Abstract: This paper proposes two novel schemes for pilot-aided
integer frequency offset (IFO) estimation in orthogonal frequency
division multiplexing (OFDM)-based digital video broadcastingterrestrial
(DVB-T) systems. The conventional scheme proposed for
estimating the IFO uses only partial information of combinations
that pilots can provide, which stems from a rigorous assumption
that the channel responses of pilots used for estimating the IFO
change very rapidly. Thus, in this paper, we propose the novel IFO
estimation schemes exploiting all information of combinations that
pilots can provide to improve the performance of IFO estimation.
The simulation results show that the proposed schemes are highly
accurate in terms of the IFO detection probability.
Abstract: A new dynamic clustering approach (DCPSO), based
on Particle Swarm Optimization, is proposed. This approach is
applied to unsupervised image classification. The proposed approach
automatically determines the "optimum" number of clusters and
simultaneously clusters the data set with minimal user interference.
The algorithm starts by partitioning the data set into a relatively large
number of clusters to reduce the effects of initial conditions. Using
binary particle swarm optimization the "best" number of clusters is
selected. The centers of the chosen clusters is then refined via the Kmeans
clustering algorithm. The experiments conducted show that
the proposed approach generally found the "optimum" number of
clusters on the tested images.
Abstract: Since 2004, we have been developing an in-situ storage image sensor (ISIS) that captures more than 100 consecutive images at a frame rate of 10 Mfps with ultra-high sensitivity as well as the video camera for use with this ISIS. Currently, basic research is continuing in an attempt to increase the frame rate up to 100 Mfps and above. In order to suppress electro-magnetic noise at such high frequency, a digital-noiseless imaging transfer scheme has been developed utilizing solely sinusoidal driving voltages. This paper presents highly efficient-yet-accurate expressions to estimate attenuation as well as phase delay of driving voltages through RC networks of an ultra-high-speed image sensor. Elmore metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE data, we found a simple expression that significantly improves the accuracy of the approximation. Similarly, another simple closed-form model to estimate phase delay through fundamental RC networks is also obtained. Estimation error of both expressions is much less than previous works, only less 2% for most of the cases . The framework of this analysis can be extended to address similar issues of other VLSI structures.
Abstract: Bladder carcinoma is an important worldwide health problem. Both cystoscopy and urine cytology used in detecting bladder cancer suffer from drawbacks where cystoscopy is an invasive method and urine cytology shows low sensitivity in low grade tumors. This study validates easier and less time-consuming techniques to evaluate the value of combined use of angiogenin and clusterin in comparison and combination with voided urine cytology in the detection of bladder cancer patients. This study includes malignant (bladder cancer patients, n= 50), benign (n=20) and healthy (n=20) groups. The studied groups were subjected to cystoscopic examination, detection of bilharzial antibodies, urine cytology, and estimation of urinary angiogenin and clusterin by ELISA. The overall sensitivity and specificity were 66% and 75% for angiogenin, 70% and 82.5% for clusterin and 46% and 80% for voided urine cytology. Combined sensitivity of angiogenin and clusterin with urine cytology increased from 82 to 88%.
Abstract: The tracking allows to detect the tumor affections of cervical cancer, it is particularly complex and consuming time, because it consists in seeking some abnormal cells among a cluster of normal cells. In this paper, we present our proposed computer system for helping the doctors in tracking the cervical cancer. Knowing that the diagnosis of the malignancy is based in the set of atypical morphological details of all cells, herein, we present an unsupervised genetic algorithm for the separation of cell components since the diagnosis is doing by analysis of the core and the cytoplasm. We give also the various algorithms used for computing the morphological characteristics of cells (Ratio core/cytoplasm, cellular deformity, ...) necessary for the recognition of illness.
Abstract: A mammal-s body can be seen as a blood vessel with
complex tunnels. When heart pumps blood periodically, blood runs
through blood vessels and rebounds from walls of blood vessels.
Blood pressure signals can be measured with complex but periodic
patterns. When an artery is clamped during a surgical operation, the
spectrum of blood pressure signals will be different from that of
normal situation. In this investigation, intestinal artery clamping
operations were conducted to a pig for simulating the situation of
intestinal blocking during a surgical operation. Similarity theory is a
convenient and easy tool to prove that patterns of blood pressure
signals of intestinal artery blocking and unblocking are surely
different. And, the algorithm of Hilbert Huang Transform can be
applied to extract the character parameters of blood pressure pattern.
In conclusion, the patterns of blood pressure signals of two different
situations, intestinal artery blocking and unblocking, can be
distinguished by these character parameters defined in this paper.
Abstract: Formulation of biological profile is one of the modern roles of forensic anthropologist. The present study was conducted to estimate height using foot and shoeprint length of Malaysian population. The present work can be very useful information in the process of identification of individual in forensic cases based on shoeprint evidence. It can help to narrow down suspects and ease the police investigation. Besides, stature is important parameters in determining the partial identify of unidentified and mutilated bodies. Thus, this study can help the problem encountered in cases of mass disaster, massacre, explosions and assault cases. This is because it is very hard to identify parts of bodies in these cases where people are dismembered and become unrecognizable. Samples in this research were collected from 200 Malaysian adults (100 males and 100 females) with age ranging from 20 to 45 years old. In this research, shoeprint length were measured based on the print of the shoes made from the flat shoes. Other information like gender, foot length and height of subject were also recorded. The data was analyzed using IBM® SPSS Statistics 19 software. Results indicated that, foot length has a strong correlation with stature than shoeprint length for both sides of the feet. However, in the unknown, where the gender was undetermined have shown a better correlation in foot length and shoeprint length parameter compared to males and females analyzed separately. In addition, prediction equations are developed to estimate the stature using linear regression analysis of foot length and shoeprint length. However, foot lengths give better prediction than shoeprint length.
Abstract: This paper suggests a calibration method to reduce
errors occurring due to mobile robot sliding during location estimation
using the Dead-reckoning. Due to sliding of the mobile robot caused
between its wheels and the road surface while on free run, location
estimation can be erroneous. Sliding especially occurs during
cornering of mobile robot. Therefore, in order to reduce these frequent
sliding errors in cornering, we calibrated the mobile robot-s heading
values using a vision camera and templates of the ceiling.
Abstract: The paper investigates the relationship between the foreign direct investment (FDI) and the corporate governance or transparency by investigating the country-level FDI flows, FDI inward performance, corporate governance and transparency variables. From the regression analysis with Newey-West estimator of 28 country panel data from 1990- 2002, we find strong positive relationships between corporate governance or transparency level of hosting countries and FDI inward performance within hosting countries. A strong positive relationship is found between anti-director rights level or number of analysts of hosting countries and FDI inward performance within hosting countries. Also, we find a positive relationship between the number of analysts of hosting countries and FDI inflows. The empirical results are consistent with stock market liberalizations and corporate governance explanations of reasons for FDI.
Abstract: In this paper, algorithms for the automatic localisation
of two anatomical soft tissue landmarks of the head the medial
canthus (inner corner of the eye) and the tragus (a small, pointed,
cartilaginous flap of the ear), in CT images are describet. These
landmarks are to be used as a basis for an automated image-to-patient
registration system we are developing. The landmarks are localised
on a surface model extracted from CT images, based on surface
curvature and a rule based system that incorporates prior knowledge
of the landmark characteristics. The approach was tested on a dataset
of near isotropic CT images of 95 patients. The position of the
automatically localised landmarks was compared to the position of
the manually localised landmarks. The average difference was 1.5
mm and 0.8 mm for the medial canthus and tragus, with a maximum
difference of 4.5 mm and 2.6 mm respectively.The medial canthus
and tragus can be automatically localised in CT images, with
performance comparable to manual localisation
Abstract: Dichotomization of the outcome by a single cut-off point is an important part of various medical studies. Usually the relationship between the resulted dichotomized dependent variable and explanatory variables is analyzed with linear regression, probit regression or logistic regression. However, in many real-life situations, a certain cut-off point dividing the outcome into two groups is unknown and can be specified only approximately, i.e. surrounded by some (small) uncertainty. It means that in order to have any practical meaning the regression model must be robust to this uncertainty. In this paper, we show that neither the beta in the linear regression model, nor its significance level is robust to the small variations in the dichotomization cut-off point. As an alternative robust approach to the problem of uncertain medical categories, we propose to use the linear regression model with the fuzzy membership function as a dependent variable. This fuzzy membership function denotes to what degree the value of the underlying (continuous) outcome falls below or above the dichotomization cut-off point. In the paper, we demonstrate that the linear regression model of the fuzzy dependent variable can be insensitive against the uncertainty in the cut-off point location. In the paper we present the modeling results from the real study of low hemoglobin levels in infants. We systematically test the robustness of the binomial regression model and the linear regression model with the fuzzy dependent variable by changing the boundary for the category Anemia and show that the behavior of the latter model persists over a quite wide interval.
Abstract: The paper deals with a mathematical model for fluid dynamic flows on road networks which is based on conservation laws. This nonlinear framework is based on the conservation of cars. We focus on traffic circle, which is a finite number of roads that meet at some junctions. The traffic circle with junctions having either one incoming and two outgoing or two incoming and one outgoing roads. We describe the numerical schemes with the particular boundary conditions used to produce approximated solutions of the problem.
Abstract: Recent years have witnessed the rapid development of
the Internet and telecommunication techniques. Information security
is becoming more and more important. Applications such as covert
communication, copyright protection, etc, stimulate the research of
information hiding techniques. Traditionally, encryption is used to
realize the communication security. However, important information
is not protected once decoded. Steganography is the art and science
of communicating in a way which hides the existence of the communication.
Important information is firstly hidden in a host data, such
as digital image, video or audio, etc, and then transmitted secretly
to the receiver.In this paper a data hiding model with high security
features combining both cryptography using finite state sequential
machine and image based steganography technique for communicating
information more securely between two locations is proposed.
The authors incorporated the idea of secret key for authentication
at both ends in order to achieve high level of security. Before the
embedding operation the secret information has been encrypted with
the help of finite-state sequential machine and segmented in different
parts. The cover image is also segmented in different objects through
normalized cut.Each part of the encoded secret information has been
embedded with the help of a novel image steganographic method
(PMM) on different cuts of the cover image to form different stego
objects. Finally stego image is formed by combining different stego
objects and transmit to the receiver side. At the receiving end different
opposite processes should run to get the back the original secret
message.
Abstract: Ultrasonic machining (USM) is a non-traditional
machining process being widely used for commercial machining of
brittle and fragile materials such as glass, ceramics and
semiconductor materials. However, USM could be a viable
alternative for machining a tough material such as titanium; and this
aspect needs to be explored through experimental research. This
investigation is focused on exploring the use of ultrasonic machining
for commercial machining of pure titanium (ASTM Grade-I) and
evaluation of tool wear rate (TWR) under controlled experimental
conditions. The optimal settings of parameters are determined
through experiments planned, conducted and analyzed using Taguchi
method. In all, the paper focuses on parametric optimization of
ultrasonic machining of pure titanium metal with TWR as response,
and validation of the optimized value of TWR by conducting
confirmatory experiments.
Abstract: Our aim in this piece of work is to demonstrate the
power of the Laplace Adomian decomposition method (LADM) in
approximating the solutions of nonlinear differential equations
governing the two-dimensional viscous flow induced by a shrinking
sheet.
Abstract: This paper proposes a direct power control for
doubly-fed induction machine for variable speed wind power
generation. It provides decoupled regulation of the primary side
active and reactive power and it is suitable for both electric energy
generation and drive applications. In order to control the power
flowing between the stator of the DFIG and the network, a decoupled
control of active and reactive power is synthesized using PI
controllers.The obtained simulation results show the feasibility
and the effectiveness of the suggested method
Abstract: Our results showed that for the growth of qualitative
seedling and vegetative raw material of ðó. marschallianus Willd. and
T. serphyllum L. it is more profitable to use the in vitro and
hydroponics combined method. In in vitro culture it is possible to do
micro-propagation whole year with 98-99% rhizogenesis. 30000
micro-plants were obtained from one explant during 9 months.
Hydroponic conditions provide the necessary microclimate for
microplants where the survival rate without acclimatization was
93.3%. The essential oil content in hydroponic dry herb of both
species in vegetative and blossom phase was 1.3% whereas in wild
plants it was 1.2%, the content of extractive substances and vitamin
C also exceeded wild plants. Our biochemical and radiochemical
investigations indicated that the medicinal raw materials obtained
from hydroponic and wild plants of Thymus species correspond to
the demands of SPh XI, and the content of artificial radionuclides
does not exceed the MACL.
Abstract: This paper has introduced a slope photogrammetric mapping using unmanned aerial vehicle. There are two units of UAV has been used in this study; namely; fixed wing and multi-rotor. Both UAVs were used to capture images at the study area. A consumer digital camera was mounted vertically at the bottom of UAV and captured the images at an altitude. The objectives of this study are to obtain three dimensional coordinates of slope area and to determine the accuracy of photogrammetric product produced from both UAVs. Several control points and checkpoints were established Real Time Kinematic Global Positioning System (RTK-GPS) in the study area. All acquired images from both UAVs went through all photogrammetric processes such as interior orientation, exterior orientation, aerial triangulation and bundle adjustment using photogrammetric software. Two primary results were produced in this study; namely; digital elevation model and digital orthophoto. Based on results, UAV system can be used to mapping slope area especially for limited budget and time constraints project.
Abstract: Color image segmentation plays an important role in
computer vision and image processing areas. In this paper, the
features of Volterra filter are utilized for color image segmentation.
The discrete Volterra filter exhibits both linear and nonlinear
characteristics. The linear part smoothes the image features in
uniform gray zones and is used for getting a gross representation of
objects of interest. The nonlinear term compensates for the blurring
due to the linear term and preserves the edges which are mainly used
to distinguish the various objects. The truncated quadratic Volterra
filters are mainly used for edge preserving along with Gaussian noise
cancellation. In our approach, the segmentation is based on K-means
clustering algorithm in HSI space. Both the hue and the intensity
components are fully utilized. For hue clustering, the special cyclic
property of the hue component is taken into consideration. The
experimental results show that the proposed technique segments the
color image while preserving significant features and removing noise
effects.
Abstract: The householder RLS (HRLS) algorithm is an O(N2)
algorithm which recursively updates an arbitrary square-root of the
input data correlation matrix and naturally provides the LS weight
vector. A data dependent householder matrix is applied for such
an update. In this paper a recursive estimate of the eigenvalue
spread and misalignment of the algorithm is presented at a very low
computational cost. Misalignment is found to be highly sensitive to
the eigenvalue spread of input signals, output noise of the system and
exponential window. Simulation results show noticeable degradation
in the misalignment by increase in eigenvalue spread as well as
system-s output noise, while exponential window was kept constant.