Abstract: A real-time tracking system was built to track performers on an interactive stage. Using an ordinary, up to date, desktop workstation, the performers- silhouette was segmented from the background and parameterized by calculating the normalized central image moments. In the stage system, the silhouette moments were then sent to a parallel workstation, which used them to generate corresponding 3D virtual geometry and projected the generated graphic back onto the stage.
Abstract: Eco-driving allows the driver to optimize his/her behaviour in order to achieve several types of benefits: reducing pollution emissions, increasing road safety, and fuel saving. One of the main rules for adopting eco-driving is to anticipate the traffic events by avoiding strong acceleration or braking and maintaining a steady speed when possible. Therefore, drivers have to comply with speed limits and time headway. The present study explored the role of three types of motivation and social norms in predicting French drivers- intentions to comply with speed limits and time headway as eco-driving practices as well as examine the variations according to gender and age. 1234 drivers with ages between 18 and 75 years old filled in a questionnaire which was presented as part of an online survey aiming to better understand the drivers- road habits. It included items assessing: a) behavioural intentions to comply with speed limits and time headway according to three types of motivation: reducing pollution emissions, increasing road safety, and fuel saving, b) subjective and descriptive social norms regarding the intention to comply with speed limits and time headway, and c) sociodemographical variables. Drivers expressed their intention to frequently comply with speed limits and time headway in the following 6 months; however, they showed more intention to comply with speed limits as compared to time headway regardless of the type of motivation. The subjective injunctive norms were significantly more important in predicting drivers- intentions to comply with speed limits and time headway as compared to the descriptive norms. In addition, the most frequently reported type of motivation for complying with speed limits and time headway was increasing road safety followed by fuel saving and reducing pollution emissions, hence underlining a low motivation to practice eco-driving. Practical implications of the results are discussed.
Abstract: Modern manufacturing facilities are large scale,
highly complex, and operate with large number of variables under
closed loop control. Early and accurate fault detection and diagnosis
for these plants can minimise down time, increase the safety of plant
operations, and reduce manufacturing costs. Fault detection and
isolation is more complex particularly in the case of the faulty analog
control systems. Analog control systems are not equipped with
monitoring function where the process parameters are continually
visualised. In this situation, It is very difficult to find the relationship
between the fault importance and its consequences on the product
failure. We consider in this paper an approach to fault detection and
analysis of its effect on the production quality using an adaptive
centring and scaling in the pickling process in cold rolling. The fault
appeared on one of the power unit driving a rotary machine, this
machine can not track a reference speed given by another machine.
The length of metal loop is then in continuous oscillation, this affects
the product quality. Using a computerised data acquisition system,
the main machine parameters have been monitored. The fault has
been detected and isolated on basis of analysis of monitored data.
Normal and faulty situation have been obtained by an artificial neural
network (ANN) model which is implemented to simulate the normal
and faulty status of rotary machine. Correlation between the product
quality defined by an index and the residual is used to quality
classification.
Abstract: This article presents a method for elections between the members of a group that is founded by fuzzy logic. Linguistic variables are objects for decision on election cards and deduction is based on t-norms and s-norms. In this election-s method election cards are questionnaire. The questionnaires are comprised of some questions with some choices. The choices are words from natural language. Presented method is accompanied by center of gravity (COG) defuzzification added up to a computer program by MATLAB. Finally the method is illustrated by solving two examples; choose a head for a research group-s members and a representative for students.
Abstract: As the development of digital technology is increasing,
Digital cinema is getting more spread.
However, content copy and attack against the digital cinema becomes
a serious problem. To solve the above security problem, we propose
“Additional Watermarking" for digital cinema delivery system. With
this proposed “Additional watermarking" method, we protect content
copyrights at encoder and user side information at decoder. It realizes
the traceability of the watermark embedded at encoder.
The watermark is embedded into the random-selected frames using
Hash function. Using it, the embedding position is distributed by Hash
Function so that third parties do not break off the watermarking
algorithm.
Finally, our experimental results show that proposed method is much
better than the convenient watermarking techniques in terms of
robustness, image quality and its simple but unbreakable algorithm.
Abstract: This paper outlines the research conducted to propose na framework of 'Knowledge Society' (KS) in the Malaysian context.
It is important to highlight that the emergence of KS is a result of the rapid growth in knowledge and information. However, the discussion
of KS should not only be limited to the importance of knowledge, but a holistic KS is also determined by other imperative dimensions. This
article discusses the results of a study conducted previously in Malaysia in order to identify the essential dimensions of KS, and
consequently propose a KS framework in the Malaysian context.
Two methods were employed, namely the Delphi technique and semi-structured interviews. The modified Delphi involved five
rounds with ten experts, while the interviews were conducted with two prominent figures in Malaysia. The results support the proposed
framework which contains seven major dimensions in order for Malaysia to become a KS in the future. The dimensions which are
crucial for a holistic Malaysian KS are human capital, spirituality, economy, social, institutional, sustainability, and driven by the ICT.
Abstract: Segmentation is an important step in medical image
analysis and classification for radiological evaluation or computer
aided diagnosis. The CAD (Computer Aided Diagnosis ) of lung CT
generally first segment the area of interest (lung) and then analyze
the separately obtained area for nodule detection in order to
diagnosis the disease. For normal lung, segmentation can be
performed by making use of excellent contrast between air and
surrounding tissues. However this approach fails when lung is
affected by high density pathology. Dense pathologies are present in
approximately a fifth of clinical scans, and for computer analysis
such as detection and quantification of abnormal areas it is vital that
the entire and perfectly lung part of the image is provided and no
part, as present in the original image be eradicated. In this paper we
have proposed a lung segmentation technique which accurately
segment the lung parenchyma from lung CT Scan images. The
algorithm was tested against the 25 datasets of different patients
received from Ackron Univeristy, USA and AGA Khan Medical
University, Karachi, Pakistan.
Abstract: The empirical mode decomposition (EMD) represents any time series into a finite set of basis functions. The bases are termed as intrinsic mode functions (IMFs) which are mutually orthogonal containing minimum amount of cross-information. The EMD successively extracts the IMFs with the highest local frequencies in a recursive way, which yields effectively a set low-pass filters based entirely on the properties exhibited by the data. In this paper, EMD is applied to explore the properties of the multi-year air temperature and to observe its effects on climate change under global warming. This method decomposes the original time-series into intrinsic time scale. It is capable of analyzing nonlinear, non-stationary climatic time series that cause problems to many linear statistical methods and their users. The analysis results show that the mode of EMD presents seasonal variability. The most of the IMFs have normal distribution and the energy density distribution of the IMFs satisfies Chi-square distribution. The IMFs are more effective in isolating physical processes of various time-scales and also statistically significant. The analysis results also show that the EMD method provides a good job to find many characteristics on inter annual climate. The results suggest that climate fluctuations of every single element such as temperature are the results of variations in the global atmospheric circulation.
Abstract: In nature, electromagnetic fields always appear like
atmosphere static electric field, the earth's static magnetic field and
the wide-rang frequency electromagnetic field caused by lightening.
However, besides natural electromagnetic fields (EMF), today human
beings are mostly exposed to artificial electromagnetic fields due to
technology progress and outspread use of electrical devices. To
evaluate nuisance of EMF, it is necessary to know field intensity for
every frequency which appears and compare it with allowed values.
Low frequency EMF-s around transmission and distribution lines are
time-varying quasi-static electromagnetic fields which have
conservative component of low frequency electrical field caused by
charges and eddy component of low frequency magnetic field caused
by currents. Displacement current or field delay are negligible, so
energy flow in quasi-static EMF involves diffusion, analog like heat
transfer. Electrical and magnetic field can be analyzed separately.
This paper analysis the numerical calculations in ELF-400 software
of EMF in distribution substation in shopping center. Analyzing the
results it is possible to specify locations exposed to the fields and
give useful suggestion to eliminate electromagnetic effect or reduce it
on acceptable level within the non-ionizing radiation norms and
norms of protection from EMF.
Abstract: This paper presents an optimal design of poly-phase induction motor using Quadratic Interpolation based Particle Swarm Optimization (QI-PSO). The optimization algorithm considers the efficiency, starting torque and temperature rise as objective function (which are considered separately) and ten performance related items including harmonic current as constraints. The QI-PSO algorithm was implemented on a test motor and the results are compared with the Simulated Annealing (SA) technique, Standard Particle Swarm Optimization (SPSO), and normal design. Some benchmark problems are used for validating QI-PSO. From the test results QI-PSO gave better results and more suitable to motor-s design optimization. Cµ code is used for implementing entire algorithms.
Abstract: Impinging jets are used in various industrial areas as a cooling and drying technique. The current research is concerned with the means of improving the heat transfer for configurations with a minimum distance of the nozzle to the impingement surface. The impingement heat transfer is described using numerical methods over a wide range of parameters for an array of planar jets. These parameters include varying jet flow speed, width of nozzle, distance of nozzle, angle of the jet flow, velocity and geometry of the impingement surface. Normal pressure and shear stress are computed as additional parameters. Using dimensionless characteristic numbers the parameters and the results are correlated to gain generalized equations. The results demonstrate the effect of the investigated parameters on the flow.
Abstract: A stage-structured predator-prey system with two time delays is considered. By analyzing the corresponding characteristic equation, the local stability of a positive equilibrium is investigated and the existence of Hopf bifurcations is established. Formulae are derived to determine the direction of bifurcations and the stability of bifurcating periodic solutions by using the normal form theory and center manifold theorem. Numerical simulations are carried out to illustrate the theoretical results. Based on the global Hopf bifurcation theorem for general functional differential equations, the global existence of periodic solutions is established.
Abstract: In this paper we propose a new criterion for solving
the problem of channel shortening in multi-carrier systems. In a
discrete multitone receiver, a time-domain equalizer (TEQ) reduces
intersymbol interference (ISI) by shortening the effective duration of
the channel impulse response. Minimum mean square error (MMSE)
method for TEQ does not give satisfactory results. In [1] a new
criterion for partially equalizing severe ISI channels to reduce the
cyclic prefix overhead of the discrete multitone transceiver (DMT),
assuming a fixed transmission bandwidth, is introduced. Due to
specific constrained (unit morm constraint on the target impulse
response (TIR)) in their method, the freedom to choose optimum
vector (TIR) is reduced. Better results can be obtained by avoiding
the unit norm constraint on the target impulse response (TIR). In
this paper we change the cost function proposed in [1] to the cost
function of determining the maximum of a determinant subject to
linear matrix inequality (LMI) and quadratic constraint and solve the
resulting optimization problem. Usefulness of the proposed method
is shown with the help of simulations.
Abstract: This paper provides the design steps of a robust Linear
Matrix Inequality (LMI) based iterative multivariable PID controller
whose duty is to drive a sample power system that comprises a
synchronous generator connected to a large network via a step-up
transformer and a transmission line. The generator is equipped with
two control-loops, namely, the speed/power (governor) and voltage
(exciter). Both loops are lumped in one where the error in the
terminal voltage and output active power represent the controller
inputs and the generator-exciter voltage and governor-valve position
represent its outputs. Multivariable PID is considered here because of
its wide use in the industry, simple structure and easy
implementation. It is also preferred in plants of higher order that
cannot be reduced to lower ones. To improve its robustness to
variation in the controlled variables, H∞-norm of the system transfer
function is used. To show the effectiveness of the controller, divers
tests, namely, step/tracking in the controlled variables, and variation
in plant parameters, are applied. A comparative study between the
proposed controller and a robust H∞ LMI-based output feedback is
given by its robustness to disturbance rejection. From the simulation
results, the iterative multivariable PID shows superiority.
Abstract: Many researchers are working on information hiding
techniques using different ideas and areas to hide their secrete data.
This paper introduces a robust technique of hiding secret data in
image based on LSB insertion and RSA encryption technique. The
key of the proposed technique is to encrypt the secret data. Then the
encrypted data will be converted into a bit stream and divided it into
number of segments. However, the cover image will also be divided
into the same number of segments. Each segment of data will be
compared with each segment of image to find the best match
segment, in order to create a new random sequence of segments to be
inserted then in a cover image. Experimental results show that the
proposed technique has a high security level and produced better
stego-image quality.
Abstract: Organizational culture fosters innovation, and
innovation is the main engine to be sustained within the uncertainty
market. Like other countries, the construction industry significantly
contributes to the economy, society and technology of Malaysia, yet,
innovation is still considered slow compared to other industries such
as manufacturing. Given the important role of an architect as the key
player and the contributor of new ideas in the construction industry,
there is a call to identify the issue and improve the current situation
by focusing on the architectural firms. In addition, the existing
studies tend to focus only on a few dimensions of organizational
culture and very few studies consider whether innovation is being
generated or adopted. Hence, the present research tends to fill in the
gap by identifying the organizational cultures that foster or hinder
innovation generation and/or innovation adoption, and propose a
model of organizational culture and innovation generation and/or
adoption.
Abstract: As the Internet continues to grow at a rapid pace as
the primary medium for communications and commerce and as
telecommunication networks and systems continue to expand their
global reach, digital information has become the most popular and
important information resource and our dependence upon the
underlying cyber infrastructure has been increasing significantly.
Unfortunately, as our dependency has grown, so has the threat to the
cyber infrastructure from spammers, attackers and criminal
enterprises. In this paper, we propose a new machine learning based
network intrusion detection framework for cyber security. The
detection process of the framework consists of two stages: model
construction and intrusion detection. In the model construction stage,
a semi-supervised machine learning algorithm is applied to a
collected set of network audit data to generate a profile of normal
network behavior and in the intrusion detection stage, input network
events are analyzed and compared with the patterns gathered in the
profile, and some of them are then flagged as anomalies should these
events are sufficiently far from the expected normal behavior. The
proposed framework is particularly applicable to the situations where
there is only a small amount of labeled network training data
available, which is very typical in real world network environments.
Abstract: As the enormous amount of on-line text grows on the
World-Wide Web, the development of methods for automatically
summarizing this text becomes more important. The primary goal of
this research is to create an efficient tool that is able to summarize
large documents automatically. We propose an Evolving
connectionist System that is adaptive, incremental learning and
knowledge representation system that evolves its structure and
functionality. In this paper, we propose a novel approach for Part of
Speech disambiguation using a recurrent neural network, a paradigm
capable of dealing with sequential data. We observed that
connectionist approach to text summarization has a natural way of
learning grammatical structures through experience. Experimental
results show that our approach achieves acceptable performance.
Abstract: We demonstrate single-photon interference over 10 km using a plug and play system for quantum key distribution. The quality of the interferometer is measured by using the interferometer
visibility. The coding of the signal is based on the phase coding and the value of visibility is based on the interference effect, which result a number of count. The setup gives full control of polarization inside
the interferometer. The quality measurement of the interferometer is based on number of count per second and the system produces 94 % visibility in one of the detectors.
Abstract: Feature selection study is gaining importance due to its contribution to save classification cost in terms of time and computation load. In search of essential features, one of the methods to search the features is via the decision tree. Decision tree act as an intermediate feature space inducer in order to choose essential features. In decision tree-based feature selection, some studies used decision tree as a feature ranker with a direct threshold measure, while others remain the decision tree but utilized pruning condition that act as a threshold mechanism to choose features. This paper proposed threshold measure using Manhattan Hierarchical Cluster distance to be utilized in feature ranking in order to choose relevant features as part of the feature selection process. The result is promising, and this method can be improved in the future by including test cases of a higher number of attributes.