Abstract: The antimicrobial, antiplasmid and cytotoxic activities of marine algae Halimeda opuntia and Sarconema filiforme were investigated. Antimicrobial bioassay against some human pathogenic bacteria and yeast were conducted using disc diffusion method. Halimeda extract exhibited antibacterial activity against six species of microrganisms, with significant inhibition against Staphylococcus aureus. While Sarconema extract was better potent as antifungal against Candida albicans. Comparative antibacterial studies showed that Halimeda extract showed equivalent or better activity as compared with commercial antibiotic when tested against Staphylococcus aureus. Further tests conducted using dilution method showed both extracts as having bacteriostatic mode of action against the tested microorganisms. Methanol extract of two species showed significant cytotoxicity (LC50
Abstract: Two constructions of unit-memory binary convolutional
codes from linear block codes over the finite semi-local ring F2r +vF2r , where v2 = v, are presented. In both cases, if the linear block code is systematic, then the resulting convolutional encoder
is systematic, minimal, basic and non-catastrophic. The Hamming
free distance of the convolutional code is bounded below by the
minimum Hamming distance of the block code. New examples of
binary convolutional codes that meet the Heller upper bound for
systematic codes are given.
Abstract: Many digital signal processing, techniques have been used to automatically distinguish protein coding regions (exons) from non-coding regions (introns) in DNA sequences. In this work, we have characterized these sequences according to their nonlinear dynamical features such as moment invariants, correlation dimension, and largest Lyapunov exponent estimates. We have applied our model to a number of real sequences encoded into a time series using EIIP sequence indicators. In order to discriminate between coding and non coding DNA regions, the phase space trajectory was first reconstructed for coding and non-coding regions. Nonlinear dynamical features are extracted from those regions and used to investigate a difference between them. Our results indicate that the nonlinear dynamical characteristics have yielded significant differences between coding (CR) and non-coding regions (NCR) in DNA sequences. Finally, the classifier is tested on real genes where coding and non-coding regions are well known.
Abstract: A 3.5-bit stage of the CMOS pipelined ADC is proposed. In this report, the main part of 3.5-bit stage ADC is introduced. How the MDAC, comparator and encoder worked and designed are shown in details. Besides, an OTA which is used in fully differential pipelined ADC was described. Using gain-boost architecture with differential amplifier, this OTA achieve high-gain and high-speed. This design was using CMOS 0.18um process and simulation in Cadence. The result of the simulation shows that the OTA has a gain up to 80dB, the unity gain bandwidth of about 1.138GHz with 2pF load.
Abstract: Security has been an important issue and concern in the
smart home systems. Smart home networks consist of a wide range of
wired or wireless devices, there is possibility that illegal access to
some restricted data or devices may happen. Password-based
authentication is widely used to identify authorize users, because this
method is cheap, easy and quite accurate. In this paper, a neural
network is trained to store the passwords instead of using verification
table. This method is useful in solving security problems that
happened in some authentication system. The conventional way to
train the network using Backpropagation (BPN) requires a long
training time. Hence, a faster training algorithm, Resilient
Backpropagation (RPROP) is embedded to the MLPs Neural
Network to accelerate the training process. For the Data Part, 200
sets of UserID and Passwords were created and encoded into binary
as the input. The simulation had been carried out to evaluate the
performance for different number of hidden neurons and combination
of transfer functions. Mean Square Error (MSE), training time and
number of epochs are used to determine the network performance.
From the results obtained, using Tansig and Purelin in hidden and
output layer and 250 hidden neurons gave the better performance. As
a result, a password-based user authentication system for smart home
by using neural network had been developed successfully.
Abstract: This paper describes the development of a 16-ports optical code division multiple access (OCDMA) encoder prototype based on Arrayed Waveguide Grating (AWG) and optical switches. It is potentially to provide a high security for data transmission due to all data will be transmitted in binary code form. The output signals from AWG are coded with a binary code that given to an optical switch before it signal modulate with the carrier and transmitted to the receiver. The 16-ports encoder used 16 double pole double throw (DPDT) toggle switches to control the polarization of voltage source from +5 V to -5 V for 16 optical switches. When +5 V is given, the optical switch will give code '1' and vice versa. The experimental results showed the insertion loss, crosstalk, uniformity, and optical signal-noise-ratio (OSNR) for the developed prototype are
Abstract: This paper describes a probabilistic method for
three-dimensional object recognition using a shared pool of surface
signatures. This technique uses flatness, orientation, and convexity
signatures that encode the surface of a free-form object into three
discriminative vectors, and then creates a shared pool of data by
clustering the signatures using a distance function. This method
applies the Bayes-s rule for recognition process, and it is extensible
to a large collection of three-dimensional objects.
Abstract: A new hybrid coding method for compressing
animated polygonal meshes is presented. This paper assumes
the simplistic representation of the geometric data: a temporal
sequence of polygonal meshes for each discrete frame of the
animated sequence. The method utilizes a delta coding and an
octree-based method. In this hybrid method, both the octree
approach and the delta coding approach are applied to each
single frame in the animation sequence in parallel. The
approach that generates the smaller encoded file size is chosen
to encode the current frame. Given the same quality
requirement, the hybrid coding method can achieve much
higher compression ratio than the octree-only method or the
delta-only method. The hybrid approach can represent 3D
animated sequences with higher compression factors while
maintaining reasonable quality. It is easy to implement and have
a low cost encoding process and a fast decoding process, which
make it a better choice for real time application.
Abstract: This paper provides a flexible way of controlling
Variable-Bit-Rate (VBR) of compressed digital video, applicable to
the new H264 video compression standard. The entire video
sequence is assessed in advance and the quantisation level is then set
such that bit rate (and thus the frame rate) remains within
predetermined limits compatible with the bandwidth of the
transmission system and the capabilities of the remote end, while at
the same time providing constant quality similar to VBR encoding.
A process for avoiding buffer starvation by selectively eliminating
frames from the encoded output at times when the frame rate is slow
(large number of bits per frame) will be also described. Finally, the
problem of buffer overflow will be solved by selectively eliminating
frames from the received input to the decoder. The decoder detects
the omission of the frames and resynchronizes the transmission by
monitoring time stamps and repeating frames if necessary.
Abstract: SeqWord Gene Island Sniffer, a new program for
the identification of mobile genetic elements in sequences of bacterial chromosomes is presented. This program is based on the
analysis of oligonucleotide usage variations in DNA sequences. 3,518 mobile genetic elements were identified in 637 bacterial
genomes and further analyzed by sequence similarity and the
functionality of encoded proteins. The results of this study are stored in an open database http://anjie.bi.up.ac.za/geidb/geidbhome.
php). The developed computer program and the database provide the information valuable for further investigation of the
distribution of mobile genetic elements and virulence factors among bacteria. The program is available for download at www.bi.up.ac.za/SeqWord/sniffer/index.html.
Abstract: Encoded information based on synchronization of coupled chaotic Nd:YAG lasers in master-slave configuration is numerically studied. Encoding, transmission, and decoding of information in optical chaotic communication with a single channel is presented. We analyze the robustness of the encrypted audio transmission in a channel noise. In order to illustrate this synchronization robustness, we present two cases of study: synchronization and transmission with a single channel without and with noise in the channel.
Abstract: This paper presents a new fingerprint coding technique
based on contourlet transform and multistage vector quantization.
Wavelets have shown their ability in representing natural images that
contain smooth areas separated with edges. However, wavelets
cannot efficiently take advantage of the fact that the edges usually
found in fingerprints are smooth curves. This issue is addressed by
directional transforms, known as contourlets, which have the
property of preserving edges. The contourlet transform is a new
extension to the wavelet transform in two dimensions using
nonseparable and directional filter banks. The computation and
storage requirements are the major difficulty in implementing a
vector quantizer. In the full-search algorithm, the computation and
storage complexity is an exponential function of the number of bits
used in quantizing each frame of spectral information. The storage
requirement in multistage vector quantization is less when compared
to full search vector quantization. The coefficients of contourlet
transform are quantized by multistage vector quantization. The
quantized coefficients are encoded by Huffman coding. The results
obtained are tabulated and compared with the existing wavelet based
ones.
Abstract: In this paper, a new encoding algorithm of spectral envelope based on NLMS in G.729.1 for VoIP is proposed. In the TDAC part of G.729.1, the spectral envelope and MDCT coefficients extracted in the weighted CELP coding error (lower-band) and the higher-band input signal are encoded. In order to reduce allocation bits for spectral envelope coding, a new quantization algorithm based on NLMS is proposed. Also, reduced bits are used to enhance sound quality. The performance of the proposed algorithm is evaluated by sound quality and bit reduction rates in clean and frame loss conditions.
Abstract: A new code for spectral-amplitude coding optical
code-division multiple-access system is proposed called Random
diagonal (RD) code. This code is constructed using code segment and
data segment. One of the important properties of this code is that the
cross correlation at data segment is always zero, which means that
Phase Intensity Induced Noise (PIIN) is reduced. For the performance
analysis, the effects of phase-induced intensity noise, shot noise, and
thermal noise are considered simultaneously. Bit-error rate (BER)
performance is compared with Hadamard and Modified Frequency
Hopping (MFH) codes. It is shown that the system using this new
code matrices not only suppress PIIN, but also allows larger number
of active users compare with other codes. Simulation results shown
that using point to point transmission with three encoded channels,
RD code has better BER performance than other codes, also its found
that at 0 dbm PIIN noise are 10-10 and 10-11 for RD and MFH
respectively.
Abstract: In this work, we developed the concept of
supercompression, i.e., compression above the compression standard
used. In this context, both compression rates are multiplied. In fact,
supercompression is based on super-resolution. That is to say,
supercompression is a data compression technique that superpose
spatial image compression on top of bit-per-pixel compression to
achieve very high compression ratios. If the compression ratio is very
high, then we use a convolutive mask inside decoder that restores the
edges, eliminating the blur. Finally, both, the encoder and the
complete decoder are implemented on General-Purpose computation
on Graphics Processing Units (GPGPU) cards. Specifically, the
mentio-ned mask is coded inside texture memory of a GPGPU.
Abstract: Obtaining labeled data in supervised learning is often
difficult and expensive, and thus the trained learning algorithm tends
to be overfitting due to small number of training data. As a result,
some researchers have focused on using unlabeled data which may
not necessary to follow the same generative distribution as the labeled
data to construct a high-level feature for improving performance on
supervised learning tasks. In this paper, we investigate the impact of
the relationship between unlabeled and labeled data for classification
performance. Specifically, we will apply difference unlabeled data
which have different degrees of relation to the labeled data for
handwritten digit classification task based on MNIST dataset. Our
experimental results show that the higher the degree of relation
between unlabeled and labeled data, the better the classification
performance. Although the unlabeled data that is completely from
different generative distribution to the labeled data provides the lowest
classification performance, we still achieve high classification performance.
This leads to expanding the applicability of the supervised
learning algorithms using unsupervised learning.
Abstract: The algorithm represents the DCT coefficients to concentrate signal energy and proposes combination and dictator to eliminate the correlation in the same level subband for encoding the DCT-based images. This work adopts DCT and modifies the SPIHT algorithm to encode DCT coefficients. The proposed algorithm also provides the enhancement function in low bit rate in order to improve the perceptual quality. Experimental results indicate that the proposed technique improves the quality of the reconstructed image in terms of both PSNR and the perceptual results close to JPEG2000 at the same bit rate.
Abstract: Multimedia information availability has increased
dramatically with the advent of video broadcasting on handheld
devices. But with this availability comes problems of maintaining the
security of information that is displayed in public. ISMA Encryption
and Authentication (ISMACryp) is one of the chosen technologies for
service protection in DVB-H (Digital Video Broadcasting-
Handheld), the TV system for portable handheld devices. The
ISMACryp is encoded with H.264/AVC (advanced video coding),
while leaving all structural data as it is. Two modes of ISMACryp are
available; the CTR mode (Counter type) and CBC mode (Cipher
Block Chaining) mode. Both modes of ISMACryp are based on 128-
bit AES algorithm. AES algorithms are more complex and require
larger time for execution which is not suitable for real time
application like live TV. The proposed system aims to gain a deep
understanding of video data security on multimedia technologies and
to provide security for real time video applications using selective
encryption for H.264/AVC. Five level of security proposed in this
paper based on the content of NAL unit in Baseline Constrain profile
of H.264/AVC. The selective encryption in different levels provides
encryption of intra-prediction mode, residue data, inter-prediction
mode or motion vectors only. Experimental results shown in this
paper described that fifth level which is ISMACryp provide higher
level of security with more encryption time and the one level provide
lower level of security by encrypting only motion vectors with lower
execution time without compromise on compression and quality of
visual content. This encryption scheme with compression process
with low cost, and keeps the file format unchanged with some direct
operations supported. Simulation was being carried out in Matlab.
Abstract: Recent years have seen a growing trend towards the
integration of multiple information sources to support large-scale
prediction of protein-protein interaction (PPI) networks in model
organisms. Despite advances in computational approaches, the
combination of multiple “omic" datasets representing the same type
of data, e.g. different gene expression datasets, has not been
rigorously studied. Furthermore, there is a need to further investigate
the inference capability of powerful approaches, such as fullyconnected
Bayesian networks, in the context of the prediction of PPI
networks. This paper addresses these limitations by proposing a
Bayesian approach to integrate multiple datasets, some of which
encode the same type of “omic" data to support the identification of
PPI networks. The case study reported involved the combination of
three gene expression datasets relevant to human heart failure (HF).
In comparison with two traditional methods, Naive Bayesian and
maximum likelihood ratio approaches, the proposed technique can
accurately identify known PPI and can be applied to infer potentially
novel interactions.
Abstract: The application of a high frequency signal injection method as speed and position observer in PMSM drives has been a research focus. At present, the precision of this method is nearly good as that of ten-bit encoder. But there are some questions for estimating position polarity. Based on high frequency signal injection, this paper presents a method to compensate position polarity for permanent magnet synchronous motor (PMSM). Experiments were performed to test the effectiveness of the proposed algorithm and results present the good performance.