for logic
design, simplification of Boolean functions and related fields is
presented. Such model presents suitable courses for each student in a
dynamic and adaptive manner using existing database and workflow
technologies. The main objective of this research work is to provide
an adaptive e-learning model based learners' personality using
explicit and implicit feedback. To recognize the learner-s, we develop
dimensions to decide each individual learning style in order to
accommodate different abilities of the users and to develop vital
skills. Thus, the proposed model becomes more powerful, user
friendly and easy to use and interpret. Finally, it suggests a learning
strategy and appropriate electronic media that match the learner-s
preference.