Abstract: This paper presents the novel Rao-Blackwellised
particle filter (RBPF) for mobile robot simultaneous localization and
mapping (SLAM) using monocular vision. The particle filter is
combined with unscented Kalman filter (UKF) to extending the path
posterior by sampling new poses that integrate the current observation
which drastically reduces the uncertainty about the robot pose. The
landmark position estimation and update is also implemented through
UKF. Furthermore, the number of resampling steps is determined
adaptively, which seriously reduces the particle depletion problem,
and introducing the evolution strategies (ES) for avoiding particle
impoverishment. The 3D natural point landmarks are structured with
matching Scale Invariant Feature Transform (SIFT) feature pairs. The
matching for multi-dimension SIFT features is implemented with a
KD-Tree in the time cost of O(log2
N). Experiment results on real robot
in our indoor environment show the advantages of our methods over
previous approaches.
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: Social ideology, cultural values and principles shaping environment are inferred by environment and structural characteristics of construction site. In other words, this inference manifestation also indicates ideology and culture of its foundation and also applies its principles and values and somehow plays an important role in Cultural Revolution. All human behaviors and artifacts are affected and being influenced by culture. Culture is not abstract concept, it is a spiritual domain that an individual and society grow and develop in it. Social behaviors are affected by environmental comprehension, so the architecture work influences on its audience and it is the environment that fosters social behaviors. Indeed, sustainable architecture should be considered as background of culture for establishing optimal sustainable culture. Since unidentified architecture roots in cultural non identity and abnormalities, so the society possesses identity characteristics and life and as a consequence, the society and architecture are changed by transformation of life style. This article aims to investigate the interaction of architecture, society, environment and sustainable architecture formation in its cultural basis and analyzes the results approaching behavior and sustainable culture in recent era.
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: Estimating the reliability of a computer network has been a subject of great interest. It is a well known fact that this problem is NP-hard. In this paper we present a very efficient combinatorial approach for Monte Carlo reliability estimation of a network with unreliable nodes and unreliable edges. Its core is the computation of some network combinatorial invariants. These invariants, once computed, directly provide pure and simple framework for computation of network reliability. As a specific case of this approach we obtain tight lower and upper bounds for distributed network reliability (the so called residual connectedness reliability). We also present some simulation results.
Abstract: This paper deals with tracking and estimating time delay between two signals. The simulation of this algorithm accomplished by using Mathcad package is carried out. The algorithm we will present adaptively controls and tracking the delay, so as to minimize the mean square of this error. Thus the algorithm in this case has task not only of seeking the minimum point of error but also of tracking the change of position, leading to a significant improving of performance. The flowchart of the algorithm is presented as well as several tests of different cases are carried out.
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: 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: Although electrical motors are still the main devices
used in vehicular exhaust comprises more than 95 percent of the air
pollution in Taiwan's largest city, Taipei. On average, all commuters in Taipei travel 13.6 km daily, while motorcycle commuters travel 12.2 km. The convenience and mobility of motorcycles makes them
irreplaceable in Taiwan city traffic but they add significantly to air pollution problems. In order to improve air pollution conditions, some
new types of vehicles have been proposed, such as fuel cell driven and
hybrid energy vehicles. In this study, we develop a model pneumatic hybrid motorcycle system and simulate its acceleration and mileage
(km/L) performance. The results show that the pneumatic hybrid
motorcycle can improve efficiency.
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: We compare three categorical data clustering
algorithms with respect to the problem of classifying cultural data
related to the aesthetic judgment of comics artists. Such a
classification is very important in Comics Art theory since the
determination of any classes of similarities in such kind of data will
provide to art-historians very fruitful information of Comics Art-s
evolution. To establish this, we use a categorical data set and we
study it by employing three categorical data clustering algorithms.
The performances of these algorithms are compared each other,
while interpretations of the clustering results are also given.
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: Since Software testing becomes an important part of
Software development in order to improve the quality of software,
many automation tools are created to help testing functionality of
software. There are a few issues about usability of these tools, one is
that the result log which is generated from tools contains useless
information that the tester cannot use result log to communicate
efficiently, or the result log needs to use a specific application to open.
This paper introduces a new method, SBTAR that improves usability
of automated test tools in a part of a result log. The practice will use
the capability of tools named as IBM Rational Robot to create a
customized function, the function would generate new format of a
result log which contains useful information faster and easier to
understand than using the original result log which was generated
from the tools. This result log also increases flexibility by Microsoft
Word or WordPad to make them readable.
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: 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: 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: This paper presents the prediction of air flow,
humidity and temperature patterns in a co-current pilot plant spray
dryer fitted with a pressure nozzle using a three dimensional model.
The modelling was done with a Computational Fluid Dynamic
package (Fluent 6.3), in which the gas phase is modelled as
continuum using the Euler approach and the droplet/ particle phase is
modelled by the Discrete Phase model (Lagrange approach).Good
agreement was obtained with published experimental data where the
CFD simulation correctly predicts a fast downward central flowing
core and slow recirculation zones near the walls. In this work, the
effects of the air flow pattern on droplets trajectories, residence time
distribution of droplets and deposition of the droplets on the wall also
were investigated where atomizing of maltodextrin solution was
used.
Abstract: Statistics Canada stated that the wastewater treatment
facilities in most provinces are aging and passes 63% of their useful
life in 2007 the highest ratio among public infrastructure assets.
Currently, there is no standard condition rating system for wastewater
treatment plants that give a specific rating index that describe the
physical integrity of different infrastructure elements in the treatment
plant and its environmental performance. The main objective of this
study is to develop a condition-rating index for wastewater treatment
plants mainly activated sludge systems. The proposed WWTP CRI, is
based on dividing the treatment plant into its three treatment phases;
primary phase, secondary phase and the tertiary phase. The
condition-rating index will reflect the infrastructures state for each
phase, mainly tanks, pipes, blowers and pumps.