Abstract: A comparison between the performance of Latin and
Arabic handwritten digits recognition problems is presented. The
performance of ten different classifiers is tested on two similar
Arabic and Latin handwritten digits databases. The analysis shows
that Arabic handwritten digits recognition problem is easier than that
of Latin digits. This is because the interclass difference in case of
Latin digits is smaller than in Arabic digits and variances in writing
Latin digits are larger. Consequently, weaker yet fast classifiers are
expected to play more prominent role in Arabic handwritten digits
recognition.
Abstract: Image data holds a large amount of different context
information. However, as of today, these resources remain largely
untouched. It is thus the aim of this paper to present a basic technical
framework which allows for a quick and easy exploitation of context
information from image data especially by non-expert users.
Furthermore, the proposed framework is discussed in detail
concerning important social and ethical issues which demand special
requirements in system design. Finally, a first sensor prototype is
presented which meets the identified requirements. Additionally,
necessary implications for the software and hardware design of the
system are discussed, rendering a sensor system which could be
regarded as a good, acceptable and justifiable technical and thereby
enabling the extraction of context information from image data.
Abstract: Coal fly ash (CFA) generated by coal-based thermal
power plants is mainly composed of quartz, mullite, and unburned
carbon. In this study, the effect of unburned carbon on CFA toward
its adsorption capacity was investigated. CFA with various carbon
content was obtained by refluxing it with sulfuric acid having various
concentration at various temperature and reflux time, by heating at
400-800°C, and by sieving into 100-mesh in particle size. To
evaluate the effect of unburned carbon on CFA toward its adsorption
capacity, adsorption of methyl violet solution with treated CFA was
carried out. The research shows that unburned carbon leads to
adsorption capacity decrease. The highest adsorption capacity of
treated CFA was found 5.73 x 10-4mol.g-1.
Abstract: In many industries, control charts is one of the most
frequently used tools for quality management. Hotelling-s T2 is used
widely in multivariate control chart. However, it has little defect when
detecting small or medium process shifts. The use of supplementary
sensitizing rules can improve the performance of detection. This study
applied sensitizing rules for Hotelling-s T2 control chart to improve the
performance of detection. Support vector machines (SVM) classifier
to identify the characteristic or group of characteristics that are
responsible for the signal and to classify the magnitude of the mean
shifts. The experimental results demonstrate that the support vector
machines (SVM) classifier can effectively identify the characteristic
or group of characteristics that caused the process mean shifts and the
magnitude of the shifts.
Abstract: A double module hollow fiber supported liquid
membrane (HFSLM) was applied to selectively separate lead and
mercury ions from dilute synthetic produced water. The experiments
were investigated on several variables: types of extractants
(D2EHPA, Cyanex 471, Aliquat 336, and TOA), concentration of the
selected extractant and operating time. The results clearly showed
that the double module HFSLM could selectively separate Pb(II) and
Hg(II) in feed solution at a very low concentration to less than the
regulatory discharge limit of 0.2 and 0.005 mg/L issued by the
Ministry of Industry and the Ministry of Natural Resource
Environment, Thailand. The highest extractions of lead and mercury
ions from synthetic produced water were 96% and 100% using 0.03
M D2EHPA and 0.06 M Aliquat 336 as the extractant for the first
and second modules.
Abstract: In the context of sensor networks, where every few
dB saving counts, the novel node cooperation schemes are reviewed
where MIMO techniques play a leading role. These methods could be
treated as joint approach for designing physical layer of their
communication scenarios. Then we analyzed the BER performance
of transmission diversity schemes under a general fading channel
model and proposed a power allocation strategy to the transmitting
sensor nodes. This approach is then compared to an equal-power
assignment method and its performance enhancement is verified by
the simulation. Another key point of the contribution lies in the
combination of optimal power allocation and sensor nodes-
cooperation in a transmission diversity regime (MISO). Numerical
results are given through figures to demonstrate the optimality and
efficiency of proposed combined approach.
Abstract: SoftBoost is a recently presented boosting algorithm,
which trades off the size of achieved classification margin and
generalization performance. This paper presents a performance
evaluation of SoftBoost algorithm on the generic object recognition
problem. An appearance-based generic object recognition
model is used. The evaluation experiments are performed using
a difficult object recognition benchmark. An assessment with respect
to different degrees of label noise as well as a comparison to
the well known AdaBoost algorithm is performed. The obtained
results reveal that SoftBoost is encouraged to be used in cases
when the training data is known to have a high degree of noise.
Otherwise, using Adaboost can achieve better performance.
Abstract: The presence of harmonic in power system is a major
concerned to power engineers for many years. With the increasing
usage of nonlinear loads in power systems, the harmonic pollution
becomes more serious. One of the widely used computation
algorithm for harmonic analysis is fast Fourier transform (FFT). In
this paper, a harmonic analyzer using FFT was implemented on
TMS320C6713 DSK. The supply voltage of 240 V 59 Hz is stepped
down to 5V using a voltage divider in order to match the power
rating of the DSK input. The output from the DSK was displayed on
oscilloscope and Code Composer Studio™ software. This work has
demonstrated the possibility of analyzing the 240V power supply
harmonic content using the DSK board.
Abstract: Coated tool inserts can be considered as the backbone
of machining processes due to their wear and heat resistance.
However, defects of coating can degrade the integrity of these inserts
and the number of these defects should be minimized or eliminated if
possible. Recently, the advancement of coating processes and
analytical tools open a new era for optimizing the coating tools.
First, an overview is given regarding coating technology for cutting
tool inserts. Testing techniques for coating layers properties, as well
as the various coating defects and their assessment are also surveyed.
Second, it is introduced an experimental approach to examine the
possible coating defects and flaws of worn multicoated carbide
inserts using two important techniques namely scanning electron
microscopy and atomic force microscopy. Finally, it is
recommended a simple procedure for investigating manufacturing
defects and flaws of worn inserts.
Abstract: Nowadays, people are going more and more mobile, both in terms of devices and associated applications. Moreover, services that these devices are offering are getting wider and much more complex. Even though actual handheld devices have considerable computing power, their contexts of utilization are different. These contexts are affected by the availability of connection, high latency of wireless networks, battery life, size of the screen, on-screen or hard keyboard, etc. Consequently, development of mobile applications and their associated mobile Web services, if any, should follow a concise methodology so they will provide a high Quality of Service. The aim of this paper is to highlight and discuss main issues to consider when developing mobile applications and mobile Web services and then propose a framework that leads developers through different steps and modules toward development of efficient and secure mobile applications. First, different challenges in developing such applications are elicited and deeply discussed. Second, a development framework is presented with different modules addressing each of these challenges. Third, the paper presents an example of a mobile application, Eivom Cinema Guide, which benefits from following our development framework.
Abstract: This paper presents a formant-tracking linear prediction
(FTLP) model for speech processing in noise. The main focus of this
work is the detection of formant trajectory based on Hidden Markov
Models (HMM), for improved formant estimation in noise. The
approach proposed in this paper provides a systematic framework for
modelling and utilization of a time- sequence of peaks which satisfies
continuity constraints on parameter; the within peaks are modelled
by the LP parameters. The formant tracking LP model estimation
is composed of three stages: (1) a pre-cleaning multi-band spectral
subtraction stage to reduce the effect of residue noise on formants
(2) estimation stage where an initial estimate of the LP model of
speech for each frame is obtained (3) a formant classification using
probability models of formants and Viterbi-decoders. The evaluation
results for the estimation of the formant tracking LP model tested
in Gaussian white noise background, demonstrate that the proposed
combination of the initial noise reduction stage with formant tracking
and LPC variable order analysis, results in a significant reduction in
errors and distortions. The performance was evaluated with noisy
natual vowels extracted from international french and English vocabulary
speech signals at SNR value of 10dB. In each case, the
estimated formants are compared to reference formants.
Abstract: This paper investigates the issue of building decision
trees from data with imprecise class values where imprecision is
encoded in the form of possibility distributions. The Information
Affinity similarity measure is introduced into the well-known gain
ratio criterion in order to assess the homogeneity of a set of
possibility distributions representing instances-s classes belonging to
a given training partition. For the experimental study, we proposed an
information affinity based performance criterion which we have used
in order to show the performance of the approach on well-known
benchmarks.
Abstract: This paper presents a design and prototype
implementation of new home automation system that uses WiFi
technology as a network infrastructure connecting its parts. The
proposed system consists of two main components; the first part is
the server (web server), which presents system core that manages,
controls, and monitors users- home. Users and system administrator
can locally (LAN) or remotely (internet) manage and control system
code. Second part is hardware interface module, which provides
appropriate interface to sensors and actuator of home automation
system. Unlike most of available home automation system in the
market the proposed system is scalable that one server can manage
many hardware interface modules as long as it exists on WiFi
network coverage. System supports a wide range of home
automation devices like power management components, and
security components. The proposed system is better from the
scalability and flexibility point of view than the commercially
available home automation systems.
Abstract: Plastic waste is a big issue in Thailand, but the amount of recycled plastic in Thailand is still low due to the high investment and operating cost. Hence, the rest of plastic waste are burnt to destroy or sent to the landfills. In order to be financial viable, an effective reverse logistics infrastructure is required to support the product recovery activities. However, there is a conflict between reducing the cost and raising environmental protection level. The purpose of this study is to build a goal programming (GP) so that it can be used to help analyze the proper planning of the Thailand-s plastic recycling system that involves multiple objectives. This study considers three objectives; reducing total cost, increasing the amount of plastic recovery, and raising the desired plastic materials in recycling process. The results from two priority structures show that it is necessary to raise the total cost budget in order to achieve targets on amount of recycled plastic and desired plastic materials.
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: This work presents a matched field processing (MFP)
algorithm based on Dopplerlet transform for estimating the motion
parameters of a sound source moving along a straight line and with a
constant speed by using a piecewise strategy, which can significantly
reduce the computational burden. Monte Carlo simulation results and
an experimental result are presented to verify the effectiveness of the
algorithm advocated.
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.