Abstract: WIMAX relay station mesh network has been approved by IEEE 802.16j as a standard to provide a highly data rate transmission, the RS was implemented to extend the coverage zone of the BS, for instance the MSs previously were out of the coverage of the BS they become in the coverage of the RS, therefore these MSs can have Admission control from the BS through the RS. This paper describe a problem in the mesh network Relay station, for instance the problem of how to serve the mobile stations (MSs) which are out of the Relay station coverage. This paper also proposed a solution for mobile stations out of the coverage of the WIMAX Relay stations mesh Network. Therefore Ad-hoc network defined as a solution by using its admission control schema and apply it on the mobiles inside and outside the Relay station coverage.
Abstract: In this paper, the two-dimensional stagger grid
interface pressure (SGIP) model has been generalized and presented
into three-dimensional form. For this purpose, various models of
surface tension force for interfacial flows have been investigated and
compared with each other. The VOF method has been used for
tracking the interface. To show the ability of the SGIP model for
three-dimensional flows in comparison with other models, pressure
contours, maximum spurious velocities, norm spurious flow
velocities and pressure jump error for motionless drop of liquid and
bubble of gas are calculated using different models. It has been
pointed out that SGIP model in comparison with the CSF, CSS and
PCIL models produces the least maximum and norm spurious
velocities. Additionally, the new model produces more accurate
results in calculating the pressure jumps across the interface for
motionless drop of liquid and bubble of gas which is generated in
surface tension force.
Abstract: Tacit knowledge has been one of the most discussed
and contradictory concepts in the field of knowledge management
since the mid 1990s. The concept is used relatively vaguely to refer
to any type of information that is difficult to articulate, which has led
to discussions about the original meaning of the concept (adopted
from Polanyi-s philosophy) and the nature of tacit knowing. It is
proposed that the subject should be approached from the perspective
of cognitive science in order to connect tacit knowledge to
empirically studied cognitive phenomena. Some of the most
important examples of tacit knowing presented by Polanyi are
analyzed in order to trace the cognitive mechanisms of tacit knowing
and to promote better understanding of the nature of tacit knowledge.
The cognitive approach to Polanyi-s theory reveals that the
tacit/explicit typology of knowledge often presented in the
knowledge management literature is not only artificial but totally
opposite approach compared to Polanyi-s thinking.
Abstract: This paper presents the use of a newly created network
structure known as a Self-Delaying Dynamic Network (SDN) to
create a high resolution image from a set of time stepped input
frames. These SDNs are non-recurrent temporal neural networks
which can process time sampled data. SDNs can store input data
for a lifecycle and feature dynamic logic based connections between
layers. Several low resolution images and one high resolution image
of a scene were presented to the SDN during training by a Genetic
Algorithm. The SDN was trained to process the input frames in order
to recreate the high resolution image. The trained SDN was then used
to enhance a number of unseen noisy image sets. The quality of high
resolution images produced by the SDN is compared to that of high
resolution images generated using Bi-Cubic interpolation. The SDN
produced images are superior in several ways to the images produced
using Bi-Cubic interpolation.
Abstract: Money laundering has been described by many as the lifeblood of crime and is a major threat to the economic and social well-being of societies. It has been recognized that the banking system has long been the central element of money laundering. This is in part due to the complexity and confidentiality of the banking system itself. It is generally accepted that effective anti-money laundering (AML) measures adopted by banks will make it tougher for criminals to get their "dirty money" into the financial system. In fact, for law enforcement agencies, banks are considered to be an important source of valuable information for the detection of money laundering. However, from the banks- perspective, the main reason for their existence is to make as much profits as possible. Hence their cultural and commercial interests are totally distinct from that of the law enforcement authorities. Undoubtedly, AML laws create a major dilemma for banks as they produce a significant shift in the way banks interact with their customers. Furthermore, the implementation of the laws not only creates significant compliance problems for banks, but also has the potential to adversely affect the operations of banks. As such, it is legitimate to ask whether these laws are effective in preventing money launderers from using banks, or whether they simply put an unreasonable burden on banks and their customers. This paper attempts to address these issues and analyze them against the background of the Malaysian AML laws. It must be said that effective coordination between AML regulator and the banking industry is vital to minimize problems faced by the banks and thereby to ensure effective implementation of the laws in combating money laundering.
Abstract: Multi-energy systems will enhance the system
reliability and power quality. This paper presents an integrated
approach for the design and operation of distributed energy resources
(DER) systems, based on energy hub modeling. A multi-objective
optimization model is developed by considering an integrated view of
electricity and natural gas network to analyze the optimal design and
operating condition of DER systems, by considering two conflicting
objectives, namely, minimization of total cost and the minimization
of environmental impact which is assessed in terms of CO2
emissions. The mathematical model considers energy demands of the
site, local climate data, and utility tariff structure, as well as technical
and financial characteristics of the candidate DER technologies. To
provide energy demands, energy systems including photovoltaic, and
co-generation systems, boiler, central power grid are considered. As
an illustrative example, a hotel in Iran demonstrates potential
applications of the proposed method. The results prove that
increasing the satisfaction degree of environmental objective leads to
increased total cost.
Abstract: A series of microarray experiments produces observations
of differential expression for thousands of genes across multiple
conditions.
Principal component analysis(PCA) has been widely used in
multivariate data analysis to reduce the dimensionality of the data in
order to simplify subsequent analysis and allow for summarization of
the data in a parsimonious manner. PCA, which can be implemented
via a singular value decomposition(SVD), is useful for analysis of
microarray data.
For application of PCA using SVD we use the DNA microarray
data for the small round blue cell tumors(SRBCT) of childhood
by Khan et al.(2001). To decide the number of components which
account for sufficient amount of information we draw scree plot.
Biplot, a graphic display associated with PCA, reveals important
features that exhibit relationship between variables and also the
relationship of variables with observations.
Abstract: We present a novel scheme to evaluate sinusoidal functions with low complexity and high precision using cubic spline interpolation. To this end, two different approaches are proposed to find the interpolating polynomial of sin(x) within the range [- π , π]. The first one deals with only a single data point while the other with two to keep the realization cost as low as possible. An approximation error optimization technique for cubic spline interpolation is introduced next and is shown to increase the interpolator accuracy without increasing complexity of the associated hardware. The architectures for the proposed approaches are also developed, which exhibit flexibility of implementation with low power requirement.
Abstract: The crystalline quality of the AlGaN/GaN high electron mobility transistor (HEMT) structure grown on a 200 mm silicon substrate has been investigated using UV-visible micro- Raman scattering and photoluminescence (PL). The visible Raman scattering probes the whole nitride stack with the Si substrate and shows the presence of a small component of residual in-plane stress in the thick GaN buffer resulting from a wafer bowing, while the UV micro-Raman indicates a tensile interfacial stress induced at the top GaN/AlGaN/AlN layers. PL shows a good crystal quality GaN channel where the yellow band intensity is very low compared to that of the near-band-edge transition. The uniformity of this sample is shown by measurements from several points across the epiwafer.
Abstract: Embedded systems need to respect stringent real
time constraints. Various hardware components included in such
systems such as cache memories exhibit variability and therefore
affect execution time. Indeed, a cache memory access from an
embedded microprocessor might result in a cache hit where the
data is available or a cache miss and the data need to be fetched
with an additional delay from an external memory. It is therefore
highly desirable to predict future memory accesses during
execution in order to appropriately prefetch data without incurring
delays. In this paper, we evaluate the potential of several artificial
neural networks for the prediction of instruction memory
addresses. Neural network have the potential to tackle the nonlinear
behavior observed in memory accesses during program
execution and their demonstrated numerous hardware
implementation emphasize this choice over traditional forecasting
techniques for their inclusion in embedded systems. However,
embedded applications execute millions of instructions and
therefore millions of addresses to be predicted. This very
challenging problem of neural network based prediction of large
time series is approached in this paper by evaluating various neural
network architectures based on the recurrent neural network
paradigm with pre-processing based on the Self Organizing Map
(SOM) classification technique.
Abstract: The objectives of this research are to produce
prototype coconut oil based solvent offset printing inks and to
analyze a basic quality of printing work derived from coconut oil
based solvent offset printing inks, by mean of bringing coconut oil
for producing varnish and bringing such varnish to produce black
offset printing inks. Then, analysis of qualities i.e. CIELAB value,
density value, and dot gain value of printing work from coconut oil
based solvent offset printing inks which printed on gloss-coated
woodfree paper weighs 130 grams were done. The research result of
coconut oil based solvent offset printing inks indicated that the
suitable varnish formulation is using 51% of coconut oil, 36% of
phenolic resin, and 14% of solvent oil 14%, while the result of
producing black offset ink displayed that the suitable formula of
printing ink is using varnish mixed with 20% of coconut oil, and the
analyzing printing work of coconut oil based solvent offset printing
inks which printed on paper, the results were as follows: CIELAB
value of black offset printing ink is at L* = 31.90, a* = 0.27, and b* =
1.86, density value is at 1.27 and dot gain value was high at mid tone
area of image area.
Abstract: Echocardiography imaging is one of the most common diagnostic tests that are widely used for assessing the abnormalities of the regional heart ventricle function. The main goal of the image enhancement task in 2D-echocardiography (2DE) is to solve two major anatomical structure problems; speckle noise and low quality. Therefore, speckle noise reduction is one of the important steps that used as a pre-processing to reduce the distortion effects in 2DE image segmentation. In this paper, we present the common filters that based on some form of low-pass spatial smoothing filters such as Mean, Gaussian, and Median. The Laplacian filter was used as a high-pass sharpening filter. A comparative analysis was presented to test the effectiveness of these filters after being applied to original 2DE images of 4-chamber and 2-chamber views. Three statistical quantity measures: root mean square error (RMSE), peak signal-to-ratio (PSNR) and signal-tonoise ratio (SNR) are used to evaluate the filter performance quantitatively on the output enhanced image.
Abstract: The National Agricultural Biotechnology Information
Center (NABIC) plays a leading role in the biotechnology information
database for agricultural plants in Korea. Since 2002, we have
concentrated on functional genomics of major crops, building an
integrated biotechnology database for agro-biotech information that
focuses on bioinformatics of major agricultural resources such as rice,
Chinese cabbage, and microorganisms. In the NABIC,
integration-based biotechnology database provides useful information
through a user-friendly web interface that allows analysis of genome
infrastructure, multiple plants, microbial resources, and living
modified organisms.
Abstract: In modern human computer interaction systems
(HCI), emotion recognition is becoming an imperative characteristic.
The quest for effective and reliable emotion recognition in HCI has
resulted in a need for better face detection, feature extraction and
classification. In this paper we present results of feature space analysis
after briefly explaining our fully automatic vision based emotion
recognition method. We demonstrate the compactness of the feature
space and show how the 2d/3d based method achieves superior features
for the purpose of emotion classification. Also it is exposed that
through feature normalization a widely person independent feature
space is created. As a consequence, the classifier architecture has
only a minor influence on the classification result. This is particularly
elucidated with the help of confusion matrices. For this purpose
advanced classification algorithms, such as Support Vector Machines
and Artificial Neural Networks are employed, as well as the simple k-
Nearest Neighbor classifier.
Abstract: Falling has been one of the major concerns and threats
to the independence of the elderly in their daily lives. With the
worldwide significant growth of the aging population, it is essential
to have a promising solution of fall detection which is able to operate
at high accuracy in real-time and supports large scale implementation
using multiple cameras. Field Programmable Gate Array (FPGA) is a
highly promising tool to be used as a hardware accelerator in many
emerging embedded vision based system. Thus, it is the main
objective of this paper to present an FPGA-based solution of visual
based fall detection to meet stringent real-time requirements with
high accuracy. The hardware architecture of visual based fall
detection which utilizes the pixel locality to reduce memory accesses
is proposed. By exploiting the parallel and pipeline architecture of
FPGA, our hardware implementation of visual based fall detection
using FGPA is able to achieve a performance of 60fps for a series of
video analytical functions at VGA resolutions (640x480). The results
of this work show that FPGA has great potentials and impacts in
enabling large scale vision system in the future healthcare industry
due to its flexibility and scalability.
Abstract: Research in quantum computation is looking for the consequences of having information encoding, processing and communication exploit the laws of quantum physics, i.e. the laws which govern the ultimate knowledge that we have, today, of the foreign world of elementary particles, as described by quantum mechanics. This paper starts with a short survey of the principles which underlie quantum computing, and of some of the major breakthroughs brought by the first ten to fifteen years of research in this domain; quantum algorithms and quantum teleportation are very biefly presented. The next sections are devoted to one among the many directions of current research in the quantum computation paradigm, namely quantum programming languages and their semantics. A few other hot topics and open problems in quantum information processing and communication are mentionned in few words in the concluding remarks, the most difficult of them being the physical implementation of a quantum computer. The interested reader will find a list of useful references at the end of the paper.
Abstract: In this manuscript, a wavelet-based blind
watermarking scheme has been proposed as a means to provide
security to authenticity of a fingerprint. The information used for
identification or verification of a fingerprint mainly lies in its
minutiae. By robust watermarking of the minutiae in the fingerprint
image itself, the useful information can be extracted accurately even
if the fingerprint is severely degraded. The minutiae are converted in
a binary watermark and embedding these watermarks in the detail
regions increases the robustness of watermarking, at little to no
additional impact on image quality. It has been experimentally shown
that when the minutiae is embedded into wavelet detail coefficients
of a fingerprint image in spread spectrum fashion using a
pseudorandom sequence, the robustness is observed to have a
proportional response while perceptual invisibility has an inversely
proportional response to amplification factor “K". The DWT-based
technique has been found to be very robust against noises,
geometrical distortions filtering and JPEG compression attacks and is
also found to give remarkably better performance than DCT-based
technique in terms of correlation coefficient and number of erroneous
minutiae.
Abstract: Energetic and structural results for ethanol-water mixtures as a function of the mole fraction were calculated using Monte Carlo methodology. Energy partitioning results obtained for equimolar water-ethanol mixture and ether organic liquids are compared. It has been shown that at xet=0.22 the RDFs for waterethanol and ethanol-ethanol interactions indicated strong hydrophobic interactions between ethanol molecules and the local structure of solution is less structured at this concentration as at ether ones. Results obtained for ethanol-water mixture as a function of concentration are in good agreement with the experimental data.
Abstract: Jordan exerts many efforts to nurture their academically gifted students in special schools since 2001. During
the past nine years of launching these schools, their learning and excellence environments were believed to be distinguished compared
to public schools. This study investigated the environments of gifted
students compared with other non-gifted, using a survey instrument
that measures the dimensions of family, peers, teachers, school- support, society, and resources –dimensions rooted deeply in supporting gifted education, learning, and achievement. A total
number of 109 were selected from excellence schools for
academically gifted students, and 119 non-gifted students were selected from public schools. Around 8.3% of the non-gifted students
reported that they “Never" received any support from their surrounding environments, 14.9% reported “Seldom" support, 23.7% reported “ Often" support, 26.0% reported “Frequent" support, and
32.8% reported “Very frequent" support. Where the gifted students reported more “Never" support than the non-gifted did with 11.3%,
“Seldom" support with 15.4%, “Often" support with 26.6%,
“Frequent" support with 29.0%, and reported “Very frequent" support less than the non-gifted students with 23.6%. Unexpectedly,
statistical differences were found between the two groups favoring
non-gifted students in perception of their surrounding environments
in specific dimensions, namely, school- support, teachers, and society. No statistical differences were found in the other dimensions
of the survey, namely, family, peers, and resources. As the
differences were found in teachers, school- support, and society, the
nurturing environments for the excellence schools need to be revised to adopt more creative teaching styles, rich school atmosphere and
infrastructures, interactive guiding for the students and their parents, promoting for the excellence environments, and re-build successful
identification models. Thus, families, schools, and society should
increase their cooperation, communication, and awareness of the
gifted supportive environments. However, more studies to investigate
other aspects of promoting academic giftedness and excellence are recommended.
Abstract: An immunomodulator bioproduct is prepared in a
batch bioprocess with a modified bacterium Pseudomonas
aeruginosa. The bioprocess is performed in 100 L Bioengineering
bioreactor with 42 L cultivation medium made of peptone, meat
extract and sodium chloride. The optimal bioprocess parameters were
determined: temperature – 37 0C, agitation speed - 300 rpm, aeration
rate – 40 L/min, pressure – 0.5 bar, Dow Corning Antifoam M-max.
4 % of the medium volume, duration - 6 hours. This kind of
bioprocesses are appreciated as difficult to control because their
dynamic behavior is highly nonlinear and time varying. The aim of
the paper is to present (by comparison) different models based on
experimental data.
The analysis criteria were modeling error and convergence rate.
The estimated values and the modeling analysis were done by using
the Table Curve 2D.
The preliminary conclusions indicate Andrews-s model with a
maximum specific growth rate of the bacterium in the range of
0.8 h-1.