Abstract: This paper introduces and studies new indexing techniques for content-based queries in images databases. Indexing is the key to providing sophisticated, accurate and fast searches for queries in image data. This research describes a new indexing approach, which depends on linear modeling of signals, using bases for modeling. A basis is a set of chosen images, and modeling an image is a least-squares approximation of the image as a linear combination of the basis images. The coefficients of the basis images are taken together to serve as index for that image. The paper describes the implementation of the indexing scheme, and presents the findings of our extensive evaluation that was conducted to optimize (1) the choice of the basis matrix (B), and (2) the size of the index A (N). Furthermore, we compare the performance of our indexing scheme with other schemes. Our results show that our scheme has significantly higher performance.
Abstract: Training neural networks to capture an intrinsic
property of a large volume of high dimensional data is a difficult
task, as the training process is computationally expensive. Input
attributes should be carefully selected to keep the dimensionality of
input vectors relatively small.
Technical indexes commonly used for stock market prediction
using neural networks are investigated to determine its effectiveness
as inputs. The feed forward neural network of Levenberg-Marquardt
algorithm is applied to perform one step ahead forecasting of
NASDAQ and Dow stock prices.
Abstract: In this paper, the decomposition-aggregation method
is used to carry out connective stability criteria for general linear
composite system via aggregation. The large scale system is
decomposed into a number of subsystems. By associating directed
graphs with dynamic systems in an essential way, we define the
relation between system structure and stability in the sense of
Lyapunov. The stability criteria is then associated with the stability
and system matrices of subsystems as well as those interconnected
terms among subsystems using the concepts of vector differential
inequalities and vector Lyapunov functions. Then, we show that the
stability of each subsystem and stability of the aggregate model
imply connective stability of the overall system. An example is
reported, showing the efficiency of the proposed technique.
Abstract: Air emissions from waste treatment plants often
consist of a combination of Volatile Organic Compounds (VOCs)
and odors. Hydrogen sulfide is one of the major odorous gases
present in the waste emissions coming from municipal wastewater
treatment facilities. Hydrogen sulfide (H2S) is odorous, highly toxic
and flammable. Exposure to lower concentrations can result in eye
irritation, a sore throat and cough, shortness of breath, and fluid in
the lungs. Biofiltration has become a widely accepted technology for
treating air streams containing H2S. When compared with other nonbiological
technologies, biofilter is more cost-effective for treating large
volumes of air containing low concentrations of biodegradable compounds.
Optimization of biofilter media is essential for many reasons such as:
providing a higher surface area for biofilm growth, low pressure drop,
physical stability, and good moisture retention. In this work, a novel
biofilter media is developed and tested at a pumping station of a
municipality located in the United Arab Emirates (UAE). The
media is found to be very effective (>99%) in removing H2S
concentrations that are expected in pumping stations under steady
state and shock loading conditions.
Abstract: This paper introduces an approach to construct a set of criteria for evaluating alternative options. Content analysis was used to collet criterion elements. Then the elements were classified and organized yielding to hierarchic structure. The reliability of the constructed criteria was evaluated in an experiment. Finally the criteria were used to evaluate alternative options indecision-making.
Abstract: Society has grown to rely on Internet services, and the
number of Internet users increases every day. As more and more
users become connected to the network, the window of opportunity
for malicious users to do their damage becomes very great and
lucrative. The objective of this paper is to incorporate different
techniques into classier system to detect and classify intrusion from
normal network packet. Among several techniques, Steady State
Genetic-based Machine Leaning Algorithm (SSGBML) will be used
to detect intrusions. Where Steady State Genetic Algorithm (SSGA),
Simple Genetic Algorithm (SGA), Modified Genetic Algorithm and
Zeroth Level Classifier system are investigated in this research.
SSGA is used as a discovery mechanism instead of SGA. SGA
replaces all old rules with new produced rule preventing old good
rules from participating in the next rule generation. Zeroth Level
Classifier System is used to play the role of detector by matching
incoming environment message with classifiers to determine whether
the current message is normal or intrusion and receiving feedback
from environment. Finally, in order to attain the best results,
Modified SSGA will enhance our discovery engine by using Fuzzy
Logic to optimize crossover and mutation probability. The
experiments and evaluations of the proposed method were performed
with the KDD 99 intrusion detection dataset.
Abstract: The increasing complexity of software development based on peer to peer networks makes necessary the creation of new frameworks in order to simplify the developer-s task. Additionally, some applications, e.g. fire detection or security alarms may require real-time constraints and the high level definition of these features eases the application development. In this paper, a service model based on a component model with real-time features is proposed. The high-level model will abstract developers from implementation tasks, such as discovery, communication, security or real-time requirements. The model is oriented to deploy services on small mobile devices, such as sensors, mobile phones and PDAs, where the computation is light-weight. Services can be composed among them by means of the port concept to form complex ad-hoc systems and their implementation is carried out using a component language called UM-RTCOM. In order to apply our proposals a fire detection application is described.
Abstract: The rapid urbanization of cities has a bane in the form
road accidents that cause extensive damage to life and limbs. A
number of location based factors are enablers of road accidents in the
city. The speed of travel of vehicles is non-uniform among locations
within a city. In this study, the perception of vehicle users is captured
on a 10-point rating scale regarding the degree of variation in speed
of travel at chosen locations in the city. The average rating is used to
cluster locations using fuzzy c-means clustering and classify them as
low, moderate and high speed of travel locations. The high speed of
travel locations can be classified proactively to ensure that accidents
do not occur due to the speeding of vehicles at such locations. The
advantage of fuzzy c-means clustering is that a location may be a
part of more than one cluster to a varying degree and this gives a
better picture about the location with respect to the characteristic
(speed of travel) being studied.
Abstract: An empirical linearly-hyperbolic approximation of the I - V characteristic of a solar cell is presented. This approximation is based on hyperbolic dependence of a current of p-n junctions on voltage for large currents. Such empirical approximation is compared with the early proposed formal linearly-hyperbolic approximation of a solar cell. The expressions defining laws of change of parameters of formal approximation at change of a photo current of family of characteristics are received. It allows simplifying a finding of parameters of approximation on actual curves, to specify their values. Analytical calculation of load regime for linearly - hyperbolic model leads to quadratic equation. Also, this model allows to define soundly a deviation from the maximum power regime and to compare efficiency of regimes of solar cells with different parameters.
Abstract: In this paper we consider the issue of distributed adaptive estimation over sensor networks. To deal with more realistic scenario, different variance for observation noise is assumed for sensors in the network. To solve the problem of different variance of observation noise, the proposed method is divided into two phases: I) Estimating each sensor-s observation noise variance and II) using the estimated variances to obtain the desired parameter. Our proposed algorithm is based on a diffusion least mean square (LMS) implementation with linear combiner model. In the proposed algorithm, the step-size parameter the coefficients of linear combiner are adjusted according to estimated observation noise variances. As the simulation results show, the proposed algorithm considerably improves the diffusion LMS algorithm given in literature.
Abstract: This study was conducted to investigate the incidence
of pathogenic bacteria: Salmonella, Shigella, Escherichia coli O157
and Staphylococcus aureus in cakes and tarts collected from thirtyfive
confectionery producing and selling premises located within
Tripoli city, Libya. The results revealed an incidence of S. aureus
with 94.4 and 48.0 %, E. coli O157 with 14.7 and 4.0 % and Salmonella
sp. with 5.9 and 8.0 % in cakes and tarts samples respectively;
while Shigella was not detected in all samples. In order to determine
the source of these pathogenic bacteria, cotton swabs were taken
from the hands of workers on the production line, the surfaces of
preparation tables and cream whipping instruments. The results
showed that the cotton swabs obtained from the hands of workers
contained S. aureus and Salmonella sp. with an incidence of 42.9 and
2.9 %, the cotton swabs obtained from the surfaces of preparation
tables 22.9 and 2.9 % and the cotton swabs obtained from the cream
whipping instruments 14.3 and 0.0 % respectively; while E. coli
O157 and Shigella sp. were not detected in all swabs. Additionally,
other bacteria were isolated from the hands of workers and the Surfaces
of producing equipments included: Aeromonas sp., Pseudomonas
sp., E. coli, Klebsiella sp., Enterobacter sp., Citrobacter sp.,
Proteus sp., Serratia sp. and Acinetobacter sp. These results indicate
that some of the cakes and tarts might pose threat to consumer's
health. Meanwhile, occurrences of pathogenic bacteria on the hands
of those who are working in production line and the surfaces of
equipments reflect poor hygienic practices at most confectionery
premises examined in this study. Thus, firm and continuous surveillance
of these premises is needed to insure the consumer's health and
safety.
Abstract: Khao Yai National Park is the First National Park in
Thailand and approximately 800,000 tourists visited Khao Yai yearly.
This study aimed to identify the perception of tourists in Khao Yai
National Park according to the implementation of eco-friendly
cleansers along their leisure in the campsites. Due to tourist’s
activities in the park were affected on quality of environment;
especially on water resource. Therefore, eco-friendly cleansers were
used in campsites for tourists and restaurants during high tourist
season. The results indicated positive effects of environmental
friendly cleansers on water quality in Lam Ta Khong River, as well
as the tourist’s perception on eco-friendly cleansers.
Abstract: The Bangalore City is facing the acute problem of
pollution in the atmosphere due to the heavy increase in the traffic
and developmental activities in recent years. The present study is an
attempt in the direction to assess trend of the ambient air quality
status of three stations, viz., AMCO Batteries Factory, Mysore Road,
GRAPHITE INDIA FACTORY, KHB Industrial Area, Whitefield
and Ananda Rao Circle, Gandhinagar with respect to some of the
major criteria pollutants such as Total Suspended particular matter
(SPM), Oxides of nitrogen (NOx), and Oxides of sulphur (SO2). The
sites are representative of various kinds of growths viz., commercial,
residential and industrial, prevailing in Bangalore, which are
contributing to air pollution. The concentration of Sulphur Dioxide
(SO2) at all locations showed a falling trend due to use of refined
petrol and diesel in the recent years. The concentration of Oxides of
nitrogen (NOx) showed an increasing trend but was within the
permissible limits. The concentration of the Suspended particular
matter (SPM) showed the mixed trend. The correlation between
model and observed values is found to vary from 0.4 to 0.7 for SO2,
0.45 to 0.65 for NOx and 0.4 to 0.6 for SPM. About 80% of data is
observed to fall within the error band of ±50%. Forecast test for the
best fit models showed the same trend as actual values in most of the
cases. However, the deviation observed in few cases could be
attributed to change in quality of petro products, increase in the
volume of traffic, introduction of LPG as fuel in many types of
automobiles, poor condition of roads, prevailing meteorological
conditions, etc.
Abstract: This study analyzed environmental health risks and
people-s perceptions of risks related to waste management in poor
settlements of Abidjan, to develop integrated solutions for health and
well-being improvement. The trans-disciplinary approach used relied
on remote sensing, a geographic information system (GIS),
qualitative and quantitative methods such as interviews and a
household survey (n=1800). Mitigating strategies were then
developed using an integrated participatory stakeholder workshop.
Waste management deficiencies resulting in lack of drainage and
uncontrolled solid and liquid waste disposal in the poor settlements
lead to severe environmental health risks. Health problems were
caused by direct handling of waste, as well as through broader
exposure of the population. People in poor settlements had little
awareness of health risks related to waste management in their
community and a general lack of knowledge pertaining to sanitation
systems. This unfortunate combination was the key determinant
affecting the health and vulnerability. For example, an increased
prevalence of malaria (47.1%) and diarrhoea (19.2%) was observed
in the rainy season when compared to the dry season (32.3% and
14.3%). Concerted and adapted solutions that suited all the
stakeholders concerned were developed in a participatory workshop
to allow for improvement of health and well-being.
Abstract: An electrocardiogram (ECG) feature extraction system
based on the calculation of the complex resonance frequency
employing Prony-s method is developed. Prony-s method is applied
on five different classes of ECG signals- arrhythmia as a finite sum
of exponentials depending on the signal-s poles and the resonant
complex frequencies. Those poles and resonance frequencies of the
ECG signals- arrhythmia are evaluated for a large number of each
arrhythmia. The ECG signals of lead II (ML II) were taken from
MIT-BIH database for five different types. These are the ventricular
couplet (VC), ventricular tachycardia (VT), ventricular bigeminy
(VB), and ventricular fibrillation (VF) and the normal (NR). This
novel method can be extended to any number of arrhythmias.
Different classification techniques were tried using neural networks
(NN), K nearest neighbor (KNN), linear discriminant analysis (LDA)
and multi-class support vector machine (MC-SVM).
Abstract: Mobile IPv6 (MIPv6) describes how mobile node can change its point of attachment from one access router to another. As a demand for wireless mobile devices increases, many enhancements for macro-mobility (inter-domain) protocols have been proposed, designed and implemented in Mobile IPv6. Hierarchical Mobile IPv6 (HMIPv6) is one of them that is designed to reduce the amount of signaling required and to improve handover speed for mobile connections. This is achieved by introducing a new network entity called Mobility Anchor Point (MAP). This report presents a comparative study of the Hierarchical Mobility IPv6 and Mobile IPv6 protocols and we have narrowed down the scope to micro-mobility (intra-domain). The architecture and operation of each protocol is studied and they are evaluated based on the Quality of Service (QoS) parameter; handover latency. The simulation was carried out by using the Network Simulator-2. The outcome from this simulation has been discussed. From the results, it shows that, HMIPv6 performs best under intra-domain mobility compared to MIPv6. The MIPv6 suffers large handover latency. As enhancement we proposed to HMIPv6 to locate the MAP to be in the middle of the domain with respect to all Access Routers. That gives approximately same distance between MAP and Mobile Node (MN) regardless of the new location of MN, and possible shorter distance. This will reduce the delay since the distance is shorter. As a future work performance analysis is to be carried for the proposed HMIPv6 and compared to HMIPv6.
Abstract: A new robust nonlinear control scheme of a manipulator is proposed in this paper which is robust against modeling errors and unknown disturbances. It is based on the principle of variable structure control, with sliding mode control (SMC) method. The variable structure control method is a robust method that appears to be well suited for robotic manipulators because it requers only bounds on the robotic arm parameters. But there is no single systematic procedure that is guaranteed to produce a suitable control law. Also, to reduce chattring of the control signal, we replaced the sgn function in the control law by a continuous approximation such as tangant function. We can compute the maximum load with regard to applied torque into joints. The effectivness of the proposed approach has been evaluated analitically demonstrated through computer simulations for the cases of variable load and robot arm parameters.
Abstract: The Multi-Layered Perceptron (MLP) Neural
networks have been very successful in a number of signal processing
applications. In this work we have studied the possibilities and the
met difficulties in the application of the MLP neural networks for the
prediction of daily solar radiation data. We have used the Polack-Ribière algorithm for training the neural networks. A comparison, in
term of the statistical indicators, with a linear model most used in
literature, is also performed, and the obtained results show that the
neural networks are more efficient and gave the best results.
Abstract: This study explored the correlates of forgiving
historical racial offenses and the relationship between daily
experiences of racism and forgiving historical racial offenses. 147
African Americans participated to the study. Results indicated that
guilt attribution, distrust, need of reparations, religion, and perception
of apology relate to forgiving past racial offenses. In addition the
more individuals experience racism related events, the less likely
they forgive the past mistreatments of African Americans.
Abstract: This paper presents the study of parameters affecting
the environment protection in the printing industry. The paper has
also compared LCA studies performed within the printing industry in
order to identify common practices, limitations, areas for
improvement, and opportunities for standardization. This comparison
is focused on the data sources and methodologies used in the printing
pollutants register. The presented concepts, methodology and results
represent the contribution to the sustainable development
management. Furthermore, the paper analyzes the result of the
quantitative identification of hazardous substances emitted in printing
industry of Novi Sad.