Abstract: In this paper, based on the work in [1], we further give
a general model for acquiring knowledge, which first focuses on the
research of how and when things involved in problems are made
then describes the goals, the energy and the time to give an optimum
model to decide how many related things are supposed to be involved
in. Finally, we acquire knowledge from this model in which there are
the attributes, actions and connections of the things involved at the
time when they are born and the time in their life. This model not
only improves AI theories, but also surely brings the effectiveness
and accuracy for AI system because systems are given more
knowledge when reasoning or computing is used to bring about
results.
Abstract: This paper presents a review on vision aided systems
and proposes an approach for visual rehabilitation using stereo vision
technology. The proposed system utilizes stereo vision, image
processing methodology and a sonification procedure to support
blind navigation. The developed system includes a wearable
computer, stereo cameras as vision sensor and stereo earphones, all
moulded in a helmet. The image of the scene infront of visually
handicapped is captured by the vision sensors. The captured images
are processed to enhance the important features in the scene in front,
for navigation assistance. The image processing is designed as model
of human vision by identifying the obstacles and their depth
information. The processed image is mapped on to musical stereo
sound for the blind-s understanding of the scene infront. The
developed method has been tested in the indoor and outdoor
environments and the proposed image processing methodology is
found to be effective for object identification.
Abstract: In this study, we illustrated the performance and
microbial community of single- and two-phase systems anaerobically
co-digesting cassava pulp and pig manure. The results showed that
the volatile solid reduction and biogas productivity of two-phase
CSTR were 66 ± 4% and 2000 ± 210 ml l-1 d-1, while those of singlephase
CSTR were 59 ± 1% and 1670 ± 60 ml l-1 d-1, respectively. Codigestion
in two-phase CSTR gave higher 12% solid degradation and
25% methane production than single-phase CSTR. Phylogenetic
analysis of 16S rDNA clone library revealed that the Bacteroidetes
were the most abundant group, followed by the Clostridia in singlephase
CSTR. In hydrolysis/acidification reactor of two-phase system,
the bacteria within the phylum Firmicutes, especially Clostridium,
Eubacteriaceae and Lactobacillus were the dominant phylogenetic
groups. Among the Archaea, Methanosaeta sp. was the exclusive
predominant in both digesters while the relative abundance of
Methanosaeta sp. and Methanospirillum hungatei differed between
the two systems.
Abstract: The Ant Colony Optimization (ACO) is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It has recently attracted a lot of attention and has been successfully applied to a number of different optimization problems. Due to the importance of the feature selection problem and the potential of ACO, this paper presents a novel method that utilizes the ACO algorithm to implement a feature subset search procedure. Initial results obtained using the classification of speech segments are very promising.
Abstract: Water pipe network is installed underground and once equipped, it is difficult to recognize the state of pipes when the leak or burst happens. Accordingly, post management is often delayed
after the fault occurs. Therefore, the systematic fault management system of water pipe network is required to prevent the accident and
minimize the loss. In this work, we develop online fault detection system of water pipe network using data of pipes such as flow rate
or pressure. The transient model describing water flow in pipelines
is presented and simulated using MATLAB. The fault situations such
as the leak or burst can be also simulated and flow rate or pressure data when the fault happens are collected. Faults are detected using
statistical methods of fast Fourier transform and discrete wavelet transform, and they are compared to find which method shows the
better fault detection performance.
Abstract: Cities denote instantaneously a challenge and an
opportunity for climate change policy. Cities are the place where
most energy services are needed because urbanization is closely
linked to high population densities and concentration of economic
activities and production (Urban energy demand). Consequently, it is
critical to explain about the role of cities within the world-s energy
systems and its correlation with the climate change issue. With more
than half of the world-s population already living in urban areas, and
that percentage expected to rise to 75 per cent by 2050, it is clear that
the path to sustainable development must pass through cities. Cities
expanding in size and population pose increased challenges to the
environment, of which energy is part as a natural resource, and to the
quality of life. Nowadays, most cities have already understood the
importance of sustainability, both at their local scale as in terms of
their contribution to sustainability at higher geographical scales. It
requires the perception of a city as a complex and dynamic
ecosystem, an open system, or cluster of systems, where the energy
as well as the other natural resources is transformed to satisfy the
needs of the different urban activities. In fact, buildings and
transportation generally represent most of cities direct energy
demand, i.e., between 60 per cent and 80 per cent of the overall
consumption. Buildings, both residential and services are usually
influenced by the local physical and social conditions. In terms of
transport, the energy demand is also strongly linked with the specific
characteristics of a city (urban mobility).The concept of a “smart
city" builds on statistics as seven key axes of a city-s success in
moving towards common platform (brain nerve)of sustainable urban
energy systems.
With the aforesaid knowledge, the authors have suggested a frame
work to role of cities, as energy actors for smart city management.
The authors have discusses the potential elements needed for energy
in smart cities and also identified potential energy actions and
relevant barriers. Furthermore, three levels of city smartness in cities
actions to overcome market /institutional failures with a local
approach are distinguished. The authors have made an attempt to
conceive and implement concepts of city smartness by adopting the
city or local government as nerve center through an integrated
planning approach. Finally, concluding with recommendations for
the organization of the Smart Sustainable Cities for positive changes
of urban India.
Abstract: A new strategy of control is formulated for chaos synchronization of non-identical chaotic systems with different orders using the Borne and Gentina practical criterion associated with the Benrejeb canonical arrow form matrix, to drift the stability property of dynamic complex systems. The designed controller ensures that the state variables of controlled chaotic slave systems globally synchronize with the state variables of the master systems, respectively. Numerical simulations are performed to illustrate the efficiency of the proposed method.
Abstract: In this paper, a new cooling system using a nacelle duct
is proposed for the mechanical room in the household refrigerator. The
conventional mechanical room consists of a condenser, a compressor
and an axial fan. The axial fan is mainly responsible for cooling the
condenser and the compressor. The new cooling system is developed
by replacing the axial fan with the nacelle duct including the small
centrifugal fan. The parametric study is carried out to find the optimum
designs of the nacelle duct in terms of performance and efficiency.
Through this study, it is revealed that the new system can reduce the
space, electrical power and noise compared with the conventional
system
Abstract: Micro electromechanical sensors (MEMS) play a vital
role along with global positioning devices in navigation of
autonomous vehicles .These sensors are low cost ,easily available but
depict colored noises and unpredictable discontinuities .Conventional
filters like Kalman filters and Sigma point filters are not able to cope
with nonwhite noises. This research has utilized H∞ filter in nonlinear
frame work both with Kalman filter and Unscented filter for
navigation and self alignment of an airborne vehicle. The system is
simulated for colored noises and discontinuities and results are
compared with not robust nonlinear filters. The results are found
40%-70% more robust against colored noises and discontinuities.
Abstract: Information on weed distribution within the field is
necessary to implement spatially variable herbicide application.
Since hand labor is costly, an automated weed control system could be
feasible. This paper deals with the development of an algorithm for
real time specific weed recognition system based on Histogram
Analysis of an image that is used for the weed classification. This
algorithm is specifically developed to classify images into broad and
narrow class for real-time selective herbicide application. The
developed system has been tested on weeds in the lab, which have
shown that the system to be very effectiveness in weed identification.
Further the results show a very reliable performance on images of
weeds taken under varying field conditions. The analysis of the results
shows over 95 percent classification accuracy over 140 sample images
(broad and narrow) with 70 samples from each category of weeds.
Abstract: In order to give high expertise the computer aided
design of mechanical systems involves specific activities focused on
processing two type of information: knowledge and data. Expert rule
based knowledge is generally processing qualitative information and
involves searching for proper solutions and their combination into
synthetic variant. Data processing is based on computational models
and it is supposed to be inter-related with reasoning in the knowledge
processing. In this paper an Intelligent Integrated System is proposed,
for the objective of choosing the adequate material. The software is
developed in Prolog – Flex software and takes into account various
constraints that appear in the accurate operation of gears.
Abstract: Current air conditioning system is using refrigerant as
the cooling medium. The main purpose of this study is to develop an
air conditioning system using chill water as the cooling medium. In
this system, chill water used to replace refrigerant as the cooling
medium. This study is focus on the split type unit air conditioning
system only. It will be involving some renovation on the indoor unit
and freezer. The cooling capability of this system was validate by few
series of testing, which conducted at standard 36m3 office room.
Result of the testing found that 0.1 m3 of chill water is able to
maintain the room temperature within standard up to 4 ~ 8 hours. It
expected able to maintain room temperature up to 10 hour with some
improvement.
Abstract: The mitigation of crop loss due to damaging freezes
requires accurate air temperature prediction models. Previous work
established that the Ward-style artificial neural network (ANN) is a
suitable tool for developing such models. The current research
focused on developing ANN models with reduced average prediction
error by increasing the number of distinct observations used in
training, adding additional input terms that describe the date of an
observation, increasing the duration of prior weather data included in
each observation, and reexamining the number of hidden nodes used
in the network. Models were created to predict air temperature at
hourly intervals from one to 12 hours ahead. Each ANN model,
consisting of a network architecture and set of associated parameters,
was evaluated by instantiating and training 30 networks and
calculating the mean absolute error (MAE) of the resulting networks
for some set of input patterns. The inclusion of seasonal input terms,
up to 24 hours of prior weather information, and a larger number of
processing nodes were some of the improvements that reduced
average prediction error compared to previous research across all
horizons. For example, the four-hour MAE of 1.40°C was 0.20°C, or
12.5%, less than the previous model. Prediction MAEs eight and 12
hours ahead improved by 0.17°C and 0.16°C, respectively,
improvements of 7.4% and 5.9% over the existing model at these
horizons. Networks instantiating the same model but with different
initial random weights often led to different prediction errors. These
results strongly suggest that ANN model developers should consider
instantiating and training multiple networks with different initial
weights to establish preferred model parameters.
Abstract: Elastic light single-scattering spectroscopy system
with a single optical fiber probe was employed to differentiate cancerous prostate tissue from non-cancerous prostate tissue ex-vivo just after radical prostatectomy. First, ELSSS spectra were acquired
from cancerous prostate tissue to define its spectral features. Then,
spectra were acquired from normal prostate tissue to define difference in spectral features between the cancerous and normal
prostate tissues. Of the total 66 tissue samples were evaluated from
nine patients by ELSSS system. Comparing of histopathology results
and ELSSS measurements revealed that sign of the spectral slopes of
cancerous prostate tissue is negative and non-cancerous tissue is positive in the wavelength range from 450 to 750 nm. Based on the
correlation between histopathology results and sign of the spectral
slopes, ELSSS system differentiates cancerous prostate tissue from
non- cancerous with a sensitivity of 0.95 and a specificity of 0.94.
Abstract: The Brazilian Agricultural Products Wholesale Market fits well as example of residues generating system, reaching 750 metric tons per month of total residues, from which 600 metric tons are organic material and 150 metric tons are recyclable materials. Organic material is basically composed of fruit, vegetables and flowers leftovers from the products commercialization. The recyclable compounds are generate from packing material employed in the commercialization process. This research work devoted efforts in carrying quantitative analysis of the residues generated in the agricultural enterprise at its final destination. Data survey followed the directions implemented by the Residues Management Program issued by the agricultural enterprise. It was noticed from that analysis the necessity of changing the logistics applied to the recyclable material collecting process. However, composting process was elected as the organic compounds destination which is considered adequate for a material composed of significant percentage of organic matter far higher than wood, cardboard and plastics contents.
Abstract: One of the methods for detecting the target position
error in the laser tracking systems is using Four Quadrant (4Q)
detectors. If the coordinates of the target center is yielded through the
usual relations of the detector outputs, the results will be nonlinear,
dependent on the shape, target size and its position on the detector
screen. In this paper we have designed an algorithm with using
neural network that coordinates of the target center in laser tracking
systems is calculated by using detector outputs obtained from visual
modeling. With this method, the results except from the part related
to the detector intrinsic limitation, are linear and dependent from the
shape and target size.
Abstract: More and more natural disasters are happening every
year: floods, earthquakes, volcanic eruptions, etc. In order to reduce
the risk of possible damages, governments all around the world are
investing into development of Early Warning Systems (EWS) for
environmental applications. The most important task of the EWS is
identification of the onset of critical situations affecting environment
and population, early enough to inform the authorities and general
public. This paper describes an approach for monitoring of flood
protections systems based on machine learning methods. An
Artificial Intelligence (AI) component has been developed for
detection of abnormal dike behaviour. The AI module has been
integrated into an EWS platform of the UrbanFlood project (EU
Seventh Framework Programme) and validated on real-time
measurements from the sensors installed in a dike.
Abstract: Insider abuse has recently been reported as one of
the more frequently occurring security incidents, suggesting that
more security is required for detecting and preventing unauthorised
financial transactions entered by authorised users. To address the
problem, and based on the observation that all authorised interbanking
financial transactions trigger or are triggered by other
transactions in a workflow, we have developed a security solution
based on a redefined understanding of an audit workflow. One audit
workflow where there is a log file containing the complete workflow
activity of financial transactions directly related to one financial
transaction (an electronic deal recorded at an e-trading system). The
new security solution contemplates any two parties interacting on
the basis of financial transactions recorded by their users in related
but distinct automated financial systems. In the new definition interorganizational
and intra-organization interactions can be described
in one unique audit trail. This concept expands the current ideas of
audit trails by adapting them to actual e-trading workflow activity, i.e.
intra-organizational and inter-organizational activity. With the above,
a security auditing service is designed to detect integrity drifts with
and between organizations in order to detect unauthorised financial
transactions entered by authorised users.
Abstract: In this paper, a field oriented control (FOC) induction motor drive is presented. In order to eliminate the speed sensor, an adaptation algorithm for tuning the rotor speed is proposed. Based on the Model Reference Adaptive System (MRAS) scheme, the rotor speed is tuned to obtain an exact FOC induction motor drive. The reference and adjustable models, developed in stationary stator reference frame, are used in the MRAS scheme to estimate induction rotor speed from measured terminal voltages and currents. The Integral Proportional (IP) gains speed controller are tuned by a modern approach that is the Particle Swarm Optimization (PSO) algorithm in order to optimize the parameters of the IP controller. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. The proposed algorithm has been tested by numerical simulation, showing the capability of driving load.
Abstract: The tracing methods determine the contribution the
power system sources have in their supplying. These methods can be
used to assess the transmission prices, but also to recover the
transmission fixed cost. In this paper is presented the influence of the
modification of commons structure has on the specific price of transfer
and on active power losses. The authors propose a power losses
allocation method, based on Kirschen-s method. The system operator
must make use of a few basic principles about allocation. The only
necessary information is the power flows on system branches and the
modifications applied to power system buses. In order to illustrate this
method, the 25-bus test system is used, elaborated within the Electrical
Power Engineering Department, from Timisoara, Romania.