Abstract: Analysis of heart rate variability (HRV) has become a
popular non-invasive tool for assessing the activities of autonomic
nervous system. Most of the methods were hired from techniques
used for time series analysis. Currently used methods are time
domain, frequency domain, geometrical and fractal methods. A new
technique, which searches for pattern repeatability in a time series, is
proposed for quantifying heart rate (HR) time series. These set of
indices, which are termed as pattern repeatability measure and
pattern repeatability ratio are able to distinguish HR data clearly
from noise and electroencephalogram (EEG). The results of analysis
using these measures give an insight into the fundamental difference
between the composition of HR time series with respect to EEG and
noise.
Abstract: In this paper, we study the pulsatile flow of blood through stenotic arteries. The inner layer of arterial walls is modeled as a porous medium and human blood is assumed as an incompressible fluid. A numerical algorithm based on the finite element method is developed to simulate the blood flow through both the lumen region and the porous wall. The algorithm is then applied to study the flow behaviour and to investigate the significance of the non-Newtonian effect.
Abstract: This paper presents the novel Rao-Blackwellised
particle filter (RBPF) for mobile robot simultaneous localization and
mapping (SLAM) using monocular vision. The particle filter is
combined with unscented Kalman filter (UKF) to extending the path
posterior by sampling new poses that integrate the current observation
which drastically reduces the uncertainty about the robot pose. The
landmark position estimation and update is also implemented through
UKF. Furthermore, the number of resampling steps is determined
adaptively, which seriously reduces the particle depletion problem,
and introducing the evolution strategies (ES) for avoiding particle
impoverishment. The 3D natural point landmarks are structured with
matching Scale Invariant Feature Transform (SIFT) feature pairs. The
matching for multi-dimension SIFT features is implemented with a
KD-Tree in the time cost of O(log2
N). Experiment results on real robot
in our indoor environment show the advantages of our methods over
previous approaches.
Abstract: A lot of research has been done in the past decade in the field of audio content analysis for extracting various information from audio signal. One such significant information is the "perceived mood" or the "emotions" related to a music or audio clip. This information is extremely useful in applications like creating or adapting the play-list based on the mood of the listener. This information could also be helpful in better classification of the music database. In this paper we have presented a method to classify music not just based on the meta-data of the audio clip but also include the "mood" factor to help improve the music classification. We propose an automated and efficient way of classifying music samples based on the mood detection from the audio data. We in particular try to classify the music based on mood for Indian bollywood music. The proposed method tries to address the following problem statement: Genre information (usually part of the audio meta-data) alone does not help in better music classification. For example the acoustic version of the song "nothing else matters by Metallica" can be classified as melody music and thereby a person in relaxing or chill out mood might want to listen to this track. But more often than not this track is associated with metal / heavy rock genre and if a listener classified his play-list based on the genre information alone for his current mood, the user shall miss out on listening to this track. Currently methods exist to detect mood in western or similar kind of music. Our paper tries to solve the issue for Indian bollywood music from an Indian cultural context
Abstract: The virulent debates that have dogged research on,
and the diffusion of, a wide range of technologies indicate a growing
loss of confidence in what we might call, the techno-scientific
endeavour to reshape the world. Utopian images of a world rendered
ever more amenable to human desires are now closely shadowed by
just as compelling dystopian visions of monstrosity and disaster that
are nevertheless constructed from the same cultural material. The
paper uses the case of the debates over developments in reproductive
technology to offer some observations on the ways in which such
technologies routinely become enmirred in cultural ambivalence.
Abstract: In this paper we propose a segmentation system for unconstrained Arabic online handwriting. An essential problem addressed by analytical-based word recognition system. The system is composed of two-stages the first is a newly special designed hidden Markov model (HMM) and the second is a rules based stage. In our system, handwritten words are broken up into characters by simultaneous segmentation-recognition using HMMs of unique design trained using online features most of which are novel. The HMM output characters boundaries represent the proposed segmentation points (PSP) which are then validated by rules-based post stage without any contextual information help to solve different segmentation errors. The HMM has been designed and tested using a self collected dataset (OHASD) [1]. Most errors cases are cured and remarkable segmentation enhancement is achieved. Very promising word and character segmentation rates are obtained regarding the unconstrained Arabic handwriting difficulty and not using context help.
Abstract: The purpose of this paper is to examine the financing
practices of SMEs in Libya in two different phases of business life
cycle: start-up and matured stages. Moreover, SMEs- accessing bank
loan issues is also identified. The study was conducted by taking into
account the aspect of demand. The findings are based on a sample of
76 SMEs in Libya through the adoption of questionnaires. The results
have pinpointed several things- evidently, SMEs use informal
financing sources which prefer personal savings; SME owners are
willing to apply for bank loan, that the most pressing problem has
been identified, not to apply bank loan is loan with interest (religion
factor).
Abstract: We proposed a new class of asymmetric turbo encoder for 3G systems that performs well in both “water fall" and “error floor" regions in [7]. In this paper, a modified (optimal) power allocation scheme for the different bits of new class of asymmetric turbo encoder has been investigated to enhance the performance. The simulation results and performance bound for proposed asymmetric turbo code with modified Unequal Power Allocation (UPA) scheme for the frame length, N=400, code rate, r=1/3 with Log-MAP decoder over Additive White Gaussian Noise (AWGN) channel are obtained and compared with the system with typical UPA and without UPA. The performance tests are extended over AWGN channel for different frame size to verify the possibility of implementation of the modified UPA scheme for the proposed asymmetric turbo code. From the performance results, it is observed that the proposed asymmetric turbo code with modified UPA performs better than the system without UPA and with typical UPA and it provides a coding gain of 0.4 to 0.52dB.
Abstract: When the shock front (SF) hits the central electrode
axis of plasma focus device, a reflected shock wave moves radially
outwards. The current sheath (CS) results from ionization of filled
gas between two electrodes continues to compress inwards until it
hits the out-going reflected shock front. In this paper the Lagrangian
equations are solved for a parabolic shock trajectory yielding a first
and second approximation for the CS path. To determine the
accuracy of the approximation, the same problem is solved for a
straight shock.
Abstract: We compare three categorical data clustering
algorithms with respect to the problem of classifying cultural data
related to the aesthetic judgment of comics artists. Such a
classification is very important in Comics Art theory since the
determination of any classes of similarities in such kind of data will
provide to art-historians very fruitful information of Comics Art-s
evolution. To establish this, we use a categorical data set and we
study it by employing three categorical data clustering algorithms.
The performances of these algorithms are compared each other,
while interpretations of the clustering results are also given.
Abstract: In this paper we present a GP-based method for automatically evolve projections, so that data can be more easily classified in the projected spaces. At the same time, our approach can reduce dimensionality by constructing more relevant attributes. Fitness of each projection measures how easy is to classify the dataset after applying the projection. This is quickly computed by a Simple Linear Perceptron. We have tested our approach in three domains. The experiments show that it obtains good results, compared to other Machine Learning approaches, while reducing dimensionality in many cases.
Abstract: Accurate modeling of high speed RLC interconnects
has become a necessity to address signal integrity issues in current
VLSI design. To accurately model a dispersive system of interconnects
at higher frequencies; a full-wave analysis is required.
However, conventional circuit simulation of interconnects with full
wave models is extremely CPU expensive. We present an algorithm
for reducing large VLSI circuits to much smaller ones with similar
input-output behavior. A key feature of our method, called Frequency
Shift Technique, is that it is capable of reducing linear time-varying
systems. This enables it to capture frequency-translation and sampling
behavior, important in communication subsystems such as mixers,
RF components and switched-capacitor filters. Reduction is obtained
by projecting the original system described by linear differential
equations into a lower dimension. Experiments have been carried out
using Cadence Design Simulator cwhich indicates that the proposed
technique achieves more % reduction with less CPU time than the
other model order reduction techniques existing in literature. We
also present applications to RF circuit subsystems, obtaining size
reductions and evaluation speedups of orders of magnitude with
insignificant loss of accuracy.
Abstract: Multiple-input multiple-output (MIMO) systems are
widely in use to improve quality, reliability of wireless transmission
and increase the spectral efficiency. However in MIMO systems,
multiple copies of data are received after experiencing various
channel effects. The limitations on account of complexity due to
number of antennas in case of conventional decoding techniques have
been looked into. Accordingly we propose a modified sphere decoder
(MSD-1) algorithm with lower complexity and give rise to system
with high spectral efficiency. With the aim to increase signal
diversity we apply rotated quadrature amplitude modulation (QAM)
constellation in multi dimensional space. Finally, we propose a new
architecture involving space time trellis code (STTC) concatenated
with space time block code (STBC) using MSD-1 at the receiver for
improving system performance. The system gains have been verified
with channel state information (CSI) errors.
Abstract: Machine tools are improved capacity remarkably during the 20th century. Improving the precision of machine tools are related with precision of products and accurate processing is always associated with the subject of interest. There are a lot of the elements that determine the precision of the machine, as guides, motors, structure, control, etc. In this paper we focused on the phenomenon that vertical movement system has worse precision than horizontal movement system even they were made up with same components. The vertical movement system needs to be studied differently from the horizontal movement system to develop its precision. The vertical movement system has load on its transfer direction and it makes the movement system weak in precision than the horizontal one. Some machines have mechanical counter balance, hydraulic or pneumatic counter balance to compensate the weight of the machine head. And there is several type of compensating the weight. It can push the machine head and also can use chain or wire lope to transfer the compensating force from counter balance to machine head. According to the type of compensating, there could be error from friction, pressure error of hydraulic or pressure control error. Also according to what to use for transferring the compensating force, transfer error of compensating force could be occur.
Abstract: Iris-based biometric system is gaining its importance in several applications. However, processing of iris biometric is a challenging and time consuming task. Detection of iris part in an eye image poses a number of challenges such as, inferior image quality, occlusion of eyelids and eyelashes etc. Due to these problems it is not possible to achieve 100% accuracy rate in any iris-based biometric authentication systems. Further, iris detection is a computationally intensive task in the overall iris biometric processing. In this paper, we address these two problems and propose a technique to localize iris part efficiently and accurately. We propose scaling and color level transform followed by thresholding, finding pupil boundary points for pupil boundary detection and dilation, thresholding, vertical edge detection and removal of unnecessary edges present in the eye images for iris boundary detection. Scaling reduces the search space significantly and intensity level transform is helpful for image thresholding. Experimental results show that our approach is comparable with the existing approaches. Following our approach it is possible to detect iris part with 95-99% accuracy as substantiated by our experiments on CASIA Ver-3.0, ICE 2005, UBIRIS, Bath and MMU iris image databases.
Abstract: Silver-exchanged zeolites and clays are used in
polymer composites to confer broad-spectrum antimicrobial
properties on a range of functional materials. Tobermorite is a layer
lattice mineral whose potential as a carrier for Ag+ ions in
antibacterial composites has not yet been investigated. Accordingly,
in this study, synthetic tobermorite was ion-exchanged with 10 wt%
silver ions and the resulting material was incorporated into a
composite film with chitosan. Chitosan is a biocompatible,
biodegradable derivative of chitin, a polysaccharide obtained from
the shells of crustaceans. The solvent-cast Ag+-exchanged
tobermorite-chitosan films were found to exhibit antimicrobial action
against Staphylococcus aureus, Escherichia coli and Pseudomonas
aeruginosa.
Abstract: In this paper we present a Adaptive Neuro-Fuzzy
System (ANFIS) with inputs the lagged dependent variable for the
prediction of Gross domestic Product growth rate in six countries.
We compare the results with those of Autoregressive (AR) model.
We conclude that the forecasting performance of neuro-fuzzy-system
in the out-of-sample period is much more superior and can be a very
useful alternative tool used by the national statistical services and the
banking and finance industry.
Abstract: Hollywood has produced various blockbusters on the
subject of disasters. Entering the 2000s, disaster films began to be
produced in the East Asian region as well, and as most of them were
successful, disaster films have settled as a popular genre in the region.
East Asian disaster films utilize a plot structure similar to Hollywood
films but, at the same time, represent East Asian people-s unique value
system. East Asian people-s social behavior pattern defined as
collectivism is a characteristic that distinguishes this region from other
cultural regions. In order to examine Confucian culture in disaster
films on the premise of the difference, the author conducts this
research as follows.This study first reviews the concepts disaster and
disaster film, and understands the genre through analyzing the
narrative structure and style. In addition, it discusses collectivism, a
characteristic of the East Asian region distinguished from the West,
and investigates Confucian culture in films and examines differences
among Korean, Chinese and Japanese Confucianism. Films selected
for this study are Tidal Wave (Korea, 2009), After Shock (China,
2006), and The Sinking of Japan (Japan, 2006). Using the characters in
these films, we analyze how Confucian thought is described and
reproduced.
Abstract: The concept of sacred and nature have long been
interlinked. Various cultural aspects such as religion, faith, traditions
bring people closer to nature and the natural environment. Memorial
Parks and Sacred Groves are examples of two such cultural
landscapes that exist today. The project mainly deals with the
significance of such sites to the environment and the deep rooted
significance it has to the people. These parks and groves play an
important role in biodiversity conservation and environmental
protection. There are many differences between the establishment of
memorial parks and sacred groves, but the underlying significance is
the same. Sentiments, emotions play an important role in landscape
planning and management. Hence the people and communities living
at these sites need to be involved in any planning activity or
decisions. The conservation of the environment should appeal to the
sentiments of the people; the need to be 'with nature' should be used
in the setting up of memorial forests and in the preservation of sacred
groves.
Abstract: One of the major parts of a jet engine is air intake,
which provides proper and required amount of air for the engine to
operate. There are several aerodynamic parameters which should be
considered in design, such as distortion, pressure recovery, etc. In
this research, the effects of lip ice accretion on pitot intake
performance are investigated. For ice accretion phenomenon, two
supervised multilayer neural networks (ANN) are designed, one for
ice shape prediction and another one for ice roughness estimation
based on experimental data. The Fourier coefficients of transformed
ice shape and parameters include velocity, liquid water content
(LWC), median volumetric diameter (MVD), spray time and
temperature are used in neural network training. Then, the subsonic
intake flow field is simulated numerically using 2D Navier-Stokes
equations and Finite Volume approach with Hybrid mesh includes
structured and unstructured meshes. The results are obtained in
different angles of attack and the variations of intake aerodynamic
parameters due to icing phenomenon are discussed. The results show
noticeable effects of ice accretion phenomenon on intake behavior.