Abstract: In this paper a new fast simplification method is
presented. Such method realizes Karnough map with large
number of variables. In order to accelerate the operation of the
proposed method, a new approach for fast detection of group
of ones is presented. Such approach implemented in the
frequency domain. The search operation relies on performing
cross correlation in the frequency domain rather than time one.
It is proved mathematically and practically that the number of
computation steps required for the presented method is less
than that needed by conventional cross correlation. Simulation
results using MATLAB confirm the theoretical computations.
Furthermore, a powerful solution for realization of complex
functions is given. The simplified functions are implemented
by using a new desigen for neural networks. Neural networks
are used because they are fault tolerance and as a result they
can recognize signals even with noise or distortion. This is
very useful for logic functions used in data and computer
communications. Moreover, the implemented functions are
realized with minimum amount of components. This is done
by using modular neural nets (MNNs) that divide the input
space into several homogenous regions. Such approach is
applied to implement XOR function, 16 logic functions on one
bit level, and 2-bit digital multiplier. Compared to previous
non- modular designs, a clear reduction in the order of
computations and hardware requirements is achieved.
Abstract: This paper investigates the problem of spreading
sequence and receiver code synchronization techniques for satellite
based CDMA communications systems. The performance of CDMA
system depends on the autocorrelation and cross-correlation
properties of the used spreading sequences. In this paper we propose
the uses of chaotic Lu system to generate binary sequences for
spreading codes in a direct sequence spread CDMA system. To
minimize multiple access interference (MAI) we propose the use of
genetic algorithm for optimum selection of chaotic spreading
sequences. To solve the problem of transmitter-receiver
synchronization, we use the passivity controls. The concept of
semipassivity is defined to find simple conditions which ensure
boundedness of the solutions of coupled Lu systems. Numerical
results are presented to show the effectiveness of the proposed
approach.
Abstract: This paper aimed to study the factors that relate to
working behavior of employees at Pakkred Municipality, Nonthaburi
Province. A questionnaire was utilized as the tool in collecting
information. Descriptive statistics included frequency, percentage,
mean and standard deviation. Independent- sample t- test, analysis of
variance and Pearson Correlation were also used. The findings of this
research revealed that the majority of the respondents were female,
between 25- 35 years old, married, with a Bachelor degree. The
average monthly salary of respondents was between 8,001- 12,000
Baht, and having about 4-7 years of working experience. Regarding
the overall working motivation factors, the findings showed that
interrelationship, respect, and acceptance were ranked as highly
important factors, whereas motivation, remunerations & welfare,
career growth, and working conditions were ranked as moderately
important factors. Also, overall working behavior was ranked as high.
The hypotheses testing revealed that different genders had a
different working behavior and had a different way of working as a
team, which was significant at the 0.05 confidence level, Moreover,
there was a difference among employees with different monthly
salary in working behavior, problem- solving and decision making,
which all were significant at the 0.05 confidence level. Employees
with different years of working experience were found to have work
working behavior both individual and as a team at the statistical
significance level of 0.01 and 0.05. The result of testing the
relationship between motivation in overall working revealed that
interrelationship, respect and acceptance from others, career growth,
and working conditions related to working behavior at a moderate
level, while motivation in performing duties and remunerations and
welfares related to working behavior towards the same direction at a
low level, with a statistical significance of 0.01.
Abstract: Face and facial expressions play essential roles in
interpersonal communication. Most of the current works on the facial
expression recognition attempt to recognize a small set of the
prototypic expressions such as happy, surprise, anger, sad, disgust
and fear. However the most of the human emotions are
communicated by changes in one or two of discrete features. In this
paper, we develop a facial expressions synthesis system, based on the
facial characteristic points (FCP's) tracking in the frontal image
sequences. Selected FCP's are automatically tracked using a crosscorrelation
based optical flow. The proposed synthesis system uses a
simple deformable facial features model with a few set of control
points that can be tracked in original facial image sequences.
Abstract: In this paper, the effect of receive and/or transmit
antenna spacing on the performance (BER vs. SNR) of multipleantenna
systems is determined by using an RCS (Radar Cross
Section) channel model. In this physical model, the scatterers
existing in the propagation environment are modeled by their RCS so
that the correlation of the receive signal complex amplitudes, i.e.,
both magnitude and phase, can be estimated. The proposed RCS
channel model is then compared with classical models.
Abstract: Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows drawing conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stageby- stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.
Abstract: Feature selection plays an important role in applications with high dimensional data. The assessment of the stability of feature selection/ranking algorithms becomes an important issue when the dataset is small and the aim is to gain insight into the underlying process by analyzing the most relevant features. In this work, we propose a graphical approach that enables to analyze the similarity between feature ranking techniques as well as their individual stability. Moreover, it works with whatever stability metric (Canberra distance, Spearman's rank correlation coefficient, Kuncheva's stability index,...). We illustrate this visualization technique evaluating the stability of several feature selection techniques on a spectral binary dataset. Experimental results with a neural-based classifier show that stability and ranking quality may not be linked together and both issues have to be studied jointly in order to offer answers to the domain experts.
Abstract: This study develops a relation to explore the factors influencing management and technology capabilities in strategic alliances. Alliances between firms are recognizing increasingly popular as a vehicle to create and extract greater value from the market. Firm’s alliance can be described as the collaborative problem solving process to solve problems jointly. This study starts from research questions what factors of firm’s management and technology characteristics affect performance of firms which are formed alliances. In this study, we investigated the effect of strategic alliances on company performance. That is, we try to identify whether firms made an alliance with other organizations are differed by characteristics of management and technology. And we test that alliance type and alliance experiences moderate the relationship between firm’s capabilities and its performance. We employ problem-solving perspective and resource-based view perspective to shed light on this research questions. The empirical work is based on the Survey of Business Activities conducted from2006 to 2008 by Statistics Korea. We verify correlations between to point out that these results contribute new empirical evidence on the effect of strategic alliances on company performance.
Abstract: This paper presents a distributed intrusion
detection system IDS, based on the concept of specialized
distributed agents community representing agents with the
same purpose for detecting distributed attacks. The semantic of
intrusion events occurring in a predetermined network has been
defined. The correlation rules referring the process which our
proposed IDS combines the captured events that is distributed
both spatially and temporally. And then the proposed IDS tries
to extract significant and broad patterns for set of well-known
attacks. The primary goal of our work is to provide intrusion
detection and real-time prevention capability against insider
attacks in distributed and fully automated environments.
Abstract: Wireless Sensor Network is Multi hop Self-configuring
Wireless Network consisting of sensor nodes. The deployment of
wireless sensor networks in many application areas, e.g., aggregation
services, requires self-organization of the network nodes into clusters.
Efficient way to enhance the lifetime of the system is to partition the
network into distinct clusters with a high energy node as cluster head.
The different methods of node clustering techniques have appeared in
the literature, and roughly fall into two families; those based on the
construction of a dominating set and those which are based solely on
energy considerations. Energy optimized cluster formation for a set
of randomly scattered wireless sensors is presented. Sensors within a
cluster are expected to be communicating with cluster head only. The
energy constraint and limited computing resources of the sensor nodes
present the major challenges in gathering the data. In this paper we
propose a framework to study how partially correlated data affect the
performance of clustering algorithms. The total energy consumption
and network lifetime can be analyzed by combining random geometry
techniques and rate distortion theory. We also present the relation
between compression distortion and data correlation.
Abstract: A low-complexity, high-accurate frequency offset
estimation for multi-band orthogonal frequency division multiplexing (MB-OFDM) based ultra-wide band systems is presented regarding different carrier frequency offsets, different channel frequency
responses, different preamble patterns in different bands. Utilizing a
half-cycle Constant Amplitude Zero Auto Correlation (CAZAC) sequence as the preamble sequence, the estimator with a semi-cross
contrast scheme between two successive OFDM symbols is proposed. The CRLB and complexity of the proposed algorithm are derived.
Compared to the reference estimators, the proposed method achieves
significantly less complexity (about 50%) for all preamble patterns of the MB-OFDM systems. The CRLBs turn out to be of well performance.
Abstract: Cryo-electron microscopy (CEM) in combination with
single particle analysis (SPA) is a widely used technique for
elucidating structural details of macromolecular assemblies at closeto-
atomic resolutions. However, development of automated software
for SPA processing is still vital since thousands to millions of
individual particle images need to be processed. Here, we present our
workflow for automated particle picking. Our approach integrates
peak shape analysis to the classical correlation and an iterative
approach to separate macromolecules and background by
classification. This particle selection workflow furthermore provides
a robust means for SPA with little user interaction. Processing
simulated and experimental data assesses performance of the
presented tools.
Abstract: Overloading is a technique to accommodate more
number of users than the spreading factor N. This is a bandwidth
efficient scheme to increase the number users in a fixed bandwidth.
One of the efficient schemes to overload a CDMA system is to use
two sets of orthogonal signal waveforms (O/O). The first set is
assigned to the N users and the second set is assigned to the
additional M users. An iterative interference cancellation technique is
used to cancel interference between the two sets of users. In this
paper, the performance of an overloading scheme in which the first N
users are assigned Walsh-Hadamard orthogonal codes and extra users
are assigned the same WH codes but overlaid by a fixed (quasi) bent
sequence [11] is evaluated. This particular scheme is called Quasi-
Orthogonal Sequence (QOS) O/O scheme, which is a part of
cdma2000 standard [12] to provide overloading in the downlink
using single user detector. QOS scheme are balance O/O scheme,
where the correlation between any set-1 and set-2 users are
equalized. The allowable overload of this scheme is investigated in
the uplink on an AWGN and Rayleigh fading channels, so that the
uncoded performance with iterative multistage interference
cancellation detector remains close to the single user bound. It is
shown that this scheme provides 19% and 11% overloading with
SDIC technique for N= 16 and 64 respectively, with an SNR
degradation of less than 0.35 dB as compared to single user bound at
a BER of 0.00001. But on a Rayleigh fading channel, the channel
overloading is 45% (29 extra users) at a BER of 0.0005, with an SNR
degradation of about 1 dB as compared to single user performance
for N=64. This is a significant amount of channel overloading on a
Rayleigh fading channel.
Abstract: The objectives of this research were to explore factors
influencing knowledge management process in the manufacturing
industry and develop a model to support knowledge management
processes. The studied factors were technology infrastructure, human
resource, knowledge sharing, and the culture of the organization. The
knowledge management processes included discovery, capture,
sharing, and application. Data were collected through questionnaires
and analyzed using multiple linear regression and multiple
correlation. The results found that technology infrastructure, human
resource, knowledge sharing, and culture of the organization
influenced the discovery and capture processes. However, knowledge
sharing had no influence in sharing and application processes. A
model to support knowledge management processes was developed,
which indicated that sharing knowledge needed further improvement
in the organization.
Abstract: Estimates of temperature values at a specific time of day, from daytime and daily profiles, are needed for a number of environmental, ecological, agricultural and technical applications, ranging from natural hazards assessments, crop growth forecasting to design of solar energy systems. The scope of this research is to investigate the efficiency of data mining techniques in estimating minimum, maximum and mean temperature values. For this reason, a number of experiments have been conducted with well-known regression algorithms using temperature data from the city of Patras in Greece. The performance of these algorithms has been evaluated using standard statistical indicators, such as Correlation Coefficient, Root Mean Squared Error, etc.
Abstract: In the past, there were many bridge-s collapses due to
lack of bridge structural capacity information. Most of concrete
bridge health was relied on information from visual inspection, which
sometime was inadequate. This study was conducted in order to
investigate relationship between bridge structural condition and
bridge visual condition. This study was a part of a big project
conducted at Department of Highways of Thailand. In this study, 31
bridges including slab-type bridges, plank-girder bridges, prestressed
box-beam bridges, prestressed I-girder bridges and prestressed multibeam
bridges were selected for visual inspection and load test. It was
found a positive correlation between bridge appearance and bridge-s
load carrying capacity. However, statistical characteristic revealed
low correlation between them.
Abstract: Periodicities in the environmetric time series can be
idyllically assessed by utilizing periodic models. In this
communication fugitive emission of gases from open sewer channel
Lyari which follows periodic behaviour are approximated by
employing periodic autoregressive model of order p. The orders of
periodic model for each season are selected through the examination
of periodic partial autocorrelation or information criteria. The
parameters for the selected order of season are estimated individually
for each emitted air toxin. Subsequently, adequacies of fitted models
are established by examining the properties of the residual for each
season. These models are beneficial for schemer and administrative
bodies for the improvement of implemented policies to surmount
future environmental problems.
Abstract: Internet addiction has become a critical problem on
adolescents in Taiwan, and its negative effects on various dimensions
of adolescent development caught the attention of educational and
psychological experts. This study examined the correlation between
cognitive (locus of control) and emotion (emotion venting strategies)
factors on internet addiction of adolescents in Taiwan. Using the
Compulsive Internet Use (CIU) and the Emotion Venting Strategy
scales, a survey was conducted and 215 effective samples (students
ranging from12 to14 years old) returned. Quantitative analysis
methods such as descriptive statistics, t-test, ANOVA, Pearson
correlations and multiple regression were adopted. The results were as
follows: 1. Severity of Internet addiction has significant gender
differences; boys were at a higher risk than girls in becoming addicted
to the Internet. 2. Emotion venting, locus of control and internet
addiction have been shown to be positive correlated with one another.
3. Setting the locus of control as the control variable, emotion venting
strategy has positive and significant contribution to internet addiction.
The results of this study suggest that coaching deconstructive emotion
strategies and cognitive believes are encouraged to integrate with
actual field work.
Abstract: Acute toxicity of nano SiO2, ZnO, MCM-41 (Meso
pore silica), Cu, Multi Wall Carbon Nano Tube (MWCNT), Single
Wall Carbon Nano Tube (SWCNT) , Fe (Coated) to bacteria Vibrio
fischeri using a homemade luminometer , was evaluated. The values
of the nominal effective concentrations (EC), causing 20% and 50%
inhibition of biouminescence, using two mathematical models at two
times of 5 and 30 minutes were calculated. Luminometer was
designed with Photomultiplier (PMT) detector. Luminol
chemiluminescence reaction was carried out for the calibration graph.
In the linear calibration range, the correlation coefficients and
coefficient of Variation (CV) were 0.988 and 3.21% respectively
which demonstrate the accuracy and reproducibility of the instrument
that are suitable. The important part of this research depends on how
to optimize the best condition for maximum bioluminescence. The
culture of Vibrio fischeri with optimal conditions in liquid media,
were stirring at 120 rpm at a temperature of 150C to 180C and were
incubated for 24 to 72 hours while solid medium was held at 180C
and for 48 hours. Suspension of nanoparticles ZnO, after 30 min
contact time to bacteria Vibrio fischeri, showed the highest toxicity
while SiO2 nanoparticles showed the lowest toxicity. After 5 min
exposure time, the toxicity of ZnO was the strongest and MCM-41
was the weakest toxicant component.
Abstract: Motion detection is a basic operation in the selection of significant segments of the video signals. For an effective Human Computer Intelligent Interaction, the computer needs to recognize the motion and track the moving object. Here an efficient neural network system is proposed for motion detection from the static background. This method mainly consists of four parts like Frame Separation, Rough Motion Detection, Network Formation and Training, Object Tracking. This paper can be used to verify real time detections in such a way that it can be used in defense applications, bio-medical applications and robotics. This can also be used for obtaining detection information related to the size, location and direction of motion of moving objects for assessment purposes. The time taken for video tracking by this Neural Network is only few seconds.