Abstract: This paper addresses the problem of source separation
in images. We propose a FastICA algorithm employing a modified
Gaussian contrast function for the Blind Source Separation.
Experimental result shows that the proposed Modified Gaussian
FastICA is effectively used for Blind Source Separation to obtain
better quality images. In this paper, a comparative study has been
made with other popular existing algorithms. The peak signal to
noise ratio (PSNR) and improved signal to noise ratio (ISNR) are
used as metrics for evaluating the quality of images. The ICA metric
Amari error is also used to measure the quality of separation.
Abstract: The increasing development of wireless networks and
the widespread popularity of handheld devices such as Personal
Digital Assistants (PDAs), mobile phones and wireless tablets
represents an incredible opportunity to enable mobile devices as a
universal payment method, involving daily financial transactions.
Unfortunately, some issues hampering the widespread acceptance of
mobile payment such as accountability properties, privacy protection,
limitation of wireless network and mobile device. Recently, many
public-key cryptography based mobile payment protocol have been
proposed. However, limited capabilities of mobile devices and
wireless networks make these protocols are unsuitable for mobile
network. Moreover, these protocols were designed to preserve
traditional flow of payment data, which is vulnerable to attack and
increase the user-s risk. In this paper, we propose a private mobile
payment protocol which based on client centric model and by
employing symmetric key operations. The proposed mobile payment
protocol not only minimizes the computational operations and
communication passes between the engaging parties, but also
achieves a completely privacy protection for the payer. The future
work will concentrate on improving the verification solution to
support mobile user authentication and authorization for mobile
payment transactions.
Abstract: In the oil and gas industry, energy prediction can help
the distributor and customer to forecast the outgoing and incoming
gas through the pipeline. It will also help to eliminate any
uncertainties in gas metering for billing purposes. The objective of
this paper is to develop Neural Network Model for energy
consumption and analyze the performance model. This paper
provides a comprehensive review on published research on the
energy consumption prediction which focuses on structures and the
parameters used in developing Neural Network models. This paper is
then focused on the parameter selection of the neural network
prediction model development for energy consumption and analysis
on the result. The most reliable model that gives the most accurate
result is proposed for the prediction. The result shows that the
proposed neural network energy prediction model is able to
demonstrate an adequate performance with least Root Mean Square
Error.
Abstract: In this paper, we propose improved versions of DVHop
algorithm as QDV-Hop algorithm and UDV-Hop algorithm for
better localization without the need for additional range measurement
hardware. The proposed algorithm focuses on third step of DV-Hop,
first error terms from estimated distances between unknown node and
anchor nodes is separated and then minimized. In the QDV-Hop
algorithm, quadratic programming is used to minimize the error to
obtain better localization. However, quadratic programming requires
a special optimization tool box that increases computational
complexity. On the other hand, UDV-Hop algorithm achieves
localization accuracy similar to that of QDV-Hop by solving
unconstrained optimization problem that results in solving a system
of linear equations without much increase in computational
complexity. Simulation results show that the performance of our
proposed schemes (QDV-Hop and UDV-Hop) is superior to DV-Hop
and DV-Hop based algorithms in all considered scenarios.
Abstract: This paper attempts to highlight the significant role of
knowledge management practices (KMP) and competencies in
improving the performance and efficiency of public sector
organizations. It appears that public sector organizations in
developing countries have not received much attention in the
research literature of knowledge management and competencies.
Therefore, this paper seeks to explore the role of KMP and
competencies in achieving superior performance among public sector
organizations in Malaysia in the broader perspective. Survey
questionnaires were distributed to all Administrative and Diplomatic
Officers (ADS) from 28 ministries located in Putrajaya, Malaysia.
This paper also examines preliminary empirical results on the
relationship between support for knowledge management practices,
competencies, and orientation in Malaysia-s public organizations.
This paper supports the notion that the practices of knowledge
management at the organizational level are a prerequisite for
successful organizational performance. In conclusion, the results not
only have the potential to contribute theoretically to both
management strategy and knowledge management field literature but
also to the area of organizational performance.
Abstract: Geometric design is an important part of planning
process design for physical highway to fill up basic function of roads,
to give good traffic service. It is found that most of the road safety
problems occur at the horizontal curves and complex-compound
curves. In this paper, review on Sagarinn-Myinsain Portion of Nay
Pyi Taw - Mandalay highway has been conducted in aspect of
geometric design induced road safety condition. Horizontal
alignment of geometric features and curve details are reviewed based
on (AASHTO) standard and revised by Autodesk Land Desktop
Software. Moreover, 85th Percentile Operation Speeds (V85) with
driver confidence on horizontal curves is evaluated in order to obtain
the range of highway safety factor (FS). The length of the selected
highway portion is 13.65 miles and 8 lanes. The results of this study
can be used to investigate the possible hazardous locations in
advance and to revise how design radius and super elevation should
be for better road safety performance for the selected portion.
Moreover, the relationship between highway safety and highway
geometry characteristics can also be known.
Abstract: Image interpolation is a common problem in imaging applications. However, most interpolation algorithms in existence suffer visually to some extent the effects of blurred edges and jagged artifacts in the image. This paper presents an adaptive feature preserving bidirectional flow process, where an inverse diffusion is performed to enhance edges along the normal directions to the isophote lines (edges), while a normal diffusion is done to remove artifacts (''jaggies'') along the tangent directions. In order to preserve image features such as edges, angles and textures, the nonlinear diffusion coefficients are locally adjusted according to the first and second order directional derivatives of the image. Experimental results on synthetic images and nature images demonstrate that our interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional interpolations.
Abstract: Monitoring and control of cane sugar crystallization
processes depend on the stability of the supersaturation (σ ) state.
The most widely used information to represent σ is the electrical
conductivity κ of the solutions. Nevertheless, previous studies point
out the shortcomings of this approach: κ may be regarded as
inappropriate to guarantee an accurate estimation of σ in impure
solutions. To improve the process control efficiency, additional
information is necessary. The mass of crystals in the solution ( c m )
and the solubility (mass ratio of sugar to water / s w m m ) are relevant
to complete information. Indeed, c m inherently contains information
about the mass balance and / s w m m contains information about the
supersaturation state of the solution. The main problem is that c m
and / s w m m are not available on-line. In this paper, a model based
soft-sensor is presented for a final crystallization stage (C sugar).
Simulation results obtained on industrial data show the reliability of
this approach, c m and the crystal content ( cc ) being estimated with
a sufficient accuracy for achieving on-line monitoring in industry
Abstract: When a lightning strike falls near an overhead power
line, the intense electromagnetic field radiated by the current of the
lightning return stroke coupled with power lines and there induced
transient overvoltages, which can cause a back-flashover in electrical
network. The indirect lightning represents a major danger owing to
the fact that it is more frequent than that which results from the direct
strikes.
In this paper we present an analysis of the electromagnetic
coupling between an external electromagnetic field generated by the
lightning and an electrical overhead lines, so we give an important
and original contribution: We are based on our experimental
measurements which we carried in the high voltage laboratories of
EPFL in Switzerland during the last trimester of 2005, on the recent
works of other authors and with our mathematical improvement a
new particular analytical expression of the electromagnetic field
generated by the lightning return stroke was developed and presented
in this paper. The results obtained by this new electromagnetic field
formulation were compared with experimental results and give a
reasonable approach.
Abstract: Materials added to the matrix help improving operating properties of a composite. This experimental study has targeted to investigate this aim where Silicon Oxide particles were added to glass fibre and epoxy resin at an amount of 15% to the main material to obtain a sort of new composite material. Erosive wear behavior of epoxy-resin dipped composite materials reinforced with glass fibre and Silicon Oxide under three different impingement angles (30°, 60° and 90°), three different impact velocities (23, 34 and 53 m/s), two different angular Aluminum abrasive particle sizes (approximately 200 and 400 μm) and the fibre orientation of 45° (45/-45) were investigated. In the test results, erosion rates were obtained as functions of impingement angles, impact velocities, particle sizes and fibre orientation. Moreover, materials with addition of Silicon Oxide filler material exhibited lower wear as compared to neat materials with no added filler material. In addition, SEM views showing worn out surfaces of the test specimens were scrutinized.
Abstract: In order to study the effect of phosphate solubilization
microorganisms (PSM) and plant growth promoting rhizobacteria
(PGPR) on yield and yield components of corn Zea mays (L. cv.
SC604) an experiment was conducted at research farm of Sari
Agricultural Sciences and Natural Resources University, Iran during
2007. Experiment laid out as split plot based on randomized
complete block design with three replications. Three levels of
manures (consisted of 20 Mg.ha-1 farmyard manure, 15 Mg.ha-1 green
manure and check or without any manures) as main plots and eight
levels of biofertilizers (consisted of 1-NPK or conventional fertilizer
application; 2-NPK+PSM+PGPR; 3 NP50%K+PSM+PGPR; 4-
N50%PK+PSM +PGPR; 5-N50%P50%K+PSM+ PGPR; 6-PK+PGPR; 7-
NK+PSM and 8-PSM+PGPR) as sub plots were treatments. Results
showed that farmyard manure application increased row number, ear
weight, grain number per ear, grain yield, biological yield and
harvest index compared to check. Furthermore, using of PSM and
PGPR in addition to conventional fertilizer applications (NPK) could
improve ear weight, row number and grain number per row and
ultimately increased grain yield in green manure and check plots.
According to results in all fertilizer treatments application of PSM
and PGPR together could reduce P application by 50% without any
significant reduction of grain yield. However, this treatment could
not compensate 50% reduction of N application.
Abstract: Evaluation of crop plants resistance to environmental
stresses specially in germination stage is a critical factor in their
selection in different conditions of cultivation. Therefore use of a
procedure in controllable situation can help to evaluate plants
reaction to stress quickly and precisely. In order to study germination
characteristics of flax in water and salinity stress conditions were
conducted two laboratories experimental. The two experimental were
conducted in 4-replicant completing random design for salinity and
water stress. The treatment, for salinity and water stress was three
potential (zero, 40, 80 mM) of NaCl and three potential (zero, -2, -4
bar) of PEG respectively. Germination percentage and rate, in
addition to Radical and plumule length and dry-weight and
plumule/Radical ration were measured. All of characteristics reduce
under water stress conditions. salinity stress significant reduce
germination rate and Radical and plumule length of flax seeds.
Hydropriming and osmopriming significant increased germination
rate, plumule length and plumule/Radical ration ration of flax seeds.
But germination percentage and Radical and plumule dry weight
significant increased only in hydropriming treat. Hydropriming and
osmopriming could not be used to improved germination under saline
and drought stress. But has more tolerance in salinity and drought
stress in flax by less reduce in Radical and plumule length under
saline and drought stress.
Abstract: Knowledge is the foundation for growth and development. Investment in knowledge improves new method for originate knowledge society and knowledge economy. Investment in knowledge embraces expenditure on education and R&D and software. Measuring of investment in knowledge is characteristically complicated. We examine the influence of investment in knowledge in multifactor productivity growth and numbers of patent. We analyze the annual growth of investment in knowledge and we estimate portion of each country intended for produce total investment in knowledge on the whole OECD. We determine the relative efficiency of average patent numbers with average investment in knowledge and we compare GDP growth rates and growth of knowledge investment. The main purpose in this paper is to study to evaluate different aspect, influence and output of investment in knowledge in OECD countries.
Abstract: This paper investigates the problem of automated defect
detection for textile fabrics and proposes a new optimal filter design
method to solve this problem. Gabor Wavelet Network (GWN) is
chosen as the major technique to extract the texture features from
textile fabrics. Based on the features extracted, an optimal Gabor filter
can be designed. In view of this optimal filter, a new semi-supervised
defect detection scheme is proposed, which consists of one real-valued
Gabor filter and one smoothing filter. The performance of the scheme
is evaluated by using an offline test database with 78 homogeneous
textile images. The test results exhibit accurate defect detection with
low false alarm, thus showing the effectiveness and robustness of the
proposed scheme. To evaluate the detection scheme comprehensively,
a prototyped detection system is developed to conduct a real time test.
The experiment results obtained confirm the efficiency and
effectiveness of the proposed detection scheme.
Abstract: In recent years, real estate prediction or valuation has
been a topic of discussion in many developed countries. Improper
hype created by investors leads to fluctuating prices of real estate,
affecting many consumers to purchase their own homes. Therefore,
scholars from various countries have conducted research in real estate
valuation and prediction. With the back-propagation neural network
that has been popular in recent years and the orthogonal array in the
Taguchi method, this study aimed to find the optimal parameter
combination at different levels of orthogonal array after the system
presented different parameter combinations, so that the artificial
neural network obtained the most accurate results. The experimental
results also demonstrated that the method presented in the study had a
better result than traditional machine learning. Finally, it also showed
that the model proposed in this study had the optimal predictive effect,
and could significantly reduce the cost of time in simulation operation.
The best predictive results could be found with a fewer number of
experiments more efficiently. Thus users could predict a real estate
transaction price that is not far from the current actual prices.
Abstract: In many applications there is a broad variety of
information relevant to a focal “object" of interest, and the fusion of such heterogeneous data types is desirable for classification and
categorization. While these various data types can sometimes be treated as orthogonal (such as the hull number, superstructure color,
and speed of an oil tanker), there are instances where the inference and the correlation between quantities can provide improved fusion
capabilities (such as the height, weight, and gender of a person). A
service-oriented architecture has been designed and prototyped to
support the fusion of information for such “object-centric" situations.
It is modular, scalable, and flexible, and designed to support new data sources, fusion algorithms, and computational resources without affecting existing services. The architecture is designed to simplify
the incorporation of legacy systems, support exact and probabilistic entity disambiguation, recognize and utilize multiple types of
uncertainties, and minimize network bandwidth requirements.
Abstract: This paper presents one comprehensive modelling approach for maintenance scheduling problem of thermal power units in competitive market. This problem is formulated as a 0/1 mixedinteger linear programming model. Model incorporates long-term bilateral contracts with defined profiles of power and price, and weekly forecasted market prices for market auction. The effectiveness of the proposed model is demonstrated through case study with detailed discussion.
Abstract: This paper presents a new method for estimating the nonstationary
noise power spectral density given a noisy signal. The
method is based on averaging the noisy speech power spectrum using
time and frequency dependent smoothing factors. These factors are
adjusted based on signal-presence probability in individual frequency
bins. Signal presence is determined by computing the ratio of the
noisy speech power spectrum to its local minimum, which is updated
continuously by averaging past values of the noisy speech power
spectra with a look-ahead factor. This method adapts very quickly to
highly non-stationary noise environments. The proposed method
achieves significant improvements over a system that uses voice
activity detector (VAD) in noise estimation.
Abstract: Data gathering is an essential operation in wireless
sensor network applications. So it requires energy efficiency
techniques to increase the lifetime of the network. Similarly,
clustering is also an effective technique to improve the energy
efficiency and network lifetime of wireless sensor networks. In this
paper, an energy efficient cluster formation protocol is proposed with
the objective of achieving low energy dissipation and latency without
sacrificing application specific quality. The objective is achieved by
applying randomized, adaptive, self-configuring cluster formation
and localized control for data transfers. It involves application -
specific data processing, such as data aggregation or compression.
The cluster formation algorithm allows each node to make
independent decisions, so as to generate good clusters as the end.
Simulation results show that the proposed protocol utilizes minimum
energy and latency for cluster formation, there by reducing the
overhead of the protocol.
Abstract: This paper presents an on-going research work on the
implementation of feature-based machining via macro programming.
Repetitive machining features such as holes, slots, pockets etc can
readily be encapsulated in macros. Each macro consists of methods
on how to machine the shape as defined by the feature. The macro
programming technique comprises of a main program and
subprograms. The main program allows user to select several
subprograms that contain features and define their important
parameters. With macros, complex machining routines can be
implemented easily and no post processor is required. A case study
on machining of a part that comprised of planar face, hole and pocket
features using the macro programming technique was carried out. It
is envisaged that the macro programming technique can be extended
to other feature-based machining fields such as the newly developed
STEP-NC domain.