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: In this note, we investigate the blind source separability of linear FIR-MIMO systems. The concept of semi-reversibility of a system is presented. It is shown that for a semi-reversible system, if the input signals belong to a binary alphabet, then the source data can be blindly separated. One sufficient condition for a system to be semi-reversible is obtained. It is also shown that the proposed criteria is weaker than that in the literature which requires that the channel matrix is irreducible/invertible or reversible.
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: Flexible Job Shop Problem (FJSP) is an extension of
classical Job Shop Problem (JSP). The FJSP extends the routing
flexibility of the JSP, i.e assigning machine to an operation. Thus it
makes it more difficult than the JSP. In this study, Cooperative Coevolutionary
Genetic Algorithm (CCGA) is presented to solve the
FJSP. Makespan (time needed to complete all jobs) is used as the
performance evaluation for CCGA. In order to test performance and
efficiency of our CCGA the benchmark problems are solved.
Computational result shows that the proposed CCGA is comparable
with other approaches.
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: With the development of Internet and databases application techniques, the demand that lots of databases in the Internet are permitted to remote query and access for authorized users becomes common, and the problem that how to protect the copyright of relational databases arises. This paper simply introduces the knowledge of cloud model firstly, includes cloud generators and similar cloud. And then combined with the property of the cloud, a method of protecting relational databases copyright with cloud watermark is proposed according to the idea of digital watermark and the property of relational databases. Meanwhile, the corresponding watermark algorithms such as cloud watermark embedding algorithm and detection algorithm are proposed. Then, some experiments are run and the results are analyzed to validate the correctness and feasibility of the watermark scheme. In the end, the foreground of watermarking relational database and its research direction are prospected.
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: 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.
Abstract: In this paper, we propose a modified version of the
Constant Modulus Algorithm (CMA) tailored for blind Decision
Feedback Equalizer (DFE) of first order Markovian time varying
channels. The proposed NonStationary CMA (NSCMA) is designed
so that it explicitly takes into account the Markovian structure of
the channel nonstationarity. Hence, unlike the classical CMA, the
NSCMA is not blind with respect to the channel time variations.
This greatly helps the equalizer in the case of realistic channels, and
avoids frequent transmissions of training sequences.
This paper develops a theoretical analysis of the steady state
performance of the CMA and the NSCMA for DFEs within a time
varying context. Therefore, approximate expressions of the mean
square errors are derived. We prove that in the steady state, the
NSCMA exhibits better performance than the classical CMA. These
new results are confirmed by simulation.
Through an experimental study, we demonstrate that the Bit Error
Rate (BER) is reduced by the NSCMA-DFE, and the improvement
of the BER achieved by the NSCMA-DFE is as significant as the
channel time variations are severe.
Abstract: There is a real threat on the VIPs personal pages on
the Social Network Sites (SNS). The real threats to these pages is
violation of privacy and theft of identity through creating fake pages
that exploit their names and pictures to attract the victims and spread
of lies. In this paper, we propose a new secure architecture that
improves the trusting and finds an effective solution to reduce fake
pages and possibility of recognizing VIP pages on SNS. The
proposed architecture works as a third party that is added to
Facebook to provide the trust service to personal pages for VIPs.
Through this mechanism, it works to ensure the real identity of the
applicant through the electronic authentication of personal
information by storing this information within content of their
website. As a result, the significance of the proposed architecture is
that it secures and provides trust to the VIPs personal pages.
Furthermore, it can help to discover fake page, protect the privacy,
reduce crimes of personality-theft, and increase the sense of trust and
satisfaction by friends and admirers in interacting with SNS.
Abstract: To unveil the mechanism of fast autooxidation of fish
myoglobins, the effect of temperature on the structural change of tuna
myoglobin was investigated. Purified myoglobin was subjected to
preincubation at 5, 20, 50 and 40oC. Overall helical structural decay
through thermal treatment up to 95oC was monitored by circular
dichroism spectrometry, while the structural changes around the heme
pocket was measured by ultraviolet/visible absorption spectrophotometry.
As a result, no essential structural change of myoglobin
was observed under 30oC, roughly equivalent to their body
temperature, but the structure was clearly damaged at 40oC. The Soret
band absorption hardly differed irrespective of preincubation
temperature, suggesting that the structure around the heme pocket was
not perturbed even after thermal treatment.
Abstract: An Optimal Power Flow based on Improved Particle
Swarm Optimization (OPF-IPSO) with Generator Capability Curve
Constraint is used by NN-OPF as a reference to get pattern of
generator scheduling. There are three stages in Designing NN-OPF.
The first stage is design of OPF-IPSO with generator capability curve
constraint. The second stage is clustering load to specific range and
calculating its index. The third stage is training NN-OPF using
constructive back propagation method. In training process total load
and load index used as input, and pattern of generator scheduling
used as output. Data used in this paper is power system of Java-Bali.
Software used in this simulation is MATLAB.
Abstract: This paper presents nonlinear elastic dynamic analysis
of 3-D semi-rigid steel frames including geometric and connection
nonlinearities. The geometric nonlinearity is considered by using
stability functions and updating geometric stiffness matrix. The
nonlinear behavior of the steel beam-to-column connection is
considered by using a zero-length independent connection element
comprising of six translational and rotational springs. The nonlinear
dynamic equilibrium equations are solved by the Newmark numerical
integration method. The nonlinear time-history analysis results are
compared with those of previous studies and commercial SAP2000
software to verify the accuracy and efficiency of the proposed
procedure.
Abstract: This paper presents an application of level sets for the segmentation of abdominal and thoracic aortic aneurysms in CTA
datasets. An important challenge in reliably detecting aortic is the
need to overcome problems associated with intensity
inhomogeneities. Level sets are part of an important class of methods
that utilize partial differential equations (PDEs) and have been extensively applied in image segmentation. A kernel function in the
level set formulation aids the suppression of noise in the extracted
regions of interest and then guides the motion of the evolving contour
for the detection of weak boundaries. The speed of curve evolution
has been significantly improved with a resulting decrease in segmentation time compared with previous implementations of level
sets, and are shown to be more effective than other approaches in
coping with intensity inhomogeneities. We have applied the Courant
Friedrichs Levy (CFL) condition as stability criterion for our algorithm.
Abstract: In this paper, a mathematical model of human immunodeficiency
virus (HIV) is utilized and an optimization problem is
proposed, with the final goal of implementing an optimal 900-day
structured treatment interruption (STI) protocol. Two type of commonly
used drugs in highly active antiretroviral therapy (HAART),
reverse transcriptase inhibitors (RTI) and protease inhibitors (PI), are
considered. In order to solving the proposed optimization problem an
adaptive memetic algorithm with population management (AMAPM)
is proposed. The AMAPM uses a distance measure to control the
diversity of population in genotype space and thus preventing the
stagnation and premature convergence. Moreover, the AMAPM uses
diversity parameter in phenotype space to dynamically set the population
size and the number of crossovers during the search process.
Three crossover operators diversify the population, simultaneously.
The progresses of crossover operators are utilized to set the number
of each crossover per generation. In order to escaping the local optima
and introducing the new search directions toward the global optima,
two local searchers assist the evolutionary process. In contrast to
traditional memetic algorithms, the activation of these local searchers
is not random and depends on both the diversity parameters in
genotype space and phenotype space. The capability of AMAPM in
finding optimal solutions compared with three popular metaheurestics
is introduced.